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The differentiation of both gene expression and protein function is thought to be important as a mechanism of the functionalization of duplicate genes . However , it has not been addressed whether expression or protein divergence of duplicate genes is greater in those genes that have undergone functionalization compared with those that have not . We examined a total of 492 paralogous gene pairs associated with morphological diversification in a plant model organism ( Arabidopsis thaliana ) . Classifying these paralogous gene pairs into high , low , and no morphological diversification groups , based on knock-out data , we found that the divergence rate of both gene expression and protein sequences were significantly higher in either high or low morphological diversification groups compared with those in the no morphological diversification group . These results strongly suggest that the divergence of both expression and protein sequence are important sources for morphological diversification of duplicate genes . Although both mechanisms are not mutually exclusive , our analysis suggested that changes of expression pattern play the minor role ( 33%–41% ) and that changes of protein sequence play the major role ( 59%–67% ) in morphological diversification . Finally , we examined to what extent duplicate genes are associated with expression or protein divergence exerting morphological diversification at the whole-genome level . Interestingly , duplicate genes randomly chosen from A . thaliana had not experienced expression or protein divergence that resulted in morphological diversification . These results indicate that most duplicate genes have experienced minor functionalization .
Duplicate genes rarely exhibit de novo functions ( neofunctionalization ) ; more usually , the functions of the original gene are split into multiple functions among the duplicate genes ( subfunctionalization ) [1]–[5] . Such functionalization through gene duplication is considered to be an important source of diversification in complex organisms [6] . As a mechanism of functionalization in duplicate genes , differentiation of both gene expression and protein function are thought to be important . In particular , differential patterns of gene expression among paralogs are widely believed to play a prominent role in morphological diversification , because such differences are essential for development [7]–[10] . However , substantial amounts of data support morphological diversification through divergence of protein function [11] . Many researchers have studied divergence of either expression or protein function in duplicate genes at the genome scale [12]–[24] . Although divergence of either expression or protein sequence tends to increase as a duplication ages , it is unclear whether either expression or protein divergence in duplicate genes has been elevated by functionalization . Therefore , it is of interest to compare the divergence rate of either expression pattern or protein sequence of duplicate genes of the same age that have and have not undergone functionalization . If divergence of both expression and protein function are important sources for functionalization , the divergence rate of both should be higher in duplicate genes that have undergone functionalization compared with those that have not . A . thaliana is an excellent model organism for addressing the above issue because it has a highly duplicated genome and many knock-out mutants have been generated . Here , to address how duplicate genes have contributed to morphological evolution , we classified Arabidopsis duplicate genes into high , low and no morphological diversification groups based on knock-out data , and examined the divergence rates of both expression pattern and protein sequence among the three morphological diversification groups .
From the literature and from our earlier work ( see Materials and Methods ) [25] , [26] we identified 398 pairs of duplicate genes in which the knock-out mutant of either gene in a pair induced abnormal morphological changes relative to wild type . Abnormal morphological changes were classified into seed , vegetative and reproductive phenotypes on the basis of the definition of Meinke et al [27] . When the knock-out phenotype is totally different between genes in a paralogous gene pair , it is reasonable to assume that functionalization occurred after gene duplication ( Figure 1A ) . For example , the knock-out mutant of AT4G09820 and AT5G41315 genes induced a yellow seed coat in the reproductive stage and a reduction of trichomes in the vegetative stage , respectively . Therefore , the knock-out phenotype is completely different between AT4G09820 and AT5G41315 because two abnormal phenotypes appeared in different developmental stages . Thus , paralogous genes with different phenotypes ( morphological differences between phenotypes ) are defined to have high morphological diversification . It is more common , however , to observe knock-out phenotypes that are similar or identical between paralogous genes ( Figure 1B ) . For example , the knock-out mutants of AT1G62830 and AT3G10390 genes both induced late flowering . Although the knock-out phenotype of the two genes is similar , there would appear to be functionalization in such paralogous genes because a morphological change resulting from the deletion of one gene occurs when there is no or little functional redundancy between the paralogous genes . We , therefore , thought that such paralogous genes had some degree of functionalization after gene duplication . However , it is likely that similar or identical phenotypes indicate paralogous genes that have lower functionalization compared with paralogous genes with different phenotypes . Therefore , paralogous genes with either similar or identical phenotypes ( morphological changes within phenotypes ) were defined to have low morphological diversification . In this study , we identified 163 and 235 paralogous gene pairs associated with high and low morphological diversification , respectively . As a control set , we focused on paralogous gene pairs in which abnormal morphological changes are observed only upon the deletion of multiple paralogous genes but deletion of each gene separately did not induce abnormal morphological changes ( Figure 1C ) . For example , the double knock-out mutant of AT3G58780 and AT2G42830 exhibits fruit dehiscence but knock-out of each gene alone did not induce abnormal morphological changes . Such paralogous gene pairs are likely to have some degree of functional redundancy . We , therefore , defined these paralogous gene pairs as having no morphological diversification . The number of paralogous gene pairs identified without morphological diversification was 94 . Thus , we identified a total of 492 paralogous gene pairs associated with the three kinds of morphological diversification ( Table S1 ) . To examine the expression pattern divergence for a paralogous gene pair , we obtained intensities of gene expression by microarray analysis under 634 conditions . Expression divergence in a pair of genes is usually inferred by 1 minus R ( Pearson's coefficient of correlation ) of the expression intensities among experimental conditions . Here , we transformed the value as log ( ( 1−R ) / ( 1+R ) ) , because the transformation is more sensitive for examining expression differences [19] . When we applied the log ( ( 1−R ) / ( 1+R ) ) values to paralogous gene pairs among the three morphological diversification groups , the log ( ( 1−R ) / ( 1+R ) ) values increased as morphological diversification increased ( Figure S1 ) . However , the relationship may be strongly influenced by duplication age ( sequence divergence ) in the case that morphological diversification increases as sequence divergence increases . We , therefore , investigated sequence divergence in paralogous gene pairs by examining synonymous ( Ks ) and nonsynonymous ( Ka ) distance among morphological diversification groups [28] . Consequently , both synonymous and nonsynonymous distances increased as morphological diversification increased ( P<0 . 01 by Wilcoxon's test; Figure S1 and Table S2 ) . To minimize the effect of duplication age , log ( ( 1−R ) / ( 1+R ) ) was divided by Ks . This is because expression divergence is expected to increase as duplication timing becomes earlier and Ks increases in a nearly linear fashion with duplication age [17] , [19] , [24] . Ed ( log ( ( 1−R ) / ( 1+R ) ) /Ks ) is an indicator of the expression divergence rate between a paralogous gene pair: high and low Ed indicates high and low expression divergence at the same duplication age , respectively . When we calculated Ed between a paralogous gene pair in the three morphological diversification groups , Ed increased as morphological diversification increased ( Figure 2A ) . Ed differed significantly between each pair of morphological diversification groups ( P<0 . 01 by Wilcoxon's test; Table S2 ) , suggesting that expression divergence is an important source for morphological diversification of duplicate genes . There are genetic and epigenetic factors that are the source of expression divergence . Since the differentiation of cis-regulatory elements can be a major genetic effect , we examined the proportion of known cis-regulatory elements that overlap in the promoter regions of paralogous gene pairs [29] . The proportion of cis-regulatory elements that overlap decreased as morphological diversification increased ( Figure S2 ) . The proportion of overlapping cis-regulatory elements differed significantly between each pair of morphological diversification groups ( P<0 . 05 by Wilcoxon's test; Table S2 and Figure S2 ) , indicating that the divergence of cis-regulatory elements contributes to morphological diversification . With respect to epigenetic factors , we investigated the proportion of methylated cytosines to non-methylated cytosines in the promoter regions of paralogous genes [30] . The proportional difference in paralogous gene pairs did not significantly differ between each pair of morphological diversification groups ( Table S2 and Figure S2 ) , indicating that an epigenetic effect through methylation is unlikely to contribute to morphological diversification . Taken together , expression divergence led by the differentiation of cis-regulatory elements is an important source for morphological diversification in duplicate genes . Because duplication age ( sequence divergence ) between paralogous gene pairs increased as morphological diversification increased ( Figure S1 ) , we examined divergence rates of protein sequences of the same duplication age . Divergence rates of protein sequences are commonly inferred from selection pressure in coding sequences , i . e . the ratio of the non-synonymous substitution rate ( Ka ) to Ks . High and low Ka/Ks ratios indicate high and low protein divergence rates at the same duplication age , respectively [28] . When we applied the Ka/Ks ratio to paralogous gene pairs within the three morphological diversification groups , the Ka/Ks ratio increased as the morphological diversification increased ( Figure 2B ) . The Ka/Ks ratio differed significantly between each pair of morphological diversification groups ( P<0 . 01 by Wilcoxon's test; Table S2 ) , suggesting that protein divergence is an important source for morphological diversification of duplicate genes . To analyze the kinds of amino acid replacements that have occurred during morphological diversification , we classified all amino acid replacements as either ‘chemical radical’ or ‘conservative’ on the basis of an amino acid classification generated in an earlier report [31] . We examined the ratio of the radical nonsynonymous substitution rate ( Kr ) to the conservative nonsynonymous substitution rate ( Kc ) . Interestingly , the Kr/Kc ratios of all types of paralogous gene pairs were similar ( Figure 2C and Table S2 ) , indicating that paralogous gene pairs with either high , low or no morphological diversification tend to have the same level of radical protein divergence . The Kr/Kc ratio based on this amino acid classification is significantly correlated with the Ka/Ks ratio at the whole genome level [31] . Therefore , radical changes become restricted in paralogous gene pairs with higher morphological diversification . One explanation for this restriction is that radical changes do not affect morphological diversification . However , some reports have shown that radical changes significantly influence functional divergence [23] , [32] . Therefore , it does not seem to be a reasonable explanation . Another explanation is that radical changes may induce serious functional errors . To maintain duplicate genes that encode functional proteins , radical changes may be too deleterious . Therefore , paralogous gene pairs involved in higher morphological diversification may be subject to purifying selection against radical amino acid changes . To compare the divergence rate of expression pattern with that of protein sequence in paralogous gene pairs associated with morphological diversification , we focused on paralogous gene pairs without morphological diversification because the divergence rate of expression pattern and/or protein sequence in these duplicate genes has little effect on morphological diversification . Therefore , the top 5% of Ed and Ka/Ks ratios for paralogous gene pairs without morphological diversification were defined to be the threshold of higher divergence rate of expression pattern and protein sequences , respectively . We then counted the numbers of paralogous gene pairs with a higher divergence rate in each of the high and low morphological diversification groups ( Table 1 ) . To make the relative roles clear , we simply compared the observed ratio between paralogous gene pairs with only higher expression divergence and those with only higher protein divergence , assuming no bias between expression and protein divergence in either high or low morphological diversification groups . Interestingly , the number of paralogous gene pairs ( 37 in either high or low morphological diversification groups ) with a protein divergence but no expression divergence was significantly higher than the number of paralogous gene pairs ( 62 in either high or low morphological diversification groups ) with a higher expression divergence but no protein divergence , as determined by the chi-square test ( P<0 . 05 ) . These results indicate that paralogous gene pairs with a higher divergence rate of protein sequence contribute to morphological diversification more effectively than those with a higher divergence rate of expression . The inference from these results is that protein sequence plays the major role ( 59–67% ) and expression plays the minor role ( 33–41% ) in morphological diversification . We performed the same analysis using the top 10% of Ed and Ka/Ks ratios of paralogous gene pairs without morphological diversification as the threshold of higher divergence rate of expression pattern and protein sequences , and obtained essentially the same results ( Table S3 ) . Therefore , we believed that the relative rates of expression and protein divergence are stringent in morphological diversification . Finally , we addressed to what extent duplicate genes were associated with expression or protein divergence exerting morphological diversification at the whole genome level . To examine this question , we randomly chose 1000 pairs of paralogous gene pairs . We then compared Ed and Ka/Ks ratios among the 1000 random paralogous gene pairs and among paralogous gene pairs with high , low or no morphological diversification ( Figure 2 ) . Both Ed and Ka/Ks ratios for the random paralogous gene pairs were significantly lower compared with that for the paralogous gene pairs with high or low morphological diversification but were significantly higher compared with that for the paralogous gene pairs without morphological diversification ( P<0 . 01 by Wilcoxon's test , ( Figure 2A and 2B and Table S2 ) . However , the Kr/Kc ratio was not different between any pair in the four categories ( P>0 . 05 by Wilcoxon's test , Figure 2C and Table S2 ) . As discussed earlier , the Kr/Kc ratio is not an indicator for functionalization , therefore , no difference is reasonable . These results suggest that duplicate genes have not experienced divergence of expression or protein sequence exerting morphological diversification on a genome-wide scale . It is , therefore , likely that most duplicate genes have experienced only minor functionalization , at least in A . thaliana . To understand to what extent molecular changes in duplicate genes have contributed to morphological diversification in A . thaliana , we examined the divergence rate of either expression pattern or protein sequence in duplicate genes associated with morphological diversification and found that both divergences are important sources in morphological diversification . Although both mechanisms are not mutually exclusive , our analysis suggested that changes of protein sequence play the major role and changes of expression pattern play the minor role in morphological diversification . However , randomly chosen duplicate genes have not experienced divergence of expression or protein sequence exerting morphological diversification . These results indicate that most duplicate genes have experienced minor functionalization and only a few duplicate genes are likely to be crucial to morphological evolution .
We used data from the available literature and from our bank of previously generated T-DNA insertional mutants [25] , [26] , to identify 1203 duplicate genes whose knock-out induced abnormal morphological changes relative to wild type . The nucleotide sequences of A . thaliana ( TAIR7 ) were obtained from TAIR ( www . arabidopsis . org ) . Duplicate genes were defined as proteins that matched other proteins in a BLAST search with E<1×10−4 [33] . We then classified the 1203 duplicate genes into 786 gene families by the Markov clustering algorithm ( http://micans . org/mcl/ ) . In every pair of each family , we examined the amino acid identity and the coverage ( percentage of alignable regions ) . We found 405 paralogous gene pairs with amino acid identity >0 . 3 and coverage >0 . 5 . Since tandem duplicates have a higher chance of exhibiting similar expression due to leaky expression or conserved sequences by gene conversion than non-tandem duplicates [34]–[36] , we removed tandem duplicates from the 405 paralogous gene pairs . As reported earlier [37] , tandem duplicates were defined as genes in any gene pair , T1 and T2 , that ( 1 ) belong to the same gene family , ( 2 ) are located within 100 kb of each other , and ( 3 ) are separated by at most 10 nonhomologous ( not in the same gene family as T1 and T2 ) genes . In this definition , we identified 7 tandem paralogous gene pairs . After removing these tandem paralogous gene pairs , we used 398 non-tandem paralogous gene pairs in this study . Note that each knock-out mutant of paralogous genes induced abnormal phenotypic changes . To examine the degree of morphological diversification between the genes of the paralogous gene pairs , we classified morphological changes into seed , vegetative and reproductive phenotypes , according to the definition of Meinke et al [27]; the changes were defined as high ( morphological changes between phenotypes ) and low ( morphological changes within phenotypes ) morphological diversification . Briefly , seed , reproductive and vegetative phenotypes show visible changes in development . We identified 163 paralogous gene pairs associated with high morphological diversification and 235 associated with low divergence ( Table S1 ) . As a control set , we identified from the literature165 duplicate genes that did not show morphological diversification . Absence of morphological diversification was defined as the observation of morphological change only upon the deletion of multiple paralogs; deletion of each gene separately did not induce morphological change . After removing tandem paralogous gene pairs , we found 95 paralogous gene pairs with amino acid identity >0 . 3 and coverage >0 . 5 ( Table S1 ) . We obtained Affymetrix ATH1 data from the AtGenExpress expression atlas at TAIR ( http://www . arabidopsis . org/ ) . We compiled 1280 microarray datasets under 634 conditions , consisting of 82 different developmental stages , 72 biotic treatments , 285 abiotic treatments , 11 nutrient treatments , 81 hormone treatments , 40 chemical treatments , 21 cell cycle stages and 42 different genotypes . The array intensities were processed with the Bioconductor ( http://www . bioconductor . org ) affy package in the R software environment ( http://www . r-project . org ) . Specifically , the array intensities were adjusted to reduce background with the mas5 function , and the normalize quantiles function was used for between-array normalization . The background-corrected and background-normalized intensities were used for further analysis . We obtained the mapping data of known cis-regulatory elements in 1 kb promoter regions of all A . thaliana genes at ATCOECIS ( http://bioinformatics . psb . ugent . be/ATCOECIS/ ) [29] . To examine the divergence of cis-regulatory elements in each paralogous gene pair , we used the proportion of overlapping cis-regulatory elements ( the number of overlapping cis-regulatory elements over the number of observed cis-regulatory elements ) . To examine divergence of methylation in paralogous gene pairs , we obtained the mapping data of bisulfite-treated DNA sequences in the TAIR7 genome at NCBI Gene Expression Omnibus ( GSM276809 ) [30] . The bisulfate-treatment converts cytosine to uracil in unmethylated cytosine sites but does not affect cytosine in methylated cytosine sites . Since the methylation of each cytosine site was determined multiple times , a methylated cytosine site was defined when that site is more often methylated than not . We calculated the proportion of methylated cytosine sites ( the number of methylated cytosine sites over the number of observed cytosine sites ) in promoter regions ( 500 bp upstream from either start codon or transcriptional start site ) of all A . thaliana genes because the methylation of 500 bp upstream regions is considered to be sensitive for gene expression [30] . The proportional difference of methylated cytosine sites in a paralogous gene pair was used to represent the methylation divergence in a paralogous gene pair . Nucleotide sequences of A . thaliana ( TAIR7 ) were obtained from TAIR ( www . arabidopsis . org ) . Pairwise alignment was performed with the program CLUSTALW to align coding regions [38] . Ks and Ka between paralogous genes were estimated by the modified Nei–Gojobori method [28] . The transition/transversion ratio was estimated for each paralogous gene pair , and the ratio was then used to estimate Ka and Ks . To infer the ratio of the radical non-synonymous substitution rate ( Kr ) to the conservative non-synonymous substitution rate ( Kc ) , we classified amino acids according to Hanada et al . 2007 [31] . Radical and conservative changes were defined as amino acid replacements between and within groups , respectively . The ratio of Kr to Kc for each paralogous gene pair was estimated by the Zhang method [39] . We randomly chose genes from the total set of annotated A . thaliana genes ( TAIR7 ) . For a chosen gene , similarity searches were conducted against all annotated A . thaliana genes using BLASTP [33] . We aligned the chosen gene and all homologous genes identified in the BLASTP search using CLUSTALW and estimated the amino acid similarity among them [38] . We calculated the amino acid identity and the coverage ( percentage of alignable regions ) between the chosen gene and the matched gene with the highest identity . If the paralogous gene pair had amino acid identity >0 . 3 and coverage >0 . 5 , we added the pair to a random set . We repeated this procedure until we obtained 1000 paralogous gene pairs .
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The relationship between morphological and molecular evolution is a central issue to the understanding of eukaryote evolution . In particular , there is much interest in how duplicate genes have contributed to morphological diversification during evolution . As a mechanism of functionalization of duplicate genes , differentiation of both gene expression and protein function are believed to be important . Although it has been reported that both expression and protein divergence tend to increase as a duplication ages , it is unclear whether expression or protein divergence in duplicate genes is greater in those genes that have undergone functionalization compared with those that have not . Here , we studied 492 duplicate gene pairs associated with various degrees of morphological diversification in Arabidopsis thaliana . Using these data , we found that the divergence of both expression and protein sequence were important sources for morphological diversification of duplicate genes . Although both mechanisms are not mutually exclusive , our analysis suggested that expression divergence is the minor contributor and protein divergence is the major contributor to morphological diversification . However , the expression or protein sequence of randomly chosen duplicate genes did not show significant divergence that resulted in morphological diversification . These results indicate that most duplicate genes experienced minor functionalization in the genome .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] |
[
"computational",
"biology/comparative",
"sequence",
"analysis",
"computational",
"biology/genomics",
"evolutionary",
"biology/evolutionary",
"and",
"comparative",
"genetics"
] |
2009
|
Increased Expression and Protein Divergence in Duplicate Genes Is Associated with Morphological Diversification
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Yaws is a non-venereal treponemal infection caused by Treponema pallidum subspecies pertenue . The disease is targeted by WHO for eradication by 2020 . Rapid diagnostic tests ( RDTs ) are envisaged for confirmation of clinical cases during treatment campaigns and for certification of the interruption of transmission . Yaws testing requires both treponemal ( trep ) and non-treponemal ( non-trep ) assays for diagnosis of current infection . We evaluate a sequential testing strategy ( using a treponemal RDT before a trep/non-trep RDT ) in terms of cost and cost-effectiveness , relative to a single-assay combined testing strategy ( using the trep/non-trep RDT alone ) , for two use cases: individual diagnosis and community surveillance . We use cohort decision analysis to examine the diagnostic and cost outcomes . We estimate cost and cost-effectiveness of the alternative testing strategies at different levels of prevalence of past/current infection and current infection under each use case . We take the perspective of the global yaws eradication programme . We calculate the total number of correct diagnoses for each strategy over a range of plausible prevalences . We employ probabilistic sensitivity analysis ( PSA ) to account for uncertainty and report 95% intervals . At current prices of the treponemal and trep/non-trep RDTs , the sequential strategy is cost-saving for individual diagnosis at prevalence of past/current infection less than 85% ( 81–90 ) ; it is cost-saving for surveillance at less than 100% . The threshold price of the trep/non-trep RDT ( below which the sequential strategy would no longer be cost-saving ) is US$ 1 . 08 ( 1 . 02–1 . 14 ) for individual diagnosis at high prevalence of past/current infection ( 51% ) and US$ 0 . 54 ( 0 . 52–0 . 56 ) for community surveillance at low prevalence ( 15% ) . We find that the sequential strategy is cost-saving for both diagnosis and surveillance in most relevant settings . In the absence of evidence assessing relative performance ( sensitivity and specificity ) , cost-effectiveness is uncertain . However , the conditions under which the combined test only strategy might be more cost-effective than the sequential strategy are limited . A cheaper trep/non-trep RDT is needed , costing no more than US$ 0 . 50–1 . 00 , depending on the use case . Our results will help enhance the cost-effectiveness of yaws programmes in the 13 countries known to be currently endemic . It will also inform efforts in the much larger group of 71 countries with a history of yaws , many of which will have to undertake surveillance to confirm the interruption of transmission .
Yaws is a non-venereal treponemal infection caused by Treponema pallidum subspecies pertenue affecting primarily the skin in the early stages and the bone and cartilage in the late stages . In 1950 , WHO estimated that 160 million people were infected with yaws . Between 2008 and 2012 more than 300 000 new cases were reported to the World Health Organization ( WHO ) . The disease is now targeted by WHO for eradication by 2020 . One or two rounds of mass treatment at high levels of population coverage have been shown to reduce prevalence of yaws near to elimination levels . [1] This approach is known as total community treatment ( TCT ) –treatment of an entire endemic community irrespective of the number of active clinical cases . A second important element of the WHO strategy is 6 monthly Total Targeted Treatment ( TTT ) –treatment of all active clinical cases and their contacts—to mop-up cases missed in TCT rounds . Confirmation of clinical cases during TTT programs may be carried out using a rapid diagnostic test ( RDT ) for the dual detection of treponemal and non-treponemal serological markers at or near to point-of-care . Serological testing is also envisaged for certification of the interruption of transmission of T . p pertenue . Yaws and syphilis treponemes differ in less than 0 . 2% of the genome sequence . [2] Yaws is serologically indistinguishable from syphilis , caused by T pallidum subspecies pallidum . [3] Serological tests developed for syphilis may therefore be used to diagnose yaws , especially among children , since its clinical manifestation and epidemiology differ from that of syphilis and may allow a differentiation of the two conditions . Serological diagnosis of clinically active yaws requires the detection of two distinct sets of antibodies: one against treponemal antigens and one against non-treponemal antigens . Treponemal in vitro diagnostics ( IVDs ) , including T . pallidum particle agglutination assay ( TPPA ) , T . pallidum hemagglutination assay ( TPHA ) , and fluorescent treponemal antibody absorption test ( FTA-ABS ) are highly sensitive and specific but antibodies remain detectable for life following any treponemal infection even after successful treatment . A reactive treponemal test result can therefore indicate either current or past infection and may not be sufficient to indicate no new disease in people with clinical symptoms that look like yaws . Non-treponemal IVDs , including Rapid Plasma Reagin ( RPR ) and Venereal Disease Research Laboratory ( VDRL ) assays , are less specific but since titers rise during active disease and fall following treatment , current and past infection can be distinguished . Titers refer to how many serial dilutions you can perform on the sample and still get a positive result . False positive results can occur when using non-treponemal assays alone due to acute viral infections , malaria , and connective tissue diseases which may also cause non-treponemal assays to be reactive . As a result , testing for yaws requires both treponemal and non-treponemal assays to give an accurate diagnosis of current yaws infection . The most widely recommended yaws screening tool is the laboratory-based RPR followed by a treponemal test . RPR requires laboratory capacity , trained laboratory personnel , refrigeration for storage of reagents , and electricity to run equipment such as the refrigerator , centrifuge , and shaker . Because such facilities are generally not available in the remote areas where yaws is commonly endemic , diagnosis is often made on the basis of clinical findings only which may not be adequate for surveillance purposes . In places where laboratories are able to do the RPR , serum specimens have to be transported to centralized laboratories for testing and results are available in days or weeks . This delay may result in delayed treatment and continued transmission of the disease . Rapid syphilis tests detecting treponemal antibodies ( treponemal RDTs ) are now commercially available , meeting minimum defined standards for quality , safety and performance for use at point-of-care . Treponemal RDTs have been introduced into national antenatal care programmes but these are not commonly used for yaws , as results of treponemal RDTs alone correlate poorly with presence of current infection , as explained earlier . Currently , one commercially available RDT exists that is based on the simultaneous detection of antibodies to both treponemal and non-treponemal antigens . The DPP Yaws Trep & N . Trep Assay ( Chembio , Medford , NY , USA ) is designed for use in resource-limited settings where there is limited access to laboratory facilities . For brevity , we refer generically to the assay as a treponemal/non-treponemal RDT or “trep/non-trep RDT” . The dual components of the assay allows clinicians to both screen and confirm the serological status within 15 minutes and allows for differentiation of current and past yaws . In 2014 , the use of trep/non-trep RDT for diagnosis of yaws infection was evaluated and compared with T . pallidum particle hemagglutination assay ( TPHA ) and RPR as reference standards for treponemal and non-treponemal antibodies detection , respectively . [4] In the low-resource setting of Papua New Guinea , the treponemal test line demonstrated a sensitivity of 88 . 4% and a specificity of 95 . 2%; the non-treponemal test line demonstrated a sensitivity of 87 . 9% and a specificity of 92 . 5% . A number of evaluations of a trep/non-trep RDT for the diagnosis of yaws infection have now been conducted , as synthesized in a recent meta-analysis . [5] It is expected that the simpler trep/non-trep RDT should improve access to yaws diagnosis relative to the RPR test . However , use of the trep/non-trep RDT alone may not be the most economical option , especially in low treponemal test positive prevalence settings . In yaws elimination pilot projects , WHO had negotiated a price of US$ 2 . 50 per trep/non-trep RDT and US$0 . 45 per treponemal RDT . For surveys where large number of people are non-reactive to the treponemal test , such as in low endemicity settings , a combination of two rapid tests ( treponemal RDT for screening , and trep/non-trep RDT for diagnosis ) could be cost-saving . Studies have reported that antenatal syphilis screening and treatment is highly cost-effective in low and middle income countries . [6] Some have modelled the cost-effectiveness of different screening strategies . [7][8][9][10] Terris-Prestholt et al . ( 2015 ) were the first to compare the full range of possible screening and treatment strategies for syphilis in multiple countries , including Peru , Tanzania and Zambia . This range included a sequential strategy using a treponemal RDT followed by a dual trep/non-trep RDT . They found that the dual-only strategy was significantly higher cost than the sequential strategy in all three countries , but resulted in more true cases being detected and treated , with the result that cost-effectiveness was about the same in two out of three countries , namely Tanzania and Zambia , where prevalence was highest . No such economic evaluation of testing strategies has been done for yaws . We therefore evaluate a two-assay sequential testing strategy in terms of both its cost and cost-effectiveness relative to a single-assay testing strategy . In the sequential strategy , a treponemal RDT is used as the screening assay of the testing strategy , followed by reflex testing with a trep/non-trep RDT for only the reactive treponemal specimens , as depicted in Fig 1 . This strategy avoids unnecessary dual treponemal/non-treponemal testing of individuals with no past or current yaws infection ( i . e . treponemal negative ) . The sequential testing strategy is compared to a single-assay testing strategy using the trep/non-trep RDT on the entire testing population . We aim to establish the conditions ( namely , prevalence of past/current infection and relative prices of the treponemal and trep/non-trep tests ) under which the sequential strategy would be cost-saving or cost-effective relative to the combined strategy , for the purposes of 1 ) individual diagnosis and 2 ) community surveillance . By diagnosis , we mean confirmation of clinically suspected cases in individuals before TCT or during TTT; by surveillance we mean screening of communities ( mostly asymptomatic individuals ) for the purpose of verification of the interruption of transmission in population after TCT and in countries of historic endemicity .
We use cohort decision analysis to examine the diagnostic and cost outcomes . We estimate cost and cost-effectiveness of the alternative testing strategies in a hypothetical testing population of 1000 people at different levels of past or current prevalence . We place these results in the context of treponemal positive and dually positive prevalences in Ghana , Papua New Guinea , Solomon Islands and Vanuatu—four endemic countries in which population serosurveys were undertaken in the years 2013–2014 . These surveys were administered both pre- and post-TCT . In estimating costs , we take the perspective of the global yaws eradication programme and national health systems . We include the cost of commodities to be funded in large part by the global yaws eradication programme , and the cost of other inputs such as labor to be supplied by the national health system . We apply a unit cost of US$ 2 . 50 for each trep/non-trep RDT . For the sequential strategy , we apply a unit cost of US$ 0 . 45 for each treponemal RDT , and US$ 2 . 50 for each trep/non-trep RDT . We also add the cost of alcohol swabs ( $3 for 100 ) , sterile lancets ( $375 for 2000 ) and non-sterile gloves ( $3 for 50 pairs ) . These prices are consistent with the UNICEF supply catalogue . [11] These ancillary costs increase the unit cost of each trep/non-trep RDT and treponemal RDT to US$ 2 . 78 and US$ 0 . 73 respectively . We consider that every test requires 2–5 minutes of a district-level laboratory technician’s time ( depending on experience , this is the time it takes to collect the sample , execute the test , read and report the result ) . It takes 10–15 minutes between execution of the test and reading of its results , but technicians can attend to other patients during that time . We asked national yaws eradication programmes to provide estimates of the wage of a district-level laboratory technician ( in US$ ) . It ranged from US$ 210–510 per month in 11 of the 13 endemic countries , and US$ 1500–1585 per month in two small island developing states ( Solomon Islands and Vanuatu ) . In the sequential strategy , the trep/non-trep RDT is applied only to treponemal test positives ( true and false positives ) . Total costs ( and savings ) therefore depend not only on the unit costs described above , but on the sensitivity and specificity of the treponemal RDT for yaws testing . All else equal , a less sensitive ( specific ) treponemal RDT will result in a smaller ( larger ) number of trep /non-trep RDTs required in the sequential testing strategy . We use sensitivity and specificity of the treponemal RDT from the Jafari et al . ( 2013 ) metanalysis . [12] Sensitivities and specificities are reported in Table 1 . In probabilistic sensitivity analysis ( PSA ) , we use the 95% confidence intervals for the sensitivity and specificity results . Using the Jafari et al ( 2013 ) data , we calculate sensitivity and specificity of the treponemal RDT for two relevant subgroups: clinical syphilis cases to be confirmed at sexually transmitted infection clinics , and ( asymptomatic ) pregnant women to be screened at ante natal care ( ANC ) clinics . Unfortunately , the results from Jafari et al . ( 2013 ) relate to syphilis testing only—there is no evidence of the performance of the treponemal RDT for yaws testing . Marks et al . ( 2016 ) found that the sensitivities of both components of the trep/non-trep RDT were higher in patients with syphilis than in patients with yaws at low titers , but not at high titers . [5] It is possible , if not probable , that the sensitivity of the treponemal RDT may therefore be worse for yaws than for syphilis . We therefore adjust ( downward ) the sensitivity of the treponemal RDT by the ratio of the sensitivity of the trep/non-trep RDT for yaws to the sensitivity of the trep/non-trep RDT for syphilis . This adjustment , while crude , allows for the possibility that the sensitivity of the trepenomal RDT could be inferior to that of the treponemal line of the trep/non-trep RDT . In PSA , we allow the sensitivity of the treponemal RDT to vary between this adjusted number and that of the treponemal line of the trep/non-trep RDT . We assume that the specificity of the treponemal RDT for yaws is the same as that of the treponemal line of the trep/non-trep RDT . The hypothetical performance of the treponemal RDT for yaws is reported in Table 1 . We multiply unit costs by the total number of each test required . From total costs , we calculate the cost savings associated with sequential testing strategy . We then calculate the so-called threshold unit cost of the trep/non-trep RDT at which the sequential strategy would no longer be cost-saving , assuming a fixed price for the treponemal RDT . That is , we calculate the unit cost of the trep/non-trep RDT such that: Cd×P<Ct×P+Cd×P×{Tp×Set+ ( 1−Tp ) × ( 1−Spt ) } And where: Cd is the unit cost of the dual trep/non-trep RDT , including the price of the assay as well as ancillary costs; P is the population to be tested; Ct is the unit cost of the treponemal RDT , including the price of the assay as well as ancillary costs; Tp is the prevelance of past/current infection in the testing population; Set is the sensitivity of the treponemal RDT; and Spt is the specificity of the treponemal RDT . Simplifying and re-arranging , the sequential strategy is no longer cost-saving when: Cd<Ct1−{Tp×Set+ ( 1−Tp ) × ( 1−Spt ) } Or: ( Cd−Ct ) Cd<Tp×Set+ ( 1−Tp ) × ( 1−Spt ) That is , when the percentage difference in unit cost of the treponemal RDT relative to the trep/non-trep RDT is less than the percentage of cases that will test positive using the treponemal RDT , which includes both true and false positives . This reactivity rate is determined by the treponemal positive prevelance ( Tp ) and sensitivity ( Set ) and specificity ( Spt ) of the treponemal RDT . At current prices of the trep/non-trep and treponemal RDTs , the reactivity rate would have to be more than about 74% . Of course , a low reactivity rate of the treponemal RDT , while leading to cost-savings , may not be cost-effective if it results in fewer correct diagnoses . We calculate the total number of correct diagnoses for each strategy over the full range of prevalences . Decision trees depicting the possible pathways to correct diagnosis are depicted for both strategies in Figs 2 and 3 . We assume that the percentage of past/current infections that are current is the same in the subset of true past/current infection positives identified by the treponemal RDT as it is in the total population of past/current infections ( Fig 3 ) . This assumption is thought to be reasonable; in Marks et al ( 2016 ) , 74% of TPHA positive people had positive RPR; 75% of people with a positive treponemal RDT had a positive RPR , and 77% had a positive non-trep RDT . We also assume that the prevalence of current infection among false past/current infection negatives is ( at most ) equal to the prevalence of current infection among past/current infections; in any case , in an eradication programme , the number of false negatives will tend towards zero . We use sensitivity and specificity of the trep/non-trep RDT from the Marks et al . ( 2016 ) meta-analysis . Performance characteristics depend on the use case of the trep/non-trep RDT: yaws diagnosis or yaws surveillance . In confirmation of clinical cases , more people will have high titres ( where the test performs better ) while in confirmation of the interruption of transmission more people will have low titres ( where the test performs less well ) . We therefore consider performance characteristics for primary and secondary disease , or asymptomatic cases ( Table 1 ) . The former is applied to populations with clinical symptoms requiring diagnosis , while the latter is applied to populations requiring surveillance . We calculate the cost per correct diagnosis ( true current infection positive or negative ) under each strategy ( sequential or combined strategy ) and use case ( diagnosis or surveillance ) . However , we also report the cost per true positive diagnosis , considering that true positive and negative diagnoses may not be equivalent in their benefits . In the context of individual diagnosis for eradication , for example , true positive diagnosis may be more important than a true negative diagnosis , at least from the perspective of the health system . The incremental cost of treating a false positive is relatively trivial , even considering the cost attributed to any side effects . There are very few and minor side effects associated with azithromycin and indeed , many collateral benefits for diarrheal and other diseases . From the perspective of patients , however , there may be psychosocial costs associated with false positive results . We then calculate the incremental cost-effectiveness ratio ( ICER ) of the higher cost combined strategy , for the range of treponemal and dually positive prevalences over which it is not dominated by the sequential strategy . By not dominated , we mean that while the cost is higher , the number of correct diagnoses is also higher . We present cost savings and cost-effectiveness of the alternative testing strategies in the context of survey population prevalences obtained in four countries: Ghana , Papua New Guinea ( PNG ) , Solomon Islands , and Vanuatu . [13–15] Pre-TCT survey population prevalences obtained using trep/non-trep RDTs are provided in Supporting Information S1 Table . Treponemal positive prevalence varied from 22% in Vanuatu to 51% in PNG . Among those testing treponemal positive , non-treponemal positives were between 21% in Solomon Islands and 71% in Vanuatu . Out of the total population tested , dually positive prevalences were between 7% in Solomon Islands and 18% in PNG . Post-TCT survey population prevalences obtained using trep/non-trep RDTs are presented for four countries in Supporting Information S2 Table . The treponemal positive prevalence decreased to between 15% in Ghana and 42% in Solomon Islands . Among those testing treponemal positive , non-treponemal positives were between 5% in Solomon Islands and 49% in Vanuatu . The dually positive prevalence decreased , as a percentage of the population tested , to between 1% in Solomon Islands and 8% in Vanuatu . We are not in this paper attributing these reductions in prevalence to TCT . We are simply using pre- and post-TCT prevalence as a proxy for the prevalence that one might encounter in community surveillance and individual diagnosis settings , respectively . Use cases and prevalences of the testing population are not independent . In particular , prevalences will be higher when doing individual diagnosis than when doing community surveillance . We therefore focus on the following plausible ranges of prevalence: for individual diagnosis , current/past infection prevalence of 20–55% , of which 20–75% is currently infected; for community screening , current/past infection prevalence of 15–45% , of which 5–50% are currently infected . We report best estimates using the median of 1000 simulations and the 95% confidence intervals using the 2 . 5th and 97 . 5th centiles . All data analysis and visualization were done using R ( Foundation for Statistical Computing , Vienna , Austria ) . [16] All the necessary code is provided as Supporting Information .
At the current price of the treponemal RDT and a high prevalence of past/current infection of 51% ( the treponemal positive prevalence in pre-TCT Papua New Guinea ) , we obtain a threshold unit cost for the trep/non-trep RDT of US$ 1 . 38 ( 1 . 31–1 . 46 ) , including ancillary costs ( i . e . swabs , lancets and gloves ) and laboratory technician time , or US$ 1 . 08 ( 1 . 02–1 . 14 ) for the price of the assay alone . This is the unit cost below which the sequential strategy would no longer be cost-saving for individual diagnosis in a testing population where about one in two are or have been infected . More generally , costs savings of the sequential strategy in diagnosing 1000 individuals are presented in Fig 4 ( top row ) across all scenarios of prevalence . At current prices of the treponemal and trep/non-trep RDTs , the sequential strategy is cost-saving if the prevalence of past/current infection of the testing population is less than 85% ( 81–90 ) . Within the plausible range of prevalence ( 20–55% ) , the savings are US$ 1079 ( 703–1448 ) per 1000 people tested . Above 85% , it is the combined strategy that is cost-saving . The number of correct diagnoses of current infection ( true positives and true negatives ) is presented in Supporting Information S1 Fig ( top two rows ) . Based on our assumptions about the relative performance of the treponemal RDT for yaws , the number of correct diagnoses is somewhat higher under the combined strategy than under the sequential strategy . However , in the plausible range of prevalences , more than 900 correct diagnoses are made for every 1000 people tested under both strategies . It is only at higher prevalences that differences between the strategies become non-trivial . The number of true current infection positives is presented in Supporting Information S2 Fig . Given our assumptions about the relative performance of the treponemal RDT , there is a range of prevalences over which a higher cost and ( hypothetically ) more sensitive combined strategy could be more cost-effective than the sequential strategy . Incremental cost-effectiveness ratios ( ICERs; ratio of incremental costs over incremental benefits or incremental cost per correct diagnosis gained ) are presented in Fig 5 ( top row ) , across different scenarios of prevalence . At prevalence of past/current infection of 51% and current infection of 18% ( again , the trep/non-trep RDT positive prevalences in pre-TCT Papua New Guinea ) , the ICER is US$ 58 ( 42–103 ) per correct diagnosis gained . At very high prevalence of past/current infection , where it becomes cost-saving , a more sensitive combined strategy may dominate the sequential strategy . At very low prevalence of either past/current infection or current infection , it is specificity that matters more for the number of correct diagnoses , and even a more sensitive combined strategy may be dominated by the sequential strategy . In theory , there is a combination of prevalences ( very high prevalence of past/current infection and very low prevalence of current infection ) where a more sensitive combined strategy could produce fewer correct diagnoses of current infection ( this is the area depicted by a black rectangle in Fig 5 ) . In practice , however , this combination is unlikely . In Supporting Information S3 Fig ( top row ) , we present the same figure , but using only true positive diagnoses in the denominator of the ICER . Here , the ICER is US$ 38 ( 32–48 ) at prevalence of past/current infection of 51% and current infection of 18% . Given our assumptions about the relative performance of the treponemal RDT , the combined strategy is nowhere dominated by the sequential strategy when considering only true positive diagnoses; the combined strategy dominates the sequential strategy wherever it is cost-saving . The cost-effectiveness plane is presented in Supporting Information S4 Fig ( top row ) , at the lower and upper limits of the plausible range of prevalence: for individual diagnosis , the current/past infection prevalence ranges from 20% ( lower limit ) to 55% ( upper limit ) , of which 20% ( lower limit ) or 75% ( upper limit ) are currently infected . It shows that at the lower limit , the combined testing strategy is less effective in spite of being more costly; at the upper limit it results in somewhere between 20–60 additional correct diagnoses ( per 1000 tested ) for somewhere between US$ 500–600 . At the current cost of the treponemal RDT and a low prevalence of past/current infection of 15% of the testing population ( similar to Ghana post-TCT ) , we obtain a threshold unit cost for the trep/non-trep RDT of US$ 0 . 84 ( 0 . 81–0 . 88 ) , including ancillary costs and laboratory technician time , or US$ 0 . 54 ( 0 . 52–0 . 56 ) for the price of the assay alone . At current prices of the treponemal and trep/non-trep RDTs , the sequential strategy is cost-saving in surveillance at all levels of prevalence of past/current infection—see Fig 4 ( bottom row ) . Within the plausible range of prevalence ( 15–45% ) , the savings are US$ 1527 ( 1279–1748 ) per 1000 population . The number of correct diagnoses of current infection ( true positives and true negatives ) is presented in Supporting Information S1 Fig ( bottom two rows ) . Again , based on our assumptions about the relative performance of the treponemal RDT for yaws , the number of correct diagnoses is somewhat higher under the combined strategy than under the sequential strategy . Again , under both strategies , in the plausible range of prevalences , more than 900 correct diagnoses are made for every 1000 people tested . ICERs are presented in Fig 5 ( bottom row ) . At a prevalence of past/current infection of 42% and prevalence of current infection of 6% ( similar to post-TCT Papua New Guinea ) , the best estimate is US$ 355 per correct diagnosis gained by the combined strategy . However , the low estimate is in an area of the plot where the combined strategy is dominated by the sequential strategy . Again , at very low prevalence of either past/current infection or current infection , it is specificity that matters more for the number of correct diagnoses . In Supporting Information S3 Fig ( bottom row ) , we present the same figure , but using only true positive diagnoses in the denominator of the ICER . Here , the ICER is US$ 117 ( 90–155 ) at a prevalence of past/current infection of 42% and prevalence of current infection of 6% . Given our assumptions about the relative performance of the treponemal RDT , the combined strategy is nowhere dominated by the sequential strategy when considering only true positive diagnoses; but , unlike in the diagnosis use case , the combined strategy is never cost-saving and nowhere dominates the sequential strategy . The cost-effectiveness plane is presented in Supporting Information S4 Fig ( bottom row ) , again at the lower and upper limits of the plausible range of prevalences: for community surveillance , current/past infection prevalence ranges from 15% ( lower ) to 45% ( upper ) , of which 5% ( lower ) to 50% ( upper ) are currently infected .
In summary , this study finds that , at current prices , a sequential strategy is cost-saving relative to use of a combined strategy for individual diagnosis , at a prevalence of past/current infection less than 85% ( 81–90 ) ; it is cost-saving for community surveillance at a prevalence of less than 100% ( i . e . always ) . The threshold prevalence for community surveillance is so high because when titres are low , the reactivity rate of the treponemal RDT is so low and so few people will need a non-treponemal result . It turns out that the sequential strategy is no longer cost-saving for individual diagnosis in testing populations with high prevalence of past/current infection ( i . e . 51% ) when the price of the trep/non-trep RDT is less than US$ 1 . 08 ( 1 . 02–1 . 14 ) . Likewise , the sequential strategy is no longer cost-saving for community surveillance in populations with low prevalence of past/current infection ( i . e . 15% ) when the price of the trep/non-trep RDT is less than US$ 0 . 54 ( 0 . 52–0 . 56 ) . In the absence of evidence assessing relative performance ( sensitivity and specificity ) , the cost-effectiveness of a hypothetically more sensitive combined strategy is uncertain . However , the conditions under which it might be cost-effective are fairly limited . This finding is true even under fairly pessimistic assumptions about the performance of the treponemal RDT for yaws . In addition to its relatively high cost , a major limitation of the current trep/non-trep RDT is its reduced sensitivity for low titer yaws , at least in the Solomon Islands where it was tested . Further research is required to determine whether available treponemal RDTs ( for syphilis ) perform any better for low titer yaws . Reduced sensitivity is likely to be a greater problem when using the test as part of yaws surveillance; a higher sensitivity assay will be needed to confirm interruption of transmission , such as RPR or even polymerase chain reaction ( PCR ) as PCR positive and trep/non-trep RDT negative cases have been observed . Criteria for eradication of yaws in the Morges strategy of 2012 are: 1 ) absence of new indigenous cases for 3 consecutive years; 2 ) absence of evidence of transmission for 3 continuous years measured with sero-surveys among children aged 1–5 years ( for example , no young children with RPR sero-reactivity ) ; and 3 ) negative PCR for Treponema pallidum subspecies pertenue in suspected lesions . [17] There are several limitations to this study . Serology does not result in identification of all cases of current yaws where early infection may be seronegative , and seropositive patients could have persisting antibodies after successful treatment . Therefore PCR is now considered the gold standard for the diagnosis of active yaws . The sensitivity and specificity of both the treponemal RDT and trep/non-trep RDT have not been assessed relative to PCR . However , there is no reason to believe that the bias favours the sequential testing strategy , as both the treponemal and trep/non-trep RDTs have been assessed against the same standard . As described in the methods , treponemal RDTs have not been assessed for yaws , and we have therefore had to infer sensitivity and specificity from test performance for syphilis , as reported by Jafari et al ( 2013 ) . Performance in syphilis is likely to be better than it is in yaws , as the trep/non-trep RDT also performs better in syphilis than in yaws . Although titres are often higher in syphilis compared with yaws ( especially asymptomatic disease ) , it is unclear why Marks et al ( 2016 ) found that trep/non-trep performance was worse for yaws even when controlling for titre . Again , yaws and syphilis treponemes differ in less than 0 . 2% of the genome sequence . [2] Notwithstanding , that the specificity for yaws will be equal to or lower than that reported for syphilis should possibly be further assessed . More generally , it should be noted that reported sensitivities and specificities can depend upon contextual factors , at least partially , and therefore the results of the meta-analyses of both Jafari et al ( 2013 ) and Marks et al ( 2016 ) may not fully reflect test performance in all settings , which underscores the need of interpreting our results in the light of the sensitivity analysis we performed . Our probabilistic sensitivity analysis was focused on uncertainty around the relative performance of the tests , and to a lesser extent on costs . We assumed that the cost of traded commodities , procured by the global yaws eradication programme from international markets , was deterministic . Furthermore , we had only one estimate per country for the wage of laboratory technicians at the district level . In settings where either the commodity or labor costs are highly uncertain and/or their distribution highly skewed , a more sophisticated analysis of costs could be warranted . We have not considered the time and other indirect costs incurred by the tested populations . The treponemal RDT produces results after 10 minutes; the trep/non-trep RDT requires 15 min . Under the sequential strategy , therefore , treponemal negatives wait 5 fewer minutes and treponemal positives wait 10 more minutes . Had we taken these costs into account , the results might have been less favourable to the sequential testing strategy in higher treponemal positive settings . Therefore , from a patient’s perspective too , there is a case to be made for negotiating lower prices for the trep/non-trep RDT in settings with a high prevalence of past/current infection . A cheaper trep/non-trep RDT is needed , costing no more than US$0 . 50–1 . 00 , depending on the use case . However , other strategies are theoretically possible . RPR is already available and the centralized execution and availability of results may not be a major problem in some settings . Furthermore , a non-trep point of care RDT ( alone , without the treponemal RDT ) is technically feasible but has not yet been developed . An alternative strategy could involve the treponemal RDT followed by either RPR or the non-trep RDT . A reverse sequential strategy ( non-trep test followed by the trep test ) could also be possible . Of course , these alternative sequential strategies not considered in our analysis would only be cost-saving relative to our original sequential strategy as long as the price of the RPR or non-trep RDT did not exceed the cost of the trep/non-trep RDT . Unfortunately , the cost of RPR , including transport to centralized or even international laboratories , will be prohibitively high in most of the settings in question , and we know of no plans to manufacture a non-trep point of care RDT . Diagnosis and surveillance are essential to the yaws eradication effort . However , the yaws eradication effort is yet to be funded . [18] There are two situations of particular relevance in which savings could be substantial if the sequential testing strategy was implemented: first , during mass screening campaigns , before and after TCT; second , during final screening campaigns , including verification of the interruption of transmission . Cost savings from the sequential strategy could be reallocated to other essential interventions , such as sensitization to increase treatment coverage . Our results will help enhance the cost-effectiveness of yaws programmes in the 13 countries known to be currently endemic . It will also inform efforts in the much larger group of 71 countries with a history of yaws , many of which will have to undertake surveillance to confirm the interruption of transmission .
|
Yaws is a non-venereal treponemal infection . The disease is targeted by WHO for eradication by 2020 . Testing is envisaged for diagnosis to confirm of clinical cases during treatment campaigns and for surveillance to certify the interruption of transmission . However resources available to the global eradication programme are severely limited and the cost of testing must be contained . Testing requires simultaneous detection of antibodies to both treponemal and non-treponemal antigens for diagnosis of active infection . Currently , there is one commercially available rapid diagnostic test for yaws that can do just that . However , it is considerably more expensive than the available syphilis tests detecting treponemal antibodies only . We evaluate the cost and cost-effectiveness of a sequential testing strategy ( using the treponemal test first , before the combined test ) , relative to a combined testing strategy ( using only the combined test ) . We consider the two use cases: individual diagnosis and community surveillance . We find that the sequential strategy is cost-saving for both diagnosis and surveillance in most relevant settings . Yaws eradication programme should consider adopting the sequential strategy . Still , a cheaper trep/non-trep RDT is needed , costing no more than US$ 0 . 50–1 . 00 . Our results will help enhance the cost-effectiveness of yaws programmes in the 13 countries known to be currently endemic . It will also inform efforts in the much larger group of 71 countries with a history of yaws , many of which will have to undertake surveillance to confirm the interruption of transmission .
|
[
"Abstract",
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"Results",
"Discussion"
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2017
|
The cost and cost-effectiveness of rapid testing strategies for yaws diagnosis and surveillance
|
Soil Transmitted Helminth ( STH ) infections negatively impact physical and mental development in human populations . Current WHO guidelines recommend morbidity control of these infections through mass drug administration ( MDA ) using albendazole ( ABZ ) or mebendazole . Despite major reductions in STH associated morbidity globally , not all programs have demonstrated the expected impact on prevalence of parasite infections . These therapeutic failures may be related to poor programmatic coverage , suboptimal adherence or the exposure of parasites to sub-therapeutic drug concentrations . As part of the DeWorm3 project , we sought to characterize the serum disposition kinetics and pattern of urinary excretion of ABZ and its main metabolites ABZ sulphoxide ( ABZSO ) and ABZ sulphone ( ABZSO2 ) in humans , and the assessment of the duration and optimal time point where ABZ and/or its metabolites can be measured in urine as an indirect assessment of an individual’s adherence to treatment . Consecutive venous blood and urine samples were collected from eight ( 8 ) human volunteers up to 72 h post-ABZ oral administration . ABZ/metabolites were quantified by HPLC . The ABZSO metabolite was the main analyte recovered both in serum and urine . ABZSO Cmax in serum was 1 . 20 ± 0 . 44 μg/mL , reached at 4 . 75 h post-treatment . In urine , ABZSO Cmax was 3 . 24 ± 1 . 51 μg/mL reached at 6 . 50 h post-ABZ administration . Pharmacokinetic data obtained for ABZ metabolites in serum and urine , including the recovery of the ABZ sulphoxide derivative up to 72 h in both matrixes and the recovery of the amino-ABZ sulphone metabolite in urine samples , are suggesting the possibility of developing a urine based method to assess compliance to ABZ treatment . Such an assay may be useful to optimize ABZ use in human patients . ClinicalTrials . gov NCT03192449 .
The neglected tropical diseases ( NTDs ) are a group of infections which affect the poorest regions of the world [1] . Among the NTDs , Soil-transmitted helminths ( STH , the roundworm Ascaris lumbricoides , the whipworm Trichuris trichiura and the two hookworm species Necator americanus and Ancylostoma duodenale ) are among the most prevalent parasites worldwide , disproportionately affecting human populations living without adequate water and sanitation [2] . It is estimated that more than 1 . 4 billion people are infected with at least one of the four STH species [3] . STH persist for years in the human gastrointestinal tract , negatively impacting nutritional status , individual productivity and physical and mental development [1 , 4] . The World Health Organization ( WHO ) recommendations for control of STH include preventive chemotherapy through regular mass drug administration ( MDA ) for school age children and other at-risk groups living in endemic areas where prevalence of STH exceeds 20% . Currently , deworming is carried out with single oral dose of a benzimidazole ( BZD ) anthelmintic drug ( albendazole ( ABZ ) or mebendazole ( MBZ ) ) once or twice year depending on baseline prevalence [5] . Despite significant success in scaling up deworming programs and reducing associated morbidity , program coverage globally is still less than optimal [6] . In addition , some areas report apparent reductions in treatment efficacy following multiple rounds of MDA . Treatment failure may be related to poor programmatic coverage or adherence , reduced drug efficacy through suboptimal drug formulation , poor drug absorption or the development of resistance . It is critical to differentiate a lack of coverage or adherence to drug from issues related to drug quality or the development of drug resistance . Current coverage estimates rely on subjective reporting of coverage and adherence through an interview based coverage survey . Such instruments are prone to reporter and interviewer bias and may not adequately reflect true treatment coverage and/or adherence [7] . The development of improved tools to accurately determine treatment coverage and adherence may be important to enable programs to more accurately report true coverage of MDA and to respond to situations where treatment failure is suspected . In fact , validation of compliance is extremely important also for lymphatic filariasis elimination , and like with STH , there are currently no tools to use to measure it . Accurate measurement and determination of coverage and adherence to MDA has become even more critical as the STH community begins to think beyond control towards the possibility of disease elimination . Although annual MDA may reduce the prevalence of STH infection and control morbidity in school-age children , reinfection following treatment is common and this strategy is likely to be insufficient to break STH transmission [6] . Recent mathematical modelling studies suggests that MDA might be sufficient to interrupt STH transmission if new strategies , including expanding MDA to adults and/or treating children more frequently , are used [8] . These models suggest that exceptionally high coverage and adherence will be needed to interrupt transmission through MDA alone . The widespread use of BZD anthelmintics , particularly the methylcarbamate derivatives such as ABZ , is based on their high efficacy , low toxicity , and broad-spectrum of activity [9] . While there are limited data on the pharmacokinetics ( PK ) and urinary excretion of ABZ and its metabolites in humans , it is known is that after absorption , BZD compounds are extensively metabolized . Biotransformation takes place predominantly in the liver [10] , although metabolic activity is apparent in extrahepatic tissues such as the lungs [11] and gastrointestinal ( GI ) tract [12] Consequently , ABZ ( the parent compound ) is undetectable in the systemic circulation after administration [13–18] . ABZ is rapidly oxidized into its active metabolite ABZ-sulphoxide ( ABZSO ) and further liver oxidative and hydrolytic metabolism produces ABZ sulphone ( ABZSO2 ) and albendazole amino sulphone ( ABZ-SO2–NH2 ) , respectively . ABZSO and ABZSO2 are the metabolites mainly found in the systemic circulation [15 , 16] . ABZSO appears to be the main metabolite that is recoverable in human plasma [13 , 19–21] and in urine [22] . As part of the DeWorm3 project , a large series of community cluster randomized trials to determine the feasibility of interrupting STH transmission , we sought 1 ) to develop and validate an analytical method to quantify concentrations of ABZ and its metabolites , ABZSO and ABZSO2 , in human serum and urine samples , 2 ) to conduct a study of the serum pharmacokinetics and urinary excretion of ABZ and its metabolites in human volunteers , and 3 ) to determine the optimal and the longest time period after treatment when either ABZ and/or its metabolites can be measured in urine as an indirect assessment of an individual’s adherence to treatment .
The experimental protocol and Informed Consent Form ( ICF ) were approved by the Bioethics Committee at the Colegio Médico de Salta ( Argentina ) . All the volunteers provided written consent for their participation in the study before any study procedures commenced . Volunteers received a small stipend for their collaboration . The trial is registered at clinicaltrials . gov ( REF NCT03192449 ) . Adults age between 18 and 45 years and weighting up to 75 Kg with no known chronic medical conditions and a normal physical exam were recruited for participation . Female volunteers had to use reliable contraceptive measures to be eligible to participate . Exclusion criteria were: Intake of ABZ or other BZD drugs within the last 30 days; malabsorption or other syndromes that could compromise the tolerability or absorption of ABZ; history of hypersensitivity or intolerance to ABZ or its inactive ingredients; acute clinical condition; pregnancy or breast feeding . Pure reference standards of ABZ , ABZSO , ABZSO2 and oxibendazole ( OBZ ) ( 99% purity ) were purchased from Sigma–Aldrich ( St . Louis , MO , USA ) . The HPLC grade solvents acetonitrile and methanol were from Baker , Mallinckrodt ( Baker , Phillipsburg , USA ) . Ethyl acetate was from Anedra ( BA , Argentina ) . Water was distilled and deionized using a water purification system ( Simplicity , Millipore , São Paulo , Brazil ) . ABZ tabs ( 400mg ) administered to human volunteers was provided by GlaxoSmithKline . Eight ( 8 ) healthy volunteers ( four male and four female , 18–40 years of age; body weight between 53 and 75 kg ) participated in the trial . The treatment and sampling phases of the study were conducted at the Laboratory of the “Instituto de Investigaciones en Enfermedades Tropicales” at the Oran branch of the Universidad Nacional de Salta , Argentina . Prior to ABZ treatment , all subjects were provided with a standard meal ( fat content 40 g ) and baseline blood ( 5 mL ) and urine ( 20 mL ) samples were obtained ( sampling time = 0 ) . After 15 min a single postprandial ( fat content 40 g ) oral dose of ABZ ( 400 mg ) was administered and consecutive venous blood samples were collected by a registered nurse at 2 , 4 , 8 , 12 , 24 , 36 , 48 and 72 h post-treatment ( p . t . ) . Blood was collected into tubes and centrifuged immediately . Serum samples were stored at −70°C until assayed . Urine samples were collected at the following specific times: 4 , 8 , 12 , 24 , 36 , 48 and 72 h . Samples were stored at -20°C until HPLC analysis of ABZ/metabolites . Experimental and fortified serum and urine samples were analyzed for ABZ , ABZSO and ABZSO2 by HPLC . After extraction , fifty ( 50 ) μL of sample was injected into a Shimadzu Chromatography System ( Shimadzu Corporation , Kyoto , Japan ) . The equipment is composed for a LC-20AT quaternary pump , an automatic sample injector ( SIL-10AF ) , an ultraviolet visible spectophotometric detector ( UV ) ( SPD-20A ) set at a wavelength of 292 nm , a column oven ( CTO-10AS vp ) set at 30°C , and a CBM-20A data integrator . Data and chromatograms were collected and analyzed using the Class LC10 software ( SPD-10A , Shimadzu Corporation , Kyoto , Japan ) . A C18 reversed-phase column ( Gemini , Phenomenex , USA ) of 250 x 4 . 6 mm with 5 μm particle size was used for separation . Elution from the stationary phase was carried out at a flow rate of 1 . 2 mL/min using acetonitrile and ammonium acetate buffer ( 0 . 025 M , pH 6 . 6 ) as the mobile phase that was pumped with variable gradient ( acetonitrile: ammonium acetate buffer ) during the run ( 16 min ) . The gradient changed from 27:73 to 50:50 in 5 min , then maintained for 7 min and modified to 27:73 in 1 min , in which was maintained during 4 min . The compounds were identified using the retention times of 99% pure reference standards . Before starting the measurement of ABZ , ABZSO and ABZSO2 concentrations in serum and urine samples , a complete validation of the analytical methodologies was performed . The details of the validation of the analytical methodology ( both in serum and urine ) and their results are explained as supplementary information . The pharmacokinetic analysis of the serum and urine concentrations obtained after ABZ single oral administration ( 400 mg ) was performed using the program PK Solution 2 . 0 ( Summit Research Services , Ashland , USA ) , and pharmacokinetic analysis was performed using non compartmental ( area ) and compartmental ( exponential terms ) methods without presuming any specific compartmental model . The peak concentration ( Cmax ) and time to peak concentration ( Tmax ) were displayed from the plotted concentration-time curve of each analyte . The formation half-life ( T½for ) and the elimination half-life ( T½el ) were calculated as ln2/kabs and ln2/λel , respectively , where kfor represents the first order formation rate constant and λel is the elimination rate constant . The area under the concentration time-curve ( AUC ) was calculated by means the trapezoidal rule [23] up to 72 h , and further extrapolated to infinity by dividing the last experimental concentration by the terminal slope ( β ) . Statistical moment theory was applied to calculate the mean residence time ( MRT ) in serum as follows: MRT = AUMC/AUC; where AUC is defined previously and AUMC is the area under the curve of the product of time and the serum drug concentration vs . time from zero to infinity [24] . Data are expressed as arithmetic mean ± standard deviations ( SD ) . Correlation between individual serum/urine human concentrations was performed by parametric analysis ( Pearson r , r2 ) .
The validated method was successfully applied to quantify ABZ/metabolites in both serum and urine samples from humans treated with ABZ ( 400mg ) . After ABZ administration , only trace amounts of ABZ parent drug were detected in serum between 2 and 8 h p . t . . ABZ was rapidly metabolized , with ABZSO and ABZSO2 measured in the bloodstream at the first sampling time ( 2 h p . t . ) . The pharmacologically active ABZSO metabolite was the analyte recovered at the highest concentrations which rapidly increased to reach its peak concentration ( Cmax = 1 . 20 ± 0 . 44 μg/mL ) at 4 . 75 h ( Tmax ) p . t . . The systemic drug exposure , estimated as the ABZSO AUC 0-LOQ value , was 21 . 4 ± 1 . 19 μg·h/mL . This analyte was measured in the bloodstream up to 72 h after ABZ oral administration in seven volunteers ( volunteer 2–7 ) . In serum sample collected from volunteer #1 , ABZSO was detected up to 24 h p . t . . The mean serum concentration profiles vs time for ABZ , ABZSO and ABZSO2 and the individual AUC0-LOQ value for ABZSO obtained after ABZ administration are shown in Fig 1 . Low ( and erratic ) concentrations of the inactive ABZSO2 metabolite were quantified between 4 and 12 h p . t . in some of the treated volunteers . The pharmacokinetic analysis of ABZ and its ABZSO2 in serum was not performed , since most of the measured concentration values were under the LOQ . The complete pharmacokinetic analysis , including individual and mean ( ±SD ) serum pharmacokinetic parameters obtained for ABZSO are shown in Table 1 . The ABZSO metabolite was rapidly excreted in urine following the ABZ treatment and was the main ABZ metabolite recovered between 4 h ( first sampling time ) and 72 h p . t . . ABZSO peak urine concentration ( 3 . 24 ± 1 . 51 μg/mL ) was reached at 6 . 50 h p . t . ( Tmax ) . The ABZSO urinary exposure , ( estimated as the AUC ) was 50 . 2 μg·h/mL ( Table 2 ) which resulted higher ( 2 . 3 fold ) than that measured in serum . Low concentrations of ABZSO2 were quantified in urine between 4 and 8 h p . t . , mostly under the LOQ which precluded any pharmacokinetic analysis . ABZ concentrations in urine were under the limit of detection at all sampling times . The mean urine concentration profile vs . time for ABZSO and its individual AUC0-LOQ value is illustrated in Fig 2 . The individual and mean ( ±SD ) pharmacokinetic parameters describing the urinary excretion of ABZSO are shown in Table 2 . Fig 3 shows the individual ABZSO AUC value both in serum and urine samples obtained from treated volunteers , as well as the comparative ABZSO concentrations in both matrixes up to 72 h p . t . . High correlation was obtained between individual ABZSO concentrations in serum and urine either at 24 or 48 h after ABZ administration . The Pearson correlation coefficient values were 0 . 674 ( 24h ) and 0 . 734 ( 48h ) ( P value 0 . 01 ( 24h ) and 0 . 006 ( 48 h ) ) . Fig 4 shows the mean ABZSO concentrations obtained in serum and urine samples at 24 and 48 h post ABZ-treatment and the correlation between individual ABZSO concentration in serum and urine samples ( 48 h p . t . ) . From the analysis of the urine samples from ABZ-treated volunteers , another relevant chromatographic peak was observed in addition to the ABZSO metabolite peak ( S3 Fig TIFF ) . This chromatographic peak was chemically identified as an oxidative amino-ABZ sulphone derivative . The mean retention time was 4 . 11 min under the previously described chromatographic conditions and it was detected between 4 and 72 h p . t . Although this metabolite was not included in the validation of the analytical methodology , its presence was checked by direct injections of known quantities of an amino-ABZSO2 reference standard ( 99% purity ) solutions in mobile phase .
A major factor contributing to the success of STH control programs is the true coverage and adherence achieved in MDA programs [25] . Here we report promising preliminary data suggesting that it may be possible to develop simple tools to measure metabolites of ABZ in urine to assess treatment coverage/adherence . Optimizing methods to determine coverage and adherence in treated populations offers the opportunity to accurately assess the performance of MDA programs in reaching and treating targeted individuals . In addition , these tools allow programs to modify activities based on a clearer understanding of factors contributing to less than expected STH prevalence and/or intensity reductions . Finally , as concerns emerge regarding the potential for the emergence of drug resistance to commonly used anthelmintics; accurate determination of coverage and adherence allows programs to evaluate whether potential treatment failure is due to the possible emergence of resistance mutations or is simply a result of lower than expected treatment coverage or adherence . In the present study , the serum pharmacokinetic of ABZ was tested up to 72 h post-administration of ABZ . The rapid appearance of ABZSO and ABZSO2 in serum and fast removal of the parent drug , confirm the first pass liver , GI and lungs microsomal oxidation of ABZ previously proposed [10–13] . ABZSO was the main analyte detected in serum samples and was measured up to the last treatment point at 72 hours p . t . . The low concentrations measured for ABZSO2 metabolite , precluded any pharmacokinetic analysis . The ABZSO pharmacokinetic parameters Cmax ( 1 . 20 ± 0 . 44 μg/mL ) and AUC ( 21 . 4 ± 11 . 9 μg . h/mL ) obtained here are consistent with previously reported data [19 , 20 , 26] . The high variations in ABZSO serum concentrations among subjects , observed specially in volunteers #1 ( lowest serum exposure ) and # 8 ( highest serum exposure ) are in concordance with previous reported studies [26 , 27] and may be explained by intrinsic differences among the volunteers , and may be related to individual differences in drug absorption . The overall serum PK parameters for ABZSO observed in the current work are different from those previously reported [19 , 21] , as ABZSO was quantified in higher concentrations and for longer period . The subjects involved in the current work were dosed post-prandially after a 40g fat meal . The administration of ABZ with food increases the permanence of drug formulation at the stomach , maximizing its dissolution and systemic exposure . However , this situation will not necessarily match with the real situation in the field , in which drug exposure levels after ABZ administration in “fasted” patients would be likely much lower . BZD methylcarbamates are formulated as tablets and show only limited GI absorption due to their poor solubility in water . In humans , the stomach plays a critical role in drug dissolution , since the low pH of the stomach fluid facilitates BZD water dissolution , which is the rate-limiting step in the systemic availability of the active drug/metabolites [28] . The plasma concentration profiles of ABZSO reflect the amount of dissolved drug at GI level and the overall drug exposure within the GI tract [29] . We also report here for the first time a complete urinary excretion profile of ABZ/metabolites in humans . ABZSO was the main analyte recovered in urine samples , in agreement with limited data found in the literature [22 , 30] . The urinary excretion of ABZSO was very efficient and the analyte could be measured from the first time point p . t . ( 4 h ) at high concentrations ( 2 . 52 ± 0 . 74 μg/mL ) and remained detectable up to 72 h p . t . . Relevant concentrations were detected at 24 ( 0 . 95 ± 0 . 75 μg/mL ) and 48 h ( 0 . 19 ± 0 . 14 μg/mL ) with all measures over the LOQ obtained for this metabolite . ABZSO was quantified at three days p . t . in seven of eight volunteers , at concentrations close to the LOQ ( 0 . 08 ± 0 . 10 μg/mL ) . In addition , the ABZSO Cmax in urine resulted 2 . 8 times higher than measured in the bloodstream , and the drug exposure , estimated as the ABZSO AUC value resulted 2 . 3 fold higher compared to that measured in serum . These results are promising for the potential to develop a field ready tool to evaluate adherence to treatment using non-invasively obtained biological samples such as urine , collected up to two days after ABZ administration . This “optimal” time refers to that in which the ABZSO concentration can be accurate ( above the limit of quantification ) measured with the validated methodology , and it should also be a practical sampling period for the staff involved in the implementation of control programs . It is important to highlight that the use of urinary metabolite detection as a useful way of monitoring for treatment compliance may depend on the quality of the pharmaceutical product . Drug concentration achieved in bloodstream by drug orally administered depends on the chemical properties of the drug and the pharmaceutical preparations in which the active compound is formulated . The current work has been performed with a specific product ( ABZ tabs , GlaxoSmithKline ) currently used in the MDAs programs . However , there are a wide range of other brands available on local markets of STH endemic countries , which are often more accessible to the local people , but for which the quality remain poorly explored . For instance , the use of this methodology to evaluate treatment compliance can be recommended after administration of a high quality ABZ formulation . Finally , a high positive correlation was observed between ABZSO concentrations in serum and urine in human volunteer at 24 and 48 h after ABZ administration , which could be useful to indirectly estimate ABZSO concentrations in serum , predicting any difference in drug absorption among individuals . As an additional contribution of the present trial , the amino-ABZSO2 metabolite was also recovered ( between 4 and 72 h ) in urine samples from treated human volunteers , which would be a novel approach/alternative to monitor treatment adherence . Amino-ABZSO2 has been identified in the bloodstream in cattle , pigs , sheep and humans [18 , 31 , 32] , and in urine from sheep [31 , 33] after ABZ administration . This may represent a novel metabolite that can also be measured by the validated methodology without any change to monitor treatment adherence . The analytical methodology developed for this project was simple , well-defined , reproducible , precise , accurate and easy to perform . That validated methodology was successfully applied to quantify ABZ and its metabolites , ABZSO and ABZSO2 , in both serum and urine samples from treated human volunteers , and could be also used to quantify amino-ABZSO2 . The pharmacokinetic data obtained for ABZ metabolites in serum and urine , the recovery of the ABZ sulphoxide derivative up to 72 h in both matrixes and the recovery of the amino- ABZSO2 in urine samples , are scientifically solid contributions to optimize ABZ use in MDA interventions through the development of a tool to accurately assess coverage and adherence to ABZ treatment and obtain reliable coverage rates .
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The soil-transmitted-helminths ( STH ) infections are produced by four species of parasites: Ascaris lumbricoides , Trichuris trichiura , and hookworm ( Necator americanus and Ancylostoma duodenale ) . These parasites are transmitted by eggs present in human faeces , which contaminate the environment in areas where sanitation is poor . These diseases negatively impact health and development . Current STH control is based on mass drug administration ( MDA ) programs , mainly through the use of albendazole ( ABZ ) and mebendazole . However , although MDA programs have been shown to reduce the prevalence of STH infection and to control morbidity in school-age children , rapid reinfection is common among treated children and many programs fail to reach coverage targets . Optimizing methods to assess treatment coverage may allow programs to more effectively deliver MDA to populations requiring treatment . We conducted a controlled trial to evaluate the serum pharmacokinetic behaviour and urinary excretion of ABZ and its metabolites in human volunteers . The study focused also on to evaluate , by mean of non-invasively measures , ABZ treatment coverage and adherence . The measurement of ABZSO concentrations both in serum and urine may be useful methods to monitor adherence to ABZ treatment and serve as a more objective measurement of program coverage .
|
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"Abstract",
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"Materials",
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"Results",
"Discussion"
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"medicine",
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"health",
"sciences",
"body",
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"chromatography",
"urine",
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2018
|
Assessment of serum pharmacokinetics and urinary excretion of albendazole and its metabolites in human volunteers
|
The pqs quorum sensing ( QS ) system is crucial for Pseudomonas aeruginosa virulence both in vitro and in animal models of infection and is considered an ideal target for the development of anti-virulence agents . However , the precise role played by each individual component of this complex QS circuit in the control of virulence remains to be elucidated . Key components of the pqs QS system are 2-heptyl-4-hydroxyquinoline ( HHQ ) , 2-heptyl-3-hydroxy-4-quinolone ( PQS ) , 2-heptyl-4-hydroxyquinoline N-oxide ( HQNO ) , the transcriptional regulator PqsR and the PQS-effector element PqsE . To define the individual contribution of each of these components to QS-mediated regulation , transcriptomic analyses were performed and validated on engineered P . aeruginosa strains in which the biosynthesis of 2-alkyl-4-quinolones ( AQs ) and expression of pqsE and pqsR have been uncoupled , facilitating the identification of the genes controlled by individual pqs system components . The results obtained demonstrate that i ) the PQS biosynthetic precursor HHQ triggers a PqsR-dependent positive feedback loop that leads to the increased expression of only the pqsABCDE operon , ii ) PqsE is involved in the regulation of diverse genes coding for key virulence determinants and biofilm development , iii ) PQS promotes AQ biosynthesis , the expression of genes involved in the iron-starvation response and virulence factor production via PqsR-dependent and PqsR-independent pathways , and iv ) HQNO does not influence transcription and hence does not function as a QS signal molecule . Overall this work has facilitated identification of the specific regulons controlled by individual pqs system components and uncovered the ability of PQS to contribute to gene regulation independent of both its ability to activate PqsR and to induce the iron-starvation response .
Pseudomonas aeruginosa is a multi-antibiotic resistant pathogen commonly responsible for hospital-acquired infections and is the main cause of morbidity and mortality in cystic fibrosis [1] . The pathogenicity of P . aeruginosa is multifactorial and host specific relying on the coordinated production of multiple virulence factors and the formation of antibiotic tolerant biofilms [2 , 3] . These are controlled by a quorum sensing ( QS ) intercellular communication network that integrates information on population structure/dynamics and the metabolic status of the cell with environmental cues [4–7] . Since P . aeruginosa QS mutants display attenuated pathogenicity , QS is a promising target for anti-virulence agents [8] . In P . aeruginosa QS involves three major inter-linked QS signalling pathways , namely the las and rhl systems that employ N-acylhomoserine lactones and the pqs QS system that uses 2-alkyl-4-quinolones ( AQs ) as QS signal molecules [5] . Data from expression studies and virulence factor profiling obtained by comparing wild type with different pqs mutants have revealed the extent of the pqs regulon and its relationship with the las and rhl regulons . For example , AQs are required for full transcription of genes coding for exoenzymes , exotoxins , lectins , secondary metabolites ( e . g . , pyocyanin , hydrogen cyanide , rhamnolipids , pyochelin and pyoverdine ) and biofilm development ( reviewed in [9] ) . P . aeruginosa mutants defective in AQ biosynthesis or sensing are severely attenuated in plant and animal infection models [3 , 10 , 11] . Furthermore , AQs are detectable in sputum , blood and urine of individuals with cystic fibrosis and their presence correlates with clinical status [12] . The pqs system incorporates at least four transcriptional units , with pqsABCDE ( PA0996-PA1000 ) and pqsR ( PA1003 ) clustering at the same genetic locus , while pqsH ( PA2587 ) and pqsL ( PA4190 ) are distally located [13] . Our understanding of the molecular mechanisms governing pqs-dependent QS is however limited , largely because of the inter-dependent , auto-regulatory , multi-component nature of the system ( Fig 1 ) [9] . P . aeruginosa produces >50 different AQs [14] of which 2-heptyl-3-hydroxy-4-quinolone ( also known as the Pseudomonas Quinolone Signal , PQS ) and its immediate precursor 2-heptyl-4-hydroxyquinoline ( HHQ ) are most closely associated with QS signalling . Most of the genes required for AQ biosynthesis are located in the pqsABCDE operon ( Fig 1 ) . PqsA converts anthranilic acid to anthraniloyl-CoA that is condensed with malonyl-CoA to form 2-aminobenzoylacetyl-CoA ( 2-ABA-CoA ) in a reaction catalysed by PqsD [15 , 16] . The thioesterase activity of PqsE converts 2-ABA-CoA into 2-aminobenzoylacetate ( 2-ABA ) [17]; HHQ is formed through the condensation of octanoyl-coenzyme A and 2-ABA via the PqsBC heterodimer [18 , 19] . Additional enzymes are required for the biosynthesis of PQS and 2-heptyl-4-hydroxyquinoline N-oxide ( HQNO ) ( Fig 1 ) . Under aerobic conditions , HHQ is oxidized to PQS via the action of the monooxygenase PqsH [20] . A second monooxygenase , PqsL , is required together with the pqsABCD gene products for the synthesis of HQNO and related N-oxides [21] . The pqs system is subject to positive autoregulation , since the LysR-type transcriptional regulator PqsR ( MvfR ) , binds to the promoter region of pqsABCDE ( PpqsA ) and triggers transcription once activated by HHQ or PQS ( Fig 1 ) [22–24] . Therefore , by analogy with other QS systems , HHQ and PQS act as autoinducers by generating a positive feedback loop that accelerates their biosynthesis . Although both HHQ and PQS can function as QS signal molecules , it is not clear whether this regulatory effect is only exerted via PqsR , or also via PqsR-independent pathways . Although both HHQ and PQS activate PqsR , PQS has additional properties . For example , PQS promotes the formation of membrane vesicles ( MVs ) in which PQS is both bioactive and bioavailable [25] , although it is not essential for MV formation [26] . The 3-hydroxy substituent also confers on PQS the ability to chelate ferric iron ( Fe3+ ) [27] . Consequently , exogenous PQS triggers an iron-starvation response in P . aeruginosa , promoting the production of the siderophores , pyoverdine and pyochelin [27 , 28] . However , PQS cannot be considered as a siderophore sensu stricto , since it does not stimulate growth of a siderophore-defective P . aeruginosa mutant in iron-deficient growth conditions [27] . PQS appears instead to act as an iron trap associated with the outer membrane . In this context , the iron-chelating property of PQS may confer a survival advantage to P . aeruginosa in mixed bacterial populations by limiting the availability of iron to co-inhabitant species [29] . HQNO also contributes to the environmental competitiveness of P . aeruginosa , since it is a potent inhibitor of the cytochrome bc1 complex [30] . At present , the role played by HQNO in P . aeruginosa physiology and the mechanism by which HQNO self-poisoning is avoided , have not been determined . Mutations in the pqsA , pqsB , pqsC or pqsD biosynthetic genes or in the regulatory gene pqsR , all abolish AQ production , while P . aeruginosa pqsH and pqsL mutants accumulate either HHQ and HQNO or HHQ and PQS , respectively [9 , 14 , 31] . Notably , while PqsE converts 2-ABA-CoA to 2-ABA , a mutation in pqsE does not affect AQ biosynthesis [11] . This is probably because the PqsE thioesterase functionality can be provided by alternative thioesterases [17] . PqsE over-expression however completely abrogates PpqsA activity ( Fig 1 ) , and consequently AQ biosynthesis [11] . Although PqsE is dispensable for AQ biosynthesis , it is required for production of key virulence factors , such as pyocyanin , elastase , rhamnolipids , hydrogen cyanide , LecA lectin , and for biofilm maturation [11] . The activity of PqsE is also dependent on the N-butanoyl-homoserine lactone ( C4-HSL ) receptor RhlR , which acts downstream but in synergy with PqsE [32] . Therefore , it is likely that PqsE has , as yet unidentified , functions in addition to its thioesterase activity [17] . Transcriptomic analyses have revealed that the expression of multiple genes requires pqsE , and that full virulence in plant and animal infection models is strongly dependent on this enzyme [6 , 11] . Although the crystal structure of PqsE has been solved and key active site residues identified , the mechanism by which it controls P . aeruginosa virulence gene expression is not understood [17 , 33] . Since the HHQ- and PQS-dependent activation of pqsABCDE transcription results in increased levels of both AQs and PqsE , it is possible that functional effects previously considered to be HHQ- and/or PQS-dependent are mediated via PqsE . Alternatively , since PqsE over-expression abrogates AQ biosynthesis , some phenotypes altered as a consequence of increased pqsE expression may , at least in part , be under the control of HHQ and/or PQS . PqsE controls the expression of some virulence genes independent of contribution to AQ biosynthesis . The major reductions in LecA and pyocyanin production in an AQ-negative pqsA mutant for example could be restored fully by expressing pqsE from an inducible tac promoter [11] . Thus , the autoregulatory effect exerted by PqsE on its own transcription plays a homeostatic role in limiting AQ accumulation , thus impeding a clear understanding of the physiological role ( s ) played by PqsE . Fig 1 shows how the pqs system components are interlinked . HHQ and PQS both induce transcription of the pqsABCDE operon via PqsR , increasing AQ biosynthesis and pqsE expression . The latter in turn , exerts a repressive role on both AQ production and its own expression . This complexity has obscured comprehension of the physiological roles played by specific AQs and PqsE . Characterization of the regulons controlled by individual components of the pqs system has not yet been reported . For example , the genes controlled via the pqs system have been investigated by comparing the transcriptional profiles of P . aeruginosa PA14 wild type and its pqsH isogenic mutant [23] by evaluating the effect of exogenous PQS on the P . aeruginosa PAO1 transcriptome [28] or by comparing the wild type PAO1 with pqsA or pqsE mutants [11] . In each case , numerous genes including those involved in virulence factor production , iron homeostasis and denitrification , appeared to be PQS-controlled . However , since , in the strains used , altered PQS levels led to dysregulation of HHQ and HQNO synthesis and pqsE expression , it is not possible to discriminate between the role ( s ) played by PQS from that of the other components of the pqs system . Similarly , it is not possible to determine whether PqsE-controlled genes in strains overexpressing this protein are controlled by PqsE itself or by the lack of AQs resulting from pqsE overexpression [11] . To circumvent these limitations , a P . aeruginosa PAO1 mutant unable to synthesize AQs or convert exogenously supplied AQs was constructed . In this strain , termed ∆4AQ , pqsE expression is chemically inducible and uncoupled from the activity of the PpqsA promoter , thus exogenous AQ provision does not alter PqsE levels . Transcriptomic analyses were performed on the ∆4AQ strain grown in the absence or in the presence of either HHQ , PQS or HQNO , or the exogenous inducer of PqsE expression ( IPTG ) , thus enabling identification of the specific genes controlled by each pqs system component . Transcriptomic analyses were also performed on strains with pqsR-proficient or pqsR-deficient ( ∆5AQ ) genetic backgrounds to elucidate the physiological role ( s ) played by the transcriptional regulator PqsR .
To identify the regulons controlled individually by HHQ , PQS , HQNO and PqsE , a quadruple mutant of P . aeruginosa PAO1 , named ∆4AQ , was constructed . As depicted in Fig 1 , this carries in frame deletions of pqsA , pqsH and pqsL genes , and incorporates an isopropyl β-d-l-thiogalactopyranoside ( IPTG ) -inducible pqsE gene . Preliminary experiments were performed to validate the ∆4AQ strain . P . aeruginosa PAO1 wild type was grown in LB , while the isogenic ∆4AQ mutant was grown in LB or in LB supplemented with either HHQ , PQS , or HQNO ( 40 μM ) , or with IPTG ( 1 mM ) . All strains were grown to late exponential phase where the pqs system is maximally expressed [11] . Cell-free spent media and bacterial cells were respectively collected for determination of AQ levels by LC-MS/MS , and for quantification of pqsE mRNA levels by Real Time PCR . HHQ , PQS and HQNO were only recovered from the ∆4AQ cultures if exogenously added , and were not converted into other AQs ( S1A Fig ) . Moreover , the P . aeruginosa ∆4AQ strain grown in the absence of IPTG showed only basal levels of pqsE RNA ( ∆4AQ to wild type ratio ~ 0 . 2 ) , irrespective of the presence or absence of AQs while IPTG addition increased pqsE RNA levels by ~15-fold relative to the parental strain ( S1B Fig ) [11] . Growth of the ∆4AQ strain was not affected by exogenous provision of any AQ or IPTG ( S1C Fig ) . The transcriptional profiles of the ∆4AQ strain grown with 40 μM of HHQ , PQS or HQNO or with IPTG were compared by means of high-density oligonucleotide microarrays , using Affymetrix GeneChip for P . aeruginosa PAO1 . This method was chosen to provide a reliable comparison with previously published data [6 , 10 , 11 , 23 , 28] . Following statistical validation of the dataset , only genes with a fold change > 2 . 5 and a q-value < 0 . 05 were considered for further analysis [34] . Table 1 lists the selected genes ( see S1 Table for complete list ) satisfying this cut-off and hence significantly controlled by the AQs and/or by PqsE . In brief , the RNA levels for 0 , 3 , 145 , and 182 genes were significantly altered by HQNO , HHQ , PqsE and PQS respectively ( Fig 2 ) . HQNO had no effect on the P . aeruginosa ∆4AQ transcriptome indicating that this AQ does not function as a QS signal , implying an alternative role for HQNO in P . aeruginosa physiology . Since HQNO is a potent cytochrome bc1 complex inhibitor [9] , it is likely that HQNO acts primarily as a secondary metabolite that increases the environmental competitiveness of P . aeruginosa . Notably , only 3 genes were significantly controlled by HHQ , namely pqsB , pqsC and pqsD ( Table 1; Fig 2 ) . This suggests that HHQ controls only the pqsABCDE transcriptional unit so driving the positive feedback loop . The positive effect of HHQ on PpqsA activity is mediated by PqsR [22 , 24] , such that the primary role of HHQ as a signal is to induce the PqsR-dependent expression of the pqsABCDE transcriptional unit , ultimately resulting in increased AQ biosynthesis and pqsE expression . As expected , the pqsB , pqsC and pqsD genes were also identified among the genes up-regulated by PQS ( Table 1 ) . In the Δ4AQ mutant background , PqsE emerges as a major effector of the pqs QS system , since the microarray analysis revealed it controls the expression of 145 genes in the ∆4AQ strain , an AQ-negative background in which PqsE is unable to down-regulate AQ production . In particular , 72 genes were up-regulated and 73 down-regulated upon IPTG-induction of pqsE expression ( Fig 2; S1 Table ) . The 72 genes up-regulated by pqsE expression , included the pyocyanin biosynthetic genes ( phzA , phzB , phzC , phzD , phzE , phzF , phzG , phzM , phzS ) , the hcnABC operon required for hydrogen cyanide biosynthesis , rhlA and rhlB , required for rhamnolipid biosynthesis , and chiC , coding for the extracellular chitinase ChiC . Moreover , PqsE exerted a positive effect on the transcription of genes involved in biofilm development e . g . cupE1 , lecA and lecB , explaining the positive control of PqsE on biofilm formation [11] , and on the mexGHI-opmD operon , coding for a Resistance-Nodulation-Cell division ( RND ) efflux pump involved in antibiotic resistance that is also essential for pqs-dependent QS . This is because mexG and opmD mutants are both avirulent in plant and rat infection models and fail to produce PQS , probably as a consequence of the intracellular accumulation of a toxic AQ metabolite [35] . Furthermore , pyocyanin functions as a signal in the P . aeruginosa QS network because it induced changes in the expression of over 50 genes ( 23 up-regulated and 29 down-regulated ) [36] . Of these only mexGHI-opmD , PA2274 and PA3250 were also up-regulated via PqsE rather than PQS ( Tables 1 and S1 ) . Hence , although PqsE controls pyocyanin biosynthesis , it only regulates a sub-set of pyocyanin-dependent genes . As shown in Fig 3A , many of PqsE up-regulated genes belong to the “Secreted Factors ( toxins , enzymes , alginate ) ” and “Adaptation , Protection” functional classes ( 12 . 2% and 7 . 3% , respectively ) , highlighting the importance of PqsE in P . aeruginosa adaptive behaviour and virulence . However , most of the PqsE up-regulated genes ( 29 . 3% ) are classified as “Hypothetical , unclassified , unknown” , limiting our comprehension of its physiological role . With respect to the 73 genes down-regulated upon pqsE induction , they are mainly involved in energy metabolism and anaerobic respiration , including gapA , coding for glyceraldehyde 3-phosphate dehydrogenase , and almost all the nir , nor , nar , and nos genes ( S1 Table ) . Indeed , the majority of the PqsE-repressed genes cluster in the “Energy metabolism” ( 24 . 3% ) , “Transport of small molecules” ( 17 . 1% ) , “Carbon compound catabolism” ( 11 . 7% ) and “Biosynthesis of cofactors , prosthetic groups , and carriers” ( 9 . 0% ) functional classes ( Fig 3A ) . However , the physiological relevance of this repression is not clear , since the IPTG-mediated induction of PqsE does not affect bacterial growth , at least under aerobic conditions . It is also noticeable that two genes involved in type 6 secretion ( T6SS; tssB1 and tssC1 ) are down-regulated in response to pqsE induction ( Table 1 ) . The global effect exerted by PqsE on the P . aeruginosa transcriptome is unlikely to be direct , since this protein does not possess a DNA-binding domain [37] . Moreover , PqsE activity is not exclusively a consequence of its thioesterase activity since pqsE expression is sufficient to restore pyocyanin in an AQ-deficient ( pqsA mutant ) background [6 , 11] . Hence , the multifunctional activity of PqsE may conceivably be a consequence of a pqsE regulatory RNA acting on the expression of pqsE-controlled genes . To investigate this possibility we quantified pyocyanin production in P . aeruginosa PAO1 ∆pqsA ∆pqsE double mutant strains carrying plasmids for IPTG-inducible expression of wild type pqsE , or pqsE mutated variants lacking the first two codons ( pqsE∆1–6 ) or with a nucleotide insertion after the ATG to alter the protein frame ( pqsENoFrame ) . As shown in S2A Fig , pyocyanin production in the P . aeruginosa PAO1 ∆pqsA ∆pqsE strains was restored only upon complementation with wild type pqsE , despite the presence of a pqsE transcript in the mutated variants ( S2B Fig ) . These data suggest that the activity is not due to the pqsE RNA transcript but requires the PqsE protein , a finding that suggests PqsE has independent regulatory and thioesterase enzymatic functions . When the ∆4AQ strain was grown with IPTG , the phnAB operon was also up-regulated ( Table 1 ) . Knoten and co-workers reported that when P . aeruginosa PAO1 was grown in nutrient limiting conditions but not in LB , pqsE and phnAB were co-transcribed [38] . However , RT-PCR analysis of the PAO1 strain used in this study indicates that pqsE and phnAB are co-transcribed after growth in LB ( S3 Fig ) , a finding consistent with the fold change increases quantified for pqsE ( 22 . 8 ) , phnA ( 26 . 2 ) and phnB ( 22 . 4 ) upon addition of IPTG to the ∆4AQ strain ( Table 1 ) . Although anthranilate is an AQ precursor [15] , pqsE-overexpression results in the abrogation of AQ production via the strong repression of PpqsA promoter [11] . This repression is not apparent in our microarray analysis as a consequence of the lack of HHQ- and PQS-dependent PpqsA activation in the ∆4AQ strain . Anthranilate for AQ biosynthesis can be supplied by the anthranilate synthases TrpEG and PhnAB or via the kynurenine pathway that converts tryptophan into anthranilate [38] . The latter is the main source of anthranilate for PQS biosynthesis when tryptophan is present , and PhnAB appears to supply anthranilate only under nutrient-limiting conditions [38] . Consequently the increased transcription of phnAB following the IPTG-dependent induction of pqsE in the ∆4AQ strain may increase intracellular anthranilate levels and so impact on gene expression independent of PqsE . To explore this possibility , we first quantified intracellular anthranilate levels in the ∆4AQ strain grown in LB or in LB supplemented with 1 mM IPTG . S4A Fig shows that the IPTG-induced increase in phnAB expression did not result in higher levels of intracellular anthranilate . The slightly higher concentration of anthranilate in the ∆4AQ strain in the absence of IPTG may be a consequence of the PqsE-mediated increases in the expression of genes such as antR and catB that are involved in the degradation of anthranilate ( S1 Table ) . To confirm these data , we also compared the transcriptional profiles of a P . aeruginosa PAO1 quadruple mutant strain with deletions in pqsA , pqsH , pqsL and pqsE ( ∆pqsAHLE ) and carrying a plasmid-borne copy of pqsE or the empty vector ( pUCP18 ) . The data obtained for selected virulence related genes are summarized in Table 1 . The plasmid-mediated expression of pqsE in the ∆pqsAHLE genetic background did not affect phnAB expression . In addition , the data obtained was broadly consistent with that obtained for the inducible pqsE construct with respect to the genes involved in virulence factor production , biofilm formation and antibiotic resistance ( Table 1 ) . In addition , we validated the data with respect to the pyocyanin biosynthetic genes by introducing PphzA1::lux and PphzA2::lux transcriptional fusions onto the chromosome of the ∆pqsAHLE strain , since the microarray experiments cannot discriminate between the two phz operons as they are almost identical at the DNA level [39] . The results obtained with the reporter fusions confirm the microarray data and reveal that PqsE is responsible for driving the expression of phzA1 but not phzA2 ( S4B Fig ) . Despite the structural similarity between HHQ and PQS and their ability to activate PqsR via the same ligand binding site [24] , the microarray data revealed that , in contrast to HHQ , PQS regulates the expression of 182 genes . In particular , 103 genes were up-regulated and 79 genes were down-regulated in response to exogenous PQS ( Fig 2; S1 Table ) . The major proportion of PQS up-regulated genes ( 75% ) are also induced by iron-starvation [40 , 41] . These consist of almost all the genes involved in the biosynthesis , uptake and response to the siderophores pyoverdine and pyochelin , including the regulatory genes pvdS and pchR . Moreover , metabolic and virulence genes previously shown to be induced by iron-starvation were strongly up-regulated by PQS , including fumarate hydratase ( fumC1 ) , superoxide dismutase ( sodA ) and two proteases ( prpL and aprX ) ( Table 1 ) . These findings are consistent with the iron-chelating activity of PQS inducing an iron-starvation response [27 , 28] . In addition to the iron-regulated genes , PQS increased the transcription of genes involved in Type 3 secretion ( T3S; pcrV , pcrH , popB , popD , exsC , exsE , exsB , and pscE ) , and coding for both exotoxin ExoS ( exoS ) and its chaperone SpcS ( spcS ) , indicating that PQS , independent of PqsE , contributes to P . aeruginosa virulence gene regulation ( Table 1 ) . PQS production has been indirectly linked to the regulation of T3S effector secretion in P . aeruginosa at the post-transcriptional level [42] . Interestingly , the rhl QS system that represses both pqsA and pqsR also negatively regulates exoS [43] . As anticipated , pqsB , pqsC and pqsD genes were all up-regulated by PQS ( Table 1 ) . The 79 PQS-repressed genes mainly cluster in the “Energy metabolism” ( 42 . 7% ) , “Biosynthesis of cofactors , prosthetic groups , and carriers” ( 10 . 7% ) , and “Carbon compound catabolism” ( 7 . 8% ) functional classes ( Fig 3B ) . The repression exerted by PQS on certain metabolic genes could be due to its interaction with membranes and consequent perturbation of associated energy generation . Almost all the genes involved in denitrification ( nir , nor , nar , and nos genes ) are also down-regulated by PQS ( S1 Table ) . These data are in line with previous work demonstrating that PQS represses anaerobic growth of P . aeruginosa by inhibiting denitrifying enzymes [44] . A comparison of the genes regulated by PQS and PqsE revealed that they control quite distinct regulons and up-regulate different sets of virulence genes ( Table 1 ) . The PQS and PqsE regulons only share 30 genes ( Fig 2 ) . Notably , 28 genes independently down-regulated by PQS and PqsE are all involved in denitrification ( nir , nor , nar , and nos genes; S1 Table ) , indicating that there is some redundancy in the pqs system . The reliability of the microarray data is supported by the observation that HHQ controls only one transcriptional unit , HQNO does not affect transcription under the growth conditions employed whereas PQS regulates 182 genes . Differential expression of selected genes by PQS or PqsE in the microarray experiment was validated by Real Time PCR analysis . A comparison between Table 1 and Fig 4 shows that the results obtained match the microarray data , since the mRNA levels of the lecA , mexG and rhlA genes increased upon IPTG-dependent induction of PqsE , while nosR decreased . Similarly , PQS increased the transcription of sodA , pvdS , pchR , and aprX but repressed nosR and hcpC . PqsE did not affect the transcript levels of PQS-controlled genes ( i . e . , sodA , pvdS , pchR , aprX and hcpC ) , and conversely PQS did not alter PqsE-regulated transcript levels ( i . e . , lecA , mexG and rhlA ) . Moreover , none of these transcripts were affected by HHQ or HQNO ( Fig 4 ) . The potential effects of the AQs and/or PqsE on pqsH or pqsL transcription cannot be inferred from the microarray analysis , since both genes were deleted in the ∆4AQ strain . Therefore , the expression of chromosomal pqsH and pqsL lux promoter fusions was investigated in the P . aeruginosa ∆4AQ strain . Neither promoter was influenced by exogenous HHQ , PQS or HQNO or by pqsE induction ( S5 Fig ) . Thus , the autoregulatory activity of PQS is not directly exerted at the level of pqsH transcription , and HQNO has no effect in promoting its own biosynthesis . These data imply that a positive feedback loop exists in the pqs QS system only at the level of the pqsABCDE-phnAB transcriptional unit , with HHQ and PQS promoting their own biosynthesis by inducing PpqsA activity via PqsR . Overall , our microarray experiments are consistent with previously published transcriptomic analyses highlighting the contributions of the pqs system to virulence factor production , ferric iron acquisition and energy metabolism [6 , 10 , 11 , 23 , 28] . However , our approach enabled us to discriminate between the physiological roles played by the distinct elements of the pqs QS system . For example , both PQS and PqsE were reported to affect iron-controlled genes , probably because in previous experimental settings , PqsE could control AQ biosynthesis [6 , 11] . However , our data demonstrate clearly that PQS but not PqsE , regulates the iron-regulated genes . Similarly , certain PqsE-controlled virulence factors ( e . g . , pyocyanin , lectins , ChiC chitinase and the MexGHI-OpmD efflux pump ) were reported to be PQS-controlled , probably because in previous experiments the addition of synthetic PQS or the abrogation of PQS synthesis ( in pqsR , pqsA or pqsH mutants ) led to dysregulation of pqsE expression [10 , 23 , 28] . Moreover , the use of the ∆4AQ strain provides clear evidence that HQNO does not influence the P . aeruginosa transcriptome , and that HHQ exclusively regulates the pqsABCDE-phnAB transcriptional unit . Therefore , HHQ activity ultimately leads to the indirect control of specific physiological processes by increasing the expression of the effector protein PqsE and by acting as a substrate for PQS biosynthesis . Despite the structural similarity of the two AQs , HHQ controls the transcription of a single transcriptional unit ( i . e . , pqsABCDE-phnAB ) , while PQS regulates 182 genes . Since both AQs act as PqsR co-inducers [22 , 24] , it is possible that the PqsR-HHQ complex only affects PpqsA activity , while the PqsR-PQS complex acts more globally as do other QS regulators such as LasR . However , PQS appears to influence gene expression via PqsR-dependent and PqsR-independent mechanisms , for example , by inducing an iron-starvation response [27 , 28] . To discriminate between PqsR-dependent and PqsR-independent PQS regulons , and to characterize the PqsR regulon itself , pqsR was deleted in the ∆4AQ strain , generating the quintuple P . aeruginosa ∆5AQ mutant ( Fig 1 ) . The transcriptomes of the ∆4AQ and ∆5AQ mutants , supplemented with PQS ( 40 μM ) , were compared . Only 4 genes were significantly down-regulated in the ∆5AQ strain with respect to the ∆4AQ mutant , namely pqsR , pqsB , pqsC , and pqsD ( -101 . 2 < fold change < -186 . 2 ) . An apparent strong down-regulation of pqsR was expected since this gene has been deleted from P . aeruginosa ∆5AQ . The down-regulation of pqsB , pqsC , and pqsD in P . aeruginosa ∆5AQ strongly suggests that in PAO1 PqsR only triggers the transcription of the pqsABCDE-phnAB operon , and thus the pqsA promoter region is the only target for the PqsR-PQS complex . Overall , these data imply that , apart from the pqs genes , the other 179 genes identified as PQS-regulated ( S1 Table ) are controlled by PQS via a PqsR-independent pathway ( s ) . This regulatory activity is likely due , at least in part , to the iron-chelating activity of PQS , consistent with the finding that 77/100 genes up-regulated by PQS in a PqsR-independent manner are known to be induced by iron-starvation [40 , 41] . In contrast the 79 genes down-regulated by PQS have not previously been reported to be repressed in low-iron media . PQS could conceivably also control other phenotypes in both an iron- and a PqsR-independent manner through direct interactions with the outer membrane [25] or by acting as a pro- or anti-oxidant [45] . The transcriptome analysis performed on the ∆4AQ strain indicates that PQS is more potent than HHQ in activating transcription of the pqsABCDE-phnAB operon in LB medium ( Table 1 ) . This is also consistent with a chromosomal reporter PpqsA::lux fusion in a P . aeruginosa pqsAH mutant , which cannot convert exogenously supplied HHQ to PQS , where EC50 values of 16 . 4±2 . 6 μM and 3 . 8±1 . 6 μM for HHQ and PQS respectively have been determined in LB medium [24] . However , HHQ activates the PpqsA promoter at a similar level to PQS when the bacteria are grown in an iron-deficient casamino acids ( CAA ) medium [27] . This suggests that PQS is more effective than HHQ in stimulating PpqsA activity because it induces an iron-starvation response . This hypothesis would be in agreement with iron-chelating activity of PQS , with the evidence that high-iron concentrations negatively impact on PpqsA activity [6] . To investigate this possibility , the effect of HHQ , PQS and 2-heptyl-3-amino-4-quinolone ( 3-NH2-PQS ) on both PpqsA and PpqsR activation were compared in the ∆4AQ ( pqsR-proficient ) and ∆5AQ ( pqsR-mutant ) strains , grown in LB with or without 100 μM FeCl3 . 3-NH2-PQS is a potent PqsR agonist ( EC50 0 . 4±0 . 1 μM ) isosteric with PQS but lacking iron-chelating activity [24] . In addition , although pqsR was not identified among the AQ-controlled genes in the transcriptome analysis ( S1 Table ) we included the pqsR promoter fusion experiments since it is not possible to exclude a regulatory effect below the fold change cut-off used ( > 2 . 5 ) that has a significant effect on PpqsA activity . Consistent with previous work , PQS was more effective than HHQ in up-regulating PpqsA in LB , while HHQ and 3-NH2-PQS induced PpqsA activity at similar levels ( Fig 5A ) . HHQ and 3-NH2-PQS did not induce PpqsA in the pqsR mutant strain ∆5AQ , while PQS exerted a positive , ∼2 fold induction of PpqsA in this genetic background ( Fig 5B ) . HHQ and 3-NH2-PQS had no effect on PpqsR activity , while PpqsR was induced by PQS in both the ∆4AQ and ∆5AQ strains ( ~1 . 5 fold; Fig 5C and 5D ) . Interestingly , the PQS-dependent induction of PpqsA in the ∆4AQ strain was strongly reduced when iron was added to the medium , showing the same activation level as that induced by HHQ and 3-NH2-PQS . Iron supplementation had no effect on PpqsA activity when the promoter was induced with HHQ or 3-NH2-PQS ( Fig 5A ) . The reduced ability of PQS to induce PpqsA activity in the presence of 100 μM FeCl3 is likely due to its inability to induce PpqsA and PpqsR via the PqsR-independent pathway in the presence of high iron concentrations ( Fig 5B–5D ) . A plausible explanation for the above results is that the iron-chelating activity of PQS decreases the levels of available iron in LB medium , triggering an iron-starvation response with consequent activation of PpqsA and PpqsR via a PqsR-independent pathway . Indeed , the siderophore pyoverdine , which is only produced under iron limiting conditions [46] , is detectable when PQS is added to the ∆4AQ and ∆5AQ cultures , but not when PQS is replaced with HHQ or 3-NH2-PQS , or by excess iron ( Fig 5 ) , confirming that PQS triggers an iron-starvation response in LB . This is also in line with increased expression of the Fur-controlled iron-starvation sigma factor PvdS in the presence of PQS ( Table 1 ) . To determine whether the ability of PQS to induce the PpqsA and PpqsR promoters via a PqsR-independent pathway simply relies on its iron chelating properties , the effects of PQS and the iron chelators 2 , 2’-dipyridyl and deferiprone on PpqsA and PpqsR activity were compared in the P . aeruginosa strains ∆4AQ and ∆5AQ by means of transcriptional fusions . 2 , 2’-Dipyridyl chelates ferrous iron ( Fe2+ ) [47] , which is the prevalent intracellular iron species , while deferiprone chelates ferric iron ( Fe3+ ) , which prevails in extracellular environment , to form a 3:1 ( deferiprone:Fe3+ ) complex [48] , similar to the 3:1 ferric complexes formed by 2-hydroxy-3-alkyl-4-quinolones such as PQS [27] . Both 2 , 2’-dipyridyl and deferiprone induce iron-starvation in P . aeruginosa [49 , 50] . The results obtained show that 40 μM PQS , 500 μM 2 , 2’-dipyridyl or 160 μM deferiprone all triggered similar levels of pyoverdine production in LB-grown cultures . However , neither 2 , 2’-dipyridyl nor deferiprone induce PpqsA or PpqsR activity , irrespective of the presence of PqsR ( S6 Fig ) . These data strongly suggest that the PqsR-independent effect exerted by PQS on PpqsA and PpqsR does not depend on the ability of PQS to induce an iron-starvation response . Consistent with these findings , the activity of the PpqsA and PpqsR promoters was unchanged in the 4AQ and ∆5AQ strains upon mutation of the pvdS gene that codes for the iron-starvation response sigma factor PvdS ( S7A–S7D Fig ) ; no differences in PpqsA and PpqsR activity were observed when these promoters were tested in P . aeruginosa PAO1 wild type and its isogenic ∆pvdS mutant ( S7E Fig ) . Moreover , a Fur Titration Assay ( FurTA ) [51] revealed that the iron-response regulator Fur does not bind to the PpqsA or PpqsR promoter regions ( S7F Fig ) . Collectively , these data demonstrate that the ability of PQS to induce PpqsA and PpqsR via a PqsR-independent pathway does not rely on the capacity of PQS to induce an iron-starvation response via the master regulators PvdS and Fur . However , the effect of PQS on both promoters is inhibited when 100 μM FeCl3 is added to the LB medium ( Fig 5 ) . To clarify this finding further , the ability of PQS to induce PpqsA activity was determined in P . aeruginosa ∆4AQ grown in LB supplemented with increasing concentrations of FeCl3 without AQs or with either PQS or HHQ . In parallel , pyoverdine levels were determined in the culture supernatants of the ∆4AQ strain grown in the presence of PQS to monitor the activation of the iron-starvation response . As shown in Fig 6 , iron had no effect on the ability of HHQ to induce PpqsA activity or on the PpqsA basal level in the absence of AQs . Conversely , increasing concentrations of FeCl3 reduced the ability of PQS to promote PpqsA activity , and inhibited pyoverdine production , consistent with our previous data . Low FeCl3 concentrations ( from 0 . 4 μM to 1 . 6 μM ) were sufficient to decrease the iron-starvation response , as indicated by reduced pyoverdine production , without affecting the PQS-dependent induction of PpqsA . The ability of HHQ and PQS to induce PpqsA was comparable when the medium iron concentration approximated to the theoretical PQS-saturating value , ranging from 12 . 5 to 25 μM ( considering 40 μM PQS and 3:1 ratio of the PQS-Fe3+ complex ) . Given that iron reduces the PqsR-independent expression of the pqsA or pqsR promoters in the absence of PvdS and that Fur does not bind to either promoter , our data suggest a regulatory role for PQS in the absence of PqsR . This regulatory activity can however be abolished by increasing the medium iron content . However , of the 179 genes regulated by PQS via PqsR-independent pathways only 77 are controlled by the iron-starvation response . The remaining 102 genes ( underlined in S1 Table ) are regulated via an iron-starvation-independent and PqsR-independent PQS signalling pathway ( s ) . Most of the repressed genes are involved in energy metabolism ( 49% ) and include the nir , nar , nos genes involved in denitrification . Of the up-regulated genes , 39% are from the protein secretion/export functional class and include T3S genes such as pcrV , exsC , exsE , exoS and spcS . The mechanism by which these genes are regulated is not yet apparent but may be due to the anti-oxidant properties of PQS since these are likely to be inhibited by excess iron [45] . Since PQS promotes PpqsA activity in P . aeruginosa at different levels depending on the availability of iron , the expression of PqsE-controlled virulence factors in iron-poor environments is likely to be higher . In this context , it is tempting to speculate that the iron chelating ability of PQS may contribute to P . aeruginosa environmental fitness both by limiting the availability of iron to competing microorganisms and by increasing the expression of specific sets of genes important in challenging iron-poor environments . This process might be relevant during the colonization of the human host , when P . aeruginosa experiences iron starvation , and implies a new role for PQS as an extracellular iron sensor .
Although the central role of the pqs QS system in the control P . aeruginosa infection processes has been extensively studied , the precise role played by each individual element of this complex regulatory circuit remained to be defined . Here we have filled this knowledge gap by defining the specific genome-wide regulons for HHQ , PQS and HQNO and for the effector PqsE in the presence and absence of PqsR ( Fig 7 ) . Of 145 genes regulated via PqsE only 30 were co-regulated by PQS ( Fig 2 ) . Among the key genes controlled by PqsE in the absence of AQs are those coding for the MexGHI-OpmD efflux pump and pyocyanin biosynthesis . Although biochemically PqsE functions as a thioesterase in AQ biosynthesis [17] , the thioesterase-independent regulatory mechanism controlling gene expression requiring the PqsE protein remains to be elucidated . A striking feature of our transcriptome data is that signalling function of HHQ is simply to drive the expression of the pqsABCDE-phnAB transcriptional unit in a PqsR-dependent manner . These data highlight that unlike LuxR/AHL-based QS systems where the response regulator interacts with the promoters of multiple target genes , PqsR appears to target only one , the pqsABCDE-phnAB operon . Furthermore , HQNO , the N-oxide of HHQ , does not act as a signal molecule . In contrast to HHQ and HQNO , PQS is clearly a multi-functional molecule that operates via multiple PqsR-dependent and PqsR-independent pathways . In this it resembles N- ( 3-oxododecanoyl ) homoserine lactone ( 3OC12-HSL ) , which not only modulates the P . aeruginosa transcriptome via LasR and QscR , but also in the absence of any regulators incorporating an AHL-binding domain [52] .
The bacterial strains used in this study are listed in S2 Table . E . coli and P . aeruginosa strains were routinely grown at 37°C in Luria-Bertani ( LB ) broth with aeration . When required , LB was supplemented with synthetic 40 μM HHQ , PQS , or HQNO , or with 1 mM IPTG . FeCl3 , 2 , 2’-dipyridyl and deferiprone were used at the concentrations indicated . AQs including 3-NH2-PQS were synthesized as described previously [24] . Unless otherwise stated , antibiotics were added at the following concentrations: E . coli , 100 μg ml-1 ampicillin ( Ap ) , 10 μg ml-1 tetracycline ( Tc ) , or 30 μg ml-1 chloramphenicol ( Cm ) ; P . aeruginosa , 200 μg ml-1 tetracycline ( Tc ) , 375 μg ml-1 chloramphenicol ( Cm ) , or 400 μg ml-1 carbenicillin ( Cb ) . The plasmids and oligonucleotides used are listed in S2 and S3 Tables respectively . Preparation of plasmid DNA , purification of DNA fragments , restrictions , ligations , and transformations in E . coli DH5α or S17 . 1λpir competent cells were performed with standard procedures . DNA amplification was by Polymerase Chain Reaction ( PCR ) using the GoTaq Polymerase ( Promega ) . The P . aeruginosa ∆4AQ quadruple mutant strain was constructed by allelic exchange using the suicide vectors pDM4ΔpqsEind [11] and pDM4∆pqsL in the double mutant P . aeruginosa PAO1 ∆pqsA ∆pqsH [27] . The P . aeruginosa ∆5AQ quintuple mutant was constructed using the suicide vector pDM4ΔpqsR [24] in P . aeruginosa ∆4AQ . The P . aeruginosa PAO1 ∆pqsAHLE quadruple mutant strain was generated by allelic exchange using the suicide vectors pDM4∆pqsE [11] and pDM4∆pqsL in the double mutant P . aeruginosa PAO1 ∆pqsA ∆pqsH [27] . pDM4∆pqsL was constructed by PCR amplifying the upstream and downstream fragments ( ~500 bp ) of pqsL from PAO1 using the primers FWpqsLUP and RVpqsLUP , and FWpqsLDOWN and RVpqsLDOWN , respectively ( S3 Table ) . The same procedures were used to introduce pvdS mutations into the P . aeruginosa wild type , ∆4AQ and ∆5AQ strains . In this case , the E . coli pEX∆pvdS strain [53] was used as donor strain in the conjugation step . For promoter activity studies , transcriptional fusions between the promoter regions of pqsH , pqsL , pqsR , phzA1 , phzA2 and the luxCDABE operon were constructed using the miniCTX-lux plasmid as previously described [27] . Total RNA for the high-density oligonucleotide microarray experiments was extracted from 1 ml cultures of P . aeruginosa 4AQ , 5AQ or ∆pqsAHLE carrying the plasmid pUCP18 or pUCPpqsE , grown at 37°C with shaking at 200 rpm to an OD600 1 . 5 in LB or in LB supplemented with 40 μM HHQ , PQS , HQNO , or 1 mM IPTG . Cells were mixed with 2 ml of RNA Protect Bacteria Reagent ( Qiagen ) the cells lysed and RNA was purified using RNeasy mini-columns ( Qiagen ) , including the on-column DNase I digestion step . In addition , we treated the eluted RNA for 1 h at 37°C with TURBO DNase ( 0 . 1 units per μg of RNA; Ambion ) . DNase I was removed with the RNeasy Column Purification Kit ( Qiagen ) . RNA integrity was monitored by agarose gel electrophoresis , and the absence of contaminating chromosomal DNA was verified by PCR with primers pairs FWpqsB-RVpqsB and FW16SRT-RV16SRT ( S3 Table ) . Processing of the P . aeruginosa PAO1 Affymetrix GeneChip and statistical analysis of the dataset were performed at the Lausanne Genomic Technologies Facility , Center for Integrative Genomics , University of Lausanne , Switzerland . For each condition , two different pools of RNA were compared ( biological duplicate ) , each containing RNAs from three independent extractions ( technical triplicate ) . Fold changes > 2 . 5 with a q-value < 0 . 05 were considered as statistically significant . The q-value is the smallest False Discovery Rate ( FDR ) for which the test can be considered significant [34] . For reverse transcriptase PCR ( RT-PCR ) and Real Time PCR analyses , RNA was extracted from P . aeruginosa PAO1 wild type , ∆4AQ or ∆5AQ grown to an OD600 1 . 5 in the same conditions as described above for the microarray experiments . cDNA synthesis was performed from 1 μg of total purified RNA by using random hexamer primers and the iScript Reverse Transcription Supermix for RT-qPCR kit ( BioRad ) . For RT-PCR , 50 ng of cDNA were PCR amplified with the GoTaq Polymerase ( Promega ) and primers FWpqsERT and RVpqsERT ( for pqsE ) , FWpqsE-phnA and RVpqsE-phnA ( for transcript spanning from pqsE to phnA ) , or FWphnART and RVphnART ( for phnA ) ( S3 Table ) . After 5 min of denaturation at 95°C , the following reaction cycle was used for 30 cycles: 95°C for 30 s , 60°C for 30 s , and 72°C for 1 min . The PCR products were analysed on a 1% ( w/v ) agarose gel and stained with Midori Green DNA Stain ( Nippon Genetis Europe GmbH ) . Real-time PCRs were performed using the iTaq Universal SYBR Green Supermix ( BioRad ) and primers listed in S3 Table . Gene-specific primers employed in this analysis were designed using the Primer-Blast software ( www . ncbi . nlm . nih . gov/tools/primer-blast ) to avoid nonspecific amplification of P . aeruginosa DNA . The reaction procedure involved incubation at 95°C for 1 min and 40 cycles of amplification at 95°C for 10 s and 60°C for 45 s . Fluorescence was registered in the last 15 s of the 60°C step . 16S ribosomal RNA was chosen as the internal control to normalize the Real Time PCR data in each single run , and to calculate the relative fold change in gene expression by using the 2-∆∆Ct method . The analysis was performed in duplicate on three technical replicates . Bioluminescence was determined as a function of cell density using an automated luminometer-spectrometer ( GENios Pro ) , as previously described [27] . Pyoverdine was quantified as OD405 of culture supernatants appropriately diluted in 100 mM Tris-HCl ( pH 8 . 0 ) , and normalized for bacterial cell density ( OD600 ) [53] . AQs were quantified by LC-MS/MS after extracting cultures with acidified ethyl acetate [54] . Anthranilate levels were determined using quantitative LC-MS/MS following extraction of bacterial cell pellets with 80% ( v/v ) methanol . MS analysis was conducted under positive electrospray conditions ( +ES ) with the MS in MRM ( multiple reaction monitoring ) mode . The precursor-product ion mass transition used for the MRM detection was m/z 138 . 1–120 . 1 . The relevant chromatographic peaks were compared to those of an anthranilate standard at a range of known concentrations . For all the assays , the average data and standard deviations were calculated from at least three independent experiments . The binding of Fur to the PpqsA and PpqsR promoter regions was investigated by transforming the miniCTX-PpqsA::lux [27] and miniCTX-PpqsR::lux plasmids into E . coli H1717 competent cells [49] . As positive and negative controls miniCTX-PpchR::lux and miniCTX-lux plasmids respectively were used . PpchR::lux was obtained by cloning a PCR fragment amplified from PAO1 with FWPpchR and RVPpchR ( S3 Table ) . The resulting E . coli strains were grown for 16 h in LB broth supplemented with 10 μg ml-1 Tc at 37°C , washed twice with saline , and then isolated on MacConkey agar supplemented with 10 μg ml-1 Tc and 20 μM FeSO4 , as previously described [51] . Colony colour was checked after 24 h of incubation at 37°C .
|
Many bacterial pathogens control virulence gene expression and the development of antibiotic-resistant biofilms via intercellular communication through ‘quorum sensing’ ( QS ) . QS systems depend on the synthesis , secretion and perception of diffusible signalling molecules that enable bacteria to synchronize their behaviour at the population level and are considered ideal targets for the development of anti-virulence drugs . Pseudomonas aeruginosa employs several overlapping QS circuits including the pqs system to control the expression of virulence determinants . The pqs QS system relies on multiple 2-alkyl-4-quinolones ( AQs ) , including the Pseudomonas Quinolone Signal ( PQS ) , as signal molecules . However , the individual contributions of key AQs and the effector proteins PqsR and PqsE within the auto-regulated pqs system have not been elucidated because of their inter-dependence . By constructing P . aeruginosa strains with multiple mutations in the pqs system and determining their transcriptomes in the presence or absence of PqsR , PqsE or exogenously supplied AQs , we define the distinct regulons involved and characterize a novel PQS signalling pathway independent of PqsR and the iron-starvation response .
|
[
"Abstract",
"Introduction",
"Results",
"and",
"Discussion",
"Conclusions",
"Materials",
"and",
"Methods"
] |
[
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2016
|
Unravelling the Genome-Wide Contributions of Specific 2-Alkyl-4-Quinolones and PqsE to Quorum Sensing in Pseudomonas aeruginosa
|
Understanding the mechanisms that influence the population dynamics and spatial genetic structure of the vectors of pathogens infecting humans is a central issue in tropical epidemiology . In view of the rapid changes in the features of landscape pathogen vectors live in , this issue requires new methods that consider both natural and human systems and their interactions . In this context , individual-based model ( IBM ) simulations represent powerful yet poorly developed approaches to explore the response of pathogen vectors in heterogeneous social-ecological systems , especially when field experiments cannot be performed . We first present guidelines for the use of a spatially explicit IBM , to simulate population genetics of pathogen vectors in changing landscapes . We then applied our model with Triatoma brasiliensis , originally restricted to sylvatic habitats and now found in peridomestic and domestic habitats , posing as the most important Trypanosoma cruzi vector in Northeastern Brazil . We focused on the effects of vector migration rate , maximum dispersal distance and attraction by domestic habitat on T . brasiliensis population dynamics and spatial genetic structure . Optimized for T . brasiliensis using field data pairwise fixation index ( FST ) from microsatellite loci , our simulations confirmed the importance of these three variables to understand vector genetic structure at the landscape level . We then ran prospective scenarios accounting for land-use change ( deforestation and urbanization ) , which revealed that human-induced land-use change favored higher genetic diversity among sampling points . Our work shows that mechanistic models may be useful tools to link observed patterns with processes involved in the population genetics of tropical pathogen vectors in heterogeneous social-ecological landscapes . Our hope is that our study may provide a testable and applicable modeling framework to a broad community of epidemiologists for formulating scenarios of landscape change consequences on vector dynamics , with potential implications for their surveillance and control .
Human-induced landscape changes are increasingly recognized as important drivers of infectious disease outbreak and emergence events , resulting in significant threats to public health [1]–[3] . Worldwide the rapid modification of natural habitats has triggered intense research on the landscape epidemiology of vector diseases to describe how the temporal dynamics of host , vector , and pathogen populations interact spatially within heterogeneous and changing environments to enable transmission ( see [4] for a review ) . Landscape changes not only affect the transmission of endemic infections by modifying contact patterns between hosts and vectors [5] , but also have an effect on selection pressure , leading to the dominance of pathogen strains and vector populations adapted to new environmental conditions [4] . While evolutionary ecologists have increasingly recognized the importance of evolutionary processes ( e . g . , local adaptive genetic variation in pathogen vectors ) to predict population response to changing landscape conditions [6] , this issue has received relatively little attention among landscape epidemiologists . As a result , we are lacking spatially and temporally explicit quantitative approaches required to understand the key causal mechanisms ( e . g . , habitat selection and adaptation , migration and resulting gene flow ) involved in pathogen vector response to landscape changes [7] . This is particularly true for pathogen vectors in tropical regions where landscape changes ( deforestation , urbanization ) occur at an accelerated rate [8] putting at risk human populations with limited resources to face disease-related challenges . The main objective of this study is to propose a methodological framework to simulate spatial population genetics of pathogen vectors in heterogeneous and changing landscapes , in order to link observed patterns with processes . We adapted the SimAdapt simulation software [9] to simulate the evolution of both neutral and adaptive genotypes of diploid , sexually reproducing pathogen vectors introduced into a landscape . This genetic model accounts for vector dispersal and adaptation to local conditions and is coupled to a cellular automaton allowing the representation of land-use and land-cover changes . It includes landscape features known to influence vectors' genetic structure ( e . g . , roads , domestic , peridomestic and sylvatic habitats linked to possible loci under selection ) . Model simulations can be compared to field data of vector's spatial genetic structure . As a step further , the model can be used to simulate the evolution of vector spatial genetic structure in changing landscapes ( e . g . , prospective scenario of deforestation or urbanization ) . After providing general guidelines on our model , we applied SimAdapt to explore local adaptation processes of pathogen vectors in a real-world landscape using Triatoma brasiliensis Neiva , 1911 ( Hemiptera , Reduviidae , Triatominae ) as a study model . T . brasiliensis is a blood sucking bug vector of the pathogen responsible for the Chagas disease ( American trypanosomiasis ) , caused by a parasite Trypanosoma cruzi ( Kinetoplastea , Trypanosomatidae ) . This disease affects approximately 10 million people in Latin America and Caribbean [10] , and is recognized by the World Health Organization as one of the world's most neglected tropical disease [11] . T . brasiliensis represents the most important vector of T . cruzi in Northeastern Brazil [12] , [13] . As for several species of native Triatominae ( e . g . , Rhodnius equatorialis , [14]; T . pseudomaculata , [15] , [16] ) , T . brasiliensis was originally restricted to sylvatic habitats but since its description it has been increasingly found invading and establishing in peridomestic and domestic habitats [17]–[20] . Among all Brazilian triatomines , T . brasiliensis is the one that exhibits the highest pressure for re-infestation after insecticide house spraying . As a consequence , six months ( sometimes longer ) after chemical treatment , human dwellings start being re-infested [21] , [22] . As a native vector , its eradication would require significant logistical and technical investment in the long term , and , therefore , control efforts are kept on insecticide house spraying and improvement . Here , we used SimAdapt to explore three parameters related to the dispersal of T . brasiliensis: i ) the migration rate; ii ) the dispersal distance ( i . e . the maximum distance covered by an individual during its life cycle , including passive and active dispersal ) ; and iii ) the attraction by domestic habitat ( i . e . the strength that avoid individual from emigrating , as a consequence of attraction by light or availability of hosts to feed on ) . Model simulations were then compared to field data of T . brasiliensis population genetic structure and prospective scenarios of landscape change effects on T . brasiliensis adaptation were run .
As an example of application of our model in the context of vector-borne tropical diseases , we used genetic field data on T . brasiliensis ( vector of the pathogen responsible for the Chagas disease ) in the Caicó municipality in Northeastern Brazil ( Rio do Grande do Norte state ) . Triatomine individuals were sampled during a field work performed in March 2011 . Domestic habitats consisted in houses , peridomestic habitats of the area 50 meters around houses and sylvatic habitats of areas at a minimum of 200 meters from any house . In total 126 individuals were collected in five different locations ( populations ) chosen to cover a range of distance between sampling points and habitat types ( three sylvatic , one peridomestic and one domestic populations; see Figure 1A ) . All individuals were genotyped according to seven microsatellites as neutral markers [21] , and pairwise fixation index ( FST ) , allelic diversity and observed heterozygosity computed using Arlequin version 3 . 5 [28] . A detailed description is available in supporting information S1 , and FST results in Table 2 . As the main objective of our study case was to explore the effect of vector dispersal on observed population genetic structure ( using FST values ) , we focused our analysis on three specific variables: i ) vector's migration rate ( m ) ; ii ) vector's dispersal distance ( i . e . , the maximum distance covered by an individual during its life cycle , including passive and active dispersal ( d ) ) ; and iii ) vector's attraction by a specific habitat type ( i . e . , the strength that impedes individual from emigrating when they are located in a specific habitat type ( l ) ) . Note that all output files from simulations were designed as input files for Arlequin ( genotypes of individuals from the 7 microsatellite loci ) , using the same sampling method , so that observed and simulated FST values could be compared .
As expected , we found a significant effect of migration rate ( m ) on the FST values ( see Table 3 ) . The effect of dispersal distance ( d ) was also significant except between two sampling sites ( A and C ) that were very close from each other ( Euclidian distance; FAC ( 1 , 8991 ) = 1 . 4 , p = 0 . 24 ) . Dispersal distance explained much less variance in the ANOVA than migration rate ( see differences in F-values in Table 3 ) . The same result was found when testing for the effect of domestic habitat attraction on FST . On average , for all 10 couples of sampled locations , 58%±7 of the variance of FST in the ANOVA models was explained by migration rate , dispersal distance , and domestic type attraction . The optimization procedure revealed that the difference between observed and simulated FST was lowest at high migration rates , average dispersal distances and low domestic habitat attractions ( see the redder zone of the ternary plot , Figure 3 ) . The best set of parameter values from this zone explained 50% of the FST values observed in the field ( see Table 4 , using m = 0 . 6; d = 3; and l = 2 ) . Note that overall , the combinations of migration rate , dispersal distance and domestic habitat attraction could significantly explain 70% of FST values . The dynamics of the spatial genetic structure of T . brasiliensis populations strongly differed between the urbanization and the "no land-use change" ( control ) scenarios ( see Figure 4 for FST between individuals located at sampling points A and B ) . In the control scenarios , FST reached a threshold and stabilized within 100 generations for all couples of sampled locations ( e . g . , mean FST threshold value of 0 . 021 between A and B with and without selection , see Figure 4 ) . Contrastingly , FST values did not reach such threshold in the urbanization scenarios ( e . g . , mean FST threshold value of 0 . 030 and 0 . 027 between A and B with and without selection , respectively ) , except between individuals at sampling locations A , C and E . We found a significant effect of land-use change on FST after 100 generations ( e . g . , between A and B: F = 24 . 6 , df = 1 , p<0 . 05 ) . Contrastingly , the effect of selection was not significant , even if FST values were generally higher in the scenarios including selection .
Understanding the dispersal behavior of vector arthropods is a central issue in the control and surveillance of vector-borne tropical diseases [48] , [49] . Although dispersal studies on vectors have been conducted since the eighties ( e . g . , [29] ) , accurate descriptions of the spatio-temporal distribution of most tropical pathogen vectors are still lacking . Along with recent advances in spatially explicit models [48] , our study proposes a contribution to better characterize the dispersal behavior of the vectors of T . cruzi , responsible for Chagas disease . This characterization is exemplified in this study with a generic platform providing a natural description of the dispersal mechanisms [50] , adapted to the social-ecological system inhabited by T . brasiliensis . Our study successfully ranked parameters of T . brasiliensis dispersal and participated in explaining observed patterns ( spatial population differentiation using FST ) by linking them to processes ( vectors ecology and behavior ) . It thus represents a contribution in understanding the underlying mechanisms of T . brasiliensis spatial genetic structure and population dynamics . Inevitably , our study made a series of assumptions and simplifications inherent to the modeling process . If some were attributable to the methodological framework , others pointed gaps in the knowledge of T . brasiliensis ecology and genetics . The selection for habitat type submodel , for instance , relied on the theoretical basis of one locus under selection per habitat type . Further studies of T . brasiliensis are needed and should allow the identification candidate genes responsible for adaptation for habitat type which would considerably refine the theoretical submodel , and possibly lead to inference on selection coefficients . Moreover , additional field studies , such as those conducted for other Triatomine species ( e . g . , studies describing and quantifying the influence on vectors of public street lights; [51] , [52]; or describing the vectors active and passive dispersal [53] ) would help refining our results for T . brasiliensis . Additionally , the use of a more complex population dynamic model might have permitted to analyze the impact of other demographic parameters on population structuring , like the density of the population or the lifespan . Consequently , prospective scenarios , grounded on actual knowledge and limited dataset , should be regarded as theoretical insights . They remain pertinent tools with implications in term of vectors surveillance and control . For example , our T . brasiliensis prospective scenarios in Northeastern Brazil revealed a significant influence of land-use on vector spatial genetic structure . It suggested that in urbanized areas , where hosts are abundant , vector population gene flow would be reduced ( higher FST between sampling points ) . While anthropogenic landscape disturbance proved to increase vector infection by T . cruzi [54] , it is more important than ever to anticipate for the effect of future landscapes on vector dynamics and spatial genetic structure , in order to establish efficient management strategies . This study on T . brasiliensis and associated prospective scenarios suggest that control techniques should be examined in their social-ecological context , accounting for anthropogenic features to come . Beyond our empirical study case , the objective of the paper was to present a methodological framework for studying vectors population genetics of pathogens which can integrate its biological , ecological and sociological components . Although various studies have assessed and described the emergence of zoonoses and vector-borne diseases as the result of social-ecological interactions ( e . g . , [55] , [56] ) , this approach has been disregarded in population and landscape genetic simulations ( [2] , [49] , but see [57] ) . Integrating social-ecological interactions in landscape genetics remains a key challenge , especially when considering that vectors of pathogens are localized in areas subject to anthropogenic disturbance across scales [58] , [59] . At the interface across disciplines , this methodological framework allows the consideration of different types of knowledge and takes into account the causes of vector spatial genetic structure at multiple levels . Our hope is that our study may provide a testable and applicable modeling framework to a broad community of epidemiologists for formulating scenarios of landscape change and foresee their consequences on vector dynamics and genetic structure , with potential implications for their surveillance and control .
|
Worldwide , humans are modifying landscapes at an unprecedented rate . These modifications have an influence on the ecology of pathogen vectors , yet this issue has received relatively little input from modeling research . The current study presents guidelines for the use of a modeling framework for the representation of the dynamics and spatial genetic structure of pathogen vectors . It allows considering spatiotemporal landscape modifications explicitly , to represent human-altered modifications and consequences . We applied this modeling framework to Triatoma brasiliensis , vector of the pathogen Trypanosoma cruzi responsible for the Chagas disease , in the semi-arid Northeastern Brazil . Using field data of pairwise fixation index ( FST ) from microsatellite loci , we found that migration rate , maximum dispersal distance and attraction by domestic habitat were all key parameters to understand vector spatial genetic structure at the landscape level . At the interface across disciplines , this study provides to the community of epidemiologists a testable and applicable framework to foresee landscape modification consequences on vector dynamics and genetic structure , with potential implications for their surveillance and control .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"biology",
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2014
|
Simulating Population Genetics of Pathogen Vectors in Changing Landscapes: Guidelines and Application with Triatoma brasiliensis
|
Infection with Leishmania results in a broad spectrum of pathologies where L . infantum and L . donovani cause fatal visceral leishmaniasis and L . major causes destructive cutaneous lesions . The identification and characterization of Leishmania virulence genes may define the genetic basis for these different pathologies . Comparison of the recently completed L . major and L . infantum genomes revealed a relatively small number of genes that are absent or present as pseudogenes in L . major and potentially encode proteins in L . infantum . To investigate the potential role of genetic differences between species in visceral infection , seven genes initially classified as absent in L . major but present in L . infantum were cloned from the closely related L . donovani genome and introduced into L . major . The transgenic L . major expressing the L . donovani genes were then introduced into BALB/c mice to select for parasites with increased virulence in the spleen to determine whether any of the L . donovani genes increased visceral infection levels . During the course of these experiments , one of the selected genes ( LinJ32_V3 . 1040 ( Li1040 ) ) was reclassified as also present in the L . major genome . Interestingly , only the Li1040 gene significantly increased visceral infection in the L . major transfectants . The Li1040 gene encodes a protein containing a putative component of an endosomal protein sorting complex involved with protein transport . These observations demonstrate that the levels of expression and sequence variations in genes ubiquitously shared between Leishmania species have the potential to significantly influence virulence and tissue tropism .
Leishmania protozoa are transmitted by the bite of an infected sandfly and cause a spectrum of diseases ranging from self-healing cutaneous lesions to fatal visceral infection [1] , [2] . There are an estimated 12 million cases in over 80 countries , with an annual incidence of 0 . 5 million new cases of the visceral leishmaniasis and 2 . 0 million cases of the cutaneous leishmaniasis [3] . More than 20 different Leishmania species can infect humans . Host health status and genetic background can influence the outcome of infection [4] , [5] and HIV co-infection has dramatically increased the incidence of visceral leishmaniasis [5] . The major factor that determines the tropism and pathology of Leishmania infection is however the species of Leishmania [1] , [2] . For example , L . donovani , L . infantum and L . chagasi are closely related members of the L . donovani complex that cause visceral leishmaniasis , which is fatal if not treated . L . major and L . tropica infections usually result in cutaneous lesions that remain localized at the site of the sandfly bite . L . ( Viannia ) braziliensis causes cutaneous leishmaniasis but can also migrate from the site of initial infection to the nasopharyngeal area resulting in highly destructive mucocutaneous leishmaniasis . The Leishmania genome projects are expected to help identify the genetic differences between these parasites which govern the pathology and tropism of infection caused by the different Leishmania species [6]–[8] . Our laboratory has previously identified the A2 gene family , which is present in Leishmania species that cause visceral infections including L . infantum and L . donovani but are not present in many of the Leishmania species that cause cutaneous infections including L . major and L . tropica [9] , [10] . A2 proteins have been shown to be essential for visceral infection with L . donovani in BALB/c mice [11] , [12] . Cross species transfection of the A2 gene from L . donovani into L . major rendered L . major more virulent in visceral organs but less virulent at cutaneous sites , phenotypes typical of L . donovani [12] , [13] . This demonstrated that species-specific genes can play a role in virulence and the pathology of Leishmania infection and provided the justification for experimentally studying species-specific genes identified through sequencing of the Leishmania genomes . We used the genetic information from the completion of the L . major , L . infantum , and L . braziliensis genomes [6] , [7] to identify genes that could potentially influence the pathology caused by these Leishmania species . Remarkably , out of more than 8000 genes within the Leishmania genome , only about 25 L . infantum-specific genes have been identified which are not present or are pseudogenes in L . major and L . braziliensis , and most encode for proteins with no known function [7] . Using the L . infantum genome sequence database , we have cloned 7 L . donovani ortholog genes that were absent or were pseudogenes in L . major and introduced these genes into L . major . The L . donovani gene containing transgenic L . major parasites were introduced into BALB/c mice to determine whether any of these genes increased virulence in visceral sites including the liver and spleen . During the course of this study , one of these selected L . infantum genes , LinJ32_V3 . 1040 ( Li1040 ) , initially classified as absent in L . major , was identified in a blast search of the L . major shotgun sequences and subsequently reclassified as present in the genomes of L . major , L . infantum , L . braziliensis and L . donovani . Surprisingly , it was the Li1040 gene , which encodes a hypothetical protein potentially involved in protein transport , which dramatically increased L . major infection levels in the liver and spleen of BALB/c mice . These observations establish the functional genomic approach to study virulence genes in Leishmania and demonstrate that the levels of expression and/or sequence variation in genes conserved among different Leishmania species have the potential to contribute significantly to virulence and tissue tropism .
The detail comparison of three sequenced Leishmania genomes have been described [7] . However , gene-by-gene comparisons for this study were made in the first release of the L . infantum genome sequence ( September 17 2004 ) , following automatic annotation of translational open reading frames via BLAST analysis and comparison with L . major . This first stage analysis has demonstrated high conservation in both gene content and order ( synteny ) between the L . infantum and L . major genomes . At start of this study , only up to 20 genes have been identified that are either present in L . infantum and absent in L . major or which are present as complete open reading frames in L . infantum but occur as pseudogenes in L . major . In this study , we chose seven of these potential L . infantum specific genes , which we cloned from L . donovani 1S/Cl2D using primer sequences derived from the corresponding L . infantum genes . This L . donovani strain causes visceral infection in mice when introduced intravenously . The cloned L . donovani genes were subsequently transfected into L . major for crossing species transfection studies ( Table 1 ) although one of these , Li1040 was later identified to be also present in L . major and L . braziliensis . To detect L . donovani gene products expressed in L . major , we modified the Leishmania expression vector ( pLPneo ) [14] by adding a 10 amino acid A2 epitope tag or a GFP tag into its multiple cloning site . Briefly , the pLA2tag vector was constructed by inserting an adapter sequence encoding 10 A2 amino acids ( QSVGPLSVGP ) and a stop codon flanked by BamH I and Not I sites into the multiple cloning sites ( BamH I and Not I ) of the pLPneo vector . The adapter sequences are: 5′ GATCCGCAGTCCGTCGG CCCGCTCTCCGTTGGCCC GTAGC ( plus strain ) and 5′GGCCGCTACGGGCCAAC GGAGAGCGGGCCGACGGACTGCG ( minus strain ) . pLA2tag vector is therefore suitable for expressing fusion protein with A2 tag at its C-terminus . pLGFPC vector was constructed by following two steps: 1 ) a 820 bp Nhe I and Bcl I fragment containing green fluorescent protein ( GFP ) gene was removed from pEGFP-C3 vector ( BD Biosciences Clontech ) . 2 ) the 820 bp Nhe I and Bcl I fragment was ligated into the Xba I and BamH I sites of pLPneo vector , generating pLGFPC vector . pLGFPC is suitable for expressing GFP fusion proteins with GFP at the N terminus . To facilitate cloning of L . donovani genes into pLA2tag or pLGFPC vector , a restriction enzyme site ( Hind III , BamH I or Bgl II ) was added to the 5′ end of PCR primers . The PCR primers for LinJ32_V3 . 1040 are 5′cccaagcttACAATGGAGCTGACACTGCATC , 5′cgagatctGTGGGGAACATCATCTTGAGCTG and 5′cgagatctTAGGGGAACATC ATCTTGAGCTG; primers for LinJ08_V3 . 0560 are 5′cccaagcttCCAAGCTTCCAAGCATGGAAAACCGGCCA and 5′cgggatccgtCGGCCGGTACACGCTGACGTA; primers for LinJ36_V3 . 0640 are 5′cccaagcttCTCACCATGGCGGCAACTCATC and 5′cgggatcccaCTT CGGCAAACCGTTCTTTCG; primers for LinJ32_V3 . 1580 are 5′cccaagcttTCAAGCATGAGCACCAGTGCAG and 5′cgagatctGTCTTGTGACGCAATGGACCGATG; Primers for LinJ15_V3 . 1370 are 5′cccaagcttGGTAAGACGACTATGCGCAGCAG and 5′cgagatctGTACCGGCGAAGTAGCTGTGCAG; Primers for LinJ36_V3 . 4190 are 5′cccaagcttGCGATGGGGCGAATCGACTC and 5′cgagatctgtAGAGTTAG TCGGCAGCCGAGG: Primers for LinJ08_V3 . 0140 are 5′cccaagcttAACATTATG TTGGCTAGCGCTG and 5′cgagatctgtGAGCAGATTCGCAGCACGCA; Primers for LmjF32 . 0985 are 5′cccaagcttACAATGGAGCTGACACTGCATC and 5′cgagatctGT TTGGGTGAACATCATCTTGAGCTG . PCR amplifications were performed using Taq DNA polymerase ( Invitrogen ) following manufacturer's instruction . L . major Friedlin V9 , L . donovani 1S/Cl2D strains were used in this study . Promastigotes were routinely cultured at 27°C in M199 medium ( pH 7 . 4 ) supplemented with 10% heat-inactivated fetal bovine serum , 40 mM Hepes ( pH 7 . 4 ) , 0 . 1 mM Adenine , 5 mg l−1 Haemin , 1 mg l−1 Biotin , 1 mg l−1 Biopterine , 50 U ml−1 Penicillin and 50 µg ml−1 Streptomycin . To determine the Li1040 gene transcript levels in different culture conditions , L . donovani and L . major promastigotes were also shifted to 37°C , pH 5 . 5 culture media for 6 hours to mimic the macrophage phagolysosome environment associated with the amastigote stage . Under these conditions , L . donovani remains viable and is induced to differentiate into amastigotes . Although the majority of L . major remain viable for this 6 hours period , they are unable to differentiate into amastigotes [13] . The procedure for transfection was as previously described [14] . Briefly , 10–20 µg of plasmid DNA was used in each transfection . After electroporation , the Leishmania promastigotes were transferred into a drug-free culture medium and the following day , G418 was added to make the final concentration of G418 100 µg ml−1 . To avoid selection of spontaneous mutants , pooled transfectants were used for all subsequent studies including mice infections , growth in culture , Southern , Northern and Western blot analysis . Female BALB/c mice weighing 18–20 g were purchased from Charles River Breeding Laboratories and maintained in the animal care facility under pathogen-free conditions . BALB/c mice were infected by tail vein injection with 1×108 stationary-phase promastigotes in 100 µl PBS per mouse [11]–[13] . Six weeks post infection , the in vivo infection-selected amastigotes were isolated from the spleen as described [15] . The isolated amastigotes were transformed into promastigotes in M199 L . major culture medium containing 50 µg ml−1 G418 . When the G418-resistant culture was established , the culture was subjected to Westernblot analysis . To subsequently compare the virulence of plasmid transfectants , BALB/c mice were infected by tail vein injection with 1×108 stationary-phase promastigotes in 100 µl of PBS per mouse . The amastigotes were isolated from infected mice after 4 , 6 , 8 and 10 weeks of visceral infection respectively . The recovered amastigotes were cultured in promastigote culture medium , and the Leishmania parasite burdens were determined by limiting dilution . For cutaneous infections , mice were infected subcutaneously with 5×106 stationary-phase promastigotes in their hind footpads . Disease progression was monitored by weekly caliper measurement of footpad swelling . The growth curves of Leishmania transfectants were measured in 96-well plates . Promastigotes in stationary phase were seeded at a concentration of 4×105 ml−1 into wells containing 200 µl of medium with 50 µg ml−1 G418 . Each sample was plated in triplicate . The OD600 values were measured daily for total 7 days . Total Leishmania protein , RNA , genomic DNA were prepared and analysed as previously described [16] . The DNA probes were labelled with [α-32P]-dCTP by random priming . Indirect immunofluoresence was performed as described [14] , [17] , [18] . Anti-A2 monoclonal antibody C9 hybridoma supernatant without further dilution was used as the primary antibody in the immunofluoresence study .
At the beginning of this study , about 20 genes were identified as present in L . infantum and absent or were pseudogenes in the L . major genome . Among these genes , only a few encode products whose function could be predicted by sequence similarity searches . To investigate whether these species-specific genes are involved in tropism and pathology of Leishmania infection , 7 genes were initially selected for expression in L . major . This selection included 4 genes intact only in L . infantum , 2 genes intact in L . infantum and L . braziliensis but absent in L . major , and 1 gene which was intact in L . infantum , L , braziliensis , and L . major ( Table 1 ) . The single gene ( Li1040 ) that is intact in all species was initially classified as absent in L . major but during the course of this study was reclassified as present in all Leishmania species . It is likely that the Li1040 gene was initially classified as absent in L . major during the assembly of the genome because it is flanked by two identical 384 repeat sequences ( Figure 1 ) . L . infantum and L . donovani both belong to the L . donovani species complex . We thus assumed that genes present in L . infantum would be largely identical in L . donovani and therefore the corresponding L . donovani genes were introduced into L . major . We carried out PCR amplification of the L . infantum ortholog genes from L . donovani 1S/Cl2D genomic DNA and ligated them into a Leishmania expression vector , pLPneo [14] , that was engineered to encode a 10 amino acid L . donovani A2 peptide epitope tag at the C terminus as detailed in Methods ( Figure 2A ) . Since L . donovani A2 proteins are absent in L . major [8] , [10] , [11] , inclusion of the 10 amino acid A2 peptide epitope tag enabled detection of the L . donovani transgene products expressed in L . major using an anti-A2 monoclonal antibody ( Mab ) . Expression of these L . donovani genes in transfected L . major were determined by Western blot analysis with anti-A2 Mabs and revealed that 6 out of the 7 selected genes expressed the corresponding proteins at the predicted molecular weights ( Figure 2B , lanes 1–8 ) . All of the transgenic L . major parasites except the LinJ36_V3 . 4190 transfectant stably expressed detectable levels of the L . donovani ortholog proteins . We initially performed an in vivo selection in BALB/c mice to determine whether any of the transgenic L . major parasites were better adapted for survival in visceral organs . The transgenic L . major parasites including the vector control ( Neo ) were pooled , and injected into the tail vein of BALB/c mice . Amastigotes were recovered from the spleens of infected mice 6 weeks following injection , cultured out as promastigotes and subjected to Western blot analysis with anti-A2 epitope tag Mab to determine whether any of the L . donovani transgenes were expressed in the spleen derived parasites . As shown in Figure 2B , lane 9 , the transgenic L . major parasites expressing the L . donovani Li1040 ortholog gene were detectable . This suggests that , relative to the other transfectants , the transgenic L . major expressing the L . donovani Li1040 ortholog gene displayed enhanced survival in the spleen . In addition to the in vivo selection in BALB/c mice , we also performed an in vitro selection in axenic amastigote culture media . The pooled transgenic L . major promastigotes were placed in amastigote culture conditions at pH 5 . 5 and 37°C for 3 days , conditions that mimic the phagolysosomal compartment of macrophage cells in visceral organs . These culture conditions typically result in loss of viability of L . major , which are unable to adapt and proliferate under these conditions . In contrast , L . donovani differentiate into amastigote like parasites and are able to proliferate under these culture conditions . Following this in vitro selection , some of the transgenic L . major survived and were shifted back to promastigotes culture conditions ( pH 7 . 4 , 27°C ) to allow them to proliferate . The resulting in vitro selected transgenic L . major was subjected to Western blot analysis with the anti-A2 epitope Mabs to detect expression of the L . donovani transgene products . As shown in Figure 2B lane 10 , similar to the in vivo infection selection , the Li1040 protein was the major transgene product detectable in the in vitro selected transgenic L . major . Taken together , the in vivo and in vitro selection protocols resulted in selection for L . major parasites expressing the Li1040 ortholog gene . The preceding experiments argue that expression of the L . donovani Li1040 gene ortholog in L . major provided a survival advantage in the spleen of BALB/c mice . It was therefore necessary to directly confirm this by comparing parasite numbers following infection with L . major expressing the Li1040 ortholog to the control L . major transfectants ( Neo ) containing the empty vector . Parasite burdens were determined in the liver and spleen after 4 , 6 , 8 and 10 weeks following infection via the tail vein . Replicate experiments are shown for this analysis to confirm reproducibility since the kinetics and levels of infection can vary considerably between visceral infection experiments . As shown in Figure 3A , expression of the L . donovani Li1040 ortholog in L . major gave rise to increased parasite numbers in the liver and spleen , which was most prominent at 8 weeks in the liver , and 6 to 10 weeks in the spleen and this was consistent in the duplicate experiments ( Figure 3B , C ) . We also repeated this analysis by over-expressing the Li1040 gene with the A2 epitope tag removed , to rule out the possibility that the 10 amino acid A2 sequence may have been responsible for the increased virulence associated with the expression of the A2 epitope-tagged Li1040 . The Li1040 ortholog gene containing no A2-tag was cloned into Leishmania expression vector pLPneo and introduced into L . major . As shown in Figure 3C , L . major transfected with Li1040 gene with no A2-tag displayed similar visceral infection kinetics in BALB/c mice as L . major expressing Li1040 containing the A2-tag . This demonstrated that the A2-tag was not responsible for the increased virulence associated with over-expression of the Li1040 protein in L . major . Since L . major typically causes cutaneous infections , it was necessary to determine whether expression of the L . donovani Li1040 ortholog in L . major also increased virulence at cutaneous sites or increased proliferation in cultured promastigotes . BALB/c mice were infected subcutaneously in the rear left footpad with L . major expressing the Li1040 ortholog and the control vector containing L . major and lesion development were measured weekly . As shown in Figure 4A , expression of the L . donovani Li1040 ortholog gene in L . major did increase the level of cutaneous infection in the footpad although not to the same extent as was observed in the liver and spleen . Although the L . donovani Li1040 ortholog gene enhanced L . major virulence in vivo , it did not provide a growth advantage to promastigotes in culture ( Figure 4B ) . Our original assumption was that L . infantum/L . donovani specific genes would be the most likely to increase visceral infection when expressed in L . major , similar to what we observed previously with the L . donovani specific A2 gene [12] . It was therefore unexpected that the L . donovani Li1040 ortholog gene , which was also present in L . major and L . braziliensis , was selected for in the visceral organs of BALB/c mice and increased virulence in the liver , spleen and to a lesser extent in the skin . The ectopic expression of the L . donovani Li1040 ortholog in L . major may have increased virulence due to increased levels of expression or to sequence variations resulting in a protein with enhanced function . Sequencing of the L . donovani Li1040 ortholog gene revealed that it differed by only 5 nucleotides from the L . infantum Li1040 gene and none of these nucleotide changes altered the amino acid sequence ( Figure 5 ) . Alignment of the L . infantum/L . donovani Li1040 protein with the L . major and L . braziliensis orthologs revealed that Li1040 has 92% identity with the L . major ortholog and 82% identity with the L . braziliensis ortholog ( Figure 5 ) . This is exactly the same percentage ( 92% ) as the genome average amino acid identity between L . major and L . infantum [5] arguing that there was no selective evolutionary pressure to alter the Li1040 sequence relative to the rest of the genome . The Li1040 ortholog gene is also present in other Kinetoplastids including Trypanosoma cruzi ( 33% identity ) and Trypanosoma brucei ( 32% identity ) ( Figure 5 ) . Interestingly , a Vps23 core domain of the yeast vacuolar protein-sorting protein 23 ( Vps23 , or Tumor susceptibility gene 101 ( Tsg101 ) in human ) was identified between amino acid 267 and 331 of the Li1040 protein ( see Figure 5 highlighted sequences ) . The Vps23/Tsg101 proteins have been shown to be involved in protein sorting from endosomes to lysosomes [19] , [20] , ( see more in discussion ) . Considering the above observations , it was necessary to investigate the possibility that the endogenous Li1040 ortholog gene was expressed at higher levels in L donovani than in L . major . Total RNA was extracted from wildtype L . donovani and L . major cultured under promastigote conditions ( 27°C , pH 7 . 4 ) and amastigotes conditions ( 37°C , pH 5 . 5 ) and subjected to Northern blot analysis with the L . donovani Li1040 ortholog gene . As shown in Figure 6 , the Li1040 ortholog gene was constitutively expressed in L . donovani promastigotes and amastigote-like cultures . The expression level of the Li1040 ortholog gene in L . major promastigotes was similar to that in L . donovani promastigotes . The lower level of expression in the L . major amastigotes culture conditions was likely due to reduced viability of some of the L . major cells when cultured briefly at 37°C pH5 . 5 since the level of the control α-tubulin mRNA was also reduced under these conditions . Compared with the α-tubulin gene , the expression level of Li1040 ortholog gene in both L . donovani and L . major is low , since only a weak signal was apparent after 2 days of film exposure on the blot and a strong signal was only apparent after 7 days of film exposure . In comparison , a strong signal was apparent for α-tubulin mRNA after less than a day of film exposure with a probe containing the same level of specific radioactivity as the Li1040 ortholog gene probe . Although the level of mRNA is similar , the possibility remains that the Li1040 protein is present in higher levels in L . donovani than in L . major since the mRNA levels in Leishmania generally correlate poorly with the corresponding protein level [21] . Future studies are needed to generate antibodies to the endogenous Li1040 gene product to directly compare protein levels in L . major and L . donovani . Since the sequence analysis of the Li1040 ortholog gene in L . donovani and L . major showed they are very similar , we sought to determine its cellular localization in these parasites . The L . donovani Li1040 ortholog gene was fused with the GFP gene and introduced into L . donovani and L . major . As shown in Figure 7A , the GFP-Li1040 fusion proteins were expressed at the expected size ( 791kDa ) in L . donovani and L . major . Fluorescence microscopy revealed that although the GFP-Li1040 ortholog fusion proteins were distributed throughout the cell including the flagella in both L . major and L . donovani transfectants , the majority of GFP-Li1040 fusion protein appear to be present as cytoplasmic aggregates ( Figure 7B ) . Similar localization of the A2-tagged L . donovani Li1040 ortholog protein was shown in transgenic L . major using anti-A2 Mabs ( Figure 7C ) . Interestingly , comparable cellular appearance and distribution were reported for the mammalian Tsg101 protein , the potential homolog of Leishmania Li1040 [22] . The above described experimental analyses suggest that the increased expression level of plasmid derived Li1040 may have played a greater role in increasing parasite virulence than the sequence differences between the corresponding L . donovani and L . major ortholog genes . We attempted to address this issue by over-expressing the L . major Lm0985 gene in L . major . Lm0985 is the L . major ortholog of L . infantum/donovani Li1040 . As shown in Figure 8A , epitope tagged L . major Lm0985 was detectable in transfected L . major . Over-expression of the L . major Lm0985 and L . donovani Li1040 othologs in transgenic L . major both resulted in increased parasite levels in the liver and spleen at various times following infection ( Figure 8B , C ) . The generally high levels of infection seen with the Li1040 transgenic L . major parasites relative to the Lm0985 transgenic parasites could have however been due to the higher expression levels of Li1040 relative to Lm0985 ( Figure 8A ) . Taken together these results argue that over-expression of either Lm0985 or Li1040 results in increased parasite virulence . It was also noteworthy that , although there was approximately a 4 fold increase in spleen parasite numbers with the Li1040 gene expressing L . major compared to the control Neo L . major parasites at 10 weeks following infection ( Figure 8C ) , this difference was less than the previous 3 independent infection experiments shown in Figure 3 . This highlights the importance of carrying out multiple repeat independent infection experiments which taken together confirm that over-expression of Li1040 results in increased virulence .
In the present study we have developed an experimental approach to generate and follow transgenic L . major expressing L . donovani genes in vivo in BALB/c mice . Rational for this study comes from our previous observations where expression of the L . donovani specific A2 gene increased L . major survival in visceral organs [12] and we therefore anticipated that additional L . donovani/L . infantum specific genes could also increase L . major virulence in the visceral organs . L . major expressing the L . donovani Li1040 ortholog gene was selected for in the spleen of BALB/c mice and further shown to dramatically increase L . major parasite numbers in the liver and spleen and to a much lesser extent in the skin . This outcome was somewhat unexpected since the Li1040 ortholog gene was subsequently established to be present in L . major and L . braziliensis in addition to L . donovani and L . infantum . This revealed that genes ubiquitously present in different Leishmania species could also have a dramatic effect on parasite tropism and virulence . It is noteworthy that Li1040 expressing transgenic L . major were rapidly selected for in vitro after 3 days when placed under amastigote culture conditions at 37°C and pH 5 . 5 . Over-expression of the Li1040 ortholog however did not enhance promastigotes proliferation in culture at 27°C and pH 7 . 4 ( Figure 4B ) . This suggests that the Li1040 product enables amastigotes to survive under conditions associated with host macrophage phagolysosomes . This was consistent with the observation that Li1040 ortholog expressing L . major were likewise selected for in vivo after several weeks in the liver and spleen of BALB/c mice ( Figure 2 ) . Although these observations suggest that Li1040 plays a greater central role in the amastigote stage , it also appears to be essential for survival as promastigotes since repeated attempts to generate homozygous L . donovani Li1040 gene deletions in promastigotes have so far been unsuccessful . It was interesting to find that the Li1040 protein contains the Vps23 core domain of the Vps23 and Tsg101 proteins in yeast and human respectively . Vps23 is one of the four protein subunits ( Vps23 , Vps28 , Vps37 and Mvb12 ) of the yeast ESCRT-I ( Endosomal Sorting Complex Required for Transport ) complex , which forms the complex driving protein transport from endosomes to lysosomes [19] , [20] . The core domain of the Vps23 has been shown to be essential for formation of ESCRT-I complex [19] , [20] . Moreover , the homologs of the three other subunits of ESCRT-I complex ( Vps28 , Vps37 and Mvb12 ) also appear to be present in the Leishmania genome ( LinJ36_V3 . 5400 encodes a homolog of Vps28 , and several potential homologue proteins for Vps37 and Mvb12 are also present in Leishmania , data not shown ) . Since all 4 ESCRT-1 subunits appear to be present in Leishmania , this suggests that , similar to Vps23 , Li1040 may also be involved in protein transport . In higher eukaryotes , the Tsg101 ( tumour susceptibility gene 101 ) plays an essential role in embryonic development [23] , [24] and loss of Tsg101 in cell lines is associated with neoplastic transformation [25] confirming it plays an essential role in cell biology . It is noteworthy that the focus of this study was on genes whose expression was selected for in the parasites isolated from the spleen of BALB/c mice . Although this approach proved successful to identify the ability of the Li1040 gene to increase virulence , this does not rule out the possibility that some of the other species-specific genes can also increase virulence . Since there are relatively few species-specific genes , it may be possible to further study the role of individual genes without performing the in vivo selection used in this study . For example , the cyclopropane fatty acyl phospholipid synthase ( CFAS ) gene is present in L . infantum and L . braziliensis but not L . major . The CFAS gene in Mycobacterium tuberculosis ( Mtb ) has been shown to modify cell surface glycolipids , which promotes an inflammatory response and granuloma formation ( Table 1 ) [26] . It would be interesting to determine whether CFAS affects Leishmania surface glycolipid composition and virulence even though it was not enriched for following in vivo selection in mice in this study . The gene encoding Sec14 cytosolic factor is present in L . infantum but is a pseudogene in L . braziliensis and absent in L . major ( Table 1 ) [7] . The Sec14 cytosolic factor has been implicated in the release of secretory vesicles from the trans-golgi network [27] and therefore may influence cell-surface molecule expression in L . infantum and affect host-parasite interactions . These examples and others could be tested individually by transfecting the L . infantum genes into L . major and studying the phenotype of the resulting transgenic parasites . We are currently focusing on additional L . infantum specific genes , which are absent in both L . major and L . braziliensis and introducing these into L . major to assay for changes in virulence as described in this study . The genetic determining factor ( s ) controlling tropism and virulence could however be widely embedded throughout these different genomes involving a combination of species-specific genes , posttranscriptional regulation and gene polymorphisms . The Li1040 gene identified in this study may be among those playing a major role in virulence and tropism .
|
Parasites of the genus Leishmania cause a variety of human diseases that range from destructive skin lesions caused by L . major to visceral infections of the liver and spleen caused by L . donovani that result in death . The Leishmania genes responsible for these different pathologies are not known . In the present study , we used a comparative genome-based approach to introduce and over-express L . donovani genes in L . major to determine whether this results in increased virulence of L . major in visceral organs of infected mice . Through this approach , a novel gene termed Li1040 was identified that is potentially involved in protein transport and was shown to increase pathogenesis in the visceral organs in mice . The Li1040 gene may therefore represent a Leishmania virulence gene that has the potential to regulate the pathology of infection in the mammalian host . These observations help to define how Leishmania causes fatal infections in humans and therefore provide a parasite-specific target for therapy .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"infectious",
"diseases/neglected",
"tropical",
"diseases",
"infectious",
"diseases/tropical",
"and",
"travel-associated",
"diseases",
"genetics",
"and",
"genomics/comparative",
"genomics",
"genetics",
"and",
"genomics/functional",
"genomics"
] |
2008
|
A Genomic-Based Approach Combining In Vivo Selection in Mice to Identify a Novel Virulence Gene in Leishmania
|
MicroRNAs ( miRNAs ) have been found to regulate gene expression across eukaryotic species , but the function of most miRNA genes remains unknown . Here we describe how the analysis of the expression patterns of a well-conserved miRNA gene , mir-57 , at cellular resolution for every minute during early development of Caenorhabditis elegans provided key insights in understanding its function . Remarkably , mir-57 expression shows strong positional bias but little tissue specificity , a pattern reminiscent of Hox gene function . Despite the minor defects produced by a loss of function mutation , overexpression of mir-57 causes dramatic posterior defects , which also mimic the phenotypes of mutant alleles of a posterior Hox gene , nob-1 , an Abd homolog . More importantly , nob-1 expression is found in the same two posterior AB sublineages as those expressing mir-57 but with an earlier onset . Intriguingly , nob-1 functions as an activator for mir-57 expression; it is also a direct target of mir-57 . In agreement with this , loss of mir-57 function partially rescues the nob-1 allele defects , indicating a negative feedback regulatory loop between the miRNA and Hox gene to provide positional cues . Given the conservation of the miRNA and Hox gene , the regulatory mechanism might be broadly used across species . The strategy used here to explore mir-57 function provides a path to dissect the regulatory relationship between genes .
miRNAs are small endogenous RNA molecules found in most eukaryotic species that are involved in post-transcriptional regulation of genes required for cell fate determination , metabolism and carcinogenesis among other processes [1] . Like protein coding genes , miRNA genes are transcribed by RNA polymerase II [2] , [3] , suggesting a transcriptional regulatory mechanism similar to that of messenger RNAs . Over 155 miRNAs have been identified in C . elegans through a combination of molecular and bioinformatics methods [4]–[8] . Many of these are well conserved across eukaryotes , but only a few have been functionally characterized . For example in C . elegans , the founding members of miRNAs lin-4 and let-7 [9] , [10] regulate lin-14 and hbl-1 respectively and are involved in controlling timing of development . In addition , the lys-6 and mir-273 miRNAs function sequentially and asymmetrically to control chemosensory neuronal development [11] , [12] . mir-61 has been shown to be a direct transcriptional target of LIN-12 , and is involved in down regulation of vav-1 , which in turn promotes LIN-12 activity in presumptive 2° VPCs [13] . let-7 and its paralog mir-84 act synergistically to direct cessation of molting via the conserved nuclear hormone receptors NHR-23 and NHR-25 [14] . However , most miRNA genes in C . elegans show no or only very subtle phenotypic effects when the gene is deleted from the genome [15] , making their function elusive by classical genetic assays . One approach to determining the function of these miRNAs would be to use their detailed expression patterns to find genes with which they might interact . We have recently developed technology that allows automated determination of embryonic expression patterns of individual cells with one minute time resolution [16] , [17] . To apply the system to miRNAs and to see how the information might yield insights into their function , we examined the expression patterns of several miRNA genes of unknown function and found that mir-57 , a miRNA gene conserved from nematodes to mammals ( where it is named miR-10 ) [7] , produced a particularly intriguing expression pattern . Strains carrying the mir-57 promoter fused to a red fluorescent reporter , mCherry , showed the gene is exclusively expressed in the posterior sublineages of ABp ( l/r ) ( a/p ) p and a variety of sublineages of the C founder cell . These lineages produce a variety of cell types but have in common a posterior location in the embryo . Genetic analysis of a deletion mutant and overexpressing lines of mir-57 supported its role in the development of the tail of the animal . This apparent position rather than tissue/cell dependent expression pattern and impact led us to examine its interactions with other genes known to be involved in posterior fate specification , including nob-1 , vab-7 , and members of the Wnt and Notch pathways , pop-1 and lag-1 . Interactions of mir-57 and nob-1 mutants along with the presence of a putative mir-57 binding site in the 3′ UTR of a nob-1 isoform suggested that mir-57 might directly regulate nob-1 expression . To test this we examined the effects of the nob-1 3′ UTR on reporter expression . Our combined results from functional assays provide support for a negative regulatory loop between the miRNA and Hox gene , giving mir-57 an important role in posterior fate determination .
With the expectation that detailed expression analysis might suggest possible targets for mir-57 , we began our investigation of the gene by determining its embryonic expression pattern with cellular resolution at one-minute time intervals [16] , [17] . Stably integrated lines with a 2 . 26 kb fragment upstream of the mir-57 mature sequence fused with a fluorescent reporter mCherry [18] showed expression in the posterior cells of the embryo in a variety of tissues ( Figure 1 ) . Automated analysis of 3D time-lapse movies followed by manual editing revealed that the reporter was expressed in a bilaterally symmetric pattern in the posterior daughters of sublineages of AB and C founder cells , beginning at about the 200-cell stage ( Figure 1F ) . The cells from these sublineages lie in the posterior part of the embryo only and represent a wide variety of cell types , including tail seam cells , the hypodermal cells hyp10 and hyp11 , the cells producing the tail spike , rectal cells , the P11/12 cells and even body wall muscle cells ( Figure 1F , Figure S1 ) . Inspection of the movies beyond the comma stage also showed expression in the intestinal cells after elongation ( data not shown ) . Examination of larvae and adults showed that the reporter expression remained confined to the posterior of the animal with the exception of weak expression in more anterior intestinal cells ( Figure 1E ) . Signal appears to increase through the L2 stage , after which it decreases with only minimal levels detectable in the tails of adults in hermaphrodites ( data not shown ) . By contrast in males the adult tail shows high levels of expression ( Figure S2 ) . To confirm that the expression patterns of the promoter-reporter fusion reflect those of the native mir-57 expression , we performed in situ hybridization on whole mounted embryos using an LNA-modified probe . This method lacks the cellular resolution obtained through the automated lineaging system , but staining was clearly most pronounced in the posterior of the embryo in a pattern consistent with the results of the reporter assay ( Figure 1C ) , while no apparent staining was observed in the mir-57 deletion strain ( Figure 1D ) . To gain insight into the possible functional roles of mir-57 , we examined animals homozygous for a presumptive null allele , gk175 , a 414 bp deletion that removes the entire stem loop structure of the miRNA ( Figure 2A ) . The mature sequences of mir-57 are identical between C . elegans and C . briggsae ( Figure 2B and 2C ) . In agreement with previous results [15] , at lower temperatures ( 15° and 20°C ) we observed no obvious phenotype associated with the homozygous mutant and similar or only slightly increased rates of embryonic or L1 larval arrest and adult sterility compared to wild type hermaphrodite animals ( Table 1 ) . However , at 26°C the mutants exhibited significantly increased rates of arrest and sterility ( p<0 . 05 , Student's T test ) . Many animals arrested as embryos before elongation ( data not shown ) . Those arrested as larvae often had abnormal tails ( 23 of 47 examined ) . Most commonly , the tail contained a preanal bulge and vacuolated regions ( Figure 3A and 3B ) . In about 5% of the arrested larvae , we observed a forked tail spike , something we have never observed in wild type ( Figure 3B ) . Because we had also observed expression of mir-57 in the adult male tail , we wondered if the male tail morphology might be a more sensitive assay for mir-57 activity . However , of mir-57 null males that develop into adulthood and were recognizably male , we found no defects in their tail structures compared to wild type at either room and elevated temperature ( 26°C , n = 38 ) . In summary , the spatial correlation observed between mir-57 expressing cells in embryos and the defects associated with its loss of function suggests a likely role of mir-57 in regulating posterior cell fate specification in development . Because the loss-of-function allele for mir-57 only produced moderate defects in embryos and the larval tail , we reasoned that the effect of the allele is possibly masked by other miRNAs or factors that function redundantly with mir-57 . An alternative approach to defining the roles of functionally redundant genes is to over express individual genes . Therefore , we examined the phenotypic effects of mir-57 overexpression . In contrast to the low copy , integrated transgenes generated by bombardment that were used to assay expression , we used microinjection to create extrachromosomal arrays , which are expected to have many copies of the transgenes . Arrays containing the intact structural gene along with the upstream region ( −2 , 260 to +234 ) produced pronounced defects exclusively in posterior region that resembled those seen in mutations of a posterior Hox gene , nob-1 , which produces Vab ( Variably ABnormal in tail ) and Nob ( NO-Back end ) animals ( Figure 3C–3F and see below ) . These phenotypes were typically more severe and affected a higher proportion of the adults at 20°C than were seen in the null allele at 26°C ( Table 1 and Table 2 ) . mir-57 ( gk175 ) animals injected with the same fragment also produced a comparable frequency of Vab progeny ( Table 2 ) . Adult male worms carrying the array often failed to develop proper tail rays ( Figure 3G and 3H ) and were unable to mate successfully to produce progeny ( n = 34 ) . The average ray number of each side of a male tail in the array containing animals is 3 . 2±1 . 2 ( n = 38 ) compared to the 8 . 6±1 . 2 ( n = 57 ) in wide type animals . The array containing males also produce only a few sperm ( Figure S3A ) compared to wild type ( Figure S3B ) . Both the tail defects and the paucity of sperm likely contribute to the inability of mir-57 overexpressing males to produce progeny . No defects were seen in the anterior body of either hermaphrodites ( 112 ) or males ( n = 320 ) that carry the arrays , consistent with the expression patterns of mir-57 . To examine the cell patterning defects in the tail , we injected the mir-57 promoter ( a 2260 bp fragment upstream from the miRNA mature sequence , see below ) into a strain expressing hypodermal marker , ajm-1::GFP . As expected , the injection produced Vab and Nob animals as did in N2 animals ( Table 2 ) . The marker showed that the hypodermal cells are severely disorganized in the tails of Nob/Vab animals as opposed to those in uninjected control animals ( Figure 4 ) , supporting a role of mir-57 in patterning posterior cells . The tail defects associated with the mir-57 arrays could derive either from elevated expression of the transgene or from the action of other sequences/elements in the 2 . 26 kb construct , which contains several regions conserved in C . briggsae ( Figure 2 ) . To test the first possibility , we drove mir-57 expression by a vab-7 promoter . The vab-7 gene , an even-skipped homolog , is expressed in the posterior of the embryo in regions overlapping with those expressing mir-57 , as determined by automated lineage-based expression analysis of a vab-7 promoter::mCherry fusion integrated transgene ( Figure S4 , See Text S1 ) . Extrachromosomal arrays of the pvab-7::mir-57 construct produced Vab/Nob animals , albeit at a lower rate than the native mir-57 promoter . The transgenic animals also yielded other phenotypes , including Dpy ( 12% , n = 262 ) and molting defects ( 3% , n = 340 ) ( Figure S5 ) . Importantly , a control construct with a mutated mature sequence of mir-57 produced no Vab/Nob animals ( n = 347 , Table 2 ) , indicating that presence of mir-57 structural gene on the array is essential for the development of tail defects . Therefore , the tail defects can arise either from ectopic expression of mir-57 driven by vab-7 promoter or its overexpression produced by the action of other sequences/elements in the 2 . 26 kb mir-57 promoter . We speculate that the difference in the details of the phenotypes results from the differences in vab-7 expression pattern from that of the mir-57 promoter . To test the effects of the putative cis-elements within the upstream region , we created constructs containing the upstream region separate from the structural gene . Surprisingly , injection of fragments ( −2260 to −63 ) lacking the transcribed portion of mir-57 and a predicted upstream LAG-1 binding site yielded a comparable fraction of animals with abnormal tails ( Table 2 ) . We postulated that the high copy number of the mir-57 promoter fragment could have disrupted normal regulation of the genomic copy of mir-57 , possibly titrating out an important inhibitory factor . Therefore , we introduced both the full length and truncated arrays into a background containing the genomic mir-57 deletion allele , gk175 . The full promoter-gene construct produced abnormal tails at rate similar to that seen in the wild type background . However , the absence of the genomic mir-57 gene completely abolished the Vab and Nob phenotypes produced by the mir-57 promoter fragment ( Table 2 ) , showing these effects required the presence of an intact copy of mir-57 either in the genome or on the array . Thus , the abnormal tail phenotypes produced by the mir-57 promoter fragment require at least one functioning copy of the mir-57 structural gene . To test more directly the hypothesis that the injected mir-57 upstream sequence produces increased levels of mir-57 miRNA , we performed Northern blot using a radioactive labeled LNA probe to detect the miRNA expression directly . As expected , both wild type and mir-57 mutant animals injected with the full genomic region of mir-57 ( −2260 to +234 ) showed much higher levels of the miRNA transcripts , i . e . , about 5 times higher than that of the un-injected controls . No signals were detected for the mir-57 deletion strain ( Figure 5 ) . In addition , injection of the regulatory region alone ( −2260 to −63 ) into the wild type animals also produced high levels of the miRNA transcripts , comparable to that seen for injections with the full mir-57 region ( Figure 5 , Table 2 ) . Given the partial transmission of the extrachromosomal arrays , the overexpression level for the array-containing animals is likely to be even higher than the increases measured for the populations of worms as a whole . These results strongly support the hypothesis that the array of the extra cis-regulatory fragments titrates out repressors controlling the endogenous expression of mir-57 , thus increasing mir-57 expression . Dissecting the molecular identities of the repressors is beyond the scope of this paper . Next , to observe directly the effects of the mir-57 extrachromosomal arrays on the activity of a genomic copy of the mir-57 promoter , we introduced the mir-57 promoter array into a background containing the integrated mir-57::mCherry reporter construct . Because of the instability of the promoter array , we did not carry out automated lineage-based expression analysis . However , examination of many individual expressing animals ( n = 122 ) showed a fraction of animals ( consistent with the inheritance of the array ) with much earlier , more intense and more anterior expression of the reporter ( Figure S6 ) . Taken together these results show that overexpression of mir-57 either from the arrays directly or from extra copies of the promoter region leading to the overexpression of the endogenous mir-57 gene can perturb posterior development and thus produce Vab/Nob phenotypes . Because these results implicate mir-57 in posterior development , we examined its relationship to other genes with a known role in posterior embryonic development in C . elegans . These include genes in the Notch and Wnt pathways that provide signals that differentiate anterior daughters from posterior daughters as well as homeobox and Hox related genes involved in posterior patterning [19]–[24] . We used RNAi against genes of the Notch and Wnt pathways that specify cell lineage fates to look more broadly for interactions between these pathways and mir-57 . RNAi against pop-1 , a gene involved in Wnt signaling and required for anterior-posterior lineage fate polarity [19] converts ABp ( l/r ) ap lineages to ABp ( l/r ) pp lineages , as judged by both lineage fate and expression patterns ( Figure S7 ) . The RNAi is quite effective as evidenced by the complete homeotic lineage fate transformation from MS to E . These results indicate that the correct expression of mir-57 is dependent on the lineage fate specified by the Wnt signaling pathway . Similarly , RNAi against lag-1 , a gene involved in Notch signaling , converts ABplap and ABplpp to ABalap and ABarpp fates respectively with concomitant loss of mir-57 expression in these altered lineages ( Figure S7 ) . In the C lineage , mir-57 expression is dependent on the cell fates specified by PAL-1 as RNAi against the gene completely abolished the mir-57 expression with concomitant cell fate changes as judged by the loss of asymmetry of cell cycle timing between Cxa and Cxp ( Figure S8 ) . Thus , in all these cases , mir-57 expression is dependent on the lineage fates and thus likely downstream of these decisions . These results suggest that mir-57 might be a direct target of one or more of these early regulators . Computational analysis revealed the presence of a putative LAG-1 binding motif 55 bp upstream of the mir-57 mature sequence ( Figure 2A ) , suggesting that lag-1 might directly regulate mir-57 expression . To test the hypothesis , we produced a modified mir-57::HIS-24::mCherry fusion construct with the LAG-1 site removed by site-directed mutagenesis and used it to generate transgenic lines by microinjection . Arrays without the LAG-1 site also yielded high fractions of Vab/Nob progeny ( data not shown ) , consistent with our earlier observations with the promoter region and indicating that this site is not responsible for the observed Vab/Nob phenotypes . However , arrays lacking the LAG-1 site failed to express the reporter in the tail , whereas the wild type promoter yielded strong expression , indicating that mir-57 is likely a direct target of LAG-1 . In addition to the Notch and Wnt pathways , the nob-1 gene , an ABd-B Hox gene homolog , is known to be involved in posterior pattern specification , with loss-of-function alleles resulting in embryonic lethality and larval arrest [22] . A hypomorphic allele , ct230 , produces both Nob and Vab phenotypes quite similar to those that result from mir-57 overexpression , suggesting that the mir-57 and nob-1 might function in the same pathways . To explore this possibility , we profiled the expression of nob-1 with resolution comparable to that of mir-57 by automated lineage-based expression analysis using an integrated NOB-1::GFP protein fusion transgene ( see Materials and Methods ) . The reporter was detectable from roughly the 100-cell stage in posterior progeny of ABp ( l/r ) pp and ABp ( l/r ) ap , the same sublineages in which mir-57 is also expressed ( Figure 6 ) . These results confirmed and refined the nob-1 expression pattern determined independently using a similar rescuing NOB-1::GFP construct ( E . Kress , L . Edgar and W . B . Wood unpublished ) . Despite the striking overlap of expression between mir-57 and nob-1 in the AB sublineages , their temporal expression patterns are quite different . The nob-1 reporter appears at about the 100-cell stage with a fairly uniform time of onset in different cells whereas mir-57 expression mostly appears after the 200-cell stage , although the more posterior the cells are , the earlier onset is detected . Expression of nob-1 was either very weak or not observed in the C lineage but was seen in the posterior E lineage by the 100-cell stage ( Figure 6 ) . As described above , expression of mir-57 was clearly present in the C lineage and only expressed in the E lineage after elongation ( data not shown ) so that spatial expression of nob-1 and mir-57 are not totally overlapping in these lineages Given their similar expression patterns in the AB sublineages and the earlier onset of nob-1 expression compared to that of mir-57 , we reasoned that nob-1 might be required for mir-57 expression . To test this hypothesis , we depleted nob-1 activity by RNAi and observed its effects on the mir-57 reporter expression with time using automated lineaging . The RNAi produced Vab/Nob progeny at rates comparable to the ct230 hypomorphic allele ( data not shown ) . The AB sublineage division patterns resembled those of wild type but the mir-57 reporter expression onset was delayed and expression level in the AB sublineages was significantly reduced ( n = 6 , p<0 . 01 , Student's t test ) compared to untreated animals ( Figure 7 ) , suggesting that mir-57 activity is at least partially dependent on nob-1 activity in these lineages . The residual expression of mir-57 might reflect the incomplete penetrance of the RNAi . Alternatively other factors may be responsible for the remaining activation . RNAi against nob-1 did not affect mir-57 expression in the C lineage ( data not shown ) . Other factors such as PAL-1 may be involved in the control of mir-57 expression in this sublineage ( Figure S4 and Figure S8 ) . Given that miRNAs generally act by reducing gene expression and that overexpression of mir-57 produced tail defects similar to those of nob-1 reduction-of-function mutations , we reasoned that overexpression of mir-57 might inhibit nob-1 expression , and thus produce the observed Nob/Vab phenotypes . Consistent with this , the nob-1b 3′ UTR , one of the two alternative nob-1 3′ UTRs , contains a predicted mir-57 binding site [7] ( Figure 8A and 8B ) . The putative binding site for mir-57 has the highest score among all the predicted miRNA binding sites within the nob-1 3′ UTR [7] . To explore experimentally the functional role of the mir-57 binding site , we used mir-57 promoter driven reporter constructs followed by nob-1 3′ UTRs to induce strong overexpression of the endogenous mir-57 in order to produce a robust effect . We made three constructs: two of them using the 3′ UTRs from the different splice isoforms , nob-1a and nob-1b and a third construct using the 3′ UTR from nob-1b in which the candidate mir-57 binding site was removed by site-directed mutagenesis ( See Materials and Methods ) . These constructs were introduced into the wild type N2 background by microinjection to create extrachromosomal arrays , which were then crossed into the mir-57 deletion background . In the wild type background , the arrays , because they contain the mir-57 promoter region , should result in overexpression of mir-57 from the genomic copy . As predicted , expression of the reporter gene is significantly reduced by the presence of the binding site in nob-1b ( p<0 . 01 , Student's two-tailed t test , Figure 8C and 8D ) . The reduction in reporter construct expression was not observed in the absence of a functional mir-57 gene , indicating that nob-1 is a direct functional target of mir-57 . A caveat for these experiments , however , is that all DNA constructs contained a mir-57 promoter introduced by microinjection , which as we described above leads to overexpression of mir-57 . Thus , these results may exaggerate the effects of a more physiological level of mir-57 expression , but the results clearly show that the binding site is functional in vivo . We looked genetically for further support that nob-1 is a target of mir-57 . By this hypothesis , mir-57 loss of function mutations might lead to increased expression of nob-1 although in contrast to the overexpression experiments , such an effect might be attenuated by other , redundant regulators of nob-1 . In agreement with this , overexpression of nob-1 from an extrachrormosomal array partially mimics the phenotypes of mir-57 loss of function albeit at a lower level ( Table S1 , n = 3 ) . However , we did not observe male tail defects in nob-1 overexpressing strains , suggesting that mir-57 may regulate male tail development independent of nob-1 . The lower penetrance might reflect partial transmission of extrachromosomal array , alternatively , other targets of mir-57 may also contribute to the observed phenotypes . Further , using a reporter to assay nob-1 expression , the loss of function mutation in mir-57 only produced modest effects on the nob-1 expression ( Figure S9 , See Text S1 ) , suggesting the miRNA functions redundantly with other miRNAs or pathways . To look for biochemical evidence that nob-1 is a target of mir-57 , we measured the endogenous levels of the two alternative nob-1 transcripts , nob-1a and nob-1b in the presence or absence of the genomic mir-57 copy using real-time PCR assay . Deletion of mir-57 significantly increases the nob-1b transcript level ( p<0 . 01 , Student's t test , Figure 9A ) and mir-57 promoter arrays in the N2 background significantly decrease its transcript level , roughly four fold ( p<0 . 05 , Student's t test , Figure 9A ) . As expected , deletion of mir-57 had no effect on the nob-1a transcript , which does not contain a mir-57 binding site . As a potentially more sensitive test of the interaction at more physiological levels , we constructed doubly mutant mir-57 ( gk175 ) ; nob-1 ( ct230 ) animals , postulating that if mir-57 normally is responsible for down regulation of nob-1 activity , removal of mir-57 activity might ameliorate the effects of the hypomorphic allele . We found that the doubly mutant animals showed a significant reduction in the fraction of progeny exhibiting the Nob phenotypes compared to nob-1 ( ct230 ) animals ( p<0 . 01 , Student's t-test ) ( Figure 9B ) . Similarly , the penetrance of nob-1 RNAi induced phenotypes were reduced in the mir-57 ( gk175 ) background compared to the wild type animals . One explanation of this suppression of the hypomorphic nob-1 mutant is that the deletion of mir-57 prevents repression of nob-1 expression , partially restoring nob-1 activity in the mutant . Perhaps the nob-1 hypomorphic allele creates a sensitized background , exaggerating the impact of mir-57 loss of function , even in the presence of other factors redundantly regulating nob-1 activities .
The detailed analysis of the expression pattern of mir-57 and nob-1 , coupled with the phenotypes observed in the absence and overexpression of mir-57 demonstrate that the miRNA gene plays a role in combination with the posterior Hox gene to specify posterior identity . The expression patterns reported here generally agree with previously described patterns [25] but with much higher temporal and spatial resolution , allowing us to infer and test the detailed functional relationships with other genes operating in related pathways . For example , both mir-57 and nob-1 are expressed in the same AB sublineages , ABpl ( r ) ap and ABpl ( r ) pp , which give rise to a variety of tissue/organ types in the posterior region , the region where the abnormal phenotypes were observed . Based on the detailed expression map as well as their similar phenotypes , we examined the interaction between mir-57 and other genes implicated in posterior development in C . elegans including nob-1 . The expression of mir-57 in the posterior sublineages of AB founder cells was dependent upon their proper specification through the Notch and Wnt pathways . In addition the expression of the mir-57 transgene required the presence of a binding site within its promoter sequence for the Notch pathway factor LAG-1 , suggesting that the gene might be directly regulated by the pathway . More dramatically , reduced function of nob-1 delayed the onset and reduced the level of mir-57 expression and in turn , nob-1 is to be a direct target of and repressed by mir-57 . This would constitute a negative regulatory loop between the miRNA and the Hox gene in providing positional cues for posterior development . The results suggest that the Nob/Vab phenotypes produced by overexpression of mir-57 are likely caused at least in part by down regulation of nob-1 activities within the posterior region , mimicking those of hypomorphic or null nob-1 mutants . This is supported by the evidence that mir-57 promoter injection produced a significant decrease of nob-1b , but not nob-1a , transcripts ( Figure 9A ) . Similarly , the Emb phenotype observed for the mir-57 null mutant at 26°C could be partially reproduced by nob-1 overexpression . Further support for mir-57 regulation of nob-1 comes from the fact that the mir-57 mutation partially alleviated the phenotypes of nob-1 ( ct230 ) , a hypomorphic allele , presumably resulting from partial release of the repression of nob-1 . Thus , in normal development , our data suggests that nob-1 expression begins by the 100-cell stage , activates mir-57 by the 200-cell stage , which in turn dampens the expression of nob-1 , perhaps in conjunction with other miRNAs . This down regulation might function to reinforce the transcriptional silencing of nob-1 activity in late embryonic stages when it may no longer be required to provide positional cues for posterior fate specifications . Such reciprocal regulation between the Hox gene and the miRNA might provide more robust control over the regional identity than the Hox gene alone . It should be noted that mir-57 expression is very likely subject to control of positional cues other than nob-1 because expression onset of nob-1 seems synchronized but that for mir-57 are not ( Figure 6 ) . In vertebrates , miRNA genes have also been found to have a role in Hox gene regulation , helping to reinforce posterior prevalence [26] . Notably , the closest homolog to mir-57 in other species is the broadly conserved gene miR-107 . miR-10 has been found to repress Hox gene activities in zebrafish spinal cord[27] . In mouse , miR-10a and another miRNA gene , miR-196a , are embedded in a Hox gene cluster and their expression is apparently overlapping with those of Hox genes [28] . In addition , miR-196a represses Hoxb8 , indicating its restricted expression pattern likely reflects a role of microRNA in the patterning of the Hox complex . Interestingly , miR-126 has been shown to regulate Hoxa9 by binding to its target sites within the homeobox domain [29] . A negative regulatory loop between miRNA genes and other transcription factors has also been described in vertebrates [30] , [31] . By miRNA profiling using an E2F1-indicible Saos-1 cell line , miRNAs miR-449a/b were identified as direct transcriptional targets of E2F1 [30] . miR-449a/b negatively regulates E2F activity through a feedback loop mechanism by targeting oncogenic CDK6 and CDC25A , leading to dephosphorylation of pRb , which is required for activation of E2F-responsive genes to promote cell cycle progression . miR-133b is also involved in a feedback regulatory loop that includes a paired-like homeodomain transcription factor Pitx3 in mammalian midbrain dopaminergic neurons [31] . Thus , such a negative feedback regulation between miRNAs and homeodomain transcription factors may provide a conserved mechanism to control metazoan position specific patterning . Although mir-57 is not found within a Hox gene cluster , Hox genes in C . elegans are only relatively loosely clustered [32] . Like many miRNA genes , mir-57 most likely functions redundantly with other miRNA genes . Deletion of the gene had little effect on the worm's fitness except at high temperatures and even here the defects were minor and penetrance incomplete . Overexpression of the gene produced more dramatic effects , but the overexpression phenotypes of miRNAs must be interpreted with caution since high miRNA levels may create off-target effects . However , the observed phenotypes were consistent with the expression pattern . A more systematic investigation of the high resolution expression patterns of the full set of miRNA genes would provide valuable insight into the likely partners , just as the detailed expression information here provided hints as to function . The ability of the 2 . 26 kb sequence upstream of the mature mir-57 miRNA to produce Vab/Nob phenotypes is intriguing . Although no evidence of another gene in this region has been found in extensive RNA-seq studies[33] , we cannot entirely rule out the presence of such a gene . Nonetheless , the dependence of the resultant phenotypes on the presence of a functional copy of the mir-57 gene , either in cis or in the genome , argues that the presence of the fragment in high copy number results in mir-57 misexpression . Our Northern blot results provide direct evidence that injection of either the mir-57 genomic region including its mature sequence and flanking sequences or the promoter region of mir-57 alone produced overexpression of the miRNA , which likely underlies the tail defects associated with these assays . The ability of the pvab-7::mir-57 arrays to partially mimic the phenotypes also implies that overexpression of mir-57 is the primary cause for the observed defects . This would be consistent with the 2 . 2 kb fragment binding and titrating out a repressor of mir-57 but what that factor might be remains unknown . Although the nob-1 gene seems to be one direct target of mir-57 , there are undoubtedly many other direct or indirect ones both within the AB sublineages where both mir-57 and nob-1 are expressed and also in the C lineage where mir-57 is found in the absence of nob-1 . MirBase lists a total of 492 candidate targets for mir-57 [7] , [34] but which of these might be functional targets in the C lineage is unclear . Again detailed expression patterns would greatly restrict the list of possibilities . Taken together , by using the automatic high-resolution gene expression technology , we were able to identify a negative regulatory loop between mir-57 and a Hox gene to control regional identity .
All the strains were maintained on NGM plates with OP50 E . coli at room temperature except for temperature sensitive assay of mir-57 mutant phenotypes at the indicated temperature . The following strains were used in the assay: N2; VC347 , mir-57 ( gk175 ) II; RW10029 , unc-119 ( ed3 ) , stIs1007[his-72::GFP , unc-119 ( + ) ] , stIs10025[pie-1::GFP::his-58 , unc-119 ( + ) ]; RW20050 , mir-57 ( gk175 ) II; BW1379 , nob-1 ( ct230 ) III; RW20051 , mir-57 ( gk175 ) II , nob-1 ( ct230 ) III; RW10044 , unc-119 ( ed3 ) , stIs10044[pmir-57::HIS-24::mCherry , unc-119 ( + ) ]; RW10226 , unc-119 ( ed3 ) , stIs10226[HIS-72::mCherry , unc-119 ( + ) ]; BW2020 , ctIs57[NOB-1::GFP , rol-6 dm]; RW10044 , unc-119 ( ed3 ) , stIs10044[pmir-57::HIS-24::mCherry , unc-119 ( + ) ] , stIs10026[HIS-72::GFP]; RW10174 , unc-119 ( ed3 ) , stIs10174[ppal-1::HIS-24::mCherry , unc-119 ( + ) ]; RW10199 , unc-119 ( ed3 ) , stIs10199[pvab-7::HIS-24::mCherry , unc-119 ( + ) ]; RW10226 , unc-119 ( ed3 ) , ctIs57[NOB-1::GFP , rol-6 d] , stIs10226[HIS-72::mCherry]; PS4657 , unc-119 ( ed3 ) , syIs78[ajm-1::GFP + unc-119 ( + ) ] . The mir-57 ( gk175 ) allele was backcrossed to N2 Bristol strain five times before phenotypic assay . The presence of mir-57 ( gk175 ) allele was followed by single worm PCR . The following phenotypes were scored at 15°C , 20°C and 26°C respectively for N2 and RW20050 strains: Emb ( embryonic lethality ) , Lva ( larva arrest ) , Ste ( sterility ) . A 2260 bp ( −2260 to −1 ) fragment upstream of mir-57 was cloned into the restriction sites upstream of a HIS-24::mCherry cassette using AvrII and SmaI sites in the pJM20 vector [17] to give rise to pZZ1 . mCherry is a worm optimized derivative of Cherry [18] . Histone HIS-24 was used to direct the reporter signal into nucleus . pJM20 also contains transgenic selection marker unc-119 ( + ) . The pZZ1 ( Pmir-57::HIS-24::mCherry , unc-119+ ) construct was bombarded into unc-119 ( ed3 ) worms to generate integrated reporter expressing strains for expression profiling . A total of 12 independent lines were generated and all of them showed the similar expression patterns . A single line was backcrossed three times with N2 and the resultant reporter expressing strain was mated into the lineaging strain , RW10029 [16] , which ubiquitously expresses nuclear localized GFP to generate a strain RW10048 that are homozygous for both GFP and RFP loci . Similar method was used to generate reporter-expressing strains using RW10174 and RW10199 for automatic profiling of pal-1and vab-7 expression respectively ( See Text S1 for the primer used ) . To build a translational GFP fusion reporter strain for nob-1 , an approximately 15 kb fragment spanning the entire coding region plus its upstream regulatory sequences was fused in frame with GFP followed by unc-54 3′ UTR . The construct was co-injected into N2 with pRF4 ( rol-6 d ( su1006 ) ) . The resulting transgenic strain was integrated into the genome by gamma irradiation to give rise to BW2020 . The constructs for site-directed removal of the LAG binding site and the mutated mir-57 as well as for the hybrid construct between mir-57 and vab-7 promoter , were built by the fusion PCR technique as described below [35] ( See Text S1 for the primers used ) . To build the construct with site directed removal of LAG-1 site within the mir-57 promoter , the fragments flanking LAG-1 site were PCR amplified from pZZ1 and fused together by PCR . The resulting construct contains the full mir-57 promoter ( -2260 to -1 ) except for the LAG-1 site ( See Text S1 for the primer sequences ) . To build mutagenized mir-57 driven by vab-7 promoter , two pairs of primers were designed so that they overlap on the mature mir-57 sequence . The mir-57 mature sequence was mutated into an unrelated sequence ( See Text S1 for the primers used ) . To build the hybrid construct between mir-57 and vab-7 promoter , the 3400 bp vab-7 promoter was fused with 284 bp mir-57 stem-loop plus its flanking sequences . The mir-57 overexpression construct is a 2494 bp PCR product that includes 2260 bp promoter sequences and the 234 bp stem-loop and its downstream sequence . The mir-57 promoter only construct is the PCR product that is -2260 to -63 bp from the mir-57 mature sequence . These PCR products were co-injected with pRF4 ( rol-6 d ) with concentrations of 20 and 100 ng/µl , respectively . The mir-57 promoter only PCR product ( −2260 to −63 ) was also injected into both wild type and mir-57 deletion animals in the same concentrations . The overexpression phenotypes for hermaphrodite were scored from three independent transgenic lines synchronized at L2 stage . Embryonic lineaging analysis and expression profiling of mir-57 was performed with strain RW10048 using StarryNite and AceTree as described [17] , [36] with modifications . Strain RW10048 was used for profiling of mir-57 expression . Given the relatively late stage of mir-57 expression during embryogenesis , we traced the relevant embryonic lineage until the last round of cell division in both “forward” and “backward” directions . In the “forward” direction , we traced the lineage using the standard method for those up to 350-cell stage . For the “backward” direction , we started with the reporter expressing cells at a late stage of embryogenesis , for example , comma stage , and traced the cells backward until the progenitors could be reliably linked to the nuclei identified by the forward tracking method . In this way we captured the expressing lineages at the late period of embryogenesis up to comma stage . To profile nob-1 expression , we made a strain RW10226 that ubiquitously expresses histone::mCherry in somatic nuclei and crossed it into BW2020 , a NOB-1::GFP expressing strain for lineaging using mCherry labeled nuclei . Due to the lack of the germline expression of mCherry , cell lineage from one to about 70 celled embryo were manually traced using DIC images . After the embryonic cell lineage was produced for both mir-57 and nob-1 expressing strains , pixel densities from GFP ( nob-1 ) or RFP ( mir-57 ) channel were extracted and aligned against the lineage tree branch for each time point and all nuclei . To compare the expression from different experiments , division timing was normalized against those derived from Sulston lineage tree [37] and expression values interpolated accordingly . A total of six and four embryos were profiled for mir-57 and nob-1 expressing embryos respectively . To assign the expression values of reporter expressing cells , we did the background subtraction ( blot ) to eliminate marginally expressing cells and thus increase the specificity of calling the expressing cells [17] . To profile the mir-57 expression after the RNAi against nob-1 , the embryos were mounted 24 hours after their parents were injected and imaged for six hours at room temperature . A total of six RNAi treated embryos were profiled for expression up to 450-cell stage for the selected sublineages . To plot expression of ABplpp_ppppp with time , we used both raw and background subtracted expression values and the two data sets agree well with one another in terms of relative intensity ( data not shown ) . In situ hybridization was performed as described [38] , [39] with following modifications . DIG labeled LNA-modified probe complementary to the mature mir-57 was made by Exiqon with the sequence ACACACAGCTCGATCTACAGGGTA . The mix-staged embryos were immobilized on poly-lysine coated slides followed by methanol fixation . The hybridization and wash were performed at 37°C ( 20°C below the probe melting temperature ) as suggested elsewhere [39] . Worm populations synchronized at the L4 stage were incubated with acid phenol ( pH 4 . 5 ) at 65°C for one hour followed by centrifugation . The top layer was transferred to Phase Lock GelHeavy tubes ( Sigma-Aldrich ) and centrifuged for 1 minute . The aqueous layers were re-extracted with phenol and chloroform followed by precipitation and washing . A total of 20 µg total RNA was loaded onto 15% polyacrylamide denaturing ( urea ) gel for each sample and transferred to Nylon ( + ) membrane by electroblotting in 1 X TBE buffer . The mir-57 antisense LNA probe and U-6 antisense probe ( GTCATCCTTGCGCAGGGGCCATGCTAATCTTCTCTGTATTGTTCCAAT ) were 5′ labeled with γ-32P ATP . The two probes were mixed and hybridized to the membranes at 50°C overnight in the hybridization buffer ( 5 X Denhardt's , 2 X SSC , 0 . 1% SDS ) and washed twice at 50°C in the wash solutions ( 2 X SSC , 0 . 1% SDS ) . The blots were visualized and signals quantified using Amersham Biosciences phosphorimager according to the manufacturer's instructions . All RNAi experiments were done by microinjection as described [40] . The primers used for PCR amplification of genomic fragments for nob-1 , pal-1 , pop-1 and lag-1 were derived from Ahringer's oligonucleotides [41] flanked with a T3 or T7 promoter at each end . The single-stranded transcript resulted from T3 and T7 RNA polymerase were pooled and annealed at 68°C for 10 minutes and 37°C for 30 minutes . The concentration for the injected dsRNA is 200 ng/µl in ddH2O . Two- or four- celled embryos were retrieved from adult worms after 16–24 hours of after injection by cutting the uterus and mounted for imaging for about six-hours . The number of the tail rays was counted only on one side of the male tails from both N2 ( n = 57 ) , mir-57 ( gk175 ) ( n = 32 ) and the mir-57 promoter array containing animals ( n = 38 ) . For mir-57 animals , the ray number was counted on both room temperature and 26°C . To test the fertility of the array containing males , 10 males were put in the same plate with 10 N2 hermaphrodite animals in 3 replicates and the presence of the roller or male animals were examined for the successful crossing . The fertility of the mir-57 males was examined in a similar fashion but only the presence of male progeny was examined . All of the post-embryonic images were taken with a ZEISS Axioplan 2 compound microscope equipped with AxioCamHR camera using a 63X objective lens . The florescent images for embryos were taken with a ZEISS LSM510 confocal microscope . Four-D imaging for lineage analysis and gene expression profiling was conducted essentially as described previously [17] . To test the effect of the predicted mir-57 target site within the nob-1 3′ UTR on the reporter expression , the pZZ1 construct was modified so that the let-858 3′ UTR was replaced with the 3′ UTR either from nob-1a or nob-1b by the following methods . The fragment containing Pmir-57::HIS-24::mCherry was PCR amplified from pZZ1 . The 3′ UTRs from nob-1a or nob-1b , termed as nob-1a or nob-1b respectively were amplified from N2 genomic DNA ( See Text S1 for the primers used ) . The UTRs were fused with the above reporter at the 3′ end by fusion PCR . The resulting fusion products were cut with BamHI and ApaI and ligated with pZZ1 cut with the same restriction enzymes to give rise to pZZ43 ( nob-1a UTR ) and pZZ44 ( nob-1b UTR ) respectively . Sited directed removal of a putative mir-57 binding site within the nob-1b 3′ UTR was performed in the similar way as that used for LAG-1 site-directed mutation described above and was termed as nob-1 bm hereafter . The three UTR constructs for nob-1a , nob-1b and nob-1bm were co-injected with pRF4 ( rol-6d ) into wild type ( N2 ) with concentrations 20 ( UTR constructs ) and 100 ( pRF4 ) µg/ul respectively . Three independent lines were obtained for each injection . The extrachromosomal arrays of the transgenic animals were crossed into the mutant mir-57 ( gk175 ) background and genotyped by single worm PCR . The three independent transgenic lines from each injection and crossing were individually synchronized by bleaching and eggs were put on unseeded plates overnight at room temperature . The hatched worms were transferred to seeded NGM plates and allowed to grow for 24 hours . The microphotographs for tail expression were taken using AxioCamHR camera using a 63X object with 919 ms exposure for each independent lines . A total of 39 animals from each independent line were used for taking micrographic photos . The RFP intensities in tail regions ( measure from anus to tail end , if anus not available , measured from the end of intestine to the end of tail ) were quantified using ImageJ and the data were averaged for box plotting with R package . To quantify the change of nob-1 transcript in the presence and absence of genomic mir-57 , we performed Real-time RT-PCR using LightCycler ( Roche ) with QuantiTect SYBR Green Kit ( Cat # 204143 ) and QuantiTect Reverse Transcription Kit ( Cat # 205311 ) . Four strains were used for total RNA extraction using RNeasy Fibrous Tissue Mini Kit ( Cat # 74704 ) : N2 , VC347 ( mir-57 ( −/− ) ) , as well as the above two strains injected with mir-57 promoter . Worms were staged at L4 before total RNA preparation . For promoter injected strains , a total of 763 and 824 L4 array containing worms were picked for RNA preparations . The Real-time RT-PCR were performed in three triplicates using primer pairs specific for nob-1a , nob-1b , and gpd-1 ( a GAPDH encoding gene ) based on the manufacture's instructions . In the case of array containing animals , the Real-time RT-PCRs were performed in triplicate using the same template . The primers sequences are gpd-1-L: TGTCGACTGATTTCGTGTCC; gpd-1-R: TCGACAACACGGTTCGAGTA; nob-1a-L: AGGCAGTATTCAGCGGAAAG; nob-1a-R: tgaaaatccagagaagctcaaa; nob-1b-L: TGCACAATTGATGCTTGATG; nob-1b-R: GTCGTTGACGCAGTTTCTTG . Expression levels are normalized against gpd-1 before statistical analysis . nob-1 ( ct230 ) and mir-57 ( gk175 ) double mutant was made by crossing and genotyped by single worm PCR . RNAi by injection against nob-1 was performed as described previously for N2 and mir-57 mutant animals . Vab or Nob ( data not shown ) phenotypes were scored for nob-1 ( ct230 ) , nob-1 ( ct230 ) and mir-57 ( gk175 ) double , nob-1 ( RNAi ) , nob-1 ( RNAi ) and mir-57 ( gk175 ) double animals . 10 young adults were plated on a single plate for each genotypes and allowed to lay eggs for 6 hours and picked off . The phenotypes were scored for three successive days at room temperature . Each experiment was performed in three replicates .
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miRNAs are small RNAs found in many multi-cellular species that inhibit gene expression . Many of them play important roles in cancer and cell fate determination , but the function of most miRNAs is uncertain . Using live cell imaging and automated expression analysis , we found a miRNA gene , mir-57 , is expressed in a position rather than tissue dependent way . Hox genes also regulate cell fate patterning along anterior-posterior ( a-p ) axis across different tissues . By investigating interactions between genes of these classes expressed in mir-57 expressing cells , we demonstrated by both genetic analysis and gene expression assays that a negative feedback loop between a posterior Hox gene , nob-1 , and mir-57 regulates posterior cell fate determination in C . elegans . On the one hand , the Hox gene is required for normal activation of mir-57 expression , and on the other , the Hox gene functions as a direct target of and is repressed by the miRNA . Given the conservation of the two genes , a negative feedback loop between Hox and miRNA genes might be broadly used across species to regulate cell fate along the a-p axis . Detailed expression analysis may provide a general way to dissect the regulatory role of miRNAs .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology/embryology",
"genetics",
"and",
"genomics/animal",
"genetics",
"developmental",
"biology/morphogenesis",
"and",
"cell",
"biology",
"genetics",
"and",
"genomics/gene",
"expression",
"developmental",
"biology/pattern",
"formation",
"developmental",
"biology/cell",
"differentiation",
"genetics",
"and",
"genomics/gene",
"function",
"developmental",
"biology/molecular",
"development",
"genetics",
"and",
"genomics/bioinformatics"
] |
2010
|
A Negative Regulatory Loop between MicroRNA and Hox Gene Controls Posterior Identities in Caenorhabditis elegans
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Compelling evidence suggests that the transcription factor Foxp3 acts as a master switch governing the development and function of CD4+ regulatory T cells ( Tregs ) . However , whether transcriptional control of Foxp3 expression itself contributes to the development of a stable Treg lineage has thus far not been investigated . We here identified an evolutionarily conserved region within the foxp3 locus upstream of exon-1 possessing transcriptional activity . Bisulphite sequencing and chromatin immunoprecipitation revealed complete demethylation of CpG motifs as well as histone modifications within the conserved region in ex vivo isolated Foxp3+CD25+CD4+ Tregs , but not in naïve CD25−CD4+ T cells . Partial DNA demethylation is already found within developing Foxp3+ thymocytes; however , Tregs induced by TGF-β in vitro display only incomplete demethylation despite high Foxp3 expression . In contrast to natural Tregs , these TGF-β–induced Foxp3+ Tregs lose both Foxp3 expression and suppressive activity upon restimulation in the absence of TGF-β . Our data suggest that expression of Foxp3 must be stabilized by epigenetic modification to allow the development of a permanent suppressor cell lineage , a finding of significant importance for therapeutic applications involving induction or transfer of Tregs and for the understanding of long-term cell lineage decisions .
Regulatory T cells ( Tregs ) , which have been shown to play a pivotal role in the maintenance of self-tolerance within the immune system , were described originally as CD4+ T cells constitutively expressing CD25 [1] . More recently , the forkhead transcription factor Foxp3 has been shown to be specifically expressed in Tregs and to be a central control element in Treg development and function [2] . Mutation or deletion of the gene encoding Foxp3 causes severe autoimmune disease in mice and humans , due to a failure to generate CD25+CD4+ Tregs [3 , 4] , whereas ectopic expression of Foxp3 in conventional T cells confers suppressive activity [4 , 5] . These findings provided compelling evidence that Foxp3 acts as a master switch controlling the development and function of Tregs; however , the molecular mechanisms leading to its induction remain largely unknown . Recently , an initial characterization of the human FOXP3 promoter revealed a basal , T cell–specific promoter containing several NF-AT and AP-1 binding sites , which are positively regulating FOXP3 expression after triggering of the T cell receptor ( TCR ) [6] . Occurrence of autoimmunity in thymectomized mice provided initial evidence that Foxp3+CD25+CD4+ Tregs are generated as an individual lineage within the thymus [1] . Using mice harboring a GFP-Foxp3 fusion protein-reporter knockin allele , Fontenot et al . could show that Foxp3 expression becomes prominent in CD4 single-positive ( SP ) thymocytes ( ∼83% of Foxp3gfp+ thymocytes ) [7 , 8] . In addition to the thymic generation of Foxp3+ Tregs , peripheral conversion of Foxp3−CD25−CD4+ T cells into Foxp3+ Tregs has recently been demonstrated by tolerogenic antigen application in vivo [9–11] or upon activation in the presence of TGF-β in vitro [12–17] . To what extent these induced populations of Tregs acquire a stable phenotype corresponding to that of natural , thymus-derived Tregs is , however , unclear . An emerging paradigm in understanding the development of stable cellular lineages emphasizes the role of epigenetic mechanisms for the permanent , heritable fixation of distinct gene expression patterns . Molecular mechanisms of epigenetic imprinting include selective demethylation of CpG motifs and histone modifications as shown for cytokine genes [18–20] . Whether Treg differentiation also involves elements of epigenetic regulation has not been studied thus far . We therefore investigated whether epigenetic alterations such as DNA methylation and histone modifications of the foxp3 locus correlate with Foxp3 expression . The selective association of chromatin remodeling with a stable Treg phenotype suggests a role of epigenetic imprinting in the establishment of a committed regulatory cell type .
It is assumed that Foxp3+CD25+CD4+ Tregs represent an individual lineage exhibiting a stable phenotype . To prove experimentally the stability of Foxp3 expression in natural Tregs on a cellular level , we adoptively transferred sorted CD25+CD4+ T cells after CFSE ( carboxy fluorescein diacetate succinimide ester ) labeling into syngeneic recipients . Fourteen days after transfer , more than 95% of CFSE+ cells , including those that had divided once or twice according to loss of CFSE , were still Foxp3+ ( Figure 1 ) , supporting data from a recent publication using a lymphopenic transfer model [21] . Having shown that Foxp3 is stably expressed in CD25+CD4+ Tregs , we next asked whether epigenetic modifications of the foxp3 locus might account for the maintenance of the long-term identity of Foxp3+ Tregs . The lymphoproliferative disorder of scurfy mice is completely rescued by transgenic complementation with a 30 . 8-kilobase ( kb ) genomic fragment containing the foxp3 gene from wild-type mice [22] . This indicates that most key regulatory elements required for proper Foxp3 expression are located within the transgene including the entire gene , as well as 12 . 5 kb and 2 . 8 kb of 5′ and 3′ flanking sequences , respectively . We therefore focused our analysis of epigenetic modifications on sequences from the 30 . 8-kb region and selected specific regions for methylation analysis based on CpG density ( Figure 2A ) : Overlapping amplicons 1 and 2 map upstream from exon-1 , amplicons 3 and 4 align to the seventh intron . No CpG-rich regions were observed within the Foxp3 promoter located at the putative 5′ end of exon-2b , 6 . 1 kb upstream from the first coding exon [6 , 22] . We sorted CD25+CD4+ Tregs and conventional CD25−CD4+ T cells from secondary lymphoid organs of male mice . Male mice were chosen to avoid potential artifacts due to random X chromosome inactivation since Foxp3 is encoded on the X chromosome [22] . As expected , the vast majority of sorted CD25+CD4+ Tregs were Foxp3+ , whereas less than 1% of CD25−CD4+ T cells expressed Foxp3 ( Figure 2B ) . The methylation status of the foxp3 locus was analyzed by bisulphite sequencing ( see Material and Methods ) . Interestingly , striking differences between CD25+CD4+ Tregs and conventional CD25−CD4+ T cells could be observed . CpG motifs within amplicons 1 and 2 displayed a high degree of methylation ( ∼100% ) within conventional CD25−CD4+ T cells , but were almost completely demethylated within CD25+CD4+ Tregs ( Figure 2C and Table S1 ) . No significant differences were observed for amplicons 3 and 4 , showing that the demethylation process is not a random event , but is confined to defined regions as was recently found for the interleukin 2 ( IL-2 ) promoter [23] . Together , our findings suggest that demethylation of CpG motifs within selected elements of the foxp3 locus enable stable Foxp3 expression in CD25+CD4+ Tregs . This view is supported by recent findings with human natural killer ( NK ) cells , which up-regulated FOXP3 expression in response to IL-2 only after treatment with the demethylating agent 5-aza-2′deoxycytidine , demonstrating that this gene was constitutively repressed in non-Tregs by a mechanism involving DNA methylation [24] . The differentially methylated element covered by amplicons 1 and 2 is conserved between mice and humans ( 77 . 3% sequence identity ) . This is not the case for the region covered by amplicons 3 and 4 , which essentially showed no signs of differential DNA methylation . In silico analysis of the differentially methylated , conserved region predicts a number of binding sites for transcription factors , including ATF/CREB , C/EBPγ , Elk-1 , Ets-1 , Evi-1 , Foxp3 , GATA-4 , NFATc , NF-κB , SMAD-4 , STAT-1 , TCF-4 , and TTF1 ( Figure S1 ) , indicating that these factors might be involved in the induction of Foxp3 expression in CD25+CD4+ Tregs . To analyze whether the same region harbors transcriptional activity , we cloned a 1 , 160–base pair ( bp ) element containing the differentially methylated element covered by amplicons 1 and 2 into the pGL3 luciferase vector in front of a minimal SV40 promoter . The luciferase vector was transfected into a murine CD4+ T cell line , and transfected cells were either left unstimulated or were stimulated with PMA for 24 h , followed by measurement of luciferase activity . PMA treatment mimics part of the signals generated after TCR triggering , which have been shown to be essential for Foxp3 expression [6] . Interestingly , significant luciferase activity was only observed in stimulated cells transfected with the vector containing the conserved element of the foxp3 locus , but not in cells transfected with the control vector ( Figure 3 ) . Similar results showing a 5-fold to 7-fold induction of luciferase activity after stimulation were also obtained with ex vivo isolated CD25+CD4+ Tregs , albeit much lower transfection efficiencies were achieved with these primary murine T cells ( unpublished data ) . Initial experiments targeting the functional activity of selected transcription factors , for which a binding site in the differentially methylated , conserved element has been predicted , showed a reduced luciferase activity if transcription factors of the STAT family were inhibited by decoy oligonucleotides ( unpublished data ) , confirming recently published data [24] . Together , our data assuredly show that the differentially methylated , conserved element of the foxp3 locus possesses transcriptional activity . DNA demethylation is often linked to acetylation or methylation of histones , other key features of chromatin remodeling [25] . To investigate whether this also holds true for the aforementioned region of the foxp3 locus , we performed chromatin immunoprecipitation ( ChIP ) experiments using antibodies specific for acetylated histone H3 , acetylated histone H4 , and trimethylated lysine 4 of histone H3 ( H3K4 ) . Subsequently , the precipitated DNA was used as a template for amplifying the differentially methylated region of the foxp3 locus by quantitative real-time PCR . Indeed , in CD25+CD4+ Tregs , the region of interest showed a stronger association with modified histones when compared with conventional CD25−CD4+ T cells ( Figure 4 ) . Major differences were observed for the acetylated and trimethylated histone H3 , whereas minor differences were found for the acetylated histone H4 . Together , the ChIP data disclose that within conventional CD25−CD4+ T cells , the foxp3 locus is packed in a more condensed , inaccessible chromatin structure , whereas it is located within open euchromatin in CD25+CD4+ Tregs . Having shown that peripheral CD25+CD4+ Tregs display a characteristic methylation status of the foxp3 locus , we next sought to determine whether this also could be observed in developing Tregs . Generation of Foxp3+ cells in the thymus occurs preferentially at the CD4 SP stage or during transition to this stage [8] . We therefore isolated CD25+ and CD25− subsets of CD4 SP thymocytes from male mice . As expected , approximately 80% of CD25+ CD4 SP thymocytes were Foxp3+ , whereas less than 1% of CD25− CD4 SP thymocytes expressed Foxp3 ( Figure 5A ) . Only CD25+ , not CD25− CD4 SP thymocytes , displayed demethylated CpG motifs within the regions covered by amplicons 1 and 2 , whereas CpG motifs in amplicons 3 and 4 were again fully methylated in both subsets ( Figure 5B and Table S1 ) . As expected , in double-negative ( DN ) and double-positive ( DP ) thymocytes , which show hardly any Foxp3 expression [7 , 8] , CpG motifs within the regions covered by amplicons 1 and 2 were completely methylated ( Table S1 ) , supporting our assumption that Foxp3 expression is developmentally regulated and requires an opening of the foxp3 locus . When compared to peripheral CD25+CD4+ Tregs , in which the CpG motifs within amplicons 1 and 2 were almost completely demethylated ( mean degree of methylation <3% ) , CD25+ CD4 SP thymocytes showed a clearly reduced degree of demethylated DNA ( mean degree of methylation ∼50% ) with individual CpG motifs being even completely methylated ( Table S1 ) . These stark differences cannot simply be explained by the fact that , among CD25+ CD4 SP thymocytes , only 80% are Foxp3+ compared to 95% within the peripheral counterpart ( Figures 2B and 5A ) . Rather , it indicates that the locus does not become fully opened until completion of maturation and exit from the thymus . A critical issue for application of Tregs in therapeutic approaches is the availability of large numbers of cells . Recent publications have reported that conventional CD25−CD4+ T cells can be converted into Foxp3+ Tregs by stimulation in the presence of TGF-β [12–17] . However , the stability and in vivo efficacy of these cells have not been thoroughly tested so far . Analysis of the accessibility of the foxp3 locus might provide an additional clue , aside from the mere expression of Foxp3 , as to the extent to which a permanent conversion into a Treg lineage did occur . We therefore analyzed the methylation status of the foxp3 locus from CD25−CD4+ T cells , which had been activated and cultured for 6 d in the presence of TGF-β . On day 6 , more than 98% of TGF-β–cultured cells were Foxp3+ , whereas control cells cultured under Th1 conditions showed only approximately 1% Foxp3 expression ( Figure 6A ) . As expected , within cultured Th1 cells , all analyzed CpG motifs were completely methylated ( Figure 6B and Table S1 ) . In contrast , cell culture in the presence of TGF-β led to a clearly visible demethylation of CpG motifs within the region covered by amplicons 1 and 2 , whereas CpG motifs in amplicons 3 and 4 again were fully methylated . However , the degree of demethylation was far less pronounced compared to naturally occurring peripheral CD25+CD4+ Tregs ( Figure 2C ) . This prompted us to investigate whether such a weak degree of CpG demethylation might correlate with persistent expression of Foxp3 in TGF-β–induced Tregs . Therefore , we restimulated TGF-β–cultured Foxp3+ cells for another 6 d in the absence of TGF-β followed by the analysis of intracellular Foxp3 expression . As a control , we cultured ex vivo isolated Foxp3+CD25+CD4+ Tregs under comparable conditions . Whereas ex vivo CD25+CD4+ Tregs maintained high Foxp3 levels after cell culture for 6 d , TGF-β–induced Tregs have lost Foxp3 expression during the 6-d restimulation period to variable degrees , and initial results point toward an almost complete loss of the partial demethylation of the CpG motifs within amplicons 1 and 2 in the restimulated TGF-β cultures ( Figure 7 , and unpublished data ) . To rule out selective outgrowth of Foxp3− cells or enhanced cell death of Foxp3+ cells during restimulation , we performed TGF-β cultures with CD25−CD4+ T cells from GFP-Foxp3 reporter mice [7] , which allowed sorting of TGF-β–induced Foxp3+ Tregs to a purity greater than 99% before restimulation . In other control experiments , we either labeled TGF-β–induced Tregs with CFSE before restimulation or did spiking experiments with Foxp3− T cells . In none of these control experiments was outgrowth of Foxp3− cells or massive cell death observed ( unpublished data ) , confirming our previous assumption that Foxp3 expression in TGF-β–induced Tregs is lost during restimulation in the absence of TGF-β . Importantly , loss of Foxp3 expression was strictly associated with loss of suppressive activity when tested in in vitro proliferation assays ( Figure S2 ) . Viewed as a whole , our data strongly suggest that complete demethylation of CpG motifs within the foxp3 locus is required to stabilize both Foxp3 expression and suppressive capacity .
The forkhead box transcription factor Foxp3 has been identified as a specific molecular marker for Tregs , and its expression is essential for programming Treg development and function [2] . Although it is widely accepted that Foxp3+ Tregs represent a stable population mainly generated as a separate lineage in the thymus , conclusive data on the molecular mechanisms maintaining stable Foxp3 expression are not available . We here provide evidence that epigenetic modifications of the foxp3 locus are required to enable long-term identity of Foxp3+ Tregs . We have identified an element within the 5′ untranslated region of the foxp3 locus , TSDR ( Treg-specific demethylated region ) , which displays demethylated CpG motifs both in developing thymic as well as in mature , peripheral murine Foxp3+CD25+CD4+ Tregs . Interestingly , the differentially methylated element is evolutionarily conserved . Preliminary analyses using cells from human peripheral blood also showed a differential methylation of CpG motifs within the conserved element of the foxp3 locus when conventional CD25−CD4+ T cells and CD25highCD4+ Tregs were compared , implying that this region and its epigenetic regulation is of functional importance ( unpublished data ) . In addition to DNA demethylation , acetylated histones H3 and H4 as well as trimethylated histone H3 were associated with the conserved region in CD25+CD4+ Tregs , but not in conventional CD25−CD4+ T cells . Similar histone modifications have frequently been reported to concur with DNA demethylation , e . g . , as described for the loci encoding the active cytokines interferon-γ ( IFN-γ ) and IL-4 in differentiated Th1 and Th2 cells , respectively [19 , 20] . These data suggest that in terminally differentiated Tregs , epigenetic modifications of the foxp3 locus allow persistent expression of Foxp3 . The human FOXP3 promoter has recently been mapped to the putative 5′ end of exon-2b , 6 . 1 kb upstream from the first coding exon [6] . However , other studies have reported promoter activity upstream from exon-1 close to the differentially methylated region analyzed in the current study [26 , 27] corresponding to the Foxp3 mRNA species AY357712 and AY357713 . We could show here by performing luciferase assays that the differentially methylated region itself possesses transcriptional activity . Together these data suggest that the evolutionarily conserved element might belong to an alternative TATA-less promoter , which contributes to the regulation of Foxp3 expression . The differential methylation status of the foxp3 locus in Tregs appears to be a new example for epigenetic regulation of cell lineage differentiation . Although almost all cells in an individual contain the same complement of DNA code , higher organisms must impose and maintain different patterns of gene expression in the various types of differentiated cells . Most gene regulation is transitory , depending on the current state of the cell and changes in external stimuli . Persistent regulation , on the other hand , is a primary role of epigenetics: heritable regulatory patterns that do not alter the basic genetic coding of the DNA . DNA methylation is the archetypical form of epigenetic regulation; it serves as the stable memory for cells and performs a crucial role in maintaining the long-term identity of various cell types . Our finding that evolutionarily conserved sequences within the foxp3 locus are completely and selectively demethylated upon differentiation into persistent Tregs suggests an important role of epigenetic fixation for this phenotype . Moreover , this seems to be the first report that a transcription factor acting as a master switch for a certain subpopulation is itself subject to epigenetic control . The role of transcription factors such as T-bet or GATA-3 for the polarization of Th1 and Th2 cells , respectively , has been carefully studied , and their interplay with epigenetically regulated regions in the respective cytokine genes is seen as a major factor in the acquisition of cytokine memory [18 , 19] . However , foxp3 appears to be the first known example , at least in the immune system , in which the transcriptional regulation of a master transcription factor itself involves epigenetic mechanisms . A crucial finding of this study is that chromatin remodeling of the foxp3 locus does not merely correlate with Foxp3 expression . Rather , our current data provide first experimental evidence that the completely demethylated status of the evolutionarily conserved region is only confined to stable Treg populations , such as the naturally occurring , thymus-derived CD25+CD4+ cells , and might indeed be a prerequisite for the permanent commitment to the suppressor cell lineage . This assumption is based on the analysis of TGF-β–induced Tregs , which , despite Foxp3 expression and suppressive properties , have not acquired a terminally differentiated phenotype and have lost both Foxp3 expression and suppressive capacity upon restimulation in the absence of TGF-β . This indicates that the recently postulated positive autoregulatory loop involving up-regulation of endogenous TGF-β expression and subsequent Foxp3-dependent down-regulation of Smad7 , a negative regulator of TGF-β signaling , is not sufficient to induce stable Foxp3 expression in vitro [15] . As TGF-β–induced Tregs display only weakly demethylated CpG motifs within the conserved region of the foxp3 locus , a more complete CpG demethylation might be the key for a stable Foxp3 expression , similar to what has recently been reported for IL-2 [23] . The findings of this study have important implications with respect to clinical applications . First , determination of the methylation status might allow a better identification and quality control of Tregs considered for cellular therapy concepts of autoimmune diseases , graft-versus-host diseases , or transplant rejections . Temporary expression of FOXP3 can be detected in activated T cells lacking regulatory function , especially in the human system [28 , 29] . Analysis of the methylation status of the foxp3 locus promises to be a more reliable marker for the successful conversion of conventional CD4+ T cells into a stable population of suppressor cells . Second , detection of demethylated foxp3 sequences might allow the development of novel diagnostic tools for the quantification of Tregs in blood or tissues . Both in autoimmune disease and tumor patients , a correlation between Treg number and/or activity and disease status has been observed in a number of recent studies . Decreased activity and/or number of Tregs has been noted to be associated with myasthenia gravis , autoimmune polyglandular syndrome type II , ulcerative colitis , and multiple sclerosis [30–36] . In contrast , an increased number of Tregs was observed in patients with a variety of malignant cancers [37–39] , and might be involved in tumor progression [40–42] . Most notably , presence of Tregs , as defined by gene expression of FOXP3 , has been shown to constitute a significant predictive parameter for the clinical outcome in ovarian cancer patients [40 , 41] . However , the analytical value of flow cytometry , immunohistological , and mRNA expression analysis of CD25 and Foxp3 as accurate diagnostic tools is blurred by both ambiguity of the markers and instability of the biological materials . In contrast , our current data show that DNA demethylation at the foxp3 locus , both in mice and humans , strictly coincides with the generation of stable Tregs . Therefore , measurement of the methylation status of the foxp3 locus could present a more reliable and objective criterion for the identification and quantification of Tregs . Moreover , DNA methylation is intrinsically a more stable parameter than mRNA expression or protein synthesis , and can be accurately quantified [43] . Therefore , we believe that establishment of a measurement system for the methylation status of the human foxp3 locus may provide a novel diagnostic tool both in tumor and in autoimmune disease patients .
BALB/c mice were bred at the BfR ( Bundesinstitut fuer Risikobewertung , Berlin , Germany ) and used at 6–12 wk of age . All animal experiments were performed under specific pathogen-free conditions and in accordance with institutional , state , and federal guidelines . The following antibodies were produced in our laboratory: anti-FcR II/III ( 2 . 4G2 ) , anti-CD4 ( GK1 . 5 ) , anti-CD3 ( 145 . 2C11 ) , anti-CD28 ( 37 . 51 ) , and anti–IL-4 ( 11B11 ) . The following antibodies and secondary reagents were purchased from BD PharMingen ( San Diego , California , United States ) : anti-CD4 ( RM4–5 ) , anti-CD19 ( 1D3 ) , anti-CD25 ( 7D4 ) , anti-CD8 ( 53–6 . 7 ) , anti-CD25 ( PC6 . 1 ) , anti-CD62L ( Mel-14 ) , streptavidin , and appropriate isotype controls . The PE anti-mouse Foxp3 staining set was purchased from eBioscience ( San Diego , California , United States ) . All microbeads were obtained from Miltenyi Biotec ( Bergisch Gladbach , Germany ) and all cytokines from R & D systems ( Minneapolis , Minnesota , United States ) . Cytometric analysis was performed as previously described [44] using a FACS Calibur or a LSRII ( BD Biosciences , Palo Alto , California , United States ) and the CellQuest software . Dead cells were excluded by PI ( propidium iodide ) or DAPI ( diamidophenylindole ) staining ( Sigma , St . Louis , Missouri , United States ) . Intracellular Foxp3 staining was performed with the PE anti-mouse Foxp3 staining set according to the manufacturer's instructions . CD4+ T cells were isolated from pooled spleen and lymph node ( LN ) single-cell suspensions by using anti–CD4-FITC plus anti-FITC multisort microbeads and the AutoMACS magnetic separation system ( Miltenyi Biotec ) . After release of beads according to the manufacturer's instructions , CD25+ and CD25− cells were separated using anti–CD25-APC plus anti-APC microbeads . Thymic single-cell suspensions were sorted for CD8+ and CD8− cells using anti-CD8 microbeads and the AutoMACS magnetic separation system . MACS-sorted CD8− thymocytes were subsequently stained using anti–CD4-FITC , anti–CD25-APC , and anti–CD19-PE , and sorted into CD25+ and CD25− subsets of CD4 SP thymocytes as well as into CD19− DN thymocytes by fluorescence-activated cell sorting ( FACS ) ( FACSAria; BD Bioscience ) . Magnetic-activated cell sorting ( MACS ) -sorted CD8+ thymocytes were stained using anti–CD4-FITC and anti–CD8-PerCP , and sorted into DP thymocytes by FACS . All subsets were sorted to a purity of greater than 98% . Sorted CD25+CD4+ T cells were labeled with CFSE ( Molecular Probes , Eugene , Oregon , United States ) as described before [45] . A total of 2 × 106 CFSE-labeled cells were adoptively transferred into syngenic recipients . Fourteen days after transfer , single-cell suspensions of spleen , peripheral , and mesenteric LNs were prepared and stained for CD4 , CD25 , and Foxp3 as described above . CD4+ T cells were isolated from pooled spleen and LN single-cell suspensions by using anti–CD4-FITC plus anti-FITC multisort microbeads and the AutoMACS magnetic separation system ( Miltenyi Biotec ) . After release of beads according to the manufacturer's instructions , CD25+ cells were depleted by using anti–CD25-APC plus anti-APC microbeads . To avoid the expansion of precommitted Foxp3+ Tregs , we excluded the majority of residual Foxp3+ Tregs from the CD25−CD4+ T cell fraction by sorting for CD62Lhigh cells using anti-CD62L microbeads . MACS-sorted CD62LhighCD25−CD4+ T cells were stimulated for 3 d using plate-bound anti-CD3 ( 6 μg/ml ) and anti-CD28 ( 4 μg/ml ) . For Th1 cultures , 5-μg/ml anti–IL-4 , 20-ng/ml IFN-γ and 5-ng/ml IL-12 were added to the medium . For TGF-β cultures , 5-ng/ml TGF-β and 10-ng/ml IL-2 was used . After 3 d , cells were removed from the stimulus , transferred to non-coated plates , and cultured for another 3 d . All cell culture was done with RPMI 1640 ( GIBCO , San Diego , California , United States ) supplemented with 10% FCS ( Sigma ) . On day 6 , cultured cells were stained using anti–CD25-APC and sorted for CD25+ cells by FACS ( FACSAria ) . Foxp3 expression of sorted CD25+ cells was analyzed by intracellular staining . For restimulation experiments , TGF-β–induced Tregs were sorted for CD25+ cells by FACS ( FACSAria ) , and sorted CD25+ cells were stimulated for 3 d using plate-bound anti-CD3 ( 6 μg/ml ) and anti-CD28 ( 4 μg/ml ) plus IL-2 ( 10 ng/ml ) . After 3 d , cells were removed from the stimulus , transferred to non-coated plates , and cultured for another 3 d . On day 6 , cultured cells were stained for CD25 and Foxp3 as described above . CD25+ cells were enriched from pooled spleen and LN single-cell suspensions by using anti–CD25-FITC , anti-FITC microbeads , and the AutoMACS magnetic separation system ( Miltenyi Biotec ) . MACS-enriched CD25+ T cells were subsequently stained using anti–CD4-PerCP and anti–CD62L-APC , and sorted for CD62LhighCD25+CD4+ Tregs by FACS ( FACSAria ) . CD62Lhigh Tregs were used to avoid the expansion of Foxp3−CD25+ effector T cells . FACS-sorted CD62LhighCD25+CD4+ Tregs were stimulated for 3 d using plate-bound anti-CD3 ( 6 μg/ml ) and anti-CD28 ( 4 μg/ml ) plus IL-2 ( 40 ng/ml ) , followed by transfer to non-coated plates and culture for another 3 d . On day 6 , cultured cells were stained for CD25 and Foxp3 as described above . The assay was performed as previously described [45] . Proliferation of naïve CD62LhighCD25−CD4+ responder cells was evaluated according to CFSE dilution . Genomic DNA was isolated from purified T cells using the DNeasy tissue kit ( Qiagen , Valencia , California , United States ) following the supplier's recommendations . Sodium bisulphite treatment of genomic DNA was performed according to Olek et al . [46] with minor modifications , resulting in the deamination of unmethylated cytosines to uracil , whereas methylated cytosines remain unchanged . In a subsequent PCR amplification , uracils were replicated as thymidines . Thus , detection of a “C” in sequencing reactions reflects methylation of the genomic DNA at that site . Detection of a “T” at the same site reflects instead the absence of a methyl modification of the genomic cytosine . PCRs were performed on MJ Research thermocyclers ( Waltham , Massachusetts , United States ) in a final volume of 25 μl containing 1× PCR Buffer , 1-U Taq DNA polymerase ( Qiagen ) , 200 μM dNTPs , 12 . 5 pmol each of forward and reverse primers , and 7 ng of bisulphite-treated genomic DNA . The amplification conditions were 95 °C for 15 min and 40 cycles of 95 °C for 1 min , 55 °C for 45 sec , and 72 °C for 1 min , and a final extension step of 10 min at 72 °C . PCR products were purified using ExoSAP-IT ( USB Corp , Staufen , Germany ) and sequenced in both directions applying the PCR primers and the ABI Big Dye Terminator v1 . 1 cycle sequencing chemistry ( Applied Biosystems , Foster City , California , United States ) , followed by capillary electrophoresis on an ABI 3100 genetic analyzer . Trace files were interpreted using ESME , which normalizes sequence traces , corrects for incomplete bisulphite conversion , and allows for quantification of methylation signals [47] . For each sample , both PCR amplification and sequencing was repeated once . The following primers ( 5′ to 3′ direction ) were used for both PCR amplification of bisulphite converted genomic DNA and sequence reactions: Amp 1 ( fw: AGGAAGAGAAGGGGGTAGATA; rev: AAACTAACATTCCAAAACCAAC ) , Amp 2 ( fw: ATTTGAATTGGATATGGTTTGT; rev: AACCTTAAACCCCTCTAACATC ) , Amp 3 ( fw: AGAGGTTGAAGGAGGAGTATTT; rev: ACTATCTATCCAATTCCCCAAC ) , and Amp 4 ( fw: TGGTTGTTTTGGAGTTTAGTGT; rev: CACTTTTCTACCTTCCACAAAT ) . The differentially methylated , conserved element ( CE ) of the foxp3 locus was amplified by PCR using the mouse BAC RPCIB731D08143Q2 ( RZPD ) as a template and the following primers: 5′-GATCGGTACCTTGTCCCAGGAGAGCGGG-3′ , and 5′-GATCCCCGGGCCCATATGGCTGGACCATGG-3′ . The amplified 1 , 160-bp element was cloned via Asp718 and XmaI into the pGL3 promoter vector ( Promega , Madison , Wisconsin , United States ) in front of the minimal SV40 promoter to generate pGL3-Foxp3-CE . RLM-11–1 cells [48] , which were kindly provided by Marc Ehlers ( Deutsches Rheuma-Forschungszentrum [DRFZ] , Berlin , Germany ) , or ex vivo isolated CD25+CD4+ Tregs were transfected using 4 μg of pGL3 promoter vector ( control ) or pGL3-Foxp3-CE . Synthetic Renilla luciferase reporter vector ( pRL-TK , 0 . 2 μg; Promega ) was used as an internal control for transfection efficiency . Four hours after transfection via nucleofection ( Amaxa Cologne , Germany ) , RLM-11–1 cells were stimulated with PMA ( 10 ng/ml; Sigma ) or with PHA ( 20 ng/ml; Sigma ) plus ionomycin ( 1 μM; Sigma ) in case of ex vivo isolated Tregs . After 18–24-h culture in IMEM ( GIBCO ) , cells were harvested and luciferase activity was measured using the dual luciferase assay system ( Promega ) . Data were normalized to the Renilla luciferase activity . ChIP analysis was carried out according to the manufacturer's protocol ( Upstate/Millipore , Billerica , Massachusetts , United States ) . Cells ( 1–5 × 106 ) were fixed with 1% formaldehyde , and chromatin was fragmented by ultrasound . For all ChIP samples , sheared chromatin was precleared by incubation with ProteinA-agarose/salmon sperm DNA ( Upstate/Millipore ) . Subsequently , chromatin was immunoprecipitated by overnight incubation at 4 °C with 4-μg antibodies ( rabbit isotype , #2027 , Santa Cruz Biotechnology [Santa Cruz , California , United States]; anti–acetyl-histone H3 , #06–599 , Upstate/Millipore; anti–acetyl-histone H4 , #06–866 , Upstate/Millipore; and anti–trimethyl-K4-histone H3 , #07–473 , Upstate/Millipore ) followed by incubation with Protein A-agarose/salmon sperm DNA for 1 h . Precipitates were defixed and DNA was purified by using the NucleoSpin Extract II kit ( Macherey-Nagel , Düren , Germany ) . The amount of immunoprecipitated DNA was quantified by real-time PCR with LightCycler ( Roche Applied Science , Basel , Switzerland ) using SYBR Green and the following primer pair ( 5′ to 3′ direction ) : Foxp3 ( 331 bp ) fw: GACTCAAGGGGGTCTCA; rev: TTGGGCTTCATCGGCAA . Sample PCR products were set in relation to the input DNA using the following expression: . Genomic sequences spanning the foxp3 locus were analyzed using the alignment software vista ( http://pipeline . lbl . gov/servlet/vgb2 ) , allowing the identification of conserved regions . Transcription factor binding sites were identified using the TRANSFAC database [49] and the search tool MATCH [50] .
The GenBank ( http://www . ncbi . nlm . nih . gov/Genbank ) accession number for the forkhead transcription factor Foxp3 is AF277994 .
|
Regulatory T cells play a pivotal role in the maintenance of self-tolerance within the immune system by preventing autoimmunity or excessive activation of the T cells that respond to pathogens ( naïve and effector T cells ) . They differentiate within the thymus , but can also be de novo induced in the rest of the body . Mechanisms determining development of a stable regulatory T cell lineage are unknown . Our study provides evidence for a critical role of epigenetic modifications in the locus coding for the forkhead transcription factor Foxp3 , which acts as a master switch controlling regulatory T cell development and function: An evolutionarily conserved region within the non-coding part of the gene contains CpG motifs , which are completely demethylated in regulatory T cells , but methylated in naïve and effector T cells , whereas we observed an inverse occurrence of acetylated histones , another epigenetic chromatin modification . Regulatory T cells induced in vitro—which , in contrast to natural regulatory T cells , do not display a stable regulatory T cell phenotype—display only incomplete DNA demethylation despite high Foxp3 expression . Our data suggest that expression of Foxp3 must be stabilized by epigenetic modification to result in a permanent suppressor cell lineage , a finding of significant importance for therapeutic applications involving induction or transfer of regulatory T cells and for the understanding of long-term cell lineage decisions .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods",
"Supporting",
"Information"
] |
[
"in",
"vitro",
"immunology",
"mus",
"(mouse)",
"homo",
"(human)"
] |
2007
|
Epigenetic Control of the foxp3 Locus in Regulatory T Cells
|
Physical activity ( PA ) may modify the genetic effects that give rise to increased risk of obesity . To identify adiposity loci whose effects are modified by PA , we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200 , 452 adults of European ( n = 180 , 423 ) or other ancestry ( n = 20 , 029 ) . We standardized PA by categorizing it into a dichotomous variable where , on average , 23% of participants were categorized as inactive and 77% as physically active . While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene , of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals , we do not identify additional loci that are sensitive to PA . In additional genome-wide meta-analyses adjusting for PA and interaction with PA , we identify 11 novel adiposity loci , suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery .
In recent decades , we have witnessed a global obesity epidemic that may be driven by changes in lifestyle such as easier access to energy-dense foods and decreased physical activity ( PA ) [1] . However , not everyone becomes obese in obesogenic environments . Twin studies suggest that changes in body weight in response to lifestyle interventions are in part determined by a person’s genetic constitution [2–4] . Nevertheless , the genes that are sensitive to environmental influences remain largely unknown . Previous studies suggest that genetic susceptibility to obesity , assessed by a genetic risk score for BMI , may be attenuated by PA [5 , 6] . A large-scale meta-analysis of the FTO obesity locus in 218 , 166 adults showed that being physically active attenuates the BMI-increasing effect of this locus by ~30% [7] . While these findings suggest that FTO , and potentially other previously established BMI loci , may interact with PA , it has been hypothesized that loci showing the strongest main effect associations in genome-wide association studies ( GWAS ) may be the least sensitive to environmental and lifestyle influences , and may therefore not make the best candidates for interactions [8] . Yet no genome-wide search for novel loci exhibiting SNP×PA interaction has been performed . A genome-wide meta-analysis of genotype-dependent phenotypic variance of BMI , a marker of sensitivity to environmental exposures , in ~170 , 000 participants identified FTO , but did not show robust evidence of environmental sensitivity for other loci [9] . Recent genome-wide meta-analyses of adiposity traits in >320 , 000 individuals uncovered loci interacting with age and sex , but also suggested that very large sample sizes are required for interaction studies to be successful [10] . Here , we report results from a large-scale genome-wide meta-analysis of SNP×PA interactions in adiposity in up to 200 , 452 adults . As part of these interaction analyses , we also examine whether adjusting for PA or jointly testing for SNP’s main effect and interaction with PA may identify novel adiposity loci .
We performed meta-analyses of results from 60 studies , including up to 180 , 423 adults of European descent and 20 , 029 adults of other ancestries to assess interactions between ~2 . 5 million genotyped or HapMap-imputed SNPs and PA on BMI and BMI-adjusted waist circumference ( WCadjBMI ) and waist-hip ratio ( WHRadjBMI ) ( S1–S5 Tables ) . Similar to a previous meta-analysis of the interaction between FTO and PA [7] , we standardized PA by categorizing it into a dichotomous variable where on average ~23% of participants were categorized as inactive and ~77% as physically active ( see Methods and S6 Table ) . On average , inactive individuals had 0 . 99 kg/m2 higher BMI , 3 . 46 cm higher WC , and 0 . 018 higher WHR than active individuals ( S4 and S5 Tables ) . Each study first performed genome-wide association analyses for each SNP’s effect on BMI in the inactive and active groups separately . Corresponding summary statistics from each cohort were subsequently meta-analyzed , and the SNP×PA interaction effect was estimated by calculating the difference in the SNP’s effect between the inactive and active groups . To identify sex-specific SNP×PA interactions , we performed the meta-analyses separately in men and women , as well as in the combined sample . In addition , we carried out meta-analyses in European-ancestry studies only and in European and other-ancestry studies combined . We used two approaches to identify loci whose effects are modified by PA . In the first approach , we searched for genome-wide significant SNP×PA interaction effects ( PINT<5x10-8 ) . As shown in Fig 1 , this approach yielded the highest power to identify cross-over interaction effects where the SNP’s effect is directionally opposite between the inactive and active groups . However , this approach has low power to identify interaction effects where the SNP’s effect is directionally concordant between the inactive and active groups ( Fig 1 ) . We identified a genome-wide significant interaction between rs986732 in cadherin 12 ( CDH12 ) and PA on BMI in European-ancestry studies ( betaINT = -0 . 076 SD/allele , PINT = 3 . 1x10-8 , n = 134 , 767 ) ( S7 Table ) . The interaction effect was directionally consistent but did not replicate in an independent sample of 31 , 097 individuals ( betaINT = -0 . 019 SD/allele , PINT = 0 . 52 ) , and the pooled association P value for the discovery and replication stages combined did not reach genome-wide significance ( NTOTAL = 165 , 864; PINT-TOTAL = 3x10-7 ) ( S1 Fig ) . No loci showed genome-wide significant interactions with PA on WCadjBMI or WHRadjBMI . CDH12 encodes an integral membrane protein mediating calcium-dependent cell-cell adhesion in the brain , where it may play a role in neurogenesis [11] . While CDH12 rs4701252 and rs268972 SNPs have shown suggestive associations with waist circumference ( P = 2x10-6 ) and BMI ( P = 5x10-5 ) in previous GWAS [12 , 13] , the SNPs are not in LD with rs986732 ( r2<0 . 1 ) . In our second approach , we tested interaction for loci showing a genome-wide significant main effect on BMI , WCadjBMI or WHRadjBMI ( S7–S12 Tables ) . We adjusted the significance threshold for SNP×PA interaction by Bonferroni correction ( P = 0 . 05/number of SNPs tested ) . As shown in Fig 1 , this approach enhanced our power to identify interaction effects where there is a difference in the magnitude of the SNP’s effect between inactive and active groups when the SNP’s effect is directionally concordant between the groups . We identified a significant SNP×PA interaction of the FTO rs9941349 SNP on BMI in the meta-analysis of European-ancestry individuals; the BMI-increasing effect was 33% smaller in active individuals ( betaACTIVE = 0 . 072 SD/allele ) than in inactive individuals ( betaINACTIVE = 0 . 106 SD/allele , PINT = 4x10-5 ) . The rs9941349 SNP is in strong LD ( r2 = 0 . 87 ) with FTO rs9939609 for which interaction with PA has been previously established in a meta-analysis of 218 , 166 adults [7] . We identified no loci interacting with PA for WCadjBMI or WHRadjBMI . In a previously published meta-analysis [7] , the FTO locus showed a geographic difference for the interaction effect where the interaction was more pronounced in studies from North America than in those from Europe . To test for geographic differences in the present study , we performed additional meta-analyses for the FTO rs9941349 SNP , stratified by geographic origin ( North America vs . Europe ) . While the interaction effect was more pronounced in studies from North America ( betaINT = 0 . 052 SD/allele , P = 5x10-4 , N = 63 , 896 ) than in those from Europe ( betaINT = 0 . 028 SD/allele , P = 0 . 006 , N = 109 , 806 ) , we did not find a statistically significant difference between the regions ( P = 0 . 14 ) . Physical activity contributes to variation in BMI , WCadjBMI , and WHRadjBMI , hence , adjusting for PA as a covariate may enhance power to identify novel adiposity loci . To that extent , each study performed genome-wide analyses for association with BMI , WCadjBMI , and WHRadjBMI while adjusting for PA . Subsequently , we performed meta-analyses of the study-specific results . We discovered 10 genome-wide significant loci ( 2 for BMI , 1 for WCadjBMI , 7 for WHRadjBMI ) that have not been reported in previous GWAS of adiposity traits ( Table 1 , S2–S4 Figs ) . To establish whether additionally accounting for SNP×PA interactions would identify novel loci , we calculated the joint significance of PA-adjusted SNP main effect and SNP×PA interaction using the method of Aschard et al [16] . As illustrated in Fig 1 , the joint test enhanced our power to identify loci where the SNP shows simultaneously a main effect and an interaction effect . We identified a novel BMI locus near ELAVL2 in men ( PJOINT = 4x10-8 ) , which also showed suggestive evidence of interaction with PA ( PINT = 9x10-4 ) ; the effect of the BMI-increasing allele was attenuated by 71% in active as compared to inactive individuals ( betaINACTIVE = 0 . 087 SD/allele , betaACTIVE = 0 . 025 SD/allele ) ( Table 1 , S2–S4 Figs ) . To evaluate the effect of PA adjustment on the results for the 11 novel loci , we performed a look-up in published GIANT consortium meta-analyses for BMI , WCadjBMI , and WHRadjBMI that did not adjust for PA [17 , 18] ( S22 Table ) . All 11 loci showed a consistent direction of effect between the present PA-adjusted and the previously published PA-unadjusted results , but the PA-unadjusted associations were less pronounced despite up to 40% greater sample size , suggesting that adjustment for PA may have increased our power to identify these loci . The biological relevance of putative candidate genes in the novel loci , based on our thorough searches of the literature , GWAS catalog look-ups , and analyses of eQTL enrichment and overlap with functional regulatory elements , are described in Tables 2 and 3 . As the novel loci were identified in a PA-adjusted model , where adjusting for PA may have contributed to their identification , we examined whether the lead SNPs in these loci are associated with the level of PA . More specifically , we performed look-ups in GWAS analyses for the levels of moderate-to-vigorous intensity leisure-time PA ( n = 80 , 035 ) , TV-viewing time ( n = 28 , 752 ) , and sedentary behavior at work ( n = 59 , 381 ) or during transportation ( n = 15 , 152 ) [personal communication with Marcel den Hoed , Marilyn Cornelis , and Ruth Loos] . However , we did not find significant associations when correcting for the number of loci that were examined ( P>0 . 005 ) ( S16 Table ) . In addition to uncovering 11 novel adiposity loci , our PA-adjusted GWAS and the joint test of SNP main effect and SNP×PA interaction confirmed 148 genome-wide significant loci ( 50 for BMI , 58 for WCadjBMI , 40 for WHRadjBMI ) that have been established in previous main effect GWAS for adiposity traits ( S7–S12 Tables , S4 Fig ) . The lead SNPs in eight of the previously established loci ( 5 for BMI , 3 for WCadjBMI ) , however , showed no LD or only weak LD ( r2<0 . 3 ) with the published lead SNP , suggesting they could represent novel secondary signals in known loci ( S17 Table ) . To test whether these eight signals are independent of the previously published signals , we performed conditional analyses [19] . Three of the eight SNPs we examined , in/near NDUFS4 , MEF2C-AS1 and CPA1 , were associated with WCadjBMI with P<5x10-8 in our PA-adjusted GWAS even after conditioning on the published lead SNP , hence representing novel secondary signals in these loci ( S17 Table ) . Epigenetic variation may underlie gene-environment interactions observed in epidemiological studies [20] and PA has been shown to induce marked epigenetic changes in the genome [21] . We examined whether the BMI or WHRadjBMI loci reaching P<1x10-5 for interaction with PA ( 13 loci for BMI , 5 for WHRadjBMI ) show overall enrichment with chromatin states in adipose , brain and muscle tissues available from the Roadmap Epigenomics Consortium [22] . However , we did not find significant enrichment ( S18 and S19 Tables ) , which may be due to the limited number of identified loci . The lack of significant findings may also be due to the assessment of chromatin states in the basal state , which may not reflect the dynamic changes that occur when cells are perturbed by PA [23] . We also tested whether the loci reaching P<5x10-8 in our PA-adjusted GWAS of BMI or WHRadjBMI show enrichment with chromatin states and found significant enrichment of the BMI loci with enhancer , weak transcription , and polycomb-repressive elements in several brain cell lines , and with enhancer elements in three muscle cell lines ( S20 and S21 Tables ) . We also found significant enrichment of the WHRadjBMI loci with enhancer elements in three adipose and six muscle cell lines , with active transcription start sites in two adipose cell lines , and with polycomb-repressive elements in seven brain cell lines . The enrichment of our PA-adjusted main effect results with chromatin annotations in skeletal muscle in particular , the tissue most affected by PA , could highlight regulatory mechanisms that may be influenced by PA .
In this genome-wide meta-analysis of more than 200 , 000 adults , we do not find evidence of interaction with PA for loci other than the established FTO locus . However , when adjusting for PA or jointly testing for SNP main effect and interaction with PA , we identify 11 novel adiposity loci , suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may increase power for gene discovery . Our results suggest that if SNP×PA interaction effects for common variants exist , they are unlikely to be of greater magnitude than observed for FTO , the BMI-increasing effect of which is attenuated by ~30% in physically active individuals . The fact that common SNPs explain less of the BMI variance among physically active compared to inactive individuals indicates that further interactions may exist , but larger meta-analyses , more accurate and precise measurement of PA , and/or improved analytical methods will be required to identify them . We found no difference between inactive and active individuals in variance explained by common SNPs in aggregate for WCadjBMI or WHRadjBMI , and no loci interacted with PA on WCadjBMI or WHRadjBMI . Therefore , PA may not modify genetic influences as strongly for body fat distribution as for overall adiposity . Furthermore , while differences in variance explained by common variants may be due to genetic effects being modified by PA , it is important to note that heritability can change in the absence of changes in genetic effects , if environmental variation differs between the inactive and active groups . Therefore , the lower BMI variance explained in the active group could be partly due to a potentially greater environmental variation in this group . While we replicated the previously observed interaction between FTO and PA [7] , it remains unclear what biological mechanisms underlie the attenuation in FTO’s effect in physically active individuals , and whether the interaction is due to PA or due to confounding by other environmental exposures . While some studies suggest that FTO may interact with diet [24–26] , a recent meta-analysis of 177 , 330 individuals did not find interaction between FTO and dietary intakes of total energy , protein , carbohydrate or fat [27] . The obesity-associated FTO variants are located in a super-enhancer region [28] and have been associated with DNA methylation levels [29–31] , suggesting that this region may be sensitive to epigenetic effects that could mediate the interaction between FTO and PA . In genome-wide analyses for SNP main effects adjusting for PA , or when testing for the joint significance of SNP main effect and SNPxPA interaction , we identify 11 novel adiposity loci , even though our sample size was up to 40% smaller than in the largest published main effect meta-analyses [17 , 18] . Our findings suggest that accounting for PA may facilitate the discovery of novel adiposity loci . Similarly , accounting for other environmental factors that contribute to variation in adiposity could lead to the discovery of additional loci . In the present meta-analyses , statistical power to identify SNPxPA interactions may have been limited due to challenges relating to the measurement and statistical modeling of PA [5] . Of the 60 participating studies , 56 assessed PA by self-report while 4 used wearable PA monitors . Measurement error and bias inherent in self-report estimates of PA [32] can attenuate effect sizes for SNP×PA interaction effects towards the null [33] . Measurement using PA monitors provides more consistent results , but the monitors are not able to cover all types of activities and the measurement covers a limited time span compared to questionnaires [34] . As sample size requirements increase nonlinearly when effect sizes decrease , any factor that leads to a deflation in the observed interaction effect estimates may make their detection very difficult , even when very large population samples are available for analysis . Finally , because of the wide differences in PA assessment tools used among the participating studies , we treated PA as a dichotomous variable , harmonizing PA into inactive and active individuals . Considerable loss of power is anticipated when a continuous PA variable is dichotomized [35] . Our power could be enhanced by using a continuous PA variable if a few larger studies with equivalent , quantitative PA measurements were available . In summary , while our results suggest that adjusting for PA or other environmental factors that contribute to variation in adiposity may increase power for gene discovery , we do not find evidence of SNP×PA interaction effects stronger than that observed for FTO . While other SNP×PA interaction effects on adiposity are likely to exist , combining many small studies with varying characteristics and PA assessment tools may be inefficient for identifying such effects [5] . Access to large cohorts with quantitative , equivalent PA variables , measured with relatively high accuracy and precision , may be necessary to uncover novel SNP×PA interactions .
|
Decline in daily physical activity is thought to be a key contributor to the global obesity epidemic . However , the impact of sedentariness on adiposity may be in part determined by a person’s genetic constitution . The specific genetic variants that are sensitive to physical activity and regulate adiposity remain largely unknown . Here , we aimed to identify genetic variants whose effects on adiposity are modified by physical activity by examining ~2 . 5 million genetic variants in up to 200 , 452 individuals . We also tested whether adjusting for physical activity as a covariate could lead to the identification of novel adiposity variants . We find robust evidence of interaction with physical activity for the strongest known obesity risk-locus in the FTO gene , of which the body mass index-increasing effect is attenuated by ~30% in physically active individuals compared to inactive individuals . Our analyses indicate that other similar gene-physical activity interactions may exist , but better measurement of physical activity , larger sample sizes , and/or improved analytical methods will be required to identify them . Adjusting for physical activity , we identify 11 novel adiposity variants , suggesting that accounting for physical activity or other environmental factors that contribute to variation in adiposity may facilitate gene discovery .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion"
] |
[
"genome-wide",
"association",
"studies",
"body",
"weight",
"medicine",
"and",
"health",
"sciences",
"functional",
"genomics",
"physical",
"activity",
"mathematics",
"physiological",
"parameters",
"statistics",
"(mathematics)",
"genome",
"analysis",
"obesity",
"epigenomics",
"research",
"and",
"analysis",
"methods",
"public",
"and",
"occupational",
"health",
"genomic",
"signal",
"processing",
"mathematical",
"and",
"statistical",
"techniques",
"statistical",
"methods",
"genetic",
"loci",
"signal",
"transduction",
"cell",
"biology",
"meta-analysis",
"physiology",
"genetics",
"biology",
"and",
"life",
"sciences",
"physical",
"sciences",
"genomics",
"cell",
"signaling",
"computational",
"biology",
"human",
"genetics"
] |
2017
|
Genome-wide physical activity interactions in adiposity ― A meta-analysis of 200,452 adults
|
Hepatitis B virus ( HBV ) capsids are found in many forms: immature single-stranded RNA-filled cores , single-stranded DNA-filled replication intermediates , mature cores with relaxed circular double-stranded DNA , and empty capsids . A capsid , the protein shell of the core , is a complex of 240 copies of core protein . Mature cores are transported to the nucleus by a complex that includes both importin α and importin β ( Impα and Impβ ) , which bind to the core protein’s C-terminal domains ( CTDs ) . Here we have investigated the interactions of HBV core protein with importins in vitro . Strikingly , empty capsids and free core protein can bind Impβ without Impα . Cryo-EM image reconstructions show that the CTDs , which are located inside the capsid , can extrude through the capsid to be bound by Impβ . Impβ density localized on the capsid exterior near the quasi-sixfold vertices , suggested a maximum of 30 Impβ per capsid . However , examination of complexes using single molecule charge-detection mass spectrometry indicate that some complexes include over 90 Impβ molecules . Cryo-EM of capsids incubated with excess Impβ shows a population of damaged particles and a population of “dark” particles with internal density , suggesting that Impβ is effectively swallowed by the capsids , which implies that the capsids transiently open and close and can be destabilized by Impβ . Though the in vitro complexes with great excess of Impβ are not biological , these results have implications for trafficking of empty capsids and free core protein; activities that affect the basis of chronic HBV infection .
Viruses take advantage of host proteins throughout their lifecycle; here we investigate interactions between Hepatitis B Virus ( HBV ) and host proteins related to nuclear transport . HBV is an enveloped virus with an icosahedral core . Mature HBV cores , which consist of a relaxed circular dsDNA genome packaged in a protein capsid , arrive in the cytoplasm as newly infecting particles or by maturation of newly assembled RNA-filled cores . In chronically infected cells , cores form in the cytoplasm when the HBV core ( or capsid ) proteins assemble around a complex of HBV reverse transcriptase and an RNA transcript of the viral genome . A large fraction of core protein assembles into empty capsids , devoid of RNA [1] . The fraction of empty capsids appears to increase in response to treatment of infected cells with TNFα or small molecules ( i . e . core protein allosteric modulators ) that drive capsid assembly [2 , 3] . Mature cores are transported to nuclear pores by a complex of importin α and importin β [4 , 5] . In a chronically infected cell , mature cores and empty cores , but not immature ssDNA-filled cores , can also be secreted from the host cell , acquiring an HBV surface antigen-studded envelope in the process [6 , 7] . The predominant form of capsid is a complex of 120 core protein dimers arranged with T = 4 icosahedral symmetry . The core protein , herein referred to as Cp183 , has 183 amino acids ( 185 for certain genotypes ) , forming two distinct domains: a helix-rich 149-residue assembly domain , capable of forming capsids on its own , and a disordered 34-residue , basic , nucleic acid-binding , C terminal domain ( CTD ) ( Fig 1 ) . The CTD can be phosphorylated at seven serines and one threonine [8–10] . The CTD phosphorylation is necessary for correct RNA packaging , affects reverse transcription , and can modulate nuclear transport [4 , 10–12] . In capsids , the CTD is localized to the interior interacting with packaged RNA or DNA [13] , but genome maturation and CTD phosphorylation lead to at least transient external exposure [4 , 8 , 14] . Indeed , cytoplasmic cores can show evidence of proteolysis of the encapsidated reverse transcriptase , implying at least transient opening of the capsids [15] . In empty capsids , CTDs readily extrude from capsid holes where they can be bound by external molecules [16] or cleaved by a protease [17] . Transport of HBV cores across the nuclear envelope is via nuclear pore complexes [18] . Genome liberation is closely linked with core interaction with nuclear pores [19 , 20]–crosslinked capsids become trapped in the nuclear pore [14] . Nuclear transport of HBV is mediated by cellular transport receptors , termed importins or karyopherins [8 , 9 , 21–23] . Canonically , the adapter protein importin α ( Impα ) binds to a nuclear localization sequence ( NLS ) , exposing Impα’s importin β-binding sequence ( IBB ) which in turn binds to the transport protein importin β ( Impβ ) [24] . An NLS consists of one or two clusters of four to six basic amino acids [25] . Interactions between importins and with cargo depend on electrostatic forces . HBV cores bind importins via CTD-associated NLS sequences [8 , 9 , 21–23 , 26 , 27] . Impα is required for transport of mature HBV cores to the nucleus [4 , 14] . As an alternative to Impα-mediated transport , Impβ can bind directly to cargos that have an IBB; a canonical IBB is comprised of 13 basic amino acids in 7 clusters distributed over 39 residues [28 , 29] . The Cp183 CTD may also contribute to forming an IBB ( Fig 1 ) . The intracellular fate of an HBV core or capsid , e . g . its nuclear transport , appears to be a function of its nucleic acid content . In this regard , there are four different forms of capsids in infected cells: RNA-filled immature , replication intermediate-containing immature , rcDNA-filled mature , and empty . Empty capsids show structural similarities to mature capsids [30] and like mature can become enveloped by the surface proteins [1] . The predominant localization of capsids varies: HBV-expressing transformed cell lines [31] and infected primary hepatocytes in culture show a cytosolic dominant phenotype , while infected hepatocytes from patients’ livers or in HBV transgenic mice mostly exhibit nuclear capsids [32–34] . Of note , cytosolic cores in patients are linked to greater hepatocellular injury [35 , 36] . Cytoplasmic expression of hepatitis B core antigen correlates with histologic activity of liver disease in young patients with chronic hepatitis B infection [36 , 37] . This is consistent with the observation that core epitopes , derived from proteasomal degradation of the core or of core protein dimers [38] are a target for the MHC class I mediated CD8+ T cell response , which can in turn modulate HBV infection [39] We have used a reductionist system comprised of Impβ and Cp183 to investigate the basis of importin-core protein interaction . We find that Impβ can bind phosphorylated and unphosphorylated Cp183 , Impβ binds Cp183 dimers and Cp183 empty capsids , and excess Impβ can spontaneously destabilize capsids . These results suggest that the combination of a dynamic capsid and a ligand like Impβ , whose binding site extends into the assembly domain , can provide a mechanical basis for initiating HBV uncoating . This activity may have roles in genome release and clearing empty capsids from the cytoplasm .
HBV CTDs are normally on the capsid interior where they bind nucleic acid [40 , 41] , but can be transiently exposed and captured on the capsid exterior by a binding partner [8 , 14 , 16 , 17] . We initially examined Cp183 capsids binding to Impα and Impβ , separately and together , using size exclusion chromatography ( SEC , Fig 2 ) . Though mature capsids had been found to require the Impα adapter protein to bind Impβ [8] , we observed that Cp183 capsids co-migrated with Impβ and both Impα and Impβ . We chose to focus on the interaction of Cp183 with Impβ ( without Impα ) for three reasons . First , we observed that the binding affinity of Impβ for empty capsids was about the same as that of the Impα+Impβ complex , which suggest direct impβ binding may be biologically relevant for empty capsids . Second , the difference in binding specificity of mature and immature cores suggests the hypothesis that there could be discrete structural or dynamic differences between them . Third , a practical issue arose: we needed to fully understand Cp183-Impβ interaction before investigating binding to an Impα+Impβ complex . Finally , up until very recently the prevalence of empty capsids in HBV infections had not been appreciated [1] . To determine the requirements for Impβ interaction with cores , we tested different forms of capsid by monitoring the co-migration of Impβ and capsids through a Superose 6 column ( Fig 2 , S1 Table ) . In these assays the concentrations of the reactants , reaction conditions , and column conditions were kept identical to allow valid comparison of the Impβ affinities . The reactant concentrations were 5 . 3 μM Impβ and 7 . 9 μM core protein dimer ( equivalent to 66 nM capsid ) ; this resulted in a molar ratio of 80 Impβ per capsid , an excess over the 30 sites anticipated from earlier studies with CTD-binding SRPK [16] . The elution profiles ( e . g . , Fig 2A ) show that Impβ binds to empty Cp183 capsids in solution . Increasing the NaCl concentration from 0 . 15 M to 0 . 25 M notably decreased binding Impβ to Cp183 capsid demonstrating the electrostatic nature of the interaction between Cp183 capsids and Impβ ( Fig 2B vs . Fig 2A ) . We observed that Cp183 capsids that contained E . coli RNA , predicted to entrap CTDs on the capsid interior , did not detectably bind Impβ using Coomassie staining ( Fig 2C ) , though a small population of bound Impβ could be detected by silver staining . Capsids of Cp149 , a core protein lacking the basic CTD , did not measurably bind Impβ ( Fig 2G ) . These data are consistent with localization of the Cp183 NLS/IBB segments to the proteins’ C-terminal domains ( CTDs ) [21 , 23 , 27] . Phosphorylation of NLS sequences can up- and down-regulate nuclear transport and alter importin binding [42] . We investigated how the phosphorylation affected HBV capsids’ affinity for Impβ by performing the column assays on phosphorylated Cp183 ( P-Cp183 ) capsids ( Fig 2D and 2E ) . P-Cp183 was prepared by co-expressing Cp183 and the protein kinase SRPK1 in E . coli [43] . The phosphorylation status of the capsids with or without RNA was characterized by mass spectrometry ( S2 Fig ) . The affinity of Impβ was much weaker for P-Cp183 than for unphosphorylated Cp183 ( compare Fig 2D with 2A ) . In the presence of 0 . 25 M NaCl , Impβ binding was further suppressed ( Fig 2E ) ; a small population of Impβ bound to P-Cp183 capsids could be observed in silver stained SDS-PAGE . Despite the lower affinity of empty P-Cp183 capsids for Impβ compared to empty Cp183 capsids , P-Cp183 capsids incorporating E . coli RNA bound more Impβ than RNA-filled Cp183 capsids ( Fig 2F vs . Fig 2C ) . This result is consistent with earlier observations suggesting that phosphorylated CTDs would be less restrained by negatively-charged RNA than un-phosphorylated CTDs [8] . In summary , we observed: ( i ) Empty HBV capsids can bind to Impβ directly without Impα . ( ii ) The binding sites are associated with CTDs and the binding interaction has an electrostatic nature . ( iii ) Phosphorylation of the CTD reduces its interaction with Impβ and , presumably , encapsidated nucleic acid . As discussed below , cryo-electron microscopy ( cryo-EM ) structural studies revealed localization of Impβ and showed that the importin and CTDs were highly disordered . Impβ-decorated capsids ( P-Cp183-Impβ and Cp183-Impβ ) were prepared for cryo-EM from a mixture of 5 . 3 μM Impβ and 7 . 9 μM Cp183 dimer , corresponding to a ratio of 80 Impβ proteins per capsid . In the absence of Impβ , control micrographs showed that empty P-Cp183 capsids and empty unphosphorylated Cp183 capsids were very similar ( compare Fig 3A in this paper to Figure 2a and 2b in reference [13] ) . Cryo-EM micrographs of Impβ-decorated capsids showed capsids festooned by sporadic protrusions of additional density ( Fig 3B and 3C , black arrows ) . In translationally aligned images of Impβ-decorated capsids we observed an additional ring located outside the capsid layer . This outer ring of density is notably stronger for unphosphorylated Cp183-Impβ capsids than phosphorylated particles ( Fig 3B and 3C , insets ) . We computed icosahedrally averaged 3D reconstructions from 16 , 591 particle images for empty P-Cp183 , 5 , 715 particle images for P-Cp183-Impβ , and 8 , 513 particles for Cp183-Impβ ( Fig 3 ) . Final resolutions were estimated to be 10 . 1 Å , 10 . 9 Å , and 10 . 2 Å , respectively , based on a Fourier shell correlation threshold of 0 . 5 ( S2 Table ) . All three structures exhibited clearly defined features typical for T = 4 HBV ( Fig 3D , 3E and 3F and S3 Fig ) . Dimer spikes were sufficiently resolved to show the component α helices . An atomic HBV capsid structure ( PDB entry 1QGT [44] ) fits the cryo-EM density attributable to capsid with no modification ( S3 Fig ) . In addition to the density expected for a capsid , flower-shaped density was observed protruding from the holes at quasi-sixfold vertices in both P-Cp183-Impβ and Cp183-Impβ structures ( Fig 3E and 3F ) , where the capsid protein CTD can extrude . This density was much weaker than protein density , suggesting only partial occupancy and/or heterogeneous binding modes . We attribute this new density to bound Impβ , agreeing the conclusion that Impβ binds to CTD . Further , we calculated a difference map by subtracting an empty P-Cp183 capsid structure from a P-Cp183-Impβ structure , generating surface shaded densities matching the molecular model of Impβ ( PDB entry 3LWW [45] ) ( S3 Fig ) . It is clear from the density and model that there is close contact between a single Impβ and the surrounding spikes at a quasi-sixfold vertex , despite the availability of six CTDs around the location . Therefore , we conclude that there is room for only one Impβ at each quasi-sixfold location , leading to a maximum of 30 sites per capsid . To definitively determine the distribution of Impβ bound to HBV capsids , we used charge detection mass spectrometry ( CDMS ) , a single particle MS technique . Unlike conventional MS techniques that measure the mass to charge ratio ( m/z ) for an ensemble of ions and require charge state deconvolution to determine z and then m , CDMS simultaneously measures m/z and z for each ion , yielding m directly . This enables the analysis of very large and heterogeneous species that resist conventional MS analysis [46] . Mass spectra of empty Cp183 particles , in the absence of Impβ , were consistent with the expected populations of capsid morphologies: a majority of T = 4 capsids ( 5 . 05 MDa ) and a small population of T = 3 capsids ( 3 . 83 MDa ) ( Fig 4A and inset ) . The CDMS spectra were fit with a series of Gaussian peaks with widths corresponding to the expected uncertainty in the mass measurement . The fits indicate that there is a small high mass shoulder on the main peak extending to 5 . 7 MDa . The high mass tail is attributed to salt adducts . CDMS spectra that were collected as a function of salt concentration show that the center of the T = 4 peak shifts linearly at a rate of 37 . 7 kDa per 0 . 1 M ammonium formate increment . This shift is also attributed to salt adducts and the masses can then be determined by extrapolating to zero salt concentration . SEC experiments showed binding was sensitive to ionic strength which is indicative of an electrostatic interaction between Impβ and capsids . We observed a similar effect using CDMS to measure the average masses of complexes formed with 66 nM capsid ( 7 . 9 μM Cp183 dimer ) and 5 . 3 μM Impβ where the ammonium formate buffer varied from 0 . 15 to 0 . 4 M ( Fig 5A ) . The average masses of the complexes decreased linearly with ionic strength . For further CDMS experiments we used 0 . 15 M ammonium formate , the minimum salt concentration that prevented capsid aggregation and precipitation in the presence and absence of Impβ . A titration of Cp183 by Impβ was measured by CDMS ( Fig 5B ) . Assuming binding occurred exclusively at the quasi-sixfold axis , we anticipated a maximum mass of 8 . 04 MDa corresponding to 30 Impβ molecules . In fact , we saw no evidence for accumulation of this complex in mass spectra . This is demonstrated in example spectra where the ratios of Impβ to quasi-sixfold sites were 1 . 5:1 and 7 . 5:1 ( 3 . 0 and 14 . 8 μM Impβ with 7 . 9 μM Cp183 dimer , respectively ) ( Fig 5A ) . For the lower ratio , the major peak was very broad and centered at 8 . 5 MDa , corresponding to T = 4 capsids with ~35 Impβ . At the 7 . 5:1 ratio , the peak in the mass histogram shifted to 10 . 3 MDa , which corresponds to a T = 4 capsid with 53 Impβ . The mass distributions with Impβ were very broad , indicating a distribution of Impβ on capsids . For the 7 . 5:1 ratio , the mass range extended from 7 to 14 . 5 MDa , corresponding to a range of 20 to 96 Impβ per capsid . Plotting the average mass of Cp183-Impβ complexes as a function of Impβ concentration , allowed calculation of an apparent dissociation constant based on a fit for non-cooperative binding of many equivalent sites [47] . A least squares fit ( the red trace in Fig 5B ) returned parameters of 53 sites per capsid each with a KD of 0 . 7 μM . This KD is notably below the cytosolic concentration of Impβ of 3 to 5 μM [48 , 49] . However , our CDMS spectra indicate that binding does not saturate at the predicted value , indicating that this fit outlines a much more complex reaction and does not portray a simple binding isotherm . At the highest concentration of Impβ tested , we observed abroad distribution of masses extending to 14 . 5 MDa ( a T = 4 capsid with 96 Impβ ) ( Fig 4A ) . It is hard to imagine how 53 Impβ molecules , let alone 96 , can bind to equivalent sites on a T = 4 capsid surface , thus these complexes were examined in greater detail . CDMS provided further information on the homogeneity , or lack thereof , of molecular species by allowing examination of the mass and charge of each ion ( Fig 4B ) . In electrospray , large ions are believed to be generated by a charge residue mechanism [50 , 51] , where the charge on each ion corresponds to the Rayleigh limit for a water droplet with the same diameter [52] . This model has been shown to account for the charges on globular proteins and protein complexes [53 , 54] . For Cp183 without Impβ , ions fall into two tight groups , T = 3 and T = 4 capsids , that fall close to the predictions for corresponding molecular and droplet diameters ( Fig 4B ) . The narrow charge distributions found for the T = 3 and T = 4 capsids are characteristic of an object with a well-defined structure . However , the complexes of Cp183 with Impβ have a very broad charge distribution centered at a much higher charge than predicted by the model . The broad distribution of charges suggests a heterogeneous mixture including non-globular structures . For monomeric proteins , a large charge is usually associated with unfolding to a more extended structure [55] , By analogy , to accommodate the number of Impβ adducts and charge , the results shown here suggest that some of the capsids may have broken open . Initial structural studies suggested the presence of 30 equivalent sites while CDMS titrations provided confounding data that capsids were heterogeneous and could bind more than 90 Impβ molecules , possibly damaging the capsids in the process . To address this conflicting information we examined the effect of excess Impβ on HBV capsid integrity using SEC . We observed three conditions where some Cp183 eluted substantively later than the capsid at ~7 . 8 ml and earlier than dimer at ~17 ml , co-eluting with the leading edge of the Impβ peak , in fractions between 15 ml and 16 ml: Cp183 that co-elutes with Impβ is much smaller than capsids , but larger than Cp183 dimers , and larger than free Impβ , which elutes at 16 ml . Therefore this Cp183 dimer was likely to be part of a complex that included one or two copies of Impβ . We reasoned that the material in the peak was scavenged from capsids dissociated by interaction with excess Impβ . Reactions where there was a substantial excess of Impβ and relatively low ionic strength provided evidence of capsid dissociation . In contrast , features that attenuated binding and stabilized capsids , e . g . phosphorylated Cp183 ( Fig 2D ) or higher ionic strength ( Fig 2B ) prevented measurable dissociation . To comprehend how > 50 Impβ molecules arrange on a capsid , as observed by CDMS in contrast to our expectation of 30 binding sites per capsid , we examined samples with a high Impβ:capsid ratio . Cp183 capsids at 11 μM dimer were incubated with 18 . 8 μM Impβ in 0 . 15 M ammonium formate at pH 7 . 4 . Negative stain micrographs of this sample demonstrated a population of typical HBV capsids and a population that appeared to sequester interior stain , “dark particles” . Similarly , cryo-micrographs showed four types of capsid-like particles ( Fig 7A ) : ( i ) morphologically normal capsids ( Fig 7A , white arrow ) , ( ii ) a minor population of T = 3 capsids ( Fig 7A , black arrowhead ) , ( iii ) defective particles suggestive of capsids caught in the act of dissociation ( Fig 7A , star ) , and ( iv ) “dark particles” that have an exterior boundary that is indistinguishable from normal capsids but a dark interior suggestive of internal content ( Fig 7A , black arrow , see also S4 Fig ) . Confirmatory reference free classification showed three different major types: 1 ) empty 30nm ( T = 3 ) capsids decorated with Impβ , 2 ) empty 36nm ( T = 4 ) capsids decorated with Impβ , and 3 ) 36nm ( T = 4 ) capsids decorated with Impβ with an additional inner ring ( S4 Fig ) ; with the last type corresponding to dark particles . Initially , we pursued cryo-EM image analysis of all T = 4 particles combined , determining a 3D structure to 10 . 1 Å resolution ( Fig 7B and 7C , left half; S1 Table ) . The outer surface of the cryo-EM density map was very similar to reconstructions of low Impβ:capsid ratio complexes ( Fig 3 ) . Impβ density was observed at the 30 quasi-sixfold axes ( Fig 7B and 7C , left half ) . However , we also observed a weak internal layer of density in 2D averages of the raw images ( Fig 7A , inset , left half ) and in 3D reconstructions ( Fig 7B , left half ) . Dark particles were then manually separated from the other ~36nm particles for structural elucidation . A translationally aligned , averaged image showed an inner annulus of density with an outer radius of ~12 nm and a width of ~4 nm ( Fig 7A , inset , right ) . Because the sample had no nucleic acid content , based on the UV absorbance , and the location of the internal density is different from that of encapsidated RNA [13] , we exclude the possibility of nucleic acid contamination during sample preparation . An image reconstruction of the dark particles was calculated to 13 . 8 Å resolution ( Figs 7B and 7C and S5 ) . We found a typical T = 4 HBV capsid with Impβ density at quasi-sixfolds and inside the capsid we observed a novel sphere of density . The capsid shell , after adjusting magnification , fit a 1QGT molecular model without modification ( S5 Fig ) . The external Impβ density at each quasi-sixfold was consistent with an Impβ atomic structure ( PDB entry [3LWW] ) that was circularly averaged about the respective axes . As with reconstructions at lower Impβ concentration , there was no evidence of Impβ density on the capsid fivefolds . The internal sphere of density could not be interpreted at a molecular level and was not stronger under fivefold or quasi-sixfold vertices , where CTDs are clustered . To ensure that dark particles were not a function of the ammonium formate buffers used in the experiment and CDMS , we obtained similar cryo-EM data for samples with more typical buffer conditions ( Fig 8 , 11 μM Cp183 dimer with 18 . 8 μM Impβ in 0 . 15 M NaCl , pH 7 . 4 ) . Given the CDMS data , it is likely that that dark particles represent capsids with a broad distribution of internalized Impβ molecules . If the internal mass was contributed by Impβ , the volume of the density ( between radii of 83 and 122 Å ) would accommodate a maximum of 48 closely packed Impβ molecules ( assuming a protein density of 1 . 43 g/cm3 ) , resulting in particles with up to 78 Impβ molecules . Furthermore , it is attractive to speculate that the broken and compromised particles observed in micrographs , relatively unusual for empty capsids , could be associated with very large numbers of importins . Nuclear transport of mature cores uses an Impα+Impβ complex yet in this study we show binding of empty HBV cores by Impβ . This led us to question the interaction of importins with unassembled core protein dimers . Because of the limited solubility of Cp183 in vitro , we adopted a different assay strategy . IBBs consist of multiple basic amino acids scattered over a 39 amino acid segment of protein [56] . This implies that Impβ binding to the empty capsids is based on exposure of the entire 34-residue CTD plus part of the assembly domain , which is supported by recent studies showing that trypsin cleavage of Cp183 capsids can involve CTD exposure beyond residue 150 [17] . To remove any ambiguity regarding the assembly state , we examined Impβ interaction with Cp expressed as a fusion protein with a GST ( Glutathione S-transferase ) at its N terminus , which interferes with capsid formation [57] . To directly demonstrate Impα and Impβ interaction with GST-Cp183 , we used a bead halo assay [58] , where sepharose beads coated with GST-Cp183 act as bait for fluorescent Impα and Impβ . Having confirmed GST ( and GST-Cp183 ) bound to the beads by Western blot , we quantified importin binding by confocal laser scan microscopy in the focal planes of the beads . As shown in Fig 9 , neither Impα nor Impβ bound to beads coated with GST alone . GST fused to the prototype NLS of SV40TAg interacted weakly with Impα alone but much stronger with Impα+Impβ . This finding is in agreement with Falces et al . [59] showing that Impβ enhances binding of Impα to the NLS of nucleoplasmin by nine-fold . A GST-IBB fusion protein bound Impβ directly but failed to interact with Impα alone . Addition of an Impα+Impβ mixture neither increased binding of Impα nor decreased binding of Impβ . GST-Cp183 coated beads exhibited a strong Impβ binding in the absence and presence of Impα but did not detectably bind Impα . GST-Cp183 thus showed the same binding pattern as GST-IBB . This suggests a difference in interaction of Impα+Impβ with unassembled Cp183 versus assembled capsid that bears more complete investigation . The Impβ interaction was dependent upon the CTD as a CTD deletion mutant also fused to GST , GST-Cp149 , did not interact with either importin .
In an infection or HBV expression system , core protein is overexpressed with respect to the amount needed for virion formation . Some of the resulting empty capsids are secreted from the host cell . As much as 99% of enveloped cores are empty [1 , 60] . In most infected patients , most core protein is localized to the nucleus [32–34] . Most nuclear core protein is unlikely to be derived from infecting HBV since only a few virions are taken up and hepatocytes are resistant to new infections after infection is established on the cellular level . The interaction of empty cores with nuclear transport proteins has been an open question . Mature HBV cores depend on Impα and Impβ for nuclear transport [8] . In this paper we observe that empty cores and free Cp183 bind to Impβ without the Impα adapter ( Figs 2 and 9 ) . HBV capsids undergo a structural changes upon genome maturation associated with capsid destabilization [61] and exposure of the last parts of the CTD . In mature capsids , this leads to Impα mediated interaction with Impβ [8] . Normally , immature RNA-filled and ssDNA-filled cores do not bind importins , though phosphorylation can modulate transient CTD exposure in RNA-filled cores presumably by attenuating interaction with nucleic acid [8 , 17] . For empty capsids we found that Impα was dispensable for Impβ binding . Though empty capsids could bind Impα+Impβ , unassembled GST-Cp183 exclusively bound Impβ . This implies a structural difference in the CTD presentation in empty and DNA-filled mature capsids . We propose that in empty capsids a larger fraction of the CTD is available than in nucleic acid-filled capsids , exposing the several arginine clusters needed to comprise an IBB . Thus , both Impα+Impβ and Impβ import paths have plausible but distinct roles in the HBV lifecycle . In addition to direct interaction of Impβ with empty capsids , two observations are peculiarly striking in this study: Impβ can destabilize capsids and Impβ can infiltrate HBV capsids . Apparently , Impβ provides an additional destabilizing influence , perhaps due to mechanical crowding at the quasi-sixfold vertex or by requiring interaction with a more extended segment of the CTD . Cryo-EM reconstructions showed that Impβ on the exterior of capsids is localized to the thirty quasi-sixfold vertices ( Figs 3 , 7 and 8 ) . The quasi-sixfold vertices have a hole large enough to allow CTDs to extrude from the capsid [16 , 17] and space to fit one Impβ . However titrations of empty capsid by Impβ and single molecule mass measurements by CDMS showed that as many as 96 Impβ molecules could be bound in a Cp183 complex , far more Impβ than could reasonably decorate the exterior of the capsid . Though in a different environment , similar infiltration of proteins into a closed capsid have been observed artificial capsids [62] . Broken capsids and dark particles together provide a basis for explaining the presence of more than 30 Impβ molecules per capsid , though the evidence is circumstantial . In cryo-EM of capsid samples prepared with high Impβ concentrations , we observed that the sample was enriched with Impβ only in broken particles and “dark particles” . On reconstruction , it was apparent that dark particles contained considerable internal density; the only sources for this density were Impβ or Cp183 that had been released from disrupted capsids . These particles are heterogeneous ( Fig 4A ) and those with the highest Impβ are likely to be broken , though only a small fraction , <5% of Cp183 , was dissociated to Impβ-associated dimer ( Fig 6 ) . Under the conditions tested , empty Cp183 capsids are at the edge of their stability under these solution conditions [63] . Capsid fragility and the intrinsic dynamic behavior of capsids , based on H-D exchange experiments [64] , are consistent with the hypothesis that capsids breathe and can transiently open to “swallow” bound Impβ . Cytoplasmic capsid destabilization may have important biological roles: ( i ) exposure of the contents of infecting capsids to facilitate partial deproteinization of the rcDNA ( i . e . proteolysis of the packaged reverse transcriptase ) [15] , ( ii ) dissociation of empty capsids and ( iii ) transport of dimers and/or intact empty capsids to nuclear pores . Nuclear core protein is associated with virus function including binding to viral nucleic acid [65–67] . Due to the preponderance of Impβ in the cytoplasm , Impβ-mediated destabilization of empty capsids should occur exclusively in this compartment , which is thus consistent with the accumulation of empty capsids in the nucleus [1 , 61 , 68] . The intracellular roles of empty cores are essentially unexplored . We speculate that empty capsids could be a storage pool for core protein bound for the nucleus and for construction of new virus , analogous to the role proposed for empty picornavirus capsids [69–71]; in this scenario , secretion of empty capsids would be homeostatic . Accumulation of capsids may modulate the interaction between infected cell and the immune system . We speculate that if HBV capsids were allowed to accumulate in the cytoplasm they could become subject to proteasomal degradation . This is seen with some core protein-directed antivirals [38] . Entry of the proteolytic fragments into the MHC class I pathway could then proceed via the ER and Golgi-bound TAP ( transporter associated with antigen processing ) , leading to core epitope exposure on the surface of hepatocytes . This hypothesis is in agreement with the observation that cytosolic capsids are associated with liver inflammation in infected patients [35 , 36] . The degree of hepatocyte cytoplasmic expression of hepatitis B core antigen correlates with the histologic activity of liver disease in the young patients with chronic hepatitis B infection [36 , 37] . Though a mechanistic connection has not been made , detection of hepatitis B virus antigens in liver tissue has been related to viral replication and histology in chronic hepatitis B infection [37] . Thus , a second path for removal of empty capsids could be important for establishing and maintaining chronic HBV infection . We must note the importance of single molecule techniques for analyzing Cp183 interaction with Impβ . Cryo-EM allowed visual examination of individual particles and their subsequent classification . CDMS revealed a far richer level of detail than would have been possible with bulk measurements . The ability to determine mass for each ion allows investigation of complex mixtures . Without CDMS , the titration analysis ( Fig 5 ) would have depended on an average ratio from a bulk technique ( e . g . SDS-PAGE analysis of SEC data ) , missing the heterogeneity , including the unexpectedly large numbers of Impβ for some core protein complexes . The distribution of charge states further indicated a structural flexibility and heterogeneity not seen in capsids without Impβ ( Fig 4B ) . This specific observation led to closer examination of capsid structure and provides insight into capsid dynamics . The fundamental observation of this paper is that HBV core protein dimer and empty HBV capsids interact with the Impβ . The recent observations of the prevalence of empty capsids in chronic infection [1 , 60] emphasizes the importance of understanding cellular responses to such capsids . From a physical perspective , the response of the capsid to Impβ offers new clues to capsid dynamics . Impβ entry into a capsid seems unlikely to proceed by complete dissociation and reassembly: if dissociation of Cp183 with two bound Impβ were thermodynamically favored we would expect that high concentrations of Impβ would exclusively lead to Impβ-decorated dimer . As complete dissociation was not observed , even after up to two days of incubation , we are led to the hypothesis that excess Impβ may decrease the energy barrier to transiently opening a capsid . The biological implications of accumulation of empty capsids , discussed above , range from distinct intracellular trafficking paths to immune modulation . In summary , further investigation of the interaction of empty , RNA-filled , and DNA-filled capsids with Impβ and/or Impα will provide additional insight into the intracellular trafficking .
Cp183 , P-Cp183 and Cp149 dimer and capsids were prepared as previously described [16 , 43 , 72 , 73] . Concentrations of dimer and empty capsids were quantified by absorbance using a per dimer extinction coefficient of ε280 = 60 , 900 M-1cm-1 ) [43] . For Cp183 or P-Cp183 capsids incorporating E . Coli RNA , the protein concentration was determined by SDS-PAGE and compared to a standard curve . The resulting protein had a calculated mass of 21 . 0 kDa . The Impβ clone was a kind gift of Dr . Lane Baker . His-tagged Impβ was expressed from a PET30a vector [74] . Lysate from IPTG-induced cells was loaded onto a His-Trap column , washed with at least 10 column volumes of 20 mM imidazole + 0 . 5 M NaCl at pH 7 . 4 and eluted with 0 . 5 M imidazole + 0 . 5 M NaCl at pH 7 . 4 . Peak fractions were desalted/dialyzed into 0 . 15 M NaCl 20mM Tris pH 7 . 4 and loaded onto a HiTrap SP HP column to which only contaminants bound . The Impβ was then loaded onto a HiTrap Q FF column and eluted by 2 M NaCl 20mM Tris pH 7 . 4 . The concentrated protein solution was dialyzed against 0 . 15 M NaCl , 10 mM DTT , 20 mM Tris-HCl at pH 7 . 4 , for storage at -20°C . Prior to binding experiments , Impβ stock solutions were further purified through a Superose 6 column with the running buffer 0 . 5 M NaCl , 10 mM DTT , 20 mM Tris-HCl at pH 7 . 4 ( S1 Fig ) . The resulting protein had a calculated mass of 97 . 0 kDa . To test for Impβ-binding , capsid samples were dialyzed into 0 . 5 M NaCl , 10 mM DTT , 20 mM Tris-HCl pH 7 . 4 , and then mixed with Impβ in the same buffer . The mixture was dialyzed overnight against 0 . 15 or 0 . 25 M NaCl , 10 mM DTT , 20 mM Tris-HCl pH 7 . 4 . CDMS samples were first dialyzed against 0 . 15 M NaCl , 10 mM DTT , 20 mM Tris-HCl pH 7 . 4 overnight , and then against 0 . 15 M ammonium formate pH 7 . 4 for a second day . For column assays , 150 μl samples were run through a Superose 6 column equilibrated in the final dialysis buffer at 0 . 5 ml/min . Throughout this process , all samples were kept at 4°C . In control experiments to identify the elution volume of free dimer , the running buffer included a non-denaturing 1 . 5 M guanidine hydrochloride not present in the experiments with Impβ [43] . For cryo-EM , Impβ-capsid complexes were prepared with initial concentrations of 7 . 9 μM Cp183 dimer ( in capsid form ) with 5 . 3 μM Impβ or 11 μM Cp183 dimer ( in capsid form ) with 18 . 8 μM Impβ . These complexes were assembled by overnight dialysis into 0 . 15 M NaCl , 10 mM DTT , 20 mM Tris-HCl at pH 7 . 4 . In some cases this was followed by dialysis into 0 . 15 M ammonium formate pH 7 . 4 . Samples were then concentrated by Nanosep 100K centrifugal device ( Pall ) to the suitable concentration for cryo-EM . All cryo-EM data were collected with a JEM-3200FS electron microscopy ( JEOL ) operated at 320 kV . Specimen preparation and EM operation followed procedures described elsewhere [13] . Briefly , a 4 μl drop of sample solution was applied to a glow-discharged holey carbon grid ( Quantifoil R2/2 ) or continuous carbon film coated grid ( EMS ) . The grids were vitrified in liquid ethane using a FEI Vitrobot . The sample preparation condition was set at 6°C , 100% humidity , and 4 s blotting time . Cryo-EM images were acquired using a Gatan Ultrascan 4000 CCD camera at the nominal magnifications of 40 , 000x or 80 , 000x , which are equal to 2 . 94 Å and 1 . 48 Å per pixel , respectively . The slit width for the energy filter was set at 20 eV . Detailed information for each dataset is listed in S1 Table . Image processing and 3D reconstructions were performed by the single particle approach with EMAN2 and AUTO3DEM software packages [75 , 76] . The quality and the defocus value of each micrograph were determined using CTFFIND3 [77] . Micrographs with significant drift or astigmatism were discarded . Particle images , representing different orientations in the 3D space , were boxed out from the micrograph using e2boxer . py . The images were then normalized and the initial model was built de novo for each dataset [78] . The initial model was then refined by the iterative process of alignment and icosahedral averaging . During processing , only phase information was applied to the contrast transfer function . This refinement process continued until no further improvement was achieved in the 3D model . The resolution of the final reconstruction was estimated based on a Fourier shell correlation ( FSC ) at 0 . 5 ( S6 Fig ) . The 3D reconstruction of dark particles prepared from Cp183 ( 11 μM dimer ) and Impβ ( 18 . 8 μM ) in NaCl was estimated using gold-standard FSC at 0 . 143 . The 3D reconstructions were visualized by RobEM and UCSF Chimera [79] . The molecular modeling analyses was performed by fitting the known atomic structures of HBV ( PDB code: 1QGT ) and Impβ ( PDB code: 3LWW ) into the cryo-EM density map using UCSF Chimera . The cryo-EM electron density maps have been deposited to EMDataBank . org . The accession numbers are EMD-3266 , EMD-3267 , EMD-3268 , EMD-3269 , EMD-3270 and EMD 3271 , respectively ( S2 Table ) . Sample preparation was the same as described for cryo-EM . In charge detection mass spectrometry ( CDMS ) the m/z and z of each ion are measured simultaneously . This allows the masses to be determined for complex mixtures of large ions that are not amenable to study by conventional mass spectrometry , where only the m/z is measured . The home-built charge detection mass spectrometer used in this study is described in detail elsewhere [80 , 81] . Briefly , ions are generated by nanoelectrospray and introduced into the instrument through a heated , stainless-steel capillary . The ions are first separated from the ambient gas flow by three differentially pumped regions containing RF ion guides . They are then accelerated to a kinetic energy of 100 eV/charge and focused into a dual hemispherical deflection analyzer that selects ions with a narrow band of kinetic energies . The energy-selected ions then pass into a modified cone trap , which contains the charge detection tube at its center . Trapped ions oscillate back and forth through the tube . When in the tube , the ion induces a charge which is detected by a charge-sensitive preamplifier . The output from the preamplifier is digitized and sent to a computer for analysis using a fast Fourier transform . The m/z of the trapped ion is determined from the frequency of the fundamental and the charge , z , is related to the magnitude of the fundamental . Multiplying m/z and z for each ion gives the mass . The masses are then binned to form a mass histogram . Only ions trapped for the entire trapping period ( ~94 ms ) are included . The HBV capsids are assembled in NaCl . Nonvolatile salts like NaCl suppress the ion signal from electrospray and lead to mass spectra with unresolved features due to extensive adduct formation [82] . A salt concentration greater than around 100mM is needed to maintain the integrity of the HBV capsids , so in order to obtain useful mass spectra it is necessary to replace the nonvolatile salt with a volatile one . Ammonium acetate is usually the salt of choice . However , in this work we found that ammonium formate provided better mass spectra and so after assembly in sodium chloride , the capsids were dialyzed in ammonium formate for the CDMS studies . The binding model used to analyze the titration of Cp183 by Impβ is based on a macroscopic dissociation constant that changes with the saturation of the target protein: Kd′ ( m ) =Kdmn−m+1 where Kd is the microscopic dissociation constant ( i . e . , the dissociation constant for a single site ) , n is the number of sites available , and m is the number of sites filled . E . coli-expressed GST proteins were purified using GSTrap FF columns ( GE Healthcare ) and dialyzed against 50 mM Tris HCl pH7 . 5 , 50 mM NaCl , 5% glycerol , 2mM DTT , 250 mM sucrose . Proteins included a full-length core , GST-Cp183 , and a C-terminal domain deletion , GST-Cp149 , which lacked all 34 residues of the CTD . E . coli-expressed importin α and β were purified using HisTrap FF columns ( GE Healthcare ) , and were labeled with Alexa Fluor 488 ( or 594 ) using Microscale Protein Labeling Kits according to the vendor ( Invitrogen ) . Further purification was realized using Zeba spin desalting columns 7K MWCO ( Thermo Fisher Scientific ) according to the vendor’s instructions . The GST-proteins were bound to glutathione sepharose beads for 2 h at 4°C while mixing on a rotation wheel . Beads were then subjected to 5 washes in washing buffer ( 1 x PBS , 500 mM NaCl , 1% ( w/v ) BSA ) . Then 2 . 5μg of importin α or/and 2 . 5μg importin β were added to the beads and incubated for 2 h at 4°C . The beads were washed 5 times with washing buffer followed by immediate analysis by microscopy using a SP5 Leica confocal microscope , 20 X objective with the standard settings for the respective fluorophore .
|
Viruses take advantage of host proteins . During infection , DNA-filled Hepatitis B Virus ( HBV ) cores are ferried to the nucleus by a complex of importin α and importin β; importinβ alone does not bind mature cores . However , a surprisingly large amount of the HBV core protein accumulates in nuclei . Here we show that both empty cores and free core protein can bind importin β alone . Using cryo-electron microscopy reconstructions we show that importin β associates with a putative importin β-binding motif , which is located on the interior of empty cores but can extrude through pores in the particle . Single-particle mass spectrometry , electron microscopy , and biochemical studies showed the importin β can destabilize empty particles . These results together demonstrate unsuspected interactions between the HBV core protein and the nuclear transport system . These interactions may have roles in regulating stability of empty capsids and transfer of HBV core protein to the nucleus .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"phosphorylation",
"medicine",
"and",
"health",
"sciences",
"protein",
"interactions",
"pathology",
"and",
"laboratory",
"medicine",
"chemical",
"compounds",
"pathogens",
"microbiology",
"viral",
"structure",
"hepatitis",
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] |
2016
|
Importin β Can Bind Hepatitis B Virus Core Protein and Empty Core-Like Particles and Induce Structural Changes
|
Whipworms ( Trichuris sp . ) are a globally distributed genus of parasitic helminths that infect a diversity of mammalian hosts . Molecular methods have successfully resolved porcine whipworm , Trichuris suis , from primate whipworm , T . trichiura . However , it remains unclear whether T . trichiura is a multi-host parasite capable of infecting a wide taxonomic breadth of primate hosts or a complex of host specific parasites that infect one or two closely related hosts . We examined the phylogenetic structure of whipworms in a multi-species community of non-human primates and humans in Western Uganda , using both traditional microscopy and molecular methods . A newly developed nested polymerase chain reaction ( PCR ) method applied to non-invasively collected fecal samples detected Trichuris with 100% sensitivity and 97% specificity relative to microscopy . Infection rates varied significantly among host species , from 13 . 3% in chimpanzees ( Pan troglodytes ) to 88 . 9% in olive baboons ( Papio anubis ) . Phylogenetic analyses based on nucleotide sequences of the Trichuris internal transcribed spacer regions 1 and 2 of ribosomal DNA revealed three co-circulating Trichuris groups . Notably , one group was detected only in humans , while another infected all screened host species , indicating that whipworms from this group are transmitted among wild primates and humans . Our results suggest that the host range of Trichuris varies by taxonomic group , with some groups showing host specificity , and others showing host generality . In particular , one Trichuris taxon should be considered a multi-host pathogen that is capable of infecting wild primates and humans . This challenges past assumptions about the host specificity of this and similar helminth parasites and raises concerns about animal and human health .
Parasites that infect multiple host species are of particular concern because they are more likely to emerge than single-host parasites [1]–[4] . Moreover , multi-host parasites are difficult to control because reservoir hosts may serve as sources of re-infection for other populations in which the parasite has been eliminated [5]–[7] . A number of ecological and evolutionary factors influence the range of hosts that a parasite can infect ( host specificity ) . Multi-host parasites of non-human primates ( hereafter primates ) have come under particular scrutiny , because physiological similarity ( due to relatedness ) between primates and humans increases the potential for zoonotic transmission . Indeed , phylogenetic relatedness between primate hosts is a stronger predictor of parasite sharing than geographic overlap [8] . Despite the probability of parasite sharing between primates and humans , only 20% of primate helminths ( parasitic worms ) are thought to infect humans [9] . Conversely , half of all primate helminths are thought to be specific to a single host species [9] , [10] . These observations suggest that , compared to other taxonomic groups of parasites , helminths have a lesser propensity for zoonotic transmission , perhaps because of their physical complexity , indirect life cycles , and long generation times [5] , [11] . Here we examine the host specificity of the whipworm genus Trichuris , a soil-transmitted helminth with a global distribution [12] . Trichuris trichiura is estimated to affect approximately 600 million people worldwide [13] , [14] , causing physical and mental growth retardation in children [12] , [15] . Trichuris infection results from ingestion of embryonated eggs shed into food , water , and soil [15] . Following ingestion , first-stage larva ( L1s ) hatch and move through the gastrointestinal tract where they develop in the caecum , molt into adults , and tunnel into the mucosa of the large intestine . After mating , female whipworms release eggs into feces . Eggs typically become infective after 20 days or more in the environment , where they are tolerant to desiccation and temperature extremes [16]–[20] . Currently , the Trichuris genus contains more than 20 described species that are generally specific to taxonomic groups of hosts [18] . Traditional parasitological research on the genus has focused on differentiating Trichuris trichiura , found in humans and primates , from Trichuris suis , found in pigs [21]–[25] . Morphologically , these two species are similar , and previous attempts to distinguish them based on variation in reproductive organ morphology were inconclusive because phenotypic plasticity could not be distinguished from genotypic differences [26] . The unsuitability of morphological characteristics for resolving differences between T . trichiura and T . suis made molecular methods a promising approach . Sequences from the internal transcribed spacer regions 1 and 2 ( ribosomal DNA ) from primate and porcine hosts suggest that T . trichiura and T . suis are two closely related but separate species [22] , a conclusion further supported by subsequent analyses of β tubulin gene sequences [23] . Morphological studies of Trichuris isolated from primates and humans conclude that the species infecting these hosts is the same , despite slight morphological variations that are distinguishable using scanning electron microscopy [21] . These results suggest that both primates and humans are infected with T . trichiura , which is capable of freely switching between primate and human hosts . Perhaps as a result of these findings , DNA sequences isolated from both primate and human hosts have been assumed to be T . trichiura by virtue of the host alone , and without the taxonomic scrutiny required to identify the parasite to species level . An empirical test of the assumption that primate and human Trichuris are identical used molecular methods to sequence DNA from Trichuris adults isolated from chacma baboons ( Papio ursinus ) and humans . Results revealed two distinct lineages of Trichuris in baboons [27] . The authors concluded that both lineages were transmissible between humans and baboons , and that T . trichiura , while perhaps not a single lineage , is a zoonotic parasite . Transmission between humans and primates is additionally supported by a molecular study of both β tubulin and ITS 2 gene regions isolated from both humans and baboons ( Papio anubis , P . hamadryas ) , where no genetic differentiation between host species was found [28] . In contrast , work on both ribosomal DNA and complete mitochondrial genome sequences has found evidence of host specificity within the Trichuris trichiura species complex [29] . These results led to the suggestion that Trichuris trichiura is not a single multi-host parasite , but rather a complex of host-specific lineages , each infecting distinct taxonomic groups of primates [29] . This suggestion is supported by molecular data from a small number of studies in non-human primate taxa [23] , [24] , [29]–[32] . In this study , we examine the phylogenetic structure of Trichuris in a host community comprised of wild primates and a nearby human population . Our study is based in and around Kibale National Park , Uganda , where Trichuris is known to infect several species [33]–[37] . Humans and primates in this region frequently overlap . For example , several species of primates raid crops , and people often enter the park to extract resources such as wood , food , and traditional medicines [38]–[41] . People and primates are exposed to the same physical environment during such events and can even interact directly [42] . Thus , the Kibale ecosystem is useful for examining the host specificity of parasites in a setting where cross-species transmission , including zoonotic transmission , is ecologically possible . Indeed , previous research in Kibale has demonstrated cryptic genetic lineages and cross-species transmission of another soil-transmitted helminth genus of primates and humans , the nodule worm ( Oesophogostomum spp . ) [43] . Our results herein demonstrate that the taxonomy and population structure of Trichuris is more complex than previously appreciated . Specifically , we identify cryptic Trichuris lineages , of which some infect multiple primate host species , including humans .
Prior to data collection , this research protocol was approved by the Uganda National Council for Science and Technology , the Uganda Wildlife Authority , and the Institutional Review Board and Animal Care and Use Committees of McGill University and the University of Wisconsin-Madison . Due to low literacy , a combination of written and oral consent following World Health Organization protocols was obtained from all participants or their parents/guardians . Consent was obtained by trained local field assistants and documented on IRB-approved forms . Samples were collected , processed and shipped according to the guidelines outlined by the Uganda National Council for Science and Technology , the Uganda Wildlife Authority , and the Public Health Agency of Canada . Kibale National Park ( 0°13′-0°41′N , 30°19′-30°32′ E ) is a 795 km2 mid-altitude rainforest located in Western Uganda . Kibale harbors nine species of diurnal primate that have been the focus of over four decades of research on primate ecology [44]–[47] , and infection , including zoonoses [42] , [48]–[54] . Kibale is surrounded by a dense human population of up to 600 people/km2 [55] . Sample collection occurred in and around Kanyawara , a North Western segment of the park ( see Ghai et al . [43] ) . Trichuris and other gastrointestinal helminths pass their eggs in the feces of their host , which offers an opportunity to conduct molecular analysis non-invasively by isolating DNA directly from parasite eggs . We collected primate fecal samples non-invasively from individuals in habituated primate groups . All primate groups were sampled only once to prevent pseudo-replication of individuals . Fecal samples were collected immediately after defecation and placed in sterile tubes . Seven diurnal monkey species were sampled: black-and-white colobus ( Colobus guereza ) , blue monkeys ( Cercopithecus mitis ) , grey-cheeked mangabeys ( Lophocebus albigena ) , l'hoest monkeys ( Cercopithecus lhoesti ) , olive baboons ( Papio anubis ) , red colobus ( Procolobus rufomitratus ) , and red-tailed guenons ( Cercopithecus ascanius ) . Chimpanzee ( Pan troglodytes ) samples were collected from two habituated groups in Kanyanchu , a section of Kibale approximately 15 km from Kanyawara . Human samples were collected from individuals between the ages of 2 and 70 residing in one of three villages within 5 km of the park boundary . Following informed consent , participants were provided with collection materials and instructions , and samples were retrieved within one day for processing . All samples underwent a procedure to concentrate nematode eggs while removing particles and debris . A modified ethyl acetate sedimentation method using one gram of feces was chosen due to its suitability for field conditions and its efficacy at recovering helminths eggs [56] . Details are provided elsewhere [43] . Samples were collected between May and August 2011 . We used microscopy to confirm infection status by identifying Trichuris eggs . Thin smears of sedimented feces were examined under 10X objective magnification on a Leica DM2500 light microscope . Length , width , color , and contents of eggs were recorded at 40X magnification , and images were captured with an Infinity1 CMOS digital microscope camera and Infinity Camera v . 6 . 2 . 0 software ( Lumenera Corporation , Ottawa , ON , Canada ) . Samples were considered positive for Trichuris when one or more eggs with the characteristic Trichuris “lemon” shape were identified . Samples were considered free of Trichuris only after the entire sediment was scanned and no Trichuris eggs were seen . All samples were examined by the same observer ( RRG ) to avoid inter-observer bias . DNA was extracted from 200 µl of sedimented feces preserved in RNAlater nucleotide stabilization solution ( Sigma-Aldrich , St . Louis , MO , USA ) using a ZR Fecal DNA MiniPrep Kit ( Zymo Research Corporation , Irvine , CA , USA ) , following manufacturer protocols . The parasite internal transcribed spacer region ( ITS ) 1 of the ribosomal DNA complex was amplified using polymerase chain reaction ( PCR ) with newly designed primers that were specific to the genus Trichuris . These primers were nested within the 18S ( small ribosomal subunit ) coding region and the 5 . 8S non-coding region ( see Romstad et al . [57] ) . Two forward primers ( external and internal ) were sited within conserved regions of 18S sequences of T . trichiura ( Genbank accession numbers: AB699091 , AB699090 , AB699092 , GQ352548 ) , T . suis ( accession no . AY851265 ) , T . vulpis ( accession no . GQ352558 ) , and T . muris ( accession no . AF036637 ) . Other enoplean nematodes ( Romanomermis , accession no . AY146544; Agamermis , accession no . DQ628908; Capillaria , accession no . EU004822; and Trichinella , accession no's . U60231 and AY487254 ) , as well as representative genera likely to occur in Kibale ( Caenorhabditis , accession no . JN636068; Strongyloides , accession no . M84229 ) were included in primer design alignments to ensure primers were specific to Trichuris . The two generated primers were: External_Trichuris-1417F ( 5′-AGGGACCAGCGACACTTTC-3′ ) and Internal_Trichuris-1567F ( 5′-GTTCTCGTGACTGGGAC-3′ ) . Reverse primers that were also specific for the genus Trichuris were designed in a similar manner , using aligned 5 . 8S sequences from T . trichiura ( accession no's . GQ301555 , GQ301554 , KC877992 ) , T . suis ( accession no's . JF690951 , AM993015 ) , T . sp ( accession no's . JF690940-JF690952 , HQ844233 ) , T . ovis ( accession no . JX218218 ) , T . muris ( accession no . FN543201 ) , T . arvicolae ( accession no . FR849687 ) , and T . discolor ( accession no . JX281223 ) . Other enoplean nematodes ( Trichinella , accession no's . AF342803 , KC006431 ) and representative genera likely to be found in Kibale ( Oesophagostomum , accession no's . AJ619979 and AB821014; Strongyloides , accession no . EF653265; Xiphinema , accession no . HM990158 ) were also included . The reverse primers generated were: ExternalITS1_Trichuris-2505R ( 5′-GAGTGTCACGTCGTTCTTCAAC-3′ ) and InternalITS1_Trichuris-2462R ( 5′-CTACGAGCCAAGTGATCC-3′ ) . External primers generated amplicons of approximately 1088 bp expected size; internal primers generated amplicons of 895 bp expected size . The ITS 2 region was amplified using primers nested within the 5 . 8S non-coding and 28S ( large ribosomal subunit ) coding regions . The ITS 1 internal reverse primer described above ( InternalITS1_Trichuris-2462R ) was reversed and used as the forward external primer ( ExternalITS2_Trichuris-2462F: 5′-GGATCACTTGGCTCGTAG-3′ ) . The internal primer , InternalITS2_Trichuris-2560F ( 5′-CTTGAATACTTTGAACGCACATTG-3′ ) was designed using the aligned 5 . 8S sequences described above and was also specific to the genus Trichuris . A previously published , conserved primer NC2 ( 5′-TTAGTTTCTTTTCCTCCGCT-3′ ) was used as the reverse primer in both external and internal reactions [58] . External primers generated amplicons of approximately 584 bp expected size; internal primers generated amplicons of 486 bp expected size . The efficacy of the protocols designed for amplifying only Trichuris ITS 1 and 2 regions was tested using dilutions of a positive control ( adult T . vulpis isolated by necropsy from an infected canine at Cornell University ) , and by implementing the protocol on samples known to contain infections with multiple parasite genera . The protocol was found to be 100% accurate at detecting only Trichuris even among mixed infections . ITS 1 external PCR was performed in 25 µL volumes using the FailSafe System ( Epicentre Biotenchnologies , Madison , WI , USA ) . Reactions contained 1X FailSafe PCR PreMix with Buffer C ( containing dNTPs and MgCl2 ) , 1 Unit of FailSafe Enzyme Mix , 2 . 5 picomoles of each primer ( ExternalITS1_Trichuris-1417F and ExternalITS1_Trichuris-2505R ) , and 1 µL of template ( extracted DNA from sedimented feces ) . Reactions were cycled in a Bio-Rad CFX96 thermocycler ( Bio-Rad Laboratories , Hercules , CA , USA ) with the following temperature profile: 94°C for 60 sec; 40 cycles of 94°C for 60 sec , 61°C for 30 sec , 72°C for 75 sec; and a final extension at 72°C for 10 min . Internal PCR was performed in 25 µL volumes using the DyNAzyme DNA Polymerase Kit ( Thermo Scientific , Asheville , NC , USA ) with reactions containing 0 . 5 Units of DyNAzyme I DNA Polymerase , 1X Buffer containing 1 . 5 mM MgCl2 , 2 . 5 picomoles of each primer ( InternalITS1_Trichuris-1567F and InternalITS1_Trichuris-2462R ) ) , 0 . 5 µL dNTPs , and 1 µL of template ( product of the external PCR reaction ) . Reactions were cycled according to the following temperature profile: 94°C for 60 sec; 35 cycles of 94°C for 30 sec , 55°C for 30 sec , 72°C for 75 sec; and a final extension at 72°C for 10 min . ITS 2 PCR used the same reagents as the ITS 1 external and internal reactions described above , with external reactions using ExternalITS2_Trichuris-2462F and NC2 primers , and internal reactions using InternalITS2_Trichuris-2560F and NC2 primers . Both external and internal reactions were cycled according to the following temperature profile: 94°C for 60 sec; 35 cycles of 94°C for 30 sec , 55°C for 30 sec , 72°C for 60 sec; and a final extension at 72°C for 10 min . PCR products were electrophoresed on 1% agarose gels stained with ethidium bromide . Amplicons were excised and purified using the Zymoclean Gel DNA Recovery Kit ( Zymo Research Corporation , Irvine , CA , USA ) according to the manufacturer's instructions . ITS 1 and 2 products were Sanger sequenced in both directions using primers InternalITS1_Trichuris-1567F and InternalITS1_Trichuris-2462R for ITS 1 and InternalITS2_Trichuris-2560F and NC2 for ITS 2 . Sequencing was performed on ABI 3730xl DNA Analyzers ( Applied Biosystems , Grand Island , NY , USA ) at the University of Wisconsin-Madison Biotechnology Center DNA Sequencing Facility . Sequences were hand-edited and assembled using Sequencher v . 4 . 9 ( Gene Codes Corporation , Ann Arbor , MI , USA ) with reference to published sequences . Generation of unambiguous sequences required repeat PCR and re-sequencing on three occasions . Newly generated sequences were deposited in GenBank , under accession numbers KJ588071-KJ588132 ( 18S , ITS 1 ) and KJ588133-KJ588167 ( 5 . 8S , ITS 2 , 28S ) ; see Supplementary Table S1 . The ratio of Trichuris egg length to width was calculated and compared among groups using Kruskal-Wallis tests and Dunn's multiple comparison post-tests in Prism6 ( GraphPad Software Inc . , La Jolia , CA , USA ) to assess shape differences between different groups of Trichuris . To compare the diagnostic performance of microscopy with newly designed PCR methods , sensitivity ( i . e . , the proportion of samples correctly identified as positive by PCR as compared to microscopy ) and specificity ( i . e . , the proportion of samples correctly identified as negative by PCR ) were calculated using MedCalc v . 12 . 5 . 0 ( MedCalc Software , Ostend , Belgium ) . Prevalence of Trichuris infection was calculated as the total number of positive samples divided by the total number of samples , with 95% confidence intervals calculated using the modified Wald method [59] . Differences in prevalence among host species were evaluated using Fisher's exact tests implemented in the program Quantitative Parasitology v . 3 . 0 [60] . Due to the number and varying sizes of indels among DNA sequences , we aligned sequences using webPRANK , a phylogeny-aware progressive alignment tool that has been shown to outperform other methods in indel-rich alignment [61] , [62] . Aligned sequences were trimmed to consistent length and missing data were coded as “ ? ” in BioEdit v . 7 . 2 . 5 [63] . Samples for which both ITS 1 and 2 were generated were concatenated in Sequence Matrix v . 1 . 7 . 8 [64] . All sequences were subjected to Gblocks treatment to remove regions of ambiguous alignment using the following parameters: “Maximum number of contiguous non-conserved positions” = 100 , “Minimum length of a block” = 4 , and “Allowed gap positions” = half [65] . Models of sequence evolution for each gene were selected using the MrModelTest v . 2 executable in PAUP* v . 4 [66] , [67] . We reconstructed phylogenetic relationships using Bayesian methods and HKY+I ( ITS 1 ) and HKY ( ITS 2 ) models , implemented in MrBayes v . 3 . 2 . 2 through the CIPRES Science Gateway [68] , [69] . Phylogenetic analyses were conducted on concatenated , Gblocks treated ITS 1 and 2 sequences . Four chains were run for 1×107 MCMC generations , sampling every 1000th generation with a diagnostic frequency of every 5000th generation . MCMC runs continued until a standard deviation of split frequency value of 0 . 01 was reached . Convergence was confirmed when all substitution model parameters reached a potential scale reduction factor value of 1 , and was visually assessed using Tracer v . 1 . 6 . The first 10% of runs were discarded as burn-in and Bayesian posterior probabilities were calculated from the remaining trees . Genetic divergence among Trichuris populations was estimated as percent nucleotide-level sequence identity , calculated as the uncorrected pairwise proportion of nucleotides ( p-distance ) in MEGA v . 5 . 1 with 1000 bootstrap replicates [70] . Analysis of molecular variance ( AMOVA ) was used to partition Trichuris genetic diversity into within host and between host components [71] in GenAlEx v . 6 . 5 [72] . Pairwise population differentiation values ( PhiPT; an analogue of FST ) , were also calculated in GenAlEx . To assess the relationship between host phylogeny and parasite phylogeny , mantel tests were used to compare pairwise distance matrices of phylogenetic branch lengths between primate hosts and p-distance among parasite clades ( calculated as described above ) using the ape package [73] in the statistical programming language R ( Development-Team 2008 ) .
We collected 282 samples from primates and 36 samples from humans , for a total of 318 samples . Of these , microscopy classified 104 samples as Trichuris-positive , making the community-wide prevalence of infection by microscopy 32 . 7% ( Table 1 ) . Eggs varied considerably in length ( 50–76 µm ) , and width ( 26–30 µm ) , but length-to-width ratios did not differ significantly among parasite clades ( see below ) or host species ( Kruskall-Wallis test , P>0 . 05; Figure 1 ) . PCR of ITS 1 and ITS 2 generated single , clear bands of expected size . PCR of ITS 1 and 2 generated identical results and were therefore considered together for the purposes of evaluating the diagnostic performance of PCR . PCR correctly classified all samples that were positive for Trichuris by microscopy . In addition , PCR classified five samples as positive for Trichuris that were negative by microscopy . Thus , the sensitivity of our new PCR assay was 100% ( 95% C . I . 96 . 5%–100 . 0% ) and the specificity was 97 . 7% ( 95% C . I . 94 . 6%–99 . 2% ) , suggesting that our new PCR assays of ITS 1 and 2 are both highly accurate . Prevalence varied significantly by species , ( χ2 = 62 . 99 , df = 8 , P<0 . 0001 ) , with chimpanzees ( 13 . 3% ) and grey-cheeked mangabeys ( 14 . 3% ) having the lowest prevalence , and olive baboons ( 88 . 9% ) the highest ( Table 1 ) . Of the 108 positive samples , 74 samples were selected for sequencing to represent the widest possible range of host species and , to the greatest extent possible , to equalize sequencing effort among host species . Because preliminary results indicated that ITS 1 provided greater phylogenetic resolution than ITS 2 , 62 sequences for ITS 1 and 35 sequences for ITS 2 were ultimately generated ( Supplementary Table S1 ) . In samples where both ITS 1 and ITS 2 sequences were generated , sequences were concatenated and gaps were coded as missing data . The final alignment length of Gblock treated and concatenated ITS 1 and ITS 2 sequences was 1083 characters . Phylogenetic analysis resolved Trichuris into three groups , which , for convenience , we designate Groups 1 , 2 and 3 in Figure 2 . Group 1 contained two samples from humans that were 98 . 2% identical to each other and that most closely matched published sequences from Chacma baboons ( Papio hamadryas ursinus ) from South Africa ( Genbank accession numbers GQ301551-2 [27] . This clade , along with a sequences from humans in Uganda [23] ( Genbank accession numbers JN181837 , JN181845 ) , are sister to the Trichuris in-group and are the most genetically divergent lineage , sharing between 71 . 7% and 88 . 1% nucleotide similarity with other T . trichiura clades ( Figure 2 ) . Group 2 contained sequences from four black-and-white colobus and one red colobus that shared 100% nucleotide identity , and were most closely related to published Trichuris sequences from another subspecies of black-and-white colobus ( Colobus guereza kikuyuensis ) and yellow-cheeked gibbons ( Nomascus gabriellae ) from a zoo in Spain [22] . Finally , Group 3 contained 59 sequences from all seven species of primate host and eight humans sampled in this study . This group shared 99 . 3% nucleotide sequence identity and clustered most closely with published sequences from humans in Cameroon ( accession number GQ301555 ) , and more distantly with Chacma baboons in South Africa from the same study ( accession number ( GQ301554 ) [27] . All three sequences representing T . suis clustered within the T . trichiura species complex , and were most distinct ( excluding outgroups ) from Group 1 ( 66 . 9% nucleotide similarity ) , and most similar to Group 2 ( 88 . 5% nucleotide similarity ) . Samples from human hosts identified in this study fell within Groups 1 and 3 . Human-derived Trichuris sequences were most similar to those from grey-cheeked mangabey ( 95 . 2% similarity ) and chimpanzees ( 95 . 1% identity ) , and most dissimilar to those of black-and-white colobus ( 91 . 2% identity; Table 2 ) . When within-group sequence variation was held constant in PhiPT analysis , sequences from black-and-white colobus and olive baboons were significantly different , but sequences from other species pairs were not ( Table 2 ) . Mantel tests comparing host phylogeny and parasite p-distances between clades were not significant ( Z-statistic = 43 . 37 , p = 0 . 305 ) . AMOVA revealed that 98% of Trichuris sequence-level variation was contained within host species , with only 2% of sequence-level variation apportioned between host species .
We investigated the taxonomy and phylogenetic structure of the whipworm genus Trichuris in a wild primate community and a nearby human population in Uganda . The overall prevalence of infection was 34% , but this varied significantly among host species , with the lowest prevalence in chimpanzees ( 13 . 3% ) and the highest prevalence in olive baboons ( 88 . 9% ) . Research in Gombe National Park , Tanzania , where these two species also overlap , found similar results , with chimpanzees having 5% infection prevalence and baboons 66% [74] . Averaging across sites in Tanzania and Senegal , another study found prevalences of 4 . 5% and 35% in chimpanzees and baboons , respectively . Interestingly , Trichuris is one of the few parasites with consistently higher prevalence in baboons than in chimpanzees [75] . In an attempt to explain interspecific differences in prevalence , we conducted a phylogenetic-least-squared regression to explore correlations between host traits ( terrestriality , home range , group size , time spent in polyspecific associations , body mass , and daily travel distance ) and prevalence ( not shown ) , but found no significant relationships . It therefore remains unclear why Trichuris prevalence varies significantly among sympatric primate hosts . In humans , our results indicate a prevalence of 30 . 6% by PCR . Previous research in Uganda has estimated prevalence to be between 12 . 9 and 28% using microscopy; however , this is among school-aged children , where the frequency of Trichuris infection is high [76] , [77] . Our estimate of 30 . 6% infection in a human community containing individuals of multiple ages suggests that this region of Uganda has a generally high rate of infection . Poor access to latrines , earthen flooring in houses , and large family sizes are likely contributing factors [78] , although improved accuracy of our methods relative to others may also help explain this difference . Our phylogenetic analysis revealed that Trichuris sequences from the Kibale primate community and neighboring human population sorted into three groups . Group 1 contained two sequences from humans and clustered closely with sequences derived from Chacma baboons [27] . Interestingly , these sequences were designated as part of the most phylogenetically distinct T . trichiura clade , most distant from T . suis [27] . The authors of these sequences therefore refrained from designating this clade T . trichiura [27] . Our results support the conclusion that this Trichuris clade represents a separate species , since our phylogenetic analysis placed Group 1 and associated published reference sequences as sister to all other Trichuris in-groups . Our p-distance analyses similarly estimate the maximum dissimilarity between Group 1 ( and associated published reference sequences ) and all other in-groups to be 33 . 1% , which is nearly twice that between previously described sequences of T . trichiura and T . suis , which are recognised as taxonomically distinct species . Group 1 sequences and GQ301551-2 were sister to sequences that were part of study that sought to identify genetic similarity between T . trichiura and T . suis derived from humans and pigs living in close proximity [23] . In the latter study , two distinct genotypes of human-derived Trichuris were defined , which they designated type 1 and type 2 [23] . Our sequences cluster with their type 1 genotype ( represented by JN181860 in Figure 2 ) , the clade more distantly related to T . suis . Despite screening the entire diurnal primate community , we detected Group 1 only in humans . However , a similar genotype has been found elsewhere in baboons [27] , suggesting that the Group 1 lineage may have a broader host range than documented in our study , perhaps indicating a potential for infrequent cross-species transmission . In contrast to Trichuris Group 1 , we detected Trichuris Group 3 in every host species sampled , including humans . This result suggests that Group 3 , including published reference sequences , represents a multi-host lineage capable of infecting multiple primate hosts , including humans . Our population analyses support these results , in that only 2% of overall Trichuris genetic variation is apportioned between host species . Group 2 , containing sequences derived from black-and-white colobus and red colobus , also appears to be a distinct lineage . This clade is most closely related to T . trichiura from other primates , namely gibbons and another subspecies of black-and-white colobus [22] . This Trichuris lineage may have an intermediate host range compared to Groups 1 and 3 , given that all samples save one were derived from colobus monkeys . The one sample that was not derived from colobines ( gibbon ) was collected from a zoo , and may therefore reflect transmission outside of a natural setting . Additional sampling and sequencing would help clarify the host range of this Trichuris taxon . We note that rDNA occurs in multiple copies , and this study does not attempt to quantify intraspecific variation or mixed lineage infections . Our data therefore reflect a minimum conservative estimate of parasite genetic variation . Similarly , we note that our data could reflect variation among paralogs within and among infections , although we found no direct evidence for this . However , such intra-individual diversity is almost certainly lower than diversity between hosts , such that it is unlikely to have confounded the overall patterns we describe . In our study area , several primates frequently raid crops , with the most common offenders being baboons , red tailed guenons , and chimpanzees [39] , [79] , [80] . Such interactions facilitate the transmission of gastrointestinal bacteria , protozoa and helminths in the Kibale system [43] , [49] , [52] , [53] , [81] , [82] . Although these interactions make cross-species transmission ecologically plausible , it remains unclear why one Trichuris lineage appears able to cross species boundaries with apparent ease , yet another other clades show host affinity ( Group 1 ) . In conclusion , our phylogenetic analysis suggests that Trichuris is not a single species , but a species complex ( see also Nissen et al . [23] and Liu et al . [29] ) of co-circulating clades that includes T . suis . Despite being sympatric , different clades appear to have different host affinity . Group 1 was specific to humans in our study , Group 2 has an intermediate host range , and Group 3 appears capable of infecting all primates sampled , including humans . While our analyses do not indicate whether Group 3 Trichuris is transmitted from primates to humans or vice versa , they do show that certain lineages within the Trichuris taxonomic complex should be considered multi-host pathogens , at least within the order Primates . Our results also demonstrate that Trichuris is among the 20% of helminths capable of cross-infecting primates and humans . Taxonomic and epidemiological studies of other soil-transmitted helminths in wild primates , many of which cause “neglected” tropical diseases [83] , may reveal yet more helminth taxa to be multi-host pathogens . If so , this would challenge past assumptions about the host specificity of helminth parasites while raising new concerns about global human and animal health .
|
Whipworms are a group of gastrointestinal worms that are both common and globally distributed . These parasites are known to stunt development , especially in school-aged children , and therefore hinder economic , social , and intellectual growth . Unfortunately , research on whipworms has lagged behind its effects , at least in part because this parasite infects the world's poorest populations . Currently , a single species of whipworm is assumed capable of infecting both humans and non-human primates . In this study , we tested this assumption by collecting fecal samples from humans and overlapping non-human primate populations containing monkeys and chimpanzees in Western Uganda . Using molecular analyses , we examined patterns of genetic similarity between human and nonhuman primate whipworms . We identified three genetically distinct groups of whipworms that could not be distinguished by microscopic examination of their eggs . One of these groups was found in all nine species of primates examined , including humans . These findings suggest that some varieties of whipworms are indeed transmissible between humans and non-human primates , which raises concerns for both human health and conservation .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"invertebrates",
"trichuris",
"parasitology",
"nematoda",
"biology",
"and",
"life",
"sciences",
"intestinal",
"parasites",
"animals",
"organisms"
] |
2014
|
Hidden Population Structure and Cross-species Transmission of Whipworms (Trichuris sp.) in Humans and Non-human Primates in Uganda
|
We elucidate the mechanisms that lead to population shifts in the conformational states of calcium-loaded calmodulin ( Ca2+-CaM ) . We design extensive molecular dynamics simulations to classify the effects that are responsible for adopting occupied conformations available in the ensemble of NMR structures . Electrostatic interactions amongst the different regions of the protein and with its vicinal water are herein mediated by lowering the ionic strength or the pH . Amino acid E31 , which is one of the few charged residues whose ionization state is highly sensitive to pH differences in the physiological range , proves to be distinctive in its control of population shifts . E31A mutation at low ionic strength results in a distinct change from an extended to a compact Ca2+-CaM conformation within tens of nanoseconds , that otherwise occur on the time scales of microseconds . The kinked linker found in this particular compact form is observed in many of the target-bound forms of Ca2+-CaM , increasing the binding affinity . This mutation is unique in controlling C-lobe dynamics by affecting the fluctuations between the EF-hand motif helices . We also monitor the effect of the ionic strength on the conformational multiplicity of Ca2+-CaM . By lowering the ionic strength , the tendency of nonspecific anions in water to accumulate near the protein surface increases , especially in the vicinity of the linker . The change in the distribution of ions in the vicinal layer of water allows N- and C- lobes to span a wide variety of relative orientations that are otherwise not observed at physiological ionic strength . E31 protonation restores the conformations associated with physiological environmental conditions even at low ionic strength .
Protein behavior in solution may be manipulated and controlled through tailored structural perturbations [1] and rational control of the solution conditions [2] http://www . pnas . org/content/109/50/E3454 . full . pdfhtml . In the living cell , proteins adapt to particular subcellular compartments which pose different environmental variables such as pH and ionic strength ( IS ) , adapting their biophysical characteristics to tolerate pH fluctuations that are caused by cellular function [3] . Furthermore , proteins interact with many other biological macromolecules while they are transferred from one compartment to another , with subtle control over protonation and pK changes upon binding to other proteins and ligands [4] , [5] . Interactions with the environment and other molecules are closely related to local anisotropy and dynamical heterogeneity of proteins [6] . The dynamics may be electrostatically guided , perhaps through long-range electrostatic interactions that select and bring interacting partners together , steering the protein to alternative conformations [7] . The main perturbation effect of the long-range electrostatic interactions is manifested on the acidic/basic groups in the protein which can be charged or neutral in relation to their conformation dependent pKa values [8] . Interacting with other molecules and changes in the environmental variables such as subcellular localization can induce shifts in ionization states of charged groups on a protein by proton uptake/release . Such changes facilitate the protein to span a large conformational space and enable it to participate in diverse interaction scenarios . Any in depth understanding developed through studying the conformational changes in proteins induced by shifts in the charge states of select amino acids would contribute to our knowledge base on diverse functionality observed in promiscuous proteins [9] . In this study , we focus on the conformation-related effects of introducing perturbations on charged group ( s ) of calmodulin ( CaM ) . CaM is a notorious example among proteins having the ability to change conformation upon binding to diverse ligands [10] , [11] . It was shown that negatively charged side chains in calcium loaded CaM ( Ca2+-CaM ) are attracted to positively charged residues in many of its targets [12] . Another study showed that Ca2+-CaM changes conformation when introduced to a solvent at low pH and low ionic strength [13] . Also , it was proposed that electrostatic interactions between acidic residues in CaM contribute to determining the most populated conformation under varying solution conditions [13] . Previously , we have studied the conformational changes in Ca2+-CaM [14] , ferric binding protein [15] and a set of 25 proteins that display a variety of conformational motions upon ligand binding ( e . g . , shear , hinge , allosteric ) [16] using the perturbation response scanning method . This coarse grained methodology is based on the assumption that the equilibrium fluctuations at a given local free energy minimum of the protein possess information on other viable conformations when an external force is applied [15]–[17] . Our study on CaM determined key residues that lead to the experimentally observed conformational changes upon application of force in specific directions [14] . Several different servers ( H++ [18] , propKa 2 . 0 [19] , pKd [20] and PHEMTO [21] , [22] ) showed that the pKa of E31 value is upshifted; furthermore , the equivalent position in Calbindin was measured to have pKa of 6 . 5 [23] . In a follow-up study , we focused on residues with upshifted pKa values and we made a systematic study of the dynamics of Ca2+-CaM on time scales up to 200 ns for three separate initial configurations; extended form , compact form and extended structure with 10 protonated residues ( 9 acidic residues and a histidine ) [24] . We found that Ca2+-CaM with 10 protonated residues undergoes a large conformational shift from the extended structure to a relatively compact form on the time scale of tens of nanoseconds . The latter was compatible with other structures reported in a nuclear magnetic resonance ( NMR ) ensemble of CaM [25] . Experimental work investigating dynamical behavior of Ca2+-CaM has shown that it occupies a number of hierarchical set of substates even in the crystal form [26] . Dynamical information obtained from fluorescence resonance energy transfer ( FRET ) experiments measuring the distance distributions between labeled sites illustrate that at least two conformations exist in solution under physiological conditions [27] . More recently , pseudo contact shifts and residual dipolar couplings of the C-terminal domain obtained using NMR [28] revealed neither the dumbbell shaped conformation observed in early crystal structures of the molecule [29] , nor the compact conformation determined later on [30] exist in significant proportions in solution . Ca2+-CaM is identified as a protein which populates multiple conformations [28] , [31] . A shift between the distribution of populations is induced by changing environmental conditions such as pH , Ca2+ concentrations and ionic strength [13] , [27] . Each of these manipulated properties has effects on the charged groups of Ca2+-CaM . The presence of multiple conformations is a physical property of Ca2+-CaM , and it is likely that the heterogeneity of structure is at least partially responsible for the ability of Ca2+-CaM to recognize diverse targets . Squier and coworkers have suggested that association of the C-terminal domain of CaM with a target may disrupt a structurally important hydrogen bond involving the central linker , facilitating formation of a compact binding conformation of Ca2+-CaM [32] . More recently , through rather benign mutations such as E47D , they have determined noninterfacial residues important for molecular recognition through indirect effects – an increase in fluctuations stabilizes the bound state [33] . It was further hypothesized that pH and ionic strength dependent shifts in the populations of conformational substates result from changes in electrostatic interactions in the central linker [13] , [27] . For example , the shift in favor of the more compact conformation at reduced pH may result from the loss of electrostatic interactions that serve as spacers at neutral pH . This hypothesis is corroborated by inspection of the proximity of side chains of glutamic and aspartic acid residues surrounding the hinge region in the compact Ca2+-CaM crystal structure [30] . In this manuscript , we report extensive molecular dynamics ( MD ) simulations of fully solvated , extended and compact Ca2+-CaM under different perturbation scenarios , with focus on E31 . We have previously shown that E31 is located in a unique position to manipulate the overall structure; it also has an upshifted pKa into the physiological range and there are several experiments implicating its involvement in signaling coordination between the two lobes ( see [14] and references cited therein ) . Structural perturbations are introduced as either E31A mutation or its protonation . We also perturb environmental factors such as pH and IS . We analyze the structural dynamics through identifiers based on reduced degrees of freedom defined specifically for Ca2+-CaM . Key events leading to or preventing conformational change are discussed . We elaborate on the events occurring along the path sampled between different conformational states identified by MD simulations and we evaluate the effect of charge balance on the conformations . The molecular mechanisms that lead to the observed effects , their relationship to the experimental data , and the consequences of the observations that enhance our understanding of the dynamics and function of Ca2+- CaM are outlined .
CaM consists of 148 amino acids made up of the N-lobe ( residues 1–68 ) , the C-lobe ( residues 92 to 148 ) and a linker which is helical in many , but not all , of the reported structures . Each lobe in CaM has two helix-loop-helix ( EF-hand motif ) calcium binding sites connected by unstructured sequences . Structured elements include helices I ( residues 5–17 ) , II ( residues 30–39 ) , III ( residues 46–54 ) , IV ( residues 69–73 ) , V ( residues 83–91 ) , VI ( residues 101–110 ) , VII ( residues 119–129 ) , and VIII ( residues 137–144 ) . Ca2+ coordinating residues in each of the four EF-hands are D20-D22-D24-E31 in loop I , D56-D58-N60-E67 in loop II , D93-D95-N97-E104 in loop III , and D129-D131-D133-E140 in loop IV . All MD simulations reported in this work include the four Ca2+ ions . The existing X-ray structures of Ca2+-loaded , peptide free calmodulin ( Ca2+-CaM ) are either in an extended or a compact form . There are many examples for the extended form in the protein data bank ( PDB ) and we utilize that with PDB code 3CLN whereby the coordinates of the first four and the last residue are not reported [29] . The compact form is represented by the 1PRW coded structure [30] , and has a bent linker as do many ligand bound Ca+2-CaM conformations present in the PDB . These particular structures have been determined at 2 . 2 and 1 . 7 Å resolution , respectively , and were both crystallized at low pH conditions in the range of 5–6 , by growth in water-organic mixture compounds . We have previously reported the RMSD comparison for the overall structure as well as the N- and C-lobes of various x-ray structures , including 3CLN , 1PRW and five ligand bound forms [14] . An ensemble of Ca2+-CaM structures have also been reported ( PDB code 2K0E ) [25] by using experimental NMR order parameters ( S2 ) together with interproton distances derived from nuclear Overhauser effects ( NOEs ) as restraints in MD simulations using RDC-refined solution structure of Ca2+-CaM . The IS of the experimental setup is 10 mM and the pH is 7 ( the conditions in ref . [25] are the same as in ref . [34]; personal communication ) . The ensemble has 160 structures and reveals that Ca2+-CaM state samples multitude of conformations including , but not limited to , the compact and extended ones . In particular , unlike in the X-ray structures , there also exist compact conformers where the linker is not bent , as we pointed out in our previous study [24] . Throughout this work , an efficient approach to distinguish between the different conformations of CaM proves to be useful: We define two low resolution degrees of freedom projecting the 3N-dimensional conformational space into a visually tractable two-dimensional one . These are the linker end-to-end distance ( l ) and torsion angle ( φ ) . The former is defined as the distance between the Cα atoms of the two outermost residues of the linker , residues 69 and 91 . The latter is the torsion angle defined by four points: the center of mass of the N-lobe ( residues 5 to 68 ) , linker beginning and end points ( Cα atoms of residues 69 and 91 ) , the center of mass of the C-lobe ( residues 92 to 147 ) . These points are schematically shown in Figure 1 . Six sets of simulations were performed with various initial starting conditions . Simulations are summarized in Table 1; IS values reported correspond to the equilibrated box dimensions . For some systems , we have performed independent runs to check the reproducibility of the results . Each condition has at least 150 ns of total sampling time . We prolong the simulation in case there are substantial changes in the relative positioning of the two lobes and/or the length of the linker , measured by the region sampled on the ( l , φ ) plane described in the previous subsection . The details of each simulation are as follows; the label for each type of simulation is indicated in parentheses and will be used throughout the text: ( ) Initial coordinates are taken from the extended 3CLN pdb coded structure and all residues are assigned their standard protonation states to study the conformational dynamics of extended form in solution . 45 Na+ and 30 Cl- ions are added to attain IS = 150 mM at the physiological range . There is a one MD run of 150 ns and an additional control run of 50 ns . ( ) Initial coordinates are taken from the compact 1PRW and all residues are assigned their physiological protonation states to study the dynamics of compact structure in solution . The system is neutralized by 15 Na+ ions . Due to the smaller box dimensions formed for this more compact structure , this protocol leads to IS = 161 mM at the physiological range . There are two runs of 200 ns each for this system . ( ) Starting from 3CLN and all residues having the same protonation states as in ( ) , the system is neutralized by 15 Na+ ions . This leads to a low IS of 82 mM . There is a on MD run of 400 ns and an additional control run of 50 ns . ( ) Starting from 3CLN structure , only E31 is protonated . The system is neutralized by 14 Na+ ions leading to IS = 91 mM; there are two runs for this system , one of length 400 ns and the other of 150 ns . ( ) Starting from 3CLN structure , E31A mutation is made . The system is neutralized by 14 Na+ ions leading to IS = 94 mM; there are three runs of 400 ns each for this system . ( ) In all the previously listed simulations , residues are assigned charge states according to pH = 7 . 4 using pKa values calculated and listed in ref . [24] . These systems are assumed to be at physiological pH . Acidic residues 11 , 31 , 67 , 84 , 93 , 104 , 122 , 133 and 140 , as well as H109 consistently have pKas shifted from their standard values to ∼5 . 5 . In the system , these are protonated to mimic the low pH conditions . The reader is referred to ref . [24] for details on the calculation of pKa values . There are two runs for this system , one of length 200 ns and the other of 100 ns . The system is neutralized by 5 Na+ ions leading to IS = 43 mM In addition , control runs of 100 ns duration have been carried out on the extended , low IS proteins , singly or doubly protonating other residues with upshifted pKa values . These are labeled , , and are not separately listed in Table 1; they are neutralized by 14 , 13 and 13 Na+ ions , respectively . We use the NAMD package to model the dynamics of the protein-water systems [35] . The protein is soaked in a water box with at least 10 Å of water from all directions using VMD 1 . 8 . 7 program with solvate plug-in version 1 . 2 [36] . The CharmM22 force field parameters are used for the protein and water molecules [37] . Water molecules are described by the TIP3P model . Each system is neutralized by using VMD autoionize plug-in . Long-range electrostatic interactions are calculated by the particle mesh Ewald sum method , with a cutoff distance of 12 Å and a switching function of 10 Å [38] . RATTLE algorithm is utilized and a step size of 2 fs is used in the Verlet algorithm [39] . Temperature control is carried out by Langevin dynamics with a damping coefficient of 5/ps . Pressure control is attained by a Langevin piston . Volumetric fluctuations are preset to be isotropic . The system is run in the NPT ensemble at 1 atm and 310 K . Equilibration of the pressure is achieved within 2 ns . The equilibrated box dimensions of each system are listed in Table 1 . The coordinate sets are saved at 2 ps intervals for further analysis .
Starting from 3CLN which represents the extended Ca+2-CaM structure captured in most X-ray studies , we externally perturb the physiological conditions for which results were displayed in figure 2: ( i ) We lower the IS while keeping the pH at 7 . 4; and ( ii ) we lower the IS as well as reducing the pH to 5 . 0 [24] . These systems are labeled and , respectively ( Table 1 ) . The regions sampled by are displayed in figure 3 . This is a continuation of the MD simulations from our previous work [24] , where the run has now been extended from 200 ns to 400 ns . The RMSD values of the subunits as well as the overall structure are shown in figure 3a . The initial conformer is not stable in solution as confirmed by the protein RMSD change . While the linker and the two lobes each display low intra-domain motions ( less than 3±1 Å RMSD ) , their relative orientations change substantially ( up to 13 Å in the overall RMSD ) . When projected on the reduced degrees of freedom ( figure 3b ) , the trajectories clearly display the three separate sampled states: The two lobes initially point towards each other and within the first 25 ns , the N- and C-lobes complete a ca . 120° torsional motion reaching state II which is then sampled for 195 ns after which a new state is reached ( III ) by a further torsional motion of 100° . In the last 180 ns of the trajectory , state III is sampled . Snapshots exemplifying these three distinct states are shown in figure 3c . We note that a prompt move into region II also occurs in the supplementary 50 ns run . All the structures that are sampled throughout the MD trajectory are compared with the experimental ones . The protein spends the first 220 ns in intermediate states with linker length ( l>31 Å ) , and φ = [−80° , 100°] . During the MD simulation , the initial ( X-ray derived ) structure 3CLN is only transient and the conformations sampled in regions I and II do not overlap with any of those from the NMR ensemble . This is consistent with other NMR and single molecule experiments where very low occupancy is assigned to the fully extended structure [31] . After 220 ns , the system eventually relaxes into a region with l = [28] , [34] Å , φ = [−210° , −130°] which overlaps with many of the 2K0E NMR ensemble members ( figure 3b ) . These observations imply that there is an energy barrier between the regions with φ = 90° and φ = 150° so that the system must counter-rotate by a large torsional angle , instead of flipping the 60° directly . In the runs , we find that by mimicking low pH , low IS environment , the sampled regions in figure 3b do not change ( see figure S1 ) , but the sampling is accelerated . We do not go into the details of these runs since we have already published a detailed account of the conformations sampled and key events leading to the conformational change [24] . However , it suffices to say that the same sequence of states I→II→III are followed in both runs . The shift from state I to II occurs at ca . 20 ns similar to the time scales observed in , but that from II to III occurs at ca . 70 ns . For both the and the systems , the main intra-domain conformational change occurs as a reorientation of helix II in the N-lobe . For example , the nearly right angle between helices I-II , that was always maintained at nearly right angles ( 80±6° ) at physiological IS in the and runs , is now reduced within the first 10–20 ns of the trajectory . It is maintained at a value of 56±7° in and 60±5° in throughout the window of observation . The major event that stabilizes the closed conformation is the formation of salt bridge ( s ) between the N-lobe and the linker in each case: E7-K77 , E11-K77 or E54-K75 in ( established in both runs prior to 50 ns ) and E7-R74 or E11-K77 in the runs ( forming permanently at ca . 40 ns in both samples ) . Despite being a counterintuitive observation , it was shown as a general result that two negatively charged nano-sized spheres may be put into close contact by utilizing the competition of hydrophobic and Coulombic interactions , provided that the charges are placed discretely along the surface [40] . At physiological IS and pH , there exists a high energy barrier between the extended and compact structures , corroborated by the 100 µs time scale of jumps between them , measured by single molecule experiments [27] . Thus , a direct passage between the black and blue shaded regions in figure 2 is not observed within the time window of observations of the MD simulations . However , once achieved , the compact conformation is stable despite the net repulsions between the two lobes ( net charge on the N- and the C-lobes are -8 and -6 , respectively ) . One may argue that the pH of the X-ray experiment ( 5 . 4 ) may have contributed to the stability of the 1PRW crystal structure , since the acidic residues 7 , 11 , 14 , 120 , 127 are found to be neutral at this pH [41] . The interface between the two lobes involves E7 and E11 on the N-lobe interacting with E127 on the C-lobe , as well as pairing between E14-E120 . Thus , it may well be that the acidic contacts do not repel each other in the crystal due to the loss of the charges . In contrast , our MD simulations starting from the 1PRW structure assigns their usual charges to these residues to mimic the physiological pH conditions . Nevertheless , the interface accommodates the repulsions between the closely located negative charges by slightly expanding around the adjacent helices and rotations in the side chains ( figure S2 ) . Thus , the initial state is maintained during the 200 ns window of MD observations , regardless of the charge states of the interface residues . With this robust accommodation of charges in mind , we seek the reasons behind the relaxation of the initial X-ray structure to new conformations when the environmental conditions are perturbed . To be noted is the conformational plasticity in the MD runs at low IS ( figure 3b ) , and the similarity between a subset of the NMR ensemble structures and state III structures . The ionized states of the acidic residues make the electrostatic component dominant and strongly oppose direct inter-domain association on the time scale of the simulations [41] . This fact does not keep the system from sampling a plethora of conformations in the φ space . Thus , to understand how the interfered charge distribution in the environment affects the vicinal solvent layer around the protein , we study the distribution of the solvated non-specific ions around the protein in each case . We display in figure 4a , the radial distribution function ( RDF ) of the ions in the solvent around the side chain heavy atoms of the protein at low and high IS . The first peak belongs solely to the contact of Na+ ions with O− atoms of the negatively charged residues . The second peak is due to the solvent mediated interactions . Interestingly , although there are plenty of positively charged residues on the surface of the protein , Cl− ions ( which only exist in the physiological IS run ) rarely interact with them . At low IS , the Na+ ions strongly interact with the negative charges on the protein , thus screening the extreme repulsions between the two lobes and allowing rotational motions around the linker . To achieve physiological IS , Cl- ions as well as additional Na+ ions are added to the system . In the presence of these additional mobile negative charges the Na+ ions mainly reside away from the protein surface and in bulk water where they may also dynamically interact with Cl− ions ( we check that there is no permanent ion pairing occurring between Na+ and Cl− ions ) . More interestingly , lack of salt in the solvent environment reduces the time scale of conformational change by three orders of magnitude , from sub-milliseconds to sub-microseconds . Decomposed into the different regions on the protein at low IS ( Figure 4a inset ) , the most significant interaction of the Na+ ions is with the linker residues , followed by those of the C-lobe and even less so with the N-lobe . We have also monitored the trajectories to find that the cations are mobile and they do not have a preferred position near the linker . These ionic distributions are contrary to expectations from the net charges , with that of the linker being only -1 , whereas those of the N- and the C-lobes are -8 and -6 , respectively . Thus , the ionic interactions are geometry specific , and designate the smooth surface of the linker ( relative to the two lobes ) as a region that has a tendency of binding non-specific ions . We conclude that the conformational plasticity of the torsional motions observed in altered charge environments is due to the clustering of the cations around the linker which screens the strong repulsions between the two lobes . We check the effect of the change in the number densities of the ions at different ionic strengths on the values of the RDF peaks . We confirm that the reduction of the peaks exceeds that expected by the 2 . 3 fold increase in the number densities of the ions in the system ( e . g . the linker peak is reduced 3 . 3 fold . ) In terms of the absolute values , the average number of Na+ ions within the first coordination shell of the acidic residues of the linker is 0 . 5 and 1 . 13 for the and systems , respectively . While the removal of Ca2+ ion from EF-hand loop I readily induced compaction of CaM in a previous MD simulation [42] , we are interested in revealing its role in CaM dynamics in fully loaded state . We have previously shown that E31located in this loop is unique in that its perturbation in a given direction reproduces the closed form structure with high overlap [14] . In fact , unlike its positional counterparts on the other EF-hand loops of CaM , the role of E31 is not as central in Ca+2 ion coordination as its involvement in signaling coordination between the two lobes . This statement is supported by a series of experimental E→K point mutation studies at the four equivalent EF-hand positions ( 31 , 67 , 104 and 140 ) [43] , [44] . Two results are striking: E31K mutation ( i ) has wild type activation on four different enzymes while the others do not; ( ii ) does not lead to apparent binding affinity changes while the rest lead to the loss of Ca+2 binding at one site . It was also shown that proton flux is an important factor affecting conformational changes in CaM and its enzyme targets [45] . We have therefore protonated E31 while keeping the IS low in the set of MD simulations . Since the topology of the residue is the same except for the reduced charge on the side chain , it still interacts with the Ca2+ in the EF hand I . We have monitored this motif throughout the trajectories and ensured there is no loosening in the motif . Strikingly , we find that the net effect of this single point protonation on the sampled conformations is similar to increasing the IS , keeping them near the initial extended structure ( compare figures 2b and S3b ) , with an average l value of 33 Å and torsional angle range φ = [80° , 130°] . Despite the protonation of a single point , the RDFs measured in these runs are also more similar to the high IS system ( figure 4b ) , significantly reducing the density of Na+ ion clustering around the protein , mainly affecting the linker region ( value reduced to 3 . 1 from 10 . 3; see Table 2 ) . E31 is able to significantly reduce the ion density around the protein and the linker at the same time ( Table 2 ) . For example , protonation of D122 , the second residue with the most significantly upshifted pKa , in a control run also leads to similar values . E31/D122 double protonation further reduces the ion density around the whole protein and the linker; while the E31/H107 double protonation does not bring in this additional effect . However , protonation of 10 residues to mimic the pH 5 environment in is effective in further reducing the charges around the linker environment , while its effect on the overall protein is less apparent . The most drastic change in the extended conformation occurs in the system . As we discuss in detail below , the E31A mutation opens a direct path between the extended conformation and compact structures with a bent linker , accessing conformations not sampled by any of the other systems . runs are characterized by increased mobility of the N-lobe ( 4 Å RMSD ) accompanied by an additional stability in the C-lobe ( RMSD<2 Å ) as well as the linker . The stability in the latter two regions , not directly perturbed by the E31A mutation , contrasts the simulations discussed in the previous subsection . We emphasize that the Ca+2 ion coordination is never lost in any part of these MD simulations which total 0 . 55 µs and 1 . 2 µs in and , respectively . By inspecting the MD trajectories , we find that the main direct difference between and runs is that while the calcium binding motif is not disrupted in the former , residue 31 can no longer participate in the motif in the latter due to its short side chain and hydrophobic character . Interestingly , the E31A mutation restores some of the depleted charge distribution around the acidic residues that occurred upon its protonation ( Figure 4b and Table 2 ) . The reorientation that takes place in the N-lobe is quantified by an increase of the RMSD value from 2 Å to 4 Å ( Figure 5a ) . The angle between helices III–IV displays a drastic change , with helix III tilting towards helix IV . This is followed by the formation of a salt bridge between residues E47 and R86 at 60 ns which may be traced in the sharp decrease in l from 34 Å to 27 Å ( Figure 5b ) . After the salt bridge formation , at 80 ns , the linker is further bent from residue 81 and l drops to 25 Å bearing a compact conformation . Snapshots are taken before and after transition and shown in Figure 5c . The observed conformational change is reversible , and the extended structure is restored at ca . 160 ns . No significant pKa shift appears for charged residues in any part of the trajectory . We find that the transition state is well defined , occurring through the same point in both forward and reverse steps . Time intervals of the transitions between the extended and compact ( forward transition ) and between compact and extended conformations ( reverse transition ) are examined in more detail in figure 6 . The positions of structures near the transition state in 200 ps intervals are plotted on the ( l , φ ) plane . Note that the axes have been zoomed in . The transition between the extended and compact states is also examined via the tool Geometrical Pathways [46] , [47] . This tool utilizes geometric targeting ( GT ) method that has recently been introduced [46] as a rapid way to generate all-atom pathways from one protein structure to some known target structure . GT is based on the philosophy that essential features of protein conformational changes can be captured by solely considering geometric relationships between atoms . The protein is modeled as a geometric system , with constraints established to enforce various aspects of structure quality such as preserving covalent bond geometry , preventing overlap of atoms , avoiding forbidden Ramachandran regions for backbone dihedral angles , avoiding eclipsed side-chain torsional angles , and maintaining hydrogen bonds and hydrophobic contacts . We note GT cannot predict relative timing of events . Using Geometrical Pathways in Biomolecules server [46] , we have generated 10 random pathways between representative structures collected structures at 50 ns ( extended ) and at 80 ns ( compact ) of the run 1 . The RMSD step size is 0 . 05 Å . The structures generated in the forward pathway by Geometrical Pathways are also plotted on figure 6 with the median of the pathway and the standard error bars along both axes . The random pathways produced via Geometrical Pathways overlaps with that visited by MD . They are widely distributed along the interdomain torsional angle dimension , but have narrow distribution in end-to-end-linker distance . GT generated pathways take energetics into account indirectly , through geometric factors only . Their overlap with the MD pathway corroborates that the conformational change may be achieved as a series of geometrically viable sequential steps , if the energy barrier between the two states allows them to take place . In fact , a stabilized conformational change between states I and II is observed in only one of the three runs . However , several attempted jumps occur with a kinked linker conformation in all simulations ( l<30 Å ) . Thus , the crucial step stabilizing the bent conformation is not the bending that is facilitated after the mutation , but the formation of the salt bridge between the N-lobe and the linker . Such attempts occur neither in nor in physiological IS runs . The relative positioning of the entering and exiting helices of the EF-hand motifs have been used to characterize the diverse conformations utilized by CaM for target recognition [48] . We therefore focus on the dynamics of the angles between the helices in EF hand motifs to understand how this “rare” conformational change is facilitated by E31A mutation . On the N-lobe , helices I and II in EF hand I , and helices III and IV in EF hand II are both initially posed at about right angles to each other , having values between 80–90° . In all three trajectories , the increase in the RMSD of the N-lobe occurs simultaneously with the loss of this perpendicular arrangement between the former pair of helices . The change in the orientation of the N-lobe helices provides E47 to make the salt bridge with R86 . Perhaps most intriguing is the diminished fluctuations between helices V and VII upon E31A mutation . The values of 38±11° in the rest of the simulations of Table 1 are suppressed to 30±5° for all three . The model for inter-lobe communication of CaM is E31 mediated . E31A mutation induces conformational changes between the two EF-hand motifs in the N-lobe , which simultaneously stabilize helix reorientational fluctuations in the C-lobe . No apparent communication pathway between the two lobes is found , thus lending support to the ensemble view of allostery [49] . As a result , the N-lobe performs an intra-lobe conformational search to establish a salt bridge with the linker . The stabilized C-lobe helps maintain the initial contact . The solvent participates in the fluctuations that establish the background for the conformations sampled by the protein .
Multiple conformations and cooperative conformational changes are an essential part of many enzyme mechanisms [50] . We explore the role of electrostatics in altering the conformation distributions as well as the dynamics of Ca2+-CaM using extensive MD simulations under physiological and low IS/pH conditions , and by mutating/protonating single residues . While the protein is stable in the initial state at physiological IS , lowering the IS or pH leads to conformational switching to more compact structures on sub-100 ns time scales ( Figures 3 and S1 ) . Although the net charges on the N- and C-lobes are significantly higher , at low IS cations approach the linker due to its relatively smooth geometry [51] , screening the repulsions between the lobes . This leads to conformational plasticity , enabling large torsional motions around the linker , eventually causing a compact conformation within 200 ns , albeit with a stiff linker . Lowering the pH in addition to the IS , which in effect deletes 10 charges on the protein surface , contributes to the process further , letting the protein achieve similar conformations within 60 ns . At high IS , the Cl− counterions are repelled by the significantly negatively charged protein ( figure 4a ) . Na+ ions are then driven into the bulk solvent , since the counterion interactions are favored over those with acidic residues both energetically and entropically . Repulsion between the two lobes is more pronounced because of ion depletion in the intervening region , restricting the protein conformation near the initial structure ( figure 2 ) . It would be interesting to make a systematic study of the effect of ions on the dynamics of CaM , including different ion types and concentrations . However , our scope here is to merely demonstrate that CaM dynamics is sensitive to ionic strength and may be moderated between rigid and very flexible . Such an observation has implications on both tuning and interpreting experimental results and on conditions selected for computer simulations . Perhaps more interestingly , neutralizing the single residue E31 at a key location by protonation has a similar effect on the ion distributions to increasing the IS ( figure 4b ) , confining the sampled conformations near the initial structure ( SI figure S3 ) . Alanine mutation of the same residue results in an intermediate distribution of ions , leading to partial mobilization of the protein . This facilitates a bending in the linker near the extended conformation ( figure 5 ) . E31A mutation accentuates the existing allosteric interactions , by introducing a change originating on the N-lobe whose action is detected on the C-lobe via the rearrangements of the helices in the EF-hands . The coupling between the two lobes is detected simultaneously , and the stabilizing salt bridge between the N-lobe and the linker is established later on in the simulation , right before the transition state is reached ( figures 5c and 6 ) . Thus , no pathway of structural distortions between the allosteric sites is observed , lending support to the ensemble view of allostery [49] . Finally , we note that the sampled structures have representatives in the NMR ensemble of conformations [25] . 40% of the 160 conformers have been visited in the cumulative MD simulations . On the downside , these are predominantly the ones with the straight linker , while the compact conformers ( those with l<25 Å ) have been rarely observed . The structures are compatible with the FRET results both in terms of the interlobe distances and the fact that lowering the pH to 5 . 0 leads to a single stable state as opposed to the presence of at least two distinct forms at pH 7 . 4 [13] . Our observations are also compatible with the findings of Bertini and coworkers [31] . Therein , low occupancies are assigned to fully compact structure of Ca2+-CaM ( 1PRW ) . Extended conformers similar to 3CLN in general have low occupancies although some other extended conformers have occupancies as high as 35% . This supports our findings that in our cumulative MD trajectories , the initial structures whether starting from compact or extended crystalline structures of Ca2+-CaM relaxes to less extended or less compact forms . Our current view suggests that at physiological IS and pH , there exists a barrier between the extended and compact forms , leading to 100 µs time scales for conformational jumps [27] . Barrier crossing is prevented by the repulsive electrostatic interactions between the two negatively charged lobes . As we show in this work , the crossing may be facilitated by tuning environmental conditions or by perturbing single residues located at key positions . The current study contributes to the knowledge-base in the direction of methods that determine how proteins adapt to changes in their environment or structure .
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Calmodulin ( CaM ) is involved in calcium signaling pathways in eukaryotic cells as an intracellular Ca2+ receptor . Exploiting pH differences in the cell , CaM performs a variety of functions by conveniently adopting different conformational states . We aim to reveal pH and ionic strength ( IS ) dependent shifts in the populations of conformational substates by modulating electrostatic interactions amongst the different regions of the protein and with its vicinal water . For this purpose , we design extensive molecular dynamics simulations to classify the effects that are responsible for adopting different conformations exhibited in the ensemble of NMR structures reported . Lowering the IS or pH , CaM experiences higher inter-lobe orientational flexibility caused by extreme change in the non-specific ion distribution in the vicinal solvent . Amongst the titratable groups sensitive to pH variations , E31 is unique in that its protonation has the same effect on the vicinal layer as increasing the IS . Furthermore , E31A mutation causes a large , reversible conformational change compatible with NMR ensemble structures populating the linker-kinked conformations . The mutation in the N lobe , at a significant distance , both modulates the electrostatic interactions in the central linker and alters the EF-hand helix orientations in the C lobe .
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[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2013
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Designing Molecular Dynamics Simulations to Shift Populations of the Conformational States of Calmodulin
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Mosquito-borne diseases are responsible for several million human deaths annually around the world . One approach to controlling mosquito populations is to disrupt molecular processes or antagonize novel metabolic targets required for the production of viable eggs . To this end , we focused our efforts on identifying proteins required for completion of embryonic development that are mosquito selective and represent potential targets for vector control . We performed bioinformatic analyses to identify putative protein-coding sequences that are specific to mosquito genomes . Systematic RNA interference ( RNAi ) screening of 40 mosquito-specific genes was performed by injecting double-stranded RNA ( dsRNA ) into female Aedes aegypti mosquitoes . This experimental approach led to the identification of eggshell organizing factor 1 ( EOF1 , AAEL012336 ) , which plays an essential role in the formation and melanization of the eggshell . Eggs deposited by EOF1-deficient mosquitoes have nonmelanized fragile eggshells , and all embryos are nonviable . Scanning electron microscopy ( SEM ) analysis identified that exochorionic eggshell structures are strongly affected in EOF1-deficient mosquitoes . EOF1 is a potential novel target , to our knowledge , for exploring the identification and development of mosquito-selective and biosafe small-molecule inhibitors .
Developing new strategies for vector control is becoming critical because worldwide cases of Aedes aegypti-transmitted dengue and Zika virus infections have risen dramatically in the last decade [1–3] . Researchers have been investigating metabolic regulation of blood meal metabolism in A . aegypti mosquitoes as a strategy for identifying novel protein targets that could be exploited for vector control [4–14] . The approach has been focused on biochemical processes that are likely to be required for completion of the gonotrophic cycle in blood-fed mosquitoes , based on what is known about mosquito biology and metabolic regulation in other organisms . Specific genes in these chosen pathways were then systematically knocked down by microinjection of double-stranded RNA ( dsRNA ) , and the resulting phenotypes were characterized in detail by molecular and biochemical approaches . The insect eggshell is important as a protective layer for embryonic development . Follicle development and eggshell formation in the A . aegypti mosquito are tightly regulated in response to blood feeding [15–20] . Once female mosquitoes acquire blood , follicle development is initiated via accumulation of vitellogenin yolk proteins . Mosquitoes contain approximately 100 ovarioles per ovary , which are composed of primary and secondary follicles and a germarium , and the ovarian follicles develop synchronously throughout oogenesis ( S1 Fig ) . A single layer of follicular epithelial cells surrounding the oocyte is mainly responsible for secreting a majority of eggshell structural components . The mosquito eggshell is made from different types of proteins ranging from structural proteins , enzymes , odorant binding proteins , and uncharacterized proteins of unknown function . A . aegypti eggshell melanization proteins were identified more than 20 years ago [21] , and several key eggshell enzymes have been well characterized [22–28] . Moreover , proteomic studies have been performed on purified mosquito eggshells to identify most of the abundant protein components [29 , 30] . However , these descriptive studies have not identified essential eggshell proteins that are required for successful embryonic development and larvae viability . Genomic sequences of Drosophila melanogaster [31] , Anopheles gambiae [32] , A . aegypti [33] , and Culex quinquefasciatus [34] have been completed . Not surprisingly , many predicted putative proteins identified in the genome of mosquitoes are homologous to proteins of known function studied in other organisms . Proteins that are conserved in a wide variety of organisms are not ideal target molecules as vector control agents because of deleterious effects on nontarget organisms such as vertebrates , pollinating agricultural insects , and beneficial predators . We reasoned that if small-molecule inhibitors could be designed to exclusively target mosquito-lineage–specific proteins , they could be used as biosafe vector control agents . The objective of this study is to identify mosquito-specific proteins that are essential for supporting embryonic development in A . aegypti mosquitoes by RNA interference ( RNAi ) screening . Our findings indicate that eggshell organizing factor 1 ( EOF1 , AAEL012336 ) is necessarily required for mosquito eggshell formation and melanization .
We performed data mining and bioinformatic analysis using the GenBank database to identify putative protein-coding sequences that are only present in the genomes of Aedes , Culex , and Anopheles mosquitoes using a cutoff for expected value threshold of 1 × 10^ ( −15 ) . Importantly , the mosquito-lineage–specific genes we identified ( S1 Table ) were found to be completely absent in evolutionarily closely related organisms , such as phantom midges , true midges , the crane fly , and sandflies within the suborder Nematocera , and thus these genes are not present in other known animals , plants , fungi , and bacteria species . In order to focus on genes that are expressed and likely to encode proteins that could potentially serve as vector control targets , we excluded genes without corresponding messenger RNA ( mRNA ) in A . aegypti expressed sequence tags ( ESTs ) or expressed orthologs in the Aedes albopictus transcriptome shotgun assembly ( TSA ) database . We also excluded mosquito-lineage–specific genes that appear to be members of a multigene family because RNAi knockdown phenotypes may not be immediately obvious because of possible functional redundancy with other gene family members . This highly selected subset of hypothetical mosquito-lineage–specific proteins may have therefore evolved independently and advantageously within the family Culicidae . Systematic RNAi screening of mosquito-specific genes was performed by directly microinjecting the corresponding dsRNA into female A . aegypti mosquitoes 3 days prior to blood feeding ( Fig 1A ) , and the blood-fed female mosquitoes were individually analyzed for their egg phenotypes , fecundity , and viability ( Fig 1B ) . 40 mosquito-specific genes were screened ( S1 Table ) , and utilizing this experimental approach led to the identification of EOF1 , which , upon RNAi knockdown , plays an essential role in the strength and structural integrity of the forming eggshell , as well as its melanization . We hypothesize that EOF1 has evolved within the family Culicidae to affect eggshell formation and melanization and therefore maximize egg survival . We did not observe any defective eggshell in mosquitoes microinjected with dsRNA against 39 other putative genes in A . aegypti mosquitoes , resulting in the production of viable eggs . We also did not observe any significant mortality in response to RNAi against these genes . Thus , we chose to focus on EOF1 in subsequent analyses . EOF1 sequences found in Aedes , Culex , and Anopheles mosquito species contain an F-box functional motif , and members of the F-box protein family are in general characterized by an approximately 50 amino acid F-box motif that interacts with a highly conserved SKP1 protein in the E3 ubiquitin ligase SCF complex [35] , suggesting that EOF1 may function to regulate intracellular protein turnover . A further RNAi study on proteins that participate in the SCF complex was not pursued since these proteins that participate in the complex are relatively highly conserved across taxa , and therefore these proteins may not be ideal target proteins to further characterize in mosquitoes . In addition , RNAi knockdown against proteins in the SCF complex may have effects on other proteins that contain the F-box motif . Recent proteomic analysis has identified over 100 mosquito eggshell proteins [29–30] , and some of these proteins identified are enzymes that may be involved in catalyzing eggshell melanization and cross-linking reactions [22–28] . However , EOF1 was not previously identified in these mosquito eggshell proteomic studies , indicating that EOF1 may be an upstream regulatory factor of eggshell proteins . As shown in Fig 1 , injection of dsRNA-EOF1 had a significant adverse impact on eggshell formation and egg viability . Single-mosquito analysis showed that phenotypes associated with RNAi-EOF1 range from totally nonmelanized and collapsed to truncated and melanized eggs , while untreated and RNAi-firefly luciferase ( Fluc ) control mosquitoes laid eggs that exhibit uniformly elongated and melanized patterns ( Fig 1C–1E ) . Approximately 60% of eggs laid by EOF1-deficient mosquitoes did not show any melanization ( Fig 1C ) , while 30% of them had mixed melanization levels ranging from nonmelanized and partially melanized to completely melanized eggshells ( Fig 1C ) . On the other hand , 10% of eggs had completely or partially melanized eggshells ( Fig 1C ) . Overall , nearly 100% of eggs from any melanization levels did not reach the larval stage . Single-mosquito analysis also showed that fecundity and viability from eggs of RNAi-EOF1 females were strongly affected by reduced EOF1 function through RNAi ( Fig 1F and 1G ) . Bleaching experiments on eggs further confirmed that mosquito-specific EOF1 is required for embryonic development in A . aegypti mosquitoes . Under a light microscope , we observed eggs throughout the 2 h eggshell dechorionation experiment period . In the majority of eggs laid by EOF1-deficient mosquitoes , embryos failed to complete embryogenesis and reach the first larval instar ( S2 Fig ) . It has been shown that when a mosquito embryo advances to form a serosal cuticle within the eggshell , bleach treatment was found to only remove the eggshell , but it cannot digest the serosal cuticle , leaving an intact embryo [36] . Thus , if a serosal cuticle has been formed during embryogenesis , the embryo or developed larva should be resistant to bleach treatment . A recently colonized A . aegypti Tucson strain from wild populations [37] also exhibited similar defective egg and embryo phenotypes associated with RNAi-EOF1 ( Fig 1H ) . We analyzed 15 mosquitoes from each group , and the fecundity ( mean ± standard error [SE] ) of eggs was 33 . 3 ± 3 . 0 , 26 . 4 ± 2 . 8 , and 17 . 5 ± 1 . 8 ( unpaired Student's t test; p < 0 . 01 ) for untreated , RNAi-Fluc , and RNAi-EOF1 , respectively . The lower number of eggs laid by the Tucson strain compared to the Rockefeller strain of A . aegypti could likely be due to reduced blood ingestion . The viability of eggs ( mean ± SE ) was 88 . 4 ± 2 . 1 , 87 . 0 ± 1 . 7 , and 2 . 4 ± 0 . 9% ( unpaired Student's t test; p < 0 . 001 ) for untreated , RNAi-Fluc , and RNAi-EOF1 , respectively . Thus , EOF1 protein is essential for complete eggshell formation and embryonic development in A . aegypti mosquitoes . Anautogenous female mosquitoes can undergo multiple gonotrophic cycles by repeating blood feeding , vitellogenesis , and oviposition events . Because EOF1 plays an essential role in eggshell formation , we wondered how long the RNAi knockdown effect of EOF1 lasts from a single dsRNA microinjection . We examined the effect of EOF1 deficiency on eggs in three consecutive gonotrophic cycles in individual containers as designed in Fig 2A and Fig 1B . Eggshell melanization ( Fig 2B and 2C ) , fecundity ( Fig 2D ) , and viability ( Fig 2E ) phenotypes are profoundly altered in EOF1-deficient mosquitoes during the first three gonotrophic cycles . Therefore , our data demonstrate that the RNAi-EOF1 effect from a single dsRNA injection remains substantial for the second and even the third gonotrophic cycles . Furthermore , we found that the timing of dsRNA microinjection is important . The dsRNA has to be microinjected a few days prior to blood feeding in both the first and second gonotrophic cycles in order to induce RNAi-mediated EOF1 depletion and produce defective egg phenotypes ( S3 Fig ) . Since little is known about this mosquito-specific EOF1 gene except for the phenotypes associated with RNAi , we determined the expression pattern of EOF1 at the mRNA level in untreated A . aegypti by quantitative real-time PCR ( qPCR ) . Five tissues including thorax , fat body , midgut , ovaries , and Malpighian tubules were dissected from sugar-fed female mosquitoes at 3 days posteclosion and blood-fed female mosquitoes at 24 and 48 h post-blood meal ( PBM ) . We also examined the mRNA expression in whole bodies of mixed-sex samples of fourth-instar larvae and pupae and adult male mosquitoes . EOF1 is predominantly expressed in ovaries , and the expression is up-regulated in the ovaries by blood feeding ( Fig 3A ) . qPCR results also indicate that mRNA encoding EOF1 is not strongly detected from larvae , pupae , and adult male mosquitoes . We then examined the pattern of EOF1 expression during the first gonotrophic cycle in detail . Ovaries were isolated at various time points PBM . In ovary samples after 36 h PBM , the primary follicles were carefully isolated from ovaries to exclude nonfollicle ovarian cell types such as muscles and trachea . qPCR data show that EOF1 mRNA expression is up-regulated in response to blood feeding , and the levels remain high even at 14 days PBM ( Fig 3B ) . Since follicular epithelial cells and nurse cells in the primary follicles undergo apoptosis by around 72 h PBM ( S4 Fig ) , mRNAs encoding EOF1 may likely originate from the unfertilized mature oocytes . EOF1 mRNA distribution in primary follicles was further determined using whole-mount fluorescent in situ hybridization ( FISH ) . FISH analysis shows that while three vitelline envelope genes [38] were exclusively expressed in the follicular epithelial cells , EOF1 mRNA transcripts are present in oocyte and nurse cells of primary follicles and weakly expressed in the secondary follicle and germarium ( S5 Fig ) . Western blot analysis showed that EOF1 expression is induced in ovaries in response to blood feeding ( Fig 3C ) . RNAi knockdown level of EOF1 mRNA and protein was confirmed by qPCR and western blot , respectively ( S6 Fig ) . In A . aegypti , EOF1-deficient female mosquitoes had low fecundity ( Fig 1F ) and laid eggs that were defective in eggshell formation , leading to the embryonic lethal phenotype ( Fig 1G ) . Similar reproductive phenotypes associated with RNAi-EOF1 were found in A . albopictus ( S7 Fig ) . EOF1 is required for proper eggshell formation , fecundity , and viability . We hypothesized that primary follicles of EOF1-deficient mosquitoes undergo cell death , removing severely affected follicles within the ovaries . We examined ovarian follicle phenotypes associated with EOF1 gene suppression by RNAi in A . aegypti mosquitoes . Representative ovaries at 36 h PBM showed that RNAi-EOF1 ovaries contain follicles that undergo caspase-mediated apoptosis indicated by the increase in red-labeled caspase inhibitor , while these dying follicles were not observed in untreated or RNAi-Fluc control ovaries ( Fig 4 ) . Approximately 40% of primary follicles in RNAi-EOF1 ovaries showed caspase-mediated apoptosis . Differential interference contrast and confocal images at a higher magnification showed that the caspase activity was more concentrated in the oocytes than in the follicular epithelial cells from RNAi-EOF1 mosquitoes ( Fig 4G and 4H ) . Mature ovaries were dissected from the abdomen of dsRNA-injected mosquitoes and photographed at 96 h PBM ( Fig 5A–5D ) . While not all RNAi-Fluc control mature follicles in ovaries have initiated melanization , we frequently observed that some follicles isolated from RNAi-EOF1 are already partially melanized in the ovaries . The partially melanized phenotype in EOF1-deficient ovaries is accompanied by a loss of structural integrity , and thus we hypothesized that decreased chorionic osmotic control results in this alteration of egg shape . To determine whether the water permeability of the mosquito eggshells was affected in response to EOF1 knockdown , we employed two chemical markers , rhodamine B and neutral red , to stain ovarian follicles . Significant differences in the permeability of both markers in ovaries were observed ( Fig 5E–5J ) . While the follicles from both untreated and RNAi-Fluc mosquitoes were only slightly stained , the majority of follicles from RNAi-EOF1 mosquitoes were strongly stained with the markers . Since follicular epithelial cells have been already shed around 72 h PBM ( S4 Fig ) , there is a single oocyte present in each follicle at this developmental stage ( 96 h PBM ) . The reduction of EOF1 expression in female mosquitoes resulted in defective eggshells , leading to increased permeability of water into oocytes ( Fig 5G and 5J ) and altered follicular shape . EOF1-deficient mosquitoes oviposited eggs with different degrees of eggshell melanization phenotypes that include nonmelanized , partially melanized , and melanized eggs ( Figs 1E and 2C ) . Since nearly 100% of eggs oviposited from RNAi-EOF1 females did not undergo complete embryogenesis ( Figs 1G and 2E ) , we hypothesized that the defective eggshell might be the primary cause of embryonic death . Light microscopy images of eggs from A . aegypti RNAi-Fluc and RNAi-EOF1 mosquitoes revealed that EOF1 may be involved in the specification of the outer chorionic area ( OCA ) surrounded by the porous nature of the exochorionic network ( EN ) ( Fig 6A–6D ) . Next , we examined the effect of RNAi-EOF1 on the ultrastructure of eggs in detail by scanning electron microscopy ( SEM ) . We observed a very similar A . aegypti eggshell ultrastructure ( Fig 6E and 6G ) to other SEM studies [39 , 40] . An exochorion outermost layer of the eggshell is characterized by the presence of a single protruding central tubercle ( CT ) and several minute peripheral tubercles ( PTs ) in the OCA ( Fig 6G ) . However , SEM images showed that the OCA in RNAi-EOF1 eggs is about 6 times larger than eggs of control mosquitoes ( Fig 6E–6H ) , suggesting that EOF1 may be involved in specifying the size of the OCA . A majority of eggshell proteins are likely secreted into the perivitelline space from follicular epithelial cells during follicle development in response to blood feeding . However , it is not well known whether the size of the OCA is strictly determined by surrounding follicular epithelial cells . We also observed that each OCA contains multiple miniaturized CT-like structures also surrounded by EN-like structures instead of one predominant CT . The SDS-PAGE analysis demonstrated that the enriched eggshell protein extracts from EOF1-deficient females showed slightly different patterns from those from RNAi-Fluc controls ( S8 Fig ) . These differences could account for aberrant exochorionic structure in RNAi-EOF1 eggs . Thus , EOF1 may act as an upstream factor to control eggshell surface patterning in A . aegypti .
Data mining was performed using all A . aegypti protein sequences available at the GenBank database in early 2015 to identify putative protein-coding sequences that are only present in the genomes of Aedes , Culex , and Anopheles mosquitoes . Through RNAi screening of putative mosquito-specific genes in A . aegypti , we identified EOF1 as an essential protein for eggshell formation and melanization . During this course of study , a whole-genome analysis in 37 dipteran species , including midges and sandflies , was performed [41] . We performed a TBLASTN search against Nematocera in the Whole-Genome-Shotgun contigs database . A global alignment between mosquito EOF1 and hypothetical proteins detected in culicoid and chaoborus midges shows only about 26%–30% identity , suggesting that it is very difficult to determine whether these highly diverged genes show orthologous relationships . The conserved amino acid residues are present in putative F-box functional domains of these proteins . Taken together , EOF1 may be uniquely evolved in mosquito lineages to play roles in eggshell formation . We observed that EOF1-deficient mosquitoes lay eggs with different melanization levels , ranging from nonmelanized to completely melanized eggshells ( Fig 1C ) . Different level of eggshell melanization in response to RNAi-EOF1 could be possible because of genetic variation . Alternatively , a differential dsRNA uptake by follicles within the ovary could explain the variation in the levels of eggshell melanization . A single layer of follicular epithelial cells surrounding the oocyte is mainly responsible for secreting a majority of eggshell structural components . Since eggshell components are directly secreted into the extracellular space between the oocyte and the surrounding follicular epithelial cells ( S1 Fig ) , intimate communication between these cells within each ovariole may exist throughout follicle maturation , eventually leading to follicular epithelial cell shedding ( S4 Fig ) , ovulation , and oviposition . In general , mature follicles from mosquitoes do not undergo premature melanization within the ovaries ( Fig 5 ) , and gravid females can hold their mature follicles for a long period of time under adverse environmental conditions and still lay viable eggs , which become melanized after oviposition . Thus , the timing of eggshell melanization may likely be tightly regulated and catalyzed by specific enzymes , and their synthesis , secretion , and activation may be critical for proper melanization and thus survival of embryos [22–28] . A possible explanation for aberrant partial melanization of follicles within the EOF1-deficient ovaries prior to an oviposition event is that a loss of EOF1 function may alter hemolymph permeability of the eggshell , affecting a delicate chemical balance within the oocytes , which in turn trigger other eggshell components to prematurely initiate eggshell melanization processes . In addition to A . aegypti , we also confirmed that EOF1 plays an essential role in eggshell formation in A . albopictus ( S7 Fig ) . Given that A . aegypti embryogenesis completes by 3 days postoviposition [36] , two lines of our experimental evidence suggest that EOF1 may be necessary for complete embryogenesis in A . aegypti mosquitoes . First , we frequently observed that a majority of eggs deposited by EOF1-deficient mosquitoes collapsed within 16 h , rupturing the oocyte plasma membrane and leaking intracellular contents , including yolk , likely because of incomplete eggshell formation . Second , our bleach assay demonstrates that nearly 100% of eggs from EOF1-deficient mosquitoes with any melanization levels did not reach the larval stage ( S2 Fig ) . Thus , female mosquitoes without EOF1 produce inviable eggs likely because of incomplete embryogenesis . However , it remains to be determined which specific embryogenesis stage was affected in eggs deposited by EOF1-deficient mosquitoes . SDS-PAGE analysis shows that enriched eggshell proteins from EOF1-deficient eggs slightly differ from those from RNAi-Fluc controls ( S8 Fig ) , and thus an identification of the downstream EOF1-dependent eggshell proteins may lead to a better understanding of molecular mechanisms for mosquito eggshell formation . Although it is beyond the scope of this study to screen and identify small molecules that specifically target mosquito EOF1 , such molecules may have great promise for controlling the mosquito population . Eggshell proteins specifically affected by EOF1-deficient mosquitoes may also be ideal proteins if they exhibit a high degree of sequence divergence to other insect taxa . Based on the presence of a conserved F-box motif in EOF1 , one possibility is that EOF1 is required in the ubiquitin pathway for controlled degradation of one or more proteins that regulate proper timing of eggshell development . Dysregulation of stage-specific ordered events in RNAi-EOF1–injected mosquitoes could lead to collapse of the developmental program at all downstream control points . The finding that RNAi-EOF1 phenotypes are observed three gonotrophic cycles beyond the time of injection ( Fig 2 ) indicates that the EOF1 protein may not be resynthesized at the onset of each gonotrophic cycle but rather establishes the eggshell development program when the reproductive phase is initiated in the female mosquito . The data in Fig 3 support this proposal in that EOF1 mRNA remains at elevated levels in the ovaries of blood-fed mosquitoes , even out to 14 days . Specifically , if EOF1 mRNA was resynthesized with each gonotrophic cycle , then one would expect EOF1 mRNA to be degraded at completion of the gonotrophic cycle in order to restart the process after the next blood feeding , and that does not appear to be the case . Another possibility is that RNAi effects are particularly long-lasting in ovary tissues and continue to abrogate EOF1 synthesis at each gonotrophic cycle . Additional studies are currently underway to distinguish between these alternative hypotheses . Results from these studies could lead to the development of mosquito control applications using novel biosafe mosquitocides that target mosquito-specific proteins required for embryonic development . It may also be possible to use clustered regularly interspaced short palindromic repeats ( CRISPR ) and CRISPR-associated protein 9 ( CRISPR-Cas9 ) gene-drive genetic manipulation [42–46] for the same purpose . If successful , such approaches would eventually result in a decrease in the mosquito population and thus lower the transmission of mosquito-borne viral infections .
Most of the experiments were carried out using A . aegypti mosquitoes ( Rockefeller strain ) and reared as previously described [5] . For comparison , A . aegypti mosquitoes ( Tucson strain ) were colonized from Tucson , Arizona [37] . A . albopictus ( Gainesville strain , MRA-804 ) mosquitoes were obtained from CDC/MR4 . Mosquitoes were maintained at 28°C , 72% relative humidity with a photoperiod of 16 h light and 8 h dark cycle in a CARON 6010 Insect Growth Chamber ( Caron Products & Services , Marietta , OH , USA ) . The larvae were fed on a diet consisting of dog food , Tetramin fish food , and liver powder ( 10∶10:1 ratio ) . Male and female adults were maintained on 10% sucrose and kept together throughout all experiments until transferred to oviposition containers . Using an artificial glass feeder , female mosquitoes were allowed to feed on expired human blood donated by the American Red Cross ( approved protocol #2010–017 ) . Only fully engorged female mosquitoes were used . Data mining and bioinformatic analysis were carried out using all A . aegypti GI numbers available at the GenBank database . To identify putative protein-coding sequences that are only present in the genomes of Aedes , Culex , and Anopheles mosquitoes , we use NCBI BLASTP with default search methods and a cutoff for expected value threshold of 1e-15 . Proteins selected were further subjected to NCBI TBLASTN search using A . aegypti ESTs or expressed orthologs in the A . albopictus TSA database to determine whether the genes are expressed . Mosquito-specific putative genes without corresponding mRNA in A . aegypti ESTs or A . albopictus TSA database were excluded as candidate genes for RNAi screening . We also excluded genes that appeared to be members of a multigene family because of possible functional redundancy with other gene family members . We also used a TBLASTN search from NCBI against Nematocera ( taxid: 7148 ) in the Whole-Genome-Shotgun contigs database . RNAi was carried out to knock down A . aegypti mosquito genes . Each gene-specific forward and reverse oligonucleotide primer was designed using a NetPrimer web-based primer analysis tool . A T7 RNA polymerase promoter sequence , TAATACGACTCACTATAGGGAGA , was added to the 5′ end of each primer ( S1 Table ) . All primers were purchased from Eurofins Genomics ( Louisville , KY , USA ) . PCR was performed using the Taq 2X Master Mix ( NEB , Ipswich , MA , USA ) with mosquito whole-body complementary DNA ( cDNA ) as a template , and the amplified PCR products were cloned into the pGEM-T easy vector ( Promega Madison , WI , USA ) for DNA sequence verification using an ABI 377 automated sequencer ( Applied Biosystems , Foster City , CA , USA ) . dsRNA was synthesized by in vitro transcription using a HiScribe T7 Quick High Yield RNA Synthesis Kit ( NEB ) . The purified dsRNA was resuspended with HPLC-grade water ( Thermo Fisher Scientific , Waltham , MA , USA ) at 7 . 3 μg/μL concentration . Cold-anesthetized female mosquitoes were injected with 2 . 0 μg dsRNA ( 276 nL ) using a Nanoject II microinjector ( Drummond Scientific Company , Broomall , PA ) . Injected mosquitoes were maintained on 10% sucrose throughout the experiments . Using TRIzol reagent ( Thermo Fisher Scientific ) , total RNA was extracted from larvae , pupae , and male adults as well as five tissues including thorax , fat body , midgut , ovaries , and Malpighian tubules dissected from sugar-fed female mosquitoes at 3 days posteclosion and blood-fed female mosquitoes at 24 and 48 h PBM . First-strand cDNA was synthesized from pools of total RNA using an oligo- ( dT ) 20 primer and reverse transcriptase . qPCR was carried out with the corresponding cDNA , EOF1 , or ribosomal protein S7 gene-specific primers ( S2 Table ) , PerfeCTa SYBR Green FastMix , and ROX ( Quanta BioSciences , Gaithersburg , MD , USA ) on the 7300 Real-Time PCR System ( Applied Biosystems ) . Mosquito ovaries were dissected in 1× PBS under a dissecting microscope and homogenized in lysis buffer ( 12 mM sodium deoxycholate , 0 . 2% SDS , 1% triton X-100 , complete mini EDTA-free protease inhibitor; Roche Applied Science , Indianapolis , IN , USA ) . Protein extracts were resolved on SDS-PAGE using a 12% acrylamide separation gel and a 3% stacking gel . The resolved proteins were either stained with GelCode Blue reagent ( Thermo Fisher Scientific ) or electrophoretically blotted to a nitrocellulose membrane ( LI-COR , Lincoln , NE , USA ) for western blot analysis . The membranes were blocked with 4% nonfat dry milk and incubated with each primary antibody in 4% nonfat milk in PBS containing 0 . 1% Tween 20 . The EOF1 rabbit polyclonal antibody was generated by GenScript Corporation ( Piscataway , NJ , USA ) based on an antigenic peptide ( LAPNSPSKEDEPAH ) . The anti-α-tubulin monoclonal antibody from Developmental Studies Hybridoma Bank ( University of Iowa , Iowa City , IA , USA ) was used as loading controls for ovaries . The dilutions of the primary antibodies were as follows: EOF1 ( 1:3 , 000 ) and α-tubulin ( 1:2 , 000 ) . The secondary antibodies were either IRDye 800CW goat anti-rabbit secondary antibody ( 1:10 , 000; LI-COR ) or IRDye 800CW goat anti-mouse secondary antibody ( 1:10 , 000; LI-COR ) . The protein bands were visualized with an Odyssey Infrared Imaging System ( LI-COR ) . Knockdown efficiency of RNAi was verified by real-time qPCR using gene-specific primers ( S2 Table ) . cDNA was synthesized from DNase-I–treated total RNA isolated from ovaries of individual dsRNA-injected mosquitoes at 48 h PBM . Normalization was done using the ribosomal protein S7 transcript levels as an internal control , and the knockdown efficiency of RNAi-EOF1 was compared using Fluc-dsRNA–injected mosquitoes as a control . The RNAi knockdown level of EOF1 protein was also determined by western blot analysis using an EOF1-specific polyclonal antibody . Ovarian protein extracts were isolated from 8 individual mosquitoes from RNAi-Fluc or RNAi-EOF1 mosquitoes at 48 h PBM . α-tubulin was used as an internal control . Eggs laid on oviposition papers remained wet for 3 days before drying at 28°C . Eggs ( about 7 days old ) on oviposition paper were submerged in water , vacuumed using a Speed Vac for 10 minutes , and allowed to hatch for 2 days . First-instar larvae were counted . A bleach assay was performed to determine viability of 4-day-old A . aegypti eggs from RNAi studies . Eggs on oviposition paper were soaked in 12% bleach ( sodium hypochlorite concentration at 0 . 72% ) at room temperature . A gradual progress of dechorionation of eggshell was observed under a microscope . Light microscopic images of eggs deposited from RNAi-Fluc and RNAi-EOF1 females prior to and after the addition of bleach were taken at 49× magnification ( Nikon , SMZ-10A; Nikon , Tokyo , Japan ) . mRNA distribution of EOF1 and vitelline envelopes ( 15a1 , 15a2 , and 15a3 ) in A . aegypti primary follicles was determined using whole-mount FISH . Primary follicles were isolated from ovaries of untreated female mosquitoes at 36 h PBM fixed with 4% paraformaldehyde . After washing with 1× PBS , the follicle samples were dehydrated with ethanol ( ETOH ) in water through a graded series for 10 min each in 10% , 30% , 50% , 70% , and 90% ETOH and 3 times 30 min each in 100% ETOH at room temperature . The samples were hydrated with 1× PBS in ETOH through a graded series for 20 min each in 25% , 50% , 75% , and 100% 1× PBS at room temperature . The follicles were permeabilized with proteinase K , postfixed with 4% paraformaldehyde with 0 . 1% Tween 20 , and treated with DEPC ( 0 . 1% ) to inactivate RNase . The follicles were then hybridized with digoxigenin-labeled antisense or sense RNA probes overnight at 65 oC . Probe DNA templates were PCR amplified by gene-specific primers ( S3 Table ) , and the RNA probes were synthesized by in vitro transcription as described in dsRNA synthesis above with DIG RNA Labeling Mix ( Sigma-Aldrich , St . Louis , MO , USA ) . After washing , the follicles in PBS were stained for actin cytoskeleton using Acti-stain 488 phalloidin-labeled ( Cytoskeleton , Denver , CO , USA ) at room temperature and incubated with rhodamine-B–conjugated anti-digoxygenin antibody ( 1:500 dilution; Jackson ImmunoResearch Laboratories , West Grove , PA , USA ) in blocking buffer ( LI-COR ) to detect the hybridized probes at 4 oC . The follicles were mounted on glass slides and viewed on a spinning disc confocal microscope ( Intelligent Imaging Innovations , Denver , CO , USA ) at the Keck Imaging Center at the University of Arizona . Images were obtained by using excitation 488 and 561 nm lasers and recorded using identical exposure times ( 100 ms ) . Female A . aegypti mosquitoes were microinjected with dsRNA at 1 day post-adult emergence , and ovaries at 36 h PBM were removed in 1× PBS under a dissecting microscope and immediately incubated with tissue culture media ( Medium 199 , Thermo Fisher Scientific ) containing a caspase inhibitor ( SR FLICA Poly Caspase Assay Kit; ImmunoChemistry Technologies , Bloomington , MN , USA ) at 37 oC in the dark for 1 h . The ovaries were washed with 1× PBS , fixed with 4% paraformaldehyde , quenched with 25 mM glycine , permeabilized with 0 . 5% Triton X100 , and stained with Acti-stain 488 phalloidin overnight at 4 oC . After washing with 1× PBS , the whole ovaries were mounted on a glass slide using ProLong Gold Antifade reagent ( Thermo Fisher Scientific ) . Immunofluorescence , differential interference contrast , and light microscopic images of the ovaries were captured using a Spinning Disk Confocal Laser Microscope in the Keck Imaging Center at the University of Arizona . The assay has an advantage in that it can quickly assess whether follicles within the ovaries may contain defective eggshell prior to oviposition . Individual follicles of untreated , RNAi-Fluc , or RNAi-EOF1 mosquitoes at 96 h PBM were dissected and gently separated from the ovaries and transferred to glass scintillation vials . Rhodamine B ( final concentration of 1 mM in H2O , Sigma-Aldrich ) and neutral red ( 0 . 5% , Sigma-Aldrich ) were used to stain primary follicles for 10 min on a rocking shaker and thoroughly rinsed with H2O . The stained primary follicles were photographed with a Coolpix 4300 ( Nikon ) . The ovaries were dissected from mosquitoes injected with Fluc control dsRNA and EOF1 dsRNA at 96 h PBM . Each follicle was carefully separated from the ovaries in 1× PBS under a dissecting microscope . The mature follicles were fixed in 2 . 5% glutaraldehyde in 0 . 1 M PIPES for 1 h at room temperature and washed twice in PIPES . The follicles were then postfixed in 1% osmium tetroxide in PIPES for 1 h and washed twice in deionized water for 10 min each . The follicles were dehydrated with ETOH in water through a graded series for 10 min each in 10% , 30% , 50% , 70% , and 90% ETOH and 3 times 30 min each in 100% ETOH at room temperature . The samples were dried with hexamethyldisilazane ( HMDS; Electron Microscopy Sciences , Hatfield , PA , USA ) in ETOH through a graded series for 20 min each in 25% , 50% , 75% , and 100% HMDS at room temperature . The follicle samples were air dried under a fume hood overnight at room temperature for SEM analysis . The dried samples were metallized with gold using Hummer 6 . 2 Sputter System ( Anatech USA , Union City , CA , USA ) . Inspect-S scanning electron microscope ( FEI , Hillsboro , OR , USA ) was used to compare the ultrastructural characteristics of the ovarian follicles of females injected with Fluc and EOF1 dsRNA . Female mosquitoes were injected with dsRNA at 1 day post-adult emergence , and ovaries were dissected in 1× PBS at 96 h PBM . The dissected ovaries were thoroughly homogenized ( 40 strokes ) in ice-cold 1× PBS using Dounce homogenizers ( B pestle ) . The eggshells were allowed to settle down to the bottom of the homogenizer on ice . The top cloudy fraction was gently aspirated , and the washing step with ice-cold 1× PBS for the eggshells was repeated four times or until the solution was completely cleared . Subsequently , the eggshell was homogenized ( 20 strokes ) in ice-cold 1× PBS using A pestle . The eggshell proteins were subjected to SDS-PAGE and stained with GelCode Blue reagent . Statistical analyses were performed using GraphPad Prism Software ( GraphPad , La Jolla , CA ) . Statistical significance for fecundity , viability , and RNAi knockdown efficiency was analyzed using an unpaired Student's t test . p values of ≤0 . 05 were considered significantly different . All experiments were performed from at least three independent cohorts .
|
Mosquito-borne pathogens infect millions of people worldwide , and the rise in insecticide resistance is exacerbating this problem . A new generation of environmentally safe insecticides will be essential to control insecticide-resistant mosquitoes . One potential route to such novel insecticide targets is the identification of proteins specifically needed for mosquito reproduction . Female mosquitoes feed on blood to produce eggs , which are covered with an eggshell; using RNA interference screening of mosquito-specific genes in Aedes aegypti ( the mosquito that transmits yellow fever ) , we identified the eggshell organizing factor 1 ( EOF1 ) protein that plays an essential role in eggshell melanization and embryonic development . Nearly 100% of eggs laid by EOF1-deficient females had a defective eggshell and were not viable . Bleach assays on eggs further confirmed that mosquito-specific EOF1 is required for embryonic development in A . aegypti . Additional experiments revealed that EOF1 also plays an essential role in eggshell formation in Aedes albopictus ( the tiger mosquito , a carrier of Zika virus and dengue fever ) . We hypothesize that EOF1 has evolved within the Culicidae family to effect eggshell formation and therefore maximize egg survival . The results provide new insights , to our knowledge , into mosquito egg maturation and eggshell synthesis and could lead to key advances in the field of mosquito vector control .
|
[
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"Materials",
"and",
"methods"
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2019
|
Identification and characterization of a mosquito-specific eggshell organizing factor in Aedes aegypti mosquitoes
|
Despite significant efforts and remarkable progress , the inference of signaling networks from experimental data remains very challenging . The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training . The problem is ill-posed due to the nonlinear nature of these systems , the fact that only a fraction of the involved proteins and their post-translational modifications can be measured , and limitations on the technologies used for growing cells in vitro , perturbing them , and measuring their variations . As a consequence , there is a pervasive lack of identifiability . To overcome these issues , we present a methodology called SELDOM ( enSEmbLe of Dynamic lOgic-based Models ) , which builds an ensemble of logic-based dynamic models , trains them to experimental data , and combines their individual simulations into an ensemble prediction . It also includes a model reduction step to prune spurious interactions and mitigate overfitting . SELDOM is a data-driven method , in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information . We have tested SELDOM on a number of experimental and in silico signal transduction case-studies , including the recent HPN-DREAM breast cancer challenge . We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology . More importantly , the utility of SELDOM goes beyond basic network inference ( i . e . uncovering static interaction networks ) : it builds dynamic ( based on ordinary differential equation ) models , which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions ( i . e . not used in the training ) . For this task , SELDOM’s ensemble prediction is not only consistently better than predictions from individual models , but also often outperforms the state of the art represented by the methods used in the HPN-DREAM challenge .
Inferring the molecular circuits of the cell from experimental data is a fundamental question of systems biology . In particular , the identification of signaling and regulatory networks in healthy and diseased human cells is a powerful approach to unravel the mechanisms controlling biological homeostasis and their malfunctioning in diseases , and can lead to the development of novel therapies [1 , 2] . Given the complexity of these networks , these problems can only be addressed effectively combining experimental techniques with computational algorithms . Such network inference ( or reverse engineering ) efforts [3] have been largely developed for gene regulation [4 , 5] , and to a lesser extent for signal transduction [1] . Extensive work has been published on the inference of molecular circuits , either as static networks—that is , recovering only the topology of interactions—[4–6] or as dynamical systems [7 , 8] . It can be beneficial to consider network inference in conjunction with the prediction of data for new conditions , since a precise topology should help in the generation of high quality predictions , and the inability of a model topology to describe a given set of experiments suggests that the model is in some sense wrong or incomplete . Signal transduction is a highly dynamic process , and the identification and analysis of the underlying systems requires dynamical data of the status of its main players ( proteins ) upon perturbation with ligands and drugs . These experiments are relatively complex and expensive , and there is a trade-off between coverage and throughput [2] that often makes the problem ill-posed , leading to identifiability issues . The problem of handling parametric and structural uncertainty in dynamic models of biological systems has received great attention in systems biology and biotechnology [9–12] . Inference and identification methods can be used to find families of dynamic models compatible with the available data , but in general these models will still suffer from lack of identifiability in a certain degree [3] . Ensemble modeling can be used to improve the predictive capabilities of models , helping to overcome the fundamental difficulties associated with lack of structural and/or practical identifiability . The usage of ensemble methods is widespread in fields such as machine learning [13] , bioinformatics [14] , and weather forecasting , but not so much in computational systems biology , although it has been successfully applied in the context of regulatory [15 , 16] , metabolic [17 , 18] , and signaling [19] networks . Although there is no universally agreed explanation of the success of ensemble methods as classifiers in machine learning [20] , it has been shown that they can improve generalization accuracy by decreasing variance [21] , bias [22] or both [23] , and the reasons for this are relatively well understood [13] . A common approach for building an ensemble is to train a number of so-called base learners in a supervised manner , using data re-sampling strategies . An example of the application of such methods in biology can be found in [24] , where the inference of gene regulatory networks is formulated as a feature selection problem , and regression is performed using tree-based ensemble methods . This approach was recently extended to accommodate dynamics [25] . Xing et al [26] used ensemble simulations of causal genetic networks to predict genes involved in rheumatoid arthritis . They showed that the use of ensembles allows for quantitative prediction of the effects of perturbation , adding robustness to predictions by accounting for uncertainty in network topology . Besides robustifying predictions , another task in which ensembles can be helpful is in the elucidation of insufficiently characterized circuits . In this context , Kuepfer et al [19] showed how to use ensembles to unravel operating principles in signaling pathways . They created an ensemble of plausible models of the target of rapamycin ( TOR ) pathway in S . cerevisiae , in which the different topologies accounted for uncertainties in network structure: each member of the ensemble extended a core model by including an additional reaction . By clustering the models according to their training errors , they determined the common features shared by those that better reproduced the experimentally observed behaviour . In this way , a new factor was proposed as the key signaling mechanism . Ensembles of dynamic systems have been used for many years in weather forecasting . In that community , sets of simulations with different initial conditions ( ensemble modeling ) and/or models developed by different groups ( multi-model ensemble ) are combined to deliver improved forecasts [27 , 28] . In the context of metabolism , Lee et al [29] have shown how to use ensembles to assess the robustness of non-native engineered metabolic pathways . Using the ensemble generation method proposed in [18] , a sampling scheme is used to generate representative sets of parameters/fluxes vectors , compatible with a known stoichiometric matrix . This approach is based on the fact that this problem is typically underdetermined , i . e . there are more reactions/fluxes than metabolites . Thus , model ensembles may be generated by considering all theoretically possible models , or a representative sample of it . The use of an ensemble composed of all models compatible with the data has been applied to gene regulatory [15] and signal transduction networks [30] . If the model structure is unknown , the ensemble generation needs to be completely data-driven . A common approach for inferring network structures from data is to use estimations of information-theoretic measures , such as entropy and mutual information . There is a plethora of methods for inferring static networks , including correlation , Bayesian inference , and information theory metrics [3 , 31–33] . We have focused on information-theoretic approaches because of their good properties regarding handling of nonlinear interactions ( which are common in signalling pathways ) and scalability . For a recent review of information-theoretic methods , see [6] . The central concept in information theory is entropy , a measure of the uncertainty of a random variable [34] . Mutual information , which can be obtained as a function of the entropies of two variables , measures the amount of information that one random variable provides about another . The mutual information between pairs of variables can be estimated from a data-set , and this can be used to determine the existence of interactions between variables , thus allowing the reverse engineering of network structure . For early examples of this approach , see e . g . the methods reviewed in [35 , 36] , which covers different modeling formalisms used in gene regulatory network inference ( GRN ) . The use of these techniques is not limited to GRNs; they can be applied to cellular networks in general [37] . Detailed comparisons of some of these methods can be found in several studies [4 , 38–40] . Some state-of-the-art information-theoretic methods for network inference are ARACNe [41] , and its extensions TD-ARACNE [42] and hARACNe [43] , Context Likelihood of Relatedness , ( CLR ) [44] , Minimum Redundancy Networks ( MRNET ) [45] , three-way Mutual Information ( MI3 ) [46] , and Mutual Information Distance and Entropy Reduction ( MIDER ) [47] , to name a few . All of them are based on estimating some information-theoretic quantity from the data and applying some criterion for determining the existence of links between pairs of variables . While the details vary from one method to another , it is difficult to single out a clearly “best” method . Instead , it has become clear in recent years that every method has its weaknesses and strengths , and their performance is highly problem-dependent; hence , the best option is often to apply “wisdom of crowds” methods , akin to the ensemble approach described above , as suggested by the results of recent DREAM challenges [48 , 49] . In this spirit , recent software tools aim at facilitating the combined use of several methods [50] . Here , we present SELDOM ( enSEmbLe of Dynamic lOgic-based Models ) , a method developed with the double goal of inferring network topologies , i . e . finding the set of causal interactions between a number of biological entities , and of generating high quality predictions about the behaviour of the system under untested experimental perturbations ( also known as out-of-sample cross-validation ) . SELDOM makes no a priori assumptions about the model structure , and hence follows a completely data-driven approach to infer networks using mutual information . At the core of SELDOM is the assumption that the information contained in the available data will not be enough to successfully reconstruct a unique network . Instead , it will be generally possible to find many models that provide a reasonable description of the data , each having its own individual bias . Hence SELDOM infers a number of plausible networks , and uses them to generate an ensemble of logic-based dynamic models , which are trained with experimental data and undergo a model reduction procedure in order to mitigate overfitting . Finally , the simulations of the different models are combined into a single ensemble prediction , which is better than the ones produced by individual models . The remainder of this paper is organised as follows . First , the Methods section provides a step by step description of the procedure followed by SELDOM . Then a number of experimental and in silico case studies of signaling pathways of different sizes and complexity are presented . In the Results section the performance of SELDOM is tested on these case studies and benchmarked against other methods . We finish by presenting some conclusions and guidelines for future work .
The mutual information M I ( y ˜ i , y ˜ j ) between two random variables y ˜ i and y ˜ j is a measure of the amount of information that one random variable contains about another . It can also be considered as the reduction in the uncertainty of one variable due to the knowledge of another . It is defined as follows: MI ( y ˜ i , y ˜ j ) = ∑ ϵ = 1 n ϵ ∑ s = 1 n s ϵ p ( y ˜ i ϵ , s , y ˜ j ϵ , s ) l o g p ( y ˜ i ϵ , s , y ˜ j ϵ , s ) p ( y ˜ i ϵ , s ) p ( y ˜ j ϵ , s ) ( 1 ) where y ˜ i and y ˜ j are discrete random vectors with probability mass functions p ( x ) and p ( y ) , and log is usually the logarithm to the base 2 , although the natural logarithm may also be used . Since mutual information is a general measure of dependency between variables , it can be used for inferring interaction networks: the stronger the interaction between two network nodes , the larger their mutual information . If the probability distributions p ( y ˜ i ) and p ( y ˜ j ) are known , M I ( y ˜ i , y ˜ j ) can be derived analytically . In network inference applications , however , this is not possible , so the mutual information must be estimated from data , a task for which several techniques have been developed [52] . In the present work we calculate mutual information using the empirical estimator included in the R package minet [53] . Whatever the approach used to estimate the MI , estimation leads to errors , due to factors such as limited measurements or noisy data . Therefore , it is often the case that MI is over-estimated , which results in false positives . Network inference methods usually adopt strategies to detect and discard false positives . For example , ARACNe uses the data processing inequality , which states that , for interactions of the type X → Y → Z , it always holds that MI ( X , Y ) ≥ MI ( X , Z ) . Thus , by removing the edge with the smallest value of a triplet , ARACNe avoids inferring spurious interactions such as X → Z . However , this in turn may lead to false negatives . In the present work we are interested in building DDNs that are as dense as possible , in the sense that these should ideally contain all the real interactions , which leads to containing some false positives too ( the issue of the false positives will be handled in the independent model reduction step ) . However , the subsequent dynamic optimization formulation used to train the models benefits from limiting the number of interactions ( i . e . the number of decision variables grows very rapidly with the in-degree ) . To find each DDN , we build an adjacency matrix using the array M I ( y ˜ i , y ˜ j ) . Each column j represents the edges starting from vi and pointing to vj . From this vector we iteratively select as many edges as the maximum in-degree ( a pre-defined parameter of the method ) . In each selection step , an edge is chosen with a probability proportional to M I ( y ˜ i , y ˜ j ) . This process is repeated for every node . The DDNs obtained in the previous step represent a set of possible directed interactions . To characterize the dynamics of these interactions we use the multivariate polynomial interpolation technique [54 , 55] , which transforms discrete models into continuous ones described by ordinary differential equations ( ODEs ) . This interpolation is particularly well suited to represent signaling pathways , since it is able to describe a wide range of behaviours including combinatorial interactions ( OR , AND , XOR , etc ) . Having an ODE-based description allows us to simulate the time courses of the model outputs . By minimizing the difference between those predictions and the experimental data we can obtain a trained model . In the following lines we present the mathematical formulation of the dynamic equations , and in the next subsection we describe the model calibration approach . Let us represent a Boolean variable by xi ∈ {0 , 1} . In logic-based ODE models each state variable x ‾ i is a generalization of a Boolean variable , and can have continuous values between zero and one , that is , x ‾ i ∈ [ 0 1 ] . Every ith state variable in the model , x ‾ i , represents a species whose behaviour is governed by a set ϕi of Ni variables which act as upstream regulators ( x ‾ i 1 , … , x ‾ i N i ) . Each of the Ni regulators in ϕi is listed by an index ϕik . For example , if a variable x ‾ 5 is regulated by the following subset of N5 = 3 nodes: ϕ 5 = { x ‾ 3 , x ‾ 7 , x ‾ 8 } , we would have three indices ϕ5 1 = 3 , ϕ5 2 = 7 , and ϕ5 3 = 8 . For each interaction we describe the nonlinearity that governs the relation between the upstream regulators x ‾ k and the downstream variable x ‾ i using the normalized Hill function H ϕik . For each index ϕik the normalized Hill function has the form: H ϕ i k = x ¯ ϕ i k n ϕ i k x ¯ ϕ i k n ϕ i k + k ϕ i k n ϕ i k · ( 1 + k ϕ i k n ϕ i k ) ( 2 ) We have chosen the normalized Hill function because it is able to represent the switch-like behaviour seen in many molecular interactions [54] , as well as other simpler behaviours such as Michaelis Menten type kinetics . The shape of this curve is defined by the parameters n ϕ ik and k ϕ ik . Using these Hill functions we write the continuous homologue of the Boolean update function for variable x ‾ i as: B i ¯ = ∑ x i 1 = 0 1 … ∑ x i N i = 0 1 w x i 1 , … , x i N i · ∏ k = 1 N i x i k H ϕ i k + [ 1 - x i k ] [ 1 - H ϕ i k ] ( 3 ) where the w* are parameters that define the model structure . Note that each w* has Ni subindices , that is , as many subindices as regulators ( this number varies from one variable to another ) . We also remark that xi1 , … , xiNi are Boolean variables , so the term ∑ x i 1 = 0 1 … ∑ x i N i = 0 1 [ … ] represents sums where the xi* elements have values zero or one . The time evolution of x ‾ i is then given by: x i ¯ ˙ = ( B i ¯ - x ¯ i ) · 1 τ i ( 4 ) where τi can be seen as the lifetime of species xi . This representation can reproduce several behaviours of interest ( see Table 1 ) . For example , if we consider that a variable is controlled by two regulators , an AND type behaviour would be defined by setting wi , 1 , 1 to 1 and the other w’s ( wi , 0 , 0 , wi , 0 , 1 , and wi , 1 , 0 ) to 0 . On the other hand , the OR gate can be represented by setting wi , 1 , 0 and wi , 0 , 1 to 1 , and wi , 1 , 1 and wi , 0 , 0 to 0 . By linear combinations of these terms it is possible to obtain any of the 16 gates that can be composed of two inputs . This framework is very general and requires very few assumptions about the system under study . This comes at the cost of a large number of parameters to estimate: in principle , both Hill constants ( n ϕ ik and k ϕ ik ) are unknown , as well as the structure parameters w* and the lifetime parameter τi . The following subsection provides a formal definition of the parameter estimation problem . For each DDN it is possible to obtain the corresponding dynamic model automatically , as explained in the preceding subsection . Every such model has a number of unknown parameters: for each variable , one or several n* , k* , w* , and τ* have to be estimated . To this end we formulate a parameter estimation problem in which the objective function ( F ) is the squared difference between the model predictions ( y ) and the experimental data ( y ˜ ) . The goal is to minimize this cost function for every experiment ( ϵ ) , observed species ( o ) and sampling point ( s ) . The model prediction obtained by simulation ( y ) is a discrete data set given by an observation function ( g ) of the model dynamics at time t . This parameter estimation problem is formally defined as: minimize n * , k * , τ * , w * F = ∑ ϵ = 1 n ϵ ∑ o = 1 n o ϵ ∑ s = 1 n s ϵ , o ( y ˜ s ϵ , o - y s ϵ , o ) 2 subject to N i = d e g - ( v i ) ϕ i = { j | e i j = 1 } , i = 1 , … , n , j = 1 , … , n H ϕ i k = x ¯ ϕ i k n ϕ i k x ¯ ϕ i k n ϕ i k + k ϕ i k n ϕ i k · ( 1 + k ϕ i k n ϕ i k ) B i ¯ = ∑ x i 1 = 0 1 … ∑ x i N i = 0 1 w x i 1 , … , x i N i · ∏ k = 1 N i x i k H ϕ i k + [ 1 - x i k ] [ 1 - H ϕ i k ] x i ¯ ˙ = ( B i ¯ - x ¯ i ) · 1 τ i x ¯ i ( t 0 ) = x ¯ i 0 y = g ( x ¯ ) 0 ≤ w i ≤ 1 LB n ≤ n ≤ UB n LB k ≤ k ≤ UB k LB τ ≤ τ ≤ UB τ , ( 5 ) where g is the output function , which often consists of a subset of the states ( if all the states are measured , it is simply y = g ( x ‾ ) = x ‾ ) . The upper and lower bounds of the parameters ( e . g . LBk ) are set to values as wide as possible based on their biochemical meaning and prior knowledge , if existing . We have recently shown [56] how to train a more constrained version of this problem using mixed-integer nonlinear programming ( MINLP ) . Here , due to its size , the problem is first relaxed into a nonlinear programming ( NLP ) problem . The corresponding parameter estimation problem is non-convex , so we use the scatter search global optimization method [57] as implemented in the MEIGO toolbox [58] . We note that performing parameter estimation entails repeatedly solving an initial value problem ( IVP ) , which consists of integrating the ODEs from a given initial condition in order to obtain the time course simulation of the model output y . Several studies that have considered simultaneous network inference and parameter estimation have chosen discretization methods for the solution of the IVP [7 , 8] . This has some advantages regarding computational tractability , but forces the x ˙ values to be estimated directly from noisy measurements , which is especially challenging when samples are sparse in time . Instead , here we solve the IVP using a state-of-the-art solver for numerical integration of differential equations , CVODE , which is included in the SUNDIALS package [59] . Model reduction is a critical step in SELDOM due to two reasons: ( i ) we are interested in reducing the network to keep only interactions that are strictly necessary to explain the data ( feature selection ) ; ( ii ) following Occam’s razor principle , it is expected that the ideal model in terms of generalization is the one with just the right level of complexity [60] . Our model reduction procedure is partially inspired by the work of Sunnaker et al [61] , where a search tree starting from the most complex model is used to find the complete set of all the simplest models by iteratively deleting parameters . In contrast to [61] , we implement a greedy heuristic algorithm . While this method does not offer guarantees of finding the simplest model , it drastically reduces the computational time needed to find the simplest solution . This heuristic helps to maintain diversity in the solutions and ensures that spurious edges are not considered . The iterative model reduction procedure is described in Algorithm 1 . At each step ( i . e . for each edge ) , the constraint H ϕ ik is set to zero ( see Table 1 ) and the model is calibrated with a local optimization method , Dynamic Hill Climbing ( DHC ) [62] . To avoid potential bias caused by the model structure , edges are deleted in a random order . To decide about the new simplified model we use the Akaike information criterion ( AIC ) , which for the purpose of model comparison is defined as: A I C = 2 K + 2 n · l n F n , ( 6 ) where K is the number of active parameters . The theoretical foundations for this simplified version of the AIC can be found in [63] . Algorithm 1: Greedy heuristic used to reduce the model . At each step of the model reduction the new ( simpler ) solution is tested against the previous ( more complex ) one using the Akaike information criteria ( AIC ) . Data: Time-course continuous data y ˜ , a graph Ga ( V , E ) and the optimal parameters ( n , k , τ , w ) Result: A simplified graph Ga ( V , E ) * for each e ϕ ik ∈ Ga do minimize n * , k * , τ * , w * F = ∑ ϵ = 1 n ϵ ∑ o = 1 n o ϵ ∑ s = 1 n s ϵ , o ( y ˜ s ϵ , o − y s ϵ , o ) 2 subject to H ϕ ik = 0 … if AIC ( n* , k* , τ* , w* ) < AIC ( n , k , τ , w ) then Ea ← Ea\e ϕ ik {n , k , τ , w}←{n* , k* , τ* , w*} end end To generate ensemble predictions for the trajectories of state xi , SELDOM uses the median value of xi across all models for a given experiment iexp and sampling time ts . This is the simplest way to combine a multi-model ensemble projection . More elaborate schemes for optimally combining individual model outputs exist . Gneiting et al . [64] point out that such statistical tools should be used to obtain the full potential of a multi-model ensemble . However , the selection of such weights requires a metric describing the model performance under novel untested conditions ( i . e . forecasting ) , and finding such metric is a non trivial task . For example , in the context of weather forecasting , Tebaldi et al [27] point out that , in the absence of a metric to quantify model performance for future projections , the usage of simple average is a valid and widely used option that is likely to improve best guess projections due to error cancellation from different models . SELDOM has been implemented mainly as an R package ( R version 2 . 15 ) , with calls to solvers implemented in C/C++ or Fortran codes using Intel compilers . The SELDOM code is open source and it is distributed as is ( with minimal documentation ) , along with the scripts needed to reproduce all the results and figures . SELDOM can be installed and run in large heterogeneous clusters and supercomputers . This configuration allows to reduce computation times thanks to the adoption of several parallelization strategies . Model training and reduction are embarrassingly parallel tasks ( i . e . they can be performed independently for each individual model ) . They are automated using shell scripts and a standard queue management system . In addition to this parallelization layer ( at the level of individual model training and reduction ) there is another parallelization layer at a lower level: for each model , each experiment is simulated in a parallel individual thread using openMP [65] , which allows exploiting multi-core processors . The dynamic optimization problem associated to model training is solved as a master ( outer ) nonlinear programming problem ( NLP ) with an inner initial value problem ( IVP ) . The NLPs are solved using the R package MEIGOR [58] , with the evaluation of the objective function performed in C code . The solutions of IVPs are obtained by using the CVODE solver [59] . The experimental data is provided using the MIDAS file format , and it is imported and managed using CellNOptR [66] . To assess the performance of SELDOM , we have chosen a number of in silico and experimental problems in the reconstruction of signaling networks . Table 2 shows a compact description of some basic properties of these case studies along with a more convenient short name for the purpose of result reporting . For each case study , two data-sets were derived , one for inference and the second one for performance analysis . We highlight that training and performance assessment data-sets are not just two realizations of the same experimental designs; they were obtained by applying different perturbations , such as different initial conditions or the introduction of inhibitors either experimentally or in silico . The logic-based ODE framework is only able to simulate values between 0 and 1 . Therefore , in each case-study , we have normalized the data by dividing every value of a measured protein by the maximum value of that protein found across all conditions and time points in the training data-set . This normalization procedure also facilitates comparison across case-studies .
In this section , we describe the numerical experiments carried to show the validity of our ensemble based approach . Besides particular considerations in the data preprocessing or additional constraints added to the dynamic optimization problem which depend on the prior knowledge existent about the case study at hand , SELDOM has two tuning parameters: the ensemble size and the maximum in-degree allowed in the training process . Thus , besides showing how the method performs and illustrating the process we also wanted to show that the method is relatively robust to the choice of these parameters and provide guidelines for the choice of such parameters in future applications . For each case study we have chosen 3 in-degrees ( A , B and C ) which are shown in Table 2 and we have chosen a fairly large ensemble size of 100 models . To assess performance in terms of training and predictive skills of the model , we use the root mean square error ( RMSE ) : RMSE = ∑ ϵ = 1 n ϵ ∑ o = 1 n o ϵ ∑ s = 1 n s ϵ , o [ y ˜ s ϵ , o - y s ϵ , o ] 2 ∑ ϵ = 1 n ϵ ∑ o = 1 n o ϵ n s ϵ , o ( 10 ) To assess performance in terms of network topology inference , we have chosen the area under precision recall ( AUPR ) curve , where precision ( P ) and recall are defined as ( R ) : P = TP TP + FP ( 11 ) and R = TP TP + FN , ( 12 ) where TP and FP correspond to the number of true and false positives , respectively and FN corresponds to the number of false negatives . Other valid metrics exist , such as the Area Under the Receiver Operator Characteristic curve ( AUROC ) . The ROC plots the recall , R , as a function of the false positive rate , FPR , which is defined as FPR = FP FP + TN . ( 13 ) However , it has been argued that ROC curves can paint an excessively optimistic picture of an algorithm’s performance [72] , because a method can have low precision ( i . e . large FP/TP ratio ) and still output a seemingly good ROC . Hence we have chosen to use the AUPR measure instead . The training data-sets in each case-study were used to obtain time-course trajectories for untested conditions . The type of trajectories obtained with SELDOM is illustrated with the help of Fig 3 which shows the time-course predictions for different conditions in the case-study 1b ( MAPKf ) . Ensemble trajectories for training and untested conditions are also given for other case-studies in S1 Text and S2 Text , respectively . In most cases the ensemble behaved better than the model with lowest RMSE training value . This effect is particularly evident in the DREAMiS case-study and is reflected in Fig 4 . Similar plots are also given for other case studies in S3 Text . In a number of case-studies ( DREAMiS , DREAMBT20 , DREAMBT549 , DREAMMCF7 and DREAMUACC812 ) there is little correlation between the training RMSE and the prediction RMSE . In Fig 5 , we show the overall picture regarding the predictive skills . Two strategies were considered for the generation of predictions: the best individual model and SELDOM . The RMSE values were normalized by problem and plotted as an heatmap . Additionally , for DREAMiS , DREAMBT20 , DREAMBT549 , DREAMMCF7 and DREAMUACC812 we added the prediction RMSE values for the top 3 performing participants in the corresponding DREAM sub-challenges ( experimental and in silico ) . To compute these RMSE scores we downloaded the participants predictions ( available online ) and normalized the data by using the maximum value of each measured signal found in the experimental data-set . The greatest gain of using an ensemble approach as shown here is in robustness . The effect of the model reduction was relatively small ( yet not neglectable ) in terms of RMSE for prediction . Comparing SELDOM results with those generated during the DREAM challenge , we managed to generate predictions with lower RMSE score than the top 3 participants ( Team34 , Team8 and Team10 ) of the in silico time-course predictions sub-challenge . Team34 ( ranked first ) built consensus networks generated by different inference algorithms applied to multiple subsets of the data . To generate the time-course predictions the previously mentioned team used generalized linear models informed by the inferred networks [70] . Regarding the experimental sub-challenge for most cases we obtained similar results to those of the top 3 participants ( Team44 , Team42 and Team10 ) with the exception of cell-line DREAMMCF7 where results where slightly better . The choice of ensemble size parameter affects the predictive skill of the ensemble and the computational resources needed to solve the problem . To verify if this choice was an appropriate one we plotted the average prediction RMSE as a function of the number of models n ℳ used to generate the ensemble . The average RMSE was computed by sampling multiple models from the family of models available to compute the trajectories . This is shown in Fig 6 for the DREAMiS case-study . Similar curves are given for all case studies as supporting information in S4 Text . With the exception of the combination MAPKp/SELDOM A the outcome for all case-studies is that SELDOM would have done similarly well with a smaller number of models and the prediction RMSE versus n ℳ always converged asymptotically . The mediocre results from the MAPKp/SELDOM A combination appear to be the result of a poor choice for the maximum in-degree parameter ( A = 1 ) which is too small .
In this paper we have presented a novel method for the generation of dynamic predictions in signaling networks . The method ( enSEmbLe of Dynamic lOgic-based Models , SELDOM ) handles the indeterminacy of the problem by generating , in a data-driven way , an ensemble of dynamic models combining methods from information theory , global optimization and model reduction . It should be noted that although this method is data-driven ( not requiring any prior knowledge of the network ) , it produces logic-based dynamic models which allow for mechanistic interpretations and are capable of making predictions in different conditions than those used for model calibration . In this study we focused mostly on the methodological aspects of SELDOM and performed comparisons based on standard metrics . SELDOM can provide cell-specific networks that can be explored to formulate biological hypotheses and guide the design of new experiments to validate them ( as an example , S7 Text shows the networks obtained with SELDOM for different cell-lines of the HPN-DREAM experimental data sub-challenge ) . We applied SELDOM to a number of challenging experimental and in silico signal transduction case-studies , including the recent HPN-DREAM breast cancer challenge . Regarding network inference , the ensemble approach did systematically well in all of the in silico cases considered in this work . This suggests that exploiting the information contained in the dynamics , as SELDOM does , helps the network inference problem allowing to disregard spurious interactions . We have also shown that , unlike most network inference methods , SELDOM is also capable of making robust dynamic predictions in untested experimental conditions . For this task , SELDOM’s ensemble predictions were not only consistently better than the outcomes of individual models , but also often outperformed the state of the art represented by the best performers in the HPN-DREAM challenge . It should be noted that the use of mechanistic dynamic models provides great flexibility regarding the simulation of complex time-varying situations . For example , it is not only possible to simulate inhibitions of several nodes in order to determine which combination produces the desired response , but also to test the outcome of sequential interventions ( i . e . taking place at different times during the course of a treatment ) , which would be impossible to model using statistical approaches that lack mechanistic detail . Another important application is the design of optimal dynamic experiments , i . e . those where the inputs acting as stimuli are designed as time-varying functions ( [76 , 77] ) . Furthermore , it is also possible to use the ensemble for extracting biological hypotheses about poorly known parts of a signaling pathway . The proposed SELDOM pipeline is flexible and can be adapted to any signaling or gene regulation dataset obtained upon perturbation , even if prior knowledge is not available . At the same time , it is also able to incorporate prior knowledge about a problem , for instance in the form of constraints ( e . g . the small-molecule inhibitors used in the HPN-DREAM challenge case studies ) . We have tackled the indeterminacy of the problem by generating a family of solutions , although other strategies , based on data-re-sampling methods and supervised learning ( similarly to what has been recently proposed by Huynh-Thu et al . [25] ) , might work well too . A systematic comparison of ensemble generation methods either based on problem structure or data re-sampling techniques should be considered in further work . Finally , a key point in the usage of ensemble methods is how to combine the models in order to obtain the best prediction possible . In this work we have chosen a simple model averaging framework . If more data become available , more sophisticated methods could be explored . For the sake of computational reproducibility , we provide the SELDOM code as open source ( http://doi . org/10 . 5281/zenodo . 250558 ) . This implementation can handle any data file in the MIDAS [51] format . Implementations for all the problems considered are also included in this distribution .
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Signaling pathways play a key role in complex diseases such as cancer , for which the development of novel therapies is a difficult , expensive and laborious task . Computational models that can predict the effect of a new combination of drugs without having to test it experimentally can help in accelerating this process . In particular , network-based dynamic models of these pathways hold promise to both understand and predict the effect of therapeutics . However , their use is currently hampered by limitations in our knowledge of the underlying biochemistry , as well as in the experimental and computational technologies used for calibrating the models . Thus , the results from such models need to be carefully interpreted and used in order to avoid biased predictions . Here we present a procedure that deals with this uncertainty by using experimental data to build an ensemble of dynamic models . The method incorporates steps to reduce overfitting and maximize predictive capability . We find that by combining the outputs of individual models in an ensemble it is possible to obtain a more robust prediction . We report results obtained with this method , which we call SELDOM ( enSEmbLe of Dynamic lOgic-based Models ) , showing that it improves the predictions previously reported for several challenging problems .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
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2017
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Data-driven reverse engineering of signaling pathways using ensembles of dynamic models
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The free-living aquatic bacterium , Caulobacter crescentus , exhibits two different morphologies during its life cycle . The morphological change from swarmer cell to stalked cell is a result of changes of function of two bi-functional histidine kinases , PleC and CckA . Here , we describe a detailed molecular mechanism by which the function of PleC changes between phosphatase and kinase state . By mathematical modeling of our proposed molecular interactions , we derive conditions under which PleC , CckA and its response regulators exhibit bistable behavior , thus providing a scenario for robust switching between swarmer and stalked states . Our simulations are in reasonable agreement with in vitro and in vivo experimental observations of wild type and mutant phenotypes . According to our model , the kinase form of PleC is essential for the swarmer-to-stalked transition and to prevent premature development of the swarmer pole . Based on our results , we reconcile some published experimental observations and suggest novel mutants to test our predictions .
The function of the cell division cycle of both prokaryotes and eukaryotes is to produce two nearly identical copies of a progenitor cell . The two progeny cells have identical genomes ( modulo unavoidable mutations in the DNA replication process ) , and they are usually quite similar in all other aspects ( called “symmetric” cell division ) . However , there are many cases of asymmetric cell division , in which the two progeny cells are notably different from each other [1] . An interesting example of asymmetric cell division is the freshwater bacterium , Caulobacter crescentus . Because Caulobacter populations typically live in low-nutrient environments , they have developed a strategy of asymmetric cell division to limit intraspecific competition [2] . During the cell division process , proteins are unequally distributed to the two halves of the cell , giving rise to two morphologically distinct daughter cells . One daughter cell ( the stalked cell ) is anchored to its place of birth via an appendage called the stalk , while the other daughter cell ( the swarmer cell ) is equipped with a flagellum and pilus that allows it to swim away from its place of birth . Hence , even though the total number of cells doubles , the number of stalked cells at a specific location stays the same . Another key difference is that , after cell division , the stalked cell immediately initiates a new round of DNA replication and cell division , while the wandering swarmer cell is not competent for DNA replication ( it is in a prokaryote version of G1 phase ) . Once the swarmer cell finds a nutritionally suitable location , it will differentiate into an immobile stalked cell , initiate DNA replication , and establish a new population . Orchestration of this asymmetric cell division cycle requires proper temporal and spatial regulation of several key proteins ( see Figure 1A ) . The temporal dynamics of these proteins was captured in a pair of papers by Li et al . [3] , [4] . At least two of these proteins , PleC and CckA , are bifunctional , capable of acting as either phosphatase or kinase . PleC kinase activity is up-regulated by its own response regulator , DivK . It is unknown how DivK alters the activity of its own phosphorylating enzyme , PleC . DivK is present at roughly constant level throughout the cell cycle [5] . However , PleC is a phosphatase during the swarmer stage of the cell cycle and kinase during the stalked stage ( see Figure 1B ) . It would be interesting to know how this cross-talk between PleC-kinase and its substrate , DivK , is restricted to the stalked stage of the cell cycle . At the level of physiology , whether a cell has a stalk or a flagellum depends on the phosphorylation status of the proteins DivK , PleD and CtrA . In the swarmer cell , CtrA∼P ( the active , phosphorylated form of CtrA ) binds to the origin of replication on the Caulobacter chromosome and inhibits initiation of DNA replication [6] . During the transition from swarmer to stalked cell , CtrA gets dephosphorylated and degraded , thereby lifting the block on DNA replication . In addition , CtrA affects the transcription of over 125 genes , so periodic changes in CtrA activity causes widespread changes in the expression profile of Caulobacter genes during the cell division cycle [7] , [8] . DivK , on the other hand , is unphosphorylated in the swarmer cell and gets phosphorylated during the transition to the stalked cell . In the phosphorylated state , DivK initiates a pathway for stalk formation [9] . It is also responsible ( indirectly ) for the dephosphorylation and proteolysis of CtrA [10]–[12] . The phosphorylation states of DivK and CtrA are governed by the bifunctional histidine kinases PleC and CckA , respectively . Both PleC and CckA can switch between two conformations: a kinase conformation and a phosphatase conformation [9] , [11] ( see Figure 1B ) . Typically , in bacteria the change in activity of a bifunctional histidine kinase is brought about by an external signal molecule binding to the sensor region of the protein [13] . However , the change in PleC from a phosphatase to a kinase is brought about by its substrate , DivK [9] . In fact , the sensor domain of PleC is not essential for its function [14] . This interaction , where substrate binding to a bifunctional histidine kinase changes its function , has , to our knowledge , been observed only for PleC in Caulobacter . It has been suggested that DivK up-regulates PleC kinase activity preferentially in stalked cells because it is in stalked cells where DivK∼P and PleC are co-localized at the poles [9] . The initial phosphorylation of DivK during the swarmer-to-stalked transition is brought about by a kinase DivJ that localizes to the old pole . Hence , DivJ is considered as the enzyme that initiates the swarmer-to-stalked transition [15] , [16] . A second and perhaps more crucial function of PleC kinase is to phosphorylate PleD , a diguanylate cyclase enzyme . On getting phosphorylated , PleD monomers dimerize and localize to the cell pole [17] . Active PleD converts two molecules of GTP into cyclic di-GMP , which signals production of the stalk [9] . Although mutations in divJ and pleC are not lethal , they result in growth and morphological defects in the cell . pleC::Tn5 mutants are stalkless [18] , [19] , while divJ-null mutants are filamentous and have elevated levels of CtrA-dependent transcription products [20] , [21] . DivK∼P level is elevated in pleC::Tn5 mutants and reduced in ΔdivJ background . ΔdivJ pleC::Tn5 double mutants exhibit an even lower level of DivK∼P than ΔdivJ single mutants [21] , indicating that PleC has a partial role , at least , as a DivK kinase . CckA acts as a kinase in the swarmer cell , keeping the level of CtrA∼P high , which in turn blocks DNA replication [22] . In the stalked cell , CckA becomes a phosphatase , and CtrA gets dephosphorylated , allowing initiation of DNA replication [23] . DivL , a tyrosine kinase has been implicated in maintaining CckA in the kinase state [11] , [12] , [24] , [25] . DivL can phosphorylate CtrA in vitro [18] . However , in vivo its role in maintaining a high level of CtrA∼P is indirect [24] . Multiple lines of evidence support the idea that DivL promotes CtrA phosphorylation via activation of CckA kinase . ( a ) divL mutants show marked reduction not only in CtrA∼P but also in CckA∼P [24] , [26] and CpdR∼P [26] . ( b ) The phenotype of divJ over-expression mutants is alleviated by mutations in divL [20] . ( c ) DivK∼P is known to bind to DivL and interfere with its ability to activate CckA kinase [11] . Although the mechanism by which DivL influences CckA is unclear , DivL seems to be the intermediate by which the PleC-DivJ-DivK∼P axis regulates the level of CtrA∼P . CckA's second substrate , CpdR , is phosphorylated and inactive in swarmer cells [23] . When CckA becomes a phosphatase in the stalked cell , active CpdR turns on the ClpXP proteolytic machinery for degrading CtrA [27] , [28] . In this manner , CckA governs both dephosphorylation and proteolysis of CtrA . Taken together , these observations suggest that PleC-DivJ-DivK and DivL-CckA-CtrA are crucial drivers of the swarmer-to-stalked transition , as summarized in Figure 1 and Figure 2 . Here , we propose a mechanism for ligand-dependent modifications of the bifunctional histidine kinase , PleC . The mechanism consists of elementary chemical reactions describing ligands ( either DivK or DivK∼P ) binding to the histidine kinase dimer in either its phosphatase or kinase form . The binding states determine the rates of the autophosphorylation , phosphotransfer , and phosphatase reactions catalyzed by PleC . If DivK∼P is more efficient than unphosphorylated DivK at promoting the transition of PleC from phosphatase to kinase , then PleC and DivK∼P would be involved in a positive feedback loop . Such positive feedback loops are well-known for their tendency to function as bistable toggle switches [29] , and toggle switches are well-known for their roles in cellular decision-making [30]–[32] including critical transitions in the eukaryotic cell cycle [33]–[35] . In the Supplementary Material ( Text S1 ) , we show that a detailed model of the interactions between DivK and PleC , under reasonable conditions on the rate constants ( or propensities ) of these reactions , exhibits robust bistability as a function of DivJ activity . That is , by carrying out the initial , limited phosphorylation of DivK , DivJ can function as the “toggle bar” for flipping the bistable switch from the PleC-phosphatase state to the PleC-kinase state . When DivJ activity is low ( swarmer cell ) , PleC is a phosphatase and DivK is predominantly dephosphorylated . As DivJ activity rises , enough DivK gets phosphorylated to flip the PleC switch to the kinase form ( stalked cell ) . By coupling DivK∼P to DivL , we show that the PleC switch can induce the transition of CckA from kinase to phosphatase form , causing CtrA∼P and CpdR∼P levels to drop in the nascent stalked cell ( Figure 1B ) . This model of a PleC bistable switch is an intermediate step on the way to a full spatial model of the asymmetric division cycle in Caulobacter cells ( in preparation ) . Using a model based on ordinary differential equations ( biochemical kinetics of spatially homogeneous reactions ) , we address in this paper only certain features of the control system that are independent of the complex spatio-temporal choreography of the cell cycle control system . In particular , we validate our model of the PleC switch against known mutant phenotypes , and then we discuss some predictions of the model: ( a ) over-expressing DivK should result in a loss of asymmetry and cell cycle arrest in the stalked cell stage , ( b ) PleC kinase is required to ensure that the nascent swarmer pole will mature only after cytokinesis , and ( c ) the swarmer-to-stalked transition is robust to fluctuations in nutrients available in the environment .
Our detailed mechanism of substrate-induced conformational changes in PleC is presented in the Supplementary Material ( Text S1 ) . The model is based on the following considerations . PleC is a homodimeric , bifunctional histidine kinase . It can bind to either DivK or DivK∼P . As a kinase , it phosphorylates DivK to DivK∼P , and as a phosphatase it hydrolyzes DivK∼P back to DivK . We assume that , when DivK or DivK∼P are bound to both subunits of PleC , the enzyme undergoes a concerted conformational change from its phosphatase form to its kinase form . The conformational change is described in the manner of the Monod-Wyman-Changeux [36] theory of allosteric enzymes . A detailed model of PleC-DivJ-DivK-PleD interactions contains 38 biochemical species ( Table S4 , Eq . 1–38; Figure S1A and B ) , many of which are involved in null-cycles . To build a kinetic model of this reaction network , we must assign reasonable values to all the forward and reverse rate constants ( kf and kr ) , respecting the fact that kf/kr = Keq = exp ( −ΔG0/RT ) , where ΔG0 is the standard Gibbs free energy change and Keq is the equilibrium constant for the reaction . In the Supplementary Material ( Text S1 ) we assign reasonable ΔG0 values to every reaction in the network , and then assign kf and kr values consistent with the computed equilibrium constants . In this way , we are assured that our kinetic model satisfies the Principle of Detailed Balance around all null-cycles . ( For a null cycle , ΔG0 = 0 and Keq = 1; hence , the product of forward rate constants around the cycle = the product of reverse rate constants around the cycle . ) Having built a kinetic model that is consistent with the thermodynamic requirements of the histidine kinase ( PleC ) —response regulator ( DivK ) system , we then show ( see Figure 3 ) that the ‘two component’ system does indeed exhibit bistability as a function of DivJ activity . In the next subsections , we examine biochemically relevant features of this bistable control system . ΔdivJ cells are filamentous [20] , [21] , show mislocalized stalks and delocalized DivK [5] . In addition , the level of phosphorylation of DivK in ΔdivJ cells is reported to be only 44% of wild-type level [21] . Not surprisingly , CtrA∼P level is higher in this deletion mutant [20] . Furthermore , mutations in divJ have an adverse effect on cell division rate [20] , [37] , [38] . Hence , DivJ is considered to be a cell-fate determinant , essential for a smooth swarmer-to-stalked transition [39] . Paul et al . [9] suggested that DivJ initiates the PleC phosphatase-to-kinase transition , by a positive feedback loop: DivK , on being phosphorylated by DivJ , activates PleC autokinase , and PleC kinase makes more DivK∼P . Their experiments , however , indicate that PleC kinase activity is up-regulated by DivK irrespective of DivK's phosphorylation state . Given that the total concentration of DivK remains the same throughout the cell cycle [5] , why isn't PleC a kinase at all times ? Presumably , the phosphatase form of PleC has a higher affinity for its substrate DivK∼P than for its product DivK . Therefore , even though the PleC phosphatase-to-kinase transition may be promoted by either DivK∼P or DivK , DivK∼P has a greater propensity than DivK to induce the conformational change . Once PleC becomes a kinase , it produces more DivK∼P , which enhances the rate of change from phosphatase to kinase . This self-reinforcing positive feedback loop between DivK∼P and PleC kinase can turn the PleC transition into a bistable “toggle” switch [29] . As shown in Figure 3A , DivJ can function as the lever of this toggle switch . As the activity of DivJ increases , PleC switches abruptly from a steady state of low kinase activity to a steady state of high kinase activity . DivK also transitions from a mostly-unphosphorylated steady state to a mostly-phosphorylated steady state ( Figure 3B and Figure S6B ) , as does PleD as well ( Figure 3C and Figure S6F ) . We propose that this toggle switch underlies the swarmer-to-stalked transition , where the arrival of DivJ at the old pole triggers PleC to switch to its kinase form , thereby triggering a new stalk end through PleD phosphorylation . It has been shown that upon glucose starvation , DivJ localization is inhibited , and the proportion of swarmer cells in the population doubles [39] . To test the signal-response curves in our model , it would be interesting to see if single cells can toggle between swarmer and stalked morphology upon changing nutrient composition . According to Paul et al . , accumulation of DivK∼P at the poles causes its local concentration to increase beyond a threshold required for the activation of PleC kinase . Our model does not address this possibility because ( at present ) it does not take space into account . While we cannot rule out the contribution of polar localization , our model shows that it is not essential for the phosphatase-to-kinase transition . Our simulations indicate that a large fraction of PleC kinase is bound to DivK ( Figure 3D ) . Hence , it is possible that localization of DivK∼P is not the cause but the consequence of PleC kinase up-regulation . PleC kinase molecules may serve as docking sites for DivK molecules at the flagellar pole . PleC phosphatase on the other hand need not have any bound DivK . This picture is in agreement with observations that PleC , DivJ and DivL contribute to localization of DivK∼P to the poles [19] , [40] . In vitro experiments show that PleC kinase activity increases in response to increasing DivK concentration , even in the absence of DivJ [9] . The specific activity of PleD in forming cyclic di-GMP was used as a proxy to measure PleC kinase activity . Surprisingly , the specific activity of PleC kinase in vitro is two-fold greater in the presence of DivKD53N , a mutant form of DivK that does not get phosphorylated . This indicates that DivK need not be phosphorylated to induce a conformational change in PleC . In vivo , however , PleC remains a phosphatase in the DivK-rich swarmer cell . Another odd result of the assay is that the specific activity of PleC kinase drops sharply at high DivK concentrations . To reproduce these results in ΔdivJ mutants , we set [DivJ] = 0 in our simulations ( Table S8 ) . To simulate the divKD53N mutation , we set the rates of all phosphotransfer reactions to zero ( Table S8 ) . In Figure 4 we plot steady-state PleD phosphorylation level against increasing total concentration of DivK ( from 0 . 3 to 30 ) . Our simulations show a qualitative similarity to the experiments [9] . PleD∼P level rises at first and then drops at high [DivK] ( Figure 4A–C ) . PleD∼P levels in ΔdivJ divKD53N simulations ( Figure 4A ) are comparable to PleD∼P levels in ΔdivJ ( Figure 4B ) and wild-type ( Figure 4C ) simulations . These results support the findings by Paul et al . [9] that unphosphorylated DivK is also able to up-regulate PleC kinase . There is a sharp drop in PleD phosphorylation at high [DivK] because PleC shifts predominantly to DivK-bound forms that do not have a free binding site for PleD ( Figure 3D ) and therefore cannot phosphorylate it . Product inhibition by cyclic di-GMP may also play a significant role [41] , but this effect is not included in our model . Since DivK is capable of activating PleC kinase in the absence of DivJ , we plotted a two-parameter bifurcation diagram to estimate the effect of varying concentrations of DivJ and DivK on PleC activity ( Figure 5A ) . The enclosed bistable region tapers off as we increase either total DivJ or total DivK ( ksyndk ) . This implies that at moderate concentrations of DivK ( e . g . , ksyndk = 0 . 015 ) , the PleC phosphatase-to-kinase transition is robust and dependent on the activity and localization of DivJ ( Figure 5B ) . However , increasing DivK in the cell would lead to transitions that are less robust and independent of DivJ . We predict that a 5- to 10-fold increase in DivK concentration will result in PleC being locked in the kinase form , and the cell will be blocked in the stalked stage of the cell cycle . We propose that in vivo the total concentration of DivK is low enough that it needs to be phosphorylated in order to induce PleC to become a kinase . In this case , the bistable PleC switch becomes reliant on the appearance of DivJ activity rather than on the polar accumulation of DivK . The DivL-CckA-CtrA module bears a striking resemblance to DivJ-PleC-DivK switch . Nonetheless , there are important differences . DivL can phosphorylate CtrA in vitro , but this reaction is of no significance in vivo [22] , [42] . Unlike PleC , which directly transfers its phosphoryl group to an aspartate residue on DivK , CckA relies on a series of phospho-transfer events [23] . To this end , it has an additional aspartate-containing domain which first picks up the phosphoryl group from the histidine residue and passes it on to the histidine residue of a downstream histidine phosphotransfer ( HPt ) protein called ChpT [43] . Finally , ChpT relays the phosphoryl group to the aspartate residue on the response regulator CtrA . In our mathematical equations , we model ChpT and CckA as a single protein , CckA , whose transition from phosphatase to kinase is promoted by binding to substrate , CtrA . The third difference is that CtrA is not known to up-regulate CckA kinase , so there is no reason to expect bistability in the CckA-ChpT-CtrA phospho-relay system . It is a well-established fact that DivK∼P inhibits CtrA activity , and the mechanistic details of this process have become progressively clear . Initial experiments showed that DivK∼P down-regulates CckA kinase activity [12] . Later experiments indicated that DivL is required for maintaining CckA as a kinase , and that DivK∼P binding to DivL inhibits this effect [11] , [44] . Since the mechanistic details regarding how DivL influences CckA activity are currently unknown , we model this process phenomenologically , using a Hill function to describe how DivL promotes CckA kinase . We couple the PleC-DivK∼P bistable switch to the CckA kinase-to-phosphatase transition by having DivK∼P bind to and inactivate DivL . In the swarmer cell , DivJ is absent and the PleC switch is in the phosphatase state ( DivK unphosphorylated ) . Hence , DivL is active and maintains CckA in the kinase state ( CtrA phosphorylated ) . The up-regulation of DivJ is the trigger for the swarmer-to-stalked transition . DivJ activity flips the PleC switch to the kinase state , DivK gets phosphorylated and binds to DivL . DivL activity drops abruptly ( Figure 6A ) , and consequently CckA returns to its default phosphatase form ( Figure 6B ) . As a result , CtrA becomes dephosphorylated and inactive ( Figure 6C and Figure S6D ) , and CpdR becomes dephosphorylated and active ( Figure 6D ) . The proposed coupling of these switches is supported by experimental evidence that a ΔdivJ mutant can be rescued by point mutations in divL and cckA genes [20] . CtrA activity , which is high in ΔdivJ cells ( Figure 7A ) , is restored to normalcy by point mutations in divL and cckA that interfere with CtrA phosphorylation ( Figure 7B–D ) . As expected , CtrA∼P level in a ΔdivJ mutant can be reduced by decreasing the specific activity of DivL ( Figure 7B ) . Interestingly , our simulations show that decreasing the specific activity of CckA kinase lowers the level of CtrA∼P ( Figure 7C ) , but increasing the specific activity of CckA phosphatase does not restore CtrA∼P level ( Figure 7D ) . Hence , we predict that the point mutations in CckA that rescue ΔdivJ mutants do so by reducing the kinase activity of CckA . To simulate the consequences of the divKD90G mutation , we make note of the fact that , in vitro , autophosphorylation of PleC is markedly reduced in the presence of DivKD90G [9] . This fact indicates that DivKD90G , unlike its wild-type counterpart , is unable to up-regulate the kinase form of PleC . Since DivKD90G is not an allosteric ligand , we set , and accordingly updated the equilibrium constants and parameters for all the concerned reactions ( Table S8 ) . In addition , although DivKD90G is phosphorylated to the same extent as wild type DivK , it is unable to bind to DivL [11] . Hence , we altered the binding equilibrium of DivKD90G to DivL ( Table S8 ) . Using the altered parameter set , we tried to reproduce two known phenotypes of divKD90G cells . Filamentous divKD90G cells initiate swarmer progeny-specific development ( SPD ) prematurely . SPD defines a range of cell cycle events , including activation of the flagellum , development of pili , release of the flagellum and ultimately development of the stalk [45] . It is important that these events take place in a timely manner and that they are restricted to the newborn swarmer cell . Filamentous divKD90G mutants , however , initiate SPD in the pre-divisional cell . In particular , pilin synthesis ( a part of SPD ) requires CtrA∼P . Hence , we examined whether CtrA∼P level is increased in simulations of divKD90G mutant cells . Figure 8 compares one-parameter bifurcation diagrams for wild-type ( green ) and mutant ( red ) cells . The levels of DivK∼P ( Figure 8A ) , PleD∼P ( Figure 8B ) and PleC kinase ( Figure 8C ) are much lower in mutant cells , while CtrA∼P level remains high ( Figure 8D ) . This could potentially lead to initiation of SPD . The divKD90G mutation is a suppressor of the pleC::Tn5 mutant phenotype . Cells lacking PleC show extended periods of bipolar localization of DivK∼P and also fail to develop stalks . A pleC::Tn5 divKD90G double mutant does not show any of these defects [45] . Our simulations show that DivK∼P level increases and CtrA∼P level drops in pleC::Tn5 background ( Figure 8E and F ) . Since DivK remains phosphorylated in the absence of PleC , it is not dislodged from the poles [19] . DivK∼P binds to DivL and suppresses CtrA phosphorylation ( Figure 8F ) , thus preventing SPD . However , in the pleC::Tn5 divKD90G double mutant , CtrA∼P level remains high in spite of elevated DivK∼P ( Figure 8E–F , red line ) . This result is in accordance with the finding that CckA∼P , CtrA∼P and Cpdr∼P levels are high when the binding of DivK∼P to DivL is weakened [11] . Restoration of CtrA∼P in the double mutant allows flagellar pole development . Hence , the restoration of unipolar localization of DivK in pleC::Tn5 divKD90G double mutant may be a natural consequence of the inability of DivKD90G to bind to DivL . Although PleC is bifunctional , its designation in the cell has primarily been that of a phosphatase . This view has been fostered by results showing an elevation in DivK∼P in pleC::Tn5 mutants [21] . Furthermore , pleCF778L mutants , which lack autokinase activity , appear to have a normal cell cycle [45] . However , later experiments have shown that , although cells possessing PleCF778L progress through the cell cycle without any problems , they show a marked reduction in holdfast attachment [9] . These cells also show lower c-di-GMP levels , indicating that PleD is not sufficiently phosphorylated and activated in the absence of PleC kinase activity . Another mutant that reduces PleC autokinase activity is divKD90G [9] . In contrast to the pleCF778L mutants , cells possessing the divKD90G mutation do not require cytokinesis to initiate SPD . If both mutations result in loss of PleC autokinase activity , why does only one of them exhibit premature SPD ? One may argue that premature SPD is not due to the loss of PleC kinase activity , but is instead a consequence of inability of DivKD90G to bind to DivL . However , we found that altering the rate constants governing the binding reaction had no effect on the phenotype , because DivKD90G∼P is low at all times and hence does not inhibit DivL . To shed light on this discrepancy , we propose a novel mutant strain of DivK , which we call divKX . The novel mutant deviates from divKD90G in that it retains wild type ability to bind to DivL . By simulations , we compare the phenotypes of divKD90G , divKX and pleCF778L ( see Figure 9 ) . To model the pleCF778L mutant , we set the autophosphorylation rates to zero ( Table S8 ) . In comparison to wild type , pleCF778L cells show a reduction in the level of PleD∼P; but DivK∼P and PleC kinase levels show only modest difference ( Figure 9A and C ) . This simulated comparison agrees with experimental observations , which show that pleCF778L cells have reduced surface attachments but otherwise cycle normally . We reason that , although pleCF778L does not have kinase activity , it still retains its ability to switch to the kinase form . Hence , in stalked and pre-divisional cells , the majority of PleC is locked in the inactive kinase conformation . It follows that the PleC phosphatase to DivJ ratio is low and most of the DivK is phosphorylated . In comparison , divKD90G and a divKX show a reduction in the PleC kinase level ( Figure 9B and D ) . Since most PleC is in the phosphatase form , DivK∼P level is low and CtrA∼P level remains high throughout the cell cycle , thereby initiating SPD prematurely . Based on these simulation results , we propose that PleC kinase is important to prevent premature SPD . In the pre-divisional cell prior to compartmentalization , DivJ maintains PleC as a kinase while DivK is phosphorylated and bound to the pole/s . Once cytokinesis occurs , DivJ and PleC find themselves in different compartments , causing PleC to switch back to a phosphatase and allowing SPD .
We propose a model of the Caulobacter swarmer-to-stalked ( G1-to-S ) transition based on a pair of bifunctional histidine kinases , PleC and CckA . We suggest that the phosphatase-to-kinase transition of the PleC bifunctional enzyme is governed by concerted conformational changes brought about by homotropic interaction with its response regulator , DivK . By formulating a mathematical model based on a set of elementary chemical reactions , we show that the transition from phosphatase to kinase can function as a bistable switch driven by the starter kinase , DivJ . Our simulations reproduce the in vitro experimental observation that DivK and/or DivK∼P up-regulate PleC kinase activity . We hypothesize that even if DivK and DivK∼P have equal potential for causing the conformational change of PleC , DivK∼P is a more efficient inducer as a natural consequence of it being a substrate to the relaxed form , the phosphatase form of PleC . That DivK∼P is a more efficient inducer of the phosphatase-to-kinase transition creates a positive feedback loop and the potential for bistability , and bistability would explain why the swarmer-to-stalked transition is irreversible [35] . The swarmer-to-stalked transition is triggered by a rise in activity of the starter kinase DivJ . Evidence suggests that DivJ accumulates in response to nutritional signals [39] . Compared to well-fed cells , a greater fraction of Caulobacter cells are devoid of DivJ foci and exist as swarmer cells under conditions of glucose exhaustion . Hence , we consider DivJ as a nutritional proxy and use it as a control parameter in our model . As observed in our bifurcation diagrams , as total DivJ accumulates , the proteins that drive the swarmer-to-stalked transition show abrupt and irreversible changes in activity at the boundary of the bistable region . Once the transition has occurred , the control system will not permit a reverse transition ( stalked-to-swarmer ) in response to a marginal drop in nutritional level ( i . e . , in total DivJ concentration ) . In our view , once the PleC flips to the kinase form , the cell is committed to a new round of DNA synthesis before it can make a new motility apparatus in the pre-divisional stage . While bistability is not an essential feature of the morphological transitions in the Caulobacter division cycle , we propose that bistability in the PleC phosphatase-to-kinase transition may ensure that the swarmer-to-stalked transition is robust and does not undergo a reverse transition in response to small fluctuations in nutrient levels . Our model is able to reproduce phenotypes of known experimental mutants and provide additional insight into the underlying physiology . Mutants overexpressing DivK show a decrease in CckA phosphorylation , in addition to filamentous growth and chromosomal over-replication [43] . Our two-parameter bifurcation diagrams indicate that cells with elevated DivK can no longer be regulated by DivJ . At higher concentrations , DivK can drive the positive feedback even in the absence of DivJ , resulting in PleC being in the kinase form and CtrA∼P being down-regulated . This prediction can be tested by overexpressing DivK in a ΔdivJ background . Conversely ΔdivJ mutants with a normal level of DivK are blocked in G1 phase owing to high CtrA∼P , while point mutations in divL and cckA rescue ΔdivJ mutants [20] . Our simulations suggest that ΔdivJ mutants can be rescued by point mutations that down-regulate CckA kinase activity , but not by mutants that up-regulate CckA's phosphatase activity . Prior experiments and a mathematical model [46] dealing with the PleC-DivJ-DivK system have focused almost exclusively on the phosphatase form of PleC , while the kinase form has been considered inconsequential . We argue on the contrary that PleC kinase activity is important for proper progression through the Caulobacter cell cycle . To demonstrate this claim , we make an important distinction between two mutants pleCF778L and divKD90G . Our simulations show that while PleCF778L has no autokinase activity , the majority of PleCF778L molecules in stalked cells are in an inactive kinase form . These cells would therefore , appear normal . On the other hand , most PleC molecules remain in the phosphatase form in cells containing DivKD90G . We predict that in wild-type pre-divisional cells , PleC localized at the new pole is in the kinase form . Compartmentalization has the effect of withdrawing DivJ , causing PleC to switch back to the phosphatase form , as seen in our signal-response curves . The PleC-containing compartment , in the absence of DivJ , transitions into a swarmer cell . In mutant divKD90G cells , we predict that PleC at the new pole is always a phosphatase . This , we reason , would cause the premature presence of CtrA∼P in pre-divisional cells resulting in premature swarmer progeny-specific development ( SPD ) . This conclusion is supported by the fact that filamentous divKD90G mutants show SPD in the absence of compartmentalization [45] . We are aware that divKD90G has a pleotropic effect of binding weakly to DivL . Hence , we hypothesize a novel mutant , divKX , which is similar to divKD90G but retains its ability to bind DivL . We simulate such a mutant and find its behavior to be comparable to divKD90G . In this work , we are focusing on a small window in the Caulobacter cell cycle , the G1-to-S transition . We have not explored here how these coupled switches would function in a spatio-temporal context and whether they play a role in generating asymmetry in the two halves of the cell at a later stage in the division cycle . To explore these questions requires a spatio-temporal model that tracks the location of proteins in the cell and takes into account the effects of protein diffusion through the cytoplasm , as in [12] , [46] . Without an accurate spatio-temporal model of these molecular interactions , we are still a long way from understanding the network of molecular interactions that governs the asymmetric life cycle of Caulobacter crescentus .
The complete reaction network ( Figure S1 ) was translated into a system of 52 non-linear ordinary differential equations ( Table S4 ) using the mass-action law of chemical kinetics , with one exception . The mechanism by which DivL promotes the kinase form of CckA is unknown , so we modeled this step phenomenologically with a Hill function . Because there are many closed loops of elementary chemical reactions in Figure S1 , we must choose rate constant values that respect the thermodynamic principle of detailed balance , as explained in Text S1 . As long as we satisfy these thermodynamic constraints , we find that the reaction network exhibits bistability over a robust range of parameter values . The parameter values that we use for our simulations of the full model ( Table S4 ) are given in Table S5 . The full model can be simplified slightly by reducing the first 28 equations in Table S4 to the first 20 equations in Table S6 , as explained in Text S1 , section D , and confirmed in Figure S4 . The equations for both the full model and the reduced model were encoded as . ode files ( Text S2 , S3 , S4 , S5 ) and simulated using the freely available software , XPP-AUT . The signal-response curves were drawn using the AUTO facility of XPP-AUT . From the data points generated by XPP-AUT , the plots shown in the figures were generated using the python library , Matplotlib [47] . Figure 3 is a simulation of the full model described in Table S4 , while Figures 4–9 are simulations of the reduced model and its corresponding mutants ( Table S4 and Table S8 ) .
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Recent evidence suggests that the transition of PleC from phosphatase to kinase is induced by its own substrate , DivK . Based on experimental clues , we propose a molecular mechanism to explain this substrate-induced conformational change in PleC . The general principles of thermodynamics , enzyme-substrate reactions and the Monod-Wyman-Changeux model of allostery motivate the elementary chemical reactions proposed in our model . Formulating our hypothesis in terms of nonlinear ordinary differential equations , we show that the PleC transition could function as a bistable switch . Although initial experimental studies have suggested that the primary role of PleC is as a phosphatase , our simulations show that the PleC kinase form is relevant for the correct temporal regulation of the Caulobacter cell cycle .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[] |
2013
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Potential Role of a Bistable Histidine Kinase Switch in the Asymmetric Division Cycle of Caulobacter crescentus
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The Varicella Zoster Virus ( VZV ) is a ubiquitous human alpha-herpesvirus that is the causative agent of chicken pox and shingles . Although an attenuated VZV vaccine ( v-Oka ) has been widely used in children in the United States , chicken pox outbreaks are still seen , and the shingles vaccine only reduces the risk of shingles by 50% . Therefore , VZV still remains an important public health concern . Knowledge of VZV replication and pathogenesis remains limited due to its highly cell-associated nature in cultured cells , the difficulty of generating recombinant viruses , and VZV's almost exclusive tropism for human cells and tissues . In order to circumvent these hurdles , we cloned the entire VZV ( p-Oka ) genome into a bacterial artificial chromosome that included a dual-reporter system ( GFP and luciferase reporter genes ) . We used PCR-based mutagenesis and the homologous recombination system in the E . coli to individually delete each of the genome's 70 unique ORFs . The collection of viral mutants obtained was systematically examined both in MeWo cells and in cultured human fetal skin organ samples . We use our genome-wide deletion library to provide novel functional annotations to 51% of the VZV proteome . We found 44 out of 70 VZV ORFs to be essential for viral replication . Among the 26 non-essential ORF deletion mutants , eight have discernable growth defects in MeWo . Interestingly , four ORFs were found to be required for viral replication in skin organ cultures , but not in MeWo cells , suggesting their potential roles as skin tropism factors . One of the genes ( ORF7 ) has never been described as a skin tropic factor . The global profiling of the VZV genome gives further insights into the replication and pathogenesis of this virus , which can lead to improved prevention and therapy of chicken pox and shingles .
Human varicella-zoster virus ( VZV ) is a widespread human alpha-herpesvirus , and the majority of the US population has been previously exposed [1] . VZV is the causative agent of chicken pox and shingles , the latter of which is associated with a significant incidence of post-herpetic neuralgia [2] , [3] . A universal chicken pox vaccine ( v-Oka strain ) was first introduced to the United States in 1995 , and this immunization program has dramatically reduced chicken pox incidence [4]–[10] . However , outbreaks of chicken pox are still seen [11]–[13] , and shingles remains an important concern because the current shingles vaccine only reduces the risk of infection by about 50% [14] . Therefore , VZV is still an important pathogen and remains a public health concern in the U . S . [7] , [15] . A better understanding of the biology and pathogenesis of VZV is essential to improve the medical prevention and the treatment of VZV infections . VZV is the smallest member of the human herpesvirus family , with a linear double-stranded DNA genome ( 125 kb ) that encodes 70 unique ORFs . As a result of the recent development of a VZV cosmid system and of the severe combined immunodeficient mouse model with xenografts of human tissue ( SCID-hu ) , many viral ORFs have been investigated in both biochemical and functional studies , shedding light upon several VZV gene functions [16]–[18] . However , the majority of VZV's 70 unique ORFs have not been studied , and their roles in viral replication and cell-/tissue-specific pathogenesis remain unclear . This is partly due to the absence of an efficient genetic tool to quickly isolate a large number of mutants and a true animal model to screen for in vivo virulence factors on a large scale [2] . Though the functions of many ORFs can only be predicted based on their homologies to other herpesviruses , such as herpes simplex virus 1 , our direct manipulation of VZV's ORFs has enabled us to provide functional annotations for the entire VZV genome . The knowledge of VZV replication and pathogenesis is limited , in part because of its highly cell-associated nature in cultured cells and the difficulty of generating recombinant viruses . In order to circumvent some of these problems , we cloned the VZV ( p-Oka strain ) genome as a bacterial artificial chromosome ( BAC ) carrying both green fluorescent protein ( GFP ) and luciferase reporter genes [19] . We then systematically deleted every open reading frame in the VZV genome . An overview of our method for genome-wide mutagenesis is shown in Figure 1 . With a highly efficient homologous recombination system and the dual-reporter system , the recombinant viruses were isolated and analyzed . Human fetal skin organ culture ( SOC ) has been previously established to mimic VZV skin infection , which allows for the study of VZV replication and pathogenesis [20] . We further combined SOC with the luciferase assay-based viral detection method to facilitate screening of skin tropism determinants . Although many investigators utilize SCID-hu models ( grafts of human tissue in severe combined immunodeficient mice ) to study VZV pathogenesis in vivo [21] , SOC is a more suitable and cost efficient approach for genome-wide screening the VZV mutant phenotypes . Nevertheless , any interesting findings can be further verified by further in-depth SCID-hu model studies . The luciferase VZV BAC ( VZVLuc ) was used to individually delete and/or mutate each of the 70 unique ORFs by employing the E . coli DY380 strain recombination system [22] . As a result , a library of whole-ORF deletion mutants was created . Each mutant DNA obtained from E . coli was transfected into human melanoma ( MeWo ) cells , and the results provide direct evidence of that 44 ORFs are essential for viral replication in cultured MeWo cells and 26 are non-essential . Moreover , among the non-essential gene group , 8 ORF deletion mutants showed significant growth defects compared to the wild-type strain ( p-value <6 . 07×10−21; see “Statistical Analysis of Mutant Growth Kinetics” section in Materials and Methods ) , while 18 ORFs were dispensable . All 26 non-essential ORF deletion mutant VZV variants obtained have been tested in SOC . Interestingly , four ORFs were found to be required for optimal viral replication in cultured skin tissue samples , but not in MeWo cells , suggesting their potential roles as skin tropism factors . The results obtained from this study are in agreement with most of those regarding these particular ORFs that have been published to date , and we have provided explanations of all possible discrepancies in the literature . Overall , we provide 51% novel functional annotations to the VZV proteome ( 36 ORFs ) .
All VZV ORF deletion mutants were constructed from BAC mutants with a luciferase reporter ( VZVLuc ) using a PCR-based approach [19] , [22] ( also see Supplementary Text S1 ) . Construction of ORF rescued BAC mutants was carried out by adapting a two-step homologous recombination approach in E . coli [19] , [22] ( also see Supplementary Text S1 ) . The generation of a rescue virus is important in order to prove that the deleted fragment was responsible for any growth defect observed in analyses of the mutants . The rescue virus should be able to fully restore the wild-type phenotypes . Because of the large number of ORFs , we chose a small subset of VZV open reading frames to rescure and we have shown these rescue mutants behave as the wild –type strain . A detailed description of these protocols is provided in [19] , [22] and an overview is shown in Figure 1 . Previous studies in our laboratory have shown that the BAC mutant has an identical growth curve to the wild-type virus [19] and that addition of the luciferase reporter to the BAC virus does not change its growth properties [22] . All of VZV's 70 unique ORFs were deleted and analyzed based on a bioluminescence detection method , as described previously [19] . For 14 ORFs that overlap with adjacent ORFs ( ORF8 , ORF9A , ORF25 , ORF26 , ORF27 , ORF28 , ORF46 , ORF47 , ORF48 , ORF49 , ORF50 , ORF54 , ORF59 and ORF60 ) , respective partial ORF deletions have been constructed and analyzed . A detailed description of these partial ORFs is included in Supplementary Table S2 . The results suggest that 44 ORFs are essential for viral replication in cultured MeWo cells ( Table 1 and Figure 2 ) . We have confirmed that ORF4 and ORF5 are essential by making genetic rescue viruses . For the essential group , we provide novel functional annotations for 31 of 44 ORFs . All of these VZV essential genes have HSV-1 homologies ( Table 1 ) , and the majority of them are conserved among other herpesviruses . These ORFs encode important viral structural proteins , enzymes involved in DNA replication , and transcriptional regulatory proteins . Among VZV's 44 essential ORFs , the majority encodes proteins with vital functions throughout the viral life cycle . Most VZV proteins that regulate transcription ( ORF4 , ORF62/71 , ORF63/70 , and ORF 61 ) were found to be essential in this study . ORF4 and ORF62/71 are incorporated into the viral tegument , and both encode immediate-early ( IE ) proteins with transcriptional regulatory activity [23]–[26] . ORF4 and ORF62/71 have been extensively studied , and their essential natures have been suggested previously [27] , [28] . Both ORF63/70 and ORF61 encode phosphoproteins primarily localized to the nuclei of infected cells [25] . Although it has been suggested that ORF 63/70 is not essential for viral replication in vitro [29] , we could not generate a viable virus from a 63/70 double deletion; this result is in agreement with several other studies [30] , [31] . Most of the VZV ORFs that encode glycoproteins are essential . Glycoprotein K ( gK ) ( encoded by ORF5 ) [32] , gB ( ORF31 ) , gH ( ORF37 ) , gM ( ORF50 ) [33] , gL ( ORF60 ) [34] , [35] , and gE ( ORF68 ) [32] , [36] are required for viral replication , and many of them had previously been investigated and reported . Only glycoprotein C ( ORF14 ) [37] , [38] and gI ( ORF67 ) [36] , [39] , [40] deletion mutants produced viable viral progenies , and both of these mutants appeared to suffer a severe growth defect . The results regarding the essentiality of VZV glycoprotein genes in this study are in agreement with the published data . Essential VZV genes have significantly different enrichment for functional categories than do non-essential genes ( Figure 3A ) . In order to make this calculation , we first listed every gene in a functional category , such as “DNA replication” for a DNA polymerase gene . Then , we compared the proportion of essential ( and then of non-essential ) genes in each functional category to the background rate expected by chance ( e . g . the proportion of genes in that functional category for the entire VZV genome ) . This calculation was performed using a hypergeometric test . For example , essential genes are significantly enriched for DNA replication ( Bonferroni corrected p-value <10−4 ) and for DNA packaging ( Bonferroni corrected p-value <10−4 ) ; ORF28 encodes the catalytic subunit of VZV DNA polymerase and ORF16 encodes the subunit of the viral DNA polymerase processivity factor [2] . DNA binding proteins include proteins encoded by ORF6 ( primase ) , ORF29 , ORF33 ( capsid protein ) , ORF41 ( capsid protein ) , ORF51 ( helicase ) , ORF52 ( component of helicase/primase complex ) , and ORF55 ( component of helicase/primase complex ) [41] , [42] . Not surprisingly , almost all of the ORFs that encode DNA packaging proteins—including ORF25 , ORF26 , ORF30 , ORF34 , ORF42/45 , ORF43 , ORF54 , and nucleocapsid proteins including ORF21 , ORF33 . 5 , and ORF40—also fall into the essential gene category . In contrast , non-essential genes were significantly enriched for other ( Bonferroni corrected p-value <10−3 ) and unknown ( Bonferroni corrected p-value <0 . 01 ) functional categories ( Figure 3B ) . In this study , we found that 26 ORFs are non-essential genes and 6 of these lack HSV-1 homologies ( ORF0 , ORF1 , ORF2 , ORF13 , ORF32 , and ORF57 ) ( Table 1 ) . According to the growth kinetics ( in cultured MeWo cells ) , 8 ORF mutants had significant growth defects ( p-value <6 . 07×10−21 ) , and the peak signals of the viral detection assay were at least 5-fold less than were those of the wild-type parental strain ( Figure 4A ) . Two of these VZV ORF deletion growth phenotypes , ORF18 and ORF32 , have not been previously reported , and two others ( ORF23 and ORF35 deletions ) have been confirmed to have growth defects in vitro , which is in accordance with previously published data [43] , [44] . ORF0 deletion's growth defect has been confirmed by making its genetic revertant [19] . ORF18 and ORF19 respectively encode the small and large subunits of ribonucleotide reductase , and both of them diminished viral growth when deleted in this study . The result on ORF19 is in accordance with previous publications [45] . ORF32 encodes a phosphoprotein that is post-translationally modified by ORF47 protein kinase [46] . Among these 8 viral mutants showing severe growth defects , atypical morphology of virally infected cells was frequently observed , including reduced plaque sizes and altered syncytia formation . The remaining 18 VZV ORFs had wild type growth curves for viral replication in cultured MeWo cells . In vitro growth curve analysis showed that these ORF deletion mutants had the same growth kinetics as their wild-type parental strain , VZVLuc ( Table 1 ) . Previous studies have reported that 15 of these genes ( ORF1 , ORF2 , ORF3 , ORF8 , ORF10 , ORF11 , ORF12 , ORF13 , ORF14 , ORF47 , ORF57 , ORF59 , ORF58 , ORF64/69 , and ORF65 ) are non-essential [17] , [31] , [38] , [46]–[54] . In this study , three of these ORF mutants ( ORF7 , ORF15 , and ORF36 ) have been shown to be dispensable for in vitro viral replication for the first time . The human fetal skin organ culture ( SOC ) model has been proven to be a simple and convenient alternative to the SCID-hu mouse model in the study of VZV pathogenesis [20] , especially in the case of an initial genome-wide screening for skin tropism determinants . Although 26 VZV ORFs were found to be non-essential for viral replication in cultured MeWo cells , it was possible that some of these viral genes encode proteins critical for optimal viral infection in skin tissue . To test this hypothesis , all 26 non-essential ORF deletion viruses were further analyzed in cultured skin-tissue samples . Every deletion mutant that showed severe growth defects in cultured MeWo cells also demonstrated significantly slow growth kinetics in human skin samples when compared to wild-type VZV ( p-value <9 . 05×10−19 ) . Only two of these genes ( ORF35 and ORF67 ) have been previously reported to be required for viral growth in SCID-hu skin mouse models [40] , [44] . Therefore , we have been able to provide novel functional annotations for the other 6 deletion mutants with severe growth defects . Many non-essential genes appear to cluster together , particularly between ORF0 to ORF15 ( Figure 2 ) . More than 70% of ORFs ( 12 out of 17 ) in this region are non-essential , compared to 37% of the entire genome . Four out of six VZV ORFs without HSV-1 homologues are also located in this region , so this region may be more evolutionarily variable compared to other highly conserved regions Among the 18 VZV ORFs dispensable for viral replication in cultured MeWo cells , 14 were also dispensable for viral replication in skin tissue ( Table 1 ) . Among the above 14 deletion mutants , we have been able to provide novel ex vivo functional annotations for all but one of these 18 genes ( ORF64/69 ) [31] . Interestingly , among non-essential VZV ORFs , four ORFs ( ORF7 , ORF10 , ORF14 , and ORF47 ) appear to have selective impacts on viral replication in skin tissue . The growth of each virus in SOC was compared with its growth in cultured MeWo cells . These ORF deletion mutants grew like the wild-type strain in vitro ( Figure 4B ) . In contrast , they showed significant growth defects in skin organ cultures ( p-value <9 . 51×10−19; Figure 4C ) . For instance , the ORF10 deletion mutant had a growth defect in SOC . The bioluminescence signal kept increasing during the entire 7-day experiment period; the total photon count values consistently remained approximately 10-fold less than those of the wild-type strain . The ORF7 deletion mutant virus quickly reached its growth peak around 3 days after inoculation , and then bioluminescence steadily declined . To prove that the VZV ORF7 and ORF10 growth defects observed in cultured skin-tissue samples were due to the functions of the deleted genes rather than to undesirable mutations in other regions of the genome , rescue viruses ORF7R and ORF10R were generated . The growth curve analysis indicated that ORF7R and ORF10R viruses grew in MeWo cells indistinguishably from wild-type VZV , as expected ( Figure 4B ) . In skin organ cultures , they were also able to fully recover the growth defects of the corresponding deletion mutant viruses and grew as well as the wild-type strain ( Figure 4C ) . In contrast , ORF47 deletion virus had a more severe growth defect , approximately 80–100 fold ( 2 log ) less than wild-type VZV . Our results suggest these three ORFs are important for viral replication in human skin tissue but not in cultured MeWo cells . Three skin-tropic virulence factors ( ORF10 , ORF14 , and ORF47 ) have been previously identified . VZV ORF10 encodes a tegument protein that enhances transactivation of VZV genes , and it was shown to be dispensable for VZV replication in vitro [47] . Recent studies showed that ORF10 protein is required for efficient VZV virion assembly and is a specific determinant of VZV virulence in SCID-hu skin xenografts but not in human T cells in vivo [55] , [56] . ORF14 ( gC ) has been reported to have reduced infectivity in an SCID-hu skin model [38] . VZV ORF47 encodes a serine/threonine protein kinase and was shown to be dispensable for viral replication in cultured MeWo cells [48] . It has been designated as a virulence factor for both skin tissue and T cells in SCID-hu models [38] . The findings of these three skin-tropic ORFs not only confirmed previous studies but also further verified the similarity between SCID-skin and SOC systems . In the current study , ORF7 has been identified as a novel skin-tropic virulence factor . In order to confirm the accuracy of our results , we also produced a premature stop-codon mutant ( ORF7S ) by mutating the 5th codon from TGT to the TGA stop codon ( see Table S1 ) . Just like ORF7D , ORF7S showed wild-type growth in MeWo ( Figure 4B ) but had a growth defect in SOC ( Figure 4C ) .
In this study , a global functional analysis of the entire VZV genome was performed that emphasized the identification of viral ORFs important for viral replication both in cultured MeWo cells and human fetal skin organs . We took full advantage of the highly efficient luciferase VZV BAC system and obtained a library of single ORF deletion mutants . Advanced live culture bioluminescence imaging technology allowed us to systematically test a large number of mutant viruses for comparing viral growth kinetics in different systems . VZV has a 125-kb DNA genome encoding 70 unique open reading frames ( Table 1 , Figure 2 ) . In this study , all of the predicted 70 ORFs were individually deleted . Our results directly showed that 44 ORFs encode essential genes and 26 ORFs encode non-essential genes . Among the non-essential group , 8 ORF deletion mutants suffered severe growth defects in MeWo cells . Fourteen ORFs were shown to be dispensable for viral replication , both in MeWo cells and in SOC . We also found 4 tissue tropic factors ( ORF7 , ORF10 , ORF14 , and ORF47 ) that showed a growth defect in SOC but normal growth in MeWo . Three of these tissue-tropic factors ( ORF10 , ORF14 , and ORF47 ) have been previously identified , but ORF7 has never been previously studied . In the current study , we have reported ORF7 as a novel VZV skin-tropic factor . ORF7 encodes a 29-kDa tegument protein , and its function remains unknown . The homolog of the VZV ORF7 protein in the herpes simplex virus is the UL51 protein . Recent studies showed that deletion of HSV-1 UL51 causes reduced size plaque formation and low infectivity [56] . Similarly , the function of the UL51 gene product of the pseudorabies virus ( PrV ) has been investigated by generating a deletion mutant , and the result suggested that the UL51 protein is involved in viral egress , but is not essential for viral replication [57] . Our result suggests that VZV ORF7 might serve as a skin-specific virulence factor . However , the role of ORF7 in pathogenesis needs further investigation . Despite the large differences between herpesvirus genomes ( ranging from 125 kb to >230 kb ) , all the herpes viruses studied thus far have a similar number of essential genes . For example , HSV-1 encodes 37 essential genes and 48 non-essential genes [58]; human cytomegalovirus ( HCMV ) , which is one of the largest human DNA viruses , encodes 45 essential genes and 117 non-essential genes [59] . Our data suggest that VZV , which contains the smallest genome , encodes 44 essential genes and 26 non-essential genes . A comparison between the essentiality of HSV-1 and HCMV homologues to essential VZV genes is provided in Supplementary Table S3 . Of the 44 essential genes , 26 have essential homologues in HSV , and all essential gene homologues conserved in CMV ( 18 of 44 essential VZV genes ) are essential . Therefore , we believe that several of these essential genes perform core functions for all of these herpesviruses . Unlike the other functional profiling studies performed on HCMV [59] , our results did not reveal any VZV-encoded factors that repress viral replication in cultured MeWo cells or in human fetal skin tissue . If such VZV temperance genes existed , enhanced growth kinetics should have been observed by making the corresponding ORF deletion mutants . There is also an apparent size difference between essential and non-essential ORFs . Essential ORFs are significantly larger in size compared to non-essential ones ( μ = 1250 bp vs . μ = 970 bp , respectively , p = 6×10−4 by t-test ) . The 10 largest VZV ORFs are all essential , while 8 out of 11 VZV ORFs less than 600 bp are non-essential . All of our results are in agreement with previous VZV functional annotations , except for those on ORFs 9A , 17 , 61 and 66 , for which we could not generate viral deletion mutant progenies with sufficient titers for growth studies . For example , previous studies indicated that was ORF9A not essential viral growth in cell culture ( due to insertion of a premature stop codon ) yet they also showed that failure to express either of these genes resulted in growth defects [60] . Therefore , we believe that our findings are at least in partial agreement with previous studies because this previous study utilized a premature stop codon ( thus allowing expression of a partial protein ) , whereas we completely removed ORF9A from the VZV genome . Although some studies have shown ORF17 to be dispensable for viral replication [61] , other studies have shown the gene to be essential for growth under certain conditions [62] . Therefore , we believe this discrepancy can probably be explained by subtle differences in experimental design ( such as the temperature of the growth culture , as described in [62] , and we believe that our analysis for ORF17 deletion best reflects conditions in vivo . ORF61 has also been suggested to be a non-essential gene for viral replication in vitro in a previous study [63] , [64] . However , we could not retrieve enough infectious viral progeny from the ORF61 deletion clone , even after repeated transfection and extensive incubation . Large deletion mutants of ORF61 [63] and promoter bashing experiments [64] have shown ORF61 to be important for viral replication ( albeit non-essential ) due to a considerable growth defect shown in the deletion . However , no complete deletion virus has ever been created , so it is possible that the large deletions may have only been sufficient to cause a growth defect , whereas our complete deletion results in a complete loss of VZV replication . ORF66 has been previously cited as dispensable for viral replication , but we have found it to be essential [65]–[67] . In previous studies , a premature stop codon mutant of ORF66 resulted in a decrease in viral titer , but not in a complete loss of viral replication [65] , [66] . Premature stop codons were inserted such that more than 50% of the original coding sequence remained and was able to be expressed , so we believe this discrepancy can be explained by the possible attenuated activity of the partial protein ( which did have a substantial growth defect ) , while our ORF66 deletion removed the entire sequence . For the cosmid-based studies [67] , [68] , a premature stop codon mutant ( with a 21-amino acid partial protein expressed ) had to be used to assess the impact of ORF66 on viral replication . However , the authors [68] were also unable to produce infectious virus with a complete ORF66 deletion mutant ( which is identical to our results ) . In this study , we have presented novel functional annotations for 36 VZV genes . Due to the global nature of our study and the lack of well-defined upstream and downstream regulatory regions for most VZV genes , some of our annotations may have to be redefined by more detailed studies ( genes most likely to be affected by adjacent genes are specifically noted in Table 1 ) . Moreover , the current profiling study has provided the first global view of VZV genomic functions in viral replication , which is likely to serve as the basis for further investigative studies on many VZV genes .
Human melanoma ( MeWo ) cells were grown in DMEM supplemented with 10% fetal calf serum , 100U of penicillin-streptomycin/ml , and 2 . 5ug of amphotericin B/ml , as previously described , and used to propagate VZV in vitro [18] , [69] . VZVLuc containing the entire p-Oka VZV genome was constructed as previously described [19] . Recombinant VZVLuc virus was derived by transfection methods [19] , [22] ( also see Supplementary Text S1 ) . All primer sequences are listed in Supplementary Table S1 . Primer sequences were designed based upon the Dumas VZV strain ( Accession Number: NC_001348 ) . VZVLuc DNAs were transfected into MeWo cells using the FuGene 6 transfection kit ( Roche , Indianapolis , IN ) [19] , [22] ( also see Supplementary Text S1 ) . Recombinant viruses were titrated by infectious focus assay . MeWo cells were seeded in 6-well tissue culture plates and inoculated with serial dilutions of VZV-infected MeWo cell suspensions . Plaques were counted by fluorescence microscopy at 3 days after inoculation . All transfections were performed a minimum of 3 times . Since VZV is highly cell-associated under tissue culture conditions , mutant VZV-infected MeWo cells were harvested , titrated and stored in liquid nitrogen . Wild-type infections served as positive controls and mock infections served as negative controls . In vitro growth curve analyses were carried out by live-cell bioluminescence detection assay . MeWo cells were infected with 100 PFU of infected MeWo cell suspensions on 6-well tissue culture plates . Every 24 h , the cell culture medium was replaced with medium containing 150 ug/ml D-luciferin ( Xenogen , Alameda , CA ) . After incubation at 37°C for 10 min , the bioluminescent signals were quantified and recorded using an IVIS Imaging System ( Xenogen ) , following the manufacturer's instructions . After each measurement , the luciferin-containing medium was replaced with fresh cell culture medium . Measurements were taken daily from the same plate for 7 days . Bioluminescence signal data from each sample were quantified by manually demarcating regions of interest and analyzed using LivingImage analysis software ( Xenogen ) . It has been demonstrated previously that both the infectious center assay and the luciferase assay correlate well [19] , [22] . Human fetal skin-tissue samples ( ∼20 weeks gestational age ) were acquired from Advance Biosciences Resources ( Alameda , CA ) . Skin organ-culture techniques were as previously described [20] . Ex vivo growth curve analyses were carried out by live-tissue bioluminescence assay . Infected MeWo cells were titrated and then re-suspended in skin organ culture media ( SOCM ) . After 24 h of incubation , each skin-tissue section was injected five times with 10 ul of the virus-infected cell suspension ( total inoculation was 5×103 PFU per tissue ) by a 1-ml syringe fitted with a 27-gauge needle attached to a volumetric stepper ( Tridak , Brookfield , CT ) . After inoculation , the sections were placed individually on 500 um mesh NetWell inserts ( Corning , Corning , NY ) that rested above 1ml of SOCM in each well of 12-well plates and followed by a 24 h incubation in a tissue culture incubator , 37°C , 5%CO2 . Each 24 h , SOCM was replaced with media containing 150ug/ml of D-luciferin . Following 10 min incubation at 37°C , the bioluminescence being emitted from individual cultured skin-tissue samples was recorded using the IVIS Imaging System . After the measurements , each sample ( still on a NetWell insert ) was transferred onto new 12-well plates with fresh SOCM . The measuring process was repeated every 24 h for 7 days . Bioluminescence signals from manually defined regions of interest were quantified and analyzed . All experiments were performed in triplicate . Wild-type infections served as positive controls and mock infections served as negative controls . Wild type and mutant growth curves ( 7 time points , 3 replicates each ) were compared using the “timecourse” Bioconductor package [70] , [71] . The difference in growth rate for wild type and mutant growth curves was estimated by the mb . long function was used to estimate a Hotelling T2 test statistic using the mb . long function . P-values for the T2 test statistic were calculated using an F-distribution . The T2 test statistic did an excellent job of quantifying the difference in growth curves , but a very strict p-value cutoff was required in order to define statistically significant growth defects ( implying that the test statistic may be too sensitive ) . Therefore , we used a Mann-Whitney U test in order to determine which individual time points significantly differed between wild type and deletion mutant strains . All strains with reported growth defects have at least 6 significantly reduced time points ( p<0 . 05 ) .
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The Varicella Zoster Virus ( VZV ) is the causative agent of chicken pox and shingles . The long-term efficacy of the current chickenpox vaccine is yet to be determined , and the current shingles vaccine fails to provide protective immunity for a substantial number of individuals . Shingles can also lead to post-herpetic neuralgia ( PHN ) , a debilitating condition associated with an intractable pain that can linger for life . Therefore , VZV remains an important public health concern . We use growth-rate analysis of our genome-wide deletion library to determine the essentiality of all known VZV genes , including novel annotations for 51% of the VZV proteome . We also discovered a novel skin-tropic factor encoded by ORF7 . Overall , our identification of genes essential for VZV replication and pathogenesis will serve as the basis for multiple in-depth genetic studies of VZV , which can lead to improved prevention and therapy of chicken pox and shingles . For example , essential genes may be appealing drug targets and genes whose deletion causes a substantial growth defect may be prospective candidates for novel live attenuated vaccines .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"infectious",
"diseases/viral",
"infections",
"virology"
] |
2010
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Genome-Wide Mutagenesis Reveals That ORF7 Is a Novel VZV Skin-Tropic Factor
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The human immunodeficiency virus 1 ( HIV-1 ) transcriptional transactivator ( Tat ) is essential for synthesis of full-length transcripts from the integrated viral genome by RNA polymerase II ( Pol II ) . Tat recruits the host positive transcription elongation factor b ( P-TEFb ) to the HIV-1 promoter through binding to the transactivator RNA ( TAR ) at the 5′-end of the nascent HIV transcript . P-TEFb is a general Pol II transcription factor; its cellular activity is controlled by the 7SK small nuclear RNA ( snRNA ) and the HEXIM1 protein , which sequester P-TEFb into transcriptionally inactive 7SK/HEXIM/P-TEFb snRNP . Besides targeting P-TEFb to HIV transcription , Tat also increases the nuclear level of active P-TEFb through promoting its dissociation from the 7SK/HEXIM/P-TEFb RNP by an unclear mechanism . In this study , by using in vitro and in vivo RNA-protein binding assays , we demonstrate that HIV-1 Tat binds with high specificity and efficiency to an evolutionarily highly conserved stem-bulge-stem motif of the 5′-hairpin of human 7SK snRNA . The newly discovered Tat-binding motif of 7SK is structurally and functionally indistinguishable from the extensively characterized Tat-binding site of HIV TAR and importantly , it is imbedded in the HEXIM-binding elements of 7SK snRNA . We show that Tat efficiently replaces HEXIM1 on the 7SK snRNA in vivo and therefore , it promotes the disassembly of the 7SK/HEXIM/P-TEFb negative transcriptional regulatory snRNP to augment the nuclear level of active P-TEFb . This is the first demonstration that HIV-1 specifically targets an important cellular regulatory RNA , most probably to promote viral transcription and replication . Demonstration that the human 7SK snRNA carries a TAR RNA-like Tat-binding element that is essential for the normal transcriptional regulatory function of 7SK questions the viability of HIV therapeutic approaches based on small drugs blocking the Tat-binding site of HIV TAR .
Synthesis of mRNAs by Pol II is tightly controlled at the step of transcription elongation by the positive transcription elongation factor b ( P-TEFb ) that is a cyclin-dependent kinase composed of Cdk9 and cyclin T1 ( CycT1 ) [1] , [2] , [3] , [4] , [5] . After transcription initiation and promoter clearance , Pol II is arrested by the negative elongation factor ( NELF ) and the DRB sensitivity-inducing factor ( DSIF ) . To restore productive Pol II elongation , P-TEFb phosphorylates NELF , DSIF and the heptapeptide repeats ( YSPTSPS ) in the C-terminal domain ( CTD ) of Pol II at serine 2 . P-TEFb is a general transcription factor that is required for efficient expression of most protein-coding genes as well as for production of full-length transcripts from the integrated HIV-1 genome [6] , [7] . In the nuclei of HeLa cells , about half of P-TEFb forms a kinase-inactive ribonucleoprotein ( RNP ) with the 7SK snRNA [8] , [9] . The 7SK/P-TEFb snRNP also contains the hexamethylene bisacetamide ( HMBA ) -inducible protein HEXIM1 and less often , HEXIM2 [10] , [11] , [12] , [13] , the La-related protein Larp7 [14] , [15] , [16] and the methylphosphate capping enzyme MePCE [17] , [18] . While Larp7 and MePCE bind stably to and provide stability for 7SK snRNA , P-TEFb and HEXIM1/2 show a dynamic , transcription-dependent association with 7SK . Blocking of Pol II transcription induces dissociation of P-TEFb and HEXIM proteins from the 7SK snRNP to increase the nuclear level of active P-TEFb [8] , [9] , [10] , [11] . On the contrary , inhibition of cell growth shifts P-TEFb from active to inactive 7SK-associated complexes [19] , [20] . Thus , the 7SK snRNA and HEXIM1/2 proteins function as key regulators of Pol II transcription through controlling the nuclear activity of P-TEFb . Malfunction of the 7SK–P-TEFb regulatory machine that abnormally increases P-TEFb activity can lead to development of cardiac hypertrophy or to malignant transformation of the cell [16] , [21] . The human 7SK is a 331 nt-long Pol III-transcribed abundant snRNA [22] . P-TEFb is tethered to 7SK through interacting with HEXIM1 and HEXIM2 that directly bind to the 5′ hairpin of 7SK snRNA in the forms of homo- or heterodimers [11] , [12] , [13] , [23] , [24] , [25] , [26] , [27] . HEXIM proteins interact with two copies of P-TEFb and inhibit their protein kinase activity strictly in a 7SK snRNA-dependent manner [11] , [27] . Binding of 7SK to the positively charged RNA-binding motif of HEXIM1/2 enables the acidic P-TEFb-binding domain of HEXIM1/2 to interact with CycT1 [28] . In vivo docking and inactivation of P-TEFb by the 7SK snRNP also requires the binding of CycT1 , either directly or indirectly , to the 3′ hairpin of 7SK snRNA [26] . Transcription initiated from the long terminal repeat ( LTR ) promoter of the integrated HIV-1 genome is controlled predominantly at the level of elongation [1] , [29] , [30] . The processivity of HIV transcription depends on the viral transactivator Tat that recruits P-TEFb to the stalled Pol II [31] , [32] . To capture P-TEFb , the activation domain of Tat associates with CycT1 and its RNA-binding motifs binds to the transactivation response element , TAR , an RNA hairpin at the 5′ end of the nascent HIV LTR transcript [33] , [34] , [35] , [36] . Besides tethering P-TEFb to the TAR RNA , recent studies demonstrated that Tat also promotes the disassembly of the 7SK/HEXIM/P-TEFb snRNP to increase the nuclear level of active P-TEFb [37] , [38] . Indeed , efficient transcription from the HIV LTR promoter requires considerably higher P-TEFb activity than that is needed for cellular mRNA production and host cell viability [6] , [31] , [39] , [40] , [41] . The molecular mechanism of Tat-mediated regulation of nuclear P-TEFb activity is unclear . Tat has been proposed to compete with HEXIM to displace it either from the CycT1 subunit of P-TEFb or from the 7SK snRNA [37] , [38] . In this study , we demonstrate that in HIV-infected cells , the 7SK transcriptional regulatory snRNA is the major RNA target of the accumulating Tat protein . HIV Tat binds with high specificity and efficiency to an evolutionarily highly conserved TAR RNA-like stem-bulge-stem motif of the 5′ hairpin of 7SK snRNA . We demonstrate that the newly discovered Tat-binding site of 7SK is imbedded in the HEXIM-binding elements of 7SK and therefore , Tat promotes disassembly of the 7SK/HEXIM/P-TEFb negative transcriptional regulatory snRNP through displacing the HEXIM homodimer from the 7SK snRNA .
To test whether Tat can interact with 7SK snRNA in living cells , Flag-tagged Tat ( Tat-FL ) was transiently expressed in human HeLa cells and recovered by immunoprecipitation ( IP ) with an anti-Flag antibody ( Figure 1A ) . As demonstrated by Western blot analysis , the expressed Tat-FL protein interacted with the Paf1 component of the recently reported Tat/P-TEFb-associated elongation complex , indicating that it was functionally active [42] . HeLa RNAs co-precipitated with Tat-FL were 3′ end-labeled with [5′-32P]pCp and T4 RNA ligase and analyzed on a denaturing gel ( Figure 1B , lane 2 ) . Autoradiography revealed that Tat-FL bound to a unique RNA with an electrophoretic mobility corresponding to the 331 nt-long human 7SK snRNA . To determine unequivocally its identity , the terminally labeled Tat-associated RNA was partially digested with the G-specific endoribonuclease T1 or it was moderately hydrolyzed with alkali before fractionation on a sequencing gel ( Figure 1C ) . Distribution of the G residues in the 3′-terminal part of the Tat-associated HeLa RNA perfectly matched with the nucleotide sequence of human 7SK snRNA . The faint band duplications above the RNase T1 digestion products indicate sequence heterogeneity at the 3′ end of 7SK snRNA [43] . To rule out that Tat-FL associated with 7SK in the cell extract , we performed in vivo cross-linking experiments ( Figure 1D ) . HeLa cells expressing Tat-FL were treated with formaldehyde and after extract preparation , Tat-FL was immunoprecipitated under highly stringent conditions [44] . RNase A/T1 protection analysis confirmed that 7SK snRNA was efficiently cross-linked to Tat-FL in vivo ( lane 5 ) . In control IPs performed in the absence of antibody ( lane 4 ) or from non-cross-linked cell extract ( lane 2 ) , no 7SK-Tat-FL interaction was detected under the applied harsh wash conditions . We concluded that Tat specifically and most probably , directly interacts with 7SK snRNA in living cells . To define the region of 7SK snRNA which interacts with Tat , we assayed the in vivo interaction of transiently expressed truncated 7SK RNAs with Tat-FL by IP with an anti-Flag antibody followed by Northern blot analysis ( Figure 2A ) . Co-precipitation of the endogenous HeLa 7SK snRNA with Tat-FL provided a positive control for each IP reaction . Removal of the 3′ hairpin of 7SK , although largely compromised the stability of the truncated d3′HP RNA ( lanes 9 and 11 ) , failed to prevent its association with Tat-FL ( lane 12 ) . In contrast , deletion of the 5′ hairpin eliminated the interaction of d5′HP RNA with Tat-FL ( lane 8 ) . Finally , the 5′HP RNA that represented the 5′ hairpin of 7SK efficiently interacted with Tat-FL ( lane 4 ) , demonstrating that HIV Tat binds to the 5′ hairpin of 7SK snRNA . Tat recognizes an internal stem-bulge-stem motif of HIV TAR RNA ( Figure 2B ) . The first uridine in the bulge and the G-C and A-U base-pairs in the upper stem are indispensable for Tat binding [45] , [46] , [47] , [48] . A structural rearrangement of the bulge loop provides the specificity for the Tat-TAR interaction . The bulged U forms a base-triple interaction with the A-U base-pair that stabilizes the association of the lower G residue in the major grove with an arginine of Tat [49] , [50] . We noticed that the 5′ hairpin of human 7SK snRNA carries two internal segments , G18-A27/U84-C90 and C37–C45/G64–G70 , which are highly reminiscent of the consensus minimal structure of the Tat-binding element of HIV TAR ( Figure 2C , shaded boxes ) . The putative distal ( upper ) Tat-binding element of human 7SK shows a striking conservation in all known 7SK snRNAs derived from phylogenetically distant species . To test whether the newly detected potential Tat-binding motifs of human 7SK snRNA can interact with Tat , we performed electrophoretic mobility shift assays using in vitro synthesized probe RNAs representing either the distal ( Dist ) or the proximal ( Prox ) parts of the 5′ hairpin of 7SK and a Tat-derived oligopeptide , Tat ( 38–72 ) [51] ( Figure 3A ) . The Tat peptide efficiently bound to the distal part of the 5′ hairpin of 7SK ( lanes 2–4 ) , but failed to associate with its proximal part ( lane 7–9 ) . Administration of cold Dist RNA abolished association of the Tat oligopeptide with 7SK sequences , confirming that Tat binds specifically to the distal part of the 5′ hairpin of human 7SK snRNA ( lane 5 ) . The 5′ hairpin of human 7SK contains two 10 nt-long perfect repeats ( G13–G22 and G64–G73 ) which overlap the distal and proximal putative Tat-binding elements ( Figure 3A , indicated by arrows ) . The wild-type GAUCUGGCUG repeat sequences were replaced with complementary sequences in the p5′HP expression plasmid ( Figure 3B ) . The mutant 5′HPdm ( distal mutant ) and 5′HPpm ( proximal mutant ) RNAs were transiently expressed in HeLa cells and their association with the co-expressed Tat-FL protein was tested . Northern blot analysis demonstrated that Tat-FL interacted with 5′HPpm RNA ( lane 4 ) , but it failed to associate with the 5′HPdm and the double mutant 5′HPpm+dm RNAs ( lanes 8 and 12 ) , providing strong support to the notion that Tat interacts with the distal Tat-binding motif of human 7SK snRNA . To confirm that Tat binds to the C37–C45/G64–G70 TAR RNA-like motif of human 7SK , a series of mutant 5′HP RNAs were transiently expressed and their association with Tat-FL was examined ( Figure 3C ) . Substitution of the U40 , U40–U41 bulge nucleotides or the A43 , G42-A43 , U63-C67 and U68-G70 stem nucleotides for complementary sequences fully abolished the in vivo association of the expressed mutant 5′HP RNAs with Tat-FL ( lanes 4 , 12 , 16 , 20 , 24 and 28 ) . In contrast , substitution of the U72-C75 nucleotides failed to interfere with Tat binding ( lane 8 ) . Likewise , replacing the U63 bulge nucleotide , the G60-C62 stem or the A49-C59 loop sequences with complementary nucleotides had no effect on in vivo Tat binding ( data not shown ) . We concluded that Tat binds to the evolutionarily conserved C37–C45/G64–G70 motif of 7SK that is structurally indistinguishable from the Tat-binding element of HIV TAR . The strong evolutionarily conservation of the newly identified Tat-binding site of human 7SK suggests that this element plays an important role in the normal function of 7SK snRNA ( Figure 2C ) . The positively charged arginine-rich TAR-recognition motif of HIV Tat shows strong similarity to the N-terminal part of the 7SK-binding motif of HEXIM proteins derived from evolutionarily distant species ( Figure S1 ) [52] . This suggests that Tat and HEXIM recognize similar , if not identical , target motif ( s ) in the 5′ hairpin of 7SK . HEXIM1 has been reported to be a promiscuous double-stranded RNA-binding protein that binds to 7SK between nucleotides 10 to 48 in a sequence-independent manner [53] . In contrast , we had earlier observed that in HeLa cells HEXIM1 binds to the distal part of the 5′ hairpin of 7SK with high specificity [26] . To clarify these inconsistencies and to define the precise binding site of HEXIM , we performed electrophoretic mobility shift assays ( Figure 4A ) . When the entire 5′ hairpin of 7SK ( 5′HP ) was incubated with increasing amounts of recombinant HEXIM1 , two 5′HP-HEXIM1 complexes , indicated as shift 1 and 2 , were detected on a native gel ( lanes 2–6 ) . In the presence of about two-fold excess of HEXIM1 only the upper low-mobility complex ( shift 2 ) was formed ( lane 6 ) . Administration of cold 5′HP RNA inhibited 5′HP-HEXIM1 complex formation ( lanes 7–9 ) , indicating that in accordance with previous reports , the 5′ hairpin of 7SK specifically associates with two molecules of HEXIM1 [13] , [24] , [25] . When probe RNAs representing the proximal ( Prox ) and distal ( Dist ) regions of the 5′ hairpin of 7SK were incubated with HEXIM1 , HEXIM1 specifically associated with both RNAs ( lanes 11–13 and lanes 16–18 ) . The resulting Dist-HEXIM1 and Prox-HEXIM1 complexes co-migrated with the high-mobility complex ( shift1 ) formed by the full-length 5′ hairpin and HEXIM1 . Importantly , neither the Dist nor the Prox probe RNA formed the large low-mobility complex ( shift 2 ) with HEXIM1 , demonstrating that the 5′ hairpin of 7SK contains two structurally and functionally independent HEXIM-binding sites each recruiting one HEXIM molecule in an independent fashion in vitro . We tested whether the newly defined distal Tat-binding element and the proximal Tat-binding-like motif of the 5′ hairpin of 7SK are essential for HEXIM1 binding . Mutant 5′ hairpin RNAs , 5′HPdm and 5′HPpm ( see Figure 3 ) , were incubated with HEXIM1 and the resulting complexes were analyzed on a native gel ( Figure 4B ) . Both 5′HPdm and 5′HPpm RNAs formed only the high-mobility complex with HEXIM1 ( shift 1 ) , indicating that they bind only one copy of HEXIM1 ( lanes 3–4 and 8–9 ) . As expected , the double-mutant 5′HPpm+dm RNA was inactive in HEXIM-binding ( lanes 12–14 ) . These results confirmed that the newly identified Tat-binding motif in the distal part and the Tat-binding-like element in the proximal part of the 7SK 5′ hairpin function in HEXIM-binding . To further delimit the snRNA elements directing in vitro HEXIM-binding , the distal A34-C45/G64-A77 and proximal C12-A27/U84-U95 fragments of 7SK were topped with GGAA tetraloops and stabilized with artificial basal stems ( Figure 4C ) . The resulting distal and proximal HEXIM-binding site ( DHBS and PHBS ) RNAs specifically associated with HEXIM1 ( lanes 4 and 9 ) . Any further truncations or sequence alterations abolished the HEXIM-binding capacity of the DHBS and PHBS RNAs , indicating that the A34-C45/G64-A77 and C12-A27/U84-U95 internal segments of the 5′ hairpin of 7SK contain the minimal sequence and structural information required for in vitro recognition by HEXIM1 ( data not shown ) . This conclusion was further corroborated by demonstration that similarly to the control wild-type 5′ hairpin ( Figure 4D , lane 9 ) , an artificial hairpin RNA ( 5′HPsyn ) encompassing the C12-A25/U86-U95 and A34-C45/G64-A77 fragments of human 7SK was capable of binding two HEXIM1 molecules ( lane 4 ) . Our in vitro binding studies revealed that the 5′ hairpin of human 7SK snRNA carries two structurally and functionally independent HEXIM-binding sites . However , we had earlier observed that mutations predicted to disrupt the distal HEXIM-binding element of the 5′ hairpin fully abolished the in vivo HEXIM-binding capacity of 7SK snRNA [26] . A possible interpretation of these contradictory results could be that in vivo the two HEXIM-binding sites of 7SK function in an interdependent way . To test this assumption , we investigated the in vivo HEXIM-binding ability of the mutant 5′HPpm and 5′HPdm RNAs which still bind one copy of HEXIM1 under in vitro conditions ( see Figure 4B ) . The 5′HPpm and 5′HPdm RNAs were transiently expressed in HeLa cells and their association with a co-expressed HA-tagged HEXIM1 was monitored ( Figure 5A ) . The ectopically expressed HA-HEXIM1 protein efficiently associated with the endogenous HeLa 7SK snRNA ( lanes 4 , 8 and 12 ) and the transiently expressed wild-type 5′HP RNA ( lane 4 ) , but it showed no association with the mutant 5′HPdm and 5′HPpm RNAs ( lanes 8 and 12 ) , indicating that both HEXIM1-binding sites are required for in vivo recruitment of HEXIM1 . Next , we assayed the in vivo interaction of HA-HEXIM1 with transiently expressed full-length 7SK RNAs which , similarly to the 5′HPdm and 5′HPpm RNAs , carried the pm or dm sequence alterations ( Figure 5B ) . In order to distinguish between the ectopically expressed mutant and the endogenous wild-type 7SK RNAs , RNase A/T1 mappings were performed using antisense probe RNAs specific for the mutant 7SKdm and 7SKpm snRNAs . In contrast to the endogenous 7SK snRNA , the transiently expressed 7SKdm and 7SKpm RNAs failed to efficiently associate with HA-HEXIM1 in vivo ( lanes 5 and 10 ) . Since docking of HEXIM1 is a prerequisite for P-TEFb binding , neither 7SKdm nor 7SKpm associated with P-TEFb , as demonstrated by co-IPs with HA-tagged CycT1 ( lanes 14 and 18 ) . The finding that disruption of either the distal or the proximal HEXIM-binding motif of 7SK abolishes the recruitment of both HEXIM and P-TEFb demonstrates that under in vivo conditions the distal and proximal HEXIM-binding sites of 7SK recruit two copies of HEXIM1 in a tightly interdependent manner . Demonstration that HIV Tat binds to the distal HEXIM-binding site of human 7SK snRNA is consistent with the idea that Tat competes with HEXIM for 7SK binding [37] . Indeed , replacement of one copy of HEXIM with Tat would be expected to fully disrupt the 7SK-HEXIM interaction , since in vivo recruitment of a HEXIM-dimer requires both HEXIM-binding sites of the 7SK snRNA ( Figure 5 ) . To confirm this hypothesis , increasing amounts of Tat-FL was transiently expressed in HeLa cells ( Figure 6A ) . After IP of equal amounts of HEXIM1 , co-precipitation of 7SK was monitored by Northern blot analysis followed by PhosphorImager quantification . The ectopically expressed Tat-FL efficiently disrupted the interaction of the endogenous HEXIM1 with 7SK snRNA . Since 7SK and HEXIM can form a stable complex even in the absence of P-TEFb or other components of the 7SK snRNP [26] , we assumed that the observed Tat-mediated disruption of the 7SK-HEXIM1 interaction was due to direct competition of Tat and HEXIM1 for 7SK binding . To confirm this conclusion , mutant Tat-FL proteins , Tat-FL ( K50Q ) and Tat-FL ( K50A+K51A ) [42] , lacking TAR RNA-binding capacity were transiently expressed in HeLa cells ( Figure 6B ) . Co-IP experiments demonstrated that in contrast to the wild-type Tat ( lane 2 ) , the mutant Tat proteins failed to bind 7SK snRNA and to disrupt the interaction of HEXIM1 with 7SK and CycT1 ( lanes 3 and 4 ) . The experiments presented thus far demonstrate that the RNA-binding activity of Tat is crucial for disruption of the 7SK/HEXIM/P-TEFb snRNP . However , given that Tat can specifically interact also with CycT1 , it remains possible that binding of Tat to the CycT1 subunit of the 7SK/HEXIM/P-TEFb snRNP may also contribute to the disassembly of this particle [38] . To test this possibility , we assayed the 7SK-HEXIM1 interaction in HeLa cells expressing increasing amounts of mutant Tat-FL ( C22G ) and Tat-FL ( K41A ) proteins lacking CycT1-binding ability ( Figure 6C ) . Similarly to the wild-type Tat ( see Figure 6A ) , both mutant Tat proteins reduced the association of HeLa 7SK snRNA with HEXIM1 in a concentration-dependent fashion . Next , the mutant Tat-FL ( C22G ) and Tat-FL ( K41A ) proteins missing CycT1-binding capacity were transiently expressed in HeLa G3H cells which stably expressed HA-CycT1 [54] , [55] ( Figure 6D ) . After IP of comparable amounts HA-CycT1 , co-precipitation of the endogenous 7SK snRNA and HEXIM1 as well as the ectopically expressed Tat-FL proteins was monitored . As expected , HA-CycT1 interacted with the wild-type Tat-FL , but it failed to bind to the mutant Tat-FL ( C22G ) and Tat-FL ( K41A ) proteins . More importantly , expression of the wild-type and mutant Tat proteins largely reduced the association of HA-P-TEFb with 7SK and HEXIM1 . We believe that the intact 7SK/HEXIM/P-TEFb ( about 25–35% ) that remained in the extracts likely derived from non-transfected cells . Thus , we concluded that Tat can promote the in vivo disassembly of 7SK/HEXIM/P-TEFb independently of its CycT1-binding capacity . The concept that Tat efficiently competes with HEXIM for 7SK binding , implies that Tat and HEXIM bind to the 7SK snRNA in a mutually exclusive manner . To test this , the wild-type and mutant ( C22G and K41A ) Tat-FL proteins were expressed in HeLa cells ( Figure 6E ) . Co-IP experiments showed that all Tat-FL proteins efficiently associated with HeLa 7SK snRNA but showed no detectable interaction with HEXIM1 , demonstrating that Tat and HEXIM interact with 7SK snRNA in a mutually exclusive manner ( lanes 4 , 6 and 8 ) . As expected , the mutant Tat proteins failed to associate with CycT1 ( lanes 6 and 8 ) , but the wild-type Tat-FL interacted with CycT1 ( lane 4 ) . Apparently , the wild-type Tat associates with endogenous CycT1 predominantly in a 7SK-independent manner [42] , [56] , but a minor fraction of Tat may also be involved in formation of the recently reported 7SK/Tat/P-TEFb complex [42] . To further confirm that the CycT1-binding activity of Tat is dispensable for disruption of 7SK/HEXIM/P-TEFb , we assayed whether expression of Tat-FL ( C22G ) and Tat-FL ( K41A ) could increase the nuclear level of active P-TEFb . The control and mutant Tat-FL proteins were transiently expressed in G3H cells . Upon IP with an anti-HA antibody , the beads with immobilized HA-P-TEFb were incubated with a recombinant GST-CTD protein carrying 48 C-terminal copies of the consensus CTD repeat ( YSPTSPS ) in the presence of [γ-32P]ATP ( Figure 6D ) . The phosphorylated GST-CTD was fractionated on a SDS-polyacrylamide gel and the specificity of the phosphorylation reaction was confirmed by Western blotting with an antibody specific for serine 2-phosphorylated CTD . The phosphorylation level of GST-CTD was determined by PhosphorImager quantification . Although comparable amounts of HA-P-TEFb ( HA-CycT1 ) were attached to the beads , the extracts accumulating the wild-type and mutant Tat-FL proteins showed about 1 . 5 to 2-fold higher CTD phoshorylation activity compared to the non-transfected control extract . Given that in HeLa cells about 50% of P-TEFb is sequestered into 7SK/HEXIM/P-TEFb , we concluded that expression of the wild-type and mutant Tat proteins efficiently mobilized the nuclear pool of inactive P-TEFb . These results further corroborated the notion that the CycT1-binding capacity of Tat is not required for the Tat-induced disruption of the 7SK/HEXIM/P-TEFb snRNP and for increasing the nuclear level of active P-TEFb . In HeLa cells , a fraction of 7SK snRNA is associated with hnRNP proteins , mainly A1 , A2/B1 , R and Q [44] , [57] , [58] . To exclude the formal possibility that the newly detected 7SK/Tat RNP or at least a fraction of 7SK/Tat derived from the hnRNP-associated pool of 7SK , we tested the effect of Tat expression on HeLa 7SK/hnRNP complexes ( Figure 7A ) . Transient expression of wild-type Tat-FL had no detectable effect on the level of association of hnRNP A1 and A2/B1 with 7SK snRNA ( lanes 4 and 6 ) , demonstrating that the hnRNP-associated fraction of 7SK is not available for in vivo interaction with HIV Tat . The hnRNP proteins associate with 7SK snRNA after its stress-induced release from the 7SK/HEXIM/P-TEFb snRNP [44] , [57] , [58] . We tested whether after Tat-mediated disruption of 7SK/HEXIM/P-TEFb , the resulting 7SK/Tat snRNP associates with hnRNP proteins ( Figure 7B ) . Transiently expressed Tat-FL , together with 7SK snRNA , was immunoprecipitated and co-purification of hnRNP A1 , A2/B1 , R , Q and Larp7 was tested by Western blot analysis . Although the 7SK/Tat-FL snRNP interacted with Larp7 , none of the tested hnRNP proteins were detected in the pellet , demonstrating that the newly described 7SK/Tat snRNP contains no hnRNP proteins .
Although all previous studies agreed that HEXIM binds to the 5′ hairpin of 7SK , its precise docking site remained uncertain [26] , [27] , [53] . Here , we demonstrated that the 5′ hairpin of human 7SK snRNA contains two distinct HEXIM-binding sites which are confined to the A34-C45/G64-A77 distal ( DHBS ) and the C12-A27/U84-U95 proximal ( PHBS ) segments ( Figure 4 ) . Under in vitro conditions , each HEXIM-binding motif of 7SK specifically and independently interacts with one HEXIM molecule . Both HEXIM-binding sites of the human 7SK snRNA contain a stem-bulge-stem core motif ( C37–C45/G64–G70 and G18-A27/U84-C90 ) which are highly reminiscent of the consensus structure of the minimal Tat-binding element of HIV TAR ( Figure 2B and 2C ) . Consistent with this , HIV Tat and HEXIM proteins carry similar , positively charged , arginine-rich RNA-binding motifs which are essential for interaction with TAR and 7SK RNAs ( Figure S1 ) . These observations , together with the finding that Tat binds to the distal HEXIM-binding site of 7SK ( Figure 3 ) , strongly suggest that HEXIM and Tat use similar structural and molecular principles to recognize 7SK and TAR RNAs . Along this line of speculation , given that Tat can bind to the HEXIM-binding site of 7SK , it seems to be logical to hypothesize that HEXIM can interact with the Tat-binding site of HIV TAR [38] . However , contrary to our repeated efforts , we failed to detect a specific interaction between HEXIM and TAR ( our unpublished data ) . The lack of TAR-binding ability of HEXIM could be explained by the observations that binding of HEXIM to 7SK snRNA , besides the TAR-like C37–C45/G64–G70 and G18-A27/U84-C90 stem-bulge-stem core motifs , also requires the adjacent A34-C36/C71-A77 and C12-U17/U1–U95 proximal sequences ( Figure 4 ) [26] . Thus , HEXIM seems to form a more intricate interaction with 7SK snRNA than it has been reported for the Tat-TAR complex . The Tat-like RNA-binding motifs of HEXIM proteins are N-terminally extended by highly conserved positively charged regions which may contribute to the specificity of the HEXIM-7SK interaction ( Figure S1 ) . Apparently , understanding of the accurate molecular and structural background of the interaction of HEXIM and 7SK snRNA requires further efforts . A key achievement of the current study is the demonstration that in living cells , assembly of the 7SK/HEXIM/P-TEFb snRNP requires both the distal and proximal HEXIM-binding sites of 7SK , since they recruit a homodimer of HEXIM in an strictly interdependent fashion ( Figure 5 ) . Most probably , concerted binding of two HEXIM molecules increases the 7SK-binding affinity of the tethered HEXIM-dimer . For example , structural rearrangements of HEXIM induced by dimerization may promote formation of additional molecular contacts with 7SK snRNA [59] . Interestingly , the 5′ hairpins of non-vertebrate 7SK snRNAs seem to carry only one HEXIM-docking site , suggesting that these RNAs interact with one copy of HEXIM and P-TEFb ( Figure 2C ) . Acquisition of a second HEXIM-binding site that occurred probably through sequence duplication at the early stage of vertebrate evolution seems to be advantageous for P-TEFb regulation , since a single 7SK/HEXIM/P-TEFb dissociation event can mobilize two active P-TEFb molecules . Transiently expressed HIV Tat specifically and efficiently interacts with the endogenous human 7SK snRNA , indicating that the 7SK transcriptional regulatory snRNA is the major RNA target of Tat in the host cell ( Figure 1 ) . Tat binds to the evolutionarily conserved C37–C45/G64–G70 internal stem-loop-stem region of the 5′ hairpin of human 7SK snRNA ( Figure 3 ) . The newly identified Tat-binding motif of 7SK perfectly conforms to the consensus structure of the Tat-binding motif of HIV TAR and it is part of the distal HEXIM-binding site of 7SK . Most of the available data are consistent with the idea that HIV Tat competes with HEXIM1 for 7SK snRNA binding to promote disassembly of the 7SK/HEXIM/P-TEFb snRNP and to increase the nuclear pool of active P-TEFb . Previous in vitro reconstitution experiments showed that Tat could disrupt pre-assembled 7SK/HEXIM/P-TEFb complexes , resulting in stable 7SK/Tat complex and free HEXIM and P-TEFb [38] . Unfortunately , because of the high tendency of recombinant Tat protein for oxidation and aggregate formation [48] , [60] , in vitro competition experiments require the usage of a great eccess of recombinant Tat , making it difficult to measure and compare the correct in vitro 7SK-binding affinities of Tat and HEXIM [38 , our unpublished data] . Nevertheless , the in vivo competition experiments presented in this study confirmed that Tat efficiently disrupts the association of HEXIM1 and 7SK snRNA upon formation of 7SK/Tat snRNP ( Figure 6 ) . Given that both HEXIM-binding sites of 7SK are necessary for in vivo recruitment of a HEXIM homodimer , disruption of the 7SK-HEXIM interaction at the distal HEXIM-binding site by docking Tat is expected to release both copies of HEXIM ( Figure 5 ) . Providing strong support to this idea , Tat and HEXIM bind to 7SK in a mutually exclusive manner , neither the 7SK/Tat RNP contains HEXIM nor the 7SK/HEXIM complex associates with Tat ( Figure 6 ) [42] . Binding of HEXIM to 7SK is the first and decisive step in the assembly of the 7SK/HEXIM/P-TEFb negative transcriptional regulatory snRNP , because association of HEXIM and P-TEFb is strictly 7SK-dependent [11] , [27] , [28] . Free HEXIM cannot bind to CycT1 , because its negatively charged CycT1-binding domain forms intramolecular interactions with the adjacent positively charged 7SK-binding motif [28] . Docking 7SK disrupts this autoinhibitory interaction and turns HEXIM into an active conformation ready to bind and inhibit P-TEFb . Thus , disruption of the interaction of 7SK and HEXIM by Tat is predicted to mobilize the 7SK/HEXIM-associated inactive pool of P-TEFb by triggering its release from HEXIM1 . In an alternative model , Tat has been proposed to mediate 7SK/HEXIM/P-TEFb disruption through competing with HEXIM for binding to CycT1 [37] . Arguing against this scenario , amino acid alterations which abolished the interaction of Tat with CycT1 only slightly reduced the ability of the mutant Tat proteins to disrupt 7SK/HEXIM/P-TEFb and to increase P-TEFb activity in vivo ( Figures 6D and 6F ) . In contrast , disruption of the 7SK-binding capacity of Tat fully abolished its ability to replace HEXIM1 and to disrupt 7SK/HEXIM/P-TEFb ( Figure 6B ) . Thus , although it remains possible that the CycT1-binding activity of Tat slightly contributes to the Tat-mediated disassembly of 7SK/HEXIM/P-TEFb , our results indicate that the P-TEFb mobilization capacity of Tat depends mostly , if not exclusively , on its 7SK-binding activity . During revision of the current manuscript , the human 7SK snRNA has been reported to form a stable complex with Tat and P-TEFb [42] . Since 7SK can bind only one molecule of Tat and consequently , one copy of P-TEFb ( Figure 3 ) , Tat-induced disruption of 7SK/HEXIM/P-TEFb is expected to release at least half of the associated P-TEFb in the form of free P-TEFb . However , we and others observed that Tat expression converted the nuclear pool of inactive 7SK/HEXIM1/P-TEFb into free , active P-TEFb with a very high ( 75–95% ) efficiency , suggesting that the newly described 7SK/Tat/P-TEFb accumulates at low levels ( Figure 6D ) [37] , [38] . Nevertheless , the functional significance of the novel 7SK/Tat/P-TEFb RNP played in HIV expression remains to be established . Demonstration that the distal HEXIM-binding site of the human 7SK snRNA encompasses a perfect Tat-binding motif has an important biomedical impact . Targeting the Tat-binding site of HIV TAR RNA with small-molecule drugs to block Tat-mediated transactivation is a very attractive approach for anti-viral therapy [61] . However , potential anti-HIV drugs with strong TAR-binding capacity are expected to interact also with the distal HEXIM-binding motif of 7SK and therefore , to promote the disassembly of 7SK/HEXIM/P-TEFb that shifts the P-TEFb equilibrium toward the active form . Since increased P-TEFb activity may have deleterious effects [16] , [62] , therapeutic targeting of HIV TAR requires the design of ligands which are highly specific for the TAR RNA . So , our results suggest that drug-mediated therapeutic inhibition of Tat-TAR interaction requires more precautions than anticipated before .
Unless stated otherwise , all techniques used for manipulation of DNA , RNA oligonucleotides and proteins were performed according to standard laboratory procedures . The identity of all plasmid constructs was verified by sequence analysis . Human HeLa and G3H cells , the latter was provided by Dr Q . Zhou [63] , were grown in Dulbecco's modified Eagle medium supplemented with 10% fetal calf serum ( Invitrogen ) . Expression plasmids were introduced into HeLa and G3H cells by using the FuGENE transfection reagent ( Roche ) . Construction of the p7SK , p5′HP and pHA-HEXIM1 expression plasmids has been described [26] . The pTat-FL , pTat-FL ( C22G ) , pTat-FL ( K41A ) , pTat-FL ( K50Q ) and pTat-FL ( K50A+K51A ) plasmids have been provided by Dr M . Benkirane [42] , [64] . The p7SKdm , p7SKpm , p5′HPdm , p5′HPpm , p5′HPpm+dm , p5′HP ( U40–U41 ) , p5′HP ( U72-C75 ) , p5′HP ( U68-G70 ) , p5′HP ( G64-U68 ) , p5′HP ( U40 ) , p5′HP ( A43 ) and p5′HP ( G42-A43 ) 7SK expression plasmids were generated by PCR-mediated mutagenesis using p7SK and p5′HP as templates . RNA isolation from HeLa and G3H cells and cell extracts has been described [26] . RNAs co-immunoprecipitated with Tat-FL were 3′ end-labeled with [5′-32P]pCp and T4 RNA ligase before fractionation on a 6% sequencing gel . After elution from the gel , the labeled 7SK snRNA was partially digested with RNase T1 in 25 mM Na-citrate , pH 5 . 0 , and 7 M urea at 55°C . Partial RNA hydrolysis was performed in deionized formamide containing 0 . 4 mM MgCl2 at 100°C . For Northern blot analysis , RNAs were size-fractionated on a 6% denaturing gel and electroblotted onto a Hybond-N nylon membrane ( Amersham Biosciences ) . The filters were probed with labeled oligonucleotides complementary to the human 7SK snRNA from U92 to G111 , from G272 to C291 or from C48 to C67 . To generate sequence-specific antisense RNA probes for mapping of 7SK , 7SKpm , and 7SKdm RNAs , the corresponding expression plasmids were linearized with PstI and used as templates for in vitro transcription with T7 RNA polymerase . RNase A/T1 protection analysis has been described [26] . To generate template DNAs for in vitro synthesis of internally 32P-labeled 5′HP , Dist , 5′HPdm , 5′HPpm and 5′HPdm+pm probe RNAs , the corresponding fragments of the p5′HP , p5′HPdm , p5′HPpm and p5′HPdm+pm plasmids were amplified with appropriate oligonucleotides which also incorporated the T7 promoter . Template DNAs for synthesis of Prox , DHBS , PHBS and 5′HPsyn were obtained by annealing of appropriate synthetic oligonucleotides followed by cloning into the pBluescribe plasmid . Recombinant HEXIM1 was purified as described [26] . Tat ( 38–72 ) peptide was synthesized by PolyPeptide Group [51] . RNA-protein complexes were formed in 50 mM Tris-HCl , pH 8 . 0 , 100 mM NaCl , 14 . 4 mM 2-mercaptoethanol in the presence of 20 ng/µl of E . Coli tRNA at RT . The complexes were analyzed on 4% or 5% polyacrylamide gels ( 29∶1 acrylamide∶bis-acrylamide ) containing 2 . 5% glycerol in 0 . 5× TBE . Human G3H cells transiently expressing wild-type or mutant ( C22G and K41A ) Tat-FL proteins were lysed in buffer A ( 20 mM HEPES , pH 7 . 9 , 150 mM NaCl , 1 . 5 mM MgCl2 , 1 mM DTT , 0 . 5 mM EDTA , 0 . 05% Nonidet P40 ) supplemented with 10 U/ml of RNasin ( Promega ) and protease inhibitor cocktail ( Roche ) . After centrifugation at 10 , 000× g for 10 min , the extracts were incubated with anti-HA-agarose beads ( Sigma ) for 1 hour . The beads were washed five times in buffer A , resuspended in 100 µl of buffer A and incubated with 2 µg of recombinant GST-CTD containing 48 consensus CTD repeats ( YSPTSPS ) and 10 µCi of [γ-32P]ATP ( 6000 Ci/mmol ) at 30°C . Phosphorylation of GST-CTD was measured by PhosphorImager quantification after fractionation on 8% SDS/polyacrylamide gel .
|
Expression and replication of the human immunodeficiency virus ( HIV ) is supported by the viral transcriptional transactivator ( Tat ) that recruits the host positive transcription elongation factor b ( P-TEFb ) to the promoter of the integrated viral genome . Here , we demonstrate that HIV Tat specifically and efficiently binds to the host 7SK small nuclear RNA ( snRNA ) that is a negative regulator of P-TEFb . Although HIV Tat has been reported to interact with a plethora of host factors , our results indicate that the 7SK transcriptional regulatory snRNA is a major and important cellular target of HIV Tat . We demonstrate that binding of Tat to the 7SK snRNA disrupts the 7SK-P-TEFb negative transcriptional regulatory complex and releases active P-TEFb . Thus , we propose that Tat not only targets P-TEFb for HIV transcription , but also modulates the nuclear level of active P-TEFb in HIV-infected cells .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"virology/immunodeficiency",
"viruses",
"molecular",
"biology/rna-protein",
"interactions"
] |
2010
|
Controlling Cellular P-TEFb Activity by the HIV-1 Transcriptional Transactivator Tat
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In order to investigate the potential of voles to reproduce in vitro the efficiency of prion replication previously observed in vivo , we seeded protein misfolding cyclic amplification ( PMCA ) reactions with either rodent-adapted Transmissible Spongiform Encephalopathy ( TSE ) strains or natural TSE isolates . Vole brain homogenates were shown to be a powerful substrate for both homologous or heterologous PMCA , sustaining the efficient amplification of prions from all the prion sources tested . However , after a few serial automated PMCA ( saPMCA ) rounds , we also observed the appearance of PK-resistant PrPSc in samples containing exclusively unseeded substrate ( negative controls ) , suggesting the possible spontaneous generation of infectious prions during PMCA reactions . As we could not definitively rule out cross-contamination through a posteriori biochemical and biological analyses of de novo generated prions , we decided to replicate the experiments in a different laboratory . Under rigorous prion-free conditions , we did not observe de novo appearance of PrPSc in unseeded samples of M109M and I109I vole substrates , even after many consecutive rounds of saPMCA and working in different PMCA settings . Furthermore , when positive and negative samples were processed together , the appearance of spurious PrPSc in unseeded negative controls suggested that the most likely explanation for the appearance of de novo PrPSc was the occurrence of cross-contamination during saPMCA . Careful analysis of the PMCA process allowed us to identify critical points which are potentially responsible for contamination events . Appropriate technical improvements made it possible to overcome PMCA pitfalls , allowing PrPSc to be reliably amplified up to extremely low dilutions of infected brain homogenate without any false positive results even after many consecutive rounds . Our findings underline the potential drawback of ultrasensitive in vitro prion replication and warn on cautious interpretation when assessing the spontaneous appearance of prions in vitro .
Transmissible Spongiform Encephalopathies ( TSEs ) are progressive and fatal neurodegenerative disorders that include scrapie of sheep , bovine spongiform encephalopathy ( BSE ) of cattle and Creutzfeldt-Jakob disease ( CJD ) of humans [1] . The nature of the causal agent of TSEs has long been a matter of intense scientific debate . The prion hypothesis postulates that the causal agent , the prion , consists only of proteins without nucleic acid genome [1] . Alternative hypotheses postulate the presence of a small nucleic acids genome [2] , although evidences for this are still lacking . The virino hypothesis proposes that the causal agent is an informational hybrid between the agent genome and host conformationally altered PrP [3] . Recently , new evidences were brought in support of the prion hypothesis , although a fundamental role of non proteinaceous cofactors could not be definitively excluded [4] , [5] , [6] , [7] , [8] . The accumulation in the central nervous system of a post-translationally altered isoform ( PrPSc ) of the cellular prion protein ( PrPC ) is the key event in TSE pathogenesis [1] , Nevertheless the relationships between PrPSc and infectivity are not definitively clear and evidences for high titers of TSE infectivity associated with extremely low levels of PrPSc have been reported [9] . The modification of PrPC involves mostly unknown conformational changes during which an increase in the amount of β-sheet of the normal protein and a decrease in its α-helical content is observed [10] , [11] . According to the prion theory , PrPSc thus acquires , via a template-based mechanism , the ability to trigger the conversion of PrPC into new PrPSc . The process proceeds thereafter in an autocatalytic manner , leading PrPSc aggregates to grow by including new PrPC monomers [1] , [12] . The severe outbreak of BSE , first detected in the UK in 1986 , and the announcement in 1996 that the BSE agent was responsible for a newly recognised form of TSE in humans , named variant CJD , created enormous concern among European consumers and prompted health authorities to promote the development of reliable diagnostic tools for BSE [13] , [14] , [15] . Recently , four cases of transfusion-related transmission of vCJD [16] further strengthened the need for reliable preclinical and in vivo screening tests for TSEs . The protein misfolding cyclic amplification ( PMCA ) technology developed in 2001 by Claudio Soto's group [17] , seems one of the most promising approaches . PMCA is used to amplify minute amounts of PrPSc existing in the test material to levels which can be readily detected using conventional assays such as Western blotting . The reaction is initiated by diluting TSE-infected material in normal brain homogenate , with the former providing PrPSc seeds and the latter providing PrPC and other potential cofactors for PrPSc amplification . The product is diluted in additional normal brain homogenates for subsequent serial amplification cycles that allow theoretically indefinite PrPSc amplification [18] . PMCA has usefully demonstrated that prion infectivity can be replicated in vitro [18] and that in vitro-generated prions maintain apparently unaltered strain properties [19] , [20] . Moreover , PMCA-induced replication of prion seems to reproduce in vitro several aspects of the in vivo replication and is valuable for investigating the molecular requirements for PrP trans-conformation [4] and to mimic the intra- and inter-species replication and adaptation of prions [21] . Finally , PMCA has demonstrated its ability to achieve ultrasensitive detection of PrPSc in tissues and body fluids of TSE-affected rodent models [22] , [23] , [24] . In spite of its usefulness for investigating basic aspects of TSEs , very few data have been published proving the robustness of PMCA as a diagnostic tool for natural TSEs and the appearance of spurious results has been highlighted in some papers [25] , [26] . PMCA is hampered by technical difficulties that make improvements necessary in terms of both practicability and control . For diagnostic purposes the sensitivity and specificity of PMCA need to be close to 100% . However , the appearance of protease-resistant bands identical to PrPSc , in PrPSc inoculum-free samples reported by Soto's group when more than 10 rounds of standard PMCA were performed [25] and the recent papers claiming de novo generation of infectious prions in unseeded PMCA reactions [4] , [27] raise fundamental questions about the diagnostic reliability of PMCA . If the latter findings will be corroborated by replication in different laboratories , they would assume critical importance in the interpretation of PMCA results and in its possible clinical-diagnostic use . A practical limitation of PMCA is the reported need to use a substrate that is compatible with the target to be amplified . In an attempt to transpose to an in vitro system the plasticity shown by the bank vole model in the transmission of a variety of human and animal TSEs [28] , [29] , [30] , we explored the suitability of vole brain homogenate as a substrate for PMCA . Together with the observation of a highly efficient replication of a variety of prion sources from different species , the earliest experiments produced apparently conflicting results: after serial PMCA rounds using healthy vole brain homogenates without infectious seed , the appearance of PK-resistant PrPSc was repeatedly observed . This product proved to be very infectious when inoculated into voles , thus suggesting that prions can be generated de novo from healthy brains . In the present study we illustrate , as supplementary on-line material , our early evidence of the , de novo generation of prions and describe in detail the procedures we performed to explore further and validate those results . When working in rigorously prion-free conditions , we found no evidence of de novo generation of prions . Through careful analysis of the PMCA process we identified the critical points of this procedure that are potentially responsible for contamination events and false positive results when ultrasensitive detection is desired . Here we show that technical improvements can be adopted to overcome the drawbacks of PMCA , and that PrPSc can be reliably amplified from very high dilutions of infected brain homogenate in a single PMCA round .
We previously reported the susceptibility of bank voles to different prion species , including human , rodent , cattle , sheep and elk TSEs [28 , 29 , 30 and manuscript in preparation] . Voles have a polymorphism at codon 109 of PrP , coding for either methionine or isoleucine , and this amino acid variation influences the susceptibility of voles to different prion strains [31 and Agrimi et al . , unpublished data] . In order to investigate the potential of voles to reproduce in vitro the efficiency of prion replication previously observed in vivo , we seeded PMCA reactions either with rodent-adapted prion strains , including mouse- and vole-adapted scrapie and BSE strains and hamster-adapted scrapie 263K , and with natural isolates of sheep scrapie , chronic wasting disease of elk , cattle BSE , MM1 sCJD , to a final seed homogenate/vole substrate dilution of 1/200 . Vole brain homogenates were indeed a powerful substrate for PMCA , supporting the efficient amplification of PrPSc from all the prion sources tested , either derived from voles or other species , after a single PMCA round of 80 amplification cycles ( Figure 1A ) . However , after a few serial automated PMCA ( saPMCA ) rounds , we also observed the appearance of PK-resistant PrPSc in samples containing exclusively unseeded substrate ( negative controls ) ( Figure 1B ) . This finding suggested the possible occurrence of spontaneous generation of PrPSc during PMCA reactions ( see Supplemental Text S1 ) . Additional PMCA experiments performed in similar conditions confirmed the putatively de novo appearance of PrPSc in unseeded brain homogenates from M109M and I109I voles ( Table S1 ) . In order to exclude the possibility that animals from the facility of Istituto Superiore di Sanità ( ISS ) were contaminated , PMCA was also carried out using substrates from wild voles , trapped in the countryside , with similar results ( see footnotes in Table S1 ) . Overall , the above experiments showed that: i ) the supposedly spontaneous appearance of PrPSc was a stochastic event , with each individual sample acting independently ( Table S1 ) ; ii ) two different PrPSc types could be generated during unseeded PMCA reactions in either M109M and I109I vole substrates ( Figure S1 ) ; and iii ) there was no obvious correlation between the age of the voles used for preparing PMCA substrates and the relative ability to generate supposedly de novo PrPSc ( Table S1 ) . A detailed WB analysis of PrPSc types obtained from unseeded PMCA reactions in M109M and I109I vole substrates showed that the supposedly de novo generated PrPSc types could not be unequivocally distinguished from some of the vole-passaged prion strains used in our laboratory ( Figures S2 , S3 ) . Bioassay of brain homogenates after several consecutive rounds of saPMCA showed that PrPSc from either seeded and unseeded positive PMCA reactions were infectious after intracerebral inoculation of voles ( Tables S2 , S3 and Text S2 ) . Biological strain typing in M109M voles showed that the two different de novo PrPSc types induced two easily distinguishable prion strains , based on survival times ( Table S2 ) , WB analysis of PrPSc ( Figure S4 ) and brain regional distribution of PrPSc deposition and spongiform degeneration ( Figures S5 , S6 and Text S2 ) . However , these two putatively spontaneous prion strains could not be unequivocally discriminated from other PMCA-passaged prion strains used in our experiments ( Table S3 and Figure S6 ) . Considering the importance of demonstrating the spontaneous generation of prions in experimental conditions and our inability to unequivocally exclude cross-contamination by a posteriori biochemical and biological analyses of de novo generated prions , we decided to confirm our preliminary results by replicating the experiments in a different laboratory . A new series of experiments was therefore performed in a prion-free laboratory at ISS by the same person who obtained the preliminary results at the SCRIPPS Institute ( GMC ) . Importantly , during these experiments no positive controls were used , as they had been in the previous experiments; in this way there was no danger of any cross-contamination event and the laboratory was maintained prion-free . Eleven independent saPMCA experiments were carried out using exclusively unseeded substrate samples , which were processed for 6–13 consecutive rounds ( Table 1 ) . During these experiments several factors were tested which could potentially influence the spontaneous generation of prions . These were: genetic vole PRNP genotype ( M109M or I109I ) , individual age of the animals , power of sonication , duration of sonication or incubation and the number of cycles in each round . All the conditions tested are reported in detail in Table 1 . All saPMCA samples from each round of the above experiments were analysed by Western blot . No samples showed a signal compatible with genuine PrPSc . As no seed ( positive control ) was included in the experiments , the efficiency of all substrates used in previous experiments and the efficiency of the different PMCA settings used ( Table 1 ) were further tested . For these experiments , the same substrates and PMCA settings described in Table 1 were used in PMCA experiments seeded with v586 prion strain ( see Methods ) . All substrates and all PMCA conditions successfully amplified the seed to the 10−3/10−5 dilution in a single PMCA round of 24 hours ( Figure S7 and data not shown ) . However it can be hypothesised that the de novo appearance of prions requires a high amplification efficiency . We therefore evaluated the sensitivity of our saPMCA by amplifying serial dilutions ( from 10−2 to 10−14 ) of the v586 strain in healthy vole brain homogenates in consecutive rounds of 24 hours in standard conditions . The results are shown schematically in Figure 2A . The sensitivity of detection was very high , the 10−9 dilution being positive after 3 rounds . However , after the fifth round both very high dilutions of the seed and unseeded tubes became positive . This experiment was repeated with similar results ( not shown ) . The molecular profile of PrPSc recovered from seeded and unseeded reactions revealed a molecular pattern identical to the v586 strain used as inoculum ( Figure 3 ) . Taken together , and given that the only difference in comparison with previous experiments reported in Table 1 was the presence of a positive seed , these data strongly suggest that the de novo appearance of PrPSc in unseeded tubes could have been due to cross-contamination . Given that prion-infected samples had been introduced , the laboratory was no longer considered prion-free . Because of the contrasting results obtained at SCRIPPS and at ISS , a further and final attempt to test the possibility of de novo generation of prions was made . Skilled personnel ( NF ) from the SCRIPPS Research Institute joined the local staff at ISS ( GMC ) to perform a new series of saPMCA experiments under prion-free conditions . The experiment was carried out in a bacteriology laboratory that had never been used for prions . A new sonicator ( Misonix S4000 ) , gravity oven and thermal bath were bought , along with pipettes , Potter type glass homogenisers , consumables and reagents . Seventy-two unseeded bank vole substrate samples ( derived from 11 M109M and 4 I109I voles ) were submitted to saPMCA for 10 consecutive rounds of 24 hours , using standard settings . The experiment was monitored by analysing , by Western blot , all the 720 PMCA products . As with previous experiments with unseeded samples ( Table 1 ) , no evidence of PrPSc generation was observed in any of the samples ( data not shown ) . Immediately after the completion of the experiments , the sonicator was moved to our prion laboratory in order to test the efficiency of the substrates and the proper functioning of the sonicator . Amplification of dilutions from 10−3 to 10−6 was attained with all the substrates after 1 round of 24 hours ( data not shown ) , demonstrating the efficiency of our PMCA conditions and the consistency of the negative results previously obtained . Overall the above results show that the supposedly de novo appearance of PrPSc in unseeded samples observed in our previous experiments was not replicated when working in an absolutely prion-free laboratory ( i . e . without using positive controls ) , even after many consecutive rounds of saPMCA and in different experimental conditions . By contrast the appearance of spurious PrPSc in unseeded negative controls when positive and negative samples were processed together ( Figure 2A ) , suggests that the most likely explanation for the appearance of de novo PrPSc previously observed is the occurrence of cross-contamination during saPMCA . The occurrence of cross-contamination during saPMCA raises serious doubts about the advisability of using PMCA for the detection of prions , particularly when ultrasensitive amplification is desired . We therefore focused on identifying the critical points where cross-contamination could occur and the best conditions for sensitive and specific amplification . In principle , two critical points at which contamination could have occurred were identified: 1 ) in the sonicator , during repeated cycles of sonication/incubation; 2 ) during manipulation of samples between PMCA rounds . To assess which of these two steps was responsible for cross contamination , serial dilutions of the v586 prion strain and two distinct groups of unseeded negative controls ( A and B ) were amplified for 7 consecutive rounds ( Figure 2B ) . All tubes were amplified and processed together , except that the tubes of control group A were handled separately after each round in order to avoid cross-contamination during manipulation of samples . Passages of control group A were carried out in a new laminar flow hood using a new pipette , while passages of control group B were carried out together with seeded samples . The results were comparable to those obtained in previous experiments ( compare Figures 2A and 2B ) , with control tubes of both group A and B showing positive signals after 4 and 3 PMCA rounds , respectively . A single PrPSc molecular signature , identical to the v586 inoculum , was observed in all positive samples ( data not shown ) . As the tubes used for control group A were never exposed to possible sources of contamination outside the sonicator , these data imply that cross-contamination occurs in the sonicator during the amplification cycles , although they do not allow us to exclude that tubes may also become contaminated during passages . To check if the sonicator was able to retain PrPSc molecules and to release them later as a source of contamination in subsequent experiments , we then serially amplified unseeded samples in the sonicator just used for the previous experiments . Passages were carried out under the flow hood and with the pipette used for previous seeded experiments . Following 10 consecutive rounds under standard PMCA conditions , no positive sample was obtained ( data not shown ) , showing that the sonicator , the flow hood and the pipette previously used for seeded PMCA reactions are not a strong source of contamination per se . Overall the above results indicate that the simultaneous manipulation and processing of seeded and un-seeded samples is critical and may easily give rise to cross-contamination events , with the most likely critical factor being the simultaneous presence of seeded and unseeded tubes in the sonicator during the amplification cycles . Moreover , they also indicate that indirect contamination of the environment ( benches , laminar flow hood ) and instruments ( pipettes , sonicator , thermal bath ) from previous seeded experiments is not critical , provided that general measures to limit it are taken . During PMCA , the sonication of substrates produces mechanical shearing inside the reaction tube that might force opening of the vial , thus exposing unseeded samples to cross-contamination . It is also possible that small prion particles could penetrates through microscopic cavities between the tube wall and cap contaminating water in the horn and non-seeded samples . The 0 . 2 mL PCR tubes used for PMCA do not lock and are intended to be used in a thermal cycler . In effect , the caps of the tubes in the thermal cycler are normally tightened by the pressure of a heated lid . In order to improve the tightness of the 0 . 2 mL reaction tubes , we first sealed the tubes with a small Parafilm M strip positioned on the external junction between the tube and its cap , and then developed a “sealer” with a moving arm equipped with a sonicator probe . When the probe was applied to the cap of the vial , it was fastened to the tube by the heat generated by short sonication pulses . Both procedures certainly improved the tightness of the tubes , although when serial PMCA was performed they proved inadequate to prevent cross-contamination completely ( data not shown ) . Subsequently we evaluated new vials bought on the market . We selected Multiply-Safecup Biosphere , handy 0 , 5 mL tubes with screw cap and 100 µl volume limitation that works as a double closure system ( Figure S8 ) . The ability of the new 0 , 5 mL screw-cap vials to support high amplification levels was evaluated by amplifying serial dilutions of v586 inoculum . No difference was observed when we compared the efficiency of the 0 , 2 ml vial and the 0 , 5 mL screw-cap tubes ( data not shown ) . Importantly , the screw-cap tubes were able completely to prevent cross-contamination , even after many consecutive rounds ( see below ) . In order to achieve the best conditions for high amplification efficiency , which is useful in sensitive diagnostic tests , we investigated the conditions that could lead to the highest sensitivity in a limited number of rounds using 0 , 5 mL screw-cap vials . This was done by amplifying dilution curves of v586 inoculum and evaluating the level of amplification obtained after 12 , 24 , 48 and 72 hours of PMCA using standard settings ( Figure 4 ) . By increasing the duration of PMCA from 24 to 48 hours , we observed a 3-log improvement in PrPSc amplification , making it possible to increase considerably the overall sensitivity attainable in a single round . Further increasing the duration to 72 hours did not , however , seem to be useful , since the amplification level did not substantially increase . This was further investigated by testing the ability of 48 h-old substrates ( previously treated with 48 hours of incubation/sonication cycles ) to support PrPSc amplification . The failure of 48 h-old substrates to amplify PrPSc ( Figure S9 ) confirmed that the ability of substrates to support amplification dramatically decreases after 48 hours of PMCA . Single-round 48-hour PMCA was thus set up and a limit of detection ranging from 10−9 to 10−10 was observed when the experiments were repeated several times using different v586 seeds preparations and different substrates . We then attempted the serial 48-hour PMCA in order to investigate the limit of detection of v586 under these new conditions . As shown in Figure 5 , the level of amplification reached after the first round did not increase further in successive PMCA rounds . Importantly , negative controls and dilutions exceeding the limit of 10−9 remained negative up to the seventh PMCA round . Therefore , by introducing 0 , 5 mL screw-cap vials and 48-hour PMCA rounds , cross-contamination was efficiently controlled while ultra-high sensitivity was maintained for many consecutive rounds . Since then we have performed numerous saPMCA experiments using the same working conditions . The appearance of spurious PrPSc signals was observed in only two out of more than 500 samples that were submitted to saPMCA . One of the two samples was an unseeded negative control , the other was a10−15 dilution of v586 . The PrPSc of these samples preserved the same biochemical properties as the v586 seed used in the experiments . This clearly indicates that although cross-contamination in the sonicator can be effectively prevented by screw-cap vials , contamination during manipulation of samples can still lead to rare cross-contamination events , as often happens during ultrasensitive diagnostic tests .
In the present study we describe the results of a large series of PMCA experiments under strictly controlled conditions which highlight the drawbacks and potential of PMCA when ultrasensitive detection is desired and propose technical improvements to increase the robustness of the technique . This work was stimulated by observing how the extraordinary potential of PMCA is accompanied by a disturbing production of infectious PrPSc in unseeded reaction tubes , which initially led us to hypothesise the occurrence of “spontaneous” or de novo generation of prions . The de novo generation of prions agrees with the prion theory , which postulates that sporadic TSEs may originate from the stochastic occurrence of spontaneous PrPC conversion into PrPSc . Several lines of evidence support this hypothesis . Infectious prions have been generated from β-rich recombinant mouse PrP ( 89–230 ) [5] . Aguzzi and colleagues reported the spontaneous generation of prions in transgenic mice carrying a mutated prion gene ( S170N , N174T ) [32] . They also observed prion infectivity in mice over-expressing wild type PrP ( tga20 line ) after inoculation of brain homogenates from extremely aged , uninoculated mice of the same line . The spontaneous occurrence of prions in cell cultures has recently been reported by Edgeworth and colleagues [33] . As PMCA is able to reproduce in vitro several aspects of prion biology , it appears theoretically to be an appropriate technique for modelling the de novo generation of prions , making it this field of investigation very attractive . However , the hypothesis that prions can be generated de novo is not easy to refute experimentally and - given that de novo prions are postulated to have the same characteristics and properties as other prions – there is no way to distinguish prions generated de novo from potential contaminants . Nonetheless , it was recently reported that full-length recombinant prion protein , that had been converted into the cross-beta-sheet amyloid form and subjected to annealing , gave rise to a disease with clearly distinctive phenotype from archetypal 263K , upon serial transmission in hamster [7] . However , drawing an a posteriori distinction between prions putatively generated de novo and prions from other sources recognised as putative contaminants is hampered by the potential of prions to mutate , both in vivo [34] and in vitro [35] . In our experiments , supposedly de novo prions generated in vole PMCA were not easily distinguishable from other conventional prion strains ( Figures S2 , S3 ) . The only way to obtain direct evidence of the de novo generation of prions is by establishing experimental conditions in which the occurrence of contamination can be excluded categorically . Since prions are not thought to be ubiquitous contaminants , the use of rigorously prion-free procedures appears adequate to achieve these conditions . We performed several unseeded PMCA experiments with hundreds of samples processed and analysed over more than 6 months in absolutely prion-free conditions . Different PMCA settings and several substrates from many voles of different ages were used . No evidence of de novo generation of prions was obtained , despite the high levels of sensitivity reached . Our results appear to be in contrast with those obtained by other groups . The de novo generation of prions during PMCA experiments has been reported by several authors . Saa et al . [25] reported the spontaneous generation of PrPSc in unseeded PMCA reactions , especially when more than 10 rounds of standard PMCA were performed . However , they were unable to state conclusively whether the newly generated PrPSc was the result of cross-contamination or de novo generation . Deleault et al . [4] and Thorne and Terry [26] obtained putative de novo prions in unseeded PMCA reactions only when a synthetic polyanion ( PolyA ) was added , but not in its absence . Barria et al . [27] reported that de novo generation was not seen under standard PMCA conditions but could be obtained only by prolonging the duration of PMCA rounds from 3 to 5 days . Recently Wang et al . [6] observed the appearance of infectious prions from unseeded samples after numerous consecutive rounds of saPMCA in a novel PMCA system based on purified recombinant PrP , a synthetic anionic lipid and liver RNA , but not when normal mouse brain was used . The PMCA conditions that allow prions to be generated de novo are thus still unclear . Interestingly , on the basis of the results reported by Barria and co-authors [27] , who observed de novo prions only using very extended PMCA rounds , it could be concluded that the spontaneous generation of prions does not follow the same replication model as the seeded amplification . De novo prions would seem to be generated under conditions in which PrPC and other potential co-factors contained in the substrate have lost their ability to support the seeded amplification . Both our ( Figure S9 ) and Soto's results [18] indeed demonstrate that the substrates lack their potential to support amplification after 72 hours of sonication/incubation . The key factor in demonstrating that prions have been generated de novo is the stringency of measures taken to avoid contamination . Unfortunately , details on measures taken to control cross-contamination between seeded and unseeded samples were not always presented . Although the problem of false positives has been addressed in recent papers [36] , [25] , Deleault et al . and Barria et al . [4] , [27] reported that prions were generated de novo in conditions of extremely reduced possibility of cross contamination . Nonetheless , Barria et al [27] and Wang et al [6] concluded that cross-contamination could not be entirely ruled out . The efficiency of PMCA is variable , depending on the combination of seed and substrate . Sonicator settings are often adapted to reach maximum efficiency [18] . Considering that one of the main objectives of this study was to investigate the spread of contamination during saPMCA , we decided to adopt v586 as infected inoculum for seeded experiments because it was a contaminant in origin ( see Methods ) . After seeding vole substrate with v586 strain amplification proved extremely efficient . The limit of detection , observed in several independent experiments , ranged between 10−9 and 10−10 of the infected brain homogenate in a single 48-hour round of PMCA . Additional rounds did not improve the overall sensitivity . These data are in agreement with the efficiency reported for mouse-adapted scrapie and BSE , which is the highest reported in the literature [37] . Results of the limiting dilution experiments showed that 10−10 is the highest dilution of the inoculum able to trigger a positive amplification , corresponding approximately to 6 femtoliters of infected brain homogenate . Similar levels of contamination are not easy to control , especially for a procedure that is performed using equipment originally developed for other purposes . We have also observed cross-contamination when working with PMCA substrates from other species , such as mice ( data not shown ) , although it was observed at a lower level and after an higher number of PMCA rounds . This might be due to the lower amplification efficiency we have observed with mouse-derived compared to vole-derived substrates . When ultrasensitive amplification levels are reached , such as those attained with vole brains as substrates , the risk that minimal inadvertent contamination of reactions may artificially initiate amplification is extremely high . These findings suggest the need to critically reassess previous reports of supposedly de novo prion generation obtained by standard PMCA setting . In experiments using only unseeded samples , we determined that the equipment used ( pipettes , sonicator , thermal bath ) and the working environment ( laminar flow hood , bench ) are not direct sources of contamination , provided that general safety measures are adopted . It is unlikely that they can release prions potentially acquired during previous experiments at levels able to trigger amplification in subsequent PMCA reactions . In contrast , direct or indirect cross-contamination easily occurs between seeded and unseeded samples when these are manipulated and processed at the same time . The presence of high numbers of seeded tubes in the sonicator and the progressive and dramatic increase in amplified products during serial rounds further increase the risk . Sonication pulses violently shake the samples . The generation of aerosol and micro-particles within the reaction tubes during sonication probably represents a key critical factor by enormously increasing the risk of contamination of the rim of the tube and of material leakage at the opening of the tubes . The use of Multiply-Safecup Biosphere tubes radically improved the handling of samples and , thanks to both the screw cap and the volume limitation system radically reduced the risk of leakage . The preservation of the same amplification efficiency using larger tubes with thicker walls and other significant differences compared with PCR tubes , without the need to modify the sonication parameters , demonstrates that PMCA is capable of coping well with significant changes in the operating environment . In the course of the study we observed a dramatic decrease in false positive results from the moment we adopted the screw-cap tubes . This provides strong evidence that false positive results actually derive from cross-contamination events which can be efficiently prevented by tighter closure of the sample tubes . Spurious results were observed even with the highest level of safety measures , but these were very rare and comparable to those observed with other techniques . We cannot exclude the possibility that some of these events actually concealed the de novo generation of prions , but while we cannot dismiss alternative explanations , the occurrence of inadvertent contamination still appears the most appropriate and scientifically sound interpretation . This is further strengthened by the unique molecular signature observed throughout our study , similar to the original v586 seed . The few spurious results that we observed after the adoption of screw-cap tubes occurred after several rounds of serial PMCA , and could be tentatively explained by inadvertent contamination during manipulation of the tubes for seeding successive rounds of serial PMCA . In this respect , methods able to increase the sensitivity of PMCA , as recently reported by Gonzalez-Montalban and colleagues [38] , would reduce the number of serial passages needed to achieve ultrasensitive detection of PrPSc and , conceivably , would also be valuable for preventing cross-contamination events . The results of the present study certainly do not exclude the possibility that , in different experimental conditions , prions can be generated de novo . They provide a serious warning that contamination can very easily occur when ultrasensitive levels of detection are reached and that extreme caution is needed to avoid the over- or misinterpretation of results when delicate issues such as the de novo generation of prions are explored .
The research protocol was approved by the Service for Biotechnology and Animal Welfare of the Istituto Superiore di Sanità and authorized by the Italian Ministry of Health , according to Legislative Decree 116/92 , which implemented the European Directive 86/609/EEC on laboratory animal protection in Italy . Animal welfare was routinely checked by veterinarians from the Service for Biotechnology and Animal Welfare . Substrates were prepared from male and female bank voles of different ages , carrying either M109M or I109I PrP genotypes . Unless indicated otherwise ( see Tables 1 and S1 ) , the animals were 2–4 months old . Voles were sacrificed using carbon dioxide and immediately perfused with phosphate-buffered saline ( PBS ) plus 5 mM ethylendiaminetetraacetic acid ( EDTA ) . Immediately after perfusion , the brains were dissected and frozen at −80°C . 10% brain homogenates ( weight/volume ) were prepared in conversion buffer ( PBS 1x , pH 7 , 4; 0 , 15 M NaCl; 1% Triton X-100 ) with the Roche Complete Protease inhibitor cocktail ( 1 tablet in 50 mL conversion buffer ) , using new and dedicated glass potters . Substrates were divided into aliquots and either used or stored at –80°C immediately after homogenisation . De novo generation experiments ( Tables 1 and S1 ) were carried out using substrates from individual voles while for seeded experiments ( see Results ) , requiring larger amounts of substrate , we prepared homogeneous pools of substrates by mixing together 5 individual substrates from voles of 2–4 months of age . Preparation and storage of substrates were carried out in a laboratory never previously used for prion research , using equipment specifically dedicated and maintaining rigorously prion-free conditions . The vole-passaged spontaneous M109M strain B ( see results ) , indicated in the main text as v586 , was used as prion inoculum for seeded PMCA experiments . Brain tissue from terminally affected M109M voles after second passage of M109M strain B ( see Table S2 ) was homogenised in PBS ( 10% w/v ) containing Complete Protease inhibitor cocktail ( Roche ) using disposable Teflon pestles directly in 1 . 5 mL Eppendorf tubes . Following preparation the brain homogenate was divided into aliquots and stored at −20°C . PMCA was performed according to the protocol of Castilla et al . [18] . Amplification was performed in a total volume of 60 µl . Tubes containing the reaction mix were incubated at 37°C , placed in a disk-shaped rack on the microplate horn of the sonicator ( Misonix S3000 ) . The horn was placed in a gravity oven . Water in the horn was circulated in a thermal bath at a constant temperature of 37°C . The standard sonication programme consisted of 30 second sonication pulses every 30 minutes for 24- or 48-hour periods . In particular cases single parameters of PMCA were modified ( see Table 1 ) in order to investigate different conditions of amplification . At the end of each round , the PMCA material was gently span and diluted 1∶10 in fresh substrate ready for a new amplification step . Passages of seeded experiments were carried out in a laminar flow hood , using double filter pipette tips ( Eppendorf Dualfilter T . I . P . S . ) . During this study two kinds of tube were used to contain PMCA reactions: we began working with 0 . 2 mL tubes for PCR ( NUNC , cat . 248161 ) , then continued with 0 , 5 mL screw cap Multiply- Safecup ( Sarstedt , cat . 72 . 733 . 200 ) ( see Results ) . Access to the laboratory was restricted to authorised personnel and standard operating procedures were adopted for the use of laboratory equipment and sample manipulation . All personnel wore disposable coats , shoe covers and gloves . The working surfaces and equipment were cleaned with NaOH or NaClO after each experiment . These measures were further strengthened by changing the water of the sonicator circuit and decontaminating the plastic holder and horn cap by immersion in bleach after each round . 20 µL of PMCA material were digested with 100 µg/mL proteinase K ( pK ) ( Sigma-Aldrich ) . Samples were shaken at 900 rounds per minute ( rpm ) for one hour at 37°C . Digestion was then blocked by adding 2 µL of 10 mM phenylmethylsulfonyl fluoride ( PMSF ) ( Pierce Biotechnology - Thermo Fisher Scientific ) ; samples were then incubated for 5 minutes at 4°C . Ten micro-litres of NuPAGELDS Sample Buffer ( 4X ) and 3 µL NuPAGE Sample Reducing Agent ( 10X ) were added to each tube and samples were denatured by incubation at 90°C for 10 minutes . Western blot analysis: 12 µL of pK-digested PMCA samples were resolved by SDS-PAGE on a 10% Tris-glycine gel and transferred to PVDF . The membrane was blocked with 1% powdered skim milk in PBS for one hour at room temperature and incubated with mouse anti-PrP monoclonal antibody SAF84 ( Cayman Chemical ) . After washing , the membrane was incubated with secondary HRP-conjugated antibody ( ImmunoPure Peroxidase Conjugated Goat Anti-Mouse IgG ( H+L ) Pierce Biotechnology - Thermo Fisher Scientific ) and signals were detected using SuperSignal West Femto Maximum Sensitivity Substrate ( Pierce Biotechnology - Thermo Fisher Scientific ) . Chemiluminescence was detected with the VersaDoc imaging system ( Bio-Rad ) . All measurements were performed with QuantityOne software ( Bio-Rad ) .
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In an attempt to transpose to an in vitro system the particular sensitivity of the vole model to human and animal Transmissible Spongiform Encephalopathies ( TSEs ) , we first explored the suitability of vole brain homogenate as a substrate for PMCA . As well as observing the highly efficient replication of a variety of prion sources , we also found preliminary evidence of de novo prion generation in unseeded reactions . Careful analysis of the PMCA procedure , undertaken further to investigate these findings , showed , however , that they were the result of cross-contamination with seeded samples . We next identified and investigated the critical points of this procedure that are potentially responsible for cross-contamination . Our results suggest that in vitro systems for prion amplification could be more prone to cross-contamination than previously thought , particularly when harsh procedures , such as sonication , are involved . Experimental conditions able to reproduce spontaneous prion formation in a simple and easily reproducible in vitro system would be of crucial interest for understanding TSEs and other important neurodegenerative disorders . Given that in vitro methods are increasingly used in this field , our results emphasise the possible drawbacks of such approaches and call for the use of rigorously controlled conditions and cautious interpretation of data .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"medicine",
"biology",
"veterinary",
"science"
] |
2011
|
Ultra-Efficient PrPSc Amplification Highlights Potentialities and Pitfalls of PMCA Technology
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DEF-like and GLO-like class B floral homeotic genes encode closely related MADS-domain transcription factors that act as developmental switches involved in specifying the identity of petals and stamens during flower development . Class B gene function requires transcriptional upregulation by an autoregulatory loop that depends on obligate heterodimerization of DEF-like and GLO-like proteins . Because switch-like behavior of gene expression can be displayed by single genes already , the functional relevance of this complex circuitry has remained enigmatic . On the basis of a stochastic in silico model of class B gene and protein interactions , we suggest that obligate heterodimerization of class B floral homeotic proteins is not simply the result of neutral drift but enhanced the robustness of cell-fate organ identity decisions in the presence of stochastic noise . This finding strongly corroborates the view that the appearance of this regulatory mechanism during angiosperm phylogeny led to a canalization of flower development and evolution .
Depending on the nature of the interactions of their constituents , gene regulatory circuits can display a variety of dynamical behaviors ranging from simple steady states , to switching and multistability , to oscillations . Temporal or spatial patterning during development requires activation of genes at a particular time or position , respectively , and the inhibition in the remaining time or part . Regulatory genes involved in such processes often show a switch-like temporal or spatial dynamics , which requires a direct or indirect positive non-linear feedback of the genes on their own expression , e . g . via dimers of their own product [1] . Switch-like behavior can be displayed by a single gene [2] , [3] , but many gene regulatory switches have a more complex structure . Due to the small number of molecules involved , these switches are inherently stochastic and their behavior under noisy conditions can strongly depend on their genetic architecture [4]–[6] . In some cases the complex regulatory interactions have been quite well documented , but the functional implications of the corresponding regulatory circuitry have remained enigmatic . A good case in point is provided by some floral homeotic ( or organ identity ) genes from model plants such as Arabidopsis thaliana ( thale cress; henceforth termed Arabidopsis ) and Antirrhinum majus ( snapdragon; henceforth called Antirrhinum ) . Floral homeotic genes act as developmental switches involved in specifying organ identity during flower development . According to the ‘ABC model’ , three classes of floral organ identity ( or homeotic ) genes act in a combinatorial way to specify the identity of four types of floral organs , with class A genes specifying sepals in the first floral whorl , A+B petals in the second whorl , B+C stamens ( male reproductive organs ) in the third whorl , and C alone carpels ( female organs ) in the fourth floral whorl [7] . The combinatorial genetic interaction of floral homeotic genes may involve the formation of multimeric transcription factor complexes that also include class E ( or SEPALLATA ) proteins , as outlined by the ‘floral quartet’ model [8] . In Antirrhinum , there are two different class B genes termed DEFICIENS ( DEF ) and GLOBOSA ( GLO ) . In Arabidopsis these genes are represented by APETALA3 ( AP3 ) , the putative orthologue of DEF , and PISTILLATA ( PI ) , the putative GLO orthologue . For simplicity , we will refer to DEF-like and GLO-like genes from here on . DEF-like and GLO-like genes represent paralogous gene clades that originated by the duplication of a class B gene precursor 200–300 million years ago [9] , [10] . All class B genes identified so far , like most other floral homeotic genes , belong to the family of MADS-box genes , encoding MADS-domain transcription factors [11] , [12] . Mutant phenotypes reveal that DEF-like and GLO-like genes are essential for the development of petals and stamens , since def and glo loss-of-function mutants all produce flowers with petals converted into sepals and stamens transformed into carpels [13]–[17] . When co-expressed in the context of a flower , DEF and GLO are not only required , but even sufficient for specifying petal and stamen identity , as revealed by transgenic studies ( e . g . , [18] ) . Induction and stable maintenance of switch-gene expression are typically two independent processes , depending on a transient external signal and autoregulation , respectively [19] . Whenever a transient activating signal is above a threshold , the gene activity switches from the OFF- to the ON-state . The signal is required only for initiation , but not for maintenance of gene activity . Due to the autoregulation , the gene's response becomes in a wide range independent of the exact strength of the input signal . During later stages of flower development ( in Arabidopsis from stage 5 on ) , mRNA of DEF- and GLO-like genes is detected only in whorls 2 and 3 [15] , [16] . This is so because upregulation and maintenance of class B gene expression in Arabidopsis and Antirrhinum during later stages of flower development depends on both DEF and GLO , due to an autoregulatory loop involving these proteins ( Figure 1C ) . The proteins encoded by class B genes of Arabidopsis and Antirrhinum are stable and functional in the cell only as heterodimers , i . e . , DEF-GLO complexes , because both nuclear localization and sequence-specific DNA-binding depend on obligate heterodimerization [19] , [20] . Class B protein heterodimers bind to specific cis-regulatory DNA sequence elements termed ‘CArG-boxes’ ( consensus 5′-CC ( A/T ) 6GG-3′ ) . Except PI , the promoter regions of all class B genes of Arabidopsis and Antirrhinum contain CArG-boxes that are involved in positively regulating class B gene expression [21]–[23] . These data , together with the total functional interdependence of the two class B gene paralogues , strongly corroborate the hypothesis that positive autoregulatory control of class B genes involves heterodimers of class B proteins that bind to CArG-boxes in the promoters of class B genes ( Figure 1C ) [14] . Since PI lacks CArG-boxes in a minimal promoter region , the autoregulatory feedback may work indirectly in this case [23] , [24] . Obligate heterodimerization of their encoded products involved in positive autoregulation explains why DEF-like and GLO-like genes are functionally non-redundant and totally interdependent . This raises the question as to how and why such a regulatory system originated in evolution . Studies on the interaction of class B protein orthologues from diverse gymnosperms and angiosperms suggested that , following a gene duplication within the class B gene clade , obligate heterodimerization evolved in two steps from homodimerization via facultative heterodimerization [25] . Meanwhile obligate heterodimerization of DEF-like with GLO-like proteins has also been observed outside of the eudicots Arabidopsis and Antirrhinum in diverse groups of monocots , suggesting that it originated quite early or several times independently during angiosperm evolution [26] . So why then did obligate heterodimerization evolve ? In principle , it could represent a neutral change in protein-protein interactions that occurred by random genetic drift [25] . This cannot be excluded at the moment , but for several reasons , it appears not very likely . Even though obligate heterodimerization originated early or several times independently within class B proteins , it did not occur in any other class of floral homeotic proteins , suggesting some kind of functional specificity . Moreover , it occurs within evolutionary especially ‘successful’ ( e . g . , species-rich ) groups of angiosperms , suggesting that it might provide some selective advantage . Winter et al . [25] suggested that obligate heterodimerization in combination with autoregulation may have provided a selective advantage because of the fixation of class B gene expression patterns and thus the spatial domain of the floral homeotic B-function within the flower during evolution . Mutational changes in the promoter region of only one class B gene that expand the gene's expression domain may leave the late and functionally especially relevant expression domain of the class B genes unchanged , because expression of the other partner would be missing in the ectopic expression domain . Only parallel changes in both types of class B genes , which are much less likely than changes in single genes , could lead to ectopic expression of the B-function under the assumption of obligate heterodimerization and strong autoregulation . Thus obligate heterodimerization may have evolved in parallel , or even as a prerequisite , of the canalization of floral development and thus standardization of floral structure in some groups of flowering plants [25] . Amending this ‘evolutionary’ explanation of obligate heterodimerization , we put forward and test a set of stochastic in silico models of class B gene and protein interactions as shown in Figure 1 , thus testing the hypothesis that obligate heterodimerization also provides advantages during development by providing robustness against wrong cell-fate decisions caused by stochastic noise . The models enabled us to study the influence of noise in isolation from other factors , and allowed the comparison of three major stages in the envisioned path of evolutionary transitions ( Figure 1 ) : ( A ) One ancestral gene positively regulates its transcription via a homodimer of its own gene product; ( B ) Two genes positively regulate their transcription via homo- and heterodimers of both types of products; this very likely represents the situation directly after duplication of the ancestral gene; ( C ) Obligate heterodimerization of the two products for regulation , i . e . , the situation in extant Arabidopsis and Antirrhinum . Since only a small number of individual transcription factors is actually in the nucleus at any time [24] , [25] , stochastic fluctuations play a large role in the behavior of gene regulatory circuits , and may have an influence on their evolutionary dynamics [5] , [27] . Each model consists of a set of reactions for transcription factor binding , transcription , dimerization , and decay ( Table S1 ) , where translation is modeled in one step together with dimerization for efficiency ( details in Methods section ) . In turn , each reaction is associated with a propensity function ( Tables S2 and S3 ) , which yields the probability of an occurrence of that reaction in a time step . Using the Gillespie algorithm [28] , the exact order and timing of reactions is then stochastically determined , based on the propensities . To model transient activation of the circuits , we simulate an inflow of activating molecules ( summarizing all different activating transcription factors other than DEF/GLO that act on the respective genes ) over 50 minutes of simulated time . After this time , the inflow is switched off and the system equilibrates , i . e . , reaches a state in which no change occurs except for stochastic fluctuations ( always reached after 72 hours of simulated time ) . If at this point gene product dimers are still present , the circuit is considered as active ( full expression ) , otherwise it is inactive ( no expression of class B genes ) . Linear stability analysis of the corresponding differential equation system reveals that both the active and the inactive state constitute stable fixed points in all three systems , with an unstable fixed point in between ( data not shown ) .
The activation of the DEF and GLO genes depends on a temporally limited concerted action of many more genes and proteins besides the class B genes themselves , which have been described from an evo-devo perspective [12] and by mathematical modeling [29] . To keep the focus on the self-regulation of the genetic switch , we summarize these in one common or two distinct activators for both genes , respectively . In the first experiment we used a common regulator to temporally activate both genes , and investigated the switching behavior of the three circuits with regard to the number of available activatory input molecules . Looking at the probability of reaching full expression ( Figure 2A ) , the most probable state in the one-gene circuit switches from no steady-state expression ( resulting in a non-class B cell identity ) to full expression ( class B , i . e . , petal or stamen cell ) at approximately 10 input molecules . Gene duplication without further mutational changes leads to a 3 times lower switching threshold ( Figure 2A ) , which may entail a drastically increased zone of class B gene expression in the flower . Mutations leading to obligate heterodimerization again increase the activation threshold to the previous level , thus restoring the class B gene expression region ( Figure 2A ) . Therefore , in contrast to the facultative heterodimerization circuit , obligate heterodimerization results in the same switching threshold and thus the same domain of expression as just one autoregulatory gene . This result is in contradiction to an intuitive expectation that two genes can produce twice as many dimers as a single gene . With obligate heterodimerization , however , the heterodimers assemble from translated products of one DEF and one GLO mRNA intermediate , while the homodimer in the one-gene system is produced from two translated proteins of the same type . Because mRNA is not used up in translation , this leads to equal production rates for the heterodimer in the obligate heterodimerization system and the homodimer in the one-gene system . To look at the robustness of the switching decision against stochastic noise , we calculated the decision uncertainty ( binary entropy ) , thus more uncertainty implies less robustness . Focusing on the two circuits with identical expression domains , this uncertainty is nearly equal in the first and third circuit for small numbers of activatory input molecules , until the peak of uncertainty is reached . In contrast , the probability for a decision against class B gene mediated cell identity despite large numbers of activatory input molecules is significantly higher in the one-gene circuit than in the circuit with obligate heterodimerization . With 60 activatory molecules , the probability for such a ‘false negative’ in the former circuit is still 10% , while the latter one achieves nearly 100% correct decisions under our conditions ( Figure 2B ) . Hence , comparing one autoregulatory class B gene with the circuit after duplication and reduction to obligate heterodimerization , our model suggests that an important difference lies in the response to larger numbers of activatory molecules , where the latter system exhibits a clearly reduced tendency to switch off by mistake . This is explained by the fact that although the circuit needs both DEF-like and GLO-like proteins to sustain activation , its two pools of gene products provide a buffer to temporary stochastic failure of one of the two genes . This is especially important during the initial phase of activation , where circuits that are supposed to lock themselves into permanent expression are susceptible to a run of ‘bad luck’ , i . e . , the supposedly-active genes are inactive over a longer period of time . Obligate heterodimerization of gene products therefore provides a way to gain robustness against wrong cell identity decisions while retaining the original expression domain of one autoregulatory gene . Even though the mechanisms of the initial activation of DEF-like and GLO-like genes appear to be quite similar , they are very likely not identical [23] , since the initial expression patterns of DEF- and GLO-like genes are slightly different . In Arabidopsis flowers at an early developmental stage 3 , AP3 ( DEF-like ) is expressed in the organ primordia of whorls 2 and 3 , but also in parts of whorl 1 , while PI ( GLO-like ) is expressed in whorls 2–4 at the same stage [15] , [16] . In contrast , the AP3 orthologue DEF is expressed weakly in the organ primordia of whorl 4 ( carpels ) and very weakly in those of whorl 1 ( sepals ) , while the PI orthologue GLO is expressed in sepal but not carpel primordia of early stages during Antirrhinum flower development [14] , [19] . To investigate the consequences of independent input into both genes , we explored a model setting in which the DEF-like and the GLO-like gene are activated independently by two input signals . Our experiments showed that immediately after gene duplication , the mode of integration represents a logical ‘OR’ , meaning that both inputs can independently switch on the circuit ( Figure 3A ) . In this case , each input has the role of the one input present before duplication . After the transition to obligate heterodimerization , a logic ‘AND’ function is achieved ( Figure 3B ) , thus both inputs are needed for activation . In conclusion , we are providing here , to the best of our knowledge , the first rationale , developmental genetic explanation for the intricate design of a genetic switch controlling class B floral homeotic gene expression in core eudicots , involving obligate heterodimerization and positive autoregulatory feedback of two duplicate genes or their protein products , respectively . The increased robustness against unwanted deactivation by chance found in case of obligate heterodimerization strongly suggests that this mechanism has a distinct advantage when the number of available regulatory molecules is small , leading to less cells of wrong identity in a floral organ and therefore to sharper organ identity transitions . It should be noted that since the mathematical model applies to any system with obligate heterodimerization and positive feedback , the conclusions drawn here also transfer to any such system . However , to the best of our knowledge , the phenomenon of obligate heterodimerization together with positive feedback seems quite rare in genetic regulation outside of flower development , potentially due to the high cost of maintaining this system together with a strong dependence of the predicted fitness gain on external factors that might be specific for the situation depicted here . In the standard ABC model , class A and C genes are mutually antagonistic [7] , [30] , while class B genes have no floral homeotic ‘repressor’ , possibly explaining the class-specific need for sharpened expression domains and thus obligate heterodimerization , which is not found in the other two gene classes . However , Zhao et al recently reported that the antagonistic expression of class A and class C genes is involved in defining the expression domain of class B genes in Arabidopsis [31] , suggesting that our observation may not be sufficient to explain the obligate heterodimerization of class B proteins . Taking a different perspective , the evolution of a regulatory ‘AND’ function out of an ‘OR’ function may have provided the plant with a more stringent control of the class B floral homeotic genes depending on different induction signals . The fact that there must be different inputs into DEF- and GLO-like genes is obvious from gene expression studies ( see above ) , but its functional importance may have escaped the attention of previous investigations because of the coordinate upregulation and functional importance of DEF- and GLO-like genes in the second and third floral whorl . Our results suggest that identifying these different induction pathways , and clarifying their molecular mechanisms ( e . g . , trans-acting factors and cis-regulatory DNA motifs in DEF-like and GLO-like genes being involved ) would enable an important step forward in understanding class B floral homeotic gene function in flowering plants . The functional implication of these different input signals , and hence also of our hypothesis , could be tested by transgenic experiments . For example , Arabidopsis class B gene mutants in which both the AP3 and the PI gene have been brought under the control of the AP3 or the PI promoter rather than every gene under its own promoter ( as in the wild-type ) should affect the spatial or temporal development of petals or stamens , or both . Transgenic plants mutated at the pi locus ( pi-1 ) in which wild-type PI is expressed under control of the AP3 promoter ( 5D3 ) have already been reported [32] . These plants were used only as control for other experiments and have therefore not been described in much detail concerning the traits of interest here . However , it is clear that the 5D3::PI pi-1/pi-1 plants do not just show petals in the second floral whorl and stamens in the third floral whorl , as wild-type plants do; rather , they frequently develop sepal/petal mosaics in the second whorl , and mosaic organs or even carpels in the third whorl . These observations support our hypothesis concerning the functional importance of different induction pathways controlling the expression of DEF- and GLO-like genes for a proper development of organ identity in whorls two and three . More detailed analyses should be done to better understand how exactly the transgenic plants deviate from wild-type plants , and why . In addition , complementary transgenic studies in which AP3 is expressed under control of the PI gene promoter ( pPI ) should be performed in order to determine whether the pPI::AP3 ap3/ap3 plants have also developmental defects . The construction of a transgenic plant with switched promoters ( i . e . , pAP3::PI pPI::AP3 ap3/ap3 pi/pi ) would also be of great interest . Due to the apparently symmetric roles of AP3 and PI , one might speculate that this phenotype shows less deviation from the wild type than the transgenic plants with both genes under the control of a single promoter . If the origin of obligate heterodimerization of class B proteins during evolution provided some plants with selective advantages , one may expect that this had an impact on the molecular evolution of these proteins , which indeed seems to be the case . Class B floral homeotic proteins are MIKC-type MADS-domain proteins characterized by a defined domain structure , including a MADS ( M ) , Intervening ( I ) , Keratin-like ( K ) and a C-terminal ( C ) domain [11] , [12] . The K-domain mediates heterodimerization of GLO- and DEF-like proteins and has been postulated to fold into three amphipatic α-helices termed K1 , K2 and K3 [33] . In accordance with the expectations mentioned above , phylogenetic data indicate that after the duplication leading to DEF-like and GLO-like gene lineages , positive selection acted on the sections of these genes encoding the K-domain [34] . Intriguingly , one site under positive selection [34] is in a subdomain of K1 ( “position 97-102” according to ref . [33] ) proposed to be critical for heterodimerization specificity of DEF- and GLO-like proteins , as revealed by yeast two-hybrid analyses [33] . Given that the duplicates resulting from one homodimerizing protein would be capable of homo- as well as heterodimerization , our results suggest that positive selection should have enforced the loss of the homodimerization ability , since our model with duplicated class B genes and obligatory heterodimerization implies a sharper switching characteristic and a more constrained domain of class B gene expression than the one with facultative heterodimerization . It has been proposed that within the subdomain of K1 mentioned above , the interaction of Glu-97 in PI and Arg-102 in AP3 facilitates specific heterodimerization between AP3 and PI and prevents formation of homodimers [33] . For these sites , however , positive selection has not been detected [34] . Clearly , the relationships between the molecular evolution and biophysical interactions of DEF- and GLO-like proteins deserve more detailed studies in the future . All in all , our findings strongly support the view that the unexpected complexity of the floral homeotic gene switch considered here was not simply produced by random genetic drift but evolved because it provided the plant with a clear selective advantage . This might have led to the establishment of this regulatory motif in a whole range of plant species . In line with this notion , it is intriguing that at least some basal angiosperms do not have sharp , but ‘fading borders’ of expression of orthologues of DEF-like and GLO-like genes as well as gradual transitions in organ identity [35] . This underlines the hypothesis [25] that the mechanism described here improves developmental robustness and thus helped to canalize the development and hence also the evolution of flowers within angiosperm evolution .
The model investigated in this work is simulated using the Gillespie algorithm [28] , implemented as a C++ function linked to MATLAB ( The MathWorks , Inc . 2008 ) . This method , which simulates an exact instance of the stochastic master equation , explicitly accounts for each reaction event and thus represents stochastic effects in full detail . A list of all modelled reactions is given in Table S1 , and the full model is shown in Figure S2 . Transcription factor binding and unbinding are simple reaction processes , where we assume that exactly one functional copy of both DEF and GLO genes are available . For simplicity , we assume that only activated DNA is transcribed; however , experiments with basal transcription rates have led to qualitatively similar results . The decision to model translation and dimerization in one step was taken to simplify the model while keeping the focus on transcriptional rather than translational regulation . This entails that we only model DEF and GLO mRNA and the dimerized proteins , but not the single DEF and GLO proteins . The slight loss of accuracy here has been unavoidable , as we needed to keep the model computationally tractable for the large numbers of replicated experiments . All constituents of the model decay with a linear rate . For details on all kinetic rate constants , see the Text S1 and Tables S1–S3 . We conducted 10 , 000 experiments for each parameter combination . The different types of regulation are achieved by enabling or disabling the binding and activation of one type of gene by either a transcription factor homodimer produced by itself , a heterodimer of the products of both genes , or a homodimer of the proteins encoded by the other gene . Concerning initial activation , the class B genes are regulated by a number of ( possibly interacting ) transcription factors , some of which are still unknown . Since the aim of this contribution is to investigate the effect of autoregulation on gene activity , we summarize the effects of all upstream transcription factors in two specific input factors , IDEF and IGLO , and a common input factor , IC . As developmental switches , the B-genes are transiently activated by their inputs , which are switched off after activation . Depending on the level of gene activity reached by that time , this activity either stays high or decays to a low value again , corresponding to on- and off-states of the genes . To model the transient activation , an inflow of ( on average ) N activatory molecules ( of type IDEF , IGLO or IC , respectively ) over a period of T minutes was simulated . After time T , the inflow is switched off and the system is left alone , reaching steady state . Figure S1 shows example time courses for all three modes of regulation considered here . All three systems investigated in this work represent autoactivatory circuits , which are used by the plant to establish the expression ( ON-state ) or non-expression ( OFF-state ) of homeotic genes in certain floral whorls . Therefore , a decision has to be made , depending on the number of activatory input molecules initially coming into the system . For low numbers of input molecules , the decision should be ‘OFF’ , for higher numbers it should be ‘ON’ . To measure the uncertainty of this decision , we use the binary entropy function . Let X be a random variable that takes value 1 with probability p , value 0 with probability 1−p , i . e . , a Bernoulli trial . The entropy of X is defined asIn our case , X taking value 1 means that the system reaches ON-state , value 0 means OFF-state . Repeating the simulation 10 , 000 times , we compute the probability p for each specific number N of activatory input molecules IC ( Figure 2A ) . Using the formula above , this translates to the binary entropy , or decision uncertainty ( Figure 2B ) . Alternative approaches which could potentially lead to additional insights into the functionality of the DEF-GLO system include the application of control theory [36] or an analytical calculation of the first and second stochastic moments , which should confirm the experimental results in this paper .
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The development of organs , their position , and boundaries in multicellular organisms are defined by genes that can sustain their own activation over long periods of time , termed genetic switches . A good case in point is provided by the genetic machinery controlling the development of flowers in higher plants . In Arabidopsis thaliana and other plants , a particular class of these genes—DEF-like and GLO-like floral homeotic genes—regulates the development of petals and stamens . These genes are self-activating via a heterodimer of their protein products , making the activity of each one of them fully bound to the activity of the other one . The reason for their total functional interdependence has long remained unclear , as the expression of both genes is jointly controlled by shared transcription factors in addition to the heterodimer . In principle , one gene alone could provide their switching functionality . In this study , we use computer modeling to show that the obligate heterodimerization mechanism found in DEF- and GLO-like genes reduces the susceptibility of the genetic switch to failure caused by stochastic noise . This would have provided the system an evolutionary advantage over a single gene with the same functionality .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Methods"
] |
[
"developmental",
"biology/morphogenesis",
"and",
"cell",
"biology",
"computational",
"biology/transcriptional",
"regulation",
"developmental",
"biology/developmental",
"evolution",
"developmental",
"biology/plant",
"growth",
"and",
"development",
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"biology/cell",
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"development",
"computational",
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] |
2009
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Developmental Robustness by Obligate Interaction of Class B Floral Homeotic Genes and Proteins
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The opportunistic pathogen Burkholderia cenocepacia is particularly life-threatening for cystic fibrosis ( CF ) patients . Chronic lung infections with these bacteria can rapidly develop into fatal pulmonary necrosis and septicaemia . We have recently shown that macrophages are a critical site for replication of B . cenocepacia K56-2 and the induction of fatal pro-inflammatory responses using a zebrafish infection model . Here , we show that ShvR , a LysR-type transcriptional regulator that is important for biofilm formation , rough colony morphotype and inflammation in a rat lung infection model , is also required for the induction of fatal pro-inflammatory responses in zebrafish larvae . ShvR was not essential , however , for bacterial survival and replication in macrophages . Temporal , rhamnose-induced restoration of shvR expression in the shvR mutant during intramacrophage stages unequivocally demonstrated a key role for ShvR in transition from intracellular persistence to acute fatal pro-inflammatory disease . ShvR has been previously shown to tightly control the expression of the adjacent afc gene cluster , which specifies the synthesis of a lipopeptide with antifungal activity . Mutation of afcE , encoding an acyl-CoA dehydrogenase , has been shown to give similar phenotypes as the shvR mutant . We found that , like shvR , afcE is also critical for the switch from intracellular persistence to fatal infection in zebrafish . The closely related B . cenocepacia H111 has been shown to be less virulent than K56-2 in several infection models , including Galleria mellonella and rats . Interestingly , constitutive expression of shvR in H111 increased virulence in zebrafish larvae to almost K56-2 levels in a manner that absolutely required afc . These data confirm a critical role for afc in acute virulence caused by B . cenocepacia that depends on strain-specific regulatory control by ShvR . We propose that ShvR and AFC are important virulence factors of the more virulent Bcc species , either through pro-inflammatory effects of the lipopeptide AFC , or through AFC-dependent membrane properties .
B . cenocepacia belongs to the Burkholderia cepacia complex ( Bcc ) , currently encompassing 21 officially named species [1 , 2] . These opportunistic bacteria are notorious pathogens of cystic fibrosis ( CF ) patients [3 , 4] and are emerging as the culprit of serious infections in non-CF conditions , both in and outside the hospital [5–8] . Infection of CF airways by bacteria belonging to the Bcc can be asymptomatic but often result in chronic infection with intermittent acute exacerbations resulting in progressive worsening of lung function [9 , 10] . B . cenocepacia is particularly associated with reduced survival and a high risk for development of unpredictable acute fatal necrotizing pneumonia and sepsis , termed “cepacia syndrome” . Bcc bacteria are well-known for their intrinsic resistance to stress conditions and antibiotics [11–13] , complicating disease management and treatment strategies . Bcc bacteria are ubiquitously present in the environment and in industrial settings; they have evolved intricate signalling networks to rapidly adapt to changing or stressful environments , for instance in competition for nutrients with other bacteria or fungi , or as a defence mechanism against nematodes and protozoan hosts [14–18] . These signalling networks could also play important roles in pathogenicity and adaptation during human opportunistic infections . As an example , the GacA/GacS signalling cascade in Pseudomonas spp . has been shown to be involved in adaptation to natural conditions , while playing a crucial role during infection of CF patients by P . aeruginosa by providing a switch from acute ( Type 3 secretion system-dependent ) to chronic ( biofilm life stage ) infections [19 , 20] . Several regulators , including the quorum sensing systems CepI/R and CciI/R , and the global regulator AtsR , have been shown to be involved in virulence of B . cenocepacia using different model hosts [21–23] . ShvR is a LysR-type transcriptional regulator ( LTTR ) that has been shown to be involved in lung inflammation caused by B . cenocepacia K56-2 in a rat agar bead model of chronic lung infection [24] . The shvR mutant , however , was highly persistent in the infected rat lungs . In addition , the absence of ShvR resulted in loss of antifungal activity , reduced biofilm formation on abiotic surfaces [24] and a loss of rough colony morphotype , hence the name “Regulator of SHiny Variant” . The absence of shvR has been shown to result in moderate changes in the expression of over 1000 genes [25] . Interestingly , the expression of the adjacent afc operon , encoding 24 proteins specifying the synthesis of a lipopeptide with antifungal activity against Rhizoctonia solani [26] was reduced 100-fold , showing it is under tight positive regulatory control of ShvR [25] . Mutation of the afcE gene ( BCAS0208 ) , encoding an acyl-CoA dehydrogenase , resulted in the same phenotypes as those seen for the shvR mutant , including loss of antifungal activity , reduced biofilm formation , and shiny colony morphology [25 , 27 , 28] . Furthermore , mutation of afcE resulted in significantly reduced chronic lung inflammation in experimentally infected rats , similar to that found for a shvR mutant [28] . The high persistence of the shvR mutant in a rat infection model , alongside its reduced ability to form biofilms prompted us to investigate a role for ShvR and AfcE in virulence of B . cenocepacia K56-2 using zebrafish embryos , particularly their contribution during intramacrophage stages . B . cenocepacia is an intracellular pathogen and we have recently shown that macrophages play a crucial role in bacterial proliferation and acute fatal infection by B . cenocepacia in vivo using zebrafish larvae [29] . Importantly , other Bcc strains were able to persist in macrophages , but could not efficiently disseminate and induce robust host pro-inflammatory responses [29 , 30] . The reason for these different disease outcomes , which may have important clinical impact , is not clear . In this work , we find that the expression of shvR and afcE is critical for B . cenocepacia K56-2 to progress from an intracellular persistent stage with low pro-inflammatory responses , to disseminated acute fatal infection . Bioinformatic analysis indicates that the shvR/afc genes are present in the genomes of 50% of the 19 Bcc species sequenced to date . B . cenocepacia H111 is closely related to K56-2 , but shows reduced virulence in different animal models , including zebrafish . We show that acute virulence of H111 also depends on the presence of the afc cluster . Strikingly , constitutive expression of shvR from a lac-promoter increased virulence of H111 to almost K56-2 levels in an afc-dependent manner . Altogether , our results demonstrate an important role for the afc gene cluster in pathogenicity , the severity of which may depend on strain-specific upstream regulatory control mechanisms .
We first analysed the role of B . cenocepacia K56-2 ShvR in virulence in the zebrafish infection model . Zebrafish embryos were micro-injected at 30 hours post-fertilization ( hpf ) with B . cenocepacia K56-2 ( mCherrypCR11 ) , ΔshvR ( mCherrypCR11 ) or the complemented ΔshvR ( pshvR:shvR;mCherrypCR11 ) . Analysis of embryo survival showed that ΔshvR was unable to cause fatal infection over the time course of the experiment , in contrast to its wildtype parent which caused 100% embryo mortality in 3 days ( Fig 1A and [30] ) . In agreement with the observed reduced host mortality there was a significantly lower bacterial burden of ΔshvR compared to K56-2 at 24 and 48 hours post infection ( hpi ) ( Fig 1B ) . Although all embryos survived infection with ΔshvR , some contained significantly more bacteria at 24 and 48 hpi compared to T = 0 ( Fig 1B ) , which suggests the mutant bacteria are able to replicate . Expression of shvR from its endogenous promoter introduced on a single copy plasmid restored virulence to the ΔshvR mutant ( Fig 1 ) . These results show that ShvR is required for development of acute fatal infection . Our previous work showed that macrophages efficiently phagocytose intravenously injected B . cenocepacia K56-2 , and that they are critical for bacterial replication and ensuing fatal pro-inflammatory infection in zebrafish embryos [29] . Phagocytosis of bacteria from the blood results in infected macrophages distributed over the yolk and the tail region [30] . To analyse the interaction of ΔshvR with macrophages in the host , we quantified the percentage of ΔshvR bacteria that were internalised by macrophages using confocal imaging of infected Tg ( mpeg:mCherry-F ) transgenic embryos , which express a membrane localised mCherry protein ( Fig 2A and S1 Movie ) . One hour after injection , ΔshvR bacteria were as efficiently phagocytosed by macrophages as wildtype bacteria ( Fig 2B ) . Real time experiments showed that the ΔshvR bacteria still localised in macrophages at later time points , where they sometimes reached high numbers ( Fig 2C ) in agreement with the observed increase in CFU counts ( Fig 1B ) . In contrast , at these later time points wildtype K56-2 bacteria have replicated to very high intracellular numbers , formed local infection sites ( Fig 2D ) , re-entered the blood circulation and spread systemically as shown earlier [29] . Quantification of the number of intracellular ΔshvR bacteria in infected macrophages using Tg ( mpeg:mCherry-F ) embryos at 1 hpi and 24 hpi ( Fig 2E ) showed a significant decrease in the number of macrophages containing 1 or 2 bacteria and an increase in the number of macrophages containing more than 4 bacteria , respectively , demonstrating that the ΔshvR mutant is able to survive and replicate inside macrophages . The total number of infected macrophages that were observed per embryo decreased in time from 12 . 3 ± 2 . 1 ( SEM; n = 15 embryos ) at 1 hpi to 7 . 6 ± 0 . 9 ( SEM; n = 10 embryos ) at 24 hpi , suggesting that a proportion of ΔshvR bacteria can establish a replication niche , while others get degraded . In contrast to wildtype K56-2 , which disseminates from initially infected macrophages at around 10–12 hpi culminating in acute fatal infection [29 , 30] , ΔshvR did not spread throughout the embryos . Instead , the infection was characterised by low overall bacterial burden and the absence of tissue inflammation as seen for K56-2 and the complemented mutant ( Fig 3A ) . However , real time observations showed that small infection sites with multiple infected cells sometimes developed from single infected macrophages . Although we have been unable to quantify this event due to the cell dynamics of the in vivo infection with immune cells moving around , and the mechanism behind the local spread is not known , it suggests the ΔshvR mutant can maintain low levels of chronic infection . Together , the results demonstrate that ShvR is not essential for intracellular persistence and replication , but that it regulates factors that are critical for the bacteria to disseminate efficiently and cause robust pro-inflammatory infection . We have shown earlier that acute infection caused by B . cenocepacia K56-2 correlates with systemic phagocyte death , whereas persistent infection , caused by for instance B . stabilis LMG14294 , triggers neutrophilic inflammation [29] . Neutrophil numbers were quantified during infection with wildtype K56-2 , ΔshvR and the complemented mutant at 0 , 24 , 43 , and 72 hpi using Tg ( mpx:eGFP ) transgenic embryos , which express GFP specifically in neutrophils ( S1 Fig and Fig 3B ) . Embryos infected with B . cenocepacia K56-2 showed a strong decline in the number of neutrophils , with only few cells remaining at the end stage of infection ( Fig 3B and [29] ) . In contrast , infection with ΔshvR resulted in neutrophilic inflammation with a significant increase in the number of neutrophils compared to non-infected control embryos from 43 hpi ( Fig 3B ) . The complemented mutant caused neutropenia , as seen for the wildtype strain , confirming restoration of virulence by expression of shvR in trans . B . cenocepacia K56-2 induces a robust increase in host pro-inflammatory cytokine expression ( [29]; Fig 3C and 3D ) . The expression of il1b and cxcl8/il8 upon infection with ΔshvR was , however , only moderately increased compared to PBS-injected embryos ( Fig 3C and 3D ) , as shown earlier for B . stabilis [29] . Moreover , at 24 hpi , no significant difference in gene expression was observed between embryos injected with PBS or ΔshvR . These results confirm that ShvR is required for the induction of robust pro-inflammatory responses . Based on the requirement for macrophages for intracellular bacterial replication of K56-2 and subsequent pro-inflammatory fatal infection [29] , and the restriction of the ΔshvR mutant to macrophages , we hypothesised that ShvR could be an important switch between intracellular persistence and acute pro-inflammatory infection . To address this hypothesis , we used a rhamnose inducible expression system [31] to temporally control the induction of shvR expression in the ΔshvR mutant during infection in zebrafish embryos . This allowed us to study the effect of experimental induction of shvR gene expression during intramacrophage stages of B . cenocepacia on disease outcome . The shvR coding sequence was cloned under control of the rhamnose-inducible promoter PrhaB , resulting in PrhaB:shvR and introduced in ΔshvR . The PrhaB- control plasmid , lacking the shvR coding sequence , served as a negative control . Zebrafish embryos were injected at 30 hours post fertilisation ( hpf ) with ΔshvR ( PrhaB- ) and ΔshvR ( PrhaB:shvR ) . At 24 h post injection of bacteria , at the time ΔshvR resided in macrophages ( Fig 2 ) , a 2% rhamnose solution , or PBS as a control , was injected into the circulation of the infected embryos ( see Fig 4A for schematic representation ) . In order to maintain shvR expression , the embryos were further incubated in E3 medium with 2% rhamnose . The presence of PrhaB- in ΔshvR had no effect on embryo survival or bacterial burden , even after injection of rhamnose ( Fig 4B and 4C ) . Strikingly , application of rhamnose , but not PBS , restored virulence to ΔshvR harbouring PrhaB:shvR , measured as host mortality and increase in bacterial burden ( Fig 4B and 4C ) . These results confirm a critical role for ShvR in acute infection . To visualise the effect of temporal induction of shvR expression on intracellular B . cenocepacia , fluorescence microscopy was performed using Tg ( mpx:eGFP ) transgenic embryos infected with ΔshvR ( PrhaB:shvR ) expressing mCherry . While injection with PBS in embryos infected prior with ΔshvR ( PrhaB:shvR ) did not alter the infection progression of the ΔshvR mutant , injection of rhamnose resulted in changes that are characteristic of acute infection ( Fig 5A ) . These changes include neutrophil recruitment towards infection sites , indicative of increased pro-inflammatory signalling , and as described for acute infection with B . cenocepacia K56-2 [29] . The infection rapidly worsened and at 24 h post rhamnose injection the embryos were neutropenic ( Fig 5A ) , as seen for infection with wildtype ( Fig 3A ) . The 2-log increase in bacterial burden within 48 hours post rhamnose injection ( Fig 4C ) was in agreement with real time observations using fluorescence microscopy and time lapse confocal imaging ( Fig 5A and S2 Movie ) . At later time points after rhamnose injection , tissue damage as a sign of strong pro-inflammatory responses could be observed ( Fig 5A ) . Next , we analysed whether global cytokine gene expression levels were induced after restoration of shvR expression in ΔshvR ( PrhaB:shvR ) bacteria . While no difference in relative expression levels was observed between rhamnose and PBS conditions in embryos infected with ΔshvR ( PrhaB- ) , a significant increase in the expression of cxcl8 and il1b was observed in embryos infected with ΔshvR ( PrhaB:shvR ) after injection with rhamnose ( Fig 5B and 5C ) . Thus , ShvR strongly controls the expression of genes that are required for the transition from intracellular persistence to acute pro-inflammatory infection . ShvR has been described as a global regulator of virulence factors in B . cenocepacia , moderately ( 2 to 4 fold ) changing the expression of a large set of genes . The antifungal activity cluster afc , comprising 24 genes organised in two divergently expressed operons localised adjacent to shvR , has been described to show strongly decreased expression levels ( 100 fold ) in the absence of shvR , demonstrating afc expression is under tight positive control of ShvR [25] . In addition , mutation of afcE mimics the phenotypes found for ΔshvR , including shiny colony morphology , altered membrane properties , and reduced virulence in a rat infection model [25 , 27 , 28] , suggesting the afc cluster is a major target of ShvR . In analogy to the experiments described above for ΔshvR , we therefore analysed a role for AfcE in persistent/acute transition . Infection experiments showed that ΔafcE ( DSRedpBBR ) was severely attenuated in virulence in zebrafish embryos ( Fig 6A and 6B ) . In agreement with the inability of the mutant to cause fatal infection , ΔafcE showed significantly lower bacterial burden compared to K56-2 at 24 hpi , similar to that observed for ΔshvR ( Fig 1 ) . Expression of afcE in trans ( ΔafcE ( Plac:afcE;DSRedpBBR ) complemented virulence to the ΔafcE mutant ( Fig 6A and 6B ) . ΔafcE was taken up by macrophages as efficiently as the wildtype and ΔshvR mutant from the blood circulation ( Fig 2B and S2A Fig ) . After phagocytosis by macrophages , ΔafcE bacteria were observed in macrophages also at later time points , sometimes , like ΔshvR , at high numbers ( Fig 6C ) . Quantification of intracellular ΔafcE bacteria at 1 hpi and 24 hpi ( S2B Fig ) confirmed that the ΔafcE mutant is able to survive and replicate inside macrophages , as shown for ΔshvR ( Fig 2E ) . Using non-invasive real time imaging , we observed that the ΔafcE mutant bacteria did not cause neutropenia nor disseminated infection , while expression of the afcE gene restored these wildtype features ( Fig 6D ) . Further , analysis of the global pro-inflammatory response of the host showed that the expression of the cytokine genes cxcl8 and il1b is induced to lower levels during infection with ΔafcE compared to wildtype K56-2 ( Fig 6E and 6F ) , similar to that shown for ΔshvR ( Fig 3C and 3D ) . These results clearly demonstrate that AfcE is required for acute , disseminated pro-inflammatory infection . Experiments using rhamnose-mediated induction of afcE during intramacrophage stages , as shown for shvR ( Fig 4 ) , were performed . Whereas infection with ΔafcE ( PrhaB- ) after injection of rhamnose or PBS at 24 hpi remained persistent , embryos infected with ΔafcE ( PrhaB:afcE ) and injected with rhamnose succumbed to the infection ( Fig 7A ) , which correlated with an increase in bacterial CFU at 72 hpi ( Fig 7B ) . Not all embryos showed increased bacterial numbers , however , and further experiments are needed to determine the reasons for the apparently larger biological variation in this assay for the ΔafcE mutant compared to the ΔshvR mutant ( Fig 4C ) . In addition , global cytokine expression of embryos infected with ΔafcE ( PrhaB:afcE ) was significantly induced at 24 h post injection of rhamnose , but not PBS ( Fig 7C and 7D ) . Together , these results demonstrate that AfcE is essential for bacterial dissemination and the robust pro-inflammatory fatal response seen for B . cenocepacia K56-2 , in agreement with afc being the direct target of ShvR required for acute infection caused by B . cenocepacia K56-2 . To better understand a role for ShvR/Afc in virulence within the Bcc , we performed bio-informatics analysis . The Burkholderia cepacia complex has seen a rapid increase in the number of bacterial species it contains due to improved characterization and reclassification [32] . The current methods for discrimination between species are based on recA gene sequences , multilocus sequencing and whole genome studies ( reviewed in [33] ) . At present , the complex includes 21 formally named species [1 , 2] . For the construction of a phylogenetic tree , representative genomes of each species were included ( in some cases more than one strain ) with either a complete genome and annotation status or whole genome sequence ( WGS , see S2 Table ) . A phylogenetic inference tree of these species was constructed using the nucleotide sequences of the Multilocus Sequence Typing ( MLST ) housekeeping genes ( atpD , gyrB , gltB , lepA , recA , phaC and trpD ) [34] . Fig 8 shows a maximum-likelihood phylogeny generated from concatenation of these 7 genes . B . pseudomallei K96243 , B . thailandensis E264 and Ralstonia pickettii 12J were used as out-groups . To better understand the evolution of the LTTR regulator ShvR within the complex , BLAST-analysis was performed to identify orthologs of the gene BCAS0225 from B . cenocepacia J2315 . A gene with high similarity to BCAS0225 ( identity >85% ) was identified in a subclade containing strains from 10 out of the 20 species for which complete genome sequences are available ( B . arboris has not been sequenced ) . In all cases , the gene was located on the megaplasmid pC3 . Similarly , orthologs were identified for afcE ( BCAS0208 ) . Fig 8 shows that the presence/absence of shvR within the Bcc complex matches that of afcE . Further investigation of the adjacent afc cluster showed that the 24 afc genes and their organization , including the presence and location of the shvR gene are well-conserved among shvR-containing Bcc species ( S3 Fig ) . In addition to the 19 analysed Bcc strains ( covering 10 species ) that carry the shvR-afc cluster , B . pseudomallei and B . mallei have a subset of the afc genes , including afcE . The operon in B . pseudomallei , located on chromosome 1 , shares similarity to 15 of the 22 genes in the Bcc afc cluster and is likely regulated by an LTTR regulator unrelated to ShvR , encoded by an ORF adjacent to the cluster ( BPSL0494 , S3 Fig ) . This regulator shares amino acid similarities with only the DNA binding domain of the ShvR protein ( 27% amino acid identity ) . BPSL0494 shares 77% nucleotide identity with BCAS0283 , another LTTR identified in B . cenocepacia J2315 encoded on pC3 , with homology mainly in the 5’ 200 bp and the 3’ 150 bp . A maximum-likelihood phylogeny of afcE ( S4 Fig ) confirmed that the acyl-CoA dehydrogenase from B . pseudomallei is the most distant in the Burkholderia group , although they share 80% of nucleotide similarity . Analysis of the region upstream of the shvR coding sequence amongst the shvR-positive strains of the Bcc complex showed nucleotide variations ( SNPs , indels ) , not only between species but also between strains belonging to the same species ( S5 Fig ) . As expected , strains belonging to the same species contain fewer variations , compared to , for example , those observed between the B . cenocepacia and B . lata strains . Within the B . cenocepacia species , the recA lineage IIIA and IIIB ( Fig 8 ) each appear to have their own consensus sequence for the shvR upstream region . Interestingly , a 2-nucleotide gap , at position -238 from the translation start site ( S5 Fig ) , followed by a short highly non-homologous region compared to the conserved sequence found in the other cluster , is observed in the strains of B . cepacia , B . pyrrocinia , B . stabilis , B . lata , B . contaminans , B . metallica and B . vietnamiensis . This is in agreement with the phylogenetic relationship shown in Fig 8 , and suggests that this deletion and the following non-homologous region occurred before speciation . B . cenocepacia , B . cepacia and B . contaminans , Bcc species which are generally correlated with more severe disease in humans , all carry genes encoding ShvR and Afc proteins . Several B . cenocepacia strains , including the epidemic CF isolates K56-2 and J2315 , are highly virulent in different model systems , including zebrafish [29] . However , B . cenocepacia H111 , which is very closely related to K56-2 , was shown to be less virulent in G . mellonella and rats [35 , 36] . In zebrafish , we previously described that this strain can show substantial variation between experiments [37] , with mortality rates between 20 and 60% at 4 days post fertilisation ( dpf ) , but always less virulent than K56-2 ( Fig 9 ) . We also found that H111 does not show afc-dependent antifungal activity as seen for K56-2 [37] . Comparison of the shvR coding sequences showed 3 silent SNPs between H111 and our K56-2 strain . Of note , the sequenced K56-2Valvano strain has a 4th SNP giving rise to a variant Tyr78 to Cys78 . We set out to analyse whether differences in shvR expression could account for the differences in virulence observed between K56-2 and H111 , and thus confirm the role of shvR/afc in virulence of B . cenocepacia . To be able to study the role of shvR and afc in virulence of H111 in the absence of upstream regulatory signals , we cloned the shvR gene of H111 under control of the lac-promoter on pBBR1MCS and constructed an H111 mutant lacking the complete afc cluster . K56-2 , H111 and H111Δafc were transformed with Plac-shvRpBBR or the pBBR1MCS control plasmid . Expression of shvR from the lac promoter led to a change in colony morphotype of H111 from shiny to rough , in a manner that depended on afc ( S6 Fig ) . This suggests that the endogenous shvR gene is not expressed in H111 on agar plates , but that expression of shvR in trans induces the expression of a functional AFC lipoprotein . H111 caused fatal disease in on average 40% of injected embryos over a 4-day time period , compared to 100% mortality in 2 to 3 days for K56-2 ( Fig 9 ) . Zebrafish embryos injected with the H111Δafc mutant survived and remained without any clinical signs of infection during the experimental time , in agreement with the experiments performed with K56-2ΔafcE ( Fig 6B ) . The finding that afc is essential for acute fatal infection also in H111 suggests that shvR and afc expression is induced in wildtype H111 upon injection in zebrafish larvae , but probably does not reach the level of that in K56-2 . Strikingly , overexpression of shvR from the lac promoter increased virulence in H111 , but not the H111Δafc mutant , almost to that seen with B . cenocepacia K56-2 ( Fig 9 ) . These data validate the results obtained with K56-2 that shvR/afc are critically important for acute virulence in zebrafish larvae . They also unambiguously demonstrate that shvR/afc are functional in H111 , and suggest that differences in inducing signals or upstream elements render H111 less virulent in zebrafish compared to K56-2 .
The LysR-type transcriptional regulator ShvR has been shown to tightly control the expression of an adjacent operon , called afc , involved in antifungal activity [25] . The zebrafish embryo model , in which persistent and acute infection caused by different Bcc strains can be studied in detail in the context of an innate immune response [29 , 30] was exploited to gain better insight into a role for ShvR and AfcE in virulence of B . cenocepacia K56-2 . We found that while shvR and afcE are not required for bacterial persistence in the host , they are both essential for the induction of a robust fatal pro-inflammatory infection . Our study shows that ShvR and AfcE are key elements in the transition from an intracellular bacterial stage to disseminated pro-inflammatory infection in zebrafish larvae . A previous microarray study has shown that the expression of the afc cluster is under tight positive regulatory control of ShvR [25] . The afc cluster consists of 24 genes arranged in two divergently expressed operons that specify the synthesis of a lipopeptide located in the membrane of the bacterial cells , previously identified as AFC BC11 [26] . The role of several genes in the afc cluster has been analysed in more detail . While afcA , afcB , afcC , afcD , afcE and afcF have been shown to be important for antifungal activity against Fusarium solani , BCAS0204 ( ABC transporter ) and BCAS0207 ( citrate synthase ) are dispensable [26 , 27] . In addition , AfcE and AfcF , the latter being a putative FAD-dependent oxidoreductase , but not BCAS0204 and BCAS0207 were involved in virulence in alfalfa seedlings . Previous studies have further shown that ΔafcE and ΔafcF mutants have altered membrane lipid profiles , although additional membrane properties , including membrane permeability and membrane morphology , were affected only in the ΔafcE mutant [27] . Additionally , B . cenocepacia lacking afcE produces less biofilms and displays a shiny colony morphology [27] , similar to the phenotypes observed for ΔshvR . The similarity in observed phenotypes between the ΔshvR and ΔafcE mutants suggests that the afc operon is an important regulatory target of ShvR , with a significant role for the afcE gene product . Recently , we showed the essential role of macrophages in the establishment of a replicative niche for B . cenocepacia K56-2 and in the development of a robust pro-inflammatory response that becomes rapidly fatal for zebrafish larvae [29] . In contrast , infection with the ΔshvR and ΔafcE mutants was not fatal and led to only minimal induction of inflammatory responses ( Figs 3 and 6 ) . Importantly , after phagocytosis by macrophages , the ΔshvR and ΔafcE mutants did not disseminate and total bacterial burden only slightly increased over time , in contrast to the dissemination and rapid increase in bacterial numbers seen for the wildtype [30] . However , the absence of shvR and afcE did not prevent the bacteria from replicating intracellularly ( Fig 2 and S2 Fig ) . These data show that shvR and afcE , although not required for persistence and replication in macrophages , are critical for the development of fatal pro-inflammatory disease . This is in agreement with results obtained in a chronic lung infection model in rats , where ΔshvR and ΔafcE mutants showed significant reduction in lung inflammation , while bacteria persisted in the lungs , sometimes replicating to higher numbers than the wildtype [24 , 28] . We are now investigating in more detail the virulence profile of mutants in other genes of the afc operon , and whether general changes in membrane properties or a dysfunctional AFC lipopeptide itself , caused by the absence of AfcE , are responsible for the observed lack in mounting a robust pro-inflammatory response by B . cenocepacia K56-2 . To test our hypothesis that ShvR and AfcE have an important role in the transition from intracellular persistence to acute infection we used a rhamnose-inducible expression system [31] . Our data show that the temporal induction of shvR and afcE expression in intracellular ΔshvR and ΔafcE bacteria , respectively , restored properties that are essential for bacterial dissemination and induction of pro-inflammatory responses . Rhamnose-mediated activation of shvR and afcE resulted in neutrophil recruitment and increased global expression of cxcl8 and il1b in the embryos ( Figs 5 and 7 ) . The infection rapidly worsened and became fatal for the zebrafish embryos ( Figs 4B and 7A ) , confirming our hypothesis that ShvR and AfcE are essential for persistent to acute transition in this model . Bacteria belonging to the Burkholderia cepacia complex ( Bcc ) are life threatening opportunistic pathogens of cystic fibrosis patients and immunocompromised people . One of the major concerns in CF infections is the recurrent acute exacerbations during infection that severely deteriorate the health of the patients with often fatal consequences . The underlying signals and mechanisms that regulate pathogenesis and lead to chronic-acute transitions are not known . Studies on transcriptional regulators of Pseudomonas aeruginosa , including AmpR and RetS/LadS/GacS , have shown that these are involved in regulating the switch between acute to chronic infection [19 , 38–42] . Our study describes for the first time a regulator that is absolutely required for B . cenocepacia to change a persistent intracellular lifestyle to acute pro-inflammatory infection . The data strongly suggest that the downstream regulated target of ShvR that is responsible for the acute infection is the afc gene cluster , with a major role for afcE . Our bioinformatics analysis shows that shvR and the afc cluster are present in the genomes of 10 of the 20 Bcc species of which the whole genome sequence has been published ( Fig 8 ) . It is interesting that the shvR/afc cluster is present in most of the more virulent species in the complex including B . cenocepacia , B . cepacia and B . contaminans , while B . stabilis LMG14294 for example , which causes persistent infection in the zebrafish model [30] and is reduced virulent in a rat model [43] , lacks shvR/afc . In contrast to differences in the flanking gene sequences between strains , shvR and afc have evolved as one unit with a highly conserved gene structure over time ( S3 Fig ) , suggesting an important evolutionary advantage of ShvR-dependent production of the AFC lipopeptide . Interestingly , the important human pathogens B . pseudomallei , the causative agent of melioidosis or Whitmore disease , and B . mallei , causing glanders , encode a subset of the afc genes . Although an afcE homolog is present , the LTTR encoded adjacent to the afc cluster is not an ortholog of shvR . The presence of the afc cluster also in the B . pseudomallei cluster suggests an ancestral origin that has adapted through divergent evolution in the B . pseudomallei and Bcc clusters , with loss of the cluster several times during speciation of the Bcc . Although less likely , the shvR/afc cluster may have been acquired independently during evolution in the Bcc and the B . pseudomallei cluster . It would be interesting to know whether afcE has a similar role in virulence in B . pseudomallei and B . mallei . O’Grady and colleagues have demonstrated that shvR is continuously expressed during growth of B . cenocepacia K56-2 in LB , with a peak in expression between 8 and 18 h [25] , however the signals that may either inhibit or induce its expression , including those during infection of humans and in the natural environment , are not known . Acidic pH , low aeration and/or growth on a surface to stationary phase have been suggested to be important conditions for maximal AFC production in B . pyrrocinia BC11 [26] . B . cenocepacia K56-2 of the ET12-lineage is one of the most virulent Bcc strains in different animal models and the constitutive and high expression profile of shvR in this strain under different conditions may represent a key factor for the acute and disseminated character of infection by this and other isolates of the epidemic ET12 lineage . Interestingly , for B . cenocepacia H111 it was recently shown that the afc cluster was not involved in the antifungal activity observed from this strain , due to lack of expression [37 , 44] . In addition , although H111 is more virulent than K56-2 in the C . elegans infection model since it has the nematocidal protein AidA [45] , virulence of H111 in G . mellonella [37] and zebrafish ( Fig 9 ) is reduced compared to that of K56-2 . Nonetheless , H111 is more virulent than strains including B . stabilis and B . vietnamiensis , which cause persistent infection in zebrafish [29] , and can still cause fatal infection in a manner that is totally dependent on afc . This suggests that shvR-inducing signals must be present during infection in zebrafish and G . mellonella , but that expression levels are sub-optimal compared to K56-2 , since overexpression of shvR from the lac promoter increases virulence to H111 to almost K56-2 levels . Our results with H111 validate that regulation and expression of ShvR play a major role in the afc-dependent acute virulence of B . cenocepacia . These results are also consistent with the observations that the CF patient from which H111 was isolated did not show acute symptoms and the infection was cleared after 6 months without changing the therapy regime [46] . Overall , differences in shvR/afc gene regulation , or perception and type of environmental cues , may contribute to differences in antifungal activity and/or virulence . A better understanding of these factors may reveal how Bcc bacteria rapidly adapt to different environmental conditions and may provide new insights into the virulence potential of B . cenocepacia strains in humans . This study emphasizes that properties which are important for the bacteria to thrive in the environment , may be important virulence factors in opportunistic infections . The role of lipids and lipoproteins in virulence , for instance through adherence to host cells and modulation of inflammatory processes has been recognised for many years , making for potential vaccines . New treatment strategies may be designed by improving our understanding of how Burkholderia cenocepacia resists clearance from macrophages and adapts for persistence , or , is able to cause acute disease in interaction with macrophages . We are currently studying the cellular mechanism of AFC-dependent induction of pro-inflammatory responses , and propose ShvR/AFC as a novel target to reduce pro-inflammatory responses during Bcc infection .
Zebrafish ( Danio rerio ) were kept and handled in compliance with the guidelines of the European Union for handling laboratory animals ( http://ec . europa . eu/environment/chemicals/lab_animals/home_en . htm ) . Zebrafish studies performed at VBMI are approved by the Direction Départementale de la Protection des Populations ( DDPP ) du Gard ( ID 30-189-4 ) and the Comité d'Ethique pour l'Expérimentation Animale Languedoc-Roussillon ( CEEA-LR-12186 ) . Infection experiments in this study were terminated before the larvae reached the free feeding stage and did not classify as animal experiments according to the 2010/63/EU Directive . The zebrafish line AB was used as wildtype ( WT ) , and the transgenic reporter lines Tg ( mpx:eGFP ) i114 [47] and Tg ( mpeg1:mCherry-F ) ump2Tg [48] were used to analyse host phagocyte behaviour . Care and maintenance of zebrafish was as described previously [29] . Eggs were obtained by natural spawning and incubated at 29°C in Petri dishes containing E3 medium ( 5mM NaCl , 0 . 17mM KCl , 0 . 33mM CaCl2 , 0 . 33 mM MgSO4 ) as described [49] . Methylene blue was omitted . The bacterial strains , plasmids and primers used in this study are listed in S1 Table . Strains were grown at 37°C in Lysogeny Broth ( LB ) , supplemented with ampicillin at 100 μg/mL for Escherichia coli , chloramphenicol at 30 μg/mL and 100 μg/mL for E . coli and Burkholderia cenocepacia respectively , tetracycline at 250 μg/mL ( B . cenocepacia ) and trimethoprim at 50 μg/mL ( B . cenocepacia ) . No differences in growth were observed between B . cenocepacia K56-2 and the ΔshvR and ΔafcE mutants when grown in LB medium . For the construction of pIN233 , the mCherry coding region from plasmid pSAT1:mCherry-MCS-nVenus ( pE3370 ) was amplified using primers mCherry-3 and mCherry-4 . The PCR fragment was digested with XbaI and NdeI and cloned into pIN29 [30] , replacing the DSRed coding sequence . Plasmid pIN298 resulted from cloning the mCherry coding sequence from pIN233 into pCR11 ( a gift from M . Kovach ) , a CmR derivative of the single copy plasmid pMR10 ( GenBank: AJ606312 . 1 ) , using HindIII and XbaI restriction sites . A ~1 . 6 kb fragment containing full length shvR and upstream region PshvR ( primers pshvRXhoI for and shvRXbaI rev ) , a 995 bp fragment containing the shvR coding region ( primers shvRNdeI for and shvRXbaI rev ) and a ~1 . 8 kb fragment containing the afcE coding region ( primers 0208_NdeI for and 0208_XbaI rev ) were separately amplified from K56-2 genomic DNA by PCR using Pfu polymerase ( Life technologies , USA ) . The fragments were first subcloned in pUC29 and verified by sequencing ( MWG Operon Eurofins , Germany ) . To construct pIN308 , the PCR product of PshvR:shvR was cloned into pIN29 as a XhoI/HindIII fragment , and named pIN307 . From this plasmid , the PshvR:shvR fragment was cloned into pIN298 using the SpeI and BamHI restriction enzymes ( XhoI and XbaI ) . The rhamnose inducible system from pSCPrhaB2 [31] , containing the rhamnose-regulated PrhaB promoter and the genes rhaR and rhaS of the rhamnose operon , was cloned into pIN177 using XbaI and PstI restriction sites , and named pIN299 ( or PrhaB- , serving as negative control in rhamnose induction experiments , for simplicity ) . pIN177 is a derivative of pBBR1MCS plasmid lacking the oriT/mob region and containing a strong trp termination signal ( pIN32; [30] ) , a tac promoter sequence ( PstI/NdeI fragment from pIN17; [30] ) and an additional NdeI/XbaI linker ( catatgaagctttcgcgagctcgagatctaga ) . To create PrhaB:shvR ( pIN310 ) , allowing rhamnose-inducible expression of shvR , the shvR coding sequence was cloned downstream the PrhaB promoter sequence as follows: the 995 bp shvR PCR fragment ( primers shvRNdeI for and shvRXbaI rev ) was cloned into XbaI/NdeI-digested pIN299 , and named pIN309 . A Ptac:mCherry fragment from pIN233 , cloned in pUC29 as a SpeI/NotI fragment , was then inserted in the KpnI site of pIN309 , resulting in pIN310 . Plasmid pIN311 ( PrhaB:afcE ) was constructed by digesting pIN299 with NdeI/XbaI restriction sites and inserting the afcE fragment amplified using the primers 0208_NdeI for and 0208_XbaI rev . The afcE complementation plasmid pINR139 was generated by cloning a Ptac:DSRed fragment from pIN29 as a SpeI/SacI fragment into pBBRS0208 . Plasmids were transferred into B . cenocepacia K56-2 , ΔshvR and ΔafcE mutants by electroporation as described earlier [30] . The plasmid Plac-shvRpBBR carries the coding sequence of shvR amplified from B . cenocepacia H111 , using primers shvRHindFor and shvRBamRev . The restriction sites BamHI and HindIII were used to clone the fragment in pBBR1MCS . Deletion of the afc cluster was carried out using vectors pSHAFT2-FRT and pEX18Tp-FRT , as described in [37] . A fragment adjacent to the region to be deleted ( UP ) was amplified from B . cenocepacia H111 with primers upXhoF and upBglIIR ( ~1 . 3 kb ) , and digested with XhoI and BglII . The fragment was then inserted in pSHAFT2-FRT using the same sites , resulting in pSHAFT2-FRT-afcUP . This plasmid was inserted into the genome of B . cenocepacia H111 by single crossover recombination . Correct integration was confirmed with primer pairs AFCdelUPcheckF ( GATCATCTTCTTCTCGCTCG ) and pSHAFTseqR4 ( GAACACTTAACGGCTGACAT , ~1 . 5 kb ) and pSHAFT2For3 ( GATTATTTTGCCCCGGTTTT ) and AFCdelUPcheckR ( GGAGATTTCGCATGATGTTT , 2 kb ) . A fragment bordering the afc cluster on the other side ( DOWN ) was amplified from B . cenocepacia H111 using primers downpstF and downBamR . The resultant ~1 . 3 kb fragment was digested with PstI and BamHI and inserted between these sites in pEX18Tp-FRT . This vector ( pEX18Tp-FRT-afcDOWN ) was inserted into the genome of B . cenocepacia H111 bearing the previously integrated pSHAFT2-FRT derivative by single crossover recombination . Correct integration was confirmed with primer pairs AFCdelDOWNcheckF ( GAATTGAACCGCTATCGCC ) and M13R ( ~1 . 4 kb ) and M13F and AFCdelDOWNcheckR ( GCACAGGTTGCAGGTATT , 1 . 7 kb ) . Plasmid pBBR5::FLP [50] was then introduced by conjugation , to stimulate recombination between the FRT sites integrated into the genome . Flippase-mediated recombination was carried out at 30°C , and colonies were selected using the marker present on the pBBR5::FLP derivative . Colonies were then checked for loss of the markers present on the pSHAFT-2FRT and pEX18Tp-FRT derivatives ( chloramphenicol and trimethoprim , respectively ) . Finally , deletion was confirmed by amplifying across the ends of the deleted region with primers AFCDELcheckFor and AFCDELcheckRev . Successful deletants gave rise to a band of ~700 bp . Microinjection of zebrafish embryos was performed as previously described [49] . Briefly , B . cenocepacia strains were grown overnight in LB broth with appropriate antibiotics at 37°C . Bacterial dilutions to obtain the desired inoculum concentration were prepared in PBS ( with 0 . 05% phenol red to visualize microinjection ) . Embryos were dechorionated 2 hours prior to microinjection and at 30 hours post fertilization ( hpf ) they were injected in the blood island . For microinjection , embryos were placed on agarose plates containing E3 medium with 0 . 02% buffered MS222 ( tricaine; ethyl-3-aminobenzoate methanesulfonate salt ) . Injection was performed with a Femtojet microinjector ( Eppendorf ) and a micromanipulator with pulled microcapillary pipettes , under a stereo light microscope ( Leica MS5 ) . The pool of infected embryos was then randomized over CFU plating and survival assays . Embryos were maintained individually in 48-well plates in E3 medium at 29°C . In order to specifically induce the expression of shvR and afcE in ΔshvR and ΔafcE mutants , respectively , at 24 h after injection of the bacterial inoculum , rhamnose ( 2% in PBS ) was injected directly in the blood circulation . As a negative control , half of the embryos of each group were injected with PBS . The embryos were then kept in E3+2% rhamnose or in E3 medium , respectively . Immediately after bacterial injection ( T = 0 hpi ) , 5 embryos per strain were disrupted and plated on LB agar with the appropriate antibiotics to determine the precise inoculum size . At 24 , 48 and 72 hpi ( in the rhamnose assays ) , 10 μl of each serial dilution was deposited on a squared LB-agar plate for determination of CFU . Embryo survival was determined at regular time points , starting at 42 or 44 hpi and every two hours during periods with high mortality rates . Time of death was based on the absence of a heartbeat . RNA extraction , cDNA synthesis and qPCR analysis of zebrafish genes were performed as described [49] . The peptidylprolyl isomerase A-like ( ppial ) gene was used as a reference gene . The ΔΔCt method was used for analysis of the data , represented as column bar graphs normalized to a PBS-injected control group at each time point . Three biological replicates were performed ( unless mentioned otherwise ) , each with two technical replicates . So far we have been unable to optimise qPCR of bacterial genes from infected zebrafish larvae , due to the high ratio of host to bacterial RNA . Embryos were imaged using a Leica DM IRB inverted microscope coupled with a Coolsnap fx black and white camera ( Roper Scientific ) as described [49] , or a Nikon AZ100 , coupled with Coolsnap HQ2 ( Roper Scientifique ) . MetaVue software was used for imaging . Adobe Photoshop was used to colour black and white images , prepare overlay images taken with different channels , include scale bars , and crop images for the purpose of showing enlargements/insets . For analysis of phagocytosis and quantification of intracellular ΔshvR bacteria ( sample image Fig 2A ) , the embryos were fixed in 4% PFA for 2 hours at RT , or overnight in 3% PFA at 4°C and analysed using an Olympus confocal laser scanning microscope Fv10i and Fluoview software . Quantification of neutrophil cell numbers was performed according to [51] . In brief , images taken with identical camera settings ( S1A Fig ) were converted to binary in ImageJ 1 . 47v , resulting in images in which fluorescence was converted into black pixels onto a white background ( S1 Fig ) . Five randomly selected individual cells per image ( embryo ) were taken to determine pixel size per phagocyte , as described [51] . Total pixel counts were then divided by the average of the 5 individual cells to determine the total number of fluorescent cells . A maximum likelihood phylogeny was created from 43 Burkholderia cepacia complex strains and 3 outgroup species ( B . pseudomallei K96243 , B . thalandensis E264 and Ralstonia pickettii 12J , in S2 Table ) . The tree is based on the concatenated alignment of fragments of nucleotide sequences of the Multilocus Sequence Typing ( MLST ) gene set , atpD , gyrB , gltB , lepA , phaC , recA and trpB [34] . For strains with MLST ID indicated in S2 Table , the sequences were retrieved from PubMLST database ( pubmlst . org/bcc ) , for the others the coding sequence of the genes were obtained from BLAST searches in NCBI [52] , PATRIC ( patricbrc . org , [53] ) or the Burkholderia Genome Database ( burkholderia . com , [54] ) . For those cases , the sequences were shortened upon the alignment . The sequences of each gene were first aligned in MEGA6 . 06 [55] using ClustalW [56 , 57] and then all gene sequences were concatenated using the program SequenceMatrix [58] . The concatenated genes sequences were then introduced in MEGA6 . 06 to construct a maximum likelihood tree . The General Time Reversible ( GTR ) model [59] was used to determine nucleotide distances , with gamma distribution ( 5 rate categories and 49% invariable sites ) , assuming partial deletions in the missing data and a cut-off of 95% . The maximum likelihood heuristic method used was the Nearest-Neighbour-Interchange ( NNI ) . A bootstrap of 1000 replicates was used . A BLAST analysis of the promoter region of shvR ( 500bp ) from B . cenocepacia J2315 ( BCAS0225 ) was performed using PATRIC against a genome database with the Burkholderia strains summarised in S2 Table ( except for B . arboris LMG 14939 ) . The sequences of each of the identified genes were obtained ( either from PATRIC , NCBI or Burkholderia Genome Database ) and aligned in MEGA6 . 06 [55] using ClustalW [56 , 57] . A maximum likelihood phylogenetic tree for the afcE gene was created in MEGA6 . 06 using the same parameters as described above for the Burkholderia species tree , except that the model used was Tamura 3-parameters model ( T92 ) , with gamma distribution ( 5 rate categories ) , and were considered 40% invariable sites . To analyse the similarities of the afc clusters of Burkholderia species , the pC3 genomic sequences ( or contigs ) of the 43 sequenced Bcc strains ( except for B . arboris LMG 14939 ) and B . pseudomallei K96243 , summarized in S2 Table , were retrieved from NCBI . Sequence alignments were performed with MAUVE using default parameters ( default seed weight set to 15; set for determination of Local Collinear Blocks ( LCB ) ; full alignment ( default minimum LCB weight ) ; set for iterative refinement; set for sum-of-pairs LCB scoring ) [60] . For statistical analysis GraphPad Prism 6 . 0 software was used . The average inoculum is calculated as the average CFU of 5 embryos T = 0 values ± SD , and indicated in the legend to the respective graphs . CFU counts from individual larvae at later time points were log10 transformed and the significance between the multiple selected groups was determined using one-way ANOVA with Sidak’s Multiple Comparisons test . To include larvae in which no CFU were detected at 24 or 48 hpi , the 0 count was converted to 1 , prior to log-transformation . Since the geometric mean cannot be calculated for groups that contain log10 values of 0 , we have set this value at 0 . 0001 to be able to calculate the geometric mean . No difference in significance was found when using the 0 or 0 . 0001 log value . In survival assays statistical analysis was done using a Log rank ( Mantel-Cox ) test . For statistical analysis of macrophage and neutrophil cell counts and intracellular bacterial numbers , one-way ANOVA with Sidak’s Multiple Comparisons test , unpaired t-test , and Mann-Whitney were used as indicated in the legends to each graph . The data from qRT-PCR of cytokine genes were log2-transformed , and significance of the data was analysed using one-way ANOVA with Tukey’s Multiple Comparison Test . Columns indicate mean fold with SEM . For each treatment , normalized to the corresponding PBS control , significance in relative fold-change is indicated with an asterisk above the column , significance between treatments is indicated with a connective line between the bars . In rhamnose assays , rhamnose-induction and PBS treatments in both conditions ( control plasmid and gene expressing plasmid ) were normalized to the non-infected PBS control . Significance is indicated as: ns , non-significant , * , p ≤ 0 . 05; ** , p ≤ 0 . 01; *** , p ≤ 0 . 001; **** , p ≤ 0 . 0001 .
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Burkholderia cenocepacia is a bacterial pathogen that can infect cystic fibrosis patients , causing a chronic infection that can suddenly change to often fatal inflammatory necrotic pneumonia called cepacia syndrome . The transcriptional regulator ShvR controls the expression of a lipoprotein with antifungal properties ( AFC ) . Using zebrafish larvae , we earlier found that macrophages provided an important replication niche for these bacteria , and were required for the strong pro-inflammatory response . Here , we contribute new data that show that ShvR and AfcE are absolutely required for the induction of pro-inflammatory disease by B . cenocepacia . In the absence of ShvR and AfcE B . cenocepacia is restricted to macrophages . Using a sugar-dependent expression system that allowed us to turn on shvR or afcE expression in bacteria that lack shvR or afc , respectively , we were able to mimic the transition from a restricted intracellular stage to acute disseminated infection . This result supports an important role for ShvR/AFC in the acute virulence of B . cenocepacia .
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2018
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The afc antifungal activity cluster, which is under tight regulatory control of ShvR, is essential for transition from intracellular persistence of Burkholderia cenocepacia to acute pro-inflammatory infection
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Safeguarding the proteome is central to the health of the cell . In multi-cellular organisms , the composition of the proteome , and by extension , protein-folding requirements , varies between cells . In agreement , chaperone network composition differs between tissues . Here , we ask how chaperone expression is regulated in a cell type-specific manner and whether cellular differentiation affects chaperone expression . Our bioinformatics analyses show that the myogenic transcription factor HLH-1 ( MyoD ) can bind to the promoters of chaperone genes expressed or required for the folding of muscle proteins . To test this experimentally , we employed HLH-1 myogenic potential to genetically modulate cellular differentiation of Caenorhabditis elegans embryonic cells by ectopically expressing HLH-1 in all cells of the embryo and monitoring chaperone expression . We found that HLH-1-dependent myogenic conversion specifically induced the expression of putative HLH-1-regulated chaperones in differentiating muscle cells . Moreover , disrupting the putative HLH-1-binding sites on ubiquitously expressed daf-21 ( Hsp90 ) and muscle-enriched hsp-12 . 2 ( sHsp ) promoters abolished their myogenic-dependent expression . Disrupting HLH-1 function in muscle cells reduced the expression of putative HLH-1-regulated chaperones and compromised muscle proteostasis during and after embryogenesis . In turn , we found that modulating the expression of muscle chaperones disrupted the folding and assembly of muscle proteins and thus , myogenesis . Moreover , muscle-specific over-expression of the DNAJB6 homolog DNJ-24 , a limb-girdle muscular dystrophy-associated chaperone , disrupted the muscle chaperone network and exposed synthetic motility defects . We propose that cellular differentiation could establish a proteostasis network dedicated to the folding and maintenance of the muscle proteome . Such cell-specific proteostasis networks can explain the selective vulnerability that many diseases of protein misfolding exhibit even when the misfolded protein is ubiquitously expressed .
Molecular chaperones are a diverse group of highly conserved proteins that evolved to cope with protein quality control challenges [1–3] . The cellular chaperone machinery is involved in a multitude of cellular functions , including de novo folding , assembly and disassembly of protein complexes , protein translocation across membranes , assisting proteolytic degradation and unfolding and reactivation of stress-denatured proteins [1 , 3 , 4] . The function and specificity of a chaperone-based reaction can be mediated by co-chaperones that choose the substrate , present it to the chaperone , and then coordinate cycles of binding and release by the chaperone in a manner that facilitates polypeptide unfolding [5–7] . Acute stress or chronic expression of metastable proteins leads to the accumulation of misfolded proteins that disrupts cellular protein homeostasis ( proteostasis ) . Misfolded proteins continually occupy the chaperone machinery , such that overwhelming this machinery results in a shortage of chaperones for other cellular functions [8–12] . Activation of stress responses , such as the heat shock response , can induce chaperone genes , ( chaperone and co-chaperone ) expression and restore proteostasis [13] . However , this activation is also regulated by cell non-autonomous signals that can inhibit or induce a heat shock response regardless of protein damage [14] . Although chaperone over-expression often alleviates misfolded protein-associated toxicity [2 , 15] , accumulation of chaperones and activation of the heat shock response can also be detrimental to organismal health [12 , 16–22] , possibly by disrupting sub-networks of chaperones and co-chaperones [23–25] . The chaperone network in unicellular eukaryotes consists of two separately regulated chaperone sets , where one is co-regulated with the translational apparatus and one is stress-induced [26] . In multi-cellular eukaryotes , however , the complexity of the chaperone network is increased , with expression of components of the proteostasis network being highly heterogeneous between tissues , as well as dependent on age [2 , 27] . Thus , the chaperone network may parallel the diverse composition of the proteome and its cellular folding requirements . However , it remains unknown how the expression of cell type-specific or ubiquitously expressed chaperones is regulated in different tissues . We reasoned that if chaperones expression is regulated in a cell-specific manner then differentiation transcription factors could play a role in defining the proteostatic network . Muscle differentiation in Caenorhabditis elegans provides a well-studied case of highly regulated changes in cellular proteome composition within a specific time window [28–31] , as well as information on molecular chaperones associated with muscle function [32] . C . elegans development is determined by the essentially invariant somatic cell lineage , so that the 81 embryonic muscle cells of the organism arise in a deterministic manner [33] . Muscle gene expression starts ~300 min after the first division . By ~350 min , dorsal and ventral muscle quadrants are formed , followed by the organization of muscle components into sarcomeres , and then by contraction of myofilaments at ~420–450 min [34] . Failure to properly fold and assemble the myofilaments disrupts myogenesis ( arrest at two-fold phenotype ) and can result in embryonic lethality [34] . C . elegans body-wall muscle differentiation is dependent on the core myogenic transcription factor modules HLH-1 ( MyoD ) , UNC-120 and HND-1 . Ectopic expression of each of these transcription factors can convert early blastomeres into muscle-like cells . However , in their absence only morphogenesis is disrupted and muscle differentiation can still occur [28 , 35–37] . These transcription factors regulate the expression of many muscle proteins , such as myosin and actin [28 , 30] . Many sarcomeric proteins require chaperones for their folding and assembly [32] . For instance , myosin folding and assembly requires the coordinated functions of the Hsp90 chaperone machinery ( Hsp90 and its co-chaperones STI1-AHA1-P23 ) and the myosin-specific chaperone UNC-45 [25 , 32 , 38] . Moreover , there are examples of muscle-specific diseases that are associated with mutations in a ubiquitously expressed chaperone , such as DNAJB6 associated with the limb-girdle muscular dystropy [18 , 39] . Here , we examined whether muscle chaperone expression is regulated by HLH-1 during C . elegans myogenesis . We found that the expression of chaperone genes with putative HLH-1-binding sites is induced by HLH-1-dependent myogenic conversion . We then demonstrated that disrupting the putative E-box motifs at the promoters of such chaperones inhibited HLH-1-dependent expression . Moreover , reduced HLH-1 expression resulted in a limited muscle proteostasis capacity during embryogenesis , larval development and adulthood . Finally , we showed that modulating the levels of muscle chaperones impacted the folding environment of muscle cells , disrupting muscle function and embryogenesis . We thus concluded that the myogenic transcription factor HLH-1 can regulate the expression of chaperones required for the folding and assembly of muscle proteins , establishing a cell-specific proteostasis network to fit cellular needs . We propose that cell-specific differences in the proteostatic network may contribute to tissue-specific vulnerability to protein misfolding diseases .
HLH-1 is the main myogenic transcription factor in C . elegans . To test whether chaperone expression is associated with cellular differentiation , we first assessed the potential of HLH-1 to regulate chaperone expression during muscle differentiation . Using chromatin immunoprecipitation and next-generation sequencing ( ChIP-seq ) , two independent studies mapped the occupancy sites for this factor . One study used myogenic conversion , while the second used animals expressing HLH-1::GFP to increase HLH-1 detection [29 , 30] . We used a set of 97 C . elegans chaperone genes [25] to ask whether there are putative HLH-1-binding sites associated with chaperone genes . Chaperone genes identified in at least one ChIP-seq experiment as being bound by HLH-1 were defined as chaperones with a HLH-1 occupancy site . This analysis resulted in a set of 62 chaperone genes ( Fig 1A and S1 Table ) . The occupancy sites for these genes were found mainly in the promoter region , similar to other genes possessing HLH-1 occupancy sites [29 , 30] ( Fig 1B ) . We ranked the 97 chaperone genes according to the number of independent ChIP-Seq experiments in which they were identified . Strong candidate genes , such as unc-45 and daf-21 ( Hsp90 ) , were found to bind HLH-1 in all three ChIP-Seq experiments . Unlikely candidates included hsp-17 ( sHsp ) and fkb-6 ( FKBP ) for which an HLH-1-binding site was not identified ( Fig 1A ) . We then asked whether chaperones with HLH-1 occupancy sites are expressed in muscle cells . To define muscle-expressed chaperones , we considered three independent datasets of muscle-enriched genes: ( 1 ) An RNA-sequencing dataset of genes expressed in myogenic-converted embryos [30]; ( 2 ) a microarray dataset of genes expressed in muscle cells isolated by sorting cells from dissociated embryos expressing green fluorescence protein-tagged myosin ( MYO-3::GFP ) [31]; and ( 3 ) an mRNA dataset isolated from muscle cells at the first larval stage ( L1 ) using mRNA-binding proteins expressed specifically in body-wall muscles [40] . This last dataset represents proteins that were expressed in functional muscle cells during post-embryonic development . Here , too , chaperones were ranked according to the number of datasets in which they were identified ( Fig 1A ) . Combining these datasets , we identified 46 chaperones that were muscle-enriched ( S1 Table ) . Next , we used manual curation to identify muscle-required chaperones . The literature was scanned for reports of: ( 1 ) Chaperones shown in vivo to function in the folding of abundant muscle proteins , such as CCT/TRiC that is required for actin folding; ( 2 ) chaperones known to cause myopathies in humans , such as DNAJB6 ( DNJ-24 ) , as well as chaperones that affect C . elegans motility , such as UNC-23; and ( 3 ) chaperones that are localized to the sarcomere , such as HSP-12 . 1 [18 , 25 , 38 , 39 , 41–54] ( S1 Table ) . This yielded 24 genes that were ranked according to the number of these criteria they matched ( Fig 1A ) . Supporting a role for these chaperones in the folding and assembly of muscle proteins in vivo , the muscle-required set significantly overlapped with the muscle-enriched set ( 17 of 24 , P = 0 . 008 , Fisher exact test; Fig 1C ) . Most of the chaperone genes with HLH-1 occupancy sites were associated with muscle chaperones ( enriched or required ) ( 39 of 62 , P = 0 . 025 , Fisher exact test; Fig 1D ) , while chaperones with no identifiable HLH-1 occupancy site were not significantly associated with muscle chaperones ( 14 out of 35 , P = 0 . 99 , Fisher exact test ) . Thus , many muscle-enriched or -required chaperones have HLH-1 occupancy sites and can potentially be regulated by HLH-1 . Expression of well-established HLH-1-depndent muscle genes , such as myosins , is first observed ~300 min after the first division [34] . If HLH-1 occupancy sites are functional , chaperone genes that are bound by HLH-1 are expected to show a similar pattern of expression . While changes in muscle expression of ubiquitously expressed chaperones could be masked by their expression in other tissues [56] , muscle specific or muscle-enriched chaperones are expected to show this pattern . We utilized the C . elegans developmental gene expression time course to characterize the myogenic-induced ( MI ) expression of genes during embryogenesis . This dataset , derived from whole embryos , records the expression of over 19 , 000 genes at ten different developmental stages over the course of embryogenesis [55] . Using this dataset , we first examined the expression dynamics of a set of known muscle genes that are also enriched in embryos showing increased muscle content upon myogenic conversion [30] . Of the 35 genes examined , the expression of 21 muscle-specific genes clustered into a single distinct developmental expression pattern ( S1 Fig ) . The pattern showed little change in mRNA levels during early embryogenesis ( <200 min ) but a strong increase at the ventral enclosure stage ( ~290 min ) . We then asked whether the expression of some chaperone genes with HLH-1 occupancy site also follows this pattern of muscle protein expression . Of the 62 chaperone genes in this set , eight genes clustered into the MI expression pattern , of which seven were muscle-enriched and all eight were muscle-required ( Fig 1A and 1E ) . As expected , ubiquitously expressed genes were not detected in this analysis . Thus , we were able to find a myogenic-induced expression pattern for a subset of HLH-1-associated chaperones also linked to muscle expression and function , supporting our hypothesis that muscle chaperones could be regulated by HLH-1 during muscle differentiation . To experimentally test whether HLH-1 regulates chaperone expression during muscle differentiation , we first examined whether the ectopic expression of HLH-1 that induced myogenic conversion could also induce the expression of muscle chaperones in non-muscle cells . As such , we utilized animals expressing HLH-1 under the control of the inducible hsp-16 . 41 ( sHsp ) promoter , HLH-1 ( ec ) [28] . When such animals were exposed to a short heat shock ( 30 min at 34°C ) during early embryogenesis , HLH-1 was ectopically expressed in all embryonic cells . Because heat shock induced the expression of heat shock genes , some of which are chaperones , we examined the expression of each gene in both HLH-1 ( ec ) and wild type embryos with or without exposure to heat shock ( Fig 2A ) . To control for heat shock-induced activation , animals expressing GFP under the control of the inducible chaperone promoter hsp-16 . 2 ( sHsp ) were crossed with HLH-1 ( ec ) animals and GFP expression was monitored . Upon heat shock , robust GFP expression was detected in most cells of the HLH-1 ( ec ) embryos ( Fig 2B ) , similar to wild type animals ( S2A Fig ) . Likewise , heat shock genes , such as hsp-16 . 2 ( sHsp ) and F44E5 . 4 ( Hsp70 ) , were similarly induced in both HLH-1 ( ec ) and wild type embryos ( Fig 2C ) . When we examined the expression of known HLH-1-regulated genes , such as myosin , by immuno-staining , heat shock-treated HLH-1 ( ec ) embryos showed ectopic expression of myosin heavy chain A ( MYO-3 ) in most cells of the embryo ( Fig 2B ) but not in wild type embryos ( S2A Fig ) . In agreement , levels of actin ( act-4 ) and myosin heavy chain B ( unc-54 ) were induced in heat shock-treated HLH-1 ( ec ) but not in wild type embryos ( Fig 2D ) . We then asked whether ectopic expression of HLH-1 and altered cellular fate affected the pattern and levels of expression of chaperone genes . We divided the chaperone list into four groups: ( 1 ) Chaperones with HLH-1 occupancy site identified in at least one experiment and that are muscle-associated ( 39 genes ) , or ( 2 ) that are not associated with muscle ( 21 genes ) ; ( 3 ) chaperones with no identified HLH-1 occupancy site that are associated with muscle ( 14 genes ) , or ( 4 ) that are not associated with muscle ( 22 genes ) ( S1 Table ) . We then tested candidate genes ( Fig 1A , gray shaded ) from each group for myogenesis-dependent changes in expression induced by ectopic induction of HLH-1 ( Fig 2E–2H ) . As expected , the expression of UNC-45 , considered a HLH-1-specific substrate [30] , was ectopically induced in most of the cells of the heat shocked HLH-1 ( ec ) embryos ( Fig 2B ) but not of wild type animals ( S2A Fig ) . To test for changes in expression of ubiquitously expressed chaperones , animals expressing GFP under the control of the cct-2 ( Hsp60 ) or cct-7 ( Hsp60 ) promoter were crossed with HLH-1 ( ec ) animals and GFP fluorescence was monitored . Similar to the HLH-1 muscle genes tested , cct-2 ( Hsp60 ) - and cct-7 ( Hsp60 ) -dependent GFP expression was detected in most cells of the HLH-1 ( ec ) embryos upon heat shock ( Fig 2B ) but not in wild type embryos ( S2A Fig ) . Thus , myogenic-converted cells , differentiating into muscle cells , began to express chaperone genes . Indeed , mRNA of 14 muscle-associated chaperone genes with an HLH-1 occupancy site ( group 1 ) were all induced ( 10–80 folds ) in HLH-1 ( ec ) embryos upon heat shock . This group included all MI chaperones tested ( 5 out of 8 , Fig 1E ) , as well as ubiquitously expressed chaperones . In wild type embryos , in contrast , these chaperones expression levels ( apart from sip-1 ( sHsp ) ) did not increase and indeed , some decreased following heat shock ( Fig 2E and S2B Fig ) . Although sip-1 ( sHsp ) levels increased in wild type embryos , its induction in HLH-1 ( ec ) embryos was 10-fold higher ( Fig 2E and S2B Fig ) . Chaperone genes with HLH-1 occupancy sites that were not associated with muscle ( group 2 ) also showed increased levels in HLH-1 ( ec ) embryos upon heat shock ( 3 of the 4 genes tested ) , albeit to a modest extent ( 1 . 5–3 . 5 fold ) . Thus , of the 18 chaperone genes with an identified HLH-1 occupancy site , 17 were significantly induced by ectopic expression of HLH-1 ( Fig 2E and 2F and S2B and S2C Fig ) . In contrast , when we examined chaperones for which HLH-1 occupancy sites was not identified , regardless of their muscle association ( groups 3 and 4 ) , only one gene , C01G10 . 8 ( Aha1 ) , showed increased expression in HLH-1 ( ec ) embryos upon heat shock ( Fig 2G and 2H and S2D and S2E Fig ) . Thus , under conditions of induced myogenic conversion , when HLH-1-dependent muscle differentiation is activated , chaperones genes that were shown to bind HLH-1 are induced . This indicates that the majority of HLH-1 occupancy sites identified for chaperone genes are functional ( 24 out of 26 genes tested , i . e . 92% ) and , similar to other muscle genes , are up-regulated when cells differentiate into muscle cells . To verify that chaperone expression was due to HLH-1 , HLH-1 ( ec ) embryos from animals treated with control or hlh-1 RNAi were heat shocked and changes in mRNA levels following heat shock were assessed . While expression of the inducible heat shock gene hsp-70 ( Hsp70 ) was unaffected by hlh-1 ( RNAi ) , the induced expression of the muscle genes act-4 and unc-54 and the muscle chaperone genes unc-45 , cct-2 ( Hsp60 ) and cct-5 ( Hsp60 ) was strongly reduced in hlh-1 ( RNAi ) -treated HLH-1 ( ec ) embryos , as compared to control RNAi-treated embryos ( Fig 2I ) . Likewise , the expression of muscle and chaperone genes was not significantly induced when the transcription factor CHE-1 was ectopically expressed upon heat shock in embryos expressing hsp-16 . 2::che-1 , although expression of hsp-70 ( Hsp70 ) and che-1 was induced ( Fig 2J ) . Thus , ectopic expression of HLH-1 that led to myogenic conversion , resulted in HLH-1-dependent induced expression of muscle chaperones in differentiating muscle cells . A previous attempt to validate HLH-1 function using a HLH-1-binding site upstream of a minimal promoter was very limited in its ability to induce muscle expression , even of known muscle genes [29] . We , therefore , took a different approach to examine whether HLH-1 is required for chaperone expression during muscle differentiation . Accordingly , we asked how disruption of the HLH-1 E-box-binding motif at chaperone promoters would affect their expression in myogenic-converted embryos . Because the muscle-specific chaperone UNC-45 is considered one of the “gold standard” muscle genes regulated by HLH-1 [30] , we examined two ubiquitously expressed chaperones . Specifically , DAF-21 ( Hsp90 ) , a well-established myosin chaperone and HSP-12 . 2 , a small HSP ( sHsp ) that showed a myogenic expression pattern during embryogenesis ( Fig 1E ) . The DAF-21 ( Hsp90 ) HLH-1 occupancy site was identified in three independent ChIP-seq experiments and its binding peak at the promoter showed a clear E-Box consensus motif . The HSP-12 . 2 ( sHsp ) HLH-1 occupancy site was identified in two independent ChIP-seq experiments and its binding peak at the promoter has two E-Box consensus motifs ( S1 Table ) [29 , 30] . We constructed a transcription reporter containing the promoter region of daf-21 ( Hsp90 ) or hsp-12 . 2 ( sHsp ) upstream of GFP ( daf-21::gfp or hsp12 . 2::gfp ) and mutated the E-box sequences ( Fig 3A ) . These constructs were injected into HLH-1 ( ec ) animals and stable transgenic animals were established . The expression of GFP in myogenic-converted embryos was then monitored following heat shock . In 82 . 6±0 . 4% of the daf-21 ( Hsp90 ) and 57 . 7±4 . 8% of the hsp12 . 2 ( sHsp ) embryos carrying the wild type transcription reporters , GFP was ectopically expressed in most cells of the embryos upon heat shock . In contrast , GFP expression was undetected ( less than 5 cells ) in all the heat shock embryos carrying the mutated transcription reporters ( P<0 . 05 , Fig 3B ) . When daf-21::GFP embryos were allowed to develop , expression of both wild type and mutated constructs was observed in various tissues of the adult animals , including intestine and neurons ( S3 Fig ) . However , we could not detect GFP expression in muscle cells of adult animals carrying the mutated transcription reporters . For example , no muscle expression was detected in animals carrying the mutated daf-21::GFP transcription reporter ( n = 120 ) , although wild type daf-21::GFP was expressed in muscle cells ( S3 Fig ) . Thus , disrupting putative E-box sequences abolished the HLH-1-dependent regulation of daf-21::GFP and hsp-12 . 2::GFP in embryonic muscle cells , suggesting that HLH-1 occupancy sites at these promoters are transcriptionally functional and can drive muscle expression . To complement the approach taken above and to determine the contribution of HLH-1 to muscle proteostasis , we examined the effects of down-regulating hlh-1 on chaperone expression during embryogenesis , using a truncation allele , hlh-1 ( cc561 ) . This nonsense ( Glu222Stop ) mutation does not affect HLH-1 function but results in temperature-dependent hlh-1 mRNA clearance by the nonsense mRNA decay pathway and , therefore , temperature-dependent knockdown of HLH-1 levels [28 , 57] . We thus asked whether the expression of chaperone genes with HLH-1 occupancy sites was affected in hlh-1 ( cc561 ) animals grown at 25°C , as compared to animals grown at 15°C . Wild type or hlh-1 ( cc561 ) embryos laid at 25°C were allowed to develop for 6 h . Protein expression and mRNA levels of muscle genes were then compared with those values obtained in embryos maintained at 15°C ( Fig 4A ) . Some muscle proteins , including the major myosins and actins , were unaffected by hlh-1 ( cc561 ) because UNC-120 serves a partially overlapping function and can compensate for a loss of HLH-1 [30] . In agreement , immuno-staining of hlh-1 ( cc561 ) embryos with anti-MYO-3 antibodies showed a typical organization pattern in body-wall muscle cells in embryos grown at 15°C and 25°C ( Figs 4B and S4A ) . The relative mRNA levels ( 25°C/15°C ) of act-4 and unc-54 were also similar in hlh-1 ( cc561 ) and wild type animals ( Fig 4C ) . In contrast , the localization of myosin chaperone UNC-45 was lost in hlh-1 ( cc561 ) embryos grown at 25°C and relative unc-45 mRNA levels were reduced in hlh-1 ( cc561 ) , as compared to wild type embryos ( Fig 4B and 4C and S4A Fig ) . Likewise , the expression of GFP under the control of the cct-2 ( Hsp60 ) or cct-7 ( Hsp60 ) promoter in hlh-1 ( cc561 ) embryos grown at 25°C was lost and the relative mRNA levels of different muscle chaperones shown to be regulated by HLH-1 ( ec ) ( group 1 and 2 ) were significantly reduced in hlh-1 ( cc561 ) embryos , as compared to wild type embryos ( Fig 4B and 4D , S4A and S4B Fig ) . While the expression of C01G10 . 8 ( Aha1 ) that was induced in heat-shocked and treated HLH-1 ( ec ) embryos was significant reduced ( S4C Fig ) , chaperones , such as dnj-2 ( Hsp40 ) and fkb-6 ( FKBP ) , for which no HLH-1 occupancy site or HLH-1 ( ec ) -induced expression were identified , were unaffected by hlh-1 knockdown ( Fig 4E ) . Thus , the expression of ubiquitously expressed and muscle-enriched chaperones associated with muscle protein folding and assembly was strongly reduced in hlh-1 ( cc561 ) embryos . We next considered the consequences of disrupting HLH-1-dependent chaperone expression for muscle proteostasis during embryogenesis . To challenge muscle proteostasis , we crossed hlh-1 ( cc561 ) with animals expressing yellow fluorescent protein ( YFP ) fused to 35 glutamine repeats ( Q35 ) or YFP alone ( Q0 ) expressed under the muscle-specific unc-54 myosin promoter ( Q35;hlh-1 ( cc561 ) and Q0;hlh-1 ( cc561 ) , respectively ) . As noted above , hlh-1 ( cc561 ) is a knockdown mutant . The nonsense allele occurs at a position coding 13 amino acids after the bHLH domain , resulting in a functional protein . Indeed , the hlh-1 ( cc561 ) phenotype under restrictive conditions was fully rescued by over-expression of the cc561 allele or by inhibiting the nonsense mRNA decay pathway [57] . Under permissive conditions , <10% of the animals expressing Q0;hlh-1 ( cc561 ) exhibited embryonic arrest and typical myofilaments were formed ( >90% ) ( Fig 5A and 5B ) . Likewise , embryonic development was unaffected by Q0- or Q35-expression and myofilament organization , examined by UNC-54 immuno-staining , was normal ( Fig 5A and 5B ) [11] . In contrast , 45 . 5±6% of the Q35;hlh-1 ( cc561 ) embryos were arrested at the two-fold stage and assumed deformed shapes when grown at 15°C . Q35;hlh-1 ( cc561 ) embryos showed severe mislocalization of UNC-54 and myofilaments were not formed in many of the embryos ( >60% , Fig 5A and 5B ) . This phenotype was partially rescued by inhibiting the nonsense mRNA decay pathway . RNAi knockdown of smg-2 or smg-7 did not affect Q35 embryos , yet rescued 30–50% of Q35;hlh-1 ( cc561 ) -arrested embryos , as compared to those treated with the empty vector control ( S5A Fig ) . Thus , expression of aggregation-prone Q35 in a hlh-1 ( cc561 ) background resulted in severe disruption of muscle protein folding . These data suggest that muscle proteostasis capacity is limited in hlh-1 ( cc561 ) embryos , supporting a role for hlh-1 in establishing muscle proteostasis . To examine whether reduced HLH-1 levels also impacted muscle proteostasis capacity later in life , i . e . , after muscle development has completed , we monitored Q35;hlh-1 ( cc561 ) young adults for muscle function and myosin organization . Although we excluded deformed or paralyzed animals , motility of Q35;hlh-1 ( cc561 ) young adults was reduced 2 . 5-3-fold , as compared to Q0;hlh-1 , Q0 or Q35 young adults ( Fig 5C ) . In agreement , Q35;hlh-1 ( cc561 ) young adults exhibited severe UNC-54 disorganization , while Q0;hlh-1 ( cc561 ) myofilaments maintained their striated structures and were only mildly disorganized ( Fig 5D and S5B Fig ) . Myofilament organization was normal in Q0 or Q35 young adults ( Fig 5D ) [11] . Thus , the disruption of muscle protein folding observed for Q35;hlh-1 ( cc561 ) embryos was not mitigated in adult animals . Disruption of cellular proteostasis was previously shown to increase Q35 foci formation [11] . Foci formation in Q35-expressing animals begins at the transition to reproductive adulthood [58] . As such , no foci were observed in Q35 animals at the first larval stage ( L1 ) ( n = 430 ) . Following the onset of reproduction , ( day 5 ) Q35 animals had an average of ~4 foci per animal . In contrast , foci were observed in ~10% of the Q35;hlh-1 ( cc561 ) animals ( n = 425 ) even by the L1 stage , while by day 5 , Q35;hlh-1 ( cc561 ) animals had an average of ~50 foci per animal ( Fig 5E and 5F ) . Still , Q35 protein levels in Q35;hlh-1 ( cc561 ) animals were ~50% lower than in Q35 animals ( S5C and S5D Fig ) . Thus , reduced HLH-1 levels also resulted in limited muscle proteostasis in adulthood . The disruption in muscle function and increased aggregation of Q35;hlh-1 ( cc561 ) later in life could be due to HLH-1 function after embryogenesis but could also stem from defects acquired during myogenesis . Indeed , Q35;hlh-1 ( cc561 ) L1 animals were already affected at 15°C ( Fig 5E ) . To test the impact of hlh-1 on proteostasis past embryogenesis , we treated Q35;hlh-1 ( cc561 ) animals with smg-2 ( RNAi ) at the L1 stage to rescue hlh-1 expression levels after embryogenesis was completed . We found that motility and aggregation of Q35;hlh-1 ( cc561 ) young adults treated with smg-2 ( RNAi ) from L1 were partially rescued as compared to those treated with the empty vector control ( S5E and S5F Fig ) . In contrast , shifting hlh-1 ( cc561 ) to 25°C at the L1 stage to reduced hlh-1 expression levels past embryogenesis , did not significantly affect its motility as compared to wild type ( S5G Fig ) . These data suggest that HLH-1 is not required but can contribute to muscle proteostasis in adulthood . Taken together , our data support a role for HLH-1 in establishing muscle proteostasis , as well as impacting proteostasis capacity in adulthood . The correct folding and assembly of myosin thick filaments and thus , myogenesis , requires UNC-45 . Myofilaments are assembled and begin to contract some ~420 min after the first division ( 1 . 5-fold stage ) , thereby facilitating embryo elongation ( 3-fold stage ) [34] . In contrast , proper myofilament assembly is disrupted in unc-45 null mutants , leading to muscle-dependent embryonic arrest at the two-fold stage and lethality . Given that DAF-21 ( Hsp90 ) and UNC-45 were shown to compete for myosin binding in vitro [59] , we postulated that the regulation of ubiquitously expressed chaperone genes by the myogenic transcription factor HLH-1 should also be adjusted to muscle proteomic needs . To directly test whether specifically changing the levels of ubiquitously expressed chaperone in body-wall muscle cells disrupted myogenesis , we asked how over-expression of muscle DAF-21 ( Hsp90 ) affected the folding of UNC-54 , a known Hsp90 substrate , and hence , myogenesis . A temperature-sensitive mutation in myosin , unc-54 ( e1301ts ) ( unc-54 ( ts ) ) , shows temperature-dependent misfolding [11] but only mildly induced the arrest at two-fold phenotype [34] . We crossed unc-54 ( ts ) with animals that specifically over-express DAF-21 ( Hsp90 ) in body-wall muscle cells ( strain AM780 ) . These animals express daf-21 ( Hsp90 ) tagged with GFP ( daf-21::GFP ) under the muscle specific unc-54 promoter ( HSP90M ) . We then monitored embryonic arrest and UNC-54 localization in wild type , HSP90M , unc-54 ( ts ) and HSP90M;unc-54 ( ts ) embryos laid at 20 or 25°C . HSP90M did not induce arrest at the two-fold stage when the animals were grown at 20 or 25°C ( 2 . 1±0 . 6% and 3 . 9±0 . 5% , respectively ) . unc-54 ( ts ) embryos showed a mild arrest at 20 and 25°C ( 5 . 2±0 . 6% and 13 . 6±1 . 2% , respectively ) . In contrast , HSP90M;unc-54 ( ts ) embryos were severely delayed ( S6A Fig ) , with the percentage of embryo arrested at the two-fold stage at both 20 and 25°C being increased ( 12 . 7±1 . 7% and 40 . 6±3 . 3% , respectively , Fig 6A ) . HSP90M;unc-54 ( ts ) embryos showed defective myofilament and muscle elongation . Immuno-staining with anti-UNC-54 antibodies of HSP90M;unc-54 ( ts ) embryos grown at 20°C exhibited strongly reduced UNC-54 staining ( Fig 6B ) . Although the embryos examined were arrested at the two-fold stage , most eventually hatched ( Fig 6A ) . Similar UNC-54 immuno-staining was observed for HSP90M;unc-54 ( ts ) embryos grown at 25°C but only about half of these embryos hatched ( Fig 6A and S6B Fig ) . In contrast , UNC-54 myofilament assembled correctly in most wild type , HSP90M , unc-54 ( ts ) embryos grown at 20°C ( Fig 6B ) . Our data suggest that DAF-21 ( Hsp90 ) levels are adjusted for proper myosin folding to support muscle elongation and embryo development . Thus , changes in chaperone expression can disrupt proteostasis and abrogate myogenesis . The expression of aggregation-prone proteins was suggested to disrupt proteostasis by engaging chaperones and competing for their substrates [9 , 11] . Differences in chaperones expression levels and composition could also alter chaperone and co-chaperone interactions . Thus , modulating chaperone expression in a given tissue could transform the network of that chaperone . To ask how changing chaperone levels modulate chaperone interactions , we focused on dnj-24 ( Hsp40 ) , encoding the C . elegans homolog of DNAJB6 . DNAJB6 is a ubiquitously expressed chaperone linked to limb-girdle muscular dystropy type 1D ( LGMD1D ) [18] . LGMD1D mutations were shown to result in stabilization and , therefore , increased levels of DNAJB6 . While the amino acids associated with LGMD1D are not conserved in DNJ-24 ( Hsp40 ) , DNJ-24 ( Hsp40 ) is enriched in muscle and shows the expected muscle and nuclear distribution pattern [49] . To address whether increased levels of this chaperones disrupted chaperone interactions in muscle cells , we examined the effects of muscle over-expression of dnj-24 ( Hsp40 ) ( DNJ-24M ) on synthetic motility defects induced by chaperone knock-down . We reasoned that if DNJ-24M perturbed chaperone interactions in muscle cells , then this might exacerbate the effects of knocking-down the levels of other muscle chaperones [25] . If so , then RNAi of chaperones that do not affect motility in wild type animals should induce motility defects in DNJ-24M-expressing animals . Consistent with previous work in a zebrafish model [18] , over-expression of wild type dnj-24 ( Hsp40 ) in body-wall muscle of C . elegans did not result in notable motility defects ( Fig 7 ) . However , when age-synchronized DNJ-24M-expressing animals were treated with RNAi for different Hsp70 chaperones and co-chaperones , three genes ( of 48 examined ) , namely hsp-1 , rme-8 , and dnj-8 , specifically affected the motility of DNJ-24M-expressing but not wild type or HSP90M-expressing animals ( Fig 7A and 7B ) . RNAi knock-down of the hsp-1 ( Hsc70 ) induced a strong larval arrest in wild type , HSP90M and DNJ-24M animals , yet only in the DNJ-24M animals did such treatment induce 100% paralysis ( Fig 7A and 7B ) . Of note , DNAJB6 interacts with several chaperones associated with chaperones-assisted selective autophagy , one of which is HSPA8 , a Hsp-1 ( Hsc70 ) homolog [18] . Knocking-down the expression of rme-8 ( Hsp40 ) and dnj-8 ( Hsp40 ) resulted in no motility phenotype in wild type or HSP90M animals , while knocking-down the expression of these genes in a DNJ-24M background resulted in motility defects ( 72±10 . 7 and 61±2 . 7 , p<0 . 0002 , Fig 7B ) and disrupted myosin organization ( S7 Fig ) . Thus , over-expression of DNJ-24 ( Hsp40 ) in body-wall muscle cells disrupted muscle proteostasis such that muscle cells were more susceptible to hsp-1 ( Hsc70 ) , rme-8 ( Hsp40 ) and dnj-8 ( Hsp40 ) knock-down . Cell type-specific regulation of chaperone expression could , therefore , impact tissue-specific chaperone networks .
In the present study , we asked whether the cellular chaperone network is regulated in a cell type-specific manner . Specifically , we asked whether muscle chaperones are regulated by the myogenic transcription factor HLH-1 during C . elegans myogenesis . We found that muscle chaperones that have HLH-1 occupancy sites in their promoter are induced in myogenic-converted embryos . This muscle-specific induction was fully dependent on HLH-1 , as no induction was observed for most chaperones without HLH-1 occupancy sites or when HLH-1 expression was down-regulated . Moreover , we showed that disrupting the putative HLH-1 binding sites in two different chaperone promoters inhibited their myogenic-induced expression and muscle expression later in life . Thus , HLH-1 is required for the expression of muscle chaperones with HLH-1 occupancy sites in cells undergoing differentiation into body-wall muscle cells . While a HLH-1 differentiation-independent function in embryonic muscle cells is possible , we instead propose that muscle chaperone genes are regulated by HLH-1 together with other muscle genes during myogenesis . Linking the regulation of chaperone expression to the differentiation program could result in a distinct chaperone network , ensuring that chaperones are expressed at the required levels and with proper timing . Indeed , we found that down-regulation of HLH-1 strongly restricted proteostasis capacity , leading to misfolding of muscle protein and myogenesis arrest . Tissue-specific differences in the expression levels of chaperones can explain why down-regulation of ubiquitously expressed chaperones led to a tissue-selective activation of the heat shock response [60] and why the cellular folding environment is sensitive to chronic expression of aggregation-prone proteins and expression of stress-induced chaperones [9 , 11 , 19 , 61] . The importance of regulating chaperone levels in a tissue-specific manner is supported by prior findings and our data showing that both down-regulation and over-expression of the myosin-specific chaperone UNC-45 and the ubiquitously expressed Hsp90 were detrimental to myosin assembly and muscle elongation [45 , 59] . Given that DAF-21 ( Hsp90 ) and UNC-45 were shown to compete for myosin binding in vitro , their relative levels are critical for myosin folding and can abrogate myogenesis . We , therefore , suggest that physiological tissue-specific chaperone networks can enable cells to respond to the folding requirement of their unique proteomes , leading to distinct responses to folding challenges , such as acute stress or chronic expression of misfolded proteins . We found that muscle proteostasis can also be critical for muscle differentiation and can , as in the case of UNC-45 and Hsp90 , lead to embryonic arrest and lethality . In support of this claim , a recent study showed that activation of Janus kinase 2 ( JAK2 ) signaling associated with myeloproliferative neoplasms ( MPNs ) resulted in reduced expression of proteostasis component AIRAPL ( arsenite-inducible RNA-associated protein-like ) and led to increased insulin/insulin-like growth factor 1 ( IGF1R ) stability and disrupted hematopoietic differentiation [62] . Thus , changes in expression of proteostasis components can result in modulated folding or degradation of cellular factors , such as signaling proteins that , in turn , can lead to alterations in differentiation . Our data demonstrate that the myogenic factor HLH-1 regulates the expression of chaperones in muscle cells . By extension , chaperones can be differentially regulated in different cell types to meet the needs of a specific proteome . The large available ChIP-seq dataset ( ModEncode ) [63] shows that transcription factors involved in development and differentiation can bind the promoter region of chaperone genes , supporting our proposal of tissue-specific developmental regulation of chaperone expression , and raises the possibility that tissue differentiation promotes the expression of required chaperones . In agreement , PHA-4 is required for the development of the pharynx and foregut and also regulates the expression of autophagy-required genes [64] . ChIP-seq analysis of the occupancy sites of PHA-4 [65] showed significant overlap between PHA-4 binding to chaperone promoters under starvation stress conditions and chaperone promoters occupied during embryogenesis ( 33 out of 38 overlapped between L1 stress and embryos , p = 0 . 0001 ) . This overlap suggests , in turn , a possible role for transcription factors involved in development and differentiation in tissue maintenance later in life . Indeed , the pha-4 occupancy site in the daf-21 ( hsp90 ) promoter , as identified by modEncode , was shown to be functional in cell non-autonomous expression of daf-21 ( Hsp90 ) in adult C . elegans muscle , intestinal and neuronal cells [12] . For HLH-1 , we observed disrupted proteostasis in adulthood in a Q35;hlh-1 ( cc561 ) background that could be alleviated by blocking the nonsense mRNA decay pathway and thus , hlh-1 mRNA clearance . Indeed , hlh-1 ( cc561 ) exacerbated the effect of a dystrophin mutation associated with Duchenne’s muscular dystrophy , leading to muscle degeneration in adulthood [66 , 67] . We , therefore , propose that similar to the specialization of the chaperone networks in unicellular eukaryotes into two separate sets , one dedicated to coping with stress-induced misfolding and the other to newly translated proteins [26] , the regulation of chaperone expression in multi-cellular organisms is specialized to establish chaperone networks dedicated to the folding and maintenance of cell type-specific proteomes in development and possibility in adulthood as well . Myogenic-dependent regulation of chaperones suggests that the proteostatic requirements of the muscle proteome might dictate the expression of other quality control machineries to fit functional and folding characteristics of that proteome . Careful analysis of HLH-1 targets revealed that most were not muscle-enriched [30] . One interpretation of this analysis is that the expression of general factors required for muscle differentiation is specifically regulated to meet the needs of muscle cells . Indeed , SKN-1 , required for specification of the EMS blastomeres that give rise to pharyngeal , muscle and intestinal cells , regulates the expression of the oxidative stress response [68] . As noted above , PHA-4 is involved in both development and autophagy [64] . Moreover , autophagy is activated in different tissues of zebrafish during embryogenesis and is required for vertebrate cardiac morphogenesis [69] . Likewise , efficient differentiation of human embryonic stem cells required increased expression of the 19S subunit PSMD11 [70] . We , therefore , propose that rather than relying on a generic proteostatic machinery , each cell and tissue type with a defined folding capacity possesses a specific composition of the quality control machinery and perhaps even cell type-specific heat shock response and unfolded proteins responses to deal with the highly specialized challenges of each cell type . Although the expression of many disease-associated proteins is not tissue-specific , many protein misfolding diseases exhibit tissue-specific vulnerability [71 , 72] . For example , mutations in the ubiquitously expressed co-chaperone DNAJB6 cause a tissue-specific disease , limb-girdle muscular dystropy [18] . The mechanism for this selective vulnerability in certain tissues is unknown , although differences in folding and clearance capacities were suggested to affect the onset of several tissue-specific diseases and stress activation [60 , 73–75] . Here , we showed that over-expression of the DNAJB6 homolog DNA-24 ( Hsp40 ) in muscle cells affected the muscle function of HSP-1 ( Hsc70 ) and two other DnaJ co-chaperones , RME-8 ( Hsp40 ) and DNJ-8 ( Hsp40 ) . HSP-1 ( Hsc70 ) and RME-8 ( Hsp40 ) are required for receptor-mediated and fluid-phase endocytosis [76 , 77] . This suggests that the balance between co-chaperones may affect Hsc70 function , similar to protein misfolding [9 , 11] . Indeed , a lack of RME-8 ( Hsp40 ) resulted in mislocalization and clearance of endosomal proteins to the lysosome , associated with autophagic function [78] . Given the link of DNAJB6 to autophagy [18] , it is possible that DNJ-24M disrupts HSP-1 ( Hsc70 ) and RME-8 ( Hsp40 ) interactions , in turn affecting endocytic trafficking in LGMD1D . Thus , the observed stabilization of DNAJB6 might play a role in LGMD1D muscle etiology by competing for RME-8 ( Hsp40 ) or other Hsp40s function . Differential susceptibility to misfolding or stress may , therefore , spring from cell-specific differences in the composition and expression levels of components of the proteostatic network . We propose that differences in chaperone levels and composition between tissues could impact tissue-specific vulnerability to protein misfolding diseases that are globally expressed yet which are manifested in a specific tissue .
The chaperone list was complied based on the work of Brehme et al . [79] , focusing on the main chaperone families and their co-chaperones ( 97 genes ) , including Hsp60 and Hsp10 , Hsp70 , Hsp40 and NEF , Hsp90 and Hsp90 co-chaperones and sHSP [25] . Three curated lists of HLH-1 occupancy sites were used , i . e . ChiP-seq ( e-6 ) peak call data , were provided in the manuscript as supporting information [29] and two curated lists , namely a union set of genes that were identified in experiment ( mex-3 or mex-3;skn-1;elt-1 RNAi ) and an overlap set identified in both [30] . The later curated lists ( Union and overlap ) were kindly provided by Dr . Steven Kuntz and Dr . Paul Sternberg ( S1 Table ) . Three curated lists of genes enriched in muscle were used: ( 1 ) Myogenic-converted embryos [30] , kindly provided by Dr . Steven Kuntz and Dr . Paul Sternberg; ( 2 ) Muscle cells from dissociated embryos and ( 3 ) L1 body-wall muscles [31 , 40] . These later curated lists ( 2–3 ) were provided in the manuscripts as supporting information . Chaperone genes occupancy sites and muscle enrichment were ranked according to the number of independent experiments in which they were identified , giving equal weight to each experiment . Muscle-required chaperone genes were ranked according to the number of criteria ( function , phenotype or sarcomeric localization ) they fulfilled . The list was sorted by HLH-1 occupancy ranking ( Fig 1A ) . The flowchart outlining the bioinformatics analyses and all the data included in these analyses are summarized in S1 Table . HLH-1 binds to E-Box motif ( CANNTG ) [29 , 80] . For each of the 97 chaperone genes , we downloaded upstream sequences ( 1000bp ) from the ensambel biomart webserver and searched using the FIMO tool from MEME suite 4 . 11 . 2 with a p-value<0 . 001 [81] . Putative HLH-1 E-box-binding motifs were found at the promoters of 39 of the 62 chaperones with HLH-1 occupancy sites but were not enriched in these promoters ( S1 Table ) . Venn diagrams were plotted using the BioVenn diagram generator http://www . cmbi . ru . nl/cdd/biovenn/ ( BioVenn ) [82] . Microarray-normalized data for C . elegans embryonic development gene expression was provided by Dr . Itai Yanai [55] . Data were complied and clustered using the EXPANDER ( 6 . 5 . 1 ) program [83] . The probability of overlap between chaperone sets was calculated using the Fisher exact test . The P values in Figs 2–7 were calculated using the Mann-Whitney test , where ( * ) denotes P<0 . 05 and ( ** ) denotes P<0 . 01 . The list of strains used in this work is provided in S2 Table . Nematodes were grown on NGM plates seeded with the Escherichia coli OP50-1 strain at 15°C , unless indicated otherwise . Cross-strains were generated using standard C . elegans procedures . To generate the promoter reporter constructs for daf-21 ( Hsp90 ) and hsp-12 . 2 ( sHsp ) , a 2492 bp fragment for daf-21 ( Hsp90 ) and a 921 bp fragment for the Hsp-12 . 2 ( sHsp ) promoter were amplified from N2 genomic DNA and assembled into plasmid pNU106 to create plasmids pNU314 and pNU374 , respectively , using Gibson ligation . Mutated promoter reporters for daf-21 ( Hsp90 ) and hsp-12 . 2 ( sHsp ) , pNU315::Pdaf-21 ( mut ) ::gfp and pNU375::hsp-12 . 2p ( mut ) ::gfp , respectively , were generated by site-directed mutagenesis of the putative HLH-1-binding motifs at -432 bp and at -921 bp and -266 bp to ACGCGT . Plasmids were validated by DNA sequencing and injected into animals expressing unc-119 ( ed3 ) ;hsp-16 . 41::hlh-1 . Promoter reporter constructs were generated and injected by Knudra Transgenics . Stable transgenic lines are listed in S2 Table . Synchronized animals were grown at 15°C for five days or transferred to 20 or 25°C at the L2 stage for 24–48 h to reach adulthood . These synchronized gravid adults ( first day of egg laying ) were allowed to lay eggs for 45 min and then removed . Synchronized embryos were heat shock-treated , allowed to grow for 6 h to pass the comma stage or allowed to grow for 24–48 h and complete embryogenesis . Embryos laid at 15°C were moved to new plates and were untreated or subjected to heat shock at 34°C for 30 min . To determine RNA levels , embryos were frozen immediately following heat shock . To examine expression patterns , embryos were collected after a 6 h recovery . Wild type and hlh-1 ( cc561 ) embryos laid at 15°C or 25°C for 45 min were allowed to grow for 6 h . The embryonic developmental stage was examined to determine whether embryos grown at 15°C had passed the comma stage . To determine the effect of hlh-1 ( cc561 ) on gene expression , we compared the relative mRNA levels ( 25°C/15°C ) of the genes examined . In S5G Fig , the temperature shift was carried out at L1 . RNAi knockdown treatments were performed as previously described [84] . RNAi constructs were obtained from the “RNAi chaperone library” kindly provided by Prof . Richard Morimoto , Northwestern University [79] or from the Julie Ahringer library . To collect RNAi-treated embryos , animals were grown on E . coli strain HT115 ( DE3 ) transformed with specified RNAi or empty ( pL4440 ) vectors and allowed to lay eggs , as above . Otherwise , synchronized L1 larvae stage worms were washed from regular NGM plates , transferred to RNAi plates and grown at 15°C for five days until day 1 of adulthood . RNA extraction from synchronized embryos , cDNA synthesis and quantitative real-time PCR were performed as previously described [25] . Samples were normalized ( 2-ΔΔCT method ) to T07A9 . 15 or tbc-10 , determined to be stably expressed during embryogenesis [55] . The list of primers used in this work is provided in S3 Table . To determine embryo arrest , synchronized embryos were grown at 15–25°C . Embryos that did not hatch until their siblings reached L2 ( 24–48 hours ) or hatched arrested at the two-fold state were counted as arrested embryos . Age-synchronized young adults were moved to a new plate and their movement was monitored after 10 min . Animals that did not move one body length were scored as paralyzed . Otherwise , age-synchronized young adults were placed in wells containing M9 and allowed to acclimate for 5–10 min . Each animal was monitored for 15 sec and thrashes ( changes in direction of bending at mid-body ) were counted . Embryos were fixed in methanol and 2% paraformaldehyde and permeabilized by freeze-thawing and then immuo-stained as described [85] . Adult animals were fixed with 4% paraformaldehyde and permeabilized with β-mercaptoethanol and collagenase IV treatment as described [86] . Antibodies used in this work included anti-MYO-3 ( 5–6 ) , anti-UNC-45 ( gift from Dr . Thorsten Hoppe ) and anti-UNC-54 ( 28 . 2 , gift from Dr . Jose Barral ) [87 , 88] and secondary DyLight 488 , DyLight 549 or DyLight 633 anti-mouse or anti-rabbit antibodies ( Jackson Immuno Research ) . Embryos or adult animals expressing fluorescence reporters or tagged proteins were fixed with 4% paraformaldehyde . Treated samples were imaged using an Olympus Fluoview FV1000 or an LEICA DM5500 confocal microscope with 488 or 549 or 633 nm laser lines for excitation or with LEICA DFC360FX camera . Otherwise , treated samples were imaged using an LEICA M165FC stereomicroscope with QIMAGINE Exi blue camera . The number of bright foci of age-synchronized animals expressing Q35::YFP was counted using an LEICA M165FC stereomicroscope . Age-synchronized animals were collected and lyzed in SDS sample buffer ( 95°C for 10 min ) . Samples were separated by SDS-PAGE and analyzed by western blot ( LF PVDF membrane ) , using primary anti-tubulin ( Sigma ) and anti-GFP ( Enco Scientific ) and secondary DyLight 488 and DyLight 549 , anti-mouse and anti-rabbit antibodies , respectively ( Jackson Immuno Research ) . Membranes were imaged using the ChemiDoc MP Imaging System ( BioRad ) .
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Molecular chaperones protect proteins from misfolding and aggregation . In multi-cellular organisms , the composition and expression levels of chaperones vary between tissues . However , little is known of how such differential expression is regulated . We hypothesized that the cellular differentiation that regulates the cell-type specific expression program may be involved in establishing a cell-type specific chaperone network . To test this possibility , we addressed the myogenic commitment transcription factor HLH-1 ( CeMyoD ) that converts embryonic cells to muscle cells in Caenorhabditis elegans . We demonstrated that HLH-1 regulates the expression of muscle chaperones during muscle differentiation . Moreover , we showed that HLH-1-dependent expression of chaperones is required for embryonic development and muscle function . We propose that cellular differentiation results in cell-specific differences in the chaperone network that may be detrimental in terms of the susceptibility of neurons and muscle cells to protein misfolding diseases .
|
[
"Abstract",
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"Discussion",
"Methods"
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2016
|
A Differentiation Transcription Factor Establishes Muscle-Specific Proteostasis in Caenorhabditis elegans
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Men who have sex with men ( MSM ) have differences in immune activation and gut microbiome composition compared with men who have sex with women ( MSW ) , even in the absence of HIV infection . Gut microbiome differences associated with HIV itself when controlling for MSM , as assessed by 16S rRNA sequencing , are relatively subtle . Understanding whether gut microbiome composition impacts immune activation in HIV-negative and HIV-positive MSM has important implications since immune activation has been associated with HIV acquisition risk and disease progression . To investigate the effects of MSM and HIV-associated gut microbiota on immune activation , we transplanted feces from HIV-negative MSW , HIV-negative MSM , and HIV-positive untreated MSM to gnotobiotic mice . Following transplant , 16S rRNA gene sequencing determined that the microbiomes of MSM and MSW maintained distinct compositions in mice and that specific microbial differences between MSM and MSW were replicated . Immunologically , HIV-negative MSM donors had higher frequencies of blood CD38+ HLADR+ and CD103+ T cells and their fecal recipients had higher frequencies of gut CD69+ and CD103+ T cells , compared with HIV-negative MSW donors and recipients , respectively . Significant microbiome differences were not detected between HIV-negative and HIV-positive MSM in this small donor cohort , and immune differences between their recipients were trending but not statistically significant . A larger donor cohort may therefore be needed to detect immune-modulating microbes associated with HIV . To investigate whether our findings in mice could have implications for HIV replication , we infected primary human lamina propria cells stimulated with isolated fecal microbiota , and found that microbiota from MSM stimulated higher frequencies of HIV-infected cells than microbiota from MSW . Finally , we identified several microbes that correlated with immune readouts in both fecal recipients and donors , and with in vitro HIV infection , which suggests a role for gut microbiota in immune activation and potentially HIV acquisition in MSM .
Men who have sex with men ( MSM ) comprise over half of all people living with HIV in the United States and accounted for 67% of new U . S . infections in 2016 [1] . Prevention and treatment in the MSM population is of high priority in the effort to eradicate HIV/AIDS in the U . S . Identifying novel biological factors that potentially impact transmission and/or disease in MSM could open opportunities for unique prevention and treatment strategies . Recent studies have found that a distinct gut microbiome composition is found in MSM when compared with heterosexual men ( men who have sex with women , MSW ) even in the absence of HIV infection [2–4] . Interestingly , several studies have shown that high-risk HIV-negative MSM also exhibit immune differences , such as higher blood T cell activation [5] , increased endotoxemia [6] , and increased T cell pro-inflammatory cytokine production in colon mucosa [3] , when compared with HIV-negative MSW . Given that the gut microbiome plays a significant role in shaping the immune system [7] , it is possible that the gut microbiome differences observed in HIV-negative MSM may be a driving factor of increased immune activation in this population . Subtler microbiome differences have also been linked with chronic HIV infection itself when controlling for MSM [2 , 4 , 8] , and previous work from our group has shown that these subtle differences are associated with stronger stimulation of immune cells in vitro [8] . How HIV-associated microbiome differences impact immune activation in vivo remains unknown . Establishing a direct impact of the gut microbiome on immune activation in HIV-negative and HIV-positive MSM may have important implications for transmission and disease , since vaginal immune activation in women has been associated with HIV acquisition risk [9–12] and T cell activation is well known to be a correlate of disease progression in HIV-positive individuals [13] . Whether the gut microbiome may be a risk factor for HIV transmission in MSM has not been investigated . Direct causation of immune activation by the microbiome in HIV-negative and HIV-positive MSM is difficult to demonstrate with human studies , which can be limited to correlational analyses to establish microbial-immune relationships . Human studies can also be confounded by factors such as diet , age , and lifestyle behaviors , all of which can be variable across individuals and populations and may influence both the microbiome and the immune system [14–17] . Deciphering microbiota-associated immune effects in HIV-positive MSM is further complicated by HIV itself , which can cause depletion of critical microbiome-interacting T cells [18 , 19] and stimulate immune activation through TLRs [20] . These challenges raise the need for an in vivo model to elucidate the immunological impacts of gut microbiota from HIV-negative and HIV-positive MSM . Mice have been crucial for describing the roles of gut microbiota in health and disease [21] , and offer a controlled system to isolate effects of live , active microbes on the immune system while excluding effects of lifestyle and HIV itself . In this study , we leveraged gnotobiotic ( germ-free ) mice to investigate the immunological impacts of whole fecal transplantation from HIV-negative MSW , HIV-negative MSM , and HIV-positive antiretroviral therapy ( ART ) -naïve MSM . We report that mouse fecal recipients recapitulated some of the microbiome differences associated with MSM , and that mouse recipients of feces from HIV-negative and HIV-positive MSM exhibited higher gut T cell activation than recipients of HIV-negative MSW . We extended our findings from the mouse model to an in vitro HIV infection model , and found that stimulation of primary human lamina propria cells ( LPCs ) with isolated fecal microbiota from either HIV-negative or HIV-positive MSM promoted HIV infection in cell culture . These results demonstrate the connection between gut microbiota and immune phenotypes observed in MSM , which may have implications for HIV acquisition and disease .
Previous studies have reported higher blood CD4+ and CD8+ T cell activation and higher levels of inflammatory cytokine producing colonic CD8+ T cells in HIV-negative MSM compared with HIV-negative MSW [3 , 5 , 6] . To confirm these findings in an independent cohort , we analyzed blood T cell phenotypes in 18 HIV-negative MSW and 19 HIV-negative MSM , and included 13 HIV-positive untreated MSM as controls since immune activation is well known to be increased with HIV infection [13 , 22 , 23] ( S1A Table ) . Increased frequencies of CD38 HLADR expressing CD8+ T cells , but not CD4+ T cells , were found in the blood of HIV-negative MSM compared with HIV-negative MSW ( Fig 1A–1C ) . As expected , HIV-positive MSM had the highest levels of blood T cell activation . Expression of CD69 on peripheral blood T cells was also measured ( S1A and S1B Fig ) , and frequencies of CD69+ CD4+ T cells trended higher for HIV-negative MSM and HIV-positive MSM than HIV-negative MSW , though this did not reach statistical significance . Stimulated T cells were analyzed for intracellular TNF-α and IFN-γ expression , and significantly higher frequencies of inflammatory cytokine producing T cells were observed in HIV-positive , but not HIV-negative , MSM when compared with HIV-negative MSW ( S1C and S1D Fig ) . Finally , a lower CD4/CD8 T cell ratio in the blood has been previously reported for high-risk HIV-negative MSM [6] , but was not reproduced in our cohort ( S1F Fig ) . The CD4/CD8 T cell ratio was expectedly decreased in HIV-positive MSM who were not receiving antiretroviral treatment . Gut mucosal T cell activation plays an important role in HIV replication and disease [24] . We therefore evaluated expression of the mucosal homing marker CD103 ( also known as integrin αEβ7 ) [25] on blood T cells . Frequencies of CD103+ CD4+ T cells were significantly higher and frequencies of CD103+ CD8+ T cells trended higher in HIV-negative MSM compared with HIV-negative MSW ( Fig 1D and 1E ) . CD103+ CD8+ T cell , but not CD4+ T cell frequencies were higher in HIV-positive MSM than in HIV-negative MSW . No significant differences were observed in frequencies of CD103+ T cells between HIV-negative and HIV-positive MSM . Frequencies of CD103+ CD8+ T cells significantly correlated with frequencies of CD38+ HLADR+ CD8+ T cells ( Fig 1F ) , while expression of HIV coreceptor CCR5 [26]–which was not significantly different across groups ( S1E Fig ) –significantly correlated with frequencies of CD103+ CD4+ T cells ( Fig 1G ) . Taken together , previous findings of higher immune activation in HIV-negative MSM compared with HIV-negative MSW are confirmed here in our cohort , and our results additionally show an association between blood T cell activation and mucosal homing in MSW and MSM . Microbiome differences have been previously associated with MSM and HIV [2–4 , 8] , but the extent to which these differences drive immune activation in vivo is unclear . To directly assess the in vivo immunological effect of the gut microbiome from HIV-negative and HIV-positive MSM , we transplanted feces from human donors to gnotobiotic mice . Each mouse received a single gavage of feces from a unique human donor . Stool donors were 16 HIV-negative MSW , 19 HIV-negative MSM , and 12 HIV-positive ART-naïve MSM randomly selected from a previously described cohort [4] . Of these donors , 13 HIV-negative MSW , 17 HIV-negative MSM , and 9 HIV-positive MSM are represented in the above immune data ( Fig 1 , S1 Table ) . HIV-positive MSM donors had a median viral load of 101400 copies/ml with a median CD4 T cell count of 574 cells/μl ( S1 Table ) . Each donor was tested in a single mouse recipient , with the exception of 4 HIV-negative MSW , 8 HIV-negative MSM , and 4 HIV-positive MSM which were randomly chosen to be tested in 2–3 replicate mice . A subset of donors was also tested for fecal bacterial load ( 8 HIV-negative MSW , 12 HIV-negative MSM , 11 HIV-positive MSM ) , which was not found to be significantly different across donor groups ( Fig 2B ) , indicating that each recipient group did not receive a significantly higher or lower amount of bacteria in the fecal transplant . We performed 16S rRNA gene sequencing on donor fecal samples and fecal pellets from mouse recipients at 7 , 14 , and 21 days post-gavage . Since there was little variation in composition of the mice over time ( S2 Fig ) , we focused our analysis on the terminal timepoint . Consistent with previous reports [2 , 4 , 8] , unweighted UniFrac analysis showed that microbiome composition in the human donors ( large circles ) clustered distinctly by MSM and not HIV status ( Fig 2C ) . Although the overall composition shifted along PC1 following fecal transfer , the distinct clustering of MSW and MSM along the PC2 axis was replicated in the mouse recipients ( small circles ) , which are connected to their respective donors by lines ( Fig 2C ) . Six 16S rRNA sequence variants were identified to be significantly different ( with an FDR corrected p-value<0 . 1 ) between HIV-negative MSW and HIV-negative MSM recipients , 3 of which increased ( Desulfovibrio sp . , Holdemanella biformis , Howardella ureilytica ) and 3 of which decreased ( Clostridium sp . , Bacteroides uniformis , Flavonifractor sp . ) with MSM ( S2 Table ) . Five of six of these variants were also found to be significantly different between HIV-negative MSW and HIV-negative MSM donors ( S2 Table ) . Holdemanella biformis ( formerly Eubacterium biforme ) and Bacteroides uniformis have also previously been described to be different with MSM [4 , 8] . In contrast , no statistically significant differences ( FDR p<0 . 1 ) in variant abundance were detected between HIV-negative and HIV-positive MSM donors or recipients , and previously reported bacteria differing with HIV in analyses of larger cohorts [2 , 4] were not observed in this smaller donor sample size ( S3 Table ) . These data suggest that MSM-associated microbiome differences are readily transferred to mice through fecal transplant , while transfer of subtler HIV-associated differences may require an increased sample of donors . The natural gut microbiome in mice is compositionally different from that in humans [27] , therefore changes in relative abundance of microbes less or better adapted to the mouse gut were expected to occur following fecal transfer . To characterize microbiome shifts following colonization of mice , we identified bacterial families that significantly increased or decreased in relative abundance from donors to recipients . When analyzing all groups together ( HIV-negative MSW , HIV-negative MSM , HIV-positive MSM ) , 25 families significantly changed ( FDR p<0 . 1 ) as determined by nonparametric t-test comparing donors to recipients ( S4 Table ) . These consisted of 19 families that decreased and 7 families that increased in relative abundance in recipients compared with donors . When stratifying the analyses by group , differences between donors and recipients for 20/25 families maintained consistent trends within each group , and differences for 11/25 families maintained statistical significance within each group ( S4 Table ) . A striking donor-to-recipient change was the relative abundance of Prevotellaceae , which was significantly higher in MSM compared with MSW ( Fig 2C ) [2–4] , and decreased in abundance for all groups following transfer ( S4 Table ) . Taxa bar charts showing donors and recipients grouped separately ( Fig 2D ) , or donors and their respective recipients side-by-side ( S3 Fig ) , demonstrate the overall loss of Prevotellaceae in mice . Though Prevotellaceae was undetectable in almost all mouse recipients of HIV-negative and HIV-positive MSM donors , it maintained a strong presence in the two mouse recipients of Prevotellaceae-rich HIV-negative MSW donors ( Fig 2D , S3 Fig ) . One reason that there may be colonization differences in MSW versus MSM recipients is the presence of different species or strains of Prevotella . We thus sought to explore whether different sequence variants within the Prevotella genus showed different colonization patterns . In the two mice that Prevotella successfully colonized , we identified only three Prevotella sequence variants to be present and all were classified as Prevotella copri ( S4A Fig ) . Two out of three P . copri variants were of the highest abundance in MSW donors ( S4B Fig ) , and increased in relative abundance from donors to mice . The third variant was the dominant and most abundant Prevotella sequence in both MSW and MSM donors , but only colonized recipients of MSW . Six other P . copri sequence variants that were present in at least 20% of MSM donors were identified , and only three of these could be found in Prevotella-rich MSW . None of these other six sequence variants were detectable in mouse recipients ( S4 Fig ) . To investigate the ability of Prevotella to colonize mice in the absence of competing microbes , we gavaged gnotobiotic mice ( n = 3 ) with a monoculture of P . copri ( DSMZ 18205 ) or with a monoculture B . uniformis ( ATCC 8492 ) for comparison ( Fig 2D ) . By 16S gene sequence , the P . copri monoculture was determined to be the same variant as P . copri 3 found in fecal donors and their recipients . After 21 days of colonization , sequencing showed that P . copri was still present in feces of 2/3 mice , while B . uniformis was present in 3/3 mice ( Fig 2D ) . Thus , three P . copri variants were able to colonize mice , with two of these variants being at a higher relative abundance in Prevotella-rich MSW than in MSM . The third variant , which was the dominant variant in both MSW and MSM , could only successfully colonize mice in pure culture or in the context of an MSW microbiome . Since MSM have more Prevotella than MSW , we next investigated whether the inability of Prevotella to colonize mouse recipients of MSM resulted in a larger magnitude donor-to-recipient compositional shift for MSM . Unweighted Unifrac distance , a measurement of relative compositional difference , between each donor and their recipient was calculated . For donors with replicate mouse recipients , a representative mouse was randomly selected . Donor-recipient distances were not found to be significantly different across groups , indicating the overall composition of each donor group was altered on average by the same magnitude after transfer ( S5A Fig ) . The percentages of unique sequence variants identified in each donor that were present in their mouse recipient were also not significantly different across groups , indicating equal colonization fidelity ( S5B Fig ) . Despite the loss of taxa that differed with MSM following transfer , differences in specific microbes were recapitulated in mouse recipients to maintain distinct MSW and MSM compositions . Any immunological differences between recipient groups would therefore be associated with these compositional differences . To investigate the immunological effect of the MSM and HIV-associated microbiome on mouse recipients , mice were sacrificed 21 days post gavage , and ileum , colon , and mesenteric lymph nodes were evaluated for markers of T cell activation . Due to lower cell recovery , only colons from a subset of mice ( 8 HIV-negative MSW , 10 HIV-negative MSM , 9 HIV-positive MSM ) yielded enough cells for analysis by flow cytometry . Ileum tissues from all mice were analyzed and are highly relevant to HIV infection due to the small intestine’s abundance of Th17 cells [28] , which are targets of HIV infection and play an important role in disease [18] . CD69 and CD103 were used to measure gut T cell activation , and though lowly expressed in the blood [29] , these are relevant markers in the gut , and are used to define tissue-resident memory T cells retained in gut tissue [30 , 31] . For stools that were tested in replicate mice , immune data from one replicate was used for each stool . In the ileum , frequencies of CD69+ CD8+ T cells were found to be significantly higher in mouse recipients of HIV-negative MSM compared with mouse recipients of HIV-negative MSW ( Fig 3B ) . Frequencies of CD103+ T cells were significantly elevated for both CD4+ and CD8+ T cells in the ileum of recipients of HIV-negative MSM ( Fig 3C and 3D ) . Interestingly , ileum frequencies of CD69+ or CD103+ T cells were not significantly different between recipients of HIV-negative and HIV-positive MSM , and only CD103+ CD4+ T cells were significantly higher in recipients of HIV-positive MSM compared with recipients of HIV-negative MSW ( Fig 3D ) . Finally , stool recipients that were successfully colonized with Prevotella did not display noticeably different levels of immune activation compared to the MSW group median ( S7B Fig ) . In colon tissue , frequencies of CD69+ CD4+ T cells were significantly higher for recipients of HIV-negative MSM than recipients of HIV-negative MSW ( Fig 3E ) . Recipients of HIV-positive MSM did not statistically differ from recipients of HIV-negative MSM or HIV-negative MSW in colonic T cell activation , but did trend higher for frequencies of CD69+ CD8+ and CD4+ T cells , and CD103+ CD8+ T cells , compared with either HIV-negative group ( Fig 3E , S6 Fig ) . Statistical power in detecting differences in the colon may have been limited by a small sample size and a high variance of immune measures . We therefore examined mesenteric lymph nodes ( mLN ) , which were analyzed for all mouse recipients , as a proxy of gut immune phenotypes since the mLN drain ileum and colon tissues [32] . In the mLN , mouse recipients of HIV-positive MSM displayed significantly higher frequencies of effector memory ( Tem ) CD4+ T cells ( CD62L- , CD44+ ) than recipients of HIV-negative MSW ( Fig 4A ) . Furthermore , frequencies of CD4+ Tem in the mLN significantly correlated with frequencies of CD69+ CD4+ T cells in the colon ( Fig 4B ) , indicating mLN phenotypes were representative of immune readouts in colon tissue . In mLN of monocolonized mice , which were also examined at 21 days post gavage , CD4+ Tem frequencies were within the range detected in stool recipients , and did not differ between mice gavaged with B . uniformis and mice gavaged with P . copri ( S7A Fig ) . Overall , mouse recipients displayed a significant MSM-associated effect in immune activation in the gut . Recipients of MSM also tended to have higher variation in T cell measures , with CD103+ CD4+ T cell frequencies in the ileum ( Fig 3D ) and CD69+ CD4+ T cell frequencies in the colon ( Fig 3E ) being significantly different in variance as determined by F test between HIV-negative MSM and HIV-negative MSW . Despite the lack of a significant HIV-associated effect , immunological differences between MSW and MSM recipients were enough to drive significant immune correlations between donors and recipients , including a correlation between frequencies of recipient ileum CD69+ CD8+ T cells and frequencies of donor blood CD38+ HLADR+ CD8+ T cells ( S8A Fig ) , and a correlation between frequencies of recipient colon CD69+ CD4+ T cells and frequencies of HIV-negative donor blood CD103+ CD4+ T cells ( S8B Fig ) . These correlations highlight immunological similarities between donors and their recipients . Elevated markers of gut mucosal damage have been reported for MSM and correlated with MSM-associated microbiota [3 , 6] , and are well known to be associated with HIV infection [33] . To determine if bacteria from the fecal transfer directly caused intestinal damage , ileum and colon tissue samples from 5 HIV-negative MSW , 7 HIV-negative MSM , and 6 HIV-positive MSM mouse recipients were analyzed for histopathology . Tissue health and epithelial integrity was determined to be within normal limits for all mice examined ( Fig 5A ) . Each tissue analyzed was graded with an overall inflammation score on a scale of 1–4 [34] , and all tissues were assigned the same minimum inflammation rating of 1 . In support of this , myeloperoxidase concentrations ( measured in 12 HIV-negative MSW , 11 HIV-negative MSM , and 11 HIV-positive MSM recipients ) were not different across groups in the colon ( Fig 5B ) . Levels of soluble CD14 ( sCD14 ) in the blood , a marker of monocyte activation in response to LPS [35] and bacterial translocation across the gut barrier [33] , was measured in 11 HIV-negative MSW , 15 HIV-negative MSM , and 9 HIV-positive MSM recipients , and was also not found to be significantly different across groups ( Fig 5C ) . Lack of signs of barrier damage suggest that transfer of microbiota from HIV-negative or HIV-positive men were not sufficient to cause gut tissue injury in mice ( at least within 3 weeks of colonization ) , and that barrier breakdown was not necessary for microbiota from MSM to promote gut T cell activation . Recapitulation of microbial and immune differences in mouse recipients supports a link between microbiome composition and immune activation in MSM . Microbial-immune correlations consistent across donors and recipients would further strengthen this link . We therefore correlated the relative abundance of gut microbes in donors and recipients with their respective immune data ( S5 and S6 Tables ) . Only immune data significantly different with MSM in either donors or recipients were selected for analyses , since only MSM-associated microbiome differences were detectable in this cohort . Frequencies of blood CD103+ CD8+ T cells in donors , though not significantly different with MSM , were additionally selected for analysis due to their relevance to the gut . Correlations were computed with both the full donor group , as well as with HIV-negative donors only , since HIV may independently drive immune activation in HIV-positive MSM and confound microbial correlations . All correlations that were and were not significant in donors and in mice are shown in tables S5 ( donors ) and S6 ( recipients ) . After comparing significant correlations across these datasets , we identified 8 microbes that correlated with at least one donor and one recipient immune measurement ( Table 1 ) , with 3 of these being negative and 5 of these being positive correlates . Out of these 8 microbes , 5 significantly correlated using the full donor cohort , while 3 significantly correlated using only HIV-negative donors . Two microbes , Bacteroides uniformis and Howardella ureilytica , significantly differed in relative abundance with MSM in both donors and recipients ( S2 Table ) , and also significantly correlated with immune measurements in both donors and recipients . Though few of the shared microbe-immune correlates were statistically significant with FDR correction , consistency of correlations across humans and mice suggest biological significance , and provide further evidence that immune activation in MSM is influenced by the gut microbiome . T cell activation has been correlated with HIV viral load [13] , and associated with HIV transmission in women [36] . We therefore investigated whether microbiota from MSM could promote HIV infection in vitro . Fecal bacterial communities ( FBCs ) were isolated from stools of 12 HIV-negative MSW , 15 HIV-negative MSM , and 9 HIV-positive MSM by separating whole intact bacteria in stool from debris using Histodenz columns as previously described [8] . All donors of stool used for FBC isolation are represented in the PBMC immune phenotyping data ( Fig 1 ) , while FBCs from 7 HIV-negative MSW , 15 HIV-negative MSM , and 5 HIV-positive MSM were also used as donors in the fecal transplant experiments . HIV-positive individuals used for FBC isolation had a median viral load of 47650 copies/ml and a median CD4 T cell count of 577 cells/μl ( S1 Table ) . Primary human lamina propria cells ( LPCs ) were stimulated by isolated FBCs , infected with HIVbal , and intracellular HIVgag antigen expression was measured after five days . We found that LPCs stimulated with FBCs from HIV-negative and HIV-positive MSM had higher frequencies of HIV-infected cells compared with LPCs stimulated with microbiota from HIV-negative MSW ( Fig 6A and 6B ) . LPCs stimulated with FBCs from HIV-negative and HIV-positive MSM displayed significantly elevated CD8+ T cell activation at the end of infection ( Fig 6C ) , and frequencies of HIV-infected cells significantly correlated with both CD4+ and CD8+ T cell activation of stimulated LPCs ( Fig 6D and 6E ) . FBCs from 7 HIV-negative MSW , 11 HIV-negative MSM , and 8 HIV-positive MSM used in this infection assay were also previously used to stimulate PBMC in vitro [8] , and frequencies of HIV-infected cells induced by these FBCs significantly correlated with activation levels of peripheral blood CD4+ and CD8+ T cells stimulated by these same FBCs found previously ( S8B and S8C Fig ) . 16S rRNA gene sequencing of FBCs showed that the compositional distinction between MSW and MSM was maintained following bacterial isolation ( S9A and S9C Fig ) . Unweighted UniFrac distances between donor samples and their isolated FBCs were not significantly different across groups ( S9B Fig ) , indicating the average magnitude of stool-FBC compositional shifts were consistent between groups . Specific bacteria that differed with MSM and with HIV in FBCs , and bacteria that significantly changed from stool to FBCs , were previously described [8] , and are not presented here . Infection and T cell activation levels trended higher for cells stimulated with HIV-positive MSM FBCs than cells stimulated with HIV-negative MSM FBCs , though these differences were not statistically significant . Finally , six microbes that significantly correlated with in vitro HIV infection also correlated with fecal transplant donor and/or recipient immune measurements ( Table 1 ) . Interestingly , two sequence variants of H . biformis correlated with in vitro infection , with one significantly correlating with donor blood T cell activation and the other significantly correlating with recipient gut T cell activation . Significant and non-significant correlations between all 16S sequence variants in FBCs with in vitro HIV infection are shown in S7 Table . Consistencies were therefore observed between the in vivo transplant system and the in vitro assays . These data support the findings from the mouse model , and suggest that the gut microbiome in HIV-negative and HIV-positive MSM could impact HIV infection .
Immune differences previously associated with MSM were reproduced in our cohort of fecal donors . We showed elevated blood frequencies of activated CD38+ HLADR+ CD8+ T cells in HIV-negative MSM compared with HIV-negative MSW as previously described [5] , as well as increased frequencies of CD103+ CD4+ T cells in HIV-negative MSM , which to our knowledge , is a novel finding . Frequencies of CD103+ CD4+ T cells also correlated with frequencies of CCR5+ CD4+ T cells , suggesting an association between gut homing and CCR5 expression in MSM . Other previously reported immune phenotypes in MSM , such as increased frequencies of gut mucosal Th17 cells and IFN-γ+ TNF-α+ CD8+ T cells [3] , increased endotoxemia , and lower blood CD4/CD8 ratios [6] were either not observed or not measured in our cohort . A limitation of our study was the unavailability of immune data from gut tissues in our donors , which would have indeed strengthened associations between our donors and mice . However , our observations in mice are well supported by previous findings of gut T cell activation in MSM [3] . Overall , immune differences associated with MSM in our study were subtle and observed in a small sample size , though the magnitude of these differences reflects what others have found . The subtlety of these differences is also unsurprising , since our cohort of high-risk MSM were healthy individuals without disease . Taken together , the blood T cell profiling presented here has reproduced and expanded on previous knowledge of immune phenotypes associated with MSM , and further emphasize the importance of controlling for MSM in immunological analyses of HIV-positive populations . Microbiome differences previously associated with MSM were also replicated in our donor cohort ( Fig 2C ) , including increases in Prevotellaceae , decreases in Bacteroidaceae [2–4] , and changes in specific bacterial species such as Holdemanella biformis and Bacteroides uniformis ( S3 Table ) [4 , 8 , 37] . However , previously reported microbiome differences between HIV-negative and HIV-positive MSM , such as increased abundance of Turicibacter sanguinis with HIV [4 , 8] , were not observed in our cohort . Given these results , it was unsurprising that recipient mice reproduced microbiome differences associated with MSM , but showed no significant microbiome differences between recipients of HIV-negative and HIV-positive MSM . Immune activation differences in mouse recipients largely reflected the microbiome composition , with an apparent significant increase in T cell activation associated with recipients of MSM . Immunological differences between HIV-negative and HIV-positive MSM recipients were less clear . Though CD4+ T cell activation in the colon trended higher for recipients of feces from HIV-positive MSM compared with HIV-negative MSM ( Fig 3E ) , this did not reach statistical significance . These trends reflect our previously published results showing FBCs from HIV-positive MSM could promote higher in vitro T cell activation than FBCs from HIV-negative MSM [8] , and suggest that a larger sample size of donors is needed to investigate immunological differences between mouse recipients of feces from HIV-negative and HIV-positive MSM . However , a small sample size may only partially explain why a significant effect of HIV-associated microbiota was not observed in this study , either in mice or in the in vitro infection experiments . In mice , it is possible that HIV-associated microbiota of immunological importance may not have colonized . Furthermore , loss of epithelial integrity is a hallmark of HIV infection and was not evident in these mice . Modeling barrier breakdown in mouse recipients may therefore reveal effects of HIV-associated microbiome differences in the context of HIV-induced disease . In the in vitro infection experiments , one finding from our previous work was that differences between HIV-negative MSW and HIV-negative MSM in in vitro activation of CD4+ and CD8+ T cells were detected when stimulations were performed with non-autoclaved FBCs but not autoclaved FBCs , whereas the differences in HIV-positive versus HIV-negative MSM were strongly evident with the autoclaved FBCs . Autoclaving was done to ensure that bacteria were killed and that no sporadic growth of antibiotic resistant , aerotolerant bacteria occurred . However , autoclaving could have potentially denatured immune-modulatory compounds . The in vitro infection data from this study used non-autoclaved FBCs . Taken together these results suggest that there are differences in the molecular mechanisms of immune activation in HIV-positive and HIV-negative MSM , with those in HIV-positive MSM being more driven by molecular factors that are heat-tolerant . T cell activation in stool donors and recipients were detected with different markers ( CD38 and HLADR in donors , and CD69 and CD103 in recipients ) in different compartments ( blood and gut ) , but these markers may have identified related cell populations commonly influenced by gut microbes . In support of this , gut T cell activation in mice significantly correlated with blood T cell activation in donors , and the same bacteria consistently correlated with both donor and mouse immune measurements . Several of these microbial correlates have been previously associated with disease and/or known to have immune-modulating potential . This includes Holdemanella biformis ( formerly known as Eubacterium biforme ) , which is increased with MSM in donors and recipients , and has been previously associated with stimulation of inflammatory cytokine production and correlated with T cell activation in vitro [8 , 38] . Bacteroides uniformis , a Treg and IL10 inducer [39] that has been found to be reduced in patients with Crohn’s disease [40] , is also reduced with MSM in our donors and recipients . Akkermansia muciniphila , a mucolytic bacteria associated with health and disease depending on context , has been found to be reduced in patients with ulcerative colitis and Crohn’s disease [41] , and was negatively correlated with CD4+ T cell activation in recipient colons and mucosal homing CD8+ T cells in donor blood . Finally , Desulfovibrio piger , a sulfate-reducing bacteria associated with inflammatory bowel disease [42] , was positively correlated with gut homing T cells in recipients and donors . Thus , bacteria correlated with immune function in our dataset is consistent with previous findings . Organisms identified in these correlations are ideal candidates for further investigation of their immune-modulating properties in HIV-negative and HIV-positive MSM . Transfer of the microbiome from human donors to mice was imperfect , as significant differences between MSW and MSM were not reproduced in the mice . Chief among these was Prevotella , which was lost from recipients of MSM but not recipients of MSW . Though two of the P . copri sequence variants identified may be unique features of Prevotella-rich MSW that are better adapted for mice , the inability of the third variant to colonize mice in the context of an MSM microbiome suggests that the broader community structure , which is different between MSM and Prevotella-rich non-MSM [4] , influences Prevotella colonization . Since Prevotella has been associated with inflammation in other studies , including being positively correlated with gut immune activation in HIV-positive individuals [43] , and being associated with rheumatoid arthritis [44] , successful colonization in recipients of MSM stool may have driven an even larger effect of immune activation . Alternatively , Prevotella may not be a major influencer of immune activation , since it did not induce noticeably higher activation in either monocolonized mice or Prevotella-rich MSW fecal recipients . Additionally , Prevotella variants were also not identified as significant correlates with immune measurements in donor blood . Another intriguing hypothesis is that Prevotella may only promote inflammation in a diseased state . Indeed , in mice with DSS-induced colitis , the presence of P . copri ( identical to P . copri variant 3 in this study ) led to more severe inflammation [45] . Inducing colitis to mimic gut disease during HIV infection in mouse recipients of Prevotella-rich MSW may reveal similar effects . Importantly , these results demonstrate that despite prominent microbiome differences like Prevotella abundance not being reproduced in mouse recipients , compositional distinction between MSW and MSM was maintained in mice by successful transfer of critical immune-modulating bacteria . The ability of microbiota from HIV-negative and HIV-positive MSM to promote HIV infection in vitro suggests that the gut microbiome composition could contribute to HIV infection and disease progression in MSM . There is evidence that the vaginal microbiome is a risk factor for HIV transmission in women: vaginal bacteria modulate immune activation in vaginal tissue [9] , bacterial vaginosis has been linked to vaginal HIV transmission [11 , 12] , and specific microbes in the vaginal microbiome have been associated with inflammation and increased HIV acquisition [36] . Thus , it is possible that the gut microbiome may also contribute to risk in MSM by promoting immune activation in gut tissues . Increased frequencies of CD69+ and CD103+ T cells in mouse recipients of MSM suggest there are more tissue-resident memory CD4+ T cells in the gut [31] , and memory CD4+ T cells are known to be the primary targets of HIV infection [46] . Though these cells were assessed in the ileum and colon rather than the rectum , it is clear they are driven by the gut microbiome–which was linked to both rectal T cell activation and rectal SHIV transmission in macaques [47] . Furthermore , gut microbes that correlated with T cell measures in the ileum and colon of mouse recipients also correlated with in vitro HIV infection . Therefore , microbes that influence T cell activation along the length of the gut likely also impact HIV infection at the specific site of transmission . These findings are strong rationale for conducting longitudinal studies examining the association between gut microbiome composition and HIV transmission in populations of high-risk MSM . In conclusion , this study provides evidence of a direct link between the gut microbiome and immune activation observed in high-risk MSM , by demonstrating that both microbiome and immune phenotypes in MSM donors are transferrable to mouse recipients through fecal transplantation . Mice were receptive of colonization by key immune-influencing microbes that induced immunological differences associated with MSM donors , suggesting the gut microbiome influences immune activation in MSM .
Stool samples were obtained from HIV-negative MSW , high-risk HIV-negative MSM , and HIV-positive MSM not on antiretroviral therapy . Male HIV-positive individuals enrolled in the study were determined to be MSM using a behavioral questionnaire . High-risk MSM were recruited from a high-risk cohort assembled for a study of a candidate HIV-1 preventative vaccine [48] . Designation of high-risk was according to a number of different behaviors including 1 ) a history of unprotected anal intercourse with one or more male or male-to-female transgender partners 2 ) anal intercourse with two or more male or male-to-female transgender partners and 3 ) being in a sexual relationship with a person who has been diagnosed with HIV . All enrolled individuals live in metropolitan Denver . Other inclusion criteria used were: 18–70 years old , body mass index ( BMI ) between 21–29 mg/kg2 and weight stable for at least 3 months; for HIV-positive individuals , <10 days of ART treatment at any time , or previously on ART but off treatment for the previous 6 months , prior to stool and blood collection; liver and kidney function tests within normal range . Exclusion criteria used were: weight <110 pounds; received antibiotics within the prior 90 days; active gastrointestinal disease; history of bowel resection . All subjects used in this study were previously characterized for diet and sexual behavior as part of a larger cohort; diet or any particular sexual behavior that we measured were not identified as driving factors of the most prominent microbiome differences between MSM and MSW [4] . Written informed consent was obtained from healthy HIV-negative and HIV-positive individuals for use of stool . The study protocol was approved by the Colorado Multiple Institution Review Board ( COMIRB No: 14–1595 ) . All subjects were adults . Mice were handled in accordance with the recommendations in the National Institutes of Health Guide for the Care and Use of Laboratory Animals and protocols were approved by the University of Colorado Institutional Animal Care and Use Committee Permit Number 00097 . Primary human lamina propria cells were collected from otherwise discarded tissues from gut resection surgery , and was determined to not be human subject research under protocol number 14–1184 approved by the University of Colorado Multiple Institutional Review Board . Tissues were obtained from anonymous adult patients who were not asked for consent . PBMC were isolated from patient blood by Ficoll-Paque ( GE ) , and cryopreserved and stored in liquid nitrogen before analysis . PBMC were thawed , and 5 x 105 cells were stained for 30 min at 4° C with the following antibodies: CD3-APC-Cy7 ( OKT3 , Biolegend ) , CD4-PerCP-Cy5 . 5 ( OKT4 , Biolegend ) , CD8-APC ( SK1 , Biolegend ) , CD38-BV421 ( HIT2 , Biolegend ) , CD69-BV510 ( FN50 , Biolegend ) , HLADR-FITC ( L243 , Biolegend ) , CD103-PE ( BerACT8 , Biolegend ) , CCR5-PE-Cy7 ( J418F2 , Biolegend ) . Cells were then washed in FACS buffer and fixed in 1% paraformaldehyde before being acquired on a BD FACS Canto II . 1 x 106 PBMC were stimulated with a PMA/ionomycin cell stimulation cocktail ( eBioscience ) , and treated with a protein transport inhibitor cocktail ( eBioscience ) for 4 h at 37° C , 5% CO2 . Cells were then stained for 30 min at 4° C with the following antibodies: CD3-APC-Cy7 ( OKT3 , Biolegend ) , CD4-PerCP-Cy5 . 5 ( OKT4 , Biolegend ) , CD8-APC ( SK1 , Biolegend ) . Cells were washed and treated with fix/perm buffer ( eBioscience ) for 30 min at 4° C , before being stained for intracellular cytokines for 30 min at 4° C with the following antibodies: IFN-γ-PE ( 4SB3 , Biolegend ) , TNFα-APC-Cy7 ( MAb11 , Biolegend ) . Cells were then washed in FACS buffer and fixed in 1% paraformaldehyde before being acquired on a BD FACS Canto II . 1 . 5 grams of frozen feces stored at -80° C for up to one year from each donor was thawed in an anaerobic chamber and homogenized in 3 ml of anaerobic PBS , using a syringe handle . Fecal solutions were then filtered through a 100 μm nylon filter into a 50 ml conical tube . Tubes were sealed before removing from the anaerobic chamber and transferred to the mouse facility within 1 hour of thawing . 200 μl of each fecal solution was used to gavage each mouse . 2 mg of stool from donors were homogenized in PBS , and bacteria were then isolated using two sequential rounds of sucrose density centrifugation . Isolated bacterial cells were stained with thiazol orange and propidium iodide , and acquired by a FACS Canto II ( BD ) flow cytometer in the presence of counting beads . Data were processed using Flowjo software , and the concentration of live bacterial cells per mg of stool was calculated . Germ-free C57/BL6 mice were purchased from Taconic and bred and maintained in flexible film isolator bubbles . Male mice between 6–8 weeks of age were gavaged with fecal solutions prepared from donor fecal samples and housed individually ( to ensure mice would not contaminate each other ) following gavage for 3 weeks in a Tecniplast iso-positive caging system , with each cage having HEPA filters and positive pressurization for bioexclusion . Feces were collected from mice at day 0 for 16S rRNA gene sequencing to confirm germ-free status . 16S sequencing of feces from day 7 and day 14 showed relatively little variation in composition from day 21 ( S2 Fig ) . Mice were euthanized at 21 days post gavage using isoflurane overdose and all efforts were made to minimize suffering . Blood from euthanized animals was collected using cardiac puncture and cells were pelleted in K2-EDTA tubes; plasma was then aliquoted and stored at -80° C . Data was combined from 10 batches of mice analyzed independently , with at least 4 mice per batch , and at least two donor groups represented in each batch . Ileum and colon tissues from mice at 21 days post gavage were collected for immune phenotyping and histology . Tissues were dissected length-wise and feces were washed away using PBS . 1–5 mm slices of ileum and colon closest to the cecum were taken from a subset of mice and fixed in 10% formalin and reserved for histology or ELISA . The remaining tissue was then washed in a PBS solution containing 1% EDTA for two 5 min intervals on a vortexer . Tissues were washed with PBS and strained through a 100 μm nylon filter in between intervals . Tissues were then washed for a third time in plain 1X PBS . Tissues were then minced using an octoMACs tissue dissociator ( Miltenyi ) and digested in 2 . 5 ml of a solution of complete RPMI ( 10% FBS , 1% PSG ) containing 1 mg/ml collagenase D type I ( Worthington Biotech ) at 37° C , 5% CO2 . Released cells were quenched with cold complete media , filtered through a 70 μm nylon filter and washed with complete media before staining for flow cytometry . 0 . 5–1 x 106 ileum and colon cells from each mouse were stained in FACS buffer for 30 min at 4° C with the following antibodies: CD3-PerCP-Cy5 . 5 ( 17A2 , Biolegend ) , CD4-FITC ( RM4-4 , eBioscience ) , CD8-BV510 ( 53–6 . 7 , Biolegend ) , CD69-PE-Cy7 ( h1 . 2F3 , eBioscience ) , CD103-PE-Dazzle-594 ( 2E7 , Biolegend ) . Mesenteric lymph node cells were additionally stained with CD44-AlexaFluor-700 ( IM7 , eBioscience ) , and CD62L-APC-eFluor780 ( MEL-14 , eBioscience ) . Cells were then washed with FACS buffer and fixed in 1% paraformaldehyde before being acquired on a BD LSRii flow cytometer . Colon samples that had less than 1 , 000 T cells were excluded . Plasma samples were thawed and diluted 1:10 before being assayed for sCD14 by ELISA ( R&D Systems ) according to the manufacturer’s instructions . Ileum and colon tissues cultured for 24 h at 37° C , 5% CO2 in complete RPMI were digested with CellLytic MT solution with proteinase inhibitor ( SIGMA ) , and assayed for myeloperoxidase concentrations by ELISA ( R&D Systems ) . ELISA plates were read using a Vmax Kinetic plate reader ( Molecular Devices ) . Tissue sections from the distal end of the ileum and proximal end of the colon were processed for histology and H&E stained . Scoring [34] was performed by a pathologist blinded to experimental conditions . Stool samples were collected by the patient , both on a sterile swab and with a sterile scoop within 48 hours of a clinic visit . Samples were stored immediately in a cooler with -20°C freezer packs . After delivery to the clinic , the swab was subsequently stored at -80° C to await DNA extraction . Isolation of fecal bacterial communites ( FBCs ) from stool was described previously [8] . Briefly , two grams of feces were homogenized in sterile PBS and filtered through a 100uM filter . Homogenate was then subjected to two density gradient centrifugations with 80% Histodenz ( Sigma ) . Bacterial layers were collected after each spin , visualized with a light microscope , and quantified by flow cytometry using a bead counting kit ( BD Biosciences ) . FBCs were stored at -80° C before use in in vitro assays . 16S rRNA targeted sequencing was conducted according to earth microbiome project standard protocols ( http://www . earthmicrobiome . org ) . DNA was extracted from donor stool swabs , mouse fecal pellets , and from a 250 μL aliquot of FBC isolates using the standard PowerSoil protocol ( QIAGEN ) . PCR amplification of the extracted DNA , along with water controls , was conducted with barcoded primers targeting the V4 region of the 16S rDNA gene ( 515F-806R; FWD:GTGCCAGCMGCCGCGGTAA; REV:GGACTACHVGGGTWTCTAAT ) . Amplified DNA was quantified using a PicoGreen assay ( Invitrogen ) so equal amounts of DNA from each sample could be pooled and cleaned using the UltraClean PCR Clean-up protocol ( Qiagen ) . The final DNA pool was sequenced using the Illumina MiSeq platform ( San Diego , CA ) using the V2 2x250 kit . Raw sequences were assigned to samples based on their barcodes using QIIME 2 . 6 [49] . The libraries were denoised and grouped by sequence variants using dada2 1 . 2 . 2 . Samples contained from 21 , 357 to 159 , 296 sequences; analyses that contained donor and mouse recipient feces were conducted on the standardized sequence number of 21 , 357 , analyses that contained FBC isolates and their original stool were conducted on the standardized sequence number of 21 , 812 , and analyses that contained mice monocolonized with P . copri and B . uniformis were conducted on the standardized sequence number of 31 , 812 –these numbers were determined as the minimum read number acquired for a single sample in each independent analysis . Sequence variants were classified taxonomically using the RDP classifier [50] trained on the greengenes 3_8 taxonomic database [51] . Principal Coordinates Analysis of unweighted UniFrac distance matrices , and rendering of taxa bar charts , were conducted using QIIME 2 . 6 . For immune correlations , comparisons of relative abundance between groups , and P . copri variant analysis , sequence variants not observed in at least 20% of the samples in each analysis were removed . Macroscopically healthy jejunum tissues from patients undergoing elective gut resection surgery were digested to release lamina propria cells ( LPCs ) . Briefly , tissues were trimmed of fat and the muscularis layer was removed using scissors . Trimmed tissues were incubated on a rocker with a 1 . 6 mM dithiolthreitol ( DTT ) PBS solution for 45 min at 37° C , and then with a 1 mM EDTA PBS solution for 60 min at 37° C . Tissues were then washed with PBS on a vortexer , minced using scissors , and incubated for three 45 min intervals with a digestion solution of complete RPMI ( 10% HS , 1% PSG ) containing 1 mg/ml collagenase D ( Sigma-Aldrich ) and 10 μg/ml DNase I ( Sigma-Aldrich ) . Released cells were collected and filtered through a 70 μm nylon filter after each digestion interval . Cells from each interval were pooled together , RBC lysed , and cryopreserved . LPCs were thawed in complete RPMI containing 10 μg/ml DNase I ( Sigma-Aldrich ) , and washed again with complete RPMI before plating . 5 x 105 LPCs were plated per well in a 96-well round bottom plate . Bacterial cells were added to specified wells at 5:1 bacteria:LPC ratio . HIVbal passaged in Molt4 T cells and quantified by qPCR were then added to each well at 107 HIV RNA copies/well . Cells were incubated at 37° C for 24 h to allow for infection , and then washed twice with complete RPMI to remove cell-free virus . Bacteria were added back to each well at a 5:1 ratio after washing , and cells were incubated for another 4 days at 37° C . LPCs were then stained with anti-CD3-APC-Cy7 , CD4-PerCP-Cy5 . 5 , CD8-APC , HLADR-FITC , CD38-BV421 , CD69-BV510 , and CCR5-PE-Cy7 . Cells were then washed and treated with fix/perm buffer ( eBioscience ) for 30 min at 4° C , and stained with anti-HIVgag-PE ( KC57 , Fisher ) for 1 h at 4° C . Cells were then fixed in 1% paraformaldehyde and acquired using a FACS Canto II flow cytometer ( BD Biosciences ) . Unstimulated , uninfected cells were used as controls to gate on HIVgag+ cells . Immune data were compared between groups using t-tests if data from both groups passed the D’Agostino and Pearson normality test , and Mann-Whitney tests if data from at least one group did not pass the normality test . All immune data were analyzed using Prism 7 ( Graphpad ) . Comparisons of bacterial relative abundances between groups were performed using non-parametric t-tests on non-transformed data . Spearman correlations were used for all correlation analyses . Replicate recipient mice were treated as independent observations for all microbiome comparisons and correlations . Corrected p-values were determined with the False Discovery Rate ( FDR ) technique of Benjamini and Hochberg . All statistical analyses involving 16S sequencing data were performed using QIIME 1 . 9 .
|
The communities of commensal microbes that colonize the human gut comprise the gut microbiome , which has been shown to play a significant role in shaping the immune system . Recent studies have reported a distinct gut microbiome composition in men who have sex with men ( MSM ) exhibiting HIV-risk behaviors when compared with low-risk men who have sex with women ( MSW ) , regardless of their HIV infection status . Whether these gut microbiome differences in high-risk MSM directly impact immune activation is important to understand since increased T cell activation is associated with increased HIV transmission risk and more severe disease . To test the immunological effect of the gut microbiome in MSM , we transplanted stool from HIV-negative MSW , HIV-negative high-risk MSM , and HIV-positive MSM to germ-free mice . DNA sequencing showed that specific microbiome differences associated with MSM were successfully engrafted in mice , and that these differences were associated with increased CD4+ and CD8+ T cell activation in the mice . These results provide evidence for a direct link between microbiome composition and immune activation in HIV-negative and HIV-positive MSM , and rationale for investigating the gut microbiome as a risk factor for HIV transmission .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
[
"blood",
"cells",
"hiv",
"infections",
"medicine",
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"sciences",
"immune",
"cells",
"microbiome",
"pathology",
"and",
"laboratory",
"medicine",
"immune",
"activation",
"pathogens",
"immunology",
"microbiology",
"retroviruses",
"viruses",
"immunodeficiency",
"viruses",
"rna",
"viruses",
"cytotoxic",
"t",
"cells",
"microbial",
"genomics",
"digestive",
"system",
"infectious",
"diseases",
"white",
"blood",
"cells",
"lentivirus",
"animal",
"cells",
"medical",
"microbiology",
"hiv",
"t",
"cells",
"microbial",
"pathogens",
"men",
"who",
"have",
"sex",
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"gastrointestinal",
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"people",
"and",
"places",
"cell",
"biology",
"anatomy",
"immunity",
"viral",
"pathogens",
"genetics",
"biology",
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"cellular",
"types",
"population",
"groupings",
"genomics",
"colon",
"sexuality",
"groupings",
"viral",
"diseases",
"organisms"
] |
2019
|
Gut microbiota from high-risk men who have sex with men drive immune activation in gnotobiotic mice and in vitro HIV infection
|
Buruli ulcer ( BU ) is a neglected tropical disease caused by Mycobacterium ulcerans . Usually BU begins as a painless nodule , plaque or edema , ultimately developing into an ulcer . The high number of patients presenting with ulcers in an advanced stage is striking . Such late presentation will complicate treatment and have long-term disabilities as a consequence . The disease is mainly endemic in West Africa . The primary strategy for control of this disease is early detection using community village volunteers . In this retrospective , observational study , information regarding Buruli ulcer patients that reported to one of the four BU centers in Bénin between January 2008 and December 2010 was collected using the WHO/BU01 forms . Information used from these forms included general characteristics of the patient , the results of diagnostic tests , the presence of functional limitations at start of treatment , lesion size , patient delay and the referral system . The role of the different referral systems on the stage of disease at presentation in the hospital was analyzed by a logistic regression analysis . About a quarter of the patients ( 26 . 5% ) were referred to the hospital by the community health volunteers . In our data set , patients referred to the hospital by community health volunteers appeared to be in an earlier stage of disease than patients referred by other methods , but after adjustment by the regression analysis for the health center , this effect could no longer be seen . The Polymerase Chain Reaction ( PCR ) for IS2404 positivity rate among patients referred by the community health volunteers was not systematically lower than in patients referred by other systems . This study clarifies the role played by community health volunteers in Bénin , and shows that they play an important role in the control of BU .
Buruli ulcer ( BU ) , caused by Mycobacterium ulcerans , is an emerging neglected tropical disease . It is the third most common mycobacterial disease after tuberculosis and leprosy in immuno-competent persons in Bénin . The disease has been reported in more than 30 countries worldwide , but the highest patient load is in West Africa [1]–[4] . Usually BU begins as a painless nodule , plaque or edema , ultimately developing into an ulcer . The high number of patients presenting with ulcers in an advanced stage is a major problem because treatment of advanced disease is complex and frequently has long-term disabilities as a consequence [5] , [6] . Late presentation to health care facilities is common and is influenced by practical matters such as travel costs , visits to traditional healers and the patient's perception of illness [7] , [8] . Treatment consists of antibiotic treatment using streptomycin and rifampicin for eight weeks combined with wound care till the lesion heals [4] , [9] . Lesions take a long time to heal; in a clinical trial on antibiotic treatment in Ghana , the median time to healing was 18 weeks for category I lesions . The median time to healing is larger for category II and III lesions - 30 weeks [10] . Surgery may be necessary . The size of the lesion was the main factor associated with surgery [11]–[13] . The World Health Organization ( WHO ) recommends early case detection and early treatment of the lesions for BU control . Early case detection is important because delayed presentation for medical treatment is correlated with evolution of pre-ulcerative lesions to the ulcerative form , increased risk of osteomyelitis , more extensive surgical intervention and skin grafting [14] , extended hospital admission and severe functional limitation [15]–[17] . Strategies used for early detection of BU patients are active case finding and education in the rural areas with the assistance of community health volunteers . Community health volunteers can be defined as lay individuals trained in a particular role of delivering curative or preventative care or control in their own community [18] . Community health volunteers have been shown to play an important role in controlling several endemic diseases such as onchocerciasis and dracunculiasis . To control onchocerciasis , the community health volunteers participated in ivermectin mass distribution . For dracunculiasis , they reported cases monthly [19]–[21] . In some African countries , community health volunteers contributed to the conduction of vaccine trials , and play important roles in the reduction of maternal , newborn and infant mortality as well as in the management of febrile convulsions [22]–[26] . In BU , very few studies have evaluated the role of community health volunteers . This study looks at the contribution of different actors in the current reference system in Benin , their influence on the stage of disease at presentation in the hospital and on the diagnostic confirmation rate of BU , using IS2404 PCR .
In Bénin , the National Program against Leprosy and Buruli ulcer ( PNLLUB ) is the official body that organizes and implements BU control . Each endemic area has a Center of Detection and Treatment of BU ( CDTUB ) in Bénin . In total , the program has four CDTUB respectively called A , B , C and D in this study to ensure anonymity . Detection teams are composed of two community health volunteers and two teachers in each endemic village , supervised by the nurse in charge of the health area . Main roles of the detection teams are to detect patients with suspicious lesions , to refer them to the nearest CDTUB , and to follow up cured patients after care . The volunteers do not receive compensation per BU case detection . All clinically confirmed patients are registered with the BU01 form in a CDTUB . This form ( figure 1 ) was provided by the WHO and used by all BU endemic countries to collect basic clinical data on newly registered patients for guidance of national programs since 2007 [4] . Trained nurses fill out the information on this form . Case confirmation is made by Laboratoire de Référence des Mycobactéries ( LRM ) in Cotonou for CDTUB A , B , D and in Anger ( France ) for CDTUB C . The laboratory of the Institute of Tropical Medicine in Antwerp has provided the quality control of LRM . Diagnostic tests include microscopy to detect acid-fast bacilli ( AFB ) and Polymerase Chain Reaction ( PCR ) for IS2404 . In this retrospective , observational study , patient information was collected from the WHO/BU01 forms of all Buruli ulcer patients reported to one of the four BU centers in Benin between the 1st of January 2008 and the 31st of December of 2010 . General characteristics of the patient , the results of diagnostic tests , the presence of functional limitations at start of treatment , the category of the lesion , patient delay , earlier visits to a traditional healer and the referral system were collected from the form . Patients can be referred to health centers by a health care worker , by trained community health volunteers or teachers , or by persons not included in the detection team such as family members , former patients , or they may report themselves . These items were selected from the BU01 form because they can be useful in assessing the importance of different actors in the current reference pattern in Benin , their influence on the stage of disease at presentation in the hospital and on the diagnostic precision of BU . Community education activities and geographical and socio-economic circumstances are expected to differ between treatment centers . Therefore the treatment center together with age and sex of the patients presenting to each center were evaluated as potential confounders or effect modifiers in the relation between referral system and disease stage . The presence of functional limitation at presentation was determined by visual assessment by the nurse completing the WHO form at start of treatment . Category of the lesion was registered according to the WHO classification provided by WHO [4] as follows: We defined an early lesion as a lesion in category 1 or 2 at admission ( figure 2 ) . Patient delay was defined as the time between the start of the lesion ( as indicated by the patient ) and the date of reporting at the BU centers . Statistical analysis was performed using Statistical Package for Social Science ( SPSS ) version 19 . 0 . All records of BU cases treated in the treatment centers during the study period were complete for the study variables used . The records of BU patients for whom PCR results were missing , were excluded from the analysis on diagnostic precision . χ 2 tests and t tests , or Kruskal-Wallis Test as appropriate were used for the univariate analyses on patient characteristics and the referral system . The role of the different referral systems on the stage of disease at presentation in the hospital was analyzed by a logistic regression analysis ( manually entered ) . The variables as presented in the univariate analysis were studied on confounding and effect modification . The provisional national ethical review board of the Ministry of Health Benin , nr IRB00006860 , approved the study protocol . All data analyzed were anonymized . For the picture include in this manuscript , written and verbal informed consent were obtained from all participants aged 15 years or older and legal representatives of participants younger than 15 years old .
In the study period , 1965 patients reported to one of the BU treating centers in Benin . The basic characteristics of the BU patients are presented in table 1 . Out of the 1965 individuals that presented to the health centers with BU , community health volunteers referred 521 ( 26 . 5% ) , former patients referred 433 ( 22 . 0% ) , health worker referred 396 ( 20 . 2% ) , and family members 368 ( 18 . 7% ) . Only 215 ( 10 . 9% ) BU patients reported themselves . Teachers referred 32 patients ( 1 . 6% ) with a median age of 29 , reflecting their role in the community outside their own school with young children . The percentage of patients that presented in an early stage of disease ( category 1 or 2 ) statistically differed among the different referring systems ( p<0 . 001 ) . Patients referred by the community health volunteers most frequently presented with an early lesion ( 68 . 1% ) , followed by patients referred by family members and self-reporting patients ( both 61% ) . Patients referred by a family member or self-reporting patients ( 8 weeks for both ) had less delay compared to patients referred by the other actors ( higher than or equal to 12 weeks ) . The number of patients presenting with functional limitations as well as the number of patients that visited traditional healers was lowest in patients referred by community health volunteers . Less than a third of patients ( 29 . 4% ) consulted traditional healers among patients referred by the community health volunteers . The referral pattern also differed per center ( Table 2 ) . In CDTUB A the majority of patients ( 77 . 8% ) were referred by the community health volunteers , whereas in CDTUB D the majority of patients ( 60 . 0% ) were referred by a former patient . In CDTUB C and B , most patients were referred by family members , the community health volunteers or they reported themselves . The percentages of patients reporting in an early stage of disease ( category 1 or 2 lesions ) differed among the centers . The role of the different referral systems and the stage of disease at presentation in the hospital in these different groups is shown in table 3 . In this model without any confounder or interaction included , referral by a community health volunteer protects against presentation of late stage of the disease ( category 3 ) , with an Odds ratios of 0 . 43 compared to referral by a health care worker . Table 4 shows the results of the statistical model with treatment center and age included as confounder . After correction by treatment center , the referral system does not have any statistically significant effect on the presentation of advanced stage lesions ( category 3 ) . The only statistically significant effects in the model are the high Odds ratios for presentation of advanced stage lesions in treatment centers C and D compared to treatment center A . Sex of the patient was not a confounder in the model . To obtain a workable model to control for interactions between the referral system and the treatment center , we simplified the referral system to community health volunteers versus the other referring systems . This did not reveal statistically significant interactions between the treatment center and the referral system . Early presentation can be defined as category 1 lesions only . In a post hoc analysis , this alternative definition of early disease ( i . e . , only category 1 lesions classify as early disease presentation ) showed similar results as the model presented in table 3; after adjustment for the treatment center , there was no influence of the referral system on the disease stage patients presented to the health center . PCR positivity per referral system and per health center is shown in table 5 . In total , 644 of 910 patients with a sample available ( 70 . 8% ) were confirmed by PCR and the percentage of confirmed patients differed among the different referral systems ( p<0 . 001 ) . In all , the community health volunteers referred 63 . 6% of the patients with a confirmed diagnosis of Buruli ulcer . Of these patients 14 . 2% presented with category 1 lesions and 49 . 4% presented with category 2 or category 3 lesions . The percentage of confirmed patients referred was different between centers: only in CDTUB C did the percentage of confirmed patients differ significantly by referral systems ( p = 0 . 004 ) . In the total group , patients referred by the family members are most frequently confirmed by PCR ( 92 . 1% ) ; patients referred by former patients are less frequently confirmed by PCR ( 57 . 8% ) .
This is the first study addressing the role of community health volunteers in the control of BU in Benin . Few studies address the role of CHW in BU detection worldwide [18] , [27] . The data analyzed in this study were collected in the Centers of detection and Treatment of BU ( CDTUB in Bénin ) . Health workers were trained to fill the BU 01 form . These forms developed by the WHO have proven to be beneficial to both patient care and control by the national program [28] , [29] . About a quarter of the patients were referred to the hospital by the community health volunteers . This shows that they play a major role in the control of BU . Our results confirm the impact of community health volunteers on the control of BU . The use of community health workers for BU control in countries other than Benin has been suggested [27] and also discussed in a review based on sparsely available data on their performance and training [18] . Apart from the community health volunteers , teachers , family members , and former patients also proved to be crucial in the referral system . The methods used by the community health volunteers for case detection are active case finding and education . ( Figure 3 ) . In data compiled from all centers , community health volunteers were more successful in getting patients to the health center in an early stage of disease than other referral sources . However , when health center specific data was analyzed , this effect could not be seen anymore . This suggests that the quality and/or training of community health volunteers are not uniform throughout the area . Barriers in the early presentation by community health volunteers ( e . g . logistics ) could also be different throughout the area . Visible functional limitations at the start of treatment were lower in patients referred by community health volunteers and patients referred by these volunteers less frequently visited a traditional healer than were patients in other referral groups . Earlier studies have shown that the therapeutic itinerary of patients goes through traditional healers before finally reporting to BU treatment centers [7] , [15] , [30]–[34] . In Benin , visiting a traditional healer is very common and this contributes to the patient delay in obtaining adequate treatment [7] , [32] . These findings made us hypothesize that patients referred by the community health volunteers without a visit to the traditional healer may have saved money and also are likely to present to obtain treatment from the health center earlier . From the current study it cannot be concluded how to prioritize limited means to support referral . It is not known what would be more cost effective , e . g . to increase the number of community health volunteers or to expand training activities to enforce early case detection . At least , the results show that in a health system with limited human resources , continuous efforts to support the community health volunteers are important . In Bénin , different Non-governmental organizations ( NGOs ) support the PNLLUB to organize the training to the community health volunteers . Earlier study highlighted the role of the NGOs in such training [18] . The BU program organizes at least three times per year training for the volunteers , mainly focusing on the disease symptoms at the earlier stage . Some incentives such as t-shirts are given to the community health volunteers as motivation . They also get transport costs for case detection and are reimbursed for the transport . Sometimes , bikes or motorbikes are offered to improve mobility of the community health volunteers who report many patients . It is unknown whether compensation based on performance , e . g . per reported BU patient indeed leads to referral of more patients in an early stage of disease . The effect of such intervention of course varies per setting [35] . In some circumstances Community health volunteers may have a negative impact on the health system; in Benin some community health volunteers are known to have asked money from patients or to have made medical decisions they are not qualified to make . In the BU health system , this negative impact is limited because the community health workers are recruited from the best community health workers that were earlier involved in the control of dracunculiasis where they were also supervised regularly . There is considerable heterogeneity between health systems . After adjustment for treatment center in the statistical model , no effect of the referral system on the early presentation was found . Especially in one health center a high percentage of patients ( 66 . 8% ) reported at an advanced disease stage . A significant factor here may be that this is the only center without decentralization of care . Earlier studies demonstrate the importance of spatial access to health care in developing countries [36] , [37] . Other explanations could be a difference in help seeking behavior of patients or a difference in the quality or frequency of community education activities . Apart from the community health volunteers , the family member and the former patients played important roles in referring patients . Slightly more than 40% of patients were referred by these informally trained community members ( 22% by former patients and 18 . 7% by family members ) . This high number of referrals from family members and former patients may be an effect of the education patients receive during their stay in the hospital and the community education which is conducted as part of the national program . We therefore imagine that it could be useful to actively invite former patients and their family members to become community health workers by enforcing their role with continuing education and financial compensation of travel expenses . We would not be inclined to prioritize the training to the traditional healers at this point in time . We tried earlier to expand the health promotion to some of the traditional healers . However , some of the trained traditional healers started performing BU excisions at home with inadvertent effects such as hemorrhage . As a result we abandoned this program . In Benin , patients are treated on the basis of clinical diagnostic suspicion , according to WHO recommendations [9] . Furthermore , an effort is made to confirm cases by molecular methods using PCR . Indeed , about 70% of patients started on treatment had PCR-confirmed BU . Center C has the highest number of PCR-confirmed patients and had more power to detect statistically significant differences between referral systems . The PCR positivity rate among patients referred by the community health volunteers is not systematically lower than in patients referred by other systems . This suggests that for the medical doctor the clinical case mix presented by the community health volunteer is similar to the patients presented by the other referral systems . The odds ratios used in the logistic regression are used to be able to adjust for treatment center but cannot be translated to relative risk ratios due to the high frequency of the outcome ( late presentation ) . Other limitations are the lack of adequate assessment of functional limitation at the end of treatment and limitations due to retrospective design of the study . The Buruli Ulcer Functional Limitation Scale ( BUFLS ) [38] , [39] could be included in the national program to easily assess this outcome measurement . To conclude , the study findings indicate that community health volunteers are an important link in the control of BU in Benin . Future studies should address the most effective way to improve early case detection by interventions such as training , increase in the numbers of volunteers or development of a system with financial compensation based on performance in early case detection .
|
Buruli ulcer ( BU ) is a neglected tropical disease caused by Mycobacterium ulcerans . Usually , the number of patients presenting with ulcers in an advanced stage is high . This complicates treatment and increases the risk of disabilities . The disease is endemic mainly in West Africa . The primary strategy for control is early detection using community village volunteers . In Bénin , data was collected to understand the role of the different referral systems on the stage of disease at presentation in the hospital and the diagnostic precision . About a quarter of the patients were referred to the hospital by the community health volunteers . Community health volunteers referred patients more frequently in an earlier stage of disease . The PCR confirmation rate among patients referred by the community health volunteers was not systematically lower than in patients referred by other systems . We found that community health volunteers played an important role in the referral system of BU patients in Bénin . This information is relevant for health care programs attempting to control BU but may also be relevant for health care programs working on other diseases in areas with restricted resources .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"dermatology",
"public",
"and",
"occupational",
"health",
"infectious",
"diseases",
"medicine",
"and",
"health",
"sciences",
"epidemiology"
] |
2014
|
Contribution of the Community Health Volunteers in the Control of Buruli Ulcer in Bénin
|
Analysis of immune responses in Bartonella bacilliformis carriers are needed to understand acquisition of immunity to Carrion’s disease and may allow identifying biomarkers associated with bacterial infection and disease phases . Serum samples from 144 healthy subjects from 5 villages in the North of Peru collected in 2014 were analyzed . Four villages had a Carrion’s disease outbreak in 2013 , and the other is a traditionally endemic area . Thirty cytokines , chemokines and growth factors were determined in sera by fluorescent bead-based quantitative suspension array technology , and analyzed in relation to available data on bacteremia quantified by RT-PCR , and IgM and IgG levels measured by ELISA against B . bacilliformis lysates . The presence of bacteremia was associated with low concentrations of HGF ( p = 0 . 005 ) , IL-15 ( p = 0 . 002 ) , IL-6 ( p = 0 . 05 ) , IP-10 ( p = 0 . 008 ) , MIG ( p = 0 . 03 ) and MIP-1α ( p = 0 . 03 ) . In multi-marker analysis , the same and further TH1-related and pro-inflammatory biomarkers were inversely associated with infection , whereas angiogenic chemokines and IL-10 were positively associated . Only EGF and eotaxin showed a moderate positive correlation with bacteremia . IgM seropositivity , which reflects a recent acute infection , was associated with lower levels of eotaxin ( p = 0 . 05 ) , IL-6 ( p = 0 . 001 ) , and VEGF ( p = 0 . 03 ) . Only GM-CSF and IL-10 concentrations were positively associated with higher levels of IgM ( p = 0 . 01 and p = 0 . 007 ) . Additionally , IgG seropositivity and levels were associated with high levels of angiogenic markers VEGF ( p = 0 . 047 ) and eotaxin ( p = 0 . 006 ) , respectively . Our findings suggest that B . bacilliformis infection causes immunosuppression , led in part by overproduction of IL-10 . This immunosuppression probably contributes to the chronicity of asymptomatic infections favoring B . bacilliformis persistence in the host , allowing the subsequent transmission to the vector . In addition , angiogenic markers associated with bacteremia and IgG levels may be related to the induction of endothelial cell proliferation in cutaneous lesions during chronic infections , being possible candidate biomarkers of asymptomatic infections .
Carrion’s disease ( CD ) ( ORPHANET 64692 ) is a tropical , neglected poorest-linked illness , endemic in low-income areas of Peru , but also affecting specific areas of Ecuador and Colombia , with sporadic cases reported in Bolivia and Chile [1] . It is estimated that approximately 1 . 7 million of South Americans are at risk of CD [1–3] . The bacteria Bartonella bacilliformis is the etiological agent of CD , but recently other Bartonella spp . have been related to this illness [4–6] . In the human host , B . bacilliformis is an intracellular pathogen that invades mainly erythrocytes and vascular endothelial cells [7] . B . bacilliformis is transmitted by the bite of sand flies ( members of the genus Lutzomyia ) and no reservoir has been identified other than humans , making it an eradicable disease [1 , 8] . Nowadays , CD is located in a restricted area , but in this era of globalization a future expansion to other areas cannot be ruled out , as has been described for other neglected diseases [8] . Unfortunately , no rapid diagnostic method to detect B . bacilliformis and CD has yet been developed to be available for endemic areas [8] . Currently , the infection is diagnosed by blood smear but this has several limitations including low sensitivity [9–10] and diagnosis error [11] . CD is clinically characterized by two phases . The first one , named Oroya’s Fever , consists in the acute infection that mainly affects young children ( >60% of cases ) and is characterized by fever , acute bacteremia and severe hemolytic anemia [12 , 13] . In absence of adequate treatment , Oroya's Fever achieves high levels of mortality ( 44% to 88% ) due to high bacteremia and opportunistic infections [3] . Complications during the acute phase and secondary infections are common , likely due to transient immunosuppression . The second phase , known as “Peruvian wart” , is a chronic phase usually occurring weeks or months after the acute phase and leads to a series of cutaneous lesions due to the bacterial induction of endothelial cell proliferation [3 , 12] . In addition , asymptomatic infections of undefined duration are common in people from endemic areas [14] , with a case of asymptomatic bacteremia of up to 3 years reported [15] . Estimates of the real burden of asymptomatic cases may not be accurate , but , we have recently reported rates of 37% carriers in post-outbreak areas and 52% in an endemic area by real time Polymerase Chain Reaction ( RT-PCR ) [16] . These symptomless infections that go unnoticed are probably the major reservoir of B . bacilliformis , and allow the transmission of the bacteria . Therefore , efforts leading to the development and application of new more efficient diagnostic techniques that can be used in endemic field areas are required to detect and distinguish acute , chronic and asymptomatic infections , in order to control and even eradicate CD . Information on immunity to CD and immune responses to B . bacilliformis is very limited and represents a challenge , due to the neglect of the disease and difficulty to obtain samples from the remote areas affected . Both humoral and cellular immune responses are induced during acute infection of CD [3] . It seems that antibody immunity to B . bacilliformis infection build up with age and exposure is lifelong , although it probably confers only partial protection and seropositive individuals may be asymptomatic carriers or have Peruvian warts [3] . Leukocytosis and anemia are probably responsible of the immunosuppression associated with acute infections , but cellular immune mechanisms involved remain unknown [3] . To our knowledge it is not known either what happens in asymptomatic subjects , in whom the infection persists [3] . In this exploratory study , we measured cytokines , chemokines and growth factors by quantitative multiplex fluorescent bead-based suspension arrays with the aim of providing information on the immune response to B . bacilliformis and identifying potential serum biomarkers of B . bacilliformis infection in non-acute individuals . The technology used allows evaluating simultaneously a high number of analytes using low sample volumes , which facilitates to extend the studies to specially CD vulnerable young populations .
A cross-sectional survey was done in 5 villages of Piura ( northern Peru ) on March 2014 [16] . In 4 of them ( Guayaquiles , Los Ranchos , Mayland , and Tunal ) an Oroya fever outbreak was reported between November 2013 and March 2014 , while Huancabamba is a well-established endemic area for this illness [16–17] . In Guayaquiles , Los Ranchos , Mayland and Tunal , study participants recruited were volunteers diagnosed with CD ( by clinical symptoms and/or thin blood smear ) during the previous outbreak . All subjects received ciprofloxacin antibiotic treatment during 14 days following diagnosis according to national guidelines . In Huancabamba , the volunteers were randomly recruited by house-to-house visits [16] . Clinical and demographical data were recorded [16] . The study was approved by the Universidad Peruana de Ciencias Aplicadas Ethics Committee and the Hospital Clínic of Barcelona Ethics Committee . Written informed consent was obtained from all adults and parents or guardians of any child participant on their behalf before recruitment . Serum samples from a total of 144 individuals out of 177 were randomly selected . Sample size was limited by the number of tests that could be performed in two Luminex kit plates . In a previous study , IgG and IgM levels against B . bacilliformis lysate were measured by ELISA , and B . bacilliformis was detected and quantified by RT-PCR [16] . The Cytokine Human Magnetic 30-Plex Panel from Life Technologies was used to measure the concentrations ( pg/mL ) of the following cytokines , chemokines and growth factors in serum: epidermal growth factor ( EGF ) , eotaxin , fibroblast growth factor ( FGF ) , granulocyte colony-stimulating factor ( G-CSF ) , granulocyte macrophage colony-stimulating factor ( GM-CSF ) , hepatocyte growth factor ( HGF ) , Interferon ( IFN ) -α , IFN-γ , interleukin ( IL ) -1RA , IL-1β , IL-2 , IL-2R , IL-4 , IL-5 , IL-6 , IL-7 , IL-8 , IL-10 , IL-12 ( p40/ p70 ) , IL-13 , IL-15 , IL-17 , IP-10 , monocyte chemoattractant protein-1 ( MCP-1 ) , monokine induced by gamma interferon ( MIG ) , macrophage inflammatory protein ( MIP ) -1α , MIP-1β , RANTES , tumor necrosis factor ( TNF ) , and vascular endothelial growth factor ( VEGF ) . Fifty μL of all samples were tested in single replicates distributed in two plates following manufacturer’s instructions . Each plate included 16 2-fold serial dilutions in single replicates ( at the exception of the highest concentration that was duplicated ) of a standard sample provided by the vendor with known concentration of each analyte . Two blank controls and three positive controls in duplicate of high , medium and low concentrations prepared from a reference sample were also included in each plate for quality assurance and quality control purposes . Samples were acquired on a Luminex 100/200 instrument and analyzed in xPONENT software 3 . 1 . The standard curves were fitted based on five-parameter log-logistic models . To account for background noise , median fluorescent intensity ( MFI ) of blank controls was subtracted to MFI of samples . The higher limit of quantification ( HLOQ ) was based on the higher dilution of the standard curve; and the lower limit of quantification ( LLOQ ) was calculated as the mean of blanks plus 2SD . When sample MFIs were out of quantification limits , an arbitrary value was imputed ( half of the expected concentration of the LLOQ for values < LLOQ and twice the expected concentration of the HLOQ for values > HLOQ ) . FGF , IL-1β , IL-17 and IL-7 were discarded from the analysis because > 80% measurements were out of range . In addition , the transforming growth factor β ( TGF-β ) was evaluated by an ELISA commercial kit ( LabClinics ) following manufacturer’s instructions . The studied population was categorized into 5 age groups ( ≤ 10 years , 11–25 years , 26–55 years , 56–69 years and ≥ 70 years ) as in our previous publication [16] . Localities were grouped to post-outbreak ( Guayaquiles , Los Ranchos , Mayland , and Tunal ) or endemic areas ( Huancabamba ) . IgM and IgG seropositivities were defined according to Finite Mixture Models ( FMM ) , with a cut off of 0 . 351 optical densities for IgM and 0 . 533 for IgG reported in Gomes C . et al [16] . Comparisons between groups for categorical variables were done using Fisher’s exact test . Demographic continuous variables were analyzed using the non-parametric Wilcoxon rank-sum test . IgG , IgM , marker concentration , bacteremia and age data were log10 transformed for further analysis . Comparison of levels of IgG and IgM by RT-PCR results were performed through t-test with welch correction . The effect of RT-PCR results , antibody responses , area and age on marker levels were assessed through separate simple linear regressions for each marker , with marker concentration as outcome and RT-PCR results , IgG responses , IgM responses , age and area as the predictor variable . The effect of RT-PCR results and antibody responses on single marker concentrations adjusting by age and area was assessed in multiple linear regressions with age and area as covariates and marker concentration as outcome . Correlations between continuous B . bacilliformis RT-PCR measurements , immunoglobulin levels , and cytokine , chemokine and growth factor concentrations were also calculated by Spearman correlation . To identify clusters of markers simultaneously associated with RT-PCR positivity , we performed partial least square discriminant analysis ( PLS-DA ) . PLS-DA allows compressing a high number of collinear variables into a new set of uncorrelated variables ( components ) that explain most of the variance of the data and also the outcome of interest ( RT-PCR positivity in our case ) . The most predictive components were selected by logistic regressions based on P-values <0 . 05 with RT-PCR positivity as the outcome . In addition , we also performed a multivariable model with the three components as predictors and RT-PCR positivity as outcome . We considered that biomarkers substantially contributed to the components when had loadings > |0 . 3| . All p-values were considered statistically significant when <0 . 05 . P-values were adjusted for multiple testing to control the false discovery rate using the Benjamini-Hochberg approach ( Supplementary information ) , but due to the exploratory character of the study results are discussed taking into account raw p-values and data were interpreted based on internal consistence , biological plausibility and previous literature . Box plots were performed using Graphpad Prism version 6 . 00 ( GraphPad Software , San Diego California USA ) and all data collected were analyzed using R software version 3 . 2 . 4 ( 2016-03-10 ) [18] . The DiscriMiner package [19] was used to perform the PLS-DA analysis , the ggplot2 package [20] was used to perform PLS-DA graphs and scatter plots . ROC analysis was conducted using an auc and roc . area functions from pROC package [21] . The reshape package was used for data manipulation purposes [22] .
A total of 177 serum samples were collected in 2014 in 5 villages of Northern Peru [16] . Of these , 144 sample sera ( Guayaquiles—23 , Los Ranchos—39 , Mayland—10 , Tunal—51 , and Huancabamba -21 ) were analyzed in this study . Demographic characteristics , RT-PCR data and IgM and IgG seroprevalences for the 177 subjects are described in our previous study [16] . Characteristics of the subset of 144 study subjects analyzed here were similar ( Table 1 ) , showing no bias in the sample selection for biomarker profiling . No significant differences were found in sex , age or area between subjects with detectable bacteremia ( RT-PCR positives ) and subjects without detectable bacteremia ( RT-PCR negatives ) . Age distribution was significantly different in IgM seropositive compared to IgM seronegative individuals , with higher prevalence of younger individuals among the seropositive ones . The contrary tendency was observed for IgG seropositives and negatives and a higher frequency of IgG seropositives was found in the endemic area than IgG seronegatives . We have previously reported that around 32 . 9% and 26% of RT-PCR positive individuals were IgM and IgG seropositive against B . bacilliformis lysate , respectively [16] . In the subset of subjects analyzed in this study , IgM and IgG seroprevalences were of 33 . 3% and 25 . 9% , respectively and no significant differences in IgM and IgG seropositivity ( p = 0 . 72 and p = 0 . 46 , respectively ) or IgM and IgG levels ( p = 0 . 71 and p = 0 . 72 , respectively ) were detected according to RT-PCR results . Therefore , we consider IgM responses as markers of recent acute infection , and IgG responses as markers of previous exposure and immunity . We examined the effect of B . bacilliformis bacteremia on biomarker concentrations . Subjects with detectable bacteremia had lower levels of HGF ( p = 0 . 005 ) , IL-15 ( p = 0 . 002 ) , IL-6 ( p = 0 . 05 ) , IP-10 ( p = 0 . 008 ) , MIG ( p = 0 . 03 ) and MIP-1α ( p = 0 . 03 ) ( Fig 1 , S1 Table ) compared to subjects without bacteremia . IL-1RA also had a tendency to be lower in subjects without bacteremia ( p = 0 . 059 ) . Age positively correlated with levels of eotaxin ( p<0 . 001 ) , IL-6 ( p = 0 . 008 ) and MCP-1 ( p = 0 . 002 ) , and negatively with IL-12 ( p<0 . 001 ) and IL-2 ( p = 0 . 026 ) ( S1 Table ) . Study area was also associated with levels of some markers , with higher levels of EGF ( p<0 . 001 ) , eotaxin ( p = 0 . 066 ) , and TNF ( p = 0 . 032 ) and lower levels of IP-10 ( p = 0 . 019 ) in the endemic area compared to the post-outbreak area ( S1 Table ) . Therefore , we adjusted the analysis of the effect of RT-PCR positivity on biomarker levels by age and area ( S2 Table ) . HGF ( p = 0 . 01 ) , IL-15 ( p = 0 . 002 ) , IP-10 ( p = 0 . 019 ) , MIG ( p = 0 . 044 ) and MIP-1α ( p = 0 . 033 ) maintained their significance , and IL-12 was negatively associated with positivity of B . bacilliformis by RT-PCR ( p = 0 . 017 ) . When we analyzed the impact of bacteremia on marker levels we only found bacteremia to be positively associated with EGF and eotaxin levels with moderate correlations ( Fig 2 ) . In unadjusted linear models , only eotaxin was statistically associated with bacteremia , but lost its significance after adjusting for age and area ( S3 Table ) . We identified several components from a PLS-DA analysis that were positively and independently associated with RT-PCR results in logistic regression models . The most predictive components ( components 1 , 2 and 3 ) are shown in Fig 3A . The biomarkers that contributed more to the components were the ones with higher loadings in the different components ( relevant biomarkers were considered with loadings higher than 0 . 3 or lower than -0 . 3 ) . In component 1 , the most relevant biomarkers were HGF , IL-15 , IL-6 , IP-10 , MIG and MIP-1α , all with positive loadings; in component 2 , HGF , IL-15 , IL-6 , IP-10 and MIG with positive loadings and MCP-1 and TNF with negative loadings , suggesting a different association with RT-PCR data . Finally , in component 3 , G-CSF , INF-γ , IL-15 , MIP-1α and RANTES with positive loadings , and IL-10 , IL-2 , IL-8 and MCP-1 , MIP-1β with negative loadings ( Fig 3A ) . Both simple ( component 1 coefficient ( coef ) = -0 . 26 p = 0 . 005 , component 2 coef = -0 . 49 p = 0 . 001 , and component 3 coef = -0 . 398 p = 0 . 029 ) and multivariable ( component 1 coef = -0 . 441 p = 0 . 033 , component 2 coef = -0 . 466 p = 0 . 007; and component 3 coef = -0 . 23 p = 0 . 010 , respectively ) logistic models showed a significant association between components and B . bacilliformis RT-PCR positivity . Although samples did not clearly cluster by RT-PCR results , as shown in the plots of individual samples with respect to the first 3 components ( Fig 3B ) , the multivariable model resulting from the PLS-DA had a moderate discriminatory ability with an AUC of 0 . 71 . We analyzed the association of IgM and IgG levels and seropositivity with biomarker levels to determine the impact of a recent acute infection and past exposure/immunity , respectively . On the one hand , IgM levels were inversely correlated with eotaxin , IL-6 and VEGF levels ( p<0 . 0001 , p = 0 . 046 and p = 0 . 007 , respectively; Fig 4 and S4 Table ) and consistently IgM seropositive individuals had lower levels of these three markers ( p = 0 . 05 , p = 0 . 001 and p = 0 . 03 , respectively ) ( Fig 5 and S5 Table ) . On the other hand , IL-10 and GM-CSF concentrations showed to be positively associated with levels of IgM ( p = 0 . 007 and p = 0 . 01 , respectively; Fig 4 and S4 Table ) . When adjusting the analysis by age and area , the association of IL-6 with IgM levels and eotaxin with IgM seropositivity lost its significance ( S4 and S5 Tables ) . Regarding marker concentrations according to IgG seroprevalence , a significant difference was detected only for VEGF , which showed higher levels in the IgG seropositive group ( p = 0 . 047 , Fig 5 , S6 Table ) . In addition , IgG levels were positively associated with levels of eotaxin ( p = 0 . 006 , Fig 4 and S7 Table ) . No other statistically significant associations were found . After adjusting by age and area , VEGF was positively associated with IgG levels , but eotaxin lost its significance ( S7 Table ) . Despite the statistical significance of these associations , correlations between biomarkers and IgM and IgG levels were moderate ( Table 2 ) .
Host-pathogen relations established during either symptomatic or asymptomatic B . bacilliformis infections remain understudied . Nonetheless , the knowledge of the host responses to this infection and the subsequent microorganism evasion strategies are crucial to understand the pathogenesis and advance towards CD control that will precede any eradication attempt . In this context , we analyzed serum samples from both post-outbreak and endemic areas collected in 2014 to determine , for the first time , serum biomarkers associated to non-acute infection of B . bacilliformis and provide some insights into the immune response to this pathogen . In endemic regions , an inverse correlation between age and CD incidence has been described , associated to the acquisition of partial immunological protection possibly due to antibody immunity [23] . As described in our previous work that included the samples of this study , the highest levels of IgM were found in the youngest population ( under 25 years old ) , whereas IgG was more elevated in older population ( ≥25 years old ) [16] , reflecting increased exposure and development of immunity with age . Moreover , in traditionally endemic areas , as Huancabamba , IgG levels were higher , probably as a result of higher exposure [16] . According to previous studies , the immunological response during the acute phase is characterized by an increase in IgM levels , whereas 2 to 4 weeks later there is a significant increase of both IgG and IgM levels [24] . On the contrary , in chronic phases only a slight increase in antibody levels has been observed [24] . In our previous study , we did not find IgM and IgG levels to B . bacilliformis lysate to be associated with presence of bacteremia [16] , therefore IgM would be considered a marker of recent acute-infection , whereas IgG would be a marker of past exposure and immunity . The lack of association between antibody seropositivity and levels with asymptomatic infection underscores the need to find other biomarkers such as cytokines that could identify these infections . Lower levels of HGF , IL-12 , IL-15 , IL-6 ( unadjusted analysis ) , IP-10 , MIG and MIP-1α , were found in the bacteremic group . HGF is a growth factor with pleiotropic function and it is produced in response to the pro-inflammatory cytokine IL-1 in infectious diseases [25] . IL-15 induces T and NK cell proliferation and activation , and promotes the production of TH1 and pro-inflammatory cytokines and chemokines such as IFN-γ and MIP-1α [26] . IP-10 is also a pro-inflammatory chemokine secreted in response to IFN-γ and upregulated during acute response to infection [26] . The chemokine MIP-1α is crucial for inflammation and it is also related to synthesis of TH1 and pro-inflammatory cytokines [27] . We found higher levels of IL-12 with lower age , in line with previous studies in other infectious diseases , as malaria [28] . Analysis adjusting by age revealed that IL-12 was negatively associated to detection of bacteremia . IL-12 is a key TH1 cytokine produced mainly during innate immune response by stimulated dendritic cells , it regulates their maturation and induces IFN-γ production by T cells and NK cells as well as their activation [29] . Consistently , in multi-marker analysis we found that the most relevant markers associated with presence of bacteremia were HGF , IL-15 , IL-6 , IP-10 , MIG and MIP-1-α and additionally , G-CSF , IFN-γ , RANTES . In the opposite direction , reflecting positive associations , we found IL-10 , IL-2 , IL-8 , MCP-1 , MIP-1β and TNF . G-CSF is a growth factor that induces the proliferation , differentiation and activation of granulocytes and it is increased in acute infections [30] . IL-2 is an important cytokine involved in many immune processes and responsible of T cell proliferation , response and induction of memory and TNF is a key TH1 cytokine [26] . IL-8 , MIG , RANTES , MCP-1 and MIP-1β are chemokines involved in pro-inflammatory responses , although they differ on the cell types that produce them and that are targeted . Interestingly , IL-8 and MCP-1 are considered angiogenic chemokines , whereas other chemokines such as IP-10 and MIG are considered angiostatic [31] . On the other hand , IL-10 is a well-known anti-inflammatory cytokine [26] . Therefore , in non-acute infection several markers related to TH1 and pro-inflammatory responses were diminished , whereas IL-10 was increased in multi-marker analysis , suggesting some immunosuppression in B . bacilliformis carriers . IL-10 is upregulated in pro-inflammatory processes and limits and suppresses T cell activation and pro-inflammatory cytokines [32] to avoid an exacerbated immune response that could damage the host , but this may result in impaired pathogen control [32] . In addition , IL-10 has been associated to apoptosis of dendritic cells and immune impairment in malaria infection [33] . High levels of IL-10 have been observed in patients who presented severe sepsis , mainly by gram-negative bacteria and , importantly , IL-10 has been previously associated with Bartonella infections . It is hypothesized that IL-10 induced immunosuppression is key in the development of severe Bartonellosis [34] . However , anti-inflammatory effects of IL-10 have also been described in mild Bartonella infections where this cytokine would limit immunopathogenesis at the expense of allowing persistent infections [35] . Probably , as occurs in B . quintana infection [36] , there is an IL-10 increased production that is associated with an attenuated inflammatory profile in infected compared to non-infected individuals . IgM levels correlated with low levels of some pro-inflammatory markers and higher IL-10 levels , probably still reflecting an immunosuppression of the acute phase of the infection . Indeed , an impairment of the cellular immune response in acute infection has been previously described [37] . These results , together with the associations with bacteremia described above , support the hypothesis that B . bacilliformis induces a systemic immunosuppression that could last a long time after the acute infection and could be maintained during the chronic phase . GM-CSF was also positively associated with IgM levels . GM-CSF is a growth factor that stimulates production and antibacterial functions of neutrophils , monocytes and macrophages [26] . It has an important role in acute infections [38] and has been found elevated in sepsis [39] . The higher levels found in correlation with IgM probably reflects levels still elevated from the acute infection . It seems that concurrent pro-inflammatory and anti-inflammatory responses in acute Bartonellosis may be similar to what occurs in other sepsis [40] . Interestingly , we found an association between increased bacteremia and increased levels of EGF and eotaxin , although we did not find any differences in the concentration of these markers in infected and non-infected subjects . EGF is a growth factor associated with endothelial cells and related to angiogenic processes [41] . It could be involved in the chronic phase of B . bacilliformis infection , when the infection promotes cutaneous angiogenesis that involves proliferation of endothelial cells , resulting in a series of cutaneous lesions [42] . These cutaneous lesions are characterized by small vessels coated with endothelial cells and are a junction of polymorphonuclear neutrophils , macrophages , endothelial cells and bacteria [42] . Eotaxin is a selective chemoattractant for eosinophils , but it is also involved in recruitment and activation of other immune cells in inflamed tissue [26] . Importantly , this chemokine is produced by macrophages , fibroblasts and endothelial cells [43] and also mediates angiogenesis [44] . Therefore it may also be a relevant marker in the angiogenic processes in Bartonellosis . To our knowledge , eotaxin has not been studied before in any Bartonella infection , while the induction of VEGF by Bartonella , another potent angiogenic factor secreted by endothelial cells and macrophages from the lesions [45–46] has been described . The presence of B . henselae , specifically the pili , was associated with host cell VEGF production [46] and VEGF-stimulated endothelial cells promoted the growth of B . henselae through the activation of hypoxia-inducible factor-1 [47–48] . Simultaneously , B . henselae also inhibited cell apoptosis , inducing endothelial proliferation [49] and allowing Bartonella proliferation in these cells . Despite none of the analyzed samples belongs to patients with Peruvian warts , this is with cutaneous lesions , we found that VEGF levels were higher in IgG seropositive individuals , and were inversely associated with IgM levels . Similarly , eotaxin was positively associated with IgG levels , but inversely associated with IgM levels and seropositivity . This , together with its correlation with bacteremia , suggest that this chemokine may be suppressed only in acute infection and induced by bacteremia in tissues during the chronic phase . Importantly , we also found the angiogenic chemokines IL-8 and MCP-1 and IP-10 , MIP-1α and RANTES , which are induced by B . henselae in endothelial cells [47] , macrophages [50] and in infected human myeloid angiogenic cells that differentiates to tumour associated macrophages [51] , to be associated with presence of bacteremia in multivariate analysis . Thus , we hypothesize that EGF , eotaxin , VEGF and other angiogenic chemokines described in previous in vitro studies with B . henselae [46–48 , 50–51] could be markers of chronic B . bacilliformis infection , and they could predict the appearance of cutaneous lesions . IgG levels in semi-immune individuals could be forcing Bartonella to hide into the endothelium and epidermis , where it would induce vasculogenesis and angiogenesis through the production of eotaxin , EGF , VEGF and other angiogenic chemokines that would ultimately result in the Peruvian warts [45–52] . Bartonella hiding , in conjunction with the systemic immunosupression that would avoid high antibody responses , could explain the observed lack of association between IgG response and RT-PCR results in this study . A limitation of our study was the lack of samples of acutely infected subjects or chronically infected individuals with Peruvian warts , to clarify the cytokine profile in each stage of the infection . In addition , the cross-sectional design of the study did not allow addressing kinetics of biomarkers and immune responses and associations with disease progression . In accordance with our results , we speculate that B . bacilliformis induces an immunosuppression caused at least in part by elevated levels of IL-10 in the acute phase , and this is maintained in later phases with low levels of bacteremia , as occurs in B . quintana . Due to this transient immune paralysis , levels of some TH1-related and pro-inflammatory cytokines are reduced , helping the establishment and persistence of the infection at low levels of bacteremia . This attenuated response in bacteremic individuals could be the result of mechanisms of immune tolerance defined as the absence of a specific immune response to an antigen . B . bacilliformis could be triggering these mechanisms as a strategy of immune evasion , and in this manner allowing the subsequent transmission . In addition , our findings support the idea that immune pressure mediated by IgG responses could be forcing B . bacilliformis to hide and replicate in endothelial cells [49] , slowly growing inside cells , isolated from the host immune response , enabling bacteria survival . Accordingly , angiogenic growth factors and chemokines positively associated with bacteremia and IgG levels could be useful as biomarkers of asymptomatic and chronic infection . Despite the moderate discriminatory ability of the markers identified and the considerable likelihood of false discovery rate , future studies designed and powered to evaluate biomarkers of B . bacilliformis infection at different stages should address these markers and novel markers in combination .
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Carrion’s disease is a neglected vector-borne disease limited to vulnerable population of Ecuador , Colombia and specially Peru . This illness consist in two distinct phases , the Oroya fever and Peruvian wart , but exist a high percentage of asymptomatic carriers in endemic areas that should be detected in order to perform correct surveillance and control . Moreover , information on immunity and immune responses to Bartonella bacilliformis , the causative agent , is very limited and represents a challenge . This study identified serum biomarkers associated with Carrion’s disease asymptomatic infections . In addition , it provides novel information on the complex host-immune interactions in these individuals , suggesting that the bacteria induces an immunosuppression in the acute phase that is maintained in later phases with low levels of bacteremia . This immunoppression would help the establishment and persistence of the infection .
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[
"Abstract",
"Introduction",
"Material",
"and",
"methods",
"Results",
"Discussion"
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[] |
2017
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Immunosuppressive and angiogenic cytokine profile associated with Bartonella bacilliformis infection in post-outbreak and endemic areas of Carrion's disease in Peru
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3’ uridylation is increasingly recognized as a conserved RNA modification process associated with RNA turnover in eukaryotes . 2’-O-methylation on the 3’ terminal ribose protects micro ( mi ) RNAs from 3’ truncation and 3’ uridylation in Arabidopsis . Previously , we identified HESO1 as the nucleotidyl transferase that uridylates most unmethylated miRNAs in vivo , but substantial 3’ tailing of miRNAs still remains in heso1 loss-of-function mutants . In this study , we found that among nine other potential nucleotidyl transferases , UTP:RNA URIDYLYLTRANSFERASE 1 ( URT1 ) is the single most predominant nucleotidyl transferase that tails miRNAs . URT1 and HESO1 prefer substrates with different 3’ end nucleotides in vitro and act cooperatively to tail different forms of the same miRNAs in vivo . Moreover , both HESO1 and URT1 exhibit nucleotidyl transferase activity on AGO1-bound miRNAs . Although these enzymes are able to add long tails to AGO1-bound miRNAs , the tailed miRNAs remain associated with AGO1 . Moreover , tailing of AGO1-bound miRNA165/6 drastically reduces the slicing activity of AGO1-miR165/6 , suggesting that tailing reduces miRNA activity . However , monouridylation of miR171a by URT1 endows the miRNA the ability to trigger the biogenesis of secondary siRNAs . Therefore , 3’ tailing could affect the activities of miRNAs in addition to leading to miRNA degradation .
The three major types of small RNAs in eukaryotes , microRNAs ( miRNAs ) , small interfering RNAs ( siRNAs ) and piwi-interacting RNAs ( piRNAs ) , impact many biological processes such as development , self/non-self recognition , genome stability , and adaption to environment . Given the widespread and indispensible functions of small RNAs , it is crucial to understand their biogenesis and turnover . A common step in the biogenesis of miRNAs and siRNAs in plants , as well as piRNAs and certain endogenous siRNAs in animals , is 2’-O-methylation on the 3’ terminal ribose by the small RNA methyltransferase HUA ENHANCER1 ( HEN1 ) [1 , 2 , 3 , 4 , 5 , 6 , 7] . In Arabidopsis hen1 mutants , miRNAs and siRNAs become 3’ truncated , 3’ uridylated , and reduced in abundance [8] . Similarly , in animal hen1 mutants , piRNAs and/or siRNAs become 3’ truncated and 3’ uridylated [2 , 3 , 4 , 6] . This indicates that 2’-O-methylation protects small RNAs from 3’ truncation by an exonuclease ( s ) and 3’ tailing by a nucleotidyl transferase ( s ) . In a previous study , we identified Arabidopsis HEN1 SUPPRESSOR1 ( HESO1 ) as a nucleotidyl transferase responsible for miRNA uridylation in vivo [9 , 10] . Loss of function in HESO1 results in reduced 3’ tailing and increased abundance for most miRNAs in hen1 backgrounds [9 , 10] , indicating that tailing leads to miRNA degradation . Small RNA profiling in hen1-8 , a partial loss-of-function hen1 mutant [11] , and the hen1-8 heso1-1 double mutant reveals that 3’ truncation happens independently of 3’ uridylation , and that 3’ uridylation occurs on both full-length and 3’ truncated species [10] . Among the ten genes encoding potential nucleotidyl transferases , HESO1 is the only one whose loss of function partially suppresses the morphological defects of hen1 mutants [9 , 10 , 12] , suggesting that HESO1 is the major miRNA uridylation enzyme . However , despite heso1-1 being a null allele [10] , considerable levels of miRNA uridylation were detected by small RNA profiling in the hen1-8 heso1-1 double mutant [10] , indicating that ( an ) other nucleotidyl transferases could tail unmethylated miRNAs . In vivo , a miRNA exists in miRISC ( miRNA-induced silencing complex ) in which the miRNA is bound by an ARGONAUTE ( AGO ) protein . In Arabidopsis , AGO1 is the effector for almost all miRNAs [13 , 14] . Molecular genetic evidence suggests that uridylation occurs on AGO1-bound miRNAs in vivo . First , 3’ truncated and tailed miRNAs in hen1 mutants are bound by AGO1 in vivo [12 , 15] . Second , a partial loss-of-function ago1 mutation , ago1-11 , suppresses the 3’ truncation and tailing of miRNAs in the weak hen1-2 mutant [15] . Moreover , HESO1 was shown to uridylate an in vitro reconstituted miRISC [16] . Given that uridylated miRNAs are associated with AGO1 , uridylation may also alter the activities of miRNAs in addition to its role in miRNA degradation . Some Arabidopsis miRNAs efficiently trigger the production of phased secondary siRNAs ( phasiRNAs ) from their target transcripts , and some of the phasiRNAs can also regulate genes in trans and are named trans-acting siRNAs ( ta-siRNAs ) [17 , 18 , 19] . A common feature of the trigger miRNAs—their 22 nt length—endows them with the ability to generate phasiRNAs [20 , 21] . For example , miR173 is predominantly 22 nt in vivo and initiates ta-siRNA biogenesis from two noncoding transcripts TAS1 and TAS2 [17 , 18 , 19] . In a recent study [15] , it was found that miR171a becomes predominantly 22 nt in hen1 mutants and initiates the biogenesis of phasiRNAs from its targets At2g45160 and At3g60630 , suggesting that mono-uridylation of miR171a allows it to trigger phasiRNA biogenesis . But the enzyme that mono-uridylates miR171a in hen1 mutants is not HESO1 and remains unknown [15] . In hen1 mutants , despite various degrees of tailing of many miRNAs , only miR171 family members acquire the ability to trigger phasiRNA biogenesis [15] . The effects of tailing on the activities of other miRNAs remain unknown . Most of the nine HESO1 paralogs , which we refer to as NUCLEOTIDYL TRANSFERASE PROTEIN ( NTP ) genes unless they have been previously named otherwise ( S1 Fig ) , remain uncharacterized . One gene ( At2g45620 ) was shown to encode a nucleotidyl transferase and named UTP:RNA URIDYLYLTRANSFERASE 1 ( URT1 ) [22] . URT1 was found to uridylate messenger RNAs that have an oligoadenylate tail [22] . In this study , we identified URT1 as the nucleotidyl transferase with the second highest impact on miRNA uridylation among ten nucleotidyl transferases in Arabidopsis . URT1 and HESO1 prefer miRNA substrates with different 3’ nucleotides in vitro , and act on different size variants of the same miRNAs in vivo . We found that URT1 and HESO1 act sequentially on some miRNAs , with URT1 mono-uridylating the miRNAs followed by their further uridylation by HESO1 . Both HESO1 and URT1 are able to tail AGO1-bound miRNAs and the uridylated species stay associated with AGO1 . The tailing of AGO1-bound miR165/6 reduces its slicing activity while the monouridylation of miR171a endows an ability to trigger the biogenesis of phasiRNAs . Thus , miRNA tailing affects the activities of miRNAs in addition to causing miRNA degradation .
The presence of substantial levels of miRNA uridylation in hen1-8 heso1-1 implied that ( an ) other nucleotidyl transferases can also tail miRNAs . To identify the nucleotidyl transferase ( s ) , we sought to determine the effects of mutations in each of the nine NTP genes ( S1 Table and S1A Fig ) on miRNA uridylation . A mutation in each of the nine NTP genes was combined with hen1-8 and small RNA libraries were constructed from the nine double mutants as well as hen1-8 ( S2 Table ) . Levels of tailing were calculated as the ratio of the number of reads with tails over the number of total reads for a particular miRNA . The mutation in URT1 , urt1-1 , was found to reduce the tailing of a few miRNAs . Among 107 miRNAs that were detected at 30 reads per million or greater abundance in both hen1-8 and hen1-8 urt1-1 libraries , ten showed reduced tailing in hen1-8 urt1-1 ( Fig 1A ) . The effects of urt1-1 on the tailing of a small number of miRNAs contrasted the widespread effects of heso1 mutations [9 , 10] . This suggested that HESO1 could act on most miRNAs in hen1-8 urt1-1 except for a few miRNAs . Indeed , for the miRNAs showing reduced tailing in hen1-8 urt1-1 , the heso1-1 mutation had no or little effect on them whereas it had a strong effect on other miRNAs ( Fig 1B; [10] ) . When we separately quantified tailing on full-length and 3’ truncated species , we found that urt1-1 and heso1-1 had distinct effects on the different forms of the same miRNAs ( Fig 1C and 1D ) . For example , urt1-1 strongly reduced 3’ tailing of full-length miR171a and 3’ truncated miR158a , but heso1-1 affected the tailing of 3’ truncated miR171a and full-length miR158a ( Fig 1C and 1D ) . Therefore , the two proteins appeared to prefer different miRNAs or different forms of the same miRNAs in vivo . Unlike heso1-1 , which partially rescues the hen1-8 morphological phenotype [10] , urt1-1 does not rescue the hen1-8 morphological phenotype ( S2 Fig ) . In contrast to mutations in HESO1 or URT1 , mutations in the other eight NTP genes did not cause any discernable effects on miRNA tailing ( S3 Fig ) . As an example , miR158 showed reduced tailing in hen1-8 urt1-1 as compared to hen1-8 ( arrow in Fig 2A ) . Patterns of miR158 3’ truncation and tailing in the other eight hen1-8 ntp double mutants were identical to each other and to hen1-8 ( Fig 2A and S4A Fig ) . The nearly identical patterns of hen1-8 and seven hen1-8 ntp genotypes in Fig 2A also reflected the reproducibility of the high throughput sequencing-based quantification of miRNA 3’ truncation and tailing . URT1 was previously shown to have RNA nucleotidyl transferase activity in vitro and uridylate oligoadenylated RNAs in vivo [22] . To confirm this activity and to examine its substrate preferences , we expressed and purified recombinant , 6XHis-tagged URT1 from E . coli ( S1C Fig ) . The recombinant protein was incubated with synthetic , unmethylated miR173 in the presence of different ribonucleotide triphosphates . URT1 was able to add multiple ribonucleotides to miR173 ( Fig 3 , lanes 4–7 ) , confirming that URT1 is a nucleotidyl transferase . The lengths of the products were longest when UTP was in the reaction ( Fig 3 , lanes 4–7 ) , indicating that URT1 , like HESO1 [9 , 10] , prefers UTP . To rule out the possibility that the nucleotidyl transferase activity was due to a contaminating protein from E . coli , two conserved aspartate residues in the nucleotidyl transferase domain were mutated to alanine ( S1B Fig ) . The mutant protein , 6XHis-URT1m was expressed in E . coli and purified as was the wild-type protein ( S1C Fig ) . His-URT1m failed to tail miR173 ( Fig 3 , lanes 11–12 ) . We next investigated URT1’s requirement for the 2’ OH of the 3’ terminal ribose in the substrate miRNA . When deoxyadenosine triphosphate ( dATP ) was included as the only nucleotide in the reaction , URT1 added a single deoxyadenylate to miR173 , but further nucleotide addition was inefficient ( Fig 3 , lane 8 ) . This indicated that the 2’ OH on the 3’ terminal ribose is a feature of the substrate recognized by URT1 . When 2’-O-methylated miR173 was incubated with URT1 in the presence of UTP , no tailing was observed ( Fig 3 , lanes 13–14 ) . This indicated that URT1 activity , like that of HESO1 [10] , is completely inhibited by 2’-O-methylation on its substrate RNA . Small RNA profiling in hen1-8 urt1-1 and hen1-8 heso1-1 revealed that URT1 and HESO1 preferred different forms of miR158 ( Fig 2A and 2B ) . Note that the various miR158 species will be referred to by their X and Y coordinates as shown in Fig 2A and 2B . In hen1-8 , miR158 existed in full-length and 1-nt truncated forms ( miR158 ( 0 , 0 ) and miR158 ( 1 , 0 ) , respectively ) and both underwent various degrees of tailing ( Fig 2A ) . In hen1-8 heso1-1 , tailing of the full-length form was greatly reduced , indicating that HESO1 was responsible for the tailing of full-length miR158 ( Fig 2B ) . In hen1-8 urt1-1 , full-length miR158 species with tails were unaffected , indicating that URT1 did not tail full-length miR158 ( Fig 2A ) . In hen1-8 heso1-1 , there was an increase in miR158 ( 1 , 1 ) , a miR158 species with 1-nt truncation and a 1-nt tail ( Fig 2B; arrow ) . Correspondingly , there was a decrease in the abundance of miR158 ( 1 , 1+ ) , i . e . , species of miR158 ( 1 , 1 ) with longer tails ( Fig 2B ) . Therefore , HESO1 was responsible for tailing miR158 ( 1 , 1 ) but not miR158 ( 1 , 0 ) . On the other hand , the abundance of miR158 ( 1 , 0 ) was increased with a corresponding decrease in miR158 ( 1 , 0+ ) species in hen1-8 urt1-1 ( Fig 2A ) . Taken together , these results suggested that 1 ) HESO1 but not URT1 tails full-length miR158; and 2 ) URT1 adds a 1-nt tail to the 1-nt truncated miR158 to result in miR158 ( 1 , 1 ) , which is further tailed by HESO1 . To verify these results , northern blots were carried out on wild type , hen1-8 , hen1-8 urt1-1 , and hen1-8 heso1-1 . When RNAs were separated with a 1-nt resolution , it was clear that the 20-nt miR158 band was the predominant band in hen1-8 heso1-1 ( Fig 2D ) . This 20-nt band corresponded to both miR158 ( 0 , 0 ) and miR158 ( 1 , 1 ) ( Fig 2B ) , and the northern blot results were consistent with the small RNA profiling data . On the other hand , in hen1-8 urt1-1 , the 1-nt truncated form of miR158 accumulated to a higher level relative to hen1-8 ( Fig 2D; arrow ) , consistent with the small RNA profiling data ( Fig 2A; arrow ) . We also quantified the levels of miR158 in the four genotypes by not resolving the miR158 size variants in northern blots . Consistent with previous results , the amount of miR158 was higher in hen1-8 heso1-1 as compared to hen1-8 ( Fig 2C ) . urt1-1 did not lead to an increase in miR158 abundance ( Fig 2C ) . miR158 is only partially methylated in wild type and is subjected to uridylation by both HESO1 and URT1 even in wild type background ( [15]; S4B Fig ) . As in the hen1-8 background , HESO1 and URT1 act on full-length and 1-nt truncated miR158 , respectively , in wild type ( S4B Fig ) . Next , we tested whether URT1 or HESO1 impacts the activity of miR158 by examining the expression of the miR158 target gene At3g03580 . The heso1-1 mutation caused a reduction in At3g03580 transcript levels as compared to wild type , but the urt1-1 mutation did not have a significant effect ( Fig 2E ) . The levels of the At3g03580 transcript were reduced in hen1-8 heso1-1 relative to hen1-8 ( Fig 2E ) , consistent with higher miR158 levels in this genotype ( Fig 2C ) . Interestingly , the expression of At3g03580 was decreased also in hen1-8 urt1-1 ( Fig 2E ) , despite the fact that miR158 levels were similar between hen1-8 urt1-1 and hen1-8 ( Fig 2C ) . This prompted us to test whether tailing affects the slicer activity of miRNAs ( see below ) . Small RNA sequencing revealed that URT1 and HESO1 acted sequentially to tail miR173 . miR173 is largely non-tailed in wild type ( S4C Fig ) . In hen1-8 , full-length , 22-nt miR173 was tailed to various larger sizes ( Fig 4A and 4B ) . Both heso1-1 and urt1-1 affected miR173 tailing but in different ways . In hen1-8 heso1-1 , the mono-uridylated , 23-nt form of miR173 accumulated predominantly ( Fig 4B ) , indicating that HESO1 preferentially used this 23-nt form as the substrate for uridylation in vivo . The enzyme that performed the mono-uridylation of miR173 to produce the 23-nt form was URT1 , as the 22-nt form of miR173 was the predominant species in hen1-8 urt1-1 ( Fig 4A ) . These observations from small RNA sequencing were confirmed by northern blotting . The 23-nt and larger species were predominant in hen1-8 heso1-1 , whereas the 22-nt species was predominant in hen1-8 urt1-1 ( Fig 4C ) . Taken together , these results indicate that URT1 performs mono-uridylation of miR173; subsequently , HESO1 preferentially uridylates the 23-nt miR173 . Moreover , consistent with uridylation leading to miRNA degradation , miR173 levels were increased in both hen1-8 heso1-1 and hen1-8 urt1-1 relative to hen1-8 ( Fig 4D ) . When a URT1-GFP transgene driven by the URT1 promoter was introduced into hen1-8 urt1-1 , the increase in miR173 levels was rescued in two independent transgenic lines ( S5A Fig ) . In a HEN1 background , neither heso1-1 nor urt1-1 affected the levels of miR173 ( S5B Fig ) . As a 22-nt miRNA , miR173 triggers the biogenesis of ta-siRNAs from TAS1 and TAS2 loci [17 , 18 , 19 , 20 , 21] . We next examined whether URT1 impacted ta-siRNAs whose biogenesis requires miR173 . Northern blots were performed to detect ASRP1511 , a ta-siRNA from the TAS2 locus [17] . ASRP1511 levels were higher in hen1-8 urt1-1 or hen1-8 heso1-1 than in hen1-8 ( Fig 4E ) . The increase in TAS2 ta-siRNA levels caused by urt1-1 and heso1-1 mutations could be multifactorial—an increase in miR173 levels in both hen1-8 urt1-1 and hen1-8 heso1-1 ( Fig 4D ) , an increase in the 22-nt form of miR173 in hen1-8 urt1-1 ( Fig 4C ) , and compromised uridylation of the ta-siRNAs themselves in hen1-8 heso1-1 [10] . We also examined the abundance of TAS1 , TAS2 and TAS3 ta-siRNAs in small RNA libraries . TAS3 ta-siRNAs were included as a control , as their trigger , miR390 [23] , was not affected by the urt1-1 mutation in terms of tailing ( S3 Fig ) . When normalized to total small RNAs , the abundance of TAS1 and TAS2 ta-siRNAs was much higher in hen1-8 urt1-1 than in hen1-8 , while that of TAS3 ta-siRNAs was not affected ( Fig 4F ) . hen1-8 heso1-1 was not included in the analysis as the global increase in miRNA and ta-siRNA levels prevented effective normalization . The above small RNA sequencing results described above revealed differential preferences for miR158 and miR173 forms by HESO1 and URT1 . For example , in vivo , full-length miR158 is mainly tailed by HESO1 while 1-nt truncated miR158 ( miR158-1 ) is mainly tailed by URT1 . To determine whether this reflected different substrate preferences for the two enzymes , we examined HESO1 and URT1 activities on miR158 and miR158-1 in vitro . As miR158-1 differs from miR158 both in length and in the nature of the 3’ nucleotide ( miR158-1 ends in C while miR158 ends in A ) , we also included three full-length miR158 forms ending in C , G , or U ( referred to as miR158A-C , miR158A-G , and miR158A-U , respectively ) in comparison to the natural miR158 ending in A . As the two enzymes required different buffer conditions for optimal activities , it was not reasonable to compare the activities of the two enzymes on the same substrate . But it was possible to compare the activities of an enzyme on different substrates . When comparing nucleotidyl transferase activities on different substrates , the disappearance of the substrate over a time course was considered as the criteria for preference for the substrate . Among the four full-length miR158 forms ( Fig 5A , lanes 1 , 3–4 ) , HESO1 had a clear preference for miR158A-U , as reflected by the disappearance of this substrate but not others at the earliest time point ( Fig 5A , lanes 6 , 9–10 ) . With longer time points , it was apparent that miR158A-G was the second most preferred substrate . At 4 min , less non-tailed miR158A-G was present compared to non-tailed miR158 or miR158A-C ( Fig 5A , compare lane 14 to lane 11 or 13 ) . At 10 min , while substantial amount of non-tailed miR158 or miR158A-C was present , almost all miR158A-G was tailed ( Fig 5A , compare lane 19 to lane 16 or 18 ) . URT1 showed a strong preference for miR158 ending in A , as the substrate was depleted at the earliest time point while the other miR158 forms still remained ( Fig 5B , compare lane 6 to lanes 8–10 ) . The preference for A-ending substrates is consistent with the finding that URT1 uridylates mRNAs with oligoadenylate tails in vivo [22] . The other three forms of miR158 ( miR158A-C , miR158A-G , and miR158A-U ) were similarly used by URT1 in the reaction time course ( Fig 5B , lanes 8–10 , 13–15 , and 18–20 ) . miR158-1 was the least favored substrate among the five miR158 forms tested for both HESO1 and URT1 ( Fig 5A and 5B ) . But miR158-1 was better tolerated by URT1 than by HESO1 , as it was tailed only slightly more slowly than miR158A-C , miR158A-G , or miR158A-U by URT1 ( Fig 5B , compare lane 12 to lanes 13–14 , and lane 17 to lanes 18–20 ) . But it was barely tailed by HESO1 when the full-length miR158 forms were substantially tailed ( Fig 5A , compare lane 12 to lanes 13–14 , and lane 17 to lanes 18–20 ) . This difference of the two enzymes could potentially explain the in vivo tailing of miR158-1 by URT1 but not HESO1 . We next tested whether tailing of miR158 or miR158-1 was more efficient with both HESO1 and URT1 acting together . In order to compare the activities of different enzymes , we had to use a single buffer , and we chose the URT1 buffer for all three reactions , URT1 alone , HESO1 alone , and URT1 and HESO1 together . Indeed , for both miR158 and miR158-1 , the two enzymes together tailed the miRNAs better than each enzyme alone ( S6 Fig ) . We previously showed that HESO1 is able to tail miR166 in a reconstituted AGO1-miR166 RISC [16] . We sought to determine whether URT1 had the capability to act on AGO1-bound miRNAs and to confirm the ability of HESO1 to tail AGO1-bound miRNAs in native miRISCs . To obtain native , AGO1-bound , but unmethylated miRNAs for use as substrates , we took advantage of the fact that miRNAs lack methylation and show drastically reduced uridylation in the hen1-2 heso1-2 urt1-3 background ( see Wang et al . , companion manuscript ) . AGO1 was immunoprecipated from this genetic background , and the immunoprecipate ( IP ) was subjected to western blotting to detect AGO1 and northern blotting to detect miR165/6 and miR172 . Both AGO1 and the two miRNAs were found in the IP ( Fig 6 and S7 Fig ) . In comparison to the miRNA species in wild-type plants , the miRNAs in the AGO1 IP from hen1-2 heso1-2 urt1-3 included both full-length and truncated species ( Fig 6 ) . The AGO1 IP was used as a substrate in reactions with URT1 or HESO1 and cold UTP . After the reactions , AGO1 was collected in the precipitate , and RNAs in both the precipitate ( associated with AGO1 ) and the supernatant ( released from AGO1 ) were detected by northern blotting using probes against miR165/6 or miR172 . HESO1 was able to tail the two miRNAs in native miRISCs ( Fig 6 ) . In fact , the lengths of tails added by HESO1 exceeded 100 nucleotides . Despite such long tails , the tailed miRNAs were still bound by AGO1 , as they were present in the precipitate rather than the supernatant ( Fig 6 ) . URT1 was also able to tail AGO1-bound miR165/6 and miR172 ( Fig 6 ) , but the lengths of tails introduced by URT1 were much shorter than those generated by HESO1 . The miRNAs tailed by URT1 were also associated with AGO1 ( Fig 6 ) . Given that both HESO1 and URT1 can tail miRNAs in native miRISCs and that tailed miRNAs in hen1 mutants are associated with AGO1 in vivo [12 , 15] , we asked whether tailed miRNAs could be functional . We previously observed that miR171a , which is 21-nt long ( S4D Fig ) and unable to trigger the biogenesis of secondary phasiRNAs from its target genes At2g45160 and At3g60630 in wild type , acquired this ability in hen1 mutants [15] . According to small RNA sequencing , 22-nt and 21-nt forms of miR171a were the two most abundant forms in hen1-1 and hen1-8 mutants [15] ( Fig 7A and 7B ) , and we hypothesized that the tailing of 21-nt miR171a to 22 nt endowed the ability to trigger phasiRNA biogenesis . But this hypothesis was not tested as the enzyme that tailed miR171a to 22 nt was unknown . It was not HESO1 , as in hen1-8 heso1-1 , the 22-nt form showed an increase in abundance , probably because further tailing of this form was reduced ( [15]; Fig 7B ) . We found that this enzyme was URT1 since the 21-nt form became the most abundant form in hen1-8 urt1-1 ( Fig 7A ) . In fact , the over-accumulation of miR171a ( 0 , 0 ) and miR171a ( 0 , 1 ) in hen1-8 urt1-1 and hen1-8 heso1-1 , respectively ( Fig 7A and 7B ) , indicates that URT1 tails full-length miR171a by one nucleotide in vivo and the 1-nt-tailed form is further tailed by HESO1 . To verify these results from small RNA sequencing , we performed northern blotting of miR171a at a single nucleotide resolution . In both hen1-8 and hen1-8 heso1-1 , the abundance of the 22-nt form was higher than that of the 21-nt form ( Fig 7C ) . In hen1-8 urt1-1 , the opposite was observed ( Fig 7C ) . Therefore , URT1 was responsible for the production of 22-nt miR171a by tailing miR171a by one nucleotide . Moreover , consistent with the cooperative tailing of miR171a by both URT1 and HESO1 , miR171a levels were higher in hen1-8 urt1-1 and hen1-8 heso1-1 as compared to hen1-8 ( Fig 7D ) . Next , we examined whether the urt1-1 mutation , which reduced the levels of 22-nt miR171a , affected the production of phasiRNAs triggered by miR171a in hen1-8 . From hen1-8 and hen1-8 urt1-1 small RNA libraries , secondary siRNAs mapping to At2g45160 ( a target of miR171a ) were normalized to total small RNAs and plotted along the At2g45160 gene ( Fig 7E , top panel ) . It was clear that these secondary siRNAs were reduced in abundance in hen1-8 urt1-1 . When the secondary siRNAs were examined for their phasing status , i . e . , whether they occurred in 21-nt intervals from one another , no difference was observed in the phasing scores in hen1-8 and hen1-8 urt1-1 ( Fig 7E , bottom panel ) . This indicated that phasiRNAs were produced from At2g45160 in both genotypes , but their abundance was much lower in hen1-8 urt1-1 . Therefore , the tailing of miR171a to 22 nt in hen1 by URT1 promotes miR171a-triggered phasiRNA biogenesis . Many miRNAs are normally 21-nt in length and they are tailed to various sizes including 22 nt in hen1 mutants . But miR171 is the only miRNA that acquires the ability to generate phasiRNAs in hen1 mutants [15] , suggesting that the 22-nt forms of most miRNAs are not functional . In addition , the expression of At3g03580 , a target of miR158 , was repressed more effectively in hen1 urt1 than in hen1 ( Fig 2E ) , despite the fact that miR158 was similar in abundance in the two genotypes . This suggested that tailed forms of miR158 are not as effective in target repression . We decided to examine the effects of tailing by URT1 on the activities of miRNAs in vitro using the slicer assay as the functional output of miRNAs . We immunoprecipitated AGO1 from hen1-2 heso1-2 urt1-3 , and used the IP as the substrate for the tailing reaction with URT1 . Following the tailing reaction , AGO1 was collected in the precipitate , washed , and incubated with a fragment of the PHB transcript ( a target of miR165/6 ) to assay the slicer activity of AGO1-miR165/6 ( a scheme of the procedure is shown in Fig 8A ) . While the AGO1 IP was able to cleave the PHB RNA , the AGO1 IP after the tailing reaction with URT1 failed to cleave the PHB RNA ( Fig 8B ) . miR156/6 and AGO1 were present after the URT1 reaction , as shown by northern blotting and western blotting , respectively ( Fig 8C and 8D ) . Tailing of miR165/6 by URT1 was also visible by northern blotting ( Fig 8C ) . To confirm that the loss of cleavage activity was due to miR165/6 tailing , we conducted the tailing reaction with heat-inactivated URT1 or the URT1 catalytic mutant . Neither enzyme affected the cleavage activity of miR165/6 ( Fig 8B–8D ) . This result was initially unexpected , as we did not expect 100% tailing of miR165/6 by URT1 . But upon closer examination of the profiles of miR165/6 in northern blotting ( Fig 8C ) , it seemed that most of the miR165/6 species were tailed by a small number of nucleotides , as the profiles looked different when functional URT1 was used .
In this study , we identify URT1 as a nucleotidyl transferase that tails unmethylated miRNAs and show that URT1 acts with the previously identified nucleotidyl transferase HESO1 in parallel or sequentially to tail various forms of the same miRNA in vivo . As nucleotidyl transferases , URT1 and HESO1 are similar in that both prefer UTP over the other three nucleotides and both are completely inhibited by 2’-O-methylation in their substrate RNA . These biochemical properties are consistent with molecular genetic observations that uridylated miRNAs are prevalent only in hen1 mutants [8] . URT1 and HESO1 also exhibit distinct substrate preferences , especially with regard to the identity of the 3’ nucleotide in the substrate RNA . Our biochemical studies suggest that HESO1 has the strongest preference for RNA ending in U whereas URT1 has the strongest preference for RNA ending in A . This preference , together with the tendency to use UTP instead of other nucleotides for both enzymes , could explain the predominant role of HESO1 in miRNA tailing in vivo . Once HESO1 adds a U to the end of a miRNA , regardless of the nature of its 3’ nucleotide , the resulting tailed miRNA ends in a U and is likely a preferred substrate for HESO1 . Therefore , HESO1 is likely able to hold on to the product of its reaction and use it as a substrate , i . e . , HESO1 could be a processive enzyme . URT1 , on the other hand , prefers A-ending miRNAs , but once it adds a U , the resulting miRNA is not a good substrate . In fact , this can be seen in the activity assay in Fig 5B ( lanes 6 , 11 , 16 ) , where the species with a few additional nucleotides persist . This suggests that URT1 is probably not a processive enzyme . Small RNA profiling in hen1-8 and hen1-8 urt1-1 in this study is consistent with this conclusion . We found that that URT1 mono-uridylates miR158 , miR171a , and miR173 in vivo . After mono-uridylation of miR171a and miR173 by URT1 , HESO1 further uridylates the mono-uridylated , U-ending miRNAs in vivo . When both enzymes are active in vivo , one would expect HESO1 to out-compete URT1 in miRNA tailing . When one enzyme is knocked out , such as in hen1-8 heso1-1 or hen1-8 urt1-1 , the remaining enzyme should in theory have access to all miRNAs . In hen1-8 heso1-1 , miRNA tailing is drastically reduced with monouridylation being the predominant forms left [10] . This is consistent with the conclusion that URT1 is not a highly processive enzyme . In hen1-8 urt1-1 , most miRNAs are still fully tailed , suggesting that HESO1 can act on most miRNAs . The ten miRNAs that show reduced tailing in hen1-8 urt1-1 must be refractory to HESO1 activity . In fact , most of the miRNAs end in C , A or G ( S8 Fig ) , which are non-preferred 3’ nucleotides for HESO1 . The exceptions are miR845a and b , for which the affected forms in hen1-8 urt1-1 end in U ( S6 Fig ) . It is unclear why HESO1 does not act effectively on these miRNAs in vivo . It should be noted that the preferences for the 3’ ending nucleotide cannot fully account for the substrate preferences of the enzymes , nor their processivity . For example , for both URT1 and HESO1 , miR158-1 , which ends in C , is not as good a substrate as miR158A-C , in which the last nucleotide of miR158 is mutated to C ( Fig 5 ) . The sequence of the 3’ region of the miRNA substrate probably also matters . There are ten potential nucleotidyl transferases in the genome . Two of them are now shown to tail unmethylated miRNAs . HESO1 and URT1 also act on mRNAs or mRNA fragments [16 , 22] . Both HESO1 and URT1 are completely inhibited by 2’-O-methylation in their miRNA substrates , it would be interesting to know whether any of the eight proteins can act on methylated miRNAs . It would also be interesting to know what RNA substrates these enzymes act on , such as siRNAs , other noncoding RNAs , or mRNAs . An important discovery of this study is that both HESO1 and URT1 can act on native miRISCs to tail miRNAs and that the tailed miRNAs remain bound by AGO1 in vitro . It is surprising that HESO1 is able to add more than 100 nucleotides to AGO1-bound miRNAs in vitro , as miRNAs in hen1 mutants have much shorter tails ( usually less than eight nucleotides [10 , 15] ) . As tailed miRNAs in hen1 mutants are bound by AGO1 in vivo [12 , 15] , it is likely that only miRNAs with short tails are found in vivo because only these species can be stably accommodated by AGO1 , i . e . , with the 5’ and 3’ ends of the miRNAs in the respective binding pockets in AGO1 . miRNAs with long tails are unlikely to have their 3’ end protected by the PAZ domain of AGO1 and are likely susceptible to degradation or 3’ trimming to generate miRNAs with shorter tails . Given that HESO1 and URT1 can act on AGO1-bound miRNAs and miRNAs with short tails can be accommodated by AGO1 , degradation may not be the only outcome of miRNA tailing . In this study , we show that tailing of AGO1-bound miR165/6 by URT1 nearly abolishes its target RNA cleavage activity . Most of the AGO1-bound miR165/6 species had short tails after the URT1 reaction and were bound by AGO1 , yet they lost their activity . This suggests that the tailed species are not properly positioned in AGO1 for optimal slicer activity . Our results on the expression of At3g03580 , a target of miR158 , are also consistent with tailed miR158 species not being functional ( Fig 2E ) . We suspect that miRNA tailing leads to reduced miRNA activity in general , but an exception is miR171a . Mono-uridylation of 21-nt miR171a by URT1 in hen1 mutants triggers the production of phasiRNAs from a miR171a target gene . This demonstrates that mono-uridylated miR171a is functional in vivo and that 3’ tailing alters the activities of this miRNA .
All Arabidopsis strains are in the Columbia background except for hen1-2 heso1-2 urt1-3 ( generated in the companion manuscript ) , which is in the Landsberg background . Seeds of nine ntp mutants were obtained from the Gabi-Kat collection or ARBC collection ( see S1 Table for details ) . hen1-8 ntp double mutants were made by crossing hen1-8 with ntp mutants and genotyping F2 populations for plants homozygous for both hen1-8 and ntp mutations . Plants were grown under long day ( 16 h light/ 8 h darkness ) conditions at 22°C . Towards the construction of the pURT1:URT1-GFP plasmid , a 1 . 4 kb fragment upstream of the URT1 coding region was amplified by PCR with primers 3-Kpn1-1610F ( PF ) and URT1-pst1-PR as the promoter , and cloned into TSK108 , a pENTRY-D-topo-based Gateway entry vector , at KpnI and PstI sites . Subsequently , the cDNA ( without the stop codon ) was amplified by PCR with primers URT1-pst1-CDSF and URT1-SPE1-CDSR and inserted next to the promoter at PstI and SpeI sites . Then the promoter-cDNA fragment was moved into pMDC107 [24] by LR reaction . The plasmid was used to transform hen1-8 urt1-1 plants by Agrobacterium ( GV3101 ) -mediated floral dip transformation . To construct the pET32a-URT1_WT plasmid for the expression of wild-type URT1 in E . coli , the coding sequence of URT1 was amplified using primers URT1-sac1-F and URT1-Xho1-R and cloned into pET-32a . The orientation of the insertion was confirmed by sequencing . To construct the pET32a-URT1_M plasmid for the expression of the catalytic mutant of URT1 in E . coli , mutagenesis of URT1 was first performed by PCR with primers that incorporated the D491A and D493A mutations in the URT1 coding sequence . Primers URT1-Sac1-F and URT1-DADA-R were used to generate the 5’ URT1 fragment; primers URT1-DADA-F and URT1-Xho1-R were used to generate the 3’ URT1 fragment . The two fragments were annealed and used as the template to amplify the full-length URT1m using URT1-Sac1-F and URT1-Xho1-R as primers . This full-length fragment was cloned into pET-32a . The orientation of the insertion was confirmed by sequencing . See S3 Table for sequences of primers . Reverse transcription and real-time PCR were performed as described [25] . Total RNAs were prepared from inflorescences , and converted to cDNAs using Superscript III reverse transcriptase ( Invitrogen ) and oligo-dT . The cDNAs were then used as templates for real-time PCR with gene-specific primers . Real-time PCR was performed in triplicates using on a Biorad IQcycler apparatus with the Quantitech SYBR green kit ( BioRad ) . The ACTIN8 gene was used as the internal control . Primers used are listed in S3 Table . RNA isolation and northern blotting to detect small RNAs were performed as described [26] . Total RNAs were extracted from inflorescences or AGO1 immunoprecipitate using the TRIzol reagent ( Invitrogen ) . 5′-end-labeled ( 32P ) antisense DNA oligonucleotides were used to detect miRNAs . Sequences of probes are shown in S3 Table . A phylogenetic analysis was performed for ten putative Arabidopsis nucleotidyl transferases , MUT68 from Chlamydomonas reinhardtii , TUT4 from Homo sapiens , and Cid1 from Schizosaccharomyces pombe . Sequences corresponding to the NT_PAP_TUTase ( cd05402 ) domain [27] from these proteins were aligned using ClustalW ( http://www . ebi . ac . uk/Tools/msa/clustalw2/ ) with default parameters [28] . The phylogenetic tree was generated using MEGA5 [29] . Cloning of small RNAs was carried out as described [30] . 50 μg total RNAs were resolved in a 15% polyacrylamide gel and 15–40 nt small RNAs were eluted from an excised gel piece . The small RNAs were ligated sequentially with the 3' and 5' adapters using the Small RNA Sample Preparation Kit ( Illumina ) . Sufficient amounts of products were obtained by performing a reverse transcription reaction followed by a low-cycle PCR amplification . The libraries were barcoded and sequenced in one lane on an Illumina HiSeq2000 . Small RNA reads that passed Illumina’s quality control were separated into different genotypes according to the indexes . These high-quality small RNA reads were then mapped to the TAIR10 Arabidopsis genome using Bowtie [31] . The reads that matched to annotated tRNAs/rRNAs/snRNAs/snoRNAs were removed . The total numbers of reads that passed the quality and tRNA/rRNA filters for the various genotypes and replicates are listed in S2 Table . To analyze miRNA 3’ tailing , a previously-developed bioinformatics pipeline was employed [15] . Briefly , any small RNA read that could not be perfectly mapped back to the genome was trimmed one nucleotide at a time from the 3’ end until the remaining sequence was perfectly mapped to the genome . The trimmed 3’ sequence was designated as the “tail” whereas the longest 5’ genome-mapped component ( the “head” ) was compared to all annotated miRNAs in miRBase to ascertain from which miRNAs they were derived . To quantify the extent of tailing , Arabidopsis miRNAs annotated in miRBase v17 [32] were examined . Small RNA reads with the 5’ head perfectly aligning to each one of the annotated miRNAs were identified , and the amount of tailing was calculated as the ratio of the number of reads with tails to that of total reads of variants derived from a particular miRNA . Small RNA phasing analysis was conducted as previously described [33] . Small RNA abundances from the antisense strand were combined with those of the sense strand , based on an anticipated 2 nt overhang at their 3’ ends , which is a typical feature of Dicer-produced small RNA duplexes . Phasing scores and combined abundances of small RNAs were graphed using a customized Perl script . The pET32a-URT1_WT and pET32a-URT1 _M plasmids were transformed into the E . coli strain BL21 Star™ ( DE3 ) for protein expression . The transgenic E . coli strains were cultured at 30°C until the OD reached 0 . 5 . IPTG was added to a final concentration of 0 . 1 mM and the culture was incubated at 16°C overnight . The recombinant proteins were purified using Ni-NTA agarose ( Invitrogen ) under native conditions following the manufacturer's instructions . After the extract containing a recombinant protein was loaded onto the column , the column was washed four times with the following wash buffers: wash buffer 1 ( 200 mM NaCl , 50 mM Tris-HCl pH 8 . 0 , 40 mM imidazole ) , wash buffer 2 ( 200 mM NaCl , 50 mM Tris-HCl pH 8 . 0 , 60 mM imidazole ) , wash buffer 3 ( 200 mM NaCl , 50 mM Tris-HCl pH 8 . 0 , 100 mM imidazole ) , and wash buffer 4 ( 200 mM NaCl , 50 mM Tris-HCl pH 8 . 0 , 120 mM imidazole ) . Then the recombinant protein was eluted with elution buffer ( 200 mM NaCl , 50 mM Tris-HCl pH 8 . 0 , 500 mM imidazole ) . The URT1 enzymatic activity assays in Fig 3 were conducted in 10 μl reaction mixtures containing 4 . 8 pmole recombinant wild-type or mutant URT1 , 1 μl of 40 mM miR173 and 1 mM of different nucleotide triphosphates in the URT1 reaction buffer ( 20 mM Tris-HCl pH 8 . 0 , 50 mM NaCl , 0 . 7 mM MnCl2 , 10 mM MgCl2 , 0 . 5 mM DTT , and 100 μg/mL BSA ) . Reactions were conducted at room temperature for 0–20 min , and stopped by the addition of formamide dissolved in RNA loading dye . The reaction mixtures were denatured at 95°C for 5 min , incubated on ice for 5 min , and loaded on a 15% polyacrylamide urea gel . After gel electrophoresis , the gel was stained by ethidium bromide and imaged with a Gel Doc™ XRS+ imaging system ( BIO-RAD ) . The URT1 enzymatic activity assays in Fig 5 were conducted as described above except that the RNA oligonucleotide substrates were 5’ 32P-labeled and the products were visualized by autoradiography . 1 pmole of RNA oligonucleotides and 8 pmole of URT1 were present in the reactions . The HESO1 enzymatic assays in Fig 5 were performed as described [10] . 1 pmole of RNA oligonucleotides and 2 pmole of HESO1 were present in the reactions . For the 5’ labeling of RNA oligonucleotides , a 50 μl reaction mixture containing 100 μM oligonucleotide , 20 U T4 Polynucleotide Kinase ( New England Biolabs ) , 1X T4 PNK buffer and 4 μl ATP [γ-32P] ( 3000Ci/mmol 10mCi/ml from PerkinElmer ) was incubated at 37°C for 1 hour . The RNA was then purified with Illustra MicroSpin™ G-25 Columns ( GE Healthcare ) according to the manufacturer’s instructions . The RNA oligonucleotides were resolved in a 15% denaturing polyacrylamide gel , and gel pieces containing the full-length RNAs were excised , and the RNAs were eluted and used in the URT1 or HESO1 reactions . The URT1 and HESO1 enzymatic activity assays in S6 Fig were conducted in 10 μl reaction mixtures containing 1 pmole of 5’ 32P-labeled miR158 or miR158-1 , enzymes ( see below ) , and 1 mM UTP in the URT1 reaction buffer ( described above ) . For the reactions with miR158 , 4 pmole URT1 alone , 4 pmole HESO1 alone , or 4 pmole URT1 and 4 pmole HESO1 together were used . The reaction mixtures were incubated for 1min at room temperature . For reactions with miR158-1 , 8 pmole URT1 alone , 2 pmole HESO1 alone or 8 pmole URT1 and 2 pmole HESO1 together were used . The reaction mixtures were incubated at room temperature for 30 s . 0 . 4–1 . 0g of seedling tissue from hen1-2 heso1-2 urt1-3 plants was collected and ground to a fine powder in liquid nitrogen . 1 ml of IP buffer ( 50 mM Tris pH 7 . 5 , 150 mM NaCl , 10% Glycerol , 0 . 1% NP-40 , 4mM MgCl2 , 5mM DTT and 1x protease inhibitor cocktail ( Roche ) ) was added to the powder . The suspension was incubated at 4°C for 30 min and centrifuged at 16 , 000g for 15 min at 4°C . The supernatant was collected , filtered through 2 lays of Miracloth , and centrifuged as before . The supernatant was transferred into a new tube and pre-cleared with Dynabeads-Protein-A ( Life Technologies ) for 1 h at 4°C . The supernatant was separated from the beads using a magnetic stand and transferred into a new tube . The extract was then mixed with 2 μl of AGO1 antibody ( Agrisera ) and the mixture was incubated for 2 h with gentle shaking at 4°C . 20 μl pre-cleared Dynabeads-Protein-A was added and incubation was continued for another hour . The beads were washed four times with 1 ml wash IP buffer . Finally , the beads ( i . e . , AGO1 immunoprecipitate ) were collected with a magnetic stand . AGO1 IP was first performed as described above . The beads ( AGO1 immunoprecipitate ) were equally split into four portions , two for URT1 reactions and two for HESO1 reactions . The beads were washed three times with the URT1 or the HESO1 reaction buffer . After the washes , the beads were fully resuspended and equally split into two tubes ( one for enzyme reaction and one for “no enzyme” control ) . Subsequently , the beads were collected and added to a 20 μl reaction mixture containing 0 . 7 pmole 6XHis-HESO1 or 38 . 5 pmole 6HisXURT1 , reaction buffer ( described above or in [10] ) and cold UTP . The reactions were incubated for 40 min , the beads were separated from the supernatant with a magnetic stand , and RNA extraction was performed from the beads and the supernatant . Finally RNAs were resolved by gel electrophoresis and subjected to northern blotting to detect miR165/6 and miR172 . AGO1 IP was first performed as described above using 0 . 5g of hen1-2 heso1-2 urt1-3 seedlings . The beads ( AGO1 immunoprecipitate ) were washed three times with the URT1 reaction buffer , and split into 3 equal portions , to be used for reactions with URT1 , denatured URT1 ( denaturing by boiling for 5 min ) , and the URT1 catalytic mutant ( URT1m ) , respectively . Subsequently , each portion of beads was collected and added to a 60 μl reaction mixture containing 19 pmole 6XHis-URT1 ( or denatured URT1 or URT1m ) , reaction buffer ( described above ) and cold UTP . The reactions were carried out at room temperature for 40 min; afterwards the beads were collected and washed 3 times with the IP buffer . The beads in each tube were further split into three equal portions , with one portion to be used for western blotting to quantify AGO1 , another portion to be used for northern blotting to quantify AGO1-bound miR165/166 , and the third portion to be used for the slicer assay . The beads in the third portion were collected and added to a 20 μl reaction mixture containing 15μl IP buffer , 4μl 5 X cleavage buffer and 1μl uniformly radiolabeled PHB ( see the in vitro transcription section below ) , a target of miR165/6 . The reactions were incubated for 1h , and RNA extraction was performed . Finally . RNAs were resolved by gel electrophoresis and visualized by autoradiography . 5 X cleavage buffer: 5 mM ATP , 1 mM GTP , 6 mM MgCl2 , 125 mM creatine phosphate , 150 mg/mL creatine kinase and 2 unit/mL RNasin RNase Inhibitor . The template for in vitro transcription is generated by PCR using primers specific for the miR165/166 target gene PHB . The PCR-amplified PHB fragment is about 300 bp that contains the miR165/166 target region . T7 promoter sequence is added to the 5’end of the forward primer . The Riboprobe T7 kit ( Promega ) was used to generate transcripts from this PHB fragment . In a 20 μl reaction , 1μl DNA template and 3μl UTP [α-32P] ( 3000Ci/mmol 10mCi/ml from PerkinElmer ) was added . The reaction was incubated at 37°C for 1 hour , and then stopped by the addition of formamide dissolved in RNA loading dye . The reaction mixtures were denatured at 95°C for 5 min , incubated on ice for 5 min , and loaded on a 5% polyacrylamide urea gel . The band of the expected size was excised and the RNAs were eluted and used in the cleavage assay . The small RNA sequencing data in this study have been deposited at the GEO repository under the ID# GSE61362 .
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The tailing of RNAs with non-templated uridines , known as uridylation , is often associated with RNA degradation . We previously identified HESO1 as a nucleotidyl transferase that uridylates microRNAs ( miRNAs ) to lead to their degradation in Arabidopsis . But HESO1 cannot account for all the miRNA uridylation activity in vivo . Here , we have uncovered UTP:RNA URIDYLYLTRANSFERASE 1 ( URT1 ) as another nucleotidyl transferase that uridylates miRNAs . HESO1 and URT1 have different substrate preferences and act cooperatively to tail miRNAs . We show that both enzymes are able to act on ARGONAUTE1 ( AGO1 ) -bound miRNAs and that the tailed miRNAs stay bound by AGO1 . We show that URT1-mediated tailing affects the activities of miR165/6 and miR171a differently . This study reveals intricate miRNA uridylation processes as well as functional outcomes of miRNA uridylation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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Distinct and Cooperative Activities of HESO1 and URT1 Nucleotidyl Transferases in MicroRNA Turnover in Arabidopsis
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The Hippo pathway plays a key role in regulating cell turnover in adult tissues , and abnormalities in this pathway are consistently associated with human cancers . Hippo was initially implicated in the control of cell proliferation and death , and its inhibition is linked to the expansion of stem cells and progenitors , leading to larger organ size and tumor formation . To understand the mechanism by which Hippo directs cell renewal and promotes stemness , we studied its function in planarians . These stem cell–based organisms are ideal models for the analysis of the complex cellular events underlying tissue renewal in the whole organism . hippo RNA interference ( RNAi ) in planarians decreased apoptotic cell death , induced cell cycle arrest , and could promote the dedifferentiation of postmitotic cells . hippo RNAi resulted in extensive undifferentiated areas and overgrowths , with no effect on body size or cell number . We propose an essential role for hippo in controlling cell cycle , restricting cell plasticity , and thereby preventing tumoral transformation .
The same developmental processes that drive embryogenesis also regulate the constant cell renewal required throughout the natural life span of the organism . Successful cell renewal relies on multiple events , including proliferation and differentiation of progenitor cell populations and death of unnecessary cells . Failure to correctly coordinate these events can lead to diseases such as cancer . Of the multiple molecular mechanisms involved in the control of cellular renewal , the Hippo signaling pathway has emerged as a key hub . Although first identified as a key regulator of organ size through the control of cell death and proliferation [1–4] , growing evidence suggests additional pivotal roles in coordinating stem-cell maintenance , cell differentiation , cell fate decisions , and cell survival [5–10] . At the core of the Hippo pathway is a kinase cascade that phosphorylates the nuclear effector Yorkie ( Yki ) ( YAP/TAZ in vertebrates ) and targets it for degradation . When the pathway is inactive , dephosphorylated Yki enters the nucleus to regulate gene expression [11 , 12] . In most organs and tissues , such as the liver , heart , and skin , loss of Hippo signaling , or elevated activity of Yki/YAP/TAZ , is associated with stem-cell expansion , inhibition of cell differentiation , the appearance of overgrowths , and tumorigenesis [2 , 13–15] . In line with these observations , YAP/TAZ is hyperactivated in most human cancers [16] . Importantly , in regenerative contexts , YAP/TAZ promotes regeneration of the same organs in which it produces tumors under homeostatic conditions [17 , 18] . The Hippo signaling pathway therefore appears to exert a general function , promoting stemness or amplifying the population of progenitors , that is beneficial in regenerating tissues but harmful in homeostatic conditions [2 , 8 , 14] . Despite its crucial role in everyday tissue renewal and in the maintenance of healthy organisms , the mechanism by which Hippo signaling promotes stemness remains unclear . Studies performed in several tissue types have extensively demonstrated the positive effect of Hippo inhibition on cell proliferation and the consequent expansion of the resident population of stem cells [7 , 19–22] . However , recent studies in the liver and intestine , as well as in embryonic stem ( ES ) and induced pluripotent stem ( iPS ) cell cultures , have shown that both Hippo down-regulation and YAP/TAZ nuclearization increase the plasticity of differentiated cells , allowing their dedifferentiation towards a stem-cell fate [9 , 23–25] . The plasticity of cells within the hierarchical organization of a tissue has major implications for regenerative medicine and cancer [26–28] . To better understand the role of the Hippo pathway in driving adult cellular renewal and specifically in promoting cell stemness , we studied its function in planarians . Owing to the presence of a population of pluripotent adult stem cells ( called cNeoblasts ) [29 , 30] , planarians have the ability to constantly grow and degrow depending on food availability and to regenerate any missing body part within a few days . Several lineage-restricted cycling cells ( or lineage-restricted neoblasts ) and their postmitotic descendants can be identified in planarians based on the expression of tissue-specific transcription factors [31 , 32] . In addition to the presence of a stem cell population , the continuous activation of signaling cues that coordinate cell death and cell renewal and direct precise cell fate decisions allow planarians to maintain proportioned and functional organs during growth/degrowth and regeneration . This continuous active regulation of the stem cell and postmitotic cell compartments makes the planarian an ideal in vivo model of the different events underlying homeostatic cell renewal and tissue regeneration . Furthermore , in contrast to most models of regeneration , planarian regeneration is fueled directly by the expansion of an abundant stem cell population , precluding the need for dedifferentiation [33] . Here , we investigate whether down-regulation of Hippo signaling exerts its stemness-promoting effect by increasing the proliferation of resident stem cells or by promoting cell dedifferentiation . We show that inhibition of Smed-hippo ( referred to hereafter as hippo ) in planarians reduces apoptotic activity and increases mitotic rates . However , this imbalance between cell death and mitotic activity does not lead to an increase in planarian body size or cell number , possibly because hippo RNAi does not increase the number of cycling cells but rather blocks mitotic exit and increases necrotic cell death . hippo ( RNAi ) planarians develop overgrowths and extensive regions composed of undifferentiated cells , accompanied by a general decrease in the number of differentiated cells throughout the body . A detailed study of the epidermal lineage reveals that hippo is required to determine the hierarchical transitions necessary for proper epidermal differentiation from epidermal-restricted stem cells to differentiated epidermal cells . Finally , our results indicate that hippo is required to maintain the differentiated state in planarian cells , because hippo inhibition could promote dedifferentiation of postmitotic cells . Overall , our results indicate that the overgrowths and undifferentiated regions observed after hippo inhibition in planarians are not caused by an imbalance between cell death and proliferation but by the inability of cells to reach and maintain the appropriate fate . We propose an essential role for hippo in restricting cell plasticity and hence in preventing tumoral transformation .
To study the role of the Hippo pathway in planarians , we conducted a functional analysis of hippo , the core element of the pathway , in Schmidtea mediterranea [34] . In situ hybridization ( ISH ) and in silico searches in the single-cell database Planaria SCS [35] indicated that hippo is expressed in cells of all types ( S1A and S1B Fig ) . To decipher the possible function of hippo during homeostatic cell renewal in planarians , we injected animals with hippo double-stranded RNA ( dsRNA ) for 3 weeks ( see Material and methods and S1C Fig ) . This resulted in a significant decrease in hippo mRNA levels beginning during the first week of treatment ( S1D Fig ) . The appearance of unpigmented regions , mainly around the body margin , was observed during the third week of hippo inhibition . Over time , these regions became larger or evolved into unpigmented overgrowths ( Fig 1A and S1E Fig ) . To determine whether the appearance of overgrowths was caused by an imbalance between cell death and cell proliferation , we performed TUNEL and caspase-3 assays and quantified mitotic activity by anti-phospho-Histone 3 immunostaining ( H3P ) . After 2 weeks of inhibition , hippo ( RNAi ) animals exhibited a reduction in cell death compared to controls that became more evident after 3 weeks of inhibition ( Fig 1B and S2A and S2B Fig ) . After 3 weeks of hippo RNAi , the number of apoptotic cells was reduced compared to controls , and mitotic activity was increased ( Fig 1C and S2C Fig ) . Nonetheless , measurement of body area revealed no difference between hippo ( RNAi ) planarians and controls ( Fig 1A and 1D ) . Quantification of the total number of cells using fluorescence-activated cell sorting ( FACS ) or a Neubauer chamber also revealed no differences in cell number between hippo ( RNAi ) and control planarians ( Fig 1E and S2D Fig ) . Our results thus indicate that Hippo promotes apoptotic cell death and controls mitotic activity and that its inhibition leads to the formation of unpigmented regions and overgrowths , without affecting animal size or cell number . Studies using other animal models have reported that hippo dysregulation results in defects in cell cycle progression [36 , 37] . This effect could provide a plausible explanation for our observation that the decrease in cell death and increase in mitotic activity in hippo ( RNAi ) animals do not lead to changes in cell number . To test this hypothesis , we treated cells with 5-ethynyl-2′-deoxyuridine ( EdU ) and analyzed the proportion of cells in M and S phase 16 h later in hippo ( RNAi ) animals and corresponding controls ( S3A Fig ) . We found comparable numbers of EdU+ cells in hippo ( RNAi ) animals and controls , indicating that similar numbers of cells enter the cell cycle in both conditions ( Fig 2A and S3B Fig ) . Moreover , double staining with anti-EdU and anti-H3P revealed an increase in the number of EdU+/H3P+ double-positive cells in hippo ( RNAi ) animals versus controls ( Fig 2B and S3B Fig ) . This suggests that in hippo ( RNAi ) animals , cells either transition faster from S to M phase and/or fail to complete M phase . The higher number of EdU-/H3P+ cells in hippo ( RNAi ) animals versus controls ( Fig 2C and S3B Fig ) indicates that the former group harbors a greater number of cells that are in M phase but have not passed through S phase in the previous 16 h . Thus , hippo RNAi results in the trapping of cells in M phase but does not affect the number entering the cell cycle ( Fig 2D ) . This could explain why the increase in the number of H3P+ cells does not translate to an increase in cell number . However , we cannot rule out the possibility that hippo inhibition results in faster transit of cells from S to M phase . To further understand the role of hippo in the cell cycle , we examined the organization of the mitotic spindle and chromosomes in dissociated cells from hippo ( RNAi ) animals by double immunostaining with anti-α-tubulin and anti-H3P antibodies . The results revealed abnormal microtubule organization of prophase/prometaphase spindles and spindle poles in hippo ( RNAi ) cells ( Fig 2E ) . Similarly , metaphase cells showed disorganized and less dense arrays of spindle microtubules , as well as chromosome alignment defects ( Fig 2E ) . Furthermore , in hippo ( RNAi ) cells , more than a half of all anaphases appeared in an early phase , while in controls , all were classified as late anaphases . Half of the early anaphases in hippo ( RNAi ) cells were characterized by a disorganized and less dense microtubule array ( Fig 2E ) . This result supports an essential role of hippo in the normal cell cycle progression and is consistent with the increase in the number of cells in M phase , but not S phase , observed after hippo RNAi . In agreement with the role of Hippo in cell cycle progression and specifically in the mitotic phase , we found that several genes related to cytokinesis and mitotic spindle organization were differentially expressed in the hippo ( RNAi ) RNA sequencing analysis ( RNAseq ) ( S1 Table ) . Importantly , these included genes already known to be regulated by Mst1/2 or Lats1/2 and mainly involved in spindle orientation ( afadin , Drosophila discs large , polo-like kinase 1 ) [38–40] ( S1 Table ) . Detailed analysis of the overgrowths caused by hippo inhibition ( Fig 3A ) revealed that they are caused by the accumulation of cells in the subepidermal region or the mesenchyme ( Fig 3B and S4A Fig ) and in some cases arise from the submuscular plexus region ( S1–S3 Movies ) . In line with the unpigmented appearance ( Fig 3A ) , which indicates that epidermal cells cannot produce pigment and thus are not terminally differentiated , we observed abnormal distribution of β-catenin-2 , a component of adherens junctions , in the epidermal cells of the overgrowths [41] ( Fig 3B , S1–S3 Movies ) . The defects in cell differentiation also affected the neural plexus , as evidenced by the absence of anti-synapsin staining in the overgrown areas ( Fig 3B ) . The accumulation of smedwi-1+/ SMEDWI-1+ cells in subepidermal overgrowths and among some cells of the corresponding epidermis ( Fig 3B and S4A Fig ) indicates that the overgrowths are primarily composed of undifferentiated cells . The accumulation of mitotic cells in or around the overgrowths ( Fig 3B and S1–S3 Movies ) confirms loss of the differentiated state . In addition to the specific overgrown regions , broader unpigmented areas were also observed in hippo ( RNAi ) animals ( Fig 3A ) . Analysis with specific markers revealed that differentiated structures such as the nervous system , the eyes , and the digestive system were not properly renewed or maintained in those unpigmented areas ( Fig 3C–3C” and S4B Fig ) . Furthermore , hippo ( RNAi ) animals had a poorly developed digestive system , smaller pharynx and eyes ( which , in some cases , were almost absent ) , and smaller brains ( S4B Fig ) , consistent with general defects in the maintenance of differentiated structures . Notably , the smaller brains appeared to be surrounded by ectopic mitotic cells ( S4B Fig ) . Analysis of the hippo ( RNAi ) RNAseq further indicated that most of the markers associated with terminal differentiation of multiple cell types ( opsin , pantothenate kinase 1 , synapsin , tropomyosin ) were down-regulated ( Fig 3D ) , consistent with a general defect in the process of cell differentiation or maintenance of the differentiated state . Quantification of the number of dopaminergic and serotonergic neurons by ISH with the corresponding markers ( tyrosine hydroxylase and tryptophan hydroxylase 1 ) further confirmed the general decrease in the number of differentiated neurons in hippo ( RNAi ) planarian heads ( Fig 3E ) . In several animals , the disappearance of differentiated structures coincided with the presence of cell-depleted regions ( Fig 3B and 3C ) . Therefore , using in vivo propidium iodide ( PI ) incorporation analysis , we investigated whether a general increase in cell death occurred in hippo ( RNAi ) animals . The results revealed an increase in PI+ cells in hippo ( RNAi ) animals ( S5 Fig ) . Because we previously showed that caspase-dependent cell death is decreased in hippo ( RNAi ) animals , we can conclude that necrotic cell death is increased . This increase in necrosis could compensate for the decrease in apoptosis and contribute to the maintenance of cell number in hippo ( RNAi ) animals . Taken together , these data indicate that Hippo plays an important role in the maintenance or renewal of differentiated tissues in planarians and that its inhibition leads to the appearance of extensive regions of undifferentiated cells that accumulate in overgrowths . In regenerative contexts , Yki/YAP nuclearization induced after Hippo inhibition or direct Yki/YAP overactivation is associated with increased proliferation and improved regenerative capacity [17] , [18] . Analysis of the effect of hippo inhibition following head and tail amputation ( S6A Fig ) revealed an increase in mitotic rate but the production of smaller blastemas ( Fig 4A and 4B ) , in which new tissues such as the brain and digestive system failed to properly differentiate ( S6B and S6C Fig ) . Accordingly , numbers of differentiated neural cell types , such as dopaminergic neurons ( th+ ) and eye cells ( ovo+ cells in the eye ) [42] were reduced after hippo inhibition ( Fig 4C and S6D Fig ) . Interestingly , despite the increase in mitotic rates and the defects in differentiation , overgrowths were never observed in regenerating hippo ( RNAi ) animals . Although Yki/YAP is a highly evolutionarily conserved downstream element of the Hippo pathway [5] , it has been proposed that Yki does not act downstream of Hippo in planarians [34] . To investigate the possible conservation of Hippo-Yki signaling in the control of planarian cell differentiation , we generated a specific anti-Yorkie antibody to determine the levels and pattern of Yki expression . Both western blot and immunohistochemical analysis revealed decreases in Yki levels in yki ( RNAi ) animals , as expected ( S7 Fig ) . By contrast , in hippo ( RNAi ) planarians , Yki protein levels were specifically up-regulated in the nucleus ( S7 Fig ) , suggesting conservation of a Hippo-Yki signal in planarians . We next investigated whether yki plays a role in cell differentiation in planarians . Inhibition of yki in regenerating animals led to an increase in the numbers of differentiated neurons and photoreceptors ( Fig 4C and S6D Fig ) , in direct opposition to the phenotype observed following hippo inhibition . In agreement with our results , a recent study [43] reported a general increase in the numbers of several types of differentiated cells in yki ( RNAi ) planarians . Taken together , these results indicate that a conserved Hippo-Yki signal regulates cell differentiation during planarian regeneration . In contrast to the effect observed in vertebrate systems [17 , 18] , in planarians , hippo inhibition , and hence Yki nuclearization , blocks differentiation and decreases the regenerative response . The epidermal lineage is the most abundant in planarians and its progression and determination is well understood [44] . Epidermal maturation requires temporally correlated transition states in planarians , in which stem cells ( smedwi-1+ ) become postmitotic and start to sequentially express nb21/32 , agat , and vimentin ( vim ) [44 , 45] . In parallel , epidermal precursors migrate from the inner parenchyma towards the epidermis [44] . Thus , proliferating cells are mainly found in the inner part of the animal and postmitotic epidermal cells are found at the periphery . Interestingly , in hippo ( RNAi ) planarians we detected a large number of mitotic cells in the periphery , where overgrowths and unpigmented regions were mainly found ( Fig 5A ) . Because this region should mainly contain postmitotic epidermal precursors [44] , we reasoned that the process of differentiation and/or cell fate maintenance of the epidermal lineage may be impaired in hippo ( RNAi ) animals . In agreement with this hypothesis , we found that hippo was expressed in all epidermal lineage cells ( S1A Fig and S8A Fig ) . To gain further insight into cell fate progression in hippo ( RNAi ) animals , we analyzed the number and distribution of mitotic cells ( H3P+ ) , stem cells ( smedwi-1+ ) , and postmitotic epidermal cells ( nb21/32+ , agat+ , or vim+ ) . First , we quantified H3P+ cells in 4 different regions ( inner to outermost ) in transverse sections ( Fig 5A ) . We observed a significant increase in the number of mitotic cells ( H3P+ ) in the 2 outermost regions of hippo ( RNAi ) animals as compared with controls ( S5A and S8B Figs ) . vim+ cells were located mainly in the epidermis ( fully differentiated cells ) of control animals but were predominantly detected in the mesenchyme of hippo ( RNAi ) animals ( Fig 5B and 5B′ ) . This indicates that hippo RNAi impairs the acquisition or maintenance of epithelial fate or the migration of epidermal cells . We detected higher numbers of vim+/ SMEDWI-1+ cells in the mesenchyme of hippo ( RNAi ) animals versus control animals , in which these cells were virtually absent from the mesenchyme ( Fig 5B–5B″ ) . This finding , together with the presence of ectopic mitotic cells , suggests impairment of the differentiation or fate maintenance , but not the migration , of epidermal cells following hippo inhibition . Quantification of cells that were double positive for different epidermal markers revealed an increase in smedwi-1+/agat+ , nb+/agat+ , and agat+/vim+ cells in hippo ( RNAi ) animals versus controls ( Fig 5C ) . This increase in bivalent cells in hippo ( RNAi ) animals is consistent with failure of the epidermal cells to progress appropriately through the hierarchical transitions that occur during epidermal lineage specification and suggests that they are unable to maintain a defined fate . Interestingly , double labeling of H3P+/agat+ , H3P+/nb32+ , or H3P+/smedwi-1+ revealed that mitotic cells were always smedwi-1+ but never agat+ nor nb32+ in either hippo ( RNAi ) animals or controls ( S8C Fig ) . Although we cannot exclude the possibility that ectopic mitotic cells could arise from a different lineage or from aberrant migration of stem cells , our findings suggest that mitotic cells never express postmitotic markers . Supporting the view that hippo inhibition interferes with specification of the epidermal lineage , analysis of the hippo ( RNAi ) RNA sequence revealed an increase in the expression of markers of ζ-neoblasts ( zfp-1 and p53 ) , which are precursors of the epidermal lineage [31] ( Fig 5D ) . This increase could be caused by an increase in the number of ζ-neoblasts . However , we found that while expression levels of smedwi-1 , a general marker of stem cells , decreased in the transcriptome ( Fig 5D ) , the number of cells expressing this marker was unchanged in hippo ( RNAi ) animals ( S8D Fig ) . As such , the increased expression of ζ-neoblast markers could also be due to increased expression of those markers in ζ-neoblasts or to incorrect acquisition of their expression by other cell types . Taken together , our analysis of the epidermal lineage reveals an increase in the population of cells co-expressing cell markers that define different epidermal cell lineages in hippo ( RNAi ) animals , as well as mislocalization of these markers ( Fig 5E ) . Thus , precursors and differentiated epidermal cells are both improperly defined and mislocalized . These results indicate that hippo is essential for the acquisition and/or maintenance of cell fate in the epidermal lineage . The presence of large numbers of undifferentiated cells and overgrowths following hippo RNAi could be explained either by defective differentiation of stem cells towards a specific fate or by a dedifferentiation process in which postmitotic cells are unable to maintain the committed state and begin to express stem-cell markers . To investigate the possibility that postmitotic cells undergo dedifferentiation , we depleted the stem-cell population in planarians through X-ray irradiation followed by the inhibition of hippo over 4 consecutive days ( S9A Fig ) . ISH for smedwi-1 revealed that after lethal irradiation ( 60 Gy ) no smedwi-1+ cells were detectable in either controls or hippo ( RNAi ) animals ( S9B Fig ) . However , in planarians that received irradiation at sublethal doses ( 17 . 5 Gy ) , hippo inhibition increased the number of smedwi-1+ cells ( S9C Fig ) . Importantly , anti-H3P immunostaining revealed no difference in the number of mitotic cells between sublethally irradiated/hippo ( RNAi ) planarians and their corresponding controls , indicating that the increase in smedwi-1+ cells cannot be attributed to increased proliferation ( S9D Fig ) . Because DNA damage induced by high doses of irradiation could mask the possible effect of hippo inhibition on cell dedifferentiation , we next investigated the effects of histone 2b ( h2b ) inhibition as an alternative means of depleting the neoblast population [46] , followed by hippo RNAi ( Fig 6A ) . qPCR analysis using specific primers for h2b and hippo confirmed inhibition of both genes ( S10A Fig ) . ISH for smedwi-1 revealed no differences between hippo ( RNAi ) animals and controls ( the “smedwi-1 WT” phenotype in Fig 6A ) , whereas in h2b ( RNAi ) animals , smedwi-1 expression was completely absent ( “no smedwi-1” phenotype in Fig 6A ) ( 45% ) , or reduced to a few scattered cells ( “disperse smedwi-1+ cells” phenotype in Fig 6A ) ( 55% ) , which corresponded to stem cells that escaped the effects of h2b inhibition ( Fig 6A ) . Strikingly , several animals in the h2b/hippo ( RNAi ) group had clusters of smedwi-1+ cells in the marginal region of the body ( “smedwi-1 clusters” phenotype in Fig 6A ) ( 58 . 3% ) ( Fig 6A ) . Interestingly , this corresponded to the region in which ectopic mitosis and overgrowths were observed . Moreover , despite the presence of smedwi-1 clusters , the number of H3P+ cells in h2b/hippo ( RNAi ) animals was comparable to that of h2b ( RNAi ) animals and was much lower than that of controls ( Fig 6B ) . In addition , EdU incorporation analysis revealed that the percentage of smedwi-1+ cells that entered the cell cycle in h2b/hippo ( RNAi ) animals was lower than that of h2b ( RNAi ) animals ( Fig 6C and S10B Fig ) . This result supports the view that smedwi-1+ cells originate from distinct populations in h2b ( RNAi ) and h2b/hippo ( RNAi ) animals . Taken together , our data suggest that the clusters of smedwi-1+ cells found in h2b/hippo ( RNAi ) animals are not the result of the proliferation of remaining stem cells that escape h2b inhibition but are produced by dedifferentiation of postmitotic cells that regain the expression of stem-cell markers . To better understand the nature of smedwi-1+ cells in h2b/hippo ( RNAi ) animals , we investigated whether the expression of different neoblast markers was also increased . The results revealed that expression of the stem-cell marker bruli [47] was also increased , although not to the same degree as smedwi-1 ( S10C Fig ) . Because our previous results showed that hippo is required to properly maintain epidermal fate and that the expression of ζ-neoblast markers is increased after hippo RNAi , we analyzed the smedwi-1+ clusters observed in h2b/hippo ( RNAi ) animals for expression of the ζ-neoblast marker zfp1 . ISH showed that h2b/hippo ( RNAi ) animals were mostly depleted of zfp1 , as were h2b ( RNAi ) animals ( S10D Fig ) . This result does not allow us to determine whether smedwi-1+ clusters arise from the dedifferentiation of epidermal cells . It is possible that smedwi-1+ clusters arise from a different lineage or , alternatively , that lineage restriction is not maintained during dedifferentiation of epidermal cells . Nonetheless , our results suggest that Hippo is essential to maintain the postmitotic state in planarians and that its absence may induce the dedifferentiation of postmitotic cells towards a stem-cell identity .
In the present study , we show that hippo is required to regulate the apoptotic and mitotic response in starved degrowing planarians . hippo RNAi resulted in an increase in the number of mitotic cells and a decrease in the number of apoptotic cells . Importantly , and in contrast to reports in other organisms [2 , 48 , 49] , the imbalance between apoptosis and mitosis observed following hippo inhibition did not lead to changes in planarian body size or cell number . This observation may be explained by the increase in the number of necrotic cells after hippo inhibition . Furthermore , the fact that the increase in the number of cells in M phase in hippo ( RNAi ) animals was not accompanied by an increase in the number of cells in S phase may also contribute to the maintenance of the cell number in hippo ( RNAi ) planarians . Our findings demonstrate that in planarians , Hippo is essential for proper cell cycle progression and , specifically , for successful completion of mitosis . The role of core Hippo signaling elements in critical mitotic events , namely in centrosomal duplication , chromosomal alignment , spindle formation , and completion of cytokinesis , has also been reported in Drosophila and vertebrate species [36 , 40 , 50–53] . Planarian hippo ( RNAi ) cells showed improper assembly of the mitotic spindle . This effect , together with the number of genes directly involved in mitosis that are differentially regulated in the hippo ( RNAi ) transcriptome , suggests a direct role of Hippo in regulating their expression . For instance , centriolin , which is required to complete cytokinesis , was down-regulated in the hippo ( RNAi ) transcriptome . Corroborating the important role of Hippo in the cell cycle in planarians , in the transcriptome we detected several genes previously reported to mediate the requirement of Hippo for proper cell cycle progression ( S1 Table ) . Despite defective mitotic exit , hippo ( RNAi ) animals showed no tissue regression , the phenotype normally associated with loss of the cycling cell population in planarians [29] . Indeed , the total population of stem cells or neoblasts ( smedwi-1+ cells ) was maintained in hippo ( RNAi ) animals . This suggests that only a fraction of the cells that enter the cell cycle become arrested in M phase after hippo inhibition . Supporting this view , around 30% of mitotic figures in hippo ( RNAi ) cells were defective . There is a second possible explanation for the observation that the imbalance between apoptosis and mitosis in hippo ( RNAi ) animals does not lead to changes in total cell number: a fraction of the cells found in M phase could arise from the dedifferentiation of postmitotic cells . Supporting this hypothesis , in hippo ( RNAi ) planarians we detected ectopic mitotic cells in the periphery , a region in which postmitotic cells are normally located . These mitotic cells also exhibited aberrant co-expression of committed epidermal cell markers and therefore are unlikely to be the result of incorrect migration of stem cells , which are normally located in the innermost part of the organism . Moreover , the boundaries of expression of the epidermal markers corresponding to the entire lineage were not conserved , indicating that hippo inhibition impairs the maintenance of cell identity . The poorly committed cells found in hippo ( RNAi ) animals could arise during the process of differentiation or could be the product of induced cell dedifferentiation . Importantly , we found that hippo inhibition in planarians depleted of cycling cells ( or neoblasts ) may promote dedifferentiation of postmitotic cells . It should be stressed that although a process of cell dedifferentiation that allows re-entry in the cell cycle is common in regenerative models , it has never been described in animals with the level of plasticity found in planarians , which fulfill their regenerative and renewal requirements by activating proliferation of their abundant population of totipotent stem cells [33 , 54] . Thus , our data strongly indicate that hippo plays a crucial role in the maintenance of the differentiated state and that its inhibition promotes dedifferentiation . Hippo inhibition in planarians promotes the formation of overgrowths , as described in all models in which it has been studied to date [1 , 48 , 55] . Although early studies of the Hippo pathway in model organisms attributed the appearance of tumors to an imbalance between cell death and proliferation [1 , 55] , our results indicate that the inability of cells to maintain the differentiated state following hippo inhibition may underlie the appearance of undifferentiated regions and the formation of overgrowths , which also consisted of undifferentiated cells . In agreement with this hypothesis , the formation of overgrowths was preceded by the appearance of large areas in which different tissues , including those pertaining to the neural , digestive , and visual systems , showed a loss of differentiated cell types . Those results are in good agreement with recently published findings supporting an essential role of hippo in restricting cell plasticity in the liver and intestine [9 , 23] , an effect that has been linked to its role in the recruitment of chromatin-remodeling complexes [14 , 56] . Thus , nuclear Yki/YAP , rather than pluripotency , could exert a critical role in conferring plasticity , which is a crucial property of tumor cells [57] . The formation of overgrowths could be due to the inhibition of apoptosis induced following hippo RNAi , in addition to the increase in cell plasticity ( Fig 7 ) . In wild-type animals , senescent cells and cells with DNA disarrangements are eliminated by apoptosis . However , these cells could not be eliminated in hippo ( RNAi ) animals and may contribute to the acquisition of additional genetic or epigenetic changes ( Fig 7 ) . Furthermore , the number of cells with DNA rearrangements and aneuploidies is probably increased in hippo ( RNAi ) planarians , because , according to our results , those animals display dysregulation of critical mitotic regulators and fail to complete cytokinesis , as previously demonstrated in LATS2 knockout mouse embryos [36] . Importantly , the control of apoptosis is intrinsically linked to genomic instability and malignant transformation [58] . It must be noted that the cell death that is inhibited after hippo inhibition in our experimental conditions is the one induced by starvation . However , it is likely that the damage-induced apoptosis also depends on hippo , because both starvation- and damage-induced apoptosis depend on such common mechanisms as JNK activation [59] . Taking into account the location of the overgrowths in the subepidermal region , which is abundant in epidermal precursors and is also the location of ectopic mitotic cells , it is tempting to speculate that the epidermal lineage is the origin of the cell accumulations in hippo ( RNAi ) animals . Epidermal cell plasticity promoted by hippo inhibition could account for the appearance of bivalent cells that are susceptible to tumoral transformation . Furthermore , although the total number of stem cells was not altered after hippo inhibition , we observed a marked increase in the expression of markers of ζ-neoblasts , the precursors of epidermal cells , underscoring the important role of the pathway in restricting the fate of this specific lineage . However , the fact that hippo inhibition in planarians depleted of cycling cells ( or neoblasts ) resulted in the formation of smedwi-1+ cell clusters that did not express the ζ-neoblast marker zfp1 does not support an epidermal origin . A deeper analysis of the molecular features of these smedwi-1+ cells will be required to determine whether they arise from a nonepidermal cell type or , alternatively , whether dedifferentiation keeps the cells in a more pluripotent state . Nonetheless , the fact that almost all markers of differentiation were down-regulated in the hippo ( RNAi ) transcriptome and the appearance of undifferentiated areas affecting neuronal , epithelial , and digestive cells in hippo ( RNAi ) animals indicate that hippo controls the fate of several cell types and that different cell lineages could contribute to the overgrowths observed . To understand whether hippo exerts a predominant role in specific tissues , it will be necessary to determine whether precursor cell markers are also aberrantly co-expressed following hippo inhibition in other cell types . In addition to its role in maintaining cell fate , hippo may also be required for proper cell differentiation , as reported in other organisms [10 , 13 , 14] . In our study , the role of hippo in cell differentiation was more evident in the context of regeneration , because the decrease in the number of differentiated cells observed in newly regenerating blastemas , despite the increase in mitotic cells , could not directly result from dedifferentiation . Moreover , the observed defects in differentiation may be caused by the dedifferentiation of postmitotic cells in pre-existing tissue after hippo RNAi , as previously described in intact animals , leading to misexpression by differentiated muscle cells of signaling molecules required for proper differentiation [60] . This possibility is consistent with the phenotype generated after yki inhibition in planarians , in which an increase in signaling molecules and differentiated cells is observed [43] ( Fig 4C and S6 Fig ) . The results presented here support an essential role for hippo in the acquisition and maintenance of differentiated cell fates . Thus , as demonstrated in other models , Hippo favors stemness in planarians . Importantly , although planarians possess an abundant population of totipotent stem cells , hippo inhibition promotes stemness not by increasing stem cell renewal and expansion of the stem cell compartment but rather by promoting cell plasticity and thus dedifferentiation of postmitotic cells . This finding has profound implications in the fields of regenerative medicine and cancer therapy , because the acquisition of plasticity by lineage-committed cells favors wound healing but also promotes tumorigenesis [28 , 61] . Accordingly , the cell plasticity induced by hippo inhibition is associated with beneficial effects in the context of heart and liver regeneration in vertebrates [17 , 18] . However , hippo inhibition in planarians , which have a much greater regenerative ability than vertebrates , impairs rather than promotes regeneration . One explanation for these contrasting effects is that in vertebrate regenerative systems , a process of cell dedifferentiation that allows re-entry in the cell cycle fuels the regenerative response [62 , 63] , whereas in planarians , expansion of the stem cell population is the only source of new cells [33] . In homeostatic conditions , when basal cell renewal is required , hippo inhibition is also deleterious in planarians , because tumoral transformation is facilitated by the sustained increase in cell plasticity and the probable chromosomal instability induced by the cell cycle defects and the inhibition of apoptosis . The fact that we observed no overgrowths in regenerating regions further underscores the importance of the sustained effect of hippo inhibition in specific cell types to promote transformation .
The present findings demonstrate that in a stem cell–based system such as the planarian , the main role of the Hippo pathway is not to control the balance between proliferating and dying cells nor to regulate body size or the stem-cell population; in planarians , hippo is required to successfully complete the cell cycle and to promote apoptosis . Furthermore , hippo is necessary to acquire and maintain cell fate , thus restricting cell plasticity . Consequently , long-term hippo inhibition prevents tissue renewal and leads to the formation of overgrowths . Although further evidence is required , our results suggest that in planarians , as described in other organisms , hippo may be involved in maintenance of the chromatin state and the genome stability of stem cells and postmitotic descendants . This function would explain the systematic alteration of hippo signaling elements in many types of cancer , as well as the proregenerative effect of the induction of Yki nuclearization . However , it remains unclear why hippo elements are mutated in most human tumors but never at their onset , whereas in model organisms , the appearance of overgrowths is a consistent feature of hippo inhibition . Finally , our results highlight the potentially hazardous effects of manipulating the hippo pathway for medical purposes in regenerative medicine if the stem cells and progenitors induced after hippo inhibition are in fact poorly committed cells .
Asexual planarians from a clonal strain of S . mediterranea BCN-10 were maintained at 20°C in planarian artificial medium ( PAM ) water , as previously described [64] . Animals were fed with veal liver and starved for at least 1 week before beginning experiments . To amplify the hippo fragment , we used the follow primers: 5′-CGAGCACTGTTTATGATTCCTTC-3′ and 5′-CTCGGCTTGCAAGTCTGAGTC-3′ . To amplify the yorkie fragment , the following primers were used: 5′-GTTTGGATGAATTATTCGAAGTGG-3′ and 5′-CACAATACAAAAGAAACCACATGG-3′ . hippo and yorkie PCR fragments were cloned into pCRII ( Life Technologies ) and pGEM-T Easy ( Promega ) vectors to synthesize dsRNA or ssRNA , as required . dsRNA was synthetized by in vitro transcription ( Roche ) and microinjection performed , as previously described [65] , following the standard protocol of 3 × 32 nl injection of dsRNA for 3 consecutive days . To achieve stronger hippo inhibition , we performed the same protocol over 3 consecutive weeks in starved planarians . yorkie ( RNAi ) animals were injected for only 1 week with injection of gfp during the 2 previous weeks . Regenerating animals were injected with hippo or yorkie dsRNA for 2 weeks prior to amputation of the head and tail . Animals were fixed at different times postamputation , depending on the experiment . Control animals were injected with dsRNA for green fluorescent protein ( GFP ) , a gene not present in planarians . In the h2b/hippo experiment , animals were injected with gfp or h2b on 3 consecutive days and , after 2 rest days , received another injection of gfp or h2b . Beginning the following day , animals were injected with gfp or hippo for 3 consecutive days . Animals were fixed 4 days after the last injection . Total RNA was extracted from a pool of 5 planarians each for hippo RNAi and gfp RNAi . Quantitative real-time PCR was performed as previously described [46] , and data were normalized based on the expression of EF2 or URA4 as an internal control . All experiments were performed using 3 biological replicates . The following sets of specific primers were used: hippo mRNA , 5′-TTTGGTCTTTGGGAATCAC-3′ and 5′-TGGAGGAGGTTGAGAAGG-3′; h2b mRNA , 5′-GAGAAAGTTGAACGGCCC-3′ and 5′-AAGATAATACGTACTTCAACGACG-3′ . RNA probes were synthesized in vitro using Sp6 or T7 polymerase ( Roche ) and DIG- , FITC- , or DNP-modified ( Perkin Elmer ) nucleotides . RNA probes were purified and precipitated with ethanol and 7 . 5 M ammonium acetate . For ISH and fluorescent in situ hybridization ( FISH ) , animals were fixed and processed as previously described [66 , 67] . After probe development , neoblasts were visualized with the rabbit anti-SMEDWI-1 antibody ( 1:1 , 000; kindly provided by Kerstin Bartscherer , Max Plank Institute for Molecular Biomedicine , Münster , Germany ) [47] . Nuclei were stained with DAPI ( 1:5 , 000 ) and mounted with 70% glycerol in PBS . Immunostaining was performed as previously described [68] . The following antibodies were used: mouse anti-synapsin ( anti-SYNORF-1 , 1:50; Hybridoma Bank ) ; rabbit anti-phospho-histone-H3-Ser10 ( anti-H3P ) ( 1:500; Cell Signaling Technology ) ; rabbit anti-SMEDWI-1 antibody ( 1:1 , 000 ) ; mouse anti-arrestin ( anti-VC1 ) ( 1:15 , 000; kindly provided by Professor K . Watanabe ) ; rabbit anti-β-catenin-2 ( anti-Bcat2 ) ( 1:2 , 000 ) [41] . Nuclei were stained with DAPI ( 1:5 , 000 ) and mounted with 70% glycerol in PBS . To avoid technical variance and a reliable quantification of H3P+cells , at least 2 independent experiments were performed . For ISH and immunohistochemistry , animals were killed and processed as previously described [69] . The antibodies used were rabbit anti-SMEDWI-1 ( 1:1 , 000 ) , rabbit anti-phospho-histone-H3-Ser10 ( anti-H3P ) ( 1:500; Cell Signaling Technology ) , rat anti-phospho-histone-H3-Ser10 ( anti- H3P ) ( 1:1 , 000; Millipore ) , and rabbit anti-YORKIE ( 1:200 ) . Whole animals were macerated in a solution containing methanol: glacial acetic acid: glycerol: distilled water ( 3:1:2:14 ) for 16 h at 4°C . Cells were transferred onto a slide and immunostained with mouse anti-α-Tubulin ( 1:500 , Sigma ) and rabbit anti-phospho-histone-H3-Ser10 ( anti- H3P ) ( 1:500; Cell Signaling Technology ) . For TUNEL analysis , animals were fixed and treated as previously described [70] , using the ApopTag Red In Situ Apoptosis Detection Kit ( Merck-Millipore Ref . S7165 ) . To avoid technical variance , at least 2 independent TUNEL experiments were performed . For the caspase-3 assay , total protein was extracted from a pool of 5 planarians and processed as previously described [71] . Enzyme activity was measured in a luminescence spectrophotometer ( Perkin-Elmer LS-50 ) ( 1 excitation , 380 nm ) . A unit of caspase-3 activity was defined as the amount of active enzyme necessary to produce an increase of 1 arbitrary luminescence unit after a 2-h incubation . The results are presented as units of caspase-3 activity per μg of protein . All experiments were performed using 5 biological and 3 technical replicates for each condition . To avoid technical variance , at least 2 independent experiments were performed . Dissociation of planarians , cell labeling , and isolation of cells by FACS were performed as described previously [72] . Absolute cell counts were performed by adding beads of a known concentration to the sample . Beads and cells were detected simultaneously , and absolute counts of the cells were calculated from bead numbers ( absolute counts by indirect method ) . Flow-Check Fluorospheres Polystyrene Fluorescent Microspheres ( Beckman Coulter Inc , Indianapolis , IN ) were adjusted at 1 × 106 fluorospheres/mL . A 1:100 dilution of the bead solution was applied to each sample to obtain a final concentration of 1 × 104 beads/mL . Beads and cells were identified according to their distinct patterns of scatter and fluorescence . F-ara Edu ( 32 nl; Sigma ) was injected into gfp and hippo ( RNAi ) animals at a concentration of 60 μg/mL ( diluted in 10% DMSO/PAM water ) . After 16 h , animals were processed and stained with the EdU Click-555 kit ( Baseclick Gmbh; BCK-Edu555 ) , in accordance with the manufacturer’s recommendations , following pretreatment with proteinase K ( 20 μg/mL ) for 10 min at RT . Samples were immunostained with anti-H3P , stained with DAPI , and mounted with 70% glycerol in PBS . In the h2b/hippo ( RNAi ) experiment , animals previously injected with gfp/h2b and/or gfp/hippo were injected with EdU and after 16 h were processed for FISH using the smedwi-1 probe , followed by EdU staining . Animals were injected with gfp or hippo over 3 consecutive weeks and then injected with 3 × 32 nl of a mixture of PI ( 1 . 66 × 10−3 μg/μL; Sigma ) and Hoechst 33342 ( 3 . 3 × 10−6 μg/μL; Sigma ) diluted in PAM water . Immediately , planarians were soaked in the same solution for 4 h . Single planarians were placed on a microscopy slide and enveloped in a drop of 3% low melting agarose . Confocal imaging was performed within minutes of preparation of the samples . The complete coding sequence of yorkie cDNA was cloned into a p-GEMT Easy vector ( Promega ) . Subcloning , protein expression , and antibody production were performed using ProteoGenix ( ProteoGenix , France ) . Briefly , 200 μg of recombinant protein was used as an immunogen to produce polyclonal IgGs in 2 rabbits . The postimmunization serum was purified using protein A affinity purification , precipitated in sodium azide buffer , and stored at 4°C . Protein extracts were obtained as previously described [73] . After incubation with rabbit anti-YORKIE ( 1:2 , 000 ) and mouse anti-α-TUBULIN ( 1:10 , 000; Sigma ) antibodies , the signal was developed using Clarity Western ECL Substrate ( Bio-Rad ) and chemiluminescence was detected using a C-DiGit Chemiluminescent Western Blot Scanner ( LI-COR ) . Quantifications were performed with Image Studio Lite and normalized to the anti-α-Tubulin signal . For transcriptomic analysis , total RNA was extracted from gfp ( RNAi ) and hippo ( RNAi ) animals after 1 , 3 , or 4 weeks of inhibition . Three replicates were generated per condition from a pool of 5 organisms each . RNA was extracted with Trizol ( Invitrogen ) , following the manufacturer's instructions . RNA was quantified with a Nanodrop ND-1000 spectrophotometer ( Thermo Scientific ) and quality assessment performed by capillary electrophoresis in an Agilent 2100 Bioanalyzer ( Agilent Technologies ) prior to preparation of the library . cDNA libraries were prepared using the Illumina TruSeq Stranded mRNA Library Prep Kit and sequenced as paired-end reads in an Illlumina HiSeq 2000 sequencer . Quality assessment of the reads was performed using the FastQC suite . Transcript abundances were calculated with kallisto v0 . 43 . 0 [74] on the S . mediterranea dd_Smed_v6 transcriptome assembly [75] . Differential expression analysis was carried out using the sleuth [76] and DESeq2 [77] statistical packages . Raw sequencing data in FASTQ format as well as the transcript abundances have been deposited in the NCBI Gene Expression Omnibus ( GEO ) [78] and are accessible using GEO Series accession number GSE95130 . FISH and immunostaining samples were imaged using a MZ16F stereomicroscope ( Leica ) equipped with a ProgRes C3 camera ( Jenoptik ) or an SP2 confocal laser-scanning microscope ( Leica ) . Images were processed using Fiji and Photoshop CS5 ( Adobe ) software . Brightness/contrast and color balance adjustments were always applied to the entire image . Quantifications were performed by hand using the “multi-point selection” tool of Fiji . Colocalization quantification was performed using the equivalent areas using the “ROI-manager” tool in Fiji . Nuclear area in Edu and IP experiments was measured using the “threshold” tool with the “moments” mask for all samples . Signal quantification of Yorkie antibody immunostaining was processed using Fiji software . Two planes were used to build the Z-projection . Nuclear-stained ( DAPI ) images were transformed into a mask using the “threshold” tool with the “moments” mask . The mask was used to obtain the nuclear signal with the Image calculator process . The nuclear signal obtained from the resulting image was measured to obtain the raw integrated density ( RID ) . The nuclear area was obtained from the mask . Next , the RID was normalized to the respective nuclear area . Results were averaged per group and significant differences determined by 2-tailed Student t test .
|
Constant cell renewal is required to maintain healthy organs during adult homeostasis . The highly conserved Hippo signaling pathway is essential for the regulation of basic cell behaviors that underlie tissue renewal , including cell proliferation , cell differentiation , and cell death . The Hippo protein has been implicated in several human cancers , and its inhibition in mouse and Drosophila promotes the formation of overgrowths . Nonetheless , its biological function remains poorly understood . To address this issue , we studied the role of Hippo in planarians , flatworms that continuously alter their size depending on nutrient availability , and therefore have a high rate of cellular turnover . This ability is sustained by an abundant population of adult totipotent stem cells . We show that hippo inhibition in planarians decreases apoptotic cell death , impairs cell progression through the cell cycle , and causes instability of the differentiated cell fate . These events ultimately lead to the formation of overgrowths consisting of undifferentiated cells . We propose that the main role of Hippo in planarians is not to promote proliferation but to control the cell cycle and maintain a stable differentiated cell fate .
|
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2018
|
Hippo signaling controls cell cycle and restricts cell plasticity in planarians
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The epidemiological success of pandemic and epidemic influenza A viruses relies on the ability to transmit efficiently from person-to-person via respiratory droplets . Respiratory droplet ( RD ) transmission of influenza viruses requires efficient replication and release of infectious influenza particles into the air . The 2009 pandemic H1N1 ( pH1N1 ) virus originated by reassortment of a North American triple reassortant swine ( TRS ) virus with a Eurasian swine virus that contributed the neuraminidase ( NA ) and M gene segments . Both the TRS and Eurasian swine viruses caused sporadic infections in humans , but failed to spread from person-to-person , unlike the pH1N1 virus . We evaluated the pH1N1 and its precursor viruses in a ferret model to determine the contribution of different viral gene segments on the release of influenza virus particles into the air and on the transmissibility of the pH1N1 virus . We found that the Eurasian-origin gene segments contributed to efficient RD transmission of the pH1N1 virus likely by modulating the release of influenza viral RNA-containing particles into the air . All viruses replicated well in the upper respiratory tract of infected ferrets , suggesting that factors other than viral replication are important for the release of influenza virus particles and transmission . Our studies demonstrate that the release of influenza viral RNA-containing particles into the air correlates with increased NA activity . Additionally , the pleomorphic phenotype of the pH1N1 virus is dependent upon the Eurasian-origin gene segments , suggesting a link between transmission and virus morphology . We have demonstrated that the viruses are released into exhaled air to varying degrees and a constellation of genes influences the transmissibility of the pH1N1 virus .
Influenza A viruses pose a global threat to human health . They circulate in animal hosts and can reassort to generate a virus to which the human population is naïve , creating a potential pandemic threat . Efficient person-to-person transmission of influenza A viruses via RDs is a feature of seasonal epidemics and of pandemics . Influenza viruses have caused several pandemics in the past , including one in 1918 caused by an avian-origin virus that killed 50 million people , and the most recent pandemic occurred in the spring of 2009 [1] , [2] . The 2009 pandemic of swine-origin H1N1 influenza virus spread to over 215 countries from April 2009 to August 2010 and was responsible for at least 18 , 000 laboratory-confirmed deaths [3] . Determination of the molecular requirements for influenza viruses to transmit efficiently from person-to-person is an essential contribution to our understanding of potential pandemic threats . For example , the animal influenza viruses , avian H5N1 , swine H1N1 , and swine H1N2 viruses , have sporadically infected humans [4]–[8] but have not caused an influenza pandemic , presumably because they were unable to transmit efficiently throughout the human population . The influenza A virus genome consists of 8 negative strand RNA gene segments that encode at least 11 proteins . The viral envelope is predominantly composed of the hemagglutinin ( HA ) , neuraminidase ( NA ) , and matrix ( M1 and M2 ) proteins . HA is responsible for receptor binding and viral entry into a cell , while NA aids in release from the infected cell by cleaving sialic acids on the cell surface . The M1 protein lines the inside of the plasma membrane enveloping the viral RNA and gives structure to the virion , while M2 is an ion channel important for uncoating of the virus in the endosome and for virus release [9] , [10] . The segmented genome allows reassortment to occur in nature , enhancing the genetic diversity of the virus . The 2009 pandemic H1N1 ( pH1N1 ) virus arose from a reassortment event between a North American triple reassortant swine virus ( TRS ) and a Eurasian swine virus . The Eurasian swine viruses contributed the NA and M gene segments to the pH1N1 strain , while the remaining 6 gene segments came from the TRS virus [7] , [11] . The pH1N1 precursor viruses , TRS and Eurasian swine , have transmitted from pigs to humans sporadically but secondary human cases did not occur [5] , [8] . Recent studies have attempted to identify the genetic requirements for transmission of the pH1N1 virus [12] , [13] . However , they did not identify the biological mechanisms by which these gene segments confer efficient transmission . Therefore , the biological determinants responsible for transmission of the pH1N1 virus that are lacking in the TRS and Eurasian swine viruses are still unknown . Transmission of influenza virus has been studied extensively in animal models such as guinea pigs and ferrets [14] , yet the precise mechanism or requirements for transmission are still unclear . Previous studies have suggested that host-range determinants such as receptor binding specificity and human-specific PB2 amino acid residues are important for transmission [15]–[19] . However , recent studies have demonstrated that these host-range determinants are not sufficient for transmission [20] , [21] . Additionally , the HA protein from both the pH1N1 and TRS viruses is from the classical swine lineage that binds α2 , 6-linked sialic acids and both of these viruses contain avian-specific amino acids 627 and 701 in the PB2 gene , suggesting that those characteristics alone do not determine the transmissibility of these viruses . These observations suggest a role for other gene products in the transmissibility of the pH1N1 virus . Three modes of influenza virus transmission have been defined: contact transmission , droplet spray transmission , and aerosol transmission . Contact transmission includes direct or indirect contact with a contaminated surface . Droplet spray transmission refers to person-to-person transmission via larger droplets that are deposited onto mucous membranes of the upper respiratory tract . Aerosol transmission is person-to-person transmission via aerosols composed of small , respirable particles that can be inhaled into the lower respiratory tract . The relative contribution of these different modes of transmission to person-to-person spread of influenza viruses is not known . In our study , the term respiratory droplet ( RD ) transmission includes both droplet spray and aerosol transmission . Studies attempting to distinguish between large and small aerosols have used aerosol samplers to measure the size of influenza virus-containing particles released by humans . Bio-aerosol sampling has been performed in various environmental settings such as hospitals , airplanes , and daycare centers [22]–[25] . These studies suggest that humans predominantly release small respirable particles that contain influenza virus , although larger particles containing influenza virus were also detected . There are three components to consider when studying RD transmission of influenza virus: the donor , the environment , and the recipient . The donor must be infected with a virus that replicates efficiently in the upper respiratory tract and infectious virus must be released into the surrounding air . Environmental factors can alter the size , morphology , and amount of influenza virus-containing particles present in the air that is shared by the donor and recipient [26] . Recipients must be susceptible to viral infection and exposed to enough infectious virus to establish a productive infection . Modulation of any of these parameters , including viral host-range determinants , severity of disease symptoms , environmental temperature , humidity , and susceptibility of the recipient can alter the transmissibility of a virus [27] , [28] . In this study , we used viruses generated by reverse genetics and biological isolates from human infections to explore the impact of the Eurasian-origin NA and M gene segments on transmissibility of the 2009 pH1N1 virus in a ferret model . We included the pH1N1 virus , representative Eurasian and TRS viruses that are putative precursor viruses , and a reassortant pH1N1 virus in which the NA and M gene segments were replaced with corresponding gene segments from a TRS virus . We found that the Eurasian NA and M gene segments contribute to efficient transmission of the pH1N1 virus . We used cyclone-based aerosol samplers to assess the amount and size distribution of influenza viral RNA-containing particles released by infected ferrets and determined the susceptibility of ferrets to the pH1N1 and its precursor viruses . Ferrets infected with viruses containing the Eurasian-origin NA and M gene segments efficiently released influenza viral RNA-containing particles into the air; this release correlated with higher NA activity of the pH1N1 and Eurasian viruses . Eurasian gene segments also contribute to the pleomorphic phenotype of the pH1N1 virus and this correlated with efficient RD transmission , suggesting a constellation of genes was responsible for the release of influenza virus-containing aerosols and transmissibility of the pH1N1 virus .
RD transmission of pH1N1 virus has been shown to be highly efficient in the ferret model , with transmission efficiency ranging from 66% to 100% [29]–[31] . To assess whether the Eurasian-origin gene segments contribute to this phenotype , we used reverse genetics to create a recombinant pH1N1 virus and a 6∶2 reassortant pH1N1 virus in which the Eurasian-origin NA and M gene segments were replaced with the North American TRS NA and M gene segments ( Table 1 ) . We confirmed that the recombinant wild-type ( wt ) 2009 pH1N1 virus rescued by reverse genetics behaved similarly to the biological wt virus in vitro and in vivo ( Figure S1 ) . The titer of biological pH1N1 and recombinant pH1N1 viruses differed in the lungs of ferrets on day 1 ( Figure S1B ) ; however , by day 5 post-infection , viral replication in the lungs was equivalent . Therefore , we used the recombinant 2009 pandemic virus ( rec A/California/07/2009 ) , hereafter referred to as Rec pH1N1 , as a surrogate for the biological virus in further studies . RD transmission studies were carried out in four independent transmission cages with the Rec pH1N1 virus and the recombinant A/California/07/2009+A/Ohio/02/2007 NA and M ( 6∶2 reassortant ) virus . We measured viral titers in the nasal secretions of ferrets on alternate days for 14 days and determined levels of influenza-specific serum antibodies on day 14 . A ferret was considered infected if it shed virus in the nasal secretions or seroconverted . We found that both the Rec pH1N1 and 6∶2 reassortant virus replicated to high titers in the nasal secretions of the infected ferrets ( Figure 1A and B , left panels ) . Infected ferrets shed virus for 6 days , with a mean peak titer between 104 . 2–105 . 2 TCID50/mL on days 2 or 4 post-infection . All four of the naïve ferrets exposed to Rec pH1N1 virus shed infectious virus in the nasal secretions . Three of the naïve exposed ferrets shed virus from days 3 to 7 post-exposure , with a peak titer of 103 . 2–103 . 7 TCID50/mL of virus on day 5 for two of the ferrets ( Figure 1A ) ; this pattern of viral shedding is similar to data observed by us and others on the transmission of the biological pH1N1 virus ( Figure S1D and [32] ) . The fourth ferret ( naïve 4 ) shed virus much later than the other three ( day 9 post-exposure ) . Presence of influenza-specific antibodies was found in all ferrets that shed virus in the nasal secretions ( Figure 1C ) . Antibody titers for naïve ferret 4 were lower compared to the other ferrets , most likely because of the late onset of viral shedding . Since virus was detected in all 4 naïve ferrets and they all seroconverted by HAI , we concluded that RD transmission efficiency for the Rec pH1N1 virus was 100% in our system . RD transmission of the 6∶2 reassortant virus was less efficient; virus was detected in the nasal secretions of two out of four naïve ferrets ( Figure 1B ) , with peak shedding of 103 . 2–103 . 7 TCID50/mL on day 7 post-exposure . Influenza-specific antibodies were detected in the ferrets that shed virus in their nasal secretions ( Figure 1C ) . These data demonstrate that replacement of the Eurasian-origin gene segments in the 6∶2 reassortant virus resulted in reduced transmission efficiency . Additionally , we observed severe weight loss in two out of four ferrets infected with Rec pH1N1 virus and three out of four ferrets infected with the 6∶2 reassortant virus ( Table S1 ) , indicating that disease severity , as measured by weight loss , does not correlate with efficiency of RD transmission . Sneezing was observed in one of four ferrets for both viruses . Interestingly , in each case the naïve partner became infected , suggesting that generation of aerosols by sneezing may enhance transmission . To determine whether the reduced transmission efficiency between the Rec pH1N1 and the 6∶2 reassortant virus was due to the Eurasian-origin gene segments , we evaluated the transmission efficiency of the pandemic precursor viruses . These experiments were conducted with swine-origin viruses that were isolated from humans ( Table 1 ) : for the North American TRS , an isolate obtained from an adult male in Ohio in 2007 ( A/Ohio/02/2007 ) [8] and for the Eurasian swine virus , a virus isolated from a child in Thailand in 2005 ( A/Thailand/271/2005 ) [5] . Both of these viruses had transmitted from pigs to humans , but did not spread from person-to-person [5] , [6] , [8] . Ferrets infected with the A/Ohio/02/2007 ( TRS ) virus had much lower titers of virus in their nasal secretions ( Figure 2A ) than those infected with the Rec pH1N1 or 6∶2 reassortant viruses . The peak titer was 102 . 2 TCID50/mL for most ferrets on day 2-post infection . However , in other experiments performed in our lab and by others , this virus replicated to higher levels in the upper respiratory tract of ferrets ( Table 2 , Figure S1A and [32] ) . Ferrets infected with the A/Thailand/271/2005 ( Eurasian ) virus shed high titers of the virus ( Figure 2B ) . Peak viral shedding was observed on days 2 or 4 post- infection , with peak titers of 102 . 95–104 . 95 TCID50/mL . A matched non-parametric two-way ANOVA of the nasal wash titers in animals infected with Eurasian , pH1N1 , or 6∶2 reassortant virus showed no statistical difference among these groups of viruses . One of four ferrets each infected with either the TRS or Eurasian viruses developed a distinctive cough , similar to croup ( Table S1 ) . The naïve ferrets paired with the croupy ferret became infected with influenza and shed virus in their nasal secretions , suggesting that the aerosols released by coughing enhanced RD transmission . These were the only ferrets that shed virus in the nasal secretions after exposure to ferrets infected with the TRS or Eurasian viruses . As seen with the Rec pH1N1 and 6∶2 reassortant viruses , all of the ferrets with detectable virus in the nasal secretions also produced anti-influenza antibodies ( Figure 2C ) . However , with both the TRS and Eurasian viruses , one naive ferret ( TRS naïve 3 and Eurasian naïve 1 ) that did not shed virus in the nasal secretions seroconverted . Others have also found serologic evidence of infection in the absence of virologic evidence in a ferret transmission model [33] . Thus , we conclude that the two pandemic precursor viruses transmitted with 50% efficiency in ferrets . Our data demonstrate that the Eurasian-origin NA and M gene segments are necessary , but not sufficient , for RD transmission in our ferret model . To confirm that the reduced RD transmission of the TRS ( A/Ohio/02/2007 ) was not due to the lower viral replication in the experimentally infected ferrets , we re-evaluated the replication and transmissibility of this virus with a larger number of animals . We confirmed the earlier finding of reduced transmissibility , even in the face of higher titers of virus in the experimentally infected ferrets . The TRS virus replicated to variable titers in the nasal secretions of experimentally infected ferrets; some infected ferrets had low titers ( 101 . 7–102 . 95 TCID50/mL ) , consistent with the titers we had observed in the first study ( Figure 2A ) and others had higher titers ( 103 . 7–103 . 95 TCID50/mL ) of virus ( Figure S2A ) . The peak of viral shedding was on day 2 , as previously observed . In the new transmission study , only 2 out of 6 naïve animals became infected , as defined by isolation of virus in their nasal secretions and/or seroconversion ( Figure S2B ) . The reduced transmission efficiency of the TRS virus has also been reported by others [13] , [32] . Additionally , since ferrets infected with the pH1N1 , 6∶2 reassortant , or Eurasian virus all shed virus to similar levels , we believe that RD transmission is not dependent upon efficient virus replication in the nasal secretions of animals . Therefore , efficient RD transmission is likely due to other factors such as infectivity of the virus for the naïve host or release of viral particles into the air . To determine whether the infectivity of the viruses for ferrets varied , we determined the dose of virus at which 50% of ferrets were infected ( FID50 ) . Ferrets were inoculated with 10 , 000 , 100 , or 10 TCID50 of virus , and infectivity was measured by the presence of infectious virus in nasal secretions or by seroconversion . Table 2 lists the number of ferrets at each dose that were infected among the ferrets that were inoculated with each dose . Peak virus titers obtained from the nasal secretions are also presented in Table 2 . In this experiment , ferrets infected with the TRS virus shed virus in the nasal wash at titers equivalent to the other viruses , confirming that this virus has variable replication in the upper respiratory tract of ferrets . Interestingly , administration of doses of virus as low as 10 TCID50 resulted in peak viral titers similar to that of 1000-fold higher doses . Based on the data presented in Table 2 , Rec pH1N1 and TRS viruses have a similar FID50 , and the 6∶2 reassortant and Eurasian viruses are more infectious . Surprisingly , all 3 animals infected with 10 TCID50 of the Eurasian virus shed virus in nasal washes and seroconverted ( Table 2 ) . These data demonstrate that while the pandemic virus and its precursors may differ in their infectivity in ferrets , this does not correlate with transmissibility of these viruses via RD transmission . Influenza virus particles must be released into the air for RD transmission to occur . Much work has been done recently exploring the size distribution of particles containing influenza virus that are released by humans [22]–[24] , [34] , [35] . However , few studies have been done in animal models to correlate the amount of particles released with influenza virus transmission [36] , [37] . To determine the size of influenza virus particles in the air exhaled by infected ferrets , we used cyclone-based aerosol samplers that separate particles based on size; these samplers have previously been used in clinical settings to assess exposure of health care workers to influenza [22] , [23] . The samplers have three collection surfaces: a 15 mL conical tube captures particles greater than 4 µm , a 1 . 5 mL tube captures particles between 1 and 4 µm , and a filter traps all submicron ( <1 µm ) particles . The samplers were secured to the outside of the cage , between the inner and outer doors ( Figure S3A ) , and the air on the infected ferret's side of the cage was sampled for one hour on alternate days at a rate of 3 . 5 liters per minute . The ferrets were undisturbed during air sampling . The distribution of influenza viral RNA-containing particles released by infected ferrets was determined for each virus in the study at all 3 sizes: >4 µm ( Figure 3 ) , 1 to 4 µm ( Figure 4 ) , and <1 µm ( Figure 5 ) . This system does not allow for the measurement of the total count of particles released by each ferret nor the isolation of infectious virus because the collection tubes are dry . However , it does allow for the quantification of particles containing influenza viral RNA . We used this measurement as a surrogate for the amount of viral particles present in aerosols of various sizes . We found that ferrets predominantly released influenza virus into the air in large particles ( >4 µm ) ( Compare Figures 3 , 4 , and 5 ) . The duration for which the large particles containing influenza viral RNA was detected correlated with the length of time that virus was detected in the nasal washes of the ferrets . In the case of the Rec pH1N1 virus , all four infected ferrets consistently released large particles containing influenza viral RNA for 6 days post-infection , with a peak on day 2 ( Figure 3A ) . Although virus was not detected in the nasal wash on day 8 post-infection , a low level of aerosol particles containing influenza viral RNA was observed . Ferrets infected with the Eurasian swine virus also consistently released influenza viral RNA-containing particles into the air , and in a larger quantity than the Rec pH1N1 infected ferrets ( Figure 3B ) . Ferrets infected with the 6∶2 reassortant and TRS viruses sporadically released large ( >4 µm size ) influenza viral RNA-containing particles ( Figure 3C and D ) . To compare the trend of influenza viral RNA-containing particles released by animals infected with these viruses , we calculated the average area under the curve ( AUC ) for each virus per collection tube . We found that AUC of the Rec pH1N1 and Eurasian viruses for the 15 mL collection tube are 5540 and 29 , 384 respectively . These values are higher than those for the 6∶2 reassortant and TRS viruses , which are 1338 and 2333 , respectively . These data demonstrate that while ferrets predominantly released large influenza viral RNA-containing particles , the ferrets infected with Rec pH1N1 and Eurasian viruses released more than those infected with either the TRS or 6∶2 reassortant virus . A similar phenomenon was found with the release of 1 to 4 µm-sized particles ( Figure 4 ) . Viruses containing the Eurasian-origin gene segments ( Rec pH1N1 and Eurasian ) also had a more consistent release of influenza viral RNA-containing particles at the 1–4 µm size ( Figure 4A and B ) , while the TRS and 6∶2 reassortant virus had a more sporadic release of influenza viral RNA-containing particles ( Figure 4 C and D ) . This phenomenon was confirmed by analysis of the average AUCs for each respective graph; the Rec pH1N1 and Eurasian viruses had AUC values ( 636 . 5 and 5464 , respectively ) higher than the TRS and 6∶2 reassortant viruses ( 124 . 8 and 59 . 3 , respectively ) . Ferrets infected with pH1N1 virus released 1–4 µm particles containing influenza viral RNA from day 2 to 4 with a peak at day 2 , while some animals infected with the Eurasian virus released these particles consistently on days 2 , 4 , and 6 . Very few influenza viral RNA-containing particles were detected 6 days post-infection ( Figure 4 ) . Although it is possible that the sporadic release of influenza viral RNA-containing particles from ferrets infected with the TRS virus may be linked to the low viral titers in the nasal secretions ( Figure 2A ) , a similar pattern of sporadic release was also seen in the repeat experiment of ferrets infected with the TRS virus ( Figure S2C ) . Additionally , ferrets infected with the 6∶2 reassortant virus shed virus to high titers in the nasal secretions and also displayed a sporadic release of particles containing influenza viral RNA . Therefore , we conclude that the Eurasian-origin gene segments contribute to the release of influenza viral RNA-containing particles greater than 1 µm . Interestingly , the pattern of release of submicron particles containing influenza viral RNA by the Rec pH1N1 virus was different from the other viruses ( Figure 5 A and B ) . Ferrets infected with the Rec pH1N1 virus consistently released submicron particles containing influenza viral RNA into the air , and this release was detected at every time point tested , with a similar amount on days 2 and 6 post-infection . Interestingly , infected ferret number 4 released a considerable amount of submicron particles containing influenza viral RNA on days 8 and 10 post-infection , which correlates with the late infection of its naïve pair ( refer to Figure 1A ) . In contrast to the Rec pH1N1-infected ferrets , those infected with the Eurasian virus released submicron influenza viral RNA-containing particles only sporadically . Infection with the TRS and 6∶2 reassortant virus did not result in release of submicron influenza viral RNA-containing particles into the air that were detectable by our sampling system ( Figure 5 C and D ) . There was a higher background observed in the Rec pH1N1 infected ferrets on day 0 compared to the other viruses that may be due to an environmental contaminant . Despite this , the release of influenza viral RNA-containing particles from ferrets infected with the Rec pH1N1 virus was found to be distinct from the other viruses . A comparison of the average AUC values from days 2 to 10 confirms this observation; the pH1N1 virus had an AUC value of 1043 and all of the other viruses had AUC values ranging from 56 to 59 . Additionally , a two-way ANOVA found that the difference in the amount of submicron particles that contained influenza viral RNA released by ferrets infected with Rec pH1N1 virus compared with all other viruses was significant . The release of submicron influenza viral RNA-containing particles correlates with transmission efficiency and it is tempting to speculate that RD transmission is associated with these submicron particles . Overall , our air sampling studies have found that ferrets infected with viruses that lacked the Eurasian-origin NA and M gene segments , the TRS and 6∶2 reassortant viruses , only sporadically released influenza viral RNA-containing particles of all sizes into the air ( Figures 3 , 4 , and 5 ) . This finding suggests that the Eurasian-origin gene segments contribute to the transmissibility of the pH1N1 virus by influencing the release of influenza viral RNA-containing particles into the air . The neuraminidase activity of the influenza NA protein cleaves sialic acids from the proteins on the cell surface and on the viral surface [9] . The cleavage of sialic acids by the viral neuraminidase aids in viral release and the prevention of viral agglutination after release . Therefore , it is plausible that infection with a virus with a more active NA could result in the release of more virus particles into the air . To determine whether the activity of the Eurasian-origin NA differs from that of the classical swine NA , we used an enzyme-linked lectin assay to determine the neuraminidase activity of viruses that had been normalized for infectivity using fetuin as a substrate ( Figure 6A ) . Viruses that contain the Eurasian NA ( the biological and recombinant pH1N1 and the Eurasian viruses ) had higher NA activity than the TRS and 6∶2 reassortant viruses , which have a classical swine NA protein . A similar observation has been made previously using MUNANA as a substrate [13] . To confirm these results , we performed a neuraminidase assay using MUNANA as a substrate ( Figure 6B ) . MUNANA and fetuin differ in size; MUNANA is a short α2 , 6-linked sialic acid substrate while fetuin is much larger and contains both α2 , 3- and α2 , 6-linked sialic acids [38] , [39] . Since little is known about the biological substrates cleaved by NA in vivo , it is difficult to determine which substrates are biologically most relevant . We found that the Rec pH1N1 virus had a lower NA activity than the biological pH1N1 virus in both assays . The consensus sequence for the NA gene was identical for these viruses , suggesting that differences in the minor quasispecies composition of the respective virus populations may be the factor . Interestingly , with MUNANA , the Eurasian virus had lower NA activity than the pH1N1 virus , suggesting that NA proteins may have variable activity on different substrates . Our data indicate that the pH1N1 virus has a higher neuraminidase activity than the TRS and 6∶2 reassortant viruses with both long and short substrates , and higher neuraminidase activity than the Eurasian virus with short substrates . These observations suggest that NA activity correlates with the release of virus particles and increased viral release is important for efficient RD transmission of the pH1N1 virus . The Eurasian swine virus contributed both the NA and M gene segments to the pH1N1 virus and the M protein has been implicated in determining the filamentous or spherical morphology of influenza viruses [40]–[42] . Therefore , we compared the morphology of the Rec pH1N1 , 6∶2 reassortant , Eurasian , and TRS viruses by electron microscopy ( Figure 7 ) . The pH1N1 virus has previously been reported to be pleomorphic [29] and similar morphology was observed for the Rec pH1N1 virus ( Figure 7A ) . We counted 20 or more particles and found that 60% of the Rec pH1N1 virus particles were filamentous , while the 6∶2 reassortant virus was predominantly spherical with only 4% filamentous particles ( Figure 7B ) . These data suggest that the Eurasian-origin gene segments specify the pleomorphic phenotype of the pH1N1 virus . The pH1N1 precursor viruses ( Eurasian and TRS ) were both predominantly spherical ( Figure 7C and D ) , with only 9 . 5% or 0% filamentous particles , respectively . Taken together , these observations indicate that the Eurasian-origin gene segments alone are not sufficient to specify the pleomorphic morphology of the pH1N1 virus . The cytoplasmic tails of both HA and NA have previously been shown to contribute to influenza viral morphology [43] . However , the viruses used in this manuscript all contain the classical swine HA . Therefore , it is likely that specific adaptations in the pH1N1 viral gene segments that are distinct from the Eurasian swine gene segments have arisen and these changes may have contributed to the pleomorphic nature of the pH1N1 virus . Additionally , the complete passage history of the Eurasian virus is not known but may be relevant to its morphology . Previous studies have suggested that receptor specificity correlates with RD transmission [17] , [44] . However , all of the viruses tested in this study have HA proteins that are evolutionarily similar to the classical swine virus ( Table 1 ) and are antigenically similar to each other ( data not shown ) . We evaluated receptor binding specificity using an in vitro assay with chicken RBCs specifically sialylated with α2 , 3 or α2 , 6 sialyltransferases ( Figure S4A ) and demonstrated that all of the viruses predominantly associate with α2 , 6-linked sialic acids . Since virus-receptor affinity may be altered during viral evolution [45] , we tested whether the viruses used in this study differed in their affinity for the α2 , 6 receptor by measuring their ability to agglutinate chicken red blood cells ( RBCs ) that had been treated with varying amounts of neuraminidase ( Figure S4B ) . We found that all of the viruses bound to RBCs that were desialylated with similar concentrations of bacterial neuraminidase; therefore , we conclude that neither receptor specificity nor receptor affinity are responsible for the particle release observed in this study . Taken together , our data suggest a role for the Eurasian-origin segments in the morphology and NA activity of the pH1N1 virus , one or both of which contribute to its efficient transmission .
This study was designed to identify the molecular determinants that confer transmissibility of the pH1N1 virus and the mechanism by which they promote transmission . RD transmission can be modulated at the level of the infected donor , the environment , and the recipient . We established an RD transmission caging system that allowed for aerosol sampling of infected ferrets . In our system , the Rec pH1N1 virus transmitted to 100% of the naïve animals and replacement of the NA and M gene segments with the corresponding gene segments from TRS resulted in reduced transmission efficiency . These findings indicate that the Eurasian-origin NA and M gene segments contribute to the efficient transmission of the Rec pH1N1 virus . The fact that the Eurasian virus only transmitted to 50% of the naïve animals demonstrates that gene constellation may influence this phenotype as it does other properties such as virulence [46] . Yen et al . have recently suggested that a balance between HA and the Eurasian-origin NA contribute to the transmissibility of the pH1N1 virus [13] . Unlike our study , they used swine isolates that had not infected humans; therefore , any compensatory mutations that promote the initial transmission from an animal host to human were not taken into account . Based on our results , we believe that the biological properties of both Eurasian-origin gene segments influence particle release and thus efficient RD transmission . In our study , we found that susceptibility of the recipient ferrets to the specific virus , measured as the FID50 of the virus , did not correlate with transmission efficiency . Since environmental factors such as temperature and relative humidity were unaltered during the study , they did not contribute to the transmission phenotype . Therefore , we focused our attention on the release of influenza viruses by the infected donor ferrets . The viruses used in this study shared similar receptor specificity and replicated efficiently in the upper respiratory tract of ferrets . These two factors have been implicated in the transmissibility of other influenza viruses but they did not contribute to the enhanced transmission phenotype of the pH1N1 virus in our study . Using aerosol biosamplers to measure the release of virus into the air , we found that viruses containing the Eurasian-origin NA and M gene segments released influenza viral RNA-containing particles into the air consistently and this correlated with increased NA activity of these viruses . The Eurasian-origin gene segments also conferred the pleomorphic phenotype of the pH1N1 virus . Our observations extend our knowledge of the molecular determinants of RD transmission and provide an explanation for the epidemiological success of the pH1N1 virus . An infected donor can generate aerosols during normal breathing or upon sneezing and coughing [47] . In our study , we used ferrets as donors because they are highly susceptible to influenza viruses and can both transmit the virus to humans and acquire infection from humans [48] . Ferrets infected with influenza viruses develop clinical symptoms such as weight loss , sneezing , and lethargy [49] . Disease severity in ferrets and humans varies by strain , with highly pathogenic strains such as H5N1 avian influenza viruses causing more severe disease than seasonal influenza strains [29]–[31] . We found that the 2009 pH1N1 virus and its precursor viruses caused similar disease severity in ferrets , defined by >10% weight loss and presence of clinical symptoms like sneezing and runny nose ( Table S1 ) . However , we also found that one out of four ferrets infected with TRS or Eurasian viruses developed croup and were able to efficiently transmit the virus to their naïve partners . Upon further analysis , we found a correlation between infected ferrets that were observed sneezing or coughing and infection of their naïve neighbors , indicating that generation of aerosols by sneezing and coughing enhances RD transmission . In this study , we examined the size of influenza viral RNA-containing particles released from ferrets infected intranasally ( IN ) with influenza viruses and found that the ferrets primarily released influenza viral RNA-containing particles greater than 4 µm in size into the air ( Figure 3 ) . Consistent with our observations , Gustin et al . reported that anesthetized ferrets infected IN predominantly released large ( >4 . 7 µm ) infectious particles during normal breathing . However , they found that ferrets infected by aerosol released much smaller ( 0 . 65 to 4 . 7 µm ) particles containing infectious virus into the air [37] . We found that ferrets inoculated IN with pH1N1 and Eurasian viruses released large ( >4 µm ) and small ( 1 to 4 µm ) influenza viral RNA-containing particles more consistently than ferrets infected with the TRS and 6∶2 reassortant viruses ( Figure 3 and 4 ) . The viruses with more consistent release of virus had a higher NA activity than viruses that were associated with sporadic release of influenza viral RNA-containing particles ( Figure 6 ) . Thus , NA activity correlates with the release of both large and small influenza viral RNA-containing particles . However , these particles are not sufficient for efficient RD transmission since the Eurasian virus , which consistently released large and small influenza viral RNA-containing particles , transmitted to only 50% of the naïve animals ( Figure 2B ) . Additionally , in animals infected with the TRS virus , we only detected the presence of large particles containing influenza viral RNA in the air , yet this virus transmitted to 50% of the naïve animals . These data suggest that the large particles ( >4 µm ) may contribute to RD transmission of viruses in the ferret model system . Release of large particles containing influenza has been observed in human clinical studies [23] . However , the relative importance of these particles in human transmission is unclear . Interestingly , release of submicron influenza viral RNA-containing particles differed between pH1N1 and the Eurasian viruses ( Figure 5 ) . The Rec pH1N1 infected ferrets consistently released submicron influenza viral RNA-containing particles while ferrets infected with the Eurasian virus did not . Given that the animal cages have a continuous air flow rate of 40 cubic feet per minute , it is also possible that we were unable to thoroughly capture the submicron particles released by the ferrets by sampling on the outside of the cage . Aerosol sampling in different environments suggests that humans predominantly release small , respirable particles that likely result in the respiratory or aerosol transmission of influenza viruses [22] , [23] , [34] . Since the pH1N1 infected ferrets released more submicron particles than ferrets infected with any of the other viruses , it is possible that the submicron particles are responsible for the efficient aerosol transmission of the pH1N1 virus . Previous studies have demonstrated a role for HA receptor binding specificity and specific amino acid residues in the PB2 protein on RD transmission of influenza A viruses [17]–[19] , [50] . The emergence and transmissibility of the 2009 pH1N1 virus cannot be explained by these molecular determinants of transmissibility of the virus via RDs . Instead , our study illustrates the importance of the NA and M proteins in the transmissibility of the pH1N1 virus . We found that NA activity correlates with the release of particles greater than 1 µm in size and this may be necessary , but not sufficient , for RD transmission . Additionally , we found that viral morphology correlated with transmissibility of swine-origin viruses in the ferret model . The pleomorphic Rec pH1N1 virus was more efficiently transmitted than the spherical 6∶2 reassortant , TRS , and Eurasian viruses , suggesting that this phenotype may be important for RD transmission of swine-origin viruses . While there are many examples of α2 , 6-specific receptor binding influenza viruses that do not transmit in animal models or in the human population [14] , [51] , there are no reports of RD transmission of α2 , 3-specific receptor binding influenza viruses . Therefore , virus receptor binding specificity is also necessary , but not sufficient , for transmission . Our data indicate that in order to more accurately assess pandemic threat potential , phenotypes that are important for transmission such as viral replication in the upper respiratory tract of ferrets , release of respirable influenza virus-containing particles , and receptor specificity of novel influenza viruses should be characterized .
This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The National Institutes of Health and MedImmune Animal Care and Use Committee ( ACUC ) approved the animal experiments that were conducted at the respective facilities . All efforts were made to minimize suffering . Madin-Darby canine kidney ( MDCK ) cells , obtained from the ATCC , were maintained in minimum essential media ( MEM ) and 10% fetal bovine serum ( FBS ) . 293T cells , obtained from ATCC , were maintained in Dulbecco's MEM with 10% FBS . The reverse genetics system for generating the 2009 pandemic H1N1 virus ( A/California/07/2009 ) were previously described [52] . The NA and M gene segments for the North American TRS virus ( A/Ohio/02/2007 ) were constructed as previously described [52] . The recombinant viruses generated from the reverse genetics plasmids were rescued from MDCK/293T cell co-culture and propagated in specific pathogen free ( SPF ) embryonated eggs as described [53] for 2 passages . Viruses generated by reverse genetics were confirmed by genomic sequencing . The A/Ohio/02/2007 ( H1N1 ) and A/Thailand/271/2005 ( H1N1 ) viruses were obtained from the Centers for Disease Control and Prevention ( CDC ) and were subsequently propagated in MDCK cells . The passage histories for the biological isolates are C5 and CX , C3/C2/C2 for A/Ohio/02/2007 and A/Thailand/271/2005 , respectively where X indicates an unknown number of passages . All transmission studies consisted of four RD transmission cages , 3 male cages and 1 female cage . Each transmission cage contained two ferrets – 1 naïve and 1 infected , per cage ( Figure S3 ) . For each study 6 male and 2 female , 5–8 month old adult ferrets obtained from Triple F farms ( Sayre , PA ) that were seronegative for seasonal H3 and H1 viruses , and all of the viruses used in this study . As in other RD transmission studies [27] , [33] , [51] the sample size is small . Ferrets were inoculated intranasally ( IN ) with 106 . 5 TCID50 of virus in 500 µL of Leibovitz-15 medium . All ferrets were monitored for clinical signs including sneezing , coughing , lethargy , weight loss , and body temperature changes . In accordance with NIAID Animal Care and Use Committee ( ACUC ) guidelines , ferrets were euthanized if they lost more than 20% of their initial body weight . Ferret infectivity studies were performed at MedImmune ( Mountain View , CA ) . Two male and one female adult ferrets ( 5–6 month old ) were inoculated IN with each dose ( 10 , 100 , or 10 , 000 TCID50 per 500 µL ) of virus . Ferrets were considered infected if one of the following criteria was met: detection of virus in nasal secretions or by the presence of >40 influenza-specific antibody titer in the sera . Ferret infectious dose 50 ( FID50 ) values were calculated using the method described by Reed and Muench [54] . Nasal secretions were collected by washing the right nostril of an anesthetized ferret with sterile PBS and 500 µL of liquid that was expelled from the left nostril was collected . These nasal secretions were analyzed for the presence and titer of infectious viruses and expressed as 50% tissue culture infectious doses ( TCID50 ) per mL . We designed the caging system for transmission studies based on earlier reports [33] . Briefly , large stainless steel ventilated ferret cages from Allentown ( Allentown , New Jersey ) were modified for the RD transmission studies ( Figure S3 ) . Two perforated stainless panels were welded together , 0 . 5 inches apart , and placed into the cage with a floor and ceiling guide to stabilize the panel . A door , with separate feeder and water bottles on each side of the dividing panel , was manufactured for each cage . Infected ferrets were placed into the section of the cage closest to the air inlet one day prior to infection . One day post-infection , a naïve ferret was placed into the cage on the other side of the divider . Environmental conditions inside the laboratory were monitored daily and were consistently 19±1°C and 56±2% relative humidity . The transmission experiments were conducted in the same room , to minimize any effects of caging and airflow differences on aerobiology . Nasal washes were collected and clinical signs were recorded on alternate days for 14 days . Air samples were collected between 9 am to 12 pm on alternate days for 10 days . On day 14 post-infection , blood was collected from each animal for serology . The naïve ferret was always handled before the infected ferret . Great care was taken during nasal wash collections and husbandry to ensure no direct contact occurred between the ferrets . Ferret sera were tested for the presence of anti-influenza antibodies by hemagglutination inhibition ( HAI ) assay using turkey red blood cells ( RBC ) and neutralization assay using MDCK cells as described previously [53] , [55] . Ferrets were considered to have seroconverted if the antibody titer was higher than the limit of detection . The limit of detection is 1∶10 for the HAI assay and 1∶20 for the neutralization assay . Aerosol sampling of the ferret cages was performed between 9 am and 12 pm on alternate days for 10 days , prior to nasal wash collection . The air samples were collected by placing cyclone-based air samplers ( BC251 ) developed by the National Institute for Occupational Safety and Health ( Morgantown , WV ) [22] on the outside of the infected side of the ferret transmission cage . A designated air sampler was used for each ferret to reduce cross-contamination between animals . A baseline or day 0 reading was obtained on the infected ferrets prior to inoculation and 24 hrs after the animal was placed into the transmission cage . Air was sampled for one hour at a flow rate of 3 . 5 liters per minute . The aerosol sampler flow rate was calibrated before each use using a flow meter ( TSI 4100 series ) . The NIOSH BC251 samplers separate particles based upon size . Each sampler contained an empty 15 mL conical that collected particles greater than 4 µm , a 1 . 5 mL conical that collected particles between 1–4 µm , and a 3 µm pore Fluoropore membrane filter ( Millipore ) to collect submicron particles . Processing of the samplers was performed in a bio-safety cabinet; 500 µL of Ambion RNA lysis binding buffer was placed into each collection tube and vortexed vigorously . RNA was extracted from each collection tube on a QIAGEN EZ Robot using the QIAGEN EZ1 virus mini kit , per the manufacturer's recommendations . The total amount of influenza RNA was quantified using Applied Biosystems Taqman one-step RT-PCR kit with primers ( F – 5′AGATGAGTCTTCTAACCGAGGTCG3′ , and R - 5′GCAAAGACATCTTCAAGTCTCTG3′ ) and a probe ( FAM-TCA GGC CCC CTC AAA GCC GA–[NFQ] ) specific for the influenza A M gene segment . In vitro transcribed RNA corresponding to this region of the M gene segment was used as a standard for absolute quantification . The RNA standard was created by , linearizing a pCDNA3 . 1 plasmid containing the T7 promoter and M gene sequences of influenza virus strain A/Beijing/262/95 . This DNA was used as templates with the MEGAScript In Vitro Transcript Kit ( Ambion ) to generate Flu A M gene transcript . Transcripts were purified by extraction with Phase Lock Gel ( PLG ) ( Heavy ) tubes ( Eppendorf Scientific , Inc . ) two times , followed by phenol/chloroform , chloroform extraction and ethanol precipitation . The dried RNA pellet was resuspended in RNase-free RNA storage buffer ( 1 mM sodium citrate , pH 6 . 4; Ambion ) . The concentration of the purified transcript was determined by measuring absorbance at 260 nm . 10-fold serial dilution of the FluAM transcript in RNA storage buffer was performed to generate transcript at the level of 5×106 down to 5 copies/µL . The limit of detection of the NIOSH BC251 samplers is unknown . After each use , the BC251 samplers were decontaminated by first rinsing each sampler with distilled water , making sure to wash the air inlet and other holes , then washing the samplers with isopropanol , again running the alcohol through the air inlet and all other holes . Activity of the NA protein of each virus was determined using a peanut-agglutinin based enzyme-linked lectin assay ( ELLA ) . The ELLA assay was slightly modified from a previously described assay [56] . The ELLA assay uses fetuin as a substrate for the viral neuraminidase . Viruses were normalized for infectivity , 106 . 5 TCID50 per 500 µL , prior to performing the assay . Neuraminidase activity using MUNANA as a substrate was preformed using the NA star kit obtained from Applied Biosystems , and following the manufacturers instructions . A 2 mL aliquot of each stock virus , described in the ‘Viruses’ section , was concentrated by ultra-centrifugation using a Beckman Coulter L-100 XP ultracentrifuge with a SW-55i rotor . Viruses were pelleted at 24K rpm for 2 hrs; the pellet was resuspended in 20 µL of 1x Karnovsky's fixative solution . Concentrated viruses were sent to the Electron Microscopy unit at Rocky Mountain Laboratory ( Hamilton , MT ) for negative stain and analysis . Freshly glow discharged Formvar-carbon coated copper grids ( Ted Pella , Inc . , Redding , CA ) were submerged in droplets of each sample and incubated overnight at 4 degrees C in a humid chamber . The grids were washed three times for 5 min each in deionized water , and negatively stained for 15 sec with methylamine tungstate ( Nanoprobes , Inc . , Brookhaven , NY ) . The grids were examined at 80 kV on a Hitachi H7500 transmission electron microscope . Digital images were captured on an HR-100 CCD camera ( Advanced Microscopy Techniques , Danvers , MA ) , and rendered using Adobe PhotoShop ( Adobe Systems , Inc . , San Jose , CA ) . The percent filamentous particles were calculated by counting over 20 particles for each virus from blind pictures taken randomly on the grid .
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Influenza A viruses spread rapidly from person-to-person via respiratory droplets ( RDs ) . In this study we used a ferret model to explore viral functions involved in RD transmission of influenza viruses . The 2009 pandemic H1N1 ( pH1N1 ) virus originated by reassortment of a North American triple reassortant swine ( TRS ) virus with a Eurasian swine virus . Both TRS and Eurasian swine viruses had previously caused sporadic infections in humans , but failed to spread from person-to-person , unlike the pH1N1 virus . We evaluated the release of influenza virus-containing aerosols and the transmissibility of the pH1N1 , TRS , and Eurasian viruses in ferrets and found that the Eurasian-origin gene segments contributed to efficient RD transmission of the pH1N1 virus by modulating the release of influenza viral RNA-containing particles into the air . The increased release of viral RNA-containing particles correlated with increased viral neuraminidase activity and production of filamentous viral particles . These observations enhance what we currently know about the viral requirements for influenza virus RD transmission and have implications for assessing the potential of novel influenza viruses to spread .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biology"
] |
2011
|
Eurasian-Origin Gene Segments Contribute to the Transmissibility, Aerosol Release, and Morphology of the 2009 Pandemic H1N1 Influenza Virus
|
Few animal models of Zika virus ( ZIKV ) infection have incorporated arthropod-borne transmission . Here , we establish an Aedes aegypti mosquito model of ZIKV infection of mice , and demonstrate altered vector competency among three strains , ( Orlando , ORL , Ho Chi Minh , HCM , and Patilas , PAT ) . All strains acquired ZIKV in their midguts after a blood meal from infected mice , but ZIKV transmission only occurred in mice fed upon by HCM , and to a lesser extent PAT , but not ORL , mosquitoes . This defect in transmission from ORL or PAT mosquitoes was overcome by intrathoracic injection of ZIKV into mosquito . Genetic analysis revealed significant diversity among these strains , suggesting a genetic basis for differences in ability for mosquito strains to transmit ZIKV . The intrathoracic injection mosquito-mouse transmission model is critical to understanding the influence of mosquitoes on ZIKV transmission , infectivity and pathogenesis in the vertebrate host , and represents a natural transmission route for testing vaccines and therapeutics .
Zika virus ( ZIKV ) , a member of the flaviviridae family , was originally isolated from a sentinel monkey in the Zika forest of Uganda in 1947 [1] . The first case of ZIKV infection in humans was reported in Nigeria in 1954 [2] . For half a century , serologic evidence suggests that the virus circulated in Africa and Southeast Asia , although fewer than 20 symptomatic infections were documented [3] . Recently , a large epidemic in South and Central America and the Caribbean , which also spread to limited areas in the southernmost parts of the contiguous United States , has affected over a million people [4] . Historically , ZIKV has manifested as a relatively mild self-limiting illness , with fever , rash , malaise and headache reported as the most commons symptoms , and up to 80% of infected individuals remaining asymptomatic [3 , 5 , 6] . These new epidemics , however , have been associated with Guillain-Barre syndrome in adults , and congenital deformities and neurologic syndromes in newborns [7–9] . The increase in disease severity and rapid spread of ZIKV has led to increasing alarm across the globe . ZIKV is thought to spread mainly through the bite of an infected mosquito , similar to other flaviviruses such as dengue and West Nile virus [10] . The major mosquito vector for ZIKV is Aedes aegypti , which most likely originated in Africa and is now endemic in tropical and subtropical locations . While ZIKV has regularly been found to persist in populations of Ae . aegypti in areas where this virus is circulating [8] , data related to the experimental transmission of Ae . aegypti with ZIKV in a laboratory setting has been sparse [11–13] . A recent publication has shown experimental transmission from mosquito to mouse and back to mosquito [14] , but , to date , no experimental model of the transmission cycle from infected mammalian host to mosquito and back to mammalian host has been demonstrated . Also , the importance of a robust model for mosquito transmission of ZIKV is highlighted by recent work in a macaque model , showing that mosquito bite infection of animals significantly changes the viral replication dynamics and tissue tropism as compared to needle inoculation [15] . These studies were carried out with a contemporary pandemic strain of ZIKV , but additional work is planned to determine the significance of pre- and post-pandemic viral strains on replication within the mosquito vector . A significant amount of genetic diversity exists within the Ae . aegypti species [16] , so we hypothesized that the genetic background of individual strains of Ae . aegypti plays an important role in vector competence for ZIKV . This hypothesis is supported by research showing the dissemination of ZIKV within the mosquito host differs among mosquito strains , from Dominican Republic , Brazil and U . S . A [17 , 18] , and species [17 , 18] in the wild . ZIKV poses a significant public health risk , and exploring the relationship between vector and pathogen is an important factor in determining the risk imposed by individual populations of mosquitoes . It is also vital to explore the role of the vector in ZIKV replication , infectivity , and pathogenesis within the mammalian host . In this study , we demonstrate a transmission cycle between infected mice to mosquitoes and back to mice using three Ae . aegypti colonies , which were selected based on their genetic distinctness among tested strains , the Orlando ( ORL ) strain , a common laboratory colony , the Ho Chi Minh ( HCM ) strain and the Patilas ( PAT ) strain , both recently established colonies from the field ( ~14 generations and ~3 generations , respectively ) , and using mice lacking receptors for interferon α/β/γ ( AG129 mice ) , which are susceptible to low levels of ZIKV [19] . We also show that intrathoracic inoculation with ZIKV results in highly infectious mosquitoes regardless of strain , which will be important for future studies on the effect of mosquitoes in ZIKV infection and represents a natural route of infection for future studies of vaccines and therapeutics .
All experiments were performed in accordance with guidelines from the Guide for the Care and Use of Laboratory Animals of the NIH . Protocols were reviewed and approved by the IACUC at Yale University School of Medicine ( Assurance number A3230-01 ) . Every effort was made to reduce distress in animals . Animals were anesthetized with ketamine/xylazine for mosquito infection experiments , and sacrificed using CO2 inhalation as recommended by the Yale IACUC . Vero cells ( ATCC ) were maintained in DMEM containing 10% FBS and antibiotics at 37°C with 5% CO2 and have been routinely confirmed to be mycoplasma free . Aedes albopictus C6/36 cells were grown in DMEM supplemented with 10% FBS , 1% tryptose phosphate , and antibiotics at 30°C with 5% CO2 . Mexican strain ZIKV ( ZIKVMEX , Accession number KX446950 ) , MEX2-81 , was obtained from the University of Texas Medical Branch at Galveston’s World Reference Center for Emerging Viruses and Arboviruses and propagated in C6/36 insect cells . Eggs from ORL and HCM strains of Ae . aegypti were obtained from the Connecticut Agricultural Experimental Station and the HCM colony maintained at the Powell laboratory at Yale , respectively . Other laboratory strains arrived as eggs from different laboratories: Liverpool ( D . Severson , University of Notre Dame ) , Rockefeller ( G . Dimopoulos , Johns Hopkins School of Public Health ) . Field strains came as eggs collected from traps in the wild from Amacuzac , ( Mexico ) and Patillas ( Puerto Rico ) Eggs were hatched in a shallow dish with distilled water with 2 parts brewer’s yeast ( Bioserv #1710 ) and 3 parts desiccated liver powder ( Bioserv #1320 ) . After pupae emerged , mosquitoes were collected and placed in a small crystal dish with distilled water inside a 12” x 12” x 12” metal mesh cage ( BioQuip #1450B ) . Adult mosquitoes are maintained on 10% sucrose feeders in walk-in incubator at 28o C and ~80% humidity . Egg masses are generated via blood meal on naïve mice . Three to six week old Ifnαr1-/-Ifnγr-/- mice ( AG129 –SV129 background ) were analyzed in this study . Approximately equal numbers of male and female mice were used . Mice were bred in a specific-pathogen-free facility at Yale University . Virus-specific antibodies ( IgG ) in serum from mice infected with ZIKV were analyzed by using an enzyme-linked immunosorbent assay ( ELISA ) . Recombinant ZIKV Envelope protein ( Mybiosource , MBS140822 ) ( 0 . 1μg/well ) were coated to 96 well plates overnight at 4°C . After the plates were blocked with 2% skim milk for 1 h at room temperature , the plates were then incubated with serum samples serially diluted in PBS for 1 h at room temperature . After being washed with PBS-T three times , the plates were incubated with an HRP-conjugated anti-mouse IgG antibody . After the plates were washed again with PBS-T , 3 , 3’ , 5 , 5’-Tetramethylbenzidine solution was added to each well and incubated for 15 min at room temperature . The reaction was stopped by the addition of 1M H2SO4 . The optical density at 450 nm ( OD450 ) was measured and analyzed . The cut-off value was calculated as the mean OD450 + 3SD acquired from corresponding samples from three naïve mice . Adult mosquitoes were flash frozen and total nucleic acids extracted from individual Ae . aegypti mosquitoes using the DNeasy Blood and Tissue kit ( Qiagen ) according to manufacturer instructions , with an additional RNAse A ( Qiagen ) step . Individual mosquitoes were genotyped as described in [20] . The microsatellite loci analyzed were: A1 , B2 , B3 , A9 ( tri-nucleotide repeats ) , and AC2 , CT2 , AG2 , AC4 , AC1 , AC5 , AG1 , and AG4 ( di-nucleotide repeats ) [21] . Polymerase chain reactions were conducted as 10μl reactions using the Type-it Microsatellite PCR Master Mix ( Qiagen ) , 25 nM of each forward primer , 250 nM of each reverse primer , and 500 nM of a fluorescently labeled M13 primer to allow multiplexing [22] . Microsatellite primer sequences , multiplex pairings and fluorescent primers are as described in [22] . PCR products were run for fragment analysis on an Applied Biosystems 3730xl DNA Genetic Analyzer with a GS 500 Rox internal size standard ( Applied Biosystems ) at the DNA Analysis Facility at Science Hill at Yale University . Microsatellite alleles were scored using GeneMapper v4 . 0 ( Applied Biosystems ) . For oral-infection , naïve AG129 mice are first infected subcutaneously with 105 PFU of ZIKVMEX . One day before oral-infection , mosquitoes are collected via vacuum aspiration and placed in paper cups with mesh lids without sucrose . At 4 days post ZIKV injection , infected mice are anesthetized using Ketamine-Xylazine and laid on top of mesh lids to allow mosquitoes to take infectious blood meal . Fed mosquitoes are placed back in paper cups with mesh lids and maintained in triple containment for 7 or 10 days . For ZIKV injection experiments , mosquitoes were knocked-down on ice before transfer to a cold plate under a dissecting microscope . A pulled microcapillary needle was filled with ZIKV using a Nanoject II auto-nanoliter injector ( Drummond ) . ZIKV-filled needle is carefully inserted into the thorax of each mosquito and 69 nl of virus ( ~1000 PFU ) is injected . Injected mosquitoes are placed in paper cups with mesh lids and maintained in triple containment for 7 to 10 days . The infection rate of each strain was calculated by comparing infected vs . uninfected mosquitoes ( Infection rate ( % ) = 100 x [# of infected mosquitoes/# of total mosquitoes] ) in each experiment . Three to six week old AG129 mice were inoculated with ZIKV via subcutaneous ( footpad , a volume of 50 μl ) with 105 PFU of ZIKV or anesthetized with Ketamine-Xylazine and fed on by ZIKV infected mosquitoes . Survivals and weight were monitored every day . Mice exhibiting neurologic disease or weight loss of >20% of initial body weight were euthanized . Blood was collected at 1 , 3 , 5 , and 7 dpi in Trizol , RNA was purified and RT-PCR was performed to produce cDNA . For mosquitoes , midguts ( MG ) and salivary glands ( SG ) were dissected and placed in individual tubes in RLT buffer with 0 . 1% ß-mercaptoethanol . RNA extraction was performed using RNeasy Mini Kit ( QIAGEN ) according to manufacturer’s instructions . For mice , chloroform was added to blood samples from ZIKV-infected mice . Tubes were vortexed and centrifuged for 10 min at 14 , 000 rpm at 4°C . Aqueous layers was mixed with 100% ethanol and RNA was extracted with RNeasy Mini Kit according to manufacturer’s instructions . Extracted RNA was reverse-transcribed with iScript cDNA Synthesis Kit ( Bio-rad ) according to manufacturer’s protocol . Gene expressions was measured using IQ SYBR Green Supermix . ZIKV RNA levels were normalized to mosquito Rp49 RNA levels or mouse β actin RNA levels using the 2-ΔCt calculations . Plaque assays were performed as previously described [23] . Population structure was evaluated via the Bayesian clustering method implemented by the software STRUCTURE v . 2 . 3 [24] . The most likely number of clusters ( K ) was determined by conducting 20 independent runs from each K = 1 to 4 . Each run assumed an admixture model and correlated allele frequencies using a burn-in value of 100 , 000 iterations followed by 500 , 000 repetitions . The optimal number of K clusters was determined both following the guidelines of [24] and the Delta K method from [21] with the online version of STRUCTURE HARVESTER v . 0 . 6 . 94 [24] . Plots of the most biologically informative number of clusters ( K = 2 ) were generated with the program DISTRUCT v . 1 . 1 [25] . Principal Component Analysis ( PCA ) and Discriminant analysis of Principal Components ( DAPC; [26] ) were performed on allele frequencies and plotted with the ADEGENET package [27] in R v . 3 . 2 . 2 . ( R Core Team 2013 ) . GraphPad Prism software was used to analyze all data . Log10 transformed titers used for plaque assays , and either β actin or Rp49 normalized viral RNA or tissue weight-normalized values were analyzed using one-way ANOVA and post-hoc Tukey test for multiple comparisons , where appropriate as indicated in figure legends . A p value of <0 . 05 was considered statistically significant .
Genetic strains of Ae . aegypti vary in their ability to become infected and transmit flaviviruses [11 , 28] . We genotyped six representative laboratory and field-derived Ae . aegypti colonies using 12 microsatellite markers , as described previously [16] , and used multiple population genetic analyses to compare them . Principle component analysis ( PCA ) ( Fig 1A ) shows a large amount of genetic diversity among all strains . Since it is possible that these genetic differences lead to differences in the capacity for these strains to harbor and transmit ZIKV , we examined three disparate strains in an experimental murine model of mosquito-borne ZIKV infection , a well-studied laboratory strain originally from Florida ( Orlando , ORL ) and two recently collected strains , one from Vietnam ( Ho Chi Minh , HCM ) which is shown to be genetically distinct from the ORL strain by PCA analysis and one from Puerto Rico ( Patilas , PAT ) which can be seen to group between ORL and HCM genetically by PCA analysis ( Fig 1A ) . By varying the optimal number of gene clusters in bayesian clustering analysis [24] from K = 2 ( Fig 1B upper panel ) to K = 3 ( Fig 1B lower panel ) , we are able to demonstrate that the PAT strain is distinct from both the HCM and the ORL strain , but is closer genetically to the ORL strain . The alleles driving the differentiation among these strains are AC1 and CT2 , and the allelic frequencies among the three strains further demonstrate the genetic uniqueness of these mosquito colonies ( Fig 1C ) . Furthermore , a multivariate method of discrimination analysis of principal components–DAPC [27] ( Fig 1D ) shows that these three strains are genetically distinct , but the PAT strain is more similar to the ORL strain than the HCM strain . A second PCA analysis , using only the three tested strains , also demonstrates the genetic distinction among these groups and suggests a closer genetic similarity between the PAT and ORL strains ( S1 Fig ) . Intrathoracic injection of virus has been shown to generate virus replication in mosquito models for many viruses [29 , 30] and , recently , also for ZIKV . To determine if this was also true for our three strains , we injected 103 PFU of ZIKVMex , directly into the thorax of ORL , PAT and HCM strains as described in [31] ( Fig 2A ) . ZIKV replication was detected in SG and MG of all strains of mosquitoes ( Fig 2B ) , and 100% of injected mosquitoes exhibited viral replication in both SG and MG ( Fig 2C ) . In these strains , ZIKV replication was observed in the SG and the MG at 7 and 10 days after inoculation of these mosquitoes ( Fig 2B ) . Interestingly , we observed significantly higher ZIKV levels in the MG of the HCM strain at day 10 as compared to either the PAT or ORL strain , although this experiment uses an artificial infection technique of intrathoracic injection that may not be reflected upon natural infection by blood feeding . These data demonstrate that all tested mosquito strains can sustain ZIKV replication , and the significantly higher infection in the MG of HCM mosquitoes at day 10 after ZIKV injection suggests an increased ability to replicate in these mosquitoes . To determine if intrathoracic ZIKV injected mosquitoes could efficiently transmit virus to mice , we fed these infected mosquitoes on naïve mice ( Fig 3A ) . Most mice showed ZIKV RNA in the blood after being fed upon by ZIKV-injected mosquitoes ( Fig 3B ) . Although we observed a significant difference at day 3 post feeding , there was no differences at other tested days after feeding . Of note , 67% ( 4 of 6 mice , ORL strain , 7 days post injection ) , 86% ( 6 of 7 mice , ORL strain , 10 days post injection ) , 57% ( 4 of 7 mice , PAT strain , 7 days post injection ) , 71% ( 5 of 7 mice , PAT strain , 10 days post injection ) , 25% ( 2 of 8 mice , HCM strain , 7 days post injection ) and 83% ( 5 of 6 mice , HCM strain , 10 days post injection ) of mice demonstrated significant hind-limb paralysis and were sacrificed after being infected by these mosquitoes , with no significant differences by groups ( Fig 3C ) . To further support that transmitted ZIKV was the cause of death in these mice , we performed plaque assays and showed replicating virus present in the brain of these mice ( Table 1 ) . We also examined whether mice that survived virus infection elicited ZIKV-specific antibodies after feeding . We found that most mice with positive ZIKV titers in the serum developed virus-specific antibodies after infected- mosquito feeding , which also supports mosquito-mouse transmission ( S1 Table ) . This mode of transmission is very efficient , as all mosquitoes became infected and could transmit virus , and could be useful for future studies , but we also wanted to demonstrate a more natural route of transmission of ZIKV infection from an infected mammalian host to a mosquito vector and back to a naïve mammalian host . We were also curious if the differences we observed in the higher viral replication in the MG of the HCM strain would be apparent in this mouse-mosquito-mouse cycle . To examine whether ZIKV can be transmitted from infected mice to Ae . aegypti , we subcutaneously infected AG129 mice with 105 PFU of ZIKV . Four days after infection , the ORL , PAT and HCM strains of Ae . aegypti were allowed to ingest a blood meal from the ZIKV-infected mice in which the ZIKV level was 10 5 . 0±0 . 3 plaque-forming-units ( PFU ) equivalents per ml ( Fig 4A ) . ZIKV levels were low or undetectable in MG and SG of the ORL strain at 7 and 10 days after feeding , and the results varied in the PAT strain with some mosquitoes exhibiting higher levels of virus and some showing very low levels ( Fig 4B ) . Higher levels of ZIKV were detected in the MG of the HCM strain as compared to the ORL strain at both time points , and as the PAT strain at day 10 post-feeding ( Fig 4B ) . HCM mosquitoes also showed more virus replication in the SG relative to ORL , while the PAT strain had some mosquitoes that demonstrated virus levels closer to the HCM strain ( Fig 4B ) . Overall , the infection rates were significantly different among the ORL , PAT and HCM strains , with the PAT strain , interestingly , exhibiting a phenotype that is between the HCM and ORL strains but closer to the ORL strain ( Fig 4C ) . This intermediate phenotype demonstrated in the PAT strain could be interpreted as the genetic differences among the strains , demonstrated in Fig 1A–1D , is capable of driving a difference in vector competency , although other differences could also play a role . To assess whether mosquitoes which fed on ZIKV-infected mice are capable of transmitting ZIKV to naïve mice , we allowed these ZIKV-infected mosquitoes to engorge on naïve mice ( Fig 5A ) . No animals fed on by the ZIKV-infected ORL mosquitoes developed viremia or died , consistent with the low or undetectable level of ZIKV in the SG of these mosquitoes ( Fig 5B ) . ZIKV was detected , in the blood fed on by the PAT strain in 1 of 5 mice ( PAT strain , 7 days post blood meal ) , in HCM strain in 2 of 7 mice ( HCM strain , 7 days post blood meal ) and 1 of 5 mice ( HCM strain , 10 days post blood meal ) , respectively ( Fig 5B ) , but no mice fed upon by ORL strain mice ( 0 of 8 mice on day 7 and 0 of 8 on day 10 ) or by PAT strain at day 10 of mosquito infection ( 0 of 5 mice ) . In addition , the mouse on which the most highly infected HCM mosquito ( Fig 4B ) fed developed the ZIKV viremia ( Fig 5B ) , and by day 12 this mouse developed severe paralysis and was sacrificed due to ZIKV infection , which was confirmed by a replicating virus present in the brain ( Fig 5C , Table 1 ) . These results show that ZIKV can migrate from infected mice to Ae . aegypti , disseminate from the MG to the SG , and then be transferred back to naïve mice when mosquitoes ingest a blood meal . The transmission rate however , appears to be very low and depends on the ability for the Ae . aegypti strain to replicate in both the MG and the SG . A previous study demonstrated that the bacterial microbiome can alter mosquito vector competency [32] . These strains were all raised in the same environment for at least 3 generations , suggesting that the overall composition of the microbiome should be similar , but there is a chance that the ability for control of bacteria in the MG varies by strain . Therefore , to determine if these mosquitoes harbor significantly different levels of bacteria in their MG , an analysis of the overall 16s bacteria load was performed and no differences were observed ( S2 Fig ) .
Ae . aegypti is one of the most genetically diverse species of insect ever studied , and has the ability to rapidly adapt to human habitats [16] . Here , we established an Ae . aegypti mosquito model of ZIKV infection of mice . Consistent with recent studies , ZIKV transmits from infected mosquitoes to mice [14 , 15 , 33] . This study used AG129 mice for our transmission model , and this model has advantages for analyzing the pathogenesis of ZIKV or the effect of mosquito factors on ZIKV transmission and infectivity . We also demonstrated variability in the susceptibility of three genetically diverse colonies of Ae . aegypti , the ORL , PAT and HCM strains , to ZIKV infection . As viral replication in SG is important for ZIKV transmission to the vertebrate host , our results suggest that the HCM strain may be more capable than the ORL or PAT strain of transmitting virus . Also , these results were consistent with recent studies that suggest dissemination of ZIKV in Ae . aegypti depends on both virus and mosquito strains [17 , 34] . These observations have implications for the further spread of ZIKV into distinct populations of mosquitoes across the globe . There are multiple mechanisms by which the difference in vector capacity among strains could arise , such as genetic variation in metabolic and/or immune pathways , or entry or replication factors necessary for ZIKV infection [35] . While it is impossible to make any definitive statements on genes that drive differences in vector competency based solely on the location of the microsatellite markers used to analyze genetic variability , we are able to indicate genes that are proximal to the markers driving variability among the groups , particularly AC1 and CT2 ( Table 2 ) . In order to make a more definitive statement on genes involved in vector competency , further experiments crossing the strains and mapping single nucleotide polymorphisms ( SNPs ) or targeted gene modification is necessary . After a mosquito ingests an infectious blood meal , several steps are required for viral infection and subsequent transmission back to a mammalian host . Two types of MG and SG barriers are known to prevent infection by other viruses: one barrier prevents or controls virus infection of epithelial cells in the MG or SG , and the other is a MG or SG escape barrier which can block virus from escaping from the MG epithelial cells into the hemolymph or from the SG epithelial cells into the lumen of the SG [35 , 36] . Since ZIKV levels were very similar among the three strains during intrathoracic injection but the ORL and PAT strains were lower during oral feeding , it seems that the ORL and PAT strains harbor a MG barrier to infection related to either the ability to replicate ZIKV in the MG or for the virus to escape once it does replicate . This barrier appears to be related to the underlying genetic differences among the strains , but it is also possible that the microbiome composition of the mosquito MG contributes to these phenotypes [37] . The vast majority of the microbiome of the mosquito is acquired from the environment in which it was raised [38] , and we did not observe a difference in total bacteria burden . This further strengthens our hypothesis that the differences observed in vector competence are directly related to the genetic differences demonstrated in Fig 1 , but clearly the observed phenotypic differences could be more complex and the composition of the microbiome , or even the insect-specific viriome have the potential to play a role in these infections . Alternatively , previous studies on related viruses have demonstrated that the bacterial microbiome is capable of modulating mosquito vector competence [32] . It has been suggested that bacteria affect arbovirus replication in mosquitoes by regulating immunity , affecting the production of metabolites , and inducing anti-viral miRNA expressions [32 , 39 , 40] . Our data indicate that the overall microbiome is unchanged among these strains . During transmission from mosquitoes to mammalian hosts , SG proteins from the flaviviral vector , Ae . aegypti , are known to enhance viral replication and pathogenesis of both dengue and West Nile virus in mammalian hosts [41–43] . It is also clear that the immune response to specific vector proteins in the saliva of mosquitoes can alter the severity of flaviviral disease for individual patients [44] . These findings raise the possibility that specific Ae . aegypti SG components can facilitate greater ZIKV infection in vivo . The ZIKV mosquito to mouse transmission model established here is crucial for the exploration into this phenomenon for this important human pathogen . Many studies into ZIKV have been performed using needle inoculation of virus into a mouse model [19 , 45 , 46] , an unnatural route of infection that does not recapitulate what occurs in nature . While the data gained from these studies have undoubtedly uncovered interesting mechanisms of ZIKV replication and pathogenesis , the development here of a mouse-to-mosquito-to-mouse transmission model representing a natural route of infection has the potential to reveal aspects of the viral life cycle that have heretofore remained undiscovered . In addition , further investigation into the mechanisms that underlie the differences in vector capacities of these three strains has the potential to elucidate aspects of the life cycle of ZIKV in the Ae . aegypti mosquito .
|
Zika virus ( ZIKV ) , an emerging flavivirus , is associated with severe clinical outcomes , including Guillain-Barre syndrome and birth defects . Transmission of ZIKV is primarily mosquito-borne , but the complete transmission cycle from mammalian host to mosquito and back to mammalian host has not yet been demonstrated experimentally . Here , for the first time , we establish a transmission model of ZIKV between mice lacking both interferon α and interferon γ receptor ( AG129 ) and the Aedes aegypti mosquito , the main vector of ZIKV . We also highlight differences in vector competence among a common laboratory strain , Orlando ( ORL ) , and two wild-caught strains , Ho Chi Minh ( HCM ) and Patillas ( PAT ) , of the Aedes aegypti mosquito using oral feeding on infected mice and intrathoracic inoculation of ZIKV . Our results suggest different ZIKV susceptibility among these strains , which could be relevant as this virus spreads throughout the globe . In addition , the mosquito transmission model demonstrated here can be used to better understand the effect mosquitoes have on replication and pathogenesis of this virus .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
[
"invertebrates",
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"zika",
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] |
2018
|
Altered vector competence in an experimental mosquito-mouse transmission model of Zika infection
|
Dengue is the most prevalent mosquito borne infection worldwide . Vertical transmissions after maternal dengue infection to the fetus and pregnancy losses in relation to dengue illness have been reported . The relationship of dengue to miscarriage is not known . We aimed to establish the relationship of recent dengue infection and miscarriage . Women who presented with miscarriage ( up to 22 weeks gestation ) to our hospital were approached to participate in the study . For each case of miscarriage , we recruited 3 controls with viable pregnancies at a similar gestation . A brief questionnaire on recent febrile illness and prior dengue infection was answered . Blood was drawn from participants , processed and the frozen serum was stored . Stored sera were thawed and then tested in batches with dengue specific IgM capture ELISA , dengue non-structural protein 1 ( NS1 ) antigen and dengue specific IgG ELISA tests . Controls remained in the analysis if their pregnancies continued beyond 22 weeks gestation . Tests were run on 116 case and 341 control sera . One case ( a misdiagnosed viable early pregnancy ) plus 45 controls ( 39 lost to follow up and six subsequent late miscarriages ) were excluded from analysis . Dengue specific IgM or dengue NS1 antigen ( indicating recent dengue infection ) was positive in 6/115 ( 5·2% ) cases and 5/296 ( 1·7% ) controls RR 3·1 ( 95% CI 1·0–10 ) P = 0·047 . Maternal age , gestational age , parity and ethnicity were dissimilar between cases and controls . After adjustments for these factors , recent dengue infection remained significantly more frequently detected in cases than controls ( AOR 4·2 95% CI 1·2–14 P = 0·023 ) . Recent dengue infections were more frequently detected in women presenting with miscarriage than in controls whose pregnancies were viable . After adjustments for confounders , the positive association remained .
Each year there is an estimated 100 million dengue infections [1] , 500 thousand hospitalisations due to severe dengue illness [2] and 25 thousand dengue deaths [1] worldwide . Dengue's geographical reach is expanding [3] due in part to the complex interplay of climate warming [4] coupled with travel and trade [5] impacting on the observed extension in the range of the responsible mosquito vector [6] . Dengue's intensity in endemic areas has also increased due to the spread of urbanisation [3] . Dengue illness is caused by any one of four serotypes . Infection by one serotype is thought to produce lifelong immunity to that serotype but confers only a few months immunity to the others [7] . Secondary infection by a different serotype increases the risk of severe illness [8] . Typically , dengue infection is asymptomatic or minimally symptomatic in 87% of cases [9] . Hence , obvious dengue illness is the tip of the iceberg in dengue infection . In Malaysia where dengue is hyperendemic , all four serotype circulate concurrently [10] . In a recent report on a national sample of 1000 Malaysian adults aged 35–74 , the dengue seroprevalence rate was 91 . 6% with a positive age related trend [11] . Severe dengue illness during pregnancy is associated with major adverse outcome of maternal deaths [12] , [13] , perinatal deaths [12]–[14] , preterm births [12] , [14] and haemorrhages in labour with much of the data from case reports and small case series [15] . In a large prospective study of recent dengue infection detected at delivery , the pregnancy outcome of 63 parturients who were dengue IgM positive is not different from 2468 IgM negative controls [16] . Vertical transmission to the fetus ( particularly later in pregnancy ) is established [15] . The vertical transmission rate of maternal dengue infection can vary from at least 1·6% [16] to 6·8% [17] based on prospective studies . Miscarriages have been reported in association with dengue illness [13] , [14] , [18] , [19] but it is not clear whether the miscarriages were secondary to profound systemic disturbance as a consequence of severe dengue illness or to vertically transmitted dengue infection . Little is known on the effect of dengue infection in early pregnancy with regard to the risk of miscarriage . According to a recent review , pregnancy does not appear to increase incidence or severity of dengue but the literature is very sparse with very few systematic studies of dengue infection on pregnancy available [20] . Dengue specific immunoglobulin M ( IgM ) can be detected as early as the second day of symptoms and for up to three months [21] . The IgM level typically peaks on the sixth day [22] reaching 100% detection by the eighth day [23] . The dengue IgM test cross-reacts across all four dengue serotypes [24] and is produced even in a secondary infection [25] . The dengue non structural protein 1 ( NS1 ) antigen test is designed to diagnose all serotypes of dengue infection from Day 1 to Day 9 [22] . Dengue IgG antibodies is detected in 100% of cases by Day 15 of primary infection [23] and its presence without other evidence for acute infection is usually taken as distant exposure to any combination of the four dengue serotypes . We hypothesise that miscarriage is associated with exposure to dengue during early pregnancy due either to maternal dengue illness or vertical transmission . We sought to evaluate the prevalence of recent dengue infection ( using dengue IgM and NS1 tests ) in women presenting with miscarriage and in similar gestation women with viable pregnancy and to estimate the relative risk of miscarriage in women recently exposed to dengue infection .
Ethics approval for the study was obtained from the University of Malaya Medical Centre Medical Ethics committee ( approval no . 715 . 25 dated 22nd April 2009 ) . The study was conducted in keeping with the Declaration of Helsinki ( amended Seoul , Korea 2008 ) on human study . We performed a prospective matched case control study on women who presented to our city-based university hospital with miscarriage and control women attending our hospital for pregnancy related care whose pregnancy was viable . Relevant care providers in our hospital were briefed about the study and requested to contact the research team when they diagnosed a miscarriage at up to 22 weeks gestation so that the patient can be approached and consented for study enrolment . All participants provided their written consent . From 9 June 2009 to 16 March 2011 , women who presented acutely to our hospital and diagnosed as a miscarriage were approached . For the purpose of the study , miscarriage is defined as the presence of non-viable product of conception on ultrasound or physical confirmation of expelled products and a positive pregnancy test . In the event of early miscarriage , a positive urine pregnancy test and a history of expelled products of conception is also acceptable if the uterus is empty at presentation . Gestation should not be more than 22 weeks . Gestation is calculated from the reported first day of the last menstrual period and corrected by ultrasound assessment when deemed clinically appropriate to do so . We excluded women with ectopic pregnancy or whose pregnancy was of unknown location . For every case with miscarriage , we recruited three control women with viable pregnancies matched for maternal age ( within 3 years ) and gestational age ( within 3 weeks ) . The controls were recruited at the earliest opportunity after the index miscarriage case by a researcher ( MZS ) from amongst women attending for their pregnancy care at our hospital . Miscarriage cases and controls were derived from the same providers and hospital sources . All participants answered a short questionnaire about whether they had a clinical diagnosis of dengue , made during the current pregnancy or in their lifetime prior to the current pregnancy or a febrile illness , in the last 10 days or at any juncture in their current pregnancy . Venous blood ( 5 ml ) was collected from each participant and drawn into plain blood bottles . The blood samples were sent directly to the laboratory for immediate processing or kept in a refrigerator at 4°C prior to transfer if the laboratory was closed . The laboratory is based at our university with extensive experience in dengue work . Samples were discarded if after centrifugation , the supernatant had the appearance of lysed blood . The spun samples were aliquoted and then stored at −70°C . Sera were tested for dengue specific IgM , dengue NS1 antigen and dengue specific IgG . These tests cross react against all four dengue serotypes . Dengue specific IgM was tested for using an in-house IgM capture-ELISA ( enzyme linked immunosorbent assay ) test [26] . Samples were considered positive if the ratio of optical density of the positive to negative control was at least two . Panbio Dengue Early ELISA Catalogue No . E-DEN02P ( Inverness Medical Innovations Australia Pty Ltd , Queensland , Australia ) kits were used as a dengue NS1 antigen capture ELISA test . For dengue IgG detection , we used Panbio Dengue IgG Indirect ELISA catalogue No . E-DEN01G ( Inverness Medical Innovations Australia Pty Ltd , Queensland , Australia ) kits . The Panbio kits were utilised as per manufacturer's instructions . We define a recent dengue infection as the detection in sera of dengue specific IgM and/or NS1 antigen . The miscarriage cases had their chart reviewed up to their discharge from hospital follow up . All included cases must have a confirmed diagnosis of miscarriage at hospital discharge . Cases who did not attend any hospital follow up subsequent to their recruitment into the study or whose latest follow up data were still inconclusive for a diagnosis of miscarriage were contacted by telephone at least three months after their recruitment to confirm the diagnosis of miscarriage with a view to excluding those with a misdiagnosis . Similarly , controls that did not have confirmation of pregnancy viability beyond 22 weeks gestation from chart review because they transferred care elsewhere were contacted by telephone to confirm pregnancy viability beyond 22 weeks gestation . We had planned to exclude controls that could not be confirmed to have a viable pregnancy beyond 22 weeks as we could not exclude subsequent late miscarriages in them . Our study is designed to evaluate miscarriages up to 22 weeks gestation; it would be inappropriate to have as controls , women who subsequently had miscarriages . We excluded controls who had miscarried after recruitment as we could not exclude a new dengue infection around the time of their miscarriage as no dengue testing was done then . In a recent study on parturients performed at our hospital , the maternal dengue infection rate as defined by a positive dengue IgM test was 2·5% [16] . Since pregnancy per se has no effect on the acquisition of dengue infection , we expect our control population to have a 2·5% recent dengue infection rate and for the purpose of the sample size calculation we postulate that miscarriage cases will have a 10% recent dengue infection rate . Taking alpha of 0·05 , 80% power , 1 to 2 case to control ratio ( using PS sample size calculator ) [27] , 112 cases and 224 controls are required , . As we expect significant attrition in the number of controls due to care transfer to other institutions and hence their drop out from follow up , we increased our planned recruitment ratio to 1 case to 3 controls i . e . at least 112 miscarriage cases and 336 viable pregnant controls . Data was entered in to SPSS version 15 ( SPSS Inc . San Diego CA USA ) . Comparison ( between cases and controls ) of the means of continuous variables was by the Student t test , ordinal variables by the Mann Whitney U test and categorical variables by the Chi square test . Fisher exact test is used in place of the Chi Square test for categorical variables if 2 or more cells contain <5 subjects . Multivariable logistic regression analysis , incorporating in the model all characteristics with P<0·05 on bivariate analyses between cases and controls was performed to adjust for these differences in order to establish their independent association with miscarriage . All tests were 2-sided and P<0·05 was taken as a level of significance .
Figure 1 depicted the flow of the recruits within the study and their eventual destination . We recruited and drew blood from 116 cases with a diagnosis of miscarriage and 348 similar gestational aged controls whose pregnancies were viable at recruitment , totalling 464 women for the study cohort . Blood samples from seven controls were found to be lysed after processing and discarded , leaving 457 samples to be tested for dengue IgM , NS1 antigen and IgG . On follow-up , one case of miscarriage was found to be a misdiagnosis and that pregnancy resulted in a term livebirth . Six controls miscarried before 22 weeks gestation and another 39 controls could not be confirmed to have a viable pregnancy beyond 22 weeks gestation despite attempted contact by telephone . These 46 women were excluded from the final analysis . The characteristics of included cases and controls are shown in Table 1 . Prevalence of recent dengue are 5·3% and 1·7%; RR 3·1 ( 95% 1·0–10 ) P = 0·047 in cases versus controls . Cases with miscarriages on bivariate analyses were also more likely to be older , of higher gestational age at recruitment and parity and less likely to belong to our major ethnicities of Malay , Chinese or Indian but not significantly more likely to have been ill with a fever during their pregnancy nor more likely to have had distant exposure to dengue ( dengue IgG positive status ) . All the characteristics with P<0·05 on bivariate analysis were included in the model for multivariable logistic regression analysis . After adjustment , recent dengue infection remained an independent risk factor for miscarriage; adjusted odds ratio AOR 4·2 ( 95% Confidence Interval 1·2–14 ) P = 0·023 . As a post hoc analysis , if all participants with available dengue test results ( n = 457 ) were analysed , excluding only the seven with lysed samples , the result is not altered: recent dengue infection is still a significant independent risk factor for miscarriage ( AOR 3·8 95% CI 1·2–13 P = 0·026 ) . The 11 participants from both arms of the study group who had recent dengue infection were of similar age , gestational age , parity status , prior miscarriage status , ethnicity and personal awareness of dengue diagnosis in the past but as anticipated , more likely to report a recent febrile illness ( as dengue illness is typically febrile ) and to be dengue IgG positive ( as IgG conversion follows IgM response within a week or two in primary infections ) compared to the 400 without evidence of recent dengue – Table 2 . These findings support the perception that in our environment with dengue hyperendemicity , dengue is an equal opportunity infection amongst pregnant women . Four of the five controls with recent dengue infection reported a febrile illness during pregnancy compared to two such reports amongst the six miscarriage cases . All five controls with recent dengue infection and known outcome proceeded to livebirths at term . In the six miscarriage cases , there was one case of concurrent miscarriage and severe dengue illness . That case required intensive care therapy during her hospitalisation but her miscarriage just preceded the worst of the dengue illness . These findings are not helpful in differentiating whether dengue illness or vertical dengue infection contributed more to the abortion process .
The literature on dengue and miscarriage or spontaneous abortion is sparse . We performed a PubMed ( http://www . ncbi . nlm . nih . gov/sites/entrez ) search applying terms dengue and miscarriage or dengue and abortion without limitations on October 1 , 2011 and retrieved only 11 reports . Of these 11 reports , only four publications involved the study of miscarriages in association with dengue , presenting anecdotal data on only five cases of miscarriage during dengue illness [13] , [14] , [18] , [19] . A recent report on women in refugee camps at the Thai-Burmese border investigating antenatal febrile illness has found a dengue infection rate of 9 . 5% . One woman ( of 20; 5% ) who had dengue associated fever during pregnancy subsequently miscarried [28] . Recent dengue infection was found in 11/411 ( 2·6% ) of our study participants , a very similar rate to a recent report from our hospital of 2·5% ( 63/2531 ) dengue IgM rate in unselected parturients at time of their delivery [16]; ( Chi Square test , P = 0·82 ) . This shows that as a whole , the participants of our current study closely reflect unselected parturients at our hospital with regard to the risk of recent dengue infection and supports the assertion that the selection of our study group is unbiased . The similar dengue IgG positive and reported recent febrile illness rates amongst cases and controls in our current study further bolster the above assertion . Our dengue IgG positive rate of 213/411 ( 52% ) indicating prior dengue exposure in participants whose mean age was 30 years old is similar to the 63% dengue IgG positive rate from a cross sectional community-based prevalence study on subjects aged 21 to 40 years [29] who were derived from the same geographical catchment area as our participants . This similarity lends support to our study group as a whole being a representative sample of the host population . It is noteworthy that 6/11 ( 54·5% ) of the women with recent dengue in our sample reported a febrile illness in the course of the pregnancy leading up to their recruitment at a mean gestation of only10·8 weeks whereas in an earlier study at our hospital of 63 dengue IgM positive parturients ( delivered at a mean gestation of 39·4 week ) , only 7/63 ( 11·1% ) reported a febrile illness over the entire course of pregnancy [16]; ( Chi Square test P<0·001 ) . Dengue is reported to be asymptomatic or minimally symptomatic in 87% of infections [9] , an illness rate similar to that reported by the parturients but far lower than in our current study group . Mild exposures to hyperthermia or fever during the preimplantation period and more severe exposures during embryonic and fetal development often result in prenatal death and abortion [30] . The possible interpretation is that dengue infection in very early pregnancy may give rise to a more symptomatic ( or severe ) presentation . This more severe effect may contribute to its role in miscarriage whereas dengue infection late in pregnancy is far less likely to be severe and thus did not adversely affect on delivery outcome [16] . However , with only 11 cases of recent dengue found in this study , further corroboration of this hypothesis is required . Although dengue illness can cause fatigue at two months [31] and other persistent symptoms at two years [32] beyond the acute phase , all five cases of recent dengue infection in our control group resulted in term livebirths despite the fact that four of these five had reported a febrile illness during early pregnancy . The interpretation might be that dengue infection very early on during pregnancy may have a severe impact sufficient to contribute to early miscarriage but does not have a prolonged adverse effect deeper into pregnancy . There are limitations in our study design . As dengue IgM may persist for up to six months [1] after infection though rarely , our methodology was not capable of identifying only those dengue infections that were within pregnancy – some those identified with recent dengue infection might have been infected prior to pregnancy . Specific IgM might not be detectable in a small proportion of secondary infections [1] , [25] and given the dengue IgG detection rate of just over 50% in our participants , probably half of the recent infection we detected were secondary infections . However , these limitations apply to both cases and controls , so should not affect the assessment of relative risk and if anything , would be biased against the finding of a relationship between recent dengue and miscarriage . Our IgM capture ELISA assay for dengue cross reacts with IgM against other flaviviruses notably Japanese encephalitis and Yellow fever viruses but IgM capture ELISA for dengue has demonstrated only a low cross reactivity with Japanese Encephalitis virus [33] . Both yellow fever and viral encephalitis were very rare in Malaysia with a reported rate in 2010 of 0 per 100000 and 0·2 per 100000 population respectively compared to dengue illness rate of 148·7 per 100000 population [34] . With only 11 recent dengue infections identified from a sample of 411 ( 2·6% ) , the recent dengue infection rate in our study is somewhat lower than that assumed in our sample size calculation of 2·5% recent dengue infection rate in controls and an assumed 10% in miscarriage cases . As a consequence , although analysis shows a significant association between dengue infection and miscarriage at the 5% level of significance , the relatively small number of infections means that the 95% confidence interval is wide . In summary , in the context of our setting with dengue hyperendemic , 5·2% of the women with miscarriages displayed evidence of recent dengue infection compared to 1·7% in controls with viable pregnancies ( AOR 4·2 95% CI 1·2–14: P = 0·023 ) , a statistically significant and clinically important finding . This interaction between dengue infection in early pregnancy and miscarriage is a highly relevant public health issue due to high number of dengue infections worldwide annually and the typically higher fertility rates in the dengue endemic regions of the world . There is an implication also for travellers from dengue free regions in the early stages of their pregnancies who are journeying to dengue endemic areas . Further study to replicate our data and finding is urgently needed .
|
Dengue is the most prevalent mosquito-borne infection with two billion of the world's population at risk and 100 million infections every year . Dengue is increasingly important due to expansion in the vector's range , increased population density in endemic areas from urbanisation , social and environment change . Miscarriage and stillbirth is associated with dengue when the illness is severe . Dengue can also be transmitted directly from the ill mother through the placenta to the fetus in later pregnancy with variable effect to the fetus . However , dengue infection is asymptomatic to mild only in almost 90% of cases and up to 20% of pregnancies miscarry . Little is known if dengue infection in early pregnancy particularly when it is asymptomatic or mild has an effect on miscarriage . Our study explored the relationship between dengue and miscarriage by looking at recent infection rates amongst women who had miscarried and those whose pregnancies were healthy in an area were dengue is common . Our study finds a positive association between recent dengue infection and miscarriage . This finding may be important in explaining some of the miscarriages in areas where dengue is common . It is also relevant to newly pregnant women from non-dengue travelling to dengue endemic areas .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine"
] |
2012
|
Dengue Infection and Miscarriage: A Prospective Case Control Study
|
The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues , virtually at every level of biological organization . The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data . These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach . In cancer research , this strategy has been particularly successful . It has contributed to the identification of novel biomarkers , to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology . However , so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue . Since these interactions represent an essential part of the biology of both diseased and healthy tissues , it is of paramount importance that this challenge is addressed . Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue . The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells . Moreover , by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis , we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival . Ultimately , this study represents a generalizable approach to the challenge of deciphering cell communication networks in a wide spectrum of biological systems .
Prostate Cancer is the most common cancer in males . It is characterized by a considerable molecular and phenotypic heterogeneity that results in radically different clinical outcomes [1] . The role of tumour microenvironment in the development of cancer is crucial . More specifically , the expression of growth and motility factors , extracellular matrix components produced by stromal cells , is linked to the pathophysiology of the tumour and it often predictive of clinical outcome . Stromal cells , such as fibroblasts and endothelial cells secrete many factors that influence the expansion of the tumour . For example , they secrete most of the enzymes involved in extracellular matrix breakdown and produce growth factors that control tumour cell proliferation , apoptosis , and migration [2] . They also secrete pro-inflammatory cytokines , which play a major role in a wide spectrum of pathophysiology mechanisms ( e . g . chemo attraction , neoplastic transformation , angiogenesis , tumour clonal expansion and growth , passage through the ECM , intravasation into blood or lymphatic vessels and the non-random homing of tumour metastasis to specific sites ) [3] . In addition to tumour promoting factors , they also secrete tumour suppressor factors that can potentially have an anti-tumour effect on adjacent tumour cells [4] . Current research on the role of stroma is principally focused on immune cells fibroblasts and cells of the vasculature such as endothelial cells . However , since other cell types , such as normal epithelial cells , also produce a number of these factors , such as IL-6 [5] , TNFα [6] [7] and TGFβ1 [7] it is reasonable to hypothesize that they may also play an important role in influencing the molecular and physiological state of tumour cells . The intricacy in the biology of cell-to-cell communication and the relatively small amount of available knowledge makes understanding the biological networks underlying the development of tumour microenvironment a suitable challenge for a systems-level approach . The powerful combination of functional genomics and computational biology have contributed to the discovery of novel signaling networks in the biology of cancer [8] [9] , including cell communication networks [10] . However , so far there has been no attempt to develop a completely data-driven systems biology approach to discover novel cell-communication networks . Here we describe a data-driven strategy we developed to address this challenge . Our approach is designed to “learn” the underlying structure of cell-to-cell communication networks from functional genomics datasets , representing the transcriptional state of normal and adjacent tumour cells . The application of this novel analysis strategy to prostate cancer revealed genes whose expression is associated to directional signals linking normal and tumour epithelial cells . Remarkably , experimental validation of our predictions using an in vitro co-culture system recapitulated the predicted transcriptional response and revealed that normal epithelial cells have the potential to revert some of the phenotypic traits of tumour cells . Moreover , by integrating genetics , gene expression and tumour features in a single conceptual model , we were able to show that putative cell communication networks , involved in focal adhesion and protein secretion are perturbed by genetic mutations and that are linked to survival . Ultimately , the experimental validation of the hypothesis generated from the model support the approach we have developed , which explicitly search for candidate directional signals between different cell types . Its application to a wider range of biological systems is likely to have a profound impact in the field of functional genomics .
Our study is based on a data analysis workflow which includes reverse engineering techniques to identify gene expression signatures that may be involved in cell to cell communications . The strategy we followed , which is summarized in Fig 1 , is based on several cycles of computational analysis , hypothesis generation and experimental validation . The workflow consisted of five distinct but interconnected steps . The overarching goal of this project was to develop a data driven strategy to identify molecular pathways involved in cell-to-cell crosstalk . We first set to test whether gene expression profiles across normal samples may correlate with the gene expression profiles from the matching tumour samples . We reasoned that if such correlated profiles exist they might be a manifestation of the signaling events between normal and tumour epithelial cells and may shed new light on the role of normal epithelia in prostate cancer . With this in mind , we first applied relevance networks [11] , a relatively simple network inference procedure , to link genes differentially expressed in normal and in tumour epithelia . We used a dataset developed by Singh et al . [12] , representing the transcriptional state of 47-paired prostate tumour and adjacent normal cells samples . The resulting network ( NT network ) is composed of 2581 positively and negatively correlated genes ( Fig 2 ) . These were subdivided in 1600 gene expression profiles in normal epithelia ( referred from now on as ‘normal-expressed’ genes ) and 981 gene expression profiles in tumour epithelia ( referred from now on as ‘tumour-expressed genes’ . The NT network was grouped into 68 modules by using GLay [13] , a community detection method that maximizes inter-module connectivity . Only three modules contained more than twenty nodes and thus were selected for further investigation ( Fig 2 ) . This arbitrary threshold was used to make sure that a sufficiently large number of genes was present in each module for subsequent functional analysis . The NT network and its modules fitted a power law node connectivity distribution ( p<10−2 ) , consistent with the existence of a relatively small number of genes with a very large number of connections . Module 1 displayed a marked enrichment in normal-expressed genes ( Fig 2B , p<10−4 ) and module 2 showed enrichment in tumour-expressed genes ( Fig 2C , p<10−4 ) . In module 3 , the frequency of normal- and tumour- expressed genes was as expected by random chance ( Fig 2D , p = 0 . 41 ) . Interestingly , the most connected genes in module 1 and 2 represented profiles from the tissue that was less represented ( p<10−4 ) . The most extreme case was module 1 where 19 of the 20 most connected genes were tumour-expressed genes ( expected frequency was 1 ) . Although module 3 showed no preferential tissue distribution , it still showed a higher than expected frequency of tumour-expressed genes among the 20 most connected genes ( p<10−2 ) . Functional analysis of the genes represented in each module showed that these were enriched in a wide spectrum of biological functions ( Fig 2A and S1 Table ) . The results described above ( Fig 2 ) are consistent with the notion that a relatively small number of genes expressed in either normal or tumour epithelial cells may control communication signals that can either modify or respond to the molecular state of the adjacent tissue . In order to mine the NT network for such signals we developed the polarization index ( pol ) , a novel gene connectivity metric . We design this index to represent genes that may exert an effect on the adjacent cell type only when expressed in one specific tissue . This scenario implies a directional signal , which is for example typical of soluble factors encoded by tumour suppressor genes or oncogenes . In the case of tumour suppressor genes , these may have lost the ability to control tumour cell proliferation via autocrine signaling but they may retain that function when expressed in adjacent stromal cells by a paracrine signal . We formalized this scenario as follows: Considering that a given gene gi can be expressed in both normal and tumour tissue , we define fi as the number of tumour-expressed genes that correlate with the normal-expressed gi . Similarly , we define bi as the number of normal-expressed genes that correlate with the tumour-expressed gi . We define the polarization coefficient for gene gi as: poli=fi−bifi+bi+ε ( 1 ) ε is a small positive constant designed to stabilize the ratio when fi and bi are small . Poli has a number of desirable properties: its value is proportional to the asymmetry in the number of correlated genes with gene i in the two tissues while its sign gives the direction of the effect . This metric tend to 1 or -1 for fi >>bi or fi << bi , respectively . We computed this index for all genes represented in the NT network ( Fig 2 ) and discovered that , independently of the threshold used , it is distributed accordingly to a multimodal distribution with three peaks ( Fig 3A ) . The highest frequency of the distribution is centered on zero whereas a smaller number of genes show polarization coefficients close to +1 and -1 . We focused subsequent analysis on genes with pol>|0 . 75| , a very stringent threshold that we found to have less than 1 in 8000 false positives ( Fig 3B and S2 Fig ) . This very stringent threshold identified 146 and 244 positively and negatively polarized genes , respectively ( Fig 3C and S2 Table ) . Functional analysis of the polarized genes using Gene Ontology and the Ingenuity database shows a statistically significant enrichment in functions key to cancer biology ( Fig 3D and 3E ) . The main functions significantly enriched in the negatively polarized genes are cell death of tumour cell lines , migration of tumour cell lines , necrosis and proliferation of PC cell lines ( Fig 3D ) . The main functions enriched in the positively polarized genes are proliferation of cells , migration of cells , invasion of cells and apoptosis of tumour cell lines ( Fig 3E ) . Moreover , 107 positively polarized genes ( 53% of the 204 genes that had functional annotation ) are linked to the Gene Ontology term cell communication and therefore represent a class of proteins potentially mechanistically involved with cell crosstalk ( S3 Table ) . Interestingly , only positively polarized genes are significantly enriched in this functional term ( FDR<10−2 ) . Manual curation into the role of the positive and negatively polarized genes using available literature and online databases was consistent with the computational analysis . In Table 1 we report the positively and negatively polarized genes that are either secreted factors ( potential paracrine signals ) or factors partitioned at the cell surface ( potentially involved in cell-cell communication via direct contact ) or transcription factors that may regulate the expression of cell communication genes . Additionally , almost all the network hubs described in Fig 2 are characterized by a high polarization coefficient ( either positive or negative ) . In order to investigate the potential role of polarised genes in cell-to-cell communication we first identified their first neighbours in the NT network and then we tested the resulting gene lists for functional enrichment . We could identify 1223 normal-expressed genes as targets of tumour-expressed negatively polarised genes and 794 tumour-expressed genes as targets of normal-expressed positively polarised genes ( S4 Table ) . We discovered that there was a significant overlap between them ( 520 genes , p<10−3 ) ( S3 Fig ) suggesting that although positively and negatively polarised genes are by definition different , they may ultimately target the same biological processes , in tumour and normal cells respectively . This hypothesis was supported by the functional analysis , which identified a set of terms enriched in the overlapping set of gene targets . Among these there were regulation of cell death , response to growth factor , cell adhesion and extracellular region part ( S3 Fig and S5 Table ) . We reasoned that if the cell-to-cell communication model we developed around the gene polarization index is correct , we should be able to modulate the putative targets of polarized genes by reconstructing an in vitro system where normal and tumour prostate cells share the same micro-environment . We performed such experiment by using a trans-well co-culture system where normal ( RWPE1 ) and tumour ( DU-145 ) epithelial cell lines are separated by a semipermeable membrane . In these experiments either tumour or normal cells were inserted into dishes already containing tumour cells . This experimental set up represents the aspect of the prostate tissue in which cancer epithelial cells sits in proximity but not necessarily are in direct contact ( paracrine signals ) . Four sets of samples were processed for expression profiling 24 hours after the start of the experiment . These were: 1 ) RWPE1 cultured with RWPE1 , 2 ) DU-145 cultured with DU-145 , 3 ) RWPE1 cultured in the presence of DU-145 and 4 ) DU145 cultured in the presence of RWPE1 . Genes whose expression in tumour cells is influenced by the presence of normal cells were identified by direct comparison between gene expression in DU-145 cultured on their own and gene expression in DU-145 cultured in the trans-well system in the presence of RWPE1 . Similarly , we identified genes whose expression in normal cells depended on the presence of tumour cells by direct comparison between gene expression in RWPE1 cultured on their own and RWPE1 grown in the trans-well system in the presence of DU145 . We considered the two sets of genes identified by this simple differential expression analysis as the experimental equivalents of the predicted targets of positively and negatively polarized genes , respectively . Consistent with the analysis of the targets of polarized genes ( S3 Fig ) we found a significant overlap between genes differentially expressed in normal and tumour cells as a result of co-culture ( Fig 4A , p<0 . 01 ) . We also discovered that a significant percentage of genes up regulated in tumour cells were down regulated in normal cells and vice versa ( Fig 4A ) . This is consistent with the results of a principal component analysis of these data showing that the variation between normal and tumour cells following co-culture followed anti-parallel trajectories ( Fig 4B ) . Next , we compared the predicted targets of polarized genes and the experimentally determined transcriptional signatures . The overlap between the differentially expressed genes in the co-culture system and the predicted targets of polarized genes was significant both at gene ( S4 Fig ) and at functional level ( Fig 4C and 4D ) . We concluded that remarkably , the in vitro system was able to recapitulate a significant component of the transcriptional network inferred from the clinical study . The functional analysis of these gene signatures revealed enrichment in several important cellular functions that are very relevant in cancer ( e . g . regulation of growth , apoptosis and cell adhesion ) . Since we could not identify a specific direction in differential gene expression we set to determine whether change in the transcriptional state of co-cultured cells impact a relevant cancer phenotype . We therefore performed a battery of in vitro tests on tumour cells , using the same trans-well co-culture system described above . Here we assessed whether the transcriptional signatures defined by our computational analysis and validated by the in vitro co-culture system may truly reflect a cancer relevant phenotype . We found that the presence of normal epithelial cells induced several phenotypic changes in tumour cells . More specifically , population doubling time ( PDT ) in tumour cells cultured in the presence of normal cells was considerably longer than in tumour cells cultured on their own ( 30 hours against 18 hours , Fig 5A ) . Cell numbers at the end of the experiment were consistent with this finding and also revealed that additional tumour cells in the trans-well promoted survival ( Fig 5B ) . The apoptosis test revealed that normal cells did not have any effect but tumour cells surprisingly increased the number of tumour apoptotic cells ( Fig 5C ) . We then tested the formation of cell clusters and recorded the number of cell clusters ( Fig 5D ) , the size of clusters ( Fig 5E ) and the area of the dish occupied by single cells ( Fig 5F ) . Normal cells reduced the number and size of clusters and increased the area occupied by single cells whereas tumour cells had the opposite effect ( Fig 5D–5F ) . Consistent with these findings , conditioned media from COS cells overexpressing the tumour suppressor gene SLIT2 , one of the most positively polarized genes ( pol = 0 . 99 ) which is expressed at higher levels in normal prostate tissue compared to tumour ( S5A Fig ) , was able to dramatically reduce tumour cell clone formation in a Matrigel in vitro Clonogenic assay ( Fig 5G ) . All of this data is consistent with the normal cells effectively 'normalising' the phenotypic characteristics of the tumour cells . Having inferred and experimentally validated a transcriptional network representing the interaction between normal and tumour prostate epithelial cells we then hypothesised that expression of genes within the network may be influenced by genetic/epigenetic modifications and/or correlate to tumour features and clinical outcome . We first checked whether the expression of polarised genes might be influenced by DNA methylation , a common mechanism for transcriptional silencing in cancer . By mapping genes known to be re-expressed in prostate cancer cell lines , following exposure with DNA hypomethylating agents [14][15][16] , we could show that methylation significantly affect the expression of 30 of the 245 positively polarized genes and 12 of the 146 negatively polarised genes in tumour cells ( S6 Fig and Fig 6 and S6 Table ) . Although the percentage of genes affected by methylation is relatively small , the number of positively polarised genes whose expression is affected by methylation was significantly higher than expected by random chance ( S6 Fig ) . Next we assessed the role of copy number variation ( CNV ) . We selected an independent dataset [17] , which included genetics ( CGH ) , gene expression and clinically relevant variables ( S7 Table ) . First we tested whether the expression of polarised genes was directly affected by CNV . We could only identify 9 polarised genes with significant correlation ( p<0 . 01 ) between their CNV and expression ( S8 Table ) . Next we developed a hierarchical Bayesian model to identify whether epistatic CNV could explain the expression of polarized genes in tumour cells . We were able to show that the expression of 70 polarised genes could be explained by CNV in seven genomic regions ( S9 Table and Fig 6 ) . Three of these included genes with known function ( ATAD1 , GRHL2 and KCNB2 ) ( Fig 6 and S10 Table ) . Interestingly , the large majority of polarized genes whose expression was linked to CNV were mainly positively polarised ( 59 out of 70 ) . Finally , we tested whether the expression of polarised genes was related to tumour features and clinical outcome . Indeed we found that the expression of a large number of polarised genes ( 130 ) was linked to Gleason score . A smaller number of genes ( 18 and 1 ) were linked to PSA antigen and T stage , respectively ( Fig 6 and S11 Table ) . The integration of these associations using a network representation revealed 173 polarised genes linked either to regions affected by CNV ( 89 genes ) and/or to tumour features ( 84 genes ) ( Fig 6 ) . Remarkably , while the expression of none of the polarised genes could be linked to survival , 132 of them were linked to time free of recurrence ( FDR<5% , S7A Fig and S12 Table ) . Interestingly we could also show that polarised genes linked to CNV did show significantly lower p-values than polarised genes only linked to Gleason score ( S7B Fig ) supporting the clinical relevance of the epistatic effects identified by the computational model . A group of 58 positively polarised genes and 6 negatively polarised genes ( Fig 6 and S7B Fig and Table 2 ) were linked to both CNV and Gleason score . We found that the large majority of genes in this group ( 57/58 ) were negatively associated to Gleason score and positively correlated to time free of recurrence ( S7B Fig and S12 Table ) . Intriguingly , these were highly enriched in Cytoskeleton proteins ( 24 out of 51 , over-represented in the GO term Cytoskeleton at FDR<10−8 ) ( Table 2 ) . We then tested the expression of 36 out of the 58 genes that were profiled in a dataset representing normal and tumour cells which were laser micro-dissected from prostate cancer specimens [18] ( Fig 7 ) . This analysis showed that 11 out of 36 are differentially regulated and that all except 1 were down regulated in the tumour tissue ( Fig 7 ) , an observation that is consistent with the direction of correlation with the survival free of metastases . Among these 58 genes , 8 represented genes involved in formation of cell projections ( ACTN1 , CALD1 , CLIC4 , DPYSL3 , DBN1 , ILK , PAFAH1B1 and RTN4 ) and six ( ACTN1 , CCND2 , FLNA , FLNC , ILK and MYL9 ) mapped on the KEGG pathway focal adhesion ( FDR<1% ) . Also , five were proteins known to be associated to the Golgi apparatus and involved in protein secretion ( SEC23A , CRYAB , FLNA , NUCB1 and PRNP ) . Among these were several genes with known tumour suppressor activity ( e . g . FLNA [19] , FBLN1 [20] , MYL9 [21] , CLIC4 [22] and SEC23A[23] ) .
Since the large majority of efforts have focused on understanding the role of fibroblast and endothelial cells in cancer , the interface between normal and transformed epithelial cells is still not clearly understood . Our analysis suggests that normal epithelial cells exert a “normalizing” effect on tumour cells , up to an advanced stage of tumour progression . A number of recent studies have suggested that at the initial phase of tumour expansion , normal epithelia could provide a tumour suppressive environment that cancer cells need to overcome to develop a tumour . So far , tumour suppressor activity of normal epithelial cells has been studied in cell culture systems replicating early transformation events in epithelia [24] . These models include kidney and mammary epithelial cells in culture where only a few cells are selectively transformed by oncogenic transformation or inhibition of tumour suppressor genes [24] . In these conditions , transformed cells are excluded from the epithelia and out grown by normal epithelial cells . It has been suggested that additional mutations and/or alterations in the adhesion properties of tumour cells may be needed to overcome the tumour suppressive effects and allow for clonal expansion [24] . However , the precise molecular events underlying this process are still unknown . Our work therefore provides further evidence of the tumour suppressor effects of normal epithelial cells and supports the concept that although tumour cells obviously eventually overcome these normalizing signals , the effect of normal epithelia may be relevant for the entire clinical history of prostate cancer . The models we have developed provide a link between genetic mutations and the expression of polarized genes in tumour cells . Remarkably , the functional profile of mutated genes is consistent with a pivotal anti-tumour role of the apical junctional complex and the protein secretion machinery . Among the three genes we have identified as potential epistatic regulators , GRHL2 is known to be a transcription factor known to play a pivotal role in cancer progression [25][26][27] . GRHL2 regulates epithelial cell differentiation by effectively regulating the expression of genes of the epithelial apical junctional complex [28] . It controls the expression of the adherents junction gene E-cadherin and the tight junction gene claudin 4 ( Cldn4 ) and has been linked to both pro and anti-tumour activity [25] . Moreover , GRHL2 up regulates the human telomerase reverse transcriptase ( hTERT ) gene during cellular immortalization of oral squamous cell carcinoma cells [29]; it is a proto-oncogene in breast cancer cells [25]; it regulates proliferation of hepatocellular carcinoma cells [30] and is a suppressor of epithelial-to-mesenchymal transition in breast cancer [31] . Our model predicts that increase expression of GRHL2 due to CNV down regulates the expression of a set of polarized genes that precisely encode for components of the cytoskeleton and are involved in focal adhesion and cell migration . Several of these genes are extracellular factors and one of them ( SEC23A ) has been found to control secretion of anti-tumour factors in breast cancer [23] . These observations lead to the hypothesis that increased expression of GRHL2 in tumour cells may result in the deregulation of at least two different types of tumour suppressor signals , one dependent on the establishment of focal adhesion junctions and the other directly affecting secretion of anti-tumour factors . This chain of events may contribute to tumour transformation and metastases formation and at the same time could make tumour cells sensitive to the same tumour suppressor signals that continue to be produced by adjacent normal epithelial cells . The in vitro system we have used to validate our model shows that normal epithelial cells are able to exert anti-tumour effects even if normal and tumour epithelial cells were separated by a semi-permeable membrane , suggesting that soluble factors may be playing a major role in tumour suppression . Secretion of the highly positively polarized gene SLIT2 from normal epithelial cells has the potential of exerting a tumour suppressor activity as shown by our clonogenic assay on tumour cells exposed to diluted conditioned media . More broadly , there is strong support in the literature linking several of the positively polarized genes to tumour suppression . More precisely , FLNA[19] FBLN1[20] , MYL9 [21] , CLIC4 [22] all have demonstrated tumour suppressor activity . It has been shown that Filamin A ( FLNA ) exerts anti-tumour activity via at least three different mechanisms . It represses MMP-9 expression reducing cell migration in prostate cancer . It controls focal adhesion and androgen-related cell migration in human fibrosarcoma [19] and Cyclin D1/cyclin-dependent kinase 4 mediated cell migration in breast cancer [32] . The myosin light chain ( MYL9 ) in stroma has been shown to predict malignant progression and recurrence-free survival in prostate cancer [21] . Fibulin 1 ( FBLN1 ) is down regulated in a number of tumours , including prostate [33] . CLIC4 was first characterized as intracellular chloride channel , later shown to be involved in signaling , cytoskeleton integrity and differentiation [34] and is a tumour suppressor gene in cutaneous squamous cell cancer [22] . The reverse engineering approach we have adopted is based on the assumption that gene co-expression is either directly or indirectly a reflection of important underlying mechanisms of gene regulation and as such it can reveal novel biological networks . While this concept is well accepted in the scientific community , it remains true that correlation does not necessarily imply causation , hence the importance of experimental validation . However , for a number of candidates , it is possible to hypothesize a mechanism whereby highly polarized genes may directly affect adjacent cells . For example , a number of them are secreted factors that can work as paracrine signals or membrane proteins known to be involved in cell communication ( Table 1 ) . This is the case for Slit-2 that we have experimentally verified by treating prostate cancer cells with conditioned media derived from cells over-expressing the recombinant protein . Others may indirectly control cell communication . This is for example the case with transcription factors ( e . g . GATA2 control of IGF1 signalling [35] ) , proteins controlling secretion ( e . g . LTBP1 control of TGFB1 secretion [36] ) or proteins involved in cell migration . Interestingly , the gene expression profiling analysis we have performed to validate our predictions , suggest that the polarization coefficient may have the ability to capture directional signals that are triggered by normal and tumour cells . However , the experimental system we have used is based on a trans-well system , which only validate paracrine signals . We believe our approach could have a broad impact . Although , at present there are not many suitable datasets containing both disease and adjacent normal tissue , we have verified that the distribution of polarization coefficient in two additional , datasets representing kidney and liver adjacent normal and tumour tissues are similar to the one observed in prostate cancer ( S9 Fig ) . In the future we envisage that tissue laser micro dissection and mRNA sequencing technologies may provide a very powerful combination for the identification of genome wide cell communication networks . The approach we have developed has the advantage to reverse engineer cell communication networks in the absence of any prior information . In this respect , the method is different from the recently developed computational method developed by Choi et al [10] . The latter has been successfully applied to understanding the relationship between stroma and cancer cells in a model of lung tumour metastases and is based on comprehensive ligand-receptor network information , which can be extracted from several knowledge databases . We envisage that the integration of these knowledge driven approach within the framework of statistical learning will allow the development of a more powerful set of methodologies . The study we have performed relies on cross-sectional data and therefore the correlations we estimate do not take into consideration the hierarchical sequence of events that characterize cell communication dynamically . However , such dynamics can be captured using in vivo models of tumor expansion [37] . In such scenarios , different computational methodologies may be used to reverse engineer underlying gene regulatory networks [38] . For example , suitable approaches may include ordinary differential equation ( ODE ) or state space models [39] . In conclusion , the approach we have pioneered is likely to provide a general strategy to ‘learn’ the structure of cell-to-cell communication networks in diseased and physiologically normal tissues . We anticipate that the availability of a viable strategy to infer cell communication networks will stimulate the development of experimental studies representing the molecular state of adjacent tissues and their functional interactions in physiology and disease .
This analysis initially focus on the dataset developed by Singh et al . [12] representing the transcriptional state of 47 paired prostate tumour and adjacent normal cells samples . Raw Affymetrix microarray data were normalized and processed before analysis to remove low variant and low expressed genes . Further details of the procedures can be found in S1 File . The analysis linking copy number variation ( CNV ) , gene expression , tumour features and clinical outcome was performed on the dataset developed by Taylor et al . [17] , which consist of 231 tumour samples . Raw comparative genomic hybridization Agilent data was processed as detailed in S1 File . The dataset developed by Tomlins et al [18] was used to test the expression of polarized genes in laser capture micro-dissected low and high-grade tumour and normal prostate tissue . In the Tomlins et al study , tumour grading was determined by Gleason score . A scores of 3 determined a low-grade tumour , a score of 4 or greater determined a high-grade tumour . Raw data was downloaded and normalized using the “marray” BioConductor package in R [40] . All data processing was performed in the statistical environment R . Network inference was performed using a relevance network approach [11] . Non-linear Spearman ranking correlation ( rs ) was used to infer gene-to-gene correlations . In order to estimate the number of significant correlations , 100 bootstrap versions of the original dataset were used for each dataset to draw the null distribution of rs expected by chance . The bootstrap distribution was used to estimate a p-value , which was subsequently corrected for multiple-test using an FDR correction procedure [41] ( S1 Fig ) . The use of the relevance networks based on the Spearman correlation coefficient has advantages respect to more complex reverse engineering methods such as the mutual information based ARACNE [42] algorithm . Spearman correlation measure both positive and negative correlations and is better suited for datasets with a smaller number of samples . We used a threshold of rs >|0 . 75| ( FDR<10−2 ) to select significant connections ( NT network ) . The NT network , representing statistically significant correlations between genes expressed in normal and tumour tissues , was modularized using the community finding algorithm GLay [13] , as implemented in the network analysis tool Cytoscape [43] . The algorithm begins by setting each node into a separate community and progressively merges those with the maximum increase to the modularity score . The hierarchical merging tree is cut at the point where maximum modularity is achieved . Connectivity analysis of the whole network and of the three largest modules ( defined as larger than 20 nodes ) was performed using the network analysis tool NetworkAnalizer [44] , also implemented as a Cytoscape plug-in . The general definition of the polarization index for a given gene i , have been given in the result section ( Eq 1 ) . The analysis described in this paper has been performed with the parameter ε set to 1 . Additionally , pol was set to 0 if the absolute difference between f and b was lower than 20 to avoid high pol values for low number of connections . In order to acquire confidence in the biological relevance of the polarization index we derived a null hypothesis distributions for estimating the likelihood that a given polarization value derives by random chance . This represented a scenario where the overall properties of the data are conserved in the absence of any interaction between normal and tumour samples . Random data sampled from the Singh et al . dataset were used to compute normal and tumour correlation matrices . Each matrix was fitted by a multivariate Gaussian model to generate a synthetic dataset . Synthetic datasets were then used to compute the correlation matrix whose distribution predictively resembles that of the original dataset . Subsequently , the polarization index was estimated from this correlation matrix . The multivariate fitting and subsequent random dataset generation was performed using the function rmvnorm within mvtnorm packages [45] in the R statistical software environment ( S2 Fig ) . Significantly polarized genes have been defined as poli > |0 . 75| . At this threshold we did not observed any false positives in the 8000 random simulations performed . Although the expected level of contamination of tumour tissue with normal cells is expected to be very low , we devised a computational strategy to ask whether the polarization index could arise as a result of contamination of tumour samples with normal cells . We computed the polarization index between two simulated datasets that reproduce a situation where both tumour and normal samples are derived from normal tissues with added noise , thereby simulating variation that is consistent with a true microarray experiment ( S8A Fig ) . Firstly , an adapted model of the type derived by Jain et al [46] was used to estimate the experimental noise across replicates ( S8B Fig ) . Random Gaussian noise [47] derived from this noise model was then added to the normal tissue dataset to create a synthetic normal and synthetic contaminated tumour dataset . The intensity of the added noise was controlled by adding a scaling factor γ , which was chosen to match the distribution of correlations between genes in the synthetic datasets with the distribution observed in the real data ( S8C Fig ) . The distribution of the polarization coefficient is consistent with the notion that even high levels of contamination cannot explain the observed distribution of polarization coefficient ( S8D Fig ) . In order to test whether the trimodal distribution of the polarization coefficient could be observed in other cancer types in addition to prostate cancer , we analyzed two additional public domain datasets representing kidney [48] and liver [49] , respectively . Only paired data corresponding to tumour and normal from the same tissue were used . Only one pair of samples per individual was used . In general , normal tissue was adjacent to the tumour . Datasets were normalized and processed before analysis as for the main prostate cancer dataset . Results are shown in S9 Fig . Lists of polarized genes or their correlated genes were analyzed for enrichment of curated functional categories using the QIAGEN Ingenuity Pathway Analysis tool ( IPA , www . qiagen . com/ingenuity ) . Enrichment of Gene Ontology ( GO ) terms and KEGG pathways was determined using the web-based tool gprofiler [50] . In order to reduce redundancy in the functional terms we used REVIGO and selected the functional terms with dispensability index equal to zero . Unless stated otherwise gProfiler functional clusters were considered for further investigation if they had a FDR<1% . Normal ( RWPE1 ) and tumour ( DU145 ) prostate cell lines were co-cultured in a transwell system ( transwell I used was from Nunc , Loughborough , UK , Cat . 12-565-286; Pore size , 0 . 2 μm . ) for 24 hours in the presence of DMEM containing 10% fetal calf serum . The experiment was performed in triplicate with DU145 alone or DU145 co-cultured with either RWPE1 or DU145 in the insert . Cells from all compartments were harvested and RNA extracted using a Qiagen RNeasy kit according to the manufacturer's instructions ( Qiagen , USA ) . Custom-made oligonucleotide arrays were manufactured using the Operon Human Oligo set , version 3 . 0 [51] and then hybridized with Cy3 labeled probe , as described in Sarti et al . [52] Phenotypic cell analysis was carried out in Becton Dickinson TC treated 96-well plates . 2 . 5 x 103 cells were seeded per well in DMEM containing 10% fetal calf serum . 24 hours later , some wells were fitted with inserts also seeded with 2 . 5 x 103 cells per insert . Two days later inserts were removed , media was aspirated from the wells and cells were fixed with 85% ice-cold ethanol for at least two hours . After fixation cells were stained with propidium iodide ( 10 μg per ml propidium iodide , 100 μg per ml RNase A , 0 . 1% Triton X-100 in PBS , 100 μl per well ) . Plates were incubated at 37°C for 20 min in the dark and then analysed by laser scanning cytometry ( Acumen Explorer , TTP Labtech . ) . The intensity of the propidium iodide fluorescence was proportional to the DNA content of the cells and was measured on a linear scale . Single healthy and apoptotic cells were identified based on nuclear size and DNA content [53] . Cell clusters were defined as single scanned objects that contained multiple nuclei . The size of the clusters was defined as the ratio of the total nuclear area within a cluster divided by the size of an average nucleus in the same population . Single-cell suspensions for either PC-3 or DU 145 cells , were prepared from 80% confluent cultures . The cells were counted and plated onto 24-well flat-bottomed plates using a two-layer soft agar system with 1x103 cells in 400 μl of media per well , as described previously [54] . The feeder layer was prepared with agar ( 1% ) equilibrated at 42°C . On top of the agar layers conditioned media from COS-7 cells stably transfected with a SLIT2 expression vector , or mock transfected control , was added . After 14 days of incubation , the colonies ( >50 cells ) were counted using an inverted microscope . All experiments were done at least three times in triplicate per experimental point and all statistical analyses were performed using the Student's t-test . Genes differentially expressed were first identified using SAM multi-class test [22] , with a threshold of FDR<1% . Differentially expressed genes were then used as input for principal component analysis ( PCA ) and the first two components representing 68% of variability were plotted to visualize the relationships between the different samples ( Fig 5A ) . Genes differentially expressed in a given cell type as a result of co-culture were identified by a 2-class SAM procedure ( FDR<1% ) by directly comparing RWPE1 co-cultured with DU145 ( RWPE1DU145 ) and RWPE1 cultured in isolation ( RWPE1 ) or by comparing DU145 co-cultured with RWPE1 ( DU145RWPE1 ) and DU145 cultured in isolation ( DU145 ) . Predicted targets of polarized genes and the differentially expressed genes were then compared using a Fisher exact test . The comparison of these gene lists at the functional level was performed by plotting the frequency of genes in each functional term for predicted targets ( x axis in Fig 5C and 5D ) against differentially expressed genes ( y axis in Fig 5C and 5D ) . In order to address the hypothesis that disease linked genetic mutations such as copy number variation ( CNV ) may influence the expression of polarised genes in tumour cells and that this , in turn , may be predictive of tumour features and clinical outcome we implemented a data analysis pipeline based on a number of advanced statistical procedures . We used an independent dataset [17] , which had comparative genomic hybridisation ( CGH ) , gene expression and comprehensive information on tumour features and clinical outcome for a total of 231 tumour samples . Firstly , in order to prioritise relevant genetic abnormalities we used ANOVA to rank CGH signals linked to tumour features and/or one of the clinical outcome variables ( see S1 File for further details ) . The top 2017 probes in the ranked list were selected as an input of the modelling procedure . We then mapped the 391 polarised genes we originally identified on the independent dataset . Next , we used the selected CGH data and the polarised gene expression profiling dataset as an input of a hierarchical Bayesian model [55] to find association between polarized gene expressions and CNV ( see S2 File for details of the modeling procedure as applied here ) . Next , we fit an ANCOVA model for each gene expression on the tumour features . We then computed correlations for the significant associations ( p<0 . 05 ) and integrated all information in a network format using the Cytoscape [43] software ( Fig 6 ) . Finally , we selected all polarized genes represented in the network and performed a survival analysis testing the hypothesis that their expression in tumour cells could be linked to clinical outcome ( survival and time free of recurrence ) . Survival analysis was performed as below . Briefly , for each gene we defined an optimal cutoff to separate patients in two groups of low and high-expressing tumours , using procedure described in Budczies et al [56] . Using this cut off , we dichotomized each gene expression level that was then used to fit a cox regression model .
|
In the current era of cancer research , stimulated by the release of the entire human genome , it has become increasingly clear that to understand cancer we need to understand how the many thousands of genes and proteins involved interact . Modern techniques have enabled the collection of unprecedented amounts of high quality data describing the state of these molecules during cancer development . In cancer research particularly , this strategy has been particularly successful , leading to the discovery of new drugs able to target key factors promoting cancer growth . However , a large body of research suggests that in complex organs , the interaction between cancer and its surrounding environment is an essential part of the biology of both diseased and healthy tissues , therefore it is of paramount importance that this process is further investigated . Here we report a strategy designed to reveal communication signals between cancer cells and adjacent cell types . We apply the strategy to prostate cancer and find that normal cells surrounding the tumour do exert an anti-tumour activity on prostate cancer cells . By using a statistical model which integrates multiple levels of genetic data , we show that cell-to-cell communication genes are controlled by DNA alterations and have potential prognostic value .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"cell",
"physiology",
"urology",
"medicine",
"and",
"health",
"sciences",
"genetic",
"networks",
"gene",
"regulation",
"cancers",
"and",
"neoplasms",
"genitourinary",
"tract",
"tumors",
"epithelial",
"cells",
"oncology",
"prostate",
"cancer",
"network",
"analysis",
"genome",
"analysis",
"cellular",
"structures",
"and",
"organelles",
"cytoskeleton",
"computer",
"and",
"information",
"sciences",
"genomics",
"animal",
"cells",
"cell",
"communication",
"gene",
"expression",
"biological",
"tissue",
"exocrine",
"glands",
"prostate",
"diseases",
"cell",
"biology",
"anatomy",
"genetics",
"epithelium",
"biology",
"and",
"life",
"sciences",
"cellular",
"types",
"computational",
"biology",
"prostate",
"gland"
] |
2016
|
A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells
|
Natural Killer ( NK ) cells contribute to the control of viral infection by directly killing target cells and mediating cytokine release . In C57BL/6 mice , the Ly49H activating NK cell receptor plays a key role in early resistance to mouse cytomegalovirus ( MCMV ) infection through specific recognition of the MCMV-encoded MHC class I-like molecule m157 expressed on infected cells . Here we show that transgenic expression of Ly49H failed to provide protection against MCMV infection in the naturally susceptible A/J mouse strain . Characterization of Ly49H+ NK cells from Ly49h-A transgenic animals showed that they were able to mount a robust cytotoxic response and proliferate to high numbers during the course of infection . However , compared to NK cells from C57BL/6 mice , we observed an intrinsic defect in their ability to produce IFNγ when challenged by either m157-expressing target cells , exogenous cytokines or chemical stimulants . This effect was limited to NK cells as T cells from C57BL/6 and Ly49h-A mice produced comparable cytokine levels . Using a panel of recombinant congenic strains derived from A/J and C57BL/6 progenitors , we mapped the genetic basis of defective IFNγ production to a single 6 . 6 Mb genetic interval overlapping the Ifng gene on chromosome 10 . Inspection of the genetic interval failed to reveal molecular differences between A/J and several mouse strains showing normal IFNγ production . The chromosome 10 locus is independent of MAPK signalling or decreased mRNA stability and linked to MCMV susceptibility . This study highlights the existence of a previously uncovered NK cell-specific cis-regulatory mechanism of Ifnγ transcript expression potentially relevant to NK cell function in health and disease .
Natural killer ( NK ) cells are pivotal for both the destruction of virally-infected cells and for the cytolysis of certain tumor cells [1] . These processes are dependent on the interaction of NK cell receptors with their cognate ligands on target cells . NK cell responses are controlled by the integration of multiple triggering signals from families of cell-surface-activating and -inhibitory NK receptor such as mouse Ly49 molecules and human p58 , or killer cell immunoglobulin-like receptors ( KIRs ) [2] , [3] . Activating NK cell receptors detect specific pathogen–associated structures . These receptors lack an intracellular signaling domain and associate non-covalently with the immunoreceptor tyrosine-based activation motif–containing adaptor DAP12 , CD3ξ or FcεRIγ or the Tyr-Ile-Asn-Met motif–containing adaptor DAP10 [4] . Engagement of activating receptors results in cytoskeletal rearrangement , proliferation and the secretion of lytic granules and cytokines . Conversely , inhibitory receptors possess tyrosine-based inhibitory motifs ( ITIM ) in their intracellular domains . MHC class I ligation induces ITIM phosphorylation and the subsequent recruitment of the tyrosine phosphatases SHP-1 and SHP-2 . These dephosphorylate downstream signaling molecules that are required for activating responses . Extensive evidence has demonstrated that host MHC-I expression heavily affects NK cell responsiveness; defects in NK cell-dependent target cell killing , rejection of allogeneic bone marrow , and IFNγ production are observed in MHC-I deficient mice [5] . This hyporesponsiveness has been attributed to dampened stimulatory signaling [6] , [7] . Indeed , NK cell function which include killing and cytokine production were restored upon re-introduction of an MHC-I molecule , however , only on NK cells that carry a cognate inhibitory receptor for the MHC-I molecule . These competent NK cells were therefore called “armed” or “licensed” [8] , [9] . Genetic analyses evaluating strain-dependent differences in the response to MCMV infection have provided detailed insight into NK cell activation and recognition of infected cells . In C57BL/6 ( B6 ) mice , NK cells express the Ly49H receptor , which recognizes the viral m157 glycoprotein , a MHC class I molecule expressed on the surface of infected cells [10] . Mice lacking a Ly49h gene or harbouring a non-functional DAP12 adaptor molecule are susceptible to MCMV infection [11] , [12] . Conversely , transgenic expression of Ly49h in an otherwise genetically susceptible strain imparts resistance to MCMV [13] . Engagement of the m157/Ly49h complexes triggers a number of downstream signalling events and effector functions . Firstly , NK cells mediate contact dependent cytotoxicity through the release of perforin ( Prf ) and granzymes ( Gzms ) [14] . Prf facilitates the entry and trafficking of Gzm proteases into target cells , which ultimately leads to DNA fragmentation and cell death . NK cells also secrete cytokines , such as IFNγ , during the acute phase of MCMV infection . It has been well documented that IFNγ inhibits both MCMV and HCMV viral replication in vitro [15] , [16] . Moreover , deficiency in IFNγ has been associated with high mortality and lack of viral clearance upon infection with MCMV , emphasizing its important role in protection against MCMV induced lethality and pathogenesis [17] . In the present study , we investigated the effect of the host genetic background on NK cell responses and addressed whether acquisition of Ly49H magnifies NK cell antiviral activity . Furthermore , we carried out a genetic screen to identify mechanisms that regulate IFNγ production by NK cells . These studies demonstrate that IFNγ production in the context of Ly49H is critical for NK cell anti-viral function . Moreover , they uncover a previously unknown regulatory mechanism of Ifng transcription in NK cells that correlates with increase susceptibility to CMV infection .
In C57BL/6 inbred strains of mice , the control of MCMV replication occurs via the expression of Ly49H by NK cells . Here , the mechanism underlying this Ly49H-independent susceptibility was studied in the FVB and A/J strains carrying Ly49h transgene ( A-Ly49h and FVB-Ly49h [13] , respectively ) . In a steady state situation , Ly49H is expressed by approximately 50% of NK cells derived from B6 mice [13] , [18] . Consistent with these data , B6 mice had 50% Ly49H+ NK cells , however Ly49H staining on NK cells derived from FVB-Ly49h and A-Ly49h mice were both significantly lower than B6 NK cells ( Figures 1A and 1B ) . No differences in the expression of other Ly49 receptors were detected between the FVB-Ly49h or A-Ly49h strains and their control littermates indicating that the introduction of Ly49h gene did not affect the NK cell gene expression repertoire ( Figures S1A and S1B ) . Given that the only known ligand of Ly49H is the viral protein m157 , we sought to ensure that this interaction remained intact in A-Ly49h mice . We tested the m157-Ig binding capacity and found no strain-dependent differences in m157 binding between B6 , FVB-Ly49h and A-Ly49h . However as expected , m157 binds to the inhibitory Ly49I [19] expressed by FVB NK cells ( Figures 1A and 1B ) . Altogether , these results show that , in A-Ly49h and FVB-Ly49h mice , Ly49H is properly expressed and can recognize MCMV . To assess the protective capacity of Ly49H in the A/J ( named A in the rest of the manuscript ) and FVB backgrounds , we examined several parameters of MCMV infection in these mice . We first challenged the mice with a dose of MCMV that is lethal in the absence of Ly49H expression . As expected , A-WT littermates and B6 . Ly49h−/− mice exhibited drastic weight loss and death compared to B6 and FVB-Ly49h mice which survived to the experimental endpoint ( Figures 1C and 1D ) . Remarkably , and similar to the A/J parental control , the A-Ly49h mice showed early signs of distress with a precipitous drop in body weight and 100% mortality within the first week of infection ( Figures 1C and 1D ) . To determine whether the observed mortality was a result of unchecked viral replication , we next infected the mice with a low dose of MCMV and assessed liver and spleen viral titers at day 3 post infection . All the mice expressing Ly49H were able to control viral replication efficiently as compared to the mice that lacked the receptor ( Figures 1E and 1F ) . However despite equal expression of Ly49H by NK cells from A-Ly49h and FVB-Ly49h the viral load in the spleen and liver was significantly increased in A-Ly49h mice ( Figures 1E and 1F ) . Viral replication persisted to later time points post infection and was significantly higher in the liver , spleen and heart of A-Ly49h at days 3 and 6 compared to other Ly49h expressing mice ( B6 and FVB-Ly49h ) . The virus was cleared from all organs by day 10 with the exception of the salivary glands ( Figure S2 ) . Finally we interogated whether the early death observed in A-Ly49h mice was the consequence of a systemic increase in inflammatory mediators upon MCMV infection . To this end , we quantified the level of inflammatory proteins at 36 h post MCMV infection in A-Ly49h and FVB-Ly49h mice as well as their WT counterparts . We found no significant differences between the A-WT and FVB-WT mice in terms of cytokine levels ( Figure 1G ) . However in the Ly49h transgenic mice , the serum levels of all the cytokines tested and the acute phase protein SAA , a marker of tissue injury , was significantly higher in A-Ly49h mice compared to FVB-Ly49h mice ( Figure 1H ) . Thus , the overwhelming inflammation in the A-Ly49h mice might contribute to their early death . Altogether , these results demonstrate that A/J mice are highly susceptible to MCMV infection even with transgenic expression of Ly49H . They further suggest that NK cells from A-Ly49h are incapable of efficiently controlling MCMV infection regardless of the amount of viral inoculum . In order for NK cells to proliferate and kill target cells following MCMV infection , their ability to engage activating receptors and to release mature cytotoxic granules such as Gzmb and Prf must be intact . As A-Ly49h NK cells could fully recognize m157 , we investigated the ability of these cells to proliferate and to become cytolytic upon MCMV challenge . In A-Ly49h mice , we observed a significant increase in the number of splenic BrdU+ Ly49H+ cells at day 4 post-infection , indicative of sustained proliferation ( Figure 2A ) . Cell proliferation was markedly absent in the Ly49H+ NK cells from B6 and FVB-Ly49h mice ( Figures 2A and S3A ) . Despite a decrease in proliferation in all strains by day 7 post infection , the percentage of BrdU staining remained significantly higher in A-Ly49h mice . Since increased Ly49H+ NK cell proliferation has been associated with inefficient viral clearance [20] , we examined viral replication in the spleen at days 4 and 7 post infection . While B6 and FVB-Ly49h mice had largely cleared MCMV from the spleen , viral burden remained significantly high in A-Ly49h mice at 4 and 7 days post infection ( Figures 2B and S3B ) . Although it is well established that A/J and B6 NK cells express similar amounts of Gzmb and Prf when stimulated with IL-15 [14] , we aimed to rule out the possibility that A-Ly49h NK cells are intrinsically incapable of mounting an effective cytotoxic response in vivo upon MCMV infection ( Figures 2C and 2D ) . Expression of Gzmb and Prf were assessed at day 4 post infection . We found that Gzmb and Prf expression was drastically increased in Ly49H+ and Ly49H− NK cells derived from the A-Ly49h mice compared to cells derived from B6 mice and , to a lesser extent , those derived from FVB-Ly49h mice ( Figure S3D ) . These results indicate that A-Ly49h NK cells , while highly proliferative , are still capable of mounting an effective cytotoxic response in the context of MCMV infection . It is well establish that IFNγ is required for protection against acute MCMV infection [17] , [21] . We therefore investigated the ability of A-Ly49h NK cells to produce IFNγ upon stimulation . NK cells from A-Ly49h and B6 mice were exposed to m157-target cells by co-culturing spleen cells with RMAs-m157 . These cells lack MHC-I expression and , as such , the triggering of Ly49H can be assessed in the absence of inhibitory signals originated from MHC-I/Ly49 receptor interactions . B6 Ly49H+ NK cells robustly produced IFNγ after 4–6 h of stimulation with their m157-target cells , whereas A-Ly49h NK cells lacked IFNγ+ cells in the same conditions ( Figure 3A ) . Conversely , to address the effect of MHC-I expression we co-cultured A-Ly49h splenocytes with BAF-m157 , cells derived from BALB/c bone marrows and possessing an H-2d haplotype . We found that the presence of MHC-I did not change the ability of A-Ly49h NK cells to produce IFNγ . To determine whether this defect was pathway specific , we interrogated whether these NK cells could produce IFNγ if stimulated through the IL12/IL18 receptors . Interestingly , B6 Ly49H+ NK cells produced twice as much IFNγ as Ly49H+ NK cells from A-Ly49h mice . Finally , to bypass receptor proximal signaling we activated the NK cells with phorbol myristate acetate ( PMA ) and the calcium ionophore ionomycin ( Iono ) that stimulate the cells directly by mobilizing free calcium ions and activating PKC enzymes . The differential IFNγ production was even more striking in cells stimulated with PMA plus Ionomycin ( P/I ) ( Figures 3A and 3B ) . IFNγ production by FVB-Ly49h Ly49H+ NK cells closely mirrored those observed in B6 NK cells . Overall , the production of IFNγ by NK cells from A-Ly49h was significantly decreased when compared to B6 NK cells ( Figure 3C and 3D ) . Determination of TNFα showed similar levels in NK cells from A-WT or B6 mouse strains . As stimulation of T cells by IL-12/IL18 or P/I also results in the production of IFNγ , we sought to determine whether the defect in IFNγ production in A-Ly49h was NK cell specific . Remarkably , T cells from A-Ly49h mice were found to produce similar amounts of IFNγ as those from B6 mice ( Figure 3D ) . Collectively , these data suggest that A mice carry a genetic defect that specifically affects the production of IFNγ by NK cells and that functions downstream of several immune receptor ( cytokine , PRR , NKR ) pathways or chemical stimulation . NK cell responsiveness is dictated by both the NK cell repertoire and the interaction of these with their cognate MHC-Class I molecules [22] . To evaluate whether one of these variables affected the fate of A-Ly49h NK cells , we used a panel of AcB/BcA recombinant congenic strains ( RCS ) in which each AcB strain inherits ∼12 . 5% genes from the B6 genome and ∼87 . 5% genes from A/J , and reciprocally for each BcA strain . We screened the RCS panel for two parameters of NK cell responsiveness: IFNγ production and control of viral replication . Splenocytes from all strains were stimulated with P/I for 4 h and intracellular IFNγ was determined by FACS in CD3−DX5+ NK cells ( Figure 4A ) . Surprisingly , the IFNγ production profile clearly distinguished the A/J from the B6 background . Production of IFNγ was much lower in AcB NK cells ( below a 25% threshold ) than in BcA NK cells and was not dependent on the inheritance of the A/J NKC or H2 ( as evidenced by the elevated production of IFNγ in BcA17 , BcA19 , BcA27 , and BcA4 strains ) ( Figure 4A and Table S1 ) . We found that two strains , BcA7 and BcA9 showed decreased on IFNγ production similar to the AcB strains , however this decrease was much more profound in the BcA9 strain ( Figure 4A ) . This genetic background-dependent difference in IFNγ production , however , was completely absent in T cells from the same strains ( Figure S4A ) . To determine whether the differences observed were maintained upon triggering of Ly49H receptor , splenocytes from the BcA strains ( with the exception of BCA17 , 19 and 27 which inherited the NKC from the A strain and do not express Ly49H ) were co-cultured with RMAs-m157 and IFNγ production by NK cells was analyzed by FACS . The decreased IFNγ expression characteristic of A-Ly49h NK cells was only observed in BcA9 NK cells ( Figure 4B ) . To assess the impact of differential IFNγ production on MCMV replication , we investigated viral titers in the spleens of BcA mice 3 days post infection . The AcB strains were excluded as none of them had inherited the B6 NKC ( Table S1 ) . As expected , Ly49H expression was required for efficient control of viral replication; high viral loads were observed in strains possessing the A/J NKC: A/J , BcA17 , BcA19 , and BcA27 . Among the BcA strains possessing the B6 NKC , increased susceptibility to MCMV infection was only observed in the BcA9 strain ( Figure 4C ) . This susceptibility was also confirmed when B6 and BcA9 were infected with high MCMV doses ( Figure 4D ) . Given that BcA9 retains 12 . 5% of the A background , we then investigated whether NK cells from B6 and BcA9 behave similarly in terms of expression of NK cell receptors and function . We found that CD11b , Ly49G . Ly49HIC and NKG2A are similarly expressed between the two strains with a slight decrease of KLRG1 ( in BcA9 ) , ( Figure S5A ) . In addition , NK cells from both strains were capable of rejecting MHC-I deficient cells and of killing m157 expressing splenocytes efficiently ( Figure S5B ) . Collectively , the data indicate that A-Ly49h and BcA9 NK cells behave similarly with regard to viral control and IFNγ production . Moreover , the NK cell-specific , strain-dependent differential production of IFNγ suggested that this phenotype is genetically determined . To map the genetic determinants underlying IFNγ production by NK cells , we performed a genome wide association analysis of IFNγ production as a quantitative trait using efficient mixed model association ( EMMA ) [23] . 1215 SNPs overlapping the relevant break points and representing the genetic diversity of the RCS strains were used to map a single quantitative trait locus ( QTL ) on chromosome 10 ( 113 . 59–120 . 45 , p<10−8 ) . This locus was associated with IFNγ production by NK cells ( Figure 5A ) . The same analysis performed using IFNγ production by T cells did not show any significant QTLs ( Figure S4B ) . The physical size of the chromosome 10 target interval was 6 . 6 Mbp containing 39 Refseq annotated genes including Ifng ( Figure 5C and Table S2 ) . To narrow the pool of candidates , we compared exome sequencing data from A and BcA9 strains against the reference B6 genome sequence with a required minimum of 10× sequencing depth coverage . 30 non-synonymous coding polymorphisms were identified in 11 genes in both the A and BcA9 strains ( Table S3 ) . We then removed variants found in public databases ( http://www . sanger . ac . uk/cgi-bin/modelorgs/mousegenomes/snps . pl , http://www . informatics . jax . org/and http://cgd . jax . org/cgdsnpdb/ ) shared between A and C3H , DBA/2 or 129S1 strains , as NK cells from these strains do not show a defect in IFNγ production ( Table S3 and Figure S6 ) . This left 11 coding variations affecting 8 genes mapping mostly to the 3′ and 5′UTRs . Given that the defect in IFNγ expression was not observed in T cells , we hypothesized that the underlying gene had to be expressed exclusively in NK cells . Thus , for the remaining 11 variations , we performed an in silico analysis of gene expression using public databases [24] ( https://www . immgen . org/and https://www . biogps . org ) [25] . We found that none of the 8 candidate genes were NK cells specific , thus they were given lower priority for further study ( Table S3 ) . Collectively , our mapping strategy and enquiry of the genetic variation underlying candidate genes within the target interval indicated that the NK cell intrinsic defect in IFNγ production is linked to chr . 10 and is unlikely to be due to a protein-coding defect . Because the impaired IFNγ production was observed after P/I treatment in total NK cells from the BcA9 strain , we questioned whether this decrease of IFNγ production would be observed with the treatment of other stimuli as for A-Ly49h mice . We found that decreased IFNγ production by BcA9 NK cells was also observed when total splenocytes where incubated with IL-12/IL-18 , IL-15/IL-18 as well as LPS , CPG , and Poly I:C ( Figure 6A ) . As for the expression of TNFα in B6 and A strains , we found no decrease TNFα production by NK cells from BcA9 in comparison with B6 mice after P/I stimulation ( Figure 6B ) . To better characterize the mechanism underlying differential IFNγ regulation , IFNγ mRNA and protein levels were measured in NK cells from B6 and BcA9 mice . We first generated NK cells by co-culturing splenocytes with IL-2 for 6 days . B6 and BcA9 LAK cells were then stimulated with P/I for 1–3 hours , after which IFNγ expression was determined . Intracellular and secreted IFNγ levels were decreased in BcA9 cells compared to B6 ( Figures 6C and 6D ) . IFNγ mRNA was also decreased in BcA9 cells indicating that the differential regulation occurs at the level of transcription ( Figure 6E ) . As the Ifng gene itself was located within the QTL , we looked for mutations in both the promoter region and the well-characterized regulatory elements required for proper IFNγ expression and as expected since IFNγ production is not affected in T cells , none were identified . Stimulation with P/I activates the PKC pathway and increases the calcium flux which in turn induces the phosphorylation of Erk and P38 , events that are crucial for the transcriptional regulation of IFNγ [26] . We found that IFNγ production was not effected in T cells after P/I stimulation ( Figures 3C , D and S4 ) . We therefore asked whether this pathway was also functional in NK Cells , by determining whether NK cells from BcA9 mice had impaired signalling following P/I stimulation . However , no differences in Erk or P38 phosphorylation were observed ( Figures 6F ) . These data indicate that the dysregulation of IFNγ is not part of any upstream signalling or transcriptional pathway or of any known IFNγ cis-regulatory element , yet the dysregulation is manifested at the level of transcriptional control . To investigate whether the decreased IFNγ production in the BcA9 mice was a consequence of mRNA stability , we treated NK cells from B6 and BcA9 mice with the transcriptional inhibitor actinomycin D after P/I stimulation and we found no difference in RNA levels between treated and non treated NK cells in both strains ( Figure 6G ) . These data suggest that mRNA degradation in NK cells from the BcA9 strain is not involved in the decreased production of IFNγ . We then examined if differences in DNA methylation might explain the decreased IFNγ production in NK cells from BcA9 mice by treating NK cells with the DNA methylase inhibitor 5-aza-2-Dexoxycytidine ( Aza ) . We found that IFNγ production was increased in both strains after Aza treatment . However the magnitude of increase was higher in NK cells from BcA9 ( 2 , 5 times ) than B6 mice ( 1 . 3 time ) ( Figure 6H ) . These data suggest that DNA methylation is somehow involved in the genetic regulation of IFNγ production in NK cells from BcA9 mice . We finally performed chromatin immunoprecipitation ( ChIP ) assays to determine whether BcA9 and B6 NK cells possess different epigenetic marks in the Ifnγ locus . Monomethylation of H3 lysine 4 ( H3K4me1 ) is a histone mark associated with cis-regulatory elements . This mark is enriched at the Infg promoter and at 4 upstream CNSs ( −6 kb , −22 kb , −34 kb , and −54 kb ) during Ifnγ transcription in both NK and T cells . We found that the enrichment of H3K4me1 in non-stimulated IL-2 derived NK cells was similar between B6 and BcA9 mice ( Figure 6 I left ) . This might indicate that the decreased Ifnγ transcription observed in BcA9 NK cells is not a consequence of Ifnγ long term locus silencing . However , following 1 hour of P/I treatment , increased enrichment of the H3K4me1 was observed at the Ifnγ promoter and CNSs of B6 NK cells but not of BcA9 NK cells ( Figure 6 I right ) . In addition , in another set of experiments done on fresh NK cells , the results correlate with those outlined above ( Figure 6 J ) . These results suggest that chromatin remodelling involved in P/I induced Ifnγ transcriptional activation is altered in NK cells derived from BcA9 mice . To confirm our linkage analysis and to rule out that the genetic alteration occurred elsewhere in the genome and does not act in trans on Ifng gene , we assessed IFNγ production in Css10 mice . This strain possesses chromosome 10 from A mice on a B6 background . Consistent with an A strain specific effect , production of IFNγ by Css10 and BcA9 NK cells was significantly decreased after stimulation with P/I or triggering of Ly49H receptor ( Figure 7A , 7C ) . Once again , IFNγ production by T cells was not affected , confirming that the locus on chromosome 10 controls only IFNγ production in NK cells ( Figure 7B ) . To address whether the decreased IFNγ production in these mice was likewise linked to MCMV susceptibility , B6 , Css10 and BcA9 mice were infected with MCMV . Although they showed lower MCMV load than the BcA9 strain , Css10 mice were significantly more susceptible to MCMV infection than B6 mice as determined by viral titers in spleen ( Figure 7D ) . We also investigated whether the surface expression of NK cells receptors was differently expressed between strains , before and after MCMV infection . We found that after infection , the level of NK cell receptor was similarly expressed between B6 , BcA9 and Css10 mice ( Figure S7 ) . These data indicate that the chromosome 10 locus controls both IFNγ expression by NK cells and subsequent susceptibility to MCMV infection .
We report that deficiency in IFNγ production by NK cells upon Ly49H/m157 engagement is associated with increased susceptibility to MCMV infection independent of NK cells capability to release cytolytic granules . This defect is not only linked to NK cell stimulation through an activating receptor , but seems to affect various signaling pathways for IFNγ secretion . Decreasing IFNγ secretion is seen at the level of IFNγ mRNA transcription upon engagement of ITAM-dependent and ITAM-independent upstream signaling events . We used the AcB/BcA panel of recombinant congenic strains to map the regulation of IFNγ production to a 6 . 6 Mbp region on chromosome 10 . No NK cell specific deleterious protein-coding mutations were identified in that interval however we confirmed that the locus controls both IFNγ production and viral spread . The importance of IFNγ in the modulation of MCMV infection stems from several studies using IFNγ and IFNγ receptor deficient mice . Although some reports using mice of mixed 129/B6 background suggested that the production of IFNγ by NK cells may be a predominant antiviral mechanism in the liver at six days post-infection [21] , [27] , newer studies using mice of uniform C57BL/6 origin showed that IFNγ is required for the control of MCMV in the spleen and liver as early as three days post-infection [17] . We note , however , that CSS10 mice showed about ten-fold lower viral replication than BcA9 animals suggesting that this strain carries additional MCMV-susceptibility loci , the mapping of which would require secondary crosses using BcA9 . Regardless of these considerations , our QTL analysis and co-occurrence of defective antiviral function in CSS10 mice indicate that a specific decrease in IFNγ production by NK cells and not by T cells is associated with increased MCMV susceptibility in vivo . NK cell hyporesponsiveness is often associated with self-tolerance . Self-tolerance occurs in NK cells that develop in MHC Class I deficient hosts or that lack self MHC-I-specific inhibitory receptors [6] , [7] , [9] . In these cases , impaired killing and IFNγ production is observed in NK cells following engagement of activating receptors . It follows that functional competence requires the interaction of MHC-I molecules with their cognate inhibitory receptors during NK cell development . As A-Ly49h mice exhibit impaired IFNγ production compared to B6 counterparts , it is possible that NK cells from these strains are differentially licensed by their respective MHC-I molecules . Interestingly , hyporesponsive NK cells from MHC-I deficient mice produce normal IFNγ upon stimulation with P/I and can clear MCMV infection similarly to WT NK cells [6] , [9] , [28] , [29] . We show that BcA9 NK cells are hyporesponsive despite carrying a B6 MHC-I region . Additionally , we show that decreased IFNγ production was sustained upon P/I stimulation and MCMV replication was increased compared to WT counterparts . These indicate that the defect in IFNγ production does not result from increased NK cell self-tolerance . Altogether , these findings make the interaction between MHC-I and the NK-cell receptor repertoire an improbable player in our NK cell hyporesponsiveness model . NK and T cells use redundant , non overlapping signaling pathways for IFNγ production . Such pathways regulate IFNγ production through a number of transcription factors including T-bet [30] , STAT4 [31] , STAT5 [32] , [33] , IκBζ [34] , NF-kB family members [35] , and Runx3 [36] . Here we show that decreased expression of IFNγ is specific to NK cells suggesting that a defect in any gene encoding a master transcription factor for IFNγ expression is unlikely . In addition , our genetic analysis ruled out any coding polymorphisms in these transcription factors as being linked to low IFNγ expression . Finally , as the I IFNγ defect is seen in both the BcA9 and CSS10 strains , it is unlikely that it is controlled by a de novo mutation located outside of our locus of interest . Phorbol esters such as PMA in addition to Ionomycin are potent activators of IFNγ production in NK cells and T cells . The pathways involve the activation of the PKC isozymes ( α , β Ι , β ΙΙ , γ , δ , ε , θ ) which in turn activate MAPK kinases such as ERK , p38 and JNK . Engagement of NK cell activating receptors that signal through ITAMs also results in prompt activation of PKC θ which is essential to induce IFNγ production [26] . Consistent with this idea , we observed that the MAPK pathway was not implicated in impaired IFNγ production in NK cells from the BcA9 strain . More importantly , we found that defect of IFNγ production by NK cells was correlated with changes in IFNγ mRNA levels independently of decreased mRNA stability . These data suggest that the dysregulation of IFNγ production is not modulated by post-transcriptional or translational events . Our results demonstrate that the defect in IFNγ production relates to decreased expression of IFNγ mRNA in NK cells suggesting a cis-regulatory mechanism . In fact , we found that differences in DNA methylation might in part explain the defect in IFNγ production . Proper transcription of IFNγ is dependent on the binding of specific transcription factors to conserved non-coding sequences ( CNSs ) surrounding the Ifng gene . To date , nine CNSs have been identified within ∼120 kb flanking the murine Ifng locus [37]–[40] . These become selectively activated in differentiated cells that express IFNγ [41] . Recent studies using BAC transgenic mice harboring various deletions both upstream and downstream of the human IFNγ gene revealed that distal CNSs have cell type-specific function [42] , [43] . In this regard , our in silico attempt to identify mutations that might abrogate the binding of transcription factors , whether in the promoter or CNSs of A mice , did not identify any deleterious modifications . In a recent study , NeST , a lncRNA located within our Ifng locus has been shown to be expressed in T cells and selectively affects IFNγ expression on CD8+ T cells [44] . By analyzing public databases we identified only 3 ancestral polymorphisms within NeST between B6 and A mice ( rs29312535 , rs29330422 and rs49496559 ) . Two of these were discounted because they were also present in the C3H and 129S1 mouse strains , which do not exhibit IFNγ expression deficits . It has been shown that the primary mechanism of action for polymorphism differences in NeST in T cells was to affect its own RNA expression levels , which lead to modulated IFNγ production [44] . Thus , the remaining SNP ( rs29312535 ) is unlikely to be involved in the decreased IFNγ production by NK cells in A mice since no difference in the expression of NeST in NK cells from BcA9 and B6 strains was found . However , we cannot exclude that the SNP ( rs29312535 ) might alter the physical interaction of NeST with IFNγ transcriptional complex in NK cells and this possibility has to be explored in future work . Interestingly , a recent genome-wide ChIP analysis in the Ifng locus of active ( H3K4me2 ) and repressive ( H3K27me3 ) chromatin marks from Th1 and Th17 γδT cell subsets revealed additional marks for putative active regulatory elements ( Figure S8 ) [45] . Thus , active transcriptional marks were found upstream and downstream of the Ifng gene , six of which were directly located within the NeST region ( Figure S8 ) . The presence of these new active transcriptional marks in the vicinity of Ifng suggests that our understanding of IFNγ production by T cells and more specifically by NK cells needs further investigation . In addition , proper studies using ChIP-Seq to evaluate activating and repressive epigenetic modifications will provide a more comprehensive view of IFNγ regulation by NK cells . Specific expression of a number of cytokines , including IFNγ , IL4 , IL13 and IL17 have been shown to be tightly regulated by extremely well conserved cis-regulatory elements [46] . Deletion of these elements has been correlated with decreased cytokine production , thereby shedding light on the molecular basis for lineage specific-transcription . Most studies evaluating the control of IFNγ expression have focused on CD4+ T cell differentiation into Th1 or Th2 cells . Th1 cells express IFNγ but not IL4 , IL13 and IL5 whereas the opposite is true in Th2 cells [41] . The underlying mechanism responsible for this differentiation involves the repression of the Ifng locus in Th2 cells and the Il4 and Il13 loci in Th1 cells [47] , [48] . Thus specific epigenetic events determine chromatin permissiveness and accessibility of genes for the transcriptional machinery . In contrast to T cells , the Ifng locus in NK cells is not repressed , which might allow rapid response to external stimuli [31] . However , the specific mechanisms providing lineage specific Ifng transcription are still not well understood . To conclude , the subtle quantitative allelic differences found in animal models have more often revealed that equivalent polymorphisms exist in humans . Our analysis of the mechanism of viral control and IFNγ production by NK cells have led us point out the existence of “modulatory” elements that dictate the production of IFNγ by NK cells . These findings suggest that deeper knowledge of IFNγ regulation by NK cells will offer insight into clinical immune pathologies and direct strategies for intervention .
All mice were kept under specific pathogen free conditions and handled according to the guidelines and regulations of the Canadian Council on Animal Care . Mice experimentation protocol ( Protocol number 4791 ) was approved by the McGill Facility Animal Care Committee ( FACC ) . C57BL/6 ( B6 ) , A/J ( A in the text ) , and C57BL/6J-Chr 10A/J/NaJ ( Css10 ) were purchased from The Jackson ( Jax , Bar Harbor , ME ) and FVB/N were purchased from Charles River Laboratories ( Wilmington , MA ) . FVB . Ly49h transgenic ( FVB . Ly49h ) mice and B6 . Ly49h−/− mice were obtained as previously described [12] , [13] . A . Ly49h mice were generated by backcrossing the FVB . Ly49h mice onto an A/J WT background for a minimum of 10 generations . A genome scan using 1449 single nucleotide polymorphism showed a 100% similarity between A/J and A . Ly49h mice . Transgenic mice were identified by PCR using the Ly49h specific marker , D6Ott11 as described previously [12] . Recombinant congenic mice of the AcB/BcA set were derived from two successive backcrosses ( N3 ) to either A/J ( AcB ) or B6 ( BcA ) parental mice , as previously described [49] . The B6 mice deficient for H2-DbKb ( B6 . H2−/− ) were kindly provided by Dr . Hidde L . Ploegh ( Cambridge , Massachusetts ) . The m157-Transgenic mouse was kindly provided by Dr . Sandeep K . Tripathy , ( Washington University School of Medicine , St . Louis ) . Mice were bred and maintained in a specific pathogen-free animal facility at McGill University . All experimental protocols were developed in accordance with institutional guidelines of the Canadian Council on Animal Care . Stock salivary gland Virus ( SVG ) was prepared by passaging the MCMV ( Smith strain ATCC VR-1399 , lot 1698918 ) twice in BALB/c mice . Virus was prepared from the homogenate of salivary glands at day 21 post-infection . Viral titer was evaluated in vitro by standard plaque assays ( PA ) on a confluent CD1 MEF monolayer as previously described [50] . Mice between 7 and 9 weeks were infected intraperitoneally ( IP ) for the indicated times and doses . To determine the viral titer from target organs , hearts and lungs were perfused with PBS prior to homogenization and MCMV titer was quantified by standard plaque assay . FACS was conducted on splenocytes from MCMV-infected and uninfected mice . Single spleen cell suspensions were prepared by grinding the spleen against a 70 µm nylon mesh , lysing red blood cells using ACK lysis buffer and incubating the remaining cells with 2 . 4G2 antibody to block Fc receptors . Fluorescently labeled antibodies and reagents were purchased from BD Biosciences , eBioscience , BioLegend and R&D Biosystems . For determination of the Ly49H-m157 binding , cells were stained with the m157-Ig fusion protein ( gift of L . Lanier , USCF ) followed by detection with PE-conjugated goat anti-human IgG1 ( Jackson ImmunoResearch Laboratories ) . Flow cytometry analyses of cells were performed on a FACSCalibur and Canto II cytometer ( BD Biosciences ) equipped with FACSDiva software and data were analyzed using FlowJo software ( Tree Star ) . IFNγ was measured directly from fresh NK cells ex vivo or cultured in recombinant rhIL-2 ( 1000 U/mL ) for 6 to 8 days . To analyze intracellular IFNγ , single spleen cell suspensions were plated at 5*106 cells per 6-well plate and co-cultured with 2×105 cells of BAF-m157 or RMA/s-m157 ( Gift from L . Lanier , UCSF ) per well in 6-well plates . Alternatively , cells were stimulated with PMA ( 100 ηg/ml ) /ionomycin ( 1 µg/ml ) , rmIL-12 ( 10ηg/ml ) , rmIL-18 ( 50 ηg/ml ) and rmIL-15 ( 50 ηg/ml ) for 5–6 h at 37°C or LPS ( 5 µg/ml ) , CPG ( 5 µg/ml ) and PolyI:C ( 50 µg/ml ) for 16 h . In the last 5 h of the incubation time , a 500-fold dilution of GolgiPlug ( BD Biosciences ) was added . After extracellular staining , cells were permeabilized using BD Cytofix/Cytoperm solution and stained in BD Permwash using anti-IFNγ antibody . ELISA for IFNγ was quantified from supernatants and performed according to the manufacturer's instructions ( eBioscience ) . IFNγ transcripts were analyzed by QPCR using HPRT as a control with the following primers; IFNγ: For 5′ cacggcacagtcattgaaag 3′ and Rev 5′catccttttgccagttcctc3′; HPRT: For 5′ggactgattgacaggaggactg 3′ and Rev 5′ggactgattatggacaggactg 3′ . To obtain serum for cytokine and amyloid A quantification , blood samples were obtained by cardiac puncture from mice infected for 36 h with 5000 PFU of MCMV . Serum was isolated by centrifugation for 20 minutes at 3 , 000 rpm and stored at −80°C . ELISA for IFN-γ and IL-12 p70 ( eBioscience ) , TNFα ( Biosource ) , IFNβ ( PBL ) , SAA ( Invitrogen ) were performed according to the manufacturer's instructions . For quantification of mouse IFN-α , serum samples were dispensed on 96-well microtiter plates coated with a rat anti–mouse IFN-α antibody ( RMMA-1; PBL Biomedical Laboratories ) . Subsequently , IFN-α was detected with a polyclonal rabbit anti–mouse IFN-α antibody ( PBL Biomedical Laboratories ) and a donkey anti–rabbit IgG conjugated to horseradish peroxidase ( GE Healthcare ) as previously described [51] . Absorbance was measured at 450 nm using a Fluostar optima ( BMG LabTech ) . The recombinant congenic strains of mice were genotyped using 1215 markers spanning the entire mouse genome and covering the relevant break points in the AcB/BcA panel of mice [52] . Statistical analyses were performed using the freely available package R . We used a mixed model statistical test designed to correct for genetic relatedness in mouse models known as Efficient Mixed Model Association ( http://mouse . cs . ucla . edu/emma/ ) . Negative log p-values are presented for each marker . Exome capture was performed in A/J and BcA9 Samples using a SureSelect Mouse All Exon kit ( Agilent Technologies , USA ) and parallel sequencing on an Illumina HiSeq 2000 ( 100-bp paired-end reads ) . Reads were aligned to mm9 genome assembly using BWA . Coverage was assessed using BED Tools and showed an average of 58 . 9× base coverage . Single nucleotide variants ( SNVs ) and short insertions and deletions ( indels ) were called using SAMtoolspileup and varFilter with the base alignment quality ( BAQ ) adjustment disabled , and were then quality filtered to have at least 20% of reads supporting the variant call . Variants were annotated using both Annovar and custom scripts to identify whether they affected protein coding sequence . B6 and BcA9 NK cells were cultured 5 to 8 days in rIL-2 ( 1000 U/mL ) . NK cells were stimulated with P/I for the indicated times . Proteins from cell lysates were separated by standard SDS-PAGE and analyzed by immunoblotting with antibodies specific to p38 , phosphorylated p38 , ERK1/2 , and phosphorylated ERK1/2 ( all from Cell Signaling Technology , Danvers , MA ) . Anti-actin was purchased from Santa Cruz Biotechnology ( Santa Cruz , CA ) and used as loading control . Densitometry results were analyzed with Image J software . For the RNA stability analysis , Actinomycin D ( Sigma ) treated B6 and BcA9 NK cells were cultured for 5 to 8 days in rIL-2 ( 1000 U/mL ) and stimulated for 1 h with P/I . Cells were washed with complete RPMI , then left untreated or treated with 10 µg/ml of actinomycin D for 4 h at 37°C . The RNA was then extracted as previously described and IFNγ transcript was analyzed by qPCR . For the analysis of DNA methylation , B6 and BcA9 NK cells were cultured for 6 days and treated or not with the methyltransferase inhibitor 5-aza-2-deoxycytidine ( Sigma ) at 10 µM/ml daily in the presence of rIL-2 for 72 h . Cells were then stimulated or not with P/I for 1 h and IFNγ was analysed by FACS as described before . NK cells cultured in recombinant rhIL-2 ( 1000 U/mL ) for 6 to 8 days or highly enriched T cells ( sorted using magnetic cell sorting ) ( MACS; Miltenyi ) were prepared from B6 and BcA9 mice . 10 million cells were plated on 100 mm culture grade Petri dishes . The next day , culture medium was changed and cells were treated with a vehicle or P/I for 1 h . ChIP were performed as previously described with little modifications [53] . Briefly , chromatin was crosslinked with 1% formaldehyde added to culture medium and incubated at room temperature for 10 min with gentle agitation . Crosslinking was stopped by adding glycine to compose a final 0 . 125M concentration . Cell were scraped for maximum recovery and washed sequentially with ice-cold PBS-glycine 0 . 125M and PBS . Nuclei were prepared by sequential incubations on ice for 5 min in 1 ml of buffer A ( 10 mM Tris-HCl pH 8 , 10 mM EDTA , 0 . 25% Triton X-100 , protease inhibitors ) , and for 30 min in buffer B ( 10 mM Tris-HCl pH 8 , 1 mM EDTA , 200 mM NaCl , protease inhibitors ) . Nuclei pellets were resuspended in sonication buffer ( 10 mM Tris-HCl pH 8 , 1 mM EDTA , 0 . 5% SDS , 0 . 5% Triton X-100 , 0 . 05% NaDOC , 140 mM NaCl ) and sonicated to an average 250 bp size using a Branson Digital Sonifier ( Branson Ultrasonics ) . Chromatin was subjected to immunoprecipitation overnight using 20 µl of Protein A and 20 µl of Protein G Dynabeads ( Life Technologies ) pre-bound with either 3 µg rabbit IgG ( Santa Cruz Biotechnology Inc . ) , 3 µg of H3 ( ab1791 ) or 3 µg of H3K4me1 ( ab8895 ) antibodies from Abcam Inc . Immune complexes were washed sequentially with the following buffers for 2 min at room temperature: Wash B ( 1% Triton X-100 , 0 . 1% SDS , 150 mM NaCl , 2 mM EDTA , 20 mM Tris-HCl pH 8 ) , Wash C ( 1% Triton X-100 , 0 . 1% SDS , 500 mM NaCl , 2 mM EDTA , 20 mM Tris-HCl pH 8 ) , Wash D ( 1% NP-40 , 250 mM LiCl , 1 mM EDTA , 10 mM Tris-HCl pH 8 ) , and TEN buffer ( 50 mM NaCl , 10 mM Tris-HCl pH 8 , 1 mM EDTA ) . Following decrosslink by overnight incubation at 65°C in elution buffer ( 1% SDS , 50 mM Tris-HCl pH 8 , 10 mM EDTA ) , RNase A and proteinase K treatments , DNA was recovered on QIAquick PCR purification columns ( Qiagen ) . H3K4 monomethylation ChIP enrichment level was measured relative to H3 level by QPCR with Perfecta SYBR green PCR kit ( Quanta Bioscience ) for known CNS regions , Ifnγ promoter and an unrelated negative control ( Pomc gene promoter ) using the following primers: POMC For 5′aggcagatggacgcacataggtaa3′ and Rev 5′tccacttagaactggacagaggct3′ . CNS-54kb For 5′ agcctgactggcatattggcaaac 3′ and Rev 5′aaacctgaaggtcgtggcttgact 3′; CNS-34kb For 5′ acttctgaagacaggccacaggtt 3′ and Rev 5′acagctgagactgtggttgacact 3′; CNS-22kb For 5′ ggagatgggaagtcagatcaaag 3′ and Rev 5′ cagaaatttggcctcttaggttt 3′; CNS-6kb For 5′ tgtggacttccattctccacgtca 3′ and Rev 5′ cacgttggttgaactcctggaact 3′; IFNγ prom For 5′ atcacctccattgaagggcttcct 3′ and Rev 5′ ttctcatccacagagcacagcaca . 3′ . Thereafter H3K4me1/H3 levels were compared between P/I and mock treated cells . Splenocytes from B6 . H2-/- and m157- transgenic mice were labelled with 0 . 4 mM CFSE ( CFSE low ) in RPMI medium containing 5% FCS , and splenocytes from recipient mice were labelled with 4 mM CFSE ( CFSE high ) in RPMI containing 10% FCS . The splenocytes were then incubated at 37°C for 10 min and then washed three times in RPMI containing 10% FCS . Cells ( 5×106 ) of each type were mixed , and the mixture ( 200 µl ) was injected intravenously into recipient mice . After 18 hours , spleens were harvested and red blood cells were lysed . The relative percentage of cells in each CFSE population was measured by FACS as previously described [54] . GraphPad Prism software was used to conduct Student's t-test , ANOVA Significance was set at a P value of less than 0 . 05 .
|
Cytomegalovirus ( CMV ) is a ubiquitous herpesvirus that largely infects the human population leading to a significant cause of disease and death in the immunocompromised and elderly . The study of CMV in animal models has helped understand the pathogenic consequences of CMV infection and adds substantial understanding of the complex interplay of host and virus in living systems . Natural Killer ( NK ) cells have emerged as an important player during CMV infection trough their specific recognition of viral particles determinants and subsequent secretion of cytokines and cytolytic granules . In the present study , we have generated different mouse models to specifically investigate quantify viral recognition and cytokine expression by NK cells during CMV infection as a measure of NK cell function . We found that even after proper recognition of infected cells by NK cells , the adequate production of IFNγ is crucial to restrain viral infection . Moreover , we demonstrated that IFNγ production by NK cells is genetically determined and directly linked to the IFNγ locus . Hence , we provide the first evidence for of a unique mechanism of IFNγ production by NK cells which regulates susceptibility to viral infection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"infectious",
"diseases",
"infectious",
"disease",
"immunology",
"medicine",
"and",
"health",
"sciences",
"immune",
"evasion",
"major",
"histocompatibility",
"complex",
"genetics",
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"biology",
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"cytomegalovirus",
"infection",
"immune",
"response"
] |
2014
|
Specific Dysregulation of IFNγ Production by Natural Killer Cells Confers Susceptibility to Viral Infection
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Despite the seriousness of dengue-related disease , with an estimated 50–100 million cases of dengue fever and 250 , 000–500 , 000 cases of dengue hemorrhagic fever/dengue shock syndrome each year , a clear understanding of dengue pathogenesis remains elusive . Because of the lack of a disease model in animals and the complex immune interaction in dengue infection , the study of host response and immunopathogenesis is difficult . The development of genomics technology , microarray and high throughput quantitative PCR have allowed researchers to study gene expression changes on a much broader scale . We therefore used this approach to investigate the host response in dengue virus-infected cell lines and in patients developing dengue fever . Using microarray and high throughput quantitative PCR method to monitor the host response to dengue viral replication in cell line infection models and in dengue patient blood samples , we identified differentially expressed genes along three major pathways; NF-κB initiated immune responses , type I interferon ( IFN ) and the ubiquitin proteasome pathway . Among the most highly upregulated genes were the chemokines IP-10 and I-TAC , both ligands of the CXCR3 receptor . Increased expression of IP-10 and I-TAC in the peripheral blood of ten patients at the early onset of fever was confirmed by ELISA . A highly upregulated gene in the IFN pathway , viperin , was overexpressed in A549 cells resulting in a significant reduction in viral replication . The upregulation of genes in the ubiquitin-proteasome pathway prompted the testing of proteasome inhibitors MG-132 and ALLN , both of which reduced viral replication . Unbiased gene expression analysis has identified new host genes associated with dengue infection , which we have validated in functional studies . We showed that some parts of the host response can be used as potential biomarkers for the disease while others can be used to control dengue viral replication , thus representing viable targets for drug therapy .
Although dengue-related disease results in an estimated 50–100 million cases of dengue fever and 250 , 000 to 500 , 000 cases of dengue hemorrhagic fever/dengue shock syndrome each year [1] , [2] , a clear understanding of dengue pathogenesis remains elusive . Dengue virus is an enveloped , positive-stranded RNA virus of the Flaviviridae family transmitted by the mosquito Aedes aegypti and Aedes albopictus . Four serotypes of dengue virus ( DENV1-4 ) circulate in endemic areas . Although infection with one serotype of dengue virus confers life-long protective immunity to that serotype , it does not protect the host from infection with other serotypes [3] . The initial target cells during dengue infection are believed to be Langerhans cells [4] . Through means not yet fully understood , Langerhans cells spread the virus , via the lymphatic system , to other tissues such as liver , spleen , kidney and blood , whereas monocytes , macrophages and endothelial cells are the major cell types in which the virus replicates [5] . In the majority of symptomatic dengue infections , a fever of 5–7 days duration develops together with bone and joint pain , retro-orbital pain , nausea and fatigue , this is called dengue fever ( DF ) . While the majority of DF patients recover without intervention , 2–5% develop a more severe form of the disease , called dengue hemorrhagic fever/dengue shock syndrome ( DHF/DSS ) , characterized by thrombocytopenia and vascular leakage , causing hypervolemic shock and death if not promptly treated [6] . The cause of DHF/DSS is not clear . Antibody dependent enhancement ( ADE ) is the most widely supported theory explaining the higher risk of DHF/DSS associated with a heterologous secondary infection [7] . The phenomenon of T cell “original antigenic sin” has also been described [8] . Like many viruses , dengue inhibits IFNα and IFNβ signaling by suppressing Jak-Stat activation , resulting in reduced host antiviral response [9] . The combination of a reduced host defense , increased uptake of the virus and delayed viral clearance likely synergizes to produce higher viremia resulting in a more severe outcome . Because of the lack of a disease model in animals and the complex immune interaction in dengue infection , the study of host response and immunopathogenesis is difficult . The development of genomics technology has allowed researchers to study gene expression changes on a much larger scale . A summary of published microarray data from infection of different host cell types with bacteria , viruses , yeast , protozoa and helminthes revealed a common host-transcriptional-response consisting of a cluster of IFN-stimulated and immune mediating genes [10] . One particularly successful application of microarray technology was the identification of a novel drug target , c-kit , in endothelial cells infected with Kaposi's sarcoma-associated herpesvirus ( KSHV ) [11] . With regard to dengue infection , gene expression studies have been carried out in infected human umbilical vein endothelial cells ( HUVECs ) by differential display reverse transcription ( DD-RTPCR ) and Affymetrix oligonucleotide microarrays [12] . Genes having a role in the IFN antiviral response and immune defense such as 2′–5′ oligoadenylate synthetase ( OAS ) , myxovirus protein A ( MxA ) , TNFα , galectin-9 , phospholipid scramblase 1 and human inhibitor of apoptosis-1 ( IAP1 ) were shown to be upregulated upon infection [12] . Infection with dengue of a more transformed HUVEC-like cell line , ECV304 , was analyzed by a different microarray system containing 7600 cDNA oligonucleotides [13] . In this study , the expression of 15 genes involved in cell cycle , apoptosis , membrane trafficking and cytoskeleton was found to be altered after infection[13] . Using a different gene expression approach , primary macrophages infected with a clinical isolate of dengue were analyzed by a cytokine array containing 375 human cytokine-related genes with approximately 20 genes observed to be either up- or down- regulated [14] . However , the functional importance of these changes , if any , was not studied [14] . We have used Compugen human 19K oligonucleotide arrays to study the host response to dengue infection , initially in a human hepatocytic cell line ( HepG2 ) . We identified the upregulation of three major clusters of genes; NF-κB-mediated cytokine/chemokine responses , type I IFN response , and the ubiquitin-proteasome system . Increased expression of selected genes , identified by Compugen array , was confirmed using a taqman low density array ( TLDA ) and results extended to include an additional , readily infectable , cell line ( A549 ) and PBMC derived from adult dengue fever patients from a Singapore dengue prospective cohort study . Next we sought to confirm the functional effects of these upregulated genes . We confirmed the high levels of two novel chemokines , IP-10 and I-TAC , in dengue infection , in both cell lines and in dengue patients . We also determined that overexpression of viperin , an upregulated gene in the IFN pathway , and proteasome inhibition , with MG-132 or ALLN , reduced virus replication . In summary , we have used microarray analysis to identify new host genes associated with dengue infection , and to show that components of the host response can control dengue viral replication and therefore represent potential targets for drug therapy .
Cell lines , A549 , BHK-21 , C6/36 , HeLa , HepG2 , HUV-EC-C , K562 , SK-Hep1 and THP-1 , were obtained from ATCC and maintained as instructed . The type 2 dengue virus strain TSV01 was obtained from a dengue outbreak in Townsville , Australia [15] ( GenBank , accession number AY037116 ) and was propagated in the C6/36 cell line . Heat-inactivated virus was prepared by incubating virus samples in a 55°C water bath for 1 hr . Each cell line was infected with dengue virus at a multiplicity of infection ( MOI ) of 1 and 10 for 3 , 6 , 12 , 24 , 48 , and 72 hrs before being evaluated for replication efficiency by plaque assay . Infection of cell lines was not continued beyond 72 hrs as after this point a significant degree of cell death became apparent . BHK-21 cells were cultured overnight in 24 well plates before media was removed and serial dilutions ( 10-fold ) of virus culture supernatants added to individual wells . Plates were incubated for 1 hr before media was aspirated and replaced with 0 . 5 ml of 0 . 8% methyl-cellulose medium ( with 2% FBS ) . Plates were then incubated for 5 days before the media was removed and cells fixed in 4% formaldehyde for 20 min , rinsed in water , stained with crystal violet for 20 min then rinsed again . Plaques were counted manually and concentrations of plaque forming units per ml ( pfu/ml ) in the cell culture supernatant calculated . For drug intervention studies , HepG2 cells were treated with compound , or DMSO , at the indicated concentration and time . While the culture supernatants were collected for plaque assay , cytotoxicity in HepG2 cells was monitored using fluorescein diacetate ( FDA , Acros Organics , Belgium ) , 10 µg/ml added to cells for 25 min at room temperature , and measured using a fluorescent plate reader ( 485 nm excitation/535 nm emission ) . Dengue E-protein was assessed in suspension HepG2 cells by intracellular staining and fluorescence activated cell sorter ( Becton Dickinson , USA ) and an Alexa-647 conjugated ( AlexaFluor conjugation kit , Invitrogen , USA ) monoclonal antibody ( 4G2 , ATCC ) . Cells were scraped and permeabilized using BD FACS Perm/Wash solution ( Becton Dickinson , USA ) and acquisition and analysis was performed using CellQuest software ( Becton Dickinson , USA ) . RNA was extracted from infected cells using the RNeasy Mini Kit ( Qiagen , Netherland ) . Dengue serogroup 2 virus TSV01 detection by TaqMan PCR was adapted to the ABI7900 real time instrument using previously published primers and probes [16] . Standard ABI conditions were used , incorporating primers at 900nM . Quantification was achieved by relating viral Ct value to the Ct value on a standard curve of a measured number of copies of a 750 bp section of the virus ( forward: 5′-AAAGATCAGTGGCACTCGTTCC-3′ and reverse: 5′-GCAGGTCTAAGAACCATTGCCT-3′ ) , cloned into pCR2 . 1-TOPO ( Invitrogen , USA ) . Human arrays of 19 , 800 60mer oligonucleotide probes ( representing 18861 genes ) , designed by compugen and manufactured by Sigma-Genosys were used according to the standard protocol described for cDNA microarray [17] . Dye swap was performed for each sample , at every time point and a rigorous quality check was performed before an array was used for downstream analysis [18] . 60 mer oligonucleotide probes were spotted onto poly-L-lysine-coated microscope slides using GeneMachines OmniGrid Microarray Spotter ( USA ) . For fluorescence labeling of target cDNAs , 20 µg of total RNA from universal human reference ( Strategene , USA ) and experiment samples ( RNA extracted from infected cells using Qiagen RNeasy Mini Kit ) were reverse transcribed in the presence of Cy3-dUTP and Cy5-dUTP ( Amersham Biosciences , UK ) using the Superscript reverse transcription kit ( Invitrogen , USA ) . Labeled cDNA were pooled , concentrated , re-suspended in DIG EasyHyb ( Roche , Switzerland ) buffer and hybridized overnight ( 14-16h ) in the MAUI Hybridization chamber ( BioMicro , USA ) . The arrays were scanned using a GenePix 4000B Scanner ( Axon Instruments , USA ) to generate Tiff images . The images were analyzed by GenePix Pro 4 . 0 software ( Axon Instruments , USA ) to measure Cy3 and Cy5 fluorescence signals intensity and format data for data base deposition . The array data then underwent lowess normalization [19] available in an R package aroma to remove channel specific biases ( R Development Core Team ) . Differentially expressed genes were selected using a procedure known as Significance Analysis of Microarrays ( SAM ) [20] , described in brief below . The statistic used in SAM is given as where; the numerator is the group mean difference , s the standard error , and s0 a regularizing constant . Setting s0 = 0 will yield a t-statistic . This value , called the fudge constant , is found by removing the trend in d as a function of s in moving windows across the data to reduce false positive results . As the statistic is not t-distributed , significance is computed using a permutation test . Genes with a computed statistic larger than the threshold were considered significant . The false discovery rate ( FDR ) associated with the given threshold can also be calculated from the permutation data . RNA was extracted using RNase Easy kit ( Qiagen , Netherland ) from infected cells . For patients blood samples ( see Patient Samples ) , 2 . 5 ml of blood was collected in PAXgene tubes , RNA was extracted using PAXgene Blood RNA Kit ( PreAnalytiX , Qiagne , Netherland ) . RNA was subjected to DNase treatment using an RNase-Free DNase Set ( Qiagen , Netherland ) . 100 ng of total RNA was reverse transcribed using the High-Capacity cDNA Archive Kit ( ABI , USA ) and processed for TaqMan Micro Fluidic Cards ( 3M Company , ABI , USA ) according to manufacturers instructions , together with data analysis using SDS2 . 2 software ( ABI , USA ) . Differentially expressed genes were detected as above , using SAM . We analyzed SAM gene lists using the Applied Biosystem online program PANTHER [21] ( http://www . pantherdb . org/ ) . Pathway , interaction and Gene Onotology analysis was performed using MetaCore , version 3 . 2 . 0 ( GeneGo , Inc , USA ) . Subjects were enrolled from the Early DENgue ( EDEN ) study , a dengue investigation conducted at a primary healthcare clinic in Singapore , for which local ethical approval had been granted , and informed consent from patients obtained . Participation required a PCR diagnosis of fever with duration less than 3 days ( for the details of the PCR diagnosis , see [22] ) . The enrolled dengue cases were either of serotype 1 or 3 . Ten dengue positive subjects ( n = 10 , 3 males ) were selected to represent the most severe cases of dengue by the criteria of a platelet counts below 30 ( x 103/µl; range 8–30 , mean 20 . 5 ) . Their mean age was 43 . 2 years ( range 24–67 ) . The mean fever was 38 . 3°C ( range 37 . 7–39 . 1 ) at the first visit ( Time Point 1 ) , with a mean duration of 43 hours ( range 14–72 ) from the onset of the fever . The second visit ( Time Point 2 ) occurred at 80 to 96 hours after the first visit , mean fever was 37 . 1°C ( range 36 . 2–38 . 7 ) . Dengue negative patients were enrolled with the same criteria ( fever with no respiratory infection symptoms ) , but were PCR negative for dengue . Ten subjects were taken with ( n = 10 , 4 males ) a mean age of 43 . 2 years old ( range 24–67 ) . Their mean fever was 38 . 4°C ( range 37 . 6–39 . 4 ) with a mean duration 27 hrs ( range 8–60 ) at the first visit ( Time Point 1 ) . The convalescence sample was collected at the third visit which was 3 to 4 weeks later ( Time Point 3 ) . At each time point , a 2 . 5 ml blood sample was collected in PAXgene tubes for RNA analysis . A 10 ml blood sample was collected , serum was separated within 5 hrs and stored at −80°C . Serum IP-10 and I-TAC concentrations were measured using ELISA kits from R&D Systems as per manufacturers instructions . A549 cells were transfected with an expression construct encoding viperin using lipofectamine 2000 ( Invitrogen , USA ) . Cells were selected using 500 µg/ml G418 and screened for viperin expression by immunoblotting . Cells were cultured overnight in 6 well plates before IFNβ ( Glycoferon , Singapore ) , at a final concentration of 500 U/ml , was added to each well while control wells remained untreated . Twelve hours post IFNβ treatment , cells were infected with dengue virus ( TSV01; MOI 1 ) for 48 hrs and the plaque assay was used to determine virus production .
While a number of different cell lines have been used as models for dengue infection it is not clear which of these represents the most appropriate model for the analysis of host response by microarray , which requires a high rate of infection . As such , we screened seven human cell lines for their ability to support replication of dengue virus . We used the clinical , dengue serotype 2 isolate TSV01 ( Accession number: AY037116 ) strain for infection . Human cell lines were ranked by maximum plaque forming units ( pfu ) /ml titer produced with A549>HepG2>SK-Hep1>K562>HUV-EC-C>THP-1>HeLa ( data not shown ) . The same results were obtained with the widely used NGC strain ( data not shown ) . The highest yielding cell lines A549 ( a lung carcinoma ) and HepG2 ( a hepatoma cell line ) were used in further studies , with HepG2 as the primary focus because of evidence of liver injury in DHF/DSS and the detection of dengue antigens in hepatocytes in liver [23] , [24] . Viral replication in HepG2 cells infected with dengue virus TSV01 for 3 , 6 , 12 , 24 , 48 and 72 hours , compared to heat inactivated virus , was determined by plaque assay of the virus released in the cell culture medium ( Figure 1A ) , FACS analysis of infected cells labeled intracellularly with an Alexa 674-conjugated antibody against dengue E protein ( 4G2 ) ( Figure 1B ) and real-time PCR analysis of viral RNA ( Figure 1C ) . All three methods showed that new viral replication began after 24 hours and reached a plateau at 72 hrs , with FACS analysis showing 28% of cells infected at this point . After 72 hrs a degree of cell death become apparent ( data not shown ) and the experiment was not continued . Analysis of microarrays , performed in duplicate ( dye-swapped ) on three biological replicates at each time point , comparing infectious with heat inactivated virus; using a SAM q value ( false discovery threshold ) of 25% , revealed no significantly differentially expressed genes at 3 , 6 , 12 or 24 hrs post infection . However , there were 24 transcripts identified at 48 hrs and 124 at 72 hrs ( a total of 132 transcripts representing 124 genes; Table S1 ) that were differentially expressed . At both 48 hrs and 72 hrs , clustering of transcripts using PANTHER analysis identified the IFN-mediated immunity pathway as the most significant with a P value of 10−15 ( at 72 hrs ) . Genes that are typically induced after type I IFN stimulation , including OAS1 , OAS2 , OAS3 , OASL , STAT1 , STAT2 , MX1 , IFIH and IFNβ , featured prominently in this cluster ( Figure 2 and Table S1 ) . Further analysis of the 124 genes suggested the involvement of NF-κB-mediated cytokine/chemokine responses ( NFKBIB , NFKB1A , TNFA1P , CCL4 , CCL5 , IP-10 and I-TAC amongst others ) and ubiquitin related genes ( HERC5 , HERC6 , UBE2L6 , USP15 and others ) ( Figure 2 ) . Although not completely overlapping , a core host response to pathogen involving the IFN response and the NF-κB-mediated immune defense response [10] was observed in our array results . Other genes that were significantly changed included those associated with cell signaling , lipid metabolism , cell cycle and vesicular transport ( Table S1 ) . We did not detect any significantly down regulated genes in our system . All the microarray data were deposited in a public database accessible at http://www . ncbi . nlm . nih . gov/projects/geo ( accession number is GSE6048 ) . With the evidence of upregulation of three major pathways ( NF-κB , IFN and ubiquitin ) by microarray , we decided to pursue these pathways with further confirmation and validation . Firstly , we chose 59 genes from the three major pathways that were upregulated in the HepG2 cell line as shown by microarray . Secondly we selected another 36 genes which had a functional association with these pathways or might otherwise be associated with dengue infection . A Taqman Low Density Array ( LDA ) was then constructed for these 95 genes in order to confirm their expression by quantitative real time PCR . Results for the HepG2 cell line indicated that there was again no significant difference between infectious and heat-inactivated virus at the 24 hr time point post-infection . At 48 hrs 31 of the 95 genes were differentially expressed , and at 72 hrs 62 of the 95 genes were differentially expressed ( Table S2 ) , indicating a high rate of validation of the genes detected by microarray . In order to exclude gene responses that were specific to the HepG2 cell line alone , we decided to test the expression level of these genes in the A549 cell line using the same LDA . In the A549 infection model , plaque assay revealed that peak viral production occurred earlier than in the HepG2 model ( 1 . 1×105±1 . 4×104 pfu/ml at 48 hrs ) but was still substantial at 72 hrs post-infection ( 7 . 3×104±3 . 8×104 pfu/ml ) . The quantitative PCR also revealed a higher number of differentially expressed genes , with 63 genes at the 48 hr time point and 82 genes at the 72 hr time point ( Table S2 ) . Seeking confirmation that these genes were relevant in a physiological setting , we sought to test these genes in dengue patients . Whole blood RNA samples were obtained from ten adult fever patients ( age >21 years old ) enrolled in the Singapore Early Dengue ( EDEN ) cohort study in 2005 [22] . Each was PCR diagnosed positive for either dengue serotype 1 or 3 and all showed typical dengue fever symptoms . At the second visit ( ∼5 days after onset of fever , onset of fever considered day 1 ) , their platelet count had dropped below 30 ( x 103/µl; range 8–30 , mean 20 . 5 ) , and they were admitted to hospital . When these patient samples were tested for expression of the 95 selected genes by LDA , 67 genes were shown to be differentially expressed comparing blood samples taken at acute fever stage ( first visit , 1–3 days after onset of fever ) to convalescence ( third visit , 3–4 weeks after first visit ) ( Table S2 ) . After confirmation of the expression of certain genes in two different dengue-infected cell lines and in dengue patients , we selected those that were upregulated in at least one time point in HepG2 cells and in at least one time point in A549 cells and in dengue patient samples ( comparing acute to convalescent blood samples ) . Fifty genes fulfilled these criteria ( Table S2 ) and , we felt , represented common genes involved in dengue virus response , or virus replication , while excluding responses that were cell type specific . These 50 common genes were mapped by direct interactions using the MetaCore program which illustrated the close clustering and interconnectedness of a network of 29 of genes around NF-κB , TNF-α and STAT1 . ( Figure 3A ) . The NF-κB gene alone was added to the network , despite not being from our common list , to illustrate the connections between those induced by it . For example , the upregulation of IP-10 , I-TAC , VEGF , PAI1 , B2M , TNFAIP3 and RIG-1 could all be linked to the activation of NF-κB , while NFKB1B and NFKB1A , two feedback control genes for NF-κB activation , were also upregulated reflecting the self containment of this activation ( Figure 3A ) . The degree of upregulation varied between the genes in this pathway with I-TAC and IP-10 being the most highly up-regulated ( average expression in the two cell types and patients ) genes ( Figure 3B ) . A number of genes clustered around STAT1 were associated with the IFN pathway , and examination of the common list revealed another four genes ( viperin , IFI44 , IFIH1 , G1P3 ) related to the IFN pathway that were upregulated but not mapped by the MetaCore program ( Figure 3C ) . Finally , a number of genes related to the ubiquitin-proteasome pathway also appeared on the MetaCore map ( HERC5 , USP18 and Hdm2 ) with several more ( unmapped ) genes appearing on the common list ( Figure 3D ) The two most highly upregulated common genes from the NF-κB pathway were IP-10 ( or CXCL10/IFN-inducible protein 10 ) and I-TAC ( or CXCL11/IFN-inducible I cell α chemoattractant ) ( Figure 3B ) . In order to determine if this up-regulation of gene transcription lead to translation and protein release , concentrations of IP-10 and I-TAC protein in cell culture supernatant following dengue infection were determined by ELISA . In both the A549 and HepG2 infection models , dengue infected cells produced moderate , but significant ( compared to heat-inactivated virus treated cells ) , concentrations of IP-10 ( Figure 4A ) and I-TAC ( Figure 4B ) at 72 hrs , but not at earlier time points ( data not shown ) . We next investigated if these , or other , NF-κB induced proteins were influencing dengue virus replication . Adding dexamethasone to the HepG2 infection model to inhibit NF-κB activation [25] prevented IP-10 and I-TAC production , but had no effect on viral replication ( data not shown ) . These results suggest that NF-κB activation , and IP-10 and I-TAC production , do not have a direct effect on viral replication and are , rather , simply part of the immune response to infection . Serum concentrations of IP-10 and I-TAC in the ten dengue fever patients described above , together with ten fever patients who did not have dengue ( viral PCR negative ) were also determined by ELISA . High concentrations of IP-10 ( Figure 4C ) and I-TAC ( Figure 4D ) were present in the serum of dengue fever patients . There was significantly more IP-10 in the serum of the patients during the first ( 1–2 days after fever onset ) and second ( 4–5 days after fever onset ) visits , compared to the convalescent serum ( P = 10−15 and P = 10−11 , respectively ) as well as to non-dengue fever patient serum ( P = 10−9 and P = 10−7 , respectively ) . I-TAC level was also significantly higher in first visit dengue patient serum comparing to both the convalescent ( P = 10−7 ) and non-dengue fever ( P = 10−6 ) patients . I-TAC levels in dengue fever patients at the second visit were significantly lower than at first visit ( Fig 4D ) . We detected a large number of IFN response genes induced in both cell line infections and in dengue patients ( see Figure 3C ) . In our study , viperin was one of the most highly upregulated genes in the type I IFN response pathway . Viperin has previously been identified as an IFN-induced anti-viral protein in HCMV and HCV infection [26] , [27] . In order to investigate the role of viperin in dengue infection , we used an established A549 cell line stably overexpressing viperin ( Vip ) [26] . Comparing to infection in wild type A549 cells ( WT ) , viperin overexpressing cells were significantly resistant to viral replication , as shown by plaque assay two days after infection ( Figure 5A ) , with and without pre-treatment with IFNβ ( +IFN; 500 U/ml ) . Although pre-treatment with IFNβ had the greater anti-viral effect , viperin over expression alone resulted in a small , but significant , reduction in virus production both with ( P = 0 . 038 ) and without ( P = 0 . 0004 ) IFNβ pre-treatment . These results suggest that viperin is an functional component of the IFN-mediated response to dengue , and demonstrate , for the first time , that viperin could be part of the anti-dengue response . Ubiquitination , another pathway identified in our list of common genes , is a key component of the immune system , the conjugation of single , or multiple , ubiquitin molecules to a protein targets it for defined subcellular localization , or destruction in the proteasome [28] . Components of the ubiquitin-proteasome system have been shown to be required for the maturation and release of a number of viruses ( see review [29] ) . In order to investigate the role of ubiquitin-proteasome system in dengue infection , we introduced proteasome inhibitors , MG-132 and ALLN , to the HepG2 dengue infection model [30] . At lower concentrations , both MG-132 and ALLN significantly reduced virus replication in the cell lines by over 50% ( Figure 5B ) . An examination of the effects of these compounds on the integrity and viability of inhibitor-treated cells using fluorescein diacetate revealed no cytotoxicity at these concentrations ( Figure 5C ) . Higher concentrations of the inhibitors had an even greater effect ( >90% reduction in pfu/ml ) but with a degree of cytotoxicity ( Figures 5B , 5C ) .
Despite the fact that dengue is a major disease affecting the tropical world , little is known of its pathogenesis due , partly , to the lack of a suitable animal model and the complex cell interactions in infected individuals . Using microarray analysis of gene expression and high throughput quantitative real-time PCR , we investigated the host response to dengue infection in cell lines and in DF patients . We further validated our microarray results by functional study of the identified genes . Although dendritic cells , Langerhans cells and monocytes have been proposed as the principle reservoirs of viral infection [4] , it is not clear which other tissues , if any , are targeted . Immunohistochemistry and in-situ hybridisation studies of biopsies from DHF patients have indicated that a range of tissues are infected by the virus , including cells in the liver , spleen , lung , kidney and peripheral blood [5] . We chose the HepG2 cell line as the primary cell model for this study as it readily supported viral replication , and it is derived from the liver , which might be of some clinical relevance . The A549 cell line was included as it was also an excellent supporter of viral replication even though there is , presumably , little or no clinical relevance . The final clinical relevance came from the validation of the genes in 10 DF patients from the Singapore EDEN cohort . The 10 patients were selected based on low platelet count , because of the lack of WHO DHF/DSS manifestation in Singapore adult patients . Despite the limited sample number , and the wide range of collection times , variation between individuals at the same time point was ruled out by statistical analysis . We believe that with more patients , more genes that are differentially expressed would be identified . The overlap of upregulated genes , determined by quantitative PCR , in the two cell systems and in patients removed any responses that were unique to the cell type . In fact , we observed cell type specific gene changes such as IL-8 , PAI-1 and RANTES that were upregulated in the cell lines but not the patient samples while the anti-inflammatory cytokine IL-10 was upregulated in the patient samples but not the cell lines , indicative of the effects of multiple cell types in an in vivo system . Similarly , IFNβ was upregulated in the cell lines while IFNγ was in patient samples . However , it is the large overlap between the in vitro infection and patient samples that warrants most attention . The two most highly upregulated chemokines were IP-10 and I-TAC . IP-10 and I-TAC are both ligands for the CXCR3 chemokine receptor and the production of these chemokines leads to the recruitment of CXCR3 expressing T cells and NK cells [31] , [32] . Increased IP-10 and I-TAC expression has been seen in various viral infections , especially viral meningitis [33] . In SARS patients , elevated IP-10 early in infection was shown to be a predictor for a more severe outcome [34] . Neuronal IP-10 was shown to be involved in the recruitment of T cells in West Nile virus encephalitis [35] . Elevated I-TAC mRNA and protein has also been found in the liver of chronic Hepatitis C patients [36] . In dengue infection , various chemokines have previously been found to be induced in dengue patients , including IL-8 , MIP-1α , MIP-1β , RANTES and MCP-1 , but IP-10 and I-TAC have not been examined ( see review [37] ) . In a dengue intracerebral mouse infection models , CXCR3−/− and IP10−/− mice both had higher mortality rate than wild type mice after infection , indicating that IP-10 and CXCR3 receptors are part of the host defense mechanism , most likely in recruitment of T cells to the infection site [38] . IP-10 was also proposed to compete with virus binding on the receptor in vitro [39] . However , the relevance of this study to human patients is not clear . Although IFNγ , α/β and NF-κB could all induce the production of IP-10 and I-TAC , prevention of IP-10 and I-TAC via NF-κB inhibition clearly reduced the IP-10 level in HepG2 cells . Furthermore , IFNβ and IFNγ were not consistently upregulated in the two cell lines or in DF patients in our study ( data not shown ) . Therefore , we believe that NF-κB activation rather than IFN induction played the major role in elevated IP-10 and I-TAC in dengue infection . The inhibition of NF-κB , and consequent IP-10 and I-TAC inhibition , had no demonstrable effect on dengue replication in cell lines , suggesting the more complex role for these chemokines in a multi-cellular in vivo setting . Concentrations of each chemokine were significantly higher during the early stages of dengue fever , while I-TAC levels were reduced at the second visit , IP-10 levels remained high . The persistently high level of IP-10 might also contribute to the immunopathogenesis of dengue although this would require further investigation . It may be that concentrations of IP-10 and I-TAC , in combination with a viral antigen , could be used as an early marker for dengue fever . It is interesting to note that the level of IP-10 and I-TAC were independent of previous history of dengue infection , as half of the ten tested patients were suffering from a secondary infection . The common clinical feature of the ten selected patients was the low platelet count at second visit . Because of the lack of severe dengue cases ( by WHO definition ) in Singapore , the low platelet count was used as the measure of severity by which the ten patients from the cohort study were classified as having more severe dengue fever . We cannot at this point make a link between the level of IP-10 , I-TAC and disease severity because of the small number of cases used in this study , a more detailed clinical study , currently underway , aims to determine if the concentrations of IP-10 and I-TAC during early stages of infection are linked to the progression to more severe forms of disease . The ability of IFN pre-treatment to inhibit subsequent dengue replication has been previously reported [9] , [40] , as has the importance of IFN in the anti-viral response [41] . Our results indicated that viperin was one of the most highly upregulated genes in all models following dengue infection . Viperin encodes for an IFN-inducible antiviral protein shown to be associated with the endoplasmic reticulum and redistributed to the Golgi apparatus and cytoplasmic vacuoles following human cytomegalovirus ( HCMV ) infection [26] . The induction of viperin has been suggested to be anti-viral in both HCMV [26] and hepatitis C ( HCV ) [27] infections , but this is its first association with dengue infection . The use of viperin overexpressing A549 cells demonstrated that , in addition to being significantly upregulated during infection , viperin is directly involved in the anti-viral response to dengue , as shown by the suppression of dengue replication in the presence of increased expression of viperin . This effect was not as significant as the effect of IFNβ alone suggesting that viperin is only a part of the IFN-mediated response to dengue . The molecular mechanism of the action of viperin to counter dengue infection will need to be further studied . The ubiquitin-proteasome system is the cellular machinery involved in the conjugation of single or multiple ubiquitin molecules to direct protein trafficking or degradation ( reviewed in [28] ) . In HCV infection , E6AP ubiquitin ligase was reported to mediate the ubiquitination and degradation of the virus core protein [42] . HCV polymerase has also been shown to interact with a ubiquitin-like protein leading to its degradation [43] . In dengue , ubiquitin-proteasome genes have not been reported to be involved in the dengue virus life cycle although a recent publication has shown that dengue envelope protein interacts with SUMO-1 conjugating enzyme 9 ( Ubc9 ) and that overexpression of Ubc9 reduces virus production in a cell line [44] . Our TLDA results indicated that there was significant upregulation of a number of ubiquitin-proteasome system related genes during dengue virus replication but it was unclear if this response was anti-viral or if the dengue virus utilised components of the ubiquitin-proteasome system for replication . Use of proteasome inhibitors , MG-132 and ALLN , significantly reduced the release of dengue virus following infection of the HepG2 cell line . Previously , it has been shown that the effect of proteasome inhibitors may be virus specific with these compounds less ( or non- ) effective against virus such as influenza [45] and equine infectious anemia virus [46] . The effect of proteasome inhibition on viral replication appears to be mediated via a number of different processes including the involvement of ubiquitin or the proteasome in virus assembly [45] , budding [47] and release and maturation [48] . Further studies may elucidate the exact role the ubiquitin-proteasome plays in dengue virus replication which may involve trafficking of the virus to the plasma membrane or the maturation and fusion of the virus upon release [49] . It is instructive to compare our results with those of a published microarray study investigating host responses in patient blood [50] . That study identified genes whose protein products are expressed in the ER to be the most significantly enriched , which directly overlaps with our identification of the ubiquitin pathway; specifically including UBE2 and the PSMB genes . This may represent a process fundamental to viral replication in any system . In addition , Simmons et al . described host responses associated with dengue shock syndrome that clearly overlap with our interferon related gene list . In particular , G1P genes , OAS genes , IFI genes and Mx genes were found in both studies , suggesting that the amount of viral replication may be directly related to clinical outcome . Gene arrays of a number of cell systems during dengue infection revealed many genes , and host response pathways , that were upregulated during dengue infection . Further functional analyses distinguished between host response pathways involved in initiating an innate signaling response ( NF-κB mediated genes and IFN pathway ) and those involved in virus replication ( ubiquitin-proteasome system ) . Specific components of the response to virus , such as viperin and IP-10 and I-TAC have been implicated in dengue infection for the first time . Further investigation of these components , together with the precise role of the ubiquitin-proteasome system in virus replication , may lead to drug targets for dengue . The use of gene array in multiple cell systems to investigate genes involved in virus replication , used in concert with functional studies , has proved to be a valid approach for discovery of novel markers and genes for understanding the host response to dengue and , ultimately , therapeutics against dengue .
|
Dengue is the most prevalent mosquito-born viral disease affecting humans , yet there is , at present , no drug treatment for the disease nor are there any validated host targets for therapeutic intervention . Using microarray technology to monitor the response of virtually every human gene , we aimed to identify the ways in which humans interact with dengue virus during infection in order to discover new therapeutic targets that could be exploited to control viral replication . From the activated genes , we identified three pathways common to in vitro and in vivo infection; the NF-κB initiated immune pathway , the type I interferon pathway , and the ubiquitin proteasome pathway . We next found that inhibiting the ubiquitin proteasome pathway , or activating the type I interferon pathway , resulted in significant inhibition of viral replication . However , inhibiting the NF-κB initiated immune pathway had no effect on viral replication . We suggest that drugs that target the ubiquitin proteasome pathway may prove effective at killing the dengue virus , and , if used therapeutically , improve clinical outcome in dengue disease .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"infectious",
"diseases/neglected",
"tropical",
"diseases"
] |
2007
|
Host Gene Expression Profiling of Dengue Virus Infection in Cell Lines and Patients
|
The hepatitis C virus ( HCV ) p7 protein is critical for virus production and an attractive antiviral target . p7 is an ion channel when reconstituted in artificial lipid bilayers , but channel function has not been demonstrated in vivo and it is unknown whether p7 channel activity plays a critical role in virus production . To evaluate the contribution of p7 to organelle pH regulation and virus production , we incorporated a fluorescent pH sensor within native , intracellular vesicles in the presence or absence of p7 expression . p7 increased proton ( H+ ) conductance in vesicles and was able to rapidly equilibrate H+ gradients . This conductance was blocked by the viroporin inhibitors amantadine , rimantadine and hexamethylene amiloride . Fluorescence microscopy using pH indicators in live cells showed that both HCV infection and expression of p7 from replicon RNAs reduced the number of highly acidic ( pH<5 ) vesicles and increased lysosomal pH from 4 . 5 to 6 . 0 . These effects were not present in uninfected cells , sub-genomic replicon cells not expressing p7 , or cells electroporated with viral RNA containing a channel-inactive p7 point mutation . The acidification inhibitor , bafilomycin A1 , partially restored virus production to cells electroporated with viral RNA containing the channel inactive mutation , yet did not in cells containing p7-deleted RNA . Expression of influenza M2 protein also complemented the p7 mutant , confirming a requirement for H+ channel activity in virus production . Accordingly , exposure to acid pH rendered intracellular HCV particles non-infectious , whereas the infectivity of extracellular virions was acid stable and unaffected by incubation at low pH , further demonstrating a key requirement for p7-induced loss of acidification . We conclude that p7 functions as a H+ permeation pathway , acting to prevent acidification in otherwise acidic intracellular compartments . This loss of acidification is required for productive HCV infection , possibly through protecting nascent virus particles during an as yet uncharacterized maturation process .
Hepatitis C virus ( HCV ) primarily infects human hepatocytes and results in a severe liver disease manifested by chronic inflammation , progressive fibrosis and development of hepatocellular carcinoma . The virus is highly successful in evading the host innate and adaptive immune systems [1] . HCV is highly heterogeneous , leading to genotypic-dependent variations in pathogenic manifestations and responsiveness to antiviral therapy . Standard HCV therapy , consisting of interferon and ribavirin , is only partially successful . Therefore , there is great interest in the development of new classes of antiviral agents . The HCV p7 protein is a potential antiviral target . It is not required for viral RNA replication in cell culture , yet is essential for HCV infectivity in chimpanzees [2] . It is a member of a class of viral permeability altering proteins termed “viroporins” . Viroporins are small , virally-encoded proteins that , once inserted into cellular membranes , homo-oligomerize to form pores increasing permeability to ions and small molecules [3] , [4] . In many cases , this channel activity is essential for viral propagation and infectivity . Other known viroporins include human immunodeficiency virus type 1 ( HIV-1 ) Vpu , dengue virus M protein , influenza A virus M2 protein , and poliovirus 2B [3] , [4] . The p7 protein is a small trans-membrane protein possessing two hydrophobic membrane-spanning regions separated by a short basic loop which is conserved amongst HCV genotypes [5] , [6] . HCV p7 forms a multimeric ion channel in artificial bilayers that is preferentially permeable to cations [7] , [8] , [9] yet has never been shown to act as an ion channel in biological membranes . Viroporins play vital roles in cellular entry and/or exit of several viruses including the close relative of HCV , bovine viral diarrhea virus ( BVDV ) , where its homologous p7 protein is required for infectious virus production [10] . The well characterized M2 viroporin of influenza virus plays roles both during viral entry and egress . During entry , the M2 proton channel shunts H+ from the acidic endosome to the virion interior , initiating uncoating of the genome and so allowing RNA replication . In certain subtypes , M2 also equilibrates the intraluminal pH of the trans-Golgi network with the cytoplasm , preventing premature conformational changes in the viral haemagglutinin ( HA ) during exit ( reviewed in [11] , [12] , [13] , [14] ) . While HCV p7 is clearly essential for efficient infectious particle formation , its exact function in the viral lifecycle is unknown . Similarly to the situation for M2 , p7 has been proposed to cause a proton ( H+ ) leak preventing acidification during the exocytosis of viral particles and we have previously demonstrated its ability to replace M2 in protecting HA from low pH [15] . It has thus been suggested that p7 is primarily involved in the late phase of the virus lifecycle , where it is required for the efficient release of infectious virions [16] . However , like other viroporins it is likely that p7 has multiple functions and recent evidence suggests that p7 may be involved in the earlier stages of virus production as well [17] . Moreover , mutation complementation analysis suggests that p7 interacts directly with both other viral proteins as well as host proteins essential for infectious virus production [18] . The role of p7 in the HCV lifecycle therefore remains controversial . This problem is exacerbated by the finding that amantadine , an inhibitor of the ion channel activity in p7-containing artificial lipid bilayers , is required at much higher concentrations to inhibit virus production in culture . It is further not known whether the presence of p7 is sufficient to alter pH gradients across intracellular membranes or whether p7 inhibitors efficiently block this conductance in a native system . Here , we describe a new method allowing the H+ conductance of p7 to be evaluated in native , intracellular membranes and in live cells . Importantly , we specifically show that this ion channel activity is necessary for infectious virus production in culture . The results demonstrate that , when exposed to a sudden pH shift , intracellular p7-containing vesicles equilibrate pH more rapidly than vesicles lacking p7 , and this activity can be blocked by p7 inhibitors in a genotype-specific manner , as seen previously [19] . The presence of p7 in Huh-7 . 5 cells resulted in a loss of vesicular compartment acidification , which was not observed in cells expressing the inactive p7 mutant , p7K33A/R35A ( p7KR ) . Furthermore we show that , while viral genomes containing p7KR are unable to support infectious virus production , infectivity can be partially rescued either by preventing vesicle acidification using bafilomycin , or by complementation with influenza A M2 protein . Finally , we show that intracellular infectious virus particles display greatly increased acid sensitivity compared to extracellular virions , which were unaffected by incubation at pH 4 . 0; the same pH reduced intracellular infectivity by ∼100-fold . These data support the notion that p7 prevents H+ gradient development and that this step is a necessary part of the viral lifecycle .
FLAG-p7 was expressed in 293FT cells and its subcellular localization was assessed by cell fractionation . Cells were subjected to differential centrifugation as described in Materials and Methods yielding a 3 , 000× g pellet , 3 , 000× g supernatant and 120 , 000× g vesicle pellet . Confirming previous results [20] , Fig . 1A , left panel , demonstrates that p7 was present in the 3 , 000× g heavy membrane pellet which also contained endoplasmic reticulum ( ER ) , mitochondria and lysosomes as evidenced by the markers PDI , GRP75 and LAMP-2 . The 120 , 000× g light membrane vesicle pellet also contained p7 , lysosomes and ER and was subsequently used to measure proton ( H+ ) permeability . HCV p7 contains two hydrophobic trans-membrane regions separated by a short basic loop that has been suggested to be necessary for p7 ion channel activity [15] , [16] and insertion into artificial lipid bilayers [21] , [22] . This loop is conserved amongst HCV genotypes , further suggesting that it plays a role in p7 function . To confirm that mutation of these residues does not alter its expression , lysates from FLAG-p7KR mutant-expressing cells were analyzed . Differential centrifugation of the membrane fractions showed a similar distribution of the mutant p7 to that of wild-type p7 , showing that mutation of the loop region did not alter its localization or expression ( Fig . 1A , right panel ) . In order to measure the proton permeability properties of p7 in native intracellular vesicles , we used the membrane impermeant pH-dependent fluorophore 8-hydroxypyrene-1 , 3 , 6-trisulfonic acid ( HPTS ) . This compound can be used as a ratiometric pH indicator with a near-linear response between pH 7 . 0 and 8 . 0 ( Fig . 1B ) . Isolated membrane vesicles ( 120 , 000× g pellet ) were loaded ex vivo with HPTS and purified from free dye using a Bio-Gel P-10 size exclusion column as described in Materials and Methods . HPTS-loaded vesicles exited in the void volume and were detected as a small peak in fluorescence which corresponded to a high molecular weight protein peak ( Fig . 1C , left panel , bars ) that exited well before the bulk of the fluorophore eluted from the column ( Fig . 1C , right panel , circles ) . Unloaded vesicles had no intrinsic fluorescence ( data not shown ) . Adding Triton X-100 ( final concentration of 0 . 5% ) to the loaded vesicle homogenate prior to column purification resulted in complete HPTS release ( Fig . 1D ) . This confirmed the intra-vesicular localization of fluorophore . To assess vesicular H+ conductance , we measured the fluorescence response of intra-vesicular HPTS to a sudden increase of extra-vesicular pH . HPTS-loaded intracellular membrane vesicles were pre-equilibrated at pH 7 . 0 in conductance assay buffer . Sudden addition of KOH alkalinized the extra-vesicular space , inducing a rapid pH change from 7 . 0 to 8 . 0 . Fig . 2A illustrates the response of HPTS fluorescence ratio to sudden extravesicular alkalinization . When HPTS was free in solution , i . e . in the absence of vesicles , ( Fig . 2A , circles ) , the addition of KOH rapidly alkalinized the solution from pH 7 . 0 to 8 . 0 . A rapid and immediate increase in fluorescence occurred within 5 s as a pH of 8 . 0 was immediately reached . However , when the HPTS was present within vesicles ( Fig . 2A , grey triangles ) , KOH addition produced an initial change in pH followed by a slower equilibration phase whereby the vesicle interior ultimately reached a steady-state pH of approximately 7 . 4 , considerably more acidic than the extravesicular solution . This signal resulted from an intravesicular localization of HPTS because the fluorescence ratio was not affected by the addition of a membrane-impermeant fluorescence quencher , p-xylene-bis-pyridinium bromide ( DPX ) ( Fig . 2A , black triangles ) . When added to the extravesicular environment , 15 mM DPX quenched extravesicular fluorescence , leaving the intravesicular signal intact . Fig . 2B shows that 15 mM DPX was sufficient to completely eliminate the pH-dependent fluorescence wavelength ( F450 ) of HPTS in free solution . This confirms that the addition of DPX fully quenches extravesicular HPTS . Furthermore , rapid and full equilibration to pH 8 . 0 occurred after disruption of vesicles by Triton X-100 ( data not shown ) . We postulated that vesicles prepared from normal 293FT cells might have delayed pH equilibration with the external solution because H+ conductance was rate limiting in the face of ionic transport processes that tended to produce a net acidification . To test this hypothesis we examined the effect of a proton ionophore on pH equilibration in this system . The addition of FCCP ( carbonyl cyanide 4- ( trifluoromethoxy ) phenylhydrazone ) immediately prior to vesicle alkalinization resulted in a more rapid intravesicular pH rise that reached full equilibration with the extravesicular solution ( Fig . 2D–E , red ) . Furthermore , addition of FCCP during the period of pH equilibration caused a rapid alkalinization to full pH equilibrium ( Fig . 2D–E , green ) . As expected , FCCP had no effect on HPTS fluorescence in bulk solution . This demonstrates that H+ efflux is limited by the intrinsic H+ permeability/conductance of the membrane in these vesicles . p7 sequences have been suggested to promote virus production in a genotypic-specific manner [16] , however it is unknown if this is related to ion channel function . We therefore examined the ability of p7 proteins from different HCV genotypes to alter membrane H+ permeability . Native intracellular membrane vesicles ( 120 , 000× g pellet ) expressing either genotype 1b ( J4 isolate , “FLAG-p7” ) or 2a ( JFH-1 isolate , “FLAG-JFH1p7” ) p7 displayed a significant increase in H+ permeability when compared to vesicles from control cells ( Fig . 3 ) and stabilized at an intra-vesicular pH of approximately 8 . 0 . The addition of FCCP had no additional effect on the efflux of H+ from p7-containing vesicles showing that conductive H+ flux was no longer rate limiting for pH equilibration . The membrane spanning domains of p7 are separated by a basic loop which is conserved amongst HCV genotypes further suggesting it plays a role in p7 function . We have previously shown that mutating these basic residues to alanine ( FLAG-p7K33A/R35A mutant and FLAG-JFH1p7R33A/R35A mutant ) renders p7 incapable of protecting HA from acidic pH [15] , or serving as a permeation pathway in in vitro liposome-based assays for channel function [22] . Yet its direct effect on p7-induced H+ permeability is unknown . Vesicles isolated from cells expressing the mutated FLAG-p7KR or FLAG-JFH1p7RR displayed a H+ conductance , similar to that of control vesicles from untransfected 293FT cells . Furthermore , the addition of FCCP was still able to restore rapid and full pH equilibration demonstrating that the failure of the mutant p7 to cause rapid pH equilibration was due to a lack of an effect on proton conductance . This result indicates that these conserved amino acids are in fact necessary for p7-induced H+ conductivity . Several viroporin inhibitors have been shown to abolish p7 ion channel activity in artificial lipid bilayers [7]–[9] , as well as to inhibit infectious particle production in a genotype-dependent manner [19] . However , it is not known whether they function to block intracellular H+ conductance . To confirm the specificity of our observation that p7 induces a significant H+ conductance , we assessed the effect of several candidate p7 inhibitors . Vesicles incubated with 1 µM amantadine , a concentration shown to inhibit p7 in artificial bilayers [7] , [22] , [23] as well as specifically inhibit the M2 viroporin of influenza [13] , [24] , reduced the H+ conductance induced by the J4/1b p7 to that of control vesicles ( Fig . 4A ) . Inhibition of J4/1b p7 H+ conductance was also seen with the amantadine derivative , rimantadine , as well as hexamethylene amiloride ( HMA ) . In agreement with our previous observations in vitro and in the context of infectious virus [19] , inhibitor sensitivity varied according to p7 sequence; H+ conductance induced by the JFH1/2a p7 was eliminated by rimantadine and HMA , yet was insensitive to amantadine ( Fig . 4B ) . The addition of FCCP induced an H+ conductance despite the presence of these inhibitors , indicating that the compounds did not alter vesicle stability or have a direct effect on HPTS fluorescence ( data not shown ) . To overcome limitations presented by a transfection-based system , an HCV replicon system was utilized . We studied Huh7-derived cell lines harboring RNAs from a third HCV genotype 1a strain ( H77 ) [25] , [26] . Replicon cell lines contained stably replicating sub-genomic RNA ( NS2 – NS5b ) or full-length RNA ( Core – NS5b ) . A cured full-length replicon cell line , in which the HCV RNA had been eliminated by prior treatment with interferon , served as a control . The response to a trans-vesicular pH gradient was greatly enhanced in vesicles prepared from cells containing the full-length replicon , which rapidly equilibrated to pH 8 . 0 , when compared to the cells containing the sub-genomic replicon that does not express p7 ( Fig . 5 , A–B ) . Vesicles isolated from the cured replicon cells displayed a similar conductance pattern as the vesicles isolated from sub-genomic replicon cells . Isolated full-length replicon cell vesicles also showed specific viroporin-mediated H+ permeability; as seen previously [19] , the H77 p7-induced H+ conductance was inhibited by amantadine , rimantadine and HMA . Pretreatment of vesicles from full-length replicon cells with 1 µM inhibitor resulted in almost 100% inhibition of H+ conductance . p7 thus functions as proton permeation pathway in vesicles prepared from native , intracellular membranes and has inhibitor sensitivities identical to those determined in bilayers and artificial liposomes [19] . To determine if this activity is present in live cells , we incubated replicon cells with LysoSensor Yellow/Blue DND-160 , a pH probe that exhibits a pH-dependent shift in fluorescence upon acidification . As shown in the calibration curve in Fig . 5C , LysoSensor Yellow/Blue DND-160 can be efficiently used to monitor intracellular vesicular pH of live cells . Live cell ratiometric imaging of HCV replicon-bearing cells showed punctuate vesicles of varying size ( Fig . 5D ) . Cells containing full-length HCV replicon RNAs , expressing p7 , had a net alkalinization of these vesicular structures and an average vesicular pH of nearly 6 . 0 , whereas both sub-genomic and cured cells possessed an intra-vesicular pH of approximately 4 . 5 ( Fig . 5D–E ) . To confirm these results with an alternate pH probe , we used LysoTracker Red DND-99 , a fixable fluorescent probe that has high selectivity for acidic organelles . Once inside acidic compartments , this fluorophore will fluoresce red while more neutral compartments will remain non-fluorescent . We found that cells containing the replicating full-length HCV RNA demonstrated a significant loss in acidic organelle staining with punctuate red fluorescence ( Fig . 5F–G ) compared to both sub-genomic and cured HCV replicon cells . These data strongly support the notion that p7 acts as a pH equilibrating H+ channel in vivo . Given that p7 acts as a H+ channel in cells containing HCV replicons , we sought to determine whether this conductance was also present during HCV infection . Huh-7 . 5 cells were infected with the parental HJ3-5 virus at an MOI of 0 . 1 , and stained with LysoTracker Red DND-99 to label acidic compartments . Infected cells were identified by immunofluorescence staining for core protein . Infection of Huh-7 . 5 cells with HJ3-5 resulted in a global loss of highly acidic organelles and compartments ( Fig . 6A-B , HCVcc ) . To ensure that the loss of acidic structures seen during HJ3-5 infection was due to p7 activity , we tested the effect on pH equilibration following electroporation of cells with either HJ3-5 RNA containing the wild-type or mutant p7KR sequence ( Fig . 6 ) . Unlike the parental HJ3-5 viral RNA , the p7KR mutant was unable to alter intracellular pH , confirming that p7 acts as a proton channel during HCV infection . We have shown that the channel activity of J4/1b , JFH-1/2a and H77/1a p7 proteins , when present in isolated membrane vesicles , is blocked by several viroporin inhibitors including amantadine and rimantadine . However , p7 channel inhibitors have yet to demonstrate clinical efficacy in the treatment of chronic hepatitis C , suggesting the possibility that the channel present in intact cells may not be as sensitive to these inhibitors . We therefore examined whether the p7 effects on vesicular pH in live cells could be reversed by channel inhibitors . Full-length replicon cells were loaded with LysoSensor Yellow/Blue DND-160 and treated with either amantadine or rimantadine . As shown previously , basal vesicular pH of full-length replicon cells was nearly 6 . 0 , markedly more alkaline than sub-genomic or cured full-length replicon-bearing cells ( Fig . 7A–B ) . Treatment of full-length replicons with increasing concentrations of both amantadine and rimantadine was able to partially restore vesicular acidic pH within 5 min of treatment while sub-genomic replicons and cured cells were unaffected by inhibitor treatment . Consistent with our previous observations [19] , rimantadine was a more potent inhibitor ( EC50≈15 µM ) than amantadine ( EC50≈75 µM ) , but in both cases , the concentration required to alter channel function in live cells was considerably higher than for isolated membrane vesicles , and full restoration of acidic compartments was not achieved . Rimantadine was able to re-acidify vesicular compartments to approximately pH 5 . 0 and amantadine to roughly 5 . 5 ( Fig . 7B ) . To explore the involvement of p7 H+ channel activity in virus production , we examined whether a direct correlate existed between the re-acidification achieved by blocking p7 channel activity with specific inhibitors and the observed reduction in infectious virus production and/or release . Huh-7 . 5 cells were infected with HJ3-5 virus and cultured in medium supplemented with varying concentrations of amantadine as described in Materials and Methods . Fig . 7C–D shows the titer of infectious virus released into the extracellular supernatant as well as the ratio between intracellular and extracellular virus after amantadine treatment . Consistent with replicon LysoSensor studies , amantadine at 1 µM , a concentration that nearly completely blocked p7-induced H+ conductance in isolated vesicles , had no effect on the release of infectious virus ( Fig . 7C , bars ) , Yet , similar to previous results with both amantadine and rimantadine [19] , increasing concentrations of amantadine reduced the release of infectious virus . Interestingly , the ability of amantadine to block virus production correlated directly with its ability to reverse the p7-induced loss of acidic intra-organelle pH ( Fig . 7C , compare line and bars ) . As previously reported , treatment with 100 µM amantadine for 24 h did not result in any cellular toxicity [19] . This result confirms the existence of a relationship between the antiviral effect of amantadine and its ability to specifically inhibit intracellular p7 channel activity . To definitively determine whether the p7-induced loss of vesicle acidification contributes to infectious virion production , we determined whether preventing this acidification pharmacologically using the vATPase inhibitor , bafilomycin A1 , could compensate for the p7KR defect . To perform this experiment it was necessary to first confirm that vesicular acidification could be inhibited without cellular toxicity or interference with the ability to assay for infectious virus . We determined the concentration dependence at which bafilomycin A1 affects vesicular acidification , virus entry and cell death as described in Materials and Methods ( Fig . 8A–C ) . At 2 . 5 pM , bafilomycin A1 was not cytotoxic , did not significantly inhibit viral entry , yet significantly alkalinized vesicular acidic compartments to a similar extent as seen during HJ3-5 infection where an alternative pH sensitive fluorochrome of similar pKa value was used . Huh-7 . 5 cells were then electroporated with the parental HJ3-5 virus RNA , the channel-inactive p7 mutant , HJ3-5 ( KR ) , or an RNA in which the p7 sequence had been removed by an in-frame deletion , HJ3-5 ( Δp7 ) . After four days , the media was replaced with fresh media containing 2 . 5 pM bafilomycin A1 . Twenty-four hours later , the cells were harvested and the titer of both intra- and extracellular infectious virus was determined by inoculation onto naïve Huh-7 . 5 cells . Bafilomycin A1 treatment of cells electroporated with the parental HJ3-5 virus RNA had no effect on the production of infectious virus , as intra- and extracellular virus titers remained ∼103 and ∼104 FFU/ml , respectively ( Fig . 8D–E ) . As expected , cells electroporated with either the mutant HJ3-5 ( KR ) or HJ3-5 ( Δp7 ) RNAs showed no evidence of either extracellular or intracellular infectious virus production . However , treatment with 2 . 5 pM bafilomycin A1 was able to partially rescue infectious virus production by the KR mutant , resulting in approximately 102 FFU/ml in both the intracellular and extracellular compartments . Replication foci were noticeably smaller in cells inoculated with the rescued HJ3-5 ( KR ) virus compared to the parental virus , consistent with a defect in cell-to-cell spread of virus within the naïve cells in the absence of drug treatment . Antibody to CD81 prevented infection by this HJ3-5 ( KR ) virus , suggesting that it enters cells via the well characterized HCV receptor mechanism ( data not shown ) . These results thus demonstrate that p7 H+ channel activity is essential for the production of infectious HCV , both within the cell and in cell culture supernatant fluids . Importantly , infectious virus production could not be rescued from HJ3-5 ( Δp7 ) -electroporated cells by bafilomycin A1 treatment , suggesting that other , non-H+ channel p7 functions are likely to be required for the assembly and release of infectious virus . Equal expression of HCV core protein was detected for each of these viral constructs , indicating that each of these RNAs is capable of replicating following electroporation into cells ( Fig . 8F ) . As bafilomycin A1 partially rescued infectious virus production for the channel-inactive p7KR mutant , we investigated whether the influenza A M2 ( IAV M2 ) proton channel might act similarly . We first examined the ability of M2 to alter pH gradients in live cells . Huh-7 . 5 cells were transfected with M2 or the channel inactive M2 , M2 ( A30P ) [27] and loaded with LysoSensor Yellow/Blue DND-160 . The presence of M2 caused a net alkalinization of highly acidic vesicular structures measuring an average pH of 5 . 5 while cells expressing an empty vector or the channel inactive M2 ( A30P ) measured an intravesicular pH of approximately 4 . 3 ( Fig . 9A ) . To assess whether M2 H+ channel activity was specifically able to rescue a p7-deficient HCV , we exploited the genotype-dependent sensitivity of p7 to amantadine . Thus , we assessed the ability of an amantadine-sensitive M2 protein to rescue the amantadine resistant genotype 2a JFH-1 HCV , thereby utilizing amantadine sensitivity to identify an M2-specific effect . Huh-7 . 5 cells were co-electroporated with plasmids encoding the amantadine-sensitive IAV M2 protein or the channel inactive M2 , M2 ( A30P ) , along with wild-type JFH-1 , JFH-1 ( RR ) or polymerase mutant , JFH-1 ( GND ) RNA . Following amantadine treatment , yields of extracellular infectious virus were assessed . Cells electroporated with JFH-1 RNA produced approximately 104 FFU/ml and the release of infectious virus from JFH-1-electroporated cells was not affected by the expression of M2 , M2 ( A30P ) or the presence of 50 µM amantadine ( Fig . 9B ) . JFH-1 ( RR ) RNA produced no detectable infectious virus , however , co-electroporation of JFH-1 ( RR ) and IAV M2 resulted in a partial rescue of infectious virus production , yielding between 103 and 104 FFU/ml . Unlike JFH-1 infected cells , however , the release of infectious virus by the M2 trans-complemented JFH-1 ( RR ) mutant was partially inhibited by amantadine . In addition , the M2 mutant , M2 ( A30P ) was unable to rescue the JFH-1 ( RR ) mutation . This result confirms the requirement for H+ channel activity for virus production from the HJ3-5 chimeric virus in which the p7 sequence is of genotype 1a origin . We have shown that p7 can dramatically alter the pH of intracellular compartments and that this vesicular alkalinization is required for infectious virus production . While it has previously been shown that mature HCV particles are acid resistant , we hypothesized that intracellular infectious virus particles might be acid sensitive and that p7-induced alkalinization could protect them from an acid milieu . To examine this , we isolated both extracellular and intracellular virus and exposed them to acidic solutions . Huh-7 . 5 cells were infected with cell culture passaged JFH-1 virus . After five days , both extracellular and intracellular virus was harvested and incubated for 10 min at 37°C in identical HEPES/MOPS buffer solutions to achieve final pH values of 7 . 0 , 6 . 0 , 5 . 0 , and 4 . 0 . This solution was then neutralized back to pH 7 . 0 and used to inoculate naïve Huh-7 . 5 cells . Infectious titer was determined by the standard FFU assay . Similarly to what has been reported [28] , extracellular virus was acid stable and infectivity was unaffected when the virions were exposed to pH values as low as 4 . 0 ( Fig . 10 ) . However , intracellular infectious virions displayed greatly increased acid sensitivity , with nearly a 2 log10 decrease in infectivity at pH 4 . 0 .
HCV p7 is required for infectious particle formation and plays a role during virion egress [16] , [17] . Convincing data shows that it forms ion channels in artificial lipid bilayers [7] , [8] , [9] , [29] yet , whether ion channel activity is required by the virus , or whether p7 functions as a channel at all inside infected cells has remained unknown . In the present study we evaluated the ability of p7 to facilitate equilibration of intracellular pH gradients and examined its contribution to the production of infectious virus . We demonstrate that p7 mediates proton ( H+ ) equilibration in isolated vesicles as well as in Huh7 cells in vivo . Its presence results in a loss of intracellular compartment acidification , and this reduction in acidification is required for the production of infectious virus . While mature virions are acid stable , intracellular virus can be inactivated by acidic pH . In the absence of a functional p7 channel , alternative methods to alkalinize intracellular compartments can partially rescue infectious virus production . Native vesicles without p7 expression showed a low permeability for H+ as evidenced by slow and incomplete pH equilibration upon exposure to a shift in extravesicular pH . When exposed to a sudden pH shift , they slowly equilibrate pH and fail to fully equilibrate over a 3 min period . In contrast , vesicles derived from cells expressing p7 from genotypes 1a , 1b or 2a HCV were capable of rapid pH equilibration , similar to normal vesicles in the presence of FCCP . This effect was inhibited in a genotype-specific manner [19] by amantadine , rimantadine and hexamethylene amiloride , and was not observed with channel-inactive p7 variants expressed to comparable levels . To determine the extent to which p7 alters cellular ionic homeostasis , we utilized two fluorometric pH sensors that serve as pH reporters in live cells but work by different mechanisms . LysoTracker Red DND-99 is an acidotropic probe with high selectivity for acidic organelles . Although its fluorescence is largely independent of pH , it can be fixed with paraformaldehyde and serves to mark the presence of highly acidic organelles . LysoSensor Yellow/Blue DND-160 is a ratiometric pH sensor . It concentrates in organelles with less pH sensitivity , but undergoes a pH-dependent fluorescence spectrum shift that can be used to directly measure pH . Each fluorophore showed that the expression of the HCV p7 protein by replicon RNAs or during infection resulted in an alkaline shift of organelle pH and a dramatic reduction in the number of highly acidic intracellular compartments . This loss of organelle acidity only occurred in HCV infected or p7-containing cells and did not occur with electroporation of viral RNA containing the inactive channel mutant , p7KR . It was notable that loss of acidification was not restricted to one location or structure in the cell and seemed to be a global effect . To our knowledge , this is the first time a viroporin has been shown to directly induce a global loss in organelle acidity . Our results show that the p7-associated proton conductance is inhibited by the viroporin inhibitors , amantadine and rimantadine . However , it is worthy to note that these channel blockers had very different concentration dependence in isolated vesicle systems compared with live cells . In vesicles , our results confirmed most of what has been reported for bilayers and artificial liposomes [23] . Both amantadine and rimantadine were effective at concentrations of 1 µM for genotype 1a p7 and only rimantadine was effective as a channel blocker at 1 µM for genotype 2a p7 . However , in live cells we observed a different concentration dependence . We found that amantadine did not affect or restore vesicular acidity at concentrations lower than 50 µM . Rimantadine was effective at concentrations approximately 5-fold lower . The reason for the difference between isolated vesicles and cells is not clear but could be due to limited entry into cells , active cellular extrusion or intracellular binding of the compounds . Multiple lines of evidence demonstrate that the p7-induced loss of acidification is necessary for the production of infectious virus . First , while we confirmed that the mature HCV virions are acid stable , intracellular virus is not and therefore there appears to be a phase during maturation in which protection from an acid environment is required . This idea is further supported by the observation that concentrations of the V-ATPase inhibitor bafilomycin A1 , sufficient to raise the pH of acidic organelles , partially rescued infectious virus production in the null p7KR phenotype . Virus produced from the p7KR mutant virus , as a result of bafilomycin rescue , was subsequently able to enter cells by the normal viral receptor-mediated entry pathway which was inhibited by anti-CD81 antibody . This suggests that p7 may not be required for viral entry . A second line of evidence in support of a role for p7 channel activity in infectious virus production was the observation that the JFH-RR mutant virus could be rescued by expression of influenza A M2 protein . This viroporin has been shown to be a proton equilibrating channel in the secretory pathway [12] , [13] , but is unlikely to be able to trans-complement other potential HCV p7 specific functions such as viral protein-protein interactions . A third line of evidence that supports an ion channel function for p7 in virus production is the correlation between the effects of amantadine on intravesicular pH and virus production . As shown in Fig . 7 , amantadine did prevent virus production but only at the concentrations at which it was effective as an intracellular channel inhibitor in live cells . Previous studies examining the effect of amantadine on the HCV p7 protein have been difficult to reconcile . Amantadine inhibits the genotype 1 p7 channel in bilayers at low micromolar concentrations , but it does not inhibit virus production until 50–100 µM [7] , [19] , and it has failed to have a clinically significant antiviral effect in patients where blood concentrations of 1–2 µM are the highest that can be achieved [30] . Our results in live cells , however , clearly show that higher extracellular concentrations of amantadine are required to restore the acidic pH of intracellular vesicles in p7 expressing cells . Furthermore , this effect has the same concentration dependence as does inhibition of virus production , thus implying a direct role of p7 channel activity in virus production and supporting that amantadine would have a specific antiviral effect in vivo should it reach sufficient local concentration . A notable finding in this study is that bafilomycin A1 was able to partially overcome the defect in the KR mutant but was not able to complement a p7 deletion mutant . This suggests that p7 has additional effects unrelated to its channel activity . Recent structural analysis shows that the JFH-1 p7 protein forms a hexameric structure with a luminally-facing , open orientation [31] . This exposed region is then available to provide protein-protein interaction sites . Similarly , this is seen with HIV-1 where its viroporin , Vpu , promotes HIV-1 infectivity and release of infectious virus particles through protein-protein interactions with the host such as sequestration of the virus receptor CD4 and hindering of BST-2/tetherin [32] . This supports previous data for HCV showing that incompatibilities in the sequence of NS2 in inter-genotypic HCV chimeras that limit RNA replication can be overcome by spontaneous , compensatory mutations in p7 , thus providing genetic evidence that critical protein-protein interactions exist between p7 and other non-structural proteins [17] , [18] . Overall , this suggests that p7 has additional functions unrelated to its channel activity . The KR mutant protein may serve these other functions and therefore can be rescued by pH manipulation , but the total absence of p7 produces more profound defects that cannot be overcome by pH changes alone . It was recently reported that the influenza M2 protein was not able to complement the absence of p7 in a novel trans-complementation system using a helper replicon to express the complementing protein [33] . Using a similar construct that we used in our Δp7 experiments , this study showed that a Δp7-half deletion could be complemented to varying degrees by p7 , E2p7 , and E2p7NS2 , but not by M2 . If p7 performs distinct channel-dependent and channel independent functions , then logically M2 would not be expected to restore virus production to the p7-deleted virus as it would only compensate for the loss of H+ channel function . One must also consider the possibility that polyprotein processing defects , and not loss of p7 function per se , is the reason for failure of p7 mutants to produce virus . It has been shown that the K33A/R35A channel inactive mutant results in inefficient processing of the polyprotein within the E2-p7-NS2 region ( [16] and S . Griffin , unpublished ) . This can then lead to the accumulation of E2-p7 , p7-NS2 or E2-p7-NS2 fusion proteins or possibly inadequate levels of mature p7 protein . While it is certain that the K33A/R35A protein is channel defective , we cannot rule out the possibility that the defects in this phenotype also result from aberrant processing . However p7 is still detectable within cells infected with these viral constructs , albeit at reduced levels ( S . Griffin , unpublished ) . This reduction in p7 levels could thus explain the low level complementation achieved with either M2 or bafilomycin A1 compared to wild-type infection , i . e . there would be less p7 available to perform its non-ion channel functions which are necessary to make virus particles . While the step at which acidification suppresses HCV virus production remains unclear , our findings as well as others , argue that the pH sensitive step occurs after virus entry and prior to the assembly of functional virus . M2 is required for virus disassembly in the endosomes and for equilibrating the intra-luminal pH of the trans-Golgi network ( TGN ) with the cytoplasm . It has also been demonstrated that the over-expression of M2 from particular influenza strains , induces luminal dilation of the Golgi and TGN as well as delayed transport through the secretory pathway in a similar fashion as monensin [34] , suggesting that M2 ion channel activity functions at the TGN to keep the pH above the threshold at which HA conformational changes occur . Like M2 , p7 has been suggested to also protect nascent HCV virions from premature acid-induced conformational changes . This is supported by the fact that M2 was able to complement a channel defective HCV and rescue virus production . While p7 has not been directly connected to membrane rearrangement or organelle disruption , we cannot rule out the possibility that p7-induced membrane alterations play a role in virus production . It has further been observed that p7 channel defective mutations have quantitatively different effects depending on the parent viral sequence and/or genotype as well as the expression system [16] . Our results in genotype HJ3-5 chimeric virus , in which the p7 sequence is derived from genotype 1a , show that the K33A/R35A mutation completely abrogates infectious virus production and can be partially restored by bafilomycin A1 . However , in the context of JC1 , in which the p7 sequence is derived from genotype 2a , the K33A/R35A mutation results in only a 2-log reduction in infectious virus [16] . This emphasizes the importance of strain-dependence in determining the precise quantitative consequence of p7 defects . Overall , all data agrees that p7 is vital and our new data clearly show that the channel activity is important , yet other effects such as processing defects and loss of protein-protein interactions can contribute to the specific phenotype of p7 mutations in different viral stains and culture systems . The step at which acidification suppresses HCV virus production is not yet clear . The most widely cited hypothesis , based on analogy to influenza [12] , [13] and other viruses , is that p7 protects the nascent virus from premature acid-induced conformational changes . Our finding of acid sensitivity of intracellular but not extracellular virus suggests it occurs at a step prior to final virion exocytosis . We were not able to detect infectious intracellular virus in p7KR electroporation and we observed only minimal effects of even high doses of amantadine on the ratio of intracellular to extracellular virus . These observations argue that the pH sensitive step may also occur early in the formation of intracellular infectious viral particles and not solely at the final exocytosis step . In conclusion , we have specifically shown that p7 dramatically alters the pH equilibration in intracellular vesicles and causes a loss of acidification of multiple compartments in live cells . Intracellular virus itself is acid sensitive and virus production by a p7 mutant with defective channel function can be partially rescued by using alternative approaches to prevent intracellular acidification . This definitively demonstrates that p7 functions as an H+ channel in native intracellular membranes and links p7-induced pH changes to the production of infectious intracellular viral particles . While p7 channel inhibitors have yet to demonstrate clinical efficacy in the treatment of hepatitis C , our work shows that amantadine is ineffective at the concentrations achieved clinically and thus improved agents targeting the p7 channel activity could have therapeutic potential . These novel aspects and approaches to HCV will undoubtedly reveal new details of HCV-host interactions as well as therapy , as more is uncovered about the roles of this viroporin in virus assembly and release .
General materials were purchased from Sigma-Aldrich ( St . Louis , MO ) or Fisher Scientific ( Pittsburgh , PA ) . Dulbecco's modified Eagle medium ( DMEM ) , fetal bovine serum , L-glutamine , sodium pyruvate and geneticin were purchased from Mediatech ( Manassas , VA ) . Penicillin-streptomycin , MEM nonessential amino acids , Opti-MEM , lipofectamine 2000 , DPX ( p-xylene-bis-pyridinium bromide ) , LysoSensors Yellow/Blue DND-160 and Green DND-189 and LysoTracker Red DND-99 were purchased from Invitrogen ( Carlsbad , Ca ) . Protease inhibitor cocktail ( Sigma-Aldrich , P8340 ) was used at 1∶100 dilution . Amantadine hydrochloride ( A1260 ) , rimantadine hydrochloride ( 390593 ) , 5- ( N , N-Hexamethylene ) amiloride ( HMA , A9561 ) , bafilomycin A1 ( B1793 ) , monensin and nigericin were purchased from Sigma-Aldrich . Monoclonal antibody C7-50 to core protein was purchased from Affinity BioReagents and CellTiter-Blue was purchased from Promega ( Madison , WI ) . The plasmids pcDNA-FLAGp7 and pcDNA-FLAGp7KR were described previously [15] , [20] . Both contain the p7 sequence from the J4 infectious clone of HCV genotype 1b and an N-terminal FLAG tag . The pcDNA-JFH1p7 and pcDNA-JFH1p7R33A/R35A ( p7RR ) plasmids are similar channel active and inactive p7 expression plasmids containing the p7 sequence derived from the JFH1 clone of HCV genotype 2a . They were constructed identically to the J4 plasmids ( primers available on request ) introducing an N-terminal FLAG tag by QuikChange mutagenesis ( Stratagene , La Jolla , CA ) . The parental HJ3-5 HCV plasmid , ( pH- ( NS2/NS3 ) -J/YH/QL ) has been described previously [18] . The p7KR33/35AA and Δp7 ( a . a . 2580-2675 ) mutations were introduced into the pHJ3-5 plasmid resulting in pHJ3-5 ( KR ) and pHJ3-5 ( Δp7 ) using QuikChange mutagenesis . The pcDNA-based plasmid expressing the HPAI Hong Kong '97 156 M2 protein was kindly provided by Wendy Barclay ( Imperial College , London ) and described previously [35] . The region encoding M2 was excised from this plasmid and cloned into pLVX-IRES-mCherry ( Clontech ) to yield mCherry-M2 , respectively . The channel inactive mCherry-M2 ( A30P ) [27] was created using QuikChange mutagenesis ( Stratagene , La Jolla , CA ) . All sequences were confirmed by DNA sequencing analysis . Human embryonic kidney ( HEK ) 293FT cells were routinely cultured in DMEM containing 10% fetal bovine serum , 100 IU/ml penicillin , 100 µg/ml streptomycin , 0 . 1 mM MEM non-essential amino acids , 6 mM L-glutamine , 1 mM MEM sodium pyruvate , and 500 µg/ml geneticin . Genome-length and sub-genomic genotype 1a HCV replicon cell lines were described previously [25] , [36] . Full-length and sub-genomic replicon-bearing cells were cultured in DMEM supplemented with 10% fetal bovine serum , 100 IU/ml penicillin , 100 µg/ml streptomycin , 2 µg/ml blasticidin ( Invitrogen ) and 200 µg/ml geneticin . Full-length replicon cells were “cured” by culturing with interferon-α ( 200 U/ml for 4 weeks ) . Media used for the culture of cured replicon cell lines contained no geneticin . All transfections were carried out using Lipofectamine 2000 ( Invitrogen ) . pcDNA-FLAGp7 was transfected into the cells according to the manufacturer's instructions . Due to expression variability , pcDNA-FLAGp7KR needed to be transfected using 1/3 the DNA concentration of wild-type pcDNA-FLAGp7 to achieve equal protein expression levels . Transfection complexes were incubated with the cells for 24 h in Opti-MEM serum-free medium ( Invitrogen ) before harvesting . RNA was synthesized with T7 MEGAScript reagents ( Ambion ) as in Kato et al . [37] and transfected into Huh-7 . 5 cells by electroporation . Briefly , 10 µg of RNA was mixed with 5×106 cells suspended in 250 µl of Opti-MEM media , in a cuvette with a gap width of 0 . 2 cm ( Bio-Rad ) . Electroporation consisted of one pulse of current delivered by the Gene Pulser Xcell electroporation device ( Bio-Rad ) , set at 140 V , 1000 µF , and maximum resistance . Electroporated cells were plated in complete media ( DMEM supplemented with 10% fetal bovine serum , 100 IU/ml penicillin , 100 µg/ml streptomycin and 1X nonessential amino acids ) . Culture medium was replaced after 24 h . For the bafilomycin A1 rescue experiments , Huh-7 . 5 cells were electroporated with parental HJ3-5 , HJ3-5 ( KR ) , or HJ3-5 ( Δp7 ) viral RNA and equally seeded into 2 wells of a 6-well plate . At 96 h post-electroporation , the culture medium was removed and replaced with fresh , complete media containing 2 . 5 pM bafilomycin A1 . Following an additional 24 h of incubation , supernatant medium and cell lysates were collected and assayed for infectivity . The presence of infectious HCV particles was measured by calculating focus-forming units per ml virus ( FFU/ml ) with various dilutions as described below . In undiluted samples , no attempt was made to remove bafilomycin from medium or lysates . To assay viral titers , 100 µl aliquots of serial 10-fold dilutions of supernatant cell culture fluids ( clarified by low-speed centrifugation ) were inoculated onto naïve Huh-7 . 5 cells seeded 24 h previously into 8-well chamber slides ( Nalge Nunc ) at 2×104 cells/well . Intracellular virus was isolated by freeze-thaw of cell lysates . Briefly , infected cells were washed in PBS , dislodged from the tissue culture flask with trypsin , brought to 5 . 0 ml with complete media and centrifuged at 400× g for 5 min at 4°C . The cell pellet was resuspended in 1 . 0 ml DMEM and subjected to 4 cycles of freeze and thaw using a methanol/dry ice bath and a 37°C water bath . Samples were then centrifuged at 10 , 000× g for 10 min at 4°C to remove cell debris . After inoculation , cells were maintained at 37°C , 5% CO2 and fed with 200 µl of medium 24 h later . Following 48 h additional incubation , cells were fixed in 1∶1 methanol-acetone at room temperature for 10 min , then incubated with monoclonal antibody C7-50 to core protein ( Affinity BioReagents , 1∶300 ) for 2 h at RT , washed with PBS twice , and incubated with Alexa Fluor 488-conjugated goat anti-mouse secondary antibody ( Invitrogen , 1∶500 ) for 1 h at RT . Infectivity was determined by calculating focus-forming units per ml of original culture medium or cell lysate ( FFU/ml ) . 293FT cells were dislodged from the tissue culture flask into ice-cold phosphate-buffered saline ( PBS ) and centrifuged at 1 , 000× g for 10 min at 4°C followed by two more washes in PBS . HCV replicon cells were dislodged by incubating with pre-warmed cell dissociation solution ( Sigma , C5914 ) for 15 min followed by three washes in PBS . The cell pellet was resuspended in 1 . 0 ml of homogenization media ( 250 mM sucrose , 1 mM EDTA , 20 mM HEPES [pH 7 . 4] , 2 mM MgCl2 , protease inhibitors ) and homogenized on ice using 25 strokes of a loose-fitting Dounce homogenizer until ∼95% of the cells were disrupted . Homogenates were cleared of nuclei and unbroken cells by centrifuging at 1 , 000× g for 10 min at 4°C . For vesicle isolation , the 1 , 000× g supernatant was centrifuged at 10 , 000× g for 15 min at 4°C to remove all heavy membranes . The resultant supernatant was centrifuged at 120 , 000× g in a MLS-50 swinging bucket rotor for 1 h at 4°C to pellet membrane vesicles . Vesicles were resuspended in homogenization buffer , flash frozen in liquid nitrogen and stored in 100 µg aliquots at −80°C until needed for conductance assays . For gradient analysis , the 1 , 000× g supernatant was centrifuged at 3 , 000× g for 10 min at 4°C to pellet heavy mitochondria and plasma membrane fragments . Western blotting was performed using anti-Flag M2 , 1 µg/ml ( Sigma-Aldrich ) , anti-PDI , 1∶2 , 000 ( Stressgen , Victoria , BC , Canada ) , anti-GRP75 , 1∶20 ( Affinity Bioreagents , Golden , CO ) , anti-LAMP2 H4B4 , 1∶2 , 000 ( DHSB , University of Iowa ) , anti-core , 1∶1 , 000 ( Affinity Bioreagents ) and anti-β-actin , 1∶15 , 000 ( Sigma-Aldrich ) . Horseradish peroxidase-conjugated secondary antibodies were from Pierce Biotechnologies ( Rockford , IL ) . Immunoblots were detected using the ECL Plus Western Blotting Detection System ( Amersham Biosciences , Piscataway , NJ ) . Isolated vesicles ( 200 µg ) were thawed on ice , brought to 1 . 0 ml with conductance assay buffer ( 10 mM MOPS [pH 7 . 0] , 150 mM KCl , 4 mM MgSO4 ) containing 5 mM HPTS ( 8-hydroxypyrene-1 , 3 , 6-trisulfonic acid , trisodium salt , Invitrogen ) and broken and resealed with 10 strokes of a loose-fitting Dounce homogenizer to incorporate HPTS into the vesicle lumen . To separate HPTS-loaded vesicles from extra-vesicular free dye , re-homogenized vesicles were applied to a 5 ml Bio-Gel P-10 size exclusion column , with a 20 kD exclusion limit prepared as according to manufacturer's instructions ( Bio-Rad ) . The column was eluted using HPTS-free conductance assay buffer . Fractions were collected and assayed for protein and HPTS fluorescence at ex 450 nm , em 520 nm . Protein containing fractions eluting in the void volume corresponded to a small fluorescence peak and represented HPTS-loaded vesicles . These were pooled and used for conductance assays . Protein concentration within the fractions was assayed using Bio-Rad protein assay dye reagent . Vesicular proton permeability was measured by a modification of the method described by Grover et al . [38] . Fluorescence measurements were performed at room temperature in a Fluostar Optima plate reader equipped with an integrated syringe injector ( BMG Labtech , Durham , NC ) . The excitation wavelengths were 450 nm ( pH-dependent ) and 405 nm ( pH-independent ) and data were collected every 1 s for 4 min at an emission wavelength of 520 nm . To determine changes of intravesicular pH , HPTS-loaded vesicles were diluted in HPTS-free conductance assay buffer , allowed to equilibrate at room temperature for 30 min , and subsequently pipetted into a 96 well plate , 100 µl per well . Fluorescence of the vesicle suspension was monitored and once a stable baseline was achieved , 10 µl of 50 mM KOH was injected per well while the plate was stirred and the fluorescence was monitored . The addition of base alkalinized the extra-vesicular environment from pH 7 . 0 to 8 . 0 as confirmed with a pH meter . Ionophore and inhibitor compounds were added to the vesicle suspension just prior to reading . Intravesicular pH was calculated from the fluorescence ratio using a bulk solution extracellular calibration curve performed with a conventional pH meter . In some experiments any extravesicular fluorescence signal was quenched by addition of 15 mM p-xylene-bis-pyridinium bromide ( DPX ) . HCV replicon bearing , infected or electroporated cells were plated on poly-D-lysine coated cover slips and allowed to grow overnight . The cells were then washed in HEPES solution ( 10 mM HEPES , 133 . 5 mM NaCl , 2 . 0 mM CaCl2 , 4 . 0 mM KCl , 1 . 2 mM MgS04 , 1 . 2 mM NaH2PO4 , 11 mM glucose; pH 7 . 4 ) and loaded with 5 µM LysoSensor Yellow/Blue DND-160 diluted in HEPES solution at 37°C for 45 min . The cells were washed twice and immediately imaged . Imaging was performed using a Nikon eclipse Ti PFS Quantitative Fluorescence Live-Cell and Multidimensional Imaging System equipped with a digital monochrome Coolsnap HQ2 camera ( Roper Scientific , Tucson , AZ ) . Fluorescence images were collected using Metafluor software ( Universal Imaging , Downingtown , PA ) . Data were recorded at excitation/emission wavelengths of 340/440 nm and 380/510 nm using a 410 nm dichroic . Cell fluorescence ratios were determined by image analysis of the stored single wavelength images using Metafluor software . For each cell a region of interest was delineated that encompassed the cytosolic space of the cell and excluded the nucleus . Ratio was calculated for each cell as R = ( F1-B1 ) / ( F2-B2 ) where F1 and F2 are the fluorescence intensities at 380/525 and 340/440 respectively and B1 and B2 are the corresponding background values determined from a region on the same images that was near the cell but did not contain a cell . Calibration of the relationship between R values and pH was performed by two different methods . First , a free solution calibration was performed using LysoSensor solutions of known pH and measuring R with the microscope as described . The calibration curve was well fitted by the equation pH = ln[ ( R-Yo ) /a] ·1/b , where Yo , a and b are constants . An intracellular calibration was also performed as described elsewhere [39] . Cells were loaded with LysoSensor and then permeabilized with 10 µM monensin and 10 µM nigericin . They were then serially exposed to calibration buffer solutions containing 25 mM MES , 5 mM NaCl , 115 mM KCl and 1 . 2 mM MgSO4 at fixed pH and R was measured as described . The 2 methods agreed well . The ionophores , however , resulted in loss of LysoSensor from intracellular vesicles at higher pH . This resulted in very low signals above pH 5 . 5 and made the intracellular calibration method impractical except for use at the most acid pH range . For this reason , the free solution calibration was used in most experiments . R values were converted to pH by extrapolation of the calibration curve . For experiments to determine the concentration dependence of bafilomycin on vesicular pH , Huh-7 . 5 cells were plated on poly-D-lysine coated cover slips and allowed to grow overnight , after which time the cells were washed in HEPES solution and loaded with 2 µM of the single wavelength pH indicator LysoSensor Green DND-189 for 30 min at 37°C . The cells were washed , treated with HEPES ± increasing concentrations of bafilomycin A1 and immediately imaged . The increase in vesicular pH in response to increasing concentrations of bafilomycin A1 was determined by imaging at excitation of 443 nm and emission at 500 nM . Cells , approximately 5000 , were plated on 12 mm polylysine coated glass cover slips and incubated overnight . The cells were then washed in HEPES solution and loaded with 0 . 5 µM LysoTracker Red DND-99 in HEPES solution for 30 min at 37°C . The cells were washed in PBS , fixed in 4% paraformaldehyde for 30 min at room temperature , permeabilized in ice-cold acetone for 5 min and incubated in IF buffer ( 1% BSA , 2 . 5 mM EDTA in PBS ) for 1 hr at room temperature . HCV core protein was labeled by incubating with anti-core , 1∶300 , as described above . Nuclei were counterstained by incubation for 5 min with 1 . 0 µg/ml DAPI and the cover slips were mounted in Fluorsave mounting medium ( Invitrogen ) . LysoTracker positive staining was quantitated by image analysis in a Nikon TiE system as described above . Single wavelength fluorescence images were acquired at 560 nm excitation , 607 nm emission . A region of interest was chosen to include the entire area of a single cell . Images were acquired at fixed detector gain that avoided saturation in the brightest images and mean pixel intensity of each cell was determined and reported as mean cellular fluorescence intensity . Huh-7 . 5 cells were plated in 96-well tissue culture plates at 10 , 000 cells per well and allowed to grow overnight after which time the cells were washed with PBS and the medium was replaced with fresh compete medium containing varying concentrations of bafilomycin A1 for 24 h . The cells were then washed in PBS and fresh DMEM containing 10% CellTiter-Blue reagent ( Promega ) was added . After 3 h incubation at 37°C , 5% CO2 , the fluorescence at 560/590 nm was read in a Fluostar Optima plate reader . Huh-7 . 5 cells ( 2×104 cells ) were plated in the wells of an 8-well chamber slide and incubated overnight . The cells were then washed in PBS and incubated at 37°C , 5%CO2 in complete media containing varying concentrations of bafilomycin A1 for 1 hr . The media was then removed and the cells were infected with 0 . 5 ml complete media containing HJ3-5 virus ( MOI 1 . 0 ) ± bafilomycin A1 and incubated at 37°C , 5% CO2 for 3 hr . The inoculum was then removed , the cells were washed in PBS and fresh complete media was added . Following an additional 72 hr incubation , infected cells were fixed by methanol:acetone ( 1∶1 ) , stained for core protein and foci counted as described above . Huh-7 . 5 cells ( 2 . 5×106 ) were co-electroporated with 20 µg mCherry-M2 or mCherry-M2 ( A30P ) DNA and 10 µg JFH-1 derived RNAs as described previously . The electroporated cells were resuspended into 5 ml complete media and seeded into two wells of a 6-well plate . After 48 hr , the cells were re-transfected with 20 µg mCherry-M2 or mCherry-M2 ( A30P ) using lipofectamine according to manufacturer's instructions . 24 hr after transfection , the media was removed and fresh , complete media ±50 µM amantadine was added for an additional 24 hr . Secreted infectivity was quantified by focus forming assay by infecting 2×104 naïve Huh-7 . 5 cells seeded the preceding day in an 8-well chamber slide . Infected cells were fixed by methanol:acetone ( 1∶1 ) , stained for core protein and foci counted as described above . Huh-7 . 5 cells were plated in a T-175 cm2 culture dish and infected with cell culture passaged JFH-1 virus at an MOI of 1 . 0 . After five days , the cell supernatant fluids were collected and clarified by low-speed centrifugation . Intracellular virus was obtained by freeze-thaw of washed cellular pellets as described above . Extracellular and intracellular viral stocks were then identically diluted 1∶1 in a HEPES/MES buffer ( 20 mM HEPES , 20 mM MES , 133 . 5 mM NaCl , 2 . 0 mM CaCl2 , 4 . 0 mM KCl , 1 . 2 mM MgS04 , 11 mM glucose; pH 7 . 4 ) at pH 2 . 1 , 2 . 6 , 5 . 3 , or 7 . 0 . The final pH values of the virus/buffer solutions were 4 . 0 , 5 . 0 , 6 . 0 , and 7 . 0 respectively . The virus/buffer suspensions were incubated in a 37°C water bath for 10 min and then neutralized with 1M NaOH . The samples were then clarified by low-speed centrifugation at 500× g for 5 min and diluted 1∶10 or 1∶100 in complete media . Infectivity was determined by calculating focus-forming units per ml of original culture medium or cell lysate ( FFU/ml ) . Results are expressed as mean ± SE . The Student t test was used for statistical analyses . P≤0 . 05 was considered significant .
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The hepatitis C virus ( HCV ) is the most common cause of chronic liver disease . Current therapy is only partially effective and fraught with side effects . A greater understanding of viral replication and new virus particle formation is thus important for developing new therapeutic targets . The HCV p7 protein is a virally encoded protein that is absolutely required for the production of new virus particles . It behaves as an ion channel when reconstituted into artificial lipid membranes but its function in infected cells is unknown . We have examined the possibility that p7 functions as an intracellular ion channel , preventing pH gradients from developing inside the cells . We have shown that p7 serves this function and it causes a loss of acidity in multiple intracellular compartments . We demonstrate that this alkalinization is required for successful virus production . Either direct inhibition of intracellular ATPases or replacement of p7 with an alternative ion channel is able to compensate for a defect in p7 and allow active virus to be produced . Therefore , HCV uses p7 to prevent cellular acidification processes . This understanding will allow for the targeting of this mechanism with novel therapeutic agents , and offers new insights into the mechanisms of liver pathogenesis during infection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"virology/virion",
"structure,",
"assembly,",
"and",
"egress",
"virology"
] |
2010
|
Intracellular Proton Conductance of the Hepatitis C Virus p7 Protein and Its Contribution to Infectious Virus Production
|
Development in multicellular organisms depends on the ability of individual cells to coordinate their behavior by means of small signaling molecules to form correctly patterned tissues . In plants , a unique mechanism of directional transport of the signaling molecule auxin between cells connects cell polarity and tissue patterning and thus is required for many aspects of plant development . Direction of auxin flow is determined by polar subcellular localization of PIN auxin efflux transporters . Dynamic PIN polar localization results from the constitutive endocytic cycling to and from the plasma membrane , but it is not well understood how this mechanism connects to regulators of cell polarity . The Rho family small GTPases ROPs/RACs are master regulators of cell polarity , however their role in regulating polar protein trafficking and polar auxin transport has not been established . Here , by analysis of mutants and transgenic plants , we show that the ROP interactor and polarity regulator scaffold protein ICR1 is required for recruitment of PIN proteins to the polar domains at the plasma membrane . icr1 mutant embryos and plants display an a array of severe developmental aberrations that are caused by compromised differential auxin distribution . ICR1 functions at the plasma membrane where it is required for exocytosis but does not recycle together with PINs . ICR1 expression is quickly induced by auxin but is suppressed at the positions of stable auxin maxima in the hypophysis and later in the embryonic and mature root meristems . Our results imply that ICR1 is part of an auxin regulated positive feedback loop realized by a unique integration of auxin-dependent transcriptional regulation into ROP-mediated modulation of cell polarity . Thus , ICR1 forms an auxin-modulated link between cell polarity , exocytosis , and auxin transport-dependent tissue patterning .
ROP ( Rho of Plants ) , also known as RAC GTPases , have been implicated as master regulators of cell polarity [1] , [2] . In their GTP-bound , active state , ROPs interact with downstream effector proteins to regulate organization of actin and microtubules ( MT ) , vesicle trafficking , production of phosphoinositides , and gradients of reactive oxygen species ( ROS ) and Ca2+ [1]–[6] . ROPs function at the plasma membrane to which they attach by virtue of posttranslational lipid modifications prenylation and S-acylation [1] , [7]–[9] . The ability of ROPs to interact with membranes allows these proteins to regulate actin polymerization and vesicle trafficking at discrete sites of the plasma membrane and of internal membranes , which is essential for their role in the control of cell polarity [10] . ROPs are polarly localized and expression of activated dominant ROP mutants that cannot hydrolyze GTP compromises cell polarization [1]–[6] and inhibits endocytic vesicle recycling [3] . Due to their essential role in generation of cell polarity , it was plausible that ROPs also regulate distribution of polar cargos including PIN auxin efflux transporters [11] . We have previously identified a ROP interacting coiled coil domain scaffold protein Interactor of Constitutive active ROP 1 ( ICR1 ) and demonstrated that it affects cell polarity [12] . Recently , ICR1/RIP1 has been implicated as a regulator of polar pollen tube growth [13] . The primary root meristem of icr1 mutant and RNAi silenced plants collapses soon after germination , resembling mutants affected in basal localization of PIN proteins and multiple pin loss-of-function mutants [14] . These results suggested that ICR1 might form a link between Rho-regulated cell polarity and polar auxin transport . Auxin is the major signal for tissue polarity and patterning in plants . Polar auxin transport and resulting asymmetric auxin distribution within tissues ( auxin maxima and gradients ) are essential for proper development of the embryo , the root , and the shoot , differentiation and regeneration of vascular tissues , and for tropic responses [14]–[18] . Directionality of auxin transport depends on polar subcellular distribution of PINFORMED ( PIN ) family of efflux transporters [11] , [19] , [20] . Dynamic PIN polarity is a result of constitutive endocytic recycling . Recycling to the membrane requires the function of the brefeldin A ( BFA ) -sensitive ADP ribosylation factor GDP/GTP Exchange Factors ( ARF GEFs ) [21] , [22] . The endocytic step is clathrin dependent and requires function of endosomal Rab5/Ara7 [14] , [23] . However , little is known on how PIN recycling is directed to result in their polar distribution . In this work we show that ICR1 is an essential component of the auxin transport machinery functioning in exocytosis and as a part of an auxin modulated feedback loop . Thus , ICR1 links between Rho-regulated cell polarity and auxin associated pattern formation .
To address the potential function of ICR1 in auxin transport , we examined auxin distribution in wild type ( WT ) Col-0 and icr1 mutant plants using the auxin sensitive reporters DR5::GUS and DR5rev::GFP [17] , [18] . The formation of the DR5-visualized auxin maximum in the quiescent center ( QC ) and proximal columella cells is required for root meristem maintenance and correct tissue patterning [18] . In young 2 days after germination ( DAG ) icr1 roots the auxin maximum was displaced towards the distal tier of root cap and was reduced ( Figure 1A and B ) . Concomitant with the reduction of the auxin maximum at the root tip , it started to accumulate in the vascular bundle ( Figure 1A ) . In older ( 14 DAG ) roots auxin accumulated in the vascular bundle but did not reach the tip ( Figure 1A ) . These results suggested that the collapse of the root meristem in icr1 plants resulted from compromised auxin transport and in-turn gradual disappearance of the auxin maximum at the root tip . The specification of the columella at the root tip is closely associated with the formation of a stable auxin maximum [18] . Columella cells contain starch granules that can be easily identified by staining of roots with Lugol staining ( IKI ) . No starch granules were detected in the collapsed primary roots of icr1 [12] , indicating that columella identity was lost . Because the stable auxin maximum was displaced in icr1 embryos and roots , it was plausible that columella cells may be specified in young roots but would later disappear , concomitant with the proximal shift of the auxin maximum . To examine the specification of the columella cells , the existence of starch granules was examined in WT and icr1 roots at 2 , 4 , and 6 DAG ( Figure 2 ) . In 2 DAG seedlings , starch granules were detected in two cell tiers , in both WT and icr1 root tips . At 4 DAG , starch granules were detected in 3 cell tiers of WT plants but remained confined to 2 cell tiers in the icr1 roots . Furthermore , the columella initials could not be detected in icr1 . At 6 DAG , WT roots had 4 columella cell tiers , while starch granules were barely detected or absent in the icr1 roots ( Figure 2 ) . These results indicate that columella identity is initially specified in icr1 root tip cells and then gradually disappears , concomitant with the diminishing local auxin maximum . In plants , the polar shoot to root axis and the primary shoot and root meristems develop during embryogenesis . These developmental processes are associated with stereotypical series of cell divisions and gene expression and depend on auxin distribution [17] . Development of WT and icr1 mutant embryos was analyzed to further establish the role of ICR1 in auxin distribution and embryo development . About 10% ( 27/273 ) of the icr1 embryos showed defects in stereotypic cell divisions of the basal embryo pole at the globular stage as well as abnormal divisions in the suspensor , including the uppermost cell , which forms hypophysis ( Figure 3A and Figure S1 ) . The majority ( 90% , 246/273 ) of the mutant embryos developed normally through the globular stage ( Figure S2 and Table S1 ) . From the triangular stage and onward , abnormal divisions of the suspensor , QC and columella cells were detected . Moreover , abnormal division planes were observed in the protoderm at the position of future cotyledons ( Figure 3A , Figure S2 , and Table S1 ) . The variable penetrance of the icr1 mutation also resulted in reduced developmental synchronization of embryos within single siliques . Whereas in WT siliques the embryos were found in two to three developmental stages , in icr1 siliques the embryos were spread between four and five stages ( Figure S3 ) , indicating that developmental delay in icr1 occurs at different stages . The data suggested that the loss of ICR1 function results in a gradient of phenotypic defects primarily at the places of auxin maxima and in processes requiring differential auxin distribution . Next we examined the auxin distribution in embryos to determine its association with the icr1 phenotype ( Figure 3B and Figure S4 ) . In comparison to WT , in the icr1 embryos the auxin response maximum was shifted distally from the QC to the lower tier of the future columella cells ( Figure 3B , arrow ) . Furthermore , ectopically strong DR5 activity was detected at the tip of the cotyledons ( Figure 3B , arrowheads , and Figure S4 ) . The abnormal auxin distribution coincided with the non-stereotypic divisions of the future root meristem , further suggesting that the developmental abnormalities in icr1 result from compromised auxin distribution . Root and embryo patterning and QC maintenance depend on highly specific expression pattern and subcellular localization of transcriptional regulators , including WOX5 ( WUSCHEL related homeobox 5 ) and SCR ( SCARECRAW ) , that define the stem cell niche [24]–[26] . In roots , formation of a stable auxin maximum is required for correct expression pattern of WOX5 , SCR , and an additional marker SHORTROOT ( SHR ) [18] , [27] . To verify that ICR1 is indeed involved in regulation of auxin distribution rather than this gene network , the expression of WOX5 and SCR in embryos was examined ( Figure 3C and 3D and Figures S5 and S6 ) . Both WOX5 and SCR were expressed in the icr1 mutant embryos , but their expression pattern was altered , reflecting changes in cell identity and disruption of the embryo polar axis . The embryo development and auxin response further suggested that the alterations in icr1 mutant plants are related to defects in auxin distribution . To further establish that the altered patterning in icr1 mutants resulted from compromised auxin transport rather than the genetic framework that regulates root development , we compared the expression of WOX5 , SCR , and SHR in WT and icr1 roots . This analysis showed that like in embryos , all the three markers were expressed in the icr1 roots ( Figure 4 ) . Similar to laser ablation experiments of the root meristem [27] , expression of WOX5 , SCR , and SHR appeared at more proximal locations in older , 14-d-old , icr1 roots and was associated with a formation of a new auxin maximum ( Figure 4A–C and Figure 1 ) . The abnormal expression pattern of WOX5 , SCR , and SHR in roots further suggested that the compromised root development of icr1 is associated with altered auxin distribution . To further examine the function of ICR1 in root patterning , we examined the expression pattern of PIN1 in icr1 roots . In the root , PIN1 is expressed mainly in the vascular cylinder . In icr1 mutant roots , however , pPIN1-driven PIN1-GFP expression was detected also in the epidermis and root hairs where it formed intracellular aggregates ( Figure 4D ) . The mis-expression of PIN1 was a further indication that the altered auxin distribution in icr1 mutant plants resulted from compromised auxin transport and is not an indirect effect of perturbations in auxin-independent patterning mechanisms . The initiation and growth of lateral roots are separable events that depend on local auxin accumulation and polar transport [15] , [28] . Given the function of ICR1 in primary root development , it was plausible that it would affect development of lateral roots . The primary root of icr1 mutant plants collapses before formation of lateral roots . However , the mutant plants develop adventitious roots that grow for some time and then collapse [12] . The formation of these adventitious roots is preceded by formation of local auxin maxima ( unpublished data ) . Lateral roots were initiated on these adventitious roots , but their growth was arrested after emergence ( Figure 4E ) . Often , multiple initiations of lateral roots were observed ( Figure 4E , inset ) , indicating that the onset as well as growth of lateral roots was perturbed in icr1 . In the icr1 arrested lateral roots , WOX5 was mis-expressed ( Figure 4E , compare left and right panels ) , indicating that the new root meristem was not properly setup . Taken together , these results indicate that in icr1 mutant plants the basic genetic framework that regulates root development is present and that the root meristem collapse , the altered organ development , and changes in cell identities can be attributed primarily to the compromised auxin distribution . The function of roots as an auxin sink has long been postulated to play a major role in vascular differentiation [29] . The “canalization hypothesis , ” which became a hallmark for explaining auxin-dependent patterning , postulates that differentiation and regeneration of vascular tissues depend on an auxin-regulated positive feedback loop [14] , [16] , [30] . That is , auxin induces a process that enhances its own transport from cells while inhibiting its transport in neighboring cells . This process eventually leads to the formation of auxin transporting cell files that differentiate into vascular tissues . Given the involvement of ICR1 in auxin transport , we suspected that the vascular tissues in icr1 mutant plants would be abnormal . Transverse sections through rosette leaves were prepared to compare the vascular tissues in WT and icr mutant plants . Analysis of these sections showed that the leaf veins in icr1 mutant plants are much reduced compared to WT ( Figure S7 ) . The reduced vascular tissues in icr1 mutants further suggested the involvement of ICR1 protein in auxin transport and that it could be part of an auxin modulated feedback loop . In summary , the detailed phenotype analyses using markers for the auxin response and major regulators of patterning in multiple auxin-regulated processes revealed pronounced defects in icr1 mutant plants that presumably result from the defects in auxin distribution . To examine a possible mechanism by which ICR1 mediates auxin distribution , we examined the localization and expression of PIN1 and PIN2 auxin transporters in WT and icr1 roots and embryos ( Figure 5 and Figures S8 , S9 , S10 , S11 , S12 ) . Immunolocalization analysis showed a defect in polar localization of PIN proteins , in more pronounced cases resulting in basal-to-apical shift of PIN1 in the stele and of PIN2 in the cortex of icr1 roots ( Figure 5A , see arrowheads , and Figure S8 ) . Consistently , in approximately 90% of the cells , reduced association of PIN1-GFP with the plasma membrane and basal to apical shift of PIN2-GFP of the cells in the cortex were observed ( Figures S9 and S10A ) . In the epidermis , PIN2 is primarily localized at the apical side of the cells and is resistant to BFA at this location [21] , [31] . PIN2 remained associated with the apical side of the icr1 root epidermis cells ( Figures 5A and S10A ) , suggesting that ICR1 primarily interacts with a BFA sensitive PIN delivery pathway . In globular icr1 embryos showing early developmental defects , GFP-PIN1 was not expressed at the basal pole , accumulated in large aggregates inside the cells , and was largely absent from the plasma membrane ( Figure 5B , arrow , and Figure S11 ) . In embryos with late developmental aberrations , obvious changes in PIN1-GFP localization started to appear at the early heart stage and were associated with intracellular PIN1-GFP aggregations and overall loss of polar membrane localization ( Figure 5B and Figure S11 ) . The differences between the immunolocalizations and the PIN1-GFP possibly reflect differences between embryo and root cells or higher stability GFP-PIN1 . Alternatively , the changes in auxin distribution affect pPIN1-driven PIN1-GFP expression such that it accumulates at higher levels in certain cells . Importantly , localization of the plasma membrane marker LTi-GFP was not affected in icr1 mutants ( Figure 5C ) , suggesting that ICR1 does not regulate targeting of membrane proteins in general . The model in Figure S12 summarizes the effects of ICR1 on embryo patterning , PIN1 localization , and auxin distribution . The reduced polarity and membrane association of PIN1 in icr1 embryos likely leads to defective polar auxin transport and thus to defects in formation of auxin maxima in embryonic root and cotyledons . The reduction in auxin levels is associated with inhibition of PIN1 expression in the provascular tissue . This leads , in turn , to failure of the auxin maximum formation causing a collapse of the root meristem . An auxin response element ( GTGCTC ) , which is located 254 base pairs ( bp ) upstream of the initiation AUG codon of ICR1 ( Figure S13 ) , indicated that ICR1 could be part of an auxin-induced positive feedback loop that influences polarity of auxin transport . It further suggested that ICR1 might integrate nuclear auxin signaling [32] and ROP-regulated cell polarity . To examine these hypotheses , we studied the ICR1 expression pattern and subcellular localization using a genomic clone of ICR1 fused to GFP ( Figure 6 and Figure S13 ) . In globular and torpedo stage embryos , GFP-ICR1 expression was observed throughout the embryo proper but interestingly not in the hypophysis and QC where a stable auxin maximum is formed ( Figure 6A ) . Similarly in roots , ICR1 was absent from the QC and the stem cells , positions of stable auxin maxima ( Figure 6A and 6B and Video S1 ) . The absence of ICR1 expression at the position of the auxin maxima correlated with non-polar PIN4 localization in the hypophesis , QC , and columella initials [33] . Several experiments were carried out to examine whether ICR1 expression is influenced by auxin . Expression analysis by quantitative real-time RT-PCR ( q-PCR ) showed that ICR1 expression is quickly induced following 30 min of incubation in auxin ( NAA ) ( Figure 6E ) . The expression of pICR≫GFP-ICR1 and pICR1≫GUS reporters following growth of seedling on medium containing the polar auxin transport inhibitor NPA ( 1-N-naphthylphthalamic acid ) and followed by addition of auxin ( NAA ) to the growth medium were studied . Confirming the prediction , ICR1 expression was lower when seedlings were grown on NPA and was induced as early as 4–6 h following treatment with NAA ( Figure 6E and Figure S14 ) . As shown above , lateral root development is compromised in icr1 ( Figure 4E ) . The initiation of lateral roots is induced by auxin and occurs at places of transient local auxin maxima [15] , [28] . Consistently , GFP-ICR1 expression was observed at positions of lateral root initiation ( Figure 6C ) , further indicating that ICR1 expression is induced by auxin . The absence of ICR1 in the QC and stem cells , where the stable auxin maximum is formed , was in apparent discrepancy to the induction of its expression by auxin and suggested that it might be suppressed by a different mechanism . To examine whether a stable auxin maximum could suppress ICR1 expression directly , auxin was applied locally to pICR1≫GFP-ICR1 roots , using small , 1 mm2 , agar particles that contained 10 µM NAA . Strong local GFP-ICR1 expression was observed in the auxin treated roots , while no increase was observed in control roots that were treated with agar particles without auxin ( Figure 6E ) . These results reconfirmed that ICR1 expression is induced by auxin and further suggested that stable auxin maxima , likely , do not suppress ICR1 expression directly . The site of the stable auxin maximum at the root tip was shown to express a specific group of genes [18] , [27] , [34] . Thus , possibly , the suppression of ICR1 expression is associated with specific cellular processes taking place at and around the site of the stable auxin maxima . To obtain further insight into regulation of ICR1 expression , we examined whether the suppression of its expression may be associated with the ICR1 gene or protein . To this end , a GFP-rop6CA reporter ( Poraty and Yalovsky , unpublished data ) was expressed under regulation of the ICR1 promoter . To reduce the possibility of differences in expression due to position effects , expression was carried out using the LhG4/pOp transcription/transactivation system [35] , [36] , using the same pICR1 promoter activator lines to express GFP-rop6CA , GUS , or GFP-ICR1 ( Figure S13 ) . In contrast to GFP-ICR1 , the GFP-rop6CA was observed in the QC and stem cells ( Figure 6B ) , indicating that indeed the suppression of ICR1 expression in the root meristem could be regulated by a mechanism associated with the ICR1 gene or protein . To summarize these data , while auxin induced transcription of ICR1 is part of a positive feedback loop that facilitates auxin transport , the suppression of ICR1 expression in the root meristem is associated with a cell-specific mechanism/s , presumably leading to inhibition of directional auxin transport , and contributes to the formation of a stable auxin maximum . Next , we examined whether the subcellular localization of GFP-ICR1 reflects ICR1 function in polar localization of PIN proteins . GFP-ICR1 complemented root growth in icr1 mutant plants ( Figure S15 ) . Furthermore , in pollen tubes , overexpression of either GFP-ICR1 or non-fused recombinant ICR1 had the same phenotypic effects [13] . It thus appears that localization of the GFP-ICR1 fusion protein reflected that of the native ICR1 protein . Importantly , GFP-ICR1 localization was not sensitive to BFA ( Figure 7D ) , consistent with earlier studies showing that recruitment of ICR1 to the plasma membrane is not ARFGEF- but ROP-dependent [12] , [13] . GFP-ICR1 was localized both at the plasma membrane and intracellularly . Plasma membrane localization was confirmed by plasmolysis , which induces detachment of membrane from the cell wall ( Figure S16 ) . In lateral root founder cells and embryos , GFP-ICR1 had polarized localization ( Figure 6C and 6D , arrowheads ) . In the primary root , the localization of GFP-ICR1 became progressively polarized away from the auxin maximum ( Figure 6D , arrowheads ) . The non-polarized ICR localization around the auxin maximum could contribute to the reduction of auxin transport leading to the formation of stable auxin maximum . The reduced polarity and association with the plasma membrane of PIN1 and PIN2 in the icr1 plants suggested that ICR1 is required for recruitment of the PIN proteins to the plasma membrane rather than their Rab5-regulated endocytic recycling [37] . Indeed , internalization of endocytosis tracer FM4-64 into BFA bodies occurred normally in icr1 mutant roots and embryos ( Figure 7A and 7B ) . Furthermore , similar to WT roots , PIN1-GFP and PIN2-GFP were internalized into the BFA bodies in icr1 roots ( Figures 7C and S10B ) . These data confirmed that endocytosis of FM4-64-labeled plasma membrane derived vesicles in general and of PIN1 and PIN2 in particular were not affected in icr1 mutant plants . The effects of BFA on endocytic recycling are reversible . When BFA is washed from the medium , the BFA bodies disappear and PIN proteins regain their localization in the plasma membrane [21] , [22] . BFA washout experiments were carried out to examine whether PIN dynamics is compromised in icr1 . Following incubation of GFP-PIN2 and GFP-PIN2 icr1 plants in BFA , the GFP-PIN2-containing BFA bodies appeared in 80% to 90% of the cells and no significant differences were found between WT and icr1 ( Figure 8A , 8C , and 8E ) . However , following a 2-h incubation in medium without BFA , 20%–27% of the cells in the icr1 roots still contained BFA bodies compared to only 2%–5% of the cells in WT plants ( Figure 8B , 8D , and 8E ) . The differences between WT and icr1 roots in the percentage of BFA bodies containing cells were statistically significant ( p≤0 . 001; Student's t test ) . These results reconfirmed that ICR1 is likely not involved in the Rab5-mediated endocytosis accumulation of PIN proteins following BFA treatments and indicated that ICR1 affects the recycling of PIN proteins back to the plasma membrane . Previously , we showed that ICR1 interacts with AtSEC3A exocyst complex subunit and that ROPs can recruit ICR1-SEC3 complexes to the plasma membrane [12] . This suggested that ICR1 could be involved in regulation of polarized exocytosis . To test this hypothesis , comparison of the distribution of a protein secretion marker , secGFP , in WT and icr1 mutant plants was carried out . SecGFP is a secreted form of GFP that is fused to the chitinase signal peptide at its N-terminus and to HDEL , ER-retention signal , at its C-terminus and has been used in analysis of protein trafficking [38] , [39] . Secretion of secGFP to the apoplast results in weak signal due to the relatively acidic pH of this compartment . Perturbation of secretion results in fluorescence of intracellular accumulating protein . Thus , the effect of a given mutant or treatment on secretion can be evaluated by monitoring the differences in fluorescence . Transgenic plants expressing secGFP [38] , [39] were crossed into the icr1 background . Qualitative and quantitative fluorescence imaging analyses showed that the GFP fluorescence in icr1 roots was significantly stronger ( p≤0 . 001; Student's t test ) than in WT roots ( Figure 9A and B ) . Fluorescence of secreted GFP can be recovered when seedlings are grown at a pH value higher than 8 . 1 [39] . To validate that the differences in GFP fluorescence between WT and icr1 roots were associated with protein secretion rather than an unrelated mechanism , seedlings were transferred from low ( pH 5 . 5 ) to high ( pH 8 . 5 ) pH medium . Quantitative analysis showed significant ( p≤0 . 01; Student's t test ) increase in GFP fluorescence of WT roots , while no increase was observed in icr1 roots ( Figure S17 ) . These data confirmed that the secGFP secretion was compromised in icr1 . High magnification fluorescent confocal images showed that in icr1 plants secGFP accumulated in punctuate structures ( Figure 9C ) . The internalized secGFP was not co-localized with FM4-64-labeled intracellular vesicles ( Figure 9D ) and did not accumulate in BFA compartment ( Figure 9E ) .
Our results show that ICR1 regulates directionality of polar auxin transport and is thus required for the formation of a stable auxin maximum and tip localized auxin gradient during embryogenesis , organogenesis , and meristem activity . Earlier work on auxin related patterning enforced the notion that patterns do not reflect a rigid program but rather the inherent developmental potential of each cell [30] . Results presented in this work imply that ICR1 is part of an auxin regulated positive feedback loop , integrating auxin-dependent transcriptional regulation with Rho family GTPases-mediated modulation of cell polarity . Thus , ICR1 forms an auxin-modulated link between cell polarity and auxin transport-dependent tissue patterning . Dynamic PIN polarity is achieved by ( 1 ) integration of a previously described constitutive endocytic recycling that involves clathrin-dependent endocytosis [14] , [23] and BFA-sensitive ARF GEFs-mediated recycling [21] , [22] and ( 2 ) a ROP-ICR1-regulated , BFA-insensitive exocytosis ( this work ) . ROP-ICR1 complexes were detected in the plasma membrane [12] , [13] . Furthermore , following plasmolysis a substantial fraction of pICR1 driven GFP-ICR1 remained associated with the plasma membrane ( Figure S16 ) . Thus , it is likely that ICR1 functions in conjunction with ROPs to recruit PIN proteins to specific sites in the membrane . Future analysis of PINs dynamics , using techniques such as Fluorescence Recovery After Photobleaching ( FRAP ) [37] , would be required to elucidate the interactions between ICR1-associated exocytosis and the BFA-sensitive PIN endocytic recycling . The exocytosis defects in icr1 are consistent with a previous finding that ICR1 can interact with both ROPs and AtSEC3A exocyst subunit at the plasma membrane [12] . Plants have an evolutionarily conserved exocyst complex [40] that based on mutational analysis was implicated in regulation of polarized secretion , cell morphogenesis , and patterning [40]–[43] . The reduced association of PINs with the membrane , their accumulation inside the cells in the icr1 mutant background ( Figure 5 and Figures S8 , S9 , S10 , S11 ) , and the slower recruitment of PIN2 to the plasma membrane following BFA washout ( Figure 8 ) indicate that ICR1 and possibly exocyst-dependent exocytosis acting at or close to the plasma membrane is required for proper PIN localization . Thus , in the absence of ICR1 , due to endocytic recycling , the PIN proteins are degraded or accumulate in the cells . Basal to apical shift of PIN1 and PIN2 have been associated with function of PINOID ( PID ) protein kinase as well as a BFA-insensitive pathway [14] , [31] . The basal to apical shift of PIN1 and PIN2 that were observed in icr1 suggests that ICR1 has either reduced or no effect on this BFA insensitive pathway . ROPs are recruited to the plasma membrane by virtue of the posttranslational lipid modifications prenylation or S-acylation that take place on conserved C-terminal cysteine residues [1] , [7] , [8] , [9] , [44] . In addition , at least some ROPs also undergo activation-dependent transient S-acylation and consequent partitioning into detergent resistant membranes that could be lipid rafts [9] . Association with the inner leaflet of the plasma membrane also requires a polybasic domain proximal to the lipid modified cysteines [8] . It has been shown that the polybasic domain in Rho proteins associates with phosphatidylinositol 4 , 5-bisphosphate ( PtdIns-P2 ) and phosphatidylinositol 3 , 4 , 5-trisphosphate ( PtdIns-P3 ) [45] . Consistently , in pollen tubes tip , ROP/RAC proteins were shown to physically associate with a phosphatidylinositol monophosphate kinase ( PtdIns P-K ) activity [46] , and PtdIns-P2 , the product of PtdIns P-K , had similar distribution [46] , [47] . When expressed in pollen tubes , ICR1/RIP1 and ROP1 stabilized the membrane localization of each other at the growing tip , suggesting that ICR1 may interact with other components in the membrane in addition to ROPs [13] . It appears therefore that determination of ROP-ICR1 subcellular localization involves multiple mechanisms , including different protein lipid modifications , partitioning into discrete membrane microdomains , and association with phosphatidylphosphoinositides and possibly with yet unidentified components . At the root tip , localization of GFP-ICR1 became progressively associated with the plasma membrane and polarized in cells that were more distantly located away from the stable auxin maximum ( Figure 6D ) . This suggests that membrane localization and polarization of ICR1 are locally regulated , possibly by a local auxin gradient associated mechanism . Auxin modulates its polar efflux from cells by inhibiting PIN endocytosis [48] and possibly by regulating the expression of ICR1 ( this work ) . Thus , ICR1 may be part of an auxin modulated positive feedback loop that facilitates auxin efflux . ICR1 expression in the root ( Figure 6 ) coincides with pattern of auxin flux and with non-polar localization of PIN4 in the sites of the auxin maxima in the hypophesis , QC , and columella initials [14] , [33] . In most regions of the primary root , the expression of ICR1 is limited to the stele ( Figure 6 ) . The expression pattern changes in two regions: ( 1 ) lateral root founder cells and initials and ( 2 ) around the root tip where expression is detected in epidermis , cortex , endodermis , and the root cap . The stable auxin maximum and local gradient at the root tip are associated with expression of specific genes . The expression level of some of these genes has been shown to correlate with auxin levels [27] , [34] , [49] . It is likely that the repression of ICR1 expression in the QC and the meristematic stem cells is associated with one or some of these auxin maximum-specific genes . The quick induction of ICR1 expression by auxin and the strong expression of pICR1-driven GFP-ICR1 by local application of auxin further suggest that suppression of ICR1 expression at the site of auxin maxima is indirectly regulated by auxin . Interestingly , mutants in the HALTEDROOT ( HLR ) gene , which encodes an RPT2a 26S proteasome subunit , share a similar phenotype with icr1 . Like icr1 , the root meristem of hlr collapses , the QC is lost , and expression pattern of several markers including SCR and SHR is altered [50] . In contrast to icr1 , however , additional tiers of columella cells , compared to WT , were observed in 6-d-old hlr seedling , while in icr1 plants , of similar age , the specification of the columella is significantly reduced ( Figure 2 ) . No differences in the icr1 expression pattern were observed when pICR1≫GFP-ICR1 plants were treated with a proteasome inhibitor ( unpublished data ) . Thus , it is currently unclear whether the proteasome is involved in regulation of ICR1 expression . Based on computational modeling , it has been proposed that the PIN-mediated auxin fluxes in the root are sufficient for maintaining a stable auxin maximum [51] . Results of this work ( Figure 6 ) implicate the repression of ICR1 expression and possibly also regulation of its subcellular localization in the formation of the stable auxin maximum . The stable auxin maximum may facilitate a positive feedback loop that maintains the repression of ICR1 expression and its distribution in the immediate proximal and subtending cells . Constitutive active ROP-induced cell deformation has been associated with reorganization of actin and MT cytoskeleton , as well as compromised vesicle uptake at the plasma membrane [1] , [2] . Ectopic expression of ICR1 induced deformation of leaf epidermis pavement cells and root hairs [12] as well as pollen tubes [13] , resembling the effect of activated ROP mutants . Thus , ICR1 may act as a scaffold that facilitates compartmentalization of ROPs and other proteins such as the exocyst complex at specific membrane domains [12] . This also suggests that ICR1 could be involved in regulation of various processes . ROPs orchestrate cell polarization by regulating cytoskeleton organization through proteins that include RIC1 ( ROP Interacting CRIB containing 1 ) , RIC3 and RIC4 [52] , [53] , ADF/Cofilin [54] , and the WAVE and Arp2/3 complexes [55] , [56] . As shown in this work and based on previous findings [12] , the ROP-ICR1-associated cell polarization machinery is required for plasma membrane recruitment and polar localization of PIN proteins , consequently directing auxin transport .
Total RNA was isolated with “SV Total RNA isolation” according to the manufacturer's instructions ( Promega , Madison ) . cDNA first strand synthesis was carried out using Super ScriptII reverse transcriptase ( Invitrogen Carlsbad , USA ) . Quantification with the oligonucleotide primer set SY1582: TCAAAATGCCAAGACCAAGA and SY1583: TTGGAATGATTGGAATCAGAAG was carried out by q-PCR using an ABI Prism 7700 StepOnePlus™ Instrument ( Applied Biosystems , Weiterstadt , Germany ) . Study samples were run in triplicate on 8-well optical PCR strips ( Applied Biosystems ) in a final volume of 10 µl . Primers were designed using Roche Universal Probe Library ( https://www . roche-applied-science . com/sis/rtpcr/upl/index . jsp ) . The PCR cycles were run as follows: 10 min initial denaturation at 95°C , followed by 40 subsequent cycles of 15 s denaturation at 95°C , and 1 min annealing and elongation at 60°C . The specificity of the unique amplification product was determined by a melting curve analysis according to the manufacturer's instructions ( Applied Biosystems , Weiterstadt , Germany ) . Relative quantities of RNA were calculated by the ddCt method ( Applied Biosystems Incorporated ( 2001 ) , User Bulletin #2: ABI PRISM 7700 Sequence Detection System , http://www . appliedbiosystems . com ) . cDNA dilution series were prepared to calculate amplification efficiency coefficient . The relative levels of RNA were calculated according to the amplification efficiency coefficient and normalized against an UBQ21 gene standard [58] , whose level was taken as 1 . The stability of the standard in each experiment was verified with the geNorm analysis tool ( http://medgen . ugent . be/jvdesomp/genorm/ ) and was calculated as M≤0 . 7 . The analysis was repeated with three independent biological replicates . Seeds of WT Columbia-0 ( Col-0 ) and mutant Arabidopsis plants were sown on soil ( Universal potting soil , Tuff Moram Golan , Israel ) and left for 2 d at 4°C . Then , plants were transferred to a growth chamber and were grown under long-day conditions ( 16 h light/8 h dark cycles ) at 22°C . The light intensity was 100 µE m−2 s−1 . For seedling analysis , seeds were surface sterilized and sown on plates containing 0 . 5× Murashige & Skoog ( 0 . 5× MS ) salt mixture ( Duchefa ) titrated to pH 5 . 5 with MES and KOH , 1% sucrose , and 0 . 8% plant agar ( Duchefa ) and left for 2 d at 4°C . Then plates were transferred to the growth chamber and grown under long-day conditions ( 16 h light/8 h dark cycles ) at 22°C for an indicated period . The light intensity was 100 µE·m−2·s−1 . For auxin induction experiments , seedlings were germinated on plates ( as above ) for 5 d , then transferred to liquid medium ( 0 . 5× MS ) , and grown for 2 additional days before application of either NPA ( 10 µM ) or NAA ( 10 µM ) . β-Glucoronidase ( GUS ) staining was carried out as previously described [59] , except that seedling were submerged in the staining solution for 2 h and then clarified in either chloralhydrate/glycerol/water ( 8∶1∶2 ) or 70% ethanol . Clearing of Arabidopsis embryos was performed as previously described [60] . In short , growing siliques were harvested from soil-grown plants and dissected under a stereo-microscope . Ovules from individual siliques were collected and fixed for 1–4 h in ethanol/acetic acid ( 6∶1 ) at room temperature . Then , ovules were washed three times for 5 min in 100% ethanol and one time in 70% ethanol . In turn , the ovules were incubated in a clearing solution ( chloralhydrate/glycerol/water 8∶1∶2 v/v ) for 24 h , mounted on slide with 30% glycerol , and observed by Nomarsky Differential Interference Contrast ( DIC ) optics . Seedlings of indicated age were transferred into Lugol ( IKI—0 . 2% w/v iodine and 2% potassium iodine ) and incubated for 3 min . The Lugol-stained seedlings were then briefly washed with water and mounted on the slide with a clearing solution ( chloral hydrate in 30% glycerol ) . Small solid medium ( 0 . 5× MS , 1% sucrose , neutral red , 0 . 8% plant agar ) particles , approximately 1 mm2 in diameter , with or without 10 µM NAA were applied onto roots of vertically grown 7-d-old pICR1≫GFP-ICR1genomic seedlings 5 mm above the root-tip . GFP-ICR1 expression was observed 24 h after the treatment . Nomarsky/DIC imaging was performed with an Axioplan-2 Imaging microscope ( Carl Zeiss , Jena , Germany ) equipped with an Axio-Cam , cooled charge-coupled device ( CCD ) camera by using either 40× or 100× oil immersion objectives with numerical aperture ( NA ) values of 1 . 3 or a 63× water immersion objective with NA value of 1 . 2 . Low magnification imaging was carried out with Olympus MVX10 fluorescence stereomicroscope . CLSM imaging was performed with Leica TCS-SL CLSM with 20× multi-immersion , 63× water , and 63× water dipping ( cover slide-free ) objectives with NAs of 0 . 7 , 1 . 2 , and 0 . 9 , respectively . Four-day-old GFP-PIN2 and GFP-PIN2 icr1 seedlings were treated with 50 µM BFA for 1 h and then washed with 0 . 5× MS medium for 2 h . For calculation of epidermal cells with BFA bodies , at least 15 roots were used for each line and treatment . The experiment was repeated three times . Statistical analysis was performed with Student's t test . Analysis of secretion was performed as previously described [38] , [39] . Transgenic Arabidopsis homozygous line expressing 35S::secGFP in the Col-0 background was crossed to icr1 . T2 progeny homozygous for both icr1 and secGFP were selected . Seedlings were grown on 0 . 5× MS plates ( pH 5 . 5 ) supplemented with 1% sucrose for the indicated time . Images of WT and icr1 root tips were taken with Leica LCS LSCM under identical conditions using a 10× objective , fully opened pinhole ( 600 µm ) and emission/excitations of GFP as described above . The mean signal intensity was measured on an area spanning up to 500 µm from the root tip , using Image-J . DIC images of the same root were used for the adjustment of the measured area . At least 20 seedlings of each line were used in each experimental repeat . Statistical analysis was performed with Student's t test .
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The coordination of different cells during pattern formation is a fundamental process in the development of multicellular organisms . In plants , a unique mechanism of directional transport of the signaling molecule auxin between cells demonstrates the importance of cell polarity for tissue patterning . The direction of auxin flow is determined by polar subcellular localization of auxin transport proteins called PINs , which facilitate auxin efflux . At the same time , an auxin-mediated positive feedback mechanism reinforces the polar distribution of PINs . However , the molecular mechanisms that underlie polar PIN localization are not well understood . In eukaryotic cells , the Rho family of small GTPases function as central regulators of cell polarity . We show that a Rho-interacting protein from plants , called ICR1 , is required for recruitment via the secretory system of PIN proteins to polar domains in the cell membrane . As a result , ICR1 is required for directional auxin transport and distribution and thereby for proper pattern formation . In addition , both the expression and subcellular localization of ICR1 are regulated by auxin , suggesting that ICR1 could function in a positive feedback loop that reinforces auxin distribution . Thus , ICR1 forms an auxin-modulated link between cell polarity , protein secretion , and auxin-dependent tissue patterning .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology",
"cell",
"biology/cell",
"signaling",
"cell",
"biology/morphogenesis",
"and",
"cell",
"biology",
"plant",
"biology/plant",
"cell",
"biology",
"cell",
"biology",
"developmental",
"biology/pattern",
"formation",
"developmental",
"biology/plant",
"growth",
"and",
"development",
"cell",
"biology/membranes",
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"sorting",
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"biology/plant",
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"and",
"development",
"cell",
"biology/plant",
"cell",
"biology",
"developmental",
"biology/molecular",
"development"
] |
2010
|
A Rho Scaffold Integrates the Secretory System with Feedback Mechanisms in Regulation of Auxin Distribution
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Patients with HTLV-1-associated myelopathy/tropical spastic paraparesis ( HAM/TSP ) become progressively impaired , with chronic pain , immobility and bladder , bowel and sexual dysfunction . Tested antiretroviral therapies have not been effective and most patients are offered a short course of corticosteroids or interferon-α , physiotherapy and symptomatic management . Pathogenesis studies implicate activated T-lymphocytes and cytokines in tissue damage . We therefore tested the hypothesis that inhibition of T-cell activation with ciclosporin A would be safe and clinically beneficial in patients with early and/or clinically progressing HAM/TSP . Open label , proof of concept , pilot study of 48 weeks therapy with the calcineurin antagonist , ciclosporin A ( CsA ) , in seven patients with ‘early’ ( <two years ) or ‘progressive’ ( >50% deterioration in timed walk during the preceding three months ) HAM/TSP . Primary outcomes were incidence of clinical failure at 48 weeks and time to clinical failure . All patients completed 72 weeks study participation and five showed objective evidence of clinical improvement after 3 months treatment with CsA . Two patients exhibited clinical failure over 6 . 4 person-years of follow-up to week 48 . One patient had a >2 point deterioration in IPEC ( Insituto de Pesquisa Clinica Evandro Chagas ) disability score at weeks 8 and 12 , and then stopped treatment . The other stopped treatment at week 4 because of headache and tremor and deterioration in timed walk , which occurred at week 45 . Overall pain , mobility , spasticity and bladder function improved by 48 weeks . Two patients recommenced CsA during follow-up due to relapse . These data provide initial evidence that treatment with CsA is safe and may partially reverse the clinical deterioration seen in patients with early/progressive HAM/TSP . This trial supports further investigation of this agent's safety and effectiveness in larger , randomised controlled studies in carefully selected patients with disease progression .
An estimated 20 million people are infected with HTLV-1 worldwide [1] of which approximately 8% ( ∼2 million ) will develop HTLV-1-associated diseases , most notably adult T-cell leukaemia/lymphoma ( ATLL ) [2] , HTLV-1-associated myelopathy/tropical spastic paraparesis ( HAM/TSP ) [3] , HTLV-1-associated uveitis ( HAU ) [4] and infective dermatitis [5] . An association between myelopathy and HTLV-1 seropositivity in serum and cerebrospinal fluid ( CSF ) was first reported in 1985 , in patients with Tropical Spastic Paraparesis ( TSP ) in Martinique [3] , and independently in Japan in 1986 , where the condition was termed HTLV-1-associated myelopathy ( HAM ) [6] . It is accepted that HAM/TSP , a chronic and progressive spastic paraparesis in patients living in both endemic and non-endemic countries [7] , [8] , [9] , is an inflammatory condition [10] . But almost thirty years after its discovery little is known about how best to treat HAM/TSP [11] . Although corticosteroids [12] , [13] and interferon-α/β [14] have been used as therapy for HAM/TSP , they are only of transient benefit ( weeks ) , cause serious side-effects and have not been compared to placebo . Particular challenges to designing clinical trials in HAM/TSP include the uncertainties relating to the following questions: In 2006 a revision of the original WHO diagnostic criteria of HAM/TSP allowed ascertainment of three diagnostic levels: definite , probable and possible after excluding all conditions that could mimic HAM/TSP [15] . To monitor clinical progression of HAM/TSP and therapy response , clinicians now differentiate between i ) early and late ii ) clinically progressive and non-progressive and iii ) active and inactive definite HAM/TSP [11] , [16] ( and personal communication with the HAM/TSP clinical trial subgroup ) . Immunosuppressive therapy is especially attractive in patients with early , clinically progressive , or active HAM/TSP , which are defined as onset of symptoms ≤2 years , evidence of clinical progression , such as deterioration of timed walk or progression in disability scales , or evidence of CNS inflammatory activity from cerebrospinal fluid ( CSF ) analysis retrospectively . However immunosuppressive therapy given to patients with HTLV-1 infection may increase the chance of developing ATLL . Cases of ATLL following organ transplantation , for which much greater immunosuppression is prescribed than in this study , have been reported but the risk has not been quantified for any specific immunosuppressive treatment [17] , [18] , [19] , [20] , [21] , [22] . Also the optimal duration of any therapy for patients with HAM/TSP has never been examined and due to its side-effects long-term administration of corticosteroids , the most commonly prescribed first line treatment , is not recommended . With the aim to identify a long-term , safe corticosteroid-sparing immunosuppressive therapy for patients with HAM/TSP , we conducted an open , proof of principle study , which examined the potential clinical and immunological efficacy and the safety of Ciclosporin A ( CsA ) in patients with early , progressive HAM/TSP ( September 2006 to January 2010 , NCT00773292 ) . CsA is used routinely and long-term in post-allergenic organ transplants as well as inflammatory dermatological and musculoskeletal disease such as psoriasis , ectopic dermatitis and rheumatoid arthritis . It has also been used for idiopathic uveitis and severe cases of immune-mediated haemolytic anaemia . The primary objective of this study was to determine whether CsA treatment for 48 weeks improved clinical outcome measures of patients with early or progressing definite HAM/TSP . The secondary objectives were to determine i ) the safety of CsA , ii ) the effects of CsA on HTLV-1 proviral load in blood and CSF and iii ) the effect of CsA on markers of T-cell activation and proliferation . The study also explored the mechanism of pathogenesis of HAM/TSP by analysing the effect of CsA on the severity and progression of HAM/TSP .
The study protocol , patient information sheet and consent form were submitted to the National Research Ethics Service and approved by the Oxfordshire ‘A’ Research Ethics Committee ( Reference 06/Q1604/75 ) ; Clinical Trial Registration: Clinicaltrials . gov: NCT00773292 . Eligible patients had definite HAM/TSP , as defined by ‘Belem criteria’ [15] and either had developed first symptoms within the last two years or had progressive disease , as defined by ≥50% documented deterioration in 10 m timed walk over the preceding three months . All patients were older than 16 years , not pregnant or breastfeeding , and were serologically negative when tested for HIV 1/2 , HBV , HCV , syphilis and Strongyloides stercoralis . There was no evidence of pulmonary tuberculosis on chest x-rays and none of the patients had a history of malignant or autoimmune disease . After giving written informed consent , patients attending the National Centre for Human Retrovirology at St Mary's Hospital , London , underwent two baseline visits at least one day and no more than four weeks apart and trial therapy was commenced after the 2nd baseline visit . Patients were recruited sequentially and initially treated with oral CsA 2 . 5–5 mg/kg/day divided into two , 12-hourly doses and subsequently dose-adjusted to maintain plasma trough levels between 80–100ng/ml for 48 weeks with CsA plasma concentrations monitored at each on-treatment study visit . Post-treatment patients were followed for an additional 24 weeks . The primary outcome measures were i ) incidence of clinical failure at 48 weeks and ii ) time to clinical failure . Clinical failure was defined as any of the following i ) lack of any objective improvement after three months of therapy , ii ) greater than two point deterioration ( increase ) in the IPEC 1 scale compared with baseline at two consecutive visits excluding weeks 2 and 4 and iii ) ≥30% deterioration in timed walk compared with baseline at any time during the trial . Objective improvement was defined as any of the following comparing baseline measurements to 12 , 24 and 48 weeks: i ) one point decrease in the IPEC 1 scale ( Instituto de Pesquisa Clínica Evandro Chagas ) , ii ) >30% improvement in 10 m timed walk , iii ) visual analogue pain score reduced by >2 points , iv ) reduction of frequency or nocturia by greater than one or reduction of residual volume by more than 10% at two consecutive visits . Secondary outcomes were the following clinical and laboratory variables measured at 12 , 24 , 48 and 72 weeks: Seconds needed to walk 10 meters ( sec/10 m TW ) , change in walking aid , maximum pain ( visual analogue score 0–10/10 cm VAS ) , modified Ashworth scale score ( MASS , Appendix S1 ) , walking scale ( MSWS-12 , Appendix S2 ) , IPEC 1 and 2 disability scale score ( Appendix S3 ) , bladder sphincter function ( daily self-assessment and ultrasonic measurement of the residual and urgency urinary volume ) , spasticity scale ( SPAST-88 , Appendix S4 ) , SF-36 quality of life scale ( Appendix S5 ) , HTLV-1 proviral load in venous blood and in CSF , total CD4+ lymphocytes , CD8+ lymphocytes and %CD4+CD25+ T lymphocytes counts and plasma β2 microglobin as inflammatory markers .
We aimed to recruit eight patients . Of the nine eligible patients with definite , early or progressing HAM/TSP informed of the study , seven agreed to participate ( Figure 1 ) . Baseline demographic , clinical and laboratory characteristics of the patients are shown in Table 1 . Patients were on average 50 years old ( range 40–69 ) , mostly female ( 5 of 7 ) and of Afro-Caribbean origin having acquired HTLV-1 either through mother-to-child transmission or sexual intercourse . As per protocol one patient with early disease ( 0 . 8 years ) was entered into the study without a three months follow up period . The remainder had progressing disease with documented deterioration in timed walk >50% over the previous three months . All seven patients initiated treatment with body weight adjusted CsA ( 2 . 5 mg/kg/day ) with a median daily dose of 180 mg ( range 160–240 ) . The median trough CsA concentration from the 59 measurements was 87 mg/ml ( range 46–164 ) with 44% of all measurements within the target range ( Figure 2 ) . Patients were followed up for a median of 74 weeks ( range 71–92 ) . Five patients ( 72% ) completed the 48 weeks of treatment without interruption . Two of these patients requested to re-start CsA during the 24 week post therapy follow-up period due to clinical deterioration which they attributed to stopping CsA . Over 6 . 4 person-years follow-up to 48 weeks , no patient failed according to the first primary outcome criterion i . e . objective improvement was observed in all patients . However four patients met the 2nd and 3rd criteria for clinical failure by 48 weeks , which gives an incidence of 0 . 6 per person-year , although only two were true clinical failures as detailed below . One patient failed on the second criterion with a >2 point deterioration of IPEC1 scale on two consecutive visits during therapy at visit weeks 8 and 12 . This patient , with a history of urinary tract infections ( UTI ) , developed a further UTI and became depressed during treatment with CsA , which was discontinued at week 16 . Of the three patients who failed due to >30% deterioration in TW ( 3rd criterion ) , two were technical failures ( at weeks 4 and 33 respectively ) with temporary deteriorations due to accidents rather than progression of HAM/TSP and both continued CsA . The third patient developed headache and tremor attributed to CsA which was discontinued at week four but the deterioration in TW was documented at week 45 , off treatment . By intention-to-treat , 2/7 patients clinically failed this trial , and both had to discontinue CsA due to side-effects . All patients remained normotensive with no evidence of nephrotoxicity . Grade 1/2 serious adverse events were documented in four patients: one patient developed community acquired pneumonia at week 2 , which was thought not to be due to CsA treatment , since she was known to have bronchiectasis and did not develop any further infections during 48 weeks of CsA treatment . One patient developed an acute urinary tract infection as well as acute depression during week 7 . Both were not thought to be CsA related by the Data and Safety Monitoring Committee ( DMSC ) , but the patient herself opted against CsA , which was stopped . Tremor and headache , which were reported by the third patient at week 6 , are well described side effects and their pathogenesis with CsA is not well understood . Tremor was the only side-effect that was thought to be truly due to CsA in this patient and it resolved with treatment cessation . The patient's headaches were adjudged to be possibly due to long term fungal sinus infection which was retrospectively reported on a pre-trial head CT scan . The headaches did not resolve when CsA was stopped . Although many concomitant medications were taken by the study participants both for symptomatic management of HAM/TSP and for co-existent pathologies , changes to treatments that could have influenced clinical outcomes , e . g . muscle relaxants for spasticity or sympathomimetics for urgency , were avoided during the study .
A recently published review of all therapy studies in patients with HAM/TSP found that only 86 patients with HAM/TSP have to date taken therapy within randomised controlled trials [11] . Two of these studies , enrolling a total of 40 patients , have found the approach of attempting to reduce HTLV-1 proviral burden by inhibiting HTLV-1 reverse transcriptase to improve symptoms , to be disappointing [23] , [24] . Other open label , proof of concept studies with immune-modulators such as humanised anti-Tac ( daclizumab ) and interferon-β1 have reported a decrease in peripheral HTLV-1 DNA or tax RNA proviral load as well as some improvement of motor function with dacluzimab [25] , [26] . Open , observational studies describe short term improvement in motor function of HAM/TSP patients with corticosteroids or interferon-α ( IFNβ ) [12] , [13] . An open , randomised trial compared the efficacy of three dosages of IFNα and demonstrated transient , beneficial effects most marked with the highest dose [14] . The aim of the current study was to identify a safe , long-term , oral , corticosteroid sparing , anti-inflammatory and immunosuppressive treatment option for patients with HAM/TSP . CsA , was selected to determine whether the course of a disease which is believed to be caused by heightened immune activation against chronic HTLV-1 infection could be modified by modulating T-cell activation , thereby giving further insight into pathogenesis . The chief characteristic that distinguishes this trial from all other clinical trials in HAM/TSP are the very strict eligibility criteria , allowing recruitment of only those patients with early or progressing disease . It was considered that these patients would be most likely to benefit from medical intervention and that this would reduce the likelihood of under-estimating the potential of therapy . Although the comparison of the investigational drug with a placebo or another treatment option was not considered appropriate in the absence of any safety or efficacy data in patients with HAM/TSP , a comparison of on treatment data with each patient's his/her own repeat baseline measures are useful to identify a treatment signal in a small group of patients . None of the patients were lost to follow up and all were followed up at the set time points prospectively aiming to capture pre , on and post treatment data . CsA's effect on disease was described by area under the curve analyses , a useful tool in summarising changes over time in a small number of patients whose measurements tend to fluctuate . However , due to the small sample size and number of outcomes analysed , the statistical results presented should be interpreted with caution . The sample size is small for two reasons , one because of the stringent recruitment criteria , recruiting only “early and/or progressing” HAM/TSP and two to make sure this treatment , whilst known to be fairly safe and well tolerated given for other conditions , would also be safe in HTLV-1 infected patients who have a 4–6% background risk of developing ATLL . This study focused on capturing specifically improvement in mobility as well as safety with CsA since these are the two most important outcomes to patients . Reassuringly CsA was well tolerated by 5/7 patients for 48 weeks , did not have any severe adverse outcomes at 48 or 72 weeks and most importantly no patient has been diagnosed with any malignant disease or opportunistic infection during routine follow up to July 2011 ( up to 5 years additional follow up ) . We measured the time a patient takes to walk 10 meters , taking into account aid usage , as well as IPEC 1 disability scale as outcome measures apart from objective overall improvement . 10 m timed walk increased the sensitivity of measuring change in mobility , while IPEC 1 , which like Osame's Motor Disability Scale ( OMDS ) was developed specifically for patients with HAM/TSP , included many other clinical symptoms of HAM/TSP , although it's assessment of gait is crude . In this study patients , whose mobility was deteriorating at baseline , showed an overall clinical improvement after initiating treatment with CsA within a short period of time ( 6 months ) . CsA treatment was associated with specific improvements in timed walk corrected for aid usage , pain , spasticity , daily urinary frequency and nocturia . This degree of improvement was unexpected , since five patients had been symptomatic for a long time ( >2 . 5 to 17 years ) including , as illustrated in Figure 10 , patients with marked thoracic cord atrophy . Interestingly , despite the TDM driven dose adjustments CsA trough concentrations were below the target minimum on 33 . 9% of occasions , therefore the potential efficacy of CsA may have been underestimated in this study . Two patients opted to restart treatment during the follow up phase , due to worsening of symptoms after 48 weeks of treatment . Although CsA treatment seemed to yield most clinical benefits by 24 weeks the laboratory markers continued to improve up to 48 weeks . In the subset of patients with high baseline concentrations plasma β2 microglobulin normalised . β2 microglobulin , which has recently been demonstrated to distinguish patients with HAM/TSP from HTLV-1 asymptomatic carriers with a relationship between concentration and degree of motor disability [27] should therefore be tested in larger clinical trials as a peripheral blood surrogate marker of HAM/TSP response to therapy . The observed reductions in β2 microglobulin and CD4+ CD25+ T cell frequency are encouraging both in their own right and particularly in association with the clinical findings . Furthermore the unexpected , albeit small reduction in HTLV-1 proviral load , which appears to be independent of the change in CD4+CD25+ frequency ( data not shown ) suggests that clinical benefits of immunosuppressive therapy were not at the expense of reduced HTLV-1 specific immunity . In theory a reduction HTLV-1 infected CD4+ CD25+ cells would be associated with a reduction in total HTLV-1DNA load but the reduction in CD4+ cells expressing CD25+ may also occur in HTLV-1 uninfected cells as a direct consequence of CsA therapy or even secondary to a reduced host response to secondary to a reduction in the number of cells capable of expressing viral proteins . High HTLV-1 proviral load in CSF , compared with PBMCs , is recognised as a marker of HAM/TSP [28] , [29] . The four-fold greater reduction in HTLV-1 proviral load in the CSF compared with PBMCs , therefore seems biologically significant , the more so for being independent of other , traditional markers of CSF inflammation such as lymphocyte counts and protein . One possibility is that with T-cell activation inhibition , fewer infected CD4+ T cells were migrating across the blood-brain barrier . This observation needs to be further tested in future studies including later sampling post therapy to determine the duration/reversibility of this change . The optimal duration of therapy remains unknown . Whilst some participants maintained an improved clinical status after discontinuing therapy after 48 weeks others appeared to relapse early . Future , larger , clinical trials of CsA , should therefore consider treating patients for at least 48 weeks . One study participant recently relapsed again after stopping CsA for the second time , after 4 years of therapy . In conclusion CsA , a steroid-sparing immunosuppressive agent , was associated with improved disease outcome in patients with early or progressing HAM/TSP at 24 and 48 weeks follow up . This finding suggests that activated lymphocytes contribute to pathogenesis . This study also demonstrates that close monitoring , even of patients with long standing HAM/TSP , is important to detect those with clinically progressive disease who may benefit from disease modifying therapy . A multi-centre , international randomised controlled trial in patients with early and/or progressive HAM/TSP is the next step towards the establishment of an internationally acknowledged treatment protocol . Therefore the currently most commonly prescribed drug for active HAM/TSP , corticosteroids , as well as steroid sparing drugs such as INF-α , INF-β and CsA should be studied in larger phase 2 studies either in placebo-controlled or head-to-head comparative randomised controlled trials .
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HTLV-1 is a retrovirus transmitted through body fluids that is commonly seen in the West Indies , South America and Southern Japan but rarely in the UK . Although most patients remain healthy carriers , HTLV-1 causes serious conditions such as adult T cell leukaemia/lymphoma ( ATLL ) and HTLV-1-associated myelopathy/Tropical Spastic Paraparesis ( HAM/TSP ) . The infection which is life-long cannot be eradicated and treatments for the associated diseases are limited . We report the encouraging findings of the first UK Medical Research Council funded treatment study for patients with early and/or deteriorating HAM/TSP . Treatment with ciclosporin A , a drug commonly used to dampen the immune system in transplant patients , was investigated . Symptoms and signs of disease , particularly low back pain and muscle stiffness , improved by week 24 and in some patients this improvement persisted after the 48 weeks of treatment , at least to the end of the study at week 72 . Most striking was the finding that the amount of HTLV-1 in the fluid around the spinal cord , called cerebrospinal fluid , was reduced during treatment . These findings justify the further study of ciclosporin A in patients with HAM/TSP .
|
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"Abstract",
"Introduction",
"Materials",
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"Methods",
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"medicine",
"infectious",
"diseases",
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2012
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Ciclosporin A Proof of Concept Study in Patients with Active, Progressive HTLV-1 Associated Myelopathy/Tropical Spastic Paraparesis
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The Plasmodium falciparum erythrocyte membrane protein 1 ( PfEMP1 ) antigens play a major role in cytoadhesion of infected erythrocytes ( IE ) , antigenic variation , and immunity to malaria . The current consensus on control of variant surface antigen expression is that only one PfEMP1 encoded by one var gene is expressed per cell at a time . We measured var mRNA transcript levels by real-time Q-PCR , analysed var gene transcripts by single-cell FISH and directly compared these with PfEMP1 antigen surface expression and cytoadhesion in three different antibody-selected P . falciparum 3D7 sub-lines using live confocal microscopy , flow cytometry and in vitro adhesion assays . We found that one selected parasite sub-line simultaneously expressed two different var genes as surface antigens , on single IE . Importantly , and of physiological relevance to adhesion and malaria pathogenesis , this parasite sub-line was found to bind both CD31/PECAM1 and CD54/ICAM1 and to adhere twice as efficiently to human endothelial cells , compared to infected cells having only one PfEMP1 variant on the surface . These new results on PfEMP1 antigen expression indicate that a re-evaluation of the molecular mechanisms involved in P . falciparum adhesion and of the accepted paradigm of absolutely mutually exclusive var gene transcription is required .
Plasmodium falciparum is the most pathogenic human malaria parasite and a major cause of morbidity and mortality in Africa . Its pathogenesis is closely associated with the adhesive properties of the variable erythrocyte surface antigens , PfEMP1 , encoded by the var gene family [1] . These adhesins force erythrocytes infected with the parasite to bind to host receptors such as CD36 , CD31/PECAM1 and CD54/ICAM1 on the endothelial lining of venular capillaries [2]–[5] . The more mature , replicating stages of the parasite thus leave the peripheral circulation , perhaps to avoid elimination by the reticulo-endothelial system of the host spleen . Their sequestration damages the host , as occlusion and inflammation around capillaries results in damage to vital organs and sometimes leads to potentially fatal complications such as cerebral malaria [1] , [6] , [7] . The highly polymorphic var genes are concentrated at the 28 chromosome telomeres , with a minority of loci in more central regions [8] . Switching expression of PfEMP1 antigens with alternative antigenic and cytoadherent properties allows P . falciparum to evade acquired immune responses and maintain infections despite antibody-mediated immune pressure [1] , [9] . Based on distinct types of promoter sequences and their internal versus telomeric chromosomal location , the 60 member var gene family of the sequenced 3D7 clone can be classified into related groups [10] , [11] . There are three major groups , ( A , B , and C ) , two intermediate groups ( B/A and B/C ) and the more distantly related var1 and var2csa genes . Mutation and recombination have generated a vast repertoire of polymorphic variants and how this antigenic variation system operates during infection is a major question in malaria biology and clinical research . The interpretation of experiments testing the relationship between var gene transcription and the antigenic and adhesive properties of IE has been that a limited number of var mRNAs , possibly only one , is ultimately expressed as surface antigen on individual infected erythrocytes [12]–[17] . Such “mutually exclusive” var gene expression would limit exposure of antigens to the immune system and thus serve to extend infection periods . This seems advantageous to a vector-borne parasite whose transmission is governed by unpredictable environmental conditions and host availability . Northern blots , nuclear run-on assays and some single-cell RT-PCR experiments clearly demonstrated transcription of several var genes in ring stages , sometimes [16]–[18] , but not always showing a reduction in the extent of polygenic var transcription as rings develop into trophozoites [19] , [20] . This has been explained as the result of mRNA extraction from cell populations rather than individual cells and by indications that there is a trend , as intra-erythrocytic development progresses , for “loose” multi-var locus transcription to decrease , and a single mRNA type to become predominant , this dominant transcript becoming the sole translated and exported PfEMP1 [16] , [17] , [21] . Recent nuclear run-on data using A4 parasites , antibody-selected for expression of the A4varICAM1 PfEMP1 , and also parasites preselected for adhesion to CSA or CD36 have somewhat reinforced the experimental support for the existence of predominant transcripts and mutually exclusive processes of transcriptional control [22] , [23] . Strictly exclusive expression is most strongly supported by the demonstration that transfection of P . falciparum with plasmids transcribing var promoters is followed by a shut down of all endogenous var transcription [24]–[28] . These experiments elegantly demonstrate that there must be some form of epigenetic memory of transcriptional status . However , although transcriptional memory is likely to be fundamental to the control of the P . falciparum antigenic variation system , it is less clear how well transfection mimics in vivo regulation of var gene transcription in wild-type cultures . Nor is it clear how mutually exclusive expression is naturally established e . g in parasites which have not been expressing var genes such as those emerging into the bloodstream from the liver . A monoclonal antibody ( Bc6 ) , detecting the antigen encoded by the A4varICAM1 gene on the surface of A4 infected erythrocytes , has been used to correlate this var gene expression with its adhesion phenotype in several studies [14] , [15] , [18] , [29] , [30] . However , efforts to link other var transcripts to the surface expression of particular PfEMP1 on single infected erythrocytes have been hampered by difficulties in generating a broad repertoire of specific , surface-reactive anti-PfEMP1 antibodies . In this work , we have generated a number of such antisera after immunising with recombinant-produced PfEMP1 domains . We have combined these with in vitro antibody-selected P . falciparum lines [31] to identify simultaneous surface expression of PFD1235w and PF11_0008 PfEMP1 antigens on single infected erythrocytes . Given the potential importance of dual PfEMP1 expression in vivo , we also assessed the adhesion to endothelial cells of IE with either one or two different PfEMP1 variants on the cell surface . Parasites with dual expression of both the PFD1235w and PF11_0008 antigens bound to both CD54/ICAM1 and CD31/PECAM1 and showed a markedly increased binding of IE to human umbilical vein endothelial cells ( HUVEC ) . This binding is reminiscent of the multiple receptor interactions shown to be important in other vascular adhesion interactions [32] , [33] . Interestingly , the severity of malaria disease has previously been associated with adhesion of IE to multiple receptors rather than one and clinical isolates of P . falciparum will bind several receptors simultaneously [34]–[36] . The explanation previously put forward to explain this has been that distinct domains of a single PfEMP1 molecule are interacting with multiple host receptors [37] . To our knowledge , this is the first study to demonstrate that multi-receptor binding can be mediated by different PfEMP1 antigens that are co-expressed on the same infected erythrocyte surface .
The expression of particular PfEMP1 surface antigens may switch during the infection and is proposed to be mutually exclusive in the sense that any single infected erythrocyte expresses only one variant antigen at a time , on the IE surface [14] , [16] , [17] , [38] . We have shown that 3D7 parasites in culture , pre-selected using IgG from semi-immune children are transcribing several var genes . However , human IgG selected parasitized erythrocytes predominantly expressed one Group A PfEMP1 antigen ( PFD1235w ) on the IE surface [39] . Using new rat and rabbit antisera specific for the proteins encoded by two different var genes , annotated as PFD1235w and PF11_0008 , we re-examined var gene and PfEMP1 surface antigen expression in three different antibody-selected sub-lines of 3D7 . The 3D7 PFD1235w sub-line was selected from 3D7Dodowa1 [31] , [39] using an antisera targeting the DBL4γ domain of PFD1235w . The 3D7PFD1235w/PF11_0008 and 3D7PF11_0008 sub-lines were selected from 3D7 using antisera targeting the CIDR1α domain of PFD1235w and the CIDR2β domain of PF11_0008 , respectively . Each was grown in culture for only 3–5 cycles after the end of the selection period prior to the assay . We immuno-stained parasites for flow cytometry using antisera targeting DBL1α-CIDR1α , CIDR1α , DBL3β , DBL4γ , DBL5δ , DBL5δ-CIDR2β of PFD1235w , DBL4β and CIDR2β of PF11_0008 , and DBL5ε and DBL5ε-DBL6ε of VAR2CSA and also examined individual live un-fixed single invaded IE using confocal microscopy . The majority of erythrocytes infected with the 3D7PFD1235w sub-line stained positively in flow cytometry with all PFD1235w antisera ( Figure S1A1–A8 ) without expression of any PF11_0008 ( Figure S1A9 and S1A10 ) . Live confocal microscopy of individual IE showed the characteristic punctate pattern of PfEMP1 antigen staining , indicating surface expression of the PFD1235w-encoded var gene ( Figure 1A1 , A3 , A4 , A6 and Figure 2A1–A8 ) . No PF11_0008 ( Figure 1A2 , A3 , A5 , A7 and Figure 2A1–A8 ) or VAR2CSA ( Figure 1A4 , A5 , A8 ) antigen staining was observed . Similarly the majority of erythrocytes infected with the 3D7PF11_0008 sub-line stained positively with antisera targeting DBL4β and CIDR2β of PF11_0008 ( Figure S1B9–10 ) without expression of PFD1235w ( Figure S1B1–B8 ) . Confocal microscopy agreed with the flow cytometric data , indicating expression of the PF11_0008 encoded var gene ( Figure 1B2 , B3 , B5 , B7 and Figure 2B1–8 ) without PFD1235w ( Figure 1B1 , B3–B4 , B6 and Figure 2B1–8 ) or VAR2CSA ( Figure 1B4 , B5 , and B8 ) antigen staining . Contradicting the ‘mutually exclusive’ expression model [16] , [17] , [26] , [27] , single and single-infected erythrocytes infected by the 3D7PFD1235w/PF11_0008 sub-line of parasites stained positively with both of the differentially labelled antisera known to bind two different PfEMP1 antigens . In confocal microscopy the PFD1235w-DBL4γ and the CIDR2β PF11_0008 antisera showed an erythrocyte surface double staining pattern with punctate fluorescence , which showed limited or no co-localization ( Figure 1C3 and Video S1 ) . The PFD1235w-DBL4γ , PFD1235-CIDR1α and PF11_0008- CIDR2β antisera used for selection do not cross-react with trypsin-resistant parasite surface antigens , as prior trypsinization of the IE abolished reactivity with all the antisera used in flow cytometry ( Figure S2A–C ) . Blocking surface binding of these antisera with excess homologous antigen prior to staining of the sub-lines also indicated that neither antisera cross-reacted with other surface antigens on IE ( Figure S2D–F ) . To further exclude the possibility that the double staining of single IE was an artefact resulting from cross-reactivity with other surface antigens , we used various combinations of antisera with known specificity for different domains of the PfEMP1 encoded by the PFD1235w gene ( DBL1α-CIDR1α , CIDR1α* , DBL3β , DBL5δ , DBL5δ-CIDR2β ) and the PF11_0008 gene ( CIDR2β and DBL4β ) . All of the anti-PFD1235w and anti-PF11_0008 sera were specific for the 3D7PFD1235w and the 3D7PF11_0008 sub-line , respectively ( Figure S1 ) . In combination with αPF11_0008-CIDR2β , each anti-PFD1235w antiserum also double stained the 3D7PFD1235w/PF11_0008 sub-line ( Figure 2C1–C6 ) . Similar data was obtained using αPF11_0008-DBL4β in combination with αPFD1235w-CIDR1α and DBL4γ ( Figure 2C7–C8 ) . These results also indicate that single erythrocytes infected by antibody-selected 3D7 are expressing more than one PfEMP1 antigen on individual erythrocyte membranes . To further eliminate the possibility that ‘double antigen staining’ on single IE is an artefact related to the use of two different antisera , we tested a variety of additional combinations of antisera , each with different specificities . Combinations of antisera raised against PFD1235w-DBL4γ domain and antisera raised against the VAR2CSA-DBL5ε domain ( Figure 1A4–D4 ) or anti-PF11_0008-CIDR2β sera with VAR2CSA-DBL5ε antisera were tested ( Figure 1A5–D5 ) . These combinations always showed a single staining phenotype when reacting with the 3D7PFD1235w/PF11_0008 IE and the other sub-lines of 3D7 . Surface staining of the 3D7PFD1235w sub-line using two differently fluorescently labelled antibodies , a rat antiserum raised against the DBL4γ domain and rabbit antiserum raised against CIDR1β domain of the same PFD1235w antigen also showed dual staining , with limited co-localisation and distinctly labelled spots of erythrocyte surface fluorescence ( Figure 1A6 and C6 ) . Similarly , staining of the 3D7PF11_0008 sub-line using differentially labelled antibodies targeting PF11_0008 DBL4β ( rat ) and CIDR2β ( rabbit ) ( Figure 1B7 and C7 ) and staining of the 3D7VAR2CSA sub-line using antibodies targeting DBL5ε ( mouse ) and DBL5ε-DBL6ε ( rabbit ) of VAR2CSA also showed the dual staining , without significant co-localization phenotype ( Figure 1D8 ) . To obtain clonal lines of 3D7PFD1235w/PF11_0008 IE we carried out a limiting dilution cloning exercise , following which the resulting clones were grown for 7–10 cycles , prior to flow cytometry and confocal microscopy PfEMP1 surface expression analysis . Seven of nine clones originating from this experiment showed simultaneous surface expression of both PFD1235w and PF11_0008 as shown for clone 3 in Figure 3 . The double expressing phenotype was only shown by a minority of the populations in the two remaining clones 4 and 8 , indicating that the dual expression phenotype can be spontaneously lost over time as shown for clone 4 in Figure S3 . Affinity purified antisera raised in rats against PFD1235w-DBL4γ and in rabbits against CIDR2β of PF11_0008 , as well as rabbit antisera against PFD1235w-CIDR1α , were depleted of any anti-V5-HIS fusion protein reactivity . The specificity of the resulting antibodies was then assessed by both ELISA and a bead-based Luminex assay [40] . We found the three depleted antibody preparations to be specific for the homologous immunizing protein ( Figure S4 ) as none cross-reacted with any of the 48 heterologous PfEMP1 domains in the Luminex ( Figure S4D–F ) . The Luminex assay and ELISA both included the CIDR1α domain of PF08_0103 , i . e . representing a var gene transcript known to be highly abundant in the 3D7PFD1235w/PF11_0008 IE tested ( Figure 4 ) . Having tested the specificity of the antisera and of the affinity purified and depleted antibodies , we repeated the surface staining experiments presented in Figure 1 and Figure S1 and the double staining experiments shown in Figure 1 and Figure 2 , on aliquots of the same batch of parasites , with the affinity purified and tag-depleted antibodies ( Figure S5 ) . The tag-depleted PFD1235w antibodies surface stained the 3D7PFD1235w and the 3D7PFD1235w/PF11_0008 sub-lines , but not the 3D7PF11_0008 line . Similarly , the depleted PF11_0008 antibodies surface stained the 3D7PF11_0008 and the 3D7PFD1235w/PF11_0008 sub-lines , but not the 3D7PFD1235w line . All antibody purifications showing identical punctate PfEMP1 surface staining patterns to those observed with the complete antisera used in Figure 1 and Figure 2 . Likewise , flow cytometry data using purified and depleted antibodies gave the same results as obtained using crude antisera ( Figure S1 and Figure S5 ) . In parallel to the antibody-based PfEMP1 surface antigen detection studies , we measured var gene transcript levels using primer sets targeting each of the 58 active var genes and two pseudo var genes of the 3D7 genome [41]–[43] . Only the NF54VAR2CSA sub-line culture ( Figure 4D1 ) , showed exclusive transcription of a single var gene ( var2csa ) . All other sub-lines showed the presence of several major transcripts during the ring-stages , the most transcriptionally active stages for var gene expression ( Figure 4A1–C1 ) . The 3D7PFD1235w sub-line culture transcribed three different var genes in similar quantities; PFD1235w ( Group A ) , MAL6P1 . 316 ( Group A/B ) , and PFD0625c ( Group C ) . The three most abundant var transcripts in the 3D7PFD11_0008 sub-line cultures were PF11_0008 ( Group A ) , PF07_0050 ( Group B/C ) , and PFD0625c ( Group C ) . In the 3D7PFD1235w/PF11_0008 sub-line cultures the three most abundant transcripts were PFD1235w ( Group A ) , PF11_0008 ( Group A ) , and PF08_0103 ( Group B/C ) . PFD1235w and PF11_0008 constituted 19% and 1% , respectively , of the total var transcripts in the 3D7PFD1235w sub-line ( Figure 4A1 ) . They constituted 1% and 29% , respectively , in the 3D7PF11_0008 sub-line ( Figure 4B1 ) and 46% and 11% , respectively , in the 3D7PFD1235w/PFD11_0008 sub-line ( Figure 4C1 ) . To verify that the 3D7PFD1235w/PFD11_0008 culture is a homogenous population we did different experiments to enrich for PFD1235w and PF11_0008 double positive IE . Populations of 3D7PFD1235w/PFD11_0008 were enriched using antisera ( αPFD1235w-DBL4γ , αPFD1235w-CIDR1α , and αPF11_0008-CIDR2β ) bound to Protein A-coupled Dynabeads , FACS sorted using αPFD1235w-DBL4γ and αPF11_0008-CIDR2β simultanously in addition to cloning by limiting dilution as described above . The Dynabeads-enriched and FACS sorted IE were grown for less than one cycle and RNA was extracted from the ring stage . Extracted mRNA from these stages showed the presence of several major var transcripts ( Figure 4B2–D2 and Figure 4B3 ) , a profile similar to that seen in mRNA extracted from ring-stages of the unsorted 3D7PFD1235w/PFD11_0008 IE in Figure 4C1 , 4A2 , and 4A3 . Three different representative 3D7PFD1235w/PFD11_0008 clones ( 1 , 3 , and 5 ) originating from the limiting dilution experiment showed an almost identical transcript profile with the presence of several major transcripts ( Figure 4A4–C4 ) . This indicates the unsorted 3D7PFD1235w/PFD11_0008 culture largely is a homogeneous population , a conclusion also supported by the flow cytometry data ( Figure 2C1–C8 ) . Full length transcription of PFD1235w and PF11_0008 and all the var genes listed in Table S2 was tested using specific cross-intron primers . In real-time quantitative PCR assays with cDNA synthesised from total RNA extracted from the three 3D7 sub-lines and our clones we obtained similar Ct-values , whether using primers targeting exon I , or primers spanning the intron regions ( Figure S6 ) . This , in addition to Northern blotting ( Figure 5K and 5L ) , indicates that these genes are being transcribed into full length mRNA species by the parasites . In addition , sequencing of the introns of both PFD1235w and of PF11_0008 ( using genomic DNA from selected sub-line and clonal IE as template ) showed they were intact and identical to the genomic sequences available at http://plasmodb . org/plasmo/ . Sequencing of cDNA also showed the introns of PFD1235w , PF11_0008 , and the introns of the var genes in Table S2 , were correctly spliced out of the mature mRNA . Single-cell PFD1235w and PF11_0008 transcription of the two var genes located on chromosome 4 and 11 was further analysed by using RNA-FISH in situ hybridization to var gene mRNA using appropriate probes . The FISH indicates that 65–80% of single ring-stage nuclei of parasites taken from cultures of the 3D7PFD1235w and 3D7PF11_0008 sub-lines transcribe either PFD1235w ( Figure 5A–C ) or PF11_0008 ( Figure 5D–F ) . None of the 3D7PFD1235w IE showed staining with the PF11_0008 probe and vice versa . In agreement with the antibody-mediated PfEMP1 antigen surface detection data ( Figures 1–3 , Figure S1 , Figure S3 and Figure S5 ) and the real-time quantitative PCR data ( Figure 4 and Figure S6 ) PFD1235w and PF11_0008 could both be detected as hybridising mRNA species being transcribed in 99 of 100 different single nucleated cells of the 3D7PFD1235w/PF11_0008 clone 3 ( Figure 5G–I ) . The specificity of the probes for the two differently sized PfEMP1 mRNA species was further confirmed by Northern blotting ( Figure 5K and 5L ) and the identified length of mRNA agrees with that predicted as the transcript length from their respective sequenced genes ( http://plasmodb . org/plasmo/ ) . Control slides pre-treated with RNAse prior to hybridization were all negative . Having established simultaneous expression of two species of PfEMP1 on the IE surface , we then analysed whether this dual expression affects the binding phenotype of the infected erythrocytes ( Figure 6 ) . 3D7PFD1235w infected erythrocytes showed specific binding to CD54/ICAM1 transfected CHO cells ( Figure 6A ) and no binding to CHO-CD36 cells ( Figure 6B ) or wild type CHO cells ( Figure 6C ) . The observed binding was specifically inhibited by anti-CD54/ICAM1 ( 15 . 2 and My13 ) antibodies ( Figure 6A ) which have been shown to inhibit binding of PfEMP1 to ICAM1/CD54 [44] . Erythrocytes infected with 3D7PF11_0008 did not bind CD54/ICAM1 ( Figure 6A ) . The 3D7PFD1235w/PF11_0008 sub-line , which expressed both PFD1235w and PF11_0008 , bound as strongly to CD54/ICAM1 as the PFD1235w infected cells which express only this ICAM1–binding antigen ( Figure 6A ) . The 3D7PF11_0008 sub-line bound specifically to the un-stimulated HUVEC cells which constitutively express PECAM1/CD31 and von Willebrand factor . This binding was markedly reduced in the presence of antibodies to CD31/PECAM1 ( Figure 6D ) , indicating that CD31/PECAM1 was important for PfEMP1-mediated binding in this assay . Cells expressing PFD1235w also showed very slight binding to un-stimulated HUVEC cells , probably explicable by a low level expression of CD54/ICAM1 on these cells as this binding was slightly reduced by CD54/ICAM1 antibodies ( Figure 6D ) . However cells expressing both PFD1235w and PF11_0008 bound strongly to the HUVEC cells , with binding levels 2–3 times higher than the binding of the cells expressing PF11_0008 only . This binding could only be partially inhibited by anti-CD31/PECAM1 and CD54/ICAM1 antibodies . This result indicates that cells co-expressing PFD1235w and PF11_0008 can bind both CD54/ICAM1 and CD31/PECAM1 , whereas IE having only one of the two PfEMP1 species on the surface bind to one or another of the two receptors , but not both . Interestingly the binding of the 3D7PFD1235w/PF11_0008 sub-line to HUVEC cells ( Figure 6D ) was stronger than the binding of the 3D7PF11_0008 sub-line . This could reflect an additive effect of PfEMP1 co-expression .
The complete P . falciparum 3D7 genome sequence and real-time quantitative RT-PCR enable accurate measurement of the relative amounts of var gene transcripts in intra-erythrocytic malaria parasite populations . To further analyse the relationship between var gene transcripts and the individual infected erythrocyte's PfEMP1 antigen surface expression and cytoadhesion phenotype , we have combined mRNA quantification and FISH analysis with FACS and single-cell live confocal microscopy using PfEMP1 antisera of demonstrated specificity in addition to in vitro adhesion assays , in antibody-selected , but otherwise genetically unmodified parasites . The primary intention was to test the ‘mutually exclusive expression’ hypothesis for the P . falciparum PfEMP1 mediated antigenic variation system . A handful of studies have investigated this relationship between var transcripts and its eventual outcome in terms of surface PfEMP1 expression and adhesion . These have used parasites selected for rosetting [16] , [45] , adhesion to ICAM1 or CSA [15] , [17] , [19] or selected using the A4varICAM1 monoclonal antibody Bc6 [15] , [46] . Data supporting exclusive antigen expression on IE has been obtained using ‘pan-reactive’ antibodies targeting the conserved Acidic Terminal Sequence of PfEMP1 , which detected single PfEMP1-sized bands in immuno-precipitations and Western blots [16] . However , similar antibodies have also shown protein expression of several differently sized PfEMP1 bands in other experiments with adhesion-selected clonal populations [19] and immune sera-selected cultures are also known to express several species of PfEMP1 [39] . Additionally , a more recent study using a transfected A4 parasite line show surface co-expression of miniPfEMP1 protein with endogenous PfEMP1 [47] . Direct demonstration of PfEMP1 using gel electrophoretic methods is technically difficult due to the low amounts of PfEMP1 on parasitized erythrocytes and the fact that Western blot-based typing is rarely possible because typing sera usually recognise conformational epitopes and not denatured blotted PfEMP1 . However , flow cytometry and confocal microscopy can detect native PfEMP1 conformations on live cells , at both cell and population level . We used this to analyse PfEMP1 surface expression on antibody-selected IE populations known to predominantly , but not exclusively , transcribe the PFD1235w and PF11_0008 var genes . The ring-stages of antibody selected 3D7-derived lines showed polygenic var transcription with several abundant var mRNAs ( Figure 4A1–C1 , Figure 4A2 , and Figure 4A3 ) . Dynabeads sorted ( Figure 4B2–D2 ) , and FACS sorted lines ( Figure 4B3 ) also showed polygenic var gene transcription . The real-time Q-PCR data are also supported by RNA-FISH and Northern blot analysis showing co-transcription of full-length PFD1235w and PF11_0008 var genes associated with single-cell nuclei of 3D7PFD1235w/PF11_0008 ( Figure 5 ) . By contrast , the NF54VAR2CSA sub-line had a single dominant gene , var2csa , whose transcript was 98% of total var mRNA ( Figure 4D1 ) . The dominant , exclusive var2csa transcription of repeatedly CSA selected parasites [41] , [42] , [48] is the best demonstration of ‘mutually exclusive’ var transcription . However , it is also to some extent a special case . The var2csa gene has its own promoter , upsE [10] , and an unique upstream open reading frame involved in the control of var2csa expression [49] and thus its regulation has certain non-standard features [42] . Strictly monoallelic or unilocus expression of the var2csa gene has however , also been questioned by recent publications showing transcription of duplicated var2csa genes [50] , which appears to be simultaneous in individual parasites [51] . However dual expression of both VAR2CSA variants on the erythrocyte surface has not been shown . We observe neither monoallelic mRNA transcription , nor monomorphic antigen expression at the erythrocyte surface in individual 3D7PFD1235w/PF11_0008 IE . These cells clearly reacted with more than one specific anti-PfEMP1 antisera . Other selected sub-lines reacted exclusively with either antisera ( Figure 1 , Figure 2 , Figure S1 and Figure S5 ) . In our assays these antisera were highly specific for the immunizing antigen ( Figure S1 , S2 , and S4 ) . Our experiments appear to exclude the possibility that these antisera are non-specifically reacting with other surface expressed parasite antigens . We consider that these novel results indicate that , contrary to the current consensus , at least two different PfEMP1 antigens can in some circumstances be expressed on the surface of a single 3D7 IE . A puzzling phenomenon associated with PfEMP1 surface staining with antigen and domain specific antisera remains . This is the observation that differentially labelled antisera raised against separate domains ( Figure 1 ) or identical domains ( unpublished data ) of the same PfEMP1 protein consistently show non-colocalizing patterns of punctate surface fluorescence . This could be the result of some PfEMP1 topological phenomena , or more likely an artificial outcome of the experimental setup with cross-linking of primary via secondary species-specific antibodies [52] . Disregarding our flow cytometry and single-cell microscopy data the presence of several abundant full-length var mRNAs in the three antibody selected sub-lines ( Figure 4A1–C1 , Figure 4A2 , Figure 4A3 ) could be explained by that fact that mRNA was extracted from in vitro cultured cell populations rather than individual cells . To exclude this possibility we did limiting dilution of the 3D7PFD1235w/PF11_0008 sub-line to obtain a clonal population of cells . From this experiment nine clones were obtained of which seven double positive clones show a slightly reduced complexity , but still multiplicity of var gene transcripts ( compare Figure 4A4–C4 and Figure 4C1 ) . Thus , the multiple var transcripts seen ( Figure 4C1 , Figure 4A2 , and Figure 4A3 ) can not be explained by our use of a heterogeneous cell population . At the genetic level , several DNA sequences required for appropriate var gene control have been reported e . g . the pairing of a 5′var promoter with an intronic promoter at the 3′end of the same var gene [24] . We therefore screened for potential confounding defects in our parasite lines and in clone 3 . Using cross-intron primers for the abundantly transcribed var genes we found correct splicing of exon I to exon II . In addition , the real time Q-PCR for each abundant var gene transcript indicated similar transcript levels of several full-length var mRNAs in the early stage IE ( Figure S6 ) . Sequencing the intronic regions of the PFD1235w and PF11_0008 var genes located on two different chromosomes revealed that these were identical to the sequences available on PlasmoDB . Thus , constitutive transcription by single 3D7PFD1235w/PF11_0008 IE due to some defect in their respective intron sequences does not explain our dual surface expression data . In addition as shown by flow cytometry , two of the clones switched surface expression during culturing with a minor population still co-expressing PFD1235w and PF11_0008 and a majority expressing unidentified PfEMP1s ( Figure S3 ) . This strongly indicates a shut-down of PFD1235w and PF11_0008 PfEMP1 surface expression and further indicates constitutive transcription does not explain our dual surface staining data . Whether the simultaneous expression of more than one PfEMP1 occurs in single IE during natural infections is not known as we currently have a better understanding of malaria antigen variation in vitro than in vivo . In natural infections , P . falciparum sequesters in deep tissue prior to the onset of cell division and under physiological blood flow sequestration is mediated by avidity-dependent binding to multiple host-receptors , mimicking the process of leukocyte recruitment [53]–[55] . Antibodies to CD36 have been shown to reduce rolling and adhesion of IE , residual rolling being further inhibited by antibody to ICAM1 [55] . These receptors operate synergistically to mediate strong cytoadherence when coexpressed on endothelial cells [56] . PfEMP1 proteins have multiple domains [8] and most CIDR-α type domains bind CD36 [57] , while some DBLβc2 domains bind ICAM1 [58]–[61] and some single PfEMP1 species have been shown to mediate multiple independent interactions with a diverse set of host receptors including CD31/PECAM-1 , the blood group A antigen , normal nonimmune IgM , heparan sulfate–like glucosaminoglycan , and CD36 [62] . A study has suggested that the ability of parasites to bind to multiple receptors is correlated with disease severity [63] . In addition , several lines of evidence have implicated CD54/ICAM1 [64]–[67] , CD31/PECAM1 [68] as well as PFD1235w and PF11_0008 [39] , [69] , [70] as having a role in severe disease . Interestingly , we found the PFD1235w and PF11_0008 surface co-expressed on the 3D7PFD1235w/PF11_0008 sub-line to mediate binding to CD54/ICAM1 and CD31/PECAM1 , respectively ( Figure 6 ) . To our knowledge this is the first study to demonstrate dual receptor binding in malaria cytoadherence being mediated by two different PfEMP1 molecules on the surface of single IE . A potential mechanism for the two PfEMP1 interactions could involve a role for PFD1235w as a primary ligand for rolling and CD54/ICAM1 binding on the endothelium thus enabling further contacts with CD31/PECAM1 which could be mediated by PF11_0008 , when both are present on the IE surface . Adhesion would then be improved through simultaneous binding to several receptors as indicated by our data in Figure 6 . This process may be similar to that of lymphocyte rolling based on carbohydrate-receptor interactions [71] . If more than one PfEMP1 antigen is expressed on individual IE in in vivo infections it may be most advantageous during the immediately post-hepatocytic establishment phase . The first post-hepatocytic generation lacks epigenetic memory of var gene transcription and translation . Relaxed transcription [72] and translation may thus be initially unavoidable . It may also ensure the highest avidity binding interaction possible and rapid sequestration . Transcription of those var genes expressed by successfully sequestering survivors of the post-hepatocytic wave of infection would epigenetically mark these var genes for expression in their descendent population , whilst leaving their unexpressed and thus unmarked var genes to become silenced . Such an ‘early loose-tight late’ model for var gene transcription in blood stage infection is compatible with experiments demonstrating that transcription of a particular var gene promoter leads to the silencing of the other var genes in the repertoire [73] . Our var gene transcript level , PfEMP1 surface expression , and cytoadhesion data may be indicating that the primary role of the P . falciparum var genes is the sequestration reaction and that at least in the earliest phases of blood stage infection , escape of IE from the circulation to a sequestration site which ensures successful replication takes precedence over shielding the antigenic variation repertoire from immune surveillance . The tiny amounts of PfEMP1 present at very low parasitaemia are unlikely to be sufficient to promote protective seroconversion . As infections develop and variant-specific parasitaemia rises , the repertoire become protected by epigenetic silencing until finally a novel cytoadhesion phenotype expressing a new PfEMP1 variant outgrows the increasingly immunocompromised founder population and the process starts over . In summary , we have shown protein expression of two different var genes on the membrane of single erythrocytes infected with P . falciparum 3D7 to facilitate cytoadhesion of the infected cells to two different human receptors . These observations contradicts the hypothesis of mutually exclusive PfEMP1 expression and at the same time offers an additional molecular explanation for how individual IE can mediate adhesion to multiple host receptors .
The P . falciparum isolate NF54 and the NF54 derived clone 3D7 were cultured in blood group 0 erythrocytes as previously described [74] . Cultures were routinely genotyped by PCR using primers targeting the polymorphic loci MSP2 and Glurp as described [75] and mycoplasma tested using the MycoAlert Mycoplasma Detection Kit ( Lonza ) following the manufactures instructions . IgG from rabbits immunized with DBL4γ or CIDR1α of 3D7 PFD1235w and CIDR2β of 3D7 PF11_0008 were used to obtain three different sub-lines of 3D7 parasites . 3D7PFD1235w , originating from a previously selected line referred to as 3D7Dodowa1 [31] was obtained using sera targeting a PFD1235w-DBL4γ recombinant antigen . 3D7PF11_0008 originating from 3D7 was selected using sera targeting the CIDR2β of PF11_0008 and 3D7PFD1235w/PF11_0008 similarly originating from 3D7 was obtained using sera targeting a CIDR1α domain recombinant protein of PFD1235w . NF54VAR2CSA kindly provided by Morten A . Nielsen was selected using rabbit antisera raised against a DBL5ε-6ε recombinant protein based on the var2csa gene . Briefly , the different rabbit sera were depleted on human uninfected erythrocytes type 0 , incubated with gelatine purified trophozoite-stage 3D7/NF54 parasites for 30 min at 37°C , and unbound antibodies were removed by washing . Subsequently , IE were incubated with Protein A-coupled Dynabeads ( Invitrogen ) for 30 min at 37°C and bound IE were trapped using a magnet . Trapped IE were transferred to new culture flasks for continued in vitro culturing and the procedure was repeated until cultures stained positive by the selecting antisera in flow cytometry . Gelatine purified 3D7PFD1235w/PF11_0008 IE was incubated for 30 min at 37°C with rabbit sera targeting ( PFD1235w-DBL4γ , PFD1235w-CIDR1α , and PF11_0008-CIDR2β ) and incubated with Protein A-coupled Dynabeads . Bound IE were trapped as described above , grown for less than one cycle to rings , following which RNA was purified , reverse transcribed and used for real-time quantitative PCR . MACS purified 3D7PFD1235w/PF11_0008 IEs were double stained with rat PFD1235w-DBL4γ and rabbit PF11_0008-CIDR2β antisera as described below and analysed on a FACSAria ( Becton Dickinson ) . A total of 1×106 double positive IE were collected and grown for less than one cycle to rings , following which RNA was purified , reverse transcribed and used for real-time quantitative PCR . Late stage 3D7PFD1235w/PF11_0008 IE was obtained by MACS purification and cloned using a slightly modified version of the protocol described by Walliker and Beale [76] . In brief , 0 . 25 or 0 . 5 IE in a total volume of 100 µl RPMI 1640 ( Lonza ) with 1% hematocrit , 5 mg/ml Albumax II ( Life Technologies , 0 . 18 mg/ml glutamine ( Sigma-Aldrich ) , 0 . 05 mg/ml gentamicin ( Gibco ) and 10% Normal Human Serum were seeded into each well of flat bottomed 96-wells plates ( NUNC ) . New media was added every second day and additional 1% hematocrit was added on day 5 . A total of 64 wells were checked for the presence of IE by Giemsa staining on day 12 and16 yielding nine different clones . RNA was purified from all nine clones for real-time quantitative PCR analysis and the PFD1235w and PF11_0008 surface expression was similarly analysed by flow cytometry . One clone , clone 3 was selected for FISH and confocal microscopy analysis . The DNA sequence encoding amino acid # 73-739 ( DBL1α-CIDR1α: … CELDYRF…DTKTNPC ) , amino acid #473-817 ( CIDR1α*: DYCQICP:… NGEPCTG ) , amino acid # 407-798 ( CIDR1α: KDAKTDS…TLNGDIC ) , amino acid # 1239-1689 ( DBL3β: CAETGGV… YATACDC ) , amino acid #1719-2255 ( DBL4γ: PRDKTTG…LKGDKSL ) , amino acid #2258-2764 ( DBL5δ: ACALKYG… SAKQKDC ) , and amino acid # 2242-3016 ( DBL5δ-CIDR2β: CATVAKA…VTQPNIC ) of 3D7 PFD1235w , amino acid #1553-1924 ( CIDR2β: KKQEKLY…NVPANPC ) and amino acid #1994-2378 ( DBL4β: CNITKEH… HDDACAC ) of 3D7 PF11_0008 and the DNA amplified by primers listed in Table S1 was cloned and expressed in a baculovirus system as described [39] , [77]–[79] . DBL1x VAR2CSA protein was kindly provided by Ali Salanti and Madeleine Dahlbäck . All procedures complied with European or national regulations . Prior to immunization each animal was pre-bled and these sera were used as negative controls in the flow cytometry and confocal microscopy experiments . VAR2CSA DBL5ε-DBL6ε rat antisera , rabbit αDBL5ε-DBL6ε and mouse αDBL5ε antisera [80] were kindly provided by Ali Salanti and Madeleine Dahlbäck . PFD1235w-CIDR1α , PFD1235w-DBL4γ , and PF11_0008-CIDR2β rabbit , and PFD1235w-DBL1α-CIDR1α , PFD1235w-CIDR1α* , PFD1235w-DBL3β , PFD1235w-DBL4γ , PFD1235w-DBL5δ , PFD1235w-DBL5δ-CIDR2β , and PF11_0008-DBL4β were raised by subcutaneous injection of 10–20 µg protein in complete Freund's adjuvant followed by several boosters of protein in incomplete Freund's adjuvant . All experiments including immunizations and bleeding of animals was approved by The Danish Animal Procedures Committee ( “Dyreforsoegstilsynet” ) as described in permit no . 2008/561-1498 and according to the guidelines described in act no . LBK 1306 ( 23/11/2007 ) and BEK 1273 ( 12/12/2005 ) . 0 . 5 mg of PFD1235w-DBL4γ and PF11_0008-CIDR2β in each 1 ml were dialysed ON against coupling buffer and subsequently coupled to HiTrap NHS activated HP columns as described by the manufacturer ( GE Healthcare ) . A pool of 3 ml PFD1235w-DBL4γ antisera from six rats and 6 ml PF11_0008-CIDR2β antisera from one rabbit were diluted 1∶1 in PBS and affinity purified on the HiTrap columns . Following elution in Glycin buffer ( 0 . 1 M , pH 2 . 8 ) antibodies were neutralised in Hepes buffer ( 1M , pH 8 . 0 ) . The affinity purified rabbit PFD1235w-DBL4γ and PF11_0008-CIDR2β antibodies were depleted for V5-His reactivity using a non-sense peptide ( VLIM-tag ) VLIMFNEQHKRGASTYWCPGKPIPNPLLGLD STRTGHHHHHH ( Schafer-N ) containing the V5-His epitope ( underlined ) and recombinant V5-HIS tagged VAR2CSA-DBL1x . The VLIM-tag peptide and VAR2CSA-DBL1x ( both 1 mg/ml in PBS ) were coupled to Epoxy M270 Dynabeads according to the manufacturer's instructions ( Invitrogen ) . 200 µl of each of the two different species of affinity purified antibodies was incubated for 2 h at RT with 3 mg of coupled Dynabeads . Following this the supernatant containing the depleted antibody fraction was removed and re-incubated twice with freshly coupled Dynabeads . Antibodies bound to the Dynabeads were eluted in Glycin/HCl ( 0 . 1 M , pH 2 . 75 ) and neutralised in Tris buffer ( 1 M , pH 9 . 0 ) . The reactivity of depleted and non-depleted antibody fractions was tested by ELISA ( as described below ) using PFD1235w-DBL4γ , PF11_0008-CIDR2β , VAR2CSA-DBL1x , and the VLIM-tag peptide as coating antigen . Additionally , the affinity purified and depleted PFD1235w-DBL4γ and PF11_0008-CIDR2β antibodies used for flow cytometry and confocal microscopy were tested by Luminex ( as described below ) on 49 different PfEMP1 recombinant proteins . Similarly rabbit antisera against PFD1235w-CIDR1α was depleted on recombinant V5-HIS-tagged VAR2CSA-DBL1x and tested by ELISA using PFD1235w-CIDR1α , PF08_0103-CIDR1α , PF11_0008-CIDR2β , VAR2CSA-DBL1x , and the VLIM-tag peptide as coating antigen . Rat PFD1235w-DBL4γ , rabbit PFD1235w-CIDR1α or PF11_0008-CIDR2β antisera binding was blocked by incubation for 1 hr at 4°C using excess purified recombinant PFD1235w-DBL4γ , PFD1235w-CIDR1α , PF11_0008-CIDR2β , or PF08_0103-CIDR1α protein ( 3 µg/well containing 5 µl rat or 10 µl rabbit sera ) and remaining cross-reactivity to parasite antigens expressed on the surface of infected erythrocytes was subsequently tested by flow cytometry as described below . Parasite cultures were repeatedly antibody selected as described above and grown for 3–5 cycles prior to doing flow cytometry . Single colour flow cytometry surface staining was done with minor modifications as described [74] . In brief , IE were purified on a magnet-activated cell sorting column ( MACS ) and 2×105 ethidium bromide-labelled IE were incubated for 30 min at 4°C in 5 µl rat , 10 µl rabbit sera , or 15 µl affinity purified and tag-depleted antibody depleted of anti-human erythrocyte antibodies and then incubated for 30 min at 4°C with FITC-conjugated goat-anti-rat IgG ( 1∶150 , Zymed ) or FITC-conjugated goat-anti-rabbit IgG ( 1∶200 , Vector Laboratories ) . Prior to doing two colour flow cytometry surface staining the purity of the MACS-purified IE was verified by running a small sample of ethidium bromide-labelled IE on a flow cytometer . Sub-line MACS preparations with ≥90% IE were used for two colour flow cytometry . In the case of clone 3 MACS preparations with 75–80% IE were used . In brief , 2×105 MACS-purified unlabelled IE were incubated with 5 µl rat and 10 µl rabbit sera depleted of anti-human erythrocyte antibodies , followed by incubation with FITC-conjugated goat-anti-rat IgG ( 1∶150 , Zymed ) and Alexa Fluor 610-R-PE-conjugated goat-anti-rabbit IgG ( 1∶200 , Molecular Probes ) . Samples were analysed on a Cytomics FC 500 MPL flow cytometer ( Beckman Coulter ) and data analysed using WinList version 6 . 0 ( Verity Software House Inc . ) . IE stained with one surface colour was gated based on the ethidium bromide staining to exclude uninfected erythrocytes . Two colour stained non-ethidium bromide-labelled IE were gated based on forward and side scatter values since ethidium bromide could not be used due to overlapping spectra with the Alexa Fluor 610-R-PE-conjugated anti-rabbit used . For removal of surface PfEMP1 and analysis of antisera cross-reactivity with trypsin resistant surface IE antigens expressed on late-stage trophozoites and schizonts IE were treated with 1 g/l porcine trypsin and 0 . 2 g/l EDTA solution in Hanks balanced salt solution ( Sigma-Aldrich ) for 10 min at 37°C . The reaction was stopped by adding 10% foetal calf serum ( FCS ) and cells washed three times in PBS plus 2% FCS . Controls were incubated similarly in PBS plus 2% FCS or in a trypsin/EDTA solution containing 10% FCS . Laser scanning confocal microscopy was performed on all samples analysed by flow cytometry in order to observe the staining patterns on individual IE . MACS purified unlabelled infected cells from the same batches of parasites tested by flow cytometry were incubated with individual antibodies or in combination with the PFD1235w , PF11_0008 , and VAR2CSA antibodies as previously described [81] . Briefly , 1 µl packed IE were washed in 1% BSA in PBS ( BSA/PBS ) and the pellet was incubated in 100 µl BSA/PBS and 3 µl of the respective antibodies for 30 minutes at 4°C . The IE were washed three times in BSA/PBS . The IE stained with primary antibody were then incubated with secondary antibodies , either Alexa 488 anti-rat IgG ( Invitrogen ) , Alexa 568 anti-rabbit and/or 568 Alexa anti-mouse IgG ( Invitrogen ) and DAPI ( 3 µl of a 3 µg/ml solution ) for 30 minutes at 4°C . The IE were washed three times and visualised as live , unfixed cells using a Nikon TE 2000-E confocal Nikon microscope with 60x oil immersion objective lens ( DIC ) . The images were processed using Adobe Photoshop software and displayed with the 5 µm scale bar calculated by the EZ-C1 software . Affinity purified and depleted rat and rabbit antibodies were tested by ELISA . Wells of Maxisorp plates ( Nunc , Roskilde , Denmark ) were coated with 1 µg/ml of testing antigen in Glycin/HCl buffer ( 0 . 1 M , pH 2 . 75 ) , antibodies were diluted 1∶100 in blocking buffer ( PBS , 0 . 5 M NaCl , 1% Triton-X-100 , 1% BSA , pH 7 . 2 ) , and plates were washed and developed as described previously [77] . In addition , the affinity purified and depleted antibodies were tested in the BioPlex100 System ( BioRad ) as previously described [40] . Briefly , 0 . 1 mg Baculovirus produced proteins and the VLIM-tag peptide were individually coupled to 1 . 25•107 Luminex xMAP technology microsphere beads ( Ramcon ) . Plex 1 and 2 contained 6 and 45 different proteins , respectively . Three protein domains were coupled twice in plex 2 and two were identical to domains in plex 1 ( Table S1 ) . Prior to multiplexing , protein coupling was verified by incubating beads ( 1∶333 ) with mouse anti-V5 antibody ( 1∶10 , 000 , Invitrogen ) followed by biotinylated anti-mouse IgG ( 1∶500 , DakoCytomation ) . The biotinylated antibody was detected using PE-streptavidin ( 1∶500 , Sigma ) and diluents used were PBS/TB ( PBS , 0 . 05% ( v/v ) Tween-20 , 0 . 1% ( w/v ) BSA , pH 7 . 4 ) . Multiplexed beads ( 1∶333 ) were incubated with rat or rabbit antibodies ( 1∶1000 ) followed by incubation with biotinylated anti-rat IgG ( Sigma ) or anti-rabbit IgG antibody ( The Binding Site ) diluted 1∶1000 . Detection was done with PE-streptavidine 1∶100 or 1∶1000 for rat and rabbit antibodies , respectively . Beads were resuspended in 100 µl diluents and a minimum of 100 beads from each set of multiplexed beads were analyzed to yield the mean fluorescence intensity ( MFI ) . Each affinity purified and depleted antibody was analyzed in duplicates , the average MFIs and standard deviation were calculated based on three independently repeated experiments . Antibody selected IE were grown for 3–5 cycles and erythrocytes infected by trophozoite/schizont-stage parasites ( 20–48 h post invasion ) from in vitro cultures were MACS purified and used for flow cytometry , confocal microscopy and for re-invasion of uninfected erythrocytes in new cultures flasks . IE used for RNA extraction were harvested when re-invaded parasites were at the ring-stage as confirmed by microscopy of Giemsa stained thin smears . Total RNA was prepared using Trizol ( Invitrogen ) as recommended by the manufacturers and treated with DNase1 ( Invitrogen ) for 15 min at 37°C . Absence of DNA in RNA samples was confirmed by stable base fluorescence after 40 cycles of real-time PCR with seryl-tRNA synthetase and fructose-bisphosphate aldolase primers as previously described [41] . Superscript II was used to reverse transcribe DNA-free RNA primed with random hexamer primers ( Invitrogen ) at 25°C for 10 min and 42 C for 50 min followed by 70°C for 15 min . Quantitative real-time PCR was performed using a Rotorgene thermal cycler system ( Corbett Research ) , Quanti-Tect SYBR Green PCR Master Mix ( QIAGEN ) , and real-time PCR-optimized and gene-specific primers ( 0 . 5 µM ) for each of the full-length var genes in the P . falciparum 3D7 genome and to the endogenous control genes seryl-tRNA synthetase and fructose-bisphosphate aldolase . Quantification was done using Rotorgene software version 6 . 0 . mRNA transcript copy numbers were calculated for each var transcript using primer pair specific standard curves generated from real-time Q-PCR measurements of 10 fold genomic DNA dilutions as described [43] . The proportions of individual var gene transcripts relative to the total copy number of all var transcripts or to the total number of endogenous control genes was subsequently calculated for comparison of var transcript profiles within and between samples and depicted in pie-charts . RNA-FISH was done on ring stage parasites of 3D7PFD1235w , 3D7PF11_0008 , and 3D7PFD1235w/PF11_0008 IE . PCR products were amplified using 3D7 genomic DNA and PFD1235w ( fw: 5′-GGGATCCGACACGTCGAGACAGAGG-′3; rv: 5′-GGAGAAGCTTTGCAGCGGACTTCACA-′3 ) and PF11_0008 ( fw: 5′-GGGATCCTAGTTATTTGACGCACCAGC-′3 and 5′-CGTGAATTCGGTGGCTGTACCTTCCC-3′ ) specific primers containing restriction sites ( underlined ) . The PFD1235w and PF11_0008 PCR products were subsequently cloned into the pSPT19 or pSPT18 vector ( Roche Applied Science ) , respectively and sequenced on a 3130 Genetic Analyzer ( AppliedBiosystems ) . Digoxigenin ( DIG ) - and biotin-labelled antisense RNA probes were generated using a DIG RNA Labelling Kit and Biotin RNA Labelling Mix ( Roche Applied Science ) . The var2CSA anti-sense probe described previously [50] was included as a negative control . The specificity of the RNA probes was confirmed by standard Northern blotting analysis according to the DIG Application Manual found at http://www . roche-applied-science . com/PROD_INF/MANUALS/DIG_MAN/dig_toc . htm and [39] . The RNA-FISH slides were prepared according to a standard FISH protocol with minor modifications [82] , [83] . Following hybridization over-night at 48°C , single stained anti-sense RNA were detected by α-DIG HRP conjugated Ab or α-biotin HRP conjugated Ab and the dual stained anti-sense RNA were detected with both antibodies . The signal was further detected using the TSA Plus Fluorscence Palette System ( PerkinElmer ) with FITC and/or Cyanine 3 , according to the protocol as described [83] . As control , slides were treated with RNAse ( Sigma-Aldrich ) at a concentration of 100 µg/ml for 30 min at 37°C prior to hybridization with the probes . Slides were washed , mounted with anti-fade reagent containing DAPI ( Invitrogen ) and images captured using a Nikon TE 2000-E confocal microscope as described above . The positivity of a total number of 100 IE was scored in each experiment . RNA was isolated from the 3D7PFD1235w , 3D7PF11_0008 , and 3D7PFD1235w/PF11_0008 sub-lines and cDNA generated as described above . Real-time quantitative PCR was done using primers amplifying the intron spanning region and parts of exon 1 of the var genes listed in Table S2 as well as the seryl-tRNA synthetase and fructose bisphosphate aldolase [41] . In addition , PCR products were amplified from cDNA using TaKaRA La Taq ( Lonza ) and the intron spanning primers of PFD1235w and PF11_0008 and the var genes listed in Table S2 . The PCR products were sequenced on a 3130 Genetic Analyzer using the same set of primers . For comparison genomic DNA was purified from a batch culture of 3D7PFD1235w/PF11_0008 as well as from clone 3 and the intron spanning region of PFD1235w and PF11_0008 was sequenced . Adhesion assays were done as described previously [84] . In brief , ring stage IE were cultured over night in hypoxanthine-free RPMI 1640 ( Lonza ) with 10% hypoxanthine-free Albumax ( Invitrogen ) and 8 . 75 MBq 3H-hypoxanthine ( Amersham ) per ml packed erythrocytes . 96-well flat bottomed plates ( Nunc ) were coated with 1% gelatine and HUVEC cells ( PromoCell ) grown in endothelial cell growth medium ( Promocell ) to maximum 6th passage were seeded at 550 , 000 cells per well and grown to become confluent . CHO cells ( CHO-wild type , CHO-CD36 , CHO-CD54/ICAM1 from ATCC ) were grown in RPMI 1640 with 1% added glutamine and 10% foetal calf serum ( Lonza ) and similarly seeded at 550 , 000 cells per well . On the day of the assay , 3H-labelled parasite cultures were enriched for late-stages by gelatine floatation and 50 µl of labelled trophozoites ( 12 , 000 counts per minute ) were added in duplicates or triplicates to the 96-well plates containing HUVEC or CHO cells . The plates were left to incubate on a rocking table for 2 hrs at 37°C . Monoclonal mouse anti-CD54/ICAM1 My13 ( 10 µg/ml , Invitrogen ) , anti-CD54/ICAM1 15 . 2 ( 20 µg/ml , AbD Serotec ) , anti-CD36 ( 10 µg/ml , R&D ) and anti-CD31/PECAM-1 9G11 ( 20 µg/ml , R&D Systems ) was added in anti-adhesion assays . Unbound IE were removed using a washing robot ( Biomek 2000 , Beckman Coulter ) and cells binding IE were harvested onto filter paper ( Unifilter-96 , GF/C , PerkinElmer ) using a Filtermate Harvester ( PerkinElmer ) . Following addition of 50 µl/well of scintillation liquid ( Microscint-20 , PerkinElmer ) counting was done on a Topcount NXT ( Perkin-Elmer ) . The 3H max-values were determined as the counts per minute of 50 µl of parasite added to one cell-free well and harvested directly onto a filter paper . To standardise , all values obtained was given as a ratio compared to the max value obtained in the particular assay . The percentage binding of the different 3D7 sub-lines were calculated relative to the binding of the 3D7PFD1235w parasite line adhering to CD54/ICAM1 ( Figure 6A–C ) or the 3D7PF11_0008 parasite line adhering to HUVEC ( Figure 6D ) ( e . g . binding of these equalling a 100% ) . Nucleotide sequence and protein data reported in this paper are available from http://plasmodb . org/plasmo/under accession numbers ( accession numbers of data available from NCBI are shown in brackets ) : MAL6P1 . 1/PFF1595c ( XP_966307 ) , MAL6P1 . 314 ( XP_965999 ) , MAL6P1 . 316/PFF0010w ( XP_965997 ) , MAL6P1 . 4/PFF1580c ( XP_966305 ) , PF07_0049 ( XP_001349031 ) , PF07_0050 ( XP_001349033 ) , PF07_0051 ( XP_001349034 ) , PF07_0073 ( XP_001349080 ) ( seryl-tRNA synthetase ) , PF08_0103 ( XP_001349434 ) , PF08_0140 ( XP_001349512 ) , PF08_0141 ( XP_001349513 ) , PF11_0008 ( XP_001347692 ) , PF11_0521 ( XP_001348176 ) , PF13_0003 ( XP_001349740 ) , PFA0015c ( XP_001350938 ) , PFC0005w ( XP_001351080 ) , PFD0005w ( XP_001351319 . ) , PFD0020c ( XP_001351321 ) , PFD0615c ( XP_001351435 ) , PFD0625c ( XP_001351437 ) , PFD1235w ( XP_001351561 ) , PFE1640w ( XP_001351876 ) , PFI1820w ( XP_001352240 ) , PFL0005w ( XP_001350410 ) , PFL0020w ( XP_001350413 ) , PFL0030c ( XP_001350415 ) ( VAR2CSA ) , PFL1955w ( XP_001350797 ) , and PFL2665c ( XP_001350935 ) .
|
Plasmodium falciparum is the most pathogenic human malaria parasite and its virulence has been linked to its capacity to express different adhesion proteins that enable the developing parasitized erythrocyte to bind to capillaries of the host , thereby avoiding removal by the spleen . Each parasite has approximately 60 genes encoding different versions of this adhesion protein , and a switch in surface display of these proteins enables the parasite to evade the immune system . Here we show that different variants of these binding proteins can be found expressed simultaneously on single infected red blood cells mediating binding to different endothelial receptors .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"infectious",
"diseases/protozoal",
"infections",
"molecular",
"biology",
"cell",
"biology/gene",
"expression",
"microbiology/parasitology"
] |
2010
|
Surface Co-Expression of Two Different PfEMP1 Antigens on Single Plasmodium falciparum-Infected Erythrocytes Facilitates Binding to ICAM1 and PECAM1
|
Several studies have proven oseltamivir to be efficient in reducing influenza viral titer and symptom intensity . However , the usefulness of oseltamivir can be compromised by the emergence and spread of drug-resistant virus . The selective pressure exerted by different oseltamivir therapy regimens have received little attention . Combining models of drug pharmacokinetics , pharmacodynamics , viral kinetics and symptom dynamics , we explored the efficacy of oseltamivir in reducing both symptoms ( symptom efficacy ) and viral load ( virological efficacy ) . We simulated samples of 1000 subjects using previously estimated between-subject variability in viral and symptom dynamic parameters to describe the observed heterogeneity in a patient population . We simulated random mutations conferring resistance to oseltamivir . We explored the effect of therapy initiation time , dose , intake frequency and therapy duration on influenza infection , illness dynamics , and emergence of viral resistance . Symptom and virological efficacies were strongly associated with therapy initiation time . The proportion of subjects shedding resistant virus was 27-fold higher when prophylaxis was initiated during the incubation period compared with no treatment . It fell to below 1% when treatment was initiated after symptom onset for twice-a-day intakes . Lower doses and prophylaxis regimens led to lower efficacies and increased risk of resistance emergence . We conclude that prophylaxis initiated during the incubation period is the main factor leading to resistance emergence .
Besides influenza vaccination , neuraminidase inhibitors are currently the most effective pharmaceutical intervention recommended to reduce the burden of seasonal or pandemic influenza [1] , [2] , [3] , [4] , [5] , [6] . Two neuraminidase inhibitors are widely marketed: nebulised zanamivir ( Glaxo Wellcome ) and oral oseltamivir ( Hoffmann-La Roche ) . These drugs block the release of influenza virus from infected host cells and hence reduce the spread of infection in the respiratory tract [7] . Oseltamivir has been stockpiled in many countries for pandemic preparedness and is the most frequently used neuraminidase inhibitor worldwide [8] . Oseltamivir therapy accelerates the time to alleviation of influenza-like illness and post-exposure prophylaxis with oseltamivir reduces secondary transmission of influenza [9] . However , oseltamivir effectiveness strongly depends on the delay between infection ( or onset of symptoms ) and the first antiviral intake [10] . Oseltamivir effectiveness can also be compromised by the emergence and further spread of drug-resistant viruses such as the H275Y mutant strain [11] . Most resistant isolates emerge during post-exposure prophylaxis [12] or under a curative regimen in subjects with intense or prolonged viral shedding , such as children [13] , [14] or immunocompromised persons [15] , [16] , [17] . The interactions between time of infection , first oseltamivir intake , dose regimen , and host response to infection are complex with respect to symptoms , virological efficacy and emerging resistance . Moreover , the dynamics of influenza infection is highly variable between subjects [18] and the pharmacokinetics of oseltamivir leads to large concentration variations over time [19] , which can lead to variable efficacy at the individual level . To the best of our knowledge , the between-subject variability and the effect of oseltamivir pharmacokinetics have never been studied in detail . Here we explore these interactions in silico , using a hybrid deterministic/stochastic adaptation of the combination of a pharmacokinetic ( PK ) model of oseltamivir [19] and a virus kinetic/symptom dynamic ( VKSD ) model previously fitted to data on experimental human infection [18] . We provide an integrative framework to assess antiviral therapy by simultaneously taking into account random mutations , oseltamivir efficacy , and selective pressure .
We simulated viral dynamics and investigated emergent drug resistance in a sample of 1000 individuals . The three individual PK parameters and eleven individual VKSD parameters were drawn from a log-normal distribution , where is the average population value and is the average between-individual variability [18] , [20] ( Text S2 ) . and and their respective standard errors were estimated in previous studies for all parameters [18] , [20] . These studies involved healthy volunteers who in the VKSD study were on 18 to 40 years old , with serum hemagglutinin antibody titers of <1∶8 to the relevant virus strains and experimentally infected with influenza A/Texas/91 at time 0 . Finally , the resistant variant emergence rate , , was set to −6 per replication cycle ( −6 in the case of reduced infectivity of resistant strains ) so that the model reproduces previous observations showing that between 0 . 4 and 1% of patients when treated with 75 mg bid for 5 days starting one day after symptom onset shed resistant virus 2 days after treatment initiation [29] , [30] . Three oseltamivir regimens are approved in adults: 75 mg daily ( qd ) for 10 days ( post-exposure prophylaxis regimen ) , 75 mg twice-a-day ( bid ) for 5 days ( curative regimen ) and 150 mg bid for 5 days ( recommended regimen for severe pandemic influenza ) [31] . In a first set of simulations , we used the recommended curative regimen as a reference . For comparison purposes , we explored the effect of drug dose simulating 75 , 150 and 300 mg bid for 5 days . We also explored the effect of intake frequency , simulating 75 mg qd for 5 days , 75 mg bid for 5 days and 75 mg three-times-a-day ( tid ) for 5 days . Finally , we explored the effect of treatment duration , simulating 75 mg bid for 5 , 10 and 15 days . In a second set of simulations , we used the recommended post-exposure prophylaxis regimen as a reference . We investigated the effect of the dose simulating 75 , 150 and 300 mg qd for 10 days . We also explored the effect of intake frequency , simulating 75 mg qd for 10 days , 75 mg bid for 10 days and 75 mg tid for 10 days . Finally , we examined the effect of prophylaxis duration , simulating 75 mg qd for 5 , 10 and 15 days . We chose ten possible therapy initiation times . Therapy initiation was simulated at 3 , 2 and 1 day ( s ) prior to infection in order to study the impact of possible drug build-up before infection occurred . To simulate therapy initiation during the incubation period , the time of first intake was set to 0 , 0 . 5 , 1 and 1 . 5 days after infection . To simulate a typical curative regimen , we set the first intake at 2 , 3 and 4 days after infection , which corresponded to 0 , 1 and 2 days after symptom onset on average [6] . In all cases , the VKSD was simulated from the time of infection until day 8 . Finally , to simulate imperfect adherence , we considered an early discontinuation of therapy after 4 and 6 intakes ( instead of 10 ) for 75 mg qd and 75 mg bid regimens . We call therapies initiated after symptom onset treatment and those started before symptom onset prophylaxis . We assessed primarily the virological efficacy , defined here as the average decrease of the area under the curve of drug-sensitive virus titer ( without transformation ) ( ) and drug-resistant virus titer ( ) under treatment relative to the AUC of viral titers without antiviral therapy ( and ) . Virological efficacy was computed as: Symptom efficacy was measured as the average decrease in AUC of systemic symptoms ( ) under antiviral therapy relative to the AUCS without antiviral therapy ( ) . Symptom efficacy was thus computed as: The results are presented as the median value and inter-quartile range ( IQR ) . Two criteria were used to measured resistance emergence: first , the proportion of patients shedding resistant virus above the limit of detection ( LOD = 2 TCID50/mL [32] ) . We also assessed the fraction of all virus shed that was resistant . All results about viral shedding presented thereafter represent viral load ( for drug-sensitive and/or drug-resistant virus ) above the LOD , at any time of infection .
Our simulated PK model shows increases of OC concentration with peaks occurring on average 4 hours after each intake ( Fig . 2 . ) . After the last oseltamivir intake , a prolonged concentration decrease was observed ( Fig . 2 ) . The height of the peak was proportional to the regimen dose . OC concentrations above the for drug-sensitive and resistant viruses were obtained in the first hour after first oseltamivir intake , regardless of dose . While the OC concentration remained above the for both drug-sensitive and drug-resistant viruses with twice-a-day intakes , with 75 mg qd for 10 days , OC concentration was above the for drug-sensitive virus and below the for resistant virus for an average 7 . 8 hr after each intake . Simulating 1000 in silico patients , drawing parameters from previously estimated distributions [18] , [20] , we find the median viral titer peak was 4 . 5 log10 ( TCID50/mL ) ( IQR 2 . 6–5 . 3 log10 ( TCID50/mL ) ( Fig . 3 ) . The duration of viral shedding above the LOD was 7 . 0 days ( IQR 1 . 0–8 . 0 days ) . The incubation period was 1 . 9 days ( IQR 1 . 0–3 . 0 ) and the systemic symptom score peak was 3 . 9 ( IQR: 0 . 1–12 ) and lasted 2 . 4 days ( IQR 0 . 2–7 . 0 days ) . The AUC of the viral curve was 4 . 5 log10 ( TCID50/mL ) ( IQR 2 . 9–5 . 3 ) . The AUC of the systemic symptom curve was 2 . 0 ( IQR 0 . 3–7 . 7 ) . As expected due to our choice of μ , 0 . 6% patients shed resistant viruses . Using the same set of 1000 in silico patients , but now given treatment we find that the virological and symptom efficacies ( see Methods ) were strongly dependent on the therapy initiation time ( Fig . 4 ) . For all possible drug regimens , both virological and symptom efficacies were found to be greatest when prophylaxis was initiated between one day before and one day after inoculation . With the recommended curative regimen of 75 mg bid for 5 days ( red curve in all panels ) , virological efficacy during this period was above 60 . 0% with a peak at 99 . 9% for therapy initiated at the time of inoculation . When oseltamivir ( 75 mg bid for 5 days ) was started earlier , the efficacy decreased as viral replication was postponed after the last intake , as shown by the high number of infected cells in many patients after the last intake and later ( Fig . S1 ) . The virological efficacy decreased with treatments started after symptom onset and is below 5 . 0% when the treatment is initiated at day 4 ( Fig . 4 ) . This low virological efficacy is due to the fact that the viral infection is largely resolved by this time in the absence of treatment ( Fig . 3 ) A similar pattern was observed for symptom efficacy with a peak of 99 . 9% with 75 mg bid for 5 days initiated at the time of inoculation ( Fig . 4B , D , F ) . We next compared the effect of the dose on the variation of virological and symptom efficacy depending on the therapy initiation time relative to the time of infection ( Figs . 4 A & B ) . The virological and symptom efficacies increased with higher doses when the oseltamivir is initiated before inoculation and were similar for treatments started after symptom onset ( Table 2 , Figs . 4 A & B ) . For example , for oseltamivir started 1 day after inoculation , the virological efficacy was 79 . 6% with 75 mg bid for 5 days , 83 . 7% with 150 mg bid for 5 days and 92 . 5% with 300 mg bid for 5 days ( Table 2 ) . We then compared the effect of intake frequency on the variation of virological and symptom efficacy depending on the therapy initiation time relative to the time of infection ( Figs , 4 C & D ) . The virological and symptom efficacies increased with higher intake frequency for prophylaxis and curative treatments ( Table 2 , Figs . 4C & D ) . For example , for oseltamivir initiated 1 day after inoculation , the virological efficacy was 68 . 6% with 75 mg qd for 5 days , 79 . 6% with 75 mg bid for 5 days and 85 . 1% with 75 mg tid for 5 days ( Table 2 ) . We finally compared the effect of therapy duration on the variation of virological and symptom efficacy depending on the therapy initiation time relative to the time of infection ( Figs . 4 E & F ) . The virological and symptom efficacies were greater for oseltamivir given for 10 days or more compared to therapy lasting 5 days ( Table 2 , Figs . 4 E & F ) . For example , for oseltamivir started 1 day after inoculation , the virological efficacy was 79 . 6% with 75 mg bid for 5 days , 97 . 0% with 75 mg bid for 10 days and 97 . 0% with 75 mg bid for 15 days ( Table 2 ) . The difference in virological and symptom efficacy depending on the dose , therapy duration and intake frequency was below 1% ( Table 2 , Fig . 4 ) for treatment initiated 3 or 4 days after inoculation ( or 1 or 2 days after symptoms onset ) . For the set of simulation using the recommended post-exposure prophylaxis regimen ( 75 mg qd for 10 days ) as reference , both virological and symptom efficacy remained high ( above 99 . 9% ) when the prophylaxis was administered for more than 10 days and when initiation took place before inoculation or 0 . 5 days after inoculation . Virological efficacy fell to 62% for a prophylaxis initiated 1 day after inoculation and below 5 . 0% when the curative treatment was initiated 4 days after inoculation ( Fig . S2 ) . Resistance emergence can occur before therapy initiation but the median fraction of resistant virus represented less than 0 . 001% of the total amount of virus shed . Without treatment or before therapy initiation , the viral titer for drug-resistant virus followed the same pattern as the drug-sensitive virus and peaked at the exact same time as we have assumed no fitness cost associated with resistance , i . e . , the viral dynamic parameters are the same as for the drug-sensitive virus . Once under therapy , the drug-sensitive virus titer decreased rapidly while in patients shedding resistant virus the resistant virus titer increased ( Fig . S4 ) . We studied the variation of resistance emergence depending on the therapy initiation time relative to the time of infection for a set of different regimens . We observed a similar pattern of resistance emergence with the different regimens ( Figs . 5 and S3 ) . If a 5-day prophylaxis regimen was initiated before inoculation , the proportion of subjects shedding resistant virus increased the earlier prophylaxis was initiated . This reflects the fact that drug concentration above was not available long enough to suppress viral replication . This was observed for every simulated regimen except when prophylaxis lasted 10 or 15 days . In these latter cases , the proportion of subjects shedding resistant virus when the prophylaxis was initiated before inoculation remained below 1% . The fraction of resistant virus shed remained below 1% when prophylaxis was initiated before inoculation except for the recommended post-exposure prophylaxis regimen ( 75 mg qd for 10 days ) for which it was between 1 . 9 and 2 . 5% ( Fig . S3 ) . The proportion of subjects shedding resistant virus increased when oseltamivir was initiated during the incubation period with a peak between 8 . 3% ( 300 mg bid for 5 days ) and 26 . 7% ( 75 mg qd for 5 or 10 days ) for therapy initiated 1 day after inoculation ( Figs . 5 and S3 ) . Similarly the fraction of drug-resistant virus peaked for therapy initiated 1 day after inoculation . Our model predicts a peak in resistance emergence for any regimen when the first oseltamivir intake takes place 1 day after inoculation ( Fig . 5 A–F ) . The proportion of resistant virus then decreased with the time treatment was administered after symptom onset . Looking in more detail at the effect of dose on resistance emergence depending on the therapy initiation time we note resistance emergence decreased with higher doses when oseltamivir was initiated before inoculation and was similar for treatments started after symptom onset ( Figs . 5 A & B ) . For example , for oseltamivir started 1 day after inoculation , the proportion of subjects shedding resistant virus was 20 . 1% , 14 . 3% and 8 . 3% with 75 mg , 150 mg and 300 mg bid for 5 days , respectively . We then compared the effect of the intake frequency on resistance emergence depending on the therapy initiation time relative to the time of infection ( Figs . 5 C & D ) . Resistance emergence decreased with higher intake frequency for prophylaxis and curative treatments ( Figs . 5C & D ) . For example , for oseltamivir started 1 day after inoculation , the proportion of subjects shedding resistant virus was 26 . 7% , 20 . 1% and 17 . 0% with 75 mg given for 5 days qd , bid and tid , respectively . We finally compared the effect of therapy duration on resistance emergence . Resistance emergence was similar with 75 mg bid for 5 , 10 and 15 days ( Figs . 5E & F ) . For example , for a oseltamivir started 1 day after inoculation , the proportion of subject shedding resistant virus was 20 . 1% , 21 . 0% and 21 . 0% with 75 mg bid for 5 , 10 and 15 days , respectively . As expected , early therapy discontinuation was associated with a decrease of virological and symptom efficacies and with an increase of the proportion of subjects shedding resistant virus . When therapy with 75 mg bid started 1 day after inoculation the virological efficacy decreased from 79 . 6% for a 5 day therapy to 49 . 0% for a discontinuation after 4 intakes and 67 . 5% for a discontinuation after 6 intakes; symptom efficacy decreased from 72 . 3% to 44 . 5% and 46 . 3% for discontinuations after 4 and 6 intakes , respectively . The proportion of subjects shedding resistant virus increased from 20 . 1% to 26 . 4% and 22 . 6% , for discontinuations after 4 and 6 intakes , respectively ( Fig . S7 ) . We simulated viral kinetics under oseltamivir using four different to reflect the wide range of values experimentally measured in antiviral analysis [21] . The pattern was similar with all four , with maximal efficacy obtained when therapy was initiated between 1 day before and 1 day after inoculation and a peak of resistance emergence when oseltamivir was initiated during the incubation period . As expected , we found that virological and symptom efficacy would decrease , while resistance emergence would increase , when the was increased ( Fig . S5 ) . Drug efficacy varied inversely with and resistance emergence increased with ( Fig . S6 E–H ) . When we tested the effect of the conversion factor from TCID50/mL to the number of infectious virions at the site of infection , we found similar results . The virological and symptom efficacies dependency on oseltamivir initiation time was similar for all conversion factors . However , we noted an impact on the stochastic simulations as the variability of drug-resistant virus shedding is larger for smaller conversion factors . This led to similar virological and symptom efficacies but resistance emergence increased when the conversion factor was decreased ( Fig . S5 ) as more subjects shed drug-resistant virus above the LOD ( Fig . S6 ) . An infectivity decrease by 10% for resistant virus had a limited impact on the proportion of subjects shedding resistant virus above the limit of detection and the proportion of virus shed that is resistant ( Fig . S6 A–D ) . Similarly , the curves showing how the virological and symptom efficacies vary with treatment initiation time were similar to those found in the absence of any cost due to resistance ( Fig . S6 ) .
Mathematical modeling has provided significant insights into influenza viral kinetics [22] , [23] , [33] , [34] , [35] , [36] , [37] . Handel et al . used a viral kinetic model for characterizing emergence of drug resistance during oseltamivir treatment [28] , but they did not consider the effects of drug PK nor did they take into account the between-individual variability . Using the population approach , our model reflects the heterogeneity in viral kinetic and symptoms dynamic observed in the population . This allowed us to compute the proportion of subjects shedding resistant virus and therefore to assess resistance emergence . In this previous modeling study , efficacy was considered constant over time and ineffective on drug-resistant strains [28] . In contract , we allowed the drug-resistant strain to be sensitive to high OC concentrations [26] . Moreover , in our model the drug efficacy can vary greatly due to drug concentration fluctuations and between-subject variability with respect to both their viral kinetics and pharmacokinetics . We found that the OC concentration with the recommended prophylaxis regimen of 75 mg qd was above the for drug-sensitive virus and below the for drug-resistant virus for an average of 7 . 8 hr between two doses . These low concentrations favor the selection of resistant virus . Our approach using a hybrid stochastic and deterministic simulation algorithm is capable of capturing the stochastic behavior of small populations of viruses and infected cells while reducing the computational burden associated with fully stochastic algorithms . The partitioned leaping algorithm [38] employed by Handel et al . [28] to investigate a related problem in emergent neuraminidase inhibitor resistance is also well suited to problems with widely disparate rates and species populations . This algorithm assumes constant rate parameters . However , as we incorporated oseltamivir pharmacokinetics into our model , yielding time-dependent drug efficacies , which translate in our simulation to time-dependent rates , the partitioned leaping algorithm does not lend itself well to simulations of our model and was not pursued . Instead the hybrid stochastic and deterministic simulation algorithm was used as it is well adapted to models with time-dependent rates– as is the case in the present study , where we incorporated both viral dynamics and innate immune responses . Using this approach , we were able to perform model simulations under a wide variety of drug regimens and investigated further the effect of numerous covariates such as treatment initiation time , dose , intake frequency and treatment duration on efficacy and resistance emergence risk . In our model , we assumed that every subject was infected with drug-sensitive virus , which is the most optimistic scenario , and we did not consider cases in which subjects were infected with resistant virus or a mixture of both . If we allowed infection by resistant virus the selection of resistant virus would occur faster and the proportion of subjects shedding resistant virus and the fraction of resistant virus would dramatically increase . We also assumed that only resistant virus with the same fitness as drug-sensitive virus emerged . Pre-existing permissive mutations , such as R222Q , R194G , E214D , T289M , N369K , L250P or F294Y , in the drug-sensitive virus were shown to facilitate the emergence of resistant virus without any fitness loss [25] , [39] , [40] . In case of a mixture of resistant virus ( H275Y ) with and without a permissive mutation [41] , the virus with the permissive mutation grows faster than the virus without this mutation , and therefore the amount of resistant virus with fitness loss would be negligible . Our simulations show an increased efficacy for early oseltamivir initiation as the drug blocks virus release and subsequent rounds of virus infection . In case of oseltamivir initiation before infection , we show that efficacy decreases for short duration of treatment as infected cells are not cleared at the end of treatment . Efficacies are also low in case of late initiation ( after symptom onset ) of oseltamivir as the infection is already resolving . The peak in the amount of resistant virus shed and in the proportion of people shedding resistant virus observed when oseltamivir is initiated during the incubation period ( Fig . 5 ) can be explained by the selective pressure of oseltamivir on drug-sensitive strains and by the fact that at the early stage of infection there is a lack of sufficient cytokines to control the resistant virus and to stimulate the NK cell response . Our simulations were consistent with previous results in terms of virological and symptom efficacies: early administration of oseltamivir increased virological and symptom efficacy [42] , [43] , [44] . More specifically , the mean virological efficacy with 75 mg bid was 86 . 3% when oseltamivir was taken 0 . 5 days after inoculation and fell to 24% when oseltamivir was taken 3 days after inoculation , which is similar to published experimental and epidemiologic data [3] , [45] . The rates of emerging resistance predicted by our model are consistent with previously described experimental and epidemiological studies [16] , [46] , [47] , [48] , irrespective of whether the first intake was 1 day prior to inoculation , during the incubation period or after symptom onset . We found that the timing of therapy initiation is crucial to reach the right balance between efficacy and resistance emergence as it provides a global pattern that dose , intake frequency and treatment duration can modulate . Resistance emergence dramatically increased when prophylaxis was initiated during the incubation period . This was observed for every dose regimen and was exacerbated with low dose or when oseltamivir was taken once-a-day . For instance , with the recommended post-exposure prophylactic regimen ( 75 mg qd for 10 days ) , the proportion of subjects shedding resistant virus increased from 2 . 2% when prophylaxis was initiated before inoculation to 26 . 7% when prophylaxis was initiated during the incubation period and fell below 1% when treatment was initiated after symptom onset . Whereas the proportion of subjects shedding resistant virus was below 1% with treatment initiated after symptom onset , it dramatically increased and reached up to 27% with prophylaxis initiated during the incubation period . Similarly , expected the fraction of resistant virus shed by an infected person rose to 23% with prophylaxis initiated during the incubation period . We explored the effect of imperfect adherence on resistance emergence and drug efficacy ( Fig . S7 ) . We found that early discontinuation of treatment induces a decrease of both virological and symptom efficacies and an increase of the risk of resistance emergence . Our model also predicts that it is very unlikely that an individual on long-term prophylaxis ( 75 mg qd for 10 or 15 days ) will become infected by a drug-sensitive strain ( Fig . S2 ) , in line with epidemiologic findings [49] , [50] . However , this probability increases dramatically in case of an infection with a resistant virus ( Text S3 ) . Consequently , prophylaxis failure is likely caused either by infection with a resistant virus or by selection of a de novo resistant virus and switching to a curative regimen in those patients would have no impact on the time course of influenza . Our findings have several limitations . First , this study is limited to otherwise healthy adult subjects infected with drug-sensitive virus only , as parameters were obtained from studies conducted in this setting [18] . In other populations , such as children the pharmacokinetics might substantially differ . Indeed , the recommended oseltamivir dose is 1 . 0 mg/kg and 2 . 0 mg/kg bid in neonates and children aged 1–5 years , respectively , leading to lower concentrations than in adults [14] , [51] , [52] . This in part could explain the increased risk of emerging resistance observed in children [14] , [53] , [54] . Second , our model did not include an adaptive immune response . In the study subjects from which our viral kinetic parameters were derived , the anti-influenza antibody titer was below 1∶8 , suggesting that they did not have prior exposure to this strain of influenza . Thus our predictions might not apply to a population with high-level pre-existing immunity . In future studies one could use a model such as that of Miao et al . [37] or others [23] , [34] , [35] , [36] that include adaptive immune responses . However , such models have not been well parameterized for human infections , especially with regard to individual variability . Third , our model was based on experimental infection studies where the time of infection was known . Thus , we could study the effect of starting treatment at defined times relative to the time of infection . For naturally acquired infections , the time of infection is not known although if severe enough the time of symptom onset can be identified . Our model suggests that starting therapy during the incubation period , i . e . pre-symptoms , can enhance the probability of drug resistance emerging during therapy . Starting prophylaxis during the incubation period may occur in a household setting where an index case is diagnosed with influenza infection and his/her asymptomatic contacts start oseltamivir therapy to prevent new cases . In summary , we found that the recommended post-exposure prophylactic regimen should be used with caution , as it increases the risk of emerging resistance [55] . More specifically , once-a-day intake increases the proportion of subjects shedding resistant virus by 2 to 6% across all simulated dose regimes . Most importantly , initiating prophylaxis during the incubation period is the main factor leading to resistance emergence for all possible regimens . During this period , the infected cells cannot be controlled by NK cells as many of them are not yet activated and the number of target cells is still large . We thus believe that oseltamivir prophylaxis should be restricted either to subjects prone to develop severe cases ( such as immunocompromised subjects ) and treated with high doses ( 300 mg per intake ) , frequent intakes ( bid or tid ) and for longer duration ( 10 to 15 days ) , or in the otherwise healthy patients , after exclusion of an influenza infection in the incubation period ( for example using a sensitive rapid test ) , in order to decrease the risk of resistant virus emergence and to preserve oseltamivir efficacy .
|
Oseltamivir is currently the most commonly used drug against influenza but the emergence and spread of oseltamivir-resistant virus is threatening its usefulness . A previously published study quantified the risk of drug-resistance emergence and spread . In this work we investigate under what conditions drug-resistance is likely to occur and how we can mitigate it . For this purpose , we simulated populations of influenza-infected subjects under different treatment conditions varying drug dose , intake frequency and duration of therapy . We used an approach that mimics the randomness of drug-resistance emergence and allowed for between-subject variability . We measured the effect of treatment on reducing infection and symptoms and on drug-resistance emergence . We found that for subjects starting oseltamivir during the influenza incubation period , the risk of resistance emergence is dramatically increased . Thus , our findings suggest that standard prophylaxis should only be used after exclusion of an influenza infection in the incubation period by use of a rapid test . If existing infection cannot be excluded , then prophylaxis should be done with increased dose , intake frequency and duration in order to avoid emergence of drug-resistant strains and to preserve oseltamivir efficacy .
|
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2014
|
Impact of Different Oseltamivir Regimens on Treating Influenza A Virus Infection and Resistance Emergence: Insights from a Modelling Study
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Genetic diversity across different human populations can enhance understanding of the genetic basis of disease . We calculated the genetic risk of 102 diseases in 1 , 043 unrelated individuals across 51 populations of the Human Genome Diversity Panel . We found that genetic risk for type 2 diabetes and pancreatic cancer decreased as humans migrated toward East Asia . In addition , biliary liver cirrhosis , alopecia areata , bladder cancer , inflammatory bowel disease , membranous nephropathy , systemic lupus erythematosus , systemic sclerosis , ulcerative colitis , and vitiligo have undergone genetic risk differentiation . This analysis represents a large-scale attempt to characterize genetic risk differentiation in the context of migration . We anticipate that our findings will enable detailed analysis pertaining to the driving forces behind genetic risk differentiation .
Analyzing the impact of human migration on genetic disease susceptibility is critical to the understanding of complex disease . Moving to new environments causes adaptation , which can also affect disease susceptibility . The availability of methods to measure genomic differences between worldwide populations has increased our understanding of human migration . For example , a worldwide human relationships phylogenetic tree was constructed after genotyping over 50 worldwide populations [1] . This process has enabled researchers to characterize worldwide genetic variation and has provided information regarding migrations that founded entire populations [2] , [3] . At the same time , Genome-Wide Association Studies ( GWAS ) have increased discoveries of disease-associated genetic loci . These developments have paved the way for studies investigating the effects of migration on the genetic basis of disease [4]–[6] . The human genome has been subjected to many selective pressures in recent history . They include changes brought about by the domestication of crops and animals , and the rise of urbanization [7] . These changes may increase the frequency of mutations that are beneficial in the new environment . They may also lead to disruptions of biological processes . When mutations confer a net increase in fitness , they are expected to increase in frequency in affected populations [8] , [9] . A mutation increasing disease risk can accompany a beneficial mutation through linkage disequilibrium ( LD ) . Studies have shown that unlinked single nucleotide polymorphisms ( SNPs ) associated with a single phenotype may be affected as a group if the phenotype undergoes differentiation [10] , [11] . While a large set of loci may increase susceptibility to complex disease , individual loci generally make modest contributions , and their effect sizes indicate that they would not be expected to decrease reproductive success [12] . This situation allows differences in the genetic basis of disease to build naturally via genetic drift . However , deviations from genetic drift are expected when environmental changes occur due to migration [13] . Such changes provide an opportunity to learn about factors elevating disease risk in multiple populations . Adaptation to new environments may have caused genetic risk differences across many human populations . Despite the recent explosion of knowledge regarding disease-associated loci and the genetic structure of different world populations [14]–[19] , few studies have examined population-based differences in the genetic risk factors for disease . Additionally , they have included only a modest number of diseases , populations , or genetic samples . For example , Myles et al . [6] genotyped 25 disease-associated SNPs in ∼1 , 000 individuals from 53 populations in the HGDP-CEPH Human Genome Diversity Cell Line panel [15] . The study measured allele frequency differences in the SNPs and concluded that while risk allele differentiation was unusually high in some cases , overall , disease SNPs were not more differentiated between populations than random SNPs . However , 25 SNPs may not be sufficient to determine whether disease-associated SNPs as a whole have undergone risk allele differentiation in worldwide populations . These 25 SNPs are a small subset of variants that influence a small number of specific diseases . Other studies have examined interactions between migration , selection , and disease . One examined the impact of selection on hypertension variants during the migration out of Africa [20] . Others reported increased allele frequency differentiation of type 2 diabetes variants [21]–[23] . It is also plausible that allele differentiation may have occurred in unexamined combinations of diseases and populations . One study probed 2 , 186 disease-associated SNPs in the HapMap CEU cohort and concluded that they were enriched for low-frequency alleles [24] . This study used a large number of SNPs , but was conducted on a single population . A study incorporating a comprehensive catalog of SNPs and a large genetically diverse cohort would implicitly place genetic risk in the context of migration and reveal worldwide genetic risk variation with respect to many diseases . In a previous study , we surveyed 8 , 377 SNPs representing 437 diseases in 11 subpopulations . We found differences in risk distribution and protective alleles in different diseases across many subpopulations [25] . The current study examines how the differences in these distributions could have arisen . We analyzed correlations between genetic risk and migration trajectories . Our goal was to identify populations with different genetic dispositions to disease , and to pinpoint migrations preceding these differences . Our analysis highlights the role evolution has played in changing disease susceptibility across populations . Importantly , our approach controls for genetic substructure within and among diverse populations [26] . To detect differences in the genetic basis of disease across migratory events , we integrated a large curated database of geographically-annotated , disease-associated SNPs with human variation measurements in 51 populations from the Human Genome Diversity Panel ( HGDP ) . We controlled for established genetic similarity in subpopulations in order to detect differences in genetic risk exceeding those expected under genetic drift .
Figure 1A summarizes our findings for type 2 diabetes on a world map . Consistent with our previous work [25] , we found that African populations have the highest genetic risk for type 2 diabetes , followed by people from the Middle East , Europe , and Asia . The Mandinka population had the greatest risk , at a mean 0 . 95 log likelihood ratio ( LLR ) , while the Surui population had the lowest risk ( LLR: −0 . 87 ) . This high-level view revealed stark differences in genetic risk between African and Asian populations . European and Middle-Eastern populations had an intermediate genetic risk for this disease . These patterns identified worldwide trends of increases or decreases in genetic risk and show a high-level view of variation in genetic risk for different diseases . An interactive version of Figure 1A is available for over 100 diseases at geneworld . stanford . edu . Placing genetic risk on a map does not reveal close relationships between populations . Figure 2 is a worldwide phylogenetic tree displaying the relative genetic risk for each population in the context of population relationships . Relationships were inferred in a previous study [1] by analyzing 650 , 000 SNPs using a maximum-likelihood approach . Results from that analysis have been incorporated here . Each branch in the figure represents the ancestral population common to all populations below it . Figure 1A and Figure 2A show that genetic risk for type 2 diabetes has undergone independent differentiation multiple times as humans migrated out of Africa to East Asia , and finally to the Americas . “Independent differentiation event” was defined as genetic risk differentiation occurring de novo in a population rather than via inheritance from an ancestral population . “Dependent risk differentiation” is a genetic risk inherited from an ancestor . Table 1 shows individual populations with genetic risk differences for type 2 diabetes that are larger than expected under genetic drift; however , it does not distinguish between dependent and independent genetic risk differentiation . We used a maximum likelihood method to identify branches in the phylogenetic tree representing independent genetic risk differentiation events in Figure 2A . The log-likelihood of having only one event for type 2 diabetes was l1 = −108 . 848 . The log-likelihoods for 2 , 3 , 4 , 5 , and 6 events were l2 = −66 . 6083 , l3 = −40 . 7165 , l4 = −33 . 7324 , l5 = −26 . 8371 , l6 = −23 . 3415 . We used the likelihood ratio test to determine the number of branches undergoing genetic risk differentiation independently that exceeded what would be expected under genetic drift . This test allows for the calculation of a p-value for n independent branches by converting two log-likelihood scores to a χ2 variable as follows: 2 ( ln−ln−1 ) ∼χ21 . The p-value for 2 branches versus 1 branch undergoing independent genetic risk differentiation for type 2 diabetes was less than 1 . 00×10−16 , meaning there was evidence for more than one independent genetic risk differentiation event . The p-values for 3 , 4 , 5 , and 6 branches were 6 . 30×10−13 , 1 . 86×10−4 , 8 . 19×10−3 , and 5 . 64×10−2 , respectively . There was evidence for 5 distinct genetic risk differentiation events ( highlighted in green in Figure 2A ) . Figure 3 shows the genetic risk of all 1043 individuals . Each type 2 diabetes-associated genotype in each individual is displayed . The x-axis shows individual genetic risk; the y-axis corresponds to West ( bottom ) to East ( top ) migration . The figure shows that genetic risk for type 2 diabetes decreases as populations move into East Asia . The figure shows that genetic risk decreases steadily , as opposed to being caused by a single genetic risk differentiation event . Analysis of individuals showed that a person in the Mozabite population ( HGDP1255 ) had the highest genetic risk ( LLR:2 . 81 ) , and an individual in the Han population ( HGDP1291 ) had the lowest risk ( LLR: −2 . 21 ) . The effect size of each individual variant is not necessarily the same in each population [27] . While the genetic risk of disease is currently computed using all available GWASs , there is a well-known European bias , as most GWASs are based on European-derived populations [28] . Table S1 displays the populations in which SNPs associated with type 2 diabetes in this study have been replicated . In order to ensure that effect sizes unique to European populations were not solely responsible for observed levels of genetic risk differentiation , the genetic risk for type 2 diabetes was recomputed using Asian-specific effect sizes for all variants . This was accomplished by using GWASs exclusively based on Asian populations . Table S2 compares the likelihood ratio computed using GWASs in which European populations are overrepresented with the Asian-specific likelihood ratio computed using Asian based GWASs . Table S3 compares the genetic risk estimates using all available GWASs and Asian-specific GWASs . Despite major differences in overall risk estimates , significant risk differentiation was still observed in Asian populations when risks were computed with Asian-specific GWASs . Figure 1B shows the genetic risk of biliary liver cirrhosis ( BLC ) across worldwide populations . In contrast to type 2 diabetes , no worldwide trend is apparent . Figure 2B shows risk differences that were larger than expected under genetic drift ( q<0 . 05 ) . Branches were colored green if the deviation of a population below them shifted toward decreased risk compared to all other populations and red if the shift was toward increased risk . The maximum likelihood model was not applied to Figure 2B , as each population showing signs of genetic risk differentiation did not have descendant populations in the phylogenetic tree . The maximum likelihood test only distinguishes between inherited and independent genetic risk differentiation and is therefore only suitable for diseases displaying obvious worldwide deviation trends . Figure 2B shows that the Druze and Japanese populations have genetic risk differentiation exceeding what is expected under genetic drift . The Druze population shows significantly less risk , with only 28 out of 100 , 000 random draws showing less risk ( q<0 . 05 ) than all other populations combined . The genetic risk in the Japanese population was higher , with only 18 out of 100 , 000 random draws showing a higher risk . Genetic risk differentiation in BLC was localized in one European and an Asian population . We examined genetic risk in individuals to expose potential outliers ( Figure 4 ) and to visualize variation in genetic risk estimates across all individuals . The person with the lowest risk ( HGDP1201 ) was from the Mandinka population and had a risk score ( combined LLR ) of −4 . 372 . The person with the highest risk ( HGDP1279 ) was from the Mozabite population and had combined LLR of 9 . 521 . This person appears to be an outlier . The individual with the second highest genetic risk ( HGDP998 ) was from the Karitiana population ( combined LLR: 5 . 54 ) . We observed genetic risk trends associated with migration in other diseases , including prostate cancer , alopecia areata , melanoma , asthma , neuroblastoma , polycystic ovary syndrome , and pancreatic cancer . One of the most extreme examples of genetic risk differentiation was observed in ulcerative colitis . Figure 5 displays the distribution of the expected amount of genetic risk difference for this disease between the Sinhdi population and all others . The red vertical line represents the actual observed genetic risk difference between the two populations . Only 15 out of 100 , 000 randomly generated genetic risk values had a larger ulcerative colitis genetic risk difference . We found genetic risk differentiation in multiple worldwide populations for pancreatic cancer and other diseases ( Table 1 ) . Detailed information relating to genetic risk differences for many other diseases are available on ( geneworld . stanford . edu ) . Individual SNPs may have a large impact on overall levels of genetic risk differentiation ( Text S1 and Figure S1 ) . One notable case is rs13151961 , associated with inflammatory bowel disease . Figure S1 shows examples of diseases in which a few SNPs have a disproportionate impact as well as examples in which all SNPs have a uniform impact on genetic risk differentiation . Our method can detect genetic-risk differentiation that is not captured by Fst calculations . Figure S2 shows that rank normalized Fst values , after binning with SNPs having matching allele frequencies , failed to detect population structure differentiation among SNPs associated with biliary liver cirrhosis . After combining p-values for each individual SNP , the combined p-value was 0 . 91 . Our method detects genetic-risk differentiation in the Japanese and Druze populations ( Figure 2B ) . Figure S3 shows the rank normalized Fst values for SNPs associated with type 2 diabetes . The combined p-value for the observed type 2 diabetes Fst scores was not significant ( p = 0 . 30 ) . Our method detects genetic-risk differentiation for multiple populations in type 2 diabetes , as can be observed in Figure 2A . Text S1 has additional details on the Fst analysis . Individuals may be outliers with respect to genetic risk , leading to false detection of genetic risk differentiation in a population . We defined outliers as individuals deviating >1 . 5 times the interquartile genetic risk range from the median genetic risk and removed them from each population-disease sets showing genetic risk differentiation ( Table S4 ) . Each disease showed strong signs of genetic risk differentiation after removing outlying individuals . Disease-associated SNPs are likely to be biased towards genomic regions with higher LD levels where they are tagged more efficiently . We addressed this bias by resampling from SNPs reported to be associated with any phenotype ( disease or not ) as opposed to resampling from all SNPs . We discarded 614 , 563 and retained 46 , 192 of the genotyped SNPs in the HGDP cohort . Genetic risk differentiation was still detected after resampling exclusively from SNPs associated with a phenotype ( Table S5 ) .
While the HGDP is an important sampling of the worldwide distribution of genotypes , it is possible that some populations are admixed . Detecting genetic risk differentiation in admixed populations may be more difficult , as the levels of genetic risk would most likely be less extreme . The genetic risk for any two populations in which admixed individuals were erroneously sampled is expected to be somewhere between the population with the least and most genetic risk . This explains why controlling for admixture is unlikely to decrease the significance of our findings . Multiple independent genetic risk differentiation events have occurred in various worldwide populations . Table 1 shows individual populations reported to have undergone or inherited an increase/decrease in genetic risk . We applied a maximum likelihood method to identify branches in a phylogenetic tree representing independent genetic risk differentiation events for type 2 diabetes ( Figure 2A ) . Individuals migrate toward decreased genetic risk of type 2 diabetes as populations migrated East . Figure 3 shows that while there was great variability in risk within populations , there was still a steady decrease in susceptibility to type 2 diabetes . There were 44 SNPs associated with biliary liver cirrhosis used in this study . We found genetic risk differentiation in the Japanese and Druze populations ( Figure 2B ) . Risk was increased in the Japanese population . The genetic risk score ( combined LLR ) was 1 . 691 , compared to 0 . 026 for all other populations combined . The q-value for such a large risk difference was 0 . 0112 ( Table 1 ) . Consistent with results in this study , our previous work shows significantly higher biliary liver cirrhosis risk in the Japanese population ( p: 0 . 013 ) in the Hap Map III cohort [29] . Like all the diseases discussed in this study , ulcerative colitis has genetic and environmental components [30] . Our results suggest that genetic risk differentiation for this condition is increased in South Asian Sindhis ( Figure 5 ) . Previous studies have reported that prevalence rates are not necessarily correlated to significant increases in genetic risk [31] , [32] . However , our results imply that some event affected pathophysiology of this disease in a particular population . The environment , as well as currently unidentified loci , may also affect the absolute risk . In addition to the Sindhi population , genetic risk differentiation was detected in the Palestinian and Balochi populations ( Table 1 ) . Specific environmental differences inducing genetic risk differentiation in type 2 diabetes and other diseases have not been found . However , there is evidence that climate , diet , and living conditions have led to them [33] . For example , exposure to viruses may have increased risk for type 1 diabetes [34] . Autoimmune diseases show disproportionate positive selection in a trajectory toward increased versus decreased risk [35] . This finding has given rise to speculation that viral epidemics are likely to have increased the risk of these diseases by selecting for an overactive immune system . It is also established that modern cultural changes can cause drastic differences in disease prevalence in related populations [36] . However , little is known about how these changes modify risk profiles and disease prevalence over time . This study provides critical clues for the foundation for future analyses . The concepts discussed here could be used to link diseases that may share pathophysiology and environmental triggers . It is possible that modulation of environmental features in different global regions changed the genetic risk of certain diseases . If an environmental feature affects multiple diseases , risk estimates for the diseases should correlate across the same populations , even if no common genetic basis is apparent . If the environment increases risk for one disease and decreases it for another , a negative correlation is expected . Finding diseases with genetic risk estimates correlated across worldwide populations would represent a novel and potentially highly informative approach to uncover shared pathophysiologies . This type of analysis would benefit from the largest possible catalog of genetic variants . For example , in the HGDP , East Asia is biased to detect more genetic risk differentiation than the Americas , due to the increased sensitivity that comes from 17 East Asian versus 5 American populations . In addition , full genome sequence analysis enables the inclusion of copy number polymorphisms and rare variants that may be found to contribute to complex disease susceptibility . As sequencing costs decrease , analyses expanding the scope of this study will occur .
We investigated >650 , 000 SNPs from the HGDP-CEPH , which has DNA from 1043 individuals in 51 populations on 8 continents [15] . We also used the HapMap Phase 3 cohort to analyze 1 . 6 million SNPs from 11 populations [29] . Finally , we used VARIMED , a database of disease-associated SNPs [37] . VARIMED was built by curating 5 , 478 published studies with 4 , 573 disease associations . At the time of this study , it contained 67 , 678 unique phenotype-associated SNPs , of which 51 , 404 were associated with a disease . Of these , after filtering by p-value and other methods , 723 unique SNPs were on the Illumina genotyping array we used to represent disease phenotypes in the HGDP [15] . For this study , we used only GWAS SNPs that had been detected across ≥2 populations with p-values<10−6 . SNPs were excluded if information about them was insufficient to compute likelihood ratios for the genotypes of associated SNPs . VARIMED was used to compute genetic risk estimates of the resulting diseases across all HGDP populations . The HapMap Phase 3 cohort includes 11 populations with 1 . 6 million SNPs genotyped per person [29] . We used this cohort , in combination with results from previous work [25] , to check our results in individual populations with elevated levels of genetic risk differentiation . All the methods with the exception of multiple hypothesis testing are applicable to this cohort . In this paper , the sample genetic risk in a population is referred to as genetic risk . Any computation of a population's genetic risk is inaccurate , due to the inability to genotype all individuals in a population and the existence of many undiscovered disease-associated variants . The likelihood ratio ( LR ) represents the effect size of a particular genotype on genetic disease risk . SNPs in linkage disequilibrium ( R2≥0 . 2 ) in a population were excluded . For a given bi-allelic SNP , there are three possible genotypes: homozygous for the major allele , homozygous for the minor allele , or heterozygous . The function L ( g ) maps the genotype g to the estimated likelihood ratio . The LR used in our calculations represents the weighted mean LR reported across all studies [37] . Each LR was weighted by the square root of the sample size in each association study . The following is our method for combining multiple LRs from multiple GWASs . A is the vector of all sample sizes in each study . P ( g | disease is present ) i is the estimated probability that a genotype g is in the disease population of the ith GWAS . P ( g | disease is not present ) i is the estimated probability that a genotype g is present in the non-disease population of the ith GWAS . Once computed , the combined LR was used to compute the genetic disease risk for each individual , as follows . G is the vector of all genotypes in disease-associated SNPs in person m . The predicted genetic risk r for person m is the log of the combined likelihood ratios for all disease-associated variants present in that person . The genetic risk for a population was the mean risk of all its members . Derived populations created by combining multiple populations in the HGDP were treated as single populations , and the following computations applied equally . S is the vector of a population . The predicted genetic risk R for an entire population P is the mean predicted risk for everyone in the population: In order to compare genetic risk ( D ) between two populations A and B , we subtracted the genetic risk of one population from the other's: Population A's risk for a disease is higher than B's if DAB is positive and lower if DAB is negative . We constructed a distribution of the expected difference of genetic risk between two populations in order to see if the observed difference was larger than expected by random chance: . The vector H represents all SNPs associated with a particular disease . Our goal was to assess the significance of a difference in risk DAB across two populations A and B . Each element in H was replaced by a SNP randomly drawn from the entire set of SNPs in the two populations . The global major allele frequency of the randomly drawn SNP was drawn to match original SNP's global major allele frequency . In every case , the risk allele's major or minor allele status in the randomly drawn SNP matched that of the SNP it replaced . In addition , each SNP was placed in one of eight functional categories ( frameshift , nonsense , missense , untranslated , near-gene , intron , coding-synonymous , or unknown ) . Each randomly drawn SNP also matched the functional category of the SNP it replaced in vector H . Once all elements of H had been replaced , the genetic risk of all populations was recomputed , effectively assigning a randomly generated genetic risk score to each population . Since each population was assigned a genetic risk score from the same randomly drawn set of SNPs , the expected amount of correlation between genetic risk values among all populations was preserved . We created phylogenetic trees of our results with each branch representing a migration event . We computed the genetic risk difference of each migration event by subtracting the genetic risk of all descendant populations from the risk of all ancestral populations ( those above the branch ) . Branches on the human phylogenetic tree created from the HGDP populations were tested for genetic risk differences . We computed the difference in risk between all ancestral and descendant populations . A phylogenetic tree of all the HGDP populations was used as described previously [1] . Each branch in the tree partitions an ancestral and descendant population . The ancestral population is made up of populations above a branch; the descendant population is below it . The expected difference in genetic risk between all possible ancestral and descendant comparisons was computed by randomly replacing all disease-associated SNPs by performing a random draw of H 100 , 000 times . We computed a matrix representing 100 , 000 randomly generated phylogenetic trees and compared it with the observed phylogenetic tree in the context of genetic risk . Let ri , k represent the genetic risk difference between ancestral and descendant populations in branch i computed from the kth randomly generated H . This matrix of 100 , 000 randomly generated phylogenetic trees was then compared to the observed tree . Oi is the observed genetic risk difference between ancestral and descendant populations in the ith branch of the phylogenetic tree . The probability of observing a genetic risk difference between ancestral and descendant populations in the ith branch is as follows: This equation gave a probability for a specific genetic risk difference observed on branch i . However , we tested multiple strongly correlated populations simultaneously . In addition , the genetic risk differences of nearby branches in the phylogenetic tree were strongly correlated due to genetic similarity between populations . One row in matrix R represented the genetic risk difference of all branches in the tree between ancestral and descendant populations in a single random draw . The genetic risk difference was calculated with the same set of SNPs in every branch in the phylogenetic tree in each row . This preserved the correlation of genetic risk among closely related populations and enabled us to detect independent genetic risk deviations . To assess the significance of a p-value α in the context of the entire tree , we first computed the number of branches having equal or greater significance for genetic risk differentiation . Significant genetic risk differentiation events were calculated follows . N ( α ) is the observed number of branches with a p-value for genetic risk differentiation at or below α . We next computed the expected number of branches with genetic risk differentiation at significance α from the matrix representing 100 , 000 randomly generated phylogenetic trees . Q ( α ) ( the q-value ) for a branch with p-value α for genetic risk differentiation was: While Q ( ) can inform on the significance for a particular p-value , it does not estimate the total number of distinct genetic risk differentiation events in a phylogenetic tree . We estimated the most likely number of migration events independently contributing to observed genetic risk deviation in a phylogenetic tree using a maximum likelihood approach . P is the vector containing all probabilities of the observed genetic risk difference between ancestral and descendant populations of each branch of tree t . We defined a function that returns true if branch k is not a descendant of branch z: Branch z represents the branch in which an independent genetic risk differentiation event occurred . Applying the principle of maximum likelihood , the branch z that maximizes the likelihood function in tree t is shown below . The number of events refers to the number of independent genetic risk differentiation events . The log likelihood function produces the branch most likely to have undergone genetic risk differentiation , given that a single genetic risk differentiation event occurred . The ‘’ symbol represents a logical disjunction that returns true if one or more of the two operands is true . The branch that maximized likelihood was the one most likely to have caused the risk differentiation . However , there may have been multiple genetic risk differentiation events . This maximum likelihood method can be generalized to detect an arbitrary number of branches that underwent genetic risk differentiation . Find the indices z1 , z2 , … , zy for branches that maximize the following likelihood function: Due to the constraints this equation imposed , a very large number of random draws was required to produce an accurate estimate . All indicator functions in the numerator must return a non-zero value for the count to be incremented by one; this was computationally infeasible . In order to make the computation tractable , we made a simplifying assumption that only a single ancestral branch which has undergone de novo genetic risk differentiation ( as opposed to an arbitrary combination of branches that have undergone de novo genetic risk differentiation ) can pass a significantly modified genetic risk for a disease to a descendant branch . This led us to the method used for this study . The following calculation was used to find all branches with sufficient evidence of having undergone independent genetic risk differentiation . Find the indices z1 , z2 , … , zy that maximize the following likelihood function:
|
The environment humans inhabit has changed many times in the last 100 , 000 years . Migration and dynamic local environments can lead to genetic adaptations favoring beneficial traits . Many genes responsible for these adaptations can alter disease susceptibility . Genes can also affect disease susceptibility by varying randomly across different populations . We have studied genetic variants that are known to modify disease susceptibility in the context of worldwide migration . We found that variants associated with 11 diseases have been affected to an extent that is not explained by random variation . We also found that the genetic risk of type 2 diabetes has steadily decreased along the worldwide human migration trajectory from Africa to America .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"genome-wide",
"association",
"studies",
"mutation",
"genetics",
"population",
"genetics",
"population",
"biology",
"biology",
"human",
"genetics",
"genetics",
"of",
"disease"
] |
2013
|
Analysis of the Genetic Basis of Disease in the Context of Worldwide Human Relationships and Migration
|
Advances reported over the last few years and the increasing availability of protein crystal structure data have greatly improved structure-based druggability approaches . However , in practice , nearly all druggability estimation methods are applied to protein crystal structures as rigid proteins , with protein flexibility often not directly addressed . The inclusion of protein flexibility is important in correctly identifying the druggability of pockets that would be missed by methods based solely on the rigid crystal structure . These include cryptic pockets and flexible pockets often found at protein-protein interaction interfaces . Here , we apply an approach that uses protein modeling in concert with druggability estimation to account for light protein backbone movement and protein side-chain flexibility in protein binding sites . We assess the advantages and limitations of this approach on widely-used protein druggability sets . Applying the approach to all mammalian protein crystal structures in the PDB results in identification of 69 proteins with potential druggable cryptic pockets .
The majority of small molecule drug discovery efforts towards new , unprecedented biological targets do not progress past high-throughput screening or hit-to-lead optimization due to lack of pursuable chemical matter [1] , [2] . To counter this , drug discovery groups increasingly use druggability analysis methods to estimate the amenability of new targets to small molecule drug discovery efforts . In prioritizing new targets , druggability analysis results are then considered along with the strength of evidence that affecting the target will lead to human therapeutic benefit [3] . The results also inform the use of structure-based drug design resources and alternative approaches , such as those involving pro-drugs and covalent interactions , for targets that are expected to be very difficult . In a drug discovery setting , small molecule druggability is commonly defined as whether a small molecule can bind a desired biological site with good , nanomolar range potency , and , at the same time , also have good , drug-like properties conducive to oral bioavailability and clinical progression [3]–[6] . Thus , the concept refers to chemical tractability of the target . The term , bindability , is also used [7] , although the term may not capture the desire for the optimized compound to have drug-like properties . We emphasize that a binding site is not necessarily druggable simply because a ligand binds; the ligand additionally needs to have reasonable drug-like properties and potency . The concepts of ‘druglikeness’ and ‘druggability’ as we use it here cover the most common strategies for small molecule drug discovery , and alternative strategies ( e . g . , involving covalent adducts , metal chelation , prodrugs , and non-oral delivery ) can also be useful in prosecuting targets that are found to be likely ‘undruggable’ when only weak , non-covalent interactions are considered [4] . Druggability estimation has historically been based on precedence , that is , whether there are known drugs targeting the protein or one of its homologs [2] , [3] . However , this type of data is scarce or non-existent for many newer protein targets . Advances reported over the last few years allow us to leverage the increasing availability of protein crystal structure data using structure-based druggability approaches . There are at least ten published methods for estimating druggability this way [3] , [6] , and the body of work is extremely consistent in finding that druggable sites are those that have particular ranges of size , curvature , and hydrophobic character [3]–[6] . These descriptors largely characterize aspects of receptor desolvation [4] , and atomistic simulations using molecular dynamics have now shown desolvation to be relevant and sufficient for predicting druggability [8] , [9] . Many current structure-based methods for druggability estimation are remarkably accurate if the potential small molecule binding site is largely rigid [3] , [6] . Binding sites are not always rigid though , and druggability methods are less accurate if the protein readily changes conformation upon small molecule binding . This is particularly true of protein-protein interface and allosteric sites , where druggable pockets often become exposed only with protein movement [10]–[12] . These ‘cryptic pockets’ are large and shallow when bound to their biological peptide or protein partners , but tend to have high hydrophobic character , and , crucially , have flexibility such that larger , deeper pockets more typical of druggable binding sites are energetically accessible [10] , [11] . To begin to address these sites , we apply an approach to modeling conservative movements in pockets using comparative protein modeling approaches coupled closely with structure-based druggability analysis . The approach models relatively light protein motions , involving side-chain flexibility and local protein backbone movements , and maintains reasonable prediction accuracy in retrospective validation studies . It allows us to take pockets that a rigid-protein druggability analysis would deem to have some drug-like properties , but not have sufficient drug-like size , and assess whether local protein motion can result in the pocket having all the drug-like properties , including drug-like size . The approach is computationally efficient enough to enable mining of the structural proteome while taking into account light protein flexibility . Applying the method to roughly 18 , 000 mammalian protein crystal structures in the PDB results in prediction of one percent of proteins as containing likely druggable cryptic pockets .
We applied the method to two widely-used druggability validation sets to check its performance and measure any increase in false positive rate due to allowance of protein flexibility . The first validation set is a published set that covers a variety of targets , and consists of 27 targets: 17 druggable targets and 10 difficult targets [4] . A histogram of the druggability scores , Dscore+ , based on the original crystal structures , with no flexibility modeling , is shown in Figure 2a . The plot supports a Dscore+ >1 . 3 threshold for druggable versus difficult targets , with higher scores roughly indicating more druggable sites . Modeling protein flexibility for target sites that meet a threshold of Dscore+>1 . 3 results in an increase in Dscore+ , but the increase is relatively systematic ( mean = 0 . 4 , σ = 0 . 3 ) and appears to be consistent enough that a useful differentiation between difficult and druggable targets is retained . We also investigated the effect of flexibility modeling on targets with scores of Dscore+≤1 . 3 . For these additional targets , we again find an increase in scores by an average of 0 . 4 ( σ = 0 . 3 ) . Thus , difficult and druggable targets in the validation set can still be distinguished after flexibility modeling , although the distinction is less crisp than it was when scoring rigid structures . Comparing the score distributions for druggable and difficult targets using the two-sample Kolmogorov-Smirnov ( K-S ) statistic finds that the scores are significantly different from each other , both with and without flexibility modeling ( p-values of 8×10−4 and 1×10−6 , respectively ) . When we subtract 0 . 4 from each score that includes protein flexibility , the score distributions remain similar within each set . For druggable targets , the means of the with- and without-flexibility scores are 1 . 6 and 1 . 6 respectively , with variances of 0 . 05 and 0 . 07 . For difficult targets , the means of the with- and without-flexibility scores are 1 . 2 and 1 . 1 respectively , with variances of 0 . 04 and 0 . 03 . Taken together , the results suggest that a Dscore+ threshold of 1 . 7 ( i . e . , 1 . 3+0 . 4 ) should be applied to sites resulting from flexibility modeling , and this threshold is depicted in Figure 2b by a red line . We will show that this threshold value is strongly supported by analysis of a larger number of proteins ( 109 proteins ) from the mammalian proteome druggability results . While the threshold is determined empirically and the increase is not ideal , we can rationalize the increase as due to modeling of protein flexibility with an impetus towards making the pocket more hydrophobic . Turning to pocket volumes , the method should not lead to all pockets increasing significantly in volume , consistent with the belief that some sites are inherently flexible while others are less so . In this first validation set , which is composed largely of enzyme active sites , the average volume before and after flexibility modeling are both about the same ( 420 Å3 and 360 Å3 , respectively , with standard deviations of 190 Å3 and 130 Å3 ) , and are both within the drug-like range , as discussed later . In the second , validation set of protein-protein interfaces , we will see that the binding site volumes change more significantly . Resulting volumes tend towards a volume of around 300–400 Å3 , if the flexibility of the protein allows , and this appears to be related to the size of the second ligand ( tetra-substituted naphthalene ) used in the induced-fit docking step of the flexibility modeling . In the mammalian proteome analysis , we find that only one percent of proteins analyzed have cryptic pockets that change substantially from a volume substantially below the drug-like range ( ≤100 Å3 ) to a drug-like volume ( 160–800 Å3 ) . In developing our approach , the drug-like volume range was initially set roughly to 150–600 Å3 based on our judgment , and later refined to 160–800 Å3 based on quantitative analysis of the mammalian proteome results . The second validation set addresses protein-protein interaction ( PPI ) targets , and includes six targets from the 2P2I database and Wells et al . ( 2007 ) : Bcl-xL , HDM2 , IL-2R , HPV E2 , ZipA , TNFα [10] , [12] . Bcl-xL and HDM2 are classified as druggable since oral small molecule inhibitors have advanced to clinical trials . We argue that the remaining potentially high-value targets are difficult . While pioneering small-molecule inhibitors have been reported , we note that substantial efforts made over the last 15 years to identify inhibitors of TNFα , IL-2R , HPV E2 , and ZipA have not resulted in reported small molecule clinical compounds [10] . Given just the protein crystal structures , with no information on location of binding sites , the method successfully opens the relevant binding pockets for Bcl-xL , HDM2 , and TNFα and scores them as druggable based on Dscore+ and volume considerations , as shown in Table 1 . Calculated values of Dscore+ and volume that fall within the defined drug-like range are highlighted in bold . In the cases of Bcl-xL and TNFα , light flexibility results in small molecule binding pockets with roughly 50% and 100% larger volumes , respectively . Bcl-xL would have been classified as difficult based on the 2bzw PDB structure without additional flexibility modeling because the pocket size ( 112 Å3 ) is too small by any reasonable criteria for drug-like volume size . Flexibility modeling results in small changes in the binding site that , together , increases the volume of the pocket to a reasonable volume ( 172 Å3 ) . Bcl-xL is perhaps the one clear example where a protein pocket opens substantially and the druggability is known ( i . e . , orally administered small molecule inhibitors have progressed to clinic ) . We also analyzed all targets listed in 2P2I where crystal structures are provided , but some targets have either unclear experimental druggability because efforts on the targets are more recent , or known inhibitors involve metal chelation . The results for these additional targets are included in Table S1 . Comparing Dscore+ and pocket volume calculation results with and without protein flexibility modeling finds that Bcl-xL ( PDB IDs: 2bzw , 2yxj , 3qkd , 4ehr ) and a minority of HDM2 structures ( PDB IDs: 1rv1 , 3lbk ) would have been missed without the additional flexibility modeling to open up pockets to a drug-like volume . Interestingly , one IL-2Rα structure ( PDB ID: 1pw6 ) has a Dscore+ that places the target in the low end of the druggable score range , but the pocket volume does not satisfy the drug-like criteria , and this remains the case after protein flexibility modeling . Protein flexibility modeling does not always open pockets significantly . With TNFα , the known pocket at the trimer interface was identified as the top pocket in the apo-structure , and flexibility modeling resulted in a binding site with good druggability score and good drug-like volume . This result is consistent with the scores obtained using the co-complex structure with SPD-304 [28] . However , the best reported inhibitor has only single digit micromolar range potency against TNFα [28] , and although there is not really sufficient data currently to determine this , it is possible that the calculations overestimate the druggability of the pocket . With Bcl-xL , comparison of a BAD peptide-bound structure ( PDB ID: 2bzw ) with a small molecule-bound structure ( PDB ID: 2yxj ) shows that two residues , Phe105 and Leu130 , adopt alternate conformations , and the helix around Leu108 becomes disordered to create the ligand binding pocket [29] , as shown in Figure 3 . The target serves as a good illustrative example of our complete approach . First , a potentially druggable site is identified regardless of whether it is too small to hold a drug-like molecule . This is followed by induced-fit docking of naphthalene to the identified site , which moves residues , including Phe105 , as shown in Figure 3b . A second induced-fit docking of the larger ( molecular weight of 363 Da ) tetra-substituted naphthalene ( TSN ) results in a total of four models , where we see additional movements in addition to Phe105 . A representative model is shown in green in Figure 3c , and shows a Leu130 rotamer change and backbone movements around Leu108 resulting in loss of the alpha-helical secondary structure . However , the modeled structures still differ from the ligand-bound crystal structure , as shown in Figure 3d , and the model , in this case , is effectively a hybrid of the peptide-bound structure and the known ligand-bound structure . Thus , the modeling approach , in the case of Bcl-xL , successfully allows backbone motion and reproduces some of the known side-chain and backbone movements in the resultant models . We note that the TSN molecule makes similar interactions compared to the ligand , ABT-737 , in the ligand-bound crystal structure . Despite not reproducing all of the atomic details of the ABT-737 crystal structure , the flexibility modeling captures many key features and the inherent flexibility of the pocket that results in an increased binding site volume and increased druggability score . To investigate the behavior of the flexibility modeling approach on targets where protein flexibility is known based on crystal structures , we applied the method to a set of protein crystal structures with binding site flexibility from Huang and Jacobson [17] , where we've selected targets that show RMSDave >1 . 5 Å for binding site residues in different crystal structures of the same protein . We compare these results with their published druggability results , which do not account for flexibility , in Table 2 . While the two methods perform similarly on non-PPI targets ( first six targets in Table 2 ) , the flexible druggability method performs better on PPI targets ( last five targets in Table 2 ) . In particular , their docking-based druggability model predicts IL-2 and HPV E2 to be druggable ( docking hit rate>0 . 36 ) based on some structures , but predicts the same targets to be very difficult based on other structures . The flexibility modeling approach results in classification of both targets as very difficult , consistent with what is known , as previously discussed . Examining the variation in scores between different crystal structures of the same target finds that while both the static protein and flexible protein methods yield similar score variation for non-PPI targets , they have substantially different variation with PPI targets . In particular , the docking hit-rate method shows large variation in score among structures of IL-2 ( 107% ) , MDM2 ( 69% ) , and HPV E2 ( 323% ) compared with a median variation of 21% in all 11 targets . The flexibility modeling method , on the other hand , results in score variation on PPI targets that is consistent with that found with non-PPI targets . Overall , the docking method has a median score variation of 21% with a standard deviation of 94% in the dataset , while the flexibility modeling approach has a median score variation of 13% with a standard deviation of 10% . Yet , when the PPI targets are removed , the two methods have comparable score variation . Taken together , the flexibility modeling method appear to provide more reliable , consistent predictions at PPI interfaces , and this makes sense because PPI interfaces are much more likely to involve substantial protein flexibility [11] . Accounting for protein flexibility in a conservative manner , as we have done , leads to more consistent druggability predictions . We next applied the flexibility modeling approach to all publicly-available crystal structures containing mammalian proteins to estimate the number of druggable targets and identify potential druggable cryptic pockets . Analyzing the over 18 , 000 structures in the Protein Data Bank ( PDB ) [30] as of June 30 , 2012 , required approximately 35 , 000 CPU-days of calculation ( in aggregate ) on our internal Linux clusters . The analysis covered not only the crystal structures as deposited in the PDB , but also all individual monomers in the case of multimer assemblies . Five percent of PDB files generated an error , due mostly to structures containing only Cα atoms ( i . e . , no protein side-chains ) or involving large biomolecular assemblies , since we stopped calculations on a particular PDB entry if it ran for more than fourteen days . The results are summarized in Table 3 , where we also mapped PDB chains to SWISS-PROT ID's to determine the number of proteins represented . Of the 17 , 834 PDB entries analyzed , 42% had at least one site that met the Dscore+ >1 . 3 threshold for further protein flexibility modeling . Twenty percent of mammalian proteins in the PDB have a potentially druggable pocket . Of the 5 , 739 PDB entries ( 1 , 134 proteins ) that have a predicted druggable pocket , about two–thirds would be predicted druggable based on the original , static crystal structure . To identify druggable pockets with the greatest likelihood of biological relevance , we winnowed the list to protein sites in 2095 PDB structures where a small molecule could potentially disrupt a known intermolecular interaction . The interacting partner should be transiently-bound ( as opposed to obligately-bound ) and can be a protein , natural co-factor , natural ligand , or synthetic ligand . These sites are either at protein-protein interfaces or contain a small molecule of molecular weight less than 1000 Da . Including these criteria gives us higher-confidence druggability predictions and may remove many false-positives , but could result in removing sites that are functionally relevant but perhaps not well-characterized . For sites at protein-protein binding interfaces , we assessed whether the relevant protein-protein interaction is an obligate or transient interaction based on a published database , Interevol [31] . Sites involving obligate dimer interfaces were removed , but sites without any prediction or assessment were retained; there was no annotation for over half of the protein interfaces we considered . Overall , we identified predicted druggable pockets in 2 , 095 PDB structures representing 730 unique proteins . In Figure 4 , we depict the breakdown of predicted druggable pockets at these intermolecular interfaces with pockets where a bound ligand would disrupt a protein-protein interaction ( including protein-peptide interactions ) shown in blue , and pockets where a bound ligand would disrupt a protein-ligand interaction shown in red . The purple overlap region indicates protein pockets that are at both a protein-ligand and protein-protein interface . Some of these pockets are adjacent to small peptides , which can be classified as both a ligand and protein by our definition; ligands are defined as any molecule with molecular weight of 1000 kDa or less , while proteins are defined as non-HETATM molecules . The number of unique proteins in the purple region is much higher because a given protein may not only have a co-crystal structure solved bound to a protein partner , but also bound to a small molecule ligand ( or vice-versa ) . To identify cryptic pockets , we looked at potential druggable pockets that were small ( volume ≤100 Å3 ) in the static structure , as long as the initial cavity was not fully buried ( enclosure ≤96% ) . Less than 20% of these , representing 105 structures , met the flexible druggability criteria , opening up to at least 160 Å3 with flexibility modeling . These targets representing 69 unique proteins are provided in Table S2 . To compare the mammalian PDB results to a positive control set , we mapped known oral drugs from MDDR ( 2008 release ) to ligands in known crystal structures . Of the 421 oral drugs administered in tablet form , 109 could be mapped to PDB co-crystal structures that had crystallographic resolution ≤2 . 5A . The 102 pockets with ligand overlap to known co-crystalized ligands ( ligand overlap >0 ) are plotted by volume in Figure 5A , where volume is computed using SiteMap . Targets at the low end of the volume range , with volumes of 160 Å3 or less , include four complexes with large FK-506 natural product analogs that are not captured by the drug-like binding site definition in use . Targets with volumes of 800 Å3 or greater are largely natural product complexes as well ( macrocyclic antibiotics , reservatrol , and others ) . The results therefore suggest a drug-like volume range of between 160 and 800 Å3 is appropriate for the approach we use . We note that volume calculations are highly sensitive to the algorithm used , and so these volume ranges should be established independently for different implementations of our approach . The range of druggability scores for the known oral tablet drug set versus all pockets is shown in Figure 5B , where the top histogram represents the oral tablet drug set . The distributions are overlapping , and while the means of 1 . 7 and 1 . 4 are significantly different ( p = 6×10−15 based on the two-sample K-S test ) , the 95% confidence intervals overlap . While the large-scale data shows there is room for improvement in the separation of druggable and difficult targets , the 1 . 3 Dscore+ cut-off we use is nevertheless useful for identifying druggable pockets in rigid proteins , and removing 60% of pockets from further analysis with more resource-intensive flexibility modeling . Applying flexibility modeling to the MDDR targets also results in a shift in Dscore+ range , shown in Figure 5C , similar to what is seen with the smaller general validation set . The shift seen here further supports use of a Dscore+>1 . 7 cut-off in conjunction with protein flexibility modeling . To assess the effect of our flexibility modeling approach on pocket volumes , we looked at all pockets at intermolecular interfaces before and after flexibility modeling and show the results in Figure 6 . A diagonal white line indicates no change in volume . While the modeling method likely overpredicts volume increases in pockets , the majority of pockets that increase in volume increase by less than 50 Å3 . The vertical and horizontal white lines in Figure 6 indicate the 160 Å3 volume cut-off , and it is clear that most pockets under the cut-off remain under the cut-off . As expected , pockets with volumes closer to the cut-off , with volumes of 100–160 Å3 , are the most likely to increase to over 160 Å3 with protein flexibility modeling . In Figure 6 , pockets with original volumes less than about 200 Å3 tend to get larger , while pockets with original volumes greater than about 400 Å3 tend to get smaller . The likely rationale is that the tetra-substituted naphthalene ligand used in the flexibility modeling approach induces smaller pockets to grow to accommodate the ligand , while it induces larger pockets to shrink to better enshroud the ligand . These tendencies are , however , dependent on the inherent flexibility of the protein structure . While the analysis provides a good set of putative druggable proteins in the mammalian structural proteome , we are not blind to deficiencies in this analysis . The prediction error rate in the large mammalian structural proteome analysis is hard to know , and we discuss the limitations in the next section . The automated approach to protein flexibility we report here is useful for identifying druggable targets in the structural proteome . We are aware of three areas for further improvement . The first is related to pocket selection . Pocket selection is based on geometric considerations , and the pockets are subsequently scored for druggability using Dscore+ as well as , potentially , protein flexibility modeling . Ideally , the pocket selection and scoring would be done simultaneously to yield pockets that maximized the druggability score [32] . This issue , for instance , has an effect on scoring of phosphodiesterase active sites such as those in PDE-4D and PDE-5 , where protein residues at one end of the catalytic site are very polar , and known oral inhibitors do not interact in this region [32] . Figure 7a shows the binding site including the polar region that results in a low druggability score , Dscore+ = 1 . 4 , which is not representative of the druggability of the binding site . Removing the polar region shown in Figure 7b results in a more representative druggability score , Dscore+ = 1 . 6 . We were not successful in adjusting our protocol to account for this , and thus we may miss druggable sites that are similarly amphipathic in nature . In addition , despite our efforts at tuning the pocket identification algorithm , SiteMap does , in about 2% of cases , return candidate pockets with volumes over 800 Å3 , the drug-like size limit that we use . Currently we simply remove these pockets , which may cause us to miss druggable sites . Future work to resolve these issues include modifying SiteMap to identify only pockets of the desired volume ( 160–800 Å3 ) , allow for pockets that overlap with each other , and account for properties such as hydrophobicity in the pocket definition process . A second area relates to the false positive rate , that is , the fraction of pockets identified as druggable that are not truly druggable . Even though we restrict protein flexibility to side-chain motion and localized backbone movement , the protein flexibility modeled and our selection of proble molecules are biased towards increasing the hydrophobicity of the pocket under analysis , and relaxation of the resultant structures may improve results . In addition , the degree of protein flexibility modeled is probably more than that present in reality . In this work , we empirically compensated for these issues by measuring the impact of flexibility modeling in Figures 2 and 4 , which led to the use of a Dscore+≥1 . 7 criteria . While our flexibility modeling approach demonstrates statistically significant discrimination of difficult and druggable targets , we also plan to explore approaches such as protein relaxation [33] , to remove the need for an empirical correction . The flexibility modeling approach is more likely to exaggerate the flexibility of smaller proteins due to fewer stabilizing interactions within the protein . For the cryptic pocket analysis , we restricted our results to those proteins that are greater than 100 amino acids in length ( which translates to about 10 kD ) . Lastly , we need to consider that the protein structures observed in crystal structures , in a minority of cases , may not be the biologically relevant constructs or complexes . Crystal structures may be synthetic constructs or portions of proteins , which , in the context of the full-length protein , have predicted binding sites occluded . Similarly , biological obligate dimers not seen in the crystal structures can occlude the binding site . Co-factors can also affect the druggability of binding sites; here , we only account for selected , particularly tight-binding co-factors such as metals and hemes . We analyze both biological assemblies defined in the PDB as well as the individual monomer components to account for binding to intact complexes as well as unbound partners . Other partially dissociated complexes may exist however . In addition , we are looking at binding , and not functional effects of binding; weak binding at an allosteric site is sometimes sufficient to generate the desired inhibition or activation of biological activity [32] . We leverage advances in druggability assessment and modeling of protein flexibility to create an approach that allows light flexibility in the protein backbone and side-chains . The method improves the accuracy of druggability assessments when tested on two validation sets representing general pharmaceutical targets and protein-protein interactions of pharmaceutical interest . Combining this with the wealth of crystal structures available in the PDB allows us to find new protein binding sites that are potentially druggable by small molecules . Searching for such sites is thought to be like finding needles in a large haystack , and a systematic , automated approach is thus useful . Accurate modeling of protein flexibility continues to be difficult and the subject of substantial research . Even so , our approach is useful in exploring induced druggable pockets and provides a substantial number of hypotheses . For applications focused on analysis of protein pockets , the approach we take is computationally efficient and may be complementary to comprehensive analyses of static crystal structures [34] . Finally , we have long been intrigued by the possibility of combining the druggability data with biological target disease-relevance data . This has recently been done on a small-scale with cancer targets [35] , although protein flexibility was not accounted for in the druggability assessment . Inclusion of protein flexibility in such assessments can help to provide more accurate target assessment .
Protein structures were downloaded from the biounits repository at the RCSB based on criteria that the structure ( 1 ) contains protein , ( 2 ) is categorized as deriving from the class Mammalia , and ( 3 ) has an x-ray crystal structure resolution ≤2 . 5A . Ligands , defined as having molecular weight ≤1000 Da , are removed with the exception of heme groups , zinc , and magnesium ( PDB het groups HEM , MHM , HEV , VER , SRM , HEO , HEB , HEC , HDM , HDD , DDH , ZN , MG ) . Protein structures were prepared using Schrödinger Protein Preparation Wizard ( version 2012 , Schrödinger LLC , New York , NY ) , on the command line with the following options: –watdist 0 , –fillsidechains , –rehtreat , –mse , –noepik , –noimpref . These options assign bond orders , add hydrogens , remove all waters , create zero-order bonds to metals , create disulfide bonds for close cysteines , mutate selenomethionines to methionine , fill in any missing side-chains with Prime ( v3 . 1 , Schrödinger LLC , New York , NY ) , and optimize hydrogen placement and polar residue flips using PropKa . Validation test runs using restrained minimization to a heavy atom RMSD of 0 . 3 Å , a procedure known as “Impref” , did not change which sites were found and did not significantly change druggability scores on the validation dataset proteins , so we chose to increase workflow speed by avoiding this step in the protein preparation . Next , initial potential druggable surface patches were identified using Schrödinger SiteMap ( v2 . 6 , Schrödinger LLC , New York , NY ) , the results of which are used to compute Dscore+ . We run Sitemap with a fine grid ( 0 . 35 Å spacing ) and “loose” definition of hydrophobicity . In this study , all calculations were performed from the command line with options that return the 5 largest SiteMap sites , in order of the number of site points they contain . Our modified settings allow more shallow binding sites to be found and include binding site regions with slightly weaker vdW interaction energy . We used the following non-default Sitemap parameters: maxdist = 10 , enclosure = 0 . 4 , maxvdw = 1 . 0 , dthresh = 5 . 0 , mingroup = 7 , nthresh = 7 , grid = 0 . 35 , modphobic = 0 . The smaller value of maxvdw ( default is 1 . 1 kcal/mol ) and the less restrictive definition for modphobic of zero together allow gridpoints with slightly weaker vdW interaction energy to be included as sitepoints . The smaller enclosure score ( default is 0 . 5 ) and larger maxdist value ( default 8 . 0 Å ) allow more shallow binding sites to be found . The enclosure score is computed by drawing radial rays from each sitepoint , and the score is the fraction of rays that strike the receptor surface within a distance of 10 Å ( maxdist ) , averaged over the sitepoints . Decreasing dthresh from the default ( 6 . 5 Å ) and increasing nthresh from the default ( 3 ) causes SiteMap to return smaller , more compact sites than it otherwise would when using a fine grid . When considering a gridpoint for inclusion in a site , there must be at least nthresh other points within 1 . 76 Å ( square root of d2thresh ) for it to be considered . When considering whether two sites should be joined , the closest points in the two sites must be closer than dthresh . The parameter , “mingroup” , is the only parameter here that limits the number of sites found; this is the minimum number of points in a site-point group required to constitute a site ( default = 7 ) . We found that including sites with less than seven points in combination with a fine grid of 0 . 35A resulted in merging of many very small pockets to form long , stringy sites that were not realistic as small molecule binding sites . Overall , these modified SiteMap settings allow us to find shallow pockets with less hydrophobic character than is possible to find with default settings . From the SiteMap results , sites identified with a druggability score , Dscore+ , of greater than 1 . 3 are taken as candidate sites regardless of volume , where Dscore+ is defined as Dscore + 0 . 3*hydrophobic , as previously described [14] , [15] , and druggability scores are rounded to the first decimal place . The choice for the 1 . 3 value is discussed in the Results and Discussion section . Dscore is computed from physiochemical descriptors generated by SiteMap , and is a weighted sum with contributions from three components , ( 1 ) degree of site enclosure , ( 2 ) pocket size defined by the number of site points included in the site; site points are x , y , z coordinates that are outside the protein , are reasonably enclosed , and have a vdW interaction potential over a defined threshold are clustered into sites , and ( 3 ) a negative contribution from the hydrophilic score , which limits the impact of hydrophilicity in charged and highly polar sites [13] . To identify binding sites with potential flexibility , we used an iterative protein-modeling and docking approach [16] , available in the Schrödinger Suite ( 2012 release , Schrödinger LLC , New York , NY ) as the induced fit docking ( IFD ) workflow , and applied this using the ligands in Figure 8 to each candidate site . In this study , all calculations were performed from the command line with the default IFD parameters , except the variable , OUTER_BOX , which is always set to 25 Å , since we were docking the same small ligands . We defined the variable , BINDING_SITE , by a single sitepoint which is placed at the centroid of all SiteMap sitepoints from the candidate site . First , we used IFD to dock a naphthalene molecule , 1 , to the top 5 sites found by SiteMap and kept the best two naphthalene poses for each site . If poses were returned for naphthalene , we then used IFD again to dock a tetra-substituted naphthalene molecule , 2 , to the same pocket , now opened up by naphthalene . SiteMap was then applied to score the sites in the four top-scoring structural model results ( typically , at least ten models were generated per site ) . Increasing the number of models can result in better predictions of binding site conformations , but we chose to produce a smaller but reasonable set of four models to reduce the compute time required to process all mammalian crystal structures . To analyze the druggability and protein-protein interaction validation data , we automatically compared each SiteMap site to the corresponding ligand-bound structure using the Phase ( version 3 . 4 , Schrödinger LLC , New York , NY ) command-line utility phase_volcalc to compute the overlap ( measured in Å3 ) between the SiteMap sitepoints and the bound crystal ligand . After the IFD steps , we used the same utility to compute the overlap between the tetra-substituted naphthalene and the bound crystal ligand . This value is positive when there is direct overlap between the two sets of atoms . For the validation studies only , we identified the relevant protein biological assembly based on the known literature , and only retained those assemblies or protein monomers that are biologically meaningful . The calculations were otherwise performed automatically . For calculations run on all mammalian PDB structures , we used a purely automated procedure applying the method to the first “biological unit” as defined in the PDB . Calculations were performed on commodity cluster hardware running RedHat Enterprise Linux . Failed calculations were re-run up to five times , including at both Amgen and Schrödinger facilities , to ensure that failures were not the result of compute infrastructure issues . To identify protein-protein interaction interfaces , we checked whether any of the TSN molecules modeled into a predicted druggable site also overlapped with another protein chain in the crystal structure . Overlap was defined as at least one atom of the TSN molecule being within 2 Å of the additional protein chain , where hydrogens were included . To identify protein-ligand interfaces , we used the previously-described volume overlap calculation . Finally , to analyze the results of the mammalian proteins in the PDB for obligate dimers , we used the Interevol database , publicly available at http://biodev . cea . fr/interevol/interevol . aspx [31] . We downloaded the database ( July 2012 release ) and joined the data with our PDB results by matching both the four-letter PDB code and any chain identifier . PDB IDs were translated to gene ID's using the SWPROT database [36] , and all gene annotations were performed using bioDBnet [37] Structure figures were produced using PyMOL version 1 . 4 . 1 [38] . To map MDDR drugs to PDB co-crystal structures , we first identified all oral drugs in MDDR that were annotated as ‘marketed’ and delivered orally as tablets or pills . PipelinePilot ( ver . 8 . 5 . , Accelrys Software , San Diego , CA ) was used to identify identical compounds based on structural identity when compared with the SMILES strings included in the HET code file downloaded from RCSB LigandDepot [30] . PDB codes were then identified that corresponded to matched HET codes . Matlab version 7 . 9 ( R2009b , The Mathworks Inc . , Natick , MA ) was used to generate Figures 2 , 5 , and 6 , and also to calculate statistical means , variances , and two-sample Kolmogorov-Smirnov test results for the general validation set . Calculations were performed on Intel Xeon CPU ( 2 . 7GHz ) multi-core processors running RedHat Enterprise version 6 . CPU timings quoted in the paper are per single core .
We thank Nigel Walker , Philip Tagari , Yax Sun , Paul Kassner , Mike Ollman , and Astrid Ruefli-Brasse at Amgen , and Woody Sherman and Alessandro Monge at Schrödinger for their support and helpful discussions .
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Advances reported over the last few years and the increasing availability of protein crystal structure data have greatly improved structure-based druggability approaches . These algorithms predict our ability to discover small molecule drugs for protein targets and can help in identifying promising new biological targets for small molecule drug discovery . However , in practice , nearly all druggability estimation methods are applied to protein crystal structures as rigid proteins , with protein flexibility often not directly addressed . The increasing interest in finding small molecule drugs to protein-protein interfaces makes this issue particularly acute since these interfaces tend to have substantial flexibility compared to traditional enzyme targets . Here , we apply an approach that accounts for light protein backbone movement and protein side-chain flexibility in protein binding sites . We present the results of applying this method to all publicly available mammalian protein crystal structures .
|
[
"Abstract",
"Introduction",
"Results",
"and",
"Discussion",
"Materials",
"and",
"Methods",
"Acknowledgments"
] |
[
"biomacromolecule-ligand",
"interactions",
"biochemistry",
"medicinal",
"chemistry",
"proteins",
"protein",
"structure",
"biology",
"and",
"life",
"sciences",
"chemistry",
"physical",
"sciences",
"computational",
"biology",
"biophysics",
"molecular",
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"analysis",
"biophysical",
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] |
2014
|
Structure-Based Druggability Assessment of the Mammalian Structural Proteome with Inclusion of Light Protein Flexibility
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Many viruses alter expression of proteins on the surface of infected cells including molecules important for immune recognition , such as the major histocompatibility complex ( MHC ) class I and II molecules . Virus-induced downregulation of surface proteins has been observed to occur by a variety of mechanisms including impaired transcription , blocks to synthesis , and increased turnover . Viral infection or transient expression of the Ebola virus ( EBOV ) glycoprotein ( GP ) was previously shown to result in loss of staining of various host cell surface proteins including MHC1 and β1 integrin; however , the mechanism responsible for this effect has not been delineated . In the present study we demonstrate that EBOV GP does not decrease surface levels of β1 integrin or MHC1 , but rather impedes recognition by steric occlusion of these proteins on the cell surface . Furthermore , steric occlusion also occurs for epitopes on the EBOV glycoprotein itself . The occluded epitopes in host proteins and EBOV GP can be revealed by removal of the surface subunit of GP or by removal of surface N- and O- linked glycans , resulting in increased surface staining by flow cytometry . Importantly , expression of EBOV GP impairs CD8 T-cell recognition of MHC1 on antigen presenting cells . Glycan-mediated steric shielding of host cell surface proteins by EBOV GP represents a novel mechanism for a virus to affect host cell function , thereby escaping immune detection .
EBOV is an enveloped , negative-stranded RNA virus , a member of the family Filoviridae , and the causative agent of Ebola viral hemorrhagic fever . To date , five subtypes of EBOV have been identified: Zaire , Sudan , Côte d'Ivoire , Reston and Bundibugyo . EBOV Zaire is the most pathogenic subtype in humans , with mortality rates reaching 90% [1] . The basis for the high pathogenicity of EBOV is unclear , however immune dysregulation has been hypothesized to play a role [2] . Similarly to many other viral systems , EBOV infection appears to downmodulate the expression of host surface proteins involved in cellular recognition , most notably major histocompatibility complex ( MHC ) molecules and integrins [3] . EBOV encodes two forms of its glycoprotein . One is a dimeric , secreted form ( sGP ) , which is transcribed directly from the viral RNA [4] , [5] and whose function remains unclear . A second glycoprotein species results from transcriptional editing of the glycoprotein ORF and encodes a trimeric , membrane-bound form ( GP ) . This form is expressed at the cell surface and is incorporated into the virion [4] and drives viral attachment and membrane fusion . GP is initially translated as a precursor ( GP0 ) , which is then cleaved by furin in the Golgi into two subunits , a surface subunit , GP1 and a membrane-spanning subunit , GP2 [6] . These subunits remain covalently connected through a single intermolecular cysteine bond [7] . Expression of the main viral glycoprotein , GP , has been shown to cause effects in cell culture on host surface proteins similar to those observed during viral infection , and so is proposed to be an important determinant of viral pathogenesis [8] , [9] , [10] , [11] . Because sGP is the predominant form transcribed , it has been postulated that the balance between sGP and GP serves to regulate the cellular effects of GP [11] . Expression of high levels of EBOV GP in cultured cells disrupts cell adhesion resulting in loss of cell-cell contacts as well as cell rounding and loss of attachment to the culture substrate [8] , [10] , [12] . This can be observed in a variety of cell lines and primary cell types [12] . Interestingly , while transient GP expression does not cause death in human embryonic kidney 293T cells , primary human cardiac microvascular endothelial cells have been reported to undergo anoikis , or detachment-mediated apoptosis , upon transduction of GP [12] , [13] . By flow cytometry , cells expressing GP display dramatically lowered levels of various surface proteins , including several members of the integrin family and MHC class I ( MHC1 ) ; however , the exact complement of surface proteins affected by GP appears to differ by cell type [10] , [12] , [14] . Importantly , EBOV infection of 293T cells was observed to cause similar reduction of β1 integrin and MHC1 staining by flow cytometry , confirming that observations from transient GP expression are not simply artifacts of overexpression [3] . The effects of EBOV GP are caused by a highly glycosylated region in GP1 , the mucin domain [8] , [12] , [14] . This domain encompasses approximately 150 amino acids , contains numerous N- and O- linked glycosylation sites , and is a distinctive feature of filoviral GPs . The mucin domain is not only necessary , but also sufficient for the observed EBOV GP-mediated effects upon surface protein expression and cellular adhesion [8] , [15] . Few studies have been undertaken to investigate the mechanism by which EBOV GP disrupts adhesion and causes surface protein downmodulation . Our recent analysis concluded that the cellular endocytic factor dynamin does not play a role in surface protein downmodulation , suggesting the process may not involve cycling of proteins from the cell surface [15] . In contrast , Sullivan and colleagues have reported that this process requires dynamin [14] . Additionally , it has been reported that the extracellular signal-regulated kinases ( ERK 1/2 ) play a role in downmodulation [16] suggesting an active process . In the present study , we provide direct evidence that EBOV GP-mediated loss of surface protein recognition occurs via steric shielding of surface epitopes , not by protein removal from the cell surface . Moreover , we demonstrate that EBOV GP expression blocks MHC1-mediated stimulation of T cells . Based upon these findings , we present a model in which the heavily glycosylated EBOV glycoprotein acts as a “glycan umbrella” to physically occlude access to host proteins , and GP itself , thereby impairing host protein function . EBOV GP-mediated steric occlusion represents a unique viral mechanism to interfere with the function of host proteins .
EBOV GP expression can dramatically reduce the observed levels of numerous host cell surface proteins including factors involved in immune recognition and cellular adhesion [10] , [12] , [14] . This effect can be seen by analysis of MHC1 or β1 integrin by flow cytometry staining in HEK293T cells transiently expressing Zaire EBOV GP ( Figure 1A ) . Overall , a 10- to 50-fold reduction in surface levels of these host markers is observed in cells transfected with an EBOV GP cDNA . Additionally , there appears to be a critical threshold of EBOV GP expression required to induce surface protein downmodulation [15] . In parallel with the decrease in staining for host proteins , EBOV GP expression also appears to be reduced , resulting in a distinctive horseshoe-shaped flow cytometry profile ( Figure 1A and [14] , [15] , [16] ) . Despite this apparent decrease in surface protein levels observed by flow cytometry , there were no consistent , significant changes in total protein levels for the EBOV glycoprotein upon analysis by Western blot in either adherent or non-adherent EBOV GP transfected cells ( data not shown ) . To look directly at host protein expression in cells expressing EBOV GP , nonadherent , GP-transfected 293T cells were collected and analyzed by flow cytometry for expression of β1 integrin ( [15] and Figure 1B , left panel ) . As previously described [15] , these nonadherent cells represent the lower two quadrants of the “horseshoe” and appear to have reduced levels of both β1 integrin and EBOV GP . In contrast to the flow cytometry results , analysis of EBOV GP in these cells by immunofluorescence microscopy after fixation and permeabilization reveals extensive staining at the plasma membrane ( Figure 1B , right panel ) . Similar to these results , previously published microscopic analysis of cells expressing EBOV GP also shows extensive plasma membrane staining with little evidence of significant accumulation of GP in internal vesicles [15] , [17] . To evaluate steady state levels of host proteins and EBOV GP in cells transiently expressing the viral glycoprotein , the transfected cells were fixed , permeabilized and analyzed by flow cytometry . In vector-transfected cells , the permeabilization treatment had little effect upon staining for β1 integrin or MHC1 ( Figure 2A ) . However , in cells transiently expressing EBOV GP , which displayed dramatically reduced levels of β1 integrin and MHC1 by surface staining ( Figure 2B , left column ) , fixation and permeabilization reveals no decrease in either of these host proteins ( Figure 2B , right column ) . Similarly , the apparent loss of EBOV GP staining is reversed by this treatment . These effects are best illustrated by comparison of the lower two panels in Figure 2B where without treatment , 9 . 3% of the cells displayed low MHC1 and EBOV GP levels , however after fixation and permeabilization the number of double negative cells was reduced to background levels and these now appear as MHC+ , GP+ cells in the upper right quadrant . As expected , the untransfected cell population of 32–34% remains unaltered by this treatment ( Figure 2B , upper left quadrants ) . Overall , this analysis suggests that the apparent downmodulation observed is not due to reduced steady-state levels of protein . Rather these transfected cells express unaltered levels of EBOV GP and MHC1 , however these proteins are inaccessible for surface staining . Recent structural analysis of EBOV GP suggests that the recognition site for the monoclonal antibody , KZ52 , employed in the flow cytometry analysis resides near the base of the protein [18] below the globular GP1 and heavily glycosylated mucin domains in GP . This finding , coupled with our results suggesting that downmodulation in these cells was not accompanied by a reduction in steady-state levels of β1 integrin or MHC1 , or a significant re-localization of EBOV GP , prompted us to consider the hypothesis that EBOV GP mediates its effects by blocking access to epitopes of proteins on the cell surface including epitopes within GP . Additionally , this hypothesis is consistent with the apparent threshold of GP expression required for downmodulation as well as the lack of a dynamin requirement [15] . To test this hypothesis , we engineered epitopes within EBOV GP at locations which , based on their position relative to the mucin domain and the globular region of GP , are predicted to be more accessible than the KZ52 epitope . Two constructs were created with an AU1 antibody epitope tag at the N or C terminus of the mucin-like domain , termed NmucAU1 GP and CmucAU1 GP , respectively . Cartoon depictions of each construct are shown in Figure 3C and D . These constructs were well expressed , as judged by Western blot analysis for EBOV GP and the AU1 tag ( Figure 3A ) . The sub-cellular localization of these constructs was also evaluated in HeLa cells by immunofluorescence microscopy and was found to be indistinguishable from wt GP ( Figure 3B ) . Although the structure of the mucin domain is unknown , its mucin-like O glycosylation may force the domain into an extended conformation as has been suggested for cellular mucin proteins [19] . This would likely position the C terminus of the mucin domain so that it is more exposed compared to the GP core ( Figure 3C and D ) . Based upon the proposed steric occlusion model , we hypothesized that the AU1 epitope of CmucAU1 would be most accessible to antibody staining . In contrast , the AU1 epitope in NmucAU1 might be less accessible than the epitope in CmucAU1 because of its location at the base of the mucin domain . Cells expressing wt GP , CmucAU1 GP , and NmucAU1 GP were analyzed by flow cytometry . When stained with the GP-specific KZ52 antibody , the epitope-tagged mutants displayed the characteristic comma-shaped flow cytometry plot seen with wt GP ( Figure 3C and D; top rows ) . In contrast to the reduced KZ52 staining observed , the AU1 epitope in CmucAU1 was highly visible by flow cytometry ( Figure 3C and D; bottom middle panels ) . Staining of the AU1 epitope on NmucAU1 GP was intermediate relative to CmucAU1 GP and wt GP KZ52 staining ( Figure 3C and D; bottom right panels ) . In support of the shielding model , these data demonstrate that cells exhibiting reduced levels of β1 integrin and MHC1 have high surface levels of GP as revealed by AU1 staining , not reduced levels as indicated by KZ52 staining . Furthermore , these data suggest that antibody accessibility to epitopes in GP differs based on the epitope position relative to the mucin domain and the globular regions of GP1 . The data presented above are consistent with EBOV GP affecting recognition of epitopes within GP by shielding , however we wished to address if a similar mechanism was responsible for the apparent downmodulation of host surface proteins . To directly address whether EBOV GP sterically occludes host surface protein epitopes , we sought to unmask MHC1 and β1 integrin staining . We hypothesized that dissociation of the GP1 subunit , which includes the mucin domain and globular “head” region of EBOV GP , from GP2 at the cell surface should relieve the shielding of previously occluded epitopes . The GP1 subunit is covalently linked to GP2 via a single sulfahydryl bridge between residues C53 and C609 [7] . We have previously demonstrated that this bond can be reduced by incubation with DTT , allowing for dissociation of the EBOV GP1 subunit from the surface of virions [20] . To confirm that DTT is able to effectively remove GP1 from the cell surface , cells expressing GP were incubated with DTT then the supernatant was analyzed for GP by Western blot . Figure 4A reveals that GP1 was readily detected in the supernatant of cells incubated with DTT compared to mock treated cells . Control experiments also demonstrated that the DTT treatment did not significantly alter surface expression of β1 integrin or MHC1 in mock-transfected cells ( Figure 4B ) . Moreover , this treatment did not result in permeabilization of the cells ( Figure 4C ) which , as shown above ( Figure 2 ) , could also rescue β1 integrin and MHC1 staining . In addition , these and the following experiments were carried out in the presence of azide and 2-deoxy glucose to ensure that the trafficking of nascent or recycled protein did not complicate the interpretation of this assay . We next examined the effect of DTT treatment on surface staining of β1 integrin and MHC1 in cells expressing EBOV GP . Flow cytometry analysis of the DTT-treated , GP-expressing cells indicates that GP-induced loss of staining of β1 integrin and MHC1 is reversed by DTT treatment and subsequent dissociation of GP1 from the cells: upon DTT treatment , staining of β1 integrin and MHC1 is restored to nearly control levels ( Figure 4D ) . Interestingly , staining for GP was also rescued , resulting in cells that stained positively for both GP and β1 integrin or MHC1 . This is somewhat counter-intuitive , as KZ52 makes critical contacts with residues on GP1 [18] , which is removed from the cell surface by DTT . These data suggest that DTT treatment removes a significant amount of GP1 from the cell surface – enough to reverse the steric occlusion of β1 integrin and MHC1 epitopes , as well as the KZ52 epitope . However , sufficient GP1 remains on the cell surface to allow for staining of GP by flow cytometry . Supporting this hypothesis , there appears to be a very modest downmodulation of integrin and MHC1 on the cells that appear to have the highest levels of GP ( Figure 4D , upper right quadrant of the +DTT flow cytometry plots ) . This finding agrees with our previously published study that suggests a threshold level of EBOV GP is needed to downmodulate β1 integrin , MHC1 or GP [15] . Removal of surface GP1 by DTT reverses the apparent downmodulation of surface proteins induced by EBOV GP . To ensure this effect could be directly attributed to the EBOV glycoprotein we tested the effect of DTT on cells expressing a mutant form of GP lacking the endoproteolytic site required for processing GP0 into GP1 and GP2 subunits . Previous analysis demonstrated that this mutant EBOV glycoprotein , GP cl ( - ) , retains normal viral entry function [20] , [21] and is therefore likely folded similarly to wt EBOV GP . As shown in Figure 4F , GP cl ( - ) also downmodulates MHC1 similarly to wt EBOV GP . However in contrast to wt GP , DTT treatment of cells expressing this uncleaved form of GP does not relieve the observed downmodulation of MHC1 ( Figure 4F ) . As anticipated , DTT treatment of cells expressing GP cl ( - ) produced no increase in GP release compared to untreated cells ( Figure 4E ) . The EBOV glycoprotein found in the supernatant from the GP cl ( - ) expressing cells likely represents trimeric GP released by the cellular enzyme TACE [22] . Overall , these data strongly support the model proposed for EBOV GP mediated occlusion of host surface proteins . EBOV GP is a heavily glycosylated protein , and we have previously shown the mucin domain to be sufficient to induce loss of staining of host surface proteins by flow cytometry [15] . Therefore , we directly addressed whether GP glycosylation plays a role in the shielding of surface epitopes . GP-expressing cells were treated with several glycosidases or pre-treated with a small molecule inhibitor of mucin synthesis , benzyl-α-GalNAc , then assayed for β1 integrin staining by flow cytometry . Importantly , none of the glycan-interfering treatments used here increased the staining for β1 integrin in cells transfected with empty vector ( Figure 5A ) . Also , these treatments did not cause the permeabilization of cells , allowing us to attribute changes in staining to alterations at the cell surface ( Figure 5B ) . Staining for β1 integrin on GP-expressing cells was increased by incubation with PNGaseF , an endoglycosidase that cleaves N-linked sugar moieties ( Figure 5D left ) . Similarly , staining for β1 integrin was increased by incubation with neuraminidase , an exoglycosidase that cleaves sialic acid , which is a common component of mucin sugars . ( Figure 5D , middle ) . When GP-expressing cells were incubated with both PNGaseF and neuraminidase , an additive effect was seen and β1 integrin staining was further increased ( Figure 5D , right ) . The effect of glycosidase treatment on cellular GP was also analyzed by Western blot ( Figure 5C , left ) . PNGaseF treatment results in loss of the top band of GP1 , which is the maturely-glycosylated form and the appearance of bands which co-migrate with GP1 that has been PNGaseF treated under denaturing conditions , but which still contains O glycosylation . Treatment with neuraminidase did not result in a perceivable shift in migration of GP1; this is likely due to the small mass of these glycans and the resolution of the gel . These data indicate a direct role for N-linked glycans in GP-mediated loss of β1 integrin staining . To directly address the role of O glycosylation in host protein downmodulation by EBOV GP , O glycosylation was perturbed by pre-incubating cells with benzyl-α-GalNAc or the control vehicle DMSO . This compound is a competitive inhibitor of β1 , 3-galactosyltransferase , which prevents the modification of core O glycan structures , resulting in shorter O-linked glycans and reduced sialyation [23] , [24] , [25] . Cells pre-treated with benzyl-α-GalNAc , then transfected with vector encoding GP showed increased staining for β1 integrin compared to DMSO treated cells , consistent with a role for O glycoslyation in the shielding of epitopes by the GP mucin domain ( Figure 5E , left plot ) . In cells pre-treated with benzyl-α-GalNAc and expressing GP , incubation with PNGaseF further increased staining for β1 integrin ( Figure 5E , right plot ) . Cells pre-treated with benzyl-α-GalNAc were also incubated with O-glycosidase , which can cleave unmodified core GalNAc structures; however , no further increase in β1 integrin was observed ( data not shown ) . This is perhaps due to remaining modification of the core O glycans . The effect of these treatments on GP glycosylation was analyzed by Western blot ( Figure 5C , right blot ) . Treatment with benzyl-α-GalNAc results in a modest increase in mobility for bands corresponding to GP containing O glycosylation , which are most easily seen in samples that have been PNGase-treated after cell lysis . Our data here suggest that the mass of O glycosylation is reduced , but not fully eliminated . This is expected , as benzyl-α-GalNAc only reduces mucin modification , but does not prevent the synthesis of initial core glycans . Taken together , these data demonstrate that surface N- and O- linked glycans , presumably on EBOV GP , contribute to the ability of GP to mask surface β1 integrin epitopes . The data presented above demonstrate that epitopes at different locations within EBOV GP are differentially occluded in GP expressing cells ( Figure 3 ) . To determine if a similar situation occurs for cellular proteins , four monoclonal antibodies that recognize distinct regions of MHC1 were analyzed . In cells expressing GP , staining for MHC1 is blocked regardless of the epitope examined ( Supplemental Figure S1 ) . Given the ability of EBOV GP to effectively mask all of the epitopes examined on MHC1 , we wanted to address whether this had functional consequences for MHC1 . Human OV79 cells expressing the HIV Gag-derived peptide SLYNTVATL ( SL9 ) were used to test the effect of EBOV GP on MHC1 antigen presentation . These cells present the SL9 antigen using a stably expressed MHC1 , HLA-A2 . The OV79- SL9 cells were mock transduced or transduced with adenoviral vectors encoding GFP ( AdGFP ) or GFP and EBOV GP ( AdGP ) , which resulted in nearly 100% of cells expressing GFP ( Figure 6A ) . Expression of EBOV GP dramatically reduced MHC1 levels in these cells whereas the control AdGFP vector had no effect on MHC1 expression ( Figure 6B ) . Primary human CD8 T-cells transduced with a lentiviral vector expressing a T-cell receptor ( 868TCRwt ) specific for SL9 were used to assess antigen presentation by GP-expressing OV79 cells . T-cell activation was measured by intracellular staining for production of the cytokine MIP-1β in CD8+ 868TCRwt+ expressing cells ( Figure 6C ) . Production of MIP-1β has been shown to be the most sensitive indicator of HIV-specific CD8 T-cell activation [26] . Quantification of the CD8 activation results demonstrates that expression of EBOV GP had a profound effect on antigen presentation by the target cells , reducing T-cell responses to nearly background levels ( Figure 6D ) . In contrast , the AdGFP control cells only modestly reduced the number of responding T-cells . Similar results were obtained using 293T target cells ( data not shown ) . The ability of EBOV GP to interfere with T-cell function does not appear to be caused by inhibitory signaling from the GP-expressing antigen presenting cells ( APCs ) since T-cells were fully activated when anti-CD3/CD28-coated beads were added to a mixture of GP-expressing OV79 and CD8+ 868TCRwt+ cells ( data not shown ) . Given the observations that all of the queried epitopes on MHC1 were occluded by GP expression and that T-cells are not stimulated by these APCs , the most straightforward explanation is that EBOV GP expression impedes T-cell recognition of antigen presenting cells . Overall these data support a model in which EBOV GP not only masks MHC and other surface proteins from antibody recognition , it also functionally inactivates them .
An important component of the virus host interaction is viral modulation of host functions . Many viruses alter expression and/or function of host surface proteins to affect signaling , immune surveillance , or viral superinfection . EBOV GP expression in cell culture has been observed by several groups to cause dramatic changes in cell adhesion and reduction in surface protein staining by flow cytometry [10] , [12] , [14] , [16] . EBOV infection causes a similar reduction of β1 integrin and MHC1 staining by flow cytometry , suggesting that observations from transient GP expression are not simply artifacts of overexpression [3] . EBOV GP-induced effects have previously been assumed to result from removal of surface proteins from the plasma membrane . In this study we analyzed the mechanism of downmodulation of host surface proteins by the Ebola viral glycoprotein , GP . We show that reduction in surface staining for the host proteins MHC1 and β1 integrin is not accompanied by decreases in the total cellular levels of these proteins . Moreover , the observed self downmodulation of EBOV GP does not result in relocalization of GP away from the plasma membrane . Using epitopes placed at various locations in EBOV GP we find that the observed GP surface levels appear to differ based on epitope position relative to the mucin domain and the globular regions of EBOV GP . A similar observation has been made using a series of monoclonal antibodies to EBOV GP [27] . Additionally , the apparent downmodulation of surface proteins is reversed by removal of the EBOV GP1 subunit by reduction or by enzymatic digestion of the carbohydrate modification on EBOV GP . Finally , our data demonstrate that EBOV GP expression dramatically impairs antigen presentation by host cells . Taken together these data support a model in which EBOV GP utilizes a steric occlusion mechanism to downmodulate accessibility and function of host surface proteins . The ability of viruses to affect host surface proteins has been well documented . For example , viruses may downregulate their cellular receptor , as in the case of HIV downregulation of CD4 and measles virus downregulation of the complement regulatory protein [28] , [29] . Other common targets for virus mediated downmodulation are surface proteins related to immune surveillance . MHC1 is known to be downregulated from the cell surface by many viral proteins: HIV nef , Adenovirus E19 , and KSHV K3 and K5 , to name a few [30] , [31] , [32] . Activating ligands for natural killer ( NK ) cells have also been shown to be actively downregulated by KSHV and Hepatitis C virus [33] , [34] . Multiple mechanisms and cellular pathways have been implicated in viral dysregulation of the various host surface molecules ( reviewed for MHC1 in [35] ) . The model demonstrated here of glycan mediated steric occlusion by EBOV GP represents , to our knowledge , a distinctive mechanism for viral regulation of host surface proteins . Indeed , a similar steric masking model has recently been proposed for EBOV GP [27] . The polydnavirus , Microplitis demolitor bracovirus expresses a mucin domain-containing glycoprotein which can abrogate cell adhesion and thus may utilize a mechanism similar to that proposed here for EBOV [36] . Our observation that enzymatic removal of carbohydrate modification can relieve downmodulation , coupled with prior observations that the mucin domain of EBOV GP is sufficient for downregulation [8] , [15] , suggests that the steric occlusion observed is mediated , at least in part , by N- and O-linked modification of EBOV GP . A similar glycan mediated steric hindrance model has been proposed for cellular mucin proteins , which can disrupt a variety of cell-cell interactions at the plasma membrane [37] , [38] , [39] , [40] , [41] . For the cellular mucin proteins , densely-arrayed O-linked glycans are critical for disruption of cell adhesion , with different core glycan structure and subsequent modifications influencing the function and anti-adhesive properties of the protein [42] . Additionally , the number of mucin tandem repeats positively correlates with the anti-adhesive properties of Muc1 [41] . Similarly , we have shown that sequential removal of glycosylation sites in the mucin domain of EBOV GP led to a step-wise reduction in cell detachment suggesting that such modifications within GP are involved in downmodulation [12] . The O-linked glycosylation found on the EBOV GP mucin domain may promote an extended conformation as is seen for cellular mucin proteins [19] allowing this domain in GP to act as an approximately 150 residue long flexible rod that can protrude and mask epitopes in the immediate vicinity . The ability of carbohydrate modification to protect epitopes on the surface of a viral glycoprotein is well established . Indeed , a glycan shield model has been proposed for other viral glycoproteins , most notably HIV , as a mechanism to avoid host immune recognition [43] . An extended glycosylated protrusion provided by the mucin domain may be a characteristic feature that distinguishes the “glycan umbrella” of EBOV GP from other viral glycoproteins where the glycan shield does not cause steric occlusion of host factors . Another feature of the proposed model is that EBOV GP must localize in close proximity to the affected proteins; perhaps within plasma membrane microdomains inhabited by the host proteins . This requirement may explain the critical threshold for the observed GP effects as well as the variety of proteins regulated by EBOV GP . It may be that the ability to occupy these microdomains is , in addition to the extensive carbohydrate modification , a characteristic feature of EBOV GP . Based upon our results it appears likely , therefore , that the heavily glycosylated EBOV GP acts as a glycan umbrella to physically occlude access to nearby host proteins , and GP itself , thereby impairing host protein function . It is intriguing to consider the role in EBOV replication or pathogenesis of GP-induced steric occlusion of surface proteins . Based upon our observations of proteins at the plasma membrane it is plausible that EBOV GP functions to shield epitopes on the surface of virions thereby contributing to infection and/or persistence in the natural reservoir . Notably the KZ52 monoclonal antibody employed in these studies is neutralizing but fails to protect nonhuman primates from EBOV infection [44] , [45] . Perhaps variation in GP density on virions produced in vivo differentially affects the neutralization sensitivity of viruses in nonhuman primates . Additionally , the ability of GP to mask MHC1 and other molecules on the cell surface , coupled with the inhibitory effect of GP on cell-cell adhesion , may be a strategy for avoiding CD8 T cell-mediated killing of EBOV infected cells . Our data demonstrating that GP-expressing cells do not effectively activate CD8 T cells supports this hypothesis . Interestingly , this mechanism is proposed for adenocarcinomas , in which cellular mucin protein overexpression can result in metastasis due to loss of adhesion , and has been shown to prevent recognition and killing by NK and cytotoxic T cells [38] , [46] , [47] . However , the rapid time course of EBOV infection and its impairment of adaptive responses may render escape from CD8 cells unnecessary in humans . Instead , protection from NK cells may be more important and the ability of EBOV GP to effect NK cell recognition should be explored . Alternatively , the ability to mask MHC1 may be more critical for viral infection or persistence in the natural reservoir for EBOV . Finally , it is known that the interface between the innate and adaptive immune response is affected during EBOV infection ( reviewed in [2] ) . We have previously shown that EBOV GP causes rounding in macrophages [12] . It is possible that EBOV GP shielding and inhibition of adhesion molecules or other immune regulatory proteins on professional antigen presenting cells such as macrophage or dendritic cells plays a role in the immune dysfunction characteristic of EBOV infection .
For GP studies , cDNA encoding the membrane-anchored form of Zaire EBOV GP ( Mayinga strain , accession number U23187 ) was used . For AU1 tagged GPs , the amino acids , DTYRYI were added using linker insertion into GP that had been engineered to have a unique XhoI site at position 312 encoding the amino acids LE ( NmucAU1 ) and a unique NotI site replacing amino acid 463 with the amino acids KRPL ( CmucAU1 ) . EBOV GP harboring mutations in the endoproteolytic site , GP cl ( - ) , has been previously described [20] . All constructs were cloned into the pCAGGS expression vector . 293T and HeLa cells were cultured in DMEM ( Gibco ) with 10% fetal bovine serum ( HyClone ) and penicillin/streptomycin ( Gibco ) at 37°C with 5% CO2 . For flow cytometry and Western blotting , 293T cells were plated in 10 cm or 6-well plates one day prior to transfection . Cells were transiently transfected by Lipofectamine 2000 according to manufacturer's directions with 30 µg or 4 µg DNA per 10 cm plate or 6-well , respectively . Immunofluorescence microscopy was performed using HeLa cells that were plated on glass coverslips in 24-well plates and transfected with 1 . 5 µg DNA as above . Purified CD8 T cells from normal donors were obtained from the University of Pennsylvania Center for AIDS Research Immunology Core under a University of Pennsylvania IRB approved protocol . The human ovarian adenocarcinoma line OV79 has been described previously [48] . To create the OV79-SL9 antigen-presentig cells , OV79 cells were sequentially transduced to express HLA-A*02 [49] and a construct of GFP fused to a codon-optimized sequence of HIV-1 p17 Gag50–102 . High titer lentiviral vectors were produced as described previously [50] . Primary human CD8 T cells were cultured in X-Vivo 15 ( Lonza ) supplemented with 5% HABS ( Valley Biomedical , Winchester , VA ) , 2 mM GlutaMax and 25 mM HEPES ( Invitrogen ) . CD8 T-cells were transduced to express the SL9-specific HLA-A2 restricted 869TCR as described previously [51] . Transduction efficiencies were assessed by flow cytometric analysis of TRBV5-6 staining ( anti-Vbeta5a , Thermo-Fisher ) or HLA-A*02- SL9 tetramer stain ( Beckman Coulter Immunomics ) . OV79-SL9 cells were plated at 16 , 000 cells/well on 48 well plates . After an overnight incubation cells were transduced with adenovirus expressing GFP ( Ad GFP ) or GFP and the EBOV Zaire glycoprotein ( Ad GP ) as described previously [12] . Briefly , adenoviruses were diluted in media and applied to cells at an MOI of 300 . Media alone was used as a control . 48 h after transduction , target cells were analyzed for GFP and HLA expression . Floating and adherent cells , lifted by incubation with versene , were combined and stained for HLA-ABC or isotype control with APC-conjugated antibodies ( BD-Biosciences ) . Alternatively , cells were stained for different MHC1 epitopes with W6/32 ( eBiosciences ) , YTH862 . 2 ( Santa Cruz Biotechnology ) , BB7 . 2 ( BD Pharmingen ) , or GJ14 ( Chemicon ) primary antibodies , flowed by Alexa Fluor 647 ( Invitrogen ) secondary antibodies . 10 , 000 viable ( forward scatter versus side scatter ) events were collected on an LSR-II flow cytometer running BD FACSDiva-6 ( BD-Biosciences ) , and analyzed in FlowJo ( Tree Star Inc . ) . SL9-specific TCR–transduced CD8 T cells were mixed with unmodified or adenovirally transduced OV79-SL9 target cells at a 2∶1 ratio for 1 h , followed by 4 h in the presence of brefeldin-A ( Golgiplug , BD Biosciences ) . Stimulation with TPA ( 3 mg/ml , Sigma-Aldrich ) and ionomycin ( 1 mg/ml; Calbiochem ) with brefeldin-A was used as positive control . Cells were washed in PBS and surface-stained using CD8 conjugated to APC-H7 , and then fixed and permeabilized with the Caltag Fix & Perm kit ( Invitrogen ) and stained using anti-TRBV5-6 FITC and macrophage inflammatory protein-1b ( MIP-1b , CCL4 ) -PE . Sequential gates of 10 , 000 viable ( forward scatter versus side scatter ) , CD8 positive events were acquired for all conditions on an LSR-II flow cytometer running BD FACSDiva-6 ( BD-Biosciences ) . Data were analyzed for cytokine production in FlowJo ( Tree Star Inc . ) . Transfected cells were removed by resuspension in the culturing media . Cells were pelleted at 4°C for 3 min at 1300×g . Pellets were resuspended in 1% Triton X-100 or RIPA buffer with complete protease inhibitor cocktail ( Roche ) for 5 minutes . Lysates were cleared by centrifugation at 4°C at 20 , 800×g . 30 µl samples were mixed with reducing SDS buffer , boiled for 5 minutes , and separated on a 4–15% Criterion PAGE gel ( Bio-Rad ) . Proteins were transferred to PVDF ( Millipore ) at a 400 mA constant current . Membranes were blocked in 5% milk in TBS . Membranes were probed with rabbit polyclonal anti-GP sera which recognizes the GP1 subunit [52] , rabbit anti-AU1 antibodies ( Bethyl labs ) , or anti-GAPDH monoclonal antibodies ( Calbiochem ) in blocking buffer . Protein was detected with stabilized goat anti- rabbit or mouse HRP conjugated antibodies ( Pierce ) in blocking buffer . Membranes were visualized with SuperSignal Femto substrate ( Pierce ) . 293T cells were detached from the plate 24 hours post transfection with PBS lacking Ca++ and Mg++ ( −/− ) , 0 . 5 mM EDTA and combined with floating cells in culture media . Alternatively , floating cells in cluture media were removed and used exclusively ( where indicated ) . Cells were pelleted at 4°C at 250×g , then resuspended in flow wash buffer ( PBS −/− with 1% bovine calf serum and 0 . 05% NaAzide ) and aliquoted for staining . For detection of EBOV GP , cells were stained with the human MAb , KZ52 [45] and detected with FITC anti-human IgG ( PharMingen ) . For detection of AU1 epitopes , cells were stained with rabbit polyclonal anti-AU1 antibodies ( Bethyl labs ) and detected with FITC goat anti-rabbit IgG ( Rockland ) . For detection of β1 integrin , cells were stained with anti-human CD29 PE-Cy5 conjugate ( eBioscience ) ; for detection of MHC1 , cells were stained with anti- HLA-ABC PE-Cy5 conjugate ( eBioscience ) . For intracellular staining , cells were permeabilized using Cytofix/Cytoperm ( BD Biosciences ) for 20 min on ice , followed by washing with Permwash ( BD Biosciences ) . Antibodies where then diluted in Permwash buffer . For detection of GM130 and calnexin , mouse monoclonal FITC-conjugated antibodies were used ( BD Transduction Labs ) . All staining was performed on ice , followed by washing . Live cell gates were drawn based on forward and side scatter . For each sample , 10 , 000 or 20 , 000 events in the live cell gate were collected and analyzed . Data were collected on a Becton Dickinson FACSCalibur and analyzed using FlowJo software ( Tree Star , Inc . ) . For HeLa cells , media was removed at 24 hours post-transfection , cells were washed with PBS and fixed with 3% PFA in PBS for 20 minutes . For non-adherent 293T cells , media containing floating cells was removed from plate , then centrifuged onto poly-D-lysine coated coverslips ( BD Biosciences ) , then fixed . All samples were then washed with PBS , then permeabilized with 0 . 2% saponin , 1% goat serum in PBS for 5 minutes , then washed with PBS . Cells were blocked with 10% goat serum , 0 . 1% Tween-20 in PBS for 2 hours . For GP staining , coverslips were incubated with mouse anti-EBOV GP MAb 42/3 . 7 ( gift from Yoshihiro Kawaoka ) and detected with goat anti-rabbit Alexa Fluor 594 antibodies ( Invitrogen ) . For AU1 staining , coverslips were incubated with rabbit anti-AU1 antibodies ( Bethyl labs ) and detected with anti-rabbit Alexa Fluor 488 antibodies ( Invitrogen ) . Cells were washed with PBS after each staining step . Coverslips were mounted on glass slides with mounting medium containing DAPI ( Vectasheild ) . Z-section images were collected on a Leica DMRE fluorescence microscope using Open Lab software ( Improvision ) . Thirty z-sections per image were collected at 0 . 2 µm intervals . Z-section data were deconvoluted using Velocity software ( Improvision ) to a 98% confidence level or 15 iterations . Images shown are single , deconvoluted , z-sections . At 24 hours post-transfection , sodium azide was added to 0 . 1% and 2-deoxy glucose was added to 10 mM . Cells were incubated an additional 30 min . Cells were then harvested and resuspended in flow wash buffer supplemented with 0 . 1% azide and 10 mM 2-deoxy glucose . DTT was then added to 150 mM and cells were incubated at 37°C for 20 minutes . Cells were then pelleted at room temperature and the supernatant was removed and blotted for GP as described above . Cells were then washed twice in flow wash and stained for flow cytometry as described above . At 24 hours post-transfection , floating cells were harvested and resuspended in 100 µl flow wash buffer . 100 U of neuraminidase ( NEB ) and/or 1000 U of PNGaseF ( NEB ) was then added . Cells were then incubated at 37°C for 20 minutes . Cells were then washed twice and aliquoted for flow cytometry or Western blotting as described above . Alternatively , cells were incubated with 2 mM benzyl-α-GalNAc ( Sigma ) or DMSO at 31°C for 48 hours . Cells were then given fresh media with 2 mM benzyl-α-GalNAc or DMSO and cultured at 37°C for 1 hour . Cells were then transfected as described above . At 24 hours post-transfection , floating and adherent cells were harvested and resuspended in 100 µl flow wash buffer . 1000 U of PNGaseF ( NEB ) or 2 . 5 mU of O-glycosidase ( Sigma ) was then added . Cells were then incubated and analyzed as above . For PNGaseF treatment of cell lysates , 30 µl of lysate was incubated with glycoprotein denaturing buffer ( NEB ) for 10 minutes at 60°C . Samples were then incubated with G7 buffer , NP40 , and 500 U PNGase F ( NEB ) for 2 hours at 37°C , then blotted for GP as described above .
The authors would like to thank Christian Fuchs for technical assistance , Erica Ollmann Saphire and Dennis Burton for providing the KZ52 antibody , Yoshihiro Kawaoka for providing anti-GP monoclonal antibodies , and Andrew Rennekamp and Rachel Kaletsky for helpful discussion .
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The Ebola virus ( EBOV ) is a highly pathogenic virus that infects humans and non-human primates , causing severe disease or death in the majority of these cases . The interaction of this virus with its host on a cellular level is only just beginning to be understood . EBOV , like many viruses , affects the expression or function of several cell surface proteins , including adhesion factors and protein complexes responsible for allowing the immune system to recognize infected cells . Our group and others have previously shown that expression of the main viral glycoprotein of EBOV in cultured cells is sufficient to cause this disruption . Here we have identified the mechanism by which this disruption occurs . Heavily glycosylated domains of the EBOV glycoprotein form a steric shield over proteins at the cell surface . This steric interference blocks the detection of affected surface proteins using antibody reagents , but also has the functional effect of abrogating cell adhesion and preventing interactions with CD8 T cells . The results from this study highlight a novel mechanism for viral disruption of host cell surface protein functions and give insight to interactions between the Ebola virus and its host .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods",
"Achnowledgments"
] |
[
"virology/immune",
"evasion",
"virology/effects",
"of",
"virus",
"infection",
"on",
"host",
"gene",
"expression",
"virology/virulence",
"factors",
"and",
"mechanisms",
"virology/emerging",
"viral",
"diseases"
] |
2010
|
Steric Shielding of Surface Epitopes and Impaired Immune Recognition Induced by the Ebola Virus Glycoprotein
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With the recent emergence of a novel pandemic strain , there is presently intense interest in understanding the molecular signatures of virulence of influenza viruses . PB1-F2 proteins from epidemiologically important influenza A virus strains were studied to determine their function and contribution to virulence . Using 27-mer peptides derived from the C-terminal sequence of PB1-F2 and chimeric viruses engineered on a common background , we demonstrated that induction of cell death through PB1-F2 is dependent upon BAK/BAX mediated cytochrome c release from mitochondria . This function was specific for the PB1-F2 protein of A/Puerto Rico/8/34 and was not seen using PB1-F2 peptides derived from past pandemic strains . However , PB1-F2 proteins from the three pandemic strains of the 20th century and a highly pathogenic strain of the H5N1 subtype were shown to enhance the lung inflammatory response resulting in increased pathology . Recently circulating seasonal influenza A strains were not capable of this pro-inflammatory function , having lost the PB1-F2 protein's immunostimulatory activity through truncation or mutation during adaptation in humans . These data suggest that the PB1-F2 protein contributes to the virulence of pandemic strains when the PB1 gene segment is recently derived from the avian reservoir .
For the first time in more than 40 years , a novel influenza virus has emerged from an animal reservoir and caused a human pandemic [1] . In contrast to the three pandemics of the 20th century , most disease from the novel H1N1 pandemic influenza virus has been mild [2] . The reasons for this disparity in pathogenesis are unclear because the molecular signatures of virulence of pandemic viruses are not known . A comparison of the genesis of the three 20th century pandemics reveals that only 2 unique gene segments were reassorted from the avian reservoir in every case - hemagglutinin ( HA ) and PB1 [3] . It is accepted that antigenic novelty is required for a virus to achieve pandemic status , explaining why the HA gene has been new in past pandemics . However , the significance of inclusion of a novel PB1 gene segment in each of the 20th century pandemics is not yet understood . The discovery of the PB1-F2 protein , which is translated from the +1 reading frame of the PB1 gene segment , may be a clue [4] . If this gene product contributes to virulence , it may serve as a marker of the pathogenicity of pandemic strains . Intriguingly , the 2009 pandemic H1N1 contains a PB1 gene segment that is thought to have been derived from human viruses and to have been evolving in swine for approximately 15 years [5] , [6] . Its PB1-F2 open reading frame is truncated after a predicted 11 amino acids and is therefore likely non-functional if it is expressed . PB1-F2 is a short ( 87–90 a . a . ) influenza A virus protein discovered in 2001 [4] . After expression , it is rapidly degraded and it is not required for viral replication in ovo or in cultured cells [4] . The PB1-F2 protein is recognized by the human immune system , resulting in both humoral and T-cell responses during infections with seasonal H3N2 or highly pathogenic H5N1 viruses [4] , [7] , [8] . Expression of PB1-F2 has been shown to enhance viral pathogenicity in mouse models of influenza A virus infection [9] , [10] . The precise contribution of PB1-F2 to virulence and its function in the life cycle of influenza A viruses in mammalian hosts are unclear . The C-terminal portion of the PB1-F2 open reading frame contains a mitochondrial targeting sequence [4] . Expression of full length PB1-F2 has been associated with mitochondrial targeting and apoptosis [4] , [11] and it has been suggested that mitochondrial disruption with subsequent cell death could contribute to virulence [11] , [12] . A suggested second function of the PB1-F2 protein , causing immunopathology by enhancing the inflammatory response , has been demonstrated in animal models of influenza disease [10] , [13] . This mechanism for increased pathogenicity was particularly striking when the PB1-F2 from the 1918 pandemic strain was expressed , arguing for clinical relevance [10] , [13] . Finally , the PB1-F2 protein has been shown to bind PB1 in vitro , and it has been proposed that this might enhance transcription by increasing nuclear retention time [14] . Downstream effects on replication were predicted to enhance virulence . We have recently demonstrated , however , that this third property of PB1-F2 is cell-type and virus strain specific and does not result in changes in viral lung load or pathogenicity in vivo [15] . Building on the results from our recent report examining the effects of PB1-F2 on viral replication [15] , we analyze here the PB1-F2 protein's contribution to pathogenesis in a mouse model in the context of the other two proposed mechanisms , cell death and enhanced inflammation . To demonstrate the relevance of the results to human disease , PB1-F2 proteins from a variety of epidemiologically important influenza A virus strains including all pandemic strains from the 20th century , a highly pathogenic avian influenza virus of the H5N1 subtype , and representative seasonal strains were utilized . We show here that the ability to cause cell death through PB1-F2 mediated mitochondrial interactions is specific to the laboratory strain A/Puerto Rico/8/34 ( H1N1; PR8 ) among the viruses studied , arguing this function is not a likely contributor to pathogenicity in humans with most epidemiologically relevant strains . However , the capacity to enhance the inflammatory response is a general feature of PB1-F2 proteins encoded by PB1 genes that are direct introductions from the avian gene pool . These PB1 genes contributed to the formation of all pandemic strains of the 20th century and from the currently circulating highly virulent H5N1 strain that constitutes an imminent pandemic threat . The significance of these findings for future pandemic preparation and for understanding of the current H1N1 pandemic are discussed .
Influenza viruses have the capability to subvert host immunity by several mechanisms . It has been suggested that down-regulation of the host immune response through apoptosis of responding immune effector cells by PB1-F2 might contribute to virulence [12] . However , effects of PB1-F2 on cell death have been contextual; the protein's apoptotic effects have been cell type specific , have differed dependent on infection with whole virus vs . expression of PB1-F2 alone , and to this point have only been studied using the laboratory strain PR8 . We reasoned that if this mechanism formed an integral component in the influenza A virus strategy for down-regulation of the host immune response to infection , then induction of cell death would be mediated by PB1-F2 proteins from several epidemiologically important influenza A virus strains . Peptides derived from PB1-F2 C-terminal sequences of PR8 , the three 20th century pandemic strains ( 1918 , 1957 , 1968 ) , a recent highly pathogenic avian influenza virus of the H5N1 subtype , and a recent seasonal H3N2 strain were synthesized for study [10] , [15] ( Figure 1 ) . Recent seasonal H1N1 strains express a form of PB1-F2 truncated after 57 amino acids , lacking the mitochondrial targeting sequence located in the C-terminal region , and thus could not be evaluated in this manner [15] , [16] . The predicted secondary structures of these peptides were determined by circular dichroism and match the reported structure of this region as described for full-length protein and 44-mer peptides [17] , [18] ( data not shown ) . These peptides are internalized when presented to cells in vitro , and are observed to have similar intracellular distributions and kinetics of degradation as does full length protein expressed from the virus ( Figure S1; Text S1 ) . First , we exposed the human lung epithelial cell line A549 and the BalbcJ mouse derived macrophage cell line RAW264 . 7 to the panel of peptides for 1 hour at a final concentration of 50µM . Evaluation of necrosis via flow cytometric analysis of AnnexinV+PI+ events revealed that only the peptide derived from the laboratory strain PR8 induced a significant amount of cell death in the human epithelial cell line A549 ( Figure 2A ) . Both PR8 and the peptide derived from the 1918 pandemic strain caused cell death in RAW264 . 7 cells ( Figure 2B ) , but the 1918 peptide had no effect in A549 . Exposure of RAW264 . 7 or A549 cells to peptides derived from virus strains other than those derived from PR8 or the 1918 strain did not affect viability , similar to exposure to an N-terminal peptide control or unexposed controls . There were negligible AnnexinV+ only events in either cell line exposed to peptides , which suggests that the cells were dying as a result of necrosis in this assay , rather than apoptosis . To evaluate whether PB1-F2 protein expression in the context of viral infection had similar effects on induction of cell death , we next infected A549 or RAW264 . 7 cells with a panel of recombinant viruses at an MOI of 1 for 2–12 hours . This panel included previously described viruses unable to express PB1-F2 ( ΔPB1-F2/PR8 ) , or expressing the PB1-F2 of the 1918 pandemic strain ( 1918 PB1-F2/PR8 ) or the truncated 1956 H1N1 strain ( Beij PB1-F2/PR8 ) [10] , [15] . In addition , two previously described viruses [15] in a 7 gene segment PR8 background ( 7∶1 reassortants ) and encoding PB1 gene segments from a 2004 highly pathogenic avian influenza of the H5N1 subtype ( H5N1 PB1/PR8 ) or from a 1995 human H3N2 strain ( H3N2 PB1/PR8 ) were utilized along with their isogenic deletion mutants for PB1-F2 ( H5N1 ΔPB1-F2/PR8 and H3N2 ΔPB1-F2/PR8 ) . Using confocal microscopy we demonstrated that PB1-F2 proteins from the viruses which were utilized in this study and which have an intact PB1-F2 ORF are expressed and distribute throughout the cell ( Figure S2; Text S2 ) and [15] . As has been demonstrated previously [4] , [11] , [12] , PR8 virus induces significant cell death compared to uninfected controls ( Figure 2C , D ) . PB1-F2 has been shown to be maximally produced at 6–8 hours post-infection in these cells types [15] and only minimal cell death was appreciated in the first 6 hours post infection ( data not shown ) . When RAW264 . 7 cells were infected with PR8 virus , necrotic death peaked 8 hours after infection , while in A549 cells it peaked 12 hours post infection . The inability of the ΔPB1-F2/PR8 to express PB1-F2 and the truncation of the C-terminal portion of Beij PB1-F2/PR8 abrogated the ability of both viruses to cause cell death in both cell types ( Figure 2C , D ) . Interestingly , however , expression of the 1918 PB1-F2 , which has been associated with enhanced virulence [10] , [13] , did not cause significant increases in cell death over controls . In addition , deletion of PB1-F2 in either an H3N2 or H5N1 PB1 gene segment background did not alter the cell death phenotype of chimeric viruses expressing those PB1s . We conclude from these data that the ability to cause cell death through PB1-F2 is a property of specific strains and is unlikely to have contributed to the pathogenicity of the 20th century influenza virus pandemics or recent seasonal epidemics . It has been suggested that PB1-F2 is able to induce cell death by disrupting mitochondrial organization through interaction with inner mitochondrial membrane adenine nucleotide translocator 3 ( ANT3 ) and the outer mitochondrial membrane voltage channel 1 ( VDAC1 ) to produce a mitochondrial permeability transition [12] . Alternatively , the PR8 PB1-F2 has been shown to permeabilize planar membranes , and thus may be able to directly permeabilize mitochondria [19] . We therefore probed the mechanism underlying the induction of cell death mediated by the PR8 PB1-F2 . We hypothesized that the PB1-F2 C-terminal domain may promote mitochondrial outer membrane permeabilization ( MOMP ) via the activation of the pro-apoptotic Bcl-2 family effector proteins BAX and BAK . To test this hypothesis , we exposed isolated mitochondria obtained from the livers of BALBcJ mice to various concentrations of PR8 derived PB1-F2 peptide . Analysis of cytochrome c release revealed that peptide derived from the laboratory strain PR8 could promote MOMP . As PR8 is a mouse adapted laboratory strain and initial experiments utilized only murine derived intact mitochondria , we repeated peptide exposure experiments using mitochondria obtained from liver tissue of chicken embryos , outbred ferrets , and mallards . Results indicate that PR8 PB1-F2 derived peptide is a potent inducer of cytochrome c release and is not species specific ( Figure 3A ) . As little as 10µM PR8 PB1-F2 peptide was sufficient for inducing cytochrome c release from each species analyzed . As different PB1-F2 proteins may display species specificity in mitochondrial targeting by the PB1-F2 protein , we next examined MOMP and release of cytochrome c using the panel of different C-terminal PB1-F2 peptides and an N-terminal peptide from PR8 as a negative control . Again , only the PR8 PB1-F2 was able to promote MOMP ( Figure 3B ) , irrespective of the species from which the mitochondria were obtained . In contrast , mitochondria obtained from the livers of bak-/-bax-/- mice did not release cytochrome c when incubated with PB1-F2 C-terminal peptide ( Figure 3B ) . These data suggest that apoptosis induced by the PR8 PB1-F2 protein is dependent upon BAK/BAX activation and MOMP . To determine BAK/BAX dependency for PR8 PB1-F2 induction of apoptosis at the cellular level , we treated wild-type murine embryonic fibroblasts ( MEFs ) and bak-/-bax-/- MEFs with the panel of PB1-F2 peptides and analyzed for apoptosis . The PR8 PB1-F2 derived peptide induced apoptosis in wild-type MEFs , but peptides derived from other viruses did not show similar activity ( Figure 3C ) . However , apoptosis in bak-/-bax-/- MEFs was greatly reduced such that PR8 PB1-F2 induction of cell death was equivalent to cells exposed to the other peptides ( Figure 3D ) . Taken together , the cytochrome c release and apoptosis data implicate PR8 PB1-F2 in BAK/BAX activation and the mitochondrial pathway of apoptosis , but suggest that this effect is specific to certain influenza virus strains . PB1-F2 proteins from both laboratory viruses and clinically relevant strains have been shown to contribute to primary viral virulence [9] , [10] , [13] and to the pathogenesis of secondary bacterial infections [10] in mice . This appears not to be related to the proposed ability of PB1-F2 to enhance replication or cause cell death , as both of these functions are limited to specific virus strains ( [15] and this report ) . We therefore investigated the contribution of several clinically relevant PB1-F2 proteins to immunopathology . Mice were exposed to a panel of PB1-F2 derived peptides and were euthanized 24 hours later for collection of bronchoalveolar lavage fluid ( BALF ) . C-terminal PB1-F2 peptides derived from PR8 , the pandemic strains from 1918 ( H1N1 ) , 1957 ( H2N2 ) and 1968 ( H3N2 ) , and the 2004 H5N1 virus all caused significant influx of white blood cells into the BALF compared to controls . Several cell types were increased including T-cells ( data not shown ) , dendritic cells ( data not shown ) , macrophages ( Figure 4A ) and neutrophils ( Figure 4B ) . Interestingly , the peptide derived from a more recent H3N2 strain , A/Wuhan/359/1995 , did not cause an appreciable increase in inflammatory cells over controls . When peptide exposed mice were followed for morbidity for 7 days , striking differences were seen comparing the five peptides that caused inflammation with the 1995 H3N2 peptide and the controls . The “pro-inflammatory” peptides caused huddling , hunching , labored breathing , ruffled fur and weight loss which peaked in the first 24–48 hours after exposure , while the “non-inflammatory” exposures caused no clinical signs ( data not shown ) or weight loss ( Figure 4C ) . Thus , the ability to cause lung inflammation appears to be a property of PB1-F2 proteins recently emerged from the avian gene pool . H1N1 strains circulating in humans since about 1950 have a truncated PB1-F2 that lacks the C-terminal residues responsible for this effect and in contrast to their pandemic forbear from 1968 , recently circulating H3N2 strains lack a PB1-F2 capable of causing inflammation . To assess the contribution of PB1-F2 to inflammation in the context of a full virus , where expression of other proteins is likely to contribute to the inflammatory response , we utilized the previously described set of viruses on the PR8 backbone in a mouse infection model . In data previously reported with these viruses , alteration or abrogation of PB1-F2 did not result in significant differences in weight loss , in the dose needed to cause death in mice , or in viral lung titers 1 , 3 , 5 and 7 days after infection for any comparisons except those previously reported for the 1918 PB1-F2 [10] , [15] . However , the differential effects of PB1-F2 expression could clearly be seen in the inflammatory response in the lungs . Disruption of PB1-F2 expression in PR8 or replacement of the PR8 PB1-F2 with the C-terminally truncated Beij PB1-F2 both significantly reduced the number of white blood cells found in BALF 3 days post viral infection ( Figure 5A ) compared to PR8 . This significant difference was maintained when specifically assessing the influx of either macrophages or neutrophils ( Figure 5B , C ) . Expression of the 1918 PB1-F2 led to effects similar to those of the PR8 virus . Use of the virus containing the H5N1 PB1 gene segment in a PR8 background revealed that disruption of PB1-F2 expression also significantly depressed the inflammatory response compared to the virus maintaining the ability to express full length PB1-F2 ( Figure 5A , B , C ) . However , in agreement with the peptide data , no differences were seen that could be attributed to the 1995 H3N2 derived PB1-F2 . Having determined that PB1-F2 drives an influx of inflammatory cells into the lungs that is detectable in BAL fluid , we next assessed the impact of this enhanced inflammatory response on histopathologic changes in lung tissue . Groups of mice were exposed to the panel of peptides and euthanized 24 or 72 hours later for examination of the lungs by an experienced veterinary pathologist ( K . L . B . ) who was blinded to the purpose of the study and the composition of the groups . At the 24 hour timepoint , only minimal perivascular changes were observed and no differences were apparent between groups ( data not shown ) . 72 hours after exposure , however , significant pathology was observed in some groups of mice compared to others , mirroring the dichotomy in morbidity pictured in Figure 4C . Only minimal rare , perivascular infiltration of lymphocytes around small vessels was observed in mice exposed to the N-terminal control peptide or the peptide derived from the H3N2 seasonal strain A/Wuhan/359/1995 ( Figure 6E , F ) . However , in mice exposed to peptides derived from the pandemic strains from 1918 and 1957 , as well as the peptide from a 2004 H5N1 strain , hypertrophy of type II pneumocytes and thickening of alveolar septae were observed . Significant infiltration of neutrophils and macrophages was noted in both interstitial perivascular regions as well as within alveolar spaces ( Figure 6B–D ) . Macrophages grossly outnumbered neutrophils , mirroring the findings in BAL fluid following peptide exposure ( Figure 4A , B ) . In the lungs of mice exposed to the PR8 peptide , similar inflammatory changes were seen , but there was an additional finding of direct alveolar wall damage with fibrin deposition and copious necrotic debris filling the alveoli , suggestive of cell death ( Figure 6A ) . From these data and data presented in Figure 4 , we conclude that the major effect of exposure of mammalian lungs to PB1-F2 proteins is generation of a macrophage and neutrophil dominated inflammatory response which causes significant immunopathology . Following adaptation of an H3N2 to humans , this function has been lost . The additional capability of the PR8 PB1-F2 protein to cause cell death enhances the pathology seen in the animals resulting in worse clinical outcomes . In titration of this panel of peptides in mice , only the PR8 peptide caused fatal illness ( data not shown ) , suggesting that both functions of PB1-F2 can contribute to fatal viral pneumonia . To assess this inflammatory phenotype in the context of a full virus , mice were infected with WT PR8 , 1918 PB1-F2/PR8 , ΔPB1-F2/PR8 , or Beij PB1-F2/PR8 and were euthanized 72 hours later for histopathologic examination as described above . In all lungs examined , pathologic changes typical of PR8 viral infection were observed , including perivascular infiltration of lymphocytes into interstitial regions , areas of focal necrosis of terminal airways and prominent cellular debris associated with acute hemorrhage into alveoli ( Figure 7A ) . In the lungs of mice infected with PR8 or 1918 PB1-F2/PR8 , however , significantly more perivascular cuffing was noted , consisting of an admixture of both viable and degenerate neutrophils and macrophages . The number of inflammatory cells seen in both the interstitium and alveoli was noticeably greater in these mice than in mice infected with ΔPB1-F2/PR8 or Beij PB1-F2/PR8 . This finding supports the BAL data presented in Figure 5 and the histopathologic changes caused by the PB1-F2 peptide alone in Figure 6 . Staining for myeloperoxidase ( MPO ) highlighted the influx of granulocytes and resulting inflammation in the lungs of mice infected with PR8 or 1918 PB1-F2/PR8 and was significantly more intense in these lungs compared to the ΔPB1-F2/PR8 or Beij PB1-F2/PR8 infected lungs ( Figure 7B ) . We conclude that expression of full length PB1-F2 enhances lung inflammation during influenza virus pneumonia and increases the pathologic damage that occurs . During infections with viruses such as PR8 that are capable of causing PB1-F2 mediated cell death and inflammation by an unrelated mechanism , the lung injury is enhanced .
The data presented here demonstrate the capacity of the influenza A virus PB1-F2 protein to enhance the lung inflammatory response in a mouse model . This study is the first to explore the function of PB1-F2 utilizing PB1-F2 proteins from several different , epidemiologically important influenza A virus strains . These strains included those containing novel PB1 gene segments contributing to the formation of all pandemic strains of the 20th century and from the currently circulating , highly virulent H5N1 strains that constitute an imminent pandemic threat . The inflammatory response engendered by PB1-F2 was characterized by increased cellular infiltrates into the interstitial and alveolar spaces of the lungs , which largely consisted of macrophages and neutrophils . Among the viruses assessed , induction of inflammation by PB1-F2 was a property restricted to proteins encoded by PB1 gene segments that were direct introductions from the avian gene pool . Seasonal strains which had adapted to humans lacked a PB1-F2 capable of causing inflammation . One important caveat is that these experiments were done on a PR8 background , so further study of these PB1-F2 proteins in their native background is indicated . Our analysis of MOMP utilizing mitochondria from several animal species and study of cell death relating to PB1-F2 expression implicate the PR8 PB1-F2 in BAK/BAX activation and the mitochondrial pathway of apoptosis . However , induction of cell death via mitochondrial association was specific only to the PB1-F2 protein of the laboratory strain of PR8 in these studies and is not a general property of all PB1-F2 proteins . All influenza viruses infecting humans are zoonotic reassortants comprised of gene segments that derive ultimately from an avian reservoir of precursor strains . It has been appreciated for some time that one of the requirements for emergence of a pandemic strain is antigenic novelty of the HA , which facilitates high clinical attack rates [20] . However , the molecular signatures contributing to another criterion for pandemic strains , the ability to cause serious disease , are not clear at present . The inclusion of a novel PB1 gene segment in each of the virulent 20th century pandemics may be an intriguing clue . Evidence presented here implicates full length PB1-F2 protein expression , encoded by a +1 open reading frame of the PB1 gene segment , as a marker of pathogenicity of 20th century pandemic strains . The pro-inflammatory capability of the H5N1 PB1-F2 demonstrated by this study provides further reason for concern that this subtype represents a serious pandemic threat , although significant sequence diversity exists among avian strains and the specific molecular signatures for the inflammatory phenotype are not yet known . Full length PB1-F2 proteins are expressed by nearly all avian influenza virus strains [16] , but analysis of lineages after introduction of these strains into humans or pigs show evidence of permanent truncation during adaptation in mammalian hosts . This pattern implies that there is some functional utility for the protein in birds that is not evolutionarily advantageous for the virus in mammals . We speculate that the inflammatory property of PB1-F2 described here facilitates transmission from the natural host niche of influenza viruses in waterfowl , the gut , by increasing luminal secretions . If induction of inflammation in the lung is detrimental or neutral to the virus during its life-cycle in mammalian hosts , this function might be lost over time during adaptation despite a lack of evidence for strong positive selection pressure on the protein [21] . This is an obvious area for further study in relevant species . In humans , the H1N1 PB1-F2 lineage introduced in 1918 became truncated around 1948–1950 ( Figure 1 ) , losing the C-terminal region that contains the mitochondrial targeting sequence [4] , [22] and promotes inflammation ( this report ) . The currently circulating H3N2 lineage PB1-F2 proteins are still full-length , but have undergone evolutionary changes during adaptation . In this study we demonstrate that PB1-F2 derived from the 1968 pandemic strain can cause lung inflammation , but that from a recently circulating seasonal H3N2 cannot . Analysis of the PB1-F2 C-terminal regions of these strains shows that only 5 amino acid differences are found within the region selected for generating the peptides used to study inflammation ( Figure 1 ) . Two of these changes , K73R and R75H , are within the MTS at positions shown by alanine substitution to be important for mitochondrial targeting [22] . However , both changes are conservative in terms of charge , and the A/Wuhan/359/1995 PB1-F2 shows mitochondrial localization by confocal microscopy ( Figure S2 ) . This suggests alteration of mitochondrial targeting by mutation is not responsible for the change in phenotype . A clear priority is to understand which of these mutations , or what combination of them , is responsible for the diminished capacity of the 1995 H3N2 strain to generate inflammation . This may allow prediction of which avian or swine PB1 gene segment precursors represent a pandemic threat were they to reassort onto a virus crossing the species barrier . Only one other amino acid change , the N66S change in the 1918 PB1-F2 ( Figure 1 ) , has been associated with a gain in virulence [13] . However , an S at position 66 is not necessary for enhancement of inflammatory responses since the other pro-inflammatory PB1-F2 proteins studied here do not possess this residue at that position . One of the hypotheses advanced in our earlier work [10] to explain the immunopathogenic phenotype of the 1918 pandemic strain PB1-F2 was that the previously described cell death phenotype [4] , [11] was responsible for the inflammatory response by killing lung cells resulting in activation of local host defenses . However , the dissociation between cell death and immunopathology demonstrated in this report , in particular the inability of the 1918 PB1-F2 to activate mitochondrial cell death pathways , suggests that the immunostimulatory activity of PB1-F2 is a direct effect . PB1-F2 is expressed early in the course of infection [10] and has a short half-life [4] . This suggests that the trigger for these inflammatory responses is likely to take place early during infection , perhaps by direct recognition of PB1-F2 by pattern recognition receptors . Finding the potential binding partner of PB1-F2 in this pathway is of obvious interest and is a focus of ongoing studies . Although antibody is generated in humans which can recognize PB1-F2 [7] , it is not known whether this can modulate the functional outcomes of PB1-F2 expression and decrease disease . One additional caveat for these studies is that deletion of the PB1-F2 start codon has been shown to affect expression levels of a truncated version of PB1 , the N40 protein [23] . Although N40 over-expression was not shown to alter viral replication in that study , it could have unknown effects in vivo that could complicate interpretation of our experiments with PB1-F2 knock-out viruses . Since its discovery the consensus has been that the PB1-F2 proteins from selected viruses are pro-apoptotic , targeting the mitochondria and inducing pore formation through association with VDAC1 and ANT3 [4] , [11] , [12] , [19] , [24] . ANT3 and VDAC1 molecules are major components of the permeability transition pore of the mitochondrial membrane and enable cytochrome c release from the mitochondria , leading to the activation of the caspase pathway and subsequent cell death . This ionic channel however , becomes activated and induces membrane permeability , following marked oxidative stress and altered mitochondrial calcium levels [25] . Most of the available data surrounding the apoptotic pathway suggest that BAK/BAX mediation of cytochrome c release ( irrespective of whether components of the permeability transition pore complex are involved ) mark apoptotic cell death , whereas cytochrome c release exclusively mediated by VDAC and ANT implies non-apoptotic , mainly necrotic cell death [26] . We show conclusively that , among the viruses tested , only the PB1-F2 C-terminal domain of the PR8 laboratory strain efficiently engages the BAK/BAX pathway . The dependency for presence of BAK/BAX expression on the PR8 induced pore formation in mitochondria defines the role for PR8 PB1-F2 as a BH3 only protein that activates conformational change in the BAX complex within the mitochondria . Whether this complex leads to association with the VDAC/ANT ion channel formation , or activated BAX complex solely causes pore formation and subsequent cytochrome c release , is currently not understood . Analysis of the 5944 predicted amino acid sequences of PB1-F2 proteins available in the Influenza Research Database [27] in the context of these data suggests that the ILV motif from amino acids 68–70 of the PR8 PB1-F2 ORF is likely to be involved in the cell death phenotype ( Figure 1 ) . This is the only area of the C-terminal portion of the PR8 sequence that differs between PR8 and other strains studied herein . The 68I and 69L are present in only 17 of these 5944 sequences , all from human viruses . The 70V is invariably present when the 68I and 69L are present . Fourteen of these viruses circulated between 1933 and 1947 and were of the H1N1 subtype , and only 2 viruses with published PB1-F2 sequences from this era do not share this motif . The other 3 viruses with this motif are A/Victoria/68 ( H3N2 ) , A/TW/3355/97 ( H1N1 ) , and A/Russia:St . Petersburg/8/06 ( H1N1 ) . The 1918 pandemic strain has the sequence TPV from amino acids 68–70; this motif is shared with only 8 other sequences available in the database . Having this unusual motif at this position and sharing the 70V substitution with PR8 might account for the limited ability of the 1918 PB1-F2 to cause necrosis in vitro ( Figure 2 ) , although further study is needed to confirm this hypothesis . The other viruses studied in this report have more common motifs at these three positions , and both F and S are commonly found at position 71 making it an unlikely candidate . Fine mapping of the specific amino acids required to cause the cell death phenotype is required to better determine which viruses might utilize this mechanism , whether this accounts for the limited ability of the 1918 PB1-F2 to also cause some cell death , and how likely reversion to this phenotype by mutation to the necessary sequence might be . However , the current data suggest it is a rare trait in modern seasonal viruses and in the animal reservoir . The emergence of the pandemic H1N1 strain in 2009 has increased the urgency to understand the molecular basis of virulence of influenza viruses . The currently circulating pandemic strain does not encode a full-length PB1-F2 protein , so would not be expected to cause lung inflammation as effectively as previous pandemic strains . In addition , since the PB1-F2 has been shown to be a major virulence factor in the genesis and severity of secondary bacterial infections [10] , we and others have predicted that bacterial pneumonia would be a less frequent complication during this pandemic than was seen in the 20th century pandemics [28] . Indeed , although bacterial super-infections complicated more than 95% of all deaths during the 1918 pandemic [29] , bacterial pneumonia has been found on autopsy in only 29% of fatalities that have been assessed during the current pandemic thus far [30] . This could change if the pandemic H1N1 were to acquire a full length PB1-F2 through reversion of the two stop codons in the PB1-F2 ORF or by reassortment with a virus encoding a full-length PB1-F2 . Were reversion to occur , the full length PB1-F2 of the pandemic H1N1 more closely resembles the 1995 H3N2 strain than the 1968 pandemic precursor , having predicted residues 73R , 75H and 79Q ( Figure 1 ) . It also lacks the PR8 specific sequences seen at amino acids 68–70 . Based on this analysis and the data presented in this study , it is unlikely that reversion of the stop codons or reassortment of the PB1 gene segment with currently circulating seasonal influenza strains would provide the pandemic virus with a functional , pro-inflammatory PB1-F2 . Indeed , data published while this manuscript was in revision indicate that genetic reversion of the stop codons of the pandemic H1N1 strains to produce full length PB1-F2 has only minimal effects on virulence and support for secondary bacterial infections [31] . However , the less likely scenario of reassortment with an avian or swine virus with a fully functional PB1-F2 remains possible and could herald enhanced virulence and increased incidence and severity of secondary bacterial infections .
Madin-Darby canine kidney ( MDCK ) cells were grown in Minimal Essential Medium ( MEM ) supplemented with 10% heat inactivated fetal bovine serum ( FBS ) , 2mM glutamine and antibiotics . A549 cells were grown in F12K medium supplemented with 10% FBS , 2mM glutamine and antibiotics . Immortalized MEFS were produced by transfecting primary , unpassaged MEFs with SV40 genomic DNA using Lipofectamine 2000 ( standard conditions , Invitrogen ) and selected by colony formation and growth . SV40 immortalized wild type and bak−/−bax−/− . 293T , MEF and BAX−/−BAK−/−MEF cells were grown in DMEM medium supplemented with 10% FBS and antibiotics . Cell cultures were maintained at 37°C in a 5% CO2 incubator . Cells were washed once with phosphate buffered saline ( PBS ) , infected with the amount of virus indicated by indicated multiplicity of infection ( MOI ) and further incubated as described previously [10] . A set of plasmids were generated on the pHW2000 backbone as described [15] , [32] , encoding for the PB1 gene segment of PR8 , A/Vietnam/1203/04 ( H5N1 ) or A/Wuhan/359/95 ( H3N2 ) . In each of these backgrounds , the open reading frame for PB1-F2 was disrupted by altering the start codon ( T120C mutation by PB1 numbering ) so translation will not initiate and inserting a stop codon after 11 residues ( C153G ) to insure a complete 1 knock-out [9] , [10] . The PR8 PB1-F2 sequence was further altered by QuikChange site-directed mutagenesis ( Stratagene ) as described [10] , [15] so that the protein expressed was identical to either the A/Brevig Mission/1/18 ( H1N1; 1918 PB1-F2 ) or A/Beijing/11/56 ( H1N1; Beij PB1-F2 ) virus . In no case did these mutations in the PB1-F2 reading frame cause non-synonymous mutations in the PB1 reading frame . The N40 start codon [23] was intact in all plasmids . These eight PB1 plasmids were then incorporated into a corresponding set of eight viruses on a 7 gene PR8 backbone ( 7∶1 ) by reverse genetics as described [15] . Resulting viruses were rescued by one passage in MDCK cells then propagated a single time in eggs for stocks to be used in these studies . All viruses were fully sequenced to insure no inadvertent mutations occurred during virus rescue and propagation , then characterized in tissue culture and eggs as previously described [33] . Expression or lack of expression of PB1-F2 protein was confirmed for all viruses through use of confocal microscopy ( Figure S2 ) . Using the predicted amino acid sequences of the PB1-F2 proteins from PR8 , A/Brevig Mission/1/1918 , 1/Singapore/1/1957 , A/Hong Kong/1/1968 , A/Wuhan/359/1995 and A/Vietnam/1203/2004 , peptides from the C-terminal end were synthesized as described [10] . The region covered began at amino acid 61 and extended to the termination of the protein ( by PR8 sequence ) at amino acid 87 ( Figure 1 ) . An additional N-terminal peptide was synthesized from the PR8 sequence as a positive control ( MGQEQDTPWILSTGHISTQK ) as described [10] . Peptides were either synthesized on an Apex 396 multiple organic synthesizer ( Aaaptec , Luisville , KY ) or purchased from GenScript Corporation ( Piscataway , NJ ) . Immediately prior to use in animals or cell culture , peptides were suspended in PBS at a concentration of 1mM . Peptide exposure assays were conducted in 96 well round bottom tissue culture dishes , whilst virus infection assays were conducted in 24 well plates . Cells were seeded at a density of 1×106 cells/mL for 30min ( peptide assays ) or overnight ( virus assays ) in infection media ( cell growth media with BSA substituted for FCS ) . Cells were then exposed to 50uM ( final concentration ) of peptide for 1h , or infected with virus at the MOI indicated for periods ranging from 2–12h . Cells from the supernatant and monolayers were then harvested , washed and stained with APC labeled Annexin and Propidium Iodide ( PI ) ( Becton Dickinson , San Jose , CA ) for 20min . After a final wash step , cells were resuspended in 100uL FACs wash buffer ( PBS containing 3% BSA and 0 . 01% sodium azide ) and analysed on the FACs Calibur ( BD Biosciences ) and BD CellQuest Pro software ( version 5 . 2 . 1 , BD Biosciences ) . Necrotic cellular events were defined as Annexin-V+ and PI+ , whilst apoptotic events were Annexin-V+ only . Viable cells were considered as neither Annexin-V nor PI positive . Heavy membrane fractions ( referred to as mitochondria ) were purified from 10 grams of fresh liver ( duck , ferret and mouse ) or 20 chicken embryos day 14 , using dounce homogenization and differential centrifugation in trehalose mitochondrial isolation buffer ( TMIB: 300 mM trehalose , 10 mM HEPES-KOH pH 7 . 4 , 10 mM KCl , 1 mM EDTA , 1 mM EGTA , 0 . 1% BSA ) . For MOMP assays , mitochondria were incubated in TMIB supplemented to 110 mM KCl ( trehalose mitochondrial assay buffer , TMAB ) , ±caspase-8 cleaved mouse BID ( R&D Systems ) or peptides ( final concentrations are indicated in the text and figure legends ) for 60 minutes at 37°C . Reactions were then fractionated into supernatant and pellet by centrifugation at 5 , 500×g for 5 minutes and analyzed by SDS-PAGE and western blot with anti-cytochrome c . Supernatant and pellet fractions were separated using the Criterion XT 4–12% gel system ( Bio-Rad ) with 1X MOPS buffer at 150 V . Proteins were transferred to nitrocellulose by standard western conditions , blocked in 5% milk/TBST and the primary antibody ( in blocking buffer: cytochrome c 1∶2000 , clone 7H8 . 2C12 Pharmingen ) was incubated overnight at 4°C . The secondary antibody ( 1∶5000 in blocking buffer ) was incubated at 25°C for 1 hour before standard enhanced chemiluminescence detection . For MOMP assays , all peptides were resuspended in anhydrous DMSO ( 5 mM stock ) in a N2 environment , aliquoted , stored at −80°C and thawed only once . To obtain BAK- and BAX-deficient mitochondria , heavy membrane fractions were isolated from the livers of polydIdC-treated MxCre bak −/− bax f/− mice . Where indicated , total cytochrome c was determined by a sample containing mitochondria solubilized in 0 . 5% CHAPS . Six- to eight week old female Balb/c mice ( Jackson Laboratory , Bar Harbor , ME ) were maintained in a Biosafety Level 2 facility in the Animal Resource Center at SJCRH . All experimental procedures were done under general anesthesia with inhaled isoflurane 2 . 5% ( Baxter Healthcare Corporation , Deerfield , IL ) . Infectious agents and peptides were diluted in sterile PBS and administered intranasally in a volume of 100uL ( 50uL per nare ) to anesthetized mice held in an upright position . Groups of six to ten mice were weighed and followed at least daily for illness and mortality . The infectious dose for all experiments was 100 TCID50 , which with these stocks caused 10–15% weight loss and no mortality . All experimental procedures were approved by the Animal Care and Use Committee at SJCRH under relevant institutional and American Veterinary Medical Association guidelines and were performed in a Biosafety level 2 facility that is accredited by AALAAS . Following euthanasia by CO2 inhalation , the trachea was exposed and cannulated with a 21 gauge plastic catheter ( BD Insyte , Becton Dickinson , Sandy , UT ) . Lungs were lavaged thrice with 1mL of cold , sterile PBS . Flow cytometry ( FACs Calibur , Becton Dickinson , San Jose , CA ) was performed and the number of white blood cells ( WBC ) per mL determined ( Hemavet 3700 , Drew Scientific , Dallas , TX ) on the BALF suspension after red blood cell depletion using Red Cell Lysis Solution ( Sigma ) . Briefly cells were stained with 1uL/106cells Gr1 ( FITC ) /F480 ( PER-CP ) for 20 min , washed then resuspended in 100uL FACS wash buffer . The proportions of Neutrophils ( Gr1+ within the cellular region ) , Macrophages ( F480+ within the cellular region ) were assessed as a proportion of cellular events analyzed by flow cytometry as related to the number of WBC/mL . Lungs were removed immediately following euthanasia via CO2 inhalation , sufflated and fixed in 10% neutral buffered formalin overnight . The lungs were processed routinely , embedded in paraffin and sectioned at 5um . For histopathologic examination , slides were stained with hematoxylin and eosin and examined microscopically as previously described [10] . Production of myeloperoxidase ( MPO ) by affected tissue was detected via immunohistochemical staining by the Veterinary Pathology Core Laboratory at SJCRH . This was done on a LabVision autostainer at room temperature using tris-buffered saline rinses between steps . Endogenous peroxidase activity was blocked by incubation with 3% H2O2 ( Humco , Texarkana , TX ) for 5 minutes . Slides were incubated with rabbit anti-human myeloperoxidase ( DAKO , Carpinteria , CA , cat # A0398 ) at 1∶1500 for 30 minutes followed by incubation with horse-radish peroxidase-conjugated Rabbit-on-Rodent Polymer ( BioCare Medical , Concord , CA , cat # RMR622 ) for 30 minutes . Slides were incubated for 5 minutes with the chromagen DAB ( 3 , 3′ diaminobenzidine tetrahydrochloride , cat # K3466 , DAKO ) . Hematoxylin ( ThermoShandon , TA-125-MH ) was used as counterstain . Grading and description of pathology were performed by an experienced veterinary pathologist ( KLB ) blinded to the composition of the groups using methods previously described [33] . Comparison of cell death and cellularity of BAL fluid between groups was done using analysis of variance ( ANOVA ) for multiple comparisons and the Student's t-test for matched , single comparisons . A p-value of <0 . 05 was considered significant for these comparisons . SigmaStat for Windows ( SysStat Software , Inc . , V 3 . 11 ) was utilized for all statistical analyses .
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There is presently great interest in understanding how influenza viruses cause disease . In this paper , we explore the role of the influenza virus PB1-F2 protein in disease . We show that the ability of the protein to cause cell death is mediated through a mitochondrial death pathway controlled by proteins called BAX or BAK . However , this function of the protein only seems to be relevant to a restricted set of viruses and not past pandemic strains . Instead , the ability to generate inflammation in the lung proves to be a common trait of all past pandemic strains as well as the H5N1 highly pathogenic avian influenza strains which remain a significant pandemic threat . It appears likely that this pro-inflammatory phenotype is a characteristic of viruses emerging from the avian reservoir and is therefore important for new strains that cross the species barrier and establish themselves in humans . During circulation and adaptation in the mammalian lung , this function is typically lost . Of note , the novel 2009 H1N1 pandemic strain does not express a full-length PB1-F2 . Were it to acquire a fully functional , inflammatory PB1-F2 through reassortment , this could herald greatly enhanced disease potential .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"infectious",
"diseases/viral",
"infections",
"virology/virulence",
"factors",
"and",
"mechanisms"
] |
2010
|
PB1-F2 Proteins from H5N1 and 20th Century Pandemic Influenza Viruses Cause Immunopathology
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Rift Valley fever virus ( RVFV ) is a mosquito-borne pathogen that affects domesticated ruminants and occasionally humans . Classical RVF vaccines are based on formalin-inactivated virus or the live-attenuated Smithburn strain . The inactivated vaccine is highly safe but requires multiple administrations and yearly re-vaccinations . Although the Smithburn vaccine provides solid protection after a single vaccination , this vaccine is not safe for pregnant animals . An alternative live-attenuated vaccine , named Clone 13 , carries a large natural deletion in the NSs gene which encodes the major virulence factor of the virus . The Clone 13 vaccine was previously shown to be safe for young lambs and calves . Moreover , a study in pregnant ewes suggested that the vaccine could also be applied safely during gestation . To anticipate on a possible future incursion of RVFV in Europe , we have evaluated the safety of Clone 13 for young lambs and pregnant ewes . In line with the guidelines from the World Organisation for Animal health ( Office International des Epizooties , OIE ) and regulations of the European Pharmacopeia ( EP ) , these studies were performed with an overdose . Our studies with lambs showed that Clone 13 dissemination within vaccinated animals is very limited . Moreover , the Clone 13 vaccine virus was not shed nor spread to in-contact sentinels and did not revert to virulence upon animal-to-animal passage . Importantly , a large experiment with pregnant ewes demonstrated that the Clone 13 virus is able to spread to the fetus , resulting in malformations and stillbirths . Altogether , our results suggest that Clone 13 can be applied safely in lambs , but that caution should be taken when Clone 13 is used in pregnant animals , particularly during the first trimester of gestation .
Rift Valley fever ( RVF ) is a peracute or acute zoonotic disease of ruminants caused by the mosquito-borne RVF virus ( RVFV ) , which belongs to the genus Phlebovirus within the family Bunyaviridae . Outbreaks of the disease are typically reported during climatic conditions that favour the breeding of mosquito vectors . During the first decades following its identification on a farm in the Great Rift Valley in Kenia in 1930 , the virus was confined to the African continent . More recently , outbreaks have been reported on the Arabian Peninsula [1] , Madagascar [2] and the Archipelago of Comoros and Mayotte in the Indian Ocean [3] . There is considerable variation in the susceptibility to RVFV between different animal species , with sheep , goats and cattle being the most susceptible . In these species , the disease is characterized by abortion , fetal malformation , neonatal mortality and liver damage . Humans can become infected through contact with infected animal material or mosquito bite [4] . In humans , infections are usually unapparent or associated with flu-like symptoms that resolve without treatment . However , patients may develop severe complications such as haemorrhagic fever , meningoencephalitis and retinitis [5 , 6] . In a minority of patients ( 0 . 5–2% ) , the outcome of a RVFV infection is fatal [7] . Both inactivated and modified live-attenuated vaccines have been developed to control RVF epizootics . Inactivated vaccines require multiple doses in order to provide protection , whereas live vaccines generally require one dose to provide long-term immunity . In 1949 , Smithburn and co-workers developed the first veterinary RVF vaccine by serial intracerebral passage of RVFV in mice [8] . The resulting Smithburn virus is a highly effective vaccine but can still cause liver damage [9] and is able to transmit to the fetus [10] . In the early 80’s Caplen and co-workers developed another live-attenuated vaccine , named MP-12 [11] . This vaccine virus was created by passage of the wildtype virus in the presence of the mutagen 5-fluorouracil , resulting in the accumulation of attenuating mutations on each of the three genome segments [12] . Although MP-12 vaccination results in low-level viremia , the vaccine was shown to be safe for cattle and sheep , even when applied during the second or third trimester of gestation [13–16] . In another study , however , MP-12 vaccination of ewes in the first and second trimester of gestation was associated with teratogenic effects [17] . In more recent studies in which 4 gestating ewes were vaccinated with either MP-12 or a recombinant derivative named arMP-12 , no untoward effects were noted in the ewes , although 1 out of 4 ewes in each experiment was found to carry a dead fetus at the end of the experiment [13] . Since no MP-12 RNA was detected in these fetuses , the causes of death remained unknown . Altogether , these findings call for additional studies to further address the safety of MP-12 and recombinant derivatives . Considering the remaining concerns about the safety of the Smithburn and MP-12 vaccines , the isolation of the naturally attenuated Clone 13 virus is considered one of the most important breakthroughs in RVF vaccinology [18] . The Clone 13 virus , isolated from a non-fatal human case in the Central African Republic , was shown to lack 69% of the gene encoding the nonstructural protein of the S genome segment ( NSs ) . Extensive studies have demonstrated that the NSs protein counteracts host innate immune responses at different levels , e . g . by suppression of type-I interferon responses , and is thereby considered the major virulence factor [19–22] . The ability of the Clone 13 virus to induce protective immunity in lambs was recently confirmed in a vaccination-challenge study [23] and studies with calves and gestating ewes have supported the safety of Clone 13 [24–27] . In 2010 , the Onderstepoort Biological Products ( South Africa ) company obtained a marketing authorization for Clone 13 and the vaccine was also applied in Botswana , Namibia , Zambia and Mozambique [28] . The recent introductions of two other arboviruses into Europe , Bluetongue virus serotype 8 [29–31] and Schmallenberg virus [32] , have increased the concerns about potential incursions of RVFV . European-breed domesticated ruminants were shown to be highly susceptible to RVFV and several mosquito species that are associated with RVFV transmission in endemic areas are present in Europe . At this moment , several different vaccines , including Clone 13 , are being considered as emergency vaccines for applications outside current endemic areas [28 , 33] . Here , we report the results of extensive safety studies performed with Clone 13 in lambs and pregnant ewes in line with guidelines from the World Organisation for Animal health ( Office International des Epizooties , OIE ) [34] and regulations of the European Directorate for the Quality of Medicines and Health Care ( European Pharmacopeia , EP ) [35] . In line with these guidelines and regulations , the studies were performed with an overdose . Two studies addressed characteristics in terms of dissemination , shedding , spreading ( DSS study ) , and one study evaluated the potential of Clone 13 to revert to virulence ( RTV study ) . Furthermore , we evaluate the ability of Clone 13 to cross the placental barrier by inoculating ewes at 50 or 120 days of gestation . Our results suggest that the Clone 13 vaccine is safe for young lambs , even after multiple administrations of an overdose via different inoculation routes , and does not spread to the environment or contact animals . Remarkably , inoculation during gestation resulted in vertical transmission of the virus to the fetus , which was associated with malformed lambs , stillbirths and precolostral antibodies . Untoward events were most prominent in ewes inoculated during the first trimester of gestation .
All animal studies were approved by the Animal Ethics Committee of MSD Animal Health Boxmeer under permit number RVF 13 . 059 and were conducted in accordance with the Dutch Law on Animal Experiments . The Clone 13 virus [18] was kindly provided by Dr . M . Bouloy ( Institut Pasteur , France ) and was amplified in Vero cells , grown in 490 cm2 roller bottles . A total of 4 trials were performed with sheep . Trial 1 focussed on dissemination , shedding and spreading ( DSS ) of Clone 13 , trial 2 on the risk of reversion to virulence ( RTV ) , and trials 3 and 4 on safety of the virus for young lambs and pregnant ewes , respectively . Sheep were Texel/Swifter crossbreds and purchased in The Netherlands . Animals were free from RVFV and RVFV-specific antibodies at the start of the studies . Work with live virus was performed by trained personnel in biocontainment facilities of MSD Animal Health ( Boxmeer and Stevensbeek , The Netherlands ) following appropriate biosafety procedures . The virus titres in the different vaccine preparations as well as the inoculation routes and vaccine volumes used in each study are presented in Table 1 . In line with the regulations from the OIE and EP , all studies were performed with an overdose . This overdose was set at 107 TCID50 as we anticipated that the maximum virus titre likely to be contained in 1 dose of the vaccine is 106 TCID50 . All treated and control animals were observed for local and systemic reactions and rectal body temperatures were recorded daily . Blood samples were collected at pre-set time points and tested for viremia and RVFV-specific antibodies . Thirty-two 8–10 week-old lambs were randomly divided into two groups of 14 animals . On day 0 , lambs of group one were inoculated via the subcutaneous ( SC ) and intradermal ( ID ) routes with Clone 13 . Animals from group 2 were left untreated and served as sentinel animals . Between days post inoculation ( DPI ) 2–14 , two animals from each group were euthanized and necropsied every other day . The following samples were collected at necropsy: saliva , nasal mucus , lacrimal fluid , urine and faeces , gonades , kidney , adrenal gland , spleen , lymph node ( Ln ) ileocaecalis , small and large intestines , bladder , pancreas , liver , lung , thymus , heart muscle , injection sites , M . tripceps brachii , Ln prescapularis left and right , salivary gland and brain . The samples were evaluated for the presence of Clone 13 RNA using reverse transcriptase quantitative PCR ( RT-qPCR ) and virus isolation as described below . A schematic overview of the experiment is presented in Fig 1 . A reversion to virulence study was performed with a total of fourteen 7–9 week old lambs . Two lambs were inoculated via SC and ID routes with Clone 13 ( Table 1 ) . Blood samples were subsequently collected at 0 , 1 , 2 and 3 days post inoculation and prescapular lymph nodes were collected at 7 days post inoculation upon necropsy . The plasma and prescapular lymph node homogenate samples with the highest virus content , as determined by RT-qPCR , were used to inoculate 2 naïve animals ( first passage ) . Inoculation routes , sampling and testing regime of passage 1 was identical to passage 0 . Finally , the passage was repeated with another group of 10 lambs . A schematic overview of the experiment is presented in Fig 2 . Twenty 5-week-old lambs were randomly divided into two groups of 10 animals . Lambs of group 1 were inoculated with an overdose of Clone 13 by the SC , ID , intranasal ( IN ) and intraocular ( IO ) routes ( Table 1 ) . Inoculations were repeated two weeks later . Lambs of group 2 were left untreated . In addition to general clinical examination of the animals , the SC and ID injection sites were palpated to evaluate local reactions until two weeks after the second vaccination . Twelve approximately 50 days pregnant ewes ( group 1 ) and another twelve approximately 120 days pregnant ewes ( group 2 ) were inoculated with a high dose of Clone 13 via the SC and ID routes ( Table 1 ) . Two days post inoculation a blood sample was taken . Animals were subsequently monitored daily for general health and signs of abortion . Directly following natural delivery , precolostrum blood samples were taken from lambs borne alive and necropsy was performed on stillborn lambs . Lambs were euthanized at the end of the study when they were approximately two weeks old . All lambs , stillborn or alive , were examined macroscopically and histologically . Samples from brain , kidney , lung , liver , spleen and heart were tested for the presence of Clone 13 RNA by RT-qPCR and virus isolation . A schematic overview of the experiment is presented in Fig 3 . Viral RNA was isolated from EDTA blood samples and organ homogenates using the Roche MagNA Pure 96 ( MP96 ) automated system for nucleic acid purification . The presence of Clone 13 RNA was assessed by Reverse-Transcriptase quantitative Polymerase Chain Reaction ( RT-qPCR ) using the Invitrogen SuperScript III Platinum One-Step qRT-PCR Kit ( Invitrogen , 5791 Van Allen Way , Carlsbad CA , 92008 , USA ) . Primers , probes and cycling conditions were applied as described previously [36] . Cq-values and RNA copy numbers were calculated by the CFX Manager Software ( Bio-Rad , 1000 Alfred Nobel Drive , Hercules CA , 94547 , USA ) . Samples that tested positive for Clone 13 RNA were used for virus titration on Vero cells . When virus was not detected , larger volumes of the inocula were incubated with Vero cells . The latter method increases the sensitivity of the virus isolation procedure , but does not allow the determination of virus titers . Isolation of Clone 13 was confirmed by immunofluorescence assays using a RVFV-specific monoclonal antibody ( 4D4 , kindly provided by Dr . M . Bouloy , Institute Pasteur , France ) . RVFV-specific antibodies in serum samples were detected by a commercial N-protein based ELISA kit ( ID Screen Rift Valley Fever Competition Multi-species ELISA kit , IDvet , Montpellier , France ) which was used according to the manufacturer’s instructions . Tissue samples for immunohistochemistry ( IHC ) were fixed in formaline ( 4% buffered formaldehyde ) and embedded in paraffin . Sections of 3 . 5 μm were mounted on silan coated slides and subsequently deparaffinised and dehydrated . Haematoxylin & Eosin ( HE ) staining was performed according to standard procedures . For IHC , sections were first incubated with peroxidase blocking solution ( 0 . 3% H2O2 in Methanol ) for 5 min . A rabbit anti-myelin antibody ( Myelin Basic Protein Ab-1 , Thermo Scientific ) was used as a primary antibody ( 1:200 in bovine serum albumin ( 1% ) in TBS for 30 min ) and a horseradish peroxidase labelled goat anti-rabbit antibody was used as the secondary antibody . Antibody binding was subsequently visualized using diaminobenzidine chromogen substrate ( Envision System–HRP ( DAP ) , Dako ) . Between incubations , sections were washed for 5 minutes in Tris-buffered saline ( TBS ) and cell nuclei were counterstained with Mayer’s haematoxylin for 10 seconds .
To evaluate the extent of dissemination of Clone 13 within individual animals and to evaluate the potential ability of Clone 13 to spread to the environment and sentinel animals we performed a DSS study with lambs . Fourteen lambs were inoculated with Clone 13 and a group of equal size functioned as sentinels . Every other day , two inoculated lambs and two sentinel animals were euthanized and necropsied ( Fig 1 ) . No adverse reactions to the Clone 13 inoculation , such as reduced appetite , depression or elevated temperatures were observed and no Clone 13 RNA was detected in saliva , nasal mucus , lacrimal fluid , urine or faeces samples . Clone 13 RNA was detected in all but one of the plasma samples collected at dpi 2 ( Table 2 ) and at the SC and ID injection sites . In addition , Clone 13 RNA was found in the draining lymph nodes of these animals . Notably , Clone 13 RNA was also found in two spleen samples and two liver samples albeit at very low amounts . Virus was isolated from 6 plasma samples collected at dpi 2 and 4 lymph node samples collected upon necropsy between dpi 2 and 6 ( Table 2 , indicated in bold ) . No infectious virus could be recovered from samples obtained >6 dpi . As expected , all sentinel animals remained free of Clone 13 RNA and did not develop RVFV-specific antibodies . Altogether , these results show that dissemination of RVFV Clone 13 was very limited and was largely restricted to the injection sites and the draining lymph nodes . Moreover , the virus was not secreted or excreted from inoculated animals and did not spread to sentinels . To evaluate the potential of Clone 13 to gain virulence upon passage , a reversion to virulence study was performed . Two lambs were inoculated with Clone 13 via the SC and ID routes . As expected , Clone 13-specific RNA was detected in plasma samples collected one and two days post inoculation . On dpi 1 , the first lamb contained 103 . 7 RNA copies/ml plasma whereas the second lamb contained 103 . 9 RNA copies/ml plasma . On dpi 2 , viral RNA was only detected in plasma of the second lamb , with a titer of 103 . 3 RNA copies/ml . In addition , Clone 13-specific RNA was detected in the left ( lamb 1: 105 . 7 , lamb 2: 105 . 8 RNA copies/ml ) and right ( lamb 1: 105 . 7 and lamb 2: 105 . 5 RNA copies/ml ) prescapular lymph nodes collected during necropsy , which was performed 7 days post inoculation . To passage the virus to naïve animals , an inoculum was prepared of a plasma- and lymph node homogenate sample that contained the highest level of Clone 13 RNA . This sample was used to inoculate two lambs via SC and ID routes . In contrast to the plasma and lymph node samples obtained from the Clone 13 inoculated lambs , no Clone 13-specific RNA was detected in similar samples of passage 1 animals . The latter was repeated with another group of 10 lambs , with the same outcome ( Fig 2 ) . These results indicate that the risk of reversion to virulence of Clone 13 under natural conditions is very low . The results of the DSS and RTV studies suggest that Clone 13 can be safely applied in lambs when applied via SC or ID inoculation routes . To further address the safety of Clone 13 , we examined whether the vaccine is safe when applied at an overdose and after application of the virus via other routes ( Table 1 ) . As described in the M&M section , 10 lambs were inoculated with an overdose of Clone 13 via 4 different inoculation routes and 10 lambs were left untreated . Apart from elevated body temperatures in both groups on day 0 and 1 , which was probably the result of mild stress due to handling , subsequent temperature measurements were within the physiological range . None of the lambs from either group displayed clinical signs during the course of the experiment . With a few exceptions , the injection sites were not visible and could not be palpated . Altogether these results indicate that Clone 13 is highly safe in lambs , even when a high dose is administered via four different inoculation routes . The studies described above confirm that Clone 13 can be safely applied in lambs . However , the Clone 13 vaccine should preferably also be safe for pregnant animals . Safety of Clone 13 for pregnant animals was evaluated in a large trial with ewes at 50 or 120 days of gestation . As expected and similar to the lamb experiments , almost all blood samples ( 22 out of 24 ) were tested positive for RVFV RNA two days post Clone 13 inoculation . RNA levels were however too low to calculate copy numbers . With the exception of one , possibly two ewes that were inoculated at 120 days after mating , all ewes contained RVFV-specific antibodies in serum samples obtained two weeks post inoculation ( Fig 3 ) . None of the ewes developed fever or clinical signs throughout the course of the study . One ewe in the group vaccinated at approximately 50 days after mating showed signs of imminent abortion at 76 days after inoculation . This ewe was euthanized for necropsy , which revealed that the foetus had the umbilical cord strangled around its legs , probably caused by the malformation of a foreleg , and did not contain brain tissue . In the remaining ewes , pregnancy continued until the anticipated date of birth . Interestingly , the number of stillborns and of malformed lambs was much higher than would be anticipated for a healthy herd ( Fig 3 ) . The proportion of stillborn lambs was 30% for the group inoculated at approximately 50 days after mating ( including the foetus that was about to be aborted ) and 11% for the group inoculated at approximately 120 days after mating . Necropsy was performed on two ewes that did not deliver at the anticipated time point . Based on the sizes and the general appearances and maturation of the foetuses it was concluded that the conception dates of these ewes were not correctly calculated . One lamb born from an ewe inoculated with Clone 13 at 50 days after mating showed typical signs of dysfunction of the central nervous system such as ataxic movements and disorientation . To prevent unnecessary suffering , the animal was euthanized . Another lamb in the same group had to be euthanized as well because of its overall poor condition . The average number of lambs per ewe was 1 . 7 for the group inoculated at 50 days after mating and 2 . 3 for the group inoculated at 120 days after mating . No malformations were observed in lambs of ewes inoculated with Clone 13 at 120 days after mating . In contrast , as many as 7 lambs of 5 different ewes inoculated with Clone 13 at 50 days after mating showed malformations of the central nervous system such as hydranencephaly , hypoplasia of cerebrum , cerebellum and spinal cord and/or malformations of the musculoskeletal system such as; brachygnathia , arthrogryposis and scoliosis ( Fig 4A and 4B ) . Histopathological examination of the spinal cord of these animals revealed hypoplasia of the grey matter , sometimes associated with vacuolation whilst in the cerebrum often accompanied with , edema , vacuolation ( spongiosis ) and liquefactive necrosis ( Fig 4C and 4D ) . Analysis of the lamb organs and plasma samples revealed that ten lambs were positive for Clone 13 RNA in the blood or one or more organ samples , six in the 50 days group and four in the 120 days group ( Fig 3 ) . Importantly , several precolostrum serum samples , one in the 50 days group and six in the 120 days group , tested positive for RVFV-specific antibodies ( Fig 3 ) .
Here , we report the results of studies on the safety of the Clone 13 vaccine virus for lambs , pregnant ewes and the ovine fetus . The ability of Clone 13 to disseminate , shed and spread to the environment was investigated as well as its ability to revert to virulence . Additionally , the safety of Clone 13 when applied at 50 or 120 days gestation was evaluated . The safety studies addressed different administration routes and repeated doses and were performed with an overdose as prescribed by the OIE and the EP . The combined results of all four studies demonstrate that Clone 13 is very well tolerated and safe for young lambs . However , inoculation of pregnant ewes was associated with foetal infections , malformations and stillbirths . The observation that Clone 13 does not induce untoward effects in young lambs supports the notion that the vaccine can be applied safely in these animals . The dissemination , shedding and spreading ( DSS ) and reversion to virulence ( RTV ) studies also indicate that Clone 13 has a low risk of spreading from vaccinated animals . Viremia was very short-lived and of very low level , suggesting that the risk of Clone 13 transmission by mosquito vectors is negligible . According to OIE guidelines [34] and regulations of the European Directorate for the Quality of Medicines and Health Care [35] , the potential of a live-attenuated vaccine virus to revert to virulence has to be studied even if the virus does not spread from animal to animal under natural conditions . Five animal-to-animal passages have to be performed in the most susceptible category of animals , following the route of vaccination that provides the virus with the most optimal conditions to revert to virulence . The Clone 13 virus was applied via the SC and ID routes . In the DSS study , the highest levels of viral RNA were found in plasma samples collected two days after inoculation and in prescapular lymph nodes taken between four and eight days after infection . Therefore , in the RTV study , blood samples were taken one , two and three days post infection and prescapular lymph nodes were collected seven days post infection . Although the Clone 13 virus could not be isolated from the collected samples , blood samples and lymph node homogenates were found to contain significant amounts of viral RNA . The samples with the highest levels of viral RNA were used to inoculate naïve animals . Analyses of similar samples subsequently collected from these animals did not reveal Clone 13 RNA , demonstrating that Clone 13 cannot be passaged from animal to animal . The inability to passage Clone-13 between young lambs strongly suggests that the risk of reversion to virulence of Clone 13 under natural conditions is negligible . To assess the safety of Clone 13 for highly susceptible target animals , a study was conducted with very young lambs ( five weeks old ) , which generally develop severe disease after infection with wildtype RVFV . Inoculation of these lambs with Clone 13 did not result in adverse systemic or local reactions . These results support the notion that the Clone 13 vaccine can be safely applied in young lambs . Although young lambs are highly susceptible to severe disease , the ovine fetus is the most susceptible . To investigate the ability of Clone 13 to cross the placental barrier , a large study was performed with ewes either at 50 or 120 days of gestation . As expected , none of the 24 pregnant ewes developed acute adverse reactions after administration of the Clone 13 vaccine . Remarkably , however , eight lambs born from ewes vaccinated at 50 days after mating showed malformations of the central nervous system , or the skeletal system , or both . These malformations are consistent with the consequences of intra-uterine virus infections and have been reported during RVF outbreaks in the field [37] and after vaccination with the live-attenuated RVF vaccine MP-12 [17] . Similar malformations may also occur after infection of pregnant ewes with Bluetongue virus , Border disease virus and Schmallenberg virus [38] , however , these pathogens were all excluded as potential causes of the malformations observed in the present study , as no antibodies or viral RNA associated with these pathogens were detected . In addition , transplacental infection with Clone 13 was evident in 7 lambs by detection of RVFV-specific RNA in organ homogenates or blood samples and by detection of RVFV-specific antibodies in precolostral serum samples ( Fig 3 ) . Taken together , transplacental infection of Clone 13 took place in at least 6 out of the 12 ewes vaccinated approximately 50 days after mating and in 7 out of 12 ewes in the group vaccinated during the third trimester of pregnancy . The results of the pregnant ewe study seem to contradict the results reported by Dungu and colleagues [25] who did not report any negative effect on the outcome of pregnancy after inoculation of Clone 13 in pregnant ewes , as well as the experiences from field studies with Clone 13 ( 26 , 27 ) . The Clone 13 virus used in these studies originates from a master seed generously provided by Pasteur Institute ( France ) . Therefore , a number of factors alternative to passage history , or combination thereof , may explain the apparent discrepancy between the study findings . These include the difference in numbers of animals used , the difference in breed of sheep and the virus dose . The most plausible explanation for the differences in the study results is the virus dose , which was approximately 10 times higher in the study presented here . The previous studies with Clone 13 [25–27] as well as those with other live-attenuated RVF vaccines [39 , 40] were combined safety and efficacy studies , therefore animals were inoculated with a recommended dose , while the present study was designed as a dedicated safety study . In accordance with the guidelines of EU and OIE regulations , an overdose of Clone 13 was applied in the present work . In addition to the functions of NSs in counteracting host innate immune responses , the NSs protein was also reported to mediate chromosome cohesion and segregation effects , suggested to be responsible , at least partially , for RVFV-mediated teratogenesis [41] . The finding that teratogenesis also occurs in the absence of NSs was therefore unanticipated . Further studies are warranted to elucidate the underlying mechanisms of Clone 13-mediated teratogenesis . Based on the results obtained after overdose and repeated dose vaccination of young lambs , it can be concluded that Clone 13 has very favourable properties for use in lambs i . e . the virus does not cause acute local or systemic reactions , is not shed and does not spread to other animals and does not revert to virulence . However , caution should be taken when the vaccine is used in pregnant animals , especially during the first trimester of pregnancy , as Clone 13 may spread to the fetus and cause malformations and stillbirths . Our findings underline the value of safety experiments that comply with OIE guidelines and regulations described in the EP .
|
Rift Valley fever virus is a mosquito-borne virus that causes severe disease in young ruminants and occasionally humans . The virus is largely confined to the African continent , but mosquito vectors associated with transmission of RVFV are globally prevalent . There are no vaccines fully registered for use outside endemic areas . Clone 13 is a highly effective vaccine virus that was previously reported to be safe for cattle and sheep . We here report the results of safety studies performed with young lambs and pregnant ewes according to the guidelines from the OIE and regulations of the EP . In line with these guidelines and regulations , the studies were performed with an overdose . Our results confirm that Clone 13 can be safely applied in young lambs and show that the virus does not spread to the environment or contact lambs and does not revert to virulence upon animal-to-animal passage . However , inoculation of gestating ewes resulted in transmission of Clone 13 to the fetus and was associated with malformations and stillbirths .
|
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2016
|
Rift Valley Fever Vaccine Virus Clone 13 Is Able to Cross the Ovine Placental Barrier Associated with Foetal Infections, Malformations, and Stillbirths
|
Changes in synaptic efficacies need to be long-lasting in order to serve as a substrate for memory . Experimentally , synaptic plasticity exhibits phases covering the induction of long-term potentiation and depression ( LTP/LTD ) during the early phase of synaptic plasticity , the setting of synaptic tags , a trigger process for protein synthesis , and a slow transition leading to synaptic consolidation during the late phase of synaptic plasticity . We present a mathematical model that describes these different phases of synaptic plasticity . The model explains a large body of experimental data on synaptic tagging and capture , cross-tagging , and the late phases of LTP and LTD . Moreover , the model accounts for the dependence of LTP and LTD induction on voltage and presynaptic stimulation frequency . The stabilization of potentiated synapses during the transition from early to late LTP occurs by protein synthesis dynamics that are shared by groups of synapses . The functional consequence of this shared process is that previously stabilized patterns of strong or weak synapses onto the same postsynaptic neuron are well protected against later changes induced by LTP/LTD protocols at individual synapses .
Changes in the connection strength between neurons in response to appropriate stimulation are thought to be the physiological basis for learning and memory formation [1] , [2] . A minimal requirement for proper memory function is that these changes , once they are induced , persist for a long time . For several decades , experimentalists have therefore focused on Long-Term Potentiation ( LTP ) and Long-Term Depression ( LTD ) of synapses in hippocampus [3] , [4] and cortical areas [5] , [6] . LTP can be induced at groups of synapses by strong ‘tetanic’ high-frequency stimulation of the presynaptic pathway [3] while stimulation at lower frequency leads to LTD Dudek92 . Both LTP and LTD can also be induced at a single synapse or a small number of synaptic contacts if presynaptic activity is paired with either a depolarization of the postsynaptic membrane [5] , [7] or tightly timed postsynaptic spikes [8] , [9] . While the induction protocol for LTP and LTD is often as short as a few seconds , the changes in synaptic efficacy persist for much longer [9] . In typical slice experiments on LTP [and similarly for LTD or Spike-Timing Dependent Plasticity ( STDP ) ] the persistence of the change is monitored for 30 minutes to 1 hour . Accumulating evidence suggests , however , that after this early phase of LTP ( E-LTP ) different biochemical processes set in that are necessary for the further maintenance of potentiated synapses during the late phase of LTP ( L-LTP ) [10] , [11] . For an understanding of the transition from early to late LTP , the concept of ‘synaptic tagging and capture’ has become influential [12] , [13] . During induction of the early phase of LTP , each potentiated synapse sets a tag that marks that it has received a specific afferent signal . A candidate molecule , involved in the tag signaling LTP induction in apical dendrites of hippocampal neurons , is the calcium-calmodulin dependent kinase II ( CaMKII ) [13] . Newly synthesized plasticity-related proteins are ‘captured’ by the tagged synapse and transform E-LTP into L-LTP that can be maintained over hours or days . A candidate protein involved in the maintenance of potentiated hippocampal synapses is the protein kinase Mζ ( PKMζ ) [11] , [14] . The stabilization and maintenance of potentiated synapses poses a number of theoretical challenges . First , on the level of single synapses we must require synaptic strength to remain stable , despite the fact that AMPA channels in the postsynaptic membrane are continuously exchanged and recycled [15]–[17] . Thus the synapse is not ‘frozen’ but part of a dynamic loop . Second , on the level of neuronal representation in cortical areas , one finds representations of input features that are stable but at the same time sufficiently plastic to adjust to new situations [18] . In the theoretical community , this paradox has been termed the stability-plasticity dilemma in unsupervised learning [19] . Third , humans keep the ability to memorize events during adulthood , but can also remember earlier episodes years back . However , continued learning of new patterns in theoretical models of associative memory networks forces the erasure or ‘overwriting’ of old ones , the so-called palimpsest property [20] , [21] . In the context of continued learning , theoretical arguments show that synaptic plasticity on multiple time scales cannot prevent , but at most delay the erasure of memories in the presence of ongoing synaptic activity [22] . This suggests that additional mechanisms are necessary to further protect existing memories and ‘gate’ the learning of new ones . Despite these challenges for the long-term stability of synapses , most classical models of synaptic plasticity focus on the induction and early phase of LTP or LTD and completely ignore the question of maintenance . Traditional models of associative memories separate the learning phase from the retrieval phase [23] and the same holds for standard models of STDP [24]–[26] . Detailed biophysical models of LTP and LTD describe calcium dynamics and Calcium/Calmodulin-Dependent Protein Kinase II ( CaMKII ) phosphorylation during the induction and early phase of LTP [27]–[29] . While these models show that switches built of CaMKII proteins can be stable for years , they do not address aspects of tagging leading to heterosynaptic interaction during L-LTP and L-LTD . Moreover , while CaMKII phosphorylation is necessary for induction of LTP and mediate tags in the apical dendrites of hippocampal CA1 neurons [30] , it is less clear whether it is necessary for its maintenance [31] . On the other hand protein kinase Mζ is essential for maintenance of some synapse types [11] , [13] , [14] but the same molecule is potentially relevant for induction in others [30] . We wondered whether a simple model that connects the process of LTP induction with that of maintenance would account for experimental results on tagging and ‘cross-tagging’ [11]–[13] , [32] without specific assumptions about the ( partially unknown ) molecular pathways involved in the maintenance process . If so , the model should allow us to discuss functional consequences that are generic to the tagging hypothesis independent of the details of a biophysical implementation in the cell . Even though we believe that the model principles are more general , we focus on synapses from the Schaffer-Collaterals onto the CA1 neurons in hippocampus as an experimentally well-studied reference system for synaptic plasticity . Since typical tagging experiments involve the extracellular stimulation of one or several groups of synapses ( rather than single synapses ) , our model of early and late LTP/LTD is developed in the context of a neuron model with hundreds of synapses . The application of the principles of synaptic consolidation to experiments inducing E-LTP/E-LTD at single synapses is considered in the discussion section .
Our model contains three elements , Figure 1 . The first one sets the tag during the induction of E-LTP or E-LTD . A tag is indicated by a value h = 1 for LTP or l = 1 for LTD . In the absence of tags we have h = l = 0 . The second one describes the process that triggers the synthesis of plasticity related proteins . The final component describes the up-regulation of a maintenance-related process from a low value ( z = 0 ) to a high value ( z≈1 ) . The dynamics of this component is intrinsically bistable and leads to a consolidation of the previously induced change at the labeled synapses upon interaction with the protein p ( ‘protein capture’ ) . The total change Δw of the synaptic strength reported in experiments contains contributions [13] of the early components l and h as well as the late component z . Since the model describes a sequence of three steps ‘Tag-Trigger-Consolidation’ we call it in the following the TagTriC-Model ( Figure 1 ) . Results from minimal stimulation protocols which putatively activate only a single synapse suggest that the induction of LTP is a switch-like process [7] , [37] . We therefore model individual synapses as discrete quantities that can switch , during the induction of LTP , from an initial ‘non-tagged state’ ( N ) to a ‘high state’ ( H ) with a transition rate ρH that depends on the induction protocol . Similarly , induction of LTD moves the synapse from the initial non-tagged state ( N ) to a ‘low state’ ( L ) at a rate ρL . If synapse i is in the high state , the synaptic variable hi is equal to one . If it is in the low state , another local variable li is set to one . These local variables hi and li do not only control the weight of the synapse during E-LTP and E-LTD , but also serve as ‘tags’ for up- or down-regulation of the synapse . Tags reset to zero stochastically with a rate kh and kl , respectively . If both tags are zero , the synapse is in the non-tagged state N . Since the synapse is either up-regulated OR down-regulated , at most one of the tags can be non-zero ( Figure 1A ) . The stochastic transitions from the initial state N with hi = 0 and li = 0 to the down-regulated state li = 1 or an upregulated state hi = 1 depend in a Hebbian manner on presynaptic activity and the state of the postsynaptic neuron . In the absence of presynaptic activity , the LTD rate ρL vanishes . Presynaptic activity combined with a time-averaged membrane potential u̅ above a critical value ϑLTD leads in the TagTriC model to a LTD transition rate ρL proportional to [u̅ ( t ) −ϑLTD] . For a transition from the initial state to the high state , we require in addition that the momentary membrane potential is above a second threshold ϑLTP . Hence the transition rate ρH is proportional to [u̅ ( t ) −ϑLTD][u−ϑLTP] whenever these threshold conditions are satisfied; see Methods for details . Our assumptions regarding the transition rates essentially summarize the qualitative voltage dependence seen in the Artola-Bröcher-Singer experiments [5] . Indeed , when 100 synapses in the TagTriC model are stimulated at low frequency during 50 seconds while the membrane voltage is kept fixed at different values ( Figure 1D ) , the total weight change summed across all synapses exhibits LTD at low voltage and LTP at high voltage [38] , [39] . As expected , the resulting weight changes in the simulations of Figure 1E reflect the voltage dependence of the transition rates in Figure 1D . Previously induced LTP or LTD needs to be consolidated in order to last for more than one hour . Consolidation requires that protein synthesis is triggered . Experimental evidence indicates that triggering of protein synthesis needs the presence of neuromodulators such as dopamine ( in the apical CA1 region ) or other modulators ( in other regions ) . In typical tagging experiments , extracellular stimulation co-stimulates dopaminergic input leading to a phasic dopamine signal [13] , [40] . In our model , induction of E-LTP or E-LTD through appropriate stimulation protocols changes the synaptic efficacy and sets tags at the modified synapses , both described by the variables hi = 1 or li = 1 . Protein synthesis in the model is triggered ( see methods for details ) if the total number of tags Σ i ( hi+li ) ( which indirectly reflects the phasic dopamine signal ) reaches a threshold Np which depends on the level of background dopamine ( and other neuromodulators ) . More specifically , Np decreases with the concentration of background dopamine so that the presence of dopamine facilitates the trigger process [32] . If the trigger criterion is satisfied , the concentration p of synthesized plasticity related proteins approaches with rate kp a value close to one . If the number of tags falls below the threshold Np , the protein concentration p decays with a time constant τp back to zero . Further details on the role of the trigger threshold and its relation to neuromodulators can be found in the discussion section . The total weight wi of a synapse i depends on the present value of the tags hi or li as well as on its long-term value zi . The slow variable zi is a continuous variable with one or two stable states described by a generic model of bistable switches , that could be implemented by suitable auto-catalytic processes [16] . While the concentration p of plasticity related proteins is zero , the variable zi has two stable states at zi = 0 and zi = 1 , respectively . If the protein concentration takes a value of p≈1 , one of the stable states disappears and , depending on the tag that was set , the long term-value of the synapse can be up- or down-regulated; see methods and Figure 1C for details . In order to illustrate the mechanism of induction of L-LTP , let us suppose that the synapse has been initially close to the state zi = 0 . The dynamics of the synapse can be imagined as downward motion in a ‘potential’ E . The current stable state of the synapse is at the bottom of the left well in the potential pictured in Figure 1C . We assume that during a subsequent LTP induction protocol the synapse has been tagged with hi = 1 and that the total number of tags set during the LTP induction protocol surpasses the trigger threshold Np . If the protein concentration p approaches one , the potential surface is tilted so that the synapse now moves towards the remaining minimum at z≈1 . After decay of the tags , p returns to zero , and we are back to the original potential , but now with the synapse trapped in the state z = 1 . It can be maintained in this state for a long time , until another strong tagging event occurs during which the synapse is tagged with li = 1 as a result of LTD induction . In this case the potential surface can be tilted towards the left so that the only equilibrium point is at z = 0 . Since consolidation is typically studied in animals that are more than 20 days old [13] , we assume that before the beginning of the experiment 30 percent of the synapses are already in the upregulated state z = 1 and the remaining 70 percent in the state z = 0; see also [7] . Because of the bistable dynamics of consolidation , only synapses that are initially in the upregulated state z = 1 can undergo L-LTD and only synapses that start from z = 0 can undergo L-LTP; compare [7] . Note , however , that tags for potentiation and depression can be set independently of the value of z . We may speculate that the variable z is related to the activity of PKMζ [11] , [14] , or to the self-sustained clustering of AMPA receptors [41] , but the exact biochemical signaling chain is irrelevant for the functional consequences of the model discussed in the results section . In our model , the bistable dynamics of the z-variable captures the essence of synaptic persistence despite molecular turnover [15] , [16] , [28] and mobility of AMPA receptors [41] . The TagTriC model has been tested on a series of stimulation protocols that reflect induction of LTP and LTD as well as the consolidation of plasticity events . A typical LTP induction experiment starts with extracellular stimulation of a bundle of presynaptic fibers ( i . e . , the Schaffer collaterals leading from CA3 to CA1 ) that activate a large number ( typically hundreds [13] ) of presynaptic terminals . With an extracellular probe electrode placed close to one of the postsynaptic neurons , a change in synaptic efficacy is measured via the amplitude ( or initial slope ) of the evoked postsynaptic potential , representing the total response summed across all the stimulated synapses . In our simulations , we mimic these experiments by simultaneous stimulation of 100 synapses . The state of the postsynaptic neuron is described by the adaptive exponential integrate-and-fire model [42] and can be manipulated by current injection . In a preliminary set of simulation experiments done with presynaptic stimulation alone ( no manipulation of the postsynaptic neuron ) , the TagTriC model exhibits LTD or LTP depending on the frequency of the presynaptic stimulation ( Figure 1F ) in agreement with experimental results [4] , [43] . Moreover , under the assumption that LTP has been blocked pharmacologically ( ρH = 0 in the model ) , our model shows LTD even for high stimulation frequencies ( Figure 1G ) . This stems from the fact that LTD and LTP are represented in the TagTriC model by two independent pathways ( Figure 1A ) which are under control condition in competition with each other , but show up individually if one of the paths is blocked [43] . Together with the voltage dependence of Figure 1E , the above simulation results indicate that our model of LTP and LTD induction can account for a range of experiments on excitatory synapses in the hippocampal CA1 region , in particular , voltage and frequency dependence . In order to study whether consolidation of synaptic changes in our model follows the time course seen in experiments , we simulate standard experimental stimulation protocols [12] , [13] . A weak tetanus consisting of a stimulation of 100 synapses at 100 Hz for 0 . 2 seconds ( 21 pulses ) leads in our model to the induction of LTP ( change by +15 percent ) which decays back to baseline over the time course of two hours ( Figure 2A ) . Thus , after the early phase of LTP the synapses are not consolidated . A stronger stimulus consisting of stimulating the same group of hundred synapses by 100 pulses at 100 Hz ( repeated 3 times every 10 minutes ) yields stronger LTP that consolidates and remains elevated ( weight change by 22±5 percent ) for as long as the simulations are continued ( more than 10 hours , only the first 5 hours are shown in Figure 2B ) . Thus our model exhibits a transition from early to late LTP if E-LTP is induced by the strong tetanic stimulation protocol , but not the weak one , consistent with results in experiments [12] , [13] . If , however , the weak tetanus at a first group of 100 synapses is given 30 minutes before or after a strong tetanus at a second group of 100 synapses , the synapses in both the weakly and strongly stimulated groups are consolidated ( Figure 2C and 2D ) . If the weak tetanus in group one is given 120 minutes after the strong tetanus in group two , then consolidation of the synapses in the weakly stimulated group does not occur ( Figure 2E ) . Thus our model exhibits a time course of heterosynaptic interaction between the two groups of synapses as reported in classical tagging experiments [12] , [13] . An advantage of a modeling approach is that we can study the dependence of the heterosynaptic interaction between the two groups of synapses upon model parameters . A critical parameter in the model is the trigger threshold Np that needs to be reached in order to start protein synthesis ( Figure 1B ) . With our standard choice of parameters , where Np = 40 , we can plot the consolidated weight change Δw/w ( 0 ) in the weakly stimulated group ( measured 10 hours after the induction ) as a function of the time difference between the stimulation of the group receiving the strong tetanus and that receiving the weak tetanus . The curve in Figure 2F shows that for a time difference up to 1 hour there is significant interaction between the two groups of synapses leading to synaptic consolidation , whereas for time differences beyond 2 hours this is no longer the case . If the trigger threshold is increased to Np = 60 ( corresponding to less available neuromodulator ) , then the maximal time difference that still yields L-LTP in the weakly stimulated group of synapses is reduced to about 20 minutes ( Figure 2F ) whereas a reduction of Np yields an increased time window of interaction ( data not shown ) . If Np is reduced much further , the weak tetanus alone will be sufficient to allow a transition from the early to the late phase of LTP . We speculate that Np could depend on the age of the animal as well as on the background level of dopamine or other neuromodulators so as to enable a tuning of the degree of plasticity ( see discussion for details ) . We consider two experimental protocols known to induce LTD—a weak low-frequency protocol consisting of 900 pulses at 1 Hz and a strong low-frequency protocol consisting of 900 repetitions at 1 Hz of a short burst of three pulses at 20 Hz . This strong low-frequency protocol applied to 100 model synapses leads to a significant level of LTD ( reduction of weights to 70±4 percent of initial value ) which is consolidated 5 hours later at a level of 83±3 percent of initial value . If a group of 100 synapses is stimulated with the weak low-frequency protocol , an early phase of LTD is induced that is not consolidated but decays over the time course of 3 hours ( Figure 3A and 3B ) . However , if the weak low-frequency stimulation occurs after another group of 100 synapses had been stimulated by the strong low-frequency protocol , then the group that has received the weak stimulation shows consolidated synapses ( at 90±2 percent 5 hours after stimulus induction , Figure 3C ) . Moreover , consolidation of LTD ( at 92±3 percent 5 hours after stimulus induction ) in the group of synapses receiving the weak low-frequency protocol also occurs if it was stimulated thirty minutes after the stimulation of a second group of synapses by a strong tetanus , leading to LTP ( Figure 3D ) . Thus , the TagTriC model exhibits cross-tagging consistent with experiments [11] , [32] . In our model , cross-tagging occurs because the tags for LTP and LTD ( hi and li , respectively ) enter in a symmetric fashion into the trigger criterion for the synthesis of plasticity-related proteins ( see Figure 1 and Methods ) . In order to elucidate how the model gives rise to the series of results discussed in the preceding paragraphs , we have analyzed the evolution of the model variables during and after induction of LTP ( Figure 4 ) . Critical for consolidation is the synthesis of plasticity related proteins , characterized by the variable p in the model . Synthesis is only possible while the total number of tags is above the protein triggering threshold Np . For the strong tetanic stimulus this criterion is met for about 90 minutes ( shaded region in Figure 4A ) leading to high levels of plasticity related proteins . After 90 minutes the concentration of proteins starts to decay back to baseline . While the level of proteins is sufficiently elevated the consolidation variable zi of each tagged synapse moves towards zi≈1 since this is the only stable fixed point of the dynamics ( Figure 1C ) . This leads to a consolidation time of about 2 hours , enough to switch a large fraction of synapses into the up-regulated state z≈1 ( green line , Figure 4A ) . Hence the average weight of the stimulated synapses stabilizes at a value above baseline , indicating L-LTP ( Figure 4A , solid line ) . If , in a different experiment , 100 synapses are stimulated by the weak tetanus , the synthesis of plasticity related proteins is only possible during a few minutes ( Figure 4B , red line ) , which is not sufficient to switch tagged synapses from z = 0 into the upregulated state z≈1 . Hence the weights ( Figure 4B , black line ) decay together with the tags ( Figure 4B , magenta line ) back to baseline and the transition from early to late LTP does not occur . The decay of the weights is controlled by the rate kH at which tags stochastically return to zero . The evolution of the protein concentration p and the consolidation variable z after a strong tetanus that leads to 90 minutes of protein synthesis and a weaker tetanus that only leads to 40 minutes of protein synthesis has been illustrated in ( Figure 5A ) . The total amount of available protein that is synthesized depends in our model on the time that the total number of tags stays above the protein triggering threshold Np . Even though always 100 synapses are stimulated in our model , not all receive tags in each experiment; moreover because of the competition for potentiation tags ( hi = 1 ) and depression tags ( li = 1 ) during induction of plasticity , different synapses can receive different tags in the same experiment . With our strong tetanus protocol , on average 70 ( out of 100 ) synapses receive a potentiation tag and 30 a depression tag while with the weak tetanus the numbers are 30 and 10 , respectively . For the depression protocols , on average 10 synapses receive a potentiation tag and 90 a depression tag under strong low-frequency stimulation , and typically zero a potentiation tag and 40 a depression tag under the weak low-frequency protocol . These numbers vary from one trial to the next so that sometimes the protein trigger threshold Np = 40 is reached with the weak protocols and sometimes not . The important aspect is that even if the threshold is reached for a short time , the duration of protein synthesis is not long enough to provide a sufficient protein concentration p for consolidation of the tagged synapses; see Figure 4B and Figure 5A . Since the concentration p of plasticity related proteins is crucial for the transition from early to late LTP we wondered how a block of protein synthesis would interfere with the consolidation of weights in the TagTriC model . Application of a protein synthesis inhibitor ( modeled by setting the rate kp of protein synthesis to zero ) during 1 hour starting thirty minutes before a strong tetanus is given to a group of 100 synapses that would normally lead to L-LTP , induced E-LTP but prevented consolidation into L-LTP ( data not shown ) . However , if the same simulation experiment was repeated after a second group of synapses had received a strong tetanic stimulation 35 minutes prior to the application of protein synthesis blocker , then both groups of synapses showed consolidation of weights ( Figure 4D ) , consistent with experiments [12] . Closer inspection of the lower panel in Figure 4D shows that two components contribute to consolidation: Firstly , the concentration of plasticity related proteins ( red line ) that has increased because of the first strong tetanic stimulus decreases only slowly back to baseline enabling the switching of the slow components ( variable z , green line ) even in the presence of protein synthesis blocker . Secondly , even after the end of the application of the blocker , the total number of tags that has been set by LTP induction is still above the critical value Np ( shaded region in Figure 4D ) so that protein synthesis can be resumed after the end of the blocking period . In summary , the detailed analysis of the TagTriC model allows to account for many aspects of tagging experiment in terms of a limited number of variables .
Synaptic plasticity is based on intricate signal transduction chains involving numerous processing steps and a large number of different molecules [2] , [13] , [17] . Despite the complexity of the molecular processes , synaptic plasticity has experimentally been characterized by a small set of distinct phenomena such as short-term plasticity [44] as well as early and late phases of LTP and LTD [13] . Existing models of synaptic plasticity have focused on the description of short-term plasticity [44] and on the induction of LTP and LTD [24]–[26] , [33]–[36] . The question of maintenance has received much less attention and was mainly addressed in the context of bistability of the CaMKII auto-phosphorylation process [27]–[29] , AMPA receptor aggregation [41] , or four identified kinase pathways [45] . While CaMKII is necessary for induction of long-term potentiation [46] , it is probably too narrow to focus modeling studies only on a single or a few kinases such as CaMKII and neglect other proteins and signaling cascades that are involved in synaptic maintenance [13] . For example , there is strong evidence that PKMζ is involved in synaptic maintenance and necessary for the late phase of LTP in vitro [11] and in vivo [14] . However , the actual processes are complex and the molecules involved in setting tags may differ between different parts of the dendrite . For example PKMζ is involved in setting tags during E-LTP in the basal dendrite , whereas CaMKII ( or MAPK for E-LTD ) plays a similar role in apical dendrites [30] . Instead of focusing on specific signaling cascades , the TagTriC model presented in this papers aims at describing the essential ingredients of any possible functional model of L-LTP and tagging . These ingredients include ( i ) a bistable switch ( described by the dynamics of the zi-variable ) for each synapse that guarantees long-term stability in the presence of molecular turn-over [16]; ( ii ) a global triggering signal for protein synthesis ( described by the dynamics of the p variable ) ; a formalism to ( iii ) induce early forms of LTP and LTD and ( iv ) set synaptic tags . Since we aimed for the simplest possible model , we have identified the synaptic tags hi and li for potentiation and depression with the synaptic weights during the early phase of LTP and LTD , respectively , so that points ( iii ) and ( iv ) are described by the same transition of the synapse from an initial non-tagged state to the high or low state , respectively . Variants of the model where the weight during the early phase of LTP and LTD is not directly proportional to the value of the tags are conceivable . Even though we do not want to identify the synaptic variables hi , li , zi with specific biochemical signals , a couple of candidate molecules and signaling chains should be mentioned . The setting of the tag for LTP under normal physiological conditions involves NMDA receptor activation and elevated levels of calcium which in turn trigger a signaling chain involving Calmodulin and CaMKII . We therefore think that the hi variable ( representing both the tag for LTP induction and the weight increase during the early phase of LTP ) should be related to the activation of CaMKII [13] , [46] . The molecular interpretation of the tag li for LTD is less clear [13] . In our model we have taken the tags as discrete quantities that decay stochastically , but a model with continuous tags that decrease exponentially gives qualitatively the same results ( data not shown ) . The reason is that triggering protein synthesis in our model requires a large number of tags to be set , so that even in the stochastic model only the mean number of tags is relevant–and the mean ( more precisely , its expectation value ) is a continuous variable . Nevertheless , we prefer the model with discrete values over the continuous one in view of the switch-like transitions of synapses after induction of LTP and LTD [7] , [37] . Maintenance of enhanced synaptic weights is probably implemented by an increased number of AMPA receptors in the postsynaptic membrane . Whether the stability arises from a self-organization process of receptors [41] or from interaction with persistently activated CaMKII molecules [46] or from additional kinases such as PKMζ [11] , [14] , is an open problem of experimental investigation . Similarly , the exact identity of many plasticity related proteins is still unknown [13] . In our model we assume that recently synthesized plasticity related proteins are accessible to all synapses onto the same postsynaptic neuron . However , a distinction between proteins synthesized in , say , basal dendrites and that synthesized in apical dendrites would be possible by replacing the variable p by two or more distinct variables pk with similar dynamics ( but potentially different trigger thresholds Np ) , allowing for a compartmentalization of tagging [13] . Experimental cross-tagging results clearly indicate that there are two different types of synaptic tags , one for LTP and one for LTD [13] , [32] , which we called hi for LTP and li for LTD , leading to three different states during tagging ( Figure 1A ) . Since we have identified the tagging with the early phase of LTP and LTD , our model of E-LTP and E-LTD also has three different states ( whereas our model of late LTP/LTD has only two states characterized by zi = 0 and z− = 1 ) . The three-state model of early LTP/LTD presented in this paper would predict that all non-tagged synapses can undergo a transition to E-LTP or E-LTD depending on the induction protocol–whereas experiments suggest that about 70 percent of synapses show LTP but not LTD and the remaining 30 percent LTD but not LTP [7] . Moreover , only those synapses that are initially weak can be potentiated and only those that are initially strong can be depressed [7] . This aspect can be included in our model if we replace the induction rates ρH for LTP by ρH ( 1−zi ) and ρL for LTD by ρlzi so LTP is only possible from a state with zi = 0 and LTD only from an initial state zi = 1 — in agreement with a two-state model of early LTP/LTD [7] . For the tagging and induction experiments presented in this paper , the results do not change significantly when we implement this extension of the induction model . One of the advantages of a simple phenomenological model is that it should be capable of illustrating the functional consequences of tagging and L-LTP or L-LTD in a transparent manner . What are these functional consequences ? A characteristic feature that is made transparent in our model ( and which we expect to be present in any model of tagging ) is that , under typical experimental conditions , the transition from early to late LTP is only possible if a sizable group of synapses have undergone E-LTP or E-LTD . Hence , while induction of E-LTP is a local Hebbian process that is likely to take place at the postsynaptic site of the synapse ( e . g . , the dendritic spine ) , the transition from the early to the late phase of LTP requires a minimum number of synapses to be activated by appropriate stimulation including co-activation of neuromodulatory input so as to trigger synthesis of plasticity related proteins . A direct consequence of this is that synapses cannot be considered as independent . In order to predict whether a synapse memorizes an item for a long time or forgets it and re-learns some other item , it is not sufficient to consider a ‘Hebbian’ induction model , where synaptic changes depend only on the activity of pre- and postsynaptic neurons . For maintenance , it is not the synapse which decides individually , but it is the neuron as a whole ( or a large functional compartment sharing the same site of synthesis of plasticity-related proteins [13] , [30] , [47] ) which ‘decides’ whether it is going to store the present information , or not . Hence , classical [20] , [21] , [34] and recent [22] theoretical models which studied memory maintenance in the presence of ongoing neuronal activity on the level of single synapses need to be reconsidered , since the assumption of independent synapses does not hold ( Figure 5A and 5B ) . In particular , our model predicts that , after an ensemble of identical neurons have received the same stimulus , some neurons learn ( adapt a large fraction of their synapses to the stimulus ) and others don't ( keep all their synapses unchanged ) . With our choice of parameters , this happens in the TagTriC model if the number of synapses that have been tagged during the induction protocol is between 55 and 70 ( Figure 5B ) . This neuronal , rather than synaptic , decision about memorizing an input ( see also [48] ) is potentially attractive for prototype learning–a standard paradigm in neuronal clustering and categorization algorithms , e . g . , [19] . In contrast to traditional neuronal clustering models where learned memories need to be protected against overwriting by completely different memory items [19] , a model based on tagging would have an intrinsic vigilance threshold via the trigger threshold Np . Hence it is resistant to changes at a single synapse . In our view , the protein synthesis trigger threshold NP is an important control parameter in the model . The results of Figure 2F show that an increase of the trigger threshold reduces the maximal delay after which a weak tetanus leads to L-LTP after a strong tetanic stimulation in a different group of synapses . With our normal value of Np = 40 we need around 60 synapses to be initially tagged in order to retain any memory . If we decrease the trigger threshold to Np = 10 and keep all other parameters of the model unchanged , then we need at least a group of 15 synapses tagged during the induction protocol to get any consolidation since some of the initially tagged synapses loose their tag too early to get consolidated ( Figure 5B ) . Only for a very small trigger threshold , say Np = 1 , ( which could occur at high concentration of neuromodulators ) synapses become ( nearly ) independent , since a tag at a single synapse would be sufficient to trigger the synthesis of proteins which would then become available at that synapse . Repeated stimulation of the synapse alone would then be sufficient to transform E-LTP into L-LTP . In our opinion , the trigger threshold Np is significantly lower in the presence of neuromodulators such as , for example , dopamine ( for synapses from Schaffer collaterals onto CA1 pyramidal neurons ) or noradrenaline ( for synapses in the dentate gyrus ) . A simple model for the dependence of Np on dopamine would be Np = n0/ ( DAbg+c0 ) where n0 is some arbitrary number ( say n0 = 1 ) , c0 a small number ( say 0 . 001 ) and DA denotes the stationary ‘background’ concentration of dopamine ( that is , before the start of the experiment ) , normalized to 0<DAbg<1 . The phasic dopamine signal caused by co-stimulation of dopaminergic input during tagging experiments is assumed to be proportional to the number of tags . The trigger condition becomes then equivalent to the condition which shows a trade-off between the phasic dopamine signal and the stationary background level of dopamine . In particular in the presence of a large concentration of dopamine ( DA≈1 ) , single synapses can be consolidated . With the assumption that standard tagging experiments in a large group of synapses are performed at a low dopamine concentration of DA = 0 . 024 before stimulation , we retrieve the value of Np = 40 used in the main part of the results section . The dependence of the trigger criterion on the number of tags takes implicitly the co-activation of neuromodulatory input during the experimental stimulation protocol into account: the larger the number of stimulated neurons and the stronger the stimulus , the higher the probability of co-activation of dopaminergic fibers . Blocking dopamine receptors amounts in the model to setting both the background and the phasic dopamine signal to zero . In this case , protein synthesis is not possible . Our model of LTP/LTD induction does not only account for voltage and frequency dependence of LTP/LTD induction , but also for spike timing dependence . In fact , for a stimulation paradigm where postsynaptic spikes are induced by short current pulses of large amplitude either a few milliseconds before or after presynaptic spike arrival , the model of LTP/LTD induction used in the TagTriC model becomes formally equivalent to a recent model of spike-timing dependent plasticity [35] which can be seen as an extension of classical models of STDP [24]–[26] . In the case of stochastic spiking of pre- and postsynaptic neurons our model shares important features with the Bienenstock-Cooper-Munro model [33] , in particular the quadratic dependence upon the postsynaptic variables . In addition , our model also accounts for the voltage dependence of the Artola-Bröcher-Singer model [38] . Thus , the model of LTP/LTD induction shares features with numerous established theoretical models and covers a large range of experimental paradigms known to induce LTP or LTD [3]–[6] , [8] . Since the subsequent steps of protein synthesis trigger and stabilization are independent of the way early phase of LTP is induced , our model predicts that tagging experiments repeated with different stimulation paradigms , but otherwise identical experimental preparation and age of animal , should give similar results as standard tagging protocols . In particular we propose to stimulate a group of synapses in hippocampal slices by 40–60 extracellular current pulses at 10 Hz while the postsynaptic neuron is receiving intracellular current injection that triggers action potential firing either a few milliseconds before or after presynaptic spike arrival and keeps the membrane potential at a depolarized level between postsynaptic action potential firing . Our model predicts that this will induce early LTD or LTP depending on spike timing and depolarization level that is not maintained beyond 1 or 2 hours . However , if the same stimulation occurs after a second group of synapses has received a strong tetanus , then stabilization of synapses at potentiated or depressed levels should occur , similar to standard tagging and cross-tagging experiments . In our opinion , these predictions should not depend on model details , but hold for a broad class of models that combine a mathematical description of induction of synaptic plasticity with a mechanism of consolidation . Another finding—which is somewhat unexpected and in contrast to other conceptual models of synaptic tagging and capture [12] , [13] , [47]—is that during a strong tetanic stimulation a fraction of synapses receives tags for depression ( while most , but not all , receive tags for potentiation ) . This is due to the fact that during induction of plasticity , transition to E-LTP and E-LTD act in parallel [7] . The prediction is that after consolidation ( say 2 hours after the strong tetanic stimulation ) a small fraction of synapses would show L-LTD , rather than L-LTP . An essential ingredient of our model that allows long-term stability of consolidated synapses is the bistable dynamics of the variable z . In our opinion , such bistability ( or possibly multistability [49] with three or four stable states ) is necessary for synaptic maintenance in the presence of molecular turn-over , as recognized in earlier theoretical work [15] , [16] , [34] . Our model therefore predicts that L-LTP and L-LTD should have bistable , switch-like properties . While there is evidence for switch like transitions during the induction of E-LTP and E-LTD [7] , [37] , the bistability of the late phase of synaptic plasticity has so far not been shown . A possible experiment would be to combine a minimal stimulation protocol ( e . g . , a weak tetanus ) at a single synapse [7] , [37] with a medium to strong stimulus at a group of other synapses ( e . g . , tetanic stimulus varying between 30 and 100 pulses ) . The prediction is that the weight of the single synapse shows an all-or-none phenomenon with transition probabilities that depend on the stimulation of the group of other synapses . In particular , as the number of pulses of the tetanic stimulation is reduced ( covering a continuum from strong to weak tetanic stimulation ) , the maintenance in the potentiated state should become less likely ( averages across many experiments decrease ) whereas the results of individual experiments show either full potentiation or none , which should give rise to a bimodal distribution of normalized synaptic weights . A lot of questions remain open and need to be addressed in future studies . First , can a synapse that has been potentiated in the past and is maintained after a transition to late LTP undergo a further potentiation step [13] ? In our current model this is not possible since the consolidation variable z has only two stable fixed points . If we replace the function f ( z ) depicted in Figure 1 by another one with more than two stable fixed points , then the answer to the above question would be positive . Indeed , there have been suggestions that self-organization of receptors into stable sub-groups could lead to multiple stable states [49] . Second , induction of LTP or LTD is not only possible by strong extracellular stimulation of groups of synapses , but also at single synapses if presynaptic activity is paired with either a depolarization of the postsynaptic membrane [5] , [7] or tightly timed postsynaptic spikes as in STDP experiments [6] , [8] . How can it be that the change induced by STDP seems to be maintained over one hour without visible degradation ? [6] , [7] . Are synapses in these experiments consolidated , and if so what is the concentration of neuromodulators ? In the TagTriC model with the choice of parameters used in the present paper , consolidation would not be possible , since the minimum number of synapses that have undergone E-LTP or LTD is Np = 40 in order to trigger protein synthesis , but , as explained above , an increased neuromodulator concentration would make consolidation possible . Third , what is the role of NMDA receptor activation during synaptic consolidation ? In our present model , protein synthesis is triggered by appropriate induction protocols , but is independent of synaptic activity during the consolidation process . However , recent experimental results suggest that protein synthesis blocker needs synaptic stimulation during the consolidation period to become effective [50] , suggesting a subtle interplay between protein synthesis and synaptic activation that cannot be captured by our model . Fourth , has each neuron a single protein synthesis unit or is protein synthesis a local process confined to each dendritic branch ? In the first case , there is a single neuron-wide protein synthesis trigger threshold [12] and the neuron as a whole ‘decides’ whether early forms of synaptic potentiation and depression will be consolidated or not . This is the paradigm posited in the TagTriC model . In the alternative model of local protein synthesis [13] , [47] , the critical unit for consolidation are local groups of synapses on the same dendritic branch . Thus , for the same number of tagged synapses , a local group of synapses on the same dendritic branch is more likely to undergo consolidation than a distributed set of tagged synapses , leading to a form of clustered plasticity [47] . The TagTriC model can be easily adapted to the case of clustered plasticity by ( i ) replacing the point-neuron model by a neuron model with spatially distributed synapses and ( ii ) replacing the neuron-wide trigger equation ( see 4 and Figure 1B ) by a finite number of analogous , but dendrite-specific equations . Fifth , how can tags be reset ? Experiments show that a depotentiating stimulus given 5 minutes after a weak tetanus erases the trace of E-LTP ( resets the tag ) whereas depotentiation 10 or 15 minutes after the strong tetanus only transiently suppresses the E-LTP , making the consolidation of the synapse by protein capture possible [51] . We have checked in additional simulations that our present model cannot account for these experiments . In our opinion , the above tag-reset experiments show that the synapse has additional hidden states currently not included in the TagTriC model . Additional states would allow to ( i ) separate the measured early LTP during the first 5 minutes from setting the tag; and ( ii ) distinguish between depotentiation and depression of synapses . One interpretation of the tag-reset experiments [51] is that during the first five minutes the tag is not yet set whereas early LTP is already visible . The tag would be set only with a delay of 5–10 minutes . Application of a depotentiating stimulus more than 10 minutes later would then leave the potentiation tag intact , but move the synapse to a transiently depotentiated state . The final and potentially most interesting question is that of functional relevance: Can the TagTriC model be used to simulate reward-based learning in experiments in vivo [13] ? The formal theory of reinforcement learning makes use of an eligibility trace [52] which can be interpreted as a synapse specific tag . In the future we want to check whether the TagTriC model can be linked to reinforcement learning models [53]–[56] under the assumption that reward prediction errors are represented by a dopamine signal [57] which influences the protein synthesis dynamics in our model . This open link to reward-based learning is of fundamental functional importance .
In our model we assume that presynaptic spike arrival needs to be combined with a depolarization of the postsynaptic membrane ( e . g . , [5] ) in order to induce a change of the synapse . In voltage clamp experiments ( e . g . , [39] ) the postsynaptic voltage would be constant . However , in general the voltage is time-dependent and described by a variable u ( t ) . In the TagTriC model , we assume that the low-pass-filtered voltageneeds to be above a critical value ϑLTD to make a change of the synapse possible . τlowP is the time constant of the low-pass filter and ϵ = 1 ms is a short delay twice the width of a spike ( see Table 1 ) . This short delay ensures that u̅ includes effects of previous presynaptic inputs and postsynaptic spikes , but not of an ongoing postsynaptic action potential . Combining presynaptic spike arrival at synapse i ( represented by xi ) with a depolarization u̅ of the postsynaptic neuron above a threshold ϑLTD we get a rate of LTD ( 1 ) where ALTD>0 is a parameter and [ . ]+ denotes rectification , i . e . , [y]+ = y if y>0 and zero otherwise . Here denotes the presynaptic spike train with pulses at time and δ the Dirac-delta function . Formally , ρL describes the rate of stochastic transitions from the non-tagged state h = 0 , l = 0 to the low state l = 1 , Figure 1 . In simulations we work with discrete time steps of Δ = 1 ms . Eq . 1 indicates that the probability Pl = 0→l = 1 of a transition to the low-state during the time step Δ vanishes in the absence of presynaptic spike arrival and takes a value of Pl = 0→l = 1 = 1−exp ( −ALTD[u̅ ( t ) −ϑLTD]+Δ ) ≈ALTD[u̅ ( t ) −ϑLTD]+Δ if a presynaptic spike arrives at the synapse i during the time step Δ . Note that the transition from l = 0 to l = 1 is only possible if h = 0 and h remains zero during the transition . Similarly , a switch from the non-tagged state h = 0 , l = 0 to the high state h = 1 occurs at a rate ρH which also depends on postsynaptic voltage and presynaptic spike arrival . We assume that each presynaptic spike at synapse i leaves a trace x̅ i that decays exponentially with time constant τx . The exact biophysical nature of the trace is irrelevant , but could , for example , represent the amount of glutamate bound to the postsynaptic receptor . The value of the trace at time t caused by earlier spike arrivals at time is then where the sum runs over all firing times . With the trace x̅ i we write ( 2 ) which indicates that , in addition to the conditions for LTD induction we also require the momentary membrane potential u ( t ) to be above a second threshold ϑLTP . This threshold could change on the time scale of minutes or hours as a function of homeostatic processes . To summarize , the rate of LTP transition ρH is different from ρL in five aspects . First , the constant ALTP is not the same as ALTD . Second , LTP is caused by the trace x̅ i left by presynaptic spikes , rather than the spikes themselves . This trace-formulation ensures that presynaptic spikes can interact with later postsynaptic spikes as in classical models of STDP [24]–[26] . Third , the time constant of the low-pass filter in u̅ is different; fourth , the momentary voltage needs to be above a threshold ϑLTP; and fifth , the total dependence upon the postsynaptic voltage is quadratic , rather than linear . The quadratic dependence ensures that for large depolarization LTP dominates over LTD [39] . Tagged synapses with hi = 1 decay with probability Ph = 1→h = 0 = kHΔ back to the non-tagged state ( and analogously , but with rate kL for the transition li = 1→li = 0 ) . In the TagTriC model , the local synaptic values h = 1 for potentiation or l = 1 for depression act as tags indicating potential sites for further consolidation , but are also directly proportional to the weight of the synapse after induction of LTP or LTD . Since in minimal stimulation experiments LTD leads to a reduction of about 50 percent of the synaptic efficacy whereas LTP leads to an increase by up to 100 percent [7] , we model the weight change during the early phase of LTP as Δwi = ( hi−αli ) w̅ where w̅ is the weight of the non-tagged synapse and α = 0 . 5 . The total weight change Δw/w̅ measured shortly after induction of LTP or LTD with extracellular protocols corresponds to the fraction of synapses in the high or low states , respectively , hence , if all synapses start from the non-tagged state the measured weight change is where N is the number of synapses stimulated by the protocol . The set of parameters of LTP/LTD induction and tagging is given in table 1 . The triggering process is controlled by the dynamics of a variable p which describes the amount of plasticity related proteins synthesized in the postsynaptic neuron . Protein synthesis is triggered and the variable p increases while the concentration of dopamine exceeds a critical level ϑp [58] . If the dopamine concentration DA falls below ϑp , the protein concentration decays with a time constant τp . Assuming standard first-order kinetics we have ( 3 ) Protein synthesis has a maximum rate dp/dt of kp and saturates if the amount of protein approaches a value one . Θ[y] denotes the unit step function with Θ[y] = 1 for y>0 and zero otherwise . Dopamine is present at a low stationary background value . In addition a phasic dopamine component is induced in standard tagging experiments in hippocampal slices , because of co-stimulation of dopaminergic inputs during extracellular stimulation of presynaptic fibers [40] . To describe the time course of the phasic dopamine component in our model , we assume that the dopamine is proportional to the total number of tags Σ i ( hi+li ) induced by the stimulation protocol . The stationary background level of dopamine DAbg is included in the threshold ϑp = Np ( DAbg ) for protein synthesis . Hence Eq . 3 can be rewritten in the form ( 4 ) Note that we have chosen units so that the threshold for protein synthesis Np can be interpreted as the minimal number of tags necessary to stimulate protein synthesis . This interpretation is important for the discussion of the model results , in particular Figures 4 and 5 . A suitable model for dependence of the protein synthesis threshold on the background level of dopamine is Np ( DAbg ) = n0/ ( DAbg+c0 ) where n0 = 1 is a scaling factor , c0 = 0 . 001 a constant and 0≤DAbg≤1 is the normalized dopamine concentration . We note that the trigger condition [Σ i ( hi+li ) −Np ( DAbg ) ]>0 is then equivalent to the condition ( DAbg+0 . 001 ) [Σ i ( hi+li ) ]>1 . This formulation shows that there is a trade-off between background levels and phasic dopamine . Unless stated otherwise we always use in the simulation a fixed dopamine level DAbg = 0 . 024 so that Np = 40 . The specific model Np ( DAbg ) of the dependence upon background dopamine levels is therefore irrelevant . We assume that the plasticity related protein p synthesized in the postsynaptic neuron is diffused in the dendrite of the postsynaptic neuron and hence available to all the synapses under consideration . Hence , the tags hi and li have indices , since they are synapse-specific , whereas p in Eq . 4 does not . The consolidation variable z describes the late phase of LTP and follows the dynamics ( 5 ) The scaling factor γ is a function of the dopamine level DA . In the simulations we always assumed a fixed dopamine level and set γ ( DA ) = 0 . 1 . In the absence of plasticity related proteins ( p = 0 ) , or if no tags are set ( hi = li = 0 ) , the function f ( z ) = z ( 1−z ) ( z−0 . 5 ) generates a bistable dynamics with stable fixed points at z = 0 and z = 1 and an unstable fixed point at z = 0 . 5 marked by the zero crossings of the function f , Figure 1C . In the presence of a finite amount of proteins p>0 and a non-zero tag , the location of the fixed points changes and for p>0 . 47 , only one of the stable fixed points remains . The potential shown in Figure 1C is a function E with dE/dz = −f ( z ) so that dz/dt = −dE/dz . We note that a synapse i can change its consolidated value only if both a tag ( hi = 1 or li = 1 ) and protein p>0 . 47 is present–summarizing the essence of ‘synaptic tagging and capture’ [12] , [13] . The synaptic weights have contributions from early and late LTP and LTD . The total synaptic weight of a synapse i is wi = w̅ ( 1+hi−αli+βzi ) where w̅ is the value of a non-tagged synapse , α = 0 . 5 and β = 2 are parameters , hi and li are binary values indicating E-LTP and E-LTD , respectively , and zi is the value of the L-LTP trace of synapse i . Since we model slice experiments in animals older than 20 days , we assume that 30 percent of the synapses have undergone previous potentiation and have z = 1 while the remaining 70 percent of synapses are in the state z = 0 [7] . In all simulation experiments we stimulate one or several groups of N = 100 synapses each . Assuming that no tags have been set in the recent past ( hi = li = 0 ) , the initial value of the average weight in a group of N synapses is then . For all simulations in this paper we use the adaptive exponential integrate-and-fire model [42] as a compact description of neuronal firing dynamics . Briefly , it consists of two equations . The voltage equation has an exponential and a linear term as measured in experiments [59] . The second equation describes adaptation . Although firing rate adaptation is not important for the present study , it would be relevant in the context of other stimulation paradigms . Parameters for the neuron model are as in [42] and are kept fixed for all simulations presented in this paper . The voltage threshold Vs of spike initiation by a short current pulse is 25 mV above the resting potential of −70 . 6 mV [42] . Synaptic input is simulated as a short current pulse . The initial connection weight w̅ was adjusted so that simultaneous activation of 40 or more synapses triggers spike firing in the postsynaptic neuron . Hence the amplitude of a single EPSP is about 0 . 6 mV . The adaptive exponential integrate-and-fire model is defined in continuous time . If a spike is triggered by a strong current pulse , the voltage rises within less than 0 . 5 millisecond to a value of 20 mV where integration is stopped . The voltage is then reset to resting level , and integration restarted after a refractory time of 1 ms . In order to enable us to perform simulations of plasticity experiments with a time step of Δ = 1 ms , the voltage equation during the rising slope of the action potential was integrated once at a much higher resolution ( time step 0 . 02 ms ) , so as to determine the exact contribution of each postsynaptic spike to the probability of LTP induction . Every postsynaptic spike was then treated as an event in the plasticity simulations that contributed a probability Ph = 0→h = 1 of flipping the tag from h = 0 to h = 1 in a time step Δ = 1 ms which we can write as Ph = 0→h = 1 = aΔx̅ ( t ) [u̅ ( t ) −ϑLTD]+ with a numerical conversion factor aΔ = ALTP 5 ms mV derived by the above procedure; see Eq . 2 . In Figure 5 we plot the number of synapses that have been consolidated as a function of the number Ntag of initially tagged ( hi = 1 ) synapses . Since the number of tags decays exponentially with rate kH , the expected duration of protein synthesis is where Np is the protein trigger threshold . While protein synthesis is ‘ON’ the variables p and z move along the black dashed line in Figure 5A which crosses after a time t1 the separatrix ( green line in Figure 5A ) and at a time t2 the line z = 0 . 5 ( vertical dashed green line ) . Different cases have to be distinguished . ( i ) , no consolidation takes place ( see pink trajectory ) , hence Nup = 0 . ( ii ) , consolidation is guaranteed for all synapses that are still tagged at time t2 , hence Nup = Ntagexp ( −kt2 ) . ( iii ) In the case of , the time tcross needed to cross the vertical line z = 0 . 5 is numerically calculated by integrating the equations dp/dt = −p/ ( τp ) and dz/dt = f ( z ) +γ p starting at at the point on the black-dashed line ( see orange line in Figure 5A for a sample trajectory ) . The number of consolidated synapses is then Nup = Ntagexp ( −ktcross ) . The solid line in Figure 5B represents Nup as a function of Ntag calculated for the cases ( i ) – ( iii ) . With our standard set of parameters , we have t1≈28 min and t2≈60 min .
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Humans and animals learn by changing the strength of connections between neurons , a phenomenon called synaptic plasticity . These changes can be induced by rather short stimuli ( lasting sometimes only a few seconds ) but should then be stable for months or years in order to be useful for long-term memory . Experimentalists have shown that synapses undergo a sequence of steps that transforms the rapid change during the early phase of synaptic plasticity into a stable memory trace in the late phase . In this paper we introduce a model with a small number of equations that can describe the phenomena of induction of synaptic changes during the early phase of synaptic plasticity , the trigger process for protein synthesis , and the final stabilization . The model covers a broad range of experimental phenomena known as tagging experiments and makes testable predictions . The ability to model the stabilization of synapses is crucial to understand learning and memory processes in animals and humans and a necessary ingredient for any large-scale model of the brain .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"neuroscience/theoretical",
"neuroscience"
] |
2008
|
Tag-Trigger-Consolidation: A Model of Early and Late
Long-Term-Potentiation and Depression
|
Giardia intestinalis is a non-invasive protozoan parasite that causes giardiasis in humans , the most common form of parasite-induced diarrhea . Disease mechanisms are not completely defined and very few virulence factors are known . To identify putative virulence factors and elucidate mechanistic pathways leading to disease , we have used proteomics to identify the major excretory-secretory products ( ESPs ) when Giardia trophozoites of WB and GS isolates ( assemblages A and B , respectively ) interact with intestinal epithelial cells ( IECs ) in vitro . The main parts of the IEC and parasite secretomes are constitutively released proteins , the majority of which are associated with metabolism but several proteins are released in response to their interaction ( 87 and 41 WB and GS proteins , respectively , 76 and 45 human proteins in response to the respective isolates ) . In parasitized IECs , the secretome profile indicated effects on the cell actin cytoskeleton and the induction of immune responses whereas that of Giardia showed anti-oxidation , proteolysis ( protease-associated ) and induction of encystation responses . The Giardia secretome also contained immunodominant and glycosylated proteins as well as new candidate virulence factors and assemblage-specific differences were identified . A minor part of Giardia ESPs had signal peptides ( 29% for both isolates ) and extracellular vesicles were detected in the ESPs fractions , suggesting alternative secretory pathways . Microscopic analyses showed ESPs binding to IECs and partial internalization . Parasite ESPs reduced ERK1/2 and P38 phosphorylation and NF-κB nuclear translocation . Giardia ESPs altered gene expression in IECs , with a transcriptional profile indicating recruitment of immune cells via chemokines , disturbances in glucose homeostasis , cholesterol and lipid metabolism , cell cycle and induction of apoptosis . This is the first study identifying Giardia ESPs and evaluating their effects on IECs . It highlights the importance of host and parasite ESPs during interactions and reveals the intricate cellular responses that can explain disease mechanisms and attenuated inflammatory responses during giardiasis .
Giardia intestinalis is an intestinal protozoan parasite causing 280 million human diarrheal cases ( giardiasis ) annually [1] . Giardia has two life-cycle stages: infectious cysts and disease-causing trophozoites [2] . Trophozoites move by flagella and adhere to intestinal epithelial cells ( IECs ) strongly using a suction cup on the ventral surface [2] . The direct contact of Giardia with IECs induces cellular damage on the apical surface , compromising brush border enzymes function , and affect cellular junctions , leading to an increased intestinal barrier permeability [3] . These changes cause maldigestion , malabsorption and electrolyte imbalance , collectively culminating in causing diarrhea [4] . Symptoms are usually acute but chronicity is not uncommon and some patients develop intestinal and extra-intestinal complications post-infection [1 , 5] . Many Giardia infections , however , remain asymptomatic and the reason for variable disease outcomes remains obscure . Early studies of Giardia pathogenicity suggested that the parasite releases proteins that can contribute to disease induction . Excretory-secretory products ( ESPs ) of Giardia affect intestinal absorption and secretion [6] , cause histopathological alterations [7] and induce specific antibodies against glycoproteins [8] . A secreted 58 kDa glycoprotein has been shown to react with antibodies from giardiasis patients and induce fluid accumulation in ligated rabbit ileal loop experiments [9 , 10] . Nevertheless , the identity of this protein remained unknown as tryptic digests did not align with any proteins in the Giardia Database . Cysteine proteases ( CPs ) are also yet unidentified Giardia ESPs . Their involvement in virulence , however , is well studied , demonstrated by their association with parasite attachment [11] , and the degradation of extracellular matrix ( ECM ) proteins [12] , antibodies [13] and proinflammatory cytokines [14 , 15] . Arginine metabolising enzymes ( AMEs ) ( e . g . arginine deiminase ( ADI ) and ornithine carbamoyltransferase ( OCT ) ) are the best-studied examples of secreted virulence factors in Giardia . AMEs outcompete host cells for arginine uptake , inhibiting cellular proliferation [16] , abrogating nitric oxide production , a compound cytotoxic to Giardia , [17] , and inhibiting cytokine production by dendritic cells [18] . Other reports documented the secretion of elongation factor-1 alpha ( EF-1α ) [19] and the glycolytic enzyme enolase [17] into Giardia growth medium and the medium of interaction with IECs in vitro , respectively . Their functions in parasite virulence , if any , is still unknown . Finally , variable surface proteins ( VSPs ) are cysteine-rich proteins that cover trophozoite surface and they are released in large quantities into the growth medium ( ≈70% within 24h ) [20] . VSPs are immunodominant during infection [21] and their constant switching ( i . e . antigenic variation ) help the parasite evade the host immune system [22] . In view of the simple endomembrane system of Giardia , which lacks a true Golgi apparatus , peroxisomes and endosomal/lysosomal system [2] , the secretion of proteins , their sorting and trafficking remain a perplexing aspect of the parasite’s biology . Most of our knowledge about secretion and secreted proteins of Giardia derive from experiments targeting the sorting and trafficking of VSPs to the plasma membrane and cyst-wall proteins in encystation-specific vesicles ( ESVs ) to the cyst wall during encystation [23] . AMEs , EF-1α and enolase all lack signal peptides ( SPPs ) but they are still secreted by the parasite . This suggests the presence of non-conventional secretory mechanisms in Giardia such as extracellular vesicles ( EVs ) carrying protein cargo with no SSP . EVs include the exosomes ( 30–100 nm ) and microvesicles ( MVs ) ( 100–1000 nm ) , which have been shown to play roles in parasites communication , host cell colonization and immune modulation [24 , 25] . A recent study has identified MVs released from Giardia trophozoites and encysting cells [26] . The released MVs affected trophozoite attachment and dendritic cell activation [26] . In this study , we used proteomics to identify the secretome of the Giardia reference isolates WB and GS during growth and interaction with IECs in vitro in serum-free medium . We also show the release of EVs by Giardia as a part of its secretome . We demonstrate that Giardia ESPs alter gene expression in IECs , cell signalling and the production of proinflammatory cytokines . This study highlights the importance of Giardia ESPs in inducing pathological effects in IECs and suggests how this might have immunomodulatory effects on host immune responses .
The cell lines used in this study were all obtained from American Type Culture Collection ( ATCC ) : Giardia intestinalis isolates WB clone C6 ( ATCC30957; assemblage A ) and GS , clone H7 ( ATCC50581; assemblage B ) were used in this study in combination with the human colonic adenocarcinoma cell line , Caco-2 clone TC7 ( ATCC HTB-37 ) . All the experiments were approved by the Programme Review Board at Department of Cell and Molecular Biology , Uppsala University , Sweden . All chemicals were purchased from Sigma-Aldrich ( MO , USA ) , unless otherwise stated . Giardia trophozoites were cultured in 10 ml and 50 ml tubes filled with TYDK medium ( 37°C ) supplemented with 10% heat inactivated bovine serum ( Sigma-Aldrich ) as described in [27] . The Caco-2 clone TC7 ( passage numbers 7–12 ) cell line was grown and differentiated as previously described [16] . To collect Giardia ESPs from axenic cultures we used a modified RPMI-1640 medium containing 55 . 5 mM glucose , 22 . 8 mM L-arginine , 11 . 4 mM L-cysteine hydrochloride monohydrate , 11 . 4 mM ascorbic acid , 2mM Glutamax ( Gibco ) , 1 mM sodium pyruvate ( Gibco ) and 1x MEM essential amino acids . The medium was filter-sterilized and placed in a water bath ( final pH is 6 . 85 at 37°C ) until used . Confluent Giardia culture tubes , prepared as described above , were used for trophozoite viability assessment . Briefly , the TYDK medium was decanted from each tube followed by three washes in Hank’s Balanced Salt Solution with glucose ( HBSS-G ) supplemented with 11 . 4 mM L-cysteine ( pH 6 . 8 , 37°C ) . Culture tubes were replenished with the modified medium , closed tightly and incubated for 2h or 6h ( 37°C ) . At the end of each incubation , tubes were placed on ice to detach trophozoites ( 10 min ) , followed by counting using the expulsion of Trypan Blue and flagellar motility as viability criteria . Tubes with Giardia trophozoites in modified RPMI-1640 medium ( 50 ml , two tubes of each isolate ) were used to collect Giardia ESPs in axenic cultures . The tubes and media , following counting and viability assessment , were centrifuged ( 930 xg , 10 min , 4°C ) to pellet trophozoites . Collected media were filter-sterilized ( 0 . 22 μM ) and treated with protease inhibitor cocktail tablets ( cOmplete , Mini EDTA-free , Roche , Sigma-Aldrich ) . Media were concentrated down to 200–300 μl using the Amicon Ultra 15 mL centrifugal filters with 3kDa cutoff ( Merck-Millipore , Darmstadt , Germany ) . To further eliminate any traces of residual serum , concentrates were processed through the AlbuminOUT kit ( G-Biosciences , MO , USA ) according to the manufacturer’s instructions . Three biological replicates ( 2h and 6h ) were prepared and stored at -80°C until used for MS analysis . The whole experimental setup is described in Fig 1A . Differentiated Caco-2 cells ( 75 cm2 flasks ) were washed with warm PBS ( 3x ) and incubated with 6 x 107 trophozoites resuspended in 25 ml of DMEM ( no FBS ) for 2h or 6h . Trophozoites were washed ( 3x , HBSS-G plus 11 . 4 mM L-cysteine ) prior addition to cells . Caco-2 cells treated as above and incubated alone in DMEM ( 2h and 6h ) served as controls ( Fig 1A ) . All incubations were performed in 10% CO2 humidified tissue culture incubator at 37°C . At the end of each interaction , flasks were placed on ice ( 10 min ) to detach trophozoites for counting and viability assessment . Media were then collected , processed as described earlier and stored at -80°C until used for MS analysis . Three biological replicates were prepared ( 2h or 6h including controls ) . The ESP enrichment experiment for axenic cultures described earlier was repeated to collect Giardia EVs . Samples were processed with the ExoQuick TC Kit ( SBI System Biosciences , CA , USA ) according to the manufacturer’s instructions . Giardia EVs were pelleted by centrifugation ( 1500 xg , 30 min ) and resuspended in 100 μl PBS buffer and processed immediately for electron microscopy ( EM ) . Samples ( 5μl ) were adsorbed onto a Formvar-coated 200 mesh grid ( 15 seconds ) , followed by treatment with 2% molybdenum ( 10 seconds ) and contrasting using 2% uranyl acetate ( 10 seconds ) . Grids were dried and visualized using a transmission electron microscope at the BioVis Core Facility , Uppsala University , Uppsala , Sweden . A negative control ( media alone ) was included and processed similarly . Before digestion , the buffer in the collected samples was exchanged to a urea-containing lysis buffer ( 20 mM HEPES , 9 M urea , Complete Mini EDTA-free protease inhibitor cocktail ( Roche ) using 3 kDa molecular weight cut off filters ( Thermo Fisher Scientific , MA , USA ) . Proteins were then subjected to dithiothreitol ( DTT , 12 . 5 mM ) reduction and iodoacetamide ( IAA , 6 . 9 mM ) alkylation before digested in-solution with trypsin ( 1 μg added per sample ) . The samples were desalted using Pierce C18 Spin Columns ( Thermo Fisher Scientific ) . Eluates were dried and resolved in 15 μL 0 . 1% formic acid of which 5 μL were injected . The nanoLC-MS/MS experiments were performed using a Q Exactive Orbitrap mass spectrometer ( ThermoFisher Scientific , Bremen , Germany ) equipped with a nano-electrospray ion source . The peptides were separated by C18 reversed phase liquid chromatography using an EASY-nLC 1000 system ( Thermo Fisher Scientific ) . A set-up of pre-column and analytical column was used . The pre-column was a 2 cm EASYcolumn ( ID 100 μm , 5 μm particles ) ( Thermo Fisher Scientific ) while the analytical column was a 10 cm EASY-column ( ID 75 μm , 3 μm particles , Thermo Fisher Scientific ) . Peptides were eluted with a 150-min linear gradient from 4% to 100% acetonitrile at 250 nL min-1 . The mass spectrometer was operated in positive ion mode acquiring a survey mass spectrum with resolving power 70 , 000 ( full width half maximum ) , m/z 400–1750 using an automatic gain control ( AGC ) target of 3×106 . The 10 most intense ions were selected for higher-energy collisional dissociation ( HCD ) fragmentation ( 25% normalized collision energy ) and MS/MS spectra were generated with an AGC target of 5×105 at a resolution of 17 , 500 . Mass spectrometer worked in data-dependent mode . Database searches were performed using the Sequest algorithm , embedded in Proteome Discoverer 1 . 4 ( Thermo Fisher Scientific ) . Proteins in axenic cultures were identified by performing separate searches against the fasta files of the Giardia proteome for each isolate ( GS clone containing 4470 entries and WB clone 9667 entries ) ( available at www . giardiadb . org; giardiadb . org/common/downloads/release5 . 0/ ) . The fasta file for human proteins was downloaded from Uniprot 2015–05 and contained 20192 entries . Proteins in co-cultures were searched against a combined database of Giardia and human proteins in a MudPIT search combining all three replicates . For both searches , the following parameters were used for data processing: Maximum 10 ppm and 0 . 02 Da error tolerances for the survey scan and MS/MS analysis , respectively , trypsin as digesting enzyme , carbamidomethylation of cysteins as fixed modifications , oxidation of methionine and deamidation of asparagine and glutamine as variable modifications , maximum of two miss cleavages sites . The target decoy PSM validator was used to calculate false discovery rate . The search criteria for protein identification were set to at least two matching peptides of 95% confidence level per protein . Identified proteins were subject to gene ontology ( GO ) enrichment analysis to identify their biological as well as proteins class . The analysis was performed using the PANTHER algorithms provided within the Gene Ontology Consortium website ( http://geneontology . org/page/go-enrichment-analysis ) . The results were processed through the GO slim option for biological GO terms , with Bonferroni correction applied for multiple testing ( P < 0 . 05 ) . In addition , the STRING Database ( http://string-db . org/ ) was also used to search for InterPro domains , applying Bonferroni correction at P < 0 . 05 as above . Identified proteins were also analyzed for the presence of secretion signal peptides ( SSPs ) using the SignalP program embedded within the GiardiaDB ( http://giardiadb . org/giardiadb/queries_tools . jsp ) . The search criteria were set to include any of the following; a SignalP-NN conclusion score of 3 , SignalP-NN D-score of 0 . 5 and SignalP-HMM signal probability of 0 . 5 . We used RNA sequencing ( RNA Seq ) or quantitative PCR ( qPCR ) to identify differential gene expression on the RNA level in IECs ( i . e . differentiated Caco-2 cells ) exposed to Giardia ESPs in two different experimental setups ( Fig 1B ) . First , IECs ( 6-well plate ) were exposed to parasite ESPs via a Transwell insert ( 0 . 4 μm pore polyester membrane , Corning , Sigma Aldrich ) . Here , IECs were physically separated from parasite but directly exposed to their ESPs . For this experiment , we used RNA Seq to identify global changes in gene expression . Second , IECs were exposed to 1 , 5 or 10 μg/ml of ESPs from axenic cultures . This aimed at assessing changes in pro-inflammatory gene expression in IECs exposed to ESPs released in axenic culture ( i . e . no IECs ) and assess how IECs respond to different amounts of Giardia ESPs . Changes of gene expression were studied using qPCR . An illustration of the experiments above is depicted in Fig 1B . The experiments below were performed using complete DMEM with 10% HI-FBS and all incubations were performed in a 10% CO2 humidified incubator at 37°C . Before the beginning of all experiments , tissue culture flasks or well-plates were washed twice with warm PBS and incubated with fresh media for 2h . Trophozoite cultures ( 50 ml ) were washed once with warm PBS then cold PBS , incubated on ice ( 10 min ) , counted and pelleted by centrifugation ( 930 xg , 10 min , 4°C ) . Media collected in the insert experiment were centrifuged ( 930 xg , 10 min , 4°C ) , filter-sterilized ( 0 . 45 μM ) and stored at -20°C to be used later for cytokines measurement . Three biological replicates were analyzed with RNA Seq for the insert experiment , whereas four biological replicates were used for qPCR in the other experiment . Each biological replicate had a control ( IECs alone in media ) and IECs exposed to ESPs of either WB or GS isolate . For RNA collection , IECs were lyzed directly in the tissue culture flasks or well-plates using Trizol reagent ( Ambion , Thermo Fisher Scientific ) and stored at -80°C until processed later . In the insert experiment , IECs were washed and replenished with 4 ml of fresh DMEM added directly into the well . Trophozoites were processed as stated above and resuspended in DMEM , from which 2 ml ( 1 x 107 trophozoites ) were added into the Transwell inserts and incubated for 2h or 6h . Media were collected at the end of each time point . In the second experiment , IECs ( 25 cm2 flasks ) were washed and replenished with 10 ml of fresh DMEM . The amounts of protein in ESPs from either the WB and GS isolates were quantified using the Qubit protein kit ( Thermo Fisher Scientific ) and added to flasks at a concentration of 1 , 5 or 10 μg/ml followed by incubation for 2 h or 6h . Media collected from Caco-2-trophozoite interactions were analyzed by ELISA to measure the concentration of cytokines released by IECs in response to parasite ESPs . The Human CXCL8/IL-8 Quantikine ELISA Kit , Human CCL20/MIP-3 alpha Quantikine ELISA Kit and Human CXCL1/GRO alpha Quantikine ELISA Kit were purchased from R&D Signalling and the samples were processed for cytokine measurements following the manufacturer’s recommendations . The results were plotted and analyzed using a four Parameter Logistic ELISA curve fitting provided at http://www . elisaanalysis . com . Samples collected as described earlier were processed using the PureLink RNA Mini Kit ( Ambion , Thermo Fisher scientific ) according to the manufacturer’s instruction . During RNA extraction , a DNaseI treatment step ( PureLink DNase Set , Ambion , Thermo Fisher Scientific ) was performed on the spin columns to remove genomic DNA . The quality of extracted RNA was assessed by checking the 260/280 and 260/230 ratios using a NanoDrop 1000 Spectrometer ( Thermo Fisher Scientific ) and by running samples ( 500 ng ) on a 1 . 5% Tris-Borate-EDTA ( TBE ) agarose gel prepared with 20 mM of guanidium isothiocyanate ( GITC ) . For cDNA library preparation and RNA Sequencing , RNA ( 50 ng each ) from each sample was reverse transcribed according to the instructions provided in the Ion AmpliSeq Transcriptome Human Gene Expression kit ( Revision A . 0 , Thermo Fisher Scientific ) and the generated cDNA was amplified using the Ion AmpliSeq Transcriptome Human Gene Expression core panel ( Thermo Fisher Scientific ) . Primer sequences were partially digested followed by adaptors ligation ( Ion P1 Adapter and Ion Xpress Barcode Adapter , Thermo Fisher Scientific ) and purification using the Agencourt AMPure XP reagent ( Beckman Coulter Inc . , CA , USA ) . Adaptor-ligated amplicons were eluted into the amplification mix ( Platinum PCR SuperMix High Fidelity and Library Amplification Primer Mix , Thermo Fisher Scientific ) and amplified . Amplicons were subject to size-selection and purification using Agencourt AMPure XP reagent ( Beckman Coulter ) and were quantified using the Fragment Analyzer instrument ( Advanced Analytical Technologies Inc . , Ankeny , IA , USA ) with DNF-474 High Sensitivity NGS Fragment Analysis Kit ( Advanced Analytical Technologies Inc . ) . Samples were then pooled , followed by emulsion PCR on the Ion OneTouch 2 system with Ion PI Template OT2 200 Kit v3 ( Thermo Fisher Scientific ) and enrichment using the Ion OneTouch ES ( Thermo Fisher Scientific ) . Samples were loaded on an Ion PI chip Kit v3 and sequenced in the Ion Proton System using the Ion PI™ Sequencing 200 Kit v3 ( Thermo Fisher Scientific ) . Acquired reads from RNA Seq were analyzed using the hg19 AmpliSeq RNA plugin in the Torrent Suite Server with default settings . This analysis tool produces tables with raw read counts as well as normalized expression values for all genes in the Ion AmpliSeq Human Transcriptome panel . For each experiment , the RPKM values were normalized across samples using the moose2 software ( https://github . com/grabherr/moose2 ) . Differential expression was estimated based on Laplace/Normal distributions calculated from replicate samples , computing individual significance values as pij ( + ) =2 ( 1−cdf ( cln ( ri ) −ln ( rj ) ) ) pij ( − ) =2 ( 1−cdf ( cln ( rj ) −ln ( ri ) ) ) with ri and rj being the RPKM values , for up-and down-regulation respectively for all given pairwise comparisons i and j , applying a correction term c based on a normal distribution of read counts . The expectations Ekl ( + ) and Ekl ( − ) for comparing all replicates from condition k with l testing for up- or down-regulation in time point k were estimated as Ekl ( + , − ) =n∏ijpij ( + , − ) for all pij>0 and n being the number of pij values , and Bonferroni-corrected to account for multiple testing . For reporting significance , a threshold of E < 0 . 00001 was applied . Genes with significant change in the level of transcription were also subject to GO Terms analysis ( http://geneontology . org/page/go-enrichment-analysis ) to identify biological or molecular functions as well as protein class . We used the GO slim option with Bonferroni correction applied for multiple testing ( P < 0 . 05 ) . For qPCR experiments , RNA was extracted as above and cDNA was synthesized from 1μg RNA using the RevertAid H Minus First Strand cDNA Synthesis Kit ( Thermo Fisher Scientific ) following the manufacturer’s instructions . qPCR was performed on the genes , il-8 , cxcl1-3 , ccl2 and ccl20 with gapdh used as an endogenous control . The Maxima SYBR Green/ROX qPCR Master Mix ( Thermo Fisher Scientific ) was used in the qPCR reactions with 250 nM of each primer and 10 ng template . Cycling conditions included an initial polymerase heat activation step ( 10 min , 95°C ) , and 40 cycles of 15 sec denaturation ( 95°C ) , 30 sec annealing ( 60°C ) and 30 sec extension ( 72°C ) . The change in gene transcription was calculated using the ΔΔCt method . AP-1 is a transcription factor involved in inducing the transcription of inflammatory genes [28 , 29] . It is activated by MAPKs and could work in conjunction with NFκB to activate gene transcription [28 , 29] . To detect AP-1 activation in response to Giardia ESPs , Caco-2 cells were transfected with a plasmid pGL4 . 44[luc2P/AP1 RE/Hygro] expressing the luciferase reporter gene luc2P ( Photinus pyralis ) under the control of a promoter that has the transcription response element of AP-1 . The pGL4 . 75 Vector ( encoding Renilla luciferase ) was used as a normalisation control and was co-transfected into Caco-2 cells with the pGL4 . 44 plasmid . Both plasmids were purchased from Promega ( WI , USA ) . Transfections were performed in a 24-wells plate format according to the supplier’s protocol , using 1 . 1μg of plasmid DNA/105 cells and the FuGENE HD reagent ( Promega ) . In the beginning of experiment , both parasite and Caco-2 cells were washed and processed as described earlier and the wells were replenished with 500 μl DMEM ( no phenol red as it interferes with luminescence reading ) . Trophozoites were re-suspended in DMEM ( no phenol red ) and 106 trophozoites were added into the Transwell insert in a total volume of 100 μl and incubated for 2h or 6h ( 37°C , 10% CO2 ) . Three wells were used for each time point and the controls . At the end of each incubation , the inserts were removed and the cells were washed ( 3x ) with 200 μl PBS at RT , and lyzed with an equal amount of the Dual-Glo Luciferase Assay reagent . A 100 μl was dispensed into the well of 96-well plate in triplicates and luminescence was read from both plasmids following the instructions of Dual-Glo Luciferase Assay reagent and using an Infinite M200 Pro Tecan machine ( Tecan Group Ltd . , Männedorf , Switzerland ) . Cells with no plasmid ( background fluorescence ) , cells with plasmid alone ( negative control ) , and cells incubated with Phorbol 12-myristate 13-acetate ( PMA ) ( positive control ) served as controls . Three biological replicates were performed in this experiment . To correlate RNA Seq results with those at protein level , we studied the effects of Giardia ESPs on differentiated Caco-2 cells using Western blotting . We tested for the activation/inhibition of mitogen activated protein kinases ( MAPKs ) and the nuclear translocation of nuclear factor kappa-light-chain-enhancer of activated B cells ( NF-κB ) , both of which are involved in inflammatory gene transcription [30 , 31] . Briefly , the insert experiment was repeated as described earlier with the inclusion of three washes with warm PBS ( 37°C ) at the end of each incubation . In the last wash , cells were scraped off and pelleted by centrifugation ( 930 xg , 10 min , 4°C ) and the pellet was lyzed using the NE-PER Nuclear and Cytoplasmic Extraction Reagents ( Thermo Fisher Scientific ) according to supplier’s instructions . Both Halt Protease and Phosphatase Inhibitor Cocktails ( Thermo Fisher Scientific ) were added to lysis buffers during extractions . Cytoplasmic and nuclear fractions were aliquoted and stored at -80°C until later use . To confirm that Giardia ESPs can modulate/inhibit immune signaling in IECs , we repeated the experiment above but IECs were previously treated with lipopolysaccharide ( LPS , Sigma-Aldrich ) ( 10 μg/ml ) or tumour necrosis factor-alpha ( TNF-α , Sigma-Aldrich ) ( 100 ng/ml ) for 2h prior adding trophozoites into the inserts . Trophozoites in inserts and IECs , in the presence of inflammatory signal , were left to interact for 2h and 6h , upon which IECs were processed as above for protein collection . IECs treated with LPS and TNF-α were tested for MAPKs activation/inhibition and the nuclear translocation of NF-κB . Protein samples collected as described above were used for SDS-PAGE and Western blots . Briefly , 30 μg of total proteins were electrophoresed on AnykD-stain-free gels ( Bio-Rad ) ( 100 v , 4°C ) and transferred onto a PVDF membrane ( 100 v , 90 min , 4°C ) . Membranes were washed with Tris-Buffered Saline with 0 . 1% Tween-20 ( TBST ) and blocked with 5% non-fat dry milk in TBST for 1h at RT , followed by incubation with primary antibodies overnight ( 4°C ) . Blots were then washed with TBST ( 3x ) and incubated for 1h at RT with a secondary anti-mouse HRP conjugated or anti-rabbit HRP conjugated antibodies ( 1:5000 dilution , Cell Signaling Technology , MA , USA ) . Blots were developed using the Clarity ECL Western Blotting Substrate ( Bio-Rad ) . For re-probing , blots were stripped using a mild ( 200 mM glycine , 0 . 1% w/v SDS , 1% Tween 20 , pH 2 . 2 ) or harsh stripping buffer ( 2% SDS , 62 . 5 mM Tris , pH 6 . 8 , and 114 . 4 mM beta-mercaptoethanol ) and probed for the loading control , which is either an anti-human GAPDH ( cat no . MAB5718 , R&D Systems , Inc . , MN , USA ) , anti α-tubulin antibody ( Cell Signaling Technology ) or TATA box binding protein ( TBP ) for nuclear samples ( MA5-14739 , Thermo Fisher Scientific ) . To detect the activation of MAPKs ( ERK1/2 , P38 and JNK ) , the following antibodies were used against the phosphorylated and non-phosphorylated forms of kinases: phospho-p44/42 MAPK ( Erk1/2 ) ( cat no . 8544 ) and p44/42 MAPK ( Erk1/2 ) ( cat no . 4348 ) , Phospho-p38 MAPK ( cat no . 4511 ) and p38 MAPK ( cat no . 8690 ) , Phospho-SAPK/JNK ( cat no . 4671 ) and SAPK/JNK ( cat no . 9258 ) , and NF-κB1 p105/p50 ( cat no . 13586 ) . Antibodies were purchased from Cell Signaling Technology and used at the dilution recommended by the supplier . For ESPs labelling with Alexa Fluor 488 , proteins collected from axenic culture were washed ( 3x ) with cold PBS during sample concentration to remove free amino acids and antioxidants that might interfere with protein labelling ( recommended in the kit ) . ESPs ( 45μg ) were incubated with 11 . 3 nmol/μl of Alexa Fluor-488 and excess dye was removed by gel filtration following the instructions in the Alexa Fluor 488 Microscale Protein Labelling Kit ( Thermo Fisher Scientific ) . To visualise ESPs interaction with host cells , chamber slides were washed and replenished with fresh DMEM as above , followed by adding labelled ESPs to the wells at 1 or 5 μg/ml and incubation for 2 h or 6 h ( 37°C , 10% CO2 ) . The amounts of labelled proteins were quantified using a NanoDrop 1000 Spectrometer ( Thermo Fisher Scientific ) . Caco-2 cells incubated in DMEM only ( no Labelled ESPs added ) served as a control . Slides were washed , fixed ( 4% paraformaldehyde in PBS ) and mounted ( Vectashield anti-fade reagent with DAPI , Vector Laboratories , CA , USA ) , excluding the blocking step . The fluorescent label on IECs was visualised using a Zeiss LSM700 confocal microscope ( Zeiss , Oberkochen , Germany ) at the BioVis Core Facility , SciLifeLab , Uppsala , Sweden . The results from the cytokine measurements and differential gene expression for qPCR results were analysed using a one-way analysis of variance ( ANOVA ) to assess overall significance among the tested groups at α < 0 . 05 . When significant , the values from the replicates were processed through the Bonferroni-Holm’s and significance was marked at P < 0 . 05 .
In order to identify proteins in the Giardia secretome , we collected ESPs from Giardia trophozoites grown axenically or in the presence of IECs ( Fig 1A ) . The secretomes of axenic WB ( assemblage A ) and GS ( assemblage B ) Giardia trophozoites were analyzed in a modified serum-free medium ( see Materials and methods ) that could support the full viability of trophozoites for 2h and estimated viabilities of 98 . 74% ± 1 . 03 ( WB , n = 5 ) and 98 . 32% ± 0 . 81 ( GS , n = 5 ) under 6h of incubation . In total , 196 proteins were identified in the secretome of the WB isolate with 149 proteins detected in 2h culture and 180 in 6h culture; 133 proteins overlapped in both time points ( Fig 2A ) . For the GS isolate , 155 proteins were identified including 141 proteins from the 2h culture and 83 proteins from 6h culture; 69 proteins overlapped in both time points ( Fig 2A ) . The reproducibility of the secretome profiles was conserved in the three biological replicates . Full lists of identified proteins , including tryptic peptides , score , coverage and number of peptide spectrum matches ( PSM ) are presented in S1 Table ( WB ) and S2 Table ( GS ) . The secretomes of both isolates were also compared leading to the identification of 122 common secreted proteins ( S3 Table ) . We also collected and analyzed the medium from Giardia trophozoites incubated with differentiated Caco-2 cells ( Fig 1A ) . In total , 248 WB proteins were identified in the co-culture medium , 156 at 2h , 240 at 6h and 148 in both time points ( Fig 2B , S4 Table ) . For the GS isolate , 152 proteins in total were identified , 122 at 2h , 128 at 6h and 98 at both time points ( Fig 2B , S5 Table ) . The top 50 proteins , based on their peptide score , are listed in Table 1 . These proteins overlap with those in axenic culture ( S1 and S2 Tables ) . A comparison was performed between the secretomes of WB trophozoites incubated with ( S4 Table ) and without IECs ( S1 Table ) through which 161 common proteins and 87 interaction-specific proteins were identified ( Table 2 ) . Similarly , an analysis of the secreted proteins from GS isolate with ( S5 Table ) and without IECs ( S2 Table ) identified 111 common proteins and 41 proteins specific to the interaction ( Table 2 ) . Amongst the proteins specific to interactions , 13 proteins overlap between the two isolates ( denoted in Table 2 ) whereas 74 WB trophozoite proteins and 28 GS trophozoite proteins are exclusive to the interaction process and represent an isolate-specific response to IECs . This overall shows that most of the secreted Giardia proteins during interactions with IECs are conserved between the WB and GS isolates but there are assemblage-specific differences . Secreted Giardia proteins in co-culture were analyzed for the enrichment of certain biological functions and for protein class . For the GS isolate , since the current online algorithms do not support GO analysis , orthologous genes in WB were used to perform the quest . The results are presented in Fig 2D and 2E . The largest number of detected proteins have functions associated with metabolism ( 85 proteins in WB and 64 in GS ) with different subgroups in the child linages associated with protein metabolism , amino acid catabolic and metabolic processes , glycolysis , monosaccharide metabolic process and the generation of precursor metabolites and energy ( Fig 2D ) . These metabolic groups were also seen in the secretome of axenic cultures ( S1 Fig ) . Other metabolic functions such as the hexose monophosphate shunt and arginine metabolism could also be identified when secreted proteins were manually delineated into different metabolic pathways ( S1 Fig ) . Furthermore , a nuclease with endonuclease I activity ( Table 1 ) , possibly involved in nucleic acids salvaging , and proteins involved in pyrimidine salvage ( cytidine deiminase and uridine phosphorylase ( UPL-1 ) ) as well as in lipid metabolism were identified in secretome of co-culture ( S1 Fig ) . The lipid metabolic proteins included enzymes involved in phospholipids ( PLs ) remodelling and salvaging fatty acids ( phospholipase B , PLB ) , producing monoacylglycerol ( lysophospholipid phosphatase ) and generating inositol-3 phosphate ( I3P , I3P synthase ) , the precursor for all inositol containing compounds including PLs [32] . These result show that the major part of Giardia secretome is involved in different metabolic functions . The majority of proteins in the two isolates metabolo-secretome fell under four major categories: the hydrolase , dehydrogenase , oxidoreductase and protease groups . The oxidoreductase group contained 25 proteins in WB and 14 proteins in GS ( Fig 2E ) . Compared with axenic culture ( 14 proteins ) ( S2A Fig ) , the WB isolate released 11 additional proteins with oxidoreductase activity including peroxidases when incubated with IECs ( e . g . PFOR , NADH oxidase lateral transfer candidate , peroxiredoxin 1 , FixW protein alcohol dehydrogenases ( ALDs ) , glutamate dehydrogenase and glutamate synthase and a HP GL50803_9355 , Table 2 ) . This suggests a response to counteract IECs oxidative defences such as reactive oxygen species . It has been suggested that oxidative stress provides the trigger to initiate encystation [33] and proteins involved in cyst wall synthesis ( e . g . glucosamine 6-phosphate deaminase and N-acetylglucosamine 6-phosphate mutase ) were released by WB isolate interacting with IECs , corroborating this notion . For GS , on the other hand , peroxidases and antioxidant proteins were already secreted by trophozoites without exposure to IECs ( S2 Table ) and thus the results above show that the two isolates exhibit different anti-oxidative responses during interaction with IECs . The protease group contained 13 secreted proteins in both isolates ( Fig 2E ) and harboured the cysteine- ( cathepsins B and L ) , serine- ( Alanyl dipeptidyl peptidases ) and metallo-type ( Aminoacyl-histidine dipeptidases and Xaa-Pro dipeptidases ) of proteases . For WB isolate , two secreted metalloproteases ( GL50803_8407 and GL50803_3822 ) were released in response to IECs whereas the rest of proteases were the same as those in axenic culture . For GS isolate , the same proteases were detected in both co-culture and axenic culture with two serine proteases ( GL50581_3181 and GL50581_2704 ) being non-orthologous to any WB isolate proteins . Many of the proteins detected in our analysis have been previously reported as immunoreactive proteins during human giardiasis ( S6 Table ) [21] . Amongst these proteins , the variable surface proteins ( VSPs ) are immunodominant during infection [2] and together with the high cysteine membrane proteins ( HCMPs ) they occupied a large portion of the WB isolate secretome ( 23 and 12 , respectively , S1 Table ) . In the GS isolate secretome , lower numbers of VSPs and HCMPs were detected ( 4 and 5 , respectively , S2 Table ) , more likely due to the fragmented genome used in protein identification . VSPs and HCMPs are cysteine-rich proteins and those detected in our analysis have an epidermal growth factor ( EGF ) -like domain in common ( InterPro:IPR000742 , 39 in WB and 10 in GS ) which is also found in other secreted cysteine-rich proteins ( e . g . tenascins , high cysteine proteins ( HCPs ) and neurogenic locus Notch protein precursor , S1 and S2 Tables ) . EGF-like domains are often present in secreted protein [34] and thus , this promoted us to look for proteins with secretion signal peptides ( SSPs ) . A genome-wide screen in the Giardia database showed that 1361 proteins of the WB isolate have SSPs , amongst which 82 proteins were detected in our co-culture secretome analysis ( ~29% , S7 Table ) with 41 of those being N-glycosylated [35] ( S7 Table ) . For the GS isolate , 422 proteins in Giardia DB contain SSPs , 44 were detected in our analysis ( ~29% , S7 Table ) . The majority of proteins with SSPs ( S7 Table ) contained either an EGF-like domain ( 38 proteins for WB and 16 for GS ) or a peptidase C1A domain ( 8 proteins for WB and 8 proteins for GS ) . The detection of a relatively small number of proteins with SSPs in Giardia secretomes was not surprising as this has been previously reported in other protozoan parasites like Trypanosoma . brucei ( ~20% ) and Leishmania donovani ( ~9% ) [36 , 37] , suggesting the presence of alternative secretory pathways . Many protozoan parasites produce extracellular vesicles ( MVs and exosomes ) , which can release proteins without SPPs [38] . MVs have recently been shown to be released from Giardia trophozoites [26] and we could detect two types of vesicles ( 100–250 nm and 100 nm , S2B Fig ) in the supernatants of axenic trophozoite culture . These vesicles might explain the release of proteins without SSPs but further experiments are needed to show how these vesicles are formed and what proteins they contain . The secretome of differentiated Caco-2 cells incubated with WB trophozoites was analyzed for proteins released in co-culture . Overall , 384 Caco-2 cell proteins were identified in the medium of interaction with 21 proteins secreted at 2h , 136 at 6h and 227 at both time points ( Fig 2C ) . The identified proteins , together with the number of peptides , score , coverage and PSMs are presented in S4 Table . A comparison between the secretomes of Caco-2 cells incubated alone ( i . e . control , S8 Table ) and with WB trophozoites ( S4 Table ) identified 308 overlapping proteins ( S9 Table ) and 76 proteins released in response to WB trophozoites ( Table 3 ) . The secretome of Caco-2 cells incubated with GS trophozoites was also analyzed for the proteins released by host cells in response to interaction . In total , 355 proteins were secreted in co-culture , 60 proteins were secreted at 2h , 78 at 6h and 217 at both time points ( Fig 2C ) . The proteins identified , together with the number of peptides , score , coverage and PSMs are presented in S5 Table . The top 50 proteins , based on their peptide scores , are presented in Table 4 . A comparison between the secretomes of co-culture ( S5 Table ) and control ( S8 Table ) identified 310 common proteins ( S10 Table ) and 45 proteins that were specifically released in response to GS trophozoites ( Table 3 ) . Amongst the proteins specific to interaction ( 45 proteins ) 31 proteins overlapped in the response to both isolates . GO enrichment analyses of parasitized Caco-2 cell secretomes ( both isolates , Fig 2F and 2G ) revealed that the majority of proteins have metabolic functions ( 152 protein in response to WB and 135 in response to GS ) such as protein metabolism ( including proteolysis ) , carbohydrate metabolism ( including monosaccharides and polysaccharide metabolism as well as glycolysis ) , nucleobase-containing compounds metabolic process and lipid metabolism ( only WB ) . The same metabolic groups were also seen in the control Caco-2 cell secretome ( S2C Fig ) . One of the big groups that emerged in our analysis was the cytoskeletal proteins ( 41 proteins in response to WB isolate and 32 proteins in response to GS ) . This group included the intermediate filament and the actin family cytoskeletal proteins ( including non-motor actin binding protein in the child lineage ) . Except for the actin family cytoskeletal protein group which was not enriched in control Caco-2 cell secretome , the rest of cytoskeletal protein groups contained more proteins compared to the control secretome . This clearly indicates the effect of Giardia colonization on IECs actin cytoskeleton . An interesting finding is that seven microvilli proteins were detected in the secretome of Caco-2 cells incubated with WB trophozoites ( GO:0005903 , intestinal epithelial brush border ) ( e . g . villin-1 , intelectin-1 , myosin heavy chain-9 and -14 , beta 1 , 4- galactosyltransferase polypeptide 1 , plectin and LIM domain and actin binding 1 ) . These proteins might have been cleaved off/dissociated from damaged microvilli as a result of trophozoite attachment . Two of the proteins that we identified in the parasitized Caco-2 cell secretome are associated with immunological functions . The first protein is a cytokine called macrophage migration inhibitory factor ( MIF ) ( Table 3 ) . MIF is a pleiotropic cytokine that regulates the expression of inflammatory genes ( e . g . TNF-α , cyclooxygenase 2 and inducible NO synthase ( iNOS ) ) [39] , indicating its involvement in innate immune responses . The second protein is complement c3 identified in the secretome of Caco-2 cell incubated with GS only ( Table 3 ) , suggesting differences in Giardia isolates abilities to activate the complement system . In conclusion , we have identified the major secreted proteins of host and parasite during interaction . Our analysis showed that both , the host and parasite , release proteins with similar functions ( sugar , protein , lipid and nucleic acid metabolism ) . Both assemblages/isolates ( A and B ) induced similar responses but there are assemblage-specific differences that might explain observed differences in infectivity and symptoms . Interaction between Giardia trophozoites and IECs in vitro induces the transcription of a large number of genes including the chemokines ccl2 , ccl20 , and cxcl1-3 that are up-regulated up to 100-fold at the RNA level [40] . To test whether Giardia ESPs are capable of inducing similar effects , differentiated Caco-2 cells were exposed to Giardia ESPs through Transwell inserts ( Fig 1B ) for 2h and 6h . Differentially expressed genes ( DEGs ) were identified by RNA sequencing ( RNA Seq ) ( S11 Table ) . Overall , 120 and 87 genes were differentially expressed ( DE ) in IECs exposed to ESPs of WB and GS trophozoites , respectively , with a global gene expression profile showing differences between the two time points and between the two isolates ( S11 Table , Fig 3A ) . At 2h , seven genes were DE in IECs exposed to ESPs of the WB isolate , six of which were up-regulated and one gene ( il8 ) was down-regulated ( Table 5 ) . The up-regulated genes encode immediate early genes [41] , including the protein constituents of AP-1 transcription factor ( FBJ murine osteosarcoma viral oncogene homolog , fos and jun B proto-oncogene , junb ) . To verify AP-1 activation , Caco-2 cells we transfected with a plasmid expressing a luciferase gene under the control of AP-1 transcription response element and luminescence was measured upon cell exposure to Giardia ESPs . At 2h , no significant change was observed in the AP-1 promoter activity with ESPs of either isolates ( 1 . 07 for ESPs of WB isolate and 1 . 12 for ESPs of GS isolate , P > 0 . 05 ) ( Fig 3B ) . At 6h , on the other hand , despite the slight increase in AP-1 promoter activity ( 1 . 17 for ESPs of WB isolate and 1 . 15 for ESPs of GS isolate ) , the average fold change was significant ( n = 4 , P < 0 . 05 ) ( Fig 3B ) . These findings are in line with the RNA Seq results and indicate that AP-1 is activated in response to Giardia ESPs . The gene encoding DUSP1 was the highest up-regulated gene at 2h and the only up-regulated gene in IECs exposed to ESPs of GS trophozoites ( Table 5 ) . Its transcriptional level increased at 6h together with dual specificity phosphatases 4 and 5 ( dusp4 and dusp5 ) , and tribbles pseudokinase 1 ( trib1 ) ( Table 5 ) . The products of these genes play important roles in the regulation of MAPKs’ activity [42–44] . The majority of DEGs ( 120 in WB and 87 in GS ) were up-regulated at 6h ( S11 Table ) with a higher fold change for DEGs compared to 2h ( Table 5 , S11 Table ) . One exception was that the increase in RNA levels il8 in of IECs exposed to GS trophozoite ( 1 . 95 fold ) was not significant . Insulin induced gene 1 ( insig1 ) was the highest up-regulated gene in IECs in response to ESPs of both isolates at 6h ( Table 5 ) and this gene encodes a protein that regulates cholesterol metabolism , lipogenesis , and glucose homeostasis [45–47] . More genes associated with glucose uptake and response to glucose starvation ( Table 5 ) were DE at 6h , indicating that Giardia releases ESPs that interfere with glucose homeostasis . Nuclear receptor subfamily 4 group A member 1 ( nr4a1 ) was the second top up-regulated gene ( ESPs of both isolates , Table 5 ) and this gene has functions associated with cell cycle , inflammation , and induction of apoptosis [48–50] . Another two cell cycle genes associated with response to DNA damage , were amongst the top ten up-regulated genes and these include BTG family member 2 ( btg2 ) [51] and growth arrest and DNA damage inducible alpha ( gadd45a ) [52] ( ESPs of both isolates , Table 5 ) . This suggests that Giardia ESPs induce damaging effects on host DNA and arrests IECs in the cell cycle . The tight junction proteins , claudin 3 and 4 ( cldn 3 and cldn 4 ) , were also up-regulated ( Table 5 ) and these proteins play essential roles in the maintenance of the intestinal epithelial barrier ( IEB ) [53] . To obtain a general overview on the function of DEGs , they were processed through the GO Database for biological and molecular functions . For IECs exposed to ESPs of the WB isolate , cell proliferation ( GO:0008283 ) and MAPK cascade ( GO:0000165 ) constituted the biggest biological groups encompassing 11 genes each . Both chemokines ( e . g . CXCL1-3 and IL-8 ) and growth factors ( e . g . amphiregulin , proepiregulin , Proheparin-binding EGF-like growth factor ) were contained within the cell proliferation group . All chemokine genes , including ccl2 and ccl20 , were listed under chemokine activity ( GO:0008009 ) and cytokine receptor binding ( GO:0005126 ) by molecular function . In addition to these cytokines , the gene clcf1 encoding cardiotrophin-like_cytokine_factor_1 was DE in IECs exposed to ESPs of WB trophozoites . CLCF1 is an IL-6 family cytokine capable of activating NFκB and exerts stimulatory functions on B cells [54] . For MAPK cascade , it was interesting to see genes encoding RNA binding proteins ( zfp36 and zfp36l2 ) within this group , both of which are associated with anti-inflammatory functions [55] . Another DE gene is Regnase 1 ( ZC3H12A ) , an RNase that controls inflammatory responses by inducing mRNA decay of specific cytokine transcripts [56] . The rest of functional groups in this analysis included response to external stimulus ( GO:0009605 ) , locomotion ( GO:0040011 ) , localization ( GO:0051179 ) , behaviour ( GO:0007610 ) and cell death ( GO:0008219 ) . For IECs exposed to ESPs of the GS isolate , the groups cell proliferation , MAPK cascade , cell death and endoderm development ( GO:0007492 ) emerged by biological functions and no specific groups emerged by molecular function analysis . Only cxcl2 , cxcl3 and clcf1 were significantly induced in IECs exposed to ESPs of the GS trophozoites . Overall , based on the transcriptomic profile we could identify a general response in IECs exposed to Giardia ESPs , which involves inducing and regulating inflammatory responses , glucose homeostasis , apoptosis , cell cycle , and maintenance of IEB . Next , we examined which amount of ESPs could induce the transcription of pro-inflammatory genes in IECs . ESPs collected from axenic culture ( 1 , 5 and 10 μg/ml ) were incubated with IECs for 2h or 6h ( Fig 3C ) and RNA levels were assessed with qPCR . At 2h , 5 μg/ml of WB isolate ESPs induced a 2 to 2 . 9-fold increase in RNA levels of il8 , ccl20 , and cxcl1-3 but not ccl2 , scoring the highest for cxcl3 ( Fig 3C ) . The fold change , however , was statistically insignificant for all the genes tested ( P > 0 . 05 ) . The fold change in RNA levels remained below 2 for 1 μg/ml ( not shown ) and 10 μg/ml of ESPs ( Fig 3C ) . At 6h , all genes were significantly up-regulated ( 2 . 84–8 . 46 fold ) in IECs incubated with 5 μg/ml WB isolate ESPs , scoring the highest for ccl20 ( P < 0 . 05 ) and the genes ccl2 , ccl20 , cxcl1 and cxcl3 remained significantly up-regulated ( 2 . 84–4 . 76 fold ) when IECs were incubated with 10 μg/ml of ESPs ( Fig 3C ) . For ESPs of the GS isolate , the fold change at RNA level for all the genes tested at the three concentrations of ESPs was below 2 ( P > 0 . 05 ) ( Fig 3D ) . Nevertheless , at 6h , il8 , ccl20 , cxcl1 and cxcl3 were significantly up-regulated ( 4 . 23–4 . 71 fold ) with il8 being significantly up-regulated at all ESPs concentrations tested and ccl20 and cxcl1 at 10 μg/ml ( Fig 3C ) . The results show that ESPs of both isolates induce variable transcriptional responses of inflammatory genes in IECs and these responses differ with the amounts of ESPs IECs are exposed to . However , direct host-cell interactions have a much stronger effect on the induction of chemokine gene transcription [40] . To assess whether the up-regulated chemokine genes were translated into their protein products , we selected three chemokines ( IL-8 , CXCL1 and CCL20 ) and measured their levels in the collected media from the insert experiment ( Fig 3D ) . The amounts of IL8 , CXCL1 and CCL20 were very low and their concentration was similar or lower than their controls at 6h ( 50 . 2 , 42 . 1 and 57 . 9 pg/ml , respectively ) . A slight increase in the amounts of CXCL1 and CCL20 amounts could be seen at 2h upon IECs exposure to ESPs of the WB trophozoites ( 12 . 9 pg/ml in control versus 18 . 2 pg/ml ) and GS trophozoites ( 24 . 7 pg/ml in control versus 27 . 1 pg/ml ) , respectively ( P > 0 . 05 ) ( Fig 3D ) . Overall , the levels of measured chemokines were either close to control or slightly lower and no significant differences could be seen between IECs exposed or unexposed to ESPs ( P > 0 . 05 ) ( Fig 3D ) . The low levels of measured chemokines indicate that their mRNA levels are post-transcriptionally regulated or the chemokines being degraded upon release from IECs . Giardia ESPs from axenic cultures were labelled with Alexa Fluor488 and added to the medium to visualize their interaction with IECs . Confocal images taken upon 2h and 6h of incubation with IECs showed that the labelled ESPs of WB and GS trophozoites bind to the IECs surface as well as the intercellular space ( i . e . intercellular junctions ) and some are internalized into differentiated Caco-2 cells ( Fig 4 ) . This indicates the presence of ligands or receptors on IECs surface and a potential of the internalized ESPs to modulate cellular processes and signaling . We consequently examined MAPK signaling in IECs exposed to ESPs via inserts because this pathway emerged in the functional analysis of RNA Seq data . Western blot analyses showed a slight decrease in the phosphorylation levels of ERK1/2 and P38 at 2h but an increased level of nuclear translocation of NFκB compared to control ( Fig 5A ) . Despite the slight decrease in ERK1/2 and P38 phosphorylation , their roles in inducing the nuclear recruitment of NFκB cannot be excluded and it indicates a possibility of other factors contributing to NFκB activation ( e . g . growth factors , stress , hypoxia or nutrient depletion ) . At 6h , we could see a marked reduction in the phosphorylation levels of ERK1/2 and P38 compared to control and this coincided with a decrease in the levels of NFκB nuclear translocation ( Fig 5A ) . The nuclear translocation of NFκB , however , was not completely abolished . The phosphorylated form of JNK could not be detected ( S3A Fig ) . This shows that Giardia ESPs actively modulate MAPK signaling to avert the induction of strong inflammatory responses and this effect is built up upon prolonged exposure of IECs to ESPs . To test whether Giardia ESPs can also inhibit inflammatory signaling , we incubated IECs with LPS or TNF-α for 2h , then added Giardia trophozoites into Transwell inserts in the persistence of inflammatory stimuli for 2h or 6h . While the controls exhibited increased phosphorylation of ERK1/2 and P38 as well as nuclear recruitment of NFκB , these levels were reduced in inflamed tissue upon exposure to Giardia ESPs at both time points ( Fig 5B ) . These results show that Giardia ESPs can attenuate inflammatory signaling mediated by MAPK phosphorylation and NFκB recruitment . It is possible that the parasite senses IECs inflammatory signals and release specific protein factors to subvert such effects .
Several recent studies have shed the light on the secretomes of different protozoan parasites and their role in parasite physiology , adaptation to host environment , pathogenicity and immune modulation [36 , 37 , 57–59] . To date , very few Giardia ESPs have been identified , and thus we devised experiments to characterise Giardia secretome , identify secreted proteins that may be involved in virulence and better understand disease mechanism ( Fig 1 ) . We also assessed the effect of Giardia colonization on host cells and identified IECs secretory responses . Our analysis highlighted metabolic functions as a dominant secretory response when Giardia trophozoites interact with IECs ( Fig 6 ) . These functions involve carbohydrate ( including glycolysis ) , protein ( including arginine metabolism ) , lipid ( phospholipid remodelling ) and nucleic acid ( purines and pyrimidines salvage ) metabolism . One striking observation is that the same types of metabolic proteins are released by Giardia and host cells during interactions , indicating competition for acquiring nutrients ( Fig 6 ) . The release of glycolytic enzymes has been previously reported in Giardia [17] and in many parasites [60] including Trichomonas vaginalis [61] , T . brucei [36] and L . donovani [37] . Secreted glycolytic enzymes of parasites have functions associated with virulence , but those of Giardia require further investigation . The protein metabolic group contained proteins similar to those secreted by L . donovani and T . brucei [36 , 37] . In this group , a large number of CPs were identified whose activity is associated with disease induction and immune modulation [12 , 15 , 62] . Herein , we report the identity of secreted CPs ( Fig 6 ) as well as other proteases ( e . g . serine and metalloproteases ) . We also showed a variation in protease numbers between the isolates; an aspect underlying virulence [63] . Little is known about the serine and metalloproteases of Giardia but studies in Entamoeba invadens [64] , Acanthamoeba castellini [65] , Acanthamoeba lugdunensis [66] and T . brucei [67] have identified some roles in differentiation [64 , 68] , pathogenesis ( e . g . degradation of ECM and immunoglobulins ) [64–67] and invasion [69] . It will be interesting to characterize the function of these secreted proteases during Giardia infections . Giardia trophozoites cannot synthesize purines and pyrimidines de novo and rely on exogenous sources for their acquisition [70] . UPL-1 is secreted by Giardia and its gene is up-regulated during interaction with IECs [33 , 71] . This enzyme is involved in pyrimidine salvage and it is highly active in the small intestines [72] corroborating the notion of host-parasite competition for nutrients ( Fig 6 ) . UPL-1 is also an immunogenic protein recognized by sera from giardiasis patients , indicating its potential as a diagnostic and vaccine target [21] . Interacting Giardia and IECs also secrete nucleases but which nucleases’ activity can surpass the other , it is unknown . Nucleases harness nucleic acids for salvaging purines and pyrimidines as reported for E . histolytica [73] , L . donovani [37] and T . brucie [36] . Nucleases of T . brucei , have also been proposed to attenuate nucleic acids-induced inflammatory responses [36] . Giardia trophozoites cannot synthesize lipids de novo and acquire those from the host [32] . PLB is an enzyme secreted by the parasite and IECs into the interaction medium ( Fig 6 ) . PLB is involved in PLs remodeling in Giardia and it localizes to brush border membranes of mature enterocytes in humans [74] . In virulent Candida albicans strains , PLB is suggested to promote host cell damage and lysis , and the deletion of plb attenuated Candida virulence in murine models [75] . I3PS is another ESP secreted by Giardia and Caco-2 cells . I3PS synthesises I3P , the precursor for all inositol containing compounds including PLs [76] . The deletion of i3ps in Leishmania renders the parasite avirulent in vivo [77] but whether it contributes to Giardia’s virulence this requires investigation . Since the above proteins are required for parasite nutrition and thus survival , it will be interesting to test their potential targets for drugs and/or vaccines . Giardia releases proteins with antioxidant functions during growth and interaction with IECs ( Fig 6 ) . This highlights the microaerophilic nature of Giardia [78] and the mechanism by which the parasite maintains a low redox potential extracellularly leading to enhanced intracellular homeostasis . When readily released by the parasite or in response to interaction with IECs , antioxidant proteins can promptly attenuate host ROS during infection as suggested for E . histolytica [79–81] . We previously showed that the transcriptional levels of antioxidant genes vary between the WB and GS isolates during oxidative stress [82] and herein we show differences in the array of secreted antioxidant proteins , further pointing out the differences in oxidative stress responses between assemblage A and B Giardia parasites . Giardia escapes host and environmental stresses by cysts formation and thus encystation is regarded as a mean of survival for the parasite . In response to IECs , both Giardia isolates released proteins involved in cyst wall formation ( Fig 6 ) and these proteins were not detected in axenic culture indicating that host cells provide the signal to initiate encystation . Interestingly , in a recent study that investigated transcriptional changes in bioluminescent WB isolate trophozoites from high density foci in the mice intestines , the authors reported the up-regulation of encystation , oxidative stress and metabolic genes ( carbohydrate , protein , lipid and nucleoside base metabolism ) [83] . Herein , we show that the protein products for many of up-regulated genes in that study are being released into the interaction medium . Nevertheless , we did not see any cyst formation in our in vitro model , indicating that stress alone might not be a sufficient stimuli to complete encystation successfully and possibly requires other factors like bile [84] . Giardia VSPs , HCMPs and tenascin were abundant proteins detected in the secretome of both isolates ( Fig 6 ) . VSPs are constantly released from trophozoite surface and they are involved in immune evasion during infection [2 , 20] . HCMPs are similar to VSPs but lack the c-terminal tail . So far , there is no reports on HCMPs function in Giardia except for being transcriptionally up-regulated during interaction with IECs [33 , 40 , 71] . Tenascins are also up-regulated during interaction with IECs [85] . Despite the lack of true similarity with human tenascins , the presence of an EGF-like domains in these glycoproteins suggests their involvement in protein-protein interaction , cell signaling or adhesion [86 , 87] . Tenascins are also able to bind lectin [88 , 89] and thus a role for Giardia tenascins in host innate immunity have been suggested previously [85] . The fact that 8 out 10 WB isolate “tenascins” are secreted , glycosylated and up-regulated during interaction with IECs [85] might suggest interesting roles during Giardia infection . Only a small percentage of proteins in the parasite’s secretome were identified with SPP . Recently , several arguments have supported the hypothesis that many parasitic proteins are released in EVs , containing cytosolic and plasma membrane proteins but not proteins from intracellular organelles [60] . In this study , we provided EM evidence on the presence of EVs from Giardia trophozoites ( S2 Fig ) . The sorting of EVs cargo , however , is not well understood but the suggestion is that posttranslational modifications ( e . g . glycosylation , ubiquitination , phosphorylation or acylation ) could target proteins for vesicular secretion [36 , 60 , 90] . Whether this is the case in Giardia , this requires further investigation . Functional analysis of parasitized IECs secretome indicated that Giardia trophozoites induce cytoskeletal changes in IECs . It is known that Giardia adheres to IECs very strongly , leaving marks on cell surface and affecting the organisation of the actin cytoskeleton [91–93] . One interesting finding is that Giardia effect on microvilli structure was pronounced by the detection of seven microvilli proteins in the co-culture medium , one of which is villin . Villin plays an essential role in reorganizing microvilli actin filaments as well as actin bundles assembly , capping and severing [94 , 95] . Villin binds phosphatidylinositol 4 , 5-bisphosphate ( PIP2 ) , enhancing actin bundling and lysophosphatidic acid preventing all actin modifying activities [96 , 97] . This protein , however , is cleaved during Giardia infection , uncoupling its protective role from the actin cytoskeleton [62] . The secretome of parasitized IECs contained host proteins with immunological function . Examples are the MIF and complement factor c3 . MIF is a pleiotropic cytokine that induces inflammatory responses mediated by TNF-α , interferon-γ ( IFN- γ ) , IL-1β , IL-12 , IL-6 and , IL-8 , among others [39] . MIF plays a role in resistance to infection with Trypanosoma cruzi [98] , T . gondii [99] and Leishmania major [100] but many studies have also reported its contribution in disease pathology [101–103] . It will be interesting to identify its role during Giardia infections . The complement factor c3 was specifically released by IECs in response to GS isolate , which was previously shown to activate the complement system [104] . In fact , the complement system contribute to trophozoite killing both in vitro and in vivo [105 , 106] and mice with non-functional component system ( deficient in mannose-binding lectin 2 or complement factor 3a receptor [107] ) exhibit delayed parasite clearance [104] . Therefore , while these results show the induction of innate immune responses by parasitized IECs , it also shows that these responses might vary in infections with different isolates/assemblages . To our knowledge , this is the first study that has investigated transcriptional changes in IECs exposed to Giardia ESPs . Interestingly , transcriptome data brought about and highlighted important pathological processes previously shown to occur during Giardia infection . Specifically , the disturbance in glucose homeostasis [108 , 109] and IEB integrity [91 , 92] , cell cycle arrest [27] and apoptosis [93 , 110 , 111] . It could also indicate another pathomechanism that is Giardia ESPs might interfere with cholesterol and lipid metabolism based on the differential expression of insig1 gene . Of note is that transcriptional changes in IECs were not immediate and were only pronounced at 6h , possibly until enough ESPs had accumulated in the media to induce an effect . By comparison , a similar transcriptional profile was seen in parasitized IECs , but transcriptional changes occurred as early as 1 . 5h upon trophozoite attachment [40] . Therefore , while Giardia ESPs could also play a role in disease induction , these effects might be slower and less apparent compared to those induced upon trophozoite attachment to IECs . Giardia ESPs induced the transcription of chemokines genes previously shown to be induced upon trophozoite attachment ( e . g . cxcl1-3 , ccl2 and ccl20 ) [40] . When produced locally , chemokines attract immune cells ( e . g . B cells , T cells , dendritic cells and macrophages ) to the infection site [112] . Giardia ESPs also induced the transcription of il8 , an important neutrophils attractant produced during the early phase of infection . NFκB and AP-1 are TFs involved in the induction of inflammatory genes transcription [28 , 29] and their activity was evident in our results and previously reported by others in response to Giardia ESPs [113] . Despite the activation of both TFs , the upstream signaling pathway leading to their activation ( i . e . MAPK phosphorylation ) appeared to be attenuated but not abolished , even in the presence of inflammatory stimuli . Our transcriptomic data suggests that this attenuation could be mediated by DEGs encoding , dusp1 , dusp4 , dusp5 and trib1 , all of which are known to regulate/inhibit MAPKs’ activity [42–44 , 114–116] . Although the results of ERK1/2 and P38 phosphorylation were inconsistent with a previous report [113] , these discrepancies might be due to the different experimental setup used to study ESPs effects on MAPK signaling . In our model , IECs were exposed to parasite ESPs released directly into the medium whereas in the other study ESPs were added directly to IECs ( HT29 ) . In fact , we got the same result when ESPs collected in the absence of IECs were added directly to Caco-2 cells ( S3B Fig ) . This could suggest that when Giardia senses inflammatory signals it actively releases ESPs to attenuate the pathways leading to cytokines production whereas ESPs produced in the absence of IECs exert an opposite effect . The differential up-regulation of inflammatory cytokines/chemokines genes did not correlate with the amounts of cytokines measured in medium of insert experiment . Indeed , in some instances the levels of IL8 , CXCL1 and CCL20 were lower than their controls , indicating degradation of their mRNAs post-transcriptionally or upon synthesis and release into the medium . Tristetraprolin ( i . e . zfp36 or TTP ) among DEGs , encodes a protein that binds the AU rich element ( ARE ) in the 3’UTR of cytokine transcripts inducing their decay and its role in controlling inflammation is well established in the literature [117 , 118] . Which parasite factors induce TTP transcription are to be identified . Second , in a previous report , Giardia ESPs , specifically CPs , were able to degrade IL8 and this has been shown to attenuate neutrophils infiltration into mice intestines even in the presence of inflammatory stimuli [14 , 15] . Based on our findings it is plausible to propose that ESPs mediate the attenuation of inflammatory responses by promoting the decay of cytokine transcripts and/or cytokines degradation . To conclude , an interesting picture of host-parasite interactions during giardiasis emerge from this and other studies . Parasites produce ESPs that consist of secreted proteins [11 , 17 , 19 , 85] , released surface proteins [20] and EVs [26] . These ESPs affect gene expression , secretion , signaling , metabolism and immune responses in IECs [11 , 16 , 40 , 85 , 113] . Nevertheless , parasite attachment to IECs induces stronger and more complex responses compared to when IECs are exposed to ESPs only [40] . Concurrently , there is a secretory response by parasitized IECs where similar factors are released affecting parasite attachment , metabolism and gene expression [16 , 85] . So far , most studies of Giardia-host cell interactions have been performed with simplified models using a small selection of human cell lines but it will be important to follow up these results using more complex in vitro host systems like enteroids [119] . This can be complemented by in vivo experiments of secreted proteins in mice where trophozoites are mixed with early encysting cells [83] . Thus , Giardia interaction with IECs is an intricate process and further understanding of this cross-talk could be the key for understanding giardiasis .
|
Giardia intestinalis is a major contributor to the enormous burden of diarrheal diseases with 280 million symptomatic human infections ( giardiasis ) per year , mainly in children . Nonetheless , there is poor insight into how Giardia causes disease; it is not invasive and very few virulence factors are known . Here we use proteomics , large-scale protein identification , to identify proteins released by the parasite and host cells when they interact in vitro . Our analyses show that both cell types respond to interaction by the release of specific proteins . These proteins affect the metabolism of host cells and parasites , and many are involved in the modification of host’s immune responses . The secreted parasite proteins bind to host cells and some are internalized , resulting in the modulation of immune-signaling proteins , cell cycle arrest and the induction of cell death . This study provides new insights into host-parasite interactions during giardiasis and this will be the basis for further studies of specific proteins that might explain disease induction and symptoms during giardiasis .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
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"trophozoites",
"parasite",
"groups",
"protein",
"interactions",
"giardia",
"biological",
"cultures",
"dna-binding",
"proteins",
"parasitic",
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2017
|
Characterization of the Giardia intestinalis secretome during interaction with human intestinal epithelial cells: The impact on host cells
|
Many organs of higher organisms , such as the vascular system , lung , kidney , pancreas , liver and glands , are heavily branched structures . The branching process during lung development has been studied in great detail and is remarkably stereotyped . The branched tree is generated by the sequential , non-random use of three geometrically simple modes of branching ( domain branching , planar and orthogonal bifurcation ) . While many regulatory components and local interactions have been defined an integrated understanding of the regulatory network that controls the branching process is lacking . We have developed a deterministic , spatio-temporal differential-equation based model of the core signaling network that governs lung branching morphogenesis . The model focuses on the two key signaling factors that have been identified in experiments , fibroblast growth factor ( FGF10 ) and sonic hedgehog ( SHH ) as well as the SHH receptor patched ( Ptc ) . We show that the reported biochemical interactions give rise to a Schnakenberg-type Turing patterning mechanisms that allows us to reproduce experimental observations in wildtype and mutant mice . The kinetic parameters as well as the domain shape are based on experimental data where available . The developed model is robust to small absolute and large relative changes in the parameter values . At the same time there is a strong regulatory potential in that the switching between branching modes can be achieved by targeted changes in the parameter values . We note that the sequence of different branching events may also be the result of different growth speeds: fast growth triggers lateral branching while slow growth favours bifurcations in our model . We conclude that the FGF10-SHH-Ptc1 module is sufficient to generate pattern that correspond to the observed branching modes .
Branched structures are ubiquitous in nature , and the mechanism of their formation has been investigated for decades both in experimental [1]–[3] and theoretical studies [4] , [5] . Studies some 50 years ago showed that the dimension of the airway in adult lungs depends exponentially on the branch order very well up to the 10th generation [6]; based on subsequent analysis lungs were suggested to be fractals , with fractal dimension close to 3 for the adult human lung [7]–[14] . Various algorithms that generate lung trees with morphometric characteristics similar to adult mammalian lungs have been reported [4] , [5] , [15] , [16] . In a geometrically realistic model Kitaoka and co-workers required nine basic and four complementary rules to fill the 3-dimensional thoracic cavity with a branching model [16] . The rules that they defined were to a large part similar to those that were later discovered in a careful experimental study of the growing lung [17] . In this later experimental study it was shown that the branching process during lung development is remarkably stereotyped and that the branched tree is generated by the sequential use of three geometrically simple modes of branching , i . e . domain branching , planar bifurcation , and orthogonal bifurcation [17] . Errors like branch displacement are observed in less than 1% of all branching events [17] . Branching is thus not a stochastic process , but must be controlled . This raises the question of how the information required to generate a structure of such complexity is encoded in the genome . Since branched structures are created by recursive processes , a limited number of proteins can , in principle , control all of the branching in the lung from the trachea to the terminal bronchioles [3] . Genetic studies have led to the identification of key regulatory genes and morphogenes that control lung development , most importantly Fibroplast growth factor ( FGF ) 10 , Sonic hedgehog ( SHH ) , and Bone morphogen protein ( BMP ) 4 [1] , [2] , [18]–[23] ( Figure 1a ) . FGF10 is expressed in the distal mesenchyme around the epithelial bud tip and is essential for the lung bud formation , proliferation of the endoderm , and directional outgrowth [3] , [24] , [25] . FGF10 signals mainly through the epithelial FGF receptor FGFR2 , and inactivation of FGFR2 in the lung epithelium results in the disruption of lobes and small epithelial outgrowths that arise arbitrarily along the main bronchi [25] . FGF induces the expression of SHH , BMPs , and Sprouty which in turn limit the expression and signalling of FGFs [24] , [26]–[29] . SHH signals through its receptor Patched ( Ptc ) , and affects FGF10 and BMP4 activity . While many studies show that BMPs regulate lung development their detailed effects have been difficult to disentangle [1] . Adding BMP4 to organ cultures of the whole embryonic lung promotes branching morphogenesis and increases the number of peripheral epithelial buds [30] . Addition of exogenous BMP4 protein to mesenchyme-free endoderm cultured in vitro with FGFs , on the other hand , inhibits proliferation , secondary budding and differentiation [28] , [29] , [31] . Both overexpression of BMP4 and a conditional knock-out result in similar lung phenotypes [32] , [33] , suggesting that correct BMP4 levels are essential for normal lung development . These may be maintained by the many negative feedbacks that control BMP activity . Theoretical studies suggest that physical forces can play a key role in lung branching morphogenesis [34]–[37] . Recent studies demonstrate that the mechanical stresses do influence branching morphogenesis [38] . Increased internal pressure leads to an increase of lung branching in in vitro cultures [39] , and cellular contractility is critical for branching morphogenesis of the lung . Inhibiting actomyosin-mediated contractility in whole lung explants decreases branching [40] , whereas activating contractility increases branching [41] . A qualitative model that described epithelial branching in culture experiments showed that both the mechanical strength of the cytoskeleton and the reaction-diffusion kinetics can in principle affect branching morphogenesis [36] , [42] . Work on mammary glands further suggests that the geometry of tubules might dictate the position of branches [43] . Computational models can explore the impact of the signaling interactions , physical forces and domain geometries and thus discern a minimal set of rules and interactions from which the observed pattern can emerge . Hirashima and co-workers recently proposed a simple three component model on a 2-dimensional lung bud cross-section [44] to explain the mechanistic basis of different branching modes . The model focused on the interactions between SHH , transforming growth factor ( TGF ) -beta and FGF10 and suggests that domain length and shape can have a strong impact on the distribution of morphogenes and the selection of branching points in the developing lung . This prediction , however , hinges on a particular distribution of TGF-beta ( constant at the stalk ) and SHH ( fixed at the tip ) and is valid only with a particular type of boundary condition ( impermeable lung boundaries ) which is unlikely to apply ( Figure S1 ) . Turing-type models have been suggested as an alternative to explain the emergence of regular patterns as observed during lung branching morphogenesis [45] , [46] . However , to our knowledge no such mechanistic Turing model has yet been formulated for the lung . Here we present a reaction-diffusion model that we developed based on available information from the literature . The Turing-type model reproduces available experimental data both in wild type and mutant mice and provides a mechanistic explanation for the different lung branching types . We further show that the rate with which the lung bud grows can determine the branching mode .
The lung tip can be represented as a cylinder with an internal radius of and an external radius of 100 ; the thickness of the lung epithelium can be estimated from microscopy data as 5–10 [32] , [59] . To keep the calculations as simple as possible while retaining a realistic geometry we use a 2D slice in Cartesian coordinates along the lung bud axis of symmetry as shown in Figure 1b . SHH is produced in the epithelium [1] , [2] and FGF and Ptc are produced in the surrounding mesenchyme [1] , [2] . There is no experimental evidence that the mesenchyme or epithelium are surrounded by any insulating layer and accordingly the boundaries are permeable in our simulations . SHH and FGF can thus diffuse unhindered outside of the epithelium and the mesenchyme as well as in the lumen which is filled with a liquid . The unhindered diffusion of SHH and FGF in the lumen and interstitial space is reflected by the diffusion coefficient which is much larger than the diffusion coefficients , , that apply in the tissue; the receptor Ptc is a membrane protein and therefore cannot diffuse into the cavities . The concentrations of FGF and SHH infinitely far from the mesenchyme are assumed to be zero . We note that the predictions of our model are independent of the boundary conditions and similar results are obtained in simulations with zero-flux boundary conditions at the boundary of the lung tissue ( see section Robustness of the Observed Pattern for details ) . We start all our simulations with no species present , i . e . we are setting all concentrations to zero at . We consider two modes of 1-dimensional growth along the lung stalk: ( 1 ) uniform growth ( stretching ) of the domain and ( 2 ) local growth at the tip of the lung . To conserve mass ( rather than concentration ) the reaction-diffusion equations ( Eqs 6–8 ) must be expanded to include the advection and dilution terms [60] , i . e . ( 9 ) where denotes the growth speed . For homogeneous growth at rate we then have ( 10 ) where denotes the initial height of the lung tip , the height of the lung tip , and denotes time . The domain size and the time scale of the process are well established [17] , [24] . The measurement of the in vivo kinetic parameter values on the other hand is complicated and typically parameter values are known only from experiments in related systems [52]–[54] . To reduce the number of unknowns we non-dimensionalize the equations and thereby remove five independent parameters . We use , the internal radius of the lung bud , as characteristic length scale of the model and as its characteristic time scale . Moreover , we non-dimensionalize the FGF concentration with respect to the Hill constant , i . e . , and the SHH and Ptc-1 concentrations with respect to , i . e . , with . Equations 6–8 can then be rewritten in dimensionless form; the dimensionless parameters and variables are summarised in Table S1 . ( 11 ) It should be noted that the Laplacian is now with respect to the non-dimensional space variables and . Five parameters have been removed and the patterning mechanism no longer depends on absolute values of diffusion and decay constants , but only on the relative diffusion coefficients and the relative decay rates . Similarly , the absolute concentrations do not matter , but only the relative concentrations ( as a result from the relative expression and decay rates ) relative to the Hill constants and the effective binding constant . The value of the Hill coefficient was set to to account for possible cooperatively effects; however , the model gives very similar results with other values of ( Figure S4 ) . It should be noted here that the stochiometry of SHH and Ptc complex at which patterning is observed is not limited to the case m = 2 , n = 1 that we analyse in this manuscript . Similar patterns are observed as long as , ( see Figure S5 for details ) . The PDEs were solved with finite element methods as implemented in COMSOL Multiphysics 4 . 1 . COMSOL Multiphysics is a well-established software package and several studies confirm that COMSOL provides accurate solutions to reaction-diffusion equations both on constant [61] and growing two-dimensional domains [62]–[64] . Mesh and the time step were refined until further refinement no longer resulted in noticeable improvements as judged by the eye ( Figure S6 ) . When simulations were performed on an open domain the bulk solution conditions was implemented at a distance from the mesenchyme , where is the maximum time of model evaluation . It was shown that beyond this , the effects of diffusion in not important on the experimental time scale [65] . A local stability analysis was performed in the following way: parameter values were taken as indicated in Table 1 , further parameters were varied one by one until qualitative change of pattern were observed ( different number of FGF , SHH and Ptc spots ) . Accuracy of parameter value estimation was 10% or higher . The approach to estimate robustness to spatial parameter variability was adapted from ref [66] . Parameter values were assumed to be given by the formula , where is normally distributed random function with a mean value of zero and half width . The half width of the distribution was equal for all parameters , except geometrical which were not varied .
Since the model is an example of a Schnakenberg Turing-type model [58] we expected to find parameter ranges for which we would observe the emergence of FGF patterns on the lung-shaped domain . Indeed such pattern emerged from spatially uniform initial conditions . We note that the observed distribution and expression pattern correspond overall rather well to experimental observations , but since quantitative data on protein concentration distributions are not available we have to restrict ourselves to a qualitative discussion of distribution patterns . We therefore deliberately left out scale bars for better readability . Dark red colours denote the highest concentrations while dark blue colours denote the lowest concentrations . FGF10 induces SHH expression and SHH expression is highest in the epithelium adjacent to the mesenchyme with high FGF10 concentrations ( Figure S7b , e ) as also observed in experiments [24] , [32] , [48] , [67] . In situ data seem to suggest that the expression domains of Ptc-1 and Shh coincide [24] , [68] , [69] but the spatial resolution of the data may be too low to reveal the closed juxtaposition predicted by the model . Different parameter ranges resulted in steady-state patterns with FGF10 either centered at the lung bud tip ( Figure 2a ) or concentrated towards the side of the tip ( Figure 2d ) . Experiments have previously demonstrated that lung tips grow towards regions with a high FGF10 concentration [59] and accordingly FGF10 centered at the lung tip will support further outgrowth of the lung tip while FGF10 centered at the sides will induce lateral outgrowth . We thus suggest that the two types of patterns that we observe are likely to correspond to the different branching modes , i . e . lateral branching would thus correspond to the FGF10 pattern in Figure 2a with FGF10 spots at the tip and at the side , while bifurcation would correspond to the FGF10 pattern in Figure 2d with FGF10 centered only to the side but towards the tip . Our model cannot reproduce domain branching or the difference between planar and orthogonal bifurcations as these events are intrinsically three dimensional . Here we should note that the model generates pattern similar to those discussed above if extended to the third dimension ( Figure S8 ) . However , a much wider range of patterns is possible in 3D as will be discussed in detail in a separate manuscript ( Menshykau and Iber , in preparation ) . Going forward we will restrict the presentation to the FGF10 concentration pattern as these appear to mainly guide lung outgrowth . Since the parameters are difficult to determine accurately in experiments it was important to check how sensitive our results would be to variations in parameter values . We carried out a local stability analysis by altering each parameter value independently . Here we note that the non-dimensional parameters represent relative dimensional parameters . The patterning mechanism is thus robust to a parallel change in the parameter pairs listed in Table S1 , and the value of most relative parameters can be changed by 20%–30% without changing the type of the observed pattern ( Figure 3 ) . At the same time almost each parameter ( except for the degradation rate of the receptor , ) can be employed to switch the pattern between lateral branching ( Figure 3 , blue ) and bifurcation mode ( Figure 3 , red ) . The mechanism thus appears to be robust to noise yet sensitive to regulation . We note that virtually all parameter values could be affected by the many additional interactions that have been described but that we chose to ignore in this simple model that focuses only on the core of the regulatory mechanism . The domain that we chose to solve our model on is an idealization of realistic domains . We therefore also checked the impact of domain deformations ( Figure 4 ) . The lateral branching mode is indeed robust to deformations of the domain geometry , i . e . to an increased radius of the epithelium ( Figure 4a ) , the mesenchyme ( Figure 4b ) or a truncated bud ( Figure 4c ) . Similarly , the boundary conditions are not critical and similar pattern emerge with zero-flux boundary conditions both in the lateral ( Figure 4 d ) and in the bifurcation mode ( Figure 4 e ) . Linear stability analysis of Equation 11 carried out with parameter values as used to simulate lung branching on the domain with no-flux boundary conditions ( Figure 3 d , e ) showed that pattern arise because of the diffusion driven instability and therefore Turing type . Since lung buds branch as they are growing out we wondered how the growth speed and type would affect patterning . Figure 5 shows the FGF10 distribution on a growing lung bud where growth is restricted to the lung tip . At the concentration of FGF is high at the tip of the growing lung , and further regions of high concentration of FGF10 appear at the lung stalk as the lung grows out ( Figure 5 a ) . Importantly new regions of high FGF10 concentration emerge close to the tip . This pattern corresponds to the lateral branching mode . At a 4-fold lower growth speed , ( Figure 5 b ) , regions of high FGF concentration appear only at the sides of the lung tip but are absent from the tip itself . This pattern would thus correspond to the bifurcation mode of branching . If the lung bud grows uniformly in the entire domain the patterning is similar with an important difference: regions with high FGF10 concentration can appear at any position within the domain ( Figure S9 ) . Both the insertion of branches directly behind the tip and the insertion of new branches at the proximal side of the stalk have been observed . Similarly , both uniform proliferation ( Metzger and co-workers , personal communication ) , [17] and enhanced proliferation at the tip [70] have been observed . Those experiments that report a concentration of proliferating cells at the tip find 2 . 5 times more BrdU-stained cells ( a marker for dividing cells ) at the tip than in the stalk [70] , and in our model branching points appear behind the tip as long as the growth rate in the tip is at least 2–3 times larger than in the stalk . We therefore suggest that different lung branches may be growing differently , and that this may explain the different positions at which new branches emerge relative to the tip . Earlier we showed that the pattern on a constant domain is robust to small parameter variations . To test that the pattern is robust to small random changes also on growing domains we explored the patterning mechanism if parameter values are drawn from a Gaussian distribution with different standard deviations ( see Model section ) . Figure S10 shows that the domain branching mode remains stable as long as standard deviations of the random variables do not exceed 0 . 2–0 . 3 of the reference value presented in Table 1 . An important test for the suitability of a mathematical model is its consistency with a wide range of independent experimental observations . Lung branching morphogenesis has been studied intensively and a large body of experimental results exists to test the model with . These include a large number of in part counterintuitive mutant phenotypes of key signaling proteins in mice [1] . Since our model is restricted to FGF , SHH and Ptc-1 we will focus on mutations in those genes . The computational model reproduces all full knock-outs . However , these results are trivial since the lungs in mutants with fully knocked-out genes are severely truncated or do not form at all [7] , [49] , [71]–[73] . Given the key importance of all three components in the model no pattern is observed if any component is eliminated .
We have developed a model of the core signaling interactions that governs lung branching morphogenesis ( Figure 1a ) . We find that the experimentally described interactions give rise to a Schnakenberg-type Turing patterning mechanism which leads to the self-organized emergence of FGF10 pattern from homogenous initial conditions during in silico lung bud development . The predicted pattern are overall consistent with experimentally observed expression pattern both in wildtype and mutants , and the model predicts the reported increased spacing between FGF10 pattern in mutants with reduced FGF10 expression . The latter is a non-trivial prediction that cannot be explained with models reported earlier [36] , [42]–[44] . The parameter values are largely unknown for the developing lung , but many of the parameters have been established in other model systems ( Table 2 ) . To reduce the number of unknown parameters we non-dimensionalized the model and our conclusions thus only hinge on relative parameter values . In particular , we require that SHH and FGF10 diffuse about a 100-times faster than the receptor Ptc . Receptors are membrane proteins and are known to diffuse some 100–1000-fold more slowly than proteins in solution [55] , [56] . The diffusion of SHH and FGF10 in the fluid-filled cavities , , is again some 10-fold higher as is common for unhindered diffusion of proteins [81] . Since the domain size and the time span of the developmental processes are well known also the absolute values of the parameters can be estimated from their non-dimensional counterparts ( Table 2 ) , and we note that all parameter values are within physiological ranges established in other model organisms , i . e . [52] , [53] , [81] . Finally we note that introducing the simplifying quasi-steadystate assumption for the formation of the SHH-Ptc complex does not affect the observed pattern as long as the non-dimensional binding and unbinding constants are of order 1 which is in the likely physiological range . The model shows that the different branching modes could result from different patterns of FGF10 . Thus for certain parameter ranges FGF10 accumulates at the tip of the lung bud . Since FGF10 induces outgrowth towards the highest FGF10 concentration this should lead to an elongation of the lung bud . As the lung bud is elongating at the tip new FGF10 spots emerge at the stalk of the lung bud close to the tip . These spots would lead to the lateral outgrowth of the lung bud and thus to lateral branching . For other parameter ranges FGF10 is absent from the lung tip and concentrates towards the sides . The lung bud would thus no longer elongate but grow out towards the sides which could be interpreted as the bifurcation branching mode . Since we only consider a 2D slice of the lung bud the model cannot differentiate between planar and orthogonal bifurcations . Interestingly , most parameter values can alter the FGF10 distribution and thus the mode of branching ( Figure 3 ) . An increase in the diffusion constants or a lowering in domain size favour bifurcations while enhanced protein production or reduced decay tend to favour lateral branching . This may explain why genetically different individuals tend to have different branching patterns . At the same time this offers regulatory control to the many signaling factors that can affect these rates , but which we chose to ignore in this simple model that focuses on the core signaling proteins . Thus BMP signaling may lower the rate of FGF10 expression or interfere with the FGF-dependent increase in SHH expression . Both effects would favour bifurcations over lateral branching . BMP-dependent induction of Gremlin and Noggin on the other hand would lead to the sequestration of BMPs and thus limit the impact of BMPs . A strong increase or decrease in BMP activity may then move the SHH and FGF10 expression rates outside the patterning range . This may explain the detrimental impact of both Bmp overexpression and conditional knock-out on lung branching morphogenesis [32] , [33] . Further computational modelling combined with experimentation will be required to clarify this . The effective diffusion constants may be affected by the expression of glycoproteins as previously reported for the morphogen Dpp [82] . Growth has previously been reported to strongly affect pattern selection in Turing models [83] . Indeed the rate of growth also alters the branching pattern in our simulations ( Figure 5 ) . Thus we observe FGF10 pattern characteristic of lateral branching at high growth speeds and FGF10 pattern characteristic of bifurcations at low growth speeds . The growth rate used to model the lateral branching mode in our model is around 14 and gives rise to two new branches per day with branches separated by approximately 150–200 ; this is well in agreement with experimental observations [17] , [24] . To simulate the bifurcation mode of branching we use a growth rate of 3 . 6 which is close to the growth speed estimated from data in Metzger and co-workers [17] . We can speculate that the concentration of FGF10 affects the speed of outgrowth such that changes in the concentration during outgrowth would determine the sequence of the branching events . For our particular choice of parameters we observe lower FGF10 concentrations in spots close to the tips of rapidly growing lung buds ( Figure 7 ) which may lead to bifurcations in the next generation . More proximal lateral spots have higher FGF10 concentrations , and these branches may grow out to longer length as indeed observed for some of the proximal branches . We further note that the position at which new branches appear depends on the growth mode . Thus if growth is at least 2–3 times faster at the tip then new FGF10 spots emerge directly behind the tip . In case of more uniform growth FGF10 spots appear also in the more proximal domain . Both growth modes and patterning dynamics have been observed during lung branching morphogenesis , and we therefore suggest that both growth modes exist in the developing lung and lead to the different patterning sequences . Further advancements in our understanding of lung branching morphogenesis will require the development of three-dimensional models where the local growth rate is coupled to the FGF10 concentration and the inclusion of more signaling factors , most importantly those of BMPs . The parameterization and validation of such models will require new experimental data that reveal the dynamics of the three dimensional dynamics of branching and that quantify the epithelial and mesenchymal responses as well as the growth speed relative to the FGF10 concentration . Such information can now be acquired with the help of optical projection tomographs [84] , and this method has been already used to capture the three dimensional dynamics of developing kidney [85] . Further advances in experimental techniques can thus be expected to provide exciting new insights into the regulatory processes of branching morphogenesis during organ development .
|
Most organs of higher organisms , such as the vascular system , lung , kidney , pancreas , liver and glands , are heavily branched structures . The branching process during lung development has been studied in great detail and is remarkably stereotyped . The branched tree is generated by the sequential , non-random use of three geometrically simple modes of branching . While the branching sequence is identical in mice of identical genetic background it differs between mouse strains . This suggests that the positioning of branch points and the type of branching sensitively depends on information encoded in the genome . Encoding every branching point independently in the genome would require a large number of genes , and it is more likely that a recursive , self-organized process exists that determines the patterning . While many regulatory molecules have been identified an integrated understanding of the regulatory network ( program ) is missing . Based on available experimental data we have developed a model for lung branching . The model correctly predicts branching phenotypes in mutants and suggests that also the growth speed of the lung tip can affect the positioning and type of the next branching event .
|
[
"Abstract",
"Introduction",
"Model",
"Results",
"Discussion"
] |
[
"developmental",
"biology",
"organism",
"development",
"biology",
"computational",
"biology"
] |
2012
|
Branch Mode Selection during Early Lung Development
|
Trichinellosis is a serious zoonositc parasitosis worldwide . Because its clinical manifestations aren’t specific , the diagnosis of trichinellosis is not easy to be made . Trichinella spiralis muscle larva ( ML ) excretory–secretory ( ES ) antigens are the most widely applied diagnostic antigens for human trichinellosis , but the major drawback of the ES antigens for assaying anti-Trichinella antibodies is the false negative in the early Trichinella infection period . The aim of this study was to characterize the T . spiralis putative serine protease ( TsSP ) and to investigate its potential use for diagnosis of trichinellosis . The full-length TsSP sequence was cloned and expressed , and recombinant TsSP ( rTsSP ) was purified by Ni-NTA-Sefinose Column . On Western blotting analysis the rTsSP was recognized by T . spiralis-infected mouse serum , and the natural TsSP was identified in T . spiralis ML crude and ES antigens by using anti-rTsSP serum . Expression of TsSP was detected at various T . spiralis developmental stages ( newborn larvae , muscle larvae , intestinal infective larvae and adult worms ) . Immunolocalization identified the TsSP principally in cuticles and stichosomes of the nematode . The sensitivity of rTsSP-ELISA and ES-ELISA was 98 . 11% ( 52/53 ) and 88 . 68% ( 47/53 ) respectively ( P > 0 . 05 ) when the sera from trichinellosis patients were examined . However , while twenty-one serum samples of trichinellosis patients’ sera at 19 days post-infection ( dpi ) were tested , the sensitivity ( 95 . 24% ) of rTsSP-ELISA was distinctly higher than 71 . 43% of ES-ELISA ( P < 0 . 05 ) . The specificity ( 99 . 53% ) of rTsSP-ELISA was remarkably higher than 91 . 98% of ES-ELISA ( P < 0 . 01 ) . Only one out of 20 serum samples of cysticercosis patients cross-reacted with the rTsSP . Specific anti-Trichinella IgG in infected mice was first detected by rTsSP-ELISA as soon as 7 dpi and antibody positive rate reached 100% on 10 dpi , whereas the ES-ELISA did not permit detection of 100% of infected mice before 16 dpi . The rTsSP is a potential early diagnostic antigen for human trichinellosis .
Trichinellosis is an important food-borne parasitic disease worldwide . Trichinella infection occurs by ingesting raw or undercooked meat containing Trichinella muscle larvae [1] . T . spiralis is the main etiological agent of trichinellosis [2] . Outbreak of human trichinellosis was recorded in 55 countries around the world , and there were 65 , 818 cases and 42 deaths from trichinellosis reported from 41 countries during 1986–2009 [3] . Fifteen outbreaks of trichinellosis were documented in mainland China during 2004–2009 and pork is the dominating infection source [4 , 5] . A survey showed that the prevalence of porcine Trichinella infection in small pig farms in central China varied from 0 . 61% to 3 . 79% during 2010–2015 , although the larval burdens in infected pigs was less than 2 larvae per gram of muscles [6 , 7] . Hence , trichinellosis has a public health hazard and an economic impact in meat food safety [8] . Since the symptoms and signs of trichinellosis aren’t specific , the diagnosis of trichinellosis isn’t easy to be established according to the clinical manifestations of this disease [9] . At present , the serological test widely applied for diagnosis of human trichinellosis is to detect anti-Trichinella IgG by ELISA and Western blotting with T . spiralis muscle larvae ( ML ) excretory/secretory ( ES ) antigens [10] , but the principal drawback is the false negative in the early phase of this infection [11] . The occurrence of a 2–3 week window period of anti-Trichinella antibody negative is probable duo to the fact that the major ML ES antigen epitopes are the phase-specific for ML and not recognized by anti-Trichinella antibodies triggered by intestinal infective larvae ( IIL ) at 6 hours post infection ( hpi ) and adult worm ( AW ) at 3 dpi of the nematode in the early stage of Trichinella infection [12] . The ES antigens generated by the IIL and AW might firstly be exposed to host’s immune system and induced the generation of specific antibodies against the nematode . The recent investigation indicated that AW crude antigen positively reacted with swine and mouse infection sera at 7–8 dpi [13 , 14] . On Western blot analysis , the recombinant T . spiralis cystatin-like protein ( rTsCLP ) of IIL stage was probed by porcine infection sera at 15–20 dpi [15] . Anti-Trichinella IgG in serum samples of T . spiralis-infected mice was detected by ELISA using ES antigens of AW or IIL as soon as 8 dpi [16 , 17] . Therefore , it is likely that the diagnostic markers for early Trichinella infection will be exploited from the enteral worms of T . spiralis [18] . In our previous studies , immunoproteomics was used to investigate the early antigens for serodiagnosis of trichinellosis , and a putative serine protease was identified in the ES proteins from T . spiralis IIL and AW by mouse infection sera at 8–10 dpi and early trichinellosis patients’ sera at 19 dpi [12 , 19] . Additionally , the T . spiralis putative serine protease ( TsSP ) ( GenBank accession no . ABY60762 ) was highly expressed in surface proteins of IIL stage compared with those of ML stage [20] . The aim of this study was to characteriz the TsSP and investigate the prospective diagnostic values of recombinant TsSP ( rTsSP ) for early trichinellosis .
The present study was performed in the light of National Guidelines for Experimental Animal Welfare ( MOST of People’s Republic of China , 2006 ) . All animal care and use in our research were reviewed and approved by the Life Science Ethics Committee of Zhengzhou University ( No . SCXK 2015–0005 ) . All the human serum samples were collected from adults , and the written informed consent was acquired from the adults before samples were used . T . spiralis isolate ( ISS534 ) utilized in our study was acquired from a naturally infected domestic swine in Henan Province of central China . This isolate was passaged in BALB/c mice in our department . Six-week-old female BALB/c mice were provided by the Experimental Animal Center of Zhengzhou University ( Zhengzhou , China ) . Mice were kept with specific pathogen-free conditions under suitable temperature and humidity . Fifty-three serum samples from trichinellosis patients were obtained from two outbreaks of human trichinellosis in southwestern China [17] . The sera from patients with paragonimiasis ( n = 20 ) , schistosomiasis ( n = 34 ) , clonorchiasis ( n = 7 ) , cysticercosis ( n = 20 ) , echinococcosis ( n = 20 ) and sparganosis ( n = 7 ) were conserved in our laboratory . The diagnosis of these patients was established by fecal parasitological examination or serum specific antibody detection [11 , 21] . The sera from 104 presumably healthy persons , who came from non-endemic areas of trichinellosis and assayed negative for the before-mentioned helminthiases , were also examined in our study . In order to observe the dynamics of anti-Trichinella IgG , nine mice were infected orally with 300 T . spiralis ML . About 100 μl of tail blood was collected from infected mice on alternate days during 2–30 dpi and serums were isolated . Serum samples from normal mice were obtained and utilized as the negative control . T . spiralis ML were obtained from experimentally infected mice at 35 dpi by using the artificial digestion method as described [22 , 23] . The IIL were recovered from intestines of the infected mice at 6 hpi [24] , and the adult worms ( AW ) were separated from mouse duodenum and jejunum at 3 and 6 dpi , respectively [17] . The newborn larvae ( NBL ) were obtained from the adult females cultured in vitro in RPMI-1640 with 10% fetal bovine serum ( FBS; Gibco ) at 37°C in 5% CO2 for 24 h [25] . The crude soluble antigens of AW , NBL , ML and IIL , and the ML ES antigens were produced as described [26 , 27] . The complete TsSP cDNA sequence was acquired from the GenBank database with accession no . ABY60762 . The Pepstats software was applied to predict molecular weight ( MW ) , isoelectric point ( pI ) and transmembrane helices of the TsSP protein [28 , 29] . The putative N-glycosylation site was verified with the NetNGly1 . 0 server ( http://www . cbs . dtu . dk/services/NetNGlyc/ ) . The potential B and T cell epitope of the TsSP was calculated with the DNAStar software and the online server of BepiPred ( http://www . cbs . dtu . dk/services/BepiPred/ ) , respectively [30] . The tertiary structure of the TsSP protein was predicted on the Expasy website ( http://web . expasy . org/ ) . The identification of protein motifs and catalytic triad of the TsSP was from aligning the multiple protein sequences [31] . The total ML RNA was extracted with Trizol reagent ( Invitrogen , USA ) . The full-length TsSP sequences were amplified via PCR with specific primers carrying enzyme BamHI and PstI sites ( bold and italicized ) ( 5'-GGGATCCATGATCCTTTTCAAGTGCTTATTTCT-3' and 5'-GCGCTGCAGTCAGCAAACTCAATTTATTTAGAT-3' ) . The TsSP gene coding regions without a 18 amino acid signal peptide were produced by PCR with oligonucleotide primers carrying enzyme BamHI and PstI sites ( bold and italicized ) ( 5'-TTCGGATCCAATTATGAA TGTGGCACCTTAC-3' and 5'-CCGCTGCAGTTAACGGAAAAAAGTGAATGAT-3' ) . PCR amplification reaction included 25μl premix ( DNA polymerase , dNTPs and PCR buffer ) , 0 . 5 μl cDNA , 0 . 4μl DNA polymerase , 1 . 0 μl 10 μM of each primer , 22 μl ddH2O . The cycling procedure was as follows: 98°C for 5 min; 30 cycles of at 94°C for 3min , 94°C for 45 s , 60°C for 45 s , 72°C for 90 s , and finally 5 min at 72°C . The final purified PCR product was digested and cloned into the pGEM-T vector ( Promega , USA ) , then sub-cloned into the pQE-80L carrying the N-terminus His-tag ( Novagen , USA ) . The recombinant pQE-80L/TsSP was transformed into Escherichia coli BL21 ( DE3 ) ( Novagen ) . The rTsSP expression was induced by using 0 . 5 mM IPTG for 4 h at 30°C . The rTsSP were purified with a Ni-NTA His-tag affinity kit ( Novagen ) . The rTsSP protein were identified on SDS–PAGE analysis [32] . The concentration of the rTsSP protein was assayed as described [33] . The sequences of serine protease homologues from other organisms were aligned using the default settings in the program Clustal X [34] . The phylogenetic relationship among TsSP and other homologues was assayed by using a phylogenetic tree constructed in the MEGA 5 . 0 under the maximum parsimony algorithm with 1 000 bootstrap replications [35] . Thirteen BALB/c mice were immunized with rTsSP . Each mouse was injected abdomen subcutaneously with 20 μg of rTsSP emulsified in Freund’s complete adjuvant , then the mice were boosted twice with the same amount of rTsSP emulsified with Freund’s incomplete adjuvant at an intervals of 10 days [36] . About 50 μl of blood sample from immunized mice were obtained at 10 days after final immunization and serum anti-rTsSP antibody titer was assayed by ELISA with 2 μg/ml rTsSP as coating antigen [37] . Samples consisted of 5μg rTsSP , 15μg ML crude antigens and ML ES antigens per lane . The protein was separated on SDS-PAGE with 12% separation gel , subsequently transferred onto the membranes ( Millipore , USA ) at 18 V for 35 min in a semi-dry transfer cell ( Bio-Rad , USA ) [26] . The membrane was blocked by 5% skim milk in Tris–buffered saline with 0 . 05% Tween-20 ( TBST ) at room temperature for 2 h , and incubated with 1:100 dilutions of different sera ( anti-rTsSP serum , serum of T . spiralis-infected mice collected at 42 dpi , immune serum from mice immunized with ML ES and crude antigens , and uninfected normal mouse serum ) at 4°C overnight . Following being washed , the membrane was incubated with 1:10 000 dilutions of HRP-conjugated goat anti-mouse IgG at 37°C for 1 h . The membrane was colored by use of 3 , 3’-diaminobenzidine tetrahydrochloride ( DAB; Sigma ) , and terminated by washing the membrane with deionized water . To detect the relative TsSP expression level in T . spiralis different stages , 15 μg/lane of soluble proteins of ML , IIL , AW and NBL was separated with SDS-PAGE and identified by Western blotting with 1:100 dilutions of anti-rTsSP serum [38] . Rabbit anti-β-actin antibody diluted at 1:400 was utilized as a quantitative protein control to detect β-actin expression . After it was washed three times with TBST , the color development was performed by the enhanced chemiluminescence ( ECL ) kit ( CWBIO , Beijing , China ) [39] . The relative expression level of the TsSP protein at various T . spiralis phases was determined with Image J software . Total RNA was extracted respectively from diverse T . spiralis phases ( ML , IIL , AW , and NBL ) with Trizol reagent ( Invitrogen ) . The RT-PCR was carried out according to the previous report [38] . By using as an internal control , T . spiralis glyceraldehyde-3-phosphate dehydrogenase ( GAPDH , GenBank accession No . AF452239 ) was amplified as a housekeeping gene in our study . PBS was used as a negative control template in all PCR assays . The crude proteins from different T . spiralis phases ( NBL , ML , IIL and AW ) and ES proteins from AW , ML and IIL were prepared as described [27 , 40] . The above-mentioned antigens and rTsSP were diluted to a final concentration of 1 . 5 μg/ml . The ELISA procedure was performed as described previously [11] . Briefly , the microtiter plate was coated with the antigens at 4°C overnight . Following being washed with PBST , it was blocked with 5% skimmed milk in PBST at 37°C for 2 h . After washing again , the plate was incubated at 37°C for 1 h with 1:200 dilutions of trichinellosis patients’ serum or 1:100 dilutions of mouse serum , subsequently incubated with HRP-conjugated anti-human/mouse antibody IgG ( 1:10 000 ) at 37°C for 1h . After the last washing , the coloration was developed by incubation with o-phenylenediamine dihydrochloride ( OPD; Sigma ) plus 30% H2O2 for 30 min . The reaction was ceased by 2M H2SO4 . The absorbance ( optical density , OD ) was measured at 490 nm , and all serum samples were assayed in duplicate . The ratio < 2 . 1 of assayed serum/negative serum OD values was taken as negative and the ratio ≥2 . 1 as positive [41] . The cut-off value of rTsSP-ELISA and ES-ELISA for detection of the patient’s serum was 0 . 35 and 0 . 45 , respectively . The cut-off value of the above two ELISA for detection of experimentally infected mice was 0 . 20 and 0 . 21 , respectively . To confirm whether the TsSP expressed on the surface of T . spiralis diverse stages , the whole worms were used in IFT [42] . Additionally , the tissue sections with 3 μm thickness of female adults at 3 dpi , ML and IIL were separately cut by a microtome . The intact nematodes and their sections were blocked in 5% normal goat serum diluted with PBS , and incubated using a 1:10 dilution of mouse immune serum , infection serum or negative control serum . FITC-labeled goat anti-mouse IgG diluted at 1:100 ( Santa Cruz , USA ) was utilized as the second antibody . After they were washed with PBST , the intact nematode and sections were examined under a fluorescent microscopy ( Olympus , Japan ) . The statistical analysis of data was carried out by using SPSS 17 . 0 software . All the data were shown as arithmetic means ± standard deviation ( SD ) . The comparison of the TsSP expression level in T . spiralis various stages was performed with one-way ANOVA . Chi-square test was used to determine the difference between groups . The statistical test was regarded significant at P < 0 . 05 .
Bioinformatics analysis revealed that the full-length cDNA sequence of the TsSP gene was 1372 bp ( CDS: 2–1290 bp ) . The predicted MW and pI of TsSP were 47 . 55 kDa and 8 . 73 , respectively . The signal peptides were located at 1–18 aa ( MILFKCLFLLAYTTLAFA ) . The mature serine protease consisted of 411 amino acid residues of 45 . 2 kDa , and no transmembrane helix was detected , indicating that the TsSP is a secretory protein . Only one N-glycosylation site 78–81 ( NGSQ ) of the TsSP was identified . Secondary structures of the TsSP had 18 potential B cell epitopes . The SMART analysis results demonstrated that the TsSP had a domain ( at 37-277aa ) of trypsin-like serine protease carrying an active site of classic catalytic triad . In three-dimensional model , the motif of catalytic triad ( Serine–Histidine–Aspartate ) constituted a functional domain carrying substrate binding sites ( Fig 1 ) . A homology comparison of TsSP and other serine protease orthologues in the genus Trichinella was determined ( Fig 2 ) , among these sequences , the highest homology was between T . spiralis and T . nativa ( with 90% identity ) . As shown in the phylogenetic tree generated with TsSP and its orthologues ( Fig 3 ) , the Trichinella genus was displayed as a monophyletic group with bootstrap value of 87 . Within the Trichinella , the close relationships among T . spiralis , T . nativa and T . britovi were supported with a high bootstrap value ( 95 ) . The complete TsSP cDNA sequences without signal peptide were 1236 bp . The open reading frame ( ORF ) of TsSP encoded a 45 . 2 kDa protein of 411 amino acids . The TsSP coding sequences were cloned into the pQE-80L . Following induction , SDS-PAGE analysis showed that the recombinant bacteria harboring pQE-80L/TsSP expressed a protein band with 45 . 2 kDa . After being purified , the rTsSP had a single distinct protein band ( Fig 4 ) . The molecular weight ( 45 . 2 kDa ) of the rTsSP was consistent with its expected size . To determine humoral immune responses to rTsSP in immunized mice , serum specific anti-rTsSP IgG titers at days 10 after the final immunization were measured by ELISA . As shown in Fig 5 , anti-rTsSP antibodies could be triggered by the immunization with rTsSP . The titer of serum anti-rTsSP IgG was 1:105 following the last immunization , indicating that the rTsSP has a high immunogenicity . The results of SDS-PAGE analysis showed that the ML crude antigens had 44 bands with MW of 14 . 7–97 . 2 kDa , ML ES antigens had 29 bands with 14 . 4–96 . 3 kDa , and the rTsSP had only one band with 45 . 2 kDa ( Fig 6A ) . On Western blot analysis the rTsSP was probed with anti-rTsSP serum and infection serum . The native TsSP proteins with 25–47 kDa in T . spiralis ML crude and ES proteins were recognized with anti-rTsSP serum ( Fig 6B ) . Furthermore , the rTsSP was also recognized by immune serum from mice immunized with ML ES or crude antigens ( Fig 6C ) . The results indicated that TsSP is one protein component from somatic and ES products of T . spiralis ML . The TsSP transcription at different T . spiralis stages was assayed by RT-PCR assay and the transcription of GAPDH gene was used as an internal control . The TsSP mRNA transcript ( 1236 bp ) was observed at all T . spiralis lifecycle stages ( NBL , ML , IIL and AW ) . Moreover , the primers for the housekeeping gene ( GAPDH ) also produced the expected band ( 570 bp ) in different developmental stages ( Fig 7 ) . The results of ELISA revealed that the rTsSP and the native TsSP in crude and ES products of different stages ( NBL , ML , IIL and AW ) were identified by using anti-rTsSP serum ( Fig 8 ) . The results of Western blot analysis demonstrated that the native TsSP of 45 . 2 kDa in crude antigens of various stages were also probed with anti-rTsSP serum ( Fig 9 ) . These results further indicated that the TsSP was expressed at various developmental phases , and existed in both the somatic and ES proteins of the nematode . The TsSP expression level in IIL and NBL were obviously higher than those in the other three stages ( ML , AW at 3 and 6 dpi ) ( P < 0 . 05 ) . The IFT using intact parasite revealed that the immunostaining was found on cuticles of different stages ( AW , NBL , ML and IIL ) by using anti-rTsSP serum ( Fig 10 ) . While tissue sections of the nematode were incubated by anti-rTsSP serum , the staining was detected in cuticles and stichosomes of ML , IIL , AW and the embryos within uterus of female adult at 3 dpi . The sensitivity of rTsSP-ELISA and ES-ELISA for detection of anti-Trichinella IgG in serum samples from trichinellosis patients was 98 . 11% ( 52/53 ) and 88 . 68% ( 47/53 ) , respectively ( χ2 = 2 . 910 , P = 0 . 088 ) . As the patients’ serum samples at 35 dpi were tested , the sensitivity of two antigens reached 100% ( 32/32 ) . Nevertheless , while the patients’ samples at 19 dpi were examined , the sensitivity of the rTsSP was 95 . 24% ( 20/21 ) , which was obviously higher than 71 . 43% ( 15/21 ) of ES antigens ( χ2 = 4 . 286 , P = 0 . 038 ) ( Table 1 ) . The specificity of the rTsSP and ES antigens was 99 . 53% ( 211/212 ) and 91 . 98% ( 195/212 ) ( χ2 = 14 . 853 , P = 0 ) , when they were applied for detecting anti-Trichinella IgG in sera of patients with other parasitosis and healthy individuals . The cross-reaction of rTsSP with sera of patients with other parasitic diseases was not observed except for one serum sample from patients with cysticercosis ( Fig 11 ) . Serum anti-Trichinella IgG levels in infected mice at different time intervals post infection were measured by rTsSP-ELISA and ES-ELISA , respectively . Specific anti-Trichinella IgG was first detected by rTsSP-ELISA on 7 dpi and antibody positive rate reached 100% on 10 dpi ( Fig 12A ) ; when ES-ELISA was used , the specific antibody was first detected on 10 dpi and antibody detection reached 100% on 16 dpi ( Fig 12B ) .
Previous studies showed there is an evident 2–3 week window of anti-Trichinella IgG negative after Trichinella infection , the antibody detection rate could not attain 100% till 1–3 months following Trichinella infection in humans [43 , 44] . The conventional ELISA with ML ES antigens lacks perfect sensitivity at the beginning of Trichinella infection , so improvements of diagnostic antigens would be of clinical value . In theory , detection of circulating antigens or DNA from T . spiralis live worms seems an ideal early diagnostic method for trichinellosis . But the levels of Trichinella circulating antigens in serum samples are usually lower and its detection rate in patients with clinical trichinellosis was usually only 30–50% [45 , 46] . Moreover , the persistence of Trichinella DNA is transient in blood circulation and the feces of infected hosts [23 , 47] . Therefore , determination of Trichinella circulating antigens or DNA has not been used for diagnosis of human trichinellosis . Up to now , determination of anti-Trichinella IgG is the most widely applied diagnostic method of trichinellosis , which is recommended by WHO and the International Commission on Trichinellosis ( ICT ) [10 , 48] . Therefore , it would be beneficial to identify antigens better able to diagnose recent Trichinella infection . Serine protease ( or serine proteinase ) is a superfamily of widespread proteolytic enzymes in parasites , they exert an important part in physiological and pathological proceses during parasite infection [49] . The protease is related with the larval invasion , molting , digestion and fibrinolysis in parasitic nematodes [50 , 51] . Previous studies indicated that some secreted serine proteases were found in ES products from T . spiralis ML and AW , including serine protease TspSP-1 and trypsin-like 45 kDa antigen [52 , 53] , and the enzymic activity of the native serine proteases in T . spiralis ML and AW ES proteins was also detected by biochemistry assay [54 , 55] . Our previous studies demonstrated that while the ML were activated into IIL and cocultivated with intestinal epithelial cells ( IEC ) , the serine protease expression level in IIL stage was evidently increased as compared with ML stage [56 , 57] , suggeting that the serine proteases might be involved in the larval invasion of host’s enteral mucosa . These serine proteases might be the target molecular antigens of the early host’s immune response , and they are possiblly used as the new diagnostic antigens for early trichinellosis [58] . The complete TsSP cDNA sequence was cloned and expressed in this study . The TsSP is attributed to the trypsin-like serine protease superfamily and has 90% identity with T . nativa which is another encapsulated Trichinella species [59] . After being purified , the rTsSP was strongly immunogenic and used for generating anti-rTsSP antibodies . Immunization of mice with the rTsSP elicited specific humoral immune response against rTsSP . The ELISA results revealed that the titer of specific anti-rTsSP IgG in immune serum was 1:105 . On Western blotting , the rTsSP protein was recognized with anti-rTsSP serum and mouse infection serum . As shown in Fig 6B , by using anti-rTsSP serum several native TsSP proteins was identified in T . spiralis ML crude and ES antigens . The TsSP might have different isoforms , or the protein was possibly processed by means of post-translational modifications/alternative splicing [11 , 60 , 61] . The process might be involved in the phosphorylation , methylation or acetylation of the TsSP after being translated , and they are possible important for the biological functions of the TsSP [38 , 62 , 63] . Additionally , it is also possible because the TsSP is a member of serine protease family , and they have the same functional domains . The TsSP mRNA transcription was detected by RT-PCR at all T . spiralis developmental stage ( AW , NBL , ML , IIL ) ( Fig 7 ) . The TsSP expression was found by ELISA at various stage , but as shown in Fig 9 , the TsSP expression level in IIL and NBL were obviously higher than those in the other three stages ( ML , AW at 3–6 dpi ) on Western blot anlysis . The IFT results demonstrated immunostaining was principally located in cuticle and stichosome of the nematode ( Fig 10 ) . Our results indicated that the TsSP was expressed at various T . spiralis phases and the TsSP was likely from the worm’s ES products . Previous studies showed another serine proteases ( TspSP-1 . 2 ) was also expressed in T . spiralis different stages [38] . The results suggested that the TsSP is an essential protein and act a pivotal part in T . spiralis larval invasion and development . The the enzymatic activity and biological funtions of the rTsSP need to be studied in further experiments . To investigate the potential use of rTsSP for serodiagnosis of human trichinellosis , rTsSP-ELISA method was establised and applied to assay anti-Trichinella IgG in trichinellosis patients’ serum samples , and the sensitivity was compared with those of ES-ELISA . The results revealed that the sensitivity of rTsSP-ELISA and ES-ELISA was 98 . 11% ( 52/53 ) and 88 . 68% ( 47/53 ) , respectively ( P > 0 . 05 ) . Nevertheless , while the trichinellosis patients’ serum samples at 19 dpi were examined , the sensitivity ( 95 . 24% ) of rTsSP was significantly higher than 71 . 43% ( 15/21 ) of ES antigens ( P < 0 . 05 ) , demostrating that the rTsSP protein was useful for the early diagosis of human trichinellosis . The specificity ( 99 . 53% ) of the rTsSP was also superior to 91 . 98% of the ES antigens ( P < 0 . 01 ) . The cross-reaction of the rTsSP was seen only with one out of 20 serum samples of cysticercosis patients . The sensitivity and specificity of rTsSP are similar with that of recombinant T . spiralis 31 kDa protein [11] . The sensitivity of rTsSP for diagnosing early trichinellosis is comparative to those of ELISA using IIL or AW ES antigens , but the specificity of rTsSP-ELISA has an evident advantage over those of IIL and AW ES antigens [16 , 17] . Importantly , the anti-Trichinella IgG in 100% of the mice infected with 300 muscle larvae was detected by rTsSP-ELISA as soon as 10 dpi , but the ES-ELISA did not permit detection of 100% of infected mice before 16 dpi . The results suggested that the TsSP protein might be secreted by the nematode into the host’s peripheral blood circulation at the early infection stage and elicited an early specific anti-Trichinella antibody response continuing to the muscle stage [16] . Furthermore , our previous study has showed that the rTsSP could be recognized by early mouse infection sera at 8–10 dpi on Western blotting analysis [58] . Consequently , the rTsSP could be of value as potential novel antigen for the early diagnosis of T . spiralis infection in humans . In summary , this study demonstrated that the TsSP was expressed at various T . spiralis developmental stages , it was likely from the worm’s ES products , and mainly located in cuticle and stichosome of this nematode . The rTsSP was strongly immunogenic . Sensitivity and specificity of rTsSP for detecting anti-Trichinella IgG antibodies are superior to the conventional ML ES antigens which are widely used at present . The rTsSP had the potential valuable as a new diagnositic antigen for early trichinellosis . But more serum samples from patients with trichinellosis and other nematode infection ( ascariasis , trichuriasis , hookworm infection , filariasis , etc . ) should be tested to further evaluate its sensitivity and specificity .
|
Trichinellosis is an important parasitic zoonosis , and has a public health hazard and an economic impact on the safety of animal food . The diagnosis of trichinellosis is difficult and it is often misdiagnosed . There is an evident 2–3 week window stage between clinical manifestations and the anti-Trichinella IgG positive . Serine protease is a superfamily of proteolytic enzymes and exerts a major role in tissue invasion , larval development and survival of the parasites . A T . spiralis putative serine protease ( TsSP ) was characterized in ES proteins of T . spiralis intestinal infective larvae and adult worms by the immunoproteomics with early infection serum . In this study , the TsSP was expressed and purified . The results revealed that the TsSP was expressed at various T . spiralis stages ( newborn larvae , muscle larvae , intestinal infective larvae and adult worms ) and it was principally located in cuticle and stichosome of the nematode . The rTsSP was sensitive and specific for detection of anti-Trichinella IgG , and could be regarded as an early diagnostic marker of trichinellosis .
|
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2018
|
Characterization of a Trichinella spiralis putative serine protease. Study of its potential as sero-diagnostic tool
|
Increased risk of tuberculosis ( TB ) associated with HIV-1 infection is primarily attributed to deficient T helper ( Th ) 1 immune responses , but most people with active TB have robust Th1 responses , indicating that these are not sufficient to protect against disease . Recent findings suggest that favourable outcomes following Mycobacterium tuberculosis infection arise from finely balanced inflammatory and regulatory pathways , achieving pathogen control without immunopathology . We hypothesised that HIV-1 and antiretroviral therapy ( ART ) exert widespread changes to cell mediated immunity , which may compromise the optimal host protective response to TB and provide novel insights into the correlates of immune protection and pathogenesis . We sought to define these effects in patients with active TB by transcriptional profiling of tuberculin skin tests ( TST ) to make comprehensive molecular level assessments of in vivo human immune responses at the site of a standardised mycobacterial challenge . We showed that the TST transcriptome accurately reflects the molecular pathology at the site of human pulmonary TB , and used this approach to investigate immune dysregulation in HIV-1/TB co-infected patients with distinct clinical phenotypes associated with TST reactivity or anergy and unmasking TB immune reconstitution inflammatory syndrome ( IRIS ) after initiation of ART . HIV-1 infected patients with positive TSTs exhibited preserved Th1 responses but deficient immunoregulatory IL10-inducible responses . Those with clinically negative TSTs revealed profound anergy of innate as well as adaptive immune responses , except for preservation of type 1 interferon activity , implicated in impaired anti-mycobacterial immunity . Patients with unmasking TB IRIS showed recovery of Th1 immunity to normal levels , but exaggerated Th2-associated responses specifically . These mechanisms of immune dysregulation were localised to the tissue microenvironment and not evident in peripheral blood . TST molecular profiling categorised different mechanisms of immunological dysfunction in HIV-1 infection beyond the effects on CD4 T cells , each associated with increased risk of TB disease and amenable to host-directed therapies .
One and a half million deaths are attributed to nine million new cases of active tuberculosis ( TB ) per annum [1] . Most individuals infected with Mycobacterium tuberculosis ( Mtb ) do not develop disease , but co-infection with Human immunodeficiency virus ( HIV ) -1 substantially increases this risk , even before progression to advanced acquired immunodeficiency syndrome ( AIDS ) [2 , 3] . HIV-1 associated TB presents more frequently as primary infection and extrapulmonary or disseminated disease [4] , suggesting inadequate immunological control of Mtb . In addition , rare genetic immunodeficiencies show unequivocally that interferon ( IFN ) γ responses and signalling pathways associated with CD4 T helper ( Th ) 1 immunity are necessary for protection against mycobacterial infection generally [5] . However , most people with active TB typically exhibit robust Th1/IFNγ responses [6 , 7] that may even contribute to immunopathology [8 , 9] . Therefore , factors other than Th1 immunity must contribute to protection . Recent findings suggest that favourable outcomes following Mtb infection arise from finely balanced inflammatory and regulatory pathways , and point to a putative detrimental role for type 1 IFNs [10–13] . Investigation of HIV-1 associated TB has focussed on deficient CD4 T cell responses which are evident before severe depletion of circulating CD4 T cells in AIDS [14] . However , HIV-1 infection also causes persistent type 1 IFN responses and chronic immune activation by diverse mechanisms [15–17] . Therefore , increased TB disease in HIV-1 infected patients may arise as a result of inadequate inflammatory responses that are unable to control bacillary growth , or exaggerated inflammatory responses that lead to increased immunopathogenesis . The latter are widely implicated in the mechanism underlying TB immune reconstitution inflammatory syndrome ( IRIS ) which can occur after initiating treatment for HIV-1 with antiretroviral therapy ( ART ) [18 , 19] . We hypothesise that unbiased genome-wide assessments of anti-mycobacterial immune responses in HIV-1 patients with and without IRIS may identify deficient responses that contribute to host protection against TB , or exaggerated responses that drive its pathogenesis . These may also extend our general understanding of immunological correlates of protection and pathogenesis in TB , and thereby allow better stratification of the risk of disease after Mtb infection , rational design of novel vaccines and development of host-directed therapies to radically shorten duration of treatment or mitigate against increasing TB drug resistance [20 , 21] . Systems level assessments of human immunobiology in active TB have principally described changes in peripheral blood transcriptional profiles . Quantitatively these changes correlate with disease severity and resolve with treatment [13 , 22 , 23] . Therefore , differences between patient populations in cross-sectional studies are likely to be confounded by differences in the bacillary burden and duration of infection , neither of which can be measured accurately . Moreover , recent longitudinal functional imaging studies in experimental non-human primate models and in patients with active TB revealed that different foci of disease within the same host show autonomous and discordant activity [24–26] , indicating localised immunopathology within the tissue microenvironment which may not be represented faithfully by measurements in the systemic circulation . In order to address these limitations , we undertook whole genome transcriptional profiling of biopsies from the tuberculin skin test ( TST ) in order to make comprehensive molecular level assessments of human immune responses to TB at the site of a standardised experimental challenge . Clinical inflammation in response to the TST has been widely used as a measure of anti-mycobacterial T cell memory [27 , 28] , but we have previously shown that transcriptional profiling of the TST in healthy people provides quantitative and qualitative measurements of multivariate molecular components of innate and adaptive cell mediated immunity [29] . Importantly , we were also able to detect changes in transcript abundance in the absence of clinical inflammation , and thereby identify immune responses in TSTs that would otherwise be described as anergic by conventional assessments . This offers unprecedented opportunities to assess immune responses to TB in patients with advanced HIV-1 infection who frequently exhibit clinically negative TST responses [30] . In this study we demonstrate that transcriptional profiling of the TST in patients with active TB accurately models molecular pathology within foci of pulmonary TB . We use this approach to identify changes to in vivo human immune responses to TB at different stages of HIV-1 infection in patients with clinically positive or negative TSTs and in patients with unmasking TB IRIS , each group representing different immunological states associated with increased risk of active TB or increased immunopathology . By taking a genome-wide approach , we test the hypothesis that the dysregulation of anti-mycobacterial responses in each of these states extends beyond selective deficiency or exaggeration of Th1 responses to other immunological components that may also contribute to increased risk of TB .
We first sought to describe the response to 48 hour TSTs in HIV seronegative patients with active TB as early as possible after diagnosis and within one month of starting anti-mycobacterial treatment . The TST caused clinically evident inflammation and histology revealed leukocytic infiltrates consistent with a cell mediated immune response ( Fig 1A and S1 Fig ) . A TST transcriptional signature was identified , comprising 1725 genes with significantly increased transcript abundance compared to biopsies of control saline injections ( Fig 1B ) . Transcription factor binding site ( TFBS ) enrichment analysis was used to infer upstream regulation of the TST gene signature . Binding sites for NFκB family members showed most statistically significant enrichment , but enrichment of IRF2 , STAT1 and STAT3 binding sites were also evident , consistent with innate immune , IFN and other cytokine stimulated signalling associated with each of these transcription factors ( Fig 1C and S1 File ) . Pathway analysis of this gene set confirmed well established components of cell mediated immunity including enrichment of chemokine activity , antigen presentation , T cell activation and IFN signalling ( Fig 1D , S2 File ) . Although peripheral blood transcriptional changes in active TB have been reported within the first week of treatment [23] , differences in the duration of treatment of individual patients in the present study were not associated with segregated clustering of TST transcriptional signatures in principal component analysis ( PCA ) ( S3A Fig ) . Likewise , the TST transcriptional profile of patients with pulmonary and extrapulmonary TB clustered together in the PCA ( S3B Fig ) , indicating that neither time on treatment within one month , nor site of active TB disease , caused substantial confounding of the transcriptional response to tuberculin challenge . In order to validate and extend these analyses , we derived predefined cell-type and stimulus-specific gene modules ( S3 and S4 Files ) from independent experimental data to investigate the relative enrichment of each module within the genome-wide transcriptome of TSTs compared to control saline injections . Cell type specific modules were derived by comparison of transcriptomes from selected purified immune cells ( S4 and S5A Figs ) , and independently validated in data sets from purified cell types and diverse tissue specimens in which module enrichment was consistent with histological assessments of cellular composition ( S5B–S5G Fig ) . Cytokine or innate immune stimulus-specific modules were derived from differential transcriptional responses of monocyte derived macrophages ( MDM ) to selected cytokines associated with alternatively polarised T cell function and to selected innate immune stimuli associated with Mtb or alternative pathogens ( S6 Fig ) . Analysis of cellular modules showed selective accumulation of circulating leukocytes within the TST . T and NK cell , monocyte and neutrophil derived modules were most enriched , but there was significantly less enrichment of the B cell module ( Fig 1E ) . Cytokine specific gene modules showed greatest enrichment of IFNγ inducible transcripts , which we infer to predominantly reflect Th1 activity . Some enrichment of TNFα activity , which is also thought to contribute to protection to immune protection in TB [31] , and IL4/IL13 activity associated with Th2 polarised responses [32] were also evident to a lesser degree ( Fig 1F ) . Innate immune specific modules showed enrichment of genes exclusively upregulated by Mtb and TLR2 stimulation , but not genes exclusively upregulated by TLR4 or Streptococcus pneumoniae ( Spn ) ( Fig 1G ) . Although TLR2 is a well-established innate immune receptor for both Mtb and Spn , TLR2 independent responses to Spn are also recognised [33 , 34] . Therefore , we interpret the absence of any modular enrichment for TLR4 and Spn exclusive responses as evidence for specific anti-mycobacterial innate immune responses within the TST rather than non-specific inflammation . In order to confirm that differences in duration of treatment or site of disease did not confound the TST transcriptome at systems level , we also showed that neither of these variables affected the expression of cell type or stimulus specific modules ( S7 Fig ) . In order to test the validity of the TST as a model for TB immunopathology , we next assessed the expression of the TST signature within published genome-wide transcriptomes of human lung TB granulomas and healthy human lung [35] . The geometric mean expression for the TST gene signature was greater within TB granulomas ( Fig 2A ) and correlated precisely with the magnitude of genome-wide transcriptomic differences between granulomatous TB and healthy lung tissue , which was represented by molecular distance to health ( MDH ) for each of the granulomatous lesions . In contrast , a signature of the same number of randomly selected genes showed no correlation ( Fig 2B ) . Moreover , the correlation between MDH and the geometric mean of the TST signature was statistically stronger than that of any other cell or stimulus specific gene expression module ( Fig 2C ) , suggesting that the TST signature better reflects variability at the site of disease than any of its component parts . Changes in peripheral blood transcriptomes of patients with active TB have also been associated with severity of clinical disease [13] . For comparison with the TST signature , we derived a peripheral blood transcriptional signature of genes with significantly increased expression levels in our patients with active TB compared to healthy volunteers , which also showed statistically significant correlation with MDH in pulmonary TB granulomas ( S8 Fig , Fig 2C ) . The blood derived signature showed some overlap with the TST signature at molecular and systems levels ( S8 Fig ) . Importantly , however , the TST transcriptional signature included immune response genes that were not increased in the blood of patients with active TB . Notably , these included components of chemokine networks that can be expressed by endothelial cells [36 , 37] within tissue biopsy specimens and may contribute to immune cell recruitment ( S8 Fig ) . Moreover , granulomatous inflammation in response to TB , which is dependent on immune cell recruitment , occurs exclusively in tissues rather than blood . Accordingly , within pulmonary TB granulomas , the TST signature was significantly more enriched and showed a statistically stronger correlation with MDH than the blood derived signature ( Fig 2C and 2D ) . Taken together , these analyses show that the transcriptional changes within the TST reflect molecular changes at the site of active TB with much higher fidelity than changes in peripheral blood , and can be used to quantify cellular recruitment and specific innate and adaptive immune responses . We hypothesised that HIV-1 infection may have distinct effects on the immune response to TB at different stages of HIV-1 disease . Therefore , we evaluated TST responses in three separate clinical phenotypes comprising patients with active TB and HIV-1 co-infection who either exhibited a clinically positive TST response , or those who exhibited a clinically negative TST response , or patients with possible unmasking TB-IRIS ( Table 1 and S1 Table ) . The TST transcriptome of each group was compared to that of HIV seronegative patients with active TB , as a standard reference . We focussed on patients with active TB to overcome the difficulty in controlling for TB exposure in asymptomatic HIV-1 positive individuals for whom HIV-1 infection confounds peripheral blood interferon gamma release assays normally used to identify prior exposure [28 , 38 , 39] . In addition , this approach allows assessment of immune dysfunction associated with IRIS . In view of the greatly increased risk of active TB in HIV-1 infection , and the increase in immunopathogenesis in IRIS , we hypothesised that features in the TST transcriptomes that were decreased in each of the groups of HIV-1 infected patients may represent immune correlates of protection , and that features that were increased may represent immune correlates of pathogenesis . The TST transcriptome in HIV-1 infected patients with positive TSTs showed marked overlap , correlation and covariance with that of HIV seronegative patients ( Fig 3A and 3B ) . As might be expected from the effects of HIV-1 infection on Mtb-reactive CD4 T cell populations [14] , modular analysis showed reduced abundance of T cell associated transcripts in the TST , but other selected cell type and pre-defined stimulus-specific modules were comparable in the two groups ( Fig 3D ) . Comparison at the level of individual genes , identified significantly lower transcript abundance of a subset of genes in the TST of HIV-1 infected patients ( Fig 3B ) . In order to evaluate the mechanism for the lower levels of these transcripts , we performed TFBS enrichment analysis on all genes significantly reduced in the TST signature of these HIV-infected patients ( Fig 3C and S1 File ) . Enrichment of binding sites for STAT1 and NFκB RelA amongst the genes that showed diminished levels in HIV-1 infected patients suggested that IFN and TNFα or innate immune inducible genes , dependent on STAT1 and RelA respectively [40 , 41] , might be attenuated in this group of HIV-1 infected patients . This hypothesis was not supported by modular analysis , which showed no difference in IFNγ , TNFα or innate immune stimulated gene expression modules ( Fig 3D ) . However , we also found enrichment of STAT3 binding sites in the group of attenuated transcripts . STAT3 is the principal mediator of IL10 inducible transcriptional regulation [42 , 43] , suggesting that IL10 activity may be attenuated in the TST within this group of HIV-1 infected patients . IL10 upregulation in TB has been extensively described and experiments in mouse models have mostly focussed on its potential to compromise anti-mycobacterial host defences by regulating Th1 responses [44] . In contrast , recent data from non-human primate models suggest IL10 contributes to the optimal balance of host-protective immune responses within TB granulomas [12 , 45] . In addition , we reported in vitro data showing that HIV-1 infection of macrophages attenuates IL10 responses to co-infection with Mtb , leading to exaggerated inflammation [46] . Hence , increased risk of active TB in HIV-1 infected patients with preserved Th1 immunity , may principally arise from deficient IL10 immunoregulation . Therefore , we tested the hypothesis that this group of HIV-1 infected patients exhibit attenuated IL10 responses to the TST , in comparison to HIV seronegative patients , by using three independently derived modules for IL10 inducible genes . One previously published module was derived from IL10 stimulation of peripheral blood mononuclear cells [47] and two new modules we derived experimentally by stimulation of MDM with IL10 or by neutralising IL10 in zymosan stimulated MDM ( S4 File and S9A–S9D Fig ) . In HIV seronegative patients with active TB , all three IL10 modules were enriched in the TST compared to control saline injection , confirming induction of IL10 activity in the host response to TST . Consistent with the hypothesis we derived from over representation of STAT3 TFBS amongst transcripts attenuated in HIV-1 infected patients , expression of each of the three IL10 modules was significantly less in HIV-1 infected patients with clinically positive TSTs ( Fig 3E ) . These differences were not evident in whole blood transcriptional profiles from the same patients ( Fig 3F ) . Blood CD4 counts in TB/HIV-1 co-infected patients with clinically negative TSTs were significantly lower than co-infected patients with clinically positive TSTs , as previously reported [30] ( Table 1 and S1 Fig ) . In keeping with the lack of significant clinical inflammation , their TST transcriptomes showed many fewer increases in transcripts compared to saline , than the TST transcriptome of HIV seronegative patients with active TB ( Fig 4A ) who had clinically evident responses ( Table 1 ) . Importantly TB/HIV-1 co-infected patients with clinically negative TSTs also had a substantially reduced TST transcriptome compared to healthy volunteers with clinically negative TSTs [29] , who did have an immune response evident at the molecular level despite the absence of significant clinical induration ( S10A Fig ) . Therefore , we concluded that TB/HIV-1 co-infected patients with clinically negative TSTs exhibit severe immunodeficiency affecting the broad range of innate and adaptive immune responses ( S10B Fig ) . Nonetheless , changes in TST transcript abundance in 98 genes were evident in this group ( Fig 4A ) . These genes showed most significant TFBS enrichment for IRF2 ( Fig 4B and S1 File ) thus implicating a role for IFN regulated pathways [48] . Pathway analysis of the 98 gene signature revealed that they were most strongly associated with type 1 IFN signalling , in contrast to the TST transcriptome of HIV seronegative patients with active TB , in whom more transcripts were associated with the type 2 IFN signalling pathway ( Fig 4C and S2 File ) . Recent evidence suggests that type 1 IFN responses may be detrimental to host defence against mycobacteria and that the ratio of type 1 versus type 2 IFN responses may contribute to clinical outcome [11 , 47] . There is considerable overlap between type 1 and type 2 IFN stimulated genes , therefore to validate our results , we derived exclusive type 1 ( IFNβ ) or type 2 IFN ( γ ) inducible gene modules by in vitro stimulation of MDM ( S4 File and S9E and S9F Fig ) and compared the ratio of type 1 to type 2 IFN stimulated genes in each study group . Consistent with the pathway analysis , our modular analysis showed significantly greater type 1:type 2 IFN activity in HIV-1 infected patients with negative TST , compared to those with positive TST and to HIV seronegative patients ( Fig 4D ) . These differences were not reflected in the peripheral blood transcriptome of the same patients ( Fig 4E ) . Of note , type 1 IFN has been reported to upregulate IL10 expression in human peripheral blood monocytes [47] . We therefore tested the hypothesis that increased type1:2 IFN module ratio within the TST may correlate with IL10 activity . In fact , by integrating data from HIV-1 negative and non-IRIS HIV-1 infected patients , we found significant inverse correlations between the ratio of type1:2 IFN activity and each of the three IL10 modules we have employed in the present study ( S11A Fig ) . Interestingly , we also found no direct induction of IL10 upon stimulation of MDM with type 1 IFN , despite induction of other established IFN-inducible genes ( S11B–S11D Fig ) . ART substantially reduces the risk of incident TB disease associated with HIV-1 infection [49] , but it can also exacerbate the immunopathology of TB and presentation of active TB after starting ART is sometimes attributed to unmasking immunopathology as a result of IRIS [50 , 51] . ART has already been associated with recovery of clinical responses to TST [52 , 53] , but no specific immunological mechanism for IRIS has been established . In keeping with the case definition of IRIS [54] , three HIV-1 infected patients who presented with TB two to eight weeks after starting ART had strong clinical TST responses ( Table 1 and S1 Fig ) , which were also exaggerated at the transcriptional level when compared to HIV seronegative subjects ( Fig 5A ) . 52 genes showed significantly increased expression in the TB-IRIS group compared with HIV-1 seronegative patients ( Fig 5B ) . In pathway analysis , these transcripts were enriched for Th2 associated responses exemplified by genes linked to asthma and IL4-mediated signalling events ( Fig 5C ) . This finding was confirmed by modular analysis , in which only the specific module for IL4 and IL13 stimulated genes in MDM , to model Th2 activity , was significantly enriched in the TST transcriptome of TB-IRIS patients compared to both HIV seronegative patients with active TB , and to HIV-1 infected patients with clinically positive TSTs presenting with active TB that was not temporally associated with recent initiation of ARVs ( Fig 5D and S10C Fig ) . Further genome-wide comparisons of the TST transcriptomes of unmasking IRIS patients with those of non-IRIS TST positive HIV-1 infected patients also showed that unmasking IRIS was associated with an expanded TST transcriptome , with a subset of genes that show significantly higher transcript abundance enriched for Th2 associated pathways ( S12 Fig ) . Once again , these transcriptional differences in the TST were not evident in peripheral blood ( Fig 5E ) . We also sought to validate our observations in the TST transcriptome at the protein level by assessing IRF4 , which is strongly implicated in induction of Th2 responses [55] . Increased transcriptional expression of IRF4 in the TSTs of unmasking TB-IRIS cases ( Fig 5C ) was mirrored by increased protein expression demonstrated by immunostaining of IRF4 ( Fig 6 ) .
Transcriptional profiling of the TST provides genome-wide assessments of in-situ human immune responses to a standardised challenge . Using this approach , we quantified Mtb specific innate responses , cellular recruitment and cytokine activity within the TST . We demonstrated that the same changes are evident in the transcriptome of human pulmonary TB granulomas , and were quantitatively correlated to the degree of immunopathology as measured by the MDH . Hence , the transcriptional profile of the TST provides an accurate model of the immune responses observed in TB lung granulomas , with better resolution than peripheral blood profiling . In order to undertake this analysis , we used the only five published transcriptional data sets from caseous pulmonary TB granuloma . More transcriptomic data comparing pathological lesions from the site of TB disease to normal tissue , and comparing TB granuloma at different stages of maturation , are necessary to consolidate our findings . In addition , we assessed the TST at 48 hours in line with clinical practice [28 , 56] , but measurements at earlier and later time points may help build a dynamic molecular model of its initiation , amplification and resolution , each of which may contribute to differences in outcome . In order to understand the impact of HIV-1 infection on immune responses to Mtb , we reasoned that TB/HIV-1 co-infected patients with preserved clinical TST responses , those with clinically anergic TST responses and patients presenting with unmasking TB-IRIS , will each reflect distinct mechanisms of immune dysfunction that increase risk of active TB . HIV-1 infected patients with preserved clinical TST responses and relatively well preserved circulating CD4 counts experience 3-5 fold greater risk of active TB [3] . Their TST transcriptional signature showed less enrichment of the T cell module , but IFNγ and TNFα activity , which are thought to mediate protective immunity to TB [31 , 57] were intact . Instead , we found evidence of deficient IL10 responses , which mirrored our previous report of deficient IL10 responses to Mtb by HIV-1 infected macrophages in vitro [46] . Given the immunoregulatory role of IL10 and recent focus on the importance of balanced immune responses in TB [10–12 , 45] , we propose that HIV-1 infected patients with preserved Th1 immunity may incur higher risk of active TB as a result of deficient IL10 immunoregulation . Whether attenuation of TST IL10 responses in this group of HIV-1 infected patients is due to decreased IL10 production by virus infected cells or indirect effects of virus infection on the immune system , requires further investigation . Nonetheless our data suggest that stratification of patients by this phenotype or trials of immunoregulatory therapies merit investigation in this group of HIV-1 infected individuals . TB/HIV-1 co-infected patients with clinically anergic TSTs had significantly depleted circulating CD4 counts and their TST transcriptome revealed almost complete immunological anergy with markedly reduced cellular recruitment , cytokine activity and innate immune responses . Importantly , this is in striking contrast to healthy HIV seronegative people with clinically negative TSTs , in whom the full repertoire of prototypic cell mediated immune responses are evident at the molecular level [29] . The degree of immunological anergy in HIV-1 infected patients with clinically negative TSTs is likely to underpin the 20-30 fold increased risk of TB and atypical mycobacterial infection associated with advanced HIV-1 disease [2 , 58] . It is interesting to speculate that immunodeficiency of this severity may also contribute to the relative failure of isoniazid preventative therapy in HIV-1 infected patients with clinically negative TSTs [59] . We infer that immune responses may therefore contribute to effective antimicrobial therapy , encouraging development of adjuvant host-directed therapies to improve TB treatment regimens . Remarkably , a type 1 IFN response to the TST was preserved in HIV-1 infected patients with clinically negative TSTs . This evidence extends human data for type 1 IFN responses to Mtb , and indicates that type 1 IFN responses may be uncoupled from the other innate immune responses that were severely attenuated in these patients . This finding is further supported by recent in vitro evidence for differential activation of IFN and inflammasome pathways [60] . In view of the data that suggest type 1 IFN responses may compromise host immunity to mycobacteria [11 , 47] , these findings highlight the opportunity for specific therapeutic targeting of type 1 IFN activation pathways . Moreover , we hypothesise that increased proportions of type 1 to type 2 IFNs in this group of HIV-1 infected patients may further exacerbate their risk of active TB and contribute to the mechanisms of HIV immunodeficiency . Therefore , interest in targeting type 1 IFN activity to counteract chronic immune activation in HIV-1 infected patients [16 , 17] , may also help to protect against TB . A mechanism by which increased ratios of type 1:2 IFN activity may compromise host protective immunity in TB is thought to be mediated by upregulation of immunosuppressive IL10 responses [47 , 61 , 11] . Of note , we did not find a positive correlation between type 1:2 IFN activity and IL10 activity in the TST . In addition , we found no direct type 1 IFN induction of IL10 expression in MDM , which has been previously reported in human monocytes [47] . Therefore , we conclude that this potential mechanism is unlikely to play a role in advanced HIV-1 infection . HIV-1 infected patients presenting with TB two to eight weeks after starting ART , showed exaggerated transcriptional responses to the TST in keeping with the consensus case definitions for IRIS [54] . Both bioinformatic and independently derived gene module analysis provided entirely new insight into the immunopathogenesis of TB-IRIS , implicating a role for exaggerated Th2 polarised responses rather than increases in Th1 or innate immune responses . This Th2 bias was further confirmed by immunohistochemistry . This phenotype was statistically significant despite our very limited sample of three patients , but clearly merits further evaluation in future studies as it suggests that in the context of TB-IRIS at least , strategies targeting Th2 responses specifically should be considered for therapeutic intervention and may underpin the beneficial effects of glucocorticoid therapy in TB-IRIS [62 , 63] . Importantly , the effects of HIV-1 described above were specific to the site of immunological challenge and not evident in the steady state peripheral blood transcriptome of the same patients . Transcriptional profiling of the TST revealed differences in immune responses that were previously unrecognised by clinical assessments alone or previous laboratory investigations . Hence , we have identified novel and diverse molecular mechanisms by which human immune responses to Mtb are dysregulated in HIV-1 co-infected patients . Further validation of our observations in independent prospective cohorts is necessary . These data will inform rational development of host-directed adjuvant therapies to target specific immunological dysfunction in different patient groups .
This study was approved by UK National Research Ethics Service ( reference no: 11/LO/1045 ) and the University of Cape Town Human Research Ethics Committee ( reference no: 580/2012 ) . HIV-1 seropositive and seronegative adult patients ( >16 years age ) attending TB clinics in London and TB inpatient facilities and clinics in Cape Town who fulfilled inclusion/exclusion criteria ( S1 Table ) within one month of starting treatment for active tuberculosis ( TB ) were invited to participate . Written informed consent was obtained from all patients included in the study . On recruitment to the study , whole peripheral blood was collected in Tempus tubes for RNA ( Life Technologies ) . In addition HIV-1 infected patients provided peripheral blood samples for CD4 T cell and HIV-1 viral load measurements by routine clinical services . Then patients received 0 . 1 mL intradermal injection of two units tuberculin ( Serum Statens Institute ) or saline in the volar aspect of one forearm , and this site was marked with indelible ink . At 48 hours , the clinical response at the injection site was evaluated by measurement of the maximum diameter of inflammatory induration and two 3 mm adjacent punch biopsies were obtained from marked TST or saline injection site as previously described [29] . Clinical induration >10 mm at the injection site was categorized as a positive response . The demographic , clinical and laboratory data for each study group is summarised in Table 1 . Total RNA from skin biopsy samples and MDM was purified as previously described [29] . Total RNA from Tempus tubes was purified using the Tempus Spin RNA Isolation Kit ( Ambion; Life Technologies ) and globin mRNA was eliminated using the GlobinClear kit ( Life Technologies ) according to the manufacturer’s instructions . RNA was subject to DNase treatment using a TURBO DNA-free kit ( Ambion , Life Technologies ) as per the manufacturer’s instructions to remove contaminating genomic DNA . Quality and concentration of all RNA samples were assessed using the Agilent Bioanalyzer . Total RNA was amplified , reverse transcribed into cDNA and then to cRNA and labelled with Cy5 or Cy3 using the Agilent Low RNA Input Linear Amplification Kit . Cy3 and Cy5 labelled samples were hybridized to Agilent 8x60k arrays as per manufacturer’s instructions . Array images were acquired with Agilent’s dual-laser microarray scanner G2565BA and signal data were collected with Agilent Feature Extraction software ( v9 . 5 . 1 ) . Median Cy3 and Cy5 signal intensity was Log transformed and normalized using LOESS local linear regression against the mean signal of all the samples using the R package agilp ( http://www . bioconductor . org/packages/release/bioc/html/agilp . html ) . Principal component analysis ( PCA ) was performed using the prcomp function in R . Significant gene expression differences between data sets were identified using t-tests for parametric ( normally distributed ) data and Mann Whitney tests for non-parametric data in MultiExperiment Viewer v4 . 9 ( http://www . tm4 . org/mev . html ) and a filter for >two-fold difference in mean or median normalised expression values . Pathway analysis was performed in innateDB [64] and transcription factor binding site enrichment analysis was performed using the human single site analysis function in oPossum [65] with default parameters in each application . Network graphics of gene and pathway association were generated using Gephi ( http://gephi . github . io/ ) . All microarray data used in this study are available in ArrayExpress ( https://www . ebi . ac . uk/arrayexpress/ ) under the accession numbers provided in S2 Table . The clinical response to saline injection in HIV-1 infected and uninfected patients in this study was comparable ( Table 1 and S2A and S2B Fig ) . Likewise , PCA of all the de novo data from HIV-1 infected and uninfected patients with active TB confirmed that genome-wide data from all subjects who received saline injection clustered together ( S2C and S2D Fig ) . Specific comparison of data from HIV-1 infected and uninfected patients receiving saline showed significant differences ( Mann Whitney test , p<0 . 05 , fold-difference>2 ) in only 12 genes ( S2E Fig ) , which were not significantly associated with any enrichment in pathway , gene ontology or transcription factor binding site enrichment analyses . Therefore , we concluded that HIV-1 infection did not significantly confound the response to saline and we pooled these data for further analysis . The TST gene signature in each group of patients represents RefSeq [66] annotated genes that showed significantly increased expression levels ( Mann Whitney test , p<0 . 05 , fold-difference>2 ) in skin biopsies from individual patients who received tuberculin were compared to that of all subjects who received control saline injections . A gene expression matrix of purified cells was derived from the processed dataset E-GEOD-22886 available on ArrayExpress repository . The extracted data were not processed further aside from adding gene symbol annotations to probe names . Cell type specific modules were generated by identifying three to five gene probes corresponding to validated markers that identify each cell type of interest ( S3 File ) . The markers were each used to identify co-correlated genes amongst all other gene probes in the expression data matrix . The top 1% of probes that were most co-correlated with the expression of each marker were identified using the Pearson correlation coefficient function in R , and cell type specific modules were then derived from the highly co-correlated probes that were common to all markers for each cell type ( S3 File ) . The specificity of these modules was validated by comparison of the geometric mean expression level for each module within genome-wide data from each cell type in E-GEOD-22886 ( from where the modules were derived ) and also in E-GEOD-28490 , an independent dataset of purified cell types ( S4 and S5A and S5B Figs ) . Furthermore , the sensitivity of cell type specific modules to detect changes for specific cell populations in tissue specimens was evaluated in published data sets which described changes to cell composition confirmed by histological assessments ( S5C–S5G Fig ) . MDM were generated as previously described [46] . Stimulus specific gene modules were derived from transcripts that were upregulated in MDM stimulated with selected cytokines , TLR ligands ( LPS for TLR4 and Pam2CSK4 for TLR2 ) , live Mycobacterium tuberculosis or Streptococcus pneumoniae . For cytokine-inducible gene expression modules , transcriptional profiling of human MDM was performed as described above after stimulation with recombinant human cytokines ( S4 File ) . Significant transcriptional upregulation in comparison to unstimulated MDMs was identified by t-test with Welch’s approximation ( p<0 . 05 ) and a ≥four-fold change threshold . The resulting gene lists were then compared and any which were upregulated ≥two-fold by more than one stimulus were excluded to create stimulus specific modules ( S4 File ) . The specificity of each module was assessed by comparison of fold-changes in the geometric mean expression of genes in each module within MDM stimulated with each combination of stimuli compared to unstimulated MDM ( S6A Fig ) . The same process was used to derive stimulus specific modules to distinguish between various innate immune stimuli in MDM ( S4 File and S6B Fig ) . Two IL10 specific modules were also derived by identifying genes that were upregulated in response to recombinant human IL10 stimulation of MDM ( 10 ng/mL for 24 hours ) or by identifying gene expression changes attributable to an endogenous IL10 response in MDM following zymosan stimulation [67] . This was performed by identifying attenuated gene expression when using neutralising antibodies to IL10 and IL10 receptor as previously described [68] , during 24 hour stimulation with zymosan ( 0 . 4 mg/mL ) . In the analysis of these data , statistical testing as described above was combined with a ≥two-fold change filter as too few genes were up-regulated ≥four-fold by IL10 . Comparison of this gene list with the directly-induced IL-10 module revealed some overlap ( S9A Fig ) and both modules showed significant TFBS enrichment for STAT3 ( S9C and S9D Fig ) , providing independent supporting evidence for generating valid IL10 associated gene expression modules using this approach . Comparison of these gene lists demonstrated minimal overlap and good functional specificity compared to other cytokine stimulation ( S9B Fig ) . To complement these two IL10 inducible gene expression modules , we adopted a third module used to identify IL10 activity derived by 24 hour IL10 stimulation of PBMC in a previously published study [47] . Two further modules were derived to distinguish type 1 or type 2 IFN inducible gene expression using transcriptional data for MDM stimulated for 4 hours with 10 ng/mL of either type 1 ( IFN β ) , or type 2 IFN ( IFNγ ) . As expected , statistically significant upregulated gene expression ( >2-fold ) showed considerable overlap ( S9E Fig ) , but stimulus-specific modules , derived as described above using a >4-fold threshold and exclusion of those upregulated by >2-fold by the other stimulus showed good specificity ( S9F Fig ) . The peripheral blood active TB gene signature in this study represents RefSeq annotated genes that showed significantly increased expression levels ( Mann Whitney test , p<0 . 05 , fold-difference>2 ) in peripheral blood transcriptomes of samples obtained prior to TST in HIV seronegative patients with active TB was compared to samples from HIV seronegative healthy volunteers Table 1 . Module scores were derived by calculating log ratio of the geometric mean of expression data for each module within individual TST biopsies compared to pooled data from saline controls . For peripheral blood and lung transcriptional profiles , the relative enrichment of each module was assessed by presenting the geometric mean expression of the module gene list in each individual Log2 transformed expression profile . Published gene expression data derived from human granulomatous lesions in pulmonary TB and healthy human lung tissue [35] was used . The molecular distance to health was derived as previously described [13] by calculating the sum of standard deviations ( >2 SD ) for data from each granulomatous lesion compared to the mean of data from healthy lung tissue . Total RNA and culture supernatants were collected from MDM cultures stimulated with IFNβ , IFNγ or zymosan ( S4 File ) . RNA was used to synthesise first strand cDNA using the qScript cDNA Supermix kit ( Quanta BioSciences ) and quantitative ( q ) PCR of IL10 , IFI16 and GAPDH was performed using TaqMan inventoried assays ( Applied Biosystems ) using according to the manufacturer’s instructions . IL10 protein was quantified in culture supernatants by ELISA ( eBioscience ) according to the manufacturer’s instructions . Punch skin biopsies for histological analysis were collected into 4% neutral buffered formalin ( NBF; LabSource ) for fixation , then embedded in paraffin , sectioned and mounted on slides , for staining with haemotoxylin and eosin or immunostaining with Mouse anti-human IRF4 ( clone MUM1P from DAKO ) . 3μm paraffin sections underwent automated dewaxing and antigen retrieval using Leica Bond ER2 ( pH9 ) at 100°C for 20 minutes , followed by peroxide blocking for 5 minutes at room temperature . Sections were then incubated sequentially with the primary antibody for 15 minutes , rabbit-anti-mouse secondary antibody and anti-rabbit poly-HRP followed by DAB ( Bond Refine detection kit ) and 0 . 5% copper sulfate . Leica Bond Wash and demineralised water were used for washing steps between reagent steps . Digital images were acquired with an AxioScan Z1 slide scanner ( Zeiss ) and presented without any subsequent processing . All histological grading was performed by a histopathologist blinded to concomitant clinical information . Histological scoring of inflammation was performed on a 0–3 scale , where 0 represented no evidence of inflammation and 3 was the most inflammation within the spectrum of samples .
|
HIV-1 infected people have substantially increased risk of tuberculosis ( TB ) leading to a large burden of disease worldwide . We aimed to investigate how HIV-1 causes this effect by altering human immune responses . We measured the products of all immune genes at injection sites of sterilized TB under the skin , in order to look for differences between TB patients with and without HIV-1 . We found that the predominant effect of early HIV-1 infection was to diminish a component of immune responses that contributes to prevention of harmful inflammation . In more advanced HIV-1 , we found almost complete absence of any immune response to TB except for immune activity which is normally part of our defence against viruses , but may also weaken immune protection against TB . In some patients , TB becomes apparent after starting treatment for HIV-1 . In these patients we found that most immune responses had recovered to normal levels , but that one type of response sometimes associated with asthma and allergies was exaggerated . Our findings provide new insights into how HIV-1 can affect immune responses and changes to the immune system that are associated with risk of TB , which will inform the development of new strategies to improve protective immunity .
|
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2016
|
In Vivo Molecular Dissection of the Effects of HIV-1 in Active Tuberculosis
|
In mammals , females are born with finite numbers of oocytes stockpiled as primordial follicles . Oocytes are “reawakened” via an ovarian-intrinsic process that initiates their growth . The forkhead transcription factor Foxo3 controls reawakening downstream of PI3K-AKT signaling . However , the identity of the presumptive upstream cell surface receptor controlling the PI3K-AKT-Foxo3 axis has been questioned . Here we show that the receptor tyrosine kinase Kit controls reawakening . Oocyte-specific expression of a novel constitutively-active KitD818V allele resulted in female sterility and ovarian failure due to global oocyte reawakening . To confirm this result , we engineered a novel loss-of-function allele , KitL . Kit inactivation within oocytes also led to premature ovarian failure , albeit via a contrasting phenotype . Despite normal initial complements of primordial follicles , oocytes remained dormant with arrested oocyte maturation . Foxo3 protein localization in the nucleus versus cytoplasm explained both mutant phenotypes . These genetic studies provide formal genetic proof that Kit controls oocyte reawakening , focusing future investigations into the causes of primary ovarian insufficiency and ovarian aging .
Primordial follicles are the reserve precursor pool for maturing follicles throughout reproductive life [1] . Primordial follicles are reawakened via an ovarian-intrinsic ( gonadotropin independent ) process whereby they are selected from the quiescent reserve into the growing follicle pool [2 , 3] . The morphologic hallmark of reawakening is oocyte growth , and this is followed by a transition of the surrounding granulosa cells from a flattened to a cuboidal shape [4] . Reawakening is irreversible , in that follicles that have initiated growth undergo atresia if not selected for subsequent stages of maturation . Primordial follicle numbers decrease with advancing age due to oocyte reawakening or apoptosis; following follicle depletion , ovulation ceases and reproductive senescence ensues . Reawakening must therefore be metered throughout reproductive life to ensure that some growing follicles are available during each estrus cycle , but at the same time , limit the number of growing follicles to forestall depletion of primordial follicles ( see Fig 1 for summary schematic of follicle maturation ) . Characterization of the molecular mechanisms underlying reawakening remains an important challenge in reproductive biology [5–8] . The forkhead transcription factor Foxo3 functions as a switch that controls ( suppresses ) reawakening . In nullizygous or oocyte-conditional Foxo3 knockout mice , primordial follicles are assembled normally [9] , but undergo global reawakening at birth . This leads to a characteristic sequential syndrome of ovarian hyperplasia , follicle depletion , and hypergonadotropic ovarian failure [10] . In the adult ovary , Foxo3 protein localizes to the primordial oocyte nucleus , where it restrains reawakening in a PI3K ( phosphoinositide-3-kinase ) -AKT dependent manner . PI3K catalyzes the formation of a lipid second messenger , phosphatidylinositol 3 , 4 , 5-trisphosphate ( PIP3 ) , from phosphatidylinositol 4 , 5-bisphosphate ( PIP2 ) . PIP3 in turn leads to the phosphorylation and activation of AKT . Pten , a lipid phosphatase that converts PIP3 back to PIP2 , potently suppresses AKT activation [11] . Oocyte-specific deletion of Pten hyperactivates AKT , resulting in Foxo3 nuclear export and global reawakening [12 , 13] . Foxo3 normally undergoes nuclear export during the primordial to primary follicle transition ( followed by its degradation within the cytoplasm via unknown mechanisms ) , suggesting that Pten inactivation mimics a naturally-occurring PI3K-dependent signal that regulates Foxo3 localization and hence reawakening [13] . Other studies have confirmed Foxo3’s role as the molecular switch controlling reawakening in a PI3K-AKT dependent manner , and the utility of Foxo3 nuclear vs . cytoplasmic localization as a marker of oocyte maturation [14–18] . Oocyte-specific inactivation of the mTOR inhibitors Tsc1 and Tsc2 also results in oocyte reawakening , establishing an important but incompletely understood role of mTOR signaling in this process [19] . As vital effectors of PI3K-AKT signaling , the Foxos serve fundamental biological roles in aging , cancer , and stem cell maintenance [20–22] . The three canonical Foxos—Foxo1 , Foxo3 , and Foxo4—are coexpressed and exhibit genetic and functional redundancy in most cell types [20 , 21 , 23] . In contrast , in the mouse germline , Foxo1 and Foxo3 have diverged to serve complementary roles in the maintenance of the male and female germline , respectively . Whereas Foxo3 is the principal Foxo protein in the oocyte , Foxo1 is the principal Foxo within undifferentiated spermatogonia , and is the only Foxo required for the maintenance of spermatogonial stem cells [20 , 24] . In both the female and male germline , genetic experiments have shown that Foxo activity is regulated by its subcellular ( nuclear vs . cytoplasmic ) localization via its AKT-dependent phosphorylation . When phosphorylated , Foxo proteins are functionally inhibited by their retention in the cytoplasm via interactions with 14-3-3 proteins [25] . In many physiological processes , the upstream activators of class I PI3Ks are transmembrane receptor tyrosine kinases ( RTKs ) such as Igf1r , insulin receptor , Ret , Pdgfr , or Kit [11] . Ligand binding activates PI3K by phosphotyrosine-mediated binding through an SH2 domain on the p85 subunit of PI3K . G protein–coupled receptors ( GPCRs ) can also activate PI3K through the p110γ catalytic subunit isoform . However , p110γ−/− mice are viable and fertile ( but display various GPCR-mediated immunological defects ) , suggesting that GPCRs may not play essential roles in the regulation of the PI3K pathway during oocyte reawakening [26] . The identification of a presumptive oocyte surface RTK that acts through PI3K-AKT-Foxo3 to regulate reawakening has remained an outstanding question in reproductive biology [27] . Several candidates including Kit have been proposed , but definitive evidence about which is the bona fide receptor has been lacking [3 , 8 , 28–30] . The unique biological features of primordial follicle reawakening , some of which are not readily modeled in vitro , prompted us to apply genetic approaches to identify and validate this factor [3] .
Kit is an RTK that acts via PI3K-AKT , and is expressed within primordial oocytes [31 , 32] . To study the role of Kit in the reawakening of primordial follicles , we generated a novel murine conditional allele , KitD818V ( L ) through homologous recombination in murine embryonic stem cells . The Kit D818V ( Asp→Val ) amino acid substitution leads to constitutive Kit activity in the absence of ligand ( KL ) , and exerts potent dominant gain-of-function effects [31 , 33] . Furthermore , it corresponds to the most common known Kit gain-of-function mutation in human germ cell tumors ( KitD816V ) , demonstrating that this mutant protein is active in germ cells [33–35] . The conditional ( floxed ) KitD818V ( L ) allele was designed to provide Kit function through a 3’ cDNA cassette encoding exons 17–21 . Cre-mediated recombination excises this cDNA cassette , permitting normal splicing of an exon 17 harboring the mutation , and thus expression of mutant D818V protein ( S1A Fig ) . With respect to nomenclature for the four new Kit alleles described in this manuscript , 1 ) genotypes signify somatic genotypes ( per tail DNA genotyping ) and 2 ) the floxed ( i . e . , latent ) alleles end in “ ( L ) ” . Whereas hemizygous Kit ( a . k . a . Dominant white spotting ) loss-of-function mutations produce abnormal coat pigmentation [36] ( see also below ) , mice harboring the KitD818V ( L ) allele were externally normal with coat pigmentation similar to sibling controls , confirming that the floxed allele indeed provided Kit function ( S1B Fig ) . The KitD818V ( L ) allele could be homozygosed , and such animals were also externally indistinguishable from littermate controls ( S1C Fig ) . These mice were then bred to the germ cell-specific Cre driver , Vasa-Cre ( a . k . a . Ddx4-cre1Dcas/J ) ( abbreviated VC ) to generate VC; KitD818V ( L ) /+ females . VC becomes active during late embryogenesis , and drives Cre-mediated recombination in >99% of oocytes by birth [37] . Ovaries were harvested at postnatal day ( PD ) 7 and ovarian cDNA was analyzed by RT-PCR , followed by Sanger sequencing . As expected , ovaries from experimental females expressed mutant cDNA at levels close to wild-type as evidenced by electrophoretogram peak intensities ( S1D Fig ) . By PD7 , VC; KitD818V ( L ) /+ ovaries were consistently larger than ovaries from sibling controls . By PD14 , these size differences were even more marked , but from PD28 onward ( up to 16 weeks of age ) , ovaries were of equal size or somewhat smaller ( Fig 2A ) . To understand the cellular basis of this increase in ovarian size ( and subsequent decrease ) , tissue sections were analyzed . At PD7 , there was an obvious increase in oocyte diameters in follicles that otherwise resembled primordial follicles ( i . e . , follicles without granulosa cell growth or change to cuboidal shape ) ( Fig 2B ) . Interestingly , whereas Kit protein is predominantly membranous in controls , Kit protein underwent a general redistribution to the cytoplasm in VC; KitD818V ( L ) /+ oocytes ( S2A–S2C Fig ) with overall Kit protein levels comparable to KitD818V ( L ) /+ controls ( S2D Fig ) . This is consistent with prior data demonstrating that Kit protein normally undergoes ligand-dependent internalization , and that constitutively active mutant variants are internalized more efficiently than the wild-type protein [38 , 39] . Of note , these morphological alterations were global , occurring in all primordial follicles . VC; KitD818V ( L ) /+ oocytes grew in size up to PD28 , resulting in aberrant follicles with dramatically enlarged oocytes ( Figs 2B and S4A ) . Some morphologically normal follicles and corpora lutea stage were also present , indicating that some of the reawakened follicles progressed normally to more advanced states of follicle maturation . Concordantly , most markers of primordial or primary follicles including periodic acid-Schiff ( PAS ) stain ( labels the zona pellucida ) , ZP1 , Inhibin , Gdf9 , Sohlh1 , Nobox , and Sall4 retained their typical patterns of expression in oocytes or granulosa cells , consistent with normal differentiation despite global reawakening ( S3 and S4A Figs ) . However , in some reawakened follicles , granulosa cells remained flattened and were negative for α-Müllerian Hormone ( AMH ) , which is normally induced at the primary follicle stage ( S4A Fig ) . A similar spectrum of abnormalities has been documented in other global reawakening mutants such as Foxo3 and Pten [10 , 12 , 13] . By 16 weeks , however , oocyte atresia occurred , resulting in morphologically abnormal , “empty” follicles depleted of oocytes ( note also the absence of more advanced follicles and corpora lutea ) ( Fig 2B ) . No teratomas or other ovarian tumors were identified . Thus , constitutive Kit activation in the female germline resulted in a classic , global primordial follicle reawakening phenotype identical to that described for Foxo3 and Pten [10 , 12 , 13] . Global reawakening occurred in all VC; KitD818V ( L ) /+ primordial oocytes , which ultimately underwent atresia resulting in loss of all oocytes with premature ovarian failure . Serum follicle stimulating hormone ( FSH ) and luteinizing hormone ( LH ) levels at 5 months of age were elevated in adult mutant females , consistent with hypergonadotropic hypogonadic premature ovarian failure ( P<0 . 003 and P<0 . 02 respectively ) ( S4B Fig ) . These results strongly implicate Kit as the upstream RTK regulating primordial oocyte reawakening . At birth to PD7 , oocyte numbers were unaltered in VC; KitD818V ( L ) /+ ovaries , indicating a normal initial endowment of oocytes [3] . Oocytes were markedly depleted by PD28 , and totally absent by 6 weeks of age ( P<0 . 02 and P<0 . 0004 , respectively ) ( Fig 3A ) . Measurements of oocyte diameters confirmed that average oocyte sizes were significantly increased by PD7 , and the difference was even more marked at PD14 ( P<0 . 0001 for both PD7 and PD14 ) . Oocytes continued to grow through PD28 , although by this timepoint , relatively few oocytes remained ( Figs 3B , 3C and S4A ) . Sections from experimental and control ovaries embedded in plastic confirmed the absence of oocytes by 6 weeks of age as well as the presence of atretic oocytes and zona pellucida remnants ( the “ghosts” of oocytes that underwent reawakening and subsequent atresia ) in VC; KitD818V ( L ) /+ females ( S4C Fig ) . Next , various markers were analyzed by immunohistochemistry at PD7 to further characterize potential abnormalities in downstream effectors such as Foxo3 . All oocytes were strongly Vasa-positive , indicating preservation of germline identity following Kit activation . Kit protein was present at high levels within oocytes , although some redistribution to the cytoplasm was evident in the mutant as was the case by immunofluorescence ( Fig 4A ) . Activated early oocytes exhibited increased phosphorylated AKT ( P-AKT ) on their cell membranes as compared to control primordial and primary follicles , which did not contain detectable P-AKT ( Fig 4A ) . This is consistent with the known role of PI3K-AKT as the key signaling pathway mediating oocyte reawakening [13] , and argues strongly that Kit controls reawakening via this pathway . Importantly , AKT hyperphosphorylation drove translocation of Foxo3 protein from the nucleus to the cytoplasm in all VC; KitD818V ( L ) /+ oocytes ( Fig 4A ) . Confocal microscopy , which allows for higher resolution than immunohistochemistry , confirmed these results; i . e . Foxo3 was predominantly nuclear in controls , but cytoplasmic in the mutant oocytes ( Fig 4B ) . The above results provided strong genetic evidence implicating Kit as the upstream RTK controlling oocyte reawakening via the PI3K-AKT-Foxo3 axis . However , phenotypes associated with gain-of-function mutations should generally be interpreted with caution , as even a single amino acid substitution could have multiple , distinct , and potentially unexpected effects on protein function and thus , phenotypes . To expand upon our genetic analyses of Kit in oocyte reawakening with a complementary genetic approach , we designed a new allele where exon 17 , which encodes the kinase domain [31] , was floxed . Kit is an essential locus due to its requirement for hematopoiesis , necessitating conditional genetic analysis . The floxed allele KitL could be homozygosed as expected , and KitL/KitL animals were born at expected Mendelian ratios ( S5A and S5B Fig ) . For oocyte-specific Kit inactivation , VC; KitL/+ fathers were bred to KitL/KitL females . VC activity in the father’s germline converts any paternally transmitted KitL allele to Kit- and thus , VC fathers can transmit a wild-type ( Kit+ ) or null Kit-allele but not a KitL allele [37] . Experimental females of the VC; KitL/- genotype ( per tail DNA ) thus harbor homozygous Kit- loss-of-function mutations in their germline . RT-PCR of ovaries ( S5C Fig ) and Sanger sequencing of PCR-amplified cDNAs ( S5D Fig ) confirmed VC-dependent deletion of exon 17 . Whereas control mice harboring the floxed allele exhibited no pigmentation or other external abnormalities , VC; KitL/- mice showed striking midline hypopigmentation , consistent with hemizygous somatic loss of Kit activity ( S5E Fig ) . At PD7 , VC; KitL/-ovaries were minute , and their small size persisted at all mouse ages analyzed , up to 12 weeks of age ( Fig 5A ) . Histological analyses revealed a striking and complete failure of oocyte reawakening . Follicles remained small and no growing oocytes were present , although granulosa cells became cuboidal . In these follicles , oocytes typically assumed an eccentric location ( Figs 5B and S6A ) . Electron microscopy ( EM ) confirmed the viability of these oocytes and their lack of physical growth . Granulosa cells exhibited some mitotic activity in the mutant follicles per Ki67 immunohistochemistry ( whereas normal primordial follicles are mitotically inactive ) ( S6D Fig ) , consistent with increased granulosa cell numbers in the aberrant follicles of VC; KitL/-ovaries . Interestingly , EM also revealed abundant lipid droplets in the granulosa cells , which could contribute to their change in shape ( S6B Fig ) . The significance of these lipid droplets is uncertain . One interpretation is that granulosa cells “sense” the lack of oocyte growth ( due to known , if poorly understood , bidirectional oocyte/granulosa cell communication ) , and respond in some manner to promote reawakening [5 , 40] . Alternatively , an abnormal hormonal milieu associated with ovarian failure could also indirectly contribute to the observed changes in granulosa cells . In any case , ZP1 , which is expressed in growing oocytes , was not expressed in any VC; KitL/- oocytes , consistent with a constitutional inability to reawaken/initiate growth despite the granulosa cell changes . Oocyte numbers were unaltered in VC; KitL/-ovaries at PD7 , demonstrating that the minute ovaries were due to a complete lack of oocyte growth , and not a diminished initial endowment of primordial follicles ( Fig 6A ) . Measurements of oocyte diameters confirmed the lack of oocyte growth ( Fig 6B and 6C ) . These quantitative and morphometric data thus revealed a complete failure of oocyte reawakening in Kit-deficient oocytes . Somewhat unexpectedly given prior studies implicating Kit in germ cell and primordial oocyte survival , VC; KitL/- oocytes did not undergo rapid apoptosis [28 , 41] . To the contrary , VC; KitL/- primary/primordial oocyte counts showed only a minor ( statistically not significant ) decrease even at 12 weeks of age , consistent with a remarkably specific role for Kit in oocyte reawakening ( Fig 6A ) . However , by 6 months of age , the ovaries were entirely depleted of follicles and oocytes and contained only luteinized stroma ( S7A–S7C Fig ) , demonstrating that Kit is required for the long-term maintenance of oocytes , in keeping with prior studies implicating Kit as an oocyte survival factor [28 , 42] . At birth , oocytes are syncytial and interconnected by intercellular bridges , which are broken down by PD3 to give rise to individualized primordial follicles . Follicle individualization ( also known as assembly ) occurred normally in VC; KitL/-ovaries ( e . g . , no follicles contained more than one oocyte ) , demonstrating that Kit is not essential for individualization despite its abundant expression within oocytes at PD1-3 when individualization takes place ( Fig 5B ) . Additional marker studies at 6 weeks of age showed that all oocytes retained germline identity , with normal expression of primordial oocyte markers such as Vasa , p63 ( an oocyte survival factor ) , Foxo3 , Sohlh1 , and Nobox ( Fig 7A ) . Granulosa cells continued to express inhibin and AMH ( markers of female gonadal somatic cell differentiation ) but did not express the Sertoli cell marker Gata-1 ( Fig 7C and 7D ) , evidence against a sex-reversal phenotype , a possibility entertained because of the morphologic resemblance of the aberrant follicles—particularly those with eccentric oocytes—to primitive male sex cords . These results are consistent with a specific role of Kit in oocyte reawakening . Additionally , Foxo3 was constitutively nuclear and P-AKT was undetectable in Kit-deficient oocytes ( Fig 7A and 7B ) further supporting a critical role of the Kit signaling pathway in regulating oocyte awakening via P-AKT/Foxo3 .
Primary ovarian insufficiency ( POI ) , also known as premature ovarian failure , is a form of hypergonadotropic hypogonadic ovarian failure that causes early menopause and infertility in 1% of women before the age of 40 , in addition to other important health consequences due to estrogen deficiency [43] . POI is associated with the accelerated depletion of primordial follicles , arguing that abnormalities in primordial follicle maintenance are the unifying pathophysiologic basis of POI . However , the identification and further study of key factors regulating primordial follicle maintenance and reawakening has proven difficult with human subjects; for example , ovaries are not biopsied in the clinical workup of POI , limiting available human ovarian tissue for direct analyses . Genome-wide studies have implicated several loci , but further and more detailed genome-wide investigations are needed to more fully define the genetic basis of POI [44–47] . Numerous factors have been proposed as regulators of reawakening , such as the AMH type 2 receptor ( AMHR2 ) , a member of the transforming growth factor β superfamily of growth and differentiation factors [48] . AMHR2 female mice are fertile with no overt defects in follicle maturation , however , arguing against an essential role in reawakening [49] . Similarly , while α-Müllerian hormone ( AMH ) has also been proposed as a regulator of oocyte utilization and reawakening , AMH-null females are fertile , suggesting that AMH plays at most a secondary role in regulating reawakening . Other factors must therefore participate in this process [50] . Kit has also been proposed as a candidate factor regulating reawakening . Kit and Kit ligand ( KL , also known as SCF ) serve diverse functions in the germ cell lineage , particularly in primordial germ cell migration/survival , primordial follicle assembly [51] , and spermatogenesis . KL is produced by granulosa cells in primordial follicles [32] and Kit is highly expressed by primordial oocytes . Thus , patterns of Kit and KL expression within the ovary make them plausible candidates as factors regulating reawakening . In vitro studies conducted with explanted ovaries treated with KL or Kit inhibitors have also been interpreted as supportive of this hypothesis [52 , 53] . On the other hand , the observed effects have been relatively small in magnitude and more importantly , these in vitro , non-genetic approaches suffer from significant potential limitations stemming from the unique biological properties of reawakening . Reawakening normally occurs at a gradual and measured pace throughout life , such that only a very small percentage of follicles are awakening at any time . Thus , available in vitro methods with explanted neonatal ovaries ( which can be maintained for only one to two weeks ) do not provide a completely adequate timescale for definitive studies including the identification of novel factors regulating reawakening . Phenotypic analysis of KitY719F homozygous female mice have provided intriguing genetic evidence implicating Kit in reawakening [28] . Kit activates PI3K through a direct interaction with an SH2 domain on the p85 regulatory subunit of PI3K . This interaction is dependent on Kit tyrosine residue 719 , which undergoes autophosphorylation following ligand binding . Mutation of this tyrosine residue prevents binding of Kit to p85 , and thus abrogates Kit signaling via PI3K [54] . Mice engineered with this KitY719F mutation ( via a “knockin” approach ) have permitted genetic dissection of the contribution of PI3K signaling to diverse Kit-dependent biological processes [55 , 56] . Homozygous KitY719F males are sterile with severe defects in spermatogenesis . KitY719F females , however , are fertile at 16 weeks of age , suggesting that Kit might not play an essential role in reawakening ( although severe defects in early follicle maturation including an arrest at the primary/secondary follicle stage were documented ) [28] . Subsequent analyses of this allele have been interpreted as supportive of a role of Kit in reawakening , rationalizing its use in studies to genetically dissect reawakening . For example , genetic inactivation of Tsc1 within primordial follicle granulosa cells leads to global reawakening via Foxo3 cytoplasmic relocalization , and this was found to occur through enhancement of Kit ligand production in primordial follicle granulosa cells . KitY719F homozygosity suppressed this Tsc1-null reawakening phenotype , arguing that the observed increase in Kit ligand was responsible for reawakening [57] . Foxo3 relocalization to the cytoplasm occurs after the primordial-primary transition , and abnormal Foxo3 relocalization has been documented in mutants undergoing global reawakening [12 , 13 , 16 , 57] . However , for reasons that are not well understood , Foxo3 relocalization as visualized by IHC/IF does not anticipate ( precede ) reawakening; i . e . , early primary follicles have nuclear Foxo3 [13] . It is possible that Foxo3 protein can be functionally inactivated in the oocyte but that the protein remains detectable in the nucleus for some time . Thus , in practice , the most useful , sensitive , and earliest indicators of reawakening ( i . e . , for scoring mutant phenotypes ) remain morphologic . As emphasized in this study , oocyte diameter is the earliest and most sensitive endpoint for reawakening . In diverse investigations of mutants with global reawakening ( e . g . , Pten and Foxo3 mutants , also in the KitD818V mutant described here ) , granulosa cells remain flattened and unilayered in many follicles with massively enlarged oocytes that have clearly undergone reawakening; indeed , such oocytes can continue to grow unabated for several weeks despite the persistence of “primordial follicle-like” granulosa cell morphology [10 , 13 , 16 , 19 , 58] . Furthermore , we have here documented in VC;KitL/- ovaries a transition in granulosa cell morphology to a cuboidal shape and mitotic activity resulting in a few layers even in follicles where oocytes were constitutionally unable ( due to Kit inactivation ) to grow/reawaken . Thus , while granulosa cells normally undergo significant changes in morphology and arrangement during reawakening , these do not always correlate with oocyte status in individual follicles and are not as useful as morphological indicators in mutants with strong reawakening phenotypes . Thus , we stress that abnormal oocyte diameters should be considered the sine qua non for scoring oocyte reawakening phenotypes and that careful measurements of oocyte diameters ( e . g . , in tissue sections ) should represent the gold standard in such analyses until earlier molecular markers of reawakening are identified . That the KitY719F mutation did not lead to a complete oocyte dormancy phenotype , as documented in earlier studies ( females were fertile up to at least 16 weeks of age ) can be explained by the hypomorphic nature of this mutation [28] . For example , residual Kit signalling via PI3K or other surrogate signalling pathways could feed back to PI3K , resulting in some PI3K tonic activity . Finally , some hypomorphic alleles of KL ( a . k . a . Steelpanda ) also accumulate follicles with cuboidal granulosa cells ( albeit with growth-arrested oocytes ) , consistent with a role of KL in reawakening , although these ovaries contain very few follicles , obscuring interpretation of phenotypes [28 , 59] . The role of KL in reawakening should be further explored in future studies; i . e . , through conditional genetic analysis of KL in granulosa cells . KL appears to be constitutively expressed in granulosa cells in primordial follicles [60] , and although KL is elevated in the Tsc1 reawakening mutant , the nature of the signals and inter/intra-follicular communication triggering reawakening via Kit-PI3K-Foxo3 in individual primordial follicles remains uncertain . More recently , conditional deficiency of the Lim homeodomain protein Lhx8 was found to promote global reawakening , with a synergistic effect of Lhx8 and Pten on Foxo3 nucleocytoplasmic translocation . These effects were mediated by Lin28a , an RNA binding protein and regulator of the let-7 microRNAs , a finding of particular interest given studies implicating the Lin28/let-7 axis in the control of PI3K-mTOR signalling [16 , 61] . Clearly , more work is needed to fully dissect the interactions of the diverse members of the PI3K and mTOR pathways and how these function together to trigger reawakening of individual primordial follicles . One notable aspect of this study is that we have now documented global oocyte reawakening and dormancy phenotypes with our KitD818V and KitL alleles , respectively . Such complementary and contrasting phenotypes with alleles that have opposite effects on Kit activity ( i . e . , gain- vs . complete loss-of-function alleles ) represent compelling genetic evidence incriminating Kit as the critical receptor upstream of PI3K-Foxo3 in the control of reawakening . The phenotype we describe for the oocyte conditional Kit knockout represents the first report of a pure global dormancy mutant; i . e . , where female sterility was associated with minute ovaries containing a numerically normal complement of primordial follicles but where a complete failure of oocyte reawakening left oocytes incapable of growth/reawakening . Conversely , Kit serves essential roles in other aspects of follicle formation , development , and survival [3 , 28 , 51] . Our genetic studies do not exclude a contribution from other cell surface receptors in reawakening , but help establish Kit as the principal upstream factor regulating reawakening , and also demonstrate a remarkably specific role for Kit in reawakening . It is surprising that Kit played such a modest role in oocyte survival , with normal oocyte counts up to 12 weeks of age , a result suggesting that other factors regulate oocyte survival and prevent apoptosis [62] . Oocyte conditional ablation ( Vasa-Cre ) of other genes encoding cell surface receptors acting through PI3K and known to be expressed on the oocyte , such as Igf1r , Insr , Ret , Pdgfr had no effect on fertility or follicle maturation ( unpublished data ) , further stressing the uniqueness of the Kit reawakening phenotypes . POI is a form of hypergonadotropic hypogonadism that causes infertility in 1% of women before the age of 40 and has important health consequences . POI is due to accelerated depletion of primordial follicles [63–66] , arguing that abnormalities in primordial follicle maintenance are the unifying pathophysiologic basis of POI . However , the molecular mechanisms that cause follicle depletion in POI are poorly understood . Elucidating these mechanisms is needed to develop better treatment strategies and assays predictive of POI . Our results should help focus further investigations on Kit and , by extension , Kit ligand , as keystone regulators of primordial oocyte maintenance and hence , female reproductive aging . Pharmacologic manipulation of this pathway may someday prove useful in fertility preservation by increasing the pool of actively growing follicles [14] . This is further underscored by the fact that PI3K-Foxo3 signaling regulates the egg supply throughout life [28] . For example , transient treatment of mouse or human oocytes with either a Pten inhibitor or a PI3K activating peptide results in activation of dormant primordial follicles . Pharmacologic control of this pathway either at the level of PI3K-AKT or Kit-KL may thus prove useful in fertility preservation by increasing the pool of growing follicles [14 , 15 , 67] .
All live animal experiments followed guidelines by the UTSW Animal Care and Use Committee who also approved the experiments performed ( 2015–101272 ) . Mice were housed in a pathogen-free animal facility in microisolator cages and fed ad libitum on standard chow under standard lighting conditions . A detailed description of the targeting strategy , assembly , primer sequences , and PCR conditions for generating the KitD818V ( L ) and KitL alleles are provided in S1 Text . Mice were genotyped from tail DNA by PCR with Promega GoTaq in 1 . 6 mM MgCl2 . Genotyping primers for the KitD818V allele were as follows: ( a1 ) 5’-ATTAGAGCCCCGATCCTGTG-3’ and ( b1 ) 5’-GCAACAGCCATTCATTTCAGC-3’ ( see S1 Fig for positions of a1/b1 primers ) , under the following cycling conditions: 95° x 2 min; 94° x 30 sec , 60° x 30 sec , 72° x 30 sec ( 35 cycles ) ; 72° x 7 min . The product sizes are 219 bp for the floxed allele KitD818V ( L ) and 171 bp for the wild type Kit allele . Genotyping primers for KitL allele are as follows: ( a1 ) 5’-AGTTCTGAAGAGACTGTCAAGGT-3’ and ( b2 ) 5’-ACACCCCATTTCCTTATTTTTGCT-3’ ( see S3 Fig for positions of a1/b1 primers ) , under the following cycling conditions: 95° x 2 min; 94° x 30 sec , 60° x 30 sec , 72° x 30 sec ( 35 cycles ) ; 72° x 7 min . The product sizes are 174 bp for the floxed KitL allele and 126 bp for the wild type Kit allele . Total RNA was prepared from ovaries with the Tripure isolation reagent ( Roche #93876820 ) per the manufacturer’s instructions . To validate the KitD818V ( L ) allele , exon 17 was amplified by one step RT-PCR ( Qiagen #210210 ) using the primers: 5’-AGATTTGGCAGCCAGGAATA-3’ ( forward ) and 5’-ATTTCCTTTGACCACGTAATTC-3’ ( reverse ) . For validation experiments of the Kit- allele , cDNA was synthesized with M-MuLV Reverse Transcriptase ( New England BioLabs #28025–013 ) . Kit cDNA sequences , spanning exons 14 to 18 were amplified by Phusion High-Fidelity DNA Polymerase ( New England BioLabs #M0530S ) . The forward primer ( close to exon 14 ) was 5’-GAGAAGGAAGCGTGACTC-3’; the reverse primer ( close to exon 18 ) was 5’-AGGAGAAGAGCTCCCAGA-3’ . PCR conditions were: 98°C x 3 min; 34 cycles of 98°C x 60 sec , 60°C x 60 sec , 72°C x 120 sec; then 72°C x 5 min . RT-PCR products were analyzed by gel electrophoresis and bands purified with the QIAquick gel extraction kit ( Qiagen #28704 ) . The KitD818V mutation or exon 17 deletion were confirmed by Sanger sequencing ( UTSW sequencing core ) . Ovaries were fixed in 10% formalin overnight , embedded in paraffin and serially sectioned ( 5 μm ) . Every fifth section was H&E stained and analyzed . For VC; KitD818V ( L ) /+ and control ovaries , the middle section of the series was used for relative follicle counts and diameter measurements as described in the text . For VC; KitL/- and control ovaries , all the primordial and primary oocytes were counted in every fifth section . The longest diameter of 50 oocytes for which nuclei were in the plane of section was determined with ImageJ . For IHC , sections were rehydrated in EtOH series after deparaffinization in xylene . Antigen retrieval was performed in parboiling 10 mM sodium citrate ( pH 6 . 0 ) x 20 min , cooled at RT , followed by peroxidase blocking ( 3% H202 ) and blocking in 0 . 5–1% BSA in PBS . Antibodies and titers for IHC were: Kit 1:750 ( Cell Signaling #3074S ) ; Vasa 1:200 ( Abcam #27591 ) ; P-AKT 1:75 ( Cell Signalling #S473 ) ; Sall4 1:1000 ( Abcam #57577 ) ; Foxo3 1:50 ( Santa Cruz #sc-11351 ) ; AMH 1:500 ( Serotec #MCA2246 ) ; P63 1:500 ( Thermo Fisher #MS-1081 ) ; Inhibin ( Biorad #MCA951ST ) ; Gata-1 ( Santa Cruz #sc-265 ) ; Zp1 ( Santa Cruz #sc-23708 ) ; Gdf9 ( Santa Cruz #sc-12244 ) ; Ki67 ( Abcam #15580 ) ; Sohlh1 and Nobox antibodies were kindly provided by Dr . Aleksandar Rajkovic ( Magee-Womens Research Institute ) . ImmPRESS ( Vector Laboratories ) was used for detection . For immunofluorescence ( IF ) , sections were rehydrated in an EtOH series after deparaffinization in xylene . Antigen retrieval was performed in parboiling 10 mM sodium citrate ( pH 6 . 0 ) x 20 min , cooled at RT , followed by PBS washes , 10 minutes of autofluorescence blocking ( 100 nm Tris Glycine ) , and blocking in 2 . 5% BSA+5% goat serum ( Vector Laboratories ) in PBS . Antibodies and titers for IF were: Foxo3 1:50; Kit 1:100 . Fluorophore conjugated secondary mouse ( Alexa Fluor 555 ) or rabbit ( Alexa Fluor 488 ) IgGs at 1:500 ( Invitrogen #A21429 and #A11029 ) were used for detection . Zeiss LSM 510 confocal microscopy was used for fluorescence imaging . Serum FSH/LH levels were measured by the Ligand Assay Core at the University of Virginia . Serum was diluted 1:10 prior to analysis . Ovaries ( two/genotype ) were homogenized in RIPA buffer supplemented with Complete Proteinase inhibitor cocktail ( Roche ) and Phosphatase Inhibitor cocktail 2 ( Sigma ) . Following homogenization , extracts were centrifuged at 10000 rpm for 7 min . Supernatants were collected , mixed with 4x Laemmli Sample Buffer ( BioRad ) and boiled for 10 min . Equal amounts were loaded in a 10% SDS PAGE and run at 100V . Gel was transferred to Immobilon P membrane ( Millipore ) . The membrane was blotted with 5% dry milk in TBS-T ( BB ) , and probed with 1:1000 dilution of Kit antibody in BB overnight at 4°C ( Cell Signaling , #3074 ) . The membrane was stripped with Restore Stripping Buffer ( Thermo Scientific ) , blotted and probed with 1:5000 α-tubulin in BB for 1hr at room temperature ( Sigma , T9026 ) . Blots were developed with SuperSignal West Dura Extended Duration Substrate ( Thermo Scientific ) and digital images acquired with a ChemiDoc system ( BioRad ) . Two ovaries per genotype were fixed , embedded in Embed 812 resin ( Electron Microscopy Sciences ) and prepared for negative staining as described [9] . Images were acquired using a FEI Tecnai G2 Spirit electron microscope . Thin sections were also stained with Toluidine blue and analyzed with light microscope . P values and means +/- S . E . M . were calculated by two-tailed unpaired Student’s t test with GraphPad Prism 6 .
|
In mammals , oocyte reawakening controls female fertility , the onset of the menopause , and thus , overall aging . We demonstrate here through complementary genetic experiments that Kit is the upstream receptor regulating oocyte reawakening . Although other cell surface receptors have been proposed as candidates , the data have remained contradictory , and definitive genetic evidence in support of any one receptor has been lacking . We engineered two novel Kit alleles in mice , one an activating ( gain-of-function ) mutation , the other an inactivating ( loss-of-function ) mutation . These alleles permitted us to conduct elegant genetic experiments whereby Kit was activated or inactivated in the oocytes of newborn mice . The results were complementary and striking . Oocyte-specific Kit activation resulted in female sterility due to reawakening of all oocytes , leading to premature ovarian failure . In contrast , Kit inactivation also led to female sterility and ovarian failure , but through a contrasting and opposite phenotype: a complete failure of primordial follicle reawakening . Additional studies demonstrated that Foxo3 , a known regulator of reawakening , was the mediator of both phenotypes , linking our findings to prior discoveries . These complementary genetic experiments thus definitively incriminate Kit as the upstream receptor regulating reawakening .
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2016
|
Control of Oocyte Reawakening by Kit
|
Tick-borne rickettsioses are caused by obligate intracellular bacteria belonging to the spotted fever group ( SFG ) rickettsiae . Although Spotted Fever is prevalent in the Middle East , no reports for the presence of tick-borne pathogens are available or any studies on the epidemiology of this disease in the West Bank . We aimed to identify the circulating hard tick vectors and genetically characterize SFG Rickettsia species in ixodid ticks from the West Bank-Palestinian territories . A total of 1 , 123 ixodid ticks belonging to eight species ( Haemaphysalis parva , Haemaphysalis adleri , Rhipicephalus turanicus , Rhipicephalus sanguineus , Rhipicephalus bursa , Hyalomma dromedarii , Hyalomma aegyptium and Hyalomma impeltatum ) were collected from goats , sheep , camels , dogs , a wolf , a horse and a tortoise in different localities throughout the West Bank during the period of January-April , 2014 . A total of 867 ticks were screened for the presence of rickettsiae by PCR targeting a partial sequence of the ompA gene followed by sequence analysis . Two additional genes , 17 kDa and 16SrRNA were also targeted for further characterization of the detected Rickettsia species . Rickettsial DNA was detected in 148 out of the 867 ( 17% ) tested ticks . The infection rates in Rh . turanicus , Rh . sanguineus , H . adleri , H . parva , H . dromedarii , and H . impeltatum ticks were 41 . 7 , 11 . 6 , 16 . 7 , 16 . 2 , 11 . 8 and 20% , respectively . None of the ticks , belonging to the species Rh . bursa and H . aegyptium , were infected . Four SFG rickettsiae were identified: Rickettsia massiliae , Rickettsia africae , Candidatus Rickettsia barbariae and Candidatus Rickettsia goldwasserii . The results of this study demonstrate the geographic distribution of SFG rickettsiae and clearly indicate the presence of at least four of them in collected ticks . Palestinian clinicians should be aware of emerging tick-borne diseases in the West Bank , particularly infections due to R . massiliae and R . africae .
Tick-borne spotted fever group ( SFG ) rickettsioses are caused by obligate intracellular Gram-negative bacteria belonging to the genus Rickettsia [1] . Feeding ticks can transmit these microorganisms to humans and animals . Various vertebrates are suspected to serve as reservoirs for Rickettsia species; however , some are susceptible to rickettsial infections and may develop rickettsemia following tick bite [2] . The human disease may present as a fever with clinical symptoms including headache , rash , and occasional eschar formation at the site of the tick bites [3] . Mediterranean spotted fever ( MSF ) , caused by Rickettsia conorii , is transmitted by the brown dog tick , Rhipicephalus sanguineus , which is well adapted to urban environments . Previous studies in Israel have documented the presence of two spotted -fever group ( SFG ) rickettsiae: the tick-borne rickettsia , Rickettsia conorii israelensis and the flea-borne rickettsia , Rickettsia felis [4] , [5] . Rickettsia conorii israelensis has been described in Tunisia , Libya , Sardinia-Italy , and Portugal [6] . Furthermore , a number of other SFG pathogenic rickettsiae including Rickettsia africae , Rickettsia massiliae and Rickettsia sibirica mongolitimonae have been detected in ticks from Israel in addition to some rickettsial species such as Candidatus Rickettsia barbariae and Candidatus Rickettsia goldwasserii which were not associated with diseases , to date [7] , [8] , [9] . The number of newly described SFG rickettsiae has increased in recent decades [4] . Sequence analysis of PCR-amplified fragments targeting genes encoding the citrate synthase ( gltA ) [10] , Rickettsia-specific outer membrane protein ( ompA ) [11] , the 17kDa lipoprotein precursor antigen gene ( 17 kDa ) [12] , and the ribosomal 16S rRNA gene [13] has become a reliable method for the identification of Rickettsia species . Molecular typing of infectious agents is important for better understanding of ecological niches and identifying circulating strains and their virulence . Although various Rickettsia species are found in ticks from Israel; to date , no entomological survey has been carried out in the West Bank , and no clinical data or reports for the presence of tick-borne pathogens are available . Thus , this study aimed at identification of the circulating hard tick vectors and Rickettsia species in naturally infected ixodid ticks collected from the West Bank , using PCR and sequence analysis with special focus on their potential threat for humans and animals .
To identify the circulating hard ticks in the West Bank and to evaluate the presence of rickettsial infection in these ticks , one to ten hard ticks per animal host , for a total of 1 , 123 , were collected during January to April , 2014 from dogs , camels , sheep , a horse , a wolf , and a tortoise residing in nine districts in the West Bank . The districts are located in three zones in the central , northern and southern regions of the country ( Fig 1 ) . All ticks were gently removed from their hosting animals by forceps or hand , and individually placed into small , labeled plastic tubes containing 70% ethanol for morphological identification . The ticks were identified using standard taxonomic keys [14] , [15] , [16] , [17] and stored at −20°C until DNA extraction . A maximum of five ticks of different tick species per hosting animal were randomly selected for DNA extraction . Genomic DNA was individually extracted from a total of 867 tick samples . Prior DNA extraction , individual ticks were washed with phosphate-buffered saline ( PBS ) , air dried for 10 min on tissue paper and separately sliced into small pieces by a sterile scalpel blade then manually homogenized with a sterile micro pestle , resuspended in 200 μl of lysis buffer and 20 μl of proteinase K . After overnight incubation at 56°C with a continuous gentle shaking , the DNA was extracted using the QIAamp DNA tissue extraction kit ( Qiagen , Hilden , Germany ) following the manufacturer's protocol . Purified DNA was stored at 4°C until use . Three μl of template DNA ( approximately 100–200 ng per tick ) were used for each PCR . Screening for the presence of rickettsial DNA was carried out by conventional PCR targeting a 250-bp fragment of the ompA gene using 107F and Rm299 primers as described previously [7] with the following modification: final volume of 25μl using PCR-Ready Supreme mix ( Syntezza Bioscience , Jerusalem ) including primers at 1μM final concentration . Positive samples were further characterized targeting a 426-bp portion of the 16SrRNA and a 265-bp portion of the 17kDa protein gene as previously described [18] , [19] . For Rickettsia species identification , strong positive samples were sent for sequencing . DNA extract of the first ompA positive sample , identified as R . massiliae , by direct sequencing , was used as a positive control and ultra pure water were used as a negative control in each amplification reaction . DNA sequences of the positive PCR products were assembled using Bioedit software , used in a BLAST search ( ncbi . nlm . nih . gov/blast ) and aligned with sequences of other rickettsial species registered in the GenBank . To infer relationships between the obtained amplicons and other reference sequences published in GenBank , a phylogenetic tree was constructed using MEGA6 program . Statistical analysis was done using the SPSS program v20 . Two –tailed t- test and Pearson’s correlation were performed . P-value <0 . 05 was considered statistically significant . The animal population was residing in different farms throughout the West Bank . Prior to ticks sampling , the animal owners were verbally informed about the goals of the project and the sampling protocol . All owners gave their verbal informed consent to collect ticks from their animals . The study was approved by the ethics committee at the Faculty of Medicine in Al-Quds University-Palestine ( EC number: ZA/196/013 ) .
A total of 1 , 123 hard ticks were collected from 320 animals ( 234 dogs , 68 sheep , 10 camels , 5 goats , one horse , one wolf and one Mediterranean spur-thighed tortoise ) . From each infested animal one to ten ticks were collected . Of them , 547 were male ticks ( 48 . 7% ) , 511 females ( 45 . 5% ) and 65 nymphs ( 5 . 8% ) . All tick samples were identified to the species level as follows: Rhipicephalus sanguineus ( n = 694 ) , Rhipicephalus turanicus ( n = 191 ) , Rhipicephalus bursa ( n = 16 ) , Rhipicephalus spp . ( n = 21 ) , Haemaphysalis parva ( n = 100 ) , Haemaphysalis adleri ( n = 20 ) , Hyalomma dromedarii ( n = 68 ) , Hyalomma impeltatum ( n = 5 ) , Hyalomma aegyptium ( n = 4 ) , and Hyalomma spp . ( n = 4 ) ( Table 1 ) . A set of 867 ticks comprising eight different species were screened for rickettsial DNA targeting Rickettsia–specific ompA ( Table 2 ) . A sample was considered positive when PCR yielded a fragment with the expected length ( 250 bp ) of the ompA rickettsial gene . The overall prevalence of rickettsiae infection was 17% ( 148/867 ) in all ticks ( Table 2 ) . The detection of rickettsial DNA was significantly higher in female ticks ( 20 . 4% ) than in male ( 15 . 7% ) and nymph ticks ( 4 . 8% , p<0 . 01 ) . The overall prevalence of rickettsial DNA was markedly higher in ticks collected from Nablus ( 34 . 3%; 66/192 ) compared to other districts ( p<0 . 01 ) ( Fig 1 ) . The infection rates in Rh . turanicus , Rh . sanguineus , Haemaphysalis adleri , H . parva , Hyalomma dromedarii and H . impeltatum ticks were 41 . 7 , 11 . 6 , 16 . 7 , 16 . 2 , 11 . 8 and 20% respectively . None of the ticks belonging to Rh . bursa ( 0/13 ) and H . aegyptium ( 0/4 ) , taken from sheep and one tortoise , respectively , were infected ( Table 2 ) . Among the positive samples ( n = 148 ) , identification of rickettsial DNA based on sequencing of the ompA amplicons were successfully obtained from 63 ( 42 . 6% ) samples which showed strong bands on agarose gel . These samples were subsequently subjected to two additional amplification reactions targeting the 16SrRNA and 17kDa genes of Rickettsia species . Successful sequences were only obtained from ( 35/63 ) and ( 36/63 ) by 16SrRNA and 17kDa PCR , respectively . BLAST analysis of the positive ompA sequences revealed 4 different rickettsial species . Twenty eight ticks were tested positive for R . massiliae-DNA including 15 Rh . turanicus , 11 Rh . sanguineus , one Haemaphysalis parva and one H . adleri , all obtained from dogs and sheep . C . R . barbariae-DNA was found in 12 ticks: 5 Rh . turanicus , 3 Rh . sanguineus and 4 H . dromedarii . The DNA of C . R . goldwasesrii- was detected in 17 ticks: 2 Rh . turanicus , 7 Rh . sanguineus , 6 H . parva and 2 H . adleri . Four ticks were positive for Rickettsia species found in four Rh . sanguineus ticks , Furthermore , R . africae-DNA was detected in two ticks , H . impeltatum and H . dromedarii obtained from two different camels in Jericho ( Fig 2A ) . There were no cases in which multiple rickettsiae species were detected in the same infected tick . Phylogenetic analysis based on ompA sequences revealed three main clusters: R . massiliae , C . R . barbariae and C . R . goldwasserii . Cluster I , representing the R . massiliae group ( n = 28 ) . In this cluster , the nucleotide ompA sequences of R . massiliae identified in this study were identical to each other and to the respective R . massiliae reference sequence ( accession no . KJ663746 . 1 ) deposited in the NCBI GenBank ( Fig 2A ) . The same samples also showed one cluster and had 100% similarity to the R . massiliae reference strains ( NR074486 . 1 and JN871727 . 1 ) based on the 16sRNA and 17kDa analysis , respectively ( Fig 2B and 2C ) . The DNA sequence of Rickettsia canadensis ( CP003304 . 1 ) that do not belong to the SFG [20] , was used as an out group in the analysis of ompA gene while the sequences of Anaplasma phagocytophilum ( EU 436157 . 1 ) and Rickettsiaceae bacterium ( CP009217 . 2 ) were used as out groups in the analyses of the 16SrRNA and 17kDa genes , respectively . On the basis of the ompA sequences , DNA sequences of four amplicons ( 1 . 4G , 1 . 4H , 14 . 8 A , 14 . 8 B ) had several nucleotide differences and showed 96–98% sequence identity to the ompA sequences of R . massiliae identified in this study and to the reference strain of R . massiliae ( KJ663746 . 1 ) . These samples showed 92% and 89% sequence identity to the ompA sequences of the reference strain sequences of R . aeschlimannii ( KF791253 . 1 ) and R . raoultii ( KR608786 . 1 ) , respectively . The four samples were further characterized by 17kDa and 16S rRNA genes , the partial 17kDa gene sequence of these samples revealed 94% and 93% similarity to the reference strain sequences of R . raoultii ( KT261760 . 1 ) and R . conorii ( JN182793 . 1 ) , respectively . Two of them ( 14 . 84A and 14 . 8B ) formed a separate branch with in this group complicating the further confirmation of this Rickettsia spp . ( Fig 2C ) . However , none of these samples ( n = 4 ) were successfully sequenced based on 16SrRNA gene . Cluster II represents the C . R . goldwasserii group . The ompA sequences had 100% similarity to the C . R . goldwasserii reference sequence ( HM136928 . 1 ) whilst the 17kDa sequences of the same samples had 100% similarity to the corresponding sequence of an incompletely described Rickettsia sp . Belarus ( JQ711214 . 1 ) ( Fig 2C ) . The 16SrRNA sequences showed 99% similarity to that of R . rickettsii ( NR103923 ) . Cluster III represents the C . R . barbariae group; the ompA and 16SrRNA sequences had 100% similarity to the Candidatus Rickettsia barbariae reference sequences ( JF700253 . 1 and EU272189 . 1 ) , respectively ( Fig 2A and 2B ) . When 17kDa sequences were obtained from the same samples , they showed 99% sequence similarity to the homologous fragments of R . raoultii ( KT261760 . 1 ) and to the other unidentified Rickettsia sp . ( KM386654 . 1 ) as revealed by BLAST analysis . A sub-cluster of two ompA sequences was identified as R . africae and showed 100% sequence similarity with a homologous fragment of R . africae ( JF700254 ) detected in Hyalomma detritum from the Golan Heights [9] . The 17kDa sequences of these two samples had also 100% nucleotide identity to that of R . africae ( KF646137 . 1 ) but they were not detected by the 16S rRNA PCR .
The overall prevalence of SFG rickettsiae detected in ixodid ticks in nine Palestinian districts was 17% . Ticks detected in this study belonged to three genera ( Rhipicephalus , Haemaphysalis and Hyalomma ) and collected from different host animals . The findings of this study highlight the importance of hard ticks for human health in the West Bank . Rhipicephalus sanguineus was the most prevalent tick species found in this study . It parasitized a wide range of mammals including dogs , sheep , goats and horses; however the main vector for SFG rickettsiae detected in this study was Rh . turanicus . Our results document the detection of two important human pathogens in ticks from the West Bank , R . massiliae and R . africae . R . massiliae was the most prevalent rickettsial species detected in this study . This pathogen was first isolated from Rh . sanguineus in Marseille in 1992 [21] , and since then it has been detected in ticks within the genus Rhipicephalus in Greece , Spain , Portugal , Switzerland , Sardinia ( Italy ) , Morocco and Israel [22] , [23] , [4] , [24] , [25] , [7] . The first isolation of R . massiliae was reported from a human patient in Sicily in 1985 and identified in 2005 [26] . The clinical presentation of R . massiliae infection has been previously described [23] , [27] , [28] . Common clinical signs include fever , night sweats , headache , maculopapular rash and necrotic eschar at the tick bite site . In agreement with other studies , all ticks infected with this pathogen in this study belonged to the genus Rhipicephalus except for two which belonged to the genus Haemaphysalis obtained from the same dog in Jenin district . However , detection of R . massiliae in Haemaphysalis punctata ticks was previously reported in southeast England [29] . In this study , most of R . massiliae- infected ticks were removed from dogs ( 77% ) and to a lesser extent from sheep ( 23% ) , increasing the risk of transmitting rickettsial infections to the animal owners , i . e . dog owners , shepherds and farmers . The phylogenetic tree based on partial DNA sequences of ompA , 16SrRNA and 17 kDa showed higher genetic variability among the R . massiliae strains using ompA gene than 16SrRNA and 17 kDa loci . The second SFG pathogenic Rickettsia found in this study was R . africae , the agent of African tick bite fever . The detection of R . africae , in Hyalomma spp . collected from camels in the West Bank confirms the results of a previous report associating R . africae with Hyalomma ticks in Egypt and Israel [30] , [8] , [9] . Livestock movements and migratory birds may play a role in the geographic spread of R . africae [31] . We observed a strong geographic correlation between the overall prevalence of rickettsial DNA in ticks collected from Nablus ( Northern district ) compared to the prevalence of infected ticks collected from other districts in the north , Ramallah ( centre ) and Hebron ( south ) . Future studies with high representative number of ticks are required to address the comparative importance of geographic distribution on the infection rate of these ticks in the West Bank . Candidatus . R . goldwasserii was also detected in Rhipicephalus ticks collected from dogs in the northern region of the West Bank . This Rickettsia was first detected in two Haemaphysalis ticks ( H . adleri and H . parva ) from golden jackals in Israel . Phylogenetic analysis based on concatenated four gene fragments ( gltA-ompA-sca4-ompB ) indicated that the nucleotide sequences of these SFG rickettsiae belonged to a novel phylogenetic lineage related to C . R . siciliensis detected in Rh . turanicus ticks . [32] . In the present study , the identification of C . R . goldwasserii in Rh . sanguineus and Rh . turanicus , in addition to the already known Haemaphysalis spp , expands the current knowledge concerning tick species that host C . R . goldwasserii in our region . Based on ompA phylogeny , high genetic homology was observed among the C . R . goldwasserii group identified in this study . However , these samples were found to be 100% similar to the corresponding sequence of a not well characterized Rickettsia sp . Belarus and 99% similar to that of R . rickettsii based on 17kDa and 16srRNA respectively . Thus , for a more accurate classification of this uncultivated SFG Rickettsia , further testing and phylogenetic analysis with additional genes is needed since no sequences of these two latter genes of C . R . goldwasserii were available in the GenBank . This is the first study to report the presence of C . R . barbariae in 9 . 6% of Hyalomma ticks in the West Bank . The presence of C . R . barbariae has been previously reported in several Rhipicephalus spp . in Portugal , Italy , France , Cyprus and later in Rhipicephalus ticks flagged from the vegetation in Israel [24] , [33] , [2] , [9] . However , no ompA sequence differences were observed in C . R . barbariae DNA detected in Hyalomma or Rhipicephalus ticks collected from camels , dogs and sheep residing in different localities throughout the West Bank . In conclusion , the findings presented in this study provide evidence for the presence of R . massiliae and R . africae in different ixodid ticks collected from various regions in the West Bank . In addition to Rhipicephalus species , members of the genus Hyalomma and Haemaphysalis may also play an important role in the epidemiology of SFG Rickettsia spp . Clinicians in the West Bank and neighboring countries should consider a range of SFG diseases in the differential diagnoses of patients present with fever of unknown origin and clinical signs compatible with rickettsioses .
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Tick borne rickettsial diseases may have similar clinical characteristics , yet epidemiologically and etiologically different diseases . To date , no studies have been conducted to detect potential tick vectors of rickettsiae in the West Bank . Therefore , we aimed to identify tick species and to determine the presence of Rickettsia pathogens in naturally infected ixodid ticks . The overall prevalence of SFG rickettsiae detected in ixodid ticks in nine Palestinian districts was 17% . Our results document for the first time the finding of two important human pathogens carried by ixodid ticks in the West Bank: R . massiliae and R . africae , the agent of African tick bite fever . Genetically , the detected Rickettsia spp . clustered into 3 different groups: R . massiliae , C . R . barbariae and C . R . goldwasserii . Most of Rickettsia-infected ticks were collected from dogs , camels and sheep , increasing the risk of transmitting rickettsial infections to animal owners , shepherds and farmers . These findings highlight the importance of hard ticks and their potential hazard for human health in the West Bank .
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[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[] |
2016
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Molecular Detection and Identification of Spotted Fever Group Rickettsiae in Ticks Collected from the West Bank, Palestinian Territories
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Neisseria gonorrhoeae causes the sexually-transmitted infection gonorrhea , a global disease that is difficult to treat and for which there is no vaccine . This pathogen employs an arsenal of conserved outer membrane proteins called TonB-dependent transporters ( TdTs ) that allow the gonococcus to overcome nutritional immunity , the host strategy of sequestering essential nutrients away from invading bacteria to handicap infectious ability . N . gonorrhoeae produces eight known TdTs , of which four are utilized for acquisition of iron or iron chelates from host-derived proteins or xenosiderophores produced by other bacteria . Of the remaining TdTs , two of them , TdfH and TdfJ , facilitate zinc uptake . TdfH was recently shown to bind Calprotectin , a member of the S100 protein family , and subsequently extract its zinc , which is then internalized by N . gonorrhoeae . Like Calprotectin , other S100s are also capable of binding transition metals such as zinc and copper , and thus have demonstrated growth suppression of numerous other pathogens via metal sequestration . Considering the functional and structural similarities of the TdTs and of the S100s , as well as the upregulation in response to Zn limitation shown by TdfH and TdfJ , we sought to evaluate whether other S100s have the ability to support gonococcal growth by means of zinc acquisition and to frame this growth in the context of the TdTs . We found that both S100A7 and S10012 are utilized by N . gonorrhoeae as a zinc source in a mechanism that depends on the zinc transport system ZnuABC . Moreover , TdfJ binds directly to S100A7 , from which it internalizes zinc . This interaction is restricted to the human version of S100A7 , and zinc presence in S100A7 is required to fully support gonococcal growth . These studies highlight how gonococci co-opt human nutritional immunity , by presenting a novel interaction between TdfJ and human S100A7 for overcoming host zinc restriction .
The obligate human pathogen Neisseria gonorrhoeae , the etiological agent of the eponymous sexually-transmitted infection ( STI ) gonorrhea , poses a growing threat to global health . In 2017 , the World Health Organization ( WHO ) estimated over 100 million new cases of gonorrhea , with surveillance from the Centers for Disease Control and Prevention ( CDC ) estimating 555 , 000 new , reported cases of this disease each year in the United States alone , and an increase in cases of 18 . 6% from 2016–2017 [1] . Gonorrhea afflicts both men and women , with symptomatic infections in men presenting as urethritis and epididymitis , and in women as cervicitis . Concerningly , up to 80% of cases in women can be asymptomatic [2] , leading to potential ascension into the upper reproductive tract and manifestations including disseminated infection , pelvic inflammatory disease and in some cases even infertility and ectopic pregnancy . Moreover , gonococcal infection poses a serious economic burden , with yearly estimates for treatment of gonorrhea in the United States reaching as high as $240 million [3] . The window of available treatment options for infection by N . gonorrhoeae is rapidly narrowing , as this naturally-competent pathogen rapidly acquires and stably maintains factors for antimicrobial drug resistance . The current treatment regimen for gonorrhea recommended by the CDC is a dual therapy of ceftriaxone and azithromycin [4] , as resistance to quinolones , penicillins , and sulfonamides is ubiquitous , and recent reports have shown treatment failures when using extended-spectrum cephalosporins alone [5–7] . Critically , gonococcal isolates resistant to all forms of approved therapy including the recommended dual therapy have been identified , thus creating a legitimate threat that gonorrhea may become untreatable , and highlighting the need for research into novel means of treatment and/or prevention of gonococcal disease [8] . In 2017 , the WHO placed N . gonorrhoeae on its watch list as a high priority pathogen for which new treatment strategies are needed . No effective vaccine for N . gonorrhoeae currently exists , and infection by the gonococcus does not confer any protective immunity against subsequent infections [9 , 10] . High-frequency phase and antigenic variation in N . gonorrhoeae result in a bacterial surface that is constantly variable , with certain structures changing at rates up to 10−2 cells in a single population [11] . The net result of this variation is that the pathogen evades both the host’s natural adaptive immunity and presents a limited number of promising targets for vaccine development [12] . Identification of these targets is paramount . A promising set of surface structure targets are the highly-conserved TonB-dependent transporters ( TdTs ) , which play a vital role in acquisition of nutrients for the gonococcus [13] . The TdTs are expressed across the genus Neisseria and show limited sequence variation . These outer membrane proteins consist of a β-barrel domain that is occluded by a globular plug , and feature extracellular loops that interact with nearby ligands . Upon binding the correct ligand , transport of specific cargo ( in this context , nutrients ) is stimulated by the TonB protein . TonB , which is situated in the inner membrane in complex with two other proteins , ExbB and ExbD , utilizes the proton motive force to energize passage of cargo though the β-barrel by modulating conformational change in the plug domain [14 , 15] . Once the cargo has reached the periplasm , it is taken across the cytoplasmic membrane by a dedicated ABC transport system . N . gonorrhoeae produces eight known TdTs , and those that have been characterized play a key role in acquisition of transition metals such as iron and zinc [13] . Neisserial TdTs have been demonstrated to interact with host-derived proteins including transferrin , lactoferrin , and hemoglobin for iron uptake [16] , and more recent studies have revealed the S100 protein Calprotectin as a zinc-binding TdT ligand . Stork et al . showed that the meningococcal protein CbpA allows utilization of Calprotectin as a zinc source [17] , and our lab recently demonstrated that the gonococcal homologue of this protein , called TdfH , is also capable of binding human Calprotectin and stripping it of zinc , which is then accumulated within the gonococcus [18] . An overview of these TdTs and their accessory proteins and known ligands is shown in Fig 1 . The process of metal piracy is implicated as a critical virulence factor for N . gonorrhoeae , as a human male infection model demonstrated that mutant gonococci incapable of utilizing iron from transferrin and lactoferrin were incapable of infection [19] , and TdfH production allows the pathogen to survive in Neutrophil Extracellular Traps ( NETs ) , which are highly enriched for Calprotectin , in vitro [18] . Gonococcal circumvention of killing by NETs is particularly nefarious , as N . gonorrhoeae specifically elicits a robust neutrophil response during infection [20 , 21] , thus effectively tricking the host into bringing a vital nutrient directly to the invading pathogen . Considered together , the TdTs discussed are part of the arsenal deployed by N . gonorrhoeae to overcome nutritional immunity [16] . Nutritional immunity refers to the host strategy of sequestering essential nutrients in order to restrict their availability to invading pathogens and therefore handicap their growth and infection potential . This phenomenon has been described in detail for iron , zinc , and manganese [22–27] . For bacteria , approximately 6% of proteins require zinc as either a key structural or catalytic component . Of these 6% , approximately 80% are enzymatic in nature , and zinc structural sites such as zinc fingers are common [28] , making zinc a necessity for bacterial survival . The human host has evolved nutritional immunity mechanisms specific for zinc sequestration . The previously mentioned protein Calprotectin binds to zinc with high affinity , and accounts for over 40% of the cytosolic protein in neutrophils [29] . Although this protein has proven incapable of inhibiting growth of N . gonorrhoeae [18] , it has demonstrated innate immune functions against other pathogens including Escherichia coli , Staphylococcus aureus , and Candida albicans [30–36] due to its ability to chelate zinc and manganese . Calprotectin is a member of the S100 calcium binding protein family , of which there are currently 24 identified members divided according to their primary location of function at the cellular level: intracellular only , extracellular only , or both [37] . They are differentially expressed according to tissue type . The S100s are EF-hand proteins whose primary role in vertebrates is modulation of calcium homeostasis , though they participate in other processes including inflammation , differentiation , apoptosis , and regulation of polymorphonuclear cells [37] . S100 proteins are obligate dimers and also form higher order oligomers , and are able to bind transition metals via sites at the dimer interface including zinc , manganese , copper , nickel and iron [24 , 38 , 39] . As such , several S100 proteins , in addition to Calprotectin , have demonstrated suppressive effects on bacterial growth through sequestration of these metals . S100A7 , also called Psoriasin due to its upregulation in psoriatic lesions [40 , 41] , has demonstrated zinc-mediated antimicrobial activity against S . aureus , Pseudomonas aeruginosa , and E . coli [42–47] . S100A12 ( Calgranulin C ) has demonstrated similar effects against several bacteria and parasites [42 , 48–50] . These findings highlight the importance of zinc at the host-pathogen interface and emphasize the need for further investigation into pathogen strategies to circumvent host nutrient depravation . Herein , we describe the conservation , regulation , and phenotypic characterization of another TdT produced by N . gonorrhoeae: TdfJ . TdfJ has been described as having differential responses to the presence of iron and zinc [18] , and both TdfJ and its meningococcal homologue , ZnuD , have demonstrated a contribution to growth of Neisseria in zinc-deplete conditions [51] . Furthermore , ZnuD directly binds to zinc in vitro [52] . In the current study , we demonstrate that gonococcal TdfJ shows additive repression by zinc and induction by iron . Furthermore , we show that wild-type N . gonorrhoeae is capable of utilizing zinc bound to S100A7 and S100A12 as a sole zinc source , and that utilization of S100A7 depends on the function of TdfJ , TonB , and the associated ABC transporter ZnuABC [53] . We demonstrate that S100A7 binds directly to both gonococcal and recombinant TdfJ in whole-cell solid-phase binding assays , and show via inductively coupled plasma optical emission spectrometry ( ICP-OES ) that the interaction between these two proteins allows N . gonorrhoeae to accumulate zinc internally . Finally , we demonstrate that TdfJ’s interaction with S100A7 is restricted to the human version of the protein , and that growth support by S100A7 depends on its molecular nature as a zinc chelator . This report marks the first time that S100A7 has been posited to be bound and directly utilized as a zinc source by an invading pathogen .
In order to assess TdfJ as a vaccine candidate , we evaluated the predicted amino acid sequence identity among the TdfJ proteins or their homologues in Neisseria genomes available in NCBI databases , and found that the protein is highly identical across all queried isolates . To demonstrate this , we performed multiple alignment of 50 of these sequences in Geneious ( Biomatters , Ltd . ) and found that the proteins shared 96 . 2% pairwise identity . Furthermore , 82 . 9% of amino acid residues in the proteins were identical across all sequences . It should be noted that a few sequences selected contain a six-residue stretch ( MRREAK ) at the amino terminus , as there is some database inconsistency as to which of two close-proximity methionines is the true start of the protein . For the purposes of alignment , these residues were ignored , but all six are identical in the sequences which include them . We also generated a consensus sequence from those queried and submitted it to DTU Bioinformatics NetSurfP-2 . 0 ( http://www . cbs . dtu . dk/services/NetSurfP/ ) for domain prediction , which identified putative β strands that constitute the protein’s transmembrane domains . Using the consensus sequence and predicted β barrel , we generated a topology prediction for TdfJ using TOPO2 from the University of California at San Francisco ( http://www . sacs . ucsf . edu/cgi-bin/open-topo2 . py ) . The resulting model was adapted to show the conserved and variable residues of TdfJ within the 2D topology diagram ( Fig 2 ) . The meningococcal homologue of TdfJ , ZnuD , has been previously crystallized and shows hallmark β barrel and globular plug domains characteristic of the TonB-dependent transporters [52] . Although gonococcal TdfJ has not yet been crystallized , based on these data we predict it to be virtually identical in structure to ZnuD , which has received considerable attention as a potential vaccine candidate for N . meningitidis [51 , 54] . For these reasons we sought to further investigate TdfJ and its potential contributions to the advancement of gonococcal vaccine development . We next identified the conditions under which TdfJ was maximally produced in N . gonorrhoeae wild-type strain FA19 [55] . We previously reported that strain FA1090 shows decreased TdfJ production in the presence of zinc and increased production in the presence of iron [18] , but the additive effects of these two metals in strain FA19 were not assessed . We performed western analysis of whole-cell lysates prepared from strain FA19 grown in Chelex-treated chemically defined media ( CDM ) supplemented with zinc , iron , and/or the high affinity zinc chelator N , N , N′ , N′-tetrakis- ( 2-pyridinylmethyl ) -1 , 2-ethanediamine ( TPEN ) at the concentrations indicated . We found that levels of TdfJ were decreased in the presence of zinc and increased in zinc-deplete conditions ( Fig 3A ) . TdfJ production was almost nonexistent when zinc was present and iron absent , which agrees with the observed phenotype for FA1090 [18] . When both zinc-deplete and iron-replete conditions were established , we observed an additive effect of their respective regulation inputs . Equal sample loading was verified by Ponceau stain of the protein blot . We then performed densitometry analysis on N = 3 blots and verified that zinc-restricted bacteria produce significantly more TdfJ than those grown in zinc-replete conditions , and that when zinc is scarce , TdfJ production is significantly higher when iron is present than when it is absent ( Fig 3B ) . These results established for us a set of conditions that are optimal for TdfJ production , and these were kept consistent in subsequent experiments . Considering the regulation of TdfJ by zinc , we hypothesized that TdfJ contributes to zinc acquisition by the gonococcus , and that the zinc-bearing ligand for TdfJ belongs to the S100 family of proteins . To test this hypothesis , we assayed the ability of wild-type strain FA19 to grow in the presence of S100 proteins that are reported to bind zinc . For these studies the dimeric S100 proteins were loaded to ~25% saturation with zinc in zinc-deplete conditions . Strikingly , we found that S100A7 and S100A12 , which have antimicrobial activity against other pathogens [42] , were able to support growth of the gonococcus as a sole zinc source in a manner similar to that observed in the presence of ZnSO4 alone ( Fig 4 ) . When no zinc source was provided , the gonococci ceased to grow after approximately 2 hours . We hypothesize that the bacteria’s internal zinc stores could sustain it for roughly one doubling before no longer being sufficient . These data imply that N . gonorrhoeae is able to overcome host nutritional immunity by directly co-opting host zinc-sequestering proteins S100A7 and S100A12 , similar to Calprotectin as we previously observed [18] . To elucidate the contribution of the Tdfs in gonococcal utilization of zinc-binding S100 proteins , we first constructed a mutant strain in the FA19 background that was incapable of producing ZnuA , the periplasmic binding portion of the ABC transport system for zinc [53] . This mutant , MCV951 , was unable to grow when presented with S100A7 or S100A12 as a sole zinc source and grew only poorly when supplemented with free ZnSO4 ( Fig 5A ) . This supports the hypothesis that ZnuABC participates in zinc uptake , and is also in line with previous observations that gonococci defective for this ABC transport system show a severe growth defect due to ZnuABC’s role in managing oxidative stress . Gonococcal ZnuABC has elsewhere been given the name MntABC due to its ability to bind and transport manganese [56–58] . With the understanding that znuA mutant gonococci are considerably hindered in their growth capabilities , we conducted endpoint viable counts of all samples in this growth assay to confirm that bacteria were able to survive when presented with a useable zinc source . These experiments indicated that at the 6-hour timepoint , the MCV951 strain was still viable when grown in the presence of free zinc ( Fig 5B ) , which presumably entered the cells in small amounts via passive diffusion . The first result that distinguished between S100A7 and S100A12 came in their respective abilities to support growth of an isogenic tonB mutant , MCV650 [59] ( Fig 5C ) . While S100A12 supported growth in a manner similar to that of free ZnSO4 and was not impacted by the tonB mutation , samples containing S100A7 grew no better than those without zinc . The inability of the gonococcus to utilize S100A7 in the absence of either ZnuA or TonB suggests that the interaction between pathogen and ligand may be mediated by one of the Tdfs . It is important to note that MCV650 cannot use the preferred iron source in our assay , which is iron-saturated human transferrin , as TonB is required for this process [60] . Instead , these samples were provided with iron in the form of free Fe ( NO3 ) 3 , which is not utilized as efficiently by the gonococcus . This may explain the overall poor growth and unusual shape of the growth curves for MCV650 . To ensure that the iron source present did not have any effect on zinc-dependent growth , growth experiments were performed with both Fe ( NO3 ) 3 and human transferrin . Overall growth was lower for samples containing Fe ( NO3 ) 3 , but all trends were recapitulated in both sets of samples . Considering the fact that utilization of S100A7 depends on function of the TonB protein , we analyzed whether its presence altered the expression of TdfJ , as this would be the expected outcome for a zinc-sequestering protein affecting a zinc-responsive gene . To test this , we grew strain FA19 in CDM supplemented with Fe ( NO3 ) 3 and equal amounts of either TPEN or apo-S100A7 to induce zinc stress . Western analysis of these samples indicated that zinc stress imposed by S100A7 results in TdfJ protein levels that are indistinguishable from those induced by TPEN presence ( Fig 6 ) . Collectively , these data suggest that TdfJ may be associated with S100A7 utilization . Since S100A7 growth support depended on ZnuA and TonB and adding S100A7 to cultures induced expression of TdfJ , we next sought to determine whether TdfJ contributed to use of S100A7 as a zinc source in the gonococcus . We grew a gonococcal mutant , strain MCV928 [61] , which is incapable of producing TdfJ , in zinc-depleted conditions containing S100A7 and assessed growth over 6 hours . In the absence of TdfJ , S100A7 was completely unable to support the growth of N . gonorrhoeae as a zinc source ( Fig 7A ) . Indeed , these samples were statistically indistinguishable from those containing no zinc . S100A12 fully supports growth of the tdfJ mutant strain , MCV928 , indicating that its use as a zinc source is unrelated to TdfJ . To confirm that TdfJ was indeed responsible for the observed phenotype , we generated a tdfJ-complemented strain of MCV928 , named MCV957 , which was inducible by addition of isopropyl β-D-1 thiogalactopyranoside ( IPTG ) . MCV957 was grown as described for MCV928 with and without IPTG . The induced sample of MCV957 completely recovered the growth phenotype in the presence of S100A7 as observed in the wild-type , while the uninduced sample remained indistinguishable from growth with no zinc ( Fig 7B ) . These data in conjunction with that observed for znuA and tonB mutants suggest that the gonococcus uses the TdT TdfJ , followed by ZnuABC transporter in the inner membrane , to acquire zinc from S100A7 and overcome host-mediated zinc sequestration . To examine whether TdfJ bound directly to S100A7 for bacterial zinc acquisition , we grew strains FA19 , MCV928 , and MCV957 with and without IPTG in CDM treated with TPEN and Fe ( NO3 ) 3 . Bacteria from cultures of a standardized density were then applied to a nitrocellulose membrane . This allowed whole-cells with an intact outer membrane to present surface proteins in their native configuration . These membranes were blocked and subsequently probed with horseradish peroxidase ( HRP ) -labeled S100A7 . Only FA19 and the induced MCV957 showed detectable binding of S100A7–HRP ( Fig 8 ) . These results demonstrate that not only is wild-type N . gonorrhoeae capable of binding directly to S100A7 , but that TdfJ is necessary for this interaction . Importantly , we recapitulated the binding of S100A7 in E . coli expressing recombinant TdfJ on its surface , showing that TdfJ expression is sufficient to mediate interaction with S100A7 . We conclude that gonococcal TdfJ is necessary and sufficient to enable binding to S100A7 . Having demonstrated that S100A7 both binds to TdfJ and supports growth as a zinc source , we next ascertained whether this pathway led to accumulation of zinc within N . gonorrhoeae . We grew strains FA19 , MCV928 , and MCV957 with and without IPTG in zinc-restricted medium in the presence of partially zinc-saturated S100A7 before quantifying the amount of zinc assimilation by using inductively coupled plasma optical emission spectrometry ( ICP-OES ) . Emitted zinc ions were detected at 213 . 857 nm and then their concentrations were determined by comparison to a standard curve generated from serial dilutions of a 10 μg/mL trace metal standard ( Inorganic Ventures ) . These concentrations were then standardized to reflect μg zinc per mg cellular protein ( Fig 9 ) . Strain FA19 internalized significantly more zinc from S100A7 than was detected for MCV928 , indicating TdfJ is necessary for this process . IPTG-induced MCV957 similarly showed significantly more zinc assimilation than both MCV928 and uninduced MCV957 , which agrees with our previous experiments that showed complementation of tdfJ recovers both gonococcal binding of and growth support by S100A7 . These data demonstrate that gonococcal TdfJ interacts with S100A7 in a manner that facilitates zinc internalization by the pathogen . N . gonorrhoeae is an exclusive human pathogen , and as such many interactions are specific for the human host [62] . We set out to determine whether gonococcal binding to and utilization of S100A7 shared this characteristic . The mouse version of S100A7 ( mS100A7 , Abbexa ) was loaded with zinc at the same saturation as used for the experiments conducted with human S100A7 and presented to wild-type FA19 cells as a sole zinc source in otherwise zinc-depleted media . mS100A7 was completely unable to support growth of gonococci , demonstrating optical densities even lower than those samples given no zinc source ( Fig 10A ) . As mS100A7 , like the human version , sequesters zinc , it is likely that this further diminished growth phenotype is due to additional , effective zinc chelation by mS100A7 during the assay as there is no mechanism present for the gonococcus to circumvent this . In addition to growth restriction , we tested the ability of gonococci and recombinant E . coli to physically bind mS100A7 by performing competition assays . FA19 , MCV928 , and MCV957 with and without IPTG , or E . coli expressing tdfJ or an empty vector were applied to nitrocellulose in standardized amounts before blocking and probing with S100A7-HRP . Simultaneously with the ligand , we added 10-fold molar excess of either mS100A7 or unlabeled human S100A7 as competitor . As before , only those cultures presenting TdfJ on the surface generated any signal from S100A7-HRP , and only samples treated with human competitor demonstrated signal reduction; mS100A7 did not compete for binding of gonococcal TdfJ ( Fig 10B ) . Likewise , when unlabeled S100A12 was included at 10-fold molar excess to S100A7-HRP , it was similarly unable to compete for binding and this resulted in no signal reduction ( Fig 10C ) . These data are consistent with the conclusion that the TdfJ-S100A7 interaction , like other gonococcal surface structure-host ligand interactions , is specific to the human protein , emphasizing the nature of N . gonorrhoeae as an obligate human pathogen . Moreover , they support the conclusion that TdfJ recognizes S100A7 specifically , instead of simply having affinity for the human S100s in general . Lastly , we were interested to see if zinc sequestered by S100A7 , as opposed to unchelated zinc or other transition metals which are freely available in the media , is specifically what allows growth support of the gonococcus in zinc-limited conditions . To test this , we grew strain FA19 in zinc-depleted CDM supplemented with an H87N+H91N double mutant S100A7 ( Zn KO S100A7 ) , which is unable to bind zinc . The zinc affinity of Zn KO S100A7 was investigated by isothermal titration calorimetry , which verified that it is devoid of zinc binding activity , whereas the zinc affinity of the wild-type S100A7 is in the nM range ( S1 Fig ) . Furthermore , bacterial growth inhibition assays [35] showed that this mutant is much less effective than the wild type protein at suppressing bacterial growth , as a by-product of its inability to sequester metals . Prior to growth assays , Zn KO S100A7 was mixed with ZnSO4 for sufficient time to allow zinc loading as for the wild-type protein , before being dialyzed against buffer containing Chelex-100 to remove unbound metals . As a control , wild-type S100A7 was prepared in an identical manner and included in the assay for comparison . When presented to gonococci in zinc-deplete conditions , Zn KO S100A7 did not support bacterial growth , and was statistically indistinguishable from samples treated with no zinc , while samples grown with wild-type S100A7 retained their previously-observed growth phenotypes ( Fig 11 ) . From these data we conclude that the ability of S100A7 to chelate zinc is essential for its ability to support growth of the gonococcus in a TdfJ-dependent manner .
Nutritional immunity , the sequestration of essential nutrients by hosts to hamper invading pathogens , and the strategies deployed by bacteria to overcome this defense , has become a prevalent theme in the evolving host-pathogen struggle . Iron , zinc , manganese , and other transition metals are key nutrients for bacterial survival and thus infection [25 , 26] . N . gonorrhoeae is particularly capable of overcoming nutritional immunity using non-traditional mechanisms . Unlike many other pathogens , N . gonorrhoeae does not produce any siderophores and therefore does not directly scavenge free iron from its environment . Instead , it utilizes an arsenal of TonB-dependent transporters that bind directly to host nutritional immunity factors including transferrin , lactoferrin , and hemoglobin and strip them of their iron cargo , effectively co-opting them for support of infection [13] . More recently , it has become clear that this phenomenon is not restricted to only iron , as both the gonococcus and meningococcus can use other TdTs to acquire zinc by a similar strategy [17 , 18 , 51] . Considering the high level of structural and functional conservation of the gonococcal TdTs , we hypothesized that the uncharacterized TdTs likewise play an important role in the ability of N . gonorrhoeae to survive and grow in the context of human nutritional immunity factors . Critically , recent studies have shown these transporters to be promising targets for vaccine development [63 , 64] . The S100 family of EF-hand calcium binding proteins play several essential roles in vertebrates , including sequestration of transition metals to starve invading bacteria of key nutrients [42] . Calprotectin , S100A12 , and S100A7 have been shown to exert suppressive activity against numerous pathogens , including E . coli , S . aureus , P . aeruginosa , Shigella flexneri , Helicobacter pylori , and C . albicans [40–47] . This report and our previous work [18] demonstrate that N . gonorrhoeae is able to overcome nutritional immunity by utilizing these otherwise antimicrobial proteins as zinc sources . Other pathogens including Aspergillus fumigatus , Salmonella enterica serovar Typhimurium , and Acinetobacter baumannii have shown the ability to circumvent S100-mediated zinc restriction by employing their own zinc acquisition systems [34 , 65] . The high-affinity zinc uptake system ZnuABC , an inner-membrane ABC transporter , has been a consistent factor present in Gram-negative bacteria that employ these acquisition systems . N . gonorrhoeae is no exception to this phenomenon , as S100A12 and S100A7 utilization explicitly depends on the function of this ABC transporter . Until recently , however , the mechanism of zinc passage through the outer membrane in N . gonorrhoeae was unknown . Jean et al [18] showed that N . gonorrhoeae utilizes TdfH for binding Calprotectin and consequent acquisition of zinc . Moreover , the meningococcal TdfJ homologue , ZnuD , has demonstrated binding of extracellular zinc [52] , and both ZnuD and TdfJ are regulated by zinc via the regulator Zur [66] , which is consistent with the expected phenotype of zinc importers . Gonococcal TdfH and meningococcal ZnuD have been shown to contribute to neisserial growth in zinc-deplete conditions [17 , 18 , 51] . For these reasons , we sought to evaluate S100A12 and S100A7 as potential ligands for other TdTs , specifically TdfJ . Our data show that growth support by S100A7 not only requires ZnuABC , but growth is also abrogated in the absence of TonB , suggesting the participation of one of the TdTs in its utilization . Indeed , S100A7 can only serve as a sole zinc source when N . gonorrhoeae produces a functional TdfJ . In vitro , this interaction , like the other TdT-mediated interactions , allows the gonococcus to overcome metal sequestration and grow effectively . Furthermore , we found in the current study that gonococci grown in the presence of S100A7 are enriched for internal zinc , which depends on TdfJ . Finally , we sought to clarify whether zinc was truly the nutritional cargo of S100A7 responsible for this interaction , and not some other adventitious metal present in the protein or media . A His-Asn double mutant S100A7 , with substantially reduced zinc affinity , was defective in growth support under zinc-depleted conditions , suggesting that zinc presence on S100A7 is indeed required for growth support . After establishing that S100A7 supports gonococcal growth in a TdfJ-dependent manner , we sought to establish whether these two proteins directly bound to each other , as is the case for the other characterized gonococcal TdTs and their ligands . When grown in conditions ideal for TdfJ production , wild-type N . gonorrhoeae and induced tdfJ-complemented strains were able to directly bind S100A7 , while mutant and uninduced strains not capable of producing TdfJ demonstrated no binding , suggesting a direct protein-protein interaction . Moreover , the growth conditions used are also ideal for production of the related zinc transporter TdfH , so this protein was present on the outer membrane as well . The lack of S100A7 binding to tdfJ mutant strains that still express a functional TdfH suggests that this binding interaction is indeed specific for TdfJ . We considered the possibility that inactivating the tdfJ gene , which encodes a membrane-embedded protein , may have generated unexpected , unintended alterations to the outer membrane as a whole and thus potentially confound binding experiments . To address this , we probed recombinant E . coli expressing either gonococcal TdfJ or containing an empty vector and found that TdfJ presence alone is sufficient for S100A7 binding , thus confirming their interaction , and aligning with previously described binding experiments between TdfH and Calprotectin [18] . As an obligate human pathogen , N . gonorrhoeae utilizes many virulence factors that are restricted to the human host [62] . We demonstrated in the current study that both gonococcal and recombinant TdfJ bind only to the human version of S100A7 , and do not interact with the mouse version . While mouse S100A7 shares only 34% sequence identity with its human counterpart , its expression patterns , structure , and function are similar in both mice and humans [67 , 68] . When present at 10-fold molar excess , mS100A7 shows no ability to compete for binding when human S100A7 is present . We showed also that when presented to the gonococcus as a zinc source , mS100A7 is unable to support gonococcal growth , and indeed seems to directly hinder growth . As noted in the methods section , mS100A7 showed detectable amounts of zinc already present upon reconstitution of the commercial protein . This means that our own addition of zinc probably exceeded our target of 25% saturation , but we do not view this as a detriment to the growth assays . Because the hypothetically more zinc-rich protein still failed to support gonococcal growth , it strengthens our conclusion that the gonococcus cannot use mouse S100A7 as a zinc source . Our finding that TdfJ is both induced by iron and repressed by zinc agrees with previous studies , and here we showed that these two regulators have additive effects on gene expression . When considered independently , downregulation by zinc had a slightly more pronounced effect than induction by iron , which is consistent with the expected phenotype of a zinc transporter . It is not expected that TPEN presence played any role in unintended chelation of iron from samples where both were present . Among the gonococcal Tdfs , only TdfJ is induced by iron; TdfH is not regulated by iron [18] , and two other proteins TdfF and TdfG are in fact iron repressed [59 , 69] . Despite the apparent regulation of TdfJ by iron , our experiments revealed no clear functional relationship between the two , so the reason for this coordinate regulation is left to speculation . One possible explanation is that TdfJ is the preferred mediator of zinc uptake for N . gonorrhoeae when iron is replete; the tdfJ gene is found across all of genus Neisseria and its protein products are highly conserved . Unlike TdfH , TdfJ is able to bind directly to free zinc , which is then internalized [52] . Furthermore , these observations are substantiated by key regulatory motifs in the N . gonorrhoeae genome . Pawlik et al [66] identified the sequence of a putative Zur binding motif ( Zur box ) for meningococci , and we found , via pattern location software ( http://www . cmbl . uga . edu/software/patloc . html ) , that a 100% match for this motif ( TGTTATATAATAACA ) is located within the promoter region of tdfJ . We used the same software to search for putative Fur boxes upstream of tdfJ and none were identified within 1 . 5 kilobases from the start of the gene . This agrees with the observation that iron presence enhanced TdfJ production rather than repressing it , as would be expected for the typical function of Fur . Paradoxically , previous reports have shown that the Fur protein binds within the promoter region of tdfJ , but the precise binding site was not mapped [70] . Therefore , at this time the mechanism of iron regulation of tdfJ is unresolved , but has been observed to occur at the transcriptional level [71] . TdfH and TdfF production is limited to pathogenic Neisseria but not commensal species [72] , and TdfG is restricted almost exclusively to N . gonorrhoeae [69] . Moreover , Tdfs G and F have as yet not demonstrated any zinc-related phenotype . In this report , we define a novel interaction between a gonococcal TdT ( TdfJ ) and the human zinc-binding protein S100A7 , wherein TdfJ on the gonococcal surface directly binds S100A7 and utilizes if for zinc internalization , thus overcoming one type of host-mediated nutrient restriction . This interaction , limited to the human host , may provide a clear selective advantage to N . gonorrhoeae in the context of infection , especially at the mucosal epithelium , a biologically relevant niche for the gonococcus where S100A7 is enriched [43 , 44] . The S100A15 protein is highly similar to S100A7 and has also demonstrated metal-sequestering antimicrobial effects [73] , so it is possible that in these or other host tissues , it may function alongside or in concert with S100A7 , but its relationship to N . gonorrhoeae and TdfJ was not explored in the current study . We also show that another zinc-binding protein , S100A12 , supports gonococcal growth as a sole zinc source by an as-yet-uncharacterized manner dependent upon ZnuABC . While the mechanism for S100A12 utilization is not yet clear , TonB-independent siderophore-iron uptake has been observed [61 , 74] . It is conceivable that ZnuABC contributes to gonococcal zinc uptake and infection in a manner independent of the TdTs , as is seen in , for example , pathogenic E . coli , Salmonella and Vibrio cholerae [75–77] . While it is not immediately apparent how the periplasmic ZnuA protein can extract zinc from extracellular S100A12 , previous reports have suggested that ZnuABC systems can help bacteria overcome zinc restriction by the S100 protein Calprotectin in the absence of a TonB-dependent transporter to shepherd the metal through the outer membrane [78] . In light of these findings , we suggest that TdfJ is a promising vaccine target for this important pathogen , and we also note the fact that ZnuD has received consideration for the same purpose in meningococcus [54] . TdfJ is exposed on the bacterial surface and is not subject to the high-frequency phase and antigenic variation that has disqualified so many other surface structures from consideration . TdfJ may contribute to in vivo survival of the gonococcus by utilization of S100A7 , which is highly upregulated in the epithelia . We also note that ZnuD has been shown to participate in interactions with epithelial cells [79] . Finally , TdfJ is ubiquitously produced across the Neisseria species , including the commensals from which gonococci and meningococci frequently acquire resistance factors , and which themselves may be opportunistic pathogens [80] . To summarize , we report a novel interaction between N . gonorrhoeae and its human host , which allows the gonococcus to overcome the innate immune mechanism of nutrient starvation . Considering the potential importance of this strategy for infection , alongside TdfJ’s presumed potential as a promising vaccine target , further characterization of the TdfJ-S100A7 interaction is underway in order to clarify the importance of TdTs as virulence factors for N . gonorrhoeae .
E . coli strains were cultured in Luria-Bertani ( LB ) medium supplemented with antibiotics at the following concentrations: 100 μg/mL for carbenicillin , 34 μg/mL for chloramphenicol , and 50 μg/mL for spectinomycin . Strains of N . gonorrhoeae were maintained on GC medium base ( Difco ) agar with Kellogg’s supplement I [81] and 12 μM Fe ( NO3 ) 3 ( GCB plates ) at 37°C at 5% CO2 . For the znuA mutant strain , MCV951 , this media and all others were supplemented with 5 mM D-mannitol ( Sigma ) [57 , 58] . For growth of N . gonorrhoeae in liquid culture , both rich and defined media were used , and zinc restriction was accomplished by addition of TPEN ( Sigma ) at the minimum amount needed to inhibit growth of the wild-type strain FA19 . Zinc-restricted growth in rich media was accomplished by inoculating GC broth treated with supplement I , 12 μM Fe ( NO3 ) 3 , and 10 μM TPEN with colonies grown on GCB plates . These cultures were grown at 37°C + 5% CO2 with shaking until log phase , at which point they were back diluted to the same optical density with the same medium and treated with 2 μM S100A7 loaded with 1 μM ZnSO4 and 1 mM IPTG , if needed . For growth in defined medium , colonies from GCB plates were used to inoculate chemically defined medium ( CDM ) that had been treated with Chelex-100 resin ( Bio-Rad ) . These cultures were grown as described until log phase before back dilution and treatment with 24 μM Fe ( NO3 ) 3 , 5 μM S100A7 , 10 μM ZnSO4 , and/or 1 or 5 μM TPEN for preparation of whole cell lysates ( WCLs ) , or treated with growth premix ( described below ) for zinc-dependent growth assays . For WCLs , growth was allowed to proceed for 6 hours as described before lysates of a standardized density were collected and subjected to SDS-PAGE and western analysis . S100A12 was produced from a pGEMEX expression vector provided by Professor Claus Heizmann and purified as described elsewhere [49] . S100A7 was produced from a pET-22b expression vector provided by Professor Joachim Grötzinger ( pET-22b-pso ) using the protocol described by Grötzinger and coworkers [82] . The Zn KO S100A7 ( H87N , H91N double mutant ) was generated by Q5 mutagenesis ( New England Biolabs ) . In brief , the pET-22b S100A7 H87N+H91N plasmid was used to transform BL21 ( DE3 ) E . coli following standard procedures . When the OD600 reached 0 . 6 , cells were induced at 37°C by the addition of 1 mM IPTG and allowed to grow 4 hours post-induction . Cells were harvested by centrifugation and were resuspended in lysis buffer ( 50 mM Tris pH 8 . 0 , 100 mM NaCl , 1 mM EDTA , 1 mM PMSF , 0 . 5% Triton X-100 ) . Cells were then sonicated and centrifuged for 20 minutes . The supernatant was filtered and loaded onto a SepharoseQ column ( GE ) . After loading , the column was washed with 3 CV buffer A ( 20mM Tris pH 8 . 0 ) and eluted with a gradient ( 10 CV , 0 -> 1 M ) to buffer B ( 20 mM Tris pH 8 . 0 , 1 M NaCl ) . Relevant fractions were pooled , concentrated , and loaded onto an S75 column . Protein was eluted with 1 CV S75 buffer ( 20 mM Tris pH 8 . 0 , 100 mM NaCl ) . Relevant fractions were pooled , flash frozen , and stored at -80°C . To confirm that no contaminating zinc was present in these preparations , ICP-MS experiments were performed on WT and mutant S100A7 produced for this study , which showed that WT proteins had less than 0 . 1 molar equivalents of Zn , while Zn KO S100A7 had less than 0 . 01 molar equivalents . Mouse S100A7 was purchased as lyophilized protein from Abbexa and was free from buffer or chelating agents upon receipt . Prior to use in experiments , the protein was reconstituted in buffer consisting of 20 mM Tris pH 8 . 0 , 100 mM NaCl , 20 mM β-Mercaptoethanol , and 1 mM CaCl2 . ICP-MS experiments were also performed on this protein , which revealed 0 . 4 molar equivalents of zinc already present prior to our own zinc loading . Comparable amounts of nickel were also detected in these preps , likely due to the use of Ni-NTA during protein purification . The affinity of wild-type and Zn KO S100A7 for zinc was determined by isothermal titration calorimetry ( S1 Fig ) as described elsewhere [83] . Human transferrin ( Sigma ) was dissolved in a mixture of 40 mM Tris , 150 mM NaCl , and 10 mM NaHCO3 at pH 8 . 4 ( initial buffer ) before being incubated with FeCl2 to result in ~30% Fe saturation . After incubation , this solution was dialyzed against excess 40 mM Tris , 150 mM NaCl , and 20 mM NaHCO3 at pH 7 . 4 ( dialysis buffer ) to remove unbound iron . Bovine apo-transferrin ( Sigma ) was dissolved in initial buffer and not treated with any metal before dialysis , such that it could sequester any residual iron in the final mix . S100 proteins were maintained in their own unique buffers after being purified as described . For zinc loading , the dimeric S100 proteins were incubated with ZnSO4 at a 2:1 molar ratio ( dimer:zinc ) to accomplish ~25% zinc loading . These ingredients plus TPEN and phosphate buffered saline , pH 7 . 4 ( PBS ) were combined into a concentrated growth “premix” which was used to restrict N . gonorrhoeae to defined sources of iron and zinc for growth in microtiter dishes . When diluted by liquid culture , final concentrations in the premix were as follows: 7 . 5 μM 30%-Fe human transferrin , 3 μM bovine apo-transferrin , 5 μM 25%-Zn S100 protein , and 1 μM TPEN . For a positive zinc control , TPEN was omitted and S100 proteins were replaced with 5 μM ZnSO4 , and for a negative control all zinc sources were omitted . To accommodate the tonB mutant strain , MCV650 , which is unable to utilize human transferrin as an iron source [60] , both human and bovine transferrin were omitted from the recipe and replaced by a final concentration of 3 μM Fe ( NO3 ) 3 . All primers used in this study were produced by New England Biolabs and can be found in Table 1 . All strains and plasmids utilized in this study are summarized in Table 2 . All restriction endonucleases were acquired from New England Biolabs . For construction of the znuA mutant strain ( MCV951 ) , primers oVCU865 and oVCU866 were used to amplify a region of the znuA gene from chromosomal DNA isolated from strain FA19 . The resulting PCR product was purified and ligated into the EcoRI site of pVCU403 [84] via the In-Fusion cloning method ( Clontech ) . This ligation mixture was used to transform TOP10 ( Invitrogen ) E . coli , and transformants were selected on 100 μg/mL carbenicillin and confirmed by PCR to generate pVCU550 . To disrupt the znuA gene , an Ω cassette ( SpcR StrR ) was ligated into the BmgB1 site of the znuA gene from pVCU550 using T4 DNA ligase . This ligation was used to transform TOP10 E . coli and transformants were selected on 50 μg/mL spectinomycin and confirmed by PCR . The resulting plasmid , pVCU551 , was linearized with SspI and used to transform a piliated polulation of FA19 , creating strain MCV951 , which was confirmed by PCR . Recovery of these transformants required GCB plates supplemented with 25 μM each of Zn and Mn plus 5 mM D-mannitol , in addition to selection on 50 μg/mL spectinomycin . To create an IPTG-inducible tdfJ complement , primers oVCU967 and oVCU968 were used to amplify the full tdfJ gene from FA19 , which was cloned via In-Fusion into pVCU234 [85] that had been linearized with XmaI and XhoI and used to transform TOP10 E . coli . pVCU234 , a modified version of pKH37 [86] inserts into an ectopic location in the gonococcal chromosome between the aspC and lctP loci . Transformants were selected on 34 μg/mL chloramphenicol and confirmed by PCR and sequencing . This plasmid , pVCU554 , was linearized with PciI and used to transform piliated MCV928 , and transformants were selected on 1 μg/mL chloramphenicol . The resulting strain , MCV957 , was confirmed by PCR . Whole-cell lysates of gonococci were harvested by pelleting cultures of a standardized optical density ( 100 Klett units in 1 mL culture ) and resuspending cells in 2X Laemmli solubilizing buffer before storage at -20°C . Immediately preceding use , samples were thawed , mixed with 5% β-mercaptoethanol , and boiled for 5 minutes . Protein samples were separated on a 7 . 5% polyacrylamide gel before transfer to nitrocellulose . Blots were stained with Ponceau S to verify equal protein sample loading . To detect TdfJ , blots were blocked in 5% ( w/v ) nonfat dry milk dissolved in low-salt Tris-buffered saline ( TBS , 150 mM NaCl ) + . 05% Tween 20 . To generate polyclonal antibodies recognizing TdfJ , peptides from predicted extracellular loops 2 and 6 were synthesized by New England Peptide , Inc . , conjugated to keyhole limpet hemocyanin , and used to immunize guinea pigs . [87] For western blots , this serum was diluted in blocker and used to probe blots for 2 hours at room temperature . Following washes with low-salt TBS , secondary antibodies conjugated to horseradish peroxidase ( Invitrogen ) were diluted in blocker and applied to blots for 1 hour at room temperature . Blots were then washed and developed using SuperSignal West Dura Extended Duration Substrate ( Thermo ) and imaged on a Bio-Rad ChemiDoc Gel Imaging System . As these are novel α-TdfJ antibodies , a full-sized western blot demonstrating the specificity of the antibodies is shown in S2 Fig . Gonococcal strains were grown in zinc-restricted CDM , as described , until log phase , at which point cultures were diluted to a standard optical density of OD600 = . 02 and added to the wells of microplates pre-treated with growth premixes prepared as described and 1 mM IPTG , if needed . OD600 measurements were recorded using a Molecular Devices Vmax Microplate Reader at 0 , 2 , 4 , and 6-hour time points . For strain MCV951 , samples at the 6-hour mark were collected and serially diluted in sterile PBS before being spotted onto GCB plates supplemented with 5 mM D-mannitol . These plates were incubated for 24 hours at 37°C at 5% CO2 before colonies were enumerated and CFU/mL calculated . S100A7 was conjugated to HRP using the ab102890 ( Abcam ) conjugation kit according to the manufacturer’s instructions . Protein concentration was then verified by bicinchoninic acid ( BCA ) assay . Gonococcal strains were grown in zinc-restricted CDM as described for 4 hours before cultures standardized to an optical density equivalent to 10 Klett units in 1 mL were applied to nitrocellulose using a dot blot apparatus ( Bio-Rad ) . Membranes were blocked in 5% ( w/v ) nonfat dry milk dissolved in low-salt TBS before incubation for 1 hour with 0 . 2 μM S100A7-HRP diluted in blocker . Membranes were washed with low-salt TBS and signal developed with a Metal Enhanced DAB Substrate Kit ( Thermo ) . For recombinant E . coli , OverExpress C41 ( Lucigen ) strains expressing tdfJ ( pVCU313 ) or containing an empty pET-11a vector were grown as described until OD600 = ~ . 5 before induction with . 02% arabinose or 1 mM IPTG , respectively , which was allowed to proceed for 4 hours . Cultures were then standardized to the same densities used for gonococci and added to nitrocellulose for S100A7 probing in an identical manner . For competition assays , N . gonorrhoeae or E . coli were applied to nitrocellulose and probed with S100A7-HRP as described , with simultaneous addition of 10-fold molar excess of either mouse S100A7 or unlabeled human S100A7 or S100A12 , and signal developed as described above . Gonococcal cultures were grown as described in Zn-restricted rich medium supplemented with S100A7 and 1 mM IPTG where needed . After 6 hours , cultures were harvested by centrifugation at 3750 RPM for 10 minutes . The pellet was washed with 5 mL cold , Chelex-treated PBS containing 1 mM EDTA . Cultures were then centrifuged and washed again for a total of two washes . This sample was added to a metal-free conical tube with 1 mL set aside for protein quantification via BCA assay . Remaining sample was centrifuged again as described and the pellet was stored overnight at -20°C . After overnight incubation , cell pellets were dissolved in a minimal volume of trace metal grade ( 67–70% ) nitric acid and heated to 95°C for 2 hours , then cooled at room temperature overnight . The resulting samples were diluted to 5% nitric acid by addition of Chelex-treated dH2O and submitted for ICP-OES analysis using an Agilent 5110 ICP-OES instrument to detect trace metals compared to a standard curve ranging from 5 to 4000 ppb generated from serial dilutions of a 10 μg/mL multi-element trace metal standard from Inorganic Ventures . 10 . 1371/journal . ppat . 1007937 . t003 Accession No . Organism Source WP_003706713 . 1 Neisseria gonorrhoeae NCBI WP_003697511 . 1 Neisseria gonorrhoeae NCBI WP_003692255 . 1 Neisseria gonorrhoeae NCBI AAW89864 . 2 Neisseria gonorrhoeae NCBI WP_014580101 . 1 Neisseria gonorrhoeae NCBI WP_020996886 . 1 Neisseria gonorrhoeae NCBI CBX21481 . 1 Neisseria lactamica NCBI WP_115118822 . 1 Neisseria lactamica NCBI WP_002221107 . 1 Neisseria meningitidis NCBI ADY95807 . 1 Neisseria meningitidis NCBI WP_045750123 . 1 Neisseria lactamica NCBI ADO31914 . 1 Neisseria meningitidis NCBI CAM10219 . 1 Neisseria meningitidis NCBI EEZ75392 . 1 Neisseria lactamica NCBI WP_118816248 . 1 Neisseria lactamica NCBI WP_118815216 . 1 Neisseria lactamica NCBI WP_029609171 . 1 Neisseria lactamica NCBI WP_012221561 . 1 Neisseria meningitidis NCBI WP_002244095 . 1 Multispecies Neisseriaceae NCBI WP_021437386 . 1 Multispecies Neisseriaceae NCBI WP_101065272 . 1 Multispecies Neisseriaceae NCBI WP_002248033 . 1 Neisseria meningitidis NCBI WP_107970711 . 1 Neisseria elongata NCBI WP_096109175 . 1 Neisseria lactamica NCBI WP_014574069 . 1 Neisseria meningitidis NCBI WP_107854563 . 1 Neisseria elongata NCBI WP_107919736 . 1 Neisseria elongata NCBI WP_114921675 . 1 Neisseria elongata NCBI WP_036469946 . 1 Neisseria lactamica NCBI WP_049248486 . 1 Neisseria elongata NCBI WP_118898890 . 1 Neisseria lactamica NCBI WP_118780086 . 1 Neisseria lactamica NCBI WP_003774512 . 1 Neisseria elongata NCBI WP_002227407 . 1 Neisseria meningitidis NCBI CBN87515 . 1 Neisseria lactamica NCBI WP_107992588 . 1 Neisseria elongata NCBI WP_114935204 . 1 Neisseria lactamica NCBI WP_118819066 . 1 Neisseria lactamica NCBI WP_118778219 . 1 Neisseria lactamica NCBI WP_115177755 . 1 Neisseria lactamica NCBI CAM08367 . 1 Neisseria meningitidis NCBI WP_118810395 . 1 Neisseria lactamica NCBI WP_118783660 . 1 Neisseria lactamica NCBI WP_118786886 . 1 Neisseria lactamica NCBI WP_042508227 . 1 Neisseria lactamica NCBI WP_118782813 . 1 Neisseria lactamica NCBI WP_118846593 . 1 Neisseria lactamica NCBI WP_074898586 . 1 Neisseria elongata NCBI WP_107884967 . 1 Neisseria elongata NCBI WP_002246893 . 1 Neisseria meningitidis NCBI
|
Neisseria gonorrhoeae causes the common sexually-transmitted infection gonorrhea . This bacteria’s ability to rapidly acquire antibiotic resistance factors , coupled with the lack of any effective vaccine to prevent infection , has resulted in a disease that poses a global threat and may become untreatable . A group of gonococcal outer membrane proteins called TonB-dependent transporters ( TdTs ) have been implicated as promising vaccine targets , as they are well-conserved and expressed across gonococcal isolates and play a vital role in allowing the pathogen to acquire essential nutrients during infection of the human host . Here , we describe the conservation and regulation of TdfJ , a gonococcal TdT whose homologues are ubiquitous in the genus Neisseria . We show that TdfJ binds directly to S100A7 , a host protein that normally sequesters zinc away from invading pathogens . This novel interaction enables N . gonorrhoeae to strip S100A7 of chelated zinc for its own use . Furthermore , we show that another zinc-binding human protein , S100A12 , is also utilized by N . gonorrhoeae as a zinc source by an as-yet-unidentified mechanism . This study provides insight into the functional role of the TdTs during infection and highlights these proteins as promising targets for both vaccine and antimicrobial therapy development .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
[
"medicine",
"and",
"health",
"sciences",
"pathology",
"and",
"laboratory",
"medicine",
"chemical",
"compounds",
"pathogens",
"immunology",
"microbiology",
"neisseria",
"gonorrhoeae",
"esters",
"membrane",
"proteins",
"mutation",
"outer",
"membrane",
"proteins",
"cellular",
"structures",
"and",
"organelles",
"bacteria",
"bacterial",
"pathogens",
"nitrocellulose",
"mutant",
"strains",
"neisseria",
"neisseria",
"meningitidis",
"medical",
"microbiology",
"zinc",
"microbial",
"pathogens",
"chemistry",
"cell",
"membranes",
"chemical",
"elements",
"cell",
"biology",
"immunity",
"genetics",
"biology",
"and",
"life",
"sciences",
"physical",
"sciences",
"organisms"
] |
2019
|
The novel interaction between Neisseria gonorrhoeae TdfJ and human S100A7 allows gonococci to subvert host zinc restriction
|
The recent emergence of leptospirosis has been linked to many environmental drivers of disease transmission . Accurate epidemiological data are lacking because of under-diagnosis , poor laboratory capacity , and inadequate surveillance . Predictive risk maps have been produced for many diseases to identify high-risk areas for infection and guide allocation of public health resources , and are particularly useful where disease surveillance is poor . To date , no predictive risk maps have been produced for leptospirosis . The objectives of this study were to estimate leptospirosis seroprevalence at geographic locations based on environmental factors , produce a predictive disease risk map for American Samoa , and assess the accuracy of the maps in predicting infection risk . Data on seroprevalence and risk factors were obtained from a recent study of leptospirosis in American Samoa . Data on environmental variables were obtained from local sources , and included rainfall , altitude , vegetation , soil type , and location of backyard piggeries . Multivariable logistic regression was performed to investigate associations between seropositivity and risk factors . Using the multivariable models , seroprevalence at geographic locations was predicted based on environmental variables . Goodness of fit of models was measured using area under the curve of the receiver operating characteristic , and the percentage of cases correctly classified as seropositive . Environmental predictors of seroprevalence included living below median altitude of a village , in agricultural areas , on clay soil , and higher density of piggeries above the house . Models had acceptable goodness of fit , and correctly classified ∼84% of cases . Environmental variables could be used to identify high-risk areas for leptospirosis . Environmental monitoring could potentially be a valuable strategy for leptospirosis control , and allow us to move from disease surveillance to environmental health hazard surveillance as a more cost-effective tool for directing public health interventions .
Leptospirosis is the most common bacterial zoonosis around the world [1] , and its emergence has been linked to many environmental and ecological drivers of disease transmission . Varying environmental health hazards operate in different settings , and include climate , flooding , land use , urbanisation , poor sanitation ( e . g . urban slums ) , international trade and travel , environmental degradation , and loss of biodiversity [2]–[11] . Accurate data on disease incidence and outbreaks are lacking in many parts of the world because of the combination of poor awareness of the disease , low clinical suspicion , varied clinical presentations leading to misdiagnosis , and the lack of laboratory facilities to confirm diagnoses [12] . Reported incidence of leptospirosis in the Pacific Islands is high compared to other parts of the world [13]–[16] , and outbreaks have been reported recently [17]–[19] . However , most Pacific Islands do not have accurate epidemiological data on leptospirosis , making it difficult to quantify the importance of risk factors or predict outbreaks . Environmental data , geographic information systems ( GIS ) , spatial statistical analysis , and predictive risk maps have been used for the investigation and management of a range of infectious diseases including schistosomiasis [20] , malaria [21]–[24] , trachoma [25] and Rift Valley fever [26] . These maps identify geographic areas with high disease prevalence and/or risk of outbreaks , and are useful for guiding allocation of scarce public health resources and interventions . Such maps are particularly useful where disease surveillance data are poor or lacking . To date , no predictive risk maps have been produced for leptospirosis . This study follows our reports on a seroprevelance study of leptospirosis in American Samoa in 2010 [27] , [28] . The overall seroprevalence was 15 . 5% for the five islands surveyed , and 16 . 2% on the main island of Tutuila where over 95% of the population lived . The three most common reactive serovars on Tutuila were L . interrogans serovars Hebdomadis , LT 751 , and LT 1163 , with seroprevalences of 10% , 4 . 3% , and 3 . 5% respectively . Significant risk factors for seropositivity included male gender , outdoor occupation , low income , lack of knowledge about leptospirosis , living below median altitude of the village , and high density of piggeries around the home [27] . The three predominant serovars differed in their geographic distribution [28] , and were associated with different risk factors [27] . This study further examined potential environmental health hazards for disease transmission using environmental data and geospatial analysis . The objectives of this study were to estimate leptospirosis seroprevalence at geographic locations based on environmental factors , produce a predictive disease risk map for American Samoa , and assess the accuracy of the maps in predicting infection risk . The results demonstrated that environmental health hazard surveillance could be a valuable strategy for identifying high-risk areas for disease transmission , and potentially be used as an adjunct or alternative to disease surveillance for targeting public health interventions for leptospirosis [29] .
Residuals of multivariable models were explored for spatial autocorrelation using semi-variograms . This was performed in the R statistical software package , version 2 . 9 . 0 ( The R Foundation for Statistical Computing ) , using the geoR package .
Four statistically significant clusters ( three seropositive and one seronegative ) were identified . When scanning all serovars , one seropositive cluster was identified in an area where over 50% of participants were seropositive . When scanning for individual serovars , two seropositive clusters were identified ( one each for LT 751 and LT 1163 ) , and a seronegative cluster was identified for LT 1163 in an area where none of the 290 participants tested positive for this serovar . Statistical details of the clusters are shown in Table 1 , and locations of the clusters are shown in Figures 2 and 3 . Statistically significant covariates on multivariable analyses and measures of goodness of fit for models A and B are shown in Table 2 . Four significant environmental risk factors were identified and included in Model A: ( i ) living below median altitude within a village , ( ii ) living on agricultural land , ( iii ) living on clay loam soils , and ( iv ) number of piggeries located within 250 m and above the house . Additionally , three individual-level risk factors were identified: ( i ) male gender , ( ii ) occupational risk ( outdoor workers and fish cleaners ) , and ( iii ) lack of knowledge about leptospirosis . Model B incorporated both environmental and individual-level risk factors . No significant residual spatial autocorrelation was found , suggesting that spatial clustering was largely explained by the covariates included in the models . Using the four subsets of the models for validation , the average AUC was 0 . 63 for Model A and 0 . 70 for Model B . An average of 84 . 05% and 83 . 11% of cases in the fourth subset were correctly classified in Model A and Model B respectively , indicating that model had acceptable predictive performance . The following seroprevalence prediction maps were generated: Based on Model A and the map in Figure 4 , the predicted seroprevalence was extracted for all houses on Tutuila to provide information on the proportion of the population exposed to different levels of risk . Figure 7 shows that based on environmental covariates alone , 58 . 3% of houses had a predicted seroprevalence of 10 to 20% , and 90 . 9% of houses had a predicted seroprevalence of 1 to 30% . A seroprevalence prediction chart was generated based on the four statistically significant environmental variables ( “number of piggeries within 250 m and above the house” , altitude , vegetation type , soil type ) . Figure 8 shows that individuals who have two or fewer piggeries within 250 m and above their home , live above the median altitude of their village , in urban built-up areas , and on clay soil have a predicted seroprevalence of 4%; whereas those who have more than six piggeries within 250 m and above their home , live below the median altitude of their village , in agricultural areas , and on non-clay soils have a predicted seroprevalence of 51 . 1% .
In American Samoa , seropositivity to leptospirosis was associated with environmental as well as individual-level factors . Significant household-level environmental hazards included those related to the natural environment ( altitude and soil type ) as well as anthropogenic activities ( agriculture and piggeries ) . Results of this study corroborate findings from other studies that the household environment is an important determinant of leptospirosis infection risk [8] , [37]–[39] . Living below the median altitude of a village was associated with seropositivity , and was likely to be related to greater exposure to run-off from higher parts of the village , carrying pathogens including leptospires . Lower altitudes would also be more prone to flooding . Living on clay soil was associated with a lower risk of infection . Clay soils absorb water poorly and would allow rain to run off rapidly . In contrast , clay loams and other soils absorb and hold water ( and leptospires ) for longer periods of time , and could thereby increase the exposure risk for those who lived in these areas . Soil temperature and acidity could also potentially affect leptospire survival in the environment [40] , but there were insufficient data on soil characteristics to explore this explanation . Living in agricultural areas was associated with seropositivity , and was likely to be related to farming activities and exposure to animals . The large number of pigs and backyard piggeries in AS have previously been implicated in leptospirosis transmission [41] . In 2010 , there were approximately 430 backyard piggeries housing 3500 pigs ( ASEPA , pers . comm ) , and efforts have been made to control and regulate their numbers and design [33] . In this study , piggery density was measured by counting the number of piggeries located within 250 m of houses and at a higher altitude . Similar analysis using greater buffer distances of 350 m , 500 m , 750 m , and 1000 m also produced statistically significantly results , but the strength of association decreased with increasing buffer distances . Larger buffers often included other valleys and watersheds , and were therefore deemed inappropriate . Analysis with buffer distances of 100 m did not produce any significant results , probably because there were few piggeries located within 100 m of houses . A buffer distance of 250 m was chosen for analysis because it provided the best prediction of seropositivity . The number of piggeries located at a lower altitude than houses was not associated with seropositivity for any of the above buffer distances , suggesting that drainage of refuse downhill from piggeries is an important source of infection . The association between piggeries and leptospirosis seropositivity was potentially epidemiological rather than causal , and the true source of infection could have been the rodents around piggeries rather than the pigs . Despite this , proper management of piggery waste should still reduce the risk of exposure for people living downhill from piggeries . Further studies involving the collection of samples from animals would be required to determine which animal species are the primary carriers of leptospiral serovars responsible for human infection . This study showed that both individual-level and environmental risk factors combined to determine the overall risk of human leptospirosis in American Samoa . Effective public health interventions would therefore need to include strategies to reduce individual risk as well as environmental exposures [27] . Strategies to reduce exposure risk in individuals include improvements in occupational health and safety ( e . g . by wearing protective clothing ) and community knowledge about leptospirosis . At the community level , proper management of piggeries and building piggeries further away from homes could reduce exposure to piggery waste . Altitude and soil type were associated with infection risk and as discussed above , are likely to be related to the risk of flooding . In the Pacific , flooding is predicted to occur more frequently with global climate change as a result of more intense rainfall and cyclones . It would therefore be important to reduce flooding risk by improving drainage and keeping drains clear of garbage and debris . Communities should also be advised to avoid floodwaters . In contrast to many other studies , rainfall and flooding risk were not statistically significantly associated with seropositivity in this study . American Samoa is one of the wettest inhabited places in the world with an average annual rainfall of more than 3000 m , and it was therefore possible that all areas of the island were at high risk in this environment . The flood risk map available was produced to identify areas susceptible to severe damage for insurance purposes , and was possibly a poor indicator of overall flooding risk and exposure [27] . The questionnaire used in the seroprevalence study explored many household-level environmental exposures known to be associated with leptospirosis infection , but none were found to be associated with overall seropositivity [27] . However , some of the exposures were widespread , making it difficult to determine their effect on infection risk . For example , 65% of participants reported sighting rats or mice at home and 75% reported bats around the home . Water and sanitation services were also very similar for all participants . Ninety-six % had piped water , 90% had an indoor toilet , 89% had an indoor shower , 87% had garbage collection services , and only one person did not have a sewage system ( mains sewage or septic tank ) at home . Furthermore , owning animals was not associated with seropositivity possibly because people in American Samoa were often exposed to animals even though they were not the owners . In this study , 67% of participants reported owning dogs but almost the entire population would be exposed to the large numbers of unrestrained dogs responsible for one of the highest reported incidence of dog bites in the world [42] . Similarly owning pigs was not associated with seropositivity , but geospatial analysis described in this study showed that piggeries around the home were associated with infection risk . In this study , geo-referenced data were more useful than questionnaire data for identifying environmental risk factors . The maps in Figures 2 and 3 show that there were geographic areas with significant clusters of seropositive and seronegative cases . Clusters varied between serovars , suggesting different environmental and ecological drivers of disease transmission . In a recent related paper that explored the ecological drivers of leptospiral serovar emergence in American Samoa , serovar LT 1163 was found to be completely absent in the more highly populated parts of the island [28] . Figure 3 shows that serovar LT 1163 was only found in the less populated parts of the island , and the seronegative cluster corresponds to the most densely populated area . In this study of predictive risk mapping , all serovars were combined in the analysis and there was no significant association between population density and overall seroprevalence . Serovar-specific predictive risk maps could be produced if future studies collected larger datasets , and might be more accurate than maps that include all serovars . The map in Figure 4 shows the variation in predicted seroprevalence based on environmental health hazards alone . Figures 5 and 6 show the predicted seroprevalence for the highest and lowest risk individuals living in different parts of the island , and that infection risk could be significantly increased by individual-level factors . The statistically significant positive cluster for all serovars on SaTScan ( Figure 2 ) corresponds accurately to an area of predicted high seroprevalence on the risk maps in Figures 4 to 6 . This area was situated on a steep hill , where there were large numbers of piggeries located behind and above houses . Figure 7 shows that the majority of houses in Tutuila were located in areas with a predicted seroprevalence of 10 to 20% , and was consistent with the observed population seroprevalence of 15 . 5% in our study in 2010 . The number of houses in different risk categories was determined by the predicted seroprevalence as well as house density at each location , and provided an indication of overall disease burden . The seroprevalence prediction chart in Figure 8 shows the combined effects of the four environmental factors in determining infection risk , and provided a more accurate estimate of seroprevalence than individual risk factors alone , or a simple count of multiple risk factors . The limitations of the seroprevalence study have been previously discussed [27] . The cross-sectional study design did not allow assessment of variations in disease incidence or risk factors over time . If available , long-term incidence data could provide additional information on the effect of seasons , rainfall , and natural disasters . There were also limitations to the use of serological tests for leptospirosis , and isolates of leptospires would be required to confirm the study findings . There were likely to be other environmental risk factors that were not explored in this study , and further research would be required to identify these hazards . The potential role that other animal species play in disease transmission should also be investigated . The accuracy of the models and risk maps were limited by the accuracy of environmental data , and changes in environmental variables over time . Prediction models and risk maps would need to be updated as environmental conditions change , and could be refined as additional information and data become available . This study showed that it was possible to identify high-risk areas for leptospirosis based on environmental variables alone , and this approach could be useful for stratifying geographic locations according to risk , particularly when disease surveillance data are lacking . Environmental health hazard surveillance could therefore be a useful strategy for identifying high-risk locations for disease transmission , and should be considered as an alternative or complement to disease surveillance , which would generally be more costly , complex and difficult to manage . This strategy could potentially provide valuable information for targeting public health interventions and optimising resource allocation , particularly in areas with limited financial and public health resources , such as the Pacific Islands . This study demonstrated the value of GIS and disease mapping for investigating the spatial distribution of leptospirosis infection , identifying geographic and environmental risk factors , and enhancing our understanding of disease transmission dynamics . The ability to accurately assess , predict , and map environmental drivers of disease transmission could also allow us to move from disease surveillance to environmental health hazard surveillance as a more cost-effective tool for directing public health interventions . Although this study was specific to the cultural and environmental conditions in American Samoa , the principles might also be applicable to other endemic areas for leptospirosis , and the findings might be pertinent to other Pacific Islands with similar climate , ecosystems , animal reservoirs , lifestyle and culture .
|
Leptospirosis is the most common bacterial infection transmitted from animals to humans . Infected animals excrete the bacteria in their urine , and humans can become infected through contact with animals or a contaminated environment such as water and soil . Environmental factors are important in determining the risk of human infection , and differ between ecological settings . The wide range of risk factors include high rainfall and flooding; poor sanitation and hygiene; urbanisation and overcrowding; contact with animals ( including rodents , livestock , pets , and wildlife ) ; outdoor recreation and ecotourism; and environmental degradation . Predictive risk maps have been produced for many infectious diseases to identify high-risk areas for transmission and guide allocation of public health resources . Maps are particularly useful where disease surveillance and epidemiological data are poor . The objectives of this study were to estimate leptospirosis seroprevalence at geographic locations based on environmental factors , produce a predictive disease risk map for American Samoa , and assess the accuracy of the maps in predicting infection risk . This study demonstrated the value of geographic information systems and disease mapping for identifying environmental risk factors for leptospirosis , and enhancing our understanding of disease transmission . Similar principles could be used to investigate the epidemiology of leptospirosis in other areas .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"public",
"health",
"and",
"epidemiology",
"infectious",
"disease",
"epidemiology",
"spatial",
"epidemiology",
"bacterial",
"diseases",
"neglected",
"tropical",
"diseases",
"infectious",
"disease",
"control",
"spatial",
"analysis",
"human",
"geography",
"disease",
"mapping",
"geography",
"infectious",
"diseases",
"disease",
"ecology",
"environmental",
"epidemiology",
"epidemiology",
"infectious",
"disease",
"modeling",
"public",
"health",
"leptospirosis",
"environmental",
"health",
"earth",
"sciences"
] |
2012
|
Leptospirosis in American Samoa – Estimating and Mapping Risk Using Environmental Data
|
Transketolase ( TKT ) is part of the non-oxidative branch of the pentose phosphate pathway ( PPP ) . Here we describe the impact of removing this enzyme from the pathogenic protozoan Leishmania mexicana . Whereas the deletion had no obvious effect on cultured promastigote forms of the parasite , the Δtkt cells were not virulent in mice . Δtkt promastigotes were more susceptible to oxidative stress and various leishmanicidal drugs than wild-type , and metabolomics analysis revealed profound changes to metabolism in these cells . In addition to changes consistent with those directly related to the role of TKT in the PPP , central carbon metabolism was substantially decreased , the cells consumed significantly less glucose , flux through glycolysis diminished , and production of the main end products of metabolism was decreased . Only minor changes in RNA abundance from genes encoding enzymes in central carbon metabolism , however , were detected although fructose-1 , 6-bisphosphate aldolase activity was decreased two-fold in the knock-out cell line . We also showed that the dual localisation of TKT between cytosol and glycosomes is determined by the C-terminus of the enzyme and by engineering different variants of the enzyme we could alter its sub-cellular localisation . However , no effect on the overall flux of glucose was noted irrespective of whether the enzyme was found uniquely in either compartment , or in both .
Leishmania are parasitic protozoa that cause a wide spectrum of diseases including a self-healing cutaneous form , a disfiguring mucocutaneous form and severe , often fatal , visceral leishmaniasis . The individual clinical manifestation and severity of the disease depends on the causative Leishmania species , immuno-susceptibility of the patient and various additional factors [1] . Leishmania are transmitted by sandflies , and they alternate in their life-cycle between two major stages , the promastigote—insect stage—and amastigote—mammalian stage . The different stages vary significantly in their morphology and biochemistry , each of them adapted to their specific environment . Better understanding of the parasites’ biology is required with focus on new drug targets and treatment development . As disruption of essential biochemical pathways has instant detrimental effects on parasites , understanding metabolism offers a means to enhance our capability to intervene against the leishmaniases . The central carbon metabolism of Leishmania mexicana has recently been described using metabolomics approaches by Saunders et al . [2 , 3] . Promastigote culture forms use glucose as a major carbon source when available , fuelling glycolysis and subsequently the tricarboxylic acid ( TCA ) cycle [2] . Aspartate was also shown to fuel the TCA cycle although other amino acids were not directly assessed in that study [2] . Fatty acids have also been proposed as possible carbon sources for L . mexicana [4] , but they are apparently utilised only in amastigotes , while promastigotes use exogenous fatty acids in lipid metabolism but not for energy generation [3] . Comparing metabolism in promastigotes and amastigotes led to the conclusion that metabolism in the latter stage is ‘stringent’ as glucose and other substrates were consumed at a comparatively lower rate and metabolic end products were generated in correspondingly reduced quantities [3 , 5] . The full extent of variation between the two major life stages remains unclear , however clear differences are evident [3 , 6–11] . One aspect of metabolism in trypanosomatid protozoa to have received particular attention is its unusual compartmentalisation with several pathways either totally , or partially , present within peroxisome-like organelles termed glycosomes , named because of the presence of many enzymes of the glycolytic pathway in this organelle . Other pathways , including the pentose phosphate pathway , fatty acid β-oxidation , nucleotide and ether lipid biosynthesis also localise to glycosomes [12] , and understanding the role of these organelles in providing metabolic homeostasis is of considerable interest [13 , 14] . The pentose phosphate pathway ( PPP ) uses glucose 6-phosphate ( G6P ) to generate NADPH ( Fig 1 ) , the primary source of electrons in reductive biosynthesis and defence against oxidative stress , and also ribose 5-phosphate used in nucleotide metabolism [15] . The oxidative branch of the PPP comprises two dehydrogenases and 6-phosphogluconolactonase , and produces two molecules of NADPH and ribulose 5-phosphate ( Ru5P ) . The following steps of the non-oxidative PPP consist of isomerisation reactions or transfer of carbons . Ru5P is converted by ribose-5-phosphate isomerase or ribulose-5-phosphate epimerase into ribose 5-phosphate ( R5P ) or xylulose 5-phosphate ( X5P ) , respectively . These and other sugar phosphates , ranging from three to nine carbons in size , are used by transketolase ( TKT ) and transaldolase ( TAL ) which freely transfer two and three carbon units between sugar substrates . Some of their products ( fructose 6-phosphate ( F6P ) , glyceraldehyde 3-phosphate ( GA3P ) ) can be fed back into glycolysis . Both glucose-6-phosphate dehydrogenase ( G6PDH ) and 6-phosphogluconate dehydrogenase ( 6PGDH ) were shown to be essential in bloodstream , but not procyclic T . brucei [13 , 16] . A G6PDH knock-out cell line in promastigote L . major suffered from severe growth defects and increased sensitivity to oxidative stress and antimonials [17] . The non-oxidative branch of the PPP has been subject to less study . Ribose-5-isomerase seems to be necessary for propagation of L . infantum and even parasites lacking just a single allele of the gene showed diminished infectivity in macrophages and in mice [18] . The discovery that TKT-like enzymes play an important role in a range of cancers [19–21] has reinvigorated interest in this enzyme . TKT transfers two carbon keto units between different sugar phosphates , ranging from three to seven carbons in size . TKT is not expressed in bloodstream form T . brucei although transaldolase ( TAL ) , an enzyme classically considered to act in concert with TKT to shuffle carbons between sugars , is [22–24] . Knock-out of TKT in procyclic T . brucei had no effect on cellular phenotype , although substantial changes in various metabolites were detected by metabolomics analysis [22] . The crystal structure of TKT from L . mexicana has been resolved at 2 . 2 Å [25] and subcellular localisation studies revealed that around 70% of the activity was associated with the cytosol , with the rest compartmentalised within glycosomes [25] . The physiological role of TKT in Leishmania was not studied and it was speculated that the subcellular localisation depended on the context of a C-terminal peroxisomal targeting sequence [25] . Here , we present a study of a L . mexicana TKT knock-out ( Δtkt ) cell line . We examined the effects of TKT deletion on promastigotes and amastigotes in culture , and on their ability to infect macrophages and establish infections in mice . The promastigote cell line , as analysed by both targeted and untargeted metabolomics , revealed substantial changes in central metabolism . Notably , Δtkt cells exhibited changes reminiscent of the ‘stringent metabolic response’ described previously in amastigotes [3] . RNAseq analysis was performed to derive insight into regulatory mechanisms allowing parasites to adapt to metabolic perturbation . In addition , subcellular localisation of TKT and its regulation was scrutinized . Finally , we showed that parasites lacking TKT could not establish a virulent infection in mice .
A TKT knock-out ( Δtkt ) cell line was constructed in L . mexicana by sequential replacement of both alleles of the gene with antibiotic resistance markers . PCR analysis revealed the gene was cleanly replaced by antibiotic resistance markers ( S1 Fig ) . Promastigote cells did not suffer from any growth defect ( Fig 2A ) . The Δtkt cell line was complemented with a copy of the TKT gene integrated into a ribosomal locus of the genome ( Δtkt + TKT ) and re-expression of TKT confirmed by Western blot ( Fig 2A inset ) . This line was also unaffected for growth rate or morphology . The Δtkt cells were , however , significantly more sensitive to oxidative stress . Reactive oxygen species ( ROS ) can be directly detected with a fluorescent probe dichlorofluorescin diacetate ( DCFDA ) [26] . This probe showed that ROS were slightly but significantly higher in Δtkt than in WT ( p = 0 . 004; Fig 3 ) . After challenge with 200 μM Sb3+ for 8 hours , the difference was much more prominent with WT maintaining the same ROS levels , whereas Δtkt showed a three fold increase in ROS levels as measured by DCFDA ( p = 1 x 10−6 ) . Surprisingly , the phenotype was even stronger in Δtkt + TKT ( five fold increase , p = 8 x 10−8 ) . When assayed with glucose oxidase added to culture medium as a constitutive source of H2O2 , Δtkt were around twice as sensitive as WT ( p = 0 . 01 ) while Δtkt + TKT re-expressor cells were partly rescued ( 1 . 5-fold decrease , p = 0 . 02 ) . Another commonly used oxidative stress inductant , methylene blue , had much weaker differential effect on the cell lines ( Table 1 ) , although little is understood about its mode or site of action and additional effects . Sensitivity to other leishmanicidal compounds was also tested and Δtkt cells were more sensitive to all of those tested , albeit not significantly so , for paromomycin and antimonyl tartrate ( Table 1 ) . The addback Δtkt + TKT cell line did not recover to WT levels either in the DCFDA assay or with most of the drugs tested . Since most leishmanicidal drugs induce oxidative stress [26] , it is probable that this enhanced sensitivity in Δtkt relates to the increased sensitivity to such stress . We also transformed Δtkt promastigotes into axenic amastigotes and showed that transformation was possible but at significantly reduced efficiency when compared to WT amastigotes , and most importantly , the Δtkt cells did not multiply as an axenic culture ( S1 Fig ) . The Δtkt line was also less able to establish infection in THP-1 macrophages ( Fig 2B and 2C ) . Although initial infection was equal in all groups , significant increase was observed in WT ( 9 . 3 fold , p = 2 . 9 x 10−4 ) and Δtkt + TKT ( 5 . 5 fold , p = 0 . 0057 ) after 96 h , but no significant increase was observed in Δtkt ( Fig 2B ) . Macrophages infected with Δtkt cells harboured in average 1 . 5 parasites per macrophage from the beginning up to 4 days , but these numbers increased over time for both WT and Δtkt + TKT ( 3 . 7 and 2 . 8 , respectively; Fig 2C ) . To test the ability of Δtkt cells to establish an in vivo infection , BALB/c mice ( n = 2 , four and five mice per group ) were infected with WT , Δtkt , and Δtkt + TKT parasites and the progression of cutaneous leishmaniasis lesions was assessed over time . Whereas mice infected with both WT and Δtkt + TKT cells developed typical footpad lesions after a few weeks , Δtkt cells did not cause any obvious lesions even after 9 weeks ( Fig 2D ) . Δtkt parasites were recovered from the popliteal lymph nodes in small numbers of the infected animals after 9 weeks , but not after 20 weeks , although parasites were recovered from infections with WT and re-expressor cells in all cases . The data show that TKT is essential to L . mexicana in establishing mammalian infection . Despite there being no discernible change to growth of Δtkt promastigote L . mexicana , LC-MS and GC-MS metabolomic analyses revealed profound changes to the cellular metabolome . Major changes to metabolites of the PPP were found . Metabolites occurring upstream of the TKT reactions , such as 6-phosphogluconate ( 6PG ) and the pentose phosphates were significantly increased in abundance , whereas the product of TKT reaction , sedoheptulose 7-phosphate ( S7P ) was massively decreased ( Fig 4 , Table 2 ) . The pool of accumulated metabolites also directs flux into additional reactions which were not detected in WT . For example , pentose phosphates are converted into their corresponding pentose alcohols or pentose phosphate alcohols . Additionally , octulose 8-phosphate ( O8P ) is accumulated , which is produced by a reaction of a pentose phosphate with a fructose 6-phosphate ( F6P ) or S7P by transaldolase , as can be verified by the labelling pattern ( S2 Fig ) . In addition to changes in the PPP metabolites and related levels of the glycolytic intermediates also decreased . Glucose accumulates while glucose 6-phosphate ( G6P ) is slightly decreased . The subsequent metabolites of glycolysis then diminish progressively , phosphoenolpyruvate ( PEP ) being decreased about seven fold compared to WT . Pyruvate is less diminished than PEP since it can be produced from malate or alanine via alternative metabolic pathways . Interestingly , various predicted hexose oligomers ( C18H32O16 , C24H42O21 , C30H52O26 , C36H62O31 ) are massively decreased in Δtkt ( Table 2 ) . Most likely these all represent mannogen , the storage sugar polymer of Leishmania [27] . Other than these mannogen derivatives , levels of many metabolites that were perturbed in Δtkt cells returned to WT levels after TKT re-expression , or indicate a trend of rescue ( Table 2 ) . The decrease in abundance of glycolytic intermediates pointed to a downregulation of flux through glycolysis , in spite of TKT not playing a direct role in the pathway . Comparing glucose consumption in WT and Δtkt cells revealed the latter consumed significantly less glucose compared to WT , 3 . 9 +/-0 . 3 and 3 . 2 +/-0 . 3 nmol/min/108 cells ( p = 0 . 02 ) , respectively ( Fig 5A ) . Similarly , the production of major secreted high-energy metabolic end products was significantly decreased in Δtkt ( Fig 5B ) . Succinate , malate and alanine were all produced and accumulated in the spent media of WT cells over four days , whereas these metabolites either did not accumulate at all , or only to a much lower extent in Δtkt . Succinate levels increased 12 fold in spent medium from WT , but only 2 fold in Δtkt , malate 7 fold in WT and 4 fold in Δtkt and alanine 3 . 5 fold in WT whilst it decreased to 70% of starting levels in Δtkt . Hence , the Δtkt cell line both consumes less glucose and produces less end products of metabolism than WT cells confirming a general decrease in glucose catabolism . In spite of the fact that TKT is not part of the Embden-Meyerhof-Parnas glycolytic scheme , it does shunt carbon that has passed through the PPP back into glycolysis in concert with TAL . The Δtkt line should lose this ability . To assess what proportion of glucose passes via the PPP , we measured relative glucose flux through different routes using a method reported by Lee et al . [28] . The method involves feeding cells with 1 , 2-13C-glucose and then measuring the label in resultant three carbon containing derivatives ( pyruvate and alanine ) . Glucose metabolised via the PPP loses the carbon from position-1 ( cleaved by 6PGDH ) , hence the three carbon derivatives have only one carbon labelled , whereas if glucose is channelled into glycolysis , there will be either two or zero labelled carbons present in the three carbon products ( Fig 6 ) . The LC-MS analysis indicated that 14% of glucose enters the PPP in WT promastigote L . mexicana . Loss of this proportion of total carbon cannot account for the measured much higher loss of glycolytic flux , ruling out disruption of the PPP as a cause for decrease in glycolytic flux . An alternative explanation could be inhibition of PGI by 6PG , with a resultant block in glycolysis , as observed in yeast and Drosophila [29 , 30] . In this case , supplementation with fructose should rescue the phenotype ( because fructose can be phosphorylated directly into F6P and channelled into glycolysis after the PGI reaction ) [13] . To test this hypothesis , metabolomics analysis was performed with cells grown solely in the presence of glucose or fructose . However , fructose did not revert the phenotype and differences observed in the metabolome of Δtkt cells fed with glucose or fructose were minimal ( Fig 7A ) . The only metabolite which was changed towards WT level was mannogen ( represented by various hexose oligomers , Fig 7B ) . Transcriptomic analysis revealed that RNA levels for genes encoding the glycolytic enzymes were changed less than two fold , although transcripts for the enzymes of the lower part of glycolysis were slightly but statistically significantly decreased ( Fig 8 , S3 Table ) . We also measured specific activities of several enzymes from cell extracts of WT and Δtkt cells . Fructose-1 , 6-bisphosphate aldolase activity was two fold lower in Δtkt ( p = 0 . 0005; Table 3 ) , whereas no significant differences were measured in activities of G6PDH , 6PGDH , hexokinase , or PGI between the two cell lines . To learn more about the overall fate of glucose in WT and Δtkt cells , parasites were cultivated in medium containing 50% of glucose fully labelled ( U-13C-glucose ) and 50% unlabelled glucose . The labelling pattern observed in WT showed hexose phosphates containing anything between zero and six labelled carbons ( 33% 0C labelled , 11% 1C labelled , 10% 2C labelled , 19% 3C labelled , 7% 4C labelled , 5% 5C labelled , 15% 6C labelled ) consistent with the carbon shuffling role played by the non-oxidative PPP ( see Fig 1 ) resulting in production of F6P ( Fig 9A ) . In contrast , practically all of the hexose phosphates in Δtkt cells were either labelled at all carbons or none ( 59% 0C labelled , 36% 6C labelled ) confirming the key role played by TKT in carbon exchange . In Δtkt cells 10% of 6PG contained one to four labelled carbons , 30% five labelled carbons , whereas 8% had six carbons labelled and 52% had no labelling , whereas WT comprised 25% one to four labelled carbons , 4% five labelled carbons , 8% six labelled carbons and 62% unlabelled ( Fig 9A ) . The most plausible explanation for such an unusual pattern is that the high accumulation of Ru5P that accompanied the loss of TKT reverses the 6PGDH reaction , leading to production of 6PG from Ru5P while assimilating CO2 [31 , 32] . TCA cycle intermediates are of decreased overall abundance in Δtkt cells , and their labelling patterns differ markedly in the mutant when compared to WT . Whereas 50–60% of these metabolites are labelled with one through to all carbons in WT , over 90% of the total TCA cycle intermediates are unlabelled in Δtkt cells ( Fig 9B ) . Of the measured 2-oxoglutarate , over 54% is labelled at one to five carbons in WT , whereas only 2% of the metabolite carried any label in Δtkt cells . Similar patterns were detected for succinate , glutamate and pyruvate . PEP consists of 29% three carbon , 9% two carbon , and 10% one carbon ( 2 . 5% is natural labelling ) labelled in WT , whereas in the Δtkt line 28% is fully labelled and 72% unlabelled with no intermediate labelled-carbon states detected ( Fig 9B ) . These results suggest that the TCA cycle is slightly decreased in Δtkt , but , more importantly , it is fed by carbon sources other than glucose . An untargeted metabolomics analysis of spent media was performed over 4 days of cultivation to determine whether other metabolites present in medium were used at enhanced rates in Δtkt as alternative sources of energy and carbon . Surprisingly , none of the amino acids was depleted more from Δtkt spent medium than in WT ( except for small consumption of alanine in Δtkt , while it is produced in WT ) . Aspartate , glutamate and other amino acids were consumed , but either to the same extent in both cell lines or actually more in WT than in Δtkt ( Fig 10A , S3 Fig ) . RNAseq analysis provided interesting complementary information on amino acid metabolism . RNA from six genes encoding members of the amino acid transporter family was around two fold increased in Δtkt , whereas mRNA of one family member was five fold decreased ( S3 Table ) . Analysis of the intracellular metabolome of the two cell types indicates that eleven amino acids are of two fold or higher abundance in Δtkt cells ( Fig 10B ) . However , neither transcriptome data ( S3 Table ) , nor metabolome data ( S1 Table ) , pointed to enhanced utilisation of those amino acids , hence , an accumulation of amino acids appears not to be accompanied by an increase in their utilisation . There was no indication of enhanced utilisation of fatty acids nor any other nutrients by Δtkt over WT cells ( S1 and S3 Tables ) . Δtkt cells , therefore are able to grow as quickly and to similar density as WT but consume fewer nutrients and create fewer partially oxidised end products of metabolism too . The situation is analogous to the so-called “stringent” response displayed by amastigote cells that also appear to reduce their consumption of metabolites when compared to promastigotes [3 , 5] . Metabolomics analysis indicated that beyond changes to the metabolite levels that could be directly attributed to loss of TKT within the PPP , there were more general changes to metabolism , including diminished flux of glucose via glycolysis and a switch to a more stringent metabolism resembling that in amastigote forms of the parasites . To assess whether changes in the steady state levels of RNA could contribute to this switch a transcriptomic analysis of WT , Δtkt and Δtkt + TKT was performed . Compared to WT , 150 genes were upregulated two fold or more and 156 downregulated to the same extent in Δtkt ( p = 5 × 10−5 , S3 Table ) . Since glucose catabolism was generally diminished we noted changes in transcripts associated with those pathways . Transcripts from the three principal tandemly arrayed glucose transporters LmGT1-3 [33] were all less abundant ( 75% levels compared to WT , p = 5 x 10−5 ) . mRNA for a myo-inositol/proton symporter [34] was , by contrast , two fold upregulated . Changes of mRNA abundance for enzymes from glycolysis and the PPP are indicated in Fig 8 , but for the majority of them the change was less than two fold . Of the PPP enzymes , mRNA of R5P isomerase gene was of almost two fold increased abundance in mutants ( p = 5 x 10−5 ) , while mRNA for xylulose reductase was of two fold lower abundance ( p = 5 x 10−5 ) . Generally , we conclude that changes in RNA levels play little or no role in diminishing glucose use in Δtkt mutants . The LC-MS analysis indicated depletion of hexose oligomers in Δtkt , which were partly restored after supplementation with fructose ( Fig 7B ) . It is possible that these hexose oligomers are representatives of the poly-hexose mannogen which is a key metabolite in Leishmania [35 , 36] . We therefore , used HPTLC analysis which allows detection of all mannogen species within the cell . The result shown in Fig 7C indicated reduction of mannogen in Δtkt to around a half of the levels seen in WT ( p = 0 . 029 ) , and levels were partly restored in Δtkt + TKT ( 0 . 8 of WT , with no statistical difference p = 0 . 14 ) . The transcriptome data indicated three fold decrease in the enzyme mannose-1-phosphate guanylyltransferase ( EC 2 . 7 . 7 . 13 , p = 5 x 10−5 ) of the mannogen biosynthetic pathway ( Fig 11 ) , but it fails to recover WT levels in the Δtkt + TKT cells . TKT was previously shown to localise to both the cytosol and glycosomes in L . mexicana , with a majority of about 70% in the first compartment [25] . The C-terminus of TKT has a canonical PTS1 motif , SKM , but how this determines the dual localisation was unknown . The crystal structure of L . mexicana TKT had revealed the C-terminus to be unordered , prompting the suggestion that variability in this structure , perhaps induced by binding of regulators to the protein , could influence the positioning of the PTS and thus determine localisation [25] . We prepared a collection of episomal constructs with a GFP tag at the N-terminus of TKT and variants of the C-terminus of the protein either truncated at the C-terminus by 10 , 20 or 30 amino acids , or elongated by 10 or 20 amino acids . The glycosomal targeting sequence was preserved in all of them and only the preceding sequence was altered . When analysed by immunofluorescence microscopy , these cell lines showed different subcellular localisation of TKT . Most strikingly , the TKT truncated by 10 AA was present solely in glycosomes , as confirmed by overlap with a known glycosomal marker triosephosphate isomerase ( Fig 12 , S4C Fig ) . The proteins elongated by 10 and 20 amino acids also showed higher signal overlapping with glycosomes , but there was still a significant part of the protein present in the cytosol . The other proteins ( reduced by 20 AA or elongated by 30 AA ) showed localisation similar to WT TKT or else a totally cytosolic TKT ( from which the glycosomal targeting sequence ‘SKM’ was removed ) . The role of the C-terminal sequence in directing the protein is therefore proven , although how different proportions are targeted to different destinations remains unknown . Obtaining a solely glycosomal TKT allowed us to further compare cells expressing TKT exclusively in this compartment . We transfected the GFP-glycoTKT ( TKT minus 10 AA ) plasmid into Δtkt cells , and in parallel a plasmid encoding a purely cytosolic TKT , i . e . one from which the PTS-1 sequence was removed . Surprisingly , these two cell lines did not show any significant differences . The growth rate of promastigote cells was the same and they were similarly sensitive to oxidative stress ( S4 Fig ) . Furthermore , metabolomics analysis also revealed no major differences ( S5 Fig , S1 Table ) with metabolites of glycolysis and the PPP reaching the same levels , the only significant difference being observed in pentose 1 , 5-bisphosphate , which reached WT levels in Δtkt + cytoTKT , while dropped two fold in Δtkt + glycoTKT .
The PPP plays critical roles in NADPH production and generation of R5P for nucleotide metabolism in most organisms including parasitic trypanosomatids . A number of structural and pharmacological differences between enzymes of the pathway in trypanosomatids and their mammalian hosts has led to suggestions they may represent suitable drug targets [37 , 38] . Both G6PDH and 6PGDH have been shown to be essential in bloodstream T . brucei although dispensable in the procyclic stage [13 , 16] . G6PDH deletion also caused a strong defect in promastigote L . major growth , although effects in the amastigote stage have not been tested [17] . R5PI has been proposed as essential for L . infantum since its deletion from the genome was not possible [18] . TKT has recently emerged as a potential therapeutic target in cancer cells [19 , 21] where its role in protecting against oxidative stress has been proposed to be critical [20] . We show here that TKT is essential for L . mexicana virulence in mice , despite being dispensable in cultured promastigotes . TKT therefore offers a potential target for new drugs aimed at treating leishmaniasis , although there will be a time lag before suitable inhibitors are available for testing . Although , Δtkt cells do not have any growth defect in the promastigote stage cultivated in rich Homem medium , the cells do develop enhanced sensitivity to oxidative stress and a variety of drugs used in therapy of leishmaniasis . These observations may be linked as most leishmanicidal drugs create oxidative stresses that contribute to their mode of action [26] . Despite there being no discernible growth phenotype in promastigote forms , metabolomics revealed that cellular metabolism was drastically altered in the knock-out cell line . A large accumulation of pentose phosphates occurred , as expected , since ribulose 5-phosphate , ribose 5-phosphate and xylulose 5-phosphate all fuel the non-oxidative branch of the pathway initiated by TKT . Correlated to this increase was a startling appearance of numerous alcohol derivatives of the pentoses . Moreover , Ru5P was converted back to 6PG by the reverse action of 6PGDH , since a substantial proportion of 6PG with five labelled carbons was detected in our heavy labelling experiment ( with the unlabelled carbon fixed from CO2 ) . This reaction will also perturb the NADP/NADPH balance in cells , which could explain the increased sensitivity to oxidative stresses . The direct product of TKT , S7P also decreased drastically in the mutant cell line as expected . In addition to the alterations around the PPP itself , other metabolites involved in central carbon metabolism were also affected . An earlier study of carbon metabolism reported by Saunders and colleagues , revealed glucose to be the dominant carbon source with aspartate also entering the TCA cycle but other amino acids or fatty acids having little or no role [2] . Another study , however , indicated that utilisation of amino acids for mannogen biogenesis was highly dependent upon the presence or absence of glucose in the culture medium [39] . Following the distribution of carbons from labelled glucose here we confirmed that glucose is the main carbon source for the TCA cycle in WT parasites under standard culture conditions . Δtkt cells consume significantly less glucose than WT , but assessment of the composition of spent medium suggested that no individual metabolite replaces glucose as a predominant carbon and energy source in the Δtkt cell line . Aspartate , asparagine , glutamate and glutamine are all consumed substantially but only to the same or to a lesser extent in Δtkt cells compared to WT . A substantial amount of alanine is produced in WT , whereas it is partly consumed in Δtkt instead , providing a good example for the ‘stringent’ metabolism adaptations , where fewer resources are consumed and used more efficiently [3] . The Δtkt line did show increased levels of a number of amino acid gene transporter transcripts and also accumulated most amino acids , but no evidence for correspondingly higher levels of their catabolism was observed . However , the TCA cycle may be fuelled by a mixture of amino acids , in contrast to WT . Moreover , excreted end products of metabolism ( malate , succinate and fumarate ) are also less abundant in the Δtkt cells , and the mutant did not acidify the medium to the same extent as WT cells as evidenced by reduced colour change from red to yellow with the pH indicator in medium . The fact that the mutant line appears to consume less metabolic precursor substrates and also produces less secreted products is analogous to the ‘stringent metabolic response’ proposed for amastigote cells [3] , possibly as a response to living in nutrient-limiting conditions , but also possibly to reduce perturbations to host metabolism which might stimulate anti-pathogen defences . An alternative to describing amastigotes and the TKT mutant as having ‘stringent’ metabolism would be to label metabolism of cultured promastigotes as ‘profligate’ since they appear to use unnecessarily high level of substrate and excrete excesses of partially oxidised end products of metabolism . Whether loss of TKT and the associated metabolic changes specifically trigger a stringent response , or such a response is a general response to ‘stress’ associated with loss of a key enzyme has yet to be resolved ( it has been shown that reducing pH and increasing temperature also provoke a stringent response in promastigote Leishmania [5] ) . Interestingly , flux via glycolysis is downregulated in Δtkt , but not as a direct consequence of the missing flux from the PPP , nor due to inhibition of PGI by accumulated 6PG as was previously shown in Drosophila and yeast [29 , 30] . In both T . brucei [13] and in promastigote L . mexicana we rule out this feedback loop since fructose , which enters glycolysis beneath the PGI step does not rescue flux through the glycolytic pathway . The drop in metabolites DHAP , GA3P and beyond is consistent with inhibition of fructose-1 , 6-bisphosphate aldolase , the enzyme that converts F1 , 6bP to DHAP and GA3P . Specific activity of aldolase was therefore measured in Δtkt cellular extracts and shown to be only half that of WT , while PPP enzymes G6PDH and 6PGDH were of comparable activity . In both plants and humans F1 , 6bP aldolase is inhibited by R5P and 6PG [40–42] . Both metabolites rise substantially in the Δtkt mutants , and the crucial amino acid residues are conserved in the protein sequence ( S6 Fig ) , although whether there is similar inhibition of the leishmanial enzyme has not been tested . Inhibition of F1 , 6bP aldolase by accumulated PPP intermediates offers a plausible explanation for the observed decrease in glycolytic flux although direct evidence corroborating this is lacking . We found that mannogen levels were two-fold decreased in the TKT mutant , and restored in the re-expressor cells . RNA sequence analysis revealed a decrease in mRNA levels of mannose-1-phosphate guanylyltransferase ( MPGT ) which may be associated with the reduction and may indicate an important role for this enzyme in the overall pathway to mannogen synthesis , as suggested previously [43] . Moreover , the hexose oligomers that may be related to mannogen are partly restored after supplementation of Δtkt with fructose in the medium . In contrast , WT cells grown on fructose contain lower levels of larger sugar oligomers , which suggests a substrate specific regulation of the pathway , although more information is lacking regarding regulatory mechanisms in mannogen synthesis or catabolism . Further work is required in order to explain the differences observed here . By tracing the isotope distribution in three-carbon products derived from glucose labelled either in position-1 or in positions-1 and -2 we calculated that 14% of glucose flux is via the PPP in promastigote L . mexicana , similar to the 11% reported previously [44] based on measurements of incorporation of radiolabelled glucose into DNA . In other organisms , glucose flux via the PPP has been reported between 10% to 41% in T . cruzi [45 , 46] , 7% in healthy humans [47] , 5 . 7% in human hepatoma cells [28] , net flux being dependent upon cellular requirements . Comparing the labelling patterns of products of glucose metabolism in WT and Δtkt cells revealed profound differences . Without TKT , the extensive and rapid shuffling of carbons seen in WT disappears , confirming the key role that TKT plays in shuffling carbons between different sugar phosphates in the non-oxidative PPP [48] . The discovery that TKT is essential for long-term viability of amastigotes in mice indicates that the enzyme may be viewed as a possible drug target . As efforts to develop inhibitors of mammalian TKT are underway , a vein of small molecules to test for activity against the Leishmania enzyme may become available . Mannogen depletion may be responsible for loss of virulence since in Δtkt , mannogen levels are decreased and this polymer has previously been reported to be essential for amastigote survival [35] . Accordingly , in the Δtkt + TKT infectivity is restored , and mannogen levels recover . Contribution of other factors cannot be excluded , including defence against oxidative stress . Since the PPP is a major source of cellular NADPH , it is also possible that perturbing the pathway disrupts the cellular redox balance to a lethal extent . In addition to diminished overall production of NADPH in the PPP , the accumulation of ribulose 5-phosphate stimulates the 6PGDH reaction to run in reverse and consumption of this key redox metabolite will exacerbate the problem . Promastigote Δtkt cells produce around three fold more ROS than WT , but amastigotes are exposed to more stress than promastigotes and this defect may be more prominent . Moreover , NADPH is also necessary for reductive biosyntheses , for example of fatty acids and ergosterol [49 , 50] . Direct toxic roles for products accumulating due to loss of the TKT reaction , or ensuing steps in amastigotes cannot be excluded . For example , octulose 8-phosphate is a metabolite not previously described in Leishmania and its production is greatly increased in TKT defective cells , as is a range of other pentose sugars and their alcohol derivatives . Loss of other metabolites e . g . S7P might also play a role . We also addressed the question of the dual localisation of TKT where the same enzyme has a primary localisation within the cytosol but a minor part is also found in glycosomes , presumably due to the presence of a canonical C-terminal type-1 peroxisomal targeting tripeptide motif , SKM . Removal of the SKM motif led to all of the enzyme being found in the cytosol . To test whether the structurally disordered sequence preceding the PTS-1 motif might be involved in altering presentation of that sequence , we created cell lines expressing the protein with altered C-termini . When we added stretches of either 10 or 20 amino acids to the sequence prior to the SKM motif , the expressed protein was now found primarily in the glycosome . However , removing 10 amino acids , also led to a protein found primarily in the glycosomes , whilst removal of 20 or addition of 30 amino acids created a protein that was mainly cytosolic . The data are not compatible with the simple notion of a retractable C-terminus ( where it would be expected that longer versions would be constitutively glycosomal and shorter versions constitutively cytosolic based on the ability of the protein to bind to PEX5 in the cytosol ) hence the molecular mechanism of dual localisation remains uncertain . Irrespective of the mechanism determining dual localisation , metabolomics analysis revealed that the cellular metabolome of L . mexicana promastigotes was similar in cells expressing solely cytosolic or solely glycosomal versions of the enzyme and sensitivity to oxidative stress was also the same . These results are consistent with the semi-permeable nature of glycosomes whereby the distribution of most small metabolites is not affected by the presence of the glycosomal membrane [51] . However , these analyses were all performed in promastigote cells cultivated in rich medium and important roles associated with the enzyme’s subcellular localisation in amastigotes , or in other stages of the parasite in its natural life cycle are not known . In summary , we show that TKT is involved primarily in the shuffling of carbon atoms between different carbohydrates in Leishmania , and that this activity may contribute to mannogen biosynthesis . It appears to have a role in protecting promastigotes against oxidative stress . Loss of the enzyme stimulates a shift towards a reduced metabolic rate redolent of the ‘stringent’ response shown by amastigote forms of the parasite . The C-terminus of the enzyme determines its subcellular localisation , although a mechanism for how it is dually localised to glycosomes and cytosol is not known . In promastigotes the enzyme’s distribution does not influence overall metabolism of the cells . Most intriguingly , TKT knockout cells were not able to establish infection in mice , although cells re-expressing the enzyme were , indicating the TKT is essential to Leishmania and a possible target for chemotherapy .
All animal experiments were performed in accordance with the Animals ( Scientific Procedures ) Act 1986 and the University of Glasgow care and maintenance guidelines . All animal protocols and procedures were approved by The Home Office of the UK government and the University of Glasgow Ethics Committee under Project license PPL 60/4442 . Leishmania mexicana M379 cells were cultivated in Homem medium ( GE Healthcare ) supplemented with 10% foetal calf serum ( FCS , Thermo Fisher Scientific ) at 26°C . Δtkt cell culture was supplemented with 25μg/ml nourseothricin ( Sigma-Aldrich ) and 25μg/ml hygromycin ( Roche ) , integrated re-expressor cell line Δtkt + TKT with additional 25μg/ml puromycin ( Sigma-Aldrich ) . Cell lines with episomal vectors were cultivated in additional 25μg/ml G418 ( Sigma-Aldrich ) . Amastigote cells were cultivated in Schneider’s Insect Medium ( Sigma-Aldrich ) supplemented with 20% FCS ( Thermo Fisher Scientific ) and 15 mg/l hemin ( Sigma-Aldrich ) , at 32°C , pH 4 . 5 , and 5% CO2 [52] . LmTKT alleles were replaced sequentially with hygromycin B phosphotransferase ( HYG ) and streptothricin acetyltransferase ( SAT ) genes , encoding resistance markers for the antibiotics hygromycin and nourseothricin , respectively . The gene deletion construct for nourseothricin selection was based on the Leishmania knockout construct JPCM5 CPA-sat ( pGL520; kindly provided by Prof . Jeremy Mottram , University of York ) , a derivative of pXG-63-hyg ( PMID 8650210 ) . Flanking sequences upstream ( 0 . 4 kb ) and downstream ( 0 . 6 kb ) of the transketolase ORF were amplified by PCR using oligonucleotides that incorporated restriction sites suitable for subsequent insertion into the polylinker regions flanking the SAT gene and DHFR-TS untranslated regions of pGL520 . The 0 . 4 kb upstream fragment was amplified with oligonucleotides 5’-TAGCGTCGACTGTGCTTGTGGGTGAGGGCG and 5’-TAGCAAGCTTGGCCGCTTCGCACCACACGA , restriction sites for SalI and HindIII are underlined . The 0 . 6 kb downstream fragment was amplified with oligonucleotides 5’-TAGCCCCGGGTGCTCCGAAACGTGAGGAAT and 5’-TAGCAGATCTACTTCCTTGCCCTTCCGATA , restriction sites for SmaI and BglII are underlined . The hygromycin B-phosphotransferase resistant plasmid was generated by replacing the streptothricin acetyltransferase resistance gene , with the hygromycin B resistance gene from pGL345 ( PMID 8650210 ) . The knockout cassettes used for transfection was released by HindIII and BglII and gel purified using the QIAquick Gel Extraction Kit ( Qiagen ) . Clonal-like population of parasites resistant to hygromycin and nourseothricin were analysed by PCR and Southern Blot . For stable integration into the ribosomal locus , a derivative of pSSU-int [53] was used . The transketolase ORF was amplified using oligonucleotides 5’-TAGACTCGAGCTTCGCCTCTCTTCGTCGCCCT and 5’-TAGAGCGGCCGCCGCCTCTTCCGGTGTCATTC , restriction sites for XhoI and NotI are underlined . Clonal-like population of parasites resistant to puromycin were analysed by PCR . For mouse infection assay , BALB/c mice were inoculated with 2 x 106 promastigote cells from cultures in stationary phase , in the right rear foot pad and the size of ensuing lesions was measured weekly . At the end of the experiment popliteal lymph nodes were removed , placed into Homem medium at 26°C , and recovery of the parasites was assessed . Presence/absence of the TKT gene in these recovered parasites was confirmed by PCR . Alamar Blue Assays were performed as described previously [54 , 55] . Briefly , the assay was started with promastigotes at 5 x 105 cells/ml cultivated in the presence of respective compounds at desired concentrations ( glucose oxidase , amphotericin B , methylene blue , miltefosine , paromomycin , potassium antimonyl tartrate ( all Sigma-Aldrich ) , pentamidine ( May & Baker ) ) after 72 h cultivation resazurin ( Sigma-Aldrich ) was added to final concentration of 49 μM and after additional 48 h incubation , absorbance was measured with fluorescence spectrometer FLUOstar OPTIMA ( BMG Labtech ) . Intracellular ROS was measured using dichlorofluorescein diacetate ( DCFDA ) as previously described but with modifications [26] . Mid-log phase promastigotes were incubated for eight hours with or without 200 μM potassium antimonyl tartrate ( Sigma-Aldrich ) . Parasites were then precipitated by centrifugation , washed once with PBS then resuspended in HEPES-NaCl assay buffer ( 21 mM HEPES , 137 mM NaCl , 5 mM KCl , 0 . 7 mM Na2HPO4 , 6 mM glucose at pH 7 . 4 ) to a density of 7 . 5 x 107 cells/ml with 4 μM DCFDA ( Sigma-Aldrich ) . Two 200 μl aliquots taken from each sample were incubated for 40 min at 25 °C before measuring fluorescence on a FLUOstar Optima microplate reader ( BMG Labtech ) with excitation wavelength of 485 nm and emission wavelength of 520 nm . The average of these technical replicates was calculated , from which was subtracted a background value , determined as the average measurements of five wells containing only HEPES-NaCl buffer with 4 μM DCFDA . Human monocyte-lineage THP-1 cells were routinely cultured in RPMI ( Gibco ) supplemented with 10% FBS ( Gibco ) , 2 mM glutamine and 100 units/ml penicillin/0 . 1 mg/ml streptomycin ( Sigma-Aldrich ) ( complete RPMI ) at 37 °C , 5% CO2 . Prior to infection , THP-1 cells were subject to differentiation for 24 hours with 40 ng/μl phorbol 12-myristate 13-acetate ( PMA , Sigma-Aldrich ) , after which cells were adherent and PMA was removed by washing with serum-free RPMI . Stationary-phase L . mexicana promastigote cultures were precipitated by centrifugation and washed twice in serum-free RPMI , prior to resuspension in complete RPMI . Infections were carried out in a 10:1 parasite:host cell ratio for four hours at 32 °C , 5% CO2 , before removal of extracellular parasites by washing five times with serum-free RPMI . Infected THP-1 cells were then incubated for variable lengths of time , washing three times daily with serum-free RPMI , before washing with PBS and subjecting cells to methanol fixation and Giemsa staining . At least 100 macrophages were counted per sample , and a total of four independent biological replicates were used . For both GC-MS and LC-MS metabolomic analyses the sample extraction was performed following the method described previously [56] . Briefly , 108 cells were used for a final 200 μl sample . Cells were rapidly cooled in a dry ice/ethanol bath to 4°C , centrifuged , washed with 1 x PBS , and resuspended in extraction solvent ( chloroform:methanol:water , 1:3:1 volume ratio ) . Following shaking for 1 h at 4°C , samples were centrifuged at 16 , 000g , 4°C for 10 min and the obtained supernatant was collected and stored under argon atmosphere at -80°C until the analysis . For medium analysis , 10 μl of medium was mixed with 190 μl extraction solvent . For the experiments involving labelling , cells were cultivated in Homem medium containing 50% of U-13C-glucose ( Cambridge Isotope Laboratories , Inc . ) , or 100% 1 , 2-13C-glucose ( Cambridge Isotope Laboratories , Inc . ) . The analyses were performed using separation on 150 x 4 . 6 mm ZIC-pHILIC ( Merck ) on UltiMate 3000 RSLC ( Thermo Scientific ) followed by mass detection on an Orbitrap Exactive mass spectrometer ( Thermo Fisher ) at Glasgow Polyomics . Analyses were performed in positive and negative polarity switching mode , using 10 μl injection volume and a flow rate of 300 μl/min . The samples were run alongside 249 authentic standards at 10 μM each . The data were processed and analyzed using mzMatch software [57] , IDEOM [58] , mzMatchISO [59] , and MetaboAnalyst [60] . All the MS analyses were performed in 4 replicates , means of which are indicated . For the studies involving U-13C-glucose labelling , non-labelled samples were run in parallel and the natural labelling subtracted . Metabolites identified based on match with respective standards are indicated , the rest is predicted based on mass and retention time . Metabolomics data have been deposited to the EMBL-EBI MetaboLights database ( 10 . 1093/nar/gks1004 . PubMed PMID: 23109552 ) with the identifier MTBLS491 . Sample derivatisation , analysis and data processing were performed at Glasgow Polyomics and reported previously [61] . A retention index mix was prepared from pure alkanes dissolved in hexane to final concentration of 6 mg/ml . Stock solutions at 1 mM were prepared for each from neat reference standard in water . A custom standard mixture of sugars , sugar phosphates , and pentose phosphate pathway intermediates were then prepared by mixing the stock solutions together and diluting with water until an acceptable peak was observed during GC-MS analysis . 30 μl of extracted sample , as well as each standard mix of sugars , sugar phosphates , and pentose phosphate pathway , were transferred into a 300 μl KIMSHIELD deactivated glass polyspring insert ( National Scientific ) . Internal standards 13C6-Glucose ( 2 nmol ) , D27-Myristic Acid ( 2 nmol ) and Scyllo-Inositol ( 1 nmol ) were added to each sample . Samples were dried in a Savant SPD1010 SpeedVac concentrator ( Thermo Scientific ) for 90 min . Inserts were placed into a 9 mm screw cap amber borosilicate glass 1 . 5 ml vial ( Thermo Scientific ) . 50 μl of 20 mg/ml ( w/v ) methoxyamine HCl in pyridine was added to each dried sample and sealed . The vial and insert were vortexed for 10 seconds and incubated at 60°C for 120 min . Following the methoximation step , 90 μl of N-Methyl-N- ( trimethylsilyl ) trifluoroacetamide + 1% trimethylchlorosilane was added , followed by a further 10 second of vortexing . Silylation was performed by incubation at 80°C for a further 120 min . Samples were cooled to room temperature . 10 μl of retention index alkane mixture was added to each sample . Samples were then ready for injection . 1μl of derivatized sample was injected into a Split/Splitless ( SSL ) injector at 280°C using a 1 in 50 split flow using a Trace 1310 gas chromatograph ( Thermo Scientific ) . Helium carrier gas at a flow rate of 1 . 2 ml/min was used for separation on a TraceGOLD TG-5SILMS 30 m length × 0 . 25 mm inner diameter × 0 . 25 μm film thickness column ( Thermo Scientific ) . The initial oven temperature was held at 70°C for 4 min , followed by an initial gradient of 20°C/min ramp rate . The final temperature was 320°C and held for 5 min . Eluting peaks were transferred through an auxiliary transfer temperature of 250°C into a GC-Q-Exactive mass spectrometer ( Thermo Scientific ) . Electron impact ( EI ) ionisation at 70 eV energy , emission current of 50 μA with an ion source of 230°C . A filament delay of 5 . 3 min was used to prevent excess reagents from being ionised . High resolution EI fragment spectra were acquired using 60 , 000 resolution with a mass range of 50–650 m/z . The best internal lock mass from 207 . 0324 , 281 . 0511 or 355 . 0699 m/z was used to maintain mass accuracy throughout the chromatogram . WT and Δtkt mutants of L . mexicana were sampled by a fast filtration method as reported in Stoffel et al . [22] . Total sampling time was below 8 s . The extraction of intracellular metabolites was carried out by transferring the filters containing the pellets into 5 ml of boiling water for 30 s . 200 μl of a uniformly 13C-labeled E . coli cell extract was added as quantification internal standard [62] , and the mixture was briefly vortexed ( ≈2 s ) . The extracts were immediately filtered ( 0 . 2 μm ) and chilled with liquid nitrogen . After lyophilisation , the dried extracts were resuspended in 200 μl Milli-Q water prior to analysis . Three replicates were taken from each culture media , sampled and analysed separately . Metabolites involved in different parts of the metabolic network of L . mexicana cells were determined by liquid ion chromatography coupled to tandem mass spectrometry as described [22] with measured concentrations of metabolites expressed as a total cellular concentration assuming a volume of 108 cells being equal to 5 . 8 μl . For RNA sequencing the RNA was isolated using RNeasy Mini Kit ( Qiagen ) . The sequencing was performed at Glasgow Polyomics on the NextSeq500 platform , using library preparation by polyA selection , paired-end samples with 13 million reads per sample . The analysis was performed using the Galaxy interface [63 , 64] , Bowtie2 software [65] and Cufflinks package [66] . To measure enzyme activities on cell extract , 2 x 107 cells were used for 100 μl of final extract . Cells were centrifuged , washed with 1 x PBS , and resuspended in TE lysis buffer ( 10 mM Tris-HCl pH 8 . 0 , 1mM EDTA ) with 0 . 15% Triton X-100 and Complete protease inhibitor cocktail ( Roche ) . After 20 min incubation , the lysates were centrifuged ( 13 , 000 g , 16°C , 10 min ) and supernatant collected . All the reactions were coupled to another enzyme , so the activity could be measured as production or consumption of NAD ( P ) H by UV-VIS Spectrophotometer ( Shimadzu ) at λ = 340 nm . In order to measure hexokinase activity , the reaction mixture was prepared containing 300 mM Tris-HCl pH 7 . 5 , 25 mM NaCl , 3 mM glucose , 2 mM ATP , 2 mM MgCl2 , 1mM NADP , and 1 U G6PDH ( all from Sigma-Aldrich ) in 1ml total volume . The reaction mixture for glucose-6-phosphate isomerase contained 100 mM triethanolamine pH 7 . 5 , 7mM MgCl2 , 1 . 3 mM F6P , 0 . 4 mM NADP , and 1U G6PDH ( all from Sigma-Aldrich ) in 1 ml total volume . The reaction mixture for fructose-1 , 6-bisphosphate aldolase contained 100 mM triethanolamine pH 7 . 6 , 2 μM EDTA , 10 μM fructose 1 , 6-bisphosphate , 1 U triosephosphate isomerase , 1 U glycerol-3-phospahte dehydrogenase and 100 μM NADH ( all from Sigma-Aldrich ) in 1 ml total volume . For 6PGDH measurement , the reaction contained 50 mM triethanolamine pH 7 . 5 , 5mM MgCl2 , 2 mM 6-phosphogluconate and 1 mM NADP ( all from Sigma-Aldrich ) . When adding 1 mM glucose 6-phosphate into that mixture , the sum of activities of G6PDH and 6PGDH was measured and G6PDH activity was subsequently calculated from the difference . The GFP-TKT construct was made using pNUS-GFPnH vector ( [67] ( http://www . ibgc . u-bordeaux2 . fr/pNUS/greenvectors . html ) . The following primers were used: 5’- TAAGATCTATGGCCTCCATTGAGAAGGTGG—3’ and 5’- TACTCGAGTTACATCTTGCTGAATGAAGA– 3’ , restriction sites for BglII and XhoI are underlined . For the TKT constructs with elongated and shortened C-termini , dsDNA constructs of the respective sequences were purchased from GenScript , USA . The DNA fragments were cloned into pNUS-GFPnH vector harboring TKT gene using internal restriction site for FspAI . For the construct omitting the PTS1 , the reverse primer 5’—TACTCGAGGAATGAAGAGTTCTTGAGCGGCGCC– 3’ was used . For preparation of samples for immunofluorescence microscopy , 200 μl of cell culture was used for each sample . Cells were washed in 1 x PBS two times , resuspended and incubated in 1% formaldehyde ( methanol free , Thermo Fisher ) for 30 min . Triton X-100 was added to final 0 . 1% concentration , after 10 min incubation glycine was added to 0 . 1 M final concentration and incubated for 10 min . Samples were centrifuged at 1 , 300 g , for 10 min , resuspended in 200 μl of PBS , and spread on microscope slides . Subsequently , slides were washed in PBS and blocked in TB solution ( 1x PBS with 0 . 1% Triton X-100 , 0 . 1% BSA ) for 1 h at room temperature . The primary α-TIM antibody was added in 1:100 dilution ( kindly provided by Prof . Paul Michels , University of Edinburgh ) in TB solution and incubated at 4°C overnight . Slides were washed three times in 1 x PBS , and incubated with secondary antibody ( AlexaFluor 594 anti-rabbit , 1:1000 , Molecular Probes ) for 1 h at room temperature . Slides were washed three times in 1 x PBS , subsequently mounted with 2 . 5 μM DAPI , and covered with cover slides . Cells were visualised using Axioplan2 ( Zeiss ) and Volocity software . To estimate glucose consumption by Leishmania parasites , cultures were started at 107 cells/ml density in fresh Homem medium containing only 1 mM glucose plus 10% FCS . At respective time points cell density was counted and a sample of spent media taken from each culture flask . Medium was kept at -20°C until the glucose concentration test was performed using GO Assay kit ( Sigma-Aldrich ) following the manufacturer’s instructions . Glucose consumption was calculated as reported previously [68] . Cellular mannogen content was visualised by HPTLC as previously described [69] . Briefly , 2 . 5 x 108 mid-log phase cells were precipitated by centrifugation , washed once with PBS and then extracted for two hours in 1:2:0 . 8 chloroform:methanol:water at room temperature , agitating continuously at 1 , 500 rpm . Metabolite extracts were cleared by centrifugation at 17 , 000 g for 10 min and precipitated pellets were retained for protein content determination . Supernatants were dried in a Savant DNA 120 SpeedVac concentrator ( Thermo ) and resuspended in 1:1 1-butanol:water . After partitioning the aqueous layer was retained and further washed twice with an equal volume of water-saturated 1-butanol , then desalted using AG501-X8 resin ( Bio-Rad ) . The aqueous phase was then dried and resuspended in 1:2:0 . 8 chloroform:methanol:water . HPTLC analysis was performed on aluminium-backed silica 60 plates ( Merck ) , developing twice in 4:3:3 1-butanol:methanol:water , then visualising by spraying with orcinol/H2SO4 and heating at 100°C for 10 min . Protein content was determined by extracting precipitated pellets in 0 . 1 M NaOH at 4°C for 30 min with continuous shaking at 1 , 500 rpm , centrifugation at maximum speed for 10 min then measuring protein concentration using the Bio-Rad protein assay dye reagent ( Bio-Rad ) in comparison to a bovine serum albumin standard curve . Quantification of mannogen was performed using ImageJ , based on three biological replicates and normalised per protein content .
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Leishmania parasites endanger over 1 billion people worldwide , infecting 300 , 000 people and causing 20 , 000 deaths annually . In this study , we scrutinized metabolism in Leishmania mexicana after deletion of the gene encoding transketolase ( TKT ) , an enzyme involved in sugar metabolism via the pentose phosphate pathway which plays key roles in creating ribose 5-phosphate for nucleotide synthesis and also defence against oxidative stress . The insect stage of the parasite , grown in culture medium , did not suffer from any obvious growth defect after the gene was deleted . However , its metabolism changed dramatically , with metabolomics indicating profound changes to flux through the pentose phosphate pathway: decreased glucose consumption , and generally enhanced efficiency in using metabolic substrates with reduced secretion of partially oxidised end products of metabolism . This ‘stringent’ metabolism is reminiscent of the mammalian stage parasites . The cells were also more sensitive to oxidative stress inducing agents and leishmanicidal drugs . Crucially , mice inoculated with the TKT knock-out parasites did not develop an infection pointing to the enzyme playing a key role in allowing the parasites to remain viable in the host , indicating that TKT may be considered a useful target for development of new drugs against leishmaniasis .
|
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"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
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"cell",
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2018
|
Deletion of transketolase triggers a stringent metabolic response in promastigotes and loss of virulence in amastigotes of Leishmania mexicana
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The dominance of the major transcript isoform relative to other isoforms from the same gene generated by alternative splicing ( AS ) is essential to the maintenance of normal cellular physiology . However , the underlying principles that determine such dominance remain unknown . Here , we analyzed the physical AS process and found that it can be modeled by a stochastic minimization process , which causes the scaled expression levels of all transcript isoforms to follow the same Weibull extreme value distribution . Surprisingly , we also found a simple equation to describe the median frequency of transcript isoforms of different dominance . This two-parameter Weibull model provides the statistical distribution of all isoforms of all transcribed genes , and reveals that previously unexplained observations concerning relative isoform expression derive from these principles .
Most genes of eukaryotic organisms , unlike those of prokaryotes , may each generate multiple different mature transcript isoforms which can encode proteins with distinct or even opposing functions [1–6] . It has also been shown that the dominance of the major transcript isoform from a single gene may radically affect cell function , identity and fate , and that disruption of this dominance may result in human disease , including abnormal osteoclast genesis , tumorigenesis and Parkinson’s disease [3–11] . In addition , three intriguing observations have been reported regarding the frequency distribution of transcript isoforms that point to universal principles governing gene transcript isoform expression: ( 1 ) genes tend to express all their isoforms simultaneously but at different levels; ( 2 ) the major and minor dominant isoform of a gene usually accounts for over 30% and 15% of total transcript expression , respectively; and ( 3 ) for any two distinct transcript isoforms from the same gene , one of them is always significantly dominant [3–14] . However , the mechanisms underlying these fundamental observations remain unclear . Indeed , the overall expression and frequency distribution of all isoforms of entire transcriptomes has rarely been subjected to systematic analysis .
Many studies have been performed to identify cis-acting elements , trans-acting factors and the specific biological processes involved in AS [1 , 15–18] . Essentially , the AS process contains two major steps: ( 1 ) intron identification by the binding of U1 and U2AF proteins to the 5’ and 3’ splice sites , respectively; and ( 2 ) intron splicing by the release of U1 and the additional binding of U4-6 snRNP [1 , 15–18] . We focused on intron identification as this decides the fate of the pre-mRNA by determining which transcript isoforms will be produced . U1 and U2AF engage in random three-dimensional ( association/dissociation ) and one-dimensional ( sliding ) Brownian search ( Fig 1A ) [19 , 20] . The binding of U1 and U2AF to the splice sites is ATP-independent , weak and reversible , and becomes stable only after the ATP-dependent binding of U2 snRNP ( Fig 1B ) [21] . Usually , in a segment of pre-mRNA presented for AS , many candidate splice sites exist and compete for the binding of U1 and U2AF . The lower the potential energy of the splice sites , the stronger the binding and the more time allowed for the formation of a stable A-complex , the more corresponding mature mRNA will be produced . This indicates that the process of AS is stochastic: the product of a transcript isoform from a pre-mRNA is probabilistically determined by the binding energy of splicing factors at splice sites . Mathematically , this process represents a stochastic minimization process in which U1 and U2AF dynamically search their global or local minimal potential energy sites on the pre-mRNA segment since non-minimal potential energy sites are not stable thus don’t have enough time to allow the formation of stable A-complex . A mature mRNA will undergo multiple rounds of the minimization process if the corresponding pre-mRNA has multiple introns to remove ( Fig 1B ) . This suggests that the expression levels of transcript isoforms may follow an extreme value distribution , of which there are only three types whatever the original distribution of the random variables; namely , Gumbel distribution ( Type I ) , Frechet distribution ( Type II ) and Weibull distribution ( Type III ) . These three distributions can be transformed to each other by a simple mathematical transformation of the original random variable [22–24] . We tested the three candidate distributions by performing whole transcriptome deep sequencing ( RNA-seq ) on highly purified resting and activated peripheral blood human CD4 T cell subsets ( naïve , central memory , transitional memory and effector memory ) from 9 healthy donors ( S1 Table ) . Because the AS mechanism is the same for all multiple-exon genes , the distribution function that their transcript isoforms follow should be similar . However , certain parameters of the distribution function may differ according to the level of expression of a gene as determined by the activation state of the cell . Thus , a scaling parameter must be applied to the raw expression levels of transcript isoforms from different cell conditions and genes . A simple scaling factor is the average expression level of all transcript isoforms from the same gene , as it positively correlates with the gene’s expression level but is independent of isoform number . The smaller the isoform number M , the greater the inaccuracy in the estimation of the scaling factor , and , for accuracy , only genes with M≥5 are used here . Our analysis reveals that the expression levels of transcript isoforms of a gene follows a type III Weibull extreme value distribution—W ( x , a , b ) ( Fig 1C ) . W ( x ) is the probability of a transcript isoform with expression level x; b is the scale parameter , which will change with the expression level of gene; and a is the shape parameter , which is specific to the AS mechanism and should be constant for all genes . The approximate values of parameters a ( 0 . 44 ) and b ( 0 . 6 ) in Fig 1C are estimated by simple curve fitting , and thus are somewhat inaccurate . For the Weibull distribution , a simple formula links a , b and the population mean of μ [24 , 25] , μ=bΓ ( 1+1a ) ( 2 ) Γ represents Gamma function . For a gene with M transcript isoforms and expression level of E , the sample mean x¯=E/M . When the isoform number M is sufficiently large , the sample mean approaches the population mean , giving an approximate formula that connects transcript isoform number M , gene expression level E and two parameters a and b , E≈bMΓ ( 1+1a ) ( 3 ) Of note , the analysis above shows that the correct scale factor b should be x¯/Γ ( 1+1a ) , not x¯ . Although the experimental data fit very well with the Weibull distribution empirically , the statistical test of the fitness-of-fit is not significant for four reasons . First , our model is a very simple one , which considers only the most important factor influencing AS , the strength of splice site binding , and disregards many other factors such as co-transcriptional splicing , histone modifications on chromatin , poison exons , non-sense mediated degradation ( NMD ) and so on; Second , there is bias in the estimation of the scale factor , and furthermore this bias changes with isoform number M . Third , it is well known that current annotations for human transcript isoforms are incomplete; thus , the transcript isoform number M used for many genes is not accurate . Fourth , although significant improvement has been made in the accuracy of calculation of transcript isoform expression levels , current algorithms nevertheless remain imperfect . We defined the frequency of a gene’s transcript isoform as the ratio of its expression level relative to the expression level of the gene , which equals the sum of expression levels of all transcript isoforms from that gene ( Fig 2A ) . Thus , for a gene with M different transcript isoforms where each isoform has the rank k in the hierarchy of expression levels , we use f ( k , M ) to represent the frequency of the kth dominant isoform . As 1≤k≤M , so f ( 1 , M ) ≥ f ( 2 , M ) ≥ … ≥ f ( M , M ) . f ( k , M ) was entirely stochastic , differed among genes and changed with cell activation state , except for f ( 1 , 1 ) which was always 100% as long as the corresponding gene was expressed . For example , f ( 1 , 2 ) —the frequency of the most dominant isoform of a gene with two transcript isoforms—varied between 50% and 100% . f ( 2 , 2 ) —the frequency of the second most dominant isoform—varied between 0 and 50% . For a specific gene , both the frequencies and the ranks of its isoforms may change with cell condition , such that the most dominant isoform of a gene in one condition may become a less dominant isoform in other conditions . Thus , for the same gene ( same M ) and same k , f ( k , M ) may represent the frequency of a different isoform under different cell conditions . While notable , this property is inconsequential as the following analyses explore the relationship solely between the frequency and rank of transcript isoforms . To analyze the frequency distribution of transcript isoforms , we grouped genes according to the number of their isoforms from group 1 , which contains genes with one isoform , through group M which contains genes with M isoforms . The variation in isoform frequency with k and M is illustrated straightforwardly in a boxplot ( Fig 2B ) which shows that the frequency of the most dominant isoform decreases with M . This trend becomes more apparent if we focus solely on the median value , mf ( k , M ) . The median frequency of the most dominant isoform mf ( 1 , M ) decreases from 100% when M = 1 , to approximately 50% when M = 10 , and approximately 30% when M = 30 . In contrast , the median frequency of the second most dominant isoform mf ( 2 , M ) initially increases , peaking when M = 6 , and then decreases with M . The median frequencies of other isoforms ( k>2 ) show a similar trend . These results confirm and extend a previous report where only the most dominant isoform ( k = 1 ) was analyzed [13] . Notably , our model was not only able to explain and provide the overall distribution of the scaled expression levels of all transcript isoforms , it could also provide the frequency distribution of all transcript isoforms . We may show this using a Monte Carlo simulation . The scale parameter b was set as 1 as it has no influence on this simulation of transcript isoform frequency . First , we showed that all mf ( k , M ) can be explained by our model and , in the process , also showed how mf ( k , M ) could give a more accurate estimation of the shape parameter a—approximately 0 . 44 . We randomly selected a number in the range ( 0 , 1 ) as the value for a and performed the following computation: for genes with M transcript isoforms , we randomly extracted M numbers from the Weibull distribution W ( a , 1 ) as the expression levels of the M simulated isoforms , which can then be transformed to their frequencies . We repeated this process 10 , 000 times for each M to obtain the simulated median frequency mf ( k , M ) and then compared it with the corresponding mf ( k , M ) from our experimental data . The Euclidian distance of all mf ( k , M ) from simulated data and experimental data in Fig 2B was calculated and reached the minimal value when a was 0 . 39 ( Fig 2C ) . Notably , 0 . 39 is also the exact solution of equation 1+1/a = Γ ( 1+1/a ) . Fig 2B shows that when a = 0 . 39 , values for mf ( k , M ) calculated from the simulated data ( red curves ) are very close to those from the experimental data ( box plot ) . The shape parameter a calculated by the Monte Carlo simulation is more accurate than that calculated by simple curve fitting for two reasons . First , the median value of a distribution is very stable , and sampling error and outliers has relatively less influence on its estimation . Second , the bias in the estimation of scale factor is same for both the experimental and simulated datasets and thus its influence is canceled out . To help understand how mf ( k , M ) changes with a , similar figures with a = 0 . 2 and a = 0 . 6 are also given in the supplemental material ( S1 Fig ) . Fig 2B reveals that the median frequency of the most dominant isoform , mf ( 1 , M ) , decreases with M and has no lower limit . This finding contradicts a previous observation that the frequency of the most dominant isoform is at least 30% , even for a gene with many isoforms [13] . Second , we showed that the frequency distribution of all transcript isoforms as well as each f ( k , M ) can be given by our model . Repeating the previous Monte Carlo simulation with a = 0 . 39 , we obtained the frequency distribution of all transcript isoforms for different gene groups ( different M ) ( Fig 3 ) and each f ( k , M ) ( Fig 4 and S2 Fig ) from the simulated data . Here , we use Kullback-Leibler divergence ( KLd ) to evaluate the difference between the two distributions , which represents the amount of information lost when we used the simulation of our Weibull model to represent the frequency distribution of the experimental data . We found that for most frequency distributions analyzed , the amount of information lost is smaller than 0 . 05 ( mean = 0 . 026 , median = 0 . 020 ) . This shows that the frequency distribution from the simulated data ( red curve ) is highly consistent with that from the experimental data ( black curve ) , although the shape and range of the distribution change with k and M . Thus , although the expression levels of transcript isoforms change with a particular gene , cell condition and rank , their overall frequency distributions do not change and can be described by our model . Third , these distributions enable statistical analysis of transcript isoform usage such as defining significantly dominant transcript isoforms . For genes with two , five , ten , 20 and 30 transcript isoforms , an isoform may be called significantly dominant if its frequency is above 0 . 99 , 0 . 852 , 0 . 529 , 0 . 269 and 0 . 174 , respectively , since the probability that an isoform randomly selected has frequencies above these thresholds is less than 5% ( S2 Table ) . Thus , the ability to define such thresholds may be used as a statistical framework to discover functionally dominant transcript isoforms with relevance to disease states . The frequency distribution of transcript isoforms changes with their rank k and the isoform number M of the gene from which they are spliced . Nonetheless , our model was able to give the distribution of each f ( k , M ) as well as their median frequency mf ( k , M ) . Remarkably , we also found that all mf ( k , M ) could be described by a simple formula: mf ( k , M ) =1/ ( kM×e ( 1+kM ) 2 ) ∑m=1M1/ ( mM×e ( 1+mM ) 2 ) =1k×e− ( 1+kM ) 2∑m=1M1m×e− ( 1+mM ) 2=e− ( 1+kM ) 2k×HM ( 4 ) Here , HM is the Mth generalized harmonic number: HM=∑m=1M1m×e− ( 1+mM ) 2 ( 5 ) Fig 2B shows that the median frequencies computed by the formula above ( blue curves ) are very close to the values from the experimental data and simulated data across all values of k and M , indicating that the median frequency of the kth dominant isoform of a gene with M isoforms is proportional to 1k×e− ( 1+kM ) 2 , which thus can be taken as its frequency index . Four important methodological points were addressed . First , to exclude the possibility that our results emerged from an intrinsic property of the analysis software , we reanalyzed the entire dataset with an independent software package , Salmon [26 , 27] , which , in contrast to Cufflinks , requires no sequence alignment . The similarity of the results derived from these two approaches indicates that the isoform frequency distribution we observed is robust and software-independent ( S3 Fig ) . Second , to exclude the possibility that our results emerged from the Expectation Maximization ( EM ) algorithm used by most software packages , we created two simulated RNA-seq datasets with transcript isoform expression level following a Normal distribution N ( 20 , 2 ) and a Weibull distribution W ( 0 . 39 , 10 ) , respectively ( See Materials and methods for details ) . The results based on the simulated RNA-seq dataset from the Normal distribution were markedly different from those from our experimental RNA-seq data ( S4 Fig ) . In contrast , the results based on the simulated RNA-seq dataset from the Weibull distribution showed a perfect match with our experimental RNA-seq data ( S5 Fig ) . Third , to exclude the possibility that our results emerged purely as a function of the particular dataset we used , we analyzed 18 different pre-existing RNA-seq datasets derived from embryonic stem cells , cancers and human cell lines ( S3 Table ) . We obtained similar results in every case ( S6 and S7 Figs ) . Finally , the result based on a merged gene set ( Euclidian distance 0 . 158 ) showed a closer match with our formula than the result based solely on the Ensembl gene set ( Euclidian distance 0 . 160; S8 Fig ) , which reflects the incomplete nature of existing datasets . The correctness of our model is strongly supported by two points . First is the simplicity of the model in that it requires only one shape parameter . Second is its general applicability in explaining the scaled expression level of all transcript isoforms , the frequency distribution of transcript isoforms of genes with different isoform number ( M ) , and furthermore the frequency distribution of individual transcript isoforms of different rank ( k ) . Here , we did not perform a strict mathematical deduction of how stochastic searching of minimal-energy U1 and U2AF binding sites leads to the Weibull distribution as this would be extremely difficult if not impossible , as Weibull himself discussed in his original paper: “it is utterly hopeless to expect a theoretical basis for distribution functions of random variables such as strength properties of materials or of machine parts of particle size” [25] . Currently , our model takes the isoform annotation of all genes given by the user as input ( we recommend the latest Ensembl transcript annotation ) , and it does not explain or predict the isoform number of genes . It should be noted that the binding potential energy landscape of U1 and U2AF on a specific pre-mRNA segment is not static but dynamic , and may change with the binding of other tissue-specific or non-specific auxiliary proteins on cis-acting AS elements induced by external signals; thus , genes may have different major transcript isoforms under different conditions . We analyzed the change of dominancy rank of transcript isoforms for every expressed gene in the four T cell subsets under the two cell conditions: resting and after in vitro activation . Using the Ensembl gene set , 540 genes underwent transformation of the most dominant transcript isoforms between resting and activated conditions across all four T cell subsets , another 891 genes underwent transformation of the most dominant isoform for three of the four T cell subsets ( S4 Table ) . The biological processes enriched in the 540 genes are very diverse and include regulation of cellular response to stress , virus-host interaction , chromosome organization , transcription , translation and protein metabolism ( S9 Fig ) . This suggests that a T cell may express not only different genes but also different transcript isoforms depending on its activation state . For example , BRD4 ( bromodomain containing 4 ) , an inhibitor gene of HIV-1 infection [28] , has 11 known transcript isoforms . Of them , ENST00000371835 is the most dominant isoform in the activated condition of all four T cell subsets and the second most dominant in the resting condition , while ENST00000263377 is the most dominant isoform in the resting condition in all four T cell subsets and the second most dominant in the activated condition ( Fig 5A ) . SRSF7 ( serine/arginine-rich splicing factor 7 ) , a splicing factor and inhibitor of HIV-1 Tat-mediated transactivation [29] , has 12 distinct transcript isoforms . Of them , ENST00000409276 is the most dominant transcript isoform in the stimulated condition across all four T cell subsets , whereas ENST00000477635 is the most dominant transcript isoform in resting condition across all four T cell subsets ( Fig 5B ) . Taken together , these and our previous results demonstrate that the dominancy rank of transcript isoforms of a gene can be regulated by external stimuli , but that the frequency distribution of transcript isoforms at each rank remains constant . It has been reported that the number of isoforms expressed increases with the number of isoforms annotated per gene [13] . We redid the analysis with our own RNA-seq data and confirmed these findings and , more importantly , can provide an explanation . To calculate the expected number of isoforms expressed , we still used the expression level of transcripts from the simulated Weibull distribution W ( 0 . 39 ) . Different genes have different expression levels; thus it is reasonable to select a cutoff of frequency rather the absolute expression level to define whether a transcript isoform would be theoretically detected . Here , we use 0 . 001 as the frequency cutoff and thus define undetectable transcript isoforms as those whose frequency is below 0 . 001 . The boxplot is the observed result from our RNA-seq data ( Fig 6 ) . The red curve is the expected median calculated from our model guided by two assumptions: 1 ) genes express all their transcript isoforms simultaneously; 2 ) the scaled expression level of transcript isoform follows W ( 0 . 39 ) . There is excellent concordance between the two plots , and they both show that the number of isoforms expressed increases with the number of transcripts annotated per gene . Our model may be applied to a number of key observations that have been made in previous studies on the usage of AS transcript isoforms but for which mechanistic explanations have been lacking . The first observation is that genes tend to express all their transcript isoforms simultaneously but at different levels [13] . We can explain this mathematically because the Weibull distribution , when a<1 ( here a = 0 . 39 ) , peaks at 0 and then decreases at a rate greater than an exponential distribution . Thus the expression level of most transcript isoforms will be slightly higher than 0 , while the expression level of the remaining transcript isoforms will be considerably higher than 0 and will differ from each other . The second observation is that the major and minor isoforms of a gene usually account for over 30% and 15% of total transcript expression , respectively [12–14] . The theoretical percentage of human genes with f ( 1 , M ) ≥ 30% can be calculated from the weighted number of genes in each gene group . We first calculated the percent of simulated genes with f ( 1 , M ) ≥ 30% for each gene group in the simulated dataset and then used the result to weight the number of human genes in that group . The result revealed that 93% of genes that undergo AS will have f ( 1 , M ) >30% . Similar analysis revealed that 60% of genes that undergo AS will have f ( 2 , M ) ≥ 15% . The third observation is that , no matter how many different transcript isoforms a gene has , if we focus only on two of them , such as the two with opposing function , one will always be significantly dominant [3–11] . The frequency distribution of f ( 1 , 2 ) ( Fig 4A ) shows that for any two isoforms from the same gene , the possibility of the dominant isoform having frequency ≥80% is greater than 73% . This explains how cells can maintain the dominancy of one transcript isoform over others including those with opposing functions . Essentially , our results ( Fig 4B ) demonstrate that the frequency distribution of the second-most dominant transcript isoform changes with M; thus , a more rational way to define the minor transcript isoform may be to use an M-related dynamic threshold based on the distribution of f ( 2 , M ) .
In conclusion , we have derived a mathematical model that describes AS based on its physical process . Alternative splicing is a very complex biological process , and many factors contribute to the splicing of a pre-mRNA segment , such as strength of binding of AS complex on splice sites , co-transcriptional splicing , histone modifications on chromatin , poison exons , non-sense mediated degradation ( NMD ) and so on . Our model only considers the most important of these factors , the strength of splice site binding , and disregards all other factors . In this sense , it is a simple model which nevertheless succeeds very well in explaining many observation regarding AS . AS in our model and in this manuscript refers to the biological process that splices the same pre-mRNA into different transcript isoforms . It covers all five basic modes of alternative splicing: exon skipping or cassette exon , mutually exclusive exons , alternative donor site ( alternative 5’ splice site ) , alternative acceptor site ( alternative 3’ splice site ) and intron retention . Our model suggests that: ( 1 ) AS is a stochastic process such that the relative expression level of different transcript isoforms from the same gene is probabilistically determined by the binding energy of splicing factors at their splice sites; ( 2 ) the expression levels of transcript isoforms of a gene follow the Weibull distribution W ( 0 . 39 , b ) , here b is a scale parameter dependent on the expression level of the gene , and the scaled expression levels of different transcript isoforms from all genes follow the same Weibull distribution W ( 0 . 39 ) ; and ( 3 ) the frequency distributions of all transcript isoforms can be calculated from the Monte Carlo simulation of the Weibull distribution W ( 0 . 39 ) . This indicates that the expression of a transcript isoform is not a deterministic event but rather a stochastic event , and the detection of a transcript isoform in an RNA-seq dataset depends on both the expression level of its related gene and sequencing depth . We found a simple formula to describe the median frequency of each transcript isoform . Our analysis also provides transcriptome-wide evidence that the dominance rank of transcript isoforms is altered by distinct external signals and identifies 540 genes that switch their major transcript isoform usage in all four T cell subsets studied . Additionally , our analysis reveals that the AS process has an intrinsic tendency to maintain the dominancy of one transcript isoform over others including those with opposing function . Finally , by incorporating previously unexplained observations , the application of our model to describing the statistical distributions of scaled expression level and frequency of transcript isoforms provides a theoretical foundation for understanding the principles that govern relative transcript isoform generation , which in turn regulates cell identity , function and fate .
Nine healthy study volunteers were recruited through the NIH Department of Transfusion Medicine and gave informed consent for leukapheresis . The study was approved by the NIH Institutional Review Board . Leukaphereses were performed at the NIH Blood Bank , followed by immediate isolation of PBMC by density gradient centrifugation . CD4 T cells were then isolated using the CD4+ T Cell Isolation Kit II ( Miltenyi ) , counted , and viably cryopreserved in a freeze medium containing 10% DMSO and 90% sterile filtered , heat inactivated fetal calf serum . Viably cryopreserved peripheral blood CD4 T cells were thawed and stained with ViViD viability dye ( Molecular Probes ) and fluorescently-labeled monoclonal antibodies against cell surface markers . Staining antibodies included CD3-H7-Allophycocyanin ( H7-APC; BD ) , CD27-Cyanin5-Phycoerythrin ( Cy5-PE; Coulter ) , CD45RO-Texas Red-PE ( Coulter ) , CCR7-Alexa680 ( Pharmingen ) , CD8-Quantum dot-655 ( QD655; Invitrogen ) , CD4-Quantum dot-605 ( QD605; Invitrogen ) , CD19-Pacific Blue ( Invitrogen ) , and CD14-Pacific Blue ( Invitrogen ) . After excluding non-viable cells and those expressing CD19 and CD14 , all viable CD3+CD4+CD8- events were gated to collect TN ( CD27+CD45RO- ) , TCM ( CD27+CD45RO+CCR7+ ) , TTM ( CD27+CD45RO+CCR7- ) and TEM ( CD27-CD45RO+ ) populations ( S1 Table ) . Cells were sorted at 4°C and collected in sterile filtered , heat inactivated fetal calf serum . Sorted CD4 TN , TCM , TTM , and TEM subsets were divided into two equal portions to allow comparison between stimulated and unstimulated conditions . Unstimulated portions were immediately subjected to nucleic acid extraction . For stimulation cultures , cells were sedimented at 420g for 7 minutes at 4°C and resuspended in complete culture medium ( RPMI 1640 + 10% heat inactivated , sterile filtered calf serum + Penicillin/Streptomycin/Glutamine ) . They were then combined with T cell activation/expansion beads ( anti-CD3/anti-CD2/anti-CD28; Miltenyi ) at a 1:2 bead:cell ratio at a final concentration of 2 x 106 cells/mL and incubated at 37°C for 5–6 hours . Following this incubation , stimulated CD4 T cell subsets were subjected to nucleic acid extraction . Cell subsets were lysed in RNAzol RT reagent ( Molecular Research Centers ) and homogenized by pipetting . Total RNA was then extracted according to the manufacturer’s instructions . Extracted RNA in pellet form was dissolved in RNAse-free water and used for mRNA library construction . Sequencing libraries were prepared and sequenced as previously described [30] . In brief , total RNA was enriched for polyadenylated species by two sequential rounds of binding to oligo-dT dynabeads ( Life Technologies ) , chemically fragmented in the presence of Mg2+ , and reverse transcribed using Superscript III reverse transcriptase ( Life Technologies ) . Second strand cDNA synthesis , end repair , A-tailing , and sequencing adaptor ligation were performed using NEBNext enzyme modules ( New England Biolands ) . Libraries were amplified using universal and indexed primers from the NEBNext system with Kapa 2x Hot Start Readymix ( Kapa Biosystems ) . Amplified libraries were size-selected using Beckman-Coulter Ampure XP beads , quantified by qPCR using the Kapa Library Quantification Kit for Illumina ( Kapa Biosystems ) , and checked for sizing by electrophoresis on a BioAnalyzer ( Agilent ) . Completed libraries were loaded on Illumina Truseq Paired-End v2 Cluster Kits and sequenced in 2 x 100 base paired-end runs on an Illumina HiSeq 2000 sequencer . The final dataset comprised 1 . 27×109 reads pairs in total , with each cell condition corresponding to 1 . 59×108 reads pairs and each sample corresponding to 1 . 76×107 reads pairs on average . Trimmomatic ( version 0 . 22 ) was used to remove adapters and low quality bases [31] . The trimmed paired-end reads were mapped to the reference human genome ( Hg19 ) using Tophat ( version 2 . 0 . 8 ) and assembled with Cufflinks ( version 2 . 2 . 1 ) [32–34] . Cuffmerge was used to merge all novel assemblies and the known human gene set ( Ensembl “Homo_sapiens . GRCh37 . 74 . gtf” ) to create a merged non-redundant transcript annotation . Finally , Cuffdiff was used to evaluate the expression of genes and their transcript isoforms . All genes with FPKM>1 are included in our analysis . To prove our results are software independent , another software , Salmon ( version 0 . 8 . 2 ) was also used to evaluate the expression of genes and their transcript isoforms [26] . Supposing f1 and f2 are two 9×30 frequency matrices , where an element in row k and column M represents the median frequency of the kth most dominant transcript isoform of gene with M isoforms , k≤M . The frequency matrix data may be derived from experimental RNA-seq data , formula ( 4 ) or from a simulation of the Weibull distribution W ( 0 . 39 ) , such as in Fig 2B . The Euclidian distance of the two matrixes can be calculated from following formula , distance ( f1 , f2 ) =∑k=19∑M=k30 ( f1 ( k , M ) −f2 ( k , M ) ) 2 Supposing P and Q are two probability distributions , P is from experimental data , Q is from simulated data of Weibull distribution , the Kullback-Leibler divergence ( KLd ) between P and Q is defined by following formula , KLd ( P∥Q ) =∫−∞∞p ( x ) logp ( x ) q ( x ) dx When P and Q are discrete probability distributions , KLd ( P∥Q ) =∑iP ( i ) logP ( i ) Q ( i ) KLd represents the amount of information lost when Q is used to approximate P . The information content or entropy of a distribution P is defined as , Entropy ( P ) =∫−∞∞p ( x ) log ( p ( x ) ) dx When P is a discrete probability distribution , Entropy ( P ) =∑iP ( i ) log ( P ( i ) ) The KLd and entropy in this study are calculated by the KL . plugin function in the R “entropy” package . First , we extracted transcript isoform sequences for all human genes from the reference genome ( Hg19 ) according to the Ensembl annotation ( Ensembl “Homo_sapiens . GRCh37 . 74 . gtf” ) . For a gene with M isoforms , we randomly extracted M values from N ( 20 , 2 ) or W ( 0 . 39 , 10 ) as their expression levels E and proceeded thus: for a transcript isoform with length L and expression level E , we randomly extracted R = int ( E*L/100/2+0 . 5 ) read pairs to uniformly cover the transcript isoform . Each read pair has 100bp on each end and an average insert length of 100bp . This ensured that the transcript isoform had an expression level of E . We then added reads info and quality info for each read pair . We repeated this process for all transcript isoforms to create simulated FASTQ files . The whole process was repeated ten times to create ten different sequence data for the Normal distribution N ( 20 , 2 ) and the Weibull distribution W ( 0 . 39 , 10 ) , respectively . We estimated the value of parameters a ( 0 . 44 ) and b ( 0 . 6 ) by curve fitting , which is not accurate due to bias in the estimation of the scale factor for each gene as shown below . To illustrate why the shape parameter computed from curve fitting is inaccurate , we performed the same scale transformation on the simulated dataset . The expression values in the simulated dataset strictly follow the Weibull distribution W ( 0 . 39 , 1 ) as they are produced from this distribution . However , the scaled expression values do not follow the Weibull distribution , and their range is from 0 to M ( S10 Fig ) . The scaled expression is always 1 when M = 1 . It has two peaks at 0 and 2 when M = 2 . The larger the M , the closer the scaled expression ( black histogram ) and original expression ( red curve ) . The difference becomes small when M = 5 . The most distinct difference lies in the maximal value . For original expression , there is no upper bound for the maximal value although the higher the expression the less chance it appears . For scaled expression , the maximal value is bound by M . Traditionally , the Weibull plot is used to calculate the shape parameter of the Weibull distribution [24 , 25] . However , this method cannot be applied here for two reasons . First , the scale parameter and distribution is different for each gene and each condition . Second , the isoform number is limited for each gene , and there is bias in the estimation of the scale parameter for each gene . The comparison of the Weibull plot between the scaled and original values from same simulated data shows that the larger the M , the closer the values ( S11 Fig ) . This indicates that we may use genes with a large M to calculate the shape parameter . However , the larger the M , the fewer the genes with that number of different transcript isoforms . Since the simulation from the Weibull distribution W ( a = 0 . 39 ) explains the frequency distribution of each f ( k , M ) , it is reasonable to try to deduce mf ( k , M ) and the distribution of f ( k , M ) by pure mathematical theoretical deduction . A theoretical deduction requires the distribution of sums of random variables from the Weibull distribution . Unfortunately , there are currently no approximation formulae that describe the distribution of sums of Weibull random variables [35] . This renders it impossible to find a closed form formula to describe the distribution of each f ( k , M ) . It is similarly impossible to obtain formula ( 4 ) from Weibull model by theoretical deduction . Supplemental Information includes 11 figures and four tables can be found with this article online .
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Alternative RNA splicing within eukaryotic cells enables each gene to generate multiple different mature transcripts which further encode proteins with distinct or even opposing functions . The relative frequencies of the transcript isoforms generated by a particular gene are essential to the maintenance of normal cellular physiology; however , the underlying mechanisms and principles that govern these frequencies are unknown . We analyzed the frequency distribution of all transcript isoforms in highly purified human T cell subsets and built a simple mathematical model , based on the physical process of alternative splicing , which provides statistical principles that govern this process . This model matches very well with the observed distributions of expression levels and relative frequencies of all transcript isoforms from different tissues and cell lines . Notably , we used this model to elucidate many previously unexplained observations concerning transcript isoform expression . More importantly , this model reveals the existence of simple statistical principles that can be applied to understanding an essential and complex biological process such as alternative splicing .
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2017
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Stochastic principles governing alternative splicing of RNA
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The evolutionary expansion of the neocortex in mammals has been linked to enlargement of the subventricular zone ( SVZ ) and increased proliferative capacity of basal progenitors ( BPs ) , notably basal radial glia ( bRG ) . The transcription factor Pax6 is known to be highly expressed in primate , but not mouse , BPs . Here , we demonstrate that sustaining Pax6 expression selectively in BP-genic apical radial glia ( aRG ) and their BP progeny of embryonic mouse neocortex suffices to induce primate-like progenitor behaviour . Specifically , we conditionally expressed Pax6 by in utero electroporation using a novel , Tis21–CreERT2 mouse line . This expression altered aRG cleavage plane orientation to promote bRG generation , increased cell-cycle re-entry of BPs , and ultimately increased upper-layer neuron production . Upper-layer neuron production was also increased in double-transgenic mouse embryos with sustained Pax6 expression in the neurogenic lineage . Strikingly , increased BPs existed not only in the SVZ but also in the intermediate zone of the neocortex of these double-transgenic mouse embryos . In mutant mouse embryos lacking functional Pax6 , the proportion of bRG among BPs was reduced . Our data identify specific Pax6 effects in BPs and imply that sustaining this Pax6 function in BPs could be a key aspect of SVZ enlargement and , consequently , the evolutionary expansion of the neocortex .
The evolutionary expansion of the mammalian neocortex is thought to be primarily the consequence of the increasing proliferative capacity of cortical stem and progenitor cells during development [1–9] . Recent studies have progressively focused on differences between species regarding the type , abundance , and modes of division of cortical stem and progenitor cells , which are thought to contribute to the variety of shapes and sizes of the neocortex present across mammals [1–8] . A hallmark of the developing cortical wall is its apical–basal polarity , with the apical side corresponding to the ventricular surface and the basal side contacting the basal lamina [4 , 10] . At the onset of neurogenesis , neuroepithelial cells , the primary cortical stem cells , transform into apical radial glia ( aRG ) [11 , 12] . aRG , together with apical intermediate progenitors , constitute apical progenitors ( APs ) , as they repeatedly undergo mitosis at the apical surface of the cortical wall [8 , 10] . Apical intermediate progenitors ( previously called short neural precursors ) undergo self-consuming division generating two neurons [13–15] . In contrast , aRG undergo self-renewing divisions , generating neurons and , more frequently , basal progenitors ( BPs ) that delaminate from the apical surface , leave the ventricular zone ( VZ ) and move basally to the subventricular zone ( SVZ ) [16–24] . BPs comprise basal radial glia ( bRG , also called outer radial glia ) and basal intermediate progenitors ( bIPs ) [8 , 10] . BPs typically undergo mitosis in the SVZ and can undergo , in principle , neurogenic ( i . e . , neuron-producing ) or proliferative ( i . e . , self-amplifying ) divisions , albeit with profound differences in occurrence between species [8 , 16–18 , 20–22 , 25–31] . bRG can be distinguished from the process-lacking bIPs by their apically and/or basally directed processes at mitosis [8 , 17 , 18 , 21–28 , 31] . Comparison of BPs in various mammalian brains has revealed key differences in their abundance and mode of cell division [1–6 , 8 , 32–34] . Thus , such differences have been reported for bIPs , which can be classified into two principal types , neurogenic and proliferative , depending on the mode of cell division ( generating two neurons and two bIPs , respectively ) [8] . In the mouse and rat SVZ , neurogenic bIPs constitute the vast majority of BPs ( >80% ) [16–18 , 21 , 22] , whereas proliferative bIPs and bRG exist in only small proportions [17 , 28–30 , 35] . Moreover , mouse bRG typically undergo asymmetric self-renewing neurogenic divisions but not symmetric proliferative divisions [28] . By contrast , in mammals exhibiting an increased abundance of BPs and an enlarged SVZ , as characterized in detail in species such as ferret , macaque , and human [1 , 4–6 , 8 , 23 , 32] , bIPs are mostly of the proliferative type , and bRG constitute at least half of all BPs [23–27] . Moreover , in these species , both bRG and proliferative bIPs undergo mostly symmetric proliferative rather than neurogenic divisions [23 , 24 , 31] . These self-amplifying divisions significantly increase the number of BPs residing in the SVZ , consequently leading to the expansion of the SVZ . Moreover , the SVZ of these animals comprises not only a rodent SVZ-related layer called the inner SVZ ( iSVZ ) but in addition a novel layer called the outer SVZ ( oSVZ ) [32] . Importantly , these alterations in the mode of cell division and the resulting increase in BP abundance and formation of an oSVZ have been hypothesized to be major causes underlying the expansion of the neocortex [2–6 , 8 , 32] . A key question then is how these differences in BP abundance and mode of cell division between rodents and primates are brought about at the molecular level . A candidate regulatory mechanism is the differential expression of transcription factors . Of particular interest in this regard is Pax6 ( accession number: AAH36957 ) , a paired-box transcription factor [36–39] . Several mouse and rat mutant models have demonstrated that Pax6 is required for normal aRG abundance and mode of cell division [37 , 40–49] . Moreover , although Pax6 mRNA levels are generally lower in BPs than APs , this down-regulation is much greater for mouse than human [50] . Consistent with this , only a minority of mouse and rat BPs ( <30% ) show Pax6 immunoreactivity ( which is of lower level than in APs ) [3 , 51 , 52] , whereas the opposite is the case for primate , notably human , BPs ( >80% Pax6-positive ) , with essentially all bRG and the majority of bIPs containing this transcription factor [3 , 23–27 , 53 , 54] . Together , these findings raise the possibility that the differences in Pax6 expression between rodent and primate BPs may be responsible , at least in part , for the greater abundance and proliferative or self-renewal capacity of the latter . We therefore sought to maintain Pax6 expression specifically in newly generated BPs in order to investigate if such expression would increase the abundance of BPs , notably of bRG , and their proliferative or self-renewal capacity . Using a novel approach of conditional Pax6 expression [16 , 21 , 55] , we find that sustaining elevated Pax6 levels in BP-genic mouse aRG and the BP progeny derived therefrom increases both the proportion of bRG among the newly generated BPs and the self-renewing capacity of BPs .
In mouse , the aRG subpopulation that gives rise to BPs , in contrast to self-amplifying aRG , specifically expresses Tis21 , a pan-neurogenic progenitor marker [16 , 21 , 55] . Thus , as a tool towards maintaining Pax6 expression in mouse BPs , we generated a Tis21–CreERT2 knock-in mouse line . In this mouse line , exon 1 of Tis21 is replaced by CreERT2 containing a herpes simplex virus ( HSV ) tag at its C-terminus via homologous recombination ( Fig 1A; for details , see S1 Fig ) , in order to limit Cre expression to Tis21-positive cells . To assess the cellular specificity of Cre expression , Tis21–CreERT2 knock-in mice were crossed with Tis21–GFP knock-in mice [16] . Immunofluorescence of the dorsolateral telencephalon of double-transgenic mice at embryonic day ( E ) 10 . 5 , corresponding to the onset of Tis21 expression , and at E13 . 5 , corresponding to the time point at which the in utero electroporations described below were conducted , showed that Cre was expressed in essentially the same cells as GFP ( Fig 1B and 1C ) , indicating its expression selectively in the neurogenic subpopulations of cortical progenitors . Specifically , quantitation at E10 . 5 revealed that 97% of the cells containing nuclear Tis21–GFP were also positive for cytoplasmic Cre ( Fig 1D ) , and no Cre was detected in Tis21–GFP-negative cells . We next ascertained that the Tis21–CreERT2 mouse exhibits tamoxifen-dependent recombination by crossing this mouse line with a conditionally activateable GFP reporter mouse line , RCE:loxP [56] ( Fig 1E ) . In these double-transgenic mice , GFP should be expressed only when CreERT2 has been translocated from the cytoplasm into the nucleus and excised a stop cassette that prevents the transcription of the GFP mRNA; the estrogen analog tamoxifen induces such CreERT2 translocation [57] . Indeed , no GFP-positive cells were observed in the absence of tamoxifen ( Fig 1G ) . In contrast , when treated with tamoxifen ( Fig 1F ) , GFP fluorescence was observed throughout the double-transgenic mouse brain ( Fig 1I ) , and GFP-positive cells were found in all layers of the embryonic neocortex ( Fig 1I’ ) . This reflected Cre recombinase activity , because no GFP expression was observed when tamoxifen was administered to RCE:loxP offspring lacking the Tis21–CreERT2 allele ( Fig 1H ) . We conclude that Tis21–CreERT2 mouse embryos can be used to obtain tamoxifen-dependent recombination specifically in the neurogenic subpopulations of cortical progenitors . To conditionally express Pax6 in BP-genic aRG of developing neocortex , we introduced a floxed Pax6 plasmid at midneurogenesis into APs of tamoxifen-treated Tis21–CreERT2 mouse embryos . Specifically , we generated a plasmid ( referred to as Pax6-expressing plasmid ) containing a constitutive promoter ( CAG ) followed by a membrane ( GAP43 ) –GFP cassette flanked by two loxP sites , mouse Pax6 , an internal ribosome entry site ( IRES ) sequence , and nuclear RFP ( nRFP ) ( Fig 2A ) . Upon Cre-mediated recombination , the membrane–GFP cassette would be excised , leading to the simultaneous expression of Pax6 and nRFP . Introduction of this plasmid into APs of tamoxifen-treated Tis21–CreERT2 mouse embryos should ensure maintenance of Pax6 expression as mouse BPs arise from aRG divisions , as well as during their subsequent migration to , and function in , the SVZ . An identical plasmid but lacking the Pax6 and IRES sequences served as control ( Fig 2A ) . We first validated the Pax6-expressing plasmid by transfection of HEK 293T cells , a cell line in which the endogenous PAX6 gene is not expressed . Transfection with the Pax6-expressing plasmid alone resulted in GFP , but not nRFP , expression . Cotransfection of the Pax6-expressing plasmid and a Cre-expressing plasmid yielded both Pax6 and nRFP expression , whereas only nRFP expression was observed upon cotransfection of the control plasmid and the Cre-expressing plasmid ( S2 Fig ) . We then explored whether the Pax6-expressing plasmid could be used in Tis21–CreERT2 mouse embryos to obtain conditional Pax6 expression specifically in the neurogenic subpopulation of APs and their progeny . To this end , we used the in utero electroporation technique where an electric field is generated across the cortical wall in order to allow for the unidirectional delivery of the negatively charged plasmid DNA , injected into the ventricular lumen , into APs . Dorsolateral telencephalon of tamoxifen-pretreated ( E12 . 5 ) Tis21–CreERT2 mice was electroporated with Pax6-expressing plasmid at E13 . 5 and analyzed at E14 . 5 , the peak of BP generation from neurogenic aRG [22] ( Fig 2B ) . For the ease of presentation , we shall refer to this approach from here onwards simply as conditional Pax6 expression . Analysis of the Pax6 expression pattern yielded the following observations . First , analysis of the level of Pax6 immunoreactivity revealed that a subpopulation of cells had higher Pax6 immunoreactivity upon conditional Pax6 expression than in the control ( Fig 2C and 2D ) . Upon closer inspection , all these highly Pax6-immunoreactive cells were RFP-positive , indicating that these cells constituted Pax6-expressing-plasmid–electroporated neurogenic APs and their progeny ( Fig 2C , 2D and 2F ) . The level of Pax6 immunoreactivity in these cells in the VZ was approximately 3-fold higher than that of the nonelectroporated APs or control-plasmid–electroporated neurogenic APs and their VZ progeny ( Fig 2G ) , essentially all of which are known to express endogenous Pax6 [37 , 51 , 52] . In the SVZ , where mouse BPs normally down-regulate Pax6 expression [3 , 50–52] , this difference was even greater ( ≈6-fold higher ) ( Fig 2H ) . Second , the appearance of these highly Pax6-immunoreactive and RFP-positive cells upon Pax6-expressing plasmid electroporation was strictly dependent on tamoxifen pretreatment ( S3 Fig ) . Together , these observations allow us to equate the RFP-positive cells with the cells containing Pax6 due to the electroporation . To distinguish these conditionally Pax6-expressing cells from the cells expressing Pax6 endogenously , we shall refer to them from here onwards as exogenous Pax6- ( exoPax6- ) expressing cells . In addition , considering the results shown in Fig 1 , we conclude that these cells constitute specifically the neurogenic subpopulation of APs and their progeny , notably the aRG-derived BPs . Third , we found that electroporation with Pax6-expressing plasmid did not affect , after 24 h , the distribution of the progeny ( RFP+ cells ) of the electroporated neurogenic APs between ( Fig 2C–2E ) and within ( S4 Fig ) the germinal layers ( i . e . , VZ and SVZ ) . This implies that conditional Pax6 expression in neurogenic APs and their progeny , even if this expression exceeds the normal endogenous level , does not cause any overt effects on cell migration within the first 24 h after electroporation . The finding that RFP-positive cells are similarly distributed in control and upon conditional Pax6 expression allows for a valid comparison between germinal layers of the effect of conditional Pax6 expression in subsequent experiments . Conditional Pax6 expression in aRG has previously been found to induce apoptosis when pan-aRG Cre drivers based on Emx1 and hGFAP promoter and regulatory sequences were used . However , this phenomenon was not observed with a Cre driver based on Ngn2 expression [58] , which , similar ( but not identical ) to Tis21 expression , is characteristic of neurogenic progenitors [59] . It was therefore important to ascertain that conditional expression of Pax6 in Tis21–CreERT2 mice would not induce apoptosis . Indeed , immunofluorescence for the apoptosis marker activated caspase-3 did not reveal any significant difference in the number of caspase-3–positive cells between the progeny of control-plasmid–and Pax6-expressing-plasmid–electroporated neurogenic APs ( S5 Fig ) . We therefore conclude that the present approach of conditional Pax6 expression is suitable to maintain high levels of Pax6 expression specifically in neurogenic APs and their progeny , notably the aRG-derived BPs , thus recapitulating the Pax6 expression pattern observed in BPs of developing primate neocortex . In assessing the functional consequences of sustained Pax6 expression in BPs , we sought to obtain initial clues as to the identity of the progeny of the Pax6-electroporated neurogenic APs . Using the cycling cell marker Ki67 , we first investigated whether the exoPax6-expressing cells exhibited the same proportion of progenitors versus neurons as control cells ( Fig 2I–2K ) . Whereas conditional Pax6 expression did not alter the percentage of Ki67-positive cells in the VZ , it did result in a significant increase in Ki67-positive cells in the SVZ ( Fig 2K ) . This suggested that the conditional Pax6 expression increased the population of cycling BPs derived from electroporated aRG . We noticed in some experiments that in both control and conditional Pax6 expression , more Ki67-positive cells were observed in the basal region of the SVZ , and in particular in the intermediate zone of the electroporated area , but not in the contralateral area nor in nonelectroporated dorsolateral telencephalon . This reflected a previously described side effect of in utero electroporation , that is , the displacement of some Pax6-positive cells towards the cortical plate [60] . Importantly , this side effect does not affect the findings described in the present study for three reasons . First , all our data are comparisons between control and conditional Pax6 expression , both of which involve identical conditions of in utero electroporation . Second , all our quantifications are confined to electroporated , RFP-positive cells , and the electroporation side effect has been reported to affect mainly nonelectroporated cells [60] . Third , our quantifications of cells in the SVZ exclude cells in the intermediate zone . To gain further insight into a possible regulation of the cell cycle of cortical progenitors by conditional Pax6 expression , we examined specific cell cycle parameters . We first examined the effect of conditional Pax6 expression on the total cell cycle length ( Tc ) of neurogenic aRG by performing live imaging on E14 . 5 organotypic slices prepared from control or Pax6-expressing plasmid–electroporated brains . The time period between two successive aRG mitoses was taken to indicate the length of the cell cycle , Tc . In both control and conditional Pax6 expression , we observed no major difference in Tc , although there was a trend for a shorter Tc upon conditional Pax6 expression ( control , 21 . 0 ± 3 . 3 h , n = 8 cells versus Pax6 , 18 . 5 ± 1 . 2 h , n = 9 cells , S1 Table top ) . To estimate the proportion of the progeny of control-plasmid–and Pax6-expressing-plasmid–electroporated neurogenic APs that were in S-phase , we performed pulse-labeling with the thymidine analog EdU one hour before analyzing the embryos at E14 . 5 . This revealed that a significantly greater proportion of the exoPax6-expressing progeny than of the control progeny was in S-phase , in both the VZ and SVZ ( Fig 3A–3C ) . Given that conditional Pax6 expression did not increase the population size of cycling APs ( Fig 2K ) , nor alter much their Tc ( S1 Table top ) , the increase in the proportion of cells in S-phase in the VZ ( Fig 3C ) likely reflected a greater share of S-phase in the AP cell cycle , rather than an increase in cycling APs as such . To address this directly , we performed a dual pulse chase experiment as previously described [61] ( see S6A Fig and Materials and Methods ) in order to determine the length of S-phase . We observed a significant increase in the length of S-phase for the sum of the electroporated aRG and their progeny upon conditional Pax6 expression ( S6 Fig ) . We further corroborated this by analyzing the pattern of immunofluorescence of the cycling cell marker proliferating cell nuclear antigen ( PCNA ) . Like other cycling cells , cortical progenitors in S-phase show a punctate nuclear PCNA pattern , whereas progenitors in G1 and G2 show diffuse nuclear PCNA immunoreactivity [23 , 52 , 62] . Based on punctate PCNA staining , we observed a proportion of neurogenic APs in S-phase upon control electroporation that was similar to previously published data on E14 . 5 Tis21-positive APs [52] ( S1 Table middle ) . Conditional Pax6 expression , however , was found to significantly increase the percentage of PCNA-positive nuclei in the VZ that showed a punctate pattern ( Fig 3D–3F ) , i . e . , increased the proportion of neurogenic APs that were in S-phase . These findings , together with the Ki67 ( Fig 2K ) and EdU ( Fig 3C ) data , imply that conditional Pax6 expression increases the relative proportion of S-phase within the AP cell cycle . As there was no significant difference in Tc but an increase in the proportion of cells in S-phase upon conditional Pax6 expression in Tis21-positive APs , we hypothesized that the G1-phase must have been shortened to compensate for the longer S-phase . Consistent with this hypothesis , a significantly smaller proportion of the exoPax6-expressing progeny in the VZ than of the control progeny of electroporated neurogenic APs was positive for cyclin D1 , a cyclin that is expressed from mid- to late-G1 ( Fig 3G–3I ) . To estimate the length of the G1-phase , we combined the data obtained from live imaging with the punctate PCNA staining data ( S1 Table bottom ) . As none of the apical mitoses observed lasted for >1 h and no difference in G2 length was reported between neural progenitors [52] , we assumed that the proportion of neurogenic aRG in G2- and M-phase remained unchanged upon conditional Pax6 expression . Similar to the data obtained for cyclin D1 ( Fig 3I ) , we estimated a shorter G1-phase upon conditional Pax6 expression ( control 15 . 6 h versus Pax6 12 . 8 h , S1 Table bottom ) . As to BPs , the increase in the proportion of EdU-positive cells in the SVZ upon conditional Pax6 expression ( Fig 3C ) was consistent with that of Ki67-positive cells ( Fig 2K ) , corroborating our conclusion that the population size of cycling BPs derived from electroporated aRG was increased under this condition . Further support for this population size increase was provided by immunofluorescence for phosphohistone H3 , a marker of cells in late G2- and M-phase , which revealed a significant increase in mitotic BPs derived from electroporated aRG ( Fig 3J–3L ) . Also in the case of BPs , conditional Pax6 expression significantly increased the relative proportion of S-phase within the cell cycle as revealed by the pattern of nuclear PCNA immunoreactivity ( Fig 3D–3F ) , albeit not at the expense of decreasing the relative proportion of G1 ( Fig 3I ) . Our group previously reported a difference in S-phase length between Tis21- positive and Tis21-negative APs [52] . As Tis21-negative and Tis21-positive APs differ in the type of division ( symmetric versus asymmetric ) and progeny produced ( APs versus BPs ) [16 , 55] , we wondered whether the increase in the relative proportion of S-phase within the cell cycle of the exoPax6-expressing APs ( Fig 3F ) may be indicative of an alteration in their mode of division . To explore this possibility , we investigated the nature of the cycling BPs that were increasingly observed upon conditional Pax6 expression ( Fig 2I–2K ) by examining the expression of two characteristic transcription factors , Tbr2 ( Fig 4A–4C ) and Sox2 ( Fig 4D–4F ) . Tbr2 is typically expressed by the differentiating progeny of Tis21-expressing aRG fated to become bIPs [22 , 51 , 52 , 63] , whereas Sox2 expression is characteristic of aRG and bRG [23 , 24 , 26 , 28 , 29 , 31 , 64] . Upon conditional Pax6 expression , analysis for the abundance of Tbr2-positive cells revealed a significant reduction in the exoPax6-expressing progeny as compared to control ( Fig 4A–4C ) . This reduction was largely accounted for by the decrease in Tbr2-positive cells in the SVZ , most of which presumably were bIPs ( Fig 4C ) . Conversely , the abundance of Sox2-positive cells was higher in the exoPax6-expressing progeny as compared to the control ( Fig 4D–4F ) . Remarkably , this increase occurred in the SVZ rather than the VZ ( Fig 4F ) . This suggested that conditional Pax6 expression , which increased the population of BPs ( Fig 2K ) , induced Tis21-expressing aRG to increasingly generate BPs with a radial glia-characteristic transcription factor expression ( i . e . , bRG ) , at the expense ( at least relatively ) of bIP production . To directly investigate a possible effect of conditional Pax6 expression on the mode of cell division of neurogenic APs , we performed a daughter cell pair assay [65] by analyzing areas of dorsolateral telencephalon that contained only a few RFP-positive cells in the VZ 24 h after electroporation . Tbr2 immunofluorescence allowed us to distinguish three types of RFP+ daughter cell pairs: ( 1 ) Tbr2–/Tbr2– ( no bIP daughter cells ) , ( 2 ) Tbr2+/Tbr2– ( 1 bIP daughter cell ) and ( 3 ) Tbr2+/Tbr2+ ( 2 bIP daughter cells ) ( Fig 4G ) . Importantly , virtually all Tbr2– daughter cells in the VZ are likely to be radial glia , either aRG or newborn bRG , based on the following considerations . Essentially all daughter cell nuclei in the VZ were PCNA-positive ( S7 Fig ) . This was in line with the findings that >80% and almost 90% of the progeny in the VZ that was derived from electroporated neurogenic APs were Ki67+ ( Fig 2K ) and Sox2+ ( Fig 4F ) , respectively . Hence , the Tbr2– daughter cells were radial glial progenitors rather than neurons . Consistent with this , almost all cells in the mouse E14 . 5 VZ are cycling [52] , and very few of them are newborn neurons [52] . Quantification of daughter cell pairs in the VZ showed that in the control , the majority ( 77% ) of these pairs derived from AP divisions that had generated bIPs . Specifically , 56% of divisions were asymmetric ( and presumably self-renewing ) ( Tbr2+/Tbr2– , Fig 4H , red ) , and 21% symmetric self-consuming ( Tbr2+/Tbr2+ , Fig 4H , green ) . These findings were in line with the fact that the progeny specifically of neurogenic APs was analyzed . Of note , only 23% of divisions did not generate any bIPs and hence were presumably symmetric proliferative with regard to the radial glia nature of the daughter cells ( Tbr2–/Tbr2– , Fig 4H , blue ) . In contrast , upon conditional Pax6 expression , the majority ( 59% ) of the daughter cell pairs were derived from neurogenic AP divisions that did not generate bIPs but radial glia ( Tbr2–/Tbr2– , Fig 4H , blue ) . This occurred at the expense of bIP-generating divisions , that is , asymmetric self-renewing divisions ( Tbr2+/Tbr2– , reduced to 32% , Fig 4H , red ) , and symmetric self-consuming divisions ( Tbr2+/Tbr2+ , reduced to 8% , Fig 4H , green ) . The observations that conditional Pax6 expression increased ( i ) the non-bIP generating divisions ( Tbr2–/Tbr2– , Fig 4H , blue ) and ( ii ) the Sox2-positive progeny in the SVZ ( Fig 4F ) suggested that the former progeny increasingly consisted of newborn bRG . As bRG are known to delaminate from the ventricular surface [24–27 , 31 , 35] , we explored whether the radial glia progeny in the VZ observed upon conditional Pax6 expression increasingly showed signs of delamination . To this end , we measured the distance of the ventricular-most nucleus of each Tbr2–/Tbr2– daughter cell pair from the ventricular surface ( Fig 4I ) . In light of the observation that the mean distance of the ventricular-most nucleus of the control and exoPax6-expressing Tbr2+/Tbr2– and Tbr2+/Tbr2+ daughter cell pairs was always >40 μm ( S8 Fig ) , whereas that of the Tbr2–/Tbr2– pairs was <26 . 5 μm ( Fig 4I , S8 Fig ) , we focused our attention on the abundance of the ventricular-most nuclei of Tbr2–/Tbr2– daughter cell pairs with a distance from the ventricular surface of ≥27 μm ( corresponding to >3 nuclear diameters and referred to as abventricular location [16] ) . Whereas only 1 of the 7 ventricular-most nuclei ( 14% ) of the Tbr2–/Tbr2– daughter cell pairs in the control was found in an abventricular location , 7 of the 15 nuclei ( 47% ) analyzed upon conditional Pax6 expression were abventricular ( Fig 4I ) . This suggested that conditional Pax6 expression promoted a substantial proportion of the radial glia progeny derived from neurogenic AP divisions to delaminate from the ventricular surface , as would be expected for newborn bRG . In species with a high abundance of bRG in the SVZ , the radial thickness of the VZ decreases concomitant with bRG generation [8 , 23 , 25–27 , 64] . In light of the findings described above , we investigated a possible reduction in VZ thickness upon conditional Pax6 expression by quantifying the total number of nuclei ( both RFP–and RFP+ ) in the VZ within a 200-μm wide , electroporated region of the dorsolateral telencephalon . Indeed , we observed a significant , approximately 10% , reduction in the number of nuclei in the VZ upon conditional Pax6 expression ( Fig 4J ) . The magnitude of this reduction was consistent with the efficiency of electroporation and the estimated increase in the proportion of the progeny of electroporated neurogenic APs that delaminated upon conditional Pax6 expression as compared to control ( Fig 4H ) . Taken together , the findings presented so far strongly suggest that mouse neurogenic APs and their progeny that constitutively express Pax6 increasingly generate bRG at the expense of generating bIPs . To corroborate and complement these findings , we next investigated the effect of conditional Pax6 expression on the proportion of bRG in the BP progeny of electroporated aRG . To this end , we analyzed the morphology of mitotic BPs using phosphovimentin immunofluorescence ( Fig 5A–5C ) , which stains both the cell bodies and processes of mitotic cortical progenitors [66] . bRG characteristically extend basally and/or apically directed processes [23–29 , 31 , 35] , whereas bIPs do not [17 , 18 , 21–26 , 28 , 35] . As the apically directed processes have been reported to be thinner than basal processes and may not be easily detected via phosphovimentin staining [23] , we focused our analysis on basal process-bearing mitotic BPs . In the control , the vast majority ( 91% ) of mitotic BPs were nonpolar and only a small minority ( 9% ) extended a basal process ( Fig 5C ) , consistent with the high abundance of bIPs and low abundance of bRG in the embryonic mouse SVZ [28 , 29 , 35] . In contrast , upon conditional Pax6 expression , we observed a more than 2-fold increase in the proportion of mitotic BPs with a basal process , i . e . of bRG within the BP population ( 23% , Fig 5C ) . These data show that , concomitant with the increase in the proportion of BPs among the aRG progeny ( Fig 2K ) , conditional Pax6 expression more than doubled the proportion of bRG within these BPs . As the apically-directed process of bRGs may be harder to detect via phosphovimentin immunofluorescence at mitosis [23] , we next investigated the diversity of bRG morphology during interphase . To do this , we made use of the residual membrane-GFP ( Fig 2A ) expressed presumably due to incomplete Cre recombination ( see Materials and Methods , live imaging ) ( Fig 5D and 5E ) . To distinguish bRG from migrating neurons , we stained for Sox2 , which is expressed in radial glia but not in neurons . In the control , all of the bRG progeny of the electroporated neurogenic APs exhibited a basal process , and 40% of them an apically-directed process as well ( Fig 5F ) . Upon conditional Pax6 expression , we found an increase in the proportion of bRG exhibiting both basally and apically directed processes ( Fig 5E and 5F , 53% ) and also observed bRG with an apically directed process only ( Fig 5D and 5F , 7% ) . Interestingly , in the macaque , bRG with both processes and bRG with an apically directed process only have been reported to have a higher self-renewing capacity as compared to bRG with a basal process only [23] . Of note , the basal process of the bRG generated upon conditional Pax6 expression sometimes extended all the way to the pia ( S9A Fig ) . The bRG generated upon conditional Pax6 expression were nestin-positive ( S9B Fig ) , could be Tbr2-negative ( S9C Fig ) , and typically exhibited a perinuclear centrosome ( S9D Fig ) . Furthermore , these cells underwent mitotic somal translocation , in which the cell soma moves rapidly in the basal or apical direction prior to mitosis [23 , 26 , 28 , 31] , as revealed by live time-lapse imaging ( S9E Fig ) . The data presented so far show increased bRG generation upon elevating Pax6 levels in neurogenic aRG and sustaining it in the BPs derived therefrom . We sought to complement these findings by a converse , loss-of-function , approach . To this end , we investigated the proportion of mitotic ( phosphovimentin-positive ) bRG among BPs in the dorsolateral telencephalon of E14 . 5 homozygous small eye ( Sey ) mutant mice , which lack functional Pax6 because of a mutation that generates a premature translational stop codon ( Fig 5G–5I ) . We found a significant reduction in the percentage of bRG as compared to littermates that have at least one copy of the Pax6 gene ( Fig 5I ) . These data indicate that although Pax6 function is not absolutely required for bRG generation , its level of expression is crucial for determining the abundance of these cells in the developing mouse neocortex . Ferret and primate bRG are known to undergo multiple rounds of self-renewing division [23–26 , 31] , whereas bIPs in mouse and rat embryonic neocortex typically undergo one round of self-consuming division [16–18 , 20–22] . In light of the increase in cycling BPs ( Fig 2K ) and bRG ( Fig 5C ) upon conditional Pax6 expression , it was therefore of interest to investigate whether conditional Pax6 expression would subsequently lead to increased cell cycle re-entry of the BP progeny derived from electroporated aRG . To this end , a single pulse of EdU was administered at 24 h after electroporation and analyzed after an additional 24 h for the proportion of cycling , Ki67-positive cells among the EdU-labeled progeny of electroporated APs , in order to identify cells that had re-entered the cell cycle ( Fig 6A ) . In the control , 75% of such daughter cells present in the VZ , but only 23% of such daughter cells in the SVZ , had re-entered the cell cycle ( Fig 6B and 6D ) . In contrast , upon conditional Pax6 expression , whereas daughter cell cycle re-entry was the same in the VZ , it nearly doubled in the SVZ ( 41% , Fig 6C and 6D ) . Again , we used the residual membrane-GFP fluorescence to determine the morphology of daughter cells that had re-entered the cell cycle . Two types of such daughter cells were observed , monopolar cells with a distinct basal process ( Fig 6E ) , i . e . , bRG , and multipolar cells with short extensions during interphase ( Fig 6F ) , presumably bIPs . We extended these data by analyzing the fate of the progeny derived from divisions of bRG , using live time-lapse imaging for at least 48 h of organotypic slices prepared from control and Pax6-expressing plasmid-electroporated E14 . 5 neocortex ( Fig 7A ) . Despite the rare occurrence of bRG in mouse neocortex , we were able to identify several RFP-positive bRG , to image their divisions , and to track their progeny for at least an additional 20 h ( i . e . , for a time period longer than the average Tc of self-renewing bRG ( see S2 Table ) ) . In the control , in two out of the seven cases analyzed , the mitotic bRG underwent an asymmetric self-renewing division , as one of the daughter cells was observed to re-enter the cell cycle ( S10 Fig ) . In the other five cases , similar to what has been previously reported for the embryonic mouse brain [28] , both daughters did not enter mitosis during the time of our observations ( S10 Fig ) . Upon conditional Pax6 expression , half of the mitotic exoPax6-expressing bRG ( three out of six ) gave rise to progeny that subsequently underwent another round of cell division ( S10 Fig ) . In two cases , these bRG divisions were asymmetric self-renewing ( S10 and S11 Figs , S1 Movie ) . Remarkably , we also observed a bRG undergoing a symmetric proliferative division ( Fig 7 , S10 Fig , S2 Movie ) , with both daughters undergoing another round of cell division . These live imaging data are consistent with the notion that bRG generated upon conditional Pax6 expression and their progeny are endowed with greater proliferative potential as compared to control . Moreover , together with the cell cycle re-entry analysis ( Fig 6 ) , these data suggest that BPs show an increased proliferative capacity upon conditional Pax6 expression . It has been reported that a nonvertical ( i . e . , oblique or horizontal ) cleavage plane orientation in relation to the ventricular surface of dividing APs ( for examples , see Fig 8A ) increases the probability that daughter cells become bRG [24 , 31 , 35 , 64] . We investigated whether the increased generation of bRG upon conditional Pax6 expression involved such alterations in cleavage plane orientation . In the control , the vast majority ( 91% ) of mitotic neurogenic APs showed a vertical , and only a small minority ( 9% ) an oblique , cleavage plane orientation ( Fig 8B ) , consistent with previous data on Tis21-expressing APs [21 , 67 , 68] . Strikingly , conditional Pax6 expression resulted in a significant increase in nonvertical cleavage planes in mitotic neurogenic APs ( 19% , Fig 8B ) . As this doubling matched the doubling in the proportion of bRG among BPs ( Fig 5C ) , our observations suggest that the increase in nonvertical cleavage plane orientations of neurogenic APs upon conditional Pax6 expression ( Fig 8B ) causally contributed to the increased generation of bRG ( Fig 4F and 4H , Fig 5C ) . The doubling in cell cycle re-entry of BPs upon conditional Pax6 expression ( Fig 6D ) matched the doubling of bRG ( Fig 5C ) , which in primates are endowed with constitutive cell cycle re-entry capacity [23 , 24 , 26] . However , the morphology of the BPs that had re-entered the cell cycle ( Fig 6E and 6F , Fig 7 ) raised the possibility that the increased cell cycle re-entry of BPs upon conditional Pax6 expression ( Fig 6D ) may not only be due to the increase in the proportion of bRG ( Fig 5C ) but may in addition reflect an increased cell cycle re-entry of bIPs ( Fig 6F , Fig 7 ) . Moreover , inducing mouse Tbr2-positive BPs to re-enter the cell cycle by forced premature expression of the transcription factor Insm1 has been shown to be associated with an alteration in their cleavage planes from the normal near-random [21 , 24 , 63] to mostly horizontal orientations [63] . Finally , not only human bRG are thought to divide preferentially with a near-horizontal cleavage plane [24] but also Tbr2-positive progenitors in the human SVZ , which , like their macaque counterpart [23] and in contrast to mouse bIPs , are endowed with proliferative capacity [26] and show a near-horizontal cleavage plane orientation in the majority of cases [25] . These considerations prompted us to investigate whether conditional Pax6 expression , concomitant with increasing the cell cycle re-entry of the mouse BPs derived from electroporated aRG , would perhaps increase the proportion of horizontal cleavages of these BPs ( for examples of vertical , oblique , and horizontal BP cleavage planes in relation to the ventricular surface , see Fig 8C ) . In the control , the BP progeny derived from neurogenic aRG showed a random cleavage plane orientation at mitosis ( Fig 8D ) , consistent with previously published data [21 , 63] . Interestingly , conditional Pax6 expression caused an increase ( albeit not statistically significant ) in the proportion of the BP progeny that divided with a horizontal cleavage plane , decreasing the proportion of oblique cleavage planes ( Fig 8D ) . Given that conditional Pax6 expression increased not only the proportion of bRG among the BP progeny derived from electroporated neurogenic aRG ( Fig 5C ) but also the proliferative capacity of this progeny in general ( Fig 2K , Fig 6D ) , our cleavage plane data are consistent with the notion that a horizontal cleavage plane may be a hallmark of BPs endowed with self-renewal capacity , that is , bRG and proliferative bIPs [24 , 31 , 63] . As conditional Pax6 expression increased the proliferative capacity of the BP progeny of neurogenic aRG and the proportion of bRG among these BPs , we finally investigated the consequences for cortical neurogenesis . To this end , we administered EdU 10 h after electroporation , at ≈E14 . 0 , i . e . , around the start of exo-Pax6 expression , in order to label the neuronal progeny born at this midneurogenesis stage , followed by their analysis in the cortical wall at E17 . 5 ( Fig 9A ) . We first quantified the population size of the total progeny at E17 . 5 . Compared to E14 . 5 , this progeny population size was increased in both the control ( 1 . 6-fold ) and upon conditional Pax6 expression ( 2 . 1-fold ) , with the latter increase being significantly greater than the former ( Fig 9D and 9E ) . This indicated that conditional Pax6 expression increased the total cell output observed at E17 . 5 . Of note , in the control , the majority ( 68% ) of the progeny had migrated to the cortical plate ( S12A and S12D Fig ) . In contrast , in the case of conditional Pax6 expression , this was observed for only approximately one third ( 31% ) of the progeny , the majority of which exhibited heterotopia in the intermediate zone ( S12B and S12D Fig ) . Strikingly , most of the heterotopia cells had a much higher level of Pax6 immunoreactivity than those that had reached the cortical plate ( S12C and S12E Fig ) . These observations are consistent with previous findings in Pax6-overexpressing mouse models , in which aggregates of Pax6-overexpressing cells in the developing cortical wall have been described [58] . Further characterization of the progeny exhibiting heterotopia showed that these cells were immature neurons ( S13 Fig ) . Next , we analyzed the neuronal fate of the progeny that had migrated to the cortical plate . To distinguish between deep-layer and upper-layer neurons , we made use of established markers , the transcription factor Tbr1 , which labels layer V and VI neurons , and the transcriptional regulators Satb2 and Brn2 , which label layer II–IV neurons [69] . Conditional Pax6 expression reduced the proportion of EdU-labeled Tbr1-positive neurons originating from the electroporated neurogenic aRG ( Fig 9B , 9C and 9F ) . Conversely , the proportion of EdU-labeled neurons that expressed Satb2 was increased ( Fig 9G–9I ) . Similarly , the percentage of Brn2-positive cells among the neuronal progeny was significantly increased upon conditional Pax6 expression ( Fig 9J ) . Together with the overall increase in progeny observed at E17 . 5 ( Fig 9D and 9E ) , these data show that conditional Pax6 expression at midneurogenesis increases the generation of upper-layer neurons . This likely reflected the increase in BP proliferative capacity ( Fig 2K , Fig 6D , Fig 7 , S10 Fig ) and relative bRG abundance ( Fig 4F , Fig 5C ) upon conditional Pax6 expression . We complemented and extended the data obtained by the conditional Pax6 expression using in utero electroporation by taking a double-transgenic approach . Specifically , we crossed the Tis21–CreERT2 mice with JoP6 mice [58] . Like the Pax6-expressing plasmid , JoP6 mice contain , under a constitutive promoter , a floxed GFP-stop cassette followed by Pax6 , an IRES sequence and a reporter [58] . Upon Cre recombination induced by tamoxifen administration at E13 . 5 ( Fig 10A ) , Pax6 will be expressed at elevated levels in neurogenic aRG , and this expression sustained in their progeny throughout the embryonic neocortex . With this approach , similar to the results obtained upon the conditional Pax6 expression via in utero electroporation of Tis21–CreERT2 mouse embryos ( Fig 9 ) , upper-layer neurons as identified by Satb2 and Brn2 expression were significantly increased when compared to control littermates ( Fig 10D and 10E ) . By contrast , deep-layer neurons as identified by Tbr1 expression were not affected ( Fig 10F ) . Strikingly , with this double-transgenic approach ( Fig 10A ) , we did not observe the heterotopia seen upon conditional Pax6 expression using in utero electroporation ( S12B Fig ) . This may reflect the more standardized way in which elevated and sustained Pax6 expression is achieved in the double-transgenic embryos . In ferret and primate neocortex , the increase in proliferating BPs is accompanied by an expansion of the SVZ in the basal direction , that is , an increase in BPs residing in the oSVZ , the key basal-most germinal layer characterized by lesser cell density [4–6 , 8 , 32] . To explore whether the Tis21–CreERT2: JoP6 double-transgenic approach resulted in an increase in BPs residing in cortical low-cell-density layers basal to the mouse SVZ proper , that is , the intermediate zone and subplate , we examined the distribution of the cell proliferation marker Ki67 . Whereas there was no significant difference in the abundance of Ki67-positive cells between control ( Tis21–CreERT2+/–: JoP6–/– ) and Pax6-overexpressing ( Tis21–CreERT2+/–: JoP6+/– ) neocortex in the VZ , we observed a significant increase in Ki67-positive cells not only in the SVZ , but also in the intermediate zone and subplate of Pax6-overexpressing mouse neocortex ( Fig 10B , 10C and 10G ) . It is therefore interesting to note that the increase in progenitors residing in cortical low-cell-density layers basal to the SVZ of embryonic mouse neocortex observed with the Tis21–CreERT2: JoP6 double-transgenic approach of Pax6 overexpression is reminiscent of one of the features of the ferret and primate oSVZ .
BPs endowed with proliferative capacity , notably bRG , are a hallmark of the developing primate neocortex [1–6 , 8 , 23 , 34 , 70] . Here we show that a single transcription factor , Pax6 , when specifically sustained in the aRG-to-BP lineage , is sufficient to generate such BPs ( Fig 11 ) . Our study differs in key aspects from previous studies in which Pax6 expression was increased in APs of dorsolateral telencephalon , as the latter either did not observe or address effects on BPs [48 , 58 , 71] , or obtained opposite results [46] . Specifically , increased Pax6 expression was previously found to increase the mRNA levels for the bIP marker Tbr2 in the VZ and SVZ [46] . In contrast , in the present study , we found a decrease of Tbr2-positive BPs in the SVZ and nascent BPs in the VZ upon conditional Pax6 expression . Our observations are consistent with the increased generation of proliferative BPs , notably bRG . These differences in results presumably reflect the fact that in the previous study , Pax6 expression was increased in all APs , whereas in the present study , conditional Pax6 expression was confined to Tis21-positive , that is , neurogenic and BP-genic , APs and their progeny . Our findings have three significant implications for elucidating the evolutionary expansion of the neocortex . First , they reveal a key role of Pax6 in the generation of a primate-like SVZ , that is , of proliferative BPs from aRG . We find that the effects elicited by increased Pax6 levels on aRG mitosis and daughter cell fate in embryonic mouse neocortex reproduce the normal situation in fetal human neocortex , which is characterized by higher Pax6 levels in human than mouse aRG ( S14 Fig ) . Specifically , increasing Pax6 levels in mouse BP-genic aRG increased their oblique cleavage plane orientation at the expense of vertical cleavage plane orientation ( Fig 11 ) , consistent with previous studies reporting a greater proportion of oblique and horizontal cleavages in human [24] than mouse [19 , 35 , 67 , 68 , 72 , 73] aRG . This alteration in cleavage plane orientation may well have been promoted by the fact that conditional Pax6 expression was selective for BP-genic aRG , which are more susceptible to spindle orientation variability due to the reduction of apical and basal astral microtubules as compared to proliferative aRG [67] . The increased oblique cleavage plane orientation of BP-genic aRG likely caused , in line with previous findings [35] , the observed increase in ( i ) self-consuming bRG-genic divisions of mouse aRG at the expense of self-renewing bIP-genic divisions and ( ii ) aRG daughter cell delamination , and consequently ( iii ) the decrease in mouse VZ thickness . Taken together , our findings provide a mechanistic explanation for the reduction in VZ thickness that occurs concomitant with the growth of the oSVZ during the progression of cortical neurogenesis in species with an enlarged neocortex [8 , 23 , 25–27 , 32 , 64] . As to the mechanism how increased Pax6 levels in BP-genic aRG promote oblique cleavage plane orientation , previous work has identified an intriguing Pax6 target gene—the mitotic spindle—and kinetochore-associated protein Spag5 [47] . An increase in nonvertical cleavage plane orientation of mouse aRG has been observed both upon knock-down of Spag5 and when Spag5 mRNA and protein levels in Pax6 mutant mice at midneurogenesis are elevated [47] , suggesting that either too low or too high Spag5 levels perturb the normal , horizontal spindle orientation that is required for aRG vertical cleavage plane orientation . This is in line with the concept that for aRG , a horizontal spindle orientation is thought to reflect the active state of the mitotic spindle orientation machinery , and nonhorizontal spindle orientations can occur upon perturbation of this machinery [19 , 35 , 67 , 72 , 73] . By contrast , for mouse BPs , a default state of the mitotic spindle orientation machinery , with random cleavage plane orientations , is thought to be the normal situation [21 , 24 , 63] , and activation of this machinery is thought to promote horizontal cleavage plane orientation . Such orientation prevails in primate BPs , notably bRG , which are endowed with much greater proliferative capacity than mouse BPs [23–26] and is increasingly observed when mouse BPs are induced to proliferate [63] . In this context , it is interesting to note that ( i ) the relative Spag5 mRNA levels are much higher in the human iSVZ and oSVZ than the mouse SVZ [50] , and ( ii ) increasing the Pax6 level in mouse BPs , which likely results in increased Spag5 levels , was found here to increase their horizontal cleavage plane orientation . Taken together , the concept emerges that Pax6 , via its downstream targets including Spag5 , increases oblique , self-consuming aRG divisions generating proliferative BPs , notably bRG , and horizontal BP divisions promoting their proliferation or self-renewal . Second , we observed that sustaining high Pax6 expression in BPs increases their cell cycle re-entry ( Fig 6 ) and their abundance not only in the SVZ but even in the layers basal to the SVZ , the intermediate zone and subplate ( Fig 10 ) . This finding implies that the maintenance of expression of Pax6 in primate , but not mouse and rat , BPs , notably bRG , is a key feature of the machinery underlying their greater proliferative or self-renewal capacity [23–26] . It thus appears that Pax6 has the potential to promote proliferation and self-renewal of cortical progenitors in general , that is , for both APs [38 , 39 , 74] and BPs ( this study ) . Conversely , as we observed a marked decrease in bRG in the dorsolateral telencephalon of Sey mouse embryos ( Fig 5G–5I ) , it would be interesting to explore whether a similar decrease in bRG is observed in human embryonic stem cell-derived organoids [75] upon PAX6 knockdown after establishment of the SVZ . As a corollary , the molecular mechanisms underlying the sustained Pax6 expression in BPs , at the level of mRNA and protein generation and stability [76–83] , then become the crucial issue for SVZ enlargement and neocortex expansion . The increased cell cycle re-entry of BPs observed here upon sustained Pax6 expression is in contrast to the previously reported increase in cell cycle exit of cortical progenitors in Pax6 overexpressing ( PAX77 ) mice [48] . Again , this discrepancy presumably reflects the difference between conditional Pax6 overexpression selectively in BP-genic APs ( present study ) and constitutive Pax6 overexpression in all APs [48] . As to the downstream targets of Pax6 that promote BP proliferation or self-renewal , at least two candidates exist . One is the transcription factor Sox2 , a well-known stimulator of stem and progenitor cell proliferation and self-renewal [38 , 59 , 84] . Pax6 has been shown to induce Sox2 expression [85] , and consistent with this , we observed that sustaining Pax6 expression in the aRG–BP lineage indeed increases the proportion of Sox2-positive BPs . The other class of candidates are extracellular matrix ( ECM ) constituents and their receptors , the integrins , which have been implicated in BP proliferation and self-renewal [25 , 50 , 52 , 62 , 86] . Interestingly , Pax6 induces the expression of ECM constituents such as tenascin-C [87] and integrin α5β1 [88] . Hence , the increased cell cycle re-entry of BPs upon sustained Pax6 expression may well reflect , at least in part , an altered , more human-like , microenvironment in the mouse SVZ that is now more conducive to BP proliferation and self-renewal . Third , the increased proliferative capacity of mouse BPs achieved by sustained Pax6 expression resulted in a phenotypic change in the cortical plate that is characteristic of primates—an increase in upper-layer neurons ( Figs 9 and 10 ) . Also , this aspect of the present phenotype is in contrast to previous findings which showed , concomitant with increased progenitor cell cycle exit , an increase in deep-layer neurons at the expense of upper-layer neurons in the constitutively Pax6 overexpressing PAX77 mice [48] . It should be noted that conditional Pax6 expression in neurogenic aRG resulted in an increase in Pax6 levels that was substantially greater than that in human as compared to mouse APs ( compare Fig 2G and S14 Fig ) . Moreover , upon the present approach of conditional expression , which used a constitutive promoter , Pax6 was found to be present even in neurons ( S12 Fig ) . It is therefore comprehensible that the present approach of conditional Pax6 expression via in utero electroporation in embryonic mouse neocortex has phenotypic consequences , some of which are not observed in fetal human neocortex and upon more controlled Pax6 expression in the double-transgenic mouse ( Fig 10 ) , such as the heterotopia which consisted mostly of highly Pax6-positive immature neurons ( S12 and S13 Figs ) . Hence , considering all aspects of the present phenotype together , sustaining Pax6 expression in BP-genic aRG and the BPs derived therefrom , as is characteristically the case in fetal primate neocortex [23–27 , 50] , is sufficient to induce primate-like progenitor behaviour in embryonic mouse neocortex , that is , ( i ) translocation of progenitors from the VZ to the SVZ , ( ii ) an increased proportion of bRG among the BPs generated , ( iii ) sustained proliferation or self-renewal of BPs in the SVZ , and ( iv ) an increased upper-layer neuron production . The differential regulation of Pax6 expression in cortical progenitors during development across mammals therefore emerges as a key issue of future studies aiming to understand the evolutionary expansion of the SVZ , and consequently the neocortex . Although sustained Pax6 expression sufficed to generate primate-like bRG in developing mouse neocortex , it was insufficient to induce cortical folding ( Figs 9 and 10 ) . This is in contrast to previous studies in which the expression of specific genes implicated in neocortex expansion led not only to the expansion of BPs but also to folding of the mouse neocortex [89 , 90] . In these studies , the expansion of BPs comprised an increase in both bRG and bIPs . Expansion of bIPs alone has been reported to be insufficient to induce cortical folding in the mouse neocortex [91] . Moreover , the presence of bRG is essential for tangential dispersion of neurons [27] in order for the basal surface to expand more than the apical surface , and ultimately for cortical folding [4 , 5 , 8 , 27] . Hence , to increase the ratio of basal to apical surface , it appears to be critical to increase the proportion of bRG among the BPs in the SVZ above a certain level . This would increase the divergence of radial fibers emanating from the SVZ , allowing for a broader dispersion of migrating neurons . Our data suggest that a mere doubling of bRG abundance in the embryonic mouse neocortex ( from 10% to 20% of all BPs ) , as was achieved by sustaining Pax6 expression , is still insufficient to result in cortical folding . On a more general note , human-specific aspects of neocortex expansion can be considered to be caused by ( i ) the presence of a relevant gene in the human as well as nonhuman genomes , but with differential regulation of expression between human and nonhuman species [50 , 89 , 92]; ( ii ) the presence of a relevant gene in the human as well as nonhuman genomes , but with human-specific alterations in the coding sequence [93 , 94]; and ( iii ) the presence of a relevant gene in the human , but not nonhuman , genomes [90] . The present study demonstrates that Pax6 , a central player in corticogenesis , can be regarded as a key example of the first scenario .
Human fetal brain tissue was obtained from the Klinik und Poliklinik für Frauenheilkunde und Geburtshilfe , Universitätsklinikum Carl Gustav Carus of the Technische Universität Dresden , following elective pregnancy termination and informed written maternal consents , and with approval of the local University Hospital Ethical Review Committees . All human fetal brain samples were anonymized . All animal experiments were performed in accordance with the German Animal Welfare legislation ( “Tierschutzgesetz” ) . All procedures pertaining to animal experiments were approved by the Governmental IACUC ( "Landesdirektion Sachsen” ) and overseen by the Institutional Animal Welfare Officer ( s ) . Mice were anaesthetised using isofluorane during the in utero electroporation procedure . Mice were killed via cervical dislocation . The license numbers concerned by the present experiments with mice are: 24–9168 . 11-9/2009-2 ( in utero work , tamoxifen , BrdU ) and 24–9168 . 24-9/2012-1 ( tissue collection without prior in vivo experimentation ) . Mice were maintained in strict pathogen-free conditions in the animal facility of the Max Planck Institute of Molecular Cell Biology and Genetics , Dresden , Germany . To characterize the Tis21–CreERT2 mouse line described below , females were crossed with either the Tis21–GFP knock-in homozygous males [16] or the RCE:LoxP line [56] . To perform the in utero electroporation experiments with heterozygous Tis21–CreERT2 embryos as described below , homozogyous Tis21–CreERT2 males were crossed with wildtype C57BL/6JOlaHSD females . For the double-transgenic mice , homozogyous Tis21–CreERT2 mice were crossed with heterozygous JoP6 mice . To study the loss of function of Pax6 on bRG generation , heterozygous Sey mice were crossed with one another . The day of the vaginal plug was defined as E0 . 5 . Tis21–GFP [16] , hACTB–Flpe [95] , RCE:LoxP [56] , and JoP6 [58] mouse lines were genotyped as previously described . Offspring from the above crossings were genotyped for the Tis21–CreERT2 allele by PCR using standard procedure as described below . To obtain pCAGGS–LoxP-GAP43-GFP-LoxP-nRFP , we first generated the intermediate plasmid pCAGGS–nRFP . RFP containing 3 C-terminal tandem SV40 nuclear localization signals ( nRFP ) was PCR-amplified using pDSV-mRFPnls [98] as template and the primer pair nRFP-forward & nRFP-reverse . The nRFP PCR product was cloned into the pCAGGS eukaryotic expression vector [99] opened with AgeI and EcoRI , yielding pCAGGS–nRFP . Subsequently , the LoxP-GAP43-GFP-LoxP cassette was PCR-amplified using a DFRS plasmid harboring GAP43-GFP [100] as template and the primer pair LoxP-GAP43-GFP-forward & LoxP-GAP43-GFP-reverse . The LoxP-GAP43-GFP-LoxP PCR product was cloned into the pCAGGS–nRFP vector opened with AgeI and XhoI , yielding pCAGGS–LoxP-GAP43-GFP-LoxP-nRFP ( Fig 2A top ) . To obtain pCAGGS–LoxP-GAP43-GFP-LoxP-Pax6-IRES-nRFP ( referred to as Pax6-expressing plasmid ) , the Pax6 and IRES sequences were amplified from DNA constructs kindly provided by Magdalena Götz [44] , using the primer pair Pax6-forward & IRES-reverse . The PCR product was cloned into the control plasmid opened with XhoI , yielding the Pax6-expressing plasmid pCAGGS–LoxP-GAP43-GFP-LoxP-Pax6-IRES-nRFP ( Fig 2A bottom ) . HEK293T cells were plated at 5x104 cells on 24-well plates and kept in culture in DMEM supplemented with 10% fetal calf serum . At 24 h after plating , cells were transfected , using 1 μl of Lipofectamine2000 ( Invitrogen ) , with 250 ng of pCAGGs-Cre [101] and/or 250 ng of either control or Pax6-expressing plasmids diluted with serum-free DMEM . Cells were incubated for 48 h , followed by fixation with 4% paraformaldehyde in 120 mM phosphate buffer pH 7 . 4 for 10 mins . The paraformaldehyde was then removed and cells were kept in PBS until further processing . Tamoxifen ( Sigma ) was dissolved in corn oil at 20 mg ml-1 . Unless specified otherwise , tamoxifen was administered orally via gavage ( 0 . 1 ml ) to pregnant dams carrying E12 . 5 embryos . This single dose was administered when animals were killed at E13 . 5 . When animals were killed at E14 . 5 , tamoxifen was administered at E12 . 5 and at E13 . 5 ( see Fig 2B ) . When animals were killed at E15 . 5 or later , tamoxifen was administered at E12 . 5 , at E13 . 5 and at E14 . 5 ( see Fig 5D and Fig 7A ) . For the Tis21–CreERT2: JoP6 experiments , tamoxifen was administered orally ( 0 . 2 ml ) to pregnant dams carrying E13 . 5 embryos . In utero electroporation was carried out essentially as previously described [100 , 102] . Briefly , tamoxifen-treated pregnant dams carrying E13 . 5 embryos were anesthesized using isofluorane . Embryos were injected intraventricularly either with 0 . 5–3 mg ml-1 control or Pax6-expressing plasmid in PBS containing 0 . 25% Fast Green ( Sigma ) using a glass micropipette followed by electroporation ( 30 V , six 50-msec pulses with 1 sec intervals ) . Electroporated brains were dissected at the indicated developmental stages and fixed for 20–70 h at 4°C in 4% paraformaldehyde in phosphate buffer for further analysis . Single EdU pulses were administered by injecting 0 . 1 ml of 1 mg ml-1 EdU intraperitoneally into pregnant dams carrying embryos of the indicated developmental stages . For the cell cycle re-entry experiments , we injected such a single pulse of EdU at E14 . 5 and sacrificed the animals 24 h later ( Fig 6A ) . At this developmental stage , the length of S+G2+M-phase of cortical progenitors is ≤11 h [52] , and a single EdU pulse is unlikely to be effective for >5 h [103] . Hence , the 24 h period between the EdU administration and analysis should be more than sufficient for essentially all cortical progenitors that incorporated EdU and that had been derived from electroporated aRG ( i . e . , that were RFP+ ) to go through M-phase , and thus for determining by Ki67 immunofluorescence whether or not the resulting daughter cells had re-entered the cell cycle . For the dual pulse chase experiments , 0 . 1 ml of 1 mg ml-1 of IdU and BrdU were sequentially injected intraperitoneally into pregnant dams carrying embryos of the indicated developmental stages ( S6A Fig ) . The length of S-phase was calculated as described previously [61] . It has previously been shown that electroporation does not randomly target APs irrespective of the phase of the cell cycle , but preferentially targets APs in late S- , G2- and M-phase [104] . Conditional Pax6 expression upon electroporation would thus be confined to a synchronized cohort of progenitors , which precludes the use of cumulative labeling with a thymidine analog to determine the length of the cell cycle and its various phases . We therefore used live imaging to measure the cell cycle length of electroporated Tis21-positive aRG . In these analyses , we have exploited the fact that the RFP+ cells still contain residual membrane-GFP fluorescence ( either by inheritance , or because not all plasmid copies electroporated into a given aRG underwent Cre recombination , or both ) . Live time-lapse imaging of dorsolateral telencephalon tissue in organotypic slice culture was prepared and carried out as previously described [67] . Stacks of 1024 x 1024 pixels x 18–21 optical sections ( xyzt sampling: 0 . 346 × 0 . 346 × 2 . 5 μm × 22 or 24 min ) were acquired for at least 48 h , using a confocal laser-scanning microscope LSM 780 equipped with a 40× C-Apochromat 1 . 2 N . A . W objective ( Carl Zeiss , Germany ) . AP divisions were defined as those occurring at the ventricular surface . The time period between two successive mitoses of the neurogenic aRG is taken to be the length of the cell cycle , Tc . In addition , we used live imaging to track the fate of the bRG progeny and for the reconstruction of the RFP-positive bRG lineage tree . We defined bRG divisions as those occurring away from the ventricular surface ( with no apical contact ) and as BPs exhibiting a basally and/or apically directed process just prior to , and often persisting through , mitosis . We included only RFP-positive bRG that had undergone division and tracked their progeny for at least an additional 20 h ( i . e . , for a time period longer than the average Tc of self-renewing bRG ) . For immunofluorescence of transfected cells [65] , fixed cells were permeabilised with 0 . 3% Triton X-100 in PBS for 30 min and then quenched with 0 . 1 M glycine in PBS for 30 min . Cells were sequentially incubated with primary antibodies for 3 h followed by secondary antibodies for 1 h at room temperature . Coverslips were mounted onto glass slides using Mowiol . For vibratome sectioning [105] , fixed brains were embedded in 3% low-melting agarose . Sections ( 50–70 μm ) were cut using a vibratome ( Leica 1000 ) and were stored in PBS ( maximally for 2 wk ) until further processing . For cryosectioning [105] , fixed brains were equilibrated in 30% ( wt/vol ) sucrose in PBS overnight at 4°C . Brains were embedded with Tissue-TEK ( O . C . T , Sakura Finetek ) and stored at −20°C . Brains were cryosectioned at 10–12 μm . Cryosections were rehydrated with PBS before further processing . Both vibratome and cryosections were subjected to an antigen retrieval protocol as follows . Unless indicated otherwise , sections were heated in 0 . 01 M citrate buffer pH 6 . 0 at 70°C for 1 h . For comparative quantification of Pax6 and phosphohistone H3 immunofluorescence levels in mouse and human mitotic APs , cryosections of paraformaldehyde-fixed embryonic mouse and fetal human neocortex were heated in the citrate buffer using a microwave oven at 800 W for 1 min followed by 140 W for 10 min . Sections were permeabilized using 0 . 3% Triton X-100 in PBS for 30 min and quenched with 0 . 1 M glycine for 30 min . Sections were then incubated with primary antibody overnight at 4°C , followed by secondary antibody for 1 h at room temperature in a solution of 0 . 2% gelatin , 300 mM NaCl , and 0 . 3% Triton X-100 in PBS . Floating sections were mounted to Superfrost Plus microscope slides ( Thermo Scientific ) using Mowiol ( Merck Biosciences ) . For BrdU and IdU detection , slices were processed after RFP immunofluorescence as follows . An additional antigen retrieval step was performed by using HCl ( 2 N HCL , 30 min incubation at 37°C ) . Slices were then blocked with 10% goat serum and incubated for 3 h at room temperature followed by 1 h of secondary antibody incubation . The following primary antibodies were used; ßIII-tubulin ( Sigma , T8578 1:500 ) , BrdU and IdU ( Becton Dickinson , 347580 , 1:100 ) , BrdU only ( Abcam , ab6326 , 1:100 ) , Brn2 ( Santa Cruz , SC-6029 , 1:200 ) , caspase-3 ( Abcam , ab2302 , 1:500 ) , cyclinD1 ( Thermo , MA1-39546 , 1:200 ) , γ-tubulin ( Sigma , T5326 , 1:200 ) , GFAP ( Millipore , MAB 360 , 1:500 ) , HSV tag ( Abcam , ab19354 , 1:200 ) , Ki67 ( Abcam , ab16667 , 1:300 ) , nestin ( Abcam , AB5968 , 1:200 ) , Olig2 ( Thermo , MA5-15810 , 1:200 ) , Pax6 ( Covance , PRB-278P , 1:200 ) , PCNA ( Millipore , MAB424 , 1:100 ) , PH3 ( Millipore , 06–570 , 1:500 ) , phosphovimentin ( Abcam , ab22651 , 1:500 ) , RFP ( Chemotek , 5F8 , 1:500 ) , SATB2 ( Abcam , ab51502 , 1:200 ) , Sox2 ( Santa Cruz , SC17320 , 1:500 ) , Tbr1 ( Abcam , ab31940 , 1:200 ) , and Tbr2 ( Abcam , ab23345 , 1:200 ) . Alexa Fluor 488 , 594 , 647 labeled secondary antibodies ( Molecular Probes ) were used ( 1:500 ) . Nuclei were counterstained with DAPI ( Sigma , 1:1 , 000 ) . In case of thymidine analog-labeled samples ( i . e . , BrdU , EdU , and IdU ) , sections were postfixed with 4% paraformaldehyde for 20 min after the secondary antibody incubation . Incorporated EdU was detected using the Click-iT EdU kit with Alexa Fluor 647 ( Invitrogen ) as described previously [52] . Vibratome sections ( 50-μm ) and 12-μm cryosections were used for Tbr2 and PCNA analysis , respectively . We used similar criteria as used previously [65] , with some modification . In summary , we examined only sparsely electroporated areas and defined two closely located RFP-positive cells as a pair of daughter cells derived from a single electroporated AP if ( i ) no other RFP-positive cells were observed within the distance of one cell body around the two cells in the z-stack; ( ii ) both cells exhibited the same RFP fluorescence intensity; and ( iii ) the two RFP-positive cells were aligned in the same radial axis and were located above one another . In the case of the Tbr2–/Tbr2– daughter cell pairs , we measured the distance of the center of the nucleus of the ventricular-most daughter cell from the ventricular surface in Fiji . Fluorescence images were acquired using a Zeiss 700 confocal microscope using 25x and 63x objectives . Images were taken as either 2 . 1 μm ( 25x ) or 0 . 9 μm ( 63x ) single optical sections . All images used for scoring of parameters in control versus conditional Pax6 expression had comparable RFP fluorescence intensities . All images showing these parameters for control versus conditional Pax6 expression were acquired with the same settings during each microscope session . Images taken as tile scans were stitched together using the ZEN software ( Zeiss ) . Quantifications were performed using Fiji . Whole-brain images were acquired with an Olympus SZX12 stereomicroscope . Cleavage plane orientation of electroporated mitotic APs and BPs was measured in 2-D based on the position of the DAPI-stained sister chromatids during late anaphase and was expressed relative to the ventricular surface . A cleavage plane parallel to the ventricular surface ( i . e . , horizontal cleavage plane ) is defined as 0° . Germinal zones were identified based on their different histological characteristics . The VZ was identified as the ventricular-most layer of densely packed , radially aligned , elongated nuclei . The SVZ was identified as the layer basal to the VZ containing less densely packed , randomly orientated , rounded nuclei . Unless specified otherwise , cells were counted in a rectangular area , 200-μm wide at the ventricular surface , within the electroporated region of the dorsolateral telencephalon . For quantifications using double-transgenic animals ( Tis21–CreERT2: JoP6 ) , cells were counted in a rectangular area , 100-μm wide at the ventricular surface . Cells were counted without using pseudocolour . All quantifications were confined to RFP-positive cells only , with the exception of ( i ) the determination of the total nuclei present in the VZ ( Fig 4J ) , and ( ii ) the analyses of the neocortex of the double-transgenic animals , ( Tis21–CreERT2: JoP6 ) ; in both cases , all DAPI-stained nuclei were quantified . For quantification of immunofluorescence intensity levels , the area of the nucleus of interphase cells in VZ and SVZ was selected using the DAPI staining as a guide , and the area of the cell body of mitotic APs was selected using the phosphohistone H3 immunofluorescence as a guide . Selected areas were quantified using Fiji [106] . Data was further processed using the Prism software ( GraphPad software ) . Student's t test was used to determine statistical significance .
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During development , neural progenitors generate all cells that make up the mammalian brain . Differences in brain size among the various mammalian species are attributed to differences in the abundance and proliferative capacity of a specific class of neural progenitors called basal progenitors . Among these , a specific progenitor type called basal radial glia is thought to have played an important role during evolution in the expansion of the neocortex , the part of the brain associated with higher cognitive functions like conscious thought and language . In the neocortex , the expression of the transcription factor Pax6 in basal progenitors is low in rodents , but high in primates , including humans . In this study , we aimed to mimic the elevated expression pattern of Pax6 seen in humans in basal progenitors of the embryonic mouse neocortex . To this end , we generated a novel , transgenic mouse line that allows sustained expression of the Pax6 gene in basal progenitors . This elevated expression resulted in an increase in the generation of basal radial glia , in the proliferative capacity of basal progenitors , and , ultimately , in the number of neurons produced . Our findings demonstrate that altering the expression of a single transcription factor from a mouse to a human-like pattern suffices to induce a primate-like proliferative behaviour in neural progenitors , which is thought to underlie the evolutionary expansion of the neocortex .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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Sustained Pax6 Expression Generates Primate-like Basal Radial Glia in Developing Mouse Neocortex
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Migrating cells employ sophisticated signal transduction systems to respond to their environment and polarize towards attractant sources . Bacterial cells also regulate their polarity dynamically to reverse their direction of movement . In Myxococcus xanthus , a GTP-bound Ras-like G-protein , MglA , activates the motility machineries at the leading cell pole . Reversals are provoked by pole-to-pole switching of MglA , which is under the control of a chemosensory-like signal transduction cascade ( Frz ) . It was previously known that the asymmetric localization of MglA at one cell pole is regulated by MglB , a GTPase Activating Protein ( GAP ) . In this process , MglB specifically localizes at the opposite lagging cell pole and blocks MglA localization at that pole . However , how MglA is targeted to the leading pole and how Frz activity switches the localizations of MglA and MglB synchronously remained unknown . Here , we show that MglA requires RomR , a previously known response regulator protein , to localize to the leading cell pole efficiently . Specifically , RomR-MglA and RomR-MglB complexes are formed and act complementarily to establish the polarity axis , segregating MglA and MglB to opposite cell poles . Finally , we present evidence that Frz signaling may regulate MglA localization through RomR , suggesting that RomR constitutes a link between the Frz-signaling and MglAB polarity modules . Thus , in Myxococcus xanthus , a response regulator protein governs the localization of a small G-protein , adding further insight to the polarization mechanism and suggesting that motility regulation evolved by recruiting and combining existing signaling modules of diverse origins .
In living organisms , cell polarization underlies many developmental and cellular processes , such as budding in yeast , cell migration and bacterial differentiation [1]–[3] . In eukaryotic cells , polarization mechanisms ensure the asymmetric positioning of subcellular organelles and its transmission upon cell division [4] . Due to their small sizes bacterial cells have long been thought to be unorganized compartments , proven a misconception with the discovery that bacterial cells also contain subcellular structures and micro-compartments [5] , [6] . In particular , the bacterial cell pole orchestrates many processes , for example chemotaxis , flagellum assembly and even chromosome segregation [5] , [7]–[10] . Polar targeting often resides on scaffolding proteins or complexes targeted to the pole through several possible mechanisms: interaction with the forming division septum [7] , [8] , recognition of specific lipid polar microdomains [11] , [12] and even direct geometric recognition of polar curvature [13] , [14] . In some cases polar localization must be dynamically regulated to segregate cell division inhibitors [9] , [10] , degrade a cell cycle regulator [15] , or invert the direction of cell movement [16] , [17] . In this study , we identify a regulator directing dynamic pole-specific activation of motility complexes in the bacterium Myxococcus xanthus . In Myxococcus xanthus , a rod-shaped delta-proteobacterium , two distinct macromolecular machines drive motility . The first system , a type-IV pilus ( T4P ) engine located at the leading cell pole binds to neighboring cells or the extracellular matrix to pull the cells forward by retraction ( S-motility , [18] ) . The second system , the recently characterized Agl-Glt complex , is also assembled at the leading cell pole where it forms focal adhesion-like complexes which distribute along the cell body to propel the cell ( A-motility , [19]–[21] ) . Myxococcus cells direct their motility by changing their direction of movement periodically in a process where the poles exchange roles , allowing the cells to resume movement in the opposite direction . These reversals require switching the directionality of the A- and S- molecular engines synchronously . Recent cytological experiments have suggested that pre-assembled T4P exist at both cell poles but are only active at one cell pole , due to asymmetric pilus-associated proteins like FrzS , Tgl , PilB and PilT [22]–[24] . The switching of pilus directionality would thus occur following pole-to-pole switching of these factors , which has been experimentally observed for FrzS and PilT [22] , [24] . The mechanism allowing the directional switch of the A-motility system is less clear but seems to involve the synchronous pole-to-pole switching of essential Agl-Glt complex proteins , which has been shown for AglZ and AglQ [21] , [25] . What drives the dynamic behavior of the A ( AglZ , AglQ ) and S motility proteins ( FrzS , PilT ) during reversals ? Recent studies identified the MglA and MglB proteins as central regulators of the reversal cycle . MglA is the founding member of a group of bacterial G-proteins of the Ras superfamily [16] , [17] , [26] . As for all other Ras-like G-proteins , MglA is a nucleotide ( GTP ) -dependent molecular switch protein , cycling between active ( GTP-bound ) and inactive ( GDP-bound ) states [26] . During motility , MglA-GTP localizes essentially at the leading cell pole and activates both T4P and the Agl/Glt system . The exact activation mechanism is unknown but may involve direct interactions with FrzS and AglZ [27] . The MglA GTP-hydrolysis activity is intrinsically low and is assisted in vivo by MglB , a GTPase-Activating Protein [16] , [17] . MglB is a spatial regulator of MglA and localizes at the opposite lagging cell pole to inhibit MglA binding at that pole [16] , [17] . Therefore , MglA and MglB form a polarity axis that can be inverted by the synchronous pole-to-pole switching of MglA and MglB , thus provoking a reversal [16] , [17] , [28] . Switching of MglAB is a regulated process and involves the signaling activity of the Frz signal transduction pathway , a chemosensory-like apparatus [16] , [17] , [28] . However , how Frz regulates the MglAB switch at the molecular level remains unknown . In summary , Myxococcus reversals are provoked by switching the activity of the motility systems ( A and S ) to the opposite cell pole which is under the control of MglA and the Frz signal transduction pathway . In this study , we investigated how MglA localizes to the cell poles . We found that the polar localization of MglA requires RomR . Previously , it was shown that RomR , an essential A-motility protein , localizes to the cell poles in a Frz-controlled bipolar asymmetric pattern where it accumulates mostly at the lagging cell pole [29] . Since RomR contains a response regulator domain , its phosphorylation by the Frz kinase ( FrzE ) may directly contribute to A-motility regulation [29] . Revisiting the role of RomR , we found that RomR functions both for A- and S-motility and acts upstream from MglA , recruiting it to the cell pole . The results further show that the polarity axis builds from the formation of RomR-MglA and RomR-MglB complexes , leading to robust asymmetric protein localization at the poles . Finally , the evidence suggests that RomR may constitute a link between the Frz and the MglAB polarity control systems .
Figure 1A&B recapitulates the known localization pattern of the previously studied switch and motility proteins , MglA , MglB , FrzS , AglZ and RomR . Previous works suggested an ordered pathway where Frz activates MglAB pole-to-pole switching to switch the localization of downstream motility system specific regulators such as FrzS ( S-motility ) , AglZ and RomR ( A-motility ) [16] , [17] , [27] , [29] . To confirm these studies in a definitive manner and identify localization interdependencies between these proteins , we systematically analyzed the localization of functional YFP/mCherry ( mCh ) fusions to MglA , MglB , FrzS , AglZ and RomR ( [16] , Figure S1 , S2 , S3 ) in all single mutants ( summarized in Figure 1C and S2 , S3 , S4 , S5 ) . Most of the results were consistent with previous reports and confirmed that MglA and MglB are required to establish a polarity axis for motility: in the mglA mutant , AglZ-YFP became diffuse and failed to accumulate both at the pole and at periodic sites; FrzS-GFP , RomR-mCh and MglB-YFP localized only to one cell pole ( Figure 1C [16] , [17] , [27] , [29] ) . In the mglB mutant , all four proteins MglA-YFP , FrzS-YFP , AglZ-YFP and RomR-mCh showed bipolar symmetrical patterns ( Figure 1C , Figure S2 and [16] , [17] ) . The absence of FrzS or AglZ did not affect the localization of any of the other four proteins and thus must be branched downstream from MglA and MglB to regulate S- and A-motility , respectively ( Figure 1C , S3 , S4 and [27] ) . In a romR mutant , MglA-YFP and AglZ-YFP showed severe localization defects: AglZ-YFP was completely diffuse ( Figure 1C and S5 ) and MglA-YFP localized in a largely diffuse pattern with only occasional minor polar foci forming in some cells ( Figure 1C and 2A ) . The localizations of FrzS-YFP and MglB-YFP were less affected: both proteins localized to one cell pole but showed no dynamic pole-to-pole oscillations ( Figure 1C , S5 and data not shown ) . In the romR mutant , the mis-localization of MglA cannot result from protein expression and/or stability defects because MglA accumulates to WT steady-state levels in the mutant as determined by Western blot analysis ( Figure S6 ) . Therefore , we further investigated the mechanism of RomR-dependent MglA polar localization . In absence of RomR , MglA mis-localization could either result from a direct defect in polar targeting or , more indirectly because MglB dynamics are affected , perturbing the spatial regulation of the MglB GAP activity . To discriminate between these possibilities , we tested whether deletion of mglB restores MglA-YFP localization . In WT cells , MglA-YFP mostly accumulates at the leading cell pole and gradually accumulates at the opposite cell pole between reversals [16] , [17] . As a result , a fluorescence snapshot of MglA-YFP expressing cells shows a mix of cells with unipolar ( 60% ) or with bipolar MglA-YFP clusters ( 40% , Figure 2A ) . Comparison of MglA-YFP in a romR and in a romR mglB mutant revealed that MglA-YFP localization is perturbed to comparable levels in the mutants: in both mutants , MglA-YFP was mostly diffuse and only accumulated as a minor unipolar cluster in less than 20% of the cells ( Figure 2A ) . Thus , in a romR mutant , MglA-YFP mis-localization is largely independent from MglB and may result directly from the absence of RomR . In the romR mutant , mis-localized MglA could interfere with MglB dynamics . To test this , we asked whether MglB-YFP dynamics are restored in a romR mglA double mutant . Consistent with its pole-to-pole dynamics MglB-YFP showed a mix of unipolar ( 75% ) or bipolar patterns ( 25% ) in WT cells ( Figure 2B ) . In both romR and romR mglA mutants , MglB-YFP was strictly unipolar showing that MglB-YFP dynamics are not significantly restored in the romR mglA mutant . Therefore , the absence of MglB-YFP pole-to-pole dynamics in the romR mutant is not simply caused by MglA-mediated interferences but likely results from the global loss of function of MglA . Consistent with this , any mutant that lacks MglA ( mglA mutant ) or cannot localize it ( romR mutant ) is affected in MglB and other motility protein switching , for example FrzS ( Figure 1C and S5 ) . In WT cells , RomR localizes in a bipolar asymmetrical pattern and accumulates in larger amounts at the lagging cell pole ( Figure 3A ) . How is this asymmetry generated and how does it relate to RomR function ? RomR-mCh localized symmetrically to both cell poles in a double mglAB mutant , showing that RomR does not require MglA and MglB to bind to the cell poles ( Figure 3A ) . Since RomR also localizes in a bipolar symmetrical pattern in the mglB mutant ( Figure 1C ) but only at one cell pole in the mglA mutant ( Figure 1C and 3B ) , these results suggest that a RomR-MglB interaction captures RomR to the lagging cell pole . Consistent with this , dual-labeling experiments showed that RomR-mCh and MglB-YFP fusions localized to the same pole in the mglA mutant ( Figure 3B ) . Of note , FrzS-GFP , which normally accumulates mostly at the leading cell pole [22] , also co-localized with MglB-mCh ( a functional MglB-mCherry fusion , [16] ) and RomR-mCh in absence of MglA ( Figure 3B , data not shown , see discussion ) . In total , these results suggest that RomR binds indiscriminately to the cell poles and that its asymmetric localization in WT cells stems from interactions with MglA at the leading cell pole and MglB at the lagging cell pole . We next tested whether the localization interdependencies between RomR , MglA and MglB stem from direct protein interactions at the cell poles . To test potential RomR-MglA and RomR-MglB interactions , we complemented the romR mutant strain with a construct allowing expression of RomR fused to a hexahistidine motif ( His6 ) at its C-terminus , under the control of the romR promoter from a chromosome integration at the Mx8 phage attachment site [16] . Expression of RomR-His6 complemented the romR deletion showing that the tagged protein is fully functional ( Figure S1 ) . Interaction between RomR , MglA and MglB was then tested by affinity chromatography of Myxococcus soluble extracts on nickel columns ( see Methods ) . Under these conditions , RomR readily co-purified with MglA and MglB , suggesting that MglA and MglB both interact with RomR ( Figure 4 ) . To further test whether RomR can form a complex with MglA and MglB independently , we conducted affinity chromatography of soluble extracts containing RomR-His6 expressed in mglA or mglB genetic backgrounds . Again , RomR-His6 co-purified with MglB and MglA in each case ( Figure 4 ) , suggesting that RomR forms independent complexes with MglA and MglB at cellular poles . We next tested how a romR mutation affects A- and S-motility . We first analyzed the behavior of single A-motile cells on hard agar , a condition where S-motility is inefficient [30] . In this assay , romR mutant cells showed a severe motility defect and only exhibited limited back and forth movements ( Figure 5A and Movie S1 ) . This movement could be attributed to the A-motility system alone because it was still detectable in a romR pilA ( S- ) mutant but fully absent from a romR aglQ A-motility motor double mutant ( Figure 5A and data not shown ) . The strong romR mutant A-motility defect is consistent with conclusions from Leonardy et al . [29] and the observed mis-localization of both MglA-YFP and AglZ-YFP in this mutant . To test the epistatic relationships between romR and mglB , we compared the motility defects of the romR mutant with the mglB and the romR mglB mutants . As previously reported , mglB mutant cells moved with a similar efficiency as WT cells but hyper-reversed ( Figure 5A and Movie S2 ) . In contrast , romR mglB mutant cells showed severely crippled motility , a motility phenotype that was comparable to the romR mutant phenotype ( Figure 5A & Movie S1 & S3 ) . Therefore , we conclude that RomR acts downstream from MglB to control A-motility . To determine whether romR acts upstream from mglA , we also compared the motility phenotypes of mglA , mglA mglB , romR mglA and romR mglB mglA mutants . All strains were completely non-motile and indistinguishable from the mglA mutant strain ( and aglQ mutant strain ) , showing that MglA acts downstream from RomR and MglB ( Figure 5A and Movie S4 ) . Since MglA is also important for S-motility , a romR mutation would also be expected to impact S-motility . This is further suggested by the fact that FrzS , an essential S-motility protein , fails to localize to both cell poles in the romR mutant ( Figure 3B and S5 ) . S-motility involves the movement of large cell groups and can be tested on soft agar ( 0 . 5% w/w ) , a substrate where A-motility is not effective [30] . In this assay and in WT cells , S-motility produces characteristic radial flares that emerge from a colony ( Figure 5B ) . This pattern is unaltered in an aglQ mutant , confirming that A-motility is not active on soft agar ( Figure 5B ) . On the contrary , a romR mutant displayed a severely defective swarm pattern ( Figure 5B ) . This pattern results from a bona fide S-motility defect because a romR aglQ ( A− ) double mutant was defective to a similar extent ( Figure 5B ) . In this highly qualitative assay , the comparison of the romR mutant with mglB and romR mglB mutants was not informative because all mutants displayed similar defective phenotypes ( Figure 5B ) . However , clear epistatic relationships could be determined with mglA mutants: mglA , mglAB , romR mglA and romR mglA mglB mutants were all completely S− , showing that MglA acts downstream from RomR and MglB to control S-motility ( Figure 5B ) . In total , the data strongly suggest that RomR acts downstream from MglB and upstream from MglA to both control A- and S-motility . The motility results are consistent with the localization results and a scenario where RomR acts as a polar targeting factor of MglA , the most downstream motility regulator . Finally , the correlation between motility phenotypes and localization defects suggests that polar localization of MglA is essential for its function . The discovery that Myxococcus cell polarity arises from dynamic interactions between RomR , MglA and MglB raises the possibility that RomR acts immediately downstream from the FrzE histidine kinase to trigger the polarity switch . Several lines of evidence suggest that RomR is a possible Frz-output regulator . First , RomR is a modular protein containing both an N-terminal response regulator domain ( RR ) and a proline-rich C-terminal domain [29] and is thus a candidate substrate for FrzE . Consistent with this , RomR pole-to-pole switching is regulated by FrzE , which specifically requires the RomR receiver domain [29] . Additionally , expression of a RomRD53E variant in which the conserved phosphorylatable Asp53 residue has been substituted by a Glutamate ( a mutation expected to mimic a constitutively active state ) bypassed the requirement for FrzE to trigger reversals [29] . Finally , there is evidence that Frz signaling is still transmitted to MglA in the absence of MglB , suggesting that Frz-signalling can be conveyed directly to MglA ( Figure 6A , see [16] for details ) . Therefore , it is conceivable that RomR is part of this branch linking FrzE to MglA . To test this possibility , we reasoned that a class of gain-of-function mutations in the frzCD receptor gene , the frzon mutations ( frzCDc , [16] ) , may restore RomR and MglA pole-to-pole dynamics in absence of MglB . frzon mutations are thought to activate the Frz pathway constitutively [31] , [32] and may thus hyper activate signals from FrzE to MglA via RomR ( Figure 6A ) . In an mglB mutant , both MglA-YFP and RomR-mCh accumulated symmetrically at the cell poles and did not switch when cells reverse ( Figure 6B , S2 and [16] , [17] ) . Strikingly , RomR pole-to-pole switching was restored inversely in frzon mglB mutant cells: RomR switched from leading cell pole-to leading cell pole , as opposed to WT cells where it switches from lagging cell pole to lagging cell pole ( Figure 6C and [29] ) . As would be expected if RomR were the major MglA localization factor , MglA-YFP pole-to-pole switching was restored coincidently in frzon mglB cells ( Figure 6D ) . A cross correlation analysis done for 30 cells of each strain showed that significant Rxy scores ( >0 . 4 ) near a 0–1 min time delay value were only obtained for RomR-mCh and MglA-YFP in frzon mglB backgrounds , confirming that RomR-mCh and MglA-YFP polar fluorescence dynamics are correlated with physical reversals in mglB frzon mutant cells but not in mglB mutant cells ( Figure 6E , see methods ) . To test whether RomR acts upstream from MglA in this regulation , we constructed an mglB romR frzon strain . mglB romR frzon mutant cells showed a romR-like motility defect ( Figure 5A ) . Therefore , a romR mutation is epistatic over a frzon mutation , establishing that RomR acts downstream from Frz in the control of MglA dynamics . Finally , the results suggest that Frz signals do not require MglB to be conveyed to MglA .
What is the role of MglA polar localization ? In all tested romR mutants , the severe mis-localization of MglA correlates with a profound motility defect , suggesting that polar MglA is essential to activate the A- and S-motility systems . It is possible that MglA regulates A- and S-motility in different ways . The S-motility proteins , FrzS and PilT , still localize to the pole in an mglA mutant ( this work and [16] , [17] , [27] , [29] ) . Importantly , FrzS and MglB/RomR , which are normally addressed to different poles , co-localize in mglA mutant cells . Therefore , MglA is not per se an S-motility protein polar localization factor but rather functions as an S-motility polar switching system . On the contrary , MglA is absolutely required for AglZ localization ( this work and [27] ) . Therefore , the RomR-MglA-AglZ branch could determine localization of the A-motility machinery , while MglB and FrzS could be part of an A- ( MglB ) and S-motility ( MglB and FrzS ) polar switching pathway . In Myxococcus , MglA is thus required to differentiate a leading cell pole , similar to other Ras-family proteins defining the leading edge in chemotaxing eukaryotic cells [33] . How MglA does this exactly remains to be determined . Unidentified polar cue ( s ) must exist to localize RomR , MglB and FrzS , which could be anchored by a common polar determinant or dedicated polar anchors . Motility machinery components themselves are likely not involved in this targeting because mutations in structural T4P or Agl/Glt proteins do not affect the reciprocal motility system [20] , [34] , [35] and any mutation that perturbs RomR or MglB localization would be expected to affect both systems . The polar cue ( s ) may be a general cell organizing structure , for example the cytokinetic machinery , lipid microdomains or membrane curvature itself [7] , [8] , [12] , [14] , [36] . In a parallel study , Keilberg et al . obtained similar results and additionally suggested that RomR co-evolved with a subfamily of MglA-MglB systems [37] . More specifically , the results from both studies suggest strongly that Myxococcus dynamic polarity results from the action of three proteins , MglA , MglB and RomR . In this work , several lines of evidence suggest that a major function of RomR is to recruit MglA to the poles: ( i ) MglA localization depends on RomR but not vice versa . Additionally , MglA localization is not restored in a romR mglB double mutant , showing that RomR does not regulate MglA upstream from MglB . ( ii ) , In mglB mutant cells , RomR and MglA localizations coincide in a bipolar symmetrical pattern . ( iii ) , RomR and MglA switch poles coincidently in a frzon mglB mutant . ( iv ) , RomR is important for both A- and S-motility , which must be expected for any factor that regulates MglA . ( v ) , RomR forms a complex with MglA in a co-purification assay . Last , Keilberg et al . [37] did not observe the restoration of MglA polar localization when YFP-MglAQ82A , an MglA GTP-locked variant [26] , was expressed in the romR mutant , strongly suggesting that RomR is a direct MglA polar determinant . However , we cannot fully exclude that RomR also regulates the nucleotide-binding state of MglA ( see below ) . The MglA polar recruitment function of RomR was not initially obvious from its subcellular localization because RomR accumulates preferentially at the lagging pole where MglB is mostly present ( Figure 1B & S1 ) . In this study we show that MglB is directly responsible for this asymmetry and forms a complex with RomR at the back of the cells . The purpose of this regulation remains to be elucidated . We speculate that the MglB-RomR complex may further modulate accumulation of MglA–GTP at the leading pole as RomR becomes titrated by MglB . Therefore , MglB may exert two independent controls over MglA localization: directly with its GAP activity and indirectly , by trapping its localization factor RomR at the opposite cell pole . In the future , it could be interesting to determine if MglA and MglB compete for RomR binding to test this hypothesis . In summary , we propose that proper segregation of MglA and MglB at opposite cell poles requires a three-protein interaction network: first , RomR-MglA complexes direct MglA indiscriminately to the cell poles ( Figure 7A ) . Second , MglB-MglA interactions repel MglA to the opposite cell pole and third , MglB-RomR interactions further modulate MglA levels at the leading cell pole . These concerted interactions thus create a robust polarity axis ( Figure 7A ) . What is the genetic pathway leading to programmed cellular reversals ? We propose a new genetic pathway that compiles this and previous studies ( Figure 7B ) . In total , three main functional gene categories can be defined based on phenotypes: frz genes control the reversal frequency and thus trigger the polarity switch; romR , mglA and mglB form a cellular compass and thus affect both motility systems; aglZ and frzS are respectively specific to the A- and S-motility branch and thus connect the upstream genes to the motility apparatus . While MglA has been physically linked to AglZ and FrzS , how it is connected to the upstream Frz proteins remains unknown . The RomR protein itself is a strong candidate to connect FrzE kinase activity and MglA directly because RomR contains a response regulator ( RR ) domain and the intracellular dynamics of RomR are regulated by Frz-signaling ( Figure 6 and [29] ) . Also , mutations in the conserved phosphorylatable Aspartate of the RomR receiver domain ( D53N and D53E ) are epistatic to a frzE mutation in the reversal pathway [29] . How is polarity switched dynamically by Frz-signaling ? While the genetic data suggests that RomR is a likely FrzE output protein , biochemical evidence showing that RomR accepts phosphates directly from FrzE is still lacking . Other questions must also be resolved to model the switch mechanism . The interactions between the various players may be regulated at different levels and the proteins exist in several states , which may affect the protein localization interdependencies . For example , RomR phosphorylation may change its affinity for MglA and/or B , or even differentially to A and B . The formation of the RomR-MglA complex could also be dictated by the nucleotide state of MglA . Conversely , RomR may also regulate the nucleotide state of MglA , directly or indirectly by regulating MglB . As mentioned above , MglA and MglB could compete for RomR binding . Last , the Frz system may use several ouput proteins ( Figure 7B ) . For example , the Frz pathway itself encodes two other receiver domain containing proteins , which are likely part of the regulatory pathway: the cognate FrzE receiver domain and the FrzZ protein [38] , [39] . While the FrzE receiver domain may not be a direct Frz output domain and mostly regulate the phosphate flow in the system [38] , [39] , the phosphorylation of FrzZ is indispensable for the reversal switch [38] , [39] . Therefore , the exact function of FrzZ and its exact connection with the RomR-MglAB system will also have to be clarified . In the future , a thorough biochemical analysis of Frz and RomR-MglAB interactions is required to elucidate the switch mechanism ( Figure 7B ) . In bacteria , response-regulators are broadly used to target proteins to cellular poles . In Caulobacter crescentus , the cell-specific clearance of the master regulator CtrA licenses cell cycle progression [40] . In this regulation , CtrA is cleared specifically at the incipient stalked pole , by the combined action of two polar response regulator proteins [15] , [41] . Response regulator proteins also regulate enzymes spatially . In another Caulobacter example , PleD an RR-containing protein localizes to the swarmer cell pole and orchestrates cell pole morphogenesis by activating local synthesis of the second messenger cyclic-di-GMP [42] , [43] . Thus , RR domains implement subcellular organization by recruiting output proteins or domains to specific subcellular sites [44] . This versatility is further exemplified in Myxococcus where an RR protein ( RomR ) recruits a Ras-like G-protein ( MglA ) to the cell pole . This modular architecture is unique because it connects proto-typical prokaryotic and eukaryotic systems: a bacterial chemosensory-like pathway and a Ras-GAP system . In eukaryotes , Ras-GAP pairs generally act downstream from seven transmembrane receptors , the so-called G-Protein-coupled Receptors ( GPCR ) , which sense ligands ( ie cAMP ) to activate Ras family proteins spatially [33] . In Myxococcus , where GPCRs are absent , the Frz pathway may therefore constitute a substitute activating module . This further illustrates how novel functions can arise from the conjunction of existing functional modules across the living kingdoms .
See Table S1 for plasmids and Table S2 for strains and their mode of construction . Primer sequences and plasmid construction schemes are provided in Tables S3 and S4 . M . xanthus strains were grown at 32°C in CYE rich media as previously described [45] . Plasmids were introduced in M . xanthus by electroporation . Mutants and transformants were obtained by homologous recombination based on a previously reported method [45] . Complementation , expression of the fusion and mutant proteins were either obtained by ectopic integration of the genes of interest at the Mx8-phage attachment site [16] under the control of their own promoter in appropriate deletion backgrounds or by expression from the endogenous locus ( Table S2 ) . Localization studies were performed using previously described FrzS-YFP , AglZ-YFP , MglB-mCherry/YFP functional fusions [16] . In the case of MglA-YFP , localization studies were performed in a merodiploid background where both MglA-YFP and MglA are expressed , a context where expression of MglA-YFP is not associated with detectable motility defects [16] . A functional RomR-mCh fusion protein was constructed for this study and expressed from the endogenous romR locus ( Table S1 , S2 , S3 , S4 and Figure S1 ) . For phenotypic assays , cells were spotted on CYE plates containing an agar concentration of 1 . 5% or 0 . 5% at a concentration of 4×109 cfu ml−1 , incubated at 32°C and photographed after 48 h with an Olympus SZ61 binocular or a Nikon Eclipse ( model TE2000E ) microscope . Western blotting was performed as previously described [16] with 1/10 , 000 dilutions of penta-His ( QIAGEN ) , MglA or MglB antisera . Time-lapse experiments were performed as previously described [46] . Microscopic analysis was performed using an automated and inverted epifluorescence microscope TE2000-E-PFS ( Nikon , France ) . The microscope is equipped with “The Perfect Focus System” ( PFS ) that automatically maintains focus so that the point of interest within a specimen is always kept in sharp focus at all times , in spite of any mechanical or thermal perturbations . Images were recorded with a CoolSNAP HQ 2 ( Roper Scientific , Roper Scientific SARL , France ) and a 40×/0 . 75 DLL “Plan-Apochro- mat” or a 100×/1 . 4 DLL objective . All fluorescence images were acquired with a minimal exposure time to minimize bleaching and phototoxicity effects . Averaged fluorescent intensity profiles were computed as follows . A two-dimensional graph of the pixel intensities along the cell axis was first computed for each cell . The cell boundaries were then defined using a threshold value and the resulting restricted profile was spliced in 15 segments of equal length . The cluster probability distribution histograms were obtained as follows: the occurrence of a fluorescence cluster within a segment was detected by defining a minimal cluster intensity threshold value and the same threshold value was used for all conditions . Cell tracking was performed automatically using a previously described macro [46] under the METAMORPH software ( Molecular devices ) ; when appropriate , manual measurements were also performed to correct tracking errors with tools built into the software . Images were processed under both ImageJ 1 . 40 g ( National Institute of Health , USA ) and METAMORPH . A measured single cell traveled distance represents the net distance travelled by a given cell , irrespective of its direction of movement . Therefore , reversals or any sort of back and forth movements are not accounted for in these measurements . The values were computed as the sum of the traveled distance by a given cell centroid in pixels during a 10 min reference time frame . Statistical analysis of cell reversals was performed as previously described for 30 reversing cells of each tested strain [16] . The time-lapse movies are composed of 30 s time frames to avoid phototoxicity and photobleaching . Since a reversal takes on average 30 s between the initial pause and movement resumption , it is difficult to capture the exact time of the pause and fluorescence switching in our movies , creating noise in the analysis . Nevertheless , a reversal time was scored as soon as movement was detected in the opposite direction . MglA-YFP and RomR-mCh switching were scored when the maximum fluorescence was reached at the new leading pole . The cross-correlation coefficient ( Rxy ) between scored reversals and fluorescence pole-to-pole switchings for a time of delay ( m ) was calculated with the following equation:</disp-formula></xsl:text> Under these conditions and despite the low temporal resolution of the time lapse , significant Rxy values ( the theoretical Rxy value for a perfect correlation is 1 ) could be obtained for a time delay near 0 value ( ±30 s ) , allowing to correlate fluorescence polar inversions ( x ( t ) ) and cellular reversals ( y ( t ) ) with confidence . Co-purification experiments were conducted by expressing a functional RomRHis6 from its endogenous promoter at the Mx8 site in the romR mutant ( which fully complemented the mutant , Figure S1 ) , respectively in WT , mglA and mglB mutant backgrounds . As a control , co-purification specificity experiments were conducted in parallel using WT , mglA and mglB single mutants expressing un-tagged RomR to show that MglA and MglB were only recovered when RomRHis6 is expressed . Co-purifications were conducted , after re-inoculating cells into 1L flasks to OD600 0 . 4–0 . 8 . The cells were collected by spinning at 5000 rpm for 20 min . The supernatant was discarded and the pellet was washed twice in wash buffer ( NaH2PO4 50 mM , NaCl 100 mM , MgCl2 5 mM , pH 8 . 0 ) before being resuspended in 20 ml lysis buffer ( NaH2PO4 50 mM , NaCl 100 mM , MgCl2 5 mM , 3 µl β-ME ( Bio-Rad ) , 200 µl Protease Inhibitor Cocktail ( PIC , Clontech ) , 10 µM GDP , 3 µl benzonase ( Sigma ) , 20 mM Imidazole pH 8 . 0 ) . The cells were then disrupted with a French press and spun down at 18 , 000 rpm , 4°C for 1 hour . The supernatants were then transferred into 50 ml Falcon tubes on ice and mixed with pre-equilibrated Nickel beads ( Biorad ) . Beads and lysates were subsequently incubated at 4°C for 2 hours on a rotating wheel at 25 rpm . The bead-bound RomR complexes were then collected by low speed centrifugation ( 1 min at 2500 rpm ) and washed three times in 50 ml lysis buffer . Elution was conducted by adding 100 µl of protein loading buffer ( Leammli ) directly to the beads and boiling at 100°C , for 10 min . Western blots were then conducted over 20 µL of the total elution volume under standard conditions to detect RomRHis6 , MglA and MglB .
|
Migrating cells have evolved a molecular compass to rapidly respond to environmental signals . During chemotaxis , small G-proteins and their regulators are activated and determine a leading cell edge towards attractant molecules . Bacteria also move across surfaces in a directed manner . The rod-shaped bacterium Myxococcus xanthus can switch its direction of movement in a process where the cell poles exchange roles ( reversal ) , allowing complex multicellular behaviors . In Myxococcus , a small G-protein , MglA , determines the leading cell pole . In this study , we investigated how MglA localizes to the pole and found that its localization depends on the dual complementary action of RomR and MglB . In this process , RomR targets MglA to the pole while , in turn , MglB prevents its accumulation at the back of the cell . Moreover , RomR potentially links MglA to the Frz signal transduction pathway , a chemosensory system controlling the reversal frequency . The results provide a new molecular basis to understand motility regulation in a bacterium , which may have arisen from co-optation and branching of prokaryotic and eukaryotic-like signaling modules .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"signal",
"transduction",
"signaling",
"in",
"cellular",
"processes",
"molecular",
"cell",
"biology",
"mechanisms",
"of",
"signal",
"transduction",
"signaling",
"pathways",
"biology",
"microbiology",
"microbial",
"growth",
"and",
"development"
] |
2012
|
A Dynamic Response Regulator Protein Modulates G-Protein–Dependent Polarity in the Bacterium Myxococcus xanthus
|
A literature survey and analysis was conducted to describe the epidemiology of dengue disease in Thailand reported between 2000 and 2011 . The literature search identified 610 relevant sources , 40 of which fulfilled the inclusion criteria defined in the review protocol . Peaks in the number of cases occurred during the review period in 2001 , 2002 , 2008 and 2010 . A shift in age group predominance towards older ages continued through the review period . Disease incidence and deaths remained highest in children aged ≤15 years and case fatality rates were highest in young children . Heterogeneous geographical patterns were observed with higher incidence rates reported in the Southern region and serotype distribution varied in time and place . Gaps identified in epidemiological knowledge regarding dengue disease in Thailand provide several avenues for future research , in particular studies of seroprevalence . PROSPERO CRD42012002170
Dengue is a global arboviral disease affecting humans . The primary vector is the Aedes aegypti ( Linnaeus ) mosquito . Dengue is present in the tropical and subtropical regions of the Americas , the eastern Mediterranean , Africa , and the World Health Organization ( WHO ) Western Pacific and Southeast Asia regions [1] . Countries included within regions designated as Southeast Asia differ according to WHO , political and geographic definitions . Unless otherwise stated , the term Southeast Asia used in this paper refers to the WHO Southeast Asia Region ( SEAR ) . Globally , more than 2 . 5 billion people are at risk [1] . The WHO estimates that more than 50 million dengue virus ( DENV ) infections and 20 , 000 dengue disease-related deaths occur annually worldwide [2] , [3] , and a recent disease distribution model estimated there were 390 million DENV infections in 2010 , including 96 million apparent infections ( i . e . , cases that manifest at any level of clinical or subclinical severity ) . Overall , 70% of these apparent infections occurred in Asia [4] . Thailand observed its first cases of dengue disease in 1949; sporadic cases continued to be reported throughout the 1950s [5] , [6] and the first major outbreak of dengue haemorrhagic fever ( DHF ) was reported in Bangkok in 1958 [7] , [8] . There were 2158 cases and 300 deaths in this outbreak [9] . DENV infection is caused by any one of four distinct DENV serotypes ( DENV-1 , -2 , -3 or -4 ) [1] . Three or possibly four virus types ( DENV-1 , possibly DENV-2 and two unidentified serotypes ) were isolated during the 1958 epidemic [10] , and the co-circulation of all four dengue serotypes was demonstrated in the early 1960s in Bangkok [11] . By the late 1970s , the disease was widespread among countries in Southeast Asia and DHF had become a leading cause of hospitalization and death among children in Thailand [12] . There was a major epidemic of dengue disease in 1987 , in which 174 , 285 cases were reported , after which the number of reported cases remained relatively low and stable , with under 100 , 000 cases reported each year . Two large outbreaks were reported in 1997 and 1998 , with 101 , 689 and 126 , 348 cases reported , respectively [9] , [13] . Before 2004 , Thailand reported the highest number of annual dengue disease cases in Southeast Asia , with an average of almost 69 , 000 cases per year reported between 1985 and 1999 [13] . After 2004 , Indonesia reported the highest number of cases from the region , accounting for 57% of the cases reported to the WHO Southeast Asia region in 2006 [13] . The epidemiology of dengue disease in Thailand is characterized by cyclical epidemic activity alternating between years of relatively low and high dengue disease incidence [14] , [15] . A reporting system for dengue surveillance in Thailand started in 1958 . The national surveillance system for DHF was initiated in 1972 by the Bureau of Epidemiology ( BoE ) , Thai Ministry of Public Health ( MoPH ) becoming fully operational in 1974 [16] . DF was included in the surveillance system in 1994 . Reports for patients diagnosed with dengue disease are collected from hospital in-patients and hospital out-patients from health facilities nationwide , all government hospitals and some private hospitals and clinics ( the reporting sites are mostly public hospitals , with a few voluntary reports from private hospitals ) . It is mandatory to report the confirmed cases , but not for the suspected cases ( which is subject to the physicians' willingness to report ) . The reporting form ( Form 506 ) is used to record demographic data — age , sex , day of onset and the address ( locality ) where the case occurred , categorised as municipalities ( ‘cities’ or ‘suburbs’ ) or ‘other’ ( mostly rural ) areas [16] . It should be noted that all reported dengue disease cases in Thailand are diagnosed by the trained physician using WHO case definition established since the 1970s , which classify dengue into dengue fever ( DF ) , DHF and dengue shock syndrome ( DSS ) [17] . Digital or hardcopy reports of dengue disease are transmitted up the system from the local level , initially to provincial health offices and then to the BoE where they are collated and analyzed . Prior to 1999 the reports were sent by post; electronic transmission of reports began in 1999 [16] . For the past 10 years , the Thai surveillance system at the central level has been systematic and relies on electronic-based data although at the local level there is no compulsory electronic proforma , indeed hospitals often generate their own software programs that are compatible with Form 506 for entering and transferring data . Epidemiological data on DF , DHF and DSS in Thailand are disseminated from central departments in the form of weekly newsletters ( the BoE Weekly Epidemiological Surveillance Report ) and published online on the MoPH website within the Annual epidemiological surveillance reports ( AESRs ) . Dengue disease laboratory diagnostics in Thailand can be ordered on an individual basis and include dengue virus isolation , viral genome detection by reverse transcription polymerase chain reaction ( RT-PCR ) , four-fold increases of paired sera ( haemagglutination inhibition ) or IgM >40 U or IgG increasing >100 U . Virological surveillance ( virus isolation and serotyping by RT-PCR ) is performed by the Department of Medical Science , especially before the outbreak season , which appoints a number of hospitals from around the country to act as sentinel sites . However , only a small proportion of reported cases are tested for DENV infection . Furthermore , the proportion of specimens sent for testing varies between provinces in each region . Thailand is divided politically into 76 provinces , with the capital , Bangkok , being a special administrative area . A four-region administrative system is used by the MoPH ( Figure S1 ) : North ( population 11 . 5 million ) , Northeast ( 18 . 8 million ) , Central ( including Bangkok ) ( 26 . 3 million ) , and South ( 8 . 9 million ) [18] . Thailand has three types of climate , a tropical rain climate in the coastal areas of the east and south , a tropical monsoon climate in the southwestern and southeastern coastal areas , and a tropical wet and dry or savannah climate in the southwest , central and northern regions . Climatic factors such as temperature , rainfall and relative humidity affect the growth and dispersion of the mosquito vector and are known to be associated with dengue outbreaks [19] . In common with other developing tropical and subtropical countries , Thailand has population demographics and socio-economic conditions that favour dengue transmission , such as rapid population growth and rural–urban migration [20] , and densely populated areas that provide suitable Aedes mosquito larval habitats [1] , [21] . This review describes the epidemiology of dengue disease in Thailand reported in the literature between 2000 and 2011 in the context of the national and regional trends and aims to identify gaps in epidemiological knowledge requiring further research . Incidence ( by age and sex ) , seroprevalence and serotype distribution and other relevant epidemiological data such as geographical distribution are described . We estimated that a time period of at least 10 years would allow observation of serotype distribution over time and through several epidemics and , in view of the 3–5-year periodicity of dengue outbreaks [7] , would also accurately reflect recent changes in dengue disease epidemiology . We set the start date as 1 January 2000 , as opposed to an earlier date , to limit the bias that any differences in surveillance practices over time would have on the results . The cut-off for our review period was set as 28 February 2012 , the date when we initiated this review .
The LRG guided the literature analysis process , defined the search strategy , and prepared the protocol and review documents . Specific search strings for each database were designed with reference to the expanded Medical Subject Headings thesaurus , encompassing the terms ‘dengue’ , ‘epidemiology’ , and ‘Thailand’ . Different search string combinations were used for each electronic database with the aim of increasing the query's sensitivity and specificity . Searches of selected online databases ( Table S1 ) were conducted between 9 February 2012 and 28 February 2012 . As stated in the protocol , studies ( as well as conference materials , grey literature and official reports and bulletins ) published in either Thai or English between 1 January 2000 and 28 February 2012 were included in the analysis . References not meeting these criteria that were found in databases that did not allow language and/or date limitations were deleted manually at the first review stage . No limits by sex , age and ethnicity of study participants or by study type were imposed , although single-case reports and studies that only reported data for the period before 1 January 2000 were excluded , as were publications of duplicate data sets , unless the articles were reporting different outcome measures . Editorials and reviews of previously published data were also excluded . Additional publications not identified by the search strategy , unpublished reports and grey literature were included if they met the inclusion criteria and were recommended by the LRG . Sources were reviewed by the LRG to ensure they complied with the search inclusion and exclusion criteria . Following a review of the source titles and abstracts , during which duplicates were removed , the LRG performed a second review of the full text of any published sources selected to make the final selection of relevant sources to include . In an amendment to the original protocol the Literature Review Group sanctioned the extraction of surveillance data for 2011 from the MoPH Bureau of Epidemiology Surveillance Database website on 16 July 2012 . We chose not to exclude articles and other data sources nor formally rank them on the basis of the quality of evidence . Whilst an assessment of study quality may add value to a literature review , we were of the view that given the expected high proportion of surveillance data among the available data sources and the nature of surveillance data ( passive reporting of clinically-suspected dengue ) , such quality assessment would not add value to our review . The selected data sources were collated and summarized using a data extraction instrument developed as a series of Excel ( Microsoft Corp . , Redmond , WA ) spreadsheets . Data from literature reviews of previously published peer-reviewed studies and pre-2000 data published within the search period were not extracted . The original data sources and the extraction tables were made available to all members of the LRG for review and analysis . In view of the expected heterogeneity of eligible studies in terms of selection and number and classification of cases , a meta-analysis was not conducted; a narrative synthesis of our findings is presented . For the purposes of the analysis , we defined national epidemics as those years in which the number of cases was above the 75th percentile for the period .
This review concentrates on national epidemiological data collated from several sources , including the latest data from the Thailand MoPH ( Table S1 ) . The literature searches identified 610 relevant data sources; of these , 40 fulfilled the inclusion criteria for the analysis ( Figure 1; Table S2 ) . Most national epidemiological data were derived from the annual surveys or statistical tables produced by the MoPH ( 12 sources [23]–[34] ) . Of the remaining 28 articles and reports , the majority were journal articles that mainly described regional epidemiological data derived from surveys and studies conducted in individual regions and provinces ( Table S2 ) and are used to support the national data with regard to regional incidence , serotype and age distribution . The AESRs published by the MoPH provide a source of country-wide reporting of dengue disease statistics for 2000–2011 [23]–[34] , albeit with some missing data owing to reporting variations . Between 2000 and 2011 , more than 860 , 000 dengue disease cases were reported , corresponding to an annual average of approximately 72 , 000 cases and 100 deaths , and an average annual incidence of 115 cases per 100 , 000 population . Peaks in the number of cases ( national epidemics ) that were above the 75th percentile ( 102 , 213 ) for the period occurred in 2001 , 2002 and 2010 , when 139 , 355 cases ( incidence rate 224/100 , 000 population ) , 114 , 800 cases ( 183/100 , 000 ) , and 116 , 947 cases ( 177/100 , 000 ) were reported , respectively; another peak of 89 , 626 cases ( 142/100 , 000 ) , which was at the 70th percentile , occurred in 2008 ( Figure 2 ) . The lowest incidence occurred in 2000 ( 30 . 14/100 , 000 ) [23]–[34] . Since 2002 , the proportion of the total number of reported cases of DF and DHF reversed , while the proportion of DSS remained relatively stable over the decade , ranging between approximately 1% and 3% ( Figure 3 ) [23]–[34] . The reasons for the change in DF∶DHF ratio change are more probably more related to reporting behaviours than changes to the reporting system . During the 2000–2011 period there were no fundamental changes to the case reporting system . There has however been a change in reporting behaviour over the review period . A DF diagnosis relies on voluntary reports , which reflect to physicians' attention and willingness to report and their sense of importance of this matter . Moreover , in 1999 the King's Project ( a large prevention and control programme for dengue ) was introduced in which the aim was to increase people's knowledge of the disease through education and television advertisements [35] . Consequently , patients attended hospital earlier resulting in early diagnosis . Physicians cooperated with the programme by reporting DF , whereas previously reporting was focused on severe forms of dengue ( DHF and DSS ) . Improved physician awareness to the disease was assisted by better diagnostic capabilities . In particular , laboratory facilities improved in many areas and the results were reported back to local hospital from the central laboratory faster than before . In addition , following the 2005 avian flu outbreak more PCR laboratories became available at the regional level [26] . Greater diagnostic capabilities ( possibly through the wider use of immunoglobulin G ( IgG ) /IgM test kits and the NS1 antigen test , which may help confirm the diagnosis of mild dengue virus infections ) and changes in surveillance methods may also have contributed to the increasing proportion of DF cases detailed in the AESR in recent years . The number of deaths due to dengue disease reported between 2000 and 2011 , and the mortality rate ( deaths per 100 , 000 population ) , broadly reflect the number and incidence of cases reported . There were 1216 deaths reported from dengue disease between 2000 and 2011 , an average of 0 . 16 deaths per 100 , 000 population [23]–[34] . The highest mortality rate occurred during the large 2001 epidemic ( 245 deaths , 0 . 39 deaths/100 , 000 population ) [23] , [24] . Between 2003 and 2011 , the average case fatality rate ( CFR ) reported by the MoPH for DHF was 0 . 05% ( 0 . 03–0 . 09 ) and for DSS it was 4 . 45% ( range: 4 . 04–5 . 92 ) ; the highest CFR for DSS was in 2006 ( 5 . 92% ) [26]–[34] . There were no deaths attributed to DF over this period . No clear trend over time in the number of reported dengue disease cases could be discerned as the pattern of the annual number of cases of dengue disease over the review period was complicated by epidemic years . There was an overall decline in case fatality rates reported between 2000 and 2010 , reflecting rates reported in most of the dengue disease endemic countries in the Southeast Asia region between 1995 and 2000 [36] . These patterns may be the result of changes in reporting and improvements in case management . Annual dengue disease case numbers evident at the national level were broadly repeated at the regional level . Consistent with its higher population density , the Central region reported the highest number of dengue cases in most years and the most deaths over the period of the review . The most cases reported was in 2002 from the northeast region ( 37 , 191 cases ) [23]–[34] . The reported incidence rate was highest in the southern region in 2001 , 2002 , 2005 , 2007 and 2010 ( Figure 4 , Table S3 ) ; the incidence rate in the southern region in 2002 was more than double that reported in the other regions ( 402 . 54/100 , 000 population ) [23]–[34] . The highest mortality rate was reported from the southern region in 2001 and 2002 ( 0 . 77/100 , 000 population ) , as well as in 2010 ( 0 . 66/100 , 000 population ) [23]–[34] . Available regional data on the proportion of DF , DHF and DSS cases for the years 2003–2011 [26]–[34] show similar increases in the proportion of reported DF cases to those seen at the national level ( Central: from 20% to 39%; North: from 33% to 46%; Northeast: from 31% to 46%; South: from 34% to 48% ) . In Thailand , dengue remains a disease of children and young adults , with most cases occurring in individuals aged between 5 years and 24 years , who represent one third of the population ( Table S4 ) . However , the age group with the highest incidence changed from those aged 5–9 years to those aged 10–14 years in 2002 , and there has been a general shift in age group predominance of dengue disease over the survey period from younger towards older individuals over 15 years of age [31]–[34] , [37]–[39] ( Figure 5a and 5b ) , continuing a trend that was first observed in the 1980s [36] , . These findings are consistent with a recent publication reporting a significant increase in the age at dengue exposure in December 2010 in Rayong Province , Southeast Thailand [42] . Throughout the review period , relatively more cases of severe dengue ( DHF and DSS ) were reported in individuals aged between 5 and 14 years compared with those aged 15 years or older . In particular , DSS was less common in individuals aged 15 years or older . Data from cohort studies indicate that many children in the 5–14 years age group may be experiencing a second infection of dengue , which could account for the high incidence of severe disease in this age group [41] . Lower incidence rates of severe disease in older age groups could be due to reduced exposure to infection or reduced severity of disease in individuals experiencing their third or fourth infection [43] . Over the review period , approximately 70% of deaths due to dengue disease reported to the MoPH were in patients younger than 15 years . Typically , the highest CFRs were seen either in young children aged 0–4 years or in older adults aged 55–64 years , a trend that likely reflects the susceptibility of the young and old to more adverse consequences of dengue disease and its clinical management , as well as the risk associated with comorbidities in older adults [44] . However , the number of reported cases in those aged 55 years and above is small compared to the other age groups . Individuals aged over 65 years had the lowest reported incidence rate of dengue overall , and the only case fatalities in this age group were recorded in 2001 , 2005 and 2010 . Comparable regional data for age-related distribution of dengue were not recorded in the studies selected for this review . Individual studies suggest a pattern similar to that seen nationally , with younger age groups more likely to contract dengue than adults and the elderly [37]–[39] . Although more females than males were reported to have the disease in 2009 ( male∶female ratio 1∶1 . 6 ) [32] , [45] , [46] , in general , slightly more males than females were affected by dengue over the survey period , with reported male∶female ratios of between 1 . 1∶1 and 1 . 2∶1 [26] , [29]–[31] , [33] . These differences may be due to differences between the sexes in health-seeking behaviours in Thailand [37] . The available data show a seasonal peak in the numbers of cases ( Figure 6 ) and deaths ( data not shown ) due to dengue between May and September annually [23]–[34] , [47] , [48] which is probably due to seasonal changes in climate [14] , and the association between the active season of the vectors and the wettest months . Thus the pattern coincides with the rainy season in Thailand , which , although it varies slightly from region to region and is largely dominated by the monsoon , can be classified broadly as May/June to October . At the time of this review , comprehensive regional DENV serotype data for Thailand from the MoPH AESRs were only available for the period 2005–2010 . These serotype data show a broadly similar pattern in each region , with a reduction in the proportion of DENV-1 and an increase in the proportion of DENV-2 isolates over that period ( Figure 7 ) [28]–[33] . DENV-4 peaked during 2005 and 2006 and then declined , but remained in circulation in the Central region throughout this 5-year period , albeit at a decreasing percentage of all dengue disease cases ( 4 . 6–6 . 2% during 2008–2010 , compared with 10 . 4% in 2007 and 46 . 1% in 2005 ) . By contrast , in 2009 and 2010 , DENV-4 was not isolated in samples from the North or Northeast regions and was reported at <2% in the South region . DENV-3 circulated in all regions throughout the whole period . In general , between 2000 and 2010 , DENV-1 and DENV-2 were the most commonly reported serotypes in national and/or regional studies in Thailand [23]–[33] , [39] , [48]–[53] ( Table S5 ) . However , during the years 2000–2002 and 2008–2010 , DENV-3 was more commonly identified than during the middle part of the decade [23]–[33]; between 2003 and 2008 , reports of DENV-4 were more common than during 2000–2002 and 2009–2010 . In 2010 , the most commonly identified serotype was DENV-2 , representing over half of all those isolated ( 54 . 6% ) , followed by DENV-1 ( 25 . 5% ) , DENV-3 ( 15 . 3% ) and DENV-4 ( 4 . 6% ) [33] . Anantapreecha et al . also found similar temporal and spatial changes in the predominant DENV serotype [50] , [54] , [55] . Whereas most epidemiological reports of dengue in Thailand address the magnitude of clinically apparent infections , a number of studies published during the review period investigated both apparent and inapparent infections . Inapparent infections may have important public health implications in understanding virus transmission and the pathogenesis of dengue disease illness [56] . A variable proportion of inapparent infections relative to clinically apparent infections were reported [48] , [56]–[60] . An active case surveillance in 2119 primary school children ( median age 9 . 3 years ) in a rural setting in Kamphaeng Phet , North region , by Endy et al . reported an overall incidence of dengue infection for the year 2000 of 2 . 2%: 0 . 8% symptomatic infections and 1 . 4% clinically inapparent infections , a symptomatic to inapparent ratio ( S∶I ratio ) of 1∶1 . 75 [48] . A later study reported an overall S∶I ratio of 1∶3 for the period 2004–2008 [56] , [57] . Similarly , during a large DF/DHF disease outbreak in Nakhon Pathom province ( Central region ) in 2001 , 8 . 8% of individuals ( age range: 0 years to over 50 years ) had an inapparent infection with dengue virus , as determined by IgM positivity , over a 2-month period between March and April . Most of the serologically positive individuals ( 80 . 8% ) reported no previous fever [58] . Like many surveillance programmes the starting point for reporting in Thailand is a visit to a healthcare provider or hospitalization . As such , the national surveillance data may be incomplete and likely under-reported similar to other Southeast Asian countries [61] . A recent analysis of data from prospectively followed cohorts with laboratory confirmation of dengue cases show that dengue incidence is under-recognized in Thailand and Cambodia by more than eight-fold [62] . Consequently changes in the level of healthcare attendance or in the level of reporting to surveillance system by physicians ( as discussed above ) may also affect the under- or over-reporting of dengue disease . Epidemiological knowledge in Thailand benefits from a nationwide surveillance system including virological surveillance , complemented by several local studies including cohort surveys . However , at the time of the review , some gaps in the epidemiological information regarding dengue disease in Thailand were identified such as age-stratified seroprevalence data , and data relating to the proportion of hospitalized cases in the reported cases which are not easily available . This literature review presents the epidemiology of dengue disease in Thailand over the period 2000–2011 . A key strength of this survey and analysis is that it describes the epidemiological data from a national aspect rather than from limited study site data . In addition , the review protocol aimed to minimize potential exclusions of valuable data sources including MoPH data , as well as searching for relevant books , unpublished data , abstracts and dissertations . More than 600 data sources were screened and the selected sources were subjected to a comprehensive data extraction method to capture the data , which adds strength to this review . However , by its very nature , this literature review captured mainly publicly available data and studies and is , therefore , subject to publication bias; the data presented here should be interpreted accordingly . Another limitation of this review is that much of the peer-reviewed data are drawn from certain regions , which may skew the findings . Use of consistent MoPH data in the analysis for this review has minimized potential bias from studies using different methodologies for collecting information , confirming disease and reporting data , although this does not guarantee a consistent approach . National surveillance systems are subject to the limitations inherent to passive surveillance data , such as under-reporting , misreporting , and reporting biases . The methods and requirements for the surveillance systems in Thailand have also changed over time and the impact of the historical evolution of the systems is unknown . In a number of papers , associations were proposed between both the burden and severity of disease and the specific DENV serotypes circulating in the population , the sequence of DENV serotypes causing primary and secondary infections or the dengue incidence in the preceding season , which indicate the multifactorial processes that influence dengue disease severity [48] , [51] , [52] , [56] , [57] , [61] , [63]–[66] . For example , DENV-1 has been linked with high morbidity and low mortality [61] , and DSS has been associated with secondary infections attributable to DENV-2 [63] . DENV-4 , which is generally found at low frequency in Southeast Asia [64] , is linked to lower levels of virulence [65] and lower reported incidence [66] . Findings such as these have prompted suggestions that changes in predominant serotypes are associated with changes in disease severity [51] ( see Guzman et al . , 2013 for full review [41] ) . While such research papers have contributed to understanding the dengue disease , in the absence of nationwide data it is not clear whether the results are circumstantial ( site specific ) and thus it is difficult to apply the findings to other parts of the country . Dengue disease is a public health priority in Southeast Asia , and Thailand contributes substantially to the regional disease burden . Over the review period wide yearly variations in incidence occurred , with regular epidemics in 2001 , 2008 and 2010 with dengue disease remaining a highly seasonal disease . Age group distribution of dengue disease shifted during the review period from younger towards older persons even if dengue disease in Thailand remain a childhood disease predominantly with higher severity reported in young children . Heterogeneous geographical patterns of the disease was observed from 2000 to 2011 including higher incidence rates reported in the South and serotype distribution variations in time and place . Passive nationwide surveillance system in Thailand is a source of consistent data including severity , age- and serotype related information . Further information on seroprevalence and on the proportion of hospitalized cases among all reported cases would be beneficial to the description and understanding of dengue epidemiology in Thailand .
|
We conducted this comprehensive systematic review to determine the impact of dengue disease in Thailand for the period 2000–2011 , and to identify future research priorities . Well-defined methods were used to search and identify relevant published research , according to predetermined inclusion criteria . In addition to information from studies published in the literature , the review draws largely on surveillance data from the Annual Epidemiological Surveillance Reports published by the Thailand Ministry of Public Health . The pattern of annual number of reported dengue cases over the review period was complicated by epidemic years; consequently , a trend in the number of reported cases could not be identified . It was apparent that despite a shift in age group distribution dengue from younger towards older persons , dengue in Thailand remains a predominantly childhood disease . The seasonality and heterogeneous spatial and temporal nature of the disease were confirmed . It is clear that the nationwide passive surveillance system is a source of consistent data relating to severity , age and serotype . However , several gaps were identified that would benefit the understanding of dengue epidemiology in Thailand , such as seroprevalence data and a record of the proportion of reported cases that are hospitalized .
|
[
"Abstract",
"Introduction",
"Methods",
"Results"
] |
[
"medicine",
"and",
"health",
"sciences",
"epidemiology"
] |
2014
|
Epidemiological Trends of Dengue Disease in Thailand (2000–2011): A Systematic Literature Review
|
Recent research has demonstrated that consumption of food -especially fruits and vegetables- can alter the effects of drugs by interfering either with their pharmacokinetic or pharmacodynamic processes . Despite the recognition of such drug-food associations as an important element for successful therapeutic interventions , a systematic approach for identifying , predicting and preventing potential interactions between food and marketed or novel drugs is not yet available . The overall objective of this work was to sketch a comprehensive picture of the interference of ∼ 4 , 000 dietary components present in ∼1800 plant-based foods with the pharmacokinetics and pharmacodynamics processes of medicine , with the purpose of elucidating the molecular mechanisms involved . By employing a systems chemical biology approach that integrates data from the scientific literature and online databases , we gained a global view of the associations between diet and dietary molecules with drug targets , metabolic enzymes , drug transporters and carriers currently deposited in DrugBank . Moreover , we identified disease areas and drug targets that are most prone to the negative effects of drug-food interactions , showcasing a platform for making recommendations in relation to foods that should be avoided under certain medications . Lastly , by investigating the correlation of gene expression signatures of foods and drugs we were able to generate a completely novel drug-diet interactome map .
Drugs and plant-based foods ( i . e . fruits , vegetables and beverages derived from them , referred to simply as “food” throughout the rest of the document ) manifest an intricate relationship in human health and have a complementary effect in disease prevention and therapy . In many diseases , such as hypertension , hyperlipidemia , and metabolic disorders , dietary interventions play a key part in the overall therapeutic strategy [1] . But there are also cases , where food can have a negative impact on drug therapy and constitute a significant problem in clinical practice . Recent research has demonstrated that foods are capable of altering the effects of drugs by interfering either with their pharmacokinetic or pharmacodynamic processes [2] . Pharmacokinetics includes the Absorption , Distribution , Metabolism and Excretion of drugs , commonly referred to jointly as ADME . Pharmacodynamic processes are related to the mechanisms of drug action , hence the therapeutic effect of drugs; interactions between food and drugs may inadvertently reduce or increase the drug therapeutic effect [3] . Until not long ago , our knowledge about drug-food interactions derived mostly from anecdotal experience , but recent scientific research can demonstrate examples , where food is shown to interfere with the pharmacokinetics and pharmacodynamics of drugs via a known , or partially known , mechanism of interaction: an inhibitory effect of grapefruit juice on Cytochrome P450 isoenzymes ( e . g . CYP3A4 ) that leads to increased bioavailability of drugs e . g . felodipine , cyclosporin and saquinavir and potential symptomatic toxicity has been reported [4]; green tea reduces plasma concentrations of the β-blocker nadolol , possibly due to inhibition of the Organic Anion Transporter Polypeptide 1A2 ( OATP1A2 ) [5]; activity and expression of P-glycoprotein ( P-gp ) , an ATP-driven efflux pump with broad substrate specificity , can be affected by food phytochemicals , such as quercetin , bergamottin and catechins , which results in altered absorption and bioavailability of drugs that are Pgp substrates [6]; an antagonistic interaction of anticoagulant drug warfarin with vitamin K1 in green vegetables ( e . g . broccoli , Brussels sprouts , kale , parsley , spinach ) , whereby the hypoprothrombinemic effect of warfarin is decreased and thromboembolic complications may develop [2]; sesame seeds have also been reported to negatively interfere with the tumor-inhibitory effect of Tamoxifen [7] . Judging from the examples above , under most in vitro drug-food interaction studies , food is either treated as one entity , or the study focuses on few , well-studied compounds , such as polyphenols , lipids and nutrients . Our main hypothesis in the current work is that the interference of food on drug pharmacokinetic or pharmacodynamic processes is mainly exerted at the molecular level via natural compounds in food ( i . e . phytochemicals ) that are biologically active towards a wide range of proteins involved in drug ADME and drug action . The hypothesis is certainly supported by the large number of natural compounds that have reached the pharmacy shelves as marketed drugs . Hence , the more information we gather about these natural compounds , such as molecular structure , experimental and predicted bioactivity profile , the greater insight we will gain about the molecular mechanisms dictating drug-food interactions , which will help us identifying , predicting and preventing potential unwanted interactions between food and marketed or novel drugs . However , unlike drug bioactivity information that has already been made available for system-level analyses via databases such as ChEMBL ( www . ebi . ac . uk/chembldb/ ) [8] and DrugBank ( http://www . drugbank . ca/ ) [9] , biological activity data and origin information of natural compounds are scarce and unstructured . To this end , we have developed a database generated by text mining of 21 million MEDLINE abstracts that pairs plant-based foods with the natural compounds they contain , their experimental bioactivity data and related human disease phenotypes [10 , 11] . In the present work , we are exploring this resource for links between the natural compound chemical-space of plant-based foods with the drug target space . By integrating protein-chemical interaction networks and gene expression signatures we provide a methodology for understanding mechanistically the effect of eating behaviors on therapeutic intervention strategies .
In order to sculpt the chemical space of the natural compounds included in plant-based foods , we resorted to our recently developed resource NutriChem ( www . cbs . dtu . dk/services/NutriChem-1 . 0 ) [11] , which includes 1 , 772 plant-based foods associated by text-mining with ∼8 , 000 unique natural compounds ( a . k . a . phytochemicals ) . Experimental bioactivity information exists in ChEMBL for less than half of these food compounds ( Fig . 1A ) . Within this cluster , we identified 463 phytochemicals with bioactivity at the range of drug activity against 207 drug targets ( i . e . targets related to drug pharmacodynamics ) , as well as 18 enzymes , 7 transporters and 3 carriers , ADME-relevant targets as deposited in DrugBank v . 3 . As shown in Fig . 1B , foods that are routinely part of our diet , such as strawberry , tomato , celery and maize , are involved via their bioactive phytochemicals in a high number of interactions with proteins within these 4 categories . Ginger’s phytochemical profile appears as the most biologically active , interacting in total with 151 proteins , most of which associated with drug pharmacodynamics . This molecular level evidence of food-drug interactions is also in line with the information from the scientific literature assembled in NutriChem , which links ginger with 87 different human disease phenotypes . It should be pointed out that the 15 highly interacting foods shown in the figure are not necessarily the best characterized in terms of number of assigned phytochemicals . The number of bioactive phytochemicals in them ranges from 18 for mango to 42 for camellia-tea , while foods like licorice and rhubarb , for example , contain similar number of bioactive compounds ( 33 and 24 respectively ) without , however , interacting with as many proteins within these 4 categories . Thus , the above result is not the outcome of data incompleteness biases in the scientific literature , but rather points towards specific structural characteristics of phytochemicals dictating drug-food interactions . In order to further hone in the dietary habits that augment the impact on drug efficiency , we created a network that relies on the number of unique protein interactions shared between different foods . As shown in Fig . 1C several sub-networks of foods interact with the same protein space; a property that could be taken into account when drugs targeting these proteins are prescribed . For example , safflower , lettuce and garlic form a small sub-network that shares more than 55 proteins with experimental activity data involving their phytochemicals . The most broadly active food group consists of guava , mango , strawberry , beansprout , camellia-tea , swede and tomato , with the average number of shared interacting proteins being more than 70 . Papaya , orange , dill , tangerine , cress and chili pepper , along with a few more foods , form an isolated module interacting with a separate protein target space . In all food clusters of Fig . 1C it is apparent that there is no phenotypic or higher level taxonomic characteristic of the foods that could be used to predict the shared interactions with the therapeutic protein space; this pattern has emerged from similarities in their phytochemical space . To get an insight of the pharmacodynamics processes that are mostly affected by the bioactive phytochemicals of our diet , we zoomed in on the interactions with drug targets . Comparing Fig . 2A , which presents the foods with the highest number of interactions with targets involved in drug pharmacodynamics , with Fig . 1B that relies on all protein interactions of a drug ( target , transporter , carrier and metabolic enzyme ) , we notice that rice and avocado have replaced maize and licorice in the top-15 list . Furthermore , categorizing drug targets based on their human disease association , demonstrates the broad spectrum of disease treatments that may be affected by dietary habits . As shown in Fig . 2A , drug targets for 13 disease categories , ranging from cancer , neurological and cardiovascular to infectious and immunological diseases , could be potentially altered by food components . Another observation from Fig . 2A , not surprising due to the well-known protective role of plant-based diet against cardiovascular and gastrointestinal diseases , is that their drug targets are highly associated with phytochemical activity . Furthermore , looking into the association between food and drug targets at a biological process level reveals a wide range of functions that are targeted by food components ( Fig . 2B ) . Nevertheless , our analysis points to that foods “show a preference” towards a specific drug target space that is significantly overrepresented ( Student’s t-test , p<0 . 05 ) with proteins involved in signal transduction , immune system and developmental processes ( Fig . 2B ) . Having identified the foods that interact the most with drug targets and the biological processes that these targets participate in , we took a step further and zoomed into individual proteins . We constructed a network for each disease category ( Fig . 2C ) , which links drug targets based on the drug-food pairs they share . For example in cancer , drug targets of the carbonic anhydrase family are tightly connected , as they share a large number of drug-food pairs . Looking into the neurological diseases we could identify a tight connection between the kappa- and delta- type opioid receptors , while for cardiovascular diseases a network of the 5-hydroxytryptamine receptors is highly targeted by the same drug-food pairs . Naturally , since many of the drug targets are shared between different disease classes , some of these networks were observed in more than one disease category . Nevertheless , similarly to our observations above at the biological process level , our analysis here revealed that drugs developed for certain protein targets are more prone to be affected by diet than others . In order to explore the identified drug-food interactions at a molecular level , we selected case studies from 5 disease categories and highlighted the food components with the highest binding affinity to the drug targets . As shown in Fig . 3 , aromatase , a protein targeted by 5 anticancer drugs ( Anastrozole , Testolactone , Exemestane , Letrozole and Aminoglutethiumide ) is also targeted by naringenin ( IC50 = 2 . 9nM ) , a compound found in licorice , beansprout and maize , among others . Kaempferol , present in lychee , onion , strawberry and other common foods has a high binding affinity ( IC50 = 3 . 0nM ) for the epidermal growth factor receptor , target of Lapatinib , Gefitinib , Vandetanib and Erlotinib anticancer drugs . For neurological diseases , serotonin , present in sunflower , potato and tomato interacts strongly ( Ki = 1 . 1nM ) with the 5-hydroxytryptamine receptors targeted by several drugs ( e . g . Loxapine , Buspirone , to name a few ) , whereas , aporphine , present in poppy-seed , binds to the D ( 2 ) dopamine receptor ( Ki = 527nM ) , target of Ofremoxipride , Sulpiride and other drugs ( Fig . 3 ) . P-hydroxybenzoic acid , a compound naturally found in coconut , currant , sprouted lentil , swede and other foods , binds strongly ( Ki = 920nM ) to carbonic anhydrase , target of the cardiovascular drug Trichlormethiazide . Lastly , resveratrol , a compound that earned its prophylactic reputation against cardiovascular diseases due to its presence in red wine ( represented by grape in Fig . 3 ) , was found in our analysis to interfere with the activity of several drugs ( Diclofenac , Raloxifene , etc . ) that target either the estrogen receptor or prostaglandin G/H synthase 2 ( involved in musculoskeletal diseases ) . Turning our focus to the effects of diet on the pharmacokinetics of drugs , we studied the interactions of phytochemicals with proteins involved in drug ADME . Fig . 4 illustrates the corresponding drug-food interaction networks for metabolic enzymes and transporters , where apigenin , quercetin , naringenin , resveratrol and nicotinic acid are the food components with the strongest binding affinities . These compounds are found in more than 40 foods; hence , a complete understanding of their interaction profile with drug ADME proteins is of utmost importance . For acetylcholinesterase and cholinesterase , two proteins involved in the metabolism of several drugs , e . g . Neostigmine ( myasthenia gravis ) , Isoflurophate ( glaucoma ) , Donepezil ( dementia ) , Galantamine ( dementia ) , the binding affinity of the phytochemicals quercetin and apigenin is lower than the one of the drugs , but still in the range of measured activities for these metabolic targets . In other cases , such as aromatase , involved in the metabolism of Anastrozole , Letrozole , Exemestane and Aminoglutethimide , drugs used against breast cancer , we encounter bioactive food components with stronger activities . Naringenin , a compound found in licorice , sugar pea , guava and others , has a binding affinity of IC50 = 1000nM against aromatase , comparable with the actual drug’s . Similarly , the ribosyl-dihydronicotinamide dehydrogenase , involved in the metabolism of primaquine , is targeted from resveratrol with binding affinity higher than that of the respective drug ( IC50 = 450nM ) ( Fig . 4 ) . Resveratrol interacts as well with the multidrug resistance protein 1 , involved in the transport of several cancer drugs ( Tamoxifen , Vinblastine ) and other types of drugs , such as the antiretroviral drug Nelfinavir or Haloperidol an antipsychotic medication . Despite a thorough investigation of the interaction network formed by the bioactive compound space of diet and the drug activity space , the obtained results of possible drug-food interactions heavily rely on the available data related to the phytochemical content of food as well as the activity of these molecules on human proteins . To overcome the barrier of data incompleteness we compared the gene expression signatures of diet with the ones of FDA approved drugs , looking for correlated and anti-correlated profiles . The statistical analysis was performed using the Connectivity Map [12] which includes gene expression signatures from 1 , 309 compounds , both FDA-approved drugs and bioactive compounds . We retrieved gene expression data for 9 foods that are linked in NutriChem with 390 unique compounds; these 390 compounds are chemically similar to both CMap compounds as well as FDA approved drugs currently present in DrugBank ( Fig . 5A ) . We could also retrieve 5 , 171 protein targets ( direct and indirect ) of these compounds , where “disease” is the most enriched pathway with 538 protein targets involved ( Fig . 5B ) . Other significantly enriched pathways include cell cycle , developmental biology and apoptosis . Looking into the gene expression profiles of these 9 foods , we noticed that collectively 9 , 072 genes appear significantly differentially expressed ( FDR corrected moderated t-test , p<0 . 05 ) between the control samples and the diet interventions . Interestingly , when these gene targets were further analyzed , the biological processes that were found significantly enriched have a high similarity with the protein space targeted by the phytochemicals ( Fig . 5B vs . Fig . 5C ) . However , what we also observed was that from the 5 , 171 proteins targeted by the food components , only 2 , 653 were found in the significantly differentially expressed ( DE ) gene list . In our attempt to understand the reasons behind this discrepancy we selected a sub-set of 56 food phytochemicals that were targeting proteins from both groups; the ones that showed a significantly different expression level and the ones that did not ( non-DE ) . We compared the binding affinity for those compounds having both DE targets and non-DE targets as well as the protein connectivity of their targets . While the protein connectivity analysis did not yield a statistically significant difference between the two groups , the IC50 values were significantly lower ( Wilcoxon rank-sum test p value< 0 . 05 ) for the compounds targeting the non-DE group of genes . Using as input the gene expression signatures of each of the 9 foods , we retrieved 133 CMap compounds , of which , 46 FDA approved drugs that have a significant correlated or anti-correlated profile ( Fig . 5D ) . These 46 FDA approved drugs were further mapped to disease categories showing that mostly drugs used against infectious diseases ( 13 ) , cancer ( 9 ) and neurological diseases ( 9 ) induce a gene expression signature that can be either enhanced or reversed by diet . In the drug-food interaction network shown in Fig . 5D , broccoli has the highest number of connections with drugs . Interestingly , all connections between broccoli and drugs are correlation-based , most of which display strong correlation coefficients . This finding sheds some additional light-from a mechanistic point of view- on the well-known beneficial effect of broccoli on human health . Orange and garlic induce a gene expression profile that is highly correlated with drugs used in cancer ( Carmustine , Mercaptopurine ) and reproductive disorders ( Dydrogesterone , Diethylstilbestrol ) ; orange specifically , is highly correlated with the activity of Orciprenaline ( drug against a metabolic disease ) , Pyrimethamine ( drug against an infectious disease ) and Hydroxyzine ( drug against a neurological disease ) . One notable case is olive oil; olive oil induces a gene expression signature highly anti-correlated with the anticancer drugs Mitoxanthrone , Irinotecan and Daunorubicin . Mitoxanthrone and Daunorubicin are typically used against leukemia , where olive oil has not demonstrated any beneficial effect . Irinotecan , on the other hand , is a drug used against colon cancer , a disease which several studies suggest that olive oil has actually a prophylactic effect on . The analysis presented here should serve as a proof-of-concept comparison of the global gene expression responses induced by drugs and foods . The food gene expression signatures used here come from multiple research groups , diverse experimental designs and different tissues from animal models or human subjects , which may influence the correlation with the drugs . Nevertheless , the significant reduction of next generation sequencing cost is expected to positively influence nutritional studies as well , and allow transcriptome profiling of diets in a high throughput manner that could then be analyzed using our approach for possible interactions with drugs .
Plant-based therapies have been used for a variety of symptoms for thousands of years while recently there has been a drastic growth in the consumption of herbs and natural supplements with health benefits . In relation to AIDS and cancer patients especially , two life-threatening diseases where classical drug treatment does not always have a guaranteed effect , the use of both multiple prescription drugs and herbal supplements is very prevalent [13 , 14] . Given that components of herbs and natural supplements interact with human proteins in a similar manner as drugs , there is a high potential for altering drug efficiency . Furthermore , phytochemicals are abundant in our diet and have been shown in vitro to influence human proteins and cell-cultures . Several have demonstrated activity against the same proteins as drugs , and thus , potentially influence their pharmacokinetics and pharmacodynamics behavior when consumed concomitantly . In the example of sesame seed that has been reported to negatively interfere with the tumor-inhibitory effect of Tamoxifen [7] , the protein responsible for the therapeutic effect of Tamoxifen is the estrogen receptor ( P03372 ) , which is also targeted by a number of different bioactive phytochemicals present in sesame , including beta-sitosterol [15][16] . Querying NutriChem for beta-sitosterol , we encounter it as phytochemical component of guava , onion , pomegranate , turnip , fennel , celery and kiwifruit—all common foods of our diet that could also be potentially involved in interactions with Tamoxifen and negatively affect its therapeutic activity . As another example , health professionals recommend to patients under medication against high blood pressure to avoid consumption of licorice ( http://www . ehow . com/list_5798754_foods-avoid-taking-beta_blockers . html ) . The mechanism of this drug-food interaction is not yet clarified , although it has been occasionally attributed to the presence of glycyrrhizin . Our analysis points though towards the phytochemical liquiritin contained in licorice . Liquiritin has been found to interact with the beta-2 adrenergic receptor ( P07550; Bioassay CHEMBL1738166 ) , which is the primary target of beta-blockers , such as Penbutolol , a drug against hypertension . The overall objective of this work was to gain knowledge on the interference of food phytochemicals with the pharmacokinetics and pharmacodynamics processes of medicine , with the purpose of elucidating the molecular mechanisms involved . To the best of our knowledge this is the first time of such a scale integration of data from the literature and online , publicly available databases coupled with gene expression analysis , for studying the effect of natural bioactive compounds from foods on proteins related to drug bioavailability and therapeutic effect . Our analysis brings into sight that cancer-related proteins are highly targeted by dietary molecules; since cancer is still one of the most deadly diseases , patients are willing to follow alternative therapeutic approaches , most often concomitantly with standard drug treatment , such as adopting a “healthy diet” that usually consists of fruits and vegetables . While this approach could be beneficial prior the onset of disease as a preventive measure , it should perhaps be adopted with caution when a patient is under drug therapy , as it may interfere with the therapeutic effect of the drug . The novelty of the platform presented here is that it takes into account the global effects of food , propelled by its rich natural compound content , increasing the level of confidence of the scientific community and medical professionals when making recommendations for foods that should be avoided under certain medications . We illustrate that ignoring the complete phytochemical content of a food and focusing on a couple of “hot” molecules , a strategy widely applied in traditional food research , will never reveal the true magnitude of drug-food interactions . Furthermore , we identify clusters of foods that target the same therapeutic space as drugs , a property that could potentially increase the chances for severe alterations of the drug activity if these foods are consumed concomitantly . We also point out a large number of food components that are potentially involved in yet not documented drug-food interactions supporting the notion that ignoring the complete chemical content of a food is a missing link for obtaining a holistic view of the effect of diet . From a methodological point of view we believe that including the actual bioactivity values of the phytochemicals against proteins related to drug bioavailability and therapeutic effect allowed us to go beyond a simple enumeration of interactions to a more comprehensive and possibly accurate mapping of food-drug associations . Our food-drug interaction network reveals that therapeutic interventions for every disease category can be potentially affected to some degree by diet , even though specific disease areas , e . g . cancer and neurological diseases , are most prone to the negative effects of drug-food interactions than others . Lastly , we believe that we have demonstrated with several examples the power of a systems-level analysis to answering the two most important questions for patients and clinicians: ( 1 ) which foods should be potentially avoided from a patient under treatment , and ( 2 ) which is the underlying mechanism behind these drug-food interactions . However we should also keep in mind that , since many of the food compounds that are strong binders to proteins are very common in our diet , it will certainly be a daunting task to actually design diets that will not include any such compounds . Thus , adding in the network analysis the actual concentration in food of each bioactive compound would give a more accurate picture of the extent and severity of these drug-food interactions .
The plant-based food compounds and their chemical structures were retrieved from NutriChem 1 . 0 [11] . FDA-approved small molecule drugs were retrieved from DrugBank v . 3 ( http://drugbank . ca/ downloaded on Jan 12th , 2014 ) . Food compounds and drugs were mapped to their protein interactions using ChEMBL v . 16 ( http://www . ebi . ac . uk/chembl/ downloaded on Sept 9th , 2013 ) . Binding activities were retrieved from ChEMBL Bioassays . Protein targets were categorized into “Drug target” , “Enzyme” , “Transporter” and “Carrier” , following the DrugBank categorization . For a food compound to be considered active against a protein target , it has to bind within the range of the drugs targeting the same protein . For proteins , for which the binding activity of drugs was unknown , the binding activity of the food compound was compared to the mean value of the binding activities for proteins from the same category ( i . e . drug target , enzyme , transporter or carrier ) . Drug protein targets were mapped to disease categories using the Therapeutic Target Database ( http://bidd . nus . edu . sg/group/cjttd/ downloaded on Sept 9th , 2013 ) [17] and the Human Disease Ontology [18] . Disease categories were selected at the third level of the human disease ontology . Drug proteins were assigned to biological systems using Reactome ( http://www . reactome . org ) . Chemical similarity between phytochemicals , CMap bioactive compounds and FDA-approved drugs . SMILES strings of phytochemicals were retrieved from PubChem [19] , while SMILES of the CMap bioactive compounds and FDA-approved small molecule drugs were retrieved from Connectivity Map build 02 [12] and DrugBank 3 . 0 [9] , respectively . Based on the chemical structures , molecular and physical descriptors were calculated for each compound using the RDKit plugin ( http://www . rdkit . org ) in KNIME [20] , including a 1024-bit Morgan circular fingerprint , Topological Polar Surface Area ( TPSA ) , octanol/water partition coefficient ( SlogP ) , Molecular Weight ( MW ) , number of Lipinski hydrogen bond acceptors ( HBA ) and donors ( HBD ) . Afterwards , a matrix of compound descriptors with 1029 columns was constructed , in which each row represented a phytochemical , a CMap bioactive compound , or an FDA-approved drug and a principle component analysis ( PCA ) using R was performed . Retrieval of direct and indirect protein targets of phytochemicals . Phytochemicals were mapped to exact InChI key matches in ChEMBL and similar ChEMBL compounds using the Morgan circular fingerprint . The Tanimoto Coefficient ( TC ) was calculated based on Morgan fingerprint . Two compounds were similar if TC ≥0 . 85 and their difference in molecular weight lower than 50 g/mol . Next , the interactions of phytochemicals and proteins were annotated by searching in ChEMBL the protein targets of those exactly matched or similar ChEMBL compounds . The bioactivities were filtered based on the following thresholds: for Ki , Kd , IC50 and EC50 , pchembl_value larger than 6; for inhibition , measurement value greater than 30%; for potency , measurement value lower than 50 μM . To deal with the multiple measurements of the same compound on the same protein , we calculated a frequency of “positive” measurements ( served as evidence of compound-protein interaction ) among all candidate measurements . Only chemical-protein interactions with a frequency of higher than 0 . 5 were considered confident and were used for further analysis . In addition to chemical-protein interactions from ChEMBL , we also included first-degree protein-protein interaction ( PPI ) partners ( a confidence score higher than 400 ) from STRING 9 . 1 [21] , in order to further expand our protein target space of phytochemicals . Note that this was only done for the protein targets of phytochemicals matching exactly to ChEMBL compounds . Only those PPI from human , rats and mice were included . After obtaining protein targets for phytochemicals , protein targets in rats and mice were mapped to their human orthologous proteins through Ensembl Biomart Homolog Service [22] . Microarray data extraction and analysis . ArrayExpress database [23] was first queried with a list of edible plants . Besides microarray data from human , experiments from rats and mice were included . For each microarray dataset , the raw data were background-corrected and normalized with RMA [24] . Quality check of the datasets was conducted in R with the arrayQualityMetrics package [25] . After manual inspection and quality check , 17 gene expression microarray experiments remained for downstream analysis . Differential expression analysis of pre-processed microarray data was performed with the R Bioconductor limma package [26] . A p-value of 0 . 05 after false discovery rate ( FDR ) correction for multiple hypothesis testing was used as the cutoff when selecting significantly differentially expressed ( DE ) genes [27] . Our analysis resulted in 9 foods with significant gene expression signatures and available phytochemical composition in NutriChem ( see S5 Table ) . For each food , the list of DE genes was split into two lists of up- and down-regulated genes , referred to as “tag lists” in Connectivity Map [12] . The genes in the tag lists were converted to the CMap-compatible probe-set IDs from Affymetrix GeneChip Human Genome U133A Array . For DE genes in rats and mice , the human homolog genes were obtained through Ensembl Biomart Homolog Service [22] before mapping to required probe-set IDs . The paired tag lists were used to query Connectivity Map to reveal the correlation or anti-correlation relationship between foods and drugs . Based on the output from Connectivity Map , CMap drugs or bioactive compounds were considered to correlate or anti-correlate with foods if they had an absolute enrichment score higher than 0 . 75 , permutation p-value less than 0 . 01 and a non-null percentage above 80% .
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Vegetables and fruits that are otherwise considered beneficial to our health can have serious consequences in medical care . Interference of plant-based foods with drug performance and pharmacological activity may potentially contribute to an increased risk of side effects or treatment failure . A well-known example of a drug-food interaction , the inhibitory effect of grapefruit juice on cytochrome P450 , results in increased bioavailability of drugs such as felodipine , cyclosporine and saquinavir , which could lead to drug toxicity and poisoning . Although the importance of drug-food interactions has long been known , a systematic approach to identify , predict and prevent potential interactions between food and drugs has not yet been established . This work sets the ground for the understanding of the key molecular mechanisms of drug-food interactions with the scope to optimize therapeutic strategies and improve patient care . We tackle this problem using NutriChem , a database we have recently developed with information from the scientific literature and online databases related to natural compound origin and bioactivity . This systems chemical biology approach provides the basis for the identification and study of the substances in plant-based foods that affect the human proteins that are relevant for the pharmacokinetics and pharmacodynamics of current medicine .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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Developing a Molecular Roadmap of Drug-Food Interactions
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Although current programmes to eliminate lymphatic filariasis have made significant progress it may be necessary to use different approaches to achieve the global goal , especially where compliance has been poor and ‘hot spots’ of continued infection exist . In the absence of alternative drugs , the use of higher or more frequent dosing with the existing drugs needs to be explored . We examined the effect of higher and/or more frequent dosing with albendazole with a fixed 300mg dose of diethylcarbamazine in a Wuchereria bancrofti endemic area in Odisha , India . Following screening , 104 consenting adults were randomly assigned to treatment with the standard regimen annually for 24 months ( S1 ) , or annually with increased dose ( 800mg albendazole ) ( H1 ) or with increased frequency ( 6 monthly ) with either standard ( S2 ) or increased ( H2 ) dose . Pre-treatment microfilaria counts ( GM ) ranged from 348 to 459 mf/ml . Subjects were followed using microfilaria counts , OG4C3 antigen levels and ultrasound scanning for adult worm nests . Microfilarial counts tended to decrease more rapidly with higher or more frequent dosing at all time points . At 12 months , Mf clearance was marginally greater with the high dose regimens , while by 24 months , there was a trend to higher Mf clearance in the arm with increased frequency and 800mg of albendazole ( 76 . 9% ) compared to other arms , ( S1:64% , S2:69 . 2% & H1:73 . 1% ) . Although higher and/or more frequent dosing showed a trend towards a greater decline in antigenemia and clearance of “nests” , all regimens demonstrated the potential macrofilaricidal effect of the combination . The higher doses of albendazole did not result in a greater number or more severe side effects . The alternative regimens could be useful in the later stages of existing elimination programmes or achieving elimination more rapidly in areas where programmes have yet to start .
The Global Lymphatic Filariasis Elimination Programme ( GPELF ) had its inception in 1998 following agreements between the World Health Organization and the international pharmaceutical companies GlaxoSmithKline ( GSK ) and Merck to donate supplies of , respectively , albendazole and ivermectin for the programme [1] . By 2013 MDA programmes had commenced in 56 of the 73 endemic countries while 13 countries had progressed to the post-MDA surveillance phase . Nearly 984 million people were targeted and 4 . 4 billion doses had been distributed between 2002 and 2012 [2] . Although the programme envisaged 5–6 annual interventions , not all countries were able to start simultaneously , and in large countries , logistic problems have forced extension over many years . Despite steady progress over the past 15 years , there have been many obstacles [3] . Currently , several countries , mainly in Africa , have yet to start their programmes [4 , 5] . Pockets of infection ( Hot Spots ) and less than anticipated decline in microfilaria rates because of poor treatment compliance have been observed especially in large countries in Asia where programmes have found it difficult to achieve the minimum recommended ( 65% ) epidemiological coverage . These problems are likely to prolong the time to achieve LF elimination targets [6] . While these difficulties were foreseen at the onset , effective solutions still need to be worked out [7] . The global programme still relies on the original pharmaceutical tools ( albendazole/ivermectin in Africa and albendazole/ diethylcarbamazine ( DEC ) elsewhere ) and alternative treatments have yet to emerge [8] . Although development of macrofilaricidal compounds is advancing , these are still a long way from regulatory approval let alone widespread deployment [9 , 10] . In such a scenario , improvement of current regimens could permit shorter periods of implementation , especially for those countries that are yet to start and bring greater effectiveness in dealing with hotspots or help accelerate sluggish programmes . The initial drug regimens used at the initiation of the Global Programme were based on existing approved doses and did not require extensive additional investigation or drug approval . However no attempts to investigate the effectiveness of alternative regimens , either or use of higher or more frequent dosing were made [11] . A study conducted in Mali in a population that had received several cycles of ivermectin for onchocerciasis and several annual cycles of albendazole/ivermectin for lymphatic filariasis [12] showed that the higher dose of albendazole ( 800 mg ) and ivermectin ( 200 mg ) given twice yearly was more effective than the standard annual regimen . The effect of similar modifications of DEC containing regimens has yet to be investigated . The current study was conducted in India to investigate the effect of increasing the dose of albendazole from 400 mg to 800 mg and /or increasing the frequency of dosing for W . bancrofti infection . Since the Indian programme uses a single dose of 300 mg DEC for all individuals > 15 years , the dose of DEC remained unchanged [13] . The study area around Bhubaneswar , in Odisha State , India has seen intermittent MDA activity initially using DEC alone and later DEC and albendazole .
The study was undertaken following ICH—GCP guidelines , with written informed consent from the participating individuals both for screening and prior to study enrolment . The protocol and consent information was approved by the Human Ethical Committee of the Regional Medical Research Centre , Bhubaneswar . The study protocol was further reviewed by Indian Council of Medical Research and Health Ministry Screening Committee , Govt . of India . The study was monitored by an independent external monitor ( Dr T K Suma , Alleppey , Kerala ) , who checked completeness of records , compliance with GCP and accuracy of data entry . A W . bancrofti endemic area within thirty kilometres of Bhubaneswar in the Khurda district of Odisha was chosen for selection of subjects . Community meetings were arranged to provide information on the importance of the filariasis elimination programme and of the study prior to enrolling individuals for the study . In the filaria endemic villages , night blood was collected by finger prick between 19 . 00 and 23 . 00hrs from all individuals between 18 and 55 years of age during a door to door survey . Thick smears from 40μl blood were examined for microfilaria . Microfilaremic individuals who provided consent were further screened for eligibility . Subsequently , in eligible subjects , an intravenous blood sample ( 5ml ) was collected between 21 . 00–22 . 00 hours and divided into two aliquots; 2ml with EDTA and 3ml without anticoagulant . From 1ml EDTA blood , the microfilaria count was determined using the Nuclepore filtration technique . Haemoglobin was estimated by automated cell counter ( MS4 , Melet Schloesing Laboratories ) ; serum ALT and creatinine were measured by automatic biochemistry analyser ( Cobas Integra 400 , Roche ) and pregnancy was excluded using a β-HCG rapid test on early morning urine samples . W . bancrofti ( OG4C3 ) antigen levels were also obtained using an ELISA kit ( TropBio , Australia ) . Subjects of either sex between 18 to 55 years of age , with microfilaria counts greater than 50/ml . of blood , who accepted the hospitalization and follow up requirements were included in the study . Female subjects who were either pregnant or lactating were excluded as were subjects with serum ALT level of > 30 units/dl , creatinine level > 1 . 2 mg/dl or haemoglobin level of <10 gm% . Individuals satisfying the inclusion and exclusion criteria and providing a second consent for study inclusion were allocated sequentially to one of four treatment groups according to a pre-determined list generated in blocks of 26 using Prism software ( Graphpad Prism 6 . 0 ) . Ultrasonography of inguinal , scrotal , axillary , thigh and arm lymphatic systems was performed prior to treatment using a Doppler Ultrasonography unit ( GE , Logique 400 PRO , WIPRO ) using a linear high resolution 7–12 Mega Hz probe , to record any “filarial dance” sign . The individuals , in groups of 4–6 , were then admitted to the hospital of the Kalinga Institute of Medical Sciences , Bhubaneswar , for study drug administration , observation and management of adverse events if required . The drugs were taken orally by the subjects around 8 . 30am after breakfast , under supervision of hospital staff . Where the subject vomited within 1hr of ingestion , the dose was repeated . The subjects were discharged from hospital after two days and followed at home for up to 7 days post drug intake . A 2x2 factorial design with albendazole at two levels ( 400mg-low , 800mg-high ) and number of doses per year at two levels ( 1dose-low , 2 doses-high ) was used . The resulting four regimens are coded as S1 , S2 , H1 and H2 . For each of the regimens 26 patients were allocated with a total of 104 for the study . These numbers were based on data comparing single and multi-dose regimens for the treatment of lymphatic filariasis [7 , 14] . We assumed that standard annual therapy would clear microfilaremia in approximately 25% of subjects at 1 year; whereas the multi-dose therapy should give 75% clearance . Seventeen subjects per group are needed to detect this difference with two-sided alpha of 0 . 05 and 80% power while with 90% power it requires 23 per group . Allowing for 10% attrition , 26 subjects were recruited for each study arm . The four treatment arms were as follows: The drug formulations used for the study were authorized drugs marketed in India as Banocide ( DEC ) 100mg tablets ( GSK , Nashik , India ) and Zentel ( albendazole ) 400mg tablets ( GSK , Solan , India ) . The subjects were followed up every 6 months up to 24 months for evaluation with drug administration as appropriate . Ultrasonography was repeated in those subjects with “filarial dance sign” detectable adult worm at base line , within 48–72 h of the first dose , and at 12 months and 24 months by the consultant ultrasonographer ( C H Mohanty ) who was unaware of the treatment received by the patients . Microfilarial count , OG4C3 antigen titre , urine β HCG test in females , serum ALT and creatinine were evaluated blind at follow up visits before the subjects received the next drug dose . All subjects were admitted to hospital for drug administration and for 2 days post drug to monitor for side effects / adverse events . Side effects/ adverse events were graded based on a previously used scale [15] and managed with simple remedies . Clinical evaluators were blind to the treatment given . The clinical and laboratory information were recorded in a predesigned format . The data was entered into Excel and analysed using SPSS version 16 with appropriate tests for parametric and non parametric variables . Correctness of data was ensured by double entry and matching of entered data . The results were expressed as percentage changes and mean reductions at 6 , 12 ( the primary endpoint ) , 18 and 24 months . The chi-square test was used to compare the proportions , Student’s t-test for comparing mean differences between two regimens and analysis of variance for comparing all the four group means at 12 months , at 18 months and at 24 months . The net effect of the high levels was quantified using the contrast of a factorial design . The significance level was fixed at 5% level .
The study was initiated in October 2008 and final two year follow ups were conducted in September 2012 , enrolling study subjects from 8 villages in the W . bancrofti endemic area of Khurda district in state of Odisha , India . This covered a rural area of around 150 square kilometres between Bhubaneswar ( 20 . 270 N , 85 . 840 E ) and Khurda ( 20 . 170N , 85 . 670E ) . The population is mostly middle and lower socioeconomic status within an agriculture based economy . In all , 1751 individuals between 18 and 55 years of age were screened to identify 118 ( 6 . 74% ) microfilaraemic subjects . 104 individuals who satisfied the inclusion/exclusion criteria and were willing to participate in the study were screened for eligibility . The subjects were randomly allocated to one of the 4 arms of the study and followed up with 6 monthly screening . All 104 individuals ( 26 in each of the four arms ) received DEC + albendazole at baseline in the dosage prescribed for the respective arm . A 40-year-old male allocated to S1 arm died 9 months after the initial treatment following an acute abdominal emergency not considered to be related to the drug or study procedures . The remaining 103 study subjects all completed 24 months follow up . The age and gender distribution of enrolled subjects ( n = 104 ) was comparable among the four arms ( p = 0 . 259 Student T test ) . There was a preponderance of males in all 4 treatment groups with approximately 17% females in each group , with most being below 35 years of age . Blood chemistry values were in the normal range in all subjects . The microfilarial density and mean OG4C3 units of the study population at enrolment are provided in Table 1 . At baseline ( 0M ) , the geometric mean microfilarial density was not significantly different in the four groups and ranged from 348 to 459 mf/ml ( p = 0 . 822 ) . The mean OG4C3 antigen units were also comparable ( p = 0 . 057 ) . Ultrasonography prior to first dose detected adult worm nests with filarial dance sign ( FDS ) in 13 subjects in each of S1 , H1 and H2 arms and 15 in S2 arm ( p = 0 . 219 ) . There was a progressive decrease in microfilaraemia and clearance of microfilaria from the circulation in all the four arms over the 24months ( Table 2 ) . The increase in dose and frequency reduced Mf counts significantly at the end of 12 months ( p = 0 . 021 ) compared to the standard regimen ( S1 ) . At 24 months , Mf clearance was higher in H2 arm ( 76 . 9% ) compared to other arms , ( S1:64% , S2:69 . 2% & H1:73 . 1% ) although this was not statistically significant ( p = 0 . 77 ) . The mean microfilarial density showed a sharp reduction by 6 months from baseline ( S1:84 . 23% , S2:80 . 30% , H1:82 . 85% , H2:85 . 57% ) in all four arms with a slower decline thereafter ( Table 3 ) . Mean percentage reductions in microfilarial density from individual baseline values are shown in Fig . 1 . The differences in geometric mean Mf density are shown in Tables 4 & 5 ( log transformed data ) . The analysis shows that , at 12 months , if albendazole is given biannually ( S2 & H2 ) , instead of annually ( S1 and H1 ) there is an extra reduction in mf count of 0 . 5 log units and if albendazole is given 800 mg ( H1 and H2 ) , instead of 400mg ( S1 & S2 ) , there is an extra reduction of 0 . 94 log units . Biannual treatment with 800mg albendazole ( H2 ) reduces the Mf count by 1 . 44 log units which is statistically significant ( p = 0 . 021 ) . At 24 months , albendazole given biannually ( S2 & H2 ) , produced an extra reduction of 0 . 74 log units and if albendazole was given at the higher dose ( 800 mg ) ( H1 and H2 ) instead of 400mg , there was an extra reduction of 0 . 64 log units . Biannual treatment with 800mg ( H2 ) albendazole reduced the Mf count by 1 . 09 log units which was statistically significant ( p = 0 . 021 ) . It can be concluded that an increase in dose and frequency can reduce Mf counts significantly at the end of 12 months and 24 months compared to the standard regimen ( S1 ) . Among the individuals showing FDS at baseline , repeat ultrasonography at day 3 , 12 months & 24 months showed that disappearance of FDS was greater in H2 treatment arm , being complete at 12 months and 24 months compared to other 3 arms ( Table 6 ) , none of which showed complete clearance during the period of follow up . However these differences were not statistically significant due to the small numbers of individuals involved . Table 7 shows the change in antigen clearance and frequency of individuals showing reduction in antigen units at different time points ( p = 12 M: 0 . 942 , 18 M: 0 . 94 & 24 M: 0 . 23 ) . Mean percentage reductions in OG4C3 from individual baseline values are shown in Fig . 2 . OG4C3 antigen clearance was seen to start at 12 months in S1 & H2 arms and at 18 months in S2 and H1 arms and increased over time . At 24 months , OG4C3 clearance ranged from 26 . 9% to 73 . 1% ( p = 0 . 007 ) . Since the variance in the antigen units was very large due to wide range of values , logarithmic transformation was used to stabilize variance and one way ANOVA was performed on the log transformed values ( Tables 8 raw data and 9 log transformed data ) Results indicated , at 12 months ( i ) if albendazole is given biannually ( S2 & H2 ) , instead of annually ( S1 & H1 ) there was an extra mean reduction of 0 . 66 log units in OG4C3 antigenemia ( ii ) if albendazole is given as 800 mg ( H1 & H2 ) , instead of 400mg ( S1 & S2 ) , there was an extra mean reduction 0 . 31 log units of OG4C3 antigenemia and ( iii ) if both are given at high level ( H2 ) there is an extra reduction of 0 . 80 log units in OG4C3 At 24 months , ( i ) If albendazole is given biannually ( S2 & H2 ) , instead of annually ( S1 & H1 ) there is an extra mean reduction of 0 . 53 log units in OG4C3 antigenemia ( ii ) If albendazole is given at 800 mg ( H1 & H2 ) , instead of 400mg ( S1 & S2 ) , there is an extra mean reduction of 0 . 86 log units of OG4C3 antigenemia and ( iii ) If both are given at high level ( H2 ) there is an extra reduction of 1 . 38 log units in OG4C3 antigenemia . It can be concluded that increase in dose and frequency reduces OG4C3 log counts at the end of 12 months and 24 months . Among individuals exhibiting adult worm ( USG ) at baseline , OG4C3 clearance was observed later at 18 month follow up ( S1 = 7 . 7% , S2 = 6 . 6% , H1 = 7 . 6% & H2 = 15 . 3% ) and increased over the subsequent 6 months ( S1 = 53 . 8% , S2 = 26 . 6% , H1 = 76 . 9% & H2 = 53 . 8% ) . Following drug administration , the frequency of adverse events was comparable in all four arms ( S1: 68 . 38% , S2: 53 . 84% , H1:61 . 53% & H2: 50% ) ( p = 0 . 669 ) after the first dose ( Table 10 ) . The difference was also not significant at 6 months ( p = 0 . 124 ) or 18 months ( p = 0 . 305 ) dosing . However , at 12 months , S1 ( 28% ) & H1 ( 15 . 4% ) annual arms had a higher frequency of adverse events compared to S2 ( 3 . 8% ) & H2 ( 3 . 8% ) biannual arms . The adverse events noted were light-headedness ( 31 . 7% ) , fever ( 22 . 1% ) , body ache ( 4 . 8% ) , unsteadiness ( 4 . 8% ) , dizziness ( 2 . 8% ) , drowsiness ( 2 . 8% ) , fatigue ( 1 . 9% ) , chills ( 1 . 9% ) , itching ( 0 . 9% ) , and weakness ( 0 . 9% ) . There was no difference in the pattern of side effects noted in different arms ( p>0 . 05 ) . There were no severe drug related adverse events reported following any treatment , and the events that did occur could be managed conservatively .
The study was undertaken to investigate alternative regimens to those currently used in GPELF mass drug administration programmes outside Africa . This is the first attempt to rationalise or improve DEC intervention regimens aiming for greater effect on microfilaria clearance and /or adult worm suppression . Since new drugs are not available , the only alternative is either to increase doses of drugs or the frequency of dosing . Since DEC is already used at close to its acceptability ceiling by programmes ( in India using 300 mg doses , rather than 6mg/kg ) , it is only possible to increase the albendazole dose [11] . Thus three test arms were used to compare with the standard regimen . This study enrolled adults infected with W . bancrofti having mf density >50mf/ml . Excluding individuals with a low mf count may reduce possible observer errors in counting low mf levels and also the interpretation of the impact of treatment on changes in mf density . Age , gender and endemicity matching of the population enrolled in different arms minimized the confounding effects . The primary endpoint for the study was taken as Mf clearance at 12 months after initiation of treatment to be consistent with past studies , but follow up and analysis was continued for a further 12 months to establish whether any differences that might be seen at 12 months were sustained . Microfilarial clearance in all the four arms was progressive over time with a higher rate of decline in the mf prevalence in H2 arm . Although the difference in mf clearance between arms was not statistically significant over the 24 months of follow-up , the decline in mf prevalence in H2 arm gives the impression that if followed further , this arm could attain 100% mf clearance earlier than the other arms . This has the potential to shorten the period required for elimination . This was also indicated by the parallel reduction in microfilarial density where at both 12 and 24 months there was a significantly greater reduction in the high dose twice yearly arm ( H2 ) compared to the other arms . A similar study using high dose twice yearly albendazole and ivermectin in Mali also showed enhanced suppression of microfilaria [12] . Although decline of antigen levels and rates of FDS occurred in all treatment groups , complete disappearance of FDS in worm nests by 12 months in the H2 arm without any recurrence at 24 months , and the decline in OG4C3 suggest that there is a significant macrofilaricidal effect at this dose . Increased adverse events/side effects directly due to the higher dose of albendazole or as a result of interaction with DEC could be a limiting factor to deployment [16 , 17 , 18 , 19] . However , 800mg albendazole has been extensively used for longer periods for systemic helminth infections such as echinococcosis and neurocysticercosis and is generally well tolerated [20] . In this study there was no increased frequency of adverse events when using 800 mg albendazole . All adverse events/side effects were self-limiting and no serious adverse events were encountered . The pattern of adverse events is typical of those encountered following treatment of microfilaria positive patients , and the higher frequency of adverse events encountered at 12 months by patients in the annual dose arms , whether high or low dose can be explained by the less effective clearance of microfilaria with an annual regimen . The results of this study have important implications for GPELF in areas where onchocerciasis is not co-endemic . The annual low dose regimen performed well in this study and clearly remains the treatment of choice for the majority of situations . However , the availability of an alternative DEC-based regimen that uses a higher dose of albendazole with increased frequency could assist programmes to meet their elimination targets . In particular , this regimen may find use in areas/countries where MDA programmes are yet to be initiated , in “hot spots” identified during surveillance of ongoing programmes and in arresting transmission within shorter time frames [6] . However , programmes will undoubtedly need to weigh the benefits of a shorter duration regimen in the context of higher costs to programmes resulting from additional demands on logistics , training and community mobilization . Drug costs are likely to be restricted to procurement of DEC because of the commitment of GSK to provide albendazole free of cost to the programme . It is likely that programme implementation costs to the states/countries can be significantly curtailed by reducing the number of years required for elimination . Clearly , further studies with larger numbers to confirm and consolidate these data will be required before policy changes are made .
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In order to achieve global elimination of lymphatic filariasis , it may be necessary to consider alternative approaches to mass treatment using higher or more frequent dosing with the existing drugs used in the programmes . Outside Africa , the drugs used are albendazole and diethylcarbamazine given annually . The current study is the first to examine the use of higher or more frequent dosing in a bancroftian filariasis endemic area outside Africa . Four groups of infected subjects were followed for two years using standard techniques for monitoring drug efficacy in Odisha , India . We showed that higher doses of albendazole , or 6-monthly treatment , were more effective than the standard regimen in producing clearance of microfilaria and reductions in antigenemia . Additionally we found that these regimens were more effective in killing the adult filarial worms in the lymphatics . Importantly , the higher doses used did not increase the risk of side effects . These alternative approaches could accelerate lymphatic filariasis elimination either at the end of existing programmes or to permit new programmes to achieve their goals faster .
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[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
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A Randomized Controlled Trial of Increased Dose and Frequency of Albendazole with Standard Dose DEC for Treatment of Wuchereria bancrofti Microfilaremics in Odisha, India
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The opportunistic fungal pathogen Candida albicans frequently produces genetically altered variants to adapt to environmental changes and new host niches in the course of its life-long association with the human host . Gain-of-function mutations in zinc cluster transcription factors , which result in the constitutive upregulation of their target genes , are a common cause of acquired resistance to the widely used antifungal drug fluconazole , especially during long-term therapy of oropharyngeal candidiasis . In this study , we investigated if C . albicans also can develop resistance to the antimicrobial peptide histatin 5 , which is secreted in the saliva of humans to protect the oral mucosa from pathogenic microbes . As histatin 5 has been shown to be transported out of C . albicans cells by the Flu1 efflux pump , we screened a library of C . albicans strains that contain artificially activated forms of all zinc cluster transcription factors of this fungus for increased FLU1 expression . We found that a hyperactive Mrr1 , which confers fluconazole resistance by upregulating the multidrug efflux pump MDR1 and other genes , also causes FLU1 overexpression . Similarly to the artificially activated Mrr1 , naturally occurring gain-of-function mutations in this transcription factor also caused FLU1 upregulation and increased histatin 5 resistance . Surprisingly , however , Mrr1-mediated histatin 5 resistance was mainly caused by the upregulation of MDR1 instead of FLU1 , revealing a previously unrecognized function of the Mdr1 efflux pump . Fluconazole-resistant clinical C . albicans isolates with different Mrr1 gain-of-function mutations were less efficiently killed by histatin 5 , and this phenotype was reverted when MRR1 was deleted . Therefore , antimycotic therapy can promote the evolution of strains that , as a consequence of drug resistance mutations , simultaneously have acquired increased resistance against an innate host defense mechanism and are thereby better adapted to certain host niches .
The yeast Candida albicans is a member of the microbiota of the oral cavity and the gastrointestinal and genitourinary tracts in most healthy persons . When host defenses are compromised , C . albicans can also cause symptomatic infections , which range from superficial skin or mucosal infections to life-threatening , disseminated infections . During both colonization and infection , C . albicans must adapt to environmental changes and stressful conditions encountered in its various host niches . To a large extent this is achieved by reversibly regulating gene expression and biochemical activities according to cellular needs [1 , 2] . In addition , C . albicans also produces genetically altered variants that are better adapted than the originally colonizing strain to long-lasting changes in its habitat or a new host niche [3–5] . The generation of such variants is facilitated by the high genomic plasticity of this diploid fungus , which often leads to the amplification or loss of partial or whole chromosomes , especially in response to stress [6] . The increased or decreased copy number of genes that are located on the affected chromosomes of the resulting aneuploid cells may confer a selective advantage under certain adverse conditions [7 , 8] . Aneuploidies are unstable , and cells can revert to the normal diploid state by chromosome loss or reduplication in the absence of selection pressure [9] . Genetic variants may also arise by simple point mutations that enable the cells to better tolerate harmful conditions . The acquisition of advantageous mutations is frequently followed by loss of heterozygosity for the mutated allele , which can occur by mitotic recombination or loss of the chromosome containing the wild-type allele [10–18] . These events are promoted in a stressful environment and further enhance the effect of the mutations [19 , 20] . A well-documented example of such microevolution within the host is the development of antifungal drug resistance during therapy [21] . Infections by C . albicans are commonly treated with fluconazole , which inhibits the biosynthesis of ergosterol , the main sterol in fungal cell membranes . Mutations in the drug target enzyme sterol 14α-demethylase , encoded by ERG11 , result in amino acid exchanges that reduce the affinity of the enzyme for the drug [22] . Similarly , mutations in FKS1 , encoding β-1 , 3-glucan synthase , the target of echinocandin drugs , also result in reduced drug binding [23] . Other point mutations that cause increased drug resistance affect transcription factors and result in permanently changed gene expression programs . The transcription factor Upc2 regulates the expression of ERG11 and other ergosterol biosynthesis genes [24 , 25] . Gain-of-function ( GOF ) mutations in Upc2 that result in hyperactivity of the transcription factor cause constitutive upregulation of its target genes and increased fluconazole resistance [15 , 26–28] . Similarly , GOF mutations in the transcription factors Mrr1 and Tac1 , which regulate the expression of the multidrug efflux pumps MDR1 and CDR1/CDR2 , respectively , result in constitutive overexpression of their target genes and are responsible for fluconazole resistance in many clinical C . albicans isolates [11–13 , 16 , 29–31] . Mrr1 , Tac1 , and Upc2 belong to the zinc cluster transcription factor family , which is unique to the fungal kingdom and characterized by a well-conserved DNA-binding motif containing six cysteine residues that coordinate two zinc atoms [32] . C . albicans possesses 82 predicted zinc cluster transcription factors , which are involved in the regulation of diverse cellular processes , although the functions of many of them have not yet been studied in detail [33 , 34] . It is conceivable that GOF mutations like those found in Mrr1 , Tac1 , and Upc2 may also occur in other members of the family and confer new phenotypes that are advantageous under adverse conditions encountered in some host niches . As many transcription factors are activated in response to specific signals and are often not active under standard growth conditions , deletion of the corresponding genes does not necessarily result in an obvious phenotype when the conditions in which they are required are not known . This was the case for Mrr1 and Tac1 , whose ability to confer drug resistance was only uncovered by the identification of GOF mutations in fluconazole-resistant clinical isolates [16 , 30] . The availability of hyperactive alleles of zinc cluster transcription factors may therefore reveal their biological function and also predict the potential of C . albicans to generate variants with novel phenotypes by acquiring GOF mutations in these transcriptional regulators . Since it cannot be generally predicted which mutations would render a wild-type transcription factor hyperactive , we recently established a method for the artificial activation of zinc cluster proteins by C-terminal fusion with the heterologous Gal4 activation domain and generated a library of C . albicans strains expressing all zinc cluster transcription factors of this fungus in a potentially hyperactive form [34] . Screening of this library showed that one of the artificially activated transcription factors , which was thereafter termed Mrr2 , conferred fluconazole resistance by upregulation of the major C . albicans multidrug efflux pump CDR1 [34] . Based on these findings , other investigators searched for naturally occurring gain-of-function mutations in the MRR2 gene in a collection of fluconazole-resistant C . albicans isolates . Indeed , three epidemiologically related isolates with elevated CDR1 expression levels contained a mutated MRR2 allele that caused CDR1 overexpression and increased fluconazole resistance when introduced into a drug-susceptible strain , demonstrating the clinical relevance of the predicted resistance mechanism [35] . In addition to antifungal drugs , which are introduced by medical treatment , C . albicans encounters many other harmful molecules within its host , which may be taken up with the diet , generated by other members of the microbiota , or produced by the host as a defense mechanism against invading pathogens . Humans secrete saliva containing different antimicrobial peptides , including histatins , in order to protect the oral mucosa from pathogenic microbes . Histatins have strong antifungal activity , with histatin 5 ( Hst 5 ) exhibiting the most potent fungicidal activity against C . albicans and other Candida species [36] . Hst 5 is an unusual antimicrobial peptide in that it is not membrane-lytic but rather acts intracellularly to cause cell death [36] . C . albicans possesses several mechanisms to evade killing by Hst 5 and thereby can tolerate the presence of low levels of this antimicrobial peptide . The extracellular glycodomain of the plasma membrane protein Msb2 is shed into the environment and binds Hst 5 as well as other antimicrobial peptides , thereby protecting C . albicans from their action , and extracellular Hst 5 is also proteolytically degraded by secreted aspartic proteases of the fungus [37–39] . Furthermore , C . albicans can recover from stresses generated by intracellular Hst 5 by mechanisms that are mediated by MAP kinases [40] . As Hst 5 acts within the cells , preventing its intracellular accumulation is another potential resistance mechanism . It was recently shown that the Flu1 efflux pump transports Hst 5 out of the cells and that mutants lacking FLU1 are hypersusceptible to killing by Hst 5 [41] . We reasoned that FLU1 expression , like that of the drug efflux pumps MDR1 , CDR1 , and CDR2 , might also be regulated by a zinc cluster protein and that C . albicans might acquire Hst 5 resistance by GOF mutations in this transcription factor . We , therefore , set out to identify transcription factors that regulate FLU1 expression and investigate whether C . albicans can develop increased Hst 5 resistance by this mechanism .
If FLU1 , like other known C . albicans efflux pumps , is regulated by a zinc cluster protein , a hyperactive form of this transcription factor should cause constitutive FLU1 overexpression and , consequently , increased Hst 5 resistance . flu1∆ mutants not only exhibit increased susceptibility to Hst 5 but are also hypersensitive to mycophenolic acid ( MPA ) , a phenotype that is easily recognizable on agar plates containing a suitable concentration of the drug [42] . We therefore screened our library of C . albicans strains expressing artificially activated forms of all zinc cluster transcription factors for increased MPA resistance . In a preliminary test , the strains were directly transferred from our stock collection in microtiter plates onto agar plates with and without MPA . Candidate strains that grew better than the wild-type control in the presence of the inhibitor were then retested in a more sensitive dilution spot assay . This resulted in the identification of four hyperactive transcription factors ( Mrr1 , Mrr2 , War1 , and Zcf35 ) that caused clearly increased MPA resistance ( Fig 1A ) . MPA resistance might be brought about by different mechanisms , for example by upregulation of the IMH3 gene , which encodes inosine monophosphate dehydrogenase , the target enzyme of MPA [43] . To investigate if the increased MPA resistance of our strains was caused by FLU1 overexpression , we introduced the artificially activated transcription factors into reporter strains containing GFP under the control of the FLU1 promoter . As can be seen in Fig 1B , basal FLU1 expression levels were detectable with GFP as a reporter gene , because the fluorescence of the wild-type reporter strains was well above background fluorescence . Intriguingly , FLU1 promoter activity was increased by all four hyperactive transcription factors ( 3- to 6-fold ) , indicating that Mrr1 , Mrr2 , War1 , and Zcf35 regulate FLU1 expression and that their activation results in overexpression of this efflux pump . We next tested if the increased MPA resistance conferred by hyperactive forms of Mrr1 , Mrr2 , War1 , and Zcf35 depended on Flu1 . For this purpose , we generated two independent series of flu1∆ mutants and complemented strains of the wild-type strain SC5314 . In accord with a previous report [42] , homozygous flu1∆ mutants were hypersusceptible to MPA , and reintroduction of a functional FLU1 copy into these mutants increased their MPA resistance to the level observed for heterozygous mutants ( S1 Fig ) . The genes encoding the hyperactive transcription factors were then introduced into the homozygous flu1∆ mutants and the MPA susceptibilities of the resulting strains compared with those of the corresponding wild-type strains . Fig 2 shows that none of the hyperactive transcription factors caused a noticeable increase in MPA resistance in the absence of Flu1 , indicating that this effect on the phenotype of the cells was entirely Flu1-dependent . Although FLU1 overexpression in the heterologous host Saccharomyces cerevisiae had previously been found to result in elevated fluconazole resistance ( hence the name given to the gene ) , deletion of FLU1 in a C . albicans laboratory strain had little effect on fluconazole susceptibility [42] . In line with these findings , we did not observe a detectable increase in fluconazole susceptibility of the flu1∆ mutants derived from the wild-type strain SC5314 , neither in dilution spot assays on agar plates nor when we determined the minimal inhibitory concentration of fluconazole in a broth microdilution assay ( Fig 2 ) . Hyperactive forms of Mrr1 , Mrr2 , and Zcf35 cause increased fluconazole resistance [34] . For Mrr1 and Mrr2 , this was also evident in the dilution spot assays on agar plates containing a defined concentration of fluconazole , whereas the strains with the hyperactive Zcf35 showed even slightly reduced growth on the fluconazole plates , despite the elevated MIC for these strains ( Fig 2 ) . The strains containing the hyperactive War1 also showed slightly reduced growth on the fluconazole agar plates , but exhibited increased fluconazole resistance when tested in the MIC assays , a phenotype that was not observed for these strains in our previous study , presumably because a different assay medium was used . The increased fluconazole resistance conferred by the four hyperactive transcription factors was also observed when they were expressed in flu1∆ mutants ( Fig 2 ) , demonstrating that FLU1 overexpression did not contribute to the fluconazole-resistant phenotype . Although FLU1 mediates Hst 5 resistance , its expression is not induced by Hst 5 [41] . Therefore , we investigated if basal FLU1 expression levels depend on any of the identified transcription factors . For this purpose , the PFLU1-GFP reporter fusion was introduced into mrr1∆ , mrr2∆ , war1∆ , and zcf35∆ mutants . S2 Fig shows that all mutants displayed wild-type FLU1 promoter activity , indicating that none of these transcription factors is required for basal FLU1 expression . As hyperactive forms of Mrr1 , Mrr2 , War1 , and Zcf35 cause FLU1 upregulation , we reasoned that they should also mediate increased resistance to Hst 5 . Therefore , we compared the percent killing of the wild-type parental strain SC5314 and derivatives containing the artificially activated transcription factors after 60 min of incubation in the presence of various Hst 5 concentrations ( Fig 3 ) . The hyperactive Mrr1 indeed conferred increased resistance to the antimicrobial peptide; in the presence of 30 μM Hst 5 , killing was reduced from 80% for the wild type to ca . 54% for strains containing the artificially activated Mrr1 . In contrast , strains with the hyperactive Mrr2 and War1 were as efficiently killed by Hst 5 as the wild type , and the strains with the hyperactive Zcf35 showed even enhanced sensitivity . Therefore , despite the increased FLU1 expression levels , artificially activated Mrr2 , War1 , and Zcf35 were unable to confer Hst 5 resistance . We speculated that these hyperactive transcription factors have additional effects on the cells that increase their susceptibility to Hst 5 and thereby abrogate any advantage conferred by FLU1 overexpression . However , subsequent experiments provided a different explanation for this result ( see below ) . Our finding that an artificially activated form of Mrr1 causes increased Hst 5 resistance was particularly intriguing , since many fluconazole-resistant clinical C . albicans isolates contain GOF mutations in Mrr1 [13 , 16 , 44] . Such mutations are selected under antifungal therapy , because the hyperactive transcription factor mediates overexpression of the multidrug efflux pump MDR1 and other genes , and thereby confers fluconazole resistance . We investigated if such naturally occurring Mrr1 GOF mutations also cause FLU1 overexpression and enhanced Hst 5 resistance . Mrr1 GOF mutations have a much stronger effect on MDR1 expression and fluconazole resistance after loss of heterozygosity for the mutated MRR1 allele [16 , 45] , and we reasoned that the same would be true for any effect on FLU1 expression and Hst 5 resistance . To assess the effect of such mutations in an isogenic background , we replaced both endogenous MRR1 alleles of strain SC5314 by alleles with GOF mutations that were originally discovered in fluconazole-resistant clinical isolates and resulted in the amino acid exchanges P683S , G997V , G878E , Q350L , N803D , T360I , K335N , and T896I . The clinical isolate 6692 contains different GOF mutations ( T360I and K335N ) in its two MRR1 alleles [13] . To reproduce this scenario , we also constructed strains containing a combination of these hyperactive alleles . In addition , strains in which the endogenous MRR1 alleles were replaced in the same fashion by an unmutated wild-type allele were included in the experiments to make sure that the sequential allele replacement strategy alone did not have a phenotypic effect . We first tested the fluconazole susceptibilities of the strains ( Table 1 ) . As previously reported [20] , replacement of the endogenous MRR1 alleles of strain SC5314 by a nonmutated MRR1 copy did not affect drug susceptibility , whereas the P683S mutation caused a 32-fold increase in the MIC of fluconazole ( from 0 . 5 μg/ml to 16 μg/ml ) . A similar effect was observed for all other GOF mutations , which raised the MIC to 16 or 32 μg/ml . In each case , identical results were obtained for two independently constructed strains . We then introduced the PFLU1-GFP reporter fusion into the strains with the different MRR1 GOF mutations to determine their effect on FLU1 expression . Fig 4A shows that all hyperactive MRR1 alleles caused elevated FLU1 expression levels , albeit to various degrees . The strongest upregulation ( ca . 7-fold ) was mediated by the N803D and T360I mutations , and the weakest effect ( 2- to 3-fold upregulation ) was observed for the P683S and T896I mutations . The differences were reproducible , because in all cases the two independently constructed reporter strains exhibited similar fluorescence values . These results demonstrated that the overexpression of FLU1 by a hyperactive Mrr1 is not a peculiar effect of the artificially generated Mrr1-GAD fusion but a general characteristic of naturally occurring activated forms of Mrr1 . We selected six different Mrr1 GOF mutations ( G997V , G878E , Q350L , N803D , T360I , T896I ) to investigate if they also resulted in increased Hst 5 resistance . As can be seen in Fig 4B , all strains containing hyperactive MRR1 alleles were less efficiently killed by Hst 5 than the parental wild-type strain SC5314 ( killing decreased from ca . 90% to ca . 60% ) , demonstrating that naturally occurring Mrr1 GOF mutations conferred increased Hst 5 resistance . In a further control experiment we confirmed that the strains in which the endogenous MRR1 alleles were replaced by a nonmutated wild-type copy exhibited wild-type Hst 5 susceptibility , as expected ( S3 Fig ) . Despite the fact that hyperactive forms of Mrr2 , War1 , and Zcf35 caused even stronger FLU1 upregulation than the artificially activated Mrr1 ( see Fig 1B ) , only the latter enhanced the resistance of the cells to Hst 5 ( Fig 3 ) . We therefore investigated if the increased Hst 5 resistance mediated by a hyperactive Mrr1 was indeed caused by FLU1 overexpression . For this purpose , we compared the percent killing by Hst 5 of wild-type and flu1∆ cells with and without the artificially activated MRR1 allele ( Fig 5 ) . Unexpectedly , deletion of FLU1 in the prototrophic wild-type strain SC5314 did not result in hypersensitivity to Hst 5 , in contrast to previous observations with the auxotrophic laboratory strain CAF4-2 [41] . Even more surprisingly , the hyperactive Mrr1 reduced the susceptibility of the cells to killing by Hst 5 both in the presence and absence of FLU1 with comparable efficiency ( at 30 μM Hst 5 , the flu1∆ mutants were even slightly more resistant in this experiment ) . Therefore , Mrr1-mediated Hst 5 resistance must be caused by other mechanisms , which might also mask any additional contribution of FLU1 overexpression in this strain background . As hyperactive forms of Mrr1 cause overexpression of many genes [16 , 45] , we searched the known Mrr1 target genes for candidates that might promote Hst 5 resistance . TPO2 encodes another putative efflux pump that is closely related to Flu1 [41] , and it is bound and upregulated by a hyperactive Mrr1 [45] . Mdr1 also has high similarity to Flu1 [42] , and MDR1 is one of the most strongly upregulated genes in strains with Mrr1 GOF mutations [16 , 45] . Although no role of TPO2 and MDR1 in Hst 5 resistance had been found in a previous study [41] , it seemed possible that these Mrr1 target genes could mediate Hst 5 resistance when they are overexpressed . Northern hybridization experiments showed that both MDR1 and TPO2 are expressed only at low levels in the wild-type strain SC5314 ( Fig 6 , left lanes ) . Interestingly , only Mrr1 , but not the other artificially activated transcription factors , Mrr2 , War1 , and Zcf35 , caused upregulation of MDR1 and , more weakly , TPO2 ( Fig 6A ) , providing a potential explanation why the latter did not cause Hst 5 resistance . Most naturally occurring GOF mutations in Mrr1 had an even stronger effect on MDR1 and TPO2 expression than the artificially activated Mrr1 , although expression levels strongly depended on the specific allele ( Fig 6B ) . As FLU1 , MDR1 , and TPO2 all are upregulated by a hyperactive Mrr1 , it was conceivable that each of these three related transporters contributes to Mrr1-mediated Hst 5 resistance and the importance of a single efflux pump would not be easily detectable . We therefore constructed flu1∆ mdr1∆ tpo2∆ triple mutants and introduced the G997V GOF mutation , which caused an efficient upregulation of all three genes ( see Fig 4A and Fig 6B ) , into both MRR1 alleles of the mutants . The deletion of the transporters in the wild-type parental strain , in which they were not or only weakly expressed , did not result in hypersusceptibility to Hst 5 ( S4 Fig ) . However , the increased Hst 5 resistance conferred by the hyperactive Mrr1 was reduced , albeit not abolished , in the triple mutants , indicating that one or more of the transporters , but also additional Mrr1 target genes , promote Hst 5 resistance ( Fig 7A ) . To assess the relative contribution of each individual transporter , we introduced the G997V mutation also into both MRR1 alleles of flu1∆ , mdr1∆ , and tpo2∆ single mutants . Deletion of FLU1 or TPO2 did not or only slightly reduce the Hst 5 resistance of cells containing the MRR1G997V mutation ( Fig 7B and 7D ) . In contrast , deletion of MDR1 increased the Hst 5 susceptibility of cells with the hyperactive Mrr1 ( killing increased from ca . 60% to ca . 80% in the presence of 30 μM Hst 5 ) , although the cells were still more resistant than the wild type ( ca . 90% killing ) ( Fig 7C ) . These results demonstrated that overexpression of MDR1 is one mechanism that contributes to the increased Hst 5 resistance of cells with Mrr1 GOF mutations . We next investigated if fluconazole-resistant clinical C . albicans isolates that have acquired MRR1 GOF mutations during antimycotic therapy also exhibit increased Hst 5 resistance . For this purpose , we selected five matched pairs of fluconazole-susceptible and -resistant isolates from AIDS patients with different MRR1 GOF mutations . We had previously generated mrr1∆ mutants from the five resistant isolates [13 , 16] , which allowed us to assess the contribution of Mrr1 to their phenotypes . To compare FLU1 expression levels , we introduced the PFLU1-GFP reporter fusion into all these strains . Two independent reporter strains were derived from each clinical isolate and one from both independently constructed mrr1∆ mutants of each resistant isolate to ensure the reproducibility of the results ( one of the mrr1∆ mutants of isolate 2271 exhibited a high unspecific autofluorescence and could not be used for these experiments ) . As can be seen in S5 Fig , FLU1 expression was moderately increased in all five resistant isolates compared to the matched susceptible isolates ( 2- to 5-fold ) , and the elevated expression levels returned to those observed in the susceptible isolates when MRR1 was deleted . These and previous results [13 , 16] demonstrate that Mrr1 GOF mutations cause concomitant upregulation of both efflux pumps , MDR1 and FLU1 , in fluconazole-resistant clinical C . albicans isolates . We then assessed if the Mrr1 GOF mutations also resulted in enhanced Hst 5 resistance of the clinical isolates . Fig 8 shows that killing by Hst 5 was reduced in all five fluconazole-resistant isolates with Mrr1 GOF mutations compared to their matched susceptible isolates , but to different degrees . A relatively minor but significant reduction in killing ( from 94% to 84% ) was observed for isolate B4 compared to isolate B3 ( Fig 8B ) , whereas isolate DSY2286 was highly resistant , as hardly any killing of this isolate was observed at the tested Hst 5 concentration ( Fig 8C ) . In four of the five cases , Hst 5 resistance was fully or largely mediated by the hyperactive Mrr1 , because the percent killing was elevated to the levels of the matched susceptible isolates when MRR1 was deleted . Isolate 6692 was an exception , because the mrr1∆ mutants derived from it retained the increased Hst 5 resistance . This strain apparently possesses other mechanisms of Hst 5 resistance that override the contribution of the hyperactive Mrr1 . Collectively , these results demonstrate that fluconazole-resistant C . albicans strains with Mrr1 GOF mutations have simultaneously acquired increased Hst 5 resistance , because the overexpression of MDR1 and other Mrr1 target genes not only mediates fluconazole resistance but also increased resistance to the antimicrobial peptide .
The acquisition of GOF mutations in zinc cluster transcription factors is a frequent cause of fluconazole resistance in clinical C . albicans strains . GOF mutations in Mrr1 , Tac1 , and Upc2 enable the cells to continue to grow in the presence of the drug and outcompete wild-type cells in the population . However , the hyperactive transcription factors also decrease the fitness of the cells in the absence of drug selection , at least under some environmental conditions [20 , 44 , 46] . As Mrr1 , Tac1 , and Upc2 regulate different sets of genes [31 , 45 , 47] , the fitness defect must have a different basis in each case; consequently , it is aggravated in highly resistant strains containing several hyperactive transcription factors [20] . The deregulated gene expression probably causes an unnecessary waste of energy and reduces the ability of the cells to appropriately adapt to specific host niches . Here , we have uncovered a previously unrecognized effect of hyperactive forms of Mrr1 in addition to their ability to mediate fluconazole resistance . The overexpression of the multidrug efflux pump MDR1 ( and possibly to some extent also FLU1 ) and other Mrr1 target genes confers increased resistance to the antifungal peptide Hst 5 , which is present in the saliva of humans . Fluconazole-resistant strains with GOF mutations in Mrr1 have mainly been isolated from the oral cavity of HIV-infected patients suffering from oropharyngeal candidiasis [13 , 14 , 16 , 42 , 44 , 48–55] . Increased Hst 5 resistance may therefore represent an additional advantage that counterbalances the fitness costs of Mrr1 hyperactivity and helps the mutants to establish themselves in this host niche . Nevertheless , Mrr1 mutations have been found only after fluconazole treatment of oropharyngeal candidiasis and have not been detected in pretreatment isolates from the same patients . This suggests that exposure to Hst 5 is not sufficient to select for Mrr1 GOF mutations when C . albicans colonizes the oral cavity as a harmless commensal without causing disease symptoms and does not have to cope with antimycotic therapy . It is difficult to estimate how strongly a hyperactive Mrr1 contributes to the survival and competitive fitness of C . albicans in the oral cavity of humans . After short-term exposure to Hst 5 , as in our in vitro experiments , strains with a hyperactive Mrr1 exhibited significantly reduced killing compared to wild-type controls . In the natural habitat , Hst 5 is constantly produced , resulting in continued exposure of C . albicans to the antifungal peptide , and the ability to avoid its toxic effects may present an even more significant advantage . The fitness gain due to enhanced Hst 5 resistance will likely also depend on the Hst 5 concentration , which varies among individuals and is generally lower in HIV-infected persons [56] . As Hst 5 is produced only by humans and other primates , the relevance of increased Hst 5 resistance cannot be meaningfully studied in mouse models of experimental candidiasis . Although we initially searched for regulators of FLU1 expression in order to identify transcription factors that might confer Hst 5 resistance , our subsequent experiments revealed that Flu1 contributed little , if at all , to Hst 5 resistance in derivatives of strain SC5314 carrying hyperactive forms of MRR1 . Instead , we unexpectedly found that overexpression of the efflux pump MDR1 was one mechanism by which such strains became less susceptible to killing by the antimicrobial peptide . MDR1 overexpression , therefore , confers increased resistance not only to fluconazole but also to Hst 5 , which is a previously unrecognized function of this efflux pump that is of potential clinical relevance . It is well possible that FLU1 makes a more important contribution in some clinical isolates with MRR1 GOF mutations , because all such isolates that were tested concomitantly overexpressed both MDR1 and FLU1 , and some of them may contain FLU1 alleles that encode more efficient Hst 5 transporters . Allelic differences that affect the efficiency of drug transport have been previously reported for the drug efflux pump CDR2 [57] . Nevertheless , a hyperactive Mrr1 still conferred increased Hst 5 resistance , albeit less efficiently , even in strains lacking both MDR1 and FLU1 as well as TPO2 , encoding a related putative transporter , indicating that additional Mrr1 target genes are involved in this phenotype . This is similar to Mrr1-mediated fluconazole resistance , which is only partially mediated by Mdr1 and involves other Mrr1 target genes that remain to be identified [45] . The effect of specific GOF mutations on the expression of individual Mrr1 target genes varies . For example , the T360I and T896I mutations caused comparable MDR1 expression levels , but only the T360I mutation also resulted in strong TPO2 overexpression ( see Fig 6B ) . Therefore , the degree of resistance to fluconazole and Hst 5 conferred by a particular Mrr1 GOF mutation will depend not only on the expression levels of MDR1 but also on those of the other target genes that contribute to these phenotypes . The successful establishment and expansion of genetically altered variants within a population require that the beneficial effects of a mutation outweigh its negative consequences . As noted above , the increased Hst 5 resistance may not sufficiently offset the fitness costs caused by a hyperactive Mrr1 to select for MRR1 GOF mutations in strains colonizing the oral cavity of healthy persons . In contrast , the increased fluconazole resistance of such strains supports their emergence in the presence of the drug . It is intriguing that antimycotic therapy promotes the evolution of strains which , as a consequence of a drug resistance mutation , have acquired increased resistance to an innate host defense mechanism and are better adapted to some stressful conditions encountered in the host even in the absence of antifungal drug treatment .
Candida albicans strains used in this study are listed in S1 Table . The complete library of C . albicans strains containing artificially activated zinc cluster transcription factors has been described previously [34] . All strains were stored as frozen stocks with 17 . 2% glycerol at -80°C and subcultured on YPD agar plates ( 10 g yeast extract , 20 g peptone , 20 g glucose , 15 g agar per litre ) at 30°C . Strains were routinely grown in YPD liquid medium at 30°C in a shaking incubator . For selection of nourseothricin-resistant transformants , 200 μg/ml nourseothricin ( Werner Bioagents , Jena , Germany ) was added to YPD agar plates . To obtain nourseothricin-sensitive derivatives in which the SAT1 flipper cassette was excised by FLP-mediated recombination , transformants were grown overnight in YCB-BSA-YE medium ( 23 . 4 g yeast carbon base , 4 g bovine serum albumin , 2 g yeast extract per litre , pH 4 . 0 ) without selective pressure to induce the SAP2 promoter controlling caFLP expression . Alternatively , strains containing a SAT1 flipper cassette in which the caFLP gene is expressed from the MAL2 promoter ( as in plasmids pMRR1R4 to pMRR1R10 ) were grown overnight in YPM medium ( 10 g yeast extract , 20 g peptone , 20 g maltose per liter ) instead of YCB-BSA-YE to induce the MAL2 promoter . Appropriate dilutions of the cultures were plated on YPD agar plates and grown for 2 days at 30°C to obtain single colonies . Nourseothricin-sensitive clones were identified by restreaking on YPD plates and on YPD plates containing 100 μg/ml nourseothricin . A FLU1 deletion construct was obtained by amplification of the FLU1 upstream and downstream regions from genomic DNA of strain SC5314 with the primer pairs FLU1 . 01/FLU1 . 02 and FLU1 . 03/FLU1 . 04 , respectively ( all oligonucleotide primers used in this study are listed in S2 Table ) . The PCR products were digested with SacI/SacII and XhoI/ApaI , respectively , and cloned on both sides of the modified SAT1 flipper cassette contained in plasmid pSFS5 [58] to result in pFLU1M1 . To reintroduce an intact FLU1 copy into flu1∆ mutants , the FLU1 coding region plus upstream and downstream sequences was amplified with primers FLU1 . 01 and FLU1_compleR . The PCR product was digested with SacI/SacII and substituted for the FLU1 upstream region of plasmid pFLU1M1 to generate pFLU1K1 . A PFLU1-GFP reporter fusion was constructed as follows . The FLU1 upstream region was amplified with primers FLU1 . 01 and FLU1rev_upstream , and a GFP-TACT1 fragment was amplified from plasmid pNIM1 [59] with primers FLU1forw_GFP and ACT19 . The gel-purified PCR products were then used as templates for a fusion PCR with primers FLU1 . 01 and ACT19 . The PCR product was digested with SacI/SacII and inserted instead of the FLU1 upstream region in plasmid pFLU1M1 to generate pFLU1G1 . A WAR1 deletion construct was generated by amplifying the WAR1 flanking sequences with the primer pairs WAR1 . 01/WAR1 . 02 and WAR1 . 03/WAR1 . 04 , digesting the PCR products with SacI/SacII and XhoI/ApaI , respectively , and inserting the fragments on both sides of the SAT1 flipper cassette of pSFS5 , generating pWAR1M1 . Similarly , a ZCF35 deletion cassette was obtained by amplifying the ZCF35 flanking sequences with the primer pairs ZCF35-7/ZCF35-8 and ZCF35-9/ZCF35-10 and cloning the SacI/SacII- and XhoI/ApaI-digested PCR products in pSFS5 to generate pZCF35M3 . A TPO2 deletion cassette was generated by amplifying the TPO2 flanking sequences with the primer pairs TPO2 . 01/TPO2 . 02 and TPO2 . 03/TPO2 . 06 and cloning the SacI/SacII- and XhoI/KpnI-digested PCR products in pSFS5 to generate pTPO2M2 . A new MDR1 deletion cassette was generated by substituting the SAT1 flipper cassette from pSFS5 for the old SAT1 flipper cassette in the previously described plasmid pMDR1M2 [45] , yielding pMDR1M3 . Plasmids pMRR1R2 and pMRR1R3 , which contain the wild-type MRR1 gene and a mutated allele with the P683S GOF mutation , respectively , have been previously described [20 , 45] . These plasmids also contain the recyclable SAT1 flipper cassette to allow the sequential replacement of both endogenous MRR1 alleles in strain SC5314 . To obtain analogous constructs with other MRR1 GOF mutations , the SacI-BglII fragments from plasmids pZCF36K5 , pZCF36K12 , pZCF36K14 , pZCF36K15 , pZCF36K17 , pZCF36K18 , and pZCF36K19 , containing G997V , G878E , Q350L , N803D , T360I , K335N , and T896I GOF mutations , respectively , in MRR1 [13] , were inserted instead of the wild-type MRR1 , generating plasmids pMRR1R4 to pMRR1R10 . C . albicans strains were transformed by electroporation [43] with the following gel-purified linear DNA fragments . The insert from pFLU1M1 was used to sequentially delete the two wild-type alleles of FLU1 in strain SC5314 , and the insert from pFLU1K1 was used to reintroduce an intact FLU1 copy into the homozygous mutants . The insert from pFLU1G1 was used to express the GFP reporter gene under the control of the endogenous FLU1 promoter in various strain backgrounds . The cassettes from plasmids pMRR1GAD1 , pZCF34GAD1 , pWAR1GAD1 , and pZCF35GAD1 [34] were used to introduce artificially activated forms of MRR1 , MRR2 , WAR1 , and ZCF35 , respectively , into PFLU1-GFP reporter strains and flu1∆ mutants . The deletion cassettes from pMDR1M3 , pTPO2M2 , pWAR1M1 , and pZCF35M3 were used to generate mdr1∆ , tpo2∆ , war1∆ , and zcf35∆ mutants of strain SC5314 . The cassettes from pMDR1M3 and pTPO2M2 were also used for the construction of flu1∆ mdr1∆ tpo2∆ triple mutants . The inserts from plasmids pMRR1R4 to pMRR1R10 were used to replace the wild-type MRR1 alleles of strain SC5314 by mutated alleles with different GOF mutations . The insert from pMRR1R4 was also used to introduce the G997V GOF mutation into both MRR1 alleles of flu1∆ , mdr1∆ , and tpo2∆ single mutants and flu1∆ mdr1∆ tpo2∆ triple mutants . The correct integration of each construct as well as recycling of the SAT1 flipper cassette were confirmed by Southern hybridization using the flanking sequences as probes . Introduction of the MRR1 GOF mutations was confirmed by reamplification of the genes from heterozygous and homozygous mutants and sequencing of the PCR products . In each case , two independent series of strains were generated and used for further analysis . Genomic DNA from C . albicans strains was isolated as described previously [60] . The DNA was digested with appropriate restriction enzymes , separated on a 1% agarose gel , transferred by vacuum blotting onto a nylon membrane , and fixed by UV crosslinking . Southern hybridization with enhanced chemiluminescence-labeled probes was performed with the Amersham ECL Direct Nucleic Acid Labelling and Detection System ( GE Healthcare UK Limited , Little Chalfont Buckinghamshire , UK ) according to the instructions of the manufacturer . Overnight cultures of the strains were diluted 10−2 in fresh YPD medium and grown for 4 h at 30°C . Total RNA was extracted by the hot acidic phenol method [61] combined with a purification step with the RNeasy Mini Kit ( Qiagen , Hilden , Germany ) . RNA samples were separated on a 1 . 2% agarose gel , transferred by capillary blotting onto a nylon membrane , fixed by UV crosslinking , and hybridized with digoxigenin-labeled MDR1 ( positions 647 to 1688 in the MDR1 coding sequence , amplified with primers NB-MDR1_FW and NB-MDR1-RV ) , TPO2 ( positions 115 to 1154 in the TPO2 coding sequence , amplified with primers TPO2_forN3 and TPO3_revN3 ) , and ACT1 ( positions 1512 to 1677 in the ACT1 coding sequence , amplified with primers ACT_RT and ACT2_RT ) probes . The bound probes were detected with a peroxidase-labeled anti-digoxigenin AP-conjugate ( Roche , Basel , Switzerland ) . The fluconazole susceptibilities of the strains were determined by a previously described broth microdilution method [62] , with slight modifications . A 2-day-old colony from a YPD agar plate was suspended in 2 ml of a 0 . 9% NaCl solution , and 4 μl of the suspension was mixed with 2 ml 2x SD-CSM medium ( 13 . 4 g yeast nitrogen base without amino acids [YNB; BIO 101 , Vista , Calif . ] , 40 g glucose , 1 . 54 g complete supplement medium [CSM , BIO101] ) . A twofold dilution series of fluconazole ( Sigma GmbH , Deisenhofen , Germany ) was prepared in water , starting from an initial concentration of 512 μg/ml . One hundred microliters of each fluconazole solution was then mixed with 100 μl of the cell suspension in a 96-well microtiter plate and the plates were incubated for 48 h at 37°C . The MIC of fluconazole was defined as the drug concentration that abolished or drastically reduced visible growth compared to a drug-free control . Overnight cultures of the strains in SD-CSM medium were diluted to an optical density at 600 nm of 2 . 0 . Ten-fold dilutions from 100 to 10−5 were prepared in a 96-well microtiter plate and ca . 5 μl of the cell suspensions transferred with a replicator onto SD-CSM agar plates without or with 0 . 5 or 1 . 0 μg/ml MPA or 5 μg/ml fluconazole . Plates were incubated for 2 days at 30°C and photographed . Overnight cultures of the GFP reporter and control strains were diluted 10−2 in fresh YPD medium and grown for 3 h at 30°C . The cultures were tenfold diluted in 1 ml cold phosphate-buffered saline ( PBS ) and flow cytometry was performed using the MACSQuantAnalyzer ( Miltenyi Biotec; Bergisch Gladbach , Germany ) equipped with an argon laser emitting at 488 nm . Fluorescence was detected using the B1 fluorescence channel equipped with a 525 nm band-pass filter ( bandwidth 50 nm ) . Twenty thousand cells were analyzed per sample and counted at a flow rate of approx . 500 cells per second . Fluorescence data were collected by using logarithmic amplifiers . The mean fluorescence ( arbitrary values ) was determined with MACSQuantify ( Version 2 . 4 , Miltenyi Biotec ) software . The susceptibility of C . albicans cells to Hst 5 was measured using microdilution plate assays as previously described [63] . Briefly , 10 ml of YPD medium was inoculated with single colonies of each strain . Cells were grown overnight at room temperature . Overnight cultures were diluted to an A600 of 0 . 3 to 0 . 4 and then incubated at 30°C with shaking ( 220 rpm ) until an A600 of ∼1 . 0 was reached . Cells were washed twice with 10 mM sodium phosphate buffer ( NaPB ) , pH 7 . 4 . The cells ( 1 × 106 ) were then mixed with different concentrations of Hst 5 at 30°C for 60 min and diluted in 10 mM NaPB . Aliquots of 500 cells were spread onto YPD agar plates and incubated for 24 to 48 h until colonies became visible . The percent killing was calculated as [1 − ( number of colonies from Hst 5-treated cells/number of colonies from control cells ) ] × 100% . Assays were performed in quadruplicate for each strain . The reference strain SC5314 was included in each set of experiments to validate assay conditions . Since the FLU1 expression and Hst 5 sensitivity assays were performed under controlled conditions in vitro , we assumed that the collected data fit a standard normal distribution . The one-way ANOVA test was used when three or more groups were compared with each other , and the two-tailed t-test was used when only two groups were compared , as indicated in the figures . Values for the two independently constructed strains A and B were combined in each case , except for the experiments shown in Fig 4B , which were performed on separate occasions . All statistical tests were conducted using GraphPad Prism version 7 . 03 software .
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The yeast Candida albicans is part of the normal microflora of most healthy persons , but it can also cause symptomatic infections when host defenses are compromised . C . albicans frequently generates genetically altered variants that are better adapted to changes in its environment during colonization and infection . We investigated if C . albicans can evolve resistance to histatin 5 ( Hst 5 ) , an antimicrobial peptide that is produced in the saliva of humans and protects the oral cavity against this pathogen . We found that activated forms of the transcription factor Mrr1 reduce the susceptibility of C . albicans to killing by Hst 5 , a phenotype that was partially caused by Mrr1-mediated overexpression of the multidrug efflux pump MDR1 . Gain-of-function ( GOF ) mutations in Mrr1 are a frequent cause of resistance to the antifungal drug fluconazole , especially during long-term treatment of oropharyngeal candidiasis in AIDS patients , but they may also reduce the fitness of the fungus in the absence of the drug . Fluconazole-resistant clinical C . albicans isolates containing GOF mutations in Mrr1 displayed enhanced Hst 5 resistance , demonstrating that antimycotic therapy can promote the evolution of strains that simultaneously have acquired increased resistance against an innate host defense mechanism and are thereby better adapted to specific host niches .
|
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2017
|
An acquired mechanism of antifungal drug resistance simultaneously enables Candida albicans to escape from intrinsic host defenses
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Macrophages are permissive hosts to intracellular pathogens , but upon activation become microbiocidal effectors of innate and cell-mediated immunity . How the fate of internalized microorganisms is monitored by macrophages , and how that information is integrated to stimulate specific immune responses is not understood . Activation of macrophages with interferon ( IFN ) –γ leads to rapid killing and degradation of Listeria monocytogenes in a phagosome , thus preventing escape of bacteria to the cytosol . Here , we show that activated macrophages induce a specific gene expression program to L . monocytogenes degraded in the phago-lysosome . In addition to activation of Toll-like receptor ( TLR ) signaling pathways , degraded bacteria also activated a TLR-independent transcriptional response that was similar to the response induced by cytosolic L . monocytogenes . More specifically , degraded bacteria induced a TLR-independent IFN-β response that was previously shown to be specific to cytosolic bacteria and not to intact bacteria localized to the phagosome . This response required the generation of bacterial ligands in the phago-lysosome and was largely dependent on nucleotide-binding oligomerization domain 2 ( NOD2 ) , a cytosolic receptor known to respond to bacterial peptidoglycan fragments . The NOD2-dependent response to degraded bacteria required the phagosomal membrane potential and the activity of lysosomal proteases . The NOD2-dependent IFN-β production resulted from synergism with other cytosolic microbial sensors . This study supports the hypothesis that in activated macrophages , cytosolic innate immune receptors are activated by bacterial ligands generated in the phagosome and transported to the cytosol .
Macrophages are highly phagocytic cells that can act as benign scavengers , sentinels of microbial infection , and hosts to intracellular pathogens [1] . However , a key property of macrophages is their capacity to be immunologically activated by cytokines such as interferon ( IFN ) –γ . Subsequent to phagocytosis of microorganisms , activation is manifested as an enhanced microbiocidal , degradative , and secretory capacity concomitant with maturation of phagosomes into acidic hydrolytic compartments [2] . How macrophages couple microbiocidal and degradative activity with the development of an appropriate immune response is critical to understanding the regulation of inflammation . Recognition of microorganisms by the innate immune system is mediated by invariable pattern recognition receptors ( PRRs ) that bind conserved molecules present on microorganisms , referred to as pathogen-associated molecular patterns ( PAMPs ) . Among PRRs are the Toll-like receptors ( TLRs ) , type I integral membrane proteins located at the cytoplasmic membrane and internal membrane-bound compartments , and nucleotide-binding oligomerization domain ( NOD ) proteins located in the cell cytosol [3 , 4] . Microbial structures exposed on the bacterial cell surface , such as lipopolysacaccharide ( LPS ) , peptidoglycan ( PGN ) , and flagellin , are recognized by TLR4 , 2 , and 5 , respectively , which are localized to the host cell surface . In contrast , microbial nucleic acids are recognized by TLR3 , 7 , and 9 , which are located within intracellular membrane-bound compartments that can fuse with phagosomes during their maturation . Treatments of cells with agents that block vacuolar acidification abrogate responses mediated by TLR3 , 7 , and 9 [5 , 6] . Whereas TLRs detect microorganisms extracellularly or within the luminal side of the phagosome , the NOD-like receptor family may comprise a surveillance system that recognizes intracellular pathogens , leading to both transcriptional responses and activation of the inflammasome [7] . Among the cytosolic innate immune receptors , RIG-I and MDA5 recognize double-stranded RNA , whereas NOD1 and NOD2 recognize bacterial PGN degradation products [7–12] . Engagement of innate immune receptors with specific microbial ligands results in signaling pathways that culminate in host transcriptional responses associated with inflammation . Signaling pathways are characterized by their shared adaptor molecules . For example , MyD88 is a major adaptor that mediates immune responses downstream of all TLRs except TLR3 , leading primarily to activation of nuclear factor ( NF ) –κB [13] . Interaction of MyD88 with TLR7 and 9 can also lead to the induction of type I IFN response through activation of interferon regulatory factor ( IRF ) 3/7 . TLR3 and TLR4 can both induce type I IFN responses via another adaptor molecule , called Trif ( Lps2 ) , again through the activation of IRF3 [13 , 14] . The cytosolic receptors that recognize RNA and DNA signal by interacting with the mitochondrial membrane adaptor MAVS/VISA/IPS-1/Cardif [15] , leading to activation of IRF3 and production of IFN-β . Less is known about the signaling pathways downstream of the NOD proteins , although NOD1 and NOD2 interact with the adaptor molecule Rip2 ( RICK ) to activate NF-κB [16] . Type I IFNs have been studied extensively with regard to their role as anti-viral cytokines , but their role in response to bacterial infection has been less studied , although bacterial LPS derived from Gram-negative bacteria is clearly an inducer of type I IFN [17] . Recently , it was shown that a Gram-positive pathogen , Listeria monocytogenes , induces type I IFN , but only upon entry into the host cell cytosol [18–21] . Mutants lacking the secreted pore-forming protein listeriolysin O ( LLO ) fail to escape from a phagosome and fail to induce IFN-β . Recognition of LLO-minus L . monocytogenes in the phagosome is largely MyD88-dependent , while recognition of cytosolic bacteria is MyD88-independent and IRF3-dependent [18–21] . The nature of the bacterial ligand ( s ) and the host PRRs responsible for the activation of IRF3 in response to cytosolic L . monocytogenes are not known , although bacterial DNA can recapitulate this response [22] . The production of type I IFN in response to L . monocytogenes is enigmatic , as mice lacking the IFNα/β receptor are more resistant to listeriosis [23–25] . A role of type I IFNs in the induction of acquired immunity has become increasingly recognized , and it has been suggested that a key feature of effective adjuvants is the capacity to induce type I IFN [26] . However , NOD2 , the target of one of the most powerful adjuvants ( muramyl dipeptide [MDP] derived from bacterial PGN ) , has not been associated with the expression of type I IFNs . In this report , we show that activated macrophages express IFN-β after phagocytosis and degradation of L . monocytogenes , and that NOD2 is necessary for full expression . IFN-β induction by LLO-minus bacteria was dependent on the activity of the macrophage vacuolar ATPase , not for acidification of the phagosome but for the generation of the phagosomal membrane potential which , we hypothesize , has a role in the active transport of bacterial ligands into the cytosol .
It was previously demonstrated that macrophages respond differently to bacteria located in their cytosol ( e . g . , wild-type [w . t . ] L . monocytogenes ) , compared to bacteria trapped in a phagosome ( e . g . , LLO-minus L . monocytogenes ) [18 , 19] . Cytosolic bacteria trigger an MyD88-independent production of IFN-β , whereas phagosomal bacteria do not [20 , 21] . However , these observations were based on the response of macrophages that were not activated and consequently weakly bacteriocidal . In vivo , during L . monocytogenes infection , cytokines such as IFN-γ act on macrophages to render them highly bacteriocidal and therefore less permissive for L . monocytogenes replication [27] . We reasoned that the bacteriocidal activity of macrophages , such as killing and degradation of bacteria , would directly affect the innate immune response to L . monocytogenes infection . In order to test this hypothesis , we studied the response of IFN-γ–activated macrophages to infection with w . t . L . monocytogenes and an LLO-minus mutant . The bacteriocidal activity of macrophages was best demonstrated when peritoneal macrophages were infected with L . monocytogenes ( Figure 1A ) . Growth curves of L . monocytogenes in activated peritoneal macrophages showed dramatic killing of w . t . bacteria . The number of bacteria recovered from the activated peritoneal macrophages decreased during 6 h of infection , while in non-activated peritoneal macrophages , bacteria were subjected to initial killing , but survivors continued to grow ( Figure 1A ) . Infection of peritoneal macrophages with the LLO-minus mutant resulted in killing of bacteria even without IFN-γ treatment ( Figure 1A ) . Unlike in peritoneal macrophages , the bacteriocidal activity of bone marrow–derived ( BMD ) macrophages was less profound and was completely dependent on IFN-γ treatment . Growth curves of w . t . L . monocytogenes in IFN-γ–activated BMD macrophages showed that IFN-γ treatment initially restricted the growth of w . t . L . monocytogenes , although bacteria were still able to escape to the cytosol and replicate ( Figure 1B ) . The bactericidal activity of BMD macrophages was best observed when the cells were infected with the LLO-minus mutant . Like in peritoneal macrophages , a one-log decrease in the number of LLO-minus bacteria was recovered after 6 h of infection ( Figure 1B ) . Since BMD macrophages killed phagosomal-trapped bacteria only upon IFN-γ activation , and w . t . L . monocytogenes were still able to escape to the cytosol in activated BMD macrophages , we chose to use these cells to study further the effect of the bacteriocidal activity on the innate immune response to L . monocytogenes . To examine whether L . monocytogenes were subjected to lysis in phagosomes , activated BMD macrophages were infected with w . t . L . monocytogenes or an LLO-minus mutant expressing cytosolic–green fluorescent protein ( GFP ) . Immunofluorescence microscopy revealed that at 6 hours post-infection ( h . p . i . ) , most w . t . bacteria were cytosolic , as many of them were engaged with actin tails , showed by co-localization of the GFP bacteria with the actin marker rhodamine-phalloidin . Only a few w . t . bacteria were labeled just with GFP , suggesting that they were trapped in the phagosome ( Figure 1C ) . Infection with a GFP-expressing LLO-minus mutant revealed that non-activated macrophages contained one to two intact GFP-expressing bacteria per cell , whereas in activated macrophages the GFP was released from the bacteria and distributed in multiple vacuoles around the cell ( Figure 1C ) . While we don't know the precise composition of these vacuoles , co-localization of some of the GFP-labeled vacuoles with the pH-sensitive dye LysoTracker RED suggested that they might have originated from the primary phagosome during its maturation to a phago-lysosome ( Figure 1C ) . As a control , w . t . L . monocytogenes did not localize with LysoTracker RED labeling ( Figure 1C ) . These results indicated that macrophage activation led to an enhanced degradative activity and trafficking of host-generated bacterial ligands , which potentially can be sensed by the innate immune system . In order to study the innate immune response of activated macrophages to L . monocytogenes infection , we used Mouse Exonic Evidence Based Oligonucleotide ( MEEBO ) microarrays [28] . Analysis of the gene expression profiles of IFN-γ–activated and non-activated BMD macrophages infected with w . t . L . monocytogenes and an LLO-minus mutant were performed . Consistent with previous studies , the response of non-activated macrophages to infection with w . t . L . monocytogenes and the LLO-minus mutant clustered into three groups of genes: i ) genes that are largely induced by w . t . cytosolic bacteria ( i . e . cytosolic-induced genes ) , ii ) genes that are largely induced by phagosomal LLO-minus bacteria ( i . e . , phagosomal-induced genes ) , and iii ) genes that are induced by both cytosolic and phagosomal bacteria ( Figure 1D; 253 genes vary > 5 . 6-fold ) . Analysis of these genes in IFN-γ–activated macrophages infected with w . t . or LLO-minus bacteria reveled that many of the genes that were cytosolic or phagosomal-specific in non-activated macrophages were induced by both bacteria in IFN-γ–activated macrophages ( Figure 1D ) . As expected , w . t . L . monocytogenes triggered expression of genes from the “phagosomal-specific genes” category in the activated macrophages . Under these conditions , some w . t . bacteria failed to escape to the cytosol and remained trapped in the phagosome; consequently , they induced phagosomal-specific genes as well ( Figure 1B and 1C ) . Pro-inflammatory cytokines such as interleukin ( IL ) –12 and IL-1α , which are normally induced by LLO-minus bacteria , were highly induced by w . t . cytosolic bacteria in activated macrophages compared to non-activated macrophages ( Figure 1E ) . Conversely , LLO-minus bacteria induced many “cytosolic-specific genes” upon activation of macrophages , including the most highly induced gene in the macrophages' response to w . t . L . monocytogenes , IFN-β ( Figure 1E ) . Like IFN-β , other cytosolic-specific genes that are normally induced by w . t . bacteria , such as IL-15 , chemokine CXC ligand 11 , chemokine C-C receptor like 2 , and type I IFN–related genes , were also induced by LLO-minus bacteria in activated macrophages ( Figure 1E ) . Interestingly , IFN-β was among the 20 most induced genes in activated macrophages infected with LLO-minus mutant ( out of 12 , 344 genes total ) , together with Nos2 , ubiquitin D , and C-C receptor like 2 ( Table S1 ) . Since the IFN-β response to w . t . L . monocytogenes is well established , we were interested in whether the IFN-β response to LLO-minus bacteria shares common signaling pathways . Further validation of IFN-β induction by the LLO-minus mutant in activated macrophages was performed using quantative real-time PCR ( Q-RT-PCR ) analysis . A time course analysis of ifnβ expression during w . t . L . monocytogenes infection demonstrated that ifnβ induction increased 10-fold in activated macrophages compared to non-activated macrophages ( Figure 2A ) . Upon infection with an LLO-minus mutant , activated macrophages induced ifnβ to the same level as in response to w . t . L . monocytogenes ( Figure 2A ) . This was also the case when activated peritoneal macrophages were infected with the LLO-minus mutant ( Figure S1 ) . These results demonstrated that bacteria trapped in the degradative phago-lysosomes of activated macrophages trigger the induction of IFN-β , a response seen in non-activated macrophages only by bacteria able to access the cytosol . An obvious consequence of bacterial degradation is the release of bacterial ligands , such as nucleic acids , that are not normally exposed by either live bacteria or killed , but non-degraded , bacteria . It is possible that these bacterial degradation products triggered the induction of IFN-β by activated macrophages infected with LLO-minus mutant . Since several TLRs are known to induce IFN-β through the adaptor molecules MyD88 and Trif , we used macrophages isolated from mice lacking each one of these adaptors to examine their role in the IFN-β response to degraded bacteria . Whereas ifnβ induction was slightly reduced in Trif-deficient macrophages , it was completely abolished in MyD88-deficient macrophages ( Figure 2B ) . However , examination of IFN-γ–activated myd88−/− macrophages infected with LLO-minus GFP-expressing mutants revealed a defect in bacterial degradation . While in C57BL/6 macrophages , bacteria were lysed as shown by GFP distribution , in MyD88-deficient macrophages the LLO-minus mutant remained intact even 6 h . p . i ( Figure 2C ) . Growth curves of the LLO-minus mutant in MyD88-deficient activated macrophages revealed a slight decrease in bacterial colony-forming units ( CFUs ) when compared to non-activated macrophages , suggesting that MyD88-deficient macrophages have a defect in killing of the LLO-minus mutant ( Figure S1 ) . This result , although striking , made it impossible to decipher the precise role played by MyD88 in the ifnβ induction by LLO-minus mutants ( see discussion below ) . Since IFN-β induction occurs downstream of TLR3 , 7 , and 9 , which are involved in nucleic acid recognition , we examined the possibility that bacterial nucleic acids , possibly released upon bacterial degradation , trigger IFN-β production in activated macrophages . Macrophages isolated from mice lacking individual TLR3 , 7 , and 9 were infected with the LLO-minus mutant to test their involvement in bacterial nucleic acid recognition . Somewhat surprisingly , none of these TLRs had any detectable affect on the induction of ifnβ by LLO-minus L . monocytogenes ( Figure 2D ) . Since none of the TLRs seemed to be playing a role in the detection of LLO-minus L . monocytogenes , we considered other host receptors that recognize bacterial ligands . NOD1 and NOD2 are cytosolic proteins that are activated by muropeptides derived from bacterial PGN [29] . Surprisingly , NOD2 was involved in production of IFN-β in response to the LLO-minus mutant , as macrophages from NOD2-minus mice expressed and secreted 50% of IFN-β ( Figure 3A ) . The induction of IFN-β by w . t L . monocytogenes or an LLO-minus mutant was independent of NOD1 ( Figure 3A ) . Although nod2 gene expression was induced by both w . t L . monocytogenes and LLO-minus bacteria ( Figure 1D ) , it affected only the IFN-β response to phagosomal bacteria ( LLO-minus ) and not to cytosolic w . t . bacteria ( Figure 3A ) . Unlike NOD2 , the transcriptional regulator IRF3 was required for IFN-β production by both vacuolar and cytosolic bacteria , suggesting that both pathways share common adaptors downstream of the signaling pathways leading to type I IFN response ( Figure 3B ) . This is the first report to our knowledge that links NOD2 activation with type I IFN responses . MDP , the well-studied ligand of NOD2 , does not induce IFN-β when delivered to the cytosol ( Figure 3C ) . However , as NOD2 synergizes with other receptors for cytokine production [30–34] , we tested the possibility that the IFN-β production in response to degraded bacteria was a result of synergism between NOD2 and other innate immune receptors . MDP was delivered with poly ( I:C ) ( a dsRNA analog that is sensed by phagosomal and cytosolic receptors ) to the activated macrophage cytosol . Whereas poly ( I:C ) alone led to production of IFN-β , when combined with MDP , the amount of IFN-β secreted by macrophages was 40% higher than with poly ( I:C ) alone ( Figure 3C ) . This increase in IFN-β production was dependent on NOD2 , demonstrating that NOD2 can synergize with other receptors leading to an enhanced type I IFN response . Since the IFN-β response to phagosomal-degraded bacteria required the cytosolic receptor NOD2 , we hypothesized that bacterial ligands were generated and transported from the phagosome and detected in the cytosol . In order to test whether degradation of bacteria is a prerequisite for IFN-β induction by LLO-minus mutants , we treated activated macrophages with bafilomycin A , a specific inhibitor of the vacuolar ATPase proton pump ( V-ATPase ) . Bafilomycin A inhibits phagosome acidification and blocks maturation of phagosomes to phago-lysosomes . Bafilomycin A–treated macrophages indeed failed to degrade internalized LLO-minus mutants ( Figure 4A ) , and did not induce ifnβ ( Figure 4B ) , whereas this treatment had no effect on induction of ifnβ by cytosolic L . monocytogenes ( Figure 4B ) . To distinguish between the requirement of degradation of bacteria or of acidification of the phagosome for IFN-β signaling , we used alternative endosomal acidification inhibitors , monensin or nigericin , which act differently than bafilomycin A . Monensin and nigericin are electro-neutral monovalent cation exchangers that are widely used to exchange K+/H+ ions across biological membranes [35] . In the presence of active V-ATPase , treatment with monensin or nigericin will induce intra-phagosomal accumulation of K+ ions as a result of exchange with luminal H+ ( Figure 4C ) . This will lead to neutralization of vacuolar pH without changing the vacuolar membrane potential [35] . Neither addition of nigericin nor monensin blocked the induction of ifnβ; in fact , both resulted in the enhanced induction of ifnβ ( Figure 4C ) , while neutralizing the phagosomal pH as determined by Lyso-Tracker RED staining ( unpublished data ) . Combining bafilomycin A with monensin ( or nigericin ) or bafilomycin A alone abrogated ifnβ induction , demonstrating that the enhanced induction originated from acidic ( phago-lysosome ) compartments ( Figure 4C ) . Immunofluorescence microscopy revealed that monensin treatment did not block phagosome maturation and bacterial degradation in activated macrophages except when combined with bafilomycin A ( Figure 4D ) . These results demonstrated that while acidification of the phagosome was not required for IFN-β signaling , phagosome maturation and bacterial degradation were necessary for this response to LLO-minus mutants . Since the V-ATPase contributes to the electrochemical potential across the phagosomal membrane [36] , bafilomycin A treatment also results in dissipation of phagosomal membrane potential , which is not the case with monensin and nigericin [37] . We asked whether the phagosomal membrane potential was important for IFN-β signaling . In order to address this question , we dissipated the phagosomal membrane potential of monensin-treated cells by using the K+-specific ionophor valinomycin . Valinomycin transports K+ ions in accordance with existing chemical gradients , which together with monensin treatment results in leakage of accumulated K+ ions from the phagosome to the cytosol and , consequently , depolarization of the phagosomal membrane ( Figure 4C ) . Treatment of valinomycin resulted in lower levels of ifnβ induction , although it did not affect degradation of bacteria ( Figure 4C and 4D ) . These results suggest that the phagosomal membrane potential is required for IFN-β signaling in response to the LLO-mutant . Next , we tested the role of NOD2 in the enhanced production of IFN-β by monensin treatment; interestingly , the induction of IFN-β was reduced by 4-fold in NOD2-deficient macrophages ( Figure 4E ) . Possibly , monensin treatment impaired the signaling from TLRs that require acidic pH [5] , leading to a greater effect on IFN-β expression in the NOD2-deficient macrophages . Importantly , NOD2 dependency was specific for a subset of cytokines like IFN-β , as other cytokines like IL-12p40 , which are induced by TLRs , were unaffected by the NOD2 mutation ( Figure 4E ) . Recently , it was demonstrated that potassium ion flux plays a role in the activation of several proteases in the phagocytic vacuole of neutrophils [38] . Since treatment with monensin generates an influx of potassium ions into the phagosome , we were interested in whether lysosomal proteases play a role in the enhancement of IFN-β signaling by monensin treatment . In order to test this hypothesis , we treated cells with the protease inhibitor , chymostatin , which inhibits lysosomal serine and cysteine proteinases and several cathepsins . Chymostatin treatment resulted in a 4-fold decrease in the ifnβ expression and had no additional effect in NOD2-deficient macrophages ( Figure 4E ) . Moreover , chymostatin treatment was also specific to ifnβ induction and had no effect on il-12p40 induction ( Figure 4E ) . These results suggest that bacterial lysis and further digestion by lysosomal proteases are required for generation of a NOD2 ligand , leading to ifnβ induction . NOD2 is activated by MDP , but how MDP is generated and transported to the cytosol is unknown . The phago-lysosome contains enzymes that can potentially degrade PGN of bacteria , such as lysozyme [39] . However , while L . monocytogenes PGN is resistant to lysozyme cleavage [40] , we asked whether it is still cleaved in the phago-lysosomes of activated macrophages . In order to address this question , we labeled the PGN of LLO-minus bacteria prior to infection with fluorescent vancomycin ( FL-Van ) that binds specifically to the terminal D-alanyl-D-alanine moieties of PGN [41] . Vancomycin labeling is localized to sites of nascent PGN synthesis , which results in polar bacterial staining ( Figure 5A ) . Whereas in non-activated macrophages we could detect intact bacteria , in activated macrophages the FL-Van PGN labeling was distributed in large vacuoles , most likely due to bacterial cell wall ( CW ) breakdown ( Figure 5A ) . The FL-Van PGN labeling was localized to acidic vacuoles determined by LysoTracker RED staining ( not shown ) . While labeling of intracellular bacteria with FL-Van was not as efficient as the GFP labeling , we were able to detect large vacuoles ( larger then a bacterial cell ) in which the FL-Van labeling was equally distributed , suggesting that the bacterial PGN was released in these vacuoles . Next , we examined whether L . monocytogenes PGN contains a NOD2 ligand and whether it can induce cytokines production in a NOD2-dependent manner . The CW fraction of L . monocytogenes was purified and treated with RNAse A and DNAse I to prevent nucleic acids contamination . While L . monocytogenes intact CW induces tumor necrosis factor ( TNF ) α and IL-6 , that response was independent of NOD2 ( Figure 5B ) . When the CW was degraded in vitro with the muramidase mutanolysin that specifically cleaves the PGN glycan backbone ( NAG-NAM ) , the degradation products ( like MDP ) triggered TNFα and IL-6 induction , which was largely dependent on NOD2 ( Figure 5B ) . The delivery of CW fragments and MDP to the macrophages cytosol was mediated by lipofectamine , which resulted in a 5-fold increase in the response to these ligands . Interestingly , only CW-derived fragments and not intact CW or MDP itself induce ifnβ . However , this induction was only partially ( 30% ) dependent on NOD2 ( Figure 5B ) . Since IFN-β expression was induced by purified bacterial CW fragments , we addressed the role of MyD88 and Trif in ifnβ induction . We found that neither of these adaptors was required for ifnβ induction , raising the possibility that cytosolic microbial sensors are involved in this response ( Figure 5C ) . These results demonstrated that L . monocytogenes PGN contains a NOD2 ligand that becomes accessible only after degradation with a muramidase , and that it can induce a pro-inflammatory response when delivered to the cytosol . However , the exact nature of the PGN fragments generated in the phago-lysosome and the in vivo ligand recognized by NOD2 are not yet known .
We have investigated the relationship between two fundamental processes of macrophages , degradation of bacteria and induction of innate immune response . In vivo , IFN-γ has a major role in controlling L . monocytogenes infection . By activating immune cells such as macrophages , IFN-γ enhances the bacteriocidal activity of macrophages and renders them less permissive to L . monocytogenes replication . In this study , we used the LLO-minus mutant to ask whether the bacteriocidal activity of macrophages has a role in the innate immune response to L . monocytogenes infection . Here , we show that phagosomal-degraded bacteria induce a specific innate immune response that is different than the response to phagosomal intact bacteria . We found that phagosomal-degraded bacteria induced type I IFN , a response that was previously shown to be specific to intracellularly growing L . monocytogenes . This research report shows that the cytosolic receptor NOD2 enhances the induction of IFN-β by phagosomal-trapped L . monocytogenes , but only when these bacteria are killed and degraded in the phago-lysosomes of IFN-γ–activated macrophages . To our knowledge , this is the first study to demonstrate that bacterial breakdown products generated in the phago-lysosome are targets for intracellular innate immune sensors . This study suggests that induction of IFN-β in response to L . monocytogenes in vivo might result from two distinct signaling pathways , one of them largely dependent on NOD2 [20] . These results are consistent with a model in which bacterial breakdown products generated in the phagosome are transported to the cytosol , where they are detected by cytosolic microbial innate immune receptors . NOD2 is activated by small muropeptides derived from bacterial PGN [29 , 42] . Although MDP ( MurNAc-l-Ala-d-Gln ) was shown to be the minimal motif recognized by NOD2 , the natural ligand ( s ) sensed by NOD2 in vivo are not known . Mammals and bacteria contain muramidases , like lysozyme , or in the case of bacteria , lytic transglycosylases , that can generate muropeptide analogs of MDP such as GlcNAc-MurNAc-l-Ala-d-Gln [43] . However , only bacteria are known to possess the endopeptidases with the specificity to generate the NOD2 ligands . For example , L . monocytogenes secrets a highly expressed endopeptidase , p60 , that cleaves the bond between D-Glu and meso-DAP , thus potentially generating NOD2 ligands [44] . In the phago-lysosome , L . monocytogenes is potentially subjected to degradation by both bacterial and host enzymes . We found that protease inhibitors blocked the NOD2-dependent response without affecting the TLR-dependent response . Therefore , lysosomal proteases might contribute to degradation of the bacterial CW , thereby facilitating further digestion of the PGN . A role for proteases was most evident upon H+/K+ ionophors treatment . Interestingly , a role for potassium influx and protease activation in neutrophils has been proposed by Reeve et al . [38] . These investigators have suggested that potassium influx into phagocytic vacuoles results in the release of cationic proteases from the anionic sulphated proteoglycan matrix , thus resulting in microbial degradation . During treatment with H+/K+ ionophors that cause a phagosomal potassium influx , we found that protease inhibitors blocked the IFN-β expression , but had no affect on expression of IL-12p40 , suggesting that proteolysis is necessary to generate the ligands transported to the cytosol , but not those recognized in the phagosome . Taken together , these results show that phagosomal degradation of L . monocytogenes resulted in the NOD2-dependent production of IFN-β , presumably due to the production of the appropriate muramyl dipeptide ( s ) generated during bacterial degradation . NOD1 and NOD2 are cytosolic proteins that are activated by small PGN fragments . Although the mechanism ( s ) that lead to PGN entry into the cytosol are not known , it was suggested that a specific transport system might be involved [45] . In the case of cytosolic pathogens such as Shigella flexneri or L . monocytogenes , it is possible that NOD1 and NOD2 recognize PGN fragments released during bacterial growth [46 , 47] . In addition , NOD1 and NOD2 may be activated by PGN fragments , introduced into host cells during infection by pathogens that possess auxiliary secretion systems . Indeed , activation of NOD1 occurred upon infection of epithelial cells by Helicobacter pylori [48] . A third hypothesis , consistent with our data , is that bacterial products leak or are actively transported from the phagosome to the cytosol [1] . An example for active transport of NOD2 ligands was demonstrated in epithelial cells where the peptide transporter hPepT1 was shown to transport MDP into the colonic epithelial cells , leading to NF-κB activation [45] . Although the mechanism of transport in macrophages is not known , here we present pharmacological evidence that the phagosomal membrane potential is crucial for NOD2-dependent IFN-β responses . While monensin and valinomycin treatments did not affect degradation of bacteria , addition of valinomycin to monensin-treated cells resulted in dissipation of the phagosomal membrane potential and reduction in IFN-β response . This observation leads to a hypothesis that the phagosomal membrane potential could have a direct role as a driving force for transport of ligands into the cytosol , or might be involved indirectly by affecting the function of membrane proteins involved in the transport process . There are a number of well-characterized host signal–transduction pathways stimulated by viral and/or bacterial products that result in the production of type I IFN [17] . Intriguingly , DNA and RNA are recognized by both intracellular TLRs and by caspase recruitment domain ( CARD ) –containing cytosolic proteins , both leading to type I IFN production . Therefore , we initially hypothesized that the induction of IFN-β by degraded L . monocytogenes was likely associated with one of these TLRs , as bacterial nucleic acids are undoubtedly released into the phagosome upon bacteriolysis . However , none of the individual TLR knockouts had a measurable affect on the production of IFN-β , although it is still possible that there is an overlapping affect of individual TLRs . Recently , two cytosolic dsRNA helicases with CARD-domains , RIG-I and MDA5 , have been identified and shown to lead to IFN-β production in response to viral nucleic acids by interacting with the mitochondrial membrane adaptor called MAVS/VISA/IPS-1/Cardif [15] . Interestingly , microarray data revealed that whereas MDA5 is induced only by w . t . L . monocytogenes in non-activated macrophages , it is induced by both w . t . and LLO-minus bacteria in activated macrophages ( Figure 1D ) . Since L . monocytogenes DNA and RNA preparations were able to induce IFN-β when delivered to the cytosol ( A . Herskovits , unpublished data; [22] ) , it is possible that cytosolic nucleic-acids sensors such as MDA5 and RIG-I are contributing to the expression of IFN-β in response to degraded L . monocytogenes . This report has demonstrated that NOD2 activation enhances IFN-β production , and although we do not know the exact nature of this signaling pathway , since NOD2 contains two CARD domains , we speculate that it may be interacting with other CARD-containing adapters . Whereas purified MDP , the synthetic activator of NOD2 , did not lead to IFN-β production , when combined with poly ( I:C ) , it enhanced the induction of IFN-β in a NOD2-dependent manner . Our in vitro preparation of CW fragments recapitulated the induction of IFN-β when delivered to the macrophage's cytosol . However , this induction was only partially dependent on NOD2 . Since NOD2 is known to act synergistically with other innate immune receptors [30–34] , we suggest that the NOD2-dependent IFN-β response is a result of synergism between PGN fragments generated in phagosomes and other bacterial ligands exposed upon bacterial lysis . Interestingly , it was recently shown that delivery of L . monocytogenes DNA to the cytosol promotes IFN-β production [22] , raising the possibility that release of bacterial nucleic acids in the cytosol might be involved in type I IFN response to degraded bacteria . This study highlights the downstream consequences that result from the enhanced microbiocidal and degradative capacity of IFN-γ–activated macrophages . Whereas non-activated macrophages show some bacteriocidal capacity , only activated macrophages killed and degraded bacteria . Bacterial degradation has a number of potential immunological consequences . A well-established consequence of phagosomal degradation is the generation of bacterial peptides ligands , which leads to the development of major histocompatibility complex class II–dependent responses [49] . In this study , we show that digestion of bacteria in a phagosome results in induction of specific innate immune responses that differ from a response to intact bacteria . We demonstrated a direct correlation between bacterial degradation and macrophage expression of IFN-β . Macrophages that failed to degrade bacteria failed to express IFN-β . Blocking degradation of bacteria by bafilomycin A treatment resulted in loss of signaling . While the role of the V-ATPase in phago-lysosome maturation is well characterized , we found that the signaling adaptor MyD88 was also essential for bacterial degradation . MyD88-deficient macrophages failed to degrade bacteria or express IFN-β when presented with intact bacteria , but did express IFN-β when bacterial CW fragments were delivered directly to the cytosol . Although the role of MyD88 in phagosome maturation is controversial , it is possible that MyD88 is involved in the initial signaling pathways that promote macrophage activation and their capacity to kill and degrade bacteria . Indeed , it was shown that the induction of many genes by IFN-γ is dependent on MyD88 [50] . Recently , it was suggested that MyD88 is required for proper assembly of the phagosomal NADPH oxidase , thus affecting the killing of Gram-negative bacteria [51] . It is clear that immune signaling pathways affect cellular processes in specialized phagocytic cells , but how these processes , such as pathogen digestion and generation of new ligands , are involved in further shaping the immune response is less understood . We speculate that macrophages can discriminate between ligands that are presented by live bacteria or ligands that are generated after degradation of bacteria ( post-mortem ) . We refer to these ligands as pathogen-associated molecular patterns post-mortem ( PAMP-PM ) . The results of this study suggest that a fully active phagosome provides PAMP-PM for detection by the innate immune system . However , this “information” is not restricted to receptors that are located in the phagosome , but crosses the phagosomal membrane to activate intracellular immune receptors as well . Lastly , we suggest that bacterial degradation in the phagosome plays a major role in the development of innate and acquired immune responses .
The L . monocytogenes strains used were a w . t . strain , 10403S and 10403S expressing GFP , or strains containing in-frame deletions of the hly gene ( LLO , DP-L2161 ) [52] and DP-L2161 expressing GFP [53] . Single colonies were inoculated into 2 ml of BHI broth ( brain-heart infusion ) and incubated overnight at 30 °C without shaking . C57BL/6 mice were obtained from The Jackson Laboratory ( http://www . jax . org ) . CD-1 mice were obtained from Charles River Laboratory ( http://www . criver . com ) . All knockout mice used in this study were on the C57BL/6 background or backcrossed with C57BL/6 mice for at least eight generations . Femurs or mice were obtained from the following source: myd88–/– from R . Medzhitov , Yale University School of Medicine , New Haven , Connecticut; tlr3−/− , tlr7−/− , tlr9−/− from K . A . Fitzgerald and D . Golenbock , University of Massachusetts Medical School , Worcester , Massachusetts; trif−/− ( lps2/lps2 ) , myd88trif−/− , from B . Beutler , The Scripps Research Institute , La Jolla . California; nod2−/− [54] from V . Dixit , Genentech , South San Francisco , California; nod1−/− from Millennium , Cambridge , Massachusetts; irf3−/− from G . Cheng , Department of Microbiology , Immunology and Molecular Genetics , University of California , Los Angeles , California . Primary cultures of resident peritoneal macrophages were prepared from CD-1 mice as previously described [27] . BMD macrophages were isolated from 6- to 8-wk-old female mice and cultured as described [55] . Activation of macrophages was done by incubating macrophage monolayer with 1 ng/ml recombinant murine IFNγ ( Biosource , http://www . biosource . com ) for 36 h before infection and during infection . Approximately 8 × 106 w . t . L . monocytogenes or 1 × 108 LLO-minus bacteria were used to infect 2 × 106 macrophages cells seeded on a 60-mm petri dish . These numbers resulted in infection of one to two bacteria per cell in the case of w . t . L . monocytogenes , and ~25–50 bacteria per cell in the case of the LLO-minus mutant . Thirty minutes after addition of bacteria , macrophage monolayers were washed three times with PBS , and fresh medium was added . At 1 h . p . i . , gentamicin was added to 50 μg/ml to limit the growth of extracellular bacteria . Unless indicated otherwise , infections were completed at 6 h . p . i , and further analyzed . Activation of macrophages was confirmed by visual inspection after infection with GFP-expressing bacteria ( Figure 1C ) . Where indicated , 0 . 5 μM bafilomycin A ( Sigma , http://www . sigmaaldrich . com ) , 1 μM monensin ( Sigma ) , 0 . 1 μM nigericin ( Sigma ) , 1 μM valinomycin ( Sigma ) , were added at 30 min post-infection . The protease inhibitor chymostatin ( 100 μM ) ( Sigma ) , was added at the time of infection . Growth curves of L . monocytogenes in macrophages cells were performed as described earlier [27] . MEEBO microarrays were printed at the Center for Advanced Technology at University of California San Francisco [28] . Each microarray experiment was done in triplicate . Macrophages were infected with w . t . and LLO-minus mutant for 5 h with and without IFN-γ treatment . Then , macrophages were washed with PBS , and total RNA was extracted using RNAqueous kit ( Ambion , http://www . ambion . com ) . A half microgram of RNA was amplified using Amino Allyl MessageAmp II aRNA Amplification Kit ( Ambion ) . A total of 5 μg of amplified RNA from each sample was labeled fluorescently with Cy5 ( Amersham , http://www . gelifesciences . com ) and mixed with a Cy3 ( Amersham ) –labeled reference pool . The common reference pool contained equal amounts ( 5 μg of each ) of amplified RNA from all the samples analyzed in the experiment ( including uninfected , hly , and w . t . samples from activated and non-activated macrophages ) . RNA was hybridized to the MEEBO microarrays for 48 h . Microarrays were gridded using SpotReader software ( Niles Scientific , http://www . nilesscientific . com ) and GenePix Pro 6 ( Molecular Devices , http://www . moleculardevices . com ) , and analyzed using Acuity 4 software ( Molecular Devices ) . Highest quality spots meeting extra-stringent criteria were identified . These highest quality spots were used to calculate normalization factors such that the median Cy5/Cy3 ratio was brought to 1 . These factors were then applied to the entire dataset after removing low quality spots . Finally , all arrays were normalized to the uninfected non-activated macrophages array . Significant analysis of microarrays ( SAM ) algorithm was used with two-class unpaired designs to identify genes that were differentially expressed in w . t . versus LLO-minus infection of non-activated macrophages , and in LLO-minus mutant infections of activated versus non-activated macrophages . Genes that showed a 5 . 6-fold or greater difference were selected for further analysis . Pearson hierarchical clustering was applied on selected genes . One liter of L . monocytogenes culture was grown at 37 °C to exponential phase and used for CW preparation . Bacterial cells were lysed by three passages through a French press at 12 , 000 PSI , and treated with DNAse I ( Invitrogen , http://www . invitrogen . com ) . After removal of cell debris , supernatant was added drop by drop to 8% boiling SDS with stirring , and was boiled for an additional 30 min [56] . The mixture was cooled overnight at room temperature , and washed with hot water . CW was washed in 0 . 1% Triton X-100 , and then washed six times with water and stored at −20 °C . Mutanolysin treatment was done overnight in 50 mM MES ( pH 5 . 88 ) , 1 mM MgCl2 . Insoluble CW was pelleted and the supernatant pH was adjusted . CW preparation and CW fragments were treated with RNAse A ( Fermentas , http://www . fermentas . com ) . L . monocytogenes CW fragments , 100 μg/ml MDP ( Calbiochem , http://www . emdbiosciences . com/html/CBC/home . html ) and 100 μg/ml poly ( I:C ) ( Invivogen ) , were delivered to macrophage cytosol with Lipofectamine 2000 ( Invitrogen ) . RNA was harvested from macrophages at 6 h . p . i . using RNeasy Mini kit ( Qiagen , http://www . qiagen . com ) . To synthesize cDNA , 1 μg of total RNA , M-MLV reverse transcriptase , Random Primers , and RNaseOUT ribonuclease inhibitor ( Invitrogen ) were used . For regular PCR analysis , 1 μg of cDNA was used with specific primers . SYBR Green−based quantitative PCR amplification was performed in 96-well plates using SYBR Green PCR core reagents ( Applied Biosystems , http://www . appliedbiosystems . com ) , the Stratagene Mx3000P Real-Time PCR System ( http://www . stratagene . com , and a 60 °C annealing temperature . For each indicated gene , as well as to the reference gene ( actin ) , a standard curve was generated to calculate the quantity of mRNA as function of the Ct value . The level of expression of each gene was determined by normalizing its mRNA quantity to the quantity of the actin mRNA at the same sample . The following mouse primer sequences were designed using Applied Biosystems Primer Express software: ifnβ-F: 5′-ctggagcagctgaatggaaag; ifnβ-R: 5′-cttgaagtccgccctgtaggt; β-actin-F: 5′-aggtgtgatggtgggaatgg; β-actin-R: 5′-gcctcgtcacccacatagga; tnfα-F: 5′-gcaccaccatcaaggactcaa; and tnfα-R: 5′-tcgaggctccagtgaattcg; il-6-F: 5′-ttccatccagttgccttcttg; and il-6-R: 5′-gaaggccgtggttgtcacc; il-12p40-F: 5′- aaccatctcctggtttgcca; and il-12p40-R: 5′- cgggagtccagtccacctc . IFN-β was measured by a mouse IFN-β enzyme-linked immunoassay ( ELISA ) kit ( R&D Systems , http://www . rndsystems . com ) . Bacterial PGN was labeled as described by Daniel and Errington [41] . A mixture of 1:1 FL-Van ( Molecular Probes , http://probes . invitrogen . com ) and unlabeled vancomycin ( Sigma ) was added to growing cultures to a final concentration of 1 μg/ml . The culture was then incubated for 30 min at 37 °C to allow absorption of the antibiotic and then washed four times in PBS . For immunofluorescence microscopy , FL-Van–labeled bacteria or GFP-expressing bacteria were used to infect macrophages on 18-mm2 glass cover slips . LysoTracker RED staining was performed according to manufacturer instructions ( Molecular Probes ) . Then , 4 h . p . i . , macrophages were washed once with PBS and fixed in 4% paraformaldehyde . Cover slips were incubated with coumarin-phalloidin or tetramethylrhodamine B isothiocyanate-phalloidin ( Sigma , 1:1 , 000 dilution ) for cytosolic F-actin staining and mounted with Vectashield mounting medium with DAPI ( Vector Laboratories , http://www . vectorlabs . com ) . Samples were viewed at ×600 with a Nikon TE300 inverted microscope .
MEEBO ( http://meebo . ucsf . edu:8080/meebo/meeboQuery . html ) gene ID numbers for the genes and gene products discussed in this paper are 5′ nucleotidase ( mMC016279 ) ; C-C receptor like 2 ( mMC024156 ) ; C-X-C ligand 1 ( mMC023634 ) ; CXC ligand 11 ( mMC011370 ) ; dual specificity phosphatase 16 ( mMA034830 ) ; IFN activated gene 205 ( mMA032762 ) ; IFN-β ( mMC16397 ) ; IL-1α ( mMR001431 ) ; IL-1 receptor agonist ( mMC015067 ) ; IL-4 ( mMC019427 ) ; IL-12 ( mMC018187 ) ; IL-15 ( mMC009424 ) ; IL-15 receptor ( mMA033400 ) ; Mda5 helicase ( mMC010553 ) ; myxovirus resistance gene ( mMC023295 ) ; NF-κB light polypeptide zeta ( mMC002655 ) ; NOD2 receptor ( mMR030202 ) ; TNFα-induced protein 2 ( mMC011682 ) ; and TNF receptor super-family member 5 ( mMR028074 ) .
|
Innate immune recognition of microorganisms has a direct impact on the type and the magnitude of the immune response elicited . While recognition of microorganisms relies on receptors that sense pathogen-associated molecular patterns , ( PAMPs ) , it was reasonable to suspect that immune cells could discriminate between live and dead bacteria . Listeria monocytogenes is an intracellular pathogenic bacterium used extensively as a model system for studying basic aspects of innate and acquired immunity . L . monocytogenes is internalized by macrophages , escapes from a vacuole , multiplies within the cytosol , and spreads from cell to cell without lysing the cells . We used wild-type and bacterial mutants of L . monocytogenes to demonstrate that macrophages not only respond differently to bacteria that are growing in the cytosol and to non-growing bacteria that are trapped in a vacuole , but that they also can discriminate between intact or degraded bacteria in the vacuole . We showed that macrophages induce specific immune response when bacteria are killed and degraded . This response was directly correlated to the ability of macrophages to degrade bacteria and involved receptors that were located in the host cell cytosol . These observations led us to suggest that bacterial degradation products may serve as messengers that inform immune cells that bacteria were killed and degraded . This information might affect directly the immune response , for example , by down-regulating inflammatory responses that can be deleterious . We call these bacterial degradation products PAMP-PM ( PAMP–post-mortem ) .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods",
"Supporting",
"Information"
] |
[
"infectious",
"diseases",
"none",
"cell",
"biology",
"immunology",
"microbiology",
"mus",
"(mouse)",
"eubacteria"
] |
2007
|
Bacterial Ligands Generated in a Phagosome Are Targets of the Cytosolic Innate Immune System
|
The role of ribosomal protein S6 ( rpS6 ) phosphorylation in mRNA translation remains poorly understood . Here , we reveal a potential role in modulating the translation rate of chemokine ( C-X-C motif ) ligand 8 ( CXCL8 or Interleukin 8 , IL8 ) . We observed that more CXCL8 protein was being secreted from less CXCL8 mRNA in primary macrophages and macrophage-like HL-60 cells relative to other cell types . This correlated with an increase in CXCL8 polyribosome association , suggesting an increase in the rate of CXCL8 translation in macrophages . The cell type-specific expression levels were replicated by a CXCL8- UTR-reporter ( Nanoluc reporter flanked by the 5’ and 3’ UTR of CXCL8 ) . Mutations of the CXCL8-UTR-reporter revealed that cell type-specific expression required: 1 ) a 3’ UTR of at least three hundred bases; and 2 ) an AU base content that exceeds fifty percent in the first hundred bases of the 3’ UTR immediately after the stop codon , which we dub AU-rich proximal UTR sequences ( APS ) . The 5’ UTR of CXCL8 enhanced expression at the protein level and conferred cell type-specific expression when paired with a 3’ UTR . A search for other APS-positive mRNAs uncovered TNF alpha induced protein 6 ( TNFAIP6 ) , another mRNA that was translationally upregulated in macrophages . The elevated translation of APS-positive mRNAs in macrophages coincided with elevated rpS6 S235/236 phosphorylation . Both were attenuated by the ERK1/2 signaling inhibitors , U0126 and AZD6244 . In A549 cells , rpS6 S235/236 phosphorylation was induced by TAK1 , Akt or PKA signaling . This enhanced the translation of the CXCL8-UTR-reporters . Thus , we propose that the induction of rpS6 S235/236 phosphorylation enhances the translation of mRNAs that contain APS motifs , such as CXCL8 and TNFAIP6 . This may contribute to the role of macrophages as the primary producer of CXCL8 , a cytokine that is essential for immune cell recruitment and activation .
Translation is an essential step in protein synthesis . Mechanisms that regulate the rate of translation determine the expression levels of a large fraction of the genome . This was revealed by metabolic pulse labeling of global cellular mRNA and protein synthesis rates [1] . Consistently , multiple large-scale transcriptomic and proteomic studies have revealed a lack of correlation between mRNA and protein abundance across different mammalian cell-types and tissues [2 , 3] . Translational control is mRNA-specific and the specificity is sometimes dependent on sequence motifs within the 5’ untranslated region ( UTRs ) , such as 5′ terminal oligopyrimidine ( TOP ) [4] , which lead to selective protein synthesis during increased activity of eukaryotic translation initiation factor 4E ( eIF4E ) . More recent studies have tentatively proposed that cytosine enriched regulator of translation ( CERT ) [4] and pyrimidine-rich translational element ( PRTE ) [5] may also regulate translation . Besides the 5’ UTR , the involvement of the 3’ UTR in conferring translational control has also been hinted [6] . While the translational control mediated by eIF4E is well-studied [5–10] , the translational control mediated by phosphorylation of ribosomal protein S6 ( rpS6 ) is still the subject of ongoing investigations . Physiologically , phosphorylation-deficient rpS6 knock-in mice display abnormalities in cell size , cell proliferation , and glucose homeostasis [11] . Aberrant rpS6 phosphorylation has also been implicated in pancreatic tumorigenesis in mice [12 , 13] . The molecular mechanisms responsible for these physiological effects remain elusive , as rpS6 phosphorylation does not appear to affect global protein synthesis . More recently , rpS6 phosphorylation-deficient transgenic mice [14] were found with impaired translation in a subset of mitochondria-related mRNAs present in neurons [15] . Thus , it appears that rpS6 phosphorylation may alter the translation of a subset of mRNAs , although the exact mechanism and RNA cis-regulatory motifs responsible for the action are unknown . A possible target for rpS6-mediated translational control is chemokine ( C-X-C motif ) ligand 8 [CXCL8 or Interleukin 8 , IL8] . Studies on CXCL8 have been complicated by the absence of the CXCL8 and CXCR1 gene homologs from the muroid lineage due to a deletion event [16] . The role of CXCL8 in mice appears to have been largely replaced by murine MIP-2 and the murine keratinocyte-derived protein chemokine KC , which activates murine CXCR2 [17 , 18] . To study CXCL8 , researchers have typically relied on clinical observations , ex vivo cultures of primary human cells and cell line models . Such methods have revealed a critical role for CXCL8 in the chemotactic recruitment , phagocytosis and degranulation of neutrophils [19]; and in the recruitment and activation of monocytes and lymphocytes during inflammation [20] . CXCL8 induces these functions by activating cell surface receptors , namely CXCR1 and CXCR2 [19] . CXCL8 signaling has also been implicated in a number of diseases including atherosclerosis [21] , asthma [22] , allergic rhinitis [23] and various cancers [24–26] . In light of the importance of CXCL8 , elucidating the mechanism of CXCL8 translational control may prompt more effective treatments that target these pathways to alleviate CXCL8-mediated diseases . Here , we investigate if CXCL8 undergoes translational regulation . While the 5’ UTR of CXCL8 does not appear to contain TOP [4] , CERT [5] or PRTE [6] motifs , certain observations hint at a cell type-specific translation rate . For example , macrophages secrete 70-fold more CXCL8 protein relative to neutrophils despite elevated CXCL8 mRNA being detected in both cell types [27 , 28] . This makes macrophages the undisputed primary producer of CXCL8 in the human system . This difference in expression is noteworthy as macrophages and neutrophils are descended from a common myeloid progenitor [29] . These observations suggest that macrophages and neutrophils are prime targets for the study of CXCL8 translation . To facilitate the acquisition of a large number of cells for in vitro studies , our initial experiments were performed with the HL-60 promyeloblast cell line . HL-60 is an established model to study myeloid progenitor cell development [30] . Similar to primary myeloid progenitors [29] , HL-60 promyeloblasts can be differentiated into either a macrophage-like ( HL-60 macrophage /HL-60 Mac ) or polymorphonuclear neutrophil-like ( HL-60 PMN ) phenotype via PMA or DMSO treatment , respectively [30] . CXCL8 translation was also studied in KHYG-1 , which is an established model of natural killer ( NK ) cells , and the A549 and NCI-H1299 lung epithelial carcinoma ( EC ) cells , [31–33] . Using a combination of primary cells and their corresponding cell line models , we elucidated the pathway and cis-regulatory RNA motif responsible for the cell type-specific expression of CXCL8 .
First , we compared the expression levels of CXCL8 between HL-60 macrophage ( HL-60 Mac ) , HL-60 neutrophils ( HL-60 PMN ) , A549 EC and KHYG-1 NK cells . We found that HL-60 Mac cells secreted more CXCL8 protein from less CXCL8 mRNA at the basal level and after stimulation with LPS or TNF ( Fig 1A ) . An increase in secreted CXCL8 protein was also observed from H1299 cells relative to A549 cells despite lower CXCL8 mRNA levels in H1299 cells ( Fig 1B ) . This increase was not observed for IL6 protein secretion , which mirrored IL6 mRNA levels and was reduced in H1299 cells relative to A549 cells . We also observed an increase in the percentage of CXCL8 mRNAs associated with the larger polysomes ( towards the right of the graph ) in HL-60 Mac relative to A549 EC and KHYG-1 NK cells ( Fig 1C ) . The same increase was not observed for the control mRNAs , RPL27 and ACTB . Since a polysome ( or polyribosome ) is formed when an mRNA molecule complexes with two or more ribosomes during the translation process , the increased polysome association of CXCL8 in Hl-60 Mac may be due to an increased rate of translation . Altogether , these observations suggest that the rate of CXCL8 translation is cell type-specific , leading to elevated CXCL8 protein secretion in macrophages . We hypothesized that the increased CXCL8 expression observed in HL-60 Mac ( Fig 1A ) may involve the 5’ and 3’ UTR sequences . To investigate the role of the UTRs , we generated expression vectors containing the CXCL8 coding sequence alone ( CXCL8-CDS ) and the full CXCL8 mRNA sequence which includes the 5’ and 3’ UTRs ( CXCL8-full ) ( Fig 2A ) . These constructs were transfected into the HL-60 Mac , A549 EC and KHYG-1 NK cells . These cell lines could be efficiently transfected ( S1A Fig ) and upon transfection with the CXCL8-full plasmid displayed an increase in CXCL8 mRNA levels relative to the empty plasmid controls ( Fig 2A ) . A proportional increase in CXCL8 protein was also observed . This suggests that vector-derived “CXCL8-full” was being expressed at the same rate as the endogenous CXCL8 found in the controls . We then determined the effect of the UTRs on CXCL8 expression by calculating the fold change of CXCL8 mRNA and CXCL8 protein in CXCL8-full transfected cells relative to CXCL8-CDS . The 3’ UTR of CXCL8 reportedly contains adenylate-uridylate-rich elements ( AREs ) which accelerated mRNA degradation [34–36] . These AREs are present in CXCL8-full but absent from the UTR-deficient CXCL8-CDS construct . This may explain why CXCL8-full transfections displayed CXCL8 mRNA that were 4- to 16-fold lower than CXCL8-CDS in all the cell types tested ( Fig 2B ) . For A549 EC and KHYG-1 NK cells , this coincided with 8- to 16-fold reductions in CXCL8 protein . For HL-60 Mac by contrast , a 4-fold increase in CXCL8 protein levels was observed . This suggests that more CXCL8 protein was being produced and secreted from less CXCL8 mRNA in HL-60 Mac relative to A549 and KHYG-1 cells . Overall , these findings suggest that the elevated CXCL8 expression in macrophages ( Fig 1 ) is reproduced by vector-derived CXCL8 mRNA and requires the UTRs ( Fig 2A and 2B ) . To determine if the CXCL8 UTR sequences alone were sufficient to confer enhanced expression in HL-60 Mac , we generated Nluc reporters with UTR fusions ( UTR-Nluc ) ( Fig 2C ) . The Nluc reporter allowed us to study a much wider range of hard-to-transfect cells including primary macrophages , NK cells and HL-60 PMNs , since even low levels of vector-derived Nluc can be accurately quantified due to a lack of endogenous Nluc expression . The effect of the fused UTRs on Nluc expression in different cell types was calculated as the fold change of UTR-Nluc relative to Cntrl-Nluc ( Nluc reporter with no UTR fusions ) ( Fig 2D ) . CXCL8-5’+3’ ( Nluc reporter with CXCL8 5’ and 3’ UTR sequences ) expression was compared between HL-60 Mac , HL-60 PMNs , A549 ECs , KHYG-1 NK and H1299 ECs ( Fig 2D ) . CXCL8-5’+3’ protein levels were elevated in HL-60 Mac and H1299 ECs . This was not due to differences in expression at the mRNA level , which remained largely unchanged among all cell types . This is consistent with an elevated rate of CXCL8-5’+3’ translation in HL-60 Mac and H1299 EC cells . The cell type-specific expression of CXCL8-5’+3’ was not noticeably altered by LPS or TNF treatments ( Fig 2E ) or by halving the amount of UTR- and Cntrl-Nluc plasmid transfected and replacing the other half with empty pcDNA3 . 1 plasmid ( Fig 2F ) . We also deleted the Nluc secretory signal from CXCL8-5’+3’ and Cntrl-Nluc , resulting in cytoplasmic expression of Nluc . CXCL8-5’+3’ ( -Sec ) protein levels remained elevated in HL-60 mac relative to A549 ECs ( Fig 2G ) . This suggests that the cell type-specific differences were not due to differences in protein secretion . Overall , these findings suggest that the CXCL8 UTR sequences contribute to its elevated expression in HL-60 Mac and H1299 cells . The cell type-specific Nluc protein fold changes observed for CXCL8-5’+3’ was also distinct from that observed for TNF-5’+3’ , IL6-5’+3’ and TIMP1-5’+3’ ( Fig 2C and 2D ) . Relative to Cntrl-Nluc , both TNF-5’+3’ and IL6-5’+3’ reduced Nluc protein expression across all cell lines . This is consistent with previous reports that the 3’ UTR sequences of TNF and IL6 contain AREs that reduce expression [37 , 38] . By contrast , the protein and mRNA levels of TIMP1-5’+3’ were not substantially different from Cntrl-Nluc , since the TIMP1 UTRs are not known to contain any AREs or other functional sequences . Altogether , these results suggest that the CXCL8 UTRs mediate a cell type-specific expression pattern , at the protein level , that is not observed for TNF , IL6 and TIMP-1 . The UTR-Nluc reporter constructs tested thus far contained both the 5’ and 3’ UTRs . We also tested constructs containing either the 5’ or 3’ UTR alone ( CXCL8-5’ and CXCL8-3’ ) to determine their individual contributions ( Fig 2C and 2D ) . The Nluc protein and mRNA fold changes of CXCL8-3’ largely followed the pattern observed for CXCL8-5’+3’ . This suggests that the cell type-specific expression of CXCL8 is largely mediated by its 3’ UTR . CXCL8-5’ protein levels were increased relative to Cntrl-Nluc in all cell lines ( positive log2 fold change values ) ( Fig 2D ) . By multiple sequence alignment , we found a conserved 37-bp motif within the 5’ UTR of CXCL8 ( Fig 3A ) , and hypothesized that it was involved in the enhancement . Indeed , the enhanced expression was retained when the 5’ UTR was shortened into a 75-bp fragment [CXCL8-5’ ( 79–153 ) ] containing the conserved 37-bp motif; and was abolished upon further shortening to the CXCL8-5’ ( 96–125 ) and CXCL8-5’ ( 121–153 ) fragments ( Fig 3B ) . The CXCL8 5’ UTR fragment also successfully enhanced mCherry [CXCL8-5’-mCherry] ( Fig 3C ) and firefly luciferase ( pNFAT-5’-Fluc ) expression ( Fig 3D ) , confirming that the enhanced expression was applicable to other genes and was not specific to Nluc . The expression enhancement also occurred when driven by the NFAT promoter ( i . e . in pNFAT-5’-Fluc” ) , which is a weaker promoter relative to the constitutive CMV promoter used for CXCL8-5’ ( 79–153 ) and CXCL8-5’-mCherry . In summary , our findings demonstrate that a conserved 75-bp sequence motif within the 5’ UTR of CXCL8 enhances expression . The reduced mRNA levels of CXCL8-full relative to CXCL8-CDS ( Fig 2A and 2B ) are consistent with previous reports of increased CXCL8 mRNA degradation due to AREs within its 3’ UTR [34–36] . Surprisingly , this reduction was not observed for CXCL8-5’+3’ relative to Cntrl-Nluc ( Fig 2B ) , which may be due to the much higher rate of mRNA transcription masking the reduction from mRNA degradation . Accordingly , when the rate of CXCL8-5’+3’ transcription was presumably reduced ( by halving the amount of UTR- and control-Nluc vector transfected and replacing the other half with empty pcDNA vector ) , we observed a reduction in CXCL8-5’+3’ mRNA levels relative to Cntrl-Nluc mRNA in A549 ECs and KHYG-1 NK cells ( Fig 2F ) . The ARE motifs reportedly also reduced CXCL8 expression [34–36] . However , when we deleted two AREs ( predicted by RegRNA2 . 0 [39] ) within the 3’ UTR of CXCL8 , the resulting CXCL8-5’+3’ΔARE mutant construct retained the cell type-specific expression observed for CXCL8-5’+3’ , albeit with increased expression across all cell types ( Fig 4A ) . This suggests that the ARE motifs reduce CXCL8 expression equally across all cell-types and are not responsible for the cell type-specific expression . To identify the CXCL8 3’ UTR sequences that are involved in the cell type-specific expression , we split the 3’ UTR and cloned the halves into the CXCL8-3’ ( 1–627 ) and CXCL8-3’ ( 628–1252 ) UTR-Nluc reporters ( Fig 4B ) . Both reporters retained increased Nluc protein levels in HL-60 Mac relative to HL-60 PMN , A549 ECs and KHYG-1 NK cells . The 3’ UTR was split further into fragments of around 300 bp in length , generating the CXCL8-3’ ( 628–969 ) and CXCL8-3’ ( 970–1252 ) reporters . These UTR-Nluc reporters continued to display increased Nluc protein levels in HL-60 Mac relative to A549 ECs . The cell type-specific protein levels were eventually lost upon further deletion into a 141-bp and 70-bp fragment [CXCL8-3’ ( 1112–1252’ ) and CXCL8-3’ ( 1183–1252 ) respectively] . Taken together , these findings suggest that all the CXCL8 UTR fragments of at least 300 bp confer cell type-specific expression . All the CXCL8 3’ UTR fragments that have conferred increased Nluc protein levels in HL-60 Mac relative to A549 ECs , have a high adenylate-uridylate or AU content in their 3’ UTR sequences ( Fig 4C ) . Accordingly , this AU-rich sequence feature is also observed in the full-length CXCL8 3’ UTR . A high AU content in the first hundred or so bases of the CXCL8 3’ UTR , appears to be conserved among the known mammalian homologs of CXCL8 ( Fig 4D ) . This may indicate a functional role that was maintained by natural selection . A relatively high AU content in the first hundred or so bases of the 3’ UTR also distinguishes CXCL8 from TNF , IL6 and TIMP1 ( Fig 4E ) . This may explain why TNF-5’+3’ , IL6-5’+3’ and TIMP1-5’+3’ displayed cell type-specific expression that were distinct from CXCL8-5’+3’ ( Fig 2D ) . Based on these observations , we hypothesized that a high AU content in the first hundred or so bases of the CXCL8 3’ UTR may be the sequence feature responsible for mediating increased protein synthesis in HL-60 Mac . Henceforth , we dub these AU-rich proximal UTR sequences ( APS ) . To investigate the role of the APS , we inserted short sequences into the 3’ UTR to disrupt or introduce the APS-motif . Performing insertions instead of substitutions ensured that the full 3’ UTRs sequences were retained . This ensured that any differences in expression observed were not due to deletions of functional motifs within the 3’ UTR sequences . The presence of the APS was determined by calculating the AU-content of the first 100 bp of the mutated 3’ UTR . We then determined if the protein levels of the mutant UTR reporter was elevated in HL-60 Mac relative to A549 ECs , which is indicative of the cell type-specific expression of CXCL8 . The insertion of 8 bases immediately upstream of the 3’ UTR sequence of the CXCL8-3’ reporter , did not disrupt the APS and cell type-specific expression ( Fig 5A ) . Only the insertion of a longer sequence , namely the first 91 bp of TNF 3’ UTR , resulted in an APS-deficient CXCL8-3’::TNF-3’ ( 1–91 ) reporter ( Fig 5B ) . This coincided with the disruption of cell type-specific expression as a much smaller difference in CXCL8-3’::TNF-3’ ( 1–91 ) reporter protein levels was observed between HL-60 Mac and A549 ECs . As a control , the first 91 bp of the TNF 3’ UTR was also inserted in between positions 285 and 286 of the 3’ UTR of “CXCL8 3’” ( Fig 5B ) . The resulting “CXCL8 Δ3’-dis” mutant remained APS-positive and displayed elevated protein levels in HL-60 Mac . Inversely , we also inserted the first 100 bp of the CXCL8 3’ UTR sequence immediately before the TNF 3’ UTR of the APS-deficient TNF-3’ reporter ( Fig 5B ) . This generated an APS-positive mutant , TNF-3’::CXCL8-3’ ( 1–100 ) which displayed elevated protein levels in HL-60 Mac relative to A549 ECs . Altogether , these data are consistent with the APS-motif conferring cell type-specific expression . We had deduced that the cell type-specific expression of CXCL8 was largely mediated by its 3’ UTR . This was based on the observation that the cell type-specific Nluc protein and mRNA fold changes of CXCL8-5’+3’ was largely replicated by CXCL8-3’ but not CXCL8-5’ ( Fig 2C and 2D ) . Indeed , the ability of the CXCL8 3’ UTR to mediate enhanced expression in HL-60 Mac relative to A549 ECs occurred even in the presence of the TNF 5’ UTR sequence , as was observed for the TNF-5’+CXCL8-3’ reporter ( Fig 5B ) . However , our subsequent assays revealed that the 5’ UTR of CXCL8 may not be entirely benign . We observed that the protein levels of CXCL8-5’+3’::TNF-3’ ( 1–91 ) and CXCL8-5’+TNF-3’ were elevated in HL-60 Mac relative to A549 EC , despite being APS-deficient ( Fig 5C ) . This may have been mediated by the presence of the 5’ UTR of CXCL8 . The lack of this cell type-specific expression in the CXCL8-5’ reporter may have been due to the absence of a 3’ UTR sequence ( Fig 2D ) . Thus , these findings suggest that the 5’ UTR of CXCL8 may confer cell type-specific expression when paired with a 3’ UTR . With the elucidation of the novel APS-motif , we then investigated if the presence of APS could be used to predict elevated translation in macrophages . An analysis of proximal AU content in the 3’ UTR of common cytokine signaling genes revealed that the TNFAIP6 , IFNG and IL2 genes possess high AU-contents in the first hundred or so bases of their 3’ UTRs ( Fig 5D ) , which is indicative of the presence of APS . Amongst these genes , only the TNFAIP6 mRNA was expressed at a detectable level in HL-60 Mac . In agreement with our prediction , the polysome association of TNFAIP6 was elevated in HL-60 Mac relative to A549 EC and KHYG-1 NK cells . This was indicated by an increase in the percentage of TNFAIP6 mRNA found in the larger polysomes fractions , towards the right of the graph , in HL-60 Mac ( Fig 5E ) . Thus , our results suggest that TNFAIP6 may also contain a functional APS-motif . Next , we elucidated the signaling pathways involved in the elevated expression of CXCL8-5’+3’ reporter protein in HL-60 Mac relative to HL-60 PMN , A549 EC and KHYG-1 NK . This cell type-specific expression remained largely unaffected by treatment with the inhibitors of mTOR ( Torin-1 ) ( S1C Fig ) , p38 ( SB203580 ) and JNK ( SP600125 ) ( S1D Fig ) . As controls , the SP600125 treatment used was sufficient to inhibit JNK-mediated phosphorylation of JUN in HL-60 Mac [40] while the SB203580 treatment used was also sufficient to inhibit the transcription of CXCL8 in LPS-activated neutrophils ( S1D Fig ) [41] . By contrast , the elevated expression of CXCL8-5’+3’ protein in HL-60 Mac cells was attenuated when ERK1/2 signaling was inhibited by treatment with U0126 ( which inhibits the upstream kinase , MAP2K1/2 ) or AZD6244 ( which directly inhibits ERK1/2 ) ( Fig 6A ) . The same U0126 treatment also reduced CXCL8-3’ reporter protein levels in HL-60 Mac; but did not reduce the expression of the APS-deficient reporters: CXCL8-5’ , TNF-5’+3’ and IL6-5’+3’ ( Fig 6A ) . The inhibition of ERK1/2 signaling in HL-60 Mac cells also reduced the polysome association of endogenous CXCL8 and TNFAIP6 relative to control untreated HL-60 Mac cells . This was indicated by a reduction in the percentage of CXCL8 and TNFAIP6 mRNA found in the larger polysome fractions ( towards the right of the graph ) ( Fig 6B ) . The same pattern was not observed for the control mRNA , ACTB . These findings suggest that ERK1/2 target proteins may be involved in the cell type-specific expression of APS-positive mRNAs . To identify the ERK1/2 target proteins involved , we examined known downstream targets of ERK1/2 such as rpS6 , 4E-BP1 and eIF4E ( Fig 7A ) . Since the protein activities were modulated by their phosphorylation states , the ratios of phosphorylated protein over total protein expression ( i . e . : [rpS6 S235/236+phos] / [rpS6] ) between different cell types were compared . Amongst the ERK1/2 target proteins , the phosphorylation ratio of rpS6 ( at S235/236 and S240/244 ) was elevated in HL-60 Mac relative to HL-60 PMN , A549 EC , KHYG-1 NK and H1299 EC ( Fig 7A ) . The expression of eIF4E was also elevated in HL-60 Mac relative to A549 EC and KHYG-1 NK ( Fig 7A ) . Next , we determined if these proteins were affected by the inhibition of ERK1/2 signaling ( via U0126 and AZD6244 ) or mTOR signaling ( via Torin-1 ) . Previous studies have found that ERK1/2 signaling induces the phosphorylation of rpS6 at S235/236 [42] while Akt-mTOR signaling induces the phosphorylation of rpS6 at S235/236 and S240/244 [11 , 43] . Here , the inhibition of ERK1/2 signaling via U0126 or AZD6244 treatment led to 8- to 16-fold reductions in rpS6 S235/236 phosphorylation . The inhibition of mTOR signaling inhibition via Torin-1 treatment led to a much smaller 2- to 4-fold reduction . The smaller effect of Torin-1 on rpS6 S235/236 phosphorylation was unlikely to be due to a lack of Torin-1 activity since the inhibitor almost completely abolished the phosphorylation of 4E-BP1 at T37/46 , an effect that was previously described [44] . The phosphorylation at S240/244 on the other hand , was equally sensitive to U0126 , AZD6244 and Torin-1 treatment , with a 4-fold reduction across all inhibitors . From these observations , we made three inferences . First , rpS6 S235/236 phosphorylation in HL-60 Mac was predominantly mediated by ERK1/2 signaling . Second , ERK1/2 signaling inhibition may attenuate the expression of APS-positive mRNAs by blocking the phosphorylation of rpS6 at S235/236 . Third , ERK1/2 signaling inhibition did not act via the blocking of rpS6 S240/244 phosphorylation since mTOR signaling inhibition also blocked rpS6 S240/244 phosphorylation to a similar degree but did not attenuate CXCL8+5’+3’ expression . Unlike rpS6 , the expression and phosphorylation of eIF4E was not affected by treatment with U0126 , AZD6244 or Torin-1 ( Fig 7B ) . This suggests that ERK1/2 inhibitors do not act via eIF4E to attenuate the cell type-specific expression observed . Since the availability of eIF4E to form the translation initiation complex has also been found to modulate the rate of mRNA translation [7–10] , further investigations were performed to either confirm or rule out its role . We expressed the 4E-BP1-4A mutant–a phosphorylation deficient mutant of 4E-BP1 which constitutively binds to and inhibits eIF4E activity [4] ( S1E Fig ) . At first glance , this appeared to have reduced CXCL8-5’+3’ protein synthesis in HL-60 Mac . However upon closer inspection , it was revealed that multiple proteins ( including rpS6 S235/236+phos , rpS6 240/244+phos , total rpS6 , eIF4E and μ-tubulin ) were up-regulated in HL-60 Mac upon 4E-BP1-4A expression . This made it difficult to narrow down the cause of the reduced CXCL8-5’+3’ protein levels . To investigate further , we expressed exogenous eIF4E to alleviate any potential shortage of eIF4E in A549 ECs . However , this did not enhance CXCL8-5’+3’ protein synthesis ( S1F Fig ) . This suggests that eIF4E shortage was not a factor at play , which is consistent with our findings on Torin-1 treatment . Treatment with Torin-1 almost completely abolished the phosphorylation of 4E-BP1 at T37/46 in HL-60 Mac cells ( Fig 7B ) but did not inhibit the expression of CXCL8-5’+3’ ( S1C Fig ) . Since the phosphorylation of 4E-BP1 at T37/46 is required for the subsequent “hyper” phosphorylation at S65/T70 which inhibits 4E-BP1 binding to eIF4E [45] , this suggests that eIF4E availability was not being reduced by interaction with unphosphorylated 4E-BP1 [46] . Thus , our assays suggest that increasing the availability of eIF4E did not enhance APS-modulated expression . To further investigate the role of rpS6 , we activated pathways leading to the induction of rpS6 phosphorylation in A549 ECs . There are three known rpS6 kinases that directly phosphorylate rpS6 [11] . The first is p90 ribosomal S6 kinase ( Rsk ) which is activated by ERK1/2 signaling [42] . We activated this pathway , as indicated by increased ERK1/2 T202/204 phosphorylation , through the co-expression of TAK1 and TAB1 [47] ( Fig 8A ) . The second is p70 S6 protein kinase ( S6K1 ) which is activated by Akt-mTOR signaling [11] . We activated of this pathway , as indicated by increased Akt S473 phosphorylation , through the expression of myristoylated Akt or myrAkt ( Fig 8A ) . Finally , the third known rpS6 kinase is protein kinase A ( PKA ) [48] . We activated this pathway through the expression of constitutively active PKA ( caPKA ) ( Fig 8B ) . In A549 EC cells , all three rpS6 kinase pathways induced rpS6 S235/236 phosphorylation and increased CXCL8-5’+3’ protein levels ( Fig 8A and 8B ) . The TAK1-ERK1/2 pathway produced a greater degree of rpS6 S235/236 phosphorylation and this coincided with increased CXCL8-5’+3’ expression relative to the myrAkt-mTOR pathway . This is consistent with our observations in HL-60 Mac where rpS6 S235/236 phosphorylation was found to be predominantly mediated by ERK1/2 signaling and not Akt-mTOR signaling ( Figs 6 and 7 ) . By contrast , CXCL8-5’+3’ protein synthesis was not increased when rpS6 S235/236 phosphorylation was not induced , such as during the expression of constitutively active MKK7-JNK ( Fig 8A ) . This is consistent with our earlier findings where the inhibition of JNK activity ( via SP600125 ) did not attenuate CXCL8-5’+3’ expression in HL-60 Mac ( Fig 6B ) . In summary , these findings demonstrate that the induction of rpS6 S235/236 phosphorylation enhances CXCL8-5’+3’ expression . Our work on cell lines suggested that CXCL8 expression was elevated in macrophages via a UTR and ERK1/2-dependent mechanism ( Figs 1 to 8 ) . Next , we determined if this mechanism was active in primary macrophages . We found that relative to primary neutrophils and NK cells , primary macrophages secrete disproportionately more CXCL8 protein from less CXCL8 mRNA ( Fig 9A ) . This matched the trend observed in the cell line counterparts ( Fig 1A ) . Primary macrophages also displayed high levels of CXCL8 and TNFAIP mRNA polysome association , which were comparable to HL-60 Mac ( Fig 9B ) . This occurred despite a reduction in ACTB and RPL27 mRNA polysome association relative to HL-60 Mac . Reduced ACTB polysome association was also reported for primary mouse macrophages relative to immortalized mouse macrophage cell lines [49] . Like their HL-60 Mac and KHYG-1 NK cell line counterparts ( Fig 2D ) , CXCL8-5’+3’ protein synthesis was elevated in primary macrophages relative to NK cells ( Fig 9C ) . This suggests that the UTR of CXCL8 confers elevated translation in primary macrophages relative to NK cells . Additionally , the ratio of phosphorylated rpS6 over total rpS6 was also increased in primary macrophages relative to NK cells ( Fig 9D ) . The elevated rpS6 phosphorylation was attenuated by ERK1/2 inhibitor ( AZD6244 ) treatment ( Fig 9E ) . These results matched their cell line counterparts ( Fig 7A and 7B ) . Finally , primary macrophages treated with the ERK1/2 signaling inhibitors ( U0126 and AZD6244 ) displayed attenuated expression of CXCL8 at the protein level but not at the mRNA level ( Fig 9F ) . The same inhibitors did not attenuate CXCL8 expression in primary neutrophils . Taken together , these findings suggest that ERK1/2 signaling induces the phosphorylation of rpS6 in primary macrophages , leading to the elevated expression of CXCL8 and TNFAIP6 in these cells .
Hitherto , the role of rpS6 phosphorylation has remained unclear as it did not appear to affect global mRNA translation rates [15] . Here , we demonstrate that the induction of rpS6 phosphorylation ( at S235/236 ) selectively enhances the translation of certain mRNA transcripts that contain novel AU-rich proximal cis-regulatory UTR sequences ( APS ) [Summarized in Fig 10] . In primary macrophages , ERK1/2 signaling induces the phosphorylation of rpS6 leading to the elevated translation of CXCL8 and TNFAIP6 . The location of the APS-motif , on the 3’ UTR , is distinct from known motifs found exclusively in the 5’ UTR [4–6 , 8 , 9] . Like previous work on CXCL8 [19–26] , our studies were conducted on primary human cells and cell line models . Studies on CXCL8 expression could not use the mouse model since the homolog of CXCL8 is deleted in mice [16] . This also meant that we could not use phospho-deficient rpS6 transgenic mice [14] , although it would have been a powerful tool to investigate the role of rpS6 phosphorylation . To study the effect of rpS6 phosphorylation , we inhibited multiple pathways upstream of rpS6 phosphorylation . The mTOR inhibitor ( Torin-1 ) only partially attenuated rpS6 S235/236 phosphorylation ( Fig 7B ) and did not reduce the translation of APS-positive CXCL8-5’+3’ in HL-60 macrophages ( S1C Fig ) . By contrast , when rpS6 S235/236 phosphorylation was more completely attenuated by the ERK1/2 signaling inhibitors ( AZD6244 and U0126 ) ( Figs 7B and 9E ) ; the translation of APS-positive CXCL8-5’+3’ , CXCL8-3’ , CXCL8 and TNFAIP6 reporters in macrophages was reduced ( Figs 6 and 9F ) . The effect of ERK1/2 signaling inhibition was cross-validated by two different inhibitors since both inhibitors are unlikely to share the same off-target effects , such as the activation of AMPK by U0126 [50] . All three inhibitors–Torin1 , U0126 and AZD6244–also reduced rpS6 S240/244 phosphorylation to a similar degree ( Fig 7B ) . This suggests that the U0126 and AZD6244 treatments did not act via the inhibition of rpS6 S240/244 phosphorylation to attenuate CXCL8-5’+3’ expression in HL-60 Mac ( Fig 6A ) . If that were the case , the Torin-1 treatment should have been just as potent in attenuating reporter expression ( S1C Fig ) . From these findings , we deduced that the elevated rpS6 S235/236 phosphorylation observed in HL-60 Mac was predominantly mediated by ERK1/2 signaling and that ERK1/2 inhibitors may attenuate the expression of APS-positive mRNAs by blocking this pathway . In addition to kinase inhibitors , the expression of exogenous wildtype and mutant proteins was also employed to study the role of rpS6 phosphorylation . The expression of constitutively active TAK1 , Akt or PKA led to increased expression of the APS-positive reporter , CXCL8-5’+3’ . This was likely due to the increased rpS6 S235/236 phosphorylation observed ( Fig 8A and 8B ) . To the best of our knowledge , rpS6 is the only known common downstream target of the TAK1 , Akt and PKA pathways . TAK1 signaling activates Rsk while Akt signaling activates S6K1 . PKA , Rsk and S6K1 are the three currently known rpS6 kinases that directly phosphorylate rpS6 at S235/236 [11] . Even though PKA is not known to phosphorylate rpS6 at S240/244 , a small increase was observed in the caPKA transfected cells ( Fig 8B ) . The increase was however , still at least 5-fold lower than that observed for 235/236 . Taken together , these findings support the hypothesis that the induction of rpS6 S235/236 phosphorylation enhances the translation of APS-positive mRNAs . Multiple mechanisms may contribute to the elevated level of CXCL8 protein secreted from macrophages . The 3’ UTR sequences have also been found to modulate the rate of mRNA transcription , mRNA stability and pre-recruitment of the signal recognition particle to the ribosome for secreted proteins [51–53] . Alterations in the rate of secretion could also occur as a result of changes in the activity of the eIF4E kinase , MNK1 [54] . Nevertheless , the rate of secretion is unlikely to be involved in the elevated cytoplasmic expression of CXCL8-5’+3’ ( -Sec ) protein observed in HL-60 Mac relative to A549 EC ( Fig 2G ) . Another possible mechanism may involve the ARE-motifs on the 3’ UTR of CXCL8 which reportedly accelerate mRNA degradation [34–36] . This may explain the reduced expression levels of CXCL8-full mRNA relative to CXCL8-CDS mRNA ( Fig 2A and 2B ) . However , the elevated expression of CXCL8-5’+3’ in macrophages was retained even after the deletion of these ARE motifs ( Fig 4A ) , which suggests that these ARE motifs were not responsible for the cell type-specific expression . Additionally , increased transcription or mRNA stability would lead to increased mRNA levels which , in this case , did not account for the level of secreted CXCL8 protein observed in macrophages that was elevated relative to CXCL8 mRNA levels ( Figs 1A , 2 and 9A ) . Thus , the elevated CXCL8 protein secretion in macrophages is most simply explained by an increase in the rate of CXCL8 translation , which was corroborated by the polysome profiles of CXCL8 in macrophages ( Figs 1C and 9B ) . Further studies are required to fully elucidate this novel mechanism of translational regulation . While it is clear that the mechanism involves: 1 ) a 3’ UTR that is at least a few hundred bases; and 2 ) an APS element; there may be other subtle requirements that await further discovery . The sequence feature in the CXCL8 5’ UTR that is responsible for its ability to enhance translation in macrophages when paired with a 3’ UTR ( Fig 5C ) also warrants further investigation . The 3’ UTR of CXCL8 in particular , is also known to be recognized by miRNA-93 , leading to the downregulation of CXCL8 mRNA and protein levels [55] . However , since various deletion mutants of the CXCL8 3’ UTR retained the same pattern of elevated expression in macrophages ( Fig 4B ) , it is highly unlikely that the same level of miRNA activity was exerted across all these deletion mutations . Additionally , it is likely that other pathways besides rpS6 phosphorylation are involved in the regulation of APS-positive mRNA expression . Certain observations point to this . For example , while the inhibition of ERK1/2 ( via U0126 ) attenuated rpS6 S235/236 phosphorylation ( Fig 7B ) , it did not reduce CXCL8-5’+3’ protein levels in HL-60 Mac to the levels observed in KHYG-1 NK cells ( Fig 6A ) . The APS-motif was elucidated in mutation assays with heterologous vector-derived CXCL8 and UTR-Nluc reporter transcripts . Vector-derived transcripts are widely employed to evaluate UTR activity and have so far been consistent with native mRNAs [5 , 6 , 8–10 , 51] . For example , both the endogenous mRNAs and vector-derived reporters that contain 5’ UTR CERT domains display selective translational repression in eIF4E haplo-insufficient mouse cells [5] . In another study , the deletion of the 3’ UTRs of endogenous CXCL1 , CXCL6 and CXCL8; led to increased mRNA stability which confirmed earlier findings based on heterologous reporter assays [51] . The deletion also led to an unexpected reduction in mRNA transcription leading to a decrease in mRNA levels despite increased mRNA stability . Thus , while the deletion of endogenous UTR sequences may lead to unintended effects on transcription , vector-derived transcripts have consistently replicated native UTR activity . Indeed , for this study , we found that the cell type-specific translation rate of endogenous CXCL8 matched that of vector-derived CXCL8-full mRNAs ( Fig 2A ) and CXCL8-5’+3’ UTR-Nluc reporters ( Fig 2D ) Future research to establish the significance of APS in regulating gene expression and its evolutionary conservation is warranted . In addition to CXCL8 and TNFAIP6 , other APS-positive mRNAs may exist . An analysis of the proximal AU content in the 3’ UTR of common cytokine signaling genes revealed the presence of potential APS in the mRNAs of TNFAIP6 , IFNG and IL2 ( Fig 5D ) but only the TNFAIP6 mRNA was expressed at sufficiently high levels for polysome profilling ( Figs 5E , 6B and 9B ) . APS-positive mRNAs may form a highly selective subset of genes as the distribution of 3’ UTR AU content in human genes appears to be skewed towards a low AU content [56] . The identification and characterization of genes that contain APS motifs may be an important area for future studies as this novel mechanism of translational control may regulate other genes that impact disease processes . In conclusion , we propose that rpS6 phosphorylation at S235/236 selectively enhances the translation of mRNAs that contain APS , a potentially novel RNA cis-regulatory element . These mRNAs possess: 1 ) a 3’ UTR of at least three hundred bases; and 2 ) an AU base content that exceeds fifty percent in the first hundred or so bases of the 3’ UTR immediately after the stop codon . In primary macrophages , the ERK1/2 pathway induces the phosphorylation of rpS6 leading to the elevated expression of CXCL8 and TNFAIP6 . This novel translational control mechanism allows macrophages to act as the primary producer of CXCL8 protein despite expressing less CXCL8 mRNA than cells such as neutrophils ( Fig 9A ) . Through the secretion of CXCL8 , macrophages recruit and activate other immune cells such as neutrophils [19] , monocytes and lymphocytes [20] to respond to infection , disease or injury . APS-modulated translation may also be aberrantly upregulated in a subset of tumour cells , leading to the overexpression of pro-oncogenic genes such as CXCL8 . Modulating the rate of APS-positive mRNA translation , such as CXCL8 , may be a novel strategy to treat diseases [57] . On its own , the 5’ UTR of CXCL8 is a potent translation enhancer . The truncated 5’ UTR sequence ( 75 bp ) could potentially be used to enhance the expression of therapeutic proteins .
This work was approved by the Institutional Review Board ( IRB ) , NUS-IRB B-14-063E , National University of Singapore ( NUS ) . The CXCL8 , Nluc and mCherry reporter vectors were generated as described in S1 Table . Positions 79 to 153 of NM_000584 was inserted immediately upstream of pNFAT Fluc ( Addgene plasmid #10959 [58] ) to form pNFAT 53’ Fluc . PCW57 . 1-4EBP1_4xAla ( from Prof David Sabatini , Addgene plasmid # 38240 [4] ) ; NFAT luciferase reporter ( from Toren Finkel , Addgene plasmid #10959 [58] ) ; pCNA-TAK1-WT , pCMV5-TAB1-FLAG , pCDNA-myr-AKT , pCDNA JNK/SAPK-MKK7 and pCMV-PKAca . Human peripheral blood monocytes , neutrophils and NK cells were isolated from healthy male adult donor aphaeresis cones ( National University Hospital , Blood Donation Centre , Singapore ) . This work was approved by the Institutional Review Board ( IRB ) , NUS-IRB B-14-063E , National University of Singapore ( NUS ) . Monocytes and NK cells were isolated as described previously [59] . Briefly , the buffy coat , which contained citrate-phosphate-dextrose ( CPD ) as anticoagulant , was diluted four times with PBS containing 2% FBS and 1 mM EDTA , and the mononuclear fraction was obtained via density gradient centrifugation with Ficoll-Paque Premium 1 . 073 ( GE Healthcare ) . From the mononuclear fraction , the monocyte and NK cell populations were enriched with the Human Monocyte Enrichment Kit and Human NK Cell Enrichment Kit ( Stemcell ) , respectively . For neutrophil isolations , buffy coats were diluted using Hank’s Balanced Salt Solution ( HBSS; Life Technologies ) . Red blood cells were sedimented by gravity using Hetasep solution ( Stemcell ) . Leukocytes were harvested and neutrophils were isolated using Human Neutrophil Enrichment kit ( Stemcell ) . Human macrophages , peripheral blood monocytes , neutrophils , NK cells , HL-60 cells , A549 cells , NCI-H1299 and KHYG-1 cells were cultured in RPMI ( with 10% FBS and 1% v/v penicillin and streptomycin ) at 37 oC . KHYG-1 cell media was supplemented with 10 ng/mL IL-2 . All cell lines were routinely tested to ensure mycoplasma-free cultures . Enriched human peripheral blood monocytes , at a cell density of 2 × 106/ml , were differentiated into macrophages by culture at 37 oC for 7 days in RPMI media containing 10% FBS and 1% v/v penicillin and streptomycin , and supplemented with 50 ng/ml M-CSF . HL-60 cells were differentiated into a macrophage-like phenotype ( HL-60 macrophage ) by plating the cells at a density of 2 x 106 cells/mL and culturing in media supplemented with 50 nM phorbol 12-myristate 13-acetate ( PMA ) for a day followed by another day in PMA-free media . HL-60 cells were differentiated into a polymorphonuclear neutrophil-like phenotype ( HL-60 PMN ) by plating the cells at a density of 1 x 106 cells/mL and culturing in media supplemented with 1 . 2% ( v/v ) dimethyl sulfoxide ( DMSO ) for 5 days . Primary cell isolations were routinely analyzed by flow cytometry , with mouse monoclonal antibodies from eBioscience . Preparations were typically more than: 85% CD14+CD16- for monocytes; 99% CD11b+CD14+ for macrophages; 95% CD66b+CD16+ for neutrophils; and 85% CD3+CD56+ for NK cells . Cells were treated at a final concentration of 10 μM U0126 ( Cell Signaling ) or 1 μM AZD6244 ( Selleckchem ) for 8 hours before samples were collected . Polysome profiling was performed as described previously [60] . Briefly , cells were preincubated with cycloheximide ( 100 μg/mL , Sigma ) for 15 min , and cytoplasmic lysates were prepared and fractionated by ultracentrifugation through 15%–50% linear sucrose gradients; 14 fractions were collected , and RNA extracted from each fraction was used for quantitative real-time PCR analysis . Immediately prior to transfection or treatment , cells were plated at a density of: 5 x 106 cells/ml for neutrophils; 2 x 106 cells/ml for NK cells and HL-60 PMN; and 1 x 106 cells/ml for macrophages and KHYG-1 cells . A549 cells were plated the day before at a density of 106 cells/mL . For HL-60 macrophages , undifferentiated HL-60 cells were plated at a density of 2 x 106 cells/mL in media supplemented with 50 nM PMA for two days . Treatments and transfections were performed in PMA-free media . Macrophage , HL-60 macrophages , NK cell , HL-60 PMN and KHYG-1 transfections were performed with the Neon Transfection System ( Invitrogen ) ; while A549 and H1299 transfections were performed with ViaFect Transfection Reagent ( Promega ) . Two hours after transfection or in non-transfection controls , cells were treated at a final concentration of 100 ng/mL Escherichia coli 055:B5 LPS ( Sigma ) , 10 ng/mL TNF ( Gibco ) , 10 μM U0126 ( Cell Signaling ) , 1 μM AZD6244 ( Selleckchem ) , 10 μM SB203580 ( Cell Signaling ) , 50 μM SP600125 ( Cell Signaling ) or 200 nM Torin-1 ( MedChem Express ) overnight before samples were collected . Secreted cytokines were measured using Human CXCL8 and IL6 ELISAs ( BD OptEIA ) . Nluc was assayed with Nano-Glo Luciferase Assay System ( Promega ) . Firefly luciferase ( Fluc ) was assayed with Luciferase Assay System ( Promega ) using . Luminescence was measured with GLOMAX 20/20 luminometer ( Promega ) . Real-time PCR was performed as previously described [61] . RNA was extracted in the presence of 4 μg glycogen ( Ambion ) using two rounds of Trizol Reagent ( Ambion ) to obtain a DNA-free sample . Purified RNAs were stored at -80 oC for less than a week before reverse transcription . RNA ( 0 . 5 μg via nanodrop ) was primed with random hexamers and reverse transcribed with the SuperScript III First-Strand Synthesis System ( Invitrogen ) . The resulting cDNA was stored in TE buffer at -20 oC . The cDNA was analyzed by real-time qPCR using the GoTaq qPCR Master Mix ( Promega ) and a LightCycler 480 ( Roche ) . qPCR experiments including primer design and efficiency tests was carried out according to the Minimum Information for Publication of Quantitative Real-Time PCR Experiments ( MIQE ) guidelines [62] . With RPL27 [63] ( 123 bp amplicon on NM_000988; forward primer:ATCGCCAAGAGATCAAAGATAA; reverse primer:TCTGAAGACATCCTTATTGACG ) and NeoR ( 84 bp amplicon on NeoR marker of pcDNA3 . 1; forward primer: CAAGATGGATTGCACGCAGG; reverse primer: GCAGCCGATTGTCTGTTGTG ) as the reference genes , we calculated the mean fold change of CXCL8 ( 132 bp amplicon on NM_000594 . 2; forward primer: TGTGAAGGTGCAGTTTTGCCAAGG; reverse primer: GTTGGCGCAGTGTGGTCCACTC ) and Nluc ( 117 bp amplicon on CDS of secNluc ( Promega ) ; forward primer: GTGTCCGTAACTCCGATCCA; reverse primer: TTCGATCTGGCCCATTTGGT ) . The expression levels relative to the control was calculated using the 2-ΔΔCT method . RPL27 has been previously validated to be stably expressed across a multitude of different cell types and experimental conditions [63] . Polysome profiling used the same RPL27 and CXCL8 primers and included the TNFAIP6 ( 212 bp amplicon on NM_007115 . 3; forward primer: TGCTGGATGGATGGCTAAGG; reverse primer: ACTCATTTGGGAAGCCTGGAG ) and ACTB ( 121 bp amplicon on NM_001101 . 5; forward primer: GTCATTCCAAATATGAGATGCGT; reverse primer: GCTATCACCTCCCCTGTGTG ) primers . DNA contamination was routinely assessed via qPCR of negative control reverse transcription reactions which lacked reverse transcriptase ( cycle thresholds above 35 ) . Total cell lysates were resolved on a denaturing SDS PAGE gel ( 12% ) and transferred onto PVDF membranes via the Trans-Blot Turbo Transfer System ( Biorad ) . These were then probed with antibodies ( all from Cell Signaling ) against rpS6 S235/236+phos ( #4858 ) , rpS6 S240/244+phos ( #5364 ) , total rpS6 ( #2217 ) , 4E-BP1 T37/46+phos ( #2855 ) , total 4E-BP1 ( #9644 ) , eIF4E S209+phos ( #9741 ) , total eIF4E ( #2067 ) , JUN S73+phos ( #3270 ) , total JUN ( #9165 ) , ERK1/2 T202/204+phos ( #4370 ) , total ERK1/2 ( #4695 ) , Akt S473+phos ( #4060 ) , total Akt ( #9272 ) , and β-Tubulin ( #2067 ) . These primary antibodies were then probed with the respective HRP-conjugated secondary antibodies . Western blot chemiluminescent signals were captured with an ImageQuant LAS 4000 mini ( GE Healthcare ) . Using ImageQuant TL 7 . 0 ( GE Healthcare ) , the band signal intensities of each sample were background subtracted ( minimum profile ) and normalized to control samples for the inhibitor treatments or the highest intensity cell sample between different cell types . The RefSeg mRNA sequences for human ( NM_000594 . 2 ) , horse ( NM_001083951 . 2 ) , pig ( NM_213867 . 1 ) , cattle ( NM_173925 . 2 ) and sheep ( NM_001009401 . 2 ) . RNA sequence motifs were predicted with RegRNA2 . 0 [39] .
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Ribosomal protein S6 ( rpS6 ) is a component of the cell translation system . This system produces proteins based on the instructions found on messenger ribonucleic acids or mRNAs . The activity of rpS6 is modified via the attachment of phosphate groups . This rpS6 “phosphorylation” regulates cell size , cell proliferation , glucose homeostasis and cancer defense . However , the molecular mechanism remains poorly understood . Here , we propose that rpS6 phosphorylation may affect the rate of translation of certain mRNAs . These mRNAs contain a high frequency of adenine and uracil bases in the first hundred or so bases of their 3’ UTR sequences , which we dub AU-rich proximal UTR sequences ( APS ) . APS-modulated mRNAs include the immune signaling proteins , CXCL8 and TNFAIP6 . This novel mechanism allows macrophages to secrete sufficient CXCL8 protein to attract and activate other immune cells such as neutrophils during injury or disease . It may also be aberrantly upregulated in a subset of tumors , leading to the overexpression of APS-positive genes such as CXCL8 . Indeed , both rpS6 phosphorylation and CXCL8 expression are consistently found , by separate studies , to be tumor-promoting and upregulated in cancers . Modulating these APS-positive mRNAs may be a novel strategy to treat diseases .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
[
"blood",
"cells",
"phosphorylation",
"medicine",
"and",
"health",
"sciences",
"immune",
"cells",
"3'",
"utr",
"immunology",
"messenger",
"rna",
"signal",
"inhibition",
"untranslated",
"regions",
"sequence",
"motif",
"analysis",
"research",
"and",
"analysis",
"methods",
"sequence",
"analysis",
"white",
"blood",
"cells",
"animal",
"cells",
"proteins",
"bioinformatics",
"gene",
"expression",
"biochemistry",
"rna",
"signal",
"transduction",
"cell",
"biology",
"post-translational",
"modification",
"nucleic",
"acids",
"protein",
"translation",
"database",
"and",
"informatics",
"methods",
"genetics",
"5'",
"utr",
"biology",
"and",
"life",
"sciences",
"cellular",
"types",
"macrophages",
"cell",
"signaling"
] |
2019
|
Novel AU-rich proximal UTR sequences (APS) enhance CXCL8 synthesis upon the induction of rpS6 phosphorylation
|
Although rabies is endemic in Laos , genetic characterization of the viruses in this country is limited . There are growing concerns that development in the region may have increased transport of dog through Laos for regional dog meat consumption , and that this may cause spillover of the viruses from dogs brought here from other countries . This study was therefore undertaken to evaluate the current rabies situation and the genetic characteristics of rabies viruses currently circulating in Laos . We determined the rate of rabies-positive samples by analyzing data from animal samples submitted to the Lao Ministry of Agriculture and Forestry’s National Animal Health Centre rabies laboratory from 2004 through 2011 . Twenty-three rabies-positive samples were used for viral genetic characterization . Full genome sequencing was performed on two rabies viruses . Rabies-positive samples increased substantially from 40 . 5% in 2004 to 60 . 2% in 2009 and continued at this level during the study period . More than 99% of the samples were from dogs , followed by cats and monkeys . Phylogenetic analyses showed that three rabies virus lineages belonging to the Southeast Asian cluster are currently circulating in Laos; these are closely related to viruses from Thailand , Cambodia and Vietnam . Lineages of the circulating Laos rabies viruses diverged from common ancestors as recently as 44 . 2 years and as much as 55 . 3 years ago , indicating periodic virus invasions . There is an increasing trend of rabies in Laotian animals . Similar to other rabies-endemic countries , dogs are the main viral reservoir . Three viral lineages closely related to viruses from neighboring countries are currently circulating in Laos . Data provide evidence of periodic historic exchanges of the viruses with neighboring countries , but no recent invasion .
Globally , an estimated 60 , 000 people die of rabies annually , and more than 31 , 000 of these deaths occur in Asia [1 , 2] . Among various Asian regions , the countries of the Association of South East Asian Nations ( ASEAN ) have been working towards substantial economic development . A call for elimination of rabies by 2020 highlights the political importance of rabies control [3] . Seven out of the 10 ASEAN member states are rabies-endemic: Cambodia , Indonesia , Laos , Myanmar , the Philippines , Thailand and Vietnam [3] . Among these countries , Laos has the lowest reported number of human deaths from rabies . However , the precise morbidity , mortality and molecular epidemiology of rabies in Laos is largely unknown . This is due to difficulty in collecting data and samples from remote areas of the country , and to the country’s modest data collection system at the centralized diagnostic facility . Survey of prevalence of canine rabies is still in its initial stages and limited to a small central part of Laos . The first reported phylogenetic study showed that Laotian rabies viruses are grouped with viruses from Thailand , Myanmar , Cambodia and Vietnam [4] . Combined analyses from geographic information system data showed that China is the likely source of the Asian rabies viruses , whereas individual migration event suggested that Cambodia may be a source of Asian rabies viruses transmission to China , Laos and Thailand [5] . The Laotian government vision is to convert the country from a ‘land-locked’ to ‘land-linked’ due to its strategic position in the ASEAN region . As a result , a number of bridges and new roads have been built to connect Laos to neighboring countries . Since ancient times , Laos has relied on its neighbors for trading . For historical , travel convenience and cultural reasons , Thailand has been a primary trading partner . The Mekong River region is well known for its culture of dog-meat consumption [6] . With growing economic prosperity and improved roads across this region , movement of people and allegedly , dogs for meat consumption has been increasing substantially . These factors may have influenced the dissemination and evolution of rabies viruses . That rabies is a neglected tropical disease is exemplified by the fact that with the exception of Thailand , a full viral genome sequence has been unavailable across the rabies-endemic South East Asian countries . Rabies belongs to the genus Lyssavirus of the family Rhabdoviridae . It is a single-stranded , negative-sense RNA of approximately 12 kb that encodes five structural proteins: nucleoprotein ( N ) , phosphoprotein ( P ) , matric protein ( M ) , glycoprotein ( G ) , and RNA-dependent RNA polymerase ( L ) . These genes are separated by intergenic regions of variable length . Phylogenetic classification of rabies viruses is based on specific genes , mostly from partial gene sequences , and thus may lead to inconsistent results . It is possible that phylogenetic classification using complete genome sequences , rather than from a partial sequence of a specific gene , would offer a more robust and comprehensive means of addressing the evolution , spread and genome-wide heterogeneity of viruses [7] . Complete genome sequencing of rabies viruses from these countries will also help explain the evolution of the viruses in Laos and the Mekong River region . Because only complete genome sequence can reveal the length , nucleotide substitution patterns , and variations in the start signal , stop signal and other motifs across the genes . As a result it can provide more information to compare and can generate reliable results on genome evolution . Therefore , this study was undertaken to quantify the current animal rabies occurrence in Laos and to complete a molecular characterization of the viruses in current circulation .
The study was approved ( No . 38/NECHR ) by the National Ethics Committee for Health Research , Ministry of Health , Laos . To determine the prevalence of rabies , we analyzed data from samples submitted from various regions of Laos to the rabies laboratory of the National Animal Health Centre , Department of Fisheries and Livestock , Ministry of Agriculture and Forestry from January 2004 through December 2011 . This is the only central animal rabies diagnostic laboratory in Laos . In Laos , dog and cat rabies are notifiable , but not wildlife rabies . For animal samples , the head of the suspected animal was submitted to the laboratory , and the brain was dissected by a trained technician . These animals had signs of rabies such as aggressive behavior , a tendency to bite and excessive salivation , with or without a history of biting humans and/or animals . There are no community veterinarians in Laos; samples from suspect animals are submitted mainly by the general public . Brain sample tests are performed using a fluorescent antibody test ( FAT ) on crushed smears of hippocampus for a fee of 30 , 000 Kip ( approximately US$ 3 . 70 ) and test results are provided on paper to the individual who submitted the sample . In emergency cases , such as when postexposure prophylaxis ( PEP ) is required , the person is informed of the results by phone . The samples submitted from Vientiane capital , Vientiane and Champasak provinces ( Fig 1 ) to the rabies laboratory of National Animal Health Centre , during February 2011 through March 2012 , were used in this study for molecular characterization ( S1 Table ) . Total RNA was extracted from about 1 g of brain homogenate by using Trizol ( Invitrogen , Carlsbad , CA , USA ) according to the manufacturer’s instruction . Extracted RNA was stored at -30°C until further analyses . Using random hexamer primers cDNA was synthesized by SuperScript III First-Strand Synthesis System ( Invitrogen ) according to the instructions of the manufacturer . The synthesized cDNA was diluted with DNase/RNase free water ( Invitrogen ) as a template . PCR was performed using TaKaRa ExTaq ( Takara Bio Inc . , Shiga , Japan ) . Nested PCR for nucleoprotein ( N ) gene was performed to detect the presence of rabies virus genome in the samples [8] . The PCR for N and glycoprotein ( G ) genes , and G-L intergenic region was performed [7] . Whole genome sequence of two strains , arbitrarily selected from Vientiane capital and Champasak samples was performed [7] . For 13 other strains only full-length N gene sequence could be performed . Cycle sequencing of the amplified product was performed using the BigDye Terminator v3 . 1 Cycle Sequencing Kit ( Applied Biosystems , Foster city , CA , USA ) . The purified amplicons were sequenced using ABI-3130 Genetic sequencer ( Applied Biosystems ) . All steps were done according to the manufacturer’s instruction . The 5′ or 3′-terminal end of the genome was amplified using SMART RACE cDNA Amplification Kit ( Clontech Laboratories , Inc . , Mountain View , CA , USA ) according to the instructions of the manufacturer . Evolutionary analysis was done using the full-length N gene . We inferred a Maximum Clade Credibility phylogenetic tree using the Bayesian Markov Chain Monte Carlo method available in the BEAST package , v1 . 6 . 1 [9] . The analysis utilized a relaxed ( uncorrelated lognormal ) molecular clock and GTR+Γ+I model of nucleotide substitution . The model was selected on the basis of Akaike Information Criterion using jModelTest software [10] . All chains were run for 60 million generations and sampled every 3000 steps . This resulted in an effective sample size of >521 for all estimated parameters . The posterior densities were calculated using with 10% burn-in and checked for convergence using Tracer , v . 1 . 5 . The nucleotide and amino acid sequences of genes and intergenic regions were compared among rabies viruses from Laos . The nucleotide sequences were used to construct the whole genome phylogenetic tree [7] . Multiple sequence alignment was done by ClustalW ver . 2 then phytogenic tree was constructed with MEGA ver . 5 using the neighbor joining ( NJ ) method and the branching pattern was statistically evaluated by bootstrap analysis of 1000 replicates .
During this eight years period , number of submitted samples peaked in 2008 and gradually decreased ( Table 1 ) . Whereas number of rabies positive samples varied annually , peaked in 2009 and gradually decreased . However the percentage of rabies positive samples increased significantly from 40 . 5% in 2004 to 60 . 2% in 2009 and continued at this level . Annually , mean 157 . 6 {95% confidence interval ( CI ) 129 . 9–185 . 3} samples were submitted for rabies diagnosis , among them 80 . 6 ( 95% CI 65 . 3–95 . 9 ) samples were rabies positive i . e . 51 . 7% ( 95% CI 45 . 0–58 . 4% ) of the submitted samples were rabies positive . Most of the submitted samples were from dogs 155 . 1 ( 95%CI 129 . 0–183 . 2 ) , followed by cats 1 . 0 ( 95% CI 0–2 . 4 ) , and monkeys 0 . 5 ( 95% CI 0–1 . 1 ) . Likewise most of the rabies positive samples were also from dogs 80 . 0 ( 95%CI 65 . 5–94 . 4 ) , followed by cats 0 . 5 ( 95%CI 0–1 . 4 ) , and other animals 0 . 13 ( 95% CI 0–0 . 4 ) . These represent that 99 . 2% of the rabies samples were from dogs followed by cats and monkeys ( 0 . 6% and 0 . 3% , respectively ) . Province-wise ( Table 2 ) data analyses showed that yearly submitted samples were mainly from Vientiane capital 115 . 1 ( 95% CI 90 . 2–140 . 0 ) , followed by Champasak 25 . 4 ( 95% CI 14 . 3–36 . 4 ) , Vientiane province 11 . 7 ( 95% CI 6 . 6–16 . 9 ) , and other provinces 5 . 4 ( 95% CI 3 . 1–7 . 6 ) . Samples from Vientiane capital represents 73 . 0% of the total submitted samples followed by Champasak ( 16 . 1% ) , Vientiane province ( 11 . 7% ) , and other provinces ( 3 . 4% ) . From other provinces sample number never exceeded more than six and usually only one per year . Samples were never received during this period from six of 18 provinces of Laos . The presence of rabies virus was confirmed in 21 of the 23 FAT positive samples by RT-PCR and partial nucleotide sequence of these amplicons . Lao9 and Lao19 samples from Vientiane capital were negative by RT-PCR . The full-length N gene sequence could be done in a total of 15 samples that were used in time-line evolutionary analysis . These samples were from Vientiane capital and Champasak provinces , the full-length N gene of the only sample from Vientiane province could not be amplified . The mean rate of nucleotide substitution estimated for the N gene was 2 . 5×104 substitutions/site/year ( 95% HDP values 1 . 6–3 . 4×104 substitutions/site/year ) . This rate is in agreement with previous studies [11] . Phylogenetic tree ( Fig 2 ) revealed that rabies strains in Laos belong to the Southeast Asian ( SEA ) cluster that diverged from the Chinese strains approximately 331 . 5 years ( 95% HPD 215 . 1–481 . 9 years ) ago . From the most recent common ancestor ( TMRCA ) of SEA cluster , approximately 84 . 5 years ( 95% HPD 58 . 8–120 . 7 years ) ago , i . e . , around 1928 ( 95% HPD range 1891 to 1953 ) , rabies virus of Myanmar segregated . Approximately 62 . 6 years ( 95% HPD 45 . 1–87 . 4 years ) ago , i . e . , around 1949 ( 95% HPD range 1925 to 1967 ) , a cluster only containing Laos rabies viruses segregated from TMRCA of the rest of the SEA cluster which contained viruses from Laos , Cambodia , Vietnam and Thailand . The Lao rabies viruses segregated approximately 44 . 2 years ( 95% HPD 29 . 0–64 . 1 years ) ago , i . e . , around 1968 ( 95% HPD range 1948 to 1983 ) , into two lineages , one containing viruses circulated during 1999–2002 designated as Laos I , and the other contained viruses we identified in 2011 and 2012 designated as Laos II . This lineage had 11 viruses only 2 were from Champasak district and rest from Vientiane capital . Approximately 55 . 3 years ( 95% HPD 40 . 7–76 . 7 years ) ago i . e . in 1957 ( 95% HPD 1935–1971 ) Laos III , containing one rabies virus from Vientiane capital and two from Champasak , diverged from rest of SEA cluster which still contained a rabies viruses from Laos . We designated this lineage as Laos IV which segregated from the other lineages of the SEA cluster , only containing rabies viruses from Cambodia , Vietnam and Thailand , approximately 46 . 4 years ( 95% HPD 35 . 6–62 . 7 years ) ago , i . e . in 1966 ( 95% HPD 1949–1976 ) . All lineages were supported by significant posterior value . We completed the whole genome sequence of two strains , strains Lao2 and Lao4 belong to Lao II and Lao III lineage , respectively . The full genome of both strains was 11924 nt long . At whole genome level there was 97 . 2% identity between the strains . The N , P , M , G and L genes , and G–L intergenic region were of same length ( Table 3 ) . The nucleotide identity of the genes and their deduced amino acid identity were 96 . 2–97 . 6% and 97 . 6–99 . 6% , respectively ( Table 3 ) . To further identify the different between Lao II and Lao III lineages , strain Lao2 were compared with strain Lao4 to detect the substitutions in the deduced amino acid sequences ( Table 4 ) . A total of 33 substitutions were identified among them 14 were in various domains of the proteins and 19 were in portion of the protein where no site/domain/region has been identified . Phylogenetic tree constructed by using whole genome showed that the bat origin rabies viruses from Americas formed a separate cluster from rest of the strains ( Fig 3 ) . Rest of the strains was divided into China , Southeast Asia , arctic/arctic like , Europe-America and Sri Lanka clusters . The China cluster consists of two major sub-clusters China I and China II . All clusters and sub-clusters were supported by bootstrap value of 100 . Phylogenetic tree revealed that rabies strains from Laos belong to the SEA cluster with Thai strains . Strain Lao4 from Champasak province was closer to Thai strain than strain Lao2 from Vientiane capital .
There is an increasing trend of rabies virus detection in animal samples in Laos , which may indicate increase of rabies since dog immunization rate is low . An integrated approach is needed such as public education , access to vaccine and rabies test at affordable cost and time . Since dogs are main animal reservoir of rabies virus in Laos , therefore it might be easier to control rabies if appropriate program is introduced . Circulating rabies viruses in Laos are closely related with the rabies viruses from neighboring countries . Possibly there is no recent invasion of rabies viruses in Laos but in the past there was periodic exchange of rabies viruses with neighboring countries . Dog movements through Laos for regional dog meat consumption did not cause any spillover recently . More regional laboratories should be established in different parts of the country for proper surveillance of rabies in Laos .
|
Laos is a land-locked rabies-endemic country in Southeast Asia that is surrounded by five rabies-endemic countries . Thus , there is increasing concern that the epidemiology of rabies in Laos is influenced by infrastructure development and economic activities , including international transport of dogs for meat consumption . Studies on the epidemiology of rabies are limited in this country . Therefore , to gain further information about the epidemiology and the genetic characteristics of circulating rabies viruses , this study was conducted using samples submitted to the rabies Lao Ministry of Agriculture and Forestry’s National Animal Health Centre rabies laboratory . Out of 18 provinces , samples were submitted mainly from the capital Vientiane and Champasak province . Data from the period 2004 through 2011 showed a gradual increase in rabies-positive samples . Dogs were the main viral reservoir , and genetic analyses of samples collected from February 2011 through March 2012 showed that three viral lineages are currently circulating in the country . These rabies viruses are related to those of neighboring countries , indicating shared ancestry but no recent viral invasion .
|
[
"Abstract",
"Background",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
|
Molecular Epidemiology of Rabies Viruses Circulating in Two Rabies Endemic Provinces of Laos, 2011–2012: Regional Diversity in Southeast Asia
|
DNA methyltransferase 3A ( DNMT3A ) is an enzyme involved in DNA methylation that is frequently mutated in human hematologic malignancies . We have previously shown that inactivation of Dnmt3a in hematopoietic cells results in chronic lymphocytic leukemia in mice . Here we show that 12% of Dnmt3a-deficient mice develop CD8+ mature peripheral T cell lymphomas ( PTCL ) and 29% of mice are affected by both diseases . 10% of Dnmt3a+/- mice develop lymphomas , suggesting that Dnmt3a is a haploinsufficient tumor suppressor in PTCL . DNA methylation was deregulated genome-wide with 10-fold more hypo- than hypermethylated promoters and enhancers , demonstrating that hypomethylation is a major event in the development of PTCL . Hypomethylated promoters were enriched for binding sites of transcription factors AML1 , NF-κB and OCT1 , implying the transcription factors potential involvement in Dnmt3a-associated methylation . Whereas 71 hypomethylated genes showed an increased expression in PTCL , only 3 hypermethylated genes were silenced , suggesting that cancer-specific hypomethylation has broader effects on the transcriptome of cancer cells than hypermethylation . Interestingly , transcriptomes of Dnmt3a+/- and Dnmt3aΔ/Δ lymphomas were largely conserved and significantly overlapped with those of human tumors . Importantly , we observed downregulation of tumor suppressor p53 in Dnmt3a+/- and Dnmt3aΔ/Δ lymphomas as well as in pre-tumor thymocytes from 9 months old but not 6 weeks old Dnmt3a+/- tumor-free mice , suggesting that p53 downregulation is chronologically an intermediate event in tumorigenesis . Decrease in p53 is likely an important event in tumorigenesis because its overexpression inhibited proliferation in mouse PTCL cell lines , suggesting that low levels of p53 are important for tumor maintenance . Altogether , our data link the haploinsufficient tumor suppressor function of Dnmt3a in the prevention of mouse mature CD8+ PTCL indirectly to a bona fide tumor suppressor of T cell malignancies p53 .
DNA methylation is an epigenetic modification involved in transcriptional regulation of gene expression . Three catalytically active DNA methyltransferases—Dnmt1 , Dnmt3a , and Dnmt3b—are involved in the generation and maintenance of DNA methylation in mammalian cells . Dnmt3a and Dnmt3b are classified as de novo enzymes due to their methylation activity during early embryogenesis [1] , whereas Dnmt1 has a high affinity for hemi-methylated sites and functions in the maintenance of methylation marks during cellular division [2 , 3] . Recent studies suggest that all Dnmts may play roles in generating and maintaining DNA methylation . For instance , in mouse hematopoietic stem cells , Dnmt3a is responsible for maintaining DNA methylation in lowly methylated regions known as canyons [4] . In addition , Dnmt1 was shown to have cancer-specific de novo activity in a mouse model of MYC-induced T cell lymphomas [5] , whereas Dnmt3a and Dnmt3b were primarily involved in maintenance methylation in tumors [6 , 7] . However , a deeper understanding of individual Dnmt’s activities in normal development and in cancer is still missing . DNA methyltransferase 3a has emerged as a central regulator of hematopoiesis over the last several years . The interest in Dnmt3a was in particular fueled by recent findings of somatic mutations in human hematologic malignancies of myeloid and T cell origin [8 , 9] . Given the importance of DNA methylation for differentiation of hematopoietic lineages [10] along with critical roles of Dnmt3a in differentiation and self-renewal of hematopoietic stem cells [11 , 12] , it is not unexpected that a disruption of Dnmt3a activity affects a variety of cell types and has the potential to transform hematopoietic lineages . For example , recent studies using the Mx1-Cre transgene to conditionally delete Dnmt3a in hematopoietic stem and progenitor cells ( HSPCs ) followed by transplantation into lethally irradiated recipients showed that a vast majority of mice develop myeloid disorders such as myeloid dysplastic syndrome and acute myeloid leukemia ( 69% ) with rare occurrences of CD4+CD8+ double positive T-ALL ( <12% ) or B-ALL ( <4% ) [13] . In addition , both myeloid deficiencies and neoplasms were observed in mice transplanted with Dnmt3a-null bone marrow obtained from Mx1-Cre;Dnmt3afl/fl mice , altogether highlighting the importance of Dnmt3a in prevention of myeloid transformation [14 , 15] . However , the role of Dnmt3a in differentiation into hematopoietic lineages and molecular functions in normal and malignant hematopoiesis in particular remain poorly understood . To elucidate the role of Dnmt3a in normal and malignant hematopoiesis we used the EμSRα-tTA;Teto-Cre;Dnmt3afl/fl;Rosa26LOXPEGFP/EGFP ( Dnmt3aΔ/Δ ) mouse model to conditionally delete Dnmt3a in all cells of the hematopoietic compartment . Using this model , we previously showed that long-term Dnmt3a-defficiency resulted in the development of a chronic lymphocytic leukemia ( CLL ) around 1 year of age [16 , 17] . In addition , we previously reported that combined inactivation of Dnmt3a and Dnmt3b results in the development of CLL and peripheral T cell lymphoma ( PTCL ) [16] , however the molecular basis of PTCL is poorly understood . Here we expanded on our previous studies by observation of a larger cohort of Dnmt3aΔ/Δ mice . These studies revealed that while ~60% of mice succumb to CLL , ~40% of mice develop CD8+ mature peripheral T cell lymphoma either in combination with CLL or as a singular disease . Furthermore , we found that loss of one allele of Dnmt3a is sufficient to induce CD8+ PTCL in 10% of Dnmt3a heterozygous mice with tumors retaining expression of the wild-type allele . Molecular profiling of methylation and gene expression identified promoter hypomethylation as a major event in tumorigenesis of PTCL , which was frequently accompanied by upregulation of gene expression . Furthermore , we identified downregulation of tumor suppressor p53 not only in Dnmt3a+/- and Dnmt3aΔ/Δ lymphomas but also in pre-tumor thymocytes , suggesting that p53 downregulation is likely relevant in the initiation/progression of lymphomagenesis . Altogether , our data demonstrate that Dnmt3a is a haploinsufficient tumor suppressor in the prevention of CD8+ T cell transformation and highlight the importance of understanding of the roles of Dnmt3a target genes in disease pathogenesis .
We previously utilized quadruple transgenic mice , EμSRα-tTA;Teto-Cre;Dnmt3afl/fl; Rosa26LOXPEGFP/EGFP ( designated hereafter as Dnmt3aΔ/Δ ) , to conditionally inactivate Dnmt3a in HSPCs as well as mature cells of all hematopoietic lineages ( Fig 1A ) . In such genetic setting , Dnmt3a is deleted in only ~40% of hematopoietic cells due to restricted patterns of EμSRα-tTA expression and cells are marked by EGFP expression driven from a reporter gene [16 , 17] . In the remaining 60% of hematopoietic cells the EμSRα-tTA transgene is not expressed and , as a result , the Dnmt3a conditional allele is not deleted and the EGFP reporter is not expressed . PCR based genotyping confirmed Dnmt3a deletion in EGFP–positive but not EGFP-negative stem cells as well as T- , B- , and myeloid cells ( Fig 1B ) . Furthermore , Dnmt3a deletion was specific to cells of the hematopoietic lineages and was not observed in solid tissues ( S1A Fig ) . Previously , we observed a small cohort of Dnmt3aΔ/Δ mice and reported the development of a CLL-like disease with a median survival of 371 days [16] . Here we utilized a larger cohort of 42 Dnmt3aΔ/Δ mice to observe the phenotypic consequences of Dnmt3a inactivation . Consistent with our previously reported data , we observed the development of a CLL-like disease in 61% of mice with a median survival of 306 days ( Fig 1C and S1B Fig ) . This disease was characterized by expansion of B220+CD19+CD5+IgM+ EGFP+ cells in the spleen , blood , bone marrow , peritoneal cavity ( IP ) and occasionally in the lymph nodes ( S1C and S1D Fig ) . Interestingly , 12% of Dnmt3aΔ/Δ mice developed a different disease ( MS = 295 days ) characterized not only by splenomegaly but also by a significant enlargement of lymph nodes that was not observed in the CLL cases ( Fig 1C , 1D and S1B Fig ) . Histological analysis of spleens showed near complete effacement of the red pulp by massively expanded white pulp ( Fig 1E ) . Small- to medium-sized cells were EGFP+ , expressed markers of mature T cells–CD3 , CD5 , TCRβ and CD8 –and were negative for the expression of CD4 , TCRγδ , NK-1 . 1 and CD16 ( Fig 1F , 1G and S1E Fig ) . To determine if Dnmt3aΔ/Δ PCTLs are clonal , we analyzed TCR-Vβ rearrangement by FACS analysis . All three Dnmt3aΔ/Δ lymphomas analyzed showed only one or two TCR-Vβ rearrangements , suggesting that they were clonally derived from a single cell following somatic recombination of the TCR-β locus ( S1F Fig and S1 Table ) . These phenotypes are most consistent with those observed in human cytotoxic peripheral T cell lymphomas not otherwise specified ( PTCL-NOS ) . Dnmt3a was efficiently deleted in lymph node cells of terminally ill mice as determined by immunoblot analysis using anti-Dnmt3a antibody ( Fig 1H ) . When lymph node cells from terminally sick Dnmt3aΔ/Δ mice were injected into the IP cavity of sublethally irradiated FVB mice , recipients developed a CD3+CD8+ PTCL similar to that observed in the donor mice ( Fig 1I ) , suggesting that Dnmt3aΔ/Δ cells have tumorigenic potential . Tumor burden ( scored as average weights of spleens in terminally ill mice ) was on average higher in PTCL than in CLL ( S1G Fig ) . In addition to the development of distinct disease types in individual mice , in 29% of mice we observed the simultaneous development of CLL and PTCL with a median survival of 293 days ( Fig 1C , S1B and S1H Fig ) . Interestingly , all CLL and PTCL cases presented with B220+CD19+CD5+ and CD3+CD8+ immunophenotypes , respectively , suggesting that normal B-1a B cells and cytotoxic CD8+ T cells are in particularly sensitive to cellular transformation in the absence of Dnmt3a . Altogether , these data suggest that Dnmt3a is a tumor suppressor gene in prevention of CLL and PTCL in mice . We have recently reported that mice harboring a conventional knockout allele of Dnmt3a ( Dnmt3a+/- mice ) develop either CLL , myeloproliferative disorder or remain healthy by 16 months of age [17] . Here we expanded these studies by observing a larger cohort of 30 Dnmt3a+/- and 20 control Dnmt3a+/+ mice . Interestingly , we found that 3 out of 30 analyzed mice developed CD8+ T cell lymphomas , which were indistinguishable from those observed in Dnmt3aΔ/Δ mice ( Fig 2A–2C ) . None of the control mice were affected by lymphoma and remained healthy during the observational period . Serial transplantation of Dnmt3a+/- lymphoma cells induced PTCL within 2 months in secondary and tertiary transplanted mice , illustrating their selective advantage to grow and induce disease ( Fig 2D ) . Dnmt3a+/- lymphomas retained approximately 50% expression of Dnmt3a , suggesting that the remaining allele is expressed in fully transformed cells ( Fig 2E ) . Like Dnmt3aΔ/Δ lymphomas , Dnmt3a+/- lymphomas were also clonal ( Fig 2F and S1 Table ) . Importantly , sequencing analysis of cDNA generated from two independent Dnmt3a+/- PTCL samples revealed no mutations in the coding sequence of Dnmt3a ( S1 File ) , demonstrating that the expressed Dnmt3a allele is in the wild-type configuration . Similarly , we did not find any mutations in the coding sequences of two genes that are commonly mutated in human T cell malignancies , Tet2 and RhoA , and their expression was not changed in Dnmt3a-deffcient lymphomas , suggesting that changes in the activity of these genes may not be involved in the transformation of T cells in this model ( S2 File and S2 Fig ) . Altogether , these data suggest that Dnmt3a is a haploinsufficient tumor suppressor gene in the prevention of CD8+ T cell lymphomas and CLL in mice . To determine the nature of deregulated molecular events during PTCL development in Dnmt3aΔ/Δ mice , we performed global methylation analysis using whole genome bisulfite sequencing ( WGBS ) and gene expression profiling by RNA-seq on CD8+ T cells isolated from Dnmt3a+/+ spleens , as this cellular population is immunophenotypically the closest normal counterpart of CD8+CD4- PTCLs . Methylation analysis revealed that 75% of 13 , 859 , 068 CpG dinucleotides were heavily methylated ( ≥76% ) , while only 6% were methylated at low levels ( ≤25% ) ( Fig 3A ) . The remaining 19% of CpG were methylated at intermediate levels ( 25% to 75% ) . Likewise , 44% of core promoters ( -300 to +150 bp relative to transcription start site; TSS ) were heavily methylated ( ≥76% ) , while 29% were lowly methylated ( ≤25% ) ( Fig 3B ) . Analysis of methylation across core promoter regions revealed that over 13 , 000 genes had a mean methylation value greater than 50% , suggesting that the majority of promoters in CD8+ T cells are heavily methylated ( Fig 3C and S2 Table ) . A combined gene expression and methylation analysis revealed that the majority of genes with low levels of promoter methylation were expressed , whereas genes with high levels of promoter methylation were largely repressed , suggesting that promoter methylation correlates with gene expression ( Fig 3D and S3 Table ) . Ingenuity pathway analysis ( IPA ) of highly expressed genes in CD8+ T cells revealed the top subcategories of genes significantly associated with organismal survival , hematological system , tissue morphology , hematopoiesis , lymphoid tissue structure ( Fig 3E ) , underlining their link to hematopoietic system . Altogether , these data reveal that a significant number of promoters are hypermethylated and inactive in normal CD8+ T cells , highlighting both the importance of DNA methylation in differentiation and potential for deregulation of these genes upon inactivation of DNA methyltransferases . To determine the effects of Dnmt3a loss on the cancer methylome , we next performed WGBS on DNA isolated from Dnmt3aΔ/Δ PTCL cells . Out of ~14 million CpG dinucleotides analyzed , we observed decreased methylation in 1 , 263 , 413 ( 9% ) CpGs and increased methylation in 155 , 977 ( 1% ) CpGs ( Fig 4A and S4 Table ) . By analysis of differentially methylated cytosines ( DMCs ) we found that the majority of DMCs were present in gene bodies and intergenic regions , where hypomethylation was 8 fold higher than hypermethylation ( Fig 4B and S4 Table ) . Although the vast majority of changes in methylcytosine levels occurred in gene bodies and intergenic regions , we detected an overall decrease in methylation in both long and short promoter regions ( -1500 to +500 bp and -300 to +150 bp relative to TSS , respectively ) in Dnmt3aΔ/Δ PTCL relative to CD8+ T cell controls ( Fig 4C and S5 Table ) . Likewise , analysis of differentially methylated regions ( DMRS ) found significant changes in the methylation of long promoters , with 500 hypomethylated DMRS and 50 hypermethylated DMRS identified in PTCL relative to CD8+ T cell controls ( Fig 4D and S6 Table ) . Similarly , short promoters were hypomethylated ( 132 ) more so than hypermethylated ( 19 ) in PTCL ( Fig 4D and S6 Table ) . Like with promoters , hypomethylated DMRS were 10-and 18-fold higher than hypermethylated DMRS in gene bodies and enhancers , respectively ( Fig 4D and S6 Table ) . Extensive hypomethylation was also observed in repeat elements , with LINE elements showing the largest degree of hypomethylation ( ~4 fold ) compared to hypermethyation ( Fig 4E ) . Next , we were interested in determining if differentially methylated promoter regions shared particular transcription factor binding motifs . This analysis revealed a significant enrichment for AML1 , NF-κB , and OCT1 binding motifs in hypomethylated promoters ( Fig 4F ) . This suggests a possible involvement of these factors in maintenance methylation performed by Dnmt3a . Similarly , AP-2rep , SOX5 , and myogenin binding motifs were enriched in gene promoters hypermethylated in tumors , possibly implying role of these factors in cancer-specific aberrant methylation ( Fig 4G ) . Further functional analysis will be required to test an involvement of these proteins in deregulated methylation in mouse lymphomas . Locus-specific analysis revealed that hypo- and hypermethylated DMRS associated with promoters and gene bodies were relatively equally distributed across the genome , with the highest number of hypomethylated promoters present on chromosomes 11 and 5 , lowest numbers on chromosomes X and 12 ( Fig 5 and S6 Table ) . Interestingly , very few differentially methylated promoters were detected on the X chromosome , suggesting that Dnmt3a is dispensable for maintenance methylation in these areas of the genome ( Fig 5 and S6 Table ) . Altogether , our data suggest that disease development in the absence of Dnmt3a results in decreased methylation across the genome with a significant number of gene promoters affected whose untimely activation may contribute to the malignant transformation of CD8+ T cells . To determine whether the methylation landscape generated by WGBS is specific to the PTCL sample profiled or rather represents common changes that occur in Dnmt3a-deficient lymphoma , we validated hypo- and hypermethylated promoters using reduced representation bisulfite sequencing ( RRBS ) on additional normal CD8+ T cells and Dnmt3aΔ/Δ T cell lymphomas . This analysis confirmed hypomethylation of 90 gene promoters identified by WGBS in Dnmt3aΔ/Δ PTCL sample ( S3A Fig , S3B Fig and S7 Table ) . In addition , 31 out of 38 gene promoters were confirmed to be hypermethylated by RRBS ( S3A Fig , S3B Fig and S7 Table ) . The lesser extent to which hypomethylated promoters were confirmed by RRBS is not surprising in view of the inherent bias of the RRBS method which tends to underestimate the number of hypomethylated events in promoters with low CG content [18] . In fact , analysis of CpG content across DMRS revealed that hypomethylated promoters represent regions of lower CpG content when compared to hypermethylated promoters ( S3C Fig ) . Altogether , these data are in good agreement with results obtained from WGBS , which show large scale promoter hypomethylation in Dnmt3a-defficient PTCLs . To further validate data obtained by global methods on Dnmt3aΔ/Δ PTCL and to assess if methylation patterns are conserved in Dnmt3a+/- PTCL , we performed locus-specific methylation analysis using Combined Bisulfite Restriction Analysis ( COBRA ) for 11 selected genes in multiple independent tumor samples from Dnmt3aΔ/Δ and Dnmt3a+/- mice . Consistently with results obtained by WGBS , promoters of Coro2a , Cxcr5 , Ikzf3 , Il2Rβ , Jdp2 , Lpar5 , Oas3 , Ppil1 , Pvt1 , RacGAP1 , and Wnt8a were found to be hypermethylated in normal CD8+ T cells but hypomethylated in three independent Dnmt3aΔ/Δ PTCL samples ( Fig 6 ) . Furthermore , all 11 promoters were hypomethylated in Dnmt3a+/- PTCL samples , suggesting that loss of a single Dnmt3a allele is sufficient to induce patterns of promoter hypomethylation similar to those observed in Dnmt3aΔ/Δ PTCL samples ( Fig 6 ) . To determine if promoter hypomethylation observed in Dnmt3aΔ/Δ and Dnmt3a+/- PTCL occurs as a result of Dnmt3a inactivation in normal CD8+ T cells due to the lack of Dnmt3a’s de novo or maintenance activity , we analyzed promoter methylation in CD8+ T cells isolated from 8-week old Dnmt3aΔ/Δ and Dnmt3a+/- mice . For all 11 genes tested , promoters were hypermethylated in Dnmt3aΔ/Δ and Dnmt3a+/- CD8+ T cells to a similar degree as in Dnmt3a+/+ CD8+ T cells , suggesting that partial or complete inactivation of Dnmt3a does not affect the methylation status of these genes in normal CD8+ T cells during development ( Fig 6 ) . Altogether , our data demonstrate that changes in promoter methylation identified using WGBS likely represent tumor-specific events occurring in mouse PTCL driven by mono or bi-allelic loss of Dnmt3a . To better understand deregulated molecular events in PTCL induced by mono or bi-allelic loss of Dnmt3a we performed global gene expression profiling of Dnmt3aΔ/Δ and Dnmt3a+/- PTCLs using RNA-seq . Comparison of gene expression patterns obtained from lymphomas to patterns obtained from normal CD8+ T cells revealed that Dnmt3aΔ/Δ and Dnmt3a+/- PTCLs shared strikingly similar expression profiles . In total , 737 ( 69% ) overexpressed and 697 ( 79% ) underexpressed genes were conserved between Dnmt3aΔ/Δ and Dnmt3a+/- PTCLs relative to CD8+ T cell controls ( Fig 7A and 7B and S8 Table ) . We also identified 329 upregulated and 185 downregulated genes specific to Dnmt3aΔ/Δ PTCL , as well as 650 upregulated and 549 downregulated genes specific to Dnmt3a+/- PTCL ( Fig 7A and 7B and S8 Table ) . Altogether , these data suggest that molecular events driving T cell transformation in Dnmt3a+/- and Dnmt3aΔ/Δ mice are likely conserved . IPA of differentially expressed genes in PTCL identified 3 Inhibited Pathways common to both Dnmt3a+/- and Dnmt3aΔ/Δ PTCL ( Tec Kinase signaling , Type I Diabetes Mellitus Signaling , 4-1BB Signaling in T Lymphocytes ) and 1 commonly Activated Pathways ( Cyclins and Cell Cycle regulation ) in Dnmt3aΔ/Δ and Dnmt3a+/- lymphomas ( S4 Fig ) . The top 5 categories for “diseases and disorders” were identical for both Dnmt3aΔ/Δ and Dnmt3a+/- tumors ( Inflammatory response , Immunological disease , Connective tissue disorder , Inflammatory disease and Skeletal and muscular disorders ) , further illustrating the similarities between their molecular landscapes . Comparison of methylation and gene expression revealed that 71 genes ( 14% ) whose promoters were hypomethylated in PTCL were associated with overexpression ( Fig 7C and 7D , referred to herein as HOT genes–Hypomethylated and overexpressed in TCL ) . In contrast , we detected only three genes—CD226 , Fhit , and Emp1—whose hypermethylation correlated with underexpression , suggesting that most of the cancer-specific hypermethylation has little effect on gene expression and tumor progression ( Fig 7C ) . Further analysis revealed 54 genes ( 7% ) whose predicted enhancer regions were hypomethylated in PTCL and were also overexpressed , whereas only 3 genes with hypermethylated enhancers were downregulated ( Fig 7C and S5 Fig ) . Altogether , these data demonstrate that hypomethylation affects gene expression on a broader scale than hypermethylation in mouse Dnmt3aΔ/Δ PTCL and thus may functionally contribute to a disease development . To determine the extent of similarity between mouse and human disease on the molecular level , we compared gene expression signatures obtained from mouse PTCL to those derived from human PTCL . We utilized microarray data obtained on a set of five normal tonsil T cells and three human PTCL samples with predicted inactivating Dnmt3a mutations [19] . When we compared expression of genes deregulated in human PTCL to those genes deregulated in either Dnmt3a+/- PTCL , we identified 316 ( 28% ) overexpressed and 415 ( 36% ) underexpressed genes that were shared between human and Dnmt3a+/- PTCL ( Fig 8A and 8B and S9 Table ) . Fewer genes ( 252 overexpressed and 239 underexpressed ) were shared between human PTCL and Dnmt3aΔ/Δ PTCL , suggesting that the transcriptome of lymphomas induced by loss of a single Dnmt3a allele more so resembles human disease than those that arise do to full inactivation of Dnmt3a ( Fig 8A and 8B and S9 Table ) . The extent of overlap in up-and downregulated genes was significant for all comparisons ( P<0 . 01 ) , suggesting that similar molecular events may drive PTCL in both species . Because promoter hypomethylation resulted in upregulated gene expression in PTCL we next asked whether any of the HOT genes may have potential oncogenic functions in the development of T cell lymphomas and whether such genes are also hypomethylated and overexpressed in human PTCLs . One such candidate gene with oncogenic function in the T cell compartment—Jun Dimerization Protein 2 protein ( Jdp2 ) —is a component of the AP-1 transcription factor that was reported to negatively regulate Trp53 and promote the development of T cell leukemia in mice [20] . Consistently with global WGBS data , Jdp2 was hypomethylated in Dnmt3aΔ/Δ PTCLs as determined by COBRA ( Fig 9A ) . Likewise , with RNA-seq data , analysis of Jdp2 transcript levels by qRT-PCR confirmed overexpression of Jdp2 in Dnmt3a+/- and Dnmt3aΔ/Δ PTCL samples ( Fig 9B ) . Next , we analyzed the methylation status of the JDP2 promoter in human CD3 T cells and PTCL samples and found that like in Dnmt3a-deficient mouse PTCL , the JDP2 promoter is hypomethylated in human PTCL relative to controls ( Fig 9C ) . To determine whether overexpression of JDP2 occurs in human PTCL , we compared transcript levels in a set of 8 human PTCLs to normal CD3+ T cells . This analysis showed ~20–1 , 700-fold increase in JDP2 levels in human PTCL relative to normal T cells ( Fig 9D ) . These data demonstrate that JDP2 promoter hypomethylation correlates with its overexpression in human PTCL . To evaluate the role of Jdp2 in tumor maintenance we used an shRNA construct to knockdown the levels of Jdp2 in a Dnmt3a-deficient MYC-induced PTCL cell line . However , decrease in the levels of Jdp2 in this cell line did not affect cellular growth , suggesting Jdp2 is not required for tumor maintenance in such setting ( S6A and S6B Fig ) . Overall , our data indicate that methylation likely plays a role in the regulation of Jdp2 in mouse and human PTCL . Because Jdp2 was reported to negatively regulate p53 transcript levels we analyzed Trp53 expression by qRT-PCR . Despite a 10-70-fold increase in Jdp2 levels in Dnmt3a+/- and Dnmt3aΔ/Δ PTCL samples , we did not observe any effects on Trp53 transcript levels ( S7 Fig ) , suggesting that in this setting Jdp2 overexpression has no direct effect on p53 transcription . However , analysis of p53 protein levels showed downregulation of p53 in all Dnmt3a+/- tumors and 3/4 Dnmt3aΔ/Δ tumors , suggesting that Jdp2 may regulate p53 at the protein level or p53 downregulation in tumors occurs independently of Jdp2 overexpression ( Fig 10A ) . Gene Set Enrichment Analysis ( GSEA ) using RNA-seq data from normal Dnmt3a+/- and Dnmt3aΔ/Δ PTCL revealed significant downregulation of the p53 pathway genes in both settings ( Fig 10B and 10C and S10 Table ) . To determine when p53 is downregulated during lymphomagenesis , we next measured protein levels in spleens , lymph nodes and thymi isolated from 9 months old Dnmt3a+/+ and Dnmt3a+/- mice . At this age , Dnmt3a+/- mice did not show any sign of lymphomagenesis or cellular changes in the hematopoietic compartment ( S8 Fig ) . Interestingly , whereas p53 levels in spleens and lymph nodes were similar between Dnmt3a+/+ and Dnmt3a+/- settings , p53 was downregulated in thymocytes of Dnmt3a+/- mice ( Fig 10D ) . To determine whether downregulation of p53 occurs as a direct response to Dnmt3a monoallelic loss we analyzed p53 protein levels in splenocytes and thymocytes of 6 weeks old Dnmt3a+/+ and Dnmt3a+/- mice . This analysis revealed no apparent differences in p53 levels , suggesting that loss of one allele of Dnmt3a is insufficient to downregulate p53 at this time point ( Fig 10E ) . Because we did not succeed in establishing CD8+ lymphoma cell lines , we utilized previously generated MYC-induced Dnmt3a+/+ and Dnmt3a-/- T cell lymphoma cell lines [7] , along with MSCV-IRES-p53-GFP overexpressing both p53 and EGFP [21] , to evaluate the role of p53 in lymphomagenesis . Overexpression of p53 induced selection against EGFP-positive cells in both Dnmt3a+/+ and Dnmt3a-/- T cell lymphoma cell lines , suggesting that exogenous p53 inhibited cellular proliferation in vitro ( Fig 10F ) . This result suggests that low p53 levels are important for tumor maintenance in vitro and therefore downregulation of p53 in vivo is likely an important event in tumorigenesis . Altogether , these data suggest that downregulation of p53 is chronologically an intermediate event in lymphomagenesis and therefore likely a relevant in initiation/progression of lymphomagenesis and may be mediated by upregulation of Jdp2 .
In this study we show that loss of Dnmt3a in HSPCs in EμSRα-tTA;Teto-Cre;Dnmt3afl/fl; Rosa26LOXPEGFP/EGFP mice not only results in the development of CLL as we reported previously [16 , 17] but also in the development of peripheral T cell lymphomas in ~40% of Dnmt3aΔ/Δ mice either alone or in combination with CLL . We further show that not only complete inactivation but also a reduction in Dnmt3a levels results in the development of PTCL in 10% of Dnmt3a+/- mice . Lymphomas that develop in both Dnmt3aΔ/Δ and Dnmt3a+/- mice are exclusively CD8+CD4- mature T cell lymphomas . Importantly , Dnmt3a+/- PTCLs retain expression of the Dnmt3a wild-type allele . Thus , consistent with heterozygous mutations of Dnmt3a found in human T cell malignancies , Dnmt3a is a haploinsufficient tumor suppressor gene in the prevention of mouse mature CD8+CD4- T cell lymphomas . The growing number of various malignant phenotypes observed in the hematopoietic system with Dnmt3a-deficiency in mice raises questions about the nature of deregulated events induced by Dnmt3a inactivation . Because Dnmt3a is a methyltransferase , we were interested in finding whether genes deregulated in a methylation dependent manner could provide clues towards understanding the pathobiology of Dnmt3aΔ/Δ PTCLs . A combined analysis of global methylation and gene expression identified promoter hypomethylation as a major deregulated event in PTCL development in the absence of Dnmt3a with as many as 500 genes hypomethylated in lymphomas . Of these genes , expression of as many as 71 genes ( 14% ) was upregulated in tumors . Since Dnmt3a has now been shown to be a tumor suppressor in the prevention of a number of hematologic malignancies in a variety of biological settings [13–17] , it is therefore possible that promoter hypomethylation along with gene upregulation may be either a contributing factor or even the primary event driving the initiation/progression of tumor development . In such a scenario , proto-oncogenes are silenced in normal cells but are progressively hypomethylated and overexpressed resulting in cellular transformation . Analysis of data derived from Dnmt3aΔ/Δ lymphomas identified several putative drivers of T cell transformation whose promoters were hypomethylated and overexpressed in tumors ( HOT genes ) . One such HOT gene is the Interleukin-2 receptor Il2rb , a component of the IL-2 signaling pathway that is important for the growth of T lymphocytes . Inappropriate activation of this pathway may promote unchecked proliferation of T cells , thus contributing to tumorigenesis [22] . The HOT gene , Stat1 , participates in cytokine signaling in T cells and has been reported to be significantly overexpressed in human PTCL-NOS [23] . In a mouse model of v-abl-induced leukemia , Stat1-/- mice were partially protected from the development of leukemia , demonstrating that Stat1 possesses tumor-promoting activity [24] . Another HOT gene , Trim14 was demonstrated to have oncogenic function in tongue squamous cell carcinoma cell lines by activating the NF-κB pathway [25] . Whereas HOT genes represent good candidates to explain the tumor suppressor function of Dnmt3a , demonstration of a causative oncogenic role in initiation/progression of lymphomagenesis for any of these genes is challenging as it requires long-term in vivo experiments in mice . Thus , only future functional studies can address the importance of these genes in the pathogenesis of Dnmt3aΔ/Δ PTCLs . An additional HOT gene with predicted oncogenic activity is Jun Dimerization Protein 2 ( JDP2 ) , which we found to be hypomethylated and overexpressed not only in mouse PTCL but also in human PTCLs . Jdp2 protein is a component of the AP-1 transcription factor complex that represses transactivation mediated by the Jun family of proteins and it plays a role in AP-1-mediated responses in UV-induced apoptosis and cell differentiation [26] . Jdp2 was reported to promote liver transformation as JDP transgenic mice displayed potentiation of liver cancer , higher mortality and increased number and size of tumors [27] . Importantly , Jdp2 was identified in a screen for oncogenes able to collaborate with the loss of p27kip1 cyclin-dependent inhibitor to induce lymphomas [28] . Altogether these data along with our findings suggest that upregulation of Jdp2 induced by loss of Dnmt3a might be a contributing factor to the development of PTCL . Because Jdp2 was reported to negatively regulate Trp53 on a transcriptional level and promote the development of T cell leukemia in mice [20] we tested whether Trp53 levels are affected in Dnmt3aΔ/Δ PTCLs . Despite a 15–70 fold increase in Jdp2 levels we did not observe any changes in Trp53 transcript levels , suggesting that in this setting Jdp2 overexpression has little effect on p53 transcription . However , western blot revealed decrease in p53 protein in the majority of tumor samples , suggesting that Jdp2 may regulate p53 by other mechanisms or p53 downregulation occurs through an independent pathway not involving Jdp2 . Regardless of the mechanism by which p53 is downregulated in tumors , decreased p53 protein is likely contributing to CD8+ T cell transformation due to its strong tumor suppressor function in T cell compartment . For example , it was previously reported that Trp53-/- mice are highly susceptible to spontaneous tumor development , with the majority of mice developing immature CD4+CD8+ thymic lymphomas [29] . To the best of our knowledge , there are no studies in mice demonstrating the tumor suppressor function of p53 specifically in CD8+ T cell lymphomas . However , a loss of the region containing the p53 gene on chromosome 17 was observed in human primary cutaneous CD8+ cytotoxic T cell lymphoma , suggesting that low p53 levels could be involved in the pathogenesis of human CD8+ PTCL [30] . The fact that p53 was downregulated in thymocytes isolated from 9 month old , but not 6 week old , Dnmt3a+/- tumor-free mice indicates that p53 downregulation is chronologically an intermediate event in lymphomagenesis and this strongly suggest that this event is relevant in the initiation/progression of CD8+ PTCL . Consistent with downregulation of p53 protein levels , GSEA revealed suppression of p53 pathway genes in both Dnmt3a+/- and Dnmt3aΔ/Δ PTCL tumors , such as GADD45a , ZFP36L1 , and KLF4 . Studies using Gadd45a-/- mice found that ablation of Gadd45a in lymphoma-prone AKR mice decreased the latency and increased the incidence of T cell lymphomas , while deletion of Gadd45a on a p53 deficient background altered the tumor spectrum to heavily favor the development of T cell lymphomas [31] . Similarly , mice deficient for ZFP36L1 and ZFP36L2 displayed altered T cell development and readily succumbed to CD8+ T cell acute lymphoblastic leukemia [32] . KLF4 was identified to be mutated in pediatric T-ALL patients [33] and was shown to induced apoptosis in primary T-ALL cells [34] . These results suggest the downregulation of p53 target genes may contribute to T cell transformation in Dnmt3a-deficient mice . Altogether , these data indicate that downregulation of p53 is an important event during lymphomagenesis in Dnmt3a+/- and Dnmt3aΔ/Δ mice . Promoter hypomethylation and p53 downregulation may not be the only relevant events involved in the development of PTCL in Dnmt3a-defficient mice . An additional DNA methylation change that could contribute to the development of PTCL in Dnmt3aΔ/Δ mice is promoter hypermethylation , as it has been linked to the inactivation of tumor suppressor genes [35 , 36] . Although such changes would not be linked to Dnmt3a directly as inactivation of this enzyme is an initiating event of tumorigenesis , promoter hypermethylation mediated by other DNA methyltransferase and subsequent gene silencing could still drive tumorigenesis . In particular , in our previous studies we observed upregulation of Dnmt3b in Dnmt3a-defficient MYC-induced T cell lymphomas , suggesting that such an event may result in aberrant de novo methylation [7] . Surprisingly , despite identification of 50 genes whose promoters are hypermethylated in PTCL relative to CD8+ T cell controls , only Fhit , CD226 , and Emp1 were underexpressed . This raises a possibility that silencing of these genes contributes to PTCL development . Fhit is a predicted tumor suppressor gene that is frequently deleted in B cell malignancies , including Burkitt’s lymphoma and primary effusion lymphoma [37 , 38] . Furthermore , in vivo studied using Fhit+/− mice found that loss of a single allele of Fhit increased susceptible to carcinogen-induced tumor development in the esophagus and forestomach , further demonstrating the role of Fhit as a tumor suppressor [39] . CD226 is expressed on different hematopoietic cells including CD8+ T cells and contributes to their activation , expansion and differentiation but its deficiency in mice did not induce lymphomas , suggesting that this gene may not be a tumor suppressor gene [40] . Similarly , Emp1 overexpression correlated with enhanced cell proliferation and poor prognosis in B cell precursor ALL leukemia , suggesting an oncogenic function of this gene at least in some hematologic malignancies [41] . However , the possible role of Fhit , CD226 , and Emp1 as tumor suppressors in CD8+ Dnmt3aΔ/Δ PTCL is unclear . Thus , the role of hypermethylation and silencing in disease development and progression in mouse Dnmt3aΔ/Δ PTCL will require further investigation . One of the interesting findings presented here is the exclusive sensitivity of CD8+ T cell to transformation in Dnmt3a+/- and Dnmt3aΔ/Δ mice . This is not a consequence of impaired T cell development as we previously reported that loss of Dnmt3a does not affect the development of hematopoietic lineages [16] . Therefore , the reason as to why CD8+ but never CD4+ or CD4+CD8+ T cells become transformed in the absence of Dnmt3a is unclear at present . We speculate that the epigenome of CD8+ T cells is more dependent on Dnmt3a than other T cell types or CD8+ T cells may acquire genetic alterations that collaborate with epimutations more readily than other T cells . Of note , a differential sensitivity of T cell subtypes to transformation has been observed in response to infection by HTLV-1 , which predominantly transforms CD4+ T cells , while HTLV-2 mainly transforms CD8+ T cells [42 , 43] . Further studies will have to clarify whether the methylome of CD4 cells is more resistant to the lack of Dnmt3a as well as the nature of events responsible for CD8+ T cell transformation . Another interesting finding from our study is association of transcription factor ( TF ) binding motifs with regions hypomethylated and hypermethylated in Dnmt3a-defficient PTCL . Analysis of TF binding sites found motifs for three TFs—AML1 , NF-κB , and OCT1 –that were enriched in hypomethylated DMRS , suggesting their potential role in maintenance methylation mediated by Dnmt3a . In such a scenario , interaction of these factors with Dnmt3a may determine which specific loci Dnmt3a is targeted to . Interestingly , the p50 subunit of the NF-κB transcription factor was reported to interact with Dnmt3a in a glioblastoma cell line [44] . Similarly , we also observed association of binding sites for Ap-2rep , SOX5 , and myogenin with hypermethylated DMRS . Whether any of these transcription factors play role in aberrant promoter hypo- or hypermethylation remains to be determines . Altogether , our data identify Dnmt3a as a critical tumor suppressor gene in the prevention of B- and T cell malignancies and link decreased Dnmt3a levels to decrease in p53 , which may functionally contribute to the development of CD8+ PTCL . These data along with its documented role in prevention of myeloid malignancies defines Dnmt3a as a protector of the methylome critical for safeguarding normal hematopoiesis .
EμSRα-tTA and Dnmt3a2loxP/2loxP ( Dnmt3afl/fl ) mice were acquired from D . W . Felsher ( Stanford University ) and R . Jaenisch ( Whitehead University ) , respectively . ROSA26EGFP and Teto-Cre mice came from the Jackson Laboratories . All transgenic mice were generated using standard crosses . All mice used in these studies were of the FVB/N background and were generated using standard genetic crosses . To obtain mice with a germline transmission of the Dnmt3a- allele , we crossed EμSRα-tTA;Teto-Cre;Dnmt3afl/fl mice with FVB mice , taking advantage of our observation that the EμSRα-tTA transgene is expressed in germ cells . To generate Dnmt3a+/- we subsequently bread out transgenes by crossing obtained mice with FVB mice . PCR-based genotyping of genomic DNA isolated from the tails was used to confirm genotypes . Dnmt3a+/- mice were harvested at the experimental end point of 16 months . Human peripheral T cell lymphoma tissue samples were acquired from Cooperative Human Tissue Network , a National Cancer Institute supported resource ( www . chtn . org ) . All analysis was performed at the Flow Cytometry Facility at the University of Nebraska Medical Center . Single cell suspensions were generated from mouse organs and labeled with fluorescently conjugated antibodies ( eBioscience ) . Data was collected using the LSR II ( BD Biosciences ) and analyzed using BD FACSDiva software ( BD Biosciences ) . Immunopheotypic criteria for normal and malignant cellular populations analyzed by flow cytometry are as follows: Cytotoxic T cells ( EGFP-negative CD3+CD8+ without population expansion ) , CD8+ peripheral T cell lymphomas ( EGFP+CD3+CD8+ with population expansion ) , B-1a cells ( EGFP-negative CD19+B220+CD5+ without population expansion ) , chronic lymphocytic leukemia ( EGFP+CD19+B220+CD5+ with population expansion ) . Clonality was assessed using the mouse Vβ TCR Screening Panel ( BD bioscience ) which uses FITC-conjugated monoclonal antibodies to recognize mouse Vβ 2 , 3 , 4 , 5 . 1 and 5 . 2 , 6 , 7 , 8 . 1 and 8 . 2 , 8 . 3 , 9 , 10b , 11 , 12 , 13 , 14 , and 17a T cell receptors . Western blots were performed as previously described [6] with use of the following antibodies: Dnmt3a ( H-295 , Santa Cruz ) , γ-Tubulin ( H-183 , Santa Cruz ) , p53 ( SC-6243 , Santa Cruz ) , HDAC1 ( ab7028 , Abcam ) , and HSC-70 ( SC-7298 , Santa Cruz ) . COBRA analysis was carried out as described previously [5 , 6] . Mouse and human bisulfite specific primers are shown in S11 Table . The mouse mm9 MotifMap database containing 2 , 237 , 515 transcription factor motifs [52 , 53] ( http://motifmap . ics . uci . edu/ ) was used to align transcription factors motifs present within promoters ( -1500 to +500 TSS ) that contained a significant hypo- or hypermethylated DMR using the Bedtools intersect routine [51] . For a control comparison 12 random sets of promoters ( 500 promoters each were used for the hypometylated controls and 50 for the hypermethylated ) were selected from the UCSC known mm9 genes database using the Excel RANDBETWEEN function and sorting from highest to lowest number . The abundance of each transcription factor within the DMR promoters and random promoters were counted using the Excel COUNTIF function . P-values were calculated used a Wilcoxon sign rank test . Only P<0 . 05 were considered significant . Splenic CD3+CD8+ T cells were isolated by FACS sorting from two Dnmt3a Δ/Δ mice with PTCL . Age-matched control T cells were FACS-sorted from spleens of FVB/N mice ( n = 2 ) . Genomic DNA was isolated using standard protocols . The RRBS libraries were prepared and sequenced at the Medical Genome Facility at the Mayo Clinic and ran on an Illumina HiSeq2500 sequencer . The Streamlined Analysis and Annotation Pipeline for RRBS data ( SAAP-RRBS ) was specifically designed to analyze RRBS data [54] . This software was used to align and determine the methylation status of CpGs associated with this type of restriction digest high throughput method . Sequences were initially aligned with genome mm9 then converted to mm10 using the UCSC Genome Browser Batch Coordinate Conversion ( liftOver ) utility . The methylation heat map was generated by taking the averages for all differentially methylated CpGs for a promoter ( -1500 to +500 base pairs relative to the transcription start site ) . Promoters were only considered to be differentially methylated if one or more CpG sites showed a 30% change in methylation . RRBS data is available for download through the NCBI Gene Expression Omnibus ( GSE78146 ) . RNA was isolated as previously described [6] from FACS sorted CD8+ T cells obtained from spleens of control FVB/N ( CD8+CD3+ ) and Dnmt3aΔ/Δ terminally ill PTCL mice ( EGFP+CD8+CD3+ ) . Library generation was performed using the TruSeq mRNA kit . The resulting libraries were sequenced on the Illumina HiSeq 2000 platform using paired-end 100bp runs ( SeqMatic , Fremont , CA ) . The resulting sequencing data was first aligned using TopHat and mapped to the Mus musculus UCSC mm10 reference genome using the Bowtie2 aligner [55] . Cufflinks 2 was used to estimate FPKM of known transcripts , perform de novo assembly of novel transcripts , and calculate differential expression [56] . For differentially expressed genes , we considered those genes with a fold change ≥ 2 and a p-value < 0 . 05 to be significant . RNA-seq data is available for download through the NCBI Gene Expression Omnibus ( GSE78146 ) . qRT-PCR was performed as previously described [6] . Mouse real time primer sequences used in experiments presented are shown in S11 Table . Data was compared in Microsoft Excel using Student’s t-test ( p<0 . 05 considered significant ) or other appropriate statistical comparison listed elsewhere in materials and methods . H&E staining was performed using standard protocols by the University of Nebraska Medical Center Tissue Science Facility . Microarray data was downloaded from the NCBI Gene Expression Omnibus . We compared gene expression of 5 normal Tonsil T cells samples ( GSE65135 ) to 3 PTCL samples in which DNMT3A was reported to be mutated ( GSE58445 ) [19] . Datasets were generated with Affymetrix U133 plus 2 arrays and analyzed using Affymetrix Expression Console and Transcriptome Analysis Console ( v3 . 0 ) . Data was analyzed using a one-way between-subject ANOVA to generate p-values and identify differentially expressed genes ( p-value < 0 . 05 and fold change >1 . 5 ) . Genes differentially expressed in human PTCL were compared to those genes identified as being over- or underexpressed in mouse Dnmt3a+/- or Dnmt3aΔ/Δ relative to CD8+ T cell controls ( RNAseq , Fold change >2 , p<0 . 05 ) . All differentially expressed genes ( p<0 . 05 , fold change >2 , analyzed by Cufflinks V2 . 0 ) for Dnmt3a+/- PTCL relative to wild-type CD8+ T cells and Dnmt3aΔ/Δ PTCL relative to wild-type CD8+ T cells were imported into IPA software . Core analysis were performed to identify top ranking pathways and categories for differentially expressed genes . Activated and inhibited pathways ( Z-score>1 . 5 , p<0 . 05 ) common to both Dnmt3a+/- and Dnmt3aΔ/Δ PTCL are shown in S4 Fig . In Fig 3E , IPA core analysis was performed on highly expressed genes ( FPKM ≥ 10 ) in wild-type CD8+ T cells and the top subcategories obtained in Physiological System , Development and Functions were displayed ( P<0 . 05 , for all subcategories ) . TopHat/Cufflinks/Cuffdiff RNA-seq gene-level read_group_tracking file was converted to GCT expression dataset and matching phenotype model using the Read_group_trackingToGct module ( http://www . broadinstitute . org/cancer/software/genepattern/modules/docs/Read_group_trackingToGct/1 ) . Gene Set Enrichment Analysis ( GSEA , http://www . broadinstitute . org/gsea/index . jsp ) was used to test the relationship between RNA-Seq mRNA expression and the Hallmark Signature gene sets ( http://software . broadinstitute . org/gsea/msigdb/genesets . jsp ? collection=H ) . From this we concentrated our effort on the Hallmark p53 pathway gene set ( http://software . broadinstitute . org/gsea/msigdb/cards/HALLMARK_P53_PATHWAY . html ) that consisting of 180+ genes involved in p53 pathway and network . HuSH 29-mer shRNA scrambled and shRNA Jdp2 in the retroviral vector pRFP-C-RS were purchased from Origene . Infections were performed as previously described [6] , using a Dnmt3a-deficient MYC-induced CD4+ T cell lymphoma line [7] . Doubling time was calculated from each measured time point relative to the starting concentration of cells at Day 0 . Each time point calculation of doubling time was considered a replicate measure and was averaged other measurements per experimental condition . The pMSCV-IRES-EGFP ( “Vector” ) and pMSCV-bla-p53 ( WT ) -IRES-EGFP ( “p53” ) , a kind gift from Dr . Ute Moll [21] , were transfected into the PhoenixEco packaging cells and retrovirus was produced . Transductions were performed as previously described [6] , using wild-type Dnmt3a and Dnmt3a-deficient MYC-induced CD4+ T cell lymphoma lines [7] . The maximum percent of EGFP expressing cells per cell population was observed at 48 hours post-transduction and all subsequent EGFP data points were normalized to this time point . EGFP was measured periodically by flow cytometry on the LSRII available at the UNMC flow cytometry core facility . Cells were cultured in RPMI-1640 media supplemented with 10% FBS , 1% pen-strep-amphotericin B , 0 . 5% β-mercaptoethanol and split ( 1:3 ) to ( 1:5 ) every 3 days . This study was performed in accordance with the guidelines established by the Guide for the Care and Use of Laboratory Animals at the National Institutes of Health . All experiments involving mice were approved by the IACUC ( Protocol number: 08-083-10-FC ) at the University of Nebraska Medical Center .
|
Global deregulation of cytosine methylation is an epigenetic hallmark of hematologic malignancies that may promote tumorigenesis by silencing tumor suppressor genes , upregulating oncogenes , and inducing genomic instability . DNA methyltransferase 3a ( DNMT3A ) is one of the three catalytically active enzymes responsible for cytosine methylation and one of the most frequently mutated genes in myeloid and T cell malignancies . Its role in malignant hematopoiesis , however , remains poorly understood . Here we show that Dnmt3a is a haploinsufficient tumor suppressor in the prevention of peripheral T cell lymphomas in mice . Our molecular studies identified a large number of genes deregulated in the absence of Dnmt3a that may be putative drivers of oncogenesis . We also show that downregulation of the tumor suppressor p53 is an important event in the development of mouse T cell lymphomas . Thus , this study establishes a novel mouse model to elucidate how epigenetic deregulation of transcription contributes to the pathogenesis of T cell lymphomas .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
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"blood",
"cells",
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"and",
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"sciences",
"immune",
"cells",
"immune",
"physiology",
"spleen",
"immunology",
"cancers",
"and",
"neoplasms",
"oncology",
"hematologic",
"cancers",
"and",
"related",
"disorders",
"animal",
"models",
"model",
"organisms",
"epigenetics",
"dna",
"cytotoxic",
"t",
"cells",
"lymphomas",
"mammalian",
"genomics",
"dna",
"methylation",
"chromatin",
"research",
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"analysis",
"methods",
"white",
"blood",
"cells",
"chromosome",
"biology",
"animal",
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"gene",
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"t",
"cells",
"chromatin",
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"hematology",
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"cellular",
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"genomics"
] |
2016
|
Dnmt3a Is a Haploinsufficient Tumor Suppressor in CD8+ Peripheral T Cell Lymphoma
|
Giardia intestinalis is a major cause of diarrheal disease worldwide and two major Giardia genotypes , assemblages A and B , infect humans . The genome of assemblage A parasite WB was recently sequenced , and the structurally compact 11 . 7 Mbp genome contains simplified basic cellular machineries and metabolism . We here performed 454 sequencing to 16× coverage of the assemblage B isolate GS , the only Giardia isolate successfully used to experimentally infect animals and humans . The two genomes show 77% nucleotide and 78% amino-acid identity in protein coding regions . Comparative analysis identified 28 unique GS and 3 unique WB protein coding genes , and the variable surface protein ( VSP ) repertoires of the two isolates are completely different . The promoters of several enzymes involved in the synthesis of the cyst-wall lack binding sites for encystation-specific transcription factors in GS . Several synteny-breaks were detected and verified . The tetraploid GS genome shows higher levels of overall allelic sequence polymorphism ( 0 . 5 versus <0 . 01% in WB ) . The genomic differences between WB and GS may explain some of the observed biological and clinical differences between the two isolates , and it suggests that assemblage A and B Giardia can be two different species .
Giardia intestinalis ( syn G . duodenalis and G . lamblia ) is a major contributor to the enormous burden of diarrheal diseases , as causes of morbidity and mortality worldwide . The human prevalence rates range from 2–7% in developed countries to 20–30% in most developing countries [1] . Infection of young farm animals is a major economical problem and G . intestinalis is a potentially zoonotic organism [2] . Nonetheless , the mechanism of giardial disease is poorly understood [3] . It is not invasive and secretes no known toxin and there is no general consensus on the cause of symptoms . However , recent data suggest that there is induction of apoptosis in intestinal epithelial cells during acute human giardiasis and that diarrhea is partly a result of increased intestinal permeability due to the apoptosis [4] . Chronic infections are common and in a hyperendemic area , 98% of drug-cured children are reinfected within six months [5] . On the other hand , about half of the infections are asymptomatic and frequently the infection spontaneously resolves [3] . Thus , both the duration and symptoms of giardiasis are highly variable . Currently , there are seven defined genotypes ( assemblages ) of G . intestinalis with only assemblages A and B being known to infect humans . Although assemblage B is the most prevalent worldwide [2] , it is inconclusive whether the various genotypes are associated with different disease outcomes [6] , [7] , [8] . Difficulties with growth of Giardia in vitro and the tetraploid genome [9] divided between two nuclei , have precluded the efficient use of biochemical , genetic and molecular biology approaches to experimentally correlate genotypic differences with virulence . Only two Giardia isolates ( WB-assemblage A and GS-assemblage B ) have been successfully cultured and studied in any detail at the molecular level in vitro [1] . Early studies suggested large sequence differences between the genes of WB and GS since the nucleotide sequence in the coding region of the triose phosphate isomerase ( tpi ) gene showed only 81% identity between the WB and GS isolates and the non-coding regions were too different to be aligned [10] . Genetic differences between WB and GS have been confirmed in several other genes in more recent studies [11] , [12] , [13] . Several biological differences have also been identified between the WB and the GS isolates [14] and GS is currently the only Giardia isolate that has been used successfully in experimental infections in humans [15] and adult mice [16] . It has even been suggested that assemblage A and B parasites should be considered as two different Giardia species [17] . Genome sequencing and comparative genomics can be used to identify genetic characteristics that are either unique or shared by all G . intestinalis assemblages and this approach has been used successfully for other protozoan parasites ( e . g . Plasmodium and Trypanosomatids [18] , [19] ) . The genome sequence of Giardia WB was recently published and it was shown to have a highly streamlined genome [20] . In order to understand in greater details the differences between Giardia assemblage A and B we decided to produce a draft genome sequence of the GS isolate . We chose to use the 454 sequencing technology ( Roche ) to characterize the genome of GS , due to the rapidness of data generation and a read length long enough to enable de novo assembly of sequence reads . Since its launch in 2005 , the 454 technology has [21] been successfully used in a number of genome sequencing projects , most notably in the resequencing of the human genome [22] , the sequencing of a Neanderthal mitochondrial genome [23] and several bacterial species [24] . However , to our knowledge this is the first study to use the 454 technology to sequence the genome of a protozoan parasite . We have produced a draft genome sequence of the assemblage B isolate GS , using a combination of de novo sequencing and resequencing , and compared it to the genome of WB . Our findings show only a few assemblage-specific genes , except for the Variable Surface Protein ( VSP ) gene family where the repertoires of the two isolates are completely different . This study has improved the annotation of the WB Giardia genome and provided a framework for further experimental investigations of clinical and biological differences between assemblage A and B Giardia isolates .
The published G . intestinalis WB genome is 11 . 7 Mbp in size , distributed in 306 contigs on 92 scaffolds [20] . Originally , 6470 open reading frames ( ORFs ) were identified in the WB genome but only 4 , 787 were shown to be associated with transcription [20] . This is slightly less than the number of protein coding sequences found in the yeast Saccharomyces cerevisiae [25] but more than the number of coding sequences found in the intestinal , eukaryotic microbial pathogens Encephalitozoon cuniculi and Cryptosporidium parvum [26] , [27] . Three rounds of sequencing of the GS genome using the 454 FLX sequencer generated 808 , 181 high-quality reads with an average length of 227 bp ( 182 Mbp; 16× coverage ) . The final assembled sequence was distributed in 2 , 931 contigs with an average length of 3 , 753 bp ( Table S1 ) . Automated ORF prediction identified 6 , 768 ORFs and manual curation of the data ( see Methods ) resulted in a final set of 4 , 470 intact ( mean length 1 , 836 bp ) and 221 interrupted protein coding genes . The mean intergenic distance was 130 bp . The number of protein coding genes is similar to what was observed in the WB genome and the intergenic distance is smaller due to annotation of an additional 754 open reading frames that were never annotated in the pioneering genome project . A small number of genes ( 64 ) were fragmented and in these cases specific primers were designed and the genes were amplified by PCR and sequenced . Fifty-eight of the fragmented genes were found to be disrupted by frame-shifts caused by single-base indels due to 454 sequencing errors and only 6 genes had actual frame-shifts ( Table S2 ) . Approximately 75% of the assembly is annotated as coding . However , the coding content is 90% in contigs with two or more genes annotated . The two genomes showed 77%±5% nucleotide and 78%±14% amino-acid identity in protein coding regions . The average GC-content was 46 . 5% in coding regions and 37 . 8% in intergenic regions . The codon usage was similar in the two isolates , but the codons in the GS ORFs have a higher level of A/T in the third positions compared to WB . We identified 124 small RNA genes in the GS genome , including tRNAs ( Table S3 and Text S1 ) . The GS isolate contains 69 tRNAs of the same number of isotypes ( 45 ) as the WB genome ( Text S1 ) . Most tRNAs are encoded by one gene , but the tRNAGln ( TGG ) gene , containing an intron , was found in 7 copies plus one copy without the intron . It has been suggested that the WB and GS isolates belong to different Giardia species [17] so we decided to study the protein coding capacities of the two isolates in order to address this issue . Comparisons between the sets of predicted protein coding genes showed that 673 WB genes lacked significant sequence similarity to any of the predicted GS genes . Searches at the nucleotide level identified conserved ORFs in GS corresponding to orthologs of 80 of the WB protein coding genes and these were therefore subsequently added to the GS annotation . Five WB protein coding genes showed sequence similarity to chromosomal GS regions without any corresponding full-length ORFs , which indicated the presence of pseudogenes in GS . Of the remaining 588 genes that lacked GS orthologs , 585 coded for proteins shorter than 200 amino-acids ( aa ) and lacked similarity to sequences present in the public databases . This suggests that these predicted proteins are most likely erroneous annotations , rather than unique WB proteins . Thus , surprisingly , only three WB genes coding for proteins longer than 200 aa are completely absent from the GS genome , all of which code for hypothetical proteins ( Table 1 ) . However , it should be noted that for this analysis members of large Giardia-specific gene families , such as the VSPs , the ankyrin-repeat domain containing Protein 21 . 1 , High Cysteine Membrane Proteins ( HCMPs ) and NIMA-Related Kinases ( NEKs ) were excluded . For 754 of the predicted GS genes no annotated orthologs could be detected in the WB genome ( www . giardiadb . org ) . However , searches against the WB scaffolds revealed that these have conserved ORFs , which were not annotated as coding sequences in the WB genome project . An additional four genes corresponded to WB chromosomal regions with putative pseudogenes . The remaining 59 protein coding genes did not show any significant sequence similarity to the WB genome , of these 23 code for proteins longer than 200 aa and are likely coding sequences ( Table 1 ) . An additional 4 sequences code for shorter proteins , but are located in proximity to longer unique genes , and a single gene shorter than 200 aa encodes a conserved hypothetical protein . We kept these and annotated them as functional proteins ( Table 1 ) . The remaining 31 short proteins without sequence similarity in the WB genome were deemed unlikely to represent functional genes and were therefore not considered further . Thus , 28 protein-coding genes were found to be unique for the GS isolate . Although the majority of these genes code for hypothetical proteins , eight showed sequence similarity to genes present in the public databases . Four of these appear to be of bacterial origin , since the best BLAST matches were to bacterial sequences , and they branched with bacterial genes in phylogenetic trees ( Table 1; Fig . 1B; Fig . S1A , B , C ) . Another four showed similarity to a gene family associated with rolling circle replication and mostly found in viruses ( Table 1; Fig . S1D ) . Homologs to these proteins of putative viral origin have previously been shown to be present in a G . intestinalis isolate BRIS/92/HEPU/1541 [28] , but they are not present in the WB genome ( Table 1 ) . Interestingly , three additional gene families were detected among the unique genes coding for hypothetical proteins , resulting in a total of 19 genes and gene families that were only present in the GS/M-H7 genome ( Table 1 ) . To get a more detailed view of the process of gene acquisition in Giardia genomes , we examined one short contig in more detail ( contig 2921 ) . This contig contained a single unique gene of bacterial origin ( GL50581_3321 , Fig . 1A ) . The 3′ end of contig 2921 terminates in a truncated Copine-1 ( CPNE1 ) gene , which suggested that the bacterial fragment has been inserted in the CPNE1 genomic environment ( Fig . 1A ) . PCR and subsequent sequencing demonstrated that the rest of the truncated CPNE1 gene ( GL50581_2716 ) is located in the end of contig 2545 , which is syntenic with scaffold CH991778 in the WB genome . Thus , contig 2921 is linked to chromosomal regions showing strong similarity to the WB genome . Searches using the 5′ end of contig 2921 revealed strong similarities to multiple parts of the assembly ( Fig . 1A ) , suggesting that the shortness of the contig is due to assembly errors caused by repetitive sequences . Searches against protein databases using the sequence outside the annotated conserved hypothetical protein revealed sequence similarity to two bacterial genes coding for carboxynorspermidine decarboxylase and signal recognition particle-docking protein ( FtsY ) , respectively ( Fig . 1A ) . However , there are three frame-shift mutations in the carboxynorspermidine decarboxylase and the ftsY genes . Inspection of the assembled reads did not reveal any sequence ambiguities that could explain the apparent frame-shifts in these two genes; resequencing using the Sanger method confirmed this observation . In addition , the 3′ part of the ftsY gene is missing from the GS genome , indicating that it is a truncated pseudogene . Phylogenetic analysis of the intact gene ( GL50581_3321 ) within contig 2921 showed it nested within mostly proteobacterial sequences , most likely indicating a recent bacterial origin ( Fig . 1B ) . Similarly , phylogenetic analyses of the reconstructed putative protein sequences for the two pseudogenes show that the Giardia sequences group with Porphyromonas gingivalis sequences nested within members of the bacterial Bacteroidetes group ( Fig . 1C , D ) . Indeed , these two genes are found in the same gene order as in the Porphyromonas genomes . This strongly suggests a recent transfer to Giardia of these two genes in a single event from a close relative of Porphyromonas , a genus of bacteria frequently found associated with humans [29] . The relatively long branches leading to the G . intestinalis sequences suggest that the pseudogenes have accumulated several mutations in addition to the frameshifts observed ( Fig . 1C , D ) . These observations show that contig 2921 of the G . intestinalis GS genome encodes three genes of recent bacterial origin , two of which likely became pseudogenes after the introduction into the genome . Inspection of the assembly of contig 2921 showed that the average coverage was about half of the expected 16 times coverage . This could be due to random variations in genome coverage but it can also indicate that this region of the genome may not be present in all four copies of the genome in the cell . To test the latter hypothesis we designed PCR primers covering the part of contig 2921 harboring bacterial genes ( Fig . 1A ) . Quantitative PCR analyses showed an approximate copy number of 0 . 3 for this part of the genome , compared to the single-copy gene beta-giardin ( data not shown ) . This is in agreement with presence of the bacterial gene and pseudogenes in only 1 or 2 of the 4 chromosomal copies in the cell , which provide additional support for a recent introduction into the GS genome . Giardia is a tetraploid organism with two diploid nuclei [9] . Sequence divergence is expected to accumulate in polyploid organisms in the absence of genetic exchange . For example , extensive sequence divergence has been observed between the two former haplotypes in asexual bdelloid rotifers [30] . However , a surprisingly low level of allelic sequence divergence , less than 0 . 01% , was reported in the WB genome [20] . PCR analyses of genes from patient samples containing assemblage B isolates often show a high degree of sequence divergence in certain positions [2] , [31] . These observations could be caused by frequently mixed infections of different assemblage B lineages , or by a higher level of allelic sequence divergence . There are two different haplotypes of tpi coding for triose phosphate isomerase in the GS isolate in the public databases . A comparison of these sequences with the sequence reads in the genome show the presence of two distinct classes of sequence reads ( Fig . 2A ) , which strongly suggest allelic sequence variation in the tpi gene . This allelic sequence divergence was also verified using PCR amplification and Sanger sequencing of individual clones ( data not shown ) . A genome-wide analysis of the presence of allelic sequence variation was performed on 8 , 618 , 167 positions with 10× coverage or more . A position was defined to contain an allelic sequence variation if two or more independent reads contained an alternative base compared to the consensus . The reads were classified as independent if they started at different positions . Insertion and deletion variation were not included because of the relatively high frequency of such sequencing errors using the 454 technology . Using these criteria , we detected 45 , 153 positions with two different bases , of which 22 , 655 were in coding regions and 22 , 498 were in non-coding regions . A strong bias towards transitions was observed ( Fig . 2B ) . The average coverage for all positions with more than 10 independent reads and positions identified as variable are 16 . 3 and 18 . 8 , respectively , which shows that the variation was not caused by the collapse of repeated genes in the assembly . Allowing for a third variant with two or more independent reads detected 106 positions with three different bases . The average coverage for these positions is slightly higher ( 23 . 9 ) , which suggests that a fraction of these indeed could represent misassembled duplicated regions . No positions with all four nucleotides represented were found . Thus , the overall level of allelic sequence divergence was 0 . 53% in the GS genome , compared to less than 0 . 01% in the WB genome [20] . As expected , the allelic sequence divergence is higher in non-coding than in coding regions , 1 . 25% and 0 . 3% , respectively . This high frequency of allelic sequence variations suggests that the “double-peaks” observed in genotyping studies [31] could be explained by allelic sequence variation within a single infecting Giardia . The presence of a large number of positions with allelic sequence variation suggests that gene sequences may differ between the two nuclei in the cell . However , analysis of the ratio between the major and minor nucleotide in the variable positions indicate that ratios that deviate from 1∶1 are common ( Fig . 2C ) , which indicates that the two chromosomes within a single nucleus may differ . Interestingly , the allelic sequence variations were not homogenously distributed among the genes ( Fig . 2D ) . Analyses of the distribution of the allelic variations along the contigs show large regions with very low sequence divergence with high divergence regions scattered within them ( Fig . 2E–H ) . This indicates that a large part of the GS genome is identical between the four copies distributed in the two nuclei , while some parts remain divergent . Thirty-eight percent of the polymorphisms change the protein sequence and these are distributed in 1 , 962 genes , suggesting that GS has an extended proteome of almost 2000 proteins with a slightly altered primary structure . This can be important for understanding the biology and virulence of the parasite . Several breaks of genome synteny ( 41 ) were identified when the GS contigs were aligned with the WB genome scaffolds ( Table S4 ) . Twenty-four of these were verified using PCR and sequencing and 21 of the breaks were between regions in the same WB-scaffold , with 3 occurring between scaffolds . The most common class among the synteny breaks ( 16 cases ) was insertions or deletions of a region in WB or GS . One example of a synteny break in this class is shown in Fig . 3 where a 15 kb region containing 7 genes , among them one VSP , two NEKs and one HCMP are missing in GS . Indeed , VSPs , NEKs , HCMPs and also protein 21 . 1 were often found associated with insertions or deletions ( 12 cases ) . Additionally , VSP fragments were detected at contig edges in GS where the syntenic region in WB is devoid of such proteins . These two observations suggest that VSPs are not confined to certain genomic locations . Another interesting observation is that regions missing from GS but present in WB had a higher GC-content than the average for the genome ( Fig . S2 ) . The GC%-profiles of WB scaffolds reveal that the genomic regions where VSPs localize have a higher GC content than the surrounding genome and that these high GC% islands may be important for VSP regulation . Intra-scaffold rearrangements were the second most prominent category of synteny breaks with 8 detected events . Of these , we detected a recombination event between two dipeptidyl-peptidase I precursors ( GL50803_28651 and GL50803_22553 ) that creates “hybrid proteases” . However , we could also detect non-recombinant variants by PCR analyses indicating that there are two different variants in the GS genome; one similar to WB and one due to recombination between the two protease genes . A fraction of putative recombination events could not be confirmed by PCR amplification and Sanger sequencing , indicating that these genes were incorrectly assembled . Mis-assembly occurred between genes in gene families containing highly conserved nucleotide stretches such as histones , protein disulfide isomerases , peroxiredoxins and acyl-CoA synthetases . This likely reflects a limitation due to the relatively short read-length obtained by 454 FLX sequencing ( 250 bp ) compared to traditional Sanger sequencing . The draft GS genome sequence is highly fragmented with 2 , 931 contigs of an average length of 3 , 753 bp . In order to see if it is feasible to generate larger contigs we designed primers against truncated genes and contig ends that were predicted to be close according to the synteny analysis . Twelve super-contigs of total size 1 , 363 , 697 bp , ( corresponding to around 10% of the total genome ) were produced after running 28 PCR reactions followed by Sanger sequencing of the products ( Table S5 ) . This shows that synteny analysis is useful for the generation of super-contigs and importantly that it is technically feasible to close the sequence gaps . Promoters in Giardia are short ( around 50 bp ) and the main feature is an initiator-like AT-rich sequence around the ATG start codon , which is enough to drive transcription [32] . AT-rich stretches around the ATG start codon could be found in most GS genes ( data not shown ) , but apart from these , there is very little intergenic sequence conservation , consistent with earlier observations of a few GS genes . Encystation-specific promoters in WB are also short , with 65 bp found to be sufficient for a developmentally regulated promoter [33] . An alignment of the promoters ( −100 to +3 ) from the three major cyst-wall proteins CWP 1–3 from WB with the orthologs from GS showed a high degree of conservation in the 65 bp directly upstream of the start codon ( see alignment of CWP 1 and 2 , Fig . 4 ) . The transcription factor Myb2 has been shown to bind to the CWP promoters and its own promoter [34] . The GS Myb2 protein is well conserved ( 77% amino acid identity ) and so is the 65 bp directly upstream of the ATG start-codon , including the Myb2 binding site ( Fig . 4 ) . This suggests that the cyst-wall proteins and Myb2 protein are regulated in the same way during encystation in the two isolates . The key-regulatory enzyme in WB , glucosamine-6 phosphate isomerase , has a promoter that is similar to the cyst-wall promoters [33] . However , the promoter of this enzyme in GS is not similar to the promoters of the cyst wall proteins ( Fig . 4 ) and , most importantly , it lacks a typical Myb2 binding sequence . The same was found to be true for the last enzyme in the pathway , UDP-N-acetylglucosamine 4′ epimerase [35] ( Fig . 4 ) . The GS isolate is known for its poor encysting ability in vitro [36] and may suggest that the regulation of cyst-wall sugar synthesis during early encystation is different in GS . Four mRNA introns were identified in the WB genome after combining cDNA and genome sequences [20] . The introns are variable in length ( 32 to 220 bp ) with conserved 5′ and 3′ motifs . Introns of similar sizes were found in the corresponding genes in GS and the 5′ ( consensus G/C TAT GT ) and 3′ motifs ( consensus A/C CT A/G AC A/C CACAG ) were conserved , whereas the sequences in the rest of the introns were highly diverged . Interestingly , we found three unique contigs containing the intron corresponding to the intron of ORF 35332 in WB . The longest contig ( c2890 ) has a consensus 3′motif , while the two other contigs ( c299 and c305 ) have an A to G mutation in the branchpoint A that is crucial for splicing . Thus , these are three allelic variants of the intron and potentially pseudo-introns . Putative spliceosomal RNAs were recently predicted in the WB genome [37] . Only the U4 and U5 RNAs showed high sequence identity ( 92 and 85% , respectively ) with GS , whereas the U1 , U2 and U6 RNAs showed less than 80% identity ( Table S3 ) . This is surprising , considering that all other verified small RNAs showed a high level of sequence identity and suggesting that some of the predicted U RNAs are not true spliceosomal RNAs or that there are less constrains in the nucleotide sequence of the giardial spliceosomal RNAs . Earlier studies using Southern blot analyses suggested that the GS genome contains approximately 150 VSP genes [38] . A search of all the reads from the GS data set using TBLASTN with the conserved C-terminal VSP region gave 3 , 183 hits with more than 80% identity over 30 aa . With a sequence coverage of 16× we could estimate that 200 VSP genes are present in the GS genome . In our study only 16 complete VSP genes were obtained and most of them were short . The low number of identified full-length VSP genes is most likely due to assembly problems caused by the repetitive nature of these genes . The higher levels of allelic sequence divergence in GS most likely also caused problems in the assembly of the VSP genes . We used the 16 ORFs coding for complete GS VSP genes and 188 VSP genes in WB to search for VSP genes in the GS genome . In this search , 15 , 249 reads over 100 nt were identified , corresponding to 1 . 9% of all reads . None of these GS VSPs showed a high degree of similarity to VSPs from WB ( 30–70% , average 55% ) , except in the conserved CXXC motifs and the C-terminal region . This is in agreement with earlier studies that have suggested that the two isolates have unique VSP repertoires [38] , [39] . It is clear that more data using other sequencing platforms is needed to get a view of the complete VSP repertoire in GS . The largest gene family in the WB genome was the kinases with 276 putative members [20] . No histidine- or tyrosine-specific kinases were identified and only four giardial kinases contain membrane-spanning regions . The core kinome in Giardia is the smallest among eukaryotes thus far with more than 70% of the kinases in WB belonging to the NEK kinase group [20] . We found that certain NEK kinases were highly conserved between the two isolates , whereas others were highly diverged or missing . We identified 360 ankyrin motif-containing proteins in GS ( Table S6 ) , with the number of repeats/protein ranging from 1–28 . The ankyrin-repeats are commonly localized downstream of the kinase domain in NEKs or in multiple repeats in the 21 . 1 protein family , indicating that this is an important protein/protein interaction domain in Giardia . The HCMP gene family [40] was discovered during the analysis of the WB genome and is similar to the VSP gene family , except for the absence of the conserved C-terminal CRGKA sequence . Twenty-one full-length HCMPs were identified in GS ( Table S6 ) and many were not complete due to assembly problems . Similar to the NEK gene family , some of the HCMP proteins were highly conserved between WB and GS , while others are highly diverged or absent . Alpha-giardins is a cytoskeleton gene family that is unique to Giardia but it is related to annexins [41] . All the 21 alpha-giardin genes in WB were conserved in GS along with the genome synteny . The amino acid identity of the alpha-giardins between the two genomes is between 70 to 95% , with the exception of alpha-7 giardin , which only displays a 57% identity . Alpha-2 giardin was recently proposed to be assemblage A specific [42] . We found an alpha-2 giardin-like gene in GS with 92% aa identity in a syntenic position but the alpha-1 giardin was less conserved with 87% aa identity and most of the changes were found in the N-terminal region . Giardia is a micro-aerophilic intestinal parasite with a very limited metabolic repertoire [43] , containing no classical mitochondrion , no Krebs cycle or nucleotide and amino acid synthesis genes or enzymes required for de novo synthesis of lipids [20] . Many key metabolic enzymes are bacterial-like , including the arginine metabolic pathway that is used for energy production in trophozoites [43] . Phylogenetic analyses indicate that these genes were acquired by the diplomonad lineage via lateral gene transfers from bacteria relatively recently , rather than being retained from a bacterial-like eukaryotic ancestor [20] , [44] , [45] , [46] . We found no differences in the metabolic gene content between the WB and GS isolates . There are 149 genes in the WB genome that have been identified as good drug targets [20] as defined by Hopkins and Groom [47] , all these genes are also found in the GS genome . This suggests that drugs directed against these particular genes can have an effect on parasites from both assemblages . One of the main observations of the WB genome project was the simplicity of major cellular machineries [20] . We investigated the same cellular processes studied in detail in the WB genome ( e . g . DNA replication , transcription , polyadenylation and actin cytoskeleton ) [20] , and came to the same conclusion for the GS genome , i . e . Giardia has a minimal and simplified cellular composition . We also extended these analyses to several more basic cellular processes and we found the same pattern . One example is the rudimentary composition of the mRNA degradation system ( Fig . 5 ) . No decapping enzymes are present , but two typical 5′ to 3′ exoribonucleases were detected . The PARN and Pan 2–3 deadenylation complexes were not detected , but weak homologs for a few proteins in the CCR4-Not complex were identified ( Fig . 5 ) . The catalytically important proteins Rpr-4 and -40 of the exosome complex were identified , but only Rpr-45 of the ring structure . It was recently shown [48] that nonsense-mediated decay of mRNAs is present in Giardia but at lower efficiency . The Upf-1 protein of the nonsense-mediated decay machinery was identified in both genomes , but Upf-2 and –3 and the other proteins found to be important for nonsense mediated decay in yeast and humans were not ( Fig . 5 ) , which may explain the low efficiency of the process in Giardia . It was recently shown that the Upf-1 protein is an important regulator of the stability of the cyst-wall protein transcripts during encystations [48] and it will be informative to see how the nonsense mediated decay machinery is composed in Giardia . An analysis of the WB genome showed no evidence of true myosin genes [20] , suggesting that cytokinesis is not performed by an actomyosin ring in Giardia . However , homologs to actin and the mitotic cyclins A and B were detected in both Giardia isolates . Furthermore , we identified giardial homologs to several Mitotic Exit Network ( MEN ) proteins; Tem1 , Cdc5 , Cdc14 , Cdc15 , Bub2 and Mob1 as well as two members of the related FEAR complex; the kinase Cdc5 and the protease Esp1 ( see Fig . S3 ) . Our results suggest that the regulation of cytokinesis in Giardia is similar to the process in other eukaryotes , even if no strong myosin ortholog has been identified [20] .
Lateral gene transfer is increasingly appreciated as an evolutionary mechanism in microbial eukaryotes [50] , [51] , and metabolic adaptations via gene acquisitions have been shown to occur in diplomonads on longer evolutionary timescales [20] , [44] , [45] , [46] . The comparative study identified 3 unique WB and 28 unique GS proteins , suggesting that gene loss or gain is ongoing within Giardia . This is in agreement with earlier findings , although the rate of the process appears relatively low . Although most unique proteins are hypothetical , there are also examples of recently introduced bacterial genes in the GS genome . One example of this is a protein coding gene flanked by two bacterial pseudogenes , indicating a very recent introduction of a member from the Bacteroidetes group . To our knowledge , this is the first report of a “dead-on-arrival” prokaryotic pseudogene incorporated into a eukaryotic nucleus . Until now no isolate-specific genes have been identified in Giardia , and further studies will show what functions these genes have in the parasite . These unique genes may be of importance for the development of new tools for diagnosis and typing of Giardia . If strain-specific genes from each assemblage are expressed at relatively high levels in trophozoites and cysts in all isolates , it may be feasible to develop antibody-based genotyping/detection assays . The role of these unique genes during host-parasite interactions will also be of great interest for future studies . One surprising result from the WB genome project was the low level of allelic sequence divergence ( <0 . 01% ) [20] . We detected a dramatically higher level of allelic sequence divergence in the GS isolate ( average 0 . 5% ) . Our analyses indicate that the sequence divergence between haplotypes for most genes is much smaller than the divergence between the genes from the two isolates ( Fig . 2D ) . This contradicts a recent report where genes classified into both assemblage A and B were found in the same Giardia isolate [11] . In that study , the GS isolate was shown to contain actin genes from both assemblages and certain intergenic regions showed >99% identity to the corresponding region in WB . We failed to identify any of these reported assemblage A-type GS sequences [11] in our 16× coverage whole genome shotgun sequencing dataset . Unfortunately , the level of genetic exchange between Giardia assemblages cannot be determined until more genomic datasets from Giardia isolates become available . The observed allelic variations are likely the result of interactions between mechanisms that create and reduce variation between the four copies of the genome in the cell . The major sources of variations are probably mutations and DNA recombination , which has been proposed to occur between different Giardia isolates [52] . It is not likely that the mutations have been induced by genetic drift during asexual mitotic growth in vitro since this is the original clone isolated by Nash et al . [17] and it has been grown relatively few generations in vitro . There are also other mechanisms that could change the level of genetic variation between the four copies of the genome . Diplomixis , a recombination process between Giardia's two nuclei , shown to occur during encystation [53] , could be an important mechanism . This is a unique process for Giardia with its two nuclei and genes related to meiotic processes in other organisms were suggested to be important in this process [53] , [54] . All identified meiosis-related genes identified in WB [55] , [56] can be found in GS . Several are well conserved ( Spo11–78% aaID , Dmc1–92% aaID , Msh6–78% aaID ) , others are not as conserved ( Mre11–62% , Rad50–60% ) and some even show deletions ( 15 aa in Rad52 ) or insertions ( 14 aa in Mlh1 ) in important regions . The higher levels of allelic sequence divergence in GS could suggest that diplomixis is less efficient in the GS isolate compared to the WB isolate , although further investigations are needed to separate the effects of different mechanisms creating and reducing allelic variation in Giardia isolates . We identified and confirmed several breaks of gene synteny when the GS contigs were aligned with the WB genome scaffolds . Twenty one of the synteny breaks occur between regions in the same WB-scaffold with 3 occurring between different WB scaffolds . The most common class of synteny breaks was insertions or deletions of chromosomal regions containing members of the large Giardia-specific gene families VSPs , NEKs , HCMPs and Protein 21 . 1 . In at least two cases we detected two different variants of gene synteny; one identical to WB and one unique for GS . These recombination events occurred between two very similar genes localized within 15 to 30 kbp of each other . It is possible that these kinds of inversions between similar regions are more common than what we have detected here and it is also possible that there are differences between the two nuclei . Several characteristics of Giardia influence the epidemiology of human giardiasis: ( a ) the rate of trophozoite growth; ( b ) the encystation efficiency; ( c ) the size of the infective dose; ( d ) the excystation efficiency; ( e ) the viability of the secreted cysts and ( f ) the number of hosts , since zoonotic parasites have larger reservoirs . Most assemblage A parasites grow faster and differentiate ( encyst and excyst ) better in vitro than the few studied assemblage B isolates [9] , [36] , [57] , [58] , [59] . We found that Myb2 binding sites in the promoters of two enzymes involved in production of cyst-wall sugars in WB were missing in GS . This can potentially explain the poor encystation observed in GS , and furthermore suggests that the encystation stimuli may be different between assemblage A and B parasites . In order to further understand the epidemiology of giardiasis , it will be important to determine if there is a correlation between Giardia assemblages and cyst production in either infected humans or animals . The most well characterized virulence factors in Giardia are the VSP proteins [14] , [59] . The genome sequencing of WB found approximately 200 genes encoding different VSPs spread over the 5 chromosomes [20] . Our results showed that the VSP repertoires are very different in GS compared to WB . Certain VSPs are known to have toxin-like motifs [60] and it is possible that the differences in symptoms seen during Giardia infections are not due to assemblage differences , but rather because of differences in VSP repertoires and expression . One major issue in the Giardia research field has been the identification of genetic differences between the two human-associated Giardia assemblages A and B that would explain the observed phenotypic differences . Early genetic studies suggested that the levels of genetic diversity between the assemblage A and B parasites parasites are sufficient to recognize them as different species [17] , [61] . It is difficult to define a general species concept in eukaryotic microbes and there are more than a dozen of alternate eukaryote-specific “species concepts” used currently [62] . The biological species concept emphasizes the property of reproductive isolation but it is not applicable for organisms that multiply far more often by asexual than sexual reproduction [62] . The ecological species concept emphasizes occupation of a distinct niche or adaptive zone whereas one version of the phylogenetic species concept emphasizes diagnosability and another version requires monophyly of members of the species in phylogenetic trees [63] , [64] , [65] . The WB and GS isolates can be considered as separate species according to the phylogenetic species concept because they group into difference assemblages in genotyping studies and our data show an extensive primary sequence divergence across the majority of the genes . However , not enough data is available to define them as separate species according to many of the other species concepts , e . g . they both infect humans . Nevertheless , several biological differences have been detected between WB and GS and/or assemblage A and B isolates . WB is more easily stably transfected by episomal plasmids than GS [66] . Cytogenetic studies showed that certain assemblage A and B isolates differ in the number of chromosomes in each nucleus [67] and pulse-field analysis detected differences in chromosome size [68] . The repertoire of VSP proteins is very different in the two different isolates [68] . The GS isolate can readily infect mice , whereas the WB is cleared before it can establish an infection [16] . The GS isolate gave more severe symptoms than the assemblage A isolate Isr in experimental human infections [15] . Here we present data that connect phenotypic differences between the WB and GS isolates ( poor encystation and no cross-protection ) to genetic differences ( differences in encystations-specific promoters and VSP repertoire ) . Our results supports the recent suggestion of a revised Giardia taxonomy [69] . However , more data is needed in order to determine if the differences detected between WB and GS is true for all assemblage A and B isolates . This study has provided the tools to do this type of studies , which is important in further studies of giardiasis since the uncertain taxonomy has had a negative effect on the understanding of the disease .
Unless otherwise indicated , the reagents were obtained from Sigma Chemical Co , USA . Giardia intestinalis strain GS , clone H7 ( ATCC50581 ) trophozoites were grown as described [70] . The GS strain was isolated from a human patient infected in Alaska [17] and H7 is a clone of the original isolate . Genomic DNA was extracted from G . intestinalis GS trophozoites using the Easy-DNA kit for genomic DNA isolation ( Invitrogen , Carlsbad , CA , US , Cat . no . K1800-01 ) . The genomic DNA was sequenced using a Genome Sequencer FLX instrument ( Roche ) . Preparation and sequencing of the sample was performed according to the manufacturer's instructions . Base-calling was performed using the bundled 454 software . The quality of the generated sequence reads was evaluated using the Phred-like [71] quality scores associated with the sequence reads . Only 2 . 98% of the bases in the pool of sequence reads were shown to have quality values less than 20 , which corresponds to 5 , 445 , 574 bases . If each one of these bases would have a score equal to 10 this would correspond to a probability of 1 in 10 , or 544 , 557 incorrectly called bases- equal to 0 . 29% of the total number of sequenced bases . Thus , low quality sequence data is not a problem in the data set . The 808 , 181 reads generated from the 454 instrument were clustered using the Newbler sequence assembler from 454 Life Sciences ( version 1 . 1 . 03 ) and the reads that were successfully clustered were extracted and reclustered using the MIRA sequence assembler ( version 2 . 9 . 26×3 for 64 bit Linux ) [72] . This combined assembly strategy was required because of the tendency of the Newbler assembler to misinterpret polymorphisms as sequencing errors and introduce artifactual gaps into the sequence . The default parameters were used for both programs . A contamination control of the assembly was performed using BLAST searches against the GenBank non-redundant nucleotide database and contaminating sequences were removed . The clustering and final analysis formed 2 , 931 contigs over 200 bp with a total assembly size of 11 Mbp ( Table S1 ) . Gene prediction was performed on the 2 , 931 contigs using Glimmer version 3 . 02 [73] and CRITICA [74] using training genes ( 6 , 500 ) from the published Giardia genome ( isolate WB ) . The programs have overlapping prediction patterns , therefore duplicated ORFs were removed , as were ORFs without proper start and/or stop codons . The genomic data from this study has been deposited in GenBank with accession number ACGJ00000000 and the genome sequence is reported as recommended by the Genome Standards Consortium [75] ( Table S7 ) . Orthologous relationships between putative coding sequences in GS and WB-C6 ( ATCC50803 ) were determined using NCBI BLASTP . The predicted ORFs from GS were queried against a database containing putative coding sequences from WB . The reciprocal best hit was used to identify orthologs . The top hit from each BLAST report was required to have an E-value<10−10 , amino acid identity above 50% and the high scoring pair had to have a length at least 60% of the CDS length in WB . The automatic GS annotations were aligned with the corresponding annotations in WB and manually inspected using the Artetmis Comparison tool [76] and SynBrowse [77] . Additional orthologs were identified by examination of the conserved gene order . Conserved , non-overlapping GS ORFs with no annotation in WB were kept in the GS annotation , and their annotations were added to the WB genome . Similarity searches with annotated WB genes with no GS ortholog assignment were used to evaluate differences in genomic gene content . For certain genes , unambiguous ortholog assignments were not possible because of their divergent nature . Truncated genes present at contig ends were listed separately . Gene synteny was analyzed using SynBrowse and the Artemis Comparison Tool . Synteny information combined with translational BLAST searches provided evidence for orthologous genes located at contig ends . Synteny breaks were verified using PCR . Contigs where PCR did not support a synteny break were split into two separate sequences . Interrupted ORFs were also amplified using PCR and 66 were sequenced using Sanger sequencing . Verification of frame-shifted genes , synteny breaks and joining of contigs were also performed by PCR and Sanger sequencing of the resulting PCR products . Primers were designed manually according to recommendations in the Phusion HotStart polymerase instruction manual ( Tm 60°C and 22–25 bp in length ) and synthesized by Sigma-Genosys ( Text S2 ) . The targets were amplified in a mixture containing 1xPhusion HF buffer with 1 . 5 mM MgCl2 , 200 µM dNTPs , 0 . 5 µM of the forward and reverse primers , 10 ng GS/M-H7 genomic DNA and 0 . 8 U Phusion HS DNA polymerase ( Finnzymes ) in a total volume of 40 µl . The reactions were incubated for 2 min at 98°C followed by ( 98°C for 15 sec , 55°C for 30 sec , 72°C for 30 sec/1 kb of expected amplicon ) ×35 cycles and were subsequently held at 4°C . The PCR products were purified using the QIAquick PCR purification kit according to the manufacturer's recommendations and eluted in 30 µl ddH2O . The purified PCR products were sequenced with their respective forward and/or reverse primers at the Uppsala Genome Center using the BigDye® Terminator v3 . 1 ( Applied Biosystems ) chemistry followed by capillary electrophoresis on an ABI3730XL sequencer ( Applied Biosystems ) . Synteny analysis identified GS contigs that were predicted to be close to but not joined in the assembly . Super-contigs were produced by PCR amplification of the missing regions between GS contigs and the PCR products were sequenced in both directions to obtain paired-read coverage . Primer design , PCR conditions and sequencing were performed as in the synteny analysis section . Pairwise nucleotide and amino acid alignments were created for the ortholog pairs using the blastn and blastp programs in the wublast package and the sequence identity for each alignment were subsequently extracted . We used the EMBOSS [78] , [79] program cusp to examine codon usage in putative coding sequences in both Giardia isolates . In-house Perl scripts were developed to identify sequence variation in the ace file generated by the MIRA sequence assembler and the 8 , 618 , 167 positions in 3 , 118 assembled contigs with at least 10-fold coverage and lacking indels and ambiguous nucleotides ( ‘n’ ) were examined for sequence variations . For a position to be classified as a polymorphism an alternative nucleotide had to be present in at least 2 reads with different start positions . The prediction of tRNA genes was performed using tRNAScan ( version 1 . 23 ) [80] with default parameters . Ribosomal and small RNAs were identified by sequence comparison of published RNA genes from Giardia WB . Sets of homologous sequences from the public databases were compiled and aligned using CLUSTALW [81] . Only unambiguously aligned regions identified by manual inspection were used in the phylogenetic analyses . The optimal substitution models for each dataset were determined using MODELGENERATOR , version 0 . 84 [82] Maximum likelihood analyses were performed using PHYML , version 2 . 4 . 5 [83] . In addition , bootstrap analyses with 100 replicates were performed for each dataset with the same parameters .
|
Giardia intestinalis is a major contributor to the enormous burden of diarrheal diseases with 250 million symptomatic infections per year , and it is part of the WHO neglected disease initiative . Nonetheless , there is poor insight into how Giardia causes disease; it is not invasive , secretes no known toxin and both the duration and symptoms of giardiasis are highly variable . Currently , there are seven defined variants ( assemblages ) of G . intestinalis , with only assemblages A and B being known to infect humans . Although assemblage B is the most prevalent worldwide , it is inconclusive whether the various genotypes are associated with different disease outcomes . We have used the 454 sequencing technology to sequence the first assemblage B isolate , and the genome was compared to the earlier sequenced assemblage A isolate . Large genetic differences were detected in genes involved in survival of the parasite during infections . The genomic differences between assemblage A and B can explain some of the observed biological and clinical differences between the two assemblages . Our data suggest that assemblage A and B Giardia can be two different species . The identification of genomic differences between assemblages is indeed very important for further studies of the disease and in the development of new methods for diagnosis and treatment of giardiasis .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"infectious",
"diseases/protozoal",
"infections",
"infectious",
"diseases/neglected",
"tropical",
"diseases",
"genetics",
"and",
"genomics/comparative",
"genomics",
"infectious",
"diseases/gastrointestinal",
"infections"
] |
2009
|
Draft Genome Sequencing of Giardia intestinalis Assemblage B Isolate GS: Is Human Giardiasis Caused by Two Different Species?
|
The accuracy of replicating the genetic code is fundamental . DNA repair mechanisms protect the fidelity of the genome ensuring a low error rate between generations . This sustains the similarity of individuals whilst providing a repertoire of variants for evolution . The mutation rate in the human genome has recently been measured to be 50–70 de novo single nucleotide variants ( SNVs ) between generations . During development mutations accumulate in somatic cells so that an organism is a mosaic . However , variation within a tissue and between tissues has not been analysed . By reprogramming somatic cells into induced pluripotent stem cells ( iPSCs ) , their genomes and the associated mutational history are captured . By sequencing the genomes of polyclonal and monoclonal somatic cells and derived iPSCs we have determined the mutation rates and show how the patterns change from a somatic lineage in vivo through to iPSCs . Somatic cells have a mutation rate of 14 SNVs per cell per generation while iPSCs exhibited a ten-fold lower rate . Analyses of mutational signatures suggested that deamination of methylated cytosine may be the major mutagenic source in vivo , whilst oxidative DNA damage becomes dominant in vitro . Our results provide insights for better understanding of mutational processes and lineage relationships between human somatic cells . Furthermore it provides a foundation for interpretation of elevated mutation rates and patterns in cancer .
From the moment of fertilisation , as each cell divides random mutations occur which are fixed and inherited by daughter cells . Most of these variants have little , if any , physiological consequence but contribute to genetic diversity within tissues . A small proportion will contribute to pathogenic processes such as cancer [1] . Whole genome sequence analysis of cancer genomes has revealed their mutational landscape [1–4] . Cancers are clonally heterogeneous , like the somatic tissues from which they originate , and arise through a series of clonal expansions over decades often acquiring aberrant DNA repair processes [3 , 5 , 6] . Thus , the extent to which mutational signatures in human cancers reflect normal non-pathological mutational patterns that have arisen in their normal non-cancerous somatic ancestors is obscure . The mutations that have arisen in somatic cells throughout development and tissue homeostasis are generally difficult to identify in tissue biopsies because these are composed of heterogeneous polyclonal populations of cells . To describe the landscape of mutations in normal somatic tissues , we sought to resolve the underlying heterogeneity of somatic tissues by reprograming the constituent cells into induced pluripotent stem cells ( iPSCs ) [7] , a process of single cell cloning that facilitates subsequent expansion . Each clonal iPSC line generated from a heterogeneous polyclonal pool will carry a constellation of mutations reflecting both somatic and culture-induced mutations . Indeed previous work has suggested that a proportion of iPSC mutations originate from the founder somatic cell [8 , 9] . However although genome sequence analysis of these clones will reveal their mutational burden , it is not possible to definitively resolve the mutations which arose in vivo from those which arose during in vitro culture and reprogramming ( Fig 1A ) . To confidently classify the origin of the mutations , we derived iPSC lines using monoclonal derived endothelial progenitor cells ( EPCs ) [10] . The iPSCs isolated from a monoclonal source would share the mutations of the founder cell ( in vivo acquired somatic mutations ) and in addition carry culture-induced mutations as unique private mutations . Sequencing of these iPSCs would allow interrogation of the number and pattern of somatic mutations present in vivo ( Fig 1A ) .
Fibroblasts and/or monoclonal EPC lines were derived from three individuals: a 65-year old alpha-1 antitrypsin deficiency male ( patient AATD [12] ) , a 22-year old healthy male ( S2 [13] ) and a 57-year old healthy male ( S7 [13] ) , which were reprogrammed into iPSCs . The iPSC lines were initially screened using array-based comparative genomic hybridization ( CGH ) to select lines with the smallest number of copy number aberrations ( S1 Table ) . In addition none of the lines selected had large scale loss of heterozygosity ( LOH ) through error-prone break recombination ( S1 Fig [14] ) . Next we sequenced the protein-coding exons of these iPSC lines to determine the number and genomic location of their somatic mutations ( Fig 1B–1E and S11–S14 Tables ) . Fibroblast-derived iPSCs from both individuals carried similar numbers of coding mutations , ranging between 14 and 28 single nucleotide variants ( SNV ) per line ( Fig 1B and 1C ) . Consistent with a polyclonal origin , these SNVs were unique to each line and no shared SNVs were identified between lines from the same individual ( Fig 1B and 1C ) . In contrast , monoclonal EPC-derived iPSC lines ( iPSC-2 , 3 , 4 and 5 from AATD and iPSC-RE2 , RE9 , RE14 , RE17 and RE19 from S7 ) carried fewer mutations , of which a subset was shared between them as well as with EPCs from the same individual . None of the shared SNVs were detected in the corresponding fibroblasts or whole blood , indicating that these SNVs were somatically acquired by the EPCs in vivo ( Fig 1D and 1E ) . In addition , private SNVs were detected which were unique to each monoclonal-derived iPSC line and these were not found in EPCs or the individual’s reference genome . Deep sequencing of the donor EPC genome revealed that some of the mutations detected in the iPSCs were in fact present in the EPCs but at very low frequencies ( Fig 1D and 1E , orange boxes; S7 and S8 Tables ) , suggesting that these mutations were acquired by the EPCs during the in vitro expansion process , prior to reprogramming . Notably no known driver mutations ( using COSMIC database ) , which could confer a selective advantage , were identified in any of the iPSC lines . These results demonstrate that iPSCs derived from monoclonal somatic cells can be used to identify in vivo acquired somatic mutations . The mutational burden of iPSCs reflects mutations accumulated in vivo in the ancestral somatic cell lineages and mutations acquired during in vitro cell culture and subsequent reprogramming . The iPSCs from heterogeneous somatic cells usually do not share any mutations but the exome sequencing data demonstrated that by using monoclonal cell sources it is possible to resolve mutations acquired in vivo from those arising during in vitro cell culture . Furthermore , identifying shared mutations in somatic cell lineages could be used to construct a cellular phylogenetic tree . We therefore performed whole genome sequencing on the S7-derived monoclonal EPCs , 3 iPSC lines ( RE2 , RE11 and RE14 ) and fibroblasts , which were used as the reference genome ( S9 Table ) . The total number of mapped bases obtained per sample was 108 . 1–122 . 8Gb with 33 – 37X sequence coverage . We identified 463 SNVs in the monoclonal EPCs and 933 , 1119 and 840 in the iPSCs , respectively ( Fig 2A ) . A proportion of the putative SNVs were validated using PCR amplicon re-sequencing . This analysis revealed that we were able to detect SNVs with mutant allele frequencies of less than 30% with high specificity ( S10 Table ) , which most likely represent mutations acquired during the first few divisions after founder cells started dividing ( Fig 2B ) . Amongst the SNVs called , 391 mutations were shared by all the iPSC lines and the monoclonal EPCs at a mutant allele frequency of approximately 50% , which is consistent with clonal mutations ( heterozygous SNVs in diploid chromosomes ) . Therefore these 391 SNVs reflect the in vivo genetic divergence of the single EPC from fertilisation through development and adulthood . Some SNVs were shared between the EPCs and only a subset of the lines ( Fig 2A ) , revealing the emergence of genetic differences during in vitro EPC culture . The remaining SNVs were unique to each iPSC line and not present in the EPCs at a detectable frequency . These private mutations in RE2 ( 506 SNVs ) , RE17 ( 419 SNVs ) and RE14 ( 719 SNVs ) represent in vitro SNVs acquired in the EPC culture and/or during reprogramming ( S2–S6 Tables ) . The SNVs detected in the EPCs and iPSCs are a historical record of the phylogenetic lineage of the cells ( Fig 2C ) . For the individual S7 , in the 57 years from fertilization to the point of derivation of the single EPC , 391 mutations had accumulated in vivo . The single EPC was then expanded in vitro prior to reprogramming . Following the first cell division of the EPC , one daughter cell ( A ) acquired at least 29 mutations and the other daughter cell ( B ) at least 9 mutations . After daughter cell A divides , two further branches appear resulting in at least 7 mutations in one granddaughter cell ( A-1 ) and at least 1 mutation in the other ( A-2 ) . The progeny of daughter cells A-1 , A-2 and B were the eventual substrates for the derived iPSC lines S7-RE2 , S7-RE17 and S7-RE14 , respectively . The detailed mutation analysis we performed enabled us to estimate the in vitro mutation rate of the EPCs . Apart from the 391 in vivo mutations , the clonal SNVs detected in the iPSCs were acquired during the EPC expansion and reprogramming and thus should be present in parental EPCs . We sought to detect these sub-clonal mutations that are present in EPCs by deep sequencing and calculate a mutation rate during in vitro EPC expansion using a statistical model ( See Materials and Methods ) . First , in order to ensure accuracy especially at the lower bound of allele frequencies , we investigated sequencing error rates . Eight genomic regions ( S15 Table and S2 Fig ) were PCR-amplified from the AATD iPSC-B cells and sequenced on a MiSeq instrument . Median error rates were 0 . 042–0 . 144% and 0 . 053–0 . 320% for the first and second reads respectively when the first and second reads were analysed separately . However , median error rates were substantially improved ( 0 . 016–0 . 025% ) when consensus sequences were first generated from the first and second reads and then bases were counted ( S2 Fig ) . We used this approach to accurately identify low-frequency subclonal mutations . We amplified approximately 40% of the in vitro SNVs from genomic DNA derived from the S7 EPCs and performed deep sequence analysis . Of this subset , we detected 60 , 51 and 58 SNVs in S7-RE2 , S7-RE14 , and S7-RE17 respectively to be present in the EPCs at allele frequencies between 41% and 0 . 05% ( Table 1 ) . The sub-clonal SNVs in the EPCs were then used to calculate the mutation rate during in vitro culture , resulting in an estimated mutation rate of 14 . 0 ± 2 . 0 SNVs per cell per generation or 2 . 1 x 10−9 per nucleotide per generation ( see Materials and Methods ) . Clinical use of iPSCs requires not only generation but also maintenance of iPSCs in cell culture . We therefore sought to measure the rate of single nucleotide mutagenesis in iPSCs . In order to calculate this precisely , we sub-cloned iPSCs from individuals S7 and S4 ( a 61-year old healthy female ) as well as H9 human embryonic stem ( ES ) cells [15] and grew these continuously for 60 divisions . At the end of the expansion period , we sampled the population from each cell line by sequencing single cell sub-clones that had been expanded to provide an adequate DNA sample for whole genome sequencing . Comparison of the DNA sequence from these sub-clones to its immediate parental population identified in vitro mutations acquired during 60 divisions . All three lines had a similarly low mutation rate of 0 . 8–1 . 7 SNVs per cell per generation or 1 . 8 x 10−10 per nucleotide per generation ( Fig 3A and 3B ) . Intriguingly , although both EPCs and pluripotent stem cells have a similar cell cycle time , the mutation rate in pluripotent stem cells was approximately tenfold lower than that in EPCs during in vitro culture . Next , we sought to understand whether the patterns of the mutations could inform us of the mutagenic processes involved both in vivo and during in vitro cell culture . We separated the S7 mutations into three groups that represented the continuous cellular lineage for this 57-year old man , from fertilisation to isolation of the single EPC ( in vivo ) , expansion of the EPCs and reprogramming ( in vitro somatic cells ) and finally maintenance of the iPSCs ( in vitro iPSCs ) ( Fig 4A ) . Using a Bayesian Dirichlet process [16 , 17] we were able to model clusters of clonal and subclonal ( generated after the 1st cell division; <30% MAF ) SNVs for each cell population . We explored the types of base substitutions seen in these groups of mutations and found variation in the overall mutation spectra ( Fig 4B ) . There is a preponderance of C:G>T:A transitions in vivo and early in the cellular lineage . In contrast , in vitro and later in the cellular lineage , there is a preponderance of C:G>A:T transversions . To explore mutational processes in more detail , we conducted Non Negative Matrix Factorization ( NNMF ) analysis [4] . Firstly , we found that the clonal mutations in S7-EPCs , representing somatic substitutions acquired in vivo , are associated with a signature that has been attributed to deamination of methylated cytosines , a process thought to occur in all cells . This signature is similar to the mutations observed in germ cells , another example of in vivo mutations in normal cells ( Fig 4C ) . Secondly , the mutation signatures acquired by the EPC population in vitro ( clonal S7REs ) were composed of a combination of deamination and C>A transversions . We speculate that this latterly acquired signature represents damage accrued during culture and may be due to oxidative DNA damage [19] . Thirdly , we detected a sharp increase in the proportion of mutations associated with C>A transversions in sub-clonal mutations in the iPSCs ( subclonal S7REs ) . These sub-clonal mutations detected in iPSCs arise in the first few cell cycles after a clonal cell line appears . Cells during this period are thought to be undergoing reprogramming , suggesting that iPSC reprogramming may stimulate a mutational process associated with C>A transversions . Finally , the in vitro mutations of iPSCs ( maintenance cell culture ) were associated with both deamination of methylated cytosines and the C>A transversions , reinforcing the suggestion that it is a putative imprint of culture-related/oxidative damage in vitro . We have extensively analysed a series of normal single-cell derived clones by whole genome and exome sequencing . We report for the first time the number and characteristics of the acquired mutations in a monoclonal cell isolated from a healthy individual and subsequently derived iPSCs . From this data we are able to reconstruct the mutational history of a cell beginning from the fertilised egg through to adulthood , then to reprogramming and maintenance of iPSCs in long-term culture , demonstrating how mutagenic processes evolve through that cellular lineage . During first in vivo then in vitro cell divisions , there is a change in the mutation signatures , suggesting a proportional reduction in the contribution of deamination of methylated cytosines and a proportional increase in oxidative stress and DNA damage . Finally , consistent with the expectation that an organism should protect its stem cells , we observed a ten-fold reduction in mutation rate in iPSCs , which mirrored that in human ES cells , which have not been subjected to reprogramming . We find that reprogramming is mutagenic at the nucleotide level and , similar to previous reports [20 , 21] , not at the chromosomal level . The nucleotide-level mutations are associated with a sharp increase in the proportion of mutations associated with oxidative DNA damage . However established iPSCs seem to be substantially protected from DNA damage by their pluripotent state . The increased DNA replication fidelity of iPSCs and ES cells may be due to the activity of homologous recombination throughout the cell cycle in pluripotent cells , whereas in somatic cells it is restricted to the stages of the cell cycle in which there is presence of replicated chromatin [22 , 23] . Although in vitro culture of iPSCs has a reassuringly low mutation rate , the culture systems used altered the mutational spectrum , which shifted from predominantly C>T transitions to C>A transversions . Over the relatively few generations we studied , we could not find any evidence of a selection sweep within the culture . Notably we did not find any driver mutations in our analyses . Understanding how mutations accrue through iPSC reprogramming and during maintenance cell culture is paramount to developing safe clinical therapies . Furthermore the mutational signatures underlying normal development and tissue homeostasis provide insights into the biological processes occurring in normal cells .
Primary tissue samples and blood were obtained from a patient with alpha-1 antitrypsin deficiency ( patient 2 ) under the ethics approval REC No . 08/H0311/201 or adult cadaveric organ transplant donors referred to the Eastern Organ Donation Services Team ( part of NHS Blood and Transplant ) . Ethics approval for the latter was obtained from Cambridgeshire Research Ethics Committee 3 ( REC No . 09/H306/73 ) . All laboratory procedures were performed according to Standard Operating Protocols and safety assessments . For each subject included in this study , around 3cm of skin was excised from the midline surgical incision . The fat and dermal layers of the skin sample were removed and the skin was cut into approximately 1mm3 pieces . These were dispersed evenly on a 10cm plate ( maximum 20 pieces ) and incubated with fibroblast growth media ( Knockout DMEM with 20% FBS ) . At 21 days the fibroblasts were harvested using trypsin . For each derivation , 100mL of blood was taken from the patient into two 50mL Falcon tubes each containing 5mL of 10% sodium citrate . The sample was mixed by inversion and transporting to the laboratory on ice . The blood samples were diluted 1:1 with Ca2+ and Mg2+ free PBS and 20mL was layered gently onto 15mL of Ficoll Paque Plus ( GE Healthcare ) and centrifuged at 400g for 35min . The buffy coat containing the mononuclear cells was transferred into a new Falcon tube , diluted 1:1 with PBS and the cells were pelleted by centrifugation at 300g for 20min . Cell pellets were re-suspended in 15mL of EPC media: EGM-2MV supplemented with growth factors ( Lonza ) supplemented with 20% FCS ( HyClone ) , and plated onto collagen coated T-75ml flasks ( BD Biosciences ) [10] . The media was changed every 2 days and colonies started appearing from Day 10 . After 21 days the EPCs were passaged using trypsin and re-plated into a new T-75 flask ( without collagen ) . The cells were expanded through sequential passages in 1:3 ratios . H9 hESCs were obtained from WiCell Research Institute . Human iPSCs and ES cells were maintained as described previously [11 , 15] . Briefly , the cells were cultured on irradiated mouse embryonic fibroblast ( MEF ) feeder layers in iPSC medium ( termed KSR + FGF-2 ) : Advanced DMEM/F12 ( Invitrogen ) supplemented with 20% Knockout Serum Replacement ( Invitrogen ) , 2mM L-glutamine ( Invitrogen ) , 0 . 1mM β-mercaptoethanol ( Sigma-Aldrich ) and 4ng/mL of recombinant human basic Fibroblast Growth Factor-2 ( R&D systems ) . Medium was changed daily and the cells were passaged every 5–10 days depending on the confluence of the plates . To split iPSCs and ES cells , the plates were washed in PBS and 3mL of each of collagenase and dispase was added ( Collagenase IV 1mg/mL , Invitrogen; Dispase 1mg/mL , Invitrogen ) . For retroviral reprogramming , four pseudo-typed Moloney murine leukaemia retroviruses containing the coding sequences of each of human POU5F1 , SOX2 , KLF4 and MYC were obtained from Vectalys . For each iPSC derivation , 1 x 105 primary cells ( fibroblasts or EPCs ) were plated one day before transduction . The 4 viruses were added at a multiplicity of infection of 10 along with 10 μg/mL of polybrene ( Millipore ) . The following day residual virus was washed off with PBS and the cells were re-fed with the fresh medium . On day 5 after infection , the cells were re-plated using trypsin onto a 10cm dish of fresh MEF feeders and 2 days later , the medium was changed from primary cell-specific media to the iPSC medium ( KSR + FGF-2 ) . The medium was changed every 2 days until colonies emerged after which the medium was changed daily . For Sendai virus-mediated reprogramming , four viruses containing the coding sequences of human POU5F1 , SOX2 , KLF4 and MYC were obtained from DNAVec . The protocol for reprogramming was identical to that of retroviruses except that 5 x 105 fibroblasts were used at a multiplicity of infection of three and polybrene was omitted . The iPSC colonies were identified by their morphology and picked once they had reached sufficient size , typically from day 25 following transduction . Each colony was first detached from the surrounding feeders by scoring around the circumference . The colony was then split into quarters or eighths and the segments gently lifted off the plate and transferred to one well of a 12 well plate of fresh MEF feeders containing iPSC media ( KSR + FGF2 ) supplemented with ROCK inhibitor ( Y-27632 , Sigma ) [24] . The majority of the iPSCs used in this study have been previously characterised in other publications [12 , 13] . This was performed as described previously [11] . Genomic DNA was extracted from cell pellets using the DNeasy Blood and Tissue kit ( Qiagen ) . Short-insert 500bp whole genome libraries were constructed , flowcells prepared and sequencing clusters generated according to the manufacturer’s protocols and sequenced using the Illumina HiSeq2000 platform ( 100bp paired-end ) . Short-insert paired-end reads were aligned to the reference human genome ( GRCh37/hg19 ) using the Burrows-Wheeler Aligner ( BWA ) [25] , duplicates removed . The average sequence coverage was 34-fold . Somatic base substitution mutations were called using CaVEMan ( Cancer Variants Through Expectation Maximization: http://cancerit . github . io/CaVEMan/ ) which provides a probabilistic estimate of a variant being a somatic mutation . Only variants with likelihoods of 95% and above were included . Post-hoc filters ( previously trained on 21 WGS cancers [3] ) that sought to remove systematic sequencing artifacts as well as artifacts that arise from mapping errors , were applied to reduce the false positive rate . SNVs , for which PCR primers could be designed , were all analyzed by amplicon re-sequencing . PCR primers were designed using BatchPrimer3 to amplify regions spanning SNVs . PCR was performed with 5ng of genomic DNA ( Fibroblasts , EPCs and iPSCs ) used as a template with Phusion Hot Start DNA Polymerase with GC buffer in the following conditions: 98°C for 1 min , 35 cycles of 98°C for 15 sec , 58°C for 15 sec and 72°C for 30 sec , followed by the final extension , 72°C for 5 min . PCR products were first pooled by sample and then purified with QIAquick PCR Purification Kit ( Qiagen ) . Purified PCR products from A1ATD patient B-derived EPCs were converted to a 454 library by emulsion-PCR and sequenced using the 454 Titanium platform according to the manufacturer’s instruction . Purified PCR products from the other samples were converted to an Illumina library by adaptor ligation and sequenced on either the MiSeq ( 150bp , paired end ) or the HiSeq2000 ( 100bp , paired end ) platforms . Reads from the 454 platform were aligned to a reference constructed from PCR-amplified regions . Paired end reads from the MiSeq or HiSeq2000 were first used to generate consensus sequences between each pair and then these were aligned to a reference using BWA SW [25] . The number of reads reporting each of the four bases was counted using Samtool . PCR primers were designed in a way that each SNV was located in a region where both Illumina reads could reach . PCR and Illumina sequencing were performed as described above . Fastq files ( 1 . fq and 2 . fq ) were first merged to generate consensus sequence reads . In this process , base calls were accepted only when a sum of Q scores from both reads was higher than 40 and both reads reported the same base . Reads were discarded if an overlapping region exhibited more than 10% mismatches between the two reads . Consensus reads were subsequently mapped onto the reference sequence using BWA SW and the number of reads reporting each of the four bases was counted using Samtool . Two-way contingency Chi-square tests were performed between the reads reporting reference and mutant variants and between fibroblasts and EPCs . Multiple test correction was performed using the Bonferroni correction . SNVs whose mutant read was significantly higher in EPCs were counted as subclonal mutations . Analyses on the subclonal SNVs with less than 0 . 1% were shown in S16 Table . It is not possible to subclone and serially expand EPCs therefore a statistical model was used to estimate the SNV mutation rate in EPCs . We obtained 13 . 5 x 106 cells at the end of S7-EPC expansion , which represents that a single EPC underwent approximately 24 cell divisions . When 5ng ( approximately 750 cells or 1 , 500 molecules ) were used as a template for each PCR , assuming that the sampling of DNA molecule follows the Poisson distribution , probability of sampling k number of DNA molecules carrying each SNV introduced at generation n is therefore given by Pn ( X=k ) =λnkexp ( −λn ) k ! , where λn ( = 1500/2n+1 ) represents the mean molecule number of each mutation introduced at generation n in the 5ng DNA . The total number of mutations that can be detected with amplicon re-sequencing is ∑n=024Pn ( X>0 ) Mave=9 . 88Mave , where Mave is the average mutation rate , assuming that the mutation rate is similar throughout EPC culture . Taking into account the numbers of sub-clonal EPC mutations detected ( SNVs detected in EPCs by deep sequencing; Table 1 ) and the 40% sampling for deep sequence analysis , we estimated mutation rate of 14 . 0 ± 2 . 0 SNVs per cell per generation or 2 . 1 x 10−9 per nucleotide per generation . All work performed as part of this project was approved by an ethics committee under the REC Nos . 09/H306/73 and 08/H0311/201 . The aCGH data has been deposited with the ArrayExpress under the accession number , E-MTAB-1319 . Whole genome sequence data have been deposited with the European Genome-phenome Archive under the accession number EGAS00001000231 and exome data under the accession number EGAS00001000492 .
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The mutation load of human tissues is unknown and represents the genetic divergence from the fertilised egg . Reprogramming of somatic cells generates induced pluripotent stem cells ( iPSCs ) , a cell type being considered for clinical applications . We generated iPSCs from tissues of healthy individuals and used whole genome sequencing to identify in vivo mutations accrued in a somatic cell during the lifetime of the individual . Next we identified in vitro mutations introduced during reprogramming and cell culture . Each has a unique mutation signature suggesting different mutagenic processes . Our study demonstrates the use of reprogramming as a tool to elucidate mutational processes within normal cells and highlights the importance of genetic characterisation of iPSCs prior to clinical translation .
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2016
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Mutational History of a Human Cell Lineage from Somatic to Induced Pluripotent Stem Cells
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The mental retardation , autistic features , and behavioral abnormalities characteristic of the Fragile X mental retardation syndrome result from the loss of function of the RNA–binding protein FMRP . The disease is usually caused by a triplet repeat expansion in the 5′UTR of the FMR1 gene . This leads to loss of function through transcriptional gene silencing , pointing to a key function for FMRP , but precluding genetic identification of critical activities within the protein . Moreover , antisense transcripts ( FMR4 , ASFMR1 ) in the same locus have been reported to be silenced by the repeat expansion . Missense mutations offer one means of confirming a central role for FMRP in the disease , but to date , only a single such patient has been described . This patient harbors an isoleucine to asparagine mutation ( I304N ) in the second FMRP KH-type RNA–binding domain , however , this single case report was complicated because the patient harbored a superimposed familial liver disease . To address these issues , we have generated a new Fragile X Syndrome mouse model in which the endogenous Fmr1 gene harbors the I304N mutation . These mice phenocopy the symptoms of Fragile X Syndrome in the existing Fmr1–null mouse , as assessed by testicular size , behavioral phenotyping , and electrophysiological assays of synaptic plasticity . I304N FMRP retains some functions , but has specifically lost RNA binding and polyribosome association; moreover , levels of the mutant protein are markedly reduced in the brain specifically at a time when synapses are forming postnatally . These data suggest that loss of FMRP function , particularly in KH2-mediated RNA binding and in synaptic plasticity , play critical roles in pathogenesis of the Fragile X Syndrome and establish a new model for studying the disorder .
Missense mutations have been especially informative for establishing links between genetics and protein function in human disease . For example , missense mutations have advanced our understanding of the relationship between autism and mutations in genes including neuroligin-3 [1] , [2] , neurexin-1 [3] , shank 3 [4] , and MeCP2 [5] . Such mutations have not generally been of help in understanding the devastating effects of the loss of function of the Fragile X mental retardation protein ( FMRP ) , which include complex behavioral deficits including mental retardation , autism , and seizures [6] . In nearly all cases , the Fragile X Syndrome is caused by transcriptional silencing of the fragile X mental retardation 1 ( FMR1 ) gene as a result of CGG repeat expansion and hypermethylation of CpG islands in the 5′UTR region ( reviewed in [7] ) , culminating in loss of FMRP expression . Moreover , antisense transcripts ( FMR4 , AS-FMR1 ) in the same locus have been reported to be silenced by the repeat expansion , raising the possibility that their loss of function may contribute to the syndrome [8] , [9] . While this transcriptional silencing precludes structure-function analysis of FMRP , a single severely affected Fragile X Syndrome patient with a de novo missense mutation in FMRP has the potential to address this issue . This patient has marked macroorchidism , with testicular volume exceeding 100ml , and mental retardation , with IQ measured below 20 , and harbors a mutation in a conserved isoleucine changing it to an asparagine ( I304N ) [10] . Nonetheless , uncertainty has surrounded the significance of this clinical observation , in part because only a single such patient has been described , and in part because this patient has a confounding liver disease [10] . Previous efforts at modeling defects in FMRP have centered on generation of an Fmr1 null mouse ( Fmr1tm1Cgr ) . This mouse has defects in synaptic plasticity [11]–[18] and long , thin dendritic spines [19] , [20] similar to those found in human brain [21] , [22] . Understanding the biochemical mechanism by which FMRP mediates proper synaptic plasticity and/or maturation is an area of intense interest . Studies of FMRP have been necessarily restricted to in vitro and cell culture models , since the mouse model is a null . FMRP associates with polyribosomes in tissue culture cells [23]–[25] and mouse brain [26]–[28] . Moreover , FMRP , and the related protein FXR1P , associate with components of the RNA-induced silencing complex ( RISC ) in Drosophila and mammalian cells [29]–[32] , and FXR1P is required to mediate miRNA-dependent translational activation in tissue culture cells [33] , [34] . FMRP has also been proposed to have a role in mRNA transport , trafficking mRNA targets as granules from cytoplasm to synapses in a microtubule-dependent manner in primary neurons [35]–[37] . FMRP has also been suggested to regulate PSD-95 mRNA stability [38] . A common theme associated with these diverse cellular roles is that a critical function of FMRP is binding to specific RNA targets . FMRP has functional domains involved in RNA binding , protein∶protein interactions and nuclear-cytoplasmic shuttling . FMRP RNA binding domains include two tandem KH-type domains ( hnRNPK homology ) , an arginine and glycine-rich RNA binding domain ( RGG box ) [39] , [40] , and an N-terminal domain similar to Tudor/Agenet domains that may be involved in both RNA binding and protein-protein interactions [41]–[44] . Protein interaction domains include an N-terminal region responsible for homodimerization and heterodimerization with its autosomal homologs FXR1P and FXR2P [45] , [46] . Finally , FMRP has a nuclear localization signal ( NLS ) mapped to approximately 100 nucleotides of the N-terminus [47] , and a Rev-like nuclear export signal ( NES ) C-terminal to the KH domains , which , when mutated at critical leucines , causes accumulation of FMRP in the nucleus [48] . Interest in the RNA binding properties of the KH2 domain has been heightened by structural data suggesting that the human I304N mutation maps to the RNA binding pocket present in KH domains [49] . For example , the first structure of a KH domain ( Nova KH3 ) bound to its RNA ligand demonstrated that the RNA binding pocket is supported by conserved hydrophobic amino acids , one of which corresponds to the isoleucine mutated in the I304N patient [50] . These observations have suggested that a key defect in FMRP loss-of-function is the loss of sequence-specific RNA binding , mediated through the FMRP KH2 domain [50] , [51] . Here we address these issues by generating and analyzing a mouse ( Fmr1tm1 ( I304N ) Drnl , termed here Fmr1I304N ) harboring the I304N mutation . We find that the I304N mutation phenocopies Fmr1 null mice . The mutant protein has lost polyribosome association and RNA binding , and is present at reduced levels that vary with age , but are particularly low at P14 , during synaptogenesis . These observations support the suggestion that sufficient levels of FMRP , and/or its RNA binding activity , are critical for normal cognition . Generation of the Fmr1I304N mouse provides a new model for understanding molecular defects in the disease , for screening potential therapies , and heightens interest in identifying FMRP-RNA interactions in the brain .
To generate Fmr1I304N mice we introduced the I304N mutation into the endogenous mouse Fmr1 locus by homologous recombination ( Figure 1A ) . An Fmr1 KH2 I304N targeting construct , including a self-excising loxP-Auto-Cre-NeoR-loxP ( ACNF ) cassette which allows self-induced deletion of the selectable marker in the male germline [52] , was electroporated into embryonic stem cells and 53 homologous recombinants were identified by Southern blot ( Figure 1B ) . Germline chimeras were bred to generate Fmr1I304N mice . These were bred for greater than 10 generations into both FVB and C57BL/6J backgrounds . We examined Fmr1 mRNA expression in male FVB Fmr1I304N mice . Because the Fmr1 gene is on the X chromosome these mice express only the I304N-mutant allele . Northern blot and quantitative RT-PCR analysis showed that I304N Fmr1 mRNA was expressed at wild type levels and was of the expected size in both brain and testes ( Figure 1C and 1D ) . Sequencing of RT-PCR products from the Fmr1I304N mice confirmed the presence of the I304N mutation ( data not shown ) . Fmr1I304N mice had no overt phenotype , were fertile with normal litter sizes , and transmitted the mutant allele with the expected X-linked Mendelian segregation ratios . Histological examination of heart , spleen , liver , lung , kidney , adrenal glands , stomach , intestines , muscles , diaphragm , bladder , and thymus of Fmr1I304N mice revealed no macroscopic abnormalities nor microscopic lesions ( data not shown ) . Further analysis focused on the brain and testes , as both organs are affected in Fragile X patients , and the I304N patient in particular . Histologic analysis of cerebellum , cortex , hippocampus and testes revealed no defects ( Figure S1A , S1B , S1C , S1D , S1E , S1F , S1G , S1H , S1I , SIJ , S1K , S1L , S1M , S1N , S1O , S1P ) , similar to Fmr1 null mice [53] , [54] . Macroorchidism of greater than 25 ml combined testicular volume is present in more than 90% of adult males with Fragile X syndrome [55] , and was particularly severe in the I304N patient whose testicular volume exceeded 100 ml [10] . We measured the testicular weights of adult Fmr1I304N mice compared to either WT or Fmr1 null littermates . Macroorchidism was evident in Fmr1I304N mice compared to WT animals ( 12–28% increased weight ) , and the most pronounced differences were evident in older animals ( Figure 2A ) . Testicular weight in Fmr1I304N mice was similar to , but surprisingly , no greater than that seen in FMR1 null mice ( Figure 2B; [53] , [54] ) . There was no significant difference in body weights between Fmr1I304N mice and wild type or Fmr1 null littermates ( Figure 2C and 2D ) . These observations indicate that the I304N mutation in mice phenocopies the macroorchidism evident in human patients , and suggests that the profound macroorchidism evident in the I304N patient may result from a combination of the I304N mutation and additional factors . Modeling the human behavior deficits seen in Fragile X Syndrome in mouse models has proven challenging , although some marked differences between Fmr1 null mice and normal littermates have been characterized [56] , [57] . We compared Fmr1I304N and WT littermates in behavioral assays , blind to genotype . We assessed a battery of 11 behavioral tests that are well established measures of deficits in Fmr1 null mice [58] , [59] . These included measures of exploratory behavior , anxiety , acoustic startle and prepulse inhibition , conditioned fear , pain sensitivity , marble burying ( as a measure of perseverative behavior ) , and susceptibility to audiogenic seizure . Results in the Fmr1I304N mice were consistent with lower levels of anxiety and greater repetitive/perseverative behavior ( Table 1 , Figure S2 , and Text S1 ) . Importantly , one of the most robust phenotypes in Fragile X null mice , increased susceptibility to audiogenic seizure , was evident in 18% of Fmr1I304N mice but not in WT mice; these results are comparable to or more severe than those reported in Fmr1 null mice ( see Text S1 for discussion ) . Taken together , our results indicate that in 10 of 11 tests , Fmr1I304N mice show similar responses to those reported for Fmr1 null mice . Both are hyperactive , have increased perseverative behavior and audiogenic seizures , and reduced anxiety and startle reflexes relative to normal mice . Fmr1 null mice have defects in synaptic plasticity . The most well-studied relates to metabotropic glutamate receptor-dependent long term depression ( mGluR-LTD ) in hippocampal CA1 neurons that normally requires de novo protein synthesis in dendrites . In Fmr1 null mice , mGluR-LTD elicited by either an mGluR agonist ( DHPG ) or electrical stimulation of Schaffer collateral inputs to CA1 neurons ( paired pulse low frequency stimulation ( PP-LFS ) ) is enhanced [11] , and no longer requires protein synthesis [60] , [61] . We assayed the protein synthesis requirement for both chemically and synaptically induced mGluR-LTD in acute hippocampal slices prepared from Fmr1I304N mice and their wild type littermates . Pre-incubation with the protein synthesis inhibitor anisomycin inhibited both DHPG ( p = 0 . 003 ) and PP-LFS ( p = 0 . 003 ) induced LTD in wild type mice ( Figure 3A and 3C ) , but had no effect on the establishment of LTD in Fmr1I304N mice ( Figure 3B and 3D ) . LTD magnitude in the absence of anisomycin was not different between Fmr1I304N and wild type littermates . We also found no significant difference between wild type and Fmr1 null mice in these studies , consistent with the lack of enhanced LTD in the I304N mice ( see Discussion ) . Finally , since the I304N patient is more severely affected than typical Fragile X patients , we examined whether mGluR-LTD is enhanced in the Fmr1I304N relative to Fmr1 null mice . We compared DHPG-elicited LTD measurements in Fmr1I304N and Fmr1 null littermates , and found that there was no difference in the degree of LTD elicited ( Figure 3E ) . Taken together , given the degree of similarity in the phenotypes between Fmr1I304N and Fmr1 null mice , including their behavior , macroorchidism and altered synaptic plasticity , we conclude that the I304N mutation in FMRP is sufficient to cause symptoms of the Fragile X Syndrome . We next used this mouse model to address the mechanism by which this missense mutation in the KH2 RNA-binding domain of FMRP results in the Fragile X phenotype . We examined I304N-FMRP expression in the brain , testes , and spleen by Western blot analysis . At 2 months of age , I304N-FMRP was expressed at ∼30% of normal levels in brain and remained at ∼30% of WT levels at 6 months of age ( Figure 4A and 4B ) . In younger mice ( P14 ) , WT FMRP levels were much higher , while I304N-FMRP was expressed at levels only slightly higher than in older mice , leading to a relatively larger difference between WT and I304N FMRP levels in the second postnatal week ( ∼13% of the WT level; Figure 4A and 4B ) . We found no evidence for a compensatory increase of the FMRP homologues , FXR1P and FXR2P , in I304N mice ( Figure 4C ) . I304N-FMRP was also present at lower steady-state levels than the WT protein in other tissues ( ∼30% in testes and spleen at 6 months of age; Figure 4D ) . Decreased protein steady-state levels with normal mRNA levels ( Figure 1C and 1D ) suggests that I304N-FMRP may either be synthesized more slowly or turned over more rapidly . We analyzed whether I304N Fmr1 mRNA was being translated by comparing its distribution on polyribosomes with WT Fmr1 mRNA in P14 mice . Quantitative RT-PCR analysis of mRNA levels showed that I304N Fmr1 and WT Fmr1 mRNA had similar distributions across 16 sucrose gradient fractions ( Figure 4E ) . These observations suggest that the lower I304N-FMRP levels do not relate to translational control , but may relate to increased turnover of the mutant protein , particularly in younger mice . FMRP associates with polyribosomes in tissue culture cells [23]–[25] and in brain [26]–[28] , suggesting that the protein may regulate mRNA translation . In contrast , in lymphoblastoid cell lines derived from the I304N patient , and in cells transfected with an EGFP-tagged I304N-FMRP reporter construct , mutant FMRP no longer associates with polyribosomes [25] , [62] . To examine whether the I304N mutation affected endogenous FMRP-polyribosome association in the brain , we examined the distribution of the mutant protein in the brains of Fmr1I304N mice . A254 traces of polyribosomes separated by sucrose density centrifugation revealed no difference between wild type and Fmr1I304N mouse brain , suggesting that global translation status was normal in the mutant mice ( data not shown ) . However , I304N-FMRP was largely dissociated from polyribosomes in mouse brain ( Figure 5A ) , and there was a reciprocal increase in I304N-FMRP present in lighter polysome fractions ( Figure 5B ) . We also found that the I304N mutation in FMRP does not significantly affect FXR1P or FXR2P polyribosome association in mouse brain ( Figure 5A ) , suggesting that their polysome-association is not FMRP-dependent . These results are consistent with previous findings in patient lymphoblastoid cell lines [25] , and suggest that the I304N mutation impacts the normal function of FMRP on polyribosomes . It has been suggested that the I304N mutation renders FMRP incapable of forming normal mRNP complexes in cultured cells [25] . We analyzed endogenous WT or I304N-FMRP particle size by Superose 6 gel filtration of mouse brain cytoplasmic extracts prepared in EDTA to release ribosomal subunits from mRNA . Wild type FMRP was found in the void volume of the Superose 6 column , indicating that FMRP is normally present in a complex of greater than 40 , 000 kDa ( Figure 6A , upper left panels ) . In contrast , the majority of I304N-FMRP was shifted into a smaller complex eluting at approximately 100–300 kDa ( Figure 6A , lower left panels ) . This complex may correspond to a small ( <440kD ) I304N complex observed in I304N patient-derived lymphoblastoid cells [25] . Mutant I304N-FMRP had no significant effect on the apparent size of FXR1P or FXR2P complexes ( Figure 6A , left panels ) . To assess whether the loss of I304N-FMRP from larger complexes might result from a loss of protein-RNA interaction , we treated brain cytoplasmic extracts with excess RNase prior to Superose 6 gel filtration . Under these conditions , the WT FMRP complex size was reduced to the size of the I304N-FMRP complex ( Figure 6A , upper panels , compare fractions 4–5 and 13–14 ) , but the I304N complex did not change in apparent size ( Figure 6A , lower panels ) ; similar results were seen when EDTA was omitted from the lysis buffer ( data not shown ) . This suggests that relative to FMRP , the I304N-FMRP in mouse brain has lost most or all of its ability to associate with RNA . We cannot rule out binding to small RNAs that would not affect migration on Superose 6 columns ( those less than ∼200 nucleotides ( 66 kDa ) , which we estimate would shift Superose 6 migration ) . We note that a small amount of I304N-FMRP is present in the void volume in an RNase sensitive manner , which could be due to heterodimerization with other RNA binding proteins or residual RNA interactions from other FMRP RNA binding domains . To assess whether the I304N protein retains reported biologic activities in vivo , we evaluated whether it was competent to interact with protein partners . We first compared the size of the RNase-treated I304N FMRP complex with that of denatured , recombinant I304N-FMRP added to mouse brain extract by Superose 6 gel filtration . Endogenous mouse brain I304N-FMRP was found in a complex significantly larger ( fractions 13 and 14 ) than the I304N recombinant protein added to the same extract ( fraction 15 ) , suggesting that the native I304N protein in brain is capable of protein interactions independent of RNA binding ( Figure 6B ) . FMRP was previously found to heterodimerize with its two autosomal homologs , FXR1P and FXR2P , by yeast two-hybrid assays [46] . In vitro studies indicated that I304N FMRP retains the ability to heterodimerize with FXR1P and FXR2P [63] . We analyzed the ability of endogenous I304N-FMRP to heterodimerize in mouse brain by immunoprecipitating I304N protein and assaying for co-precipitating FXR1P and FXR2P by Western blot . These experiments demonstrated that FXR1P and FXR2P co-precipitated with WT and I304N-FMRP , but not in control IPs from FMRP null brains ( Figure 7A ) . Less FXR1P and FXR2P are co-precipitated by I304N-FMRP as compared with wild-type FMRP , but this is likely to be accounted for by the lower FMRP levels in the I304N mutant mouse ( Figure 4 , Figure 7B , third panel ) . In vitro RNA selection studies identified a kissing complex RNA that is bound with high affinity by the FMRP KH2 domain [51] and a G-quartet RNA ligand for the C-terminal RGG–type RNA binding domain [64] , [65] . Recombinant I304N-FMRP produced in insect cells has been shown to bind to G-quartet RNA , but not the kissing complex RNA [51] . We therefore examined endogenous I304N-FMRP in mouse brain to determine whether it recapitulated these RNA binding properties . Radiolabeled G-quartet or kissing complex RNA synthesized by in vitro transcription was added to mouse brain lysates , UV-crosslinked , immunoprecipitated with an antibody against FMRP and crosslinked RNA detected by autoradiography after SDS-PAGE . A radiolabeled FMRP∶RNA complex was seen specifically in the immunoprecipitate of the I304N-FMRP extract crosslinked to the G-quartet RNA , but little or no I304N protein was crosslinked to kissing complex RNA ( Figure 7B ) . When compared with the wild type FMRP , the reduced radioactive signal from G-quartet RNA crosslinked to the I304N-FMRP in mouse brain was consistent with lower I304N-FMRP levels in the knock-in mice ( Figure 7B , third panel ) . Point mutants of G-quartet or mutant kissing complex RNAs , which are not bound by recombinant FMRP in vitro [51] , [64] did not crosslink to either endogenous wild type or I304N-FMRP in mouse brain ( data not shown ) . Taken together , these data indicate that I304N-FMRP in mouse brain retains some normal properties , as it is competent to bind both protein and , via its RGG-domain , to bind G-quartet RNA . RGG-domain RNA binding to RNA over 200nt is not evident in the I304N mouse , suggesting either that it plays a minor or dependent role to KH2 binding to large RNAs . Therefore a major biochemical defect in the Fmr1I304N mouse is the loss of KH2-dependent RNA binding . While other interpretations cannot be ruled out , including the loss of KH2-dependent interaction with a protein partner , taken together our data suggest that the resulting loss of polysome association and , presumably , proper regulation of translation of FMRP mRNA targets , is most likely to contribute to the phenotype of the Fmr1I304N mouse .
Behavioral changes in the Fmr1 null mouse relative to either wild-type or mutant littermates have been well described . We compared the Fmr1I304N mouse to wild-type littermates on the same background and using many of the same assays employed for extensive behavioral testing of the Fmr1 null mouse , the Fxr2 null mouse , double knockout of both Fmr1 and Fxr2 , and a mouse overexpressing human FMRP from a transgenic YAC construct [53] , [66]–[69] . In most cases the phenotype of the KH2 mutant Fmr1I304N mice was similar to the previously published phenotype of the Fmr1 null mice , including increased audiogenic seizure rates , decreased acoustic startle responses , and assays indicating greater exploratory behavior , decreased anxiety responses and increased perseveration . Our results measuring PPI , while consistent with Fmr1 null mice assessed in our laboratory [68] , differed from those of some investigators [70] , [71]; it is possible that strain differences may account for some of this discrepancy . In summary , our behavioral assays of Fmr1I304N mice indicate that they show abnormalities in the same tests , in the same direction , and to similar levels in all assays previously performed in our laboratory ( Table 1 ) , strongly supporting the conclusion that the I304N mutation is sufficient to phenocopy loss of the Fmr1 gene . Metabotropic glutamate receptor-dependent LTD is a hippocampal synaptic plasticity paradigm that relies on rapid protein synthesis in dendrites [72] . Previous work in the Fmr1 null mouse demonstrated that LTD is enhanced and independent of new protein synthesis and translational regulators , such as ERK and Homer [11] , [13] , [16] , [60] , [61] , [73] . From these studies , it was suggested that FMRP regulates the translation of the dendritic mRNAs required for mGluR-LTD expression . Here we demonstrate that LTD induced with either chemical or synaptic stimulation is independent of protein synthesis in the Fmr1I304N mice , recapitulating the Fmr1 null phenotype ( Figure 3 ) . This suggests that FMRP must interact with polyribosomes or kissing-complex RNAs for normal mGluR-LTD regulation . Alternatively , the effects on LTD could be due to a hypomorphic expression of I304N-FMRP . It is unclear why we did not detect alterations in the magnitude of LTD between Fmr1I304N mice and wildtype littermates or Fmr1 null littermates as demonstrated previously [13] , [16] , [60] , [61] . We also found no significant enhancement of LTD between wild type and Fmr1 null littermates in the current study . This may be due to the fact that older mice were used in this study ( 40–90 day ) than in previous work ( 21–35 day ) or other factors such as stress levels , which are known to impact mGluR-LTD magnitude [74] . Subtle genetic background differences may also play a role . Notably , the independence of LTD on protein synthesis , as seen here in the Fmr1I304N mice appears to be a more robust and reproducible phenotype in Fmr1 null mice in comparison to enhanced LTD magnitude [73] , [75] . Macroorchidism is a profound clinical finding in postpubertal Fragile X patients , affecting more than 90% of adult male patients [55] . In mouse models , the Fragile X null mouse has a 20–25% increase in testicular size [53] , [54] , [76] which is rescued by a wild type human FMRP transgene [53] . The Fmr1I304N mice display the same degree of macroorchidism as their null counterparts , and this increases with age , as in the Fmr1 null mice [54] and in the human patients [6] , supporting the conclusion that the Fmr1I304N mutation is sufficient to phenocopy the Fragile X Syndrome . Steady-state levels of endogenous I304N-FMRP were found to be decreased relative to WT FMRP . While all of the characteristic isoforms of FMRP are observed in the Fmr1I304N tissues , they are expressed at lower levels than in wild type littermates . The post-transcriptional reduction in steady state levels of I304N-FMRP compared with mRNA levels has also been observed in two lines of I304N-FMRP BAC transgenic mice ( data not shown ) , and in I307N-dfmr1 flies , which have the analogous mutation to I304N-FMRP in mammals [77] . Taken together , these data suggest that decreased protein levels are intrinsic to the mutation rather than a result of our genetic manipulation . Lower steady state levels of I304N FMRP in brain and testes are surprising in light of previous data demonstrating that I304N FMRP is expressed at normal levels in EBV transformed lymphoblastoid cells from the patient with the I304N mutation [25] and may be due to the fact that a different cell type was studied or that EBV transformation altered normal FMRP expression . We find that steady state levels of I304N-FMRP are too low in cultured primary neurons to permit standard pulse-chase immunoprecipitation experiments to quantify I304N FMRP synthesis and turnover ( data not shown ) . Another means of assessing FMRP synthesis is to analyze the distribution of its mRNA on polyribosome sucrose gradients . We have shown that I304N-Fmr1 mRNA has a normal profile on polyribosomes compared with wild-type littermates ( Figure 4E ) , suggesting that decreased protein synthesis is not likely to account for decreased protein levels . It has been reported that FMRP can bind a G-quartet motif in the coding sequence of its own mRNA , inhibiting its translation [65] . However , we find no evidence to support the consequent prediction that in the I304N mouse there would be an increase in translation of the I304N-Fmr1 mRNA . Taken together , it seems most likely that the observed decrease in I304N protein levels is due to increased turnover of the mutant protein . Interestingly , the decrease in I304N FMRP levels is much more pronounced in mice at P14 , relative to older mice ( Figure 4A and 4B ) . This correlates with the observation that there are transient alterations in the morphology of dendritic spines in Fmr1 null mice [19] . This suggests that the biochemical defect present in I304N FMRP may be compounded by a decrease in its levels during synaptogenesis , and that the phenotype may result from a combination of these effects . Several attempts have been made to assess the effect of the I304N mutation on FMRP RNA binding and function . Recombinant or in vitro translated I304N FMRPs show significantly decreased binding to ribohomopolymers or in vitro-selected RNA ligands [40] , [51] , [78] . Other studies have found that recombinant I304N FMRP produced in insect cells retained some ribohomopolymer binding , but with decreased binding to poly-U [79] . The I304N mutation in FMRP abrogates binding to high affinity in vitro selected KH2 target RNA ligands ( kcRNA ) but not RGG target ( G-quartet ) RNAs , as assessed with both full-length FMRP and isolated RNA binding domains [51] , [64] , indicating that KH-specific RNA interactions are lost in the I304N mutant in vitro . However , in lymphoblastoid cell lines derived from I304N patients , some I304N-FMRP was able to be captured on oligo-dT columns , which was interpreted as showing that I304N mRNA association was intact [25] . We also find that some I304N FMRP is retained in the void volume of the Superose 6 column in an RNase-dependent manner ( Figure 6 ) , which may be due to heterodimerization with FXR1/2P ( Figure 7A; [63] ) , or to residual RNA binding from the RGG domain ( Figure 7B ) . The conclusion that I304N FMRP KH2 domain fails to bind RNA in vivo is consistent with structural studies of several RNA-binding proteins suggesting that this mutation should affect RNA binding . Most studies of isolated protein domains ( vigilin KH6 , FMRP KH1 , and Nova-2 KH3 ) have predicted that the I304N mutation results in an unfolded KH domain , which would be expected to lead to loss of specific RNA binding . However , other KH domains harboring mutations analogous to I304N are correctly folded , including the Drosophila homolog of FMRP ( dfmr1p ) tandem KH1-KH2 [80] , and BBP/SF1 , in which RNA binding is specifically lost [81] . The first co-crystal of a KH domain—RNA complex ( Nova-RNA ) [50] , as well as a subsequent review of structures [49] , suggest that mutation of the conserved hydrophobic amino acid analogous to Ile-304 must decrease RNA binding affinity . While a consensus from these KH domain∶RNA structures is that the isoleucine mutation disrupts KH∶RNA interactions , FMRP has multiple RNA binding domains , so that RNA binding by the full-length protein may not be abrogated despite loss of KH-dependent interactions . This is consistent with our observation that I304N-FMRP in mouse brain fails to crosslink to kcRNA , but retains other activities , including the ability to crosslink to G-quartet RNA and to heterodimerize with FXR1P and FXR2P ( Figure 7 ) . While we show that the RGG box in the I304N-FMRP is still competent to bind its high affinity in vitro-selected ( G-quartet ) RNA ligand , it appears from the Superose 6 analysis that I304N-FMRP has lost most of all of its RNA interactions in vivo . We propose that RNA binding by the other RNA-binding domains of FMRP may be hierarchical , such that the KH2 domain must make proper RNA interactions for subsequent G-quadruplex binding by the RGG box to occur . Taken together these observations suggest that the I304N-FMRP mutation leads to a global loss of RNA binding in vivo , and suggest that identification of FMRP KH2-RNA targets will be of great interest . The severity of Fragile X symptoms reported in the I304N patient has led to the hypothesis that I304N-FMRP might have a dominant negative effect on its autosomal paralogs , FXR1P and FXR2P , decreasing any functional redundancy present in the absence of FMRP . We do not detect any evidence for this as the expression levels , polyribosomal association and mRNP complex sizes of FXR1P and FXR2P are unchanged in the Fmr1I304N mouse brain relative to wild type littermates . At the same time , we find that mutant protein levels vary with age , such that they are reduced ( by two-thirds ) in adult mice , but are even more markedly reduced at P14 , a time when synaptogenesis is occurring in many areas of the mouse brain , including the forebrain and cerebellum . This finding suggests that loss of FMRP activity , including but not necessarily limited to KH2 RNA binding , may play a critical role in leading to the synaptic defects evident in the mouse , and , presumably , in human patients . In addition , we find that macroorchidism in Fmr1I304N mice , while pronounced compared with wild type littermates , is no more severe than in Fmr1 null littermates . mGluR-dependent LTD in Fmr1I304N mice is equivalent to that in Fmr1 null littermates , but not enhanced . Behavioral assays give little or no indication of a more severe behavioral deficit than the Fmr1 null mouse . Taken together , these findings suggest that Fmr1I304N mice have an Fmr1 null-like phenotype , consistent with a loss of function mutation . Supporting this , the analogous I307N mutation in Drosophila dfmr1 results in a partial loss of function phenotype [77] . We propose that the severe Fragile X symptoms , including IQ below 20 , lack of verbal communication , and impressive macroorchidism observed in the I304N patient may be a result of selection bias , in that this patient may have been selected for further gene sequencing precisely due to the severity of his Fragile X phenotype . Because screening for Fragile X Syndrome is currently performed by PCR for the CGG repeat expansion , negative results may be classified as nonsyndromic mental retardation or nonspecific developmental delay , in the absence of characteristic features of Fragile X Syndrome . Although we cannot exclude that the severity of the I304N patient's symptoms may have contributions from other genetic factors , including exacerbation by his familial liver disease , we note that none of the patient's other 29 relatives affected by liver glycogenosis have mental retardation , or the neurologic and phenotypic defects found in the Fragile X patient . We cannot rule out the possibility that the I304N patient might express elevated I304N FMRP levels such that a dominant negative action exacerbates his symptoms . Nonetheless , based on our finding of decreased I304N FMRP in the mouse model and similar results from the I307N mutation in dfmr1 [77] , we infer that it is most likely that the I304N patient has lower steady state levels of neuronal I304N-FMRP . The Fmr1I304N mouse provides an additional mouse model for the Fragile X Syndrome . The most widely used model for Fragile X Syndrome , the Fmr1tm1Cgr mouse , is a complete null due to the insertion of the neo cassette in exon 5 of the Fmr1 gene . By causing loss of FMRP expression , the Fmr1tm1Cgr mutation largely recapitulates the human Fragile X Syndrome at the protein level . Nonetheless , the CGG repeat expansion , present in most human patients , is not replicated in the Fmr1tm1Cgr null mouse , and the repeat may contribute in unknown ways to the disorder ( soaking up CGG DNA binding proteins , or interfering with expression of transcripts present on the other DNA strand [8] , [9] ) . In addition , the Fmr1tm1Cgr null mouse still contains a neo-expression cassette , which has been documented in some cases to affect expression of neighboring genes and lead to confounding phenotypes . Thus as a model system , the I304N mouse genocopies the human I304N patient better than the null mouse genocopies the CGG repeat expansion . However , we appreciate that human deletions and the point mutation patient , to the extent that they share all the symptoms of Fragile X Syndrome , argue against the CGG repeat expansion itself playing a significant role in the disease , and that the I304N mutation is limited in clinical significance relative to the CGG expansion . The I304N mutation causes defective KH2-mediated RNA binding in neurons , and decreased FMRP levels , particularly in younger animals . The loss of KH2 function accounts for the dissociation of the protein from brain polyribosomes . We propose that this leads to a loss of proper translational control of FMRP mRNA targets , which in turn leads to the cognitive and behavioral deficits observed in the Fragile X Syndrome . Our observations underscore the importance of identifying FMRP KH2 RNA ligands in the mouse brain to understand the pathogenesis of the disease . Identification of a reliable and comprehensive set of in vivo RNA targets will benefit from use of the Fmr1I304N mouse model , in conjunction with the Fmr1 null [54] , Fmr1 conditional knockout [82] , and FMR1 YAC transgenic mice [53] for validation and functional studies . Finally , trials of potential clinical treatments can be tested on the Fmr1I304N mice , since they provide an additional animal model in which rescue of phenotype can be measured .
A genomic clone encoding the murine Fmr1 gene was isolated from a BAC library derived from a 129 mouse ( ES-129/SvJ BAC library , clone address 217I21 , Incyte Genomics ) . To generate an Fmr1 KH2 I304N targeting vector , a 7 . 2 kb BamHI-XhoI 5′ homology arm spanning intron 5 to intron 9 and a 1 . 9kb XhoI-KpnI fragment spanning intron 9 to intron 11 ( including exon 10 where the I304N mutation occurs , and a 3′ homology arm ( 1 . 3kb ) ) were cloned into pBluescriptIISK ( + ) ( Stratagene ) . PCR mutagenesis of the XhoI-KpnI fragment introduced the I304N mutation in exon 10 to change the sequence CTG ( Leu ) ATT ( Ile ) CAA ( Gln ) to CTT ( Leu ) AAC ( Asn ) CAG ( Gln ) ) . The two wobble mutations were introduced to create a new HindIII site for genotyping and to facilitate PCR genotyping with a mutant-specific primer . A new XbaI site was also generated in the middle of intron 10 in a region that was not conserved between the mouse and human FMR1 genes . The loxP-Auto-Cre-NeoR-loxP ( ACNF ) cassette ( from Dr . Peter Mombaerts ) was inserted in the new XbaI site . Finally , the 5′ homology arm and the XhoI- ( I304N ) - ( ACNF ) -KpnI fragment were ligated together into the pBluescript plasmid . The plasmid was linearized with NotI and used to electroporate ES cells at the Transgenic Services Laboratory at The Rockefeller University . Genomic DNA from individual colonies was digested with BamHI and screened by Southern blot analysis . The Southern probe overlapping exon 12 , which has no corresponding sequence in the mouse Fxr1 or Fxr2 gene [83] , distinguished the targeted allele , 2 . 7 kb , from wild type locus , 9 . 6 kb . Correctly targeted clones were selected for blastocyst injection and transferred to pseudopregnant females , from which germline chimeras were obtained . Fmr1tm ( I304N ) Drnl ( Fmr1I304N ) mice were bred greater than 10 generations into FVB and C57BL/6J backgrounds to generate the congenic strains FVB . Fmr1I304N and B6 . Fmr1I304N . To generate wild-type ( wt ) and Fmr1I304N mutant littermates on either background , Fmr1I304N/+ heterozygous ( het ) females were bred with wild-type ( wt ) males of the same background and male offspring were used for experiments . To generate Fmr1I304N and Fmr1 null littermates Fmr1I304N/null het females were bred with wt male mice and male offspring used . RNA from mouse tissues or polyribosome fractions was extracted using Trizol or Trizol LS Reagent , respectively , according to manufacturer's instructions ( Invitrogen ) . 10ng of in vitro translated luciferase RNA was spiked into each polyribosome fraction as a control for RNA recovery . Chloroform∶isoamyl alcohol ( 49∶1 ) was added , samples spun at 15min at 12 , 000×g , the aqueous phase collected and precipitated with ethanol at −20°C overnight . RNA was pelleted at 20 , 000×g for 20min at 4°C , washed with 75% ethanol , and dissolved in water . RNA was then RQ1 DNase ( Promega ) treated at 37°C for 1hr and underwent a second round of phenol-chloroform extraction and ethanol precipitation . Northern blots were performed following the NorthernMax-Gly protocol ( Ambion ) . Briefly , 30ug of brain RNA and 10ug of testes RNA were denatured with Glyoxal load dye at 50°C for 30min and then were separated on a 0 . 8% agarose gel in 1× Gel Prep/Gel Running buffer . RNA was transferred to a GeneScreen Plus hybridization transfer membrane ( Perkin Elmer ) in 10× SSC . 32P-labeled Fmr1 probe ( see below ) was hybridized to the membrane at 68°C for 2 hrs in QuikHyb hybridization solution ( Stratagene ) . β-actin probe was hybridized at 42°C for 1hr in ULTRAhyb-Oligo solution ( Ambion ) . Membranes were then washed with 2× SSC , 0 . 1% SDS and 0 . 1× SSC , 0 . 1% SDS at room temperature . Radiolabel was detected and quantified by PhosphorImager ( Bio-Rad ) . Fmr1 probe , complementary to the 3′UTR , was synthesized by in vitro transcription with P32-α-UTP using the MAXIscript kit ( Ambion ) according to the manufacturer's protocol . Template DNA for transcription was generated using a reverse primer that included the T7 promoter sequence ( underlined ) . F:5′TCAGCAGTATGTTTCAGTCTTTCGG 3′ R:5′TAATACGACTCACTATAGGGGAGAGTTTTCAAAGTTGAAATTCGTCATCAGG 3′ A 20nt long DNA anti-sense probe against β-actin exon 4 was 5′ end labeled with 32P-ATP with T4 polynucleotide kinase ( NEB ) and used for Northern blots . Histopathology analysis was performed by the Rockefeller University Genetically Engineered Mouse Phenotyping core facility . Four male FVB . Fmr1I304N mice , five male FVB . Fmr1 null littermates and four FVB wild-type mice were sacrificed at 10 weeks of age and tissues fixed in 10% formalin overnight and embedded in paraffin blocks . Tissue sections were deparaffinized , rehydrated , stained with hematoxylin & eosin , and visualized with a Zeiss Axioplan microscope . For testicular analysis , seminiferous tubule diameters were measured and interstitial cell numbers were counted under randomly selected 20× power fields , blind to genotype . Macroorchidism was assessed by combined weight of both testes of Fmr1I304N mice compared to that of either wt or Fmr1 null littermates at indicated ages . Measurements from multiple litters of similar ages were pooled and subjected to statistical analysis ( student's t-test ) . Both histology and testicular size measurements were performed using mice bred greater than 10 generations into the C57BL/6 background ( B6 . Fmr1 null breeding pairs were generously provided by Dr . W . Greenough , U . Illinois ) ) . B6 . Fmr1I304N/+ heterozygous female mice were shipped to Baylor College of Medicine where they were embryo rederived by mating with male C57BL/6J mice . Female offspring were backcrossed an additional generation to C57BL/6J male mice . Mice used for behavioral analysis were generated by mating these mice with B6 . Fmr1I304N/+ heterozygous females and were maintained at the same B6 backcross generation . All mice started testing between 2–3 months of age by experimenters blind to the genotype of the mice using behavioral protocols previously described [53] , [68] . Twenty-three mutant and 18 wild-type littermates were evaluated for this study . Behavioral results were analyzed using SPSS . Data were analyzed using one- and two-way ANOVA with repeated measures as appropriate . Significant interactions were analyzed using simple-effects follow-up comparisons . Levels of significance were set at p≤0 . 05 . Hippocampal slices ( 400µm ) were prepared from 30–90 day old B6 . Fmr1I304N mice and their wt or B6 . Fmr1 null littermates as described [11] , [61] . All experiments were performed blind to genotype and in the presence of the NMDA receptor antagonist D , L-AP5 ( 50 µM; Tocris ) to isolate mGluR-dependent LTD . D , L-AP5 and anisomycin were prepared fresh daily in artificial cerebrospinal fluid which consists of ( in mM ) NaCl , 124; KCl , 5; NaH2PO4 , 1 . 25; NaHCO3 , 26; MgCl2 , 1; CaCl2 , 2; dextrose , 10 . Extracellular field potentials ( FPs ) were measured in the stratum radiatum of hippocampal CA1 elicited by Schaffer collateral stimulation . mGluR-LTD was induced by application of 100µM DHPG for 5min or by pairs of stimuli ( 50 msec interstimulus interval ) delivered at 1 Hz for 20 min ( 2400 pulses; PP-LFS ) . Synaptic strength was measured as the initial slope ( 10–40% of the rising phase ) of the FP . LTD magnitude was compared at 60–70min after the onset of DHPG or PP-LFS . Slices were preincubated in antagonists or inhibitors for 20–30 min before DHPG or PP-LFS . The effects of all pharmacological treatments on LTD were evaluated by comparing interleaved control and treated slices . Independent t-tests were used to determine statistical significance . Fmr1I304N mice and their wild type littermates on the FVB background were used for determining FMRP levels by western blot . Tissues were Dounce homogenized in lysis buffer ( 0 . 5% NP-40 , 0 . 5% deoxycholic acid , 0 . 1% SDS in PBS , 50% glycerol , and 1× Complete protease inhibitor cocktail ( Roche ) ) sonicated to fully disrupt nuclei , shear nucleic acids and disrupt macromolecular complexes , and spun at 20 , 000×g at 4°C for 15min . Protein concentration was determined by Bradford assay compared with BSA standards . 50ug of protein from each sample was boiled in SDS-sample buffer and used for western analysis . The following antibodies were used throughout the work: anti-FMRP mab2160 at 1∶1000 for immunoblot ( IB ) ( Chemicon ) , anti-FMRP 2F5 at 1∶100 for IB [84] , anti-FMRP ab17722 at 1∶1000 for immunoblot ( Abcam ) , anti-FMRP 7G1-1 ascites ( Developmental Studies Hybridoma Bank ( DSHB ) , University of Iowa ) at 1∶100 for IB , also used for IP as described [85] , [86] , anti-FXR1P ML13 at 1∶10 , 000 for IB ( gift from Dr . E . Khandjian ( Université Laval , Quebec ) ) , anti-FXR2P 1G2 concentrated supernatant at 1∶100 for IB ( DSHB ) , anti-hsp90 at 1∶5000 for IB ( BD Biosciences ) , anti-gamma tubulin ( GTU-88 , Sigma ) at 1∶10 , 000 for IB , anti-ribosomal S6 protein at 1∶1000 for IB ( Cell Signaling ) , human patient serum against Nova at 1∶1000 for IB [87] , HRP-conjugated anti-His-tag at 1∶5000 for IB ( Novagen ) . HRP-conjugated anti-mouse , anti-rabbit , or anti-human IgG at 1∶10 , 000 for IB ( Jackson Immunoresearch ) . Samples were run on 8% or 4–12% gradient SDS-polyacrylamide gels and transferred to Immobilon-P membranes ( Millipore ) by standard methods . Membranes were blocked for 1hr at room temperature in 10% non-fat dry milk in western blot wash buffer ( WBWB ) ( 23mM Tris , pH 8 . 0 , 190mM NaCl , 0 . 1% w/v BSA , 1mM EDTA , 0 . 5% Triton X-100 , 0 . 02% SDS ) . Primary antibodies in 10% milk in WBWB were used during incubation for 1 hr at room temperature or overnight at 4°C . Blots were washed with WBWB 5 times for 5 min after each antibody incubation . Signals were detected by enhanced chemiluminescence ( Western Lightning detection kit , Perkin Elmer ) and quantified with a Versadoc Imaging System ( Bio-Rad ) . Purified RNA was reverse transcribed using random hexamers ( Roche ) and Superscript III reverse transcriptase ( Invitrogen ) according to manufacturer's protocols . cDNA products were amplified using SYBR green PCR master mix ( Applied Biosystems ) with 200nM of the following primers . Fmr1 1F ( spanning exon 2 to 3 ) 5′-TGAAAACAACTGGCAACCAGAGAG-3′ Fmr1 1R ( spanning exon 2 to 3 ) 5′-CAGGTGGTGGGAATCTCACATC-3′ Fmr1 2F ( spanning exon 10 to 11 ) 5′-GTCAGGAGTTGTGAGGGTGAGG-3′ Fmr1 2R ( spanning exon 10 to 11 ) 5′-GGAAGGTAGGGAACTTGGTGGC-3′ Gapdh F 5′-CATGGCCTTCCGTGTTCCTA-3′ Gapdh R 5′-GCGGCACGTCAGATCCA-3′ Luc F 5′-GCCTTGATTGACAAGGATGGA-3′ Luc R 5′-CAGAGACTTCAGGCGGTCAAC-3′ Quantitative PCR amplification was performed using a 7900HT sequence detection system ( Applied Biosystems ) at the Genomic Resource Center at The Rockefeller University . Fluorimetric intensity of SYBR green was monitored during each cycle of amplification to quantify mRNA levels . Regression curves were drawn for each sample and relative amount of mRNA was calculated from the threshold cycles using the instrument's software , SDS 2 . 0 . For expression levels in total brain , relative levels of Fmr1 mRNA were measured using the standard curve method and normalized to the internal control GAPDH mRNA . Three pairs of littermates were used for Fmr1 mRNA determination by Q-PCR . Error was calculated using the formula suggested by the ABI user bulletin , [ ( std dev for Fmr1 ) 2 + ( std dev for Gapdh ) 2]0 . 5 For polyribosome distribution , relative Fmr1 or Gapdh mRNA level in each fraction was normalized to spiked-in luciferase RNA analyzed using the ΔΔCt method . The amount of Fmr1 mRNA in each fraction was then plotted as a percentage of total Fmr1 mRNA summed over the entire polyribosome gradient . Q-PCR experiments were each repeated 2 times with two pairs of biologic replicates . Error bars reflect the technical replicates from triplicate wells in a single representative experiment from polysome gradients . Error is calculated using the formula suggested by the ABI user bulletin , [ ( std dev for Fmr1 ) 2 + ( std dev for luc ) 2]0 . 5 . Because of gradient variability from day to day they cannot be plotted together so a representative experiment is shown . Mouse brain polyribosomes were prepared essentially according to established protocols [27] , [51] . Briefly , 2 week-old mice were sacrificed by isoflurane anaesthesia and decapitation . The brain was removed and placed in ice-cold dissection buffer ( 10mM HEPES-KOH , pH 7 . 4 , 150mM KCl , 5mM MgCl2 , 100ug/ml cycloheximide ) . Cortex and cerebellum were dissected free of underlying white matter , homogenized in 1ml lysis buffer ( 10mM HEPES-KOH , pH 7 . 4 , 150mM KCl , 5mM MgCl2 , 0 . 5mM dithiothreitol , 100ug/ml cycloheximide , 1× Complete EDTA-free protease inhibitor cocktail ( Roche ) , 40U/ml rRNAsin ( Promega ) ) per brain with 12 strokes at 900rpm in a motor-driven Teflon-glass homogenizer . The homogenate was spun at 2000×g for 10min at 4°C . The supernatant ( S1 ) from the homogenized material was collected and adjusted to 1% NP-40 , incubated for 5min on ice , and spun at 20 , 000×g for 10min at 4°C . The resulting supernatant ( S2 ) was loaded onto a 20–50% w/w linear density gradient of sucrose in 10mM HEPES-KOH pH 7 . 4 , 150mM KCl , and 5mM MgCl2 . Gradients were centrifuged at 40 , 000 rpm for 2 hrs at 4°C in a Beckman SW41 rotor . Fractions of 0 . 75ml volume were collected with continuous monitoring at 260nm using an ISCO UA-6 UV detector . 400 ul of each fraction was TCA precipitated and analyzed by Western blot . A pre-packed Superose 6 Precision column PC 3 . 2/30 in a SMART system ( GE Healthcare ) was used to determine the molecular masses of protein complexes . The optimal separation range of globular proteins in this column is 5 kDa to 5000 kDa with an exclusion limit of 40 , 000 kDa . Mouse brain cytoplasmic lysates ( 0 . 3% NP-40 , 10mM HEPES , pH 7 . 4 , 150mM KCl , either with or without 30mM EDTA ) were spun over a 0 . 22um Spin-X column ( Corning ) before loading onto a Superose 6 column with a flow rate of 30ul/min . Protein profile was monitored at A280nm and fractions of 75ul were collected . Fractions were TCA precipitated for Western analysis . To calibrate the column , protein markers ( GE Healthcare ) were run and gave the following results: blue dextran ( void ≥40 , 000 kDa ) in fraction 4 , 669 kDa at the fraction 10/11 boundary , 440 kDa in fraction 13 , 67 kDa in fraction 15/16 and 13 . 7 kDa in fraction 18 . Molecular mass was extrapolated by linear regression analysis for each fraction according to the migration of these protein markers and used for identification of protein complex sizes we studied . The average MW in each fraction was: fraction 12 ( 463 kDa ) , 13 ( 261 kDa ) , 14 ( 148 kDa ) , 15 ( 83 kDa ) and 16 ( 47 kDa ) . For complete RNase digestion , recombinant RNase A and T1 ( Ambion ) were added to mouse brain lysates to a final concentration of 20 ug/ml and 10 , 000 U/ml respectively . Lysates were incubated at room temperature for 30 min before gel filtration . A 1∶1 slurry of protein A Sepharose beads ( Sigma ) was first bound to 120 ug of rabbit anti-mouse Fcγ bridging antibody ( Jackson ImmunoResearch ) for 20 minutes at room temperature , washed 3 times in 0 . 1 M phosphate buffer pH 8 . 1 , and bound to 10 ul of anti-FMRP monoclonal 7G1-1 ascites ( 5mg/ml , DSHB , U . Iowa ) . Brain cytoplasmic lysates were prepared in lysis buffer ( 0 . 5% Triton X-100 , 30mM HEPES , pH 7 . 4 , 200mM NaCl , 30mM EDTA , and Complete protease inhibitor cocktail ( Roche ) ) , by Dounce homogenization of one adult brain in 2 ml lysis buffer and centrifugation at 20 , 000×g for 10 minutes at 4 degrees , and were incubated with beads and antibodies at 4°C for 2 hrs . Immunoprecipitates were washed four times with the same lysis buffer . Sepharose beads were heated to 95° in SDS sample loading buffer and supernatants analyzed by Western analysis . 96nt long G-quartet ( GQ ) and kissing complex ( kc ) RNAs [51] , [64] were in vitro transcribed with P32-α-UTP and P32-α-GTP . RNAs were gel purified on denaturing gels and spiked into 100ul S2 brain lysate prepared as for polyribosome analysis from 2 month old mice of the indicated genotype . RNAs were incubated with the brain lysates for 15 min at room temperature and then UV crosslinked as described [88] . Lysates were then diluted with 500 ul stringent IP buffer ( 0 . 5% NP-40 , 0 . 5% deoxycholic acid , 0 . 1% SDS in PBS ) and the IP was performed as for the co-immunoprecipitation , with the exception that stringent IP buffer was both the IP and wash buffer . Immunoprecipitates were run on 4–12% SDS-PAGE , transferred to nitrocellulose membranes , and exposed by autoradiography .
|
Missense mutations in human genes provide valuable insight into the genetic causes of disease . Fragile X Syndrome ( FXS ) , a common genetic cause of autism and mental retardation , is usually caused by transcriptional silencing of the FMR1 gene . The potential importance of single patient with a missense mutation ( I304N ) in an RNA–binding domain of the Fragile X protein , FMRP , has been questioned in part because he has a confounding liver disease . We introduced the I304N mutation into the endogenous Fmr1 locus to create a mouse model of Fragile X Syndrome . We find that this mutation results in behavioral , electrophysiologic , and phenotypic features of the disease , loss of binding to RNA targets in the brain , and lower FMRP levels at a critical time during synapse formation . We conclude that loss of RNA binding and underexpression of FMRP are sufficient to cause the Fragile X Syndrome .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"neuroscience/behavioral",
"neuroscience",
"molecular",
"biology/rna-protein",
"interactions",
"physiology/neuronal",
"signaling",
"mechanisms",
"genetics",
"and",
"genomics/disease",
"models",
"neurological",
"disorders/developmental",
"and",
"pediatric",
"neurology",
"neuroscience/neurobiology",
"of",
"disease",
"and",
"regeneration"
] |
2009
|
A Mouse Model of the Human Fragile X Syndrome I304N Mutation
|
Feeding and sleep are fundamental behaviours with significant interconnections and cross-modulations . The circadian system and peptidergic signals are important components of this modulation , but still little is known about the mechanisms and networks by which they interact to regulate feeding and sleep . We show that specific thermogenetic activation of peptidergic Allatostatin A ( AstA ) -expressing PLP neurons and enteroendocrine cells reduces feeding and promotes sleep in the fruit fly Drosophila . The effects of AstA cell activation are mediated by AstA peptides with receptors homolog to galanin receptors subserving similar and apparently conserved functions in vertebrates . We further identify the PLP neurons as a downstream target of the neuropeptide pigment-dispersing factor ( PDF ) , an output factor of the circadian clock . PLP neurons are contacted by PDF-expressing clock neurons , and express a functional PDF receptor demonstrated by cAMP imaging . Silencing of AstA signalling and continuous input to AstA cells by tethered PDF changes the sleep/activity ratio in opposite directions but does not affect rhythmicity . Taken together , our results suggest that pleiotropic AstA signalling by a distinct neuronal and enteroendocrine AstA cell subset adapts the fly to a digestive energy-saving state which can be modulated by PDF .
Neuropeptides and peptide hormones transfer a wide variety of neuronal or physiological information from one cell to the other by activating specific receptors on their target cells [1] . Most if not all peptides are pleiotropic and can orchestrate diverse physiological , neuronal or behavioural processes [2 , 3] . In vertebrates , such a pleiotropic effect is especially prominent in the regulation of feeding and sleep . Many different peptides ( e . g . orexin/hypocretin , ghrelin , obestatin ) modulate different aspects of both behaviours [4 , 5] , which reciprocally influence each other [6 , 7] . The temporal pattern of neuroendocrine activity and neuropeptide release is shaped by sleep homeostasis and the circadian clock which , in turn , reciprocally affects feeding and sleep-wake cycles [7–9] . Significant progress has been made in this field during recent years . Still little characterised , however , is the neuronal architecture that enables the relevant peptidergic neurons to integrate energy status , circadian time and sleep-wake status in order to coordinate the timing of sleep , locomotor activity and feeding . Information about the output signals by which endogenous clocks provide time- and non-circadian information to relevant peptidergic cells is still limited . During the last years , the fruit fly Drosophila has become an important model for research into the regulation of feeding and sleep [10–13] . Drosophila offers advanced genetic tools , a small brain with only about 100 . 000 neurons and a quantifiable sleep- and feeding behaviour that shows characteristics very similar to that of mammals [11 , 14 , 15] . These features greatly facilitate the analysis of the neuronal and endocrine underpinnings of feeding and sleep . Like in most animals , feeding and sleep follow a circadian pattern in the fruit fly [16–18] with little characterised neuronal and hormonal pathways downstream of the central clock . Like in mammals , a number of neuropeptides have been shown to be involved in the regulation of feeding [11 , 12] or sleep [19 , 20] in Drosophila . Yet , so far , only sNPF [21–24] and likely also NPF [25 , 26] are implicated in the regulation of both feeding and sleep . Also Insulin-like peptide ( DILP ) -expressing neurons ( IPCs ) in the pars intercerebralis affect feeding and sleep , yet only feeding seems to be directly dependent on DILP signalling [27] . Recent work by Hergarden and colleagues demonstrated that neurons expressing neuropeptides of the allatostatin A ( AstA ) family regulate feeding behaviour of the fruit fly [28] . Constitutive activation of AstA cells contained in the AstA1-Gal4 expression pattern by ectopic expression of the bacterial low threshold voltage-gated NaChBac channel [29] potently inhibited starvation-induced feeding . In contrast , constitutive inactivation of AstA1 cells by expression of the inwardly rectifying Kir2 . 1 potassium channel [30] increased feeding under restricted food availability . NaChBac activation of AstA1 cells also inhibited the starvation-induced increase of the proboscis extension reflex ( PER ) , a behavioural indicator for glucose responsiveness [28] . The AstA1 expression pattern includes a large number of brain neurons plus gut-innervating thoracico-abdominal ganglion ( TAG ) neurons and enteroendocrine cells ( EECs ) in the posterior midgut [28] . This broad expression pattern is consistent with earlier described patterns of AstA-like immunoreactivity [31–34] and suggests multiple functions for AstA . Earlier work had demonstrated an effect of AstA on gut motility [35] . Two AstA receptors , DAR-1 ( = AlstR ) and DAR-2 are characterised for Drosophila [36–39] . Different genome-based phylogenetic GPCR analyses independently demonstrated their homology with the galanin receptor family of vertebrates [40–43] Using anatomical subdivision and genetic manipulation of neuronal activity , we aimed to identify AstA functions and -if possible- assign them to subsets of AstA expressing cells . Our results revealed new interconnected AstA functions that link feeding and sleep and identify AstA-expressing PLP neurons and EECs as a target of the central clock output factor PDF . Pleiotropic AstA signalling seems capable of coordinating multiple aspects of physiology and behaviour in a coherent manner to adapt the fly to a digestive energy-saving state . The functional range of AstA signalling in the fly is thus reminiscent of the pleiotropy found in mammalian galanin signalling [44–46] .
To test the specificity of AstA34-Gal4 expression in adult flies , we co-immunolabelled AstA34>GFP flies against GFP and AstA . The observed AstA immunoreactivity ( IR ) pattern was consistent with earlier descriptions [31–33] ( Fig 1 ) , and we adopted the nomenclature of Yoon and Stay ( 1995 ) . S1 Table provides a summary of the localisation of AstA34-Gal4-driven GFP expression in relation to the AstA IR . In each brain hemisphere of AstA34>GFP flies , GFP was consistently detected in two to three of the three AstA-IR PLP interneurons with somata in the posterior lateral protocerebrum ( Fig 1A and 1B ) . These cells sent a primary neurite dorsally just anterior of the calyx which typically trifurcated and then extensively arborised throughout the whole superior lateral ( SLP ) , superior intermediate ( SIP ) and superior medial ( SMP ) protocerebrum ( Fig 1A and 1B , S1 and S2 Movies ) . In the anterior-posterior axis , this large arborisation field extended from the height of the fan-shaped body to just anterior of the calyx . Furthermore , GFP was found in two to four cells per hemisphere with somata in the lateral cell body rind close to the lateral horn . These LCBR neurons were AstA immunonegative and are not contained in the AstA1-Gal4 line ( Fig 1A and 1B ) . In addition , a varying small number of AstA-IR neurons in the medulla showed generally weak GFP expression ( Fig 1A and 1C ) . In some preparations , single medulla neurons were found that exhibited a stronger GFP signal ( Fig 1C ) . In the thoracico-abdominal ganglion ( TAG ) , three pairs of AstA-IR DLAa cells within the posterior abdominal region ( [27] , Fig 1A and 1D ) sent neurites via the median abdominal nerve to innervate the hindgut and the posterior-most midgut ( Fig 1F , 1G and 1I ) . Regions with innervations include the pyloric valve and the rectal valve , which control transit of gut contents and urine from the midgut to the ileum and from the ileum to the rectum . Processes of the DLAa neurons innervating the rectum in part extend through the muscle layer ( Fig 1G ) , thus their peptide signals might target the rectal epithelium . The DLAa neurons consistently exhibited strong AstA34-driven GFP expression , while the brain neurons showed a more variable GFP labelling intensity between preparations ( see Fig 1C ) . In many preparations , one or a few variably positioned non-AstA-IR interneurons within the TAG additionally showed a weak GFP signal . Outside of the CNS , two pairs of peripheral AstA-IR neurons with somata located on the segmental nerves leading to the wings and the halteres [33] expressed GFP ( Fig 1A ) . Furthermore , GFP was detectable in most if not all AstA-IR EECs in the posterior part of the midgut ( Fig 1F–1H ) . The staining results are summarized in S1 Table . In comparison to the AstA34-Gal4 pattern , the expression pattern of AstA1-Gal4 included the following AstA-IR neurons per brain hemisphere: all three PLP neurons , 2 neurons in the superior protocerebrum , ~ 30 medulla neurons , and three neurons with cell bodies in the GNG ( gnathal ( = subesophageal ) ganglion ) thought to be important for sucrose responsiveness [28] . Thus , AstA1-Gal4 drives expression in a larger number of AstA brain neurons though it is lacking the AstA-negative LCBR brain neurons ( S1 Table ) . The expression in the TAG is identical in both AstA-Gal4 lines , while AstA34-Gal4 includes a larger fraction of AstA EECs in the midgut . A schematic summary of the expression patterns is given in S2 Fig . To test for a possible role of AstA34 cells in the control of food intake , we employed the CAFE assay [47] and measured food intake while AstA34 cells were conditionally activated by the thermogenetic effector TrpA1 . TrpA1 is a temperature sensor widely used to conditionally activate neurons by temperatures above 28°C [48 , 49] . Male AstA34>TrpA1 flies were raised on food at 20 or 22°C , and then assayed over a period of two days . At 29°C , but not at 20°/22°C , food consumption was significantly lowered in AstA34>TrpA1 flies ( Fig 2A ) . A similar reduction of food intake at 29°C was detected for AstA1>TrpA1 flies ( Fig 2B ) . This effect is not sex-specific , as a similar significant reduction in food intake was also observed in females ( S3 Fig ) . These results are consistent with a previous report showing reduced starvation-induced feeding upon constitutive activation of AstA cells by AstA1>NaChBac in a different feeding assay [28] . These findings indicate that the LCBR neurons ( lacking in AstA1 ) and AstA cells in the GNG ( lacking in AstA34 ) are dispensable to reduce food intake . Thus , activation of only the AstA34 subset appears sufficient to reduce food intake . To restrict the activation pattern further , we created tsh-Gal80; AstA34>TrpA1 ( UAS-TrpA1/tsh-Gal80; AstA34-Gal4/+ ) flies . tsh-Gal80 suppresses Gal4 expression in the thoracic and abdominal part of the CNS [50–52] , and limited TrpA1 expression to AstA34 central brain neurons and EECs ( Fig 1E and 1I ) . Thermogenetic activation of this AstA34 cell subset by a shift to 29°C was sufficient to reproduce the feeding phenotype found in AstA34>TrpA1 flies ( Fig 2C ) , indicating that the AstA neurons in the TAG and periphery are dispensable for feeding inhibition . A role for the AstA neurons in the optic lobe seems very unlikely due to their anatomy and since AstA34-Gal4 driven expression in these neurons was inconsistent and weak and comprised only few of the many AstA optic lobe neurons . Thus , we conclude that the AstA-producing PLP cells and/or EECs are sufficient to control food intake . So far , we had observed feeding inhibition upon activation of AstA cells . Inhibition of AstA1 cells by constitutive expression of UAS-Kir2 . 1 [30] has previously been reported to increase feeding under restricted food availability [28] . To exclude developmental effects due to constitutive silencing , we next conditionally manipulated AstA cells using the TARGET system [53] . At both 18°C and 30°C , tubGal80ts;AstA34>Kir2 . 1 flies showed a similar food intake as controls under non-restricted food availability in the CAFE assay ( S4 Fig ) . This suggests to us that signalling from PLP neurons or EECs is not essential for normal feeding behaviour and that PLP neurons and EECs are not core components of a feeding circuit . Rather , AstA cells modulate feeding circuits , and likely become functionally active only under specific circumstances , e . g . when flies are satiated or feeding will interfere with other behaviours . A similar situation has been found for hugin-expressing neurons in the Drosophila larva . When activated via TRPA1 , they inhibit fictive pharyngeal pumping . When silenced or ablated , fictive pharyngeal pumping is unchanged compared to controls , suggesting a modulatory role of the anorexigenic hugin pyrokinin peptide [54] . Peptides are typically co-localised with other peptides or classic transmitters [55 , 56] . To identify whether the observed feeding phenotype upon activation of AstA cells is due to AstA or a co-localised peptide/transmitter , we used AstASK4 null mutant flies generated by germline-specific CRISPR/Cas9 [57] . In contrast to controls , AstASK4 mutants are devoid of any AstA-IR in the nervous system and gut ( Fig 2E and 2F ) . We then thermogenetically activated the AstA1 neurons in an AstA null mutant background and found no difference in food uptake compared to controls ( Fig 2D ) . Similar observations were made when reducing AstA expression by RNAi in AstA34>TrpA1/ AstA-RNAi flies ( S5A Fig ) . Together , these experiments show that PLP neurons or EECs signal via AstA peptides to reduce food intake . The general lack of AstA without activation of AstA cells did , however , not reduce feeding under the experimental conditions; controls in wildtype and AstASK4 mutant background showed similar amounts of ingested food ( Fig 2D ) . Locomotor activity affects energy expenditure and consequently also appetite , and is in turn altered by hunger and feeding . We therefore asked whether activation of AstA cells affects locomotor activity . Flies were kept in small glass tubes on agar-sucrose food and their locomotor activity was monitored using the DAM system . Compared to controls , the average locomotor activity of AstA1>TrpA1 and AstA34>TrpA1 flies was strongly and significantly reduced at 29°C , but not at 22°C in both sexes ( Fig 3A and 3B , S6 Fig ) . In contrast , AstA1>TrpA1 flies were not impaired in climbing ability in a startle-induced negative geotaxis assay , independent of being fed or starved for 24h at 29°C ( Fig 3F ) , showing that the flies were not suffering from impaired locomotor ability or energy deficiency due to decreased feeding . To analyse locomotor activity in the CAFE assay , we video-monitored activity of AstA1>TrpA1 males in a slightly modified setup using Petri dishes instead of a 24 well plate . Prior to testing , flies were starved for 24h at 29°C but had free access to water . After placement into the Petri dish , we filmed pairs of flies at 29°C for 4 hours and visually categorised their behaviour ( not moving , moving , feeding ) . Fig 3C shows that AstA1>TrpA1 spent much less time moving as well as feeding compared to AstA1 x w1118 controls , with individual variations within both strains ( S7 Fig ) . Nevertheless , AstA1>TrpA1 flies were fully capable of locating the capillary and did not stay there longer than controls , which would have allowed them to feed without moving ( S7 Fig ) . We next monitored the locomotor activity of tsh-Gal80; AstA34>TrpA1 flies ( Fig 3D ) and found a reduction of locomotor activity similar to AstA1>TrpA1 flies upon thermogenetic activation . ( Fig 3A ) . Activation of PLP neurons and/or the AstA EECs seems thus sufficient to reduce locomotor activity . The inhibitory effect is again mediated by AstA peptide signalling , since thermogenetic activation of AstA cells in AstA1>TrpA1 flies in the AstASK4 null mutant background did not significantly alter locomotor activity ( Fig 3E ) . The rhythmicity and period of locomotor activity [58] was not affected by activation of AstA cells in AstA1>TrpA1 and AstA34>TrpA1 flies at 29°C and constant darkness ( Fig 4 ) . Strikingly , however , subjective evening activity was lost . ( Fig 4A and 4B ) . A general lack of AstA without activation of AstA cells did not influence locomotor activity , as controls in wildtype and AstASK4 mutant background showed similar activity levels ( Fig 3E ) . A strongly reduced locomotor activity is suggestive of abnormal sleep . Applying the widely used 5 min inactivity criterion [59] , we found that in fact thermogenetic activation of the AstA1 and AstA34 cells strongly promotes sleep , which is most apparent during the morning and evening activity peaks in both males ( Fig 5 ) and females ( S8 Fig ) . At 29°C , but not at 22°C , AstA1>TrpA1 and AstA34>TrpA1 flies showed a significant increase in both total amount of sleep and sleep bout duration ( Fig 5 ) . Thermogenetic activation of AstA1 and AstA34 cells significantly increased total sleep and sleep bout duration also under constant darkness ( Fig 4D and 4E ) , and constant light conditions known to disrupt the clock ( S9 Fig ) . Next we silenced AstA cells by constitutive expression of UAS-Kir2 . 1 [30] , yet without effect on activity or sleep ( S10 Fig ) . However , when we conditionally silenced AstA cells using the TARGET system [53] and UAS-Kir2 . 1 , sleep was significantly affected especially during the midday siesta time ( Fig 6 ) . This is in line with a significant increase in total activity ( S11A Fig ) . A similar increase in locomotor activity and decrease in sleep upon UAS-Kir2 . 1 silencing was also observable in constant darkness , while rhythmicity and period of the locomotor rhythm was not affected ( S12 Fig ) . An alternative neuronal silencer , UAS-ΔORK [60] , did also not reduce sleep when constitutively expressed ( S13 Fig ) . Under conditional expression , however , UAS-ΔORK lead to a significant increase in sleep only during the evening activity , and unexpectedly to decreased sleep during the early siesta time ( S13 Fig ) . To test for sleep intensity , we determined the arousal threshold during the day in two different assays ( Fig 7 ) . For the first assay , AstA34>TrpA1 flies were put into glass tubes as used in the DAM monitor , and kept for three days at 29°C to thermogenetically activate AstA cells . On day four , the tubes were placed onto a loudspeaker at 29°C . Five separated 5Hz sine wave stimuli were given with increasing intensity every hour during the light phase from Zeitgeber Time 1 ( ZT1 ) to ZT12 , and velocity and distance walked for 2 min after each stimulus was measured . As expected [61] , the arousal-related parameters were dynamic during the day and varied somewhat between genotypes in the controls ( Fig 7A and 7B ) . Notwithstanding , AstA34>TrpA1 flies walked on average significantly slower and covered less distance for all stimulus intensities and at all times during the light phase than controls ( Fig 7A and 7B ) . Again , this phenotype is unlikely to be caused by impaired locomotor ability since the maximum speed reached by individual flies was similar between AstA34>TrpA1 flies and controls ( S14 Fig ) . For the second assay , flies were put in small groups into Petri dishes and kept again for three days at 29°C . On day four , we monitored their activity in the Petri dishes placed on a shaker at 29°C during the light phase to better mimic the situation during the CAFE assay . The Petri dish was hourly agitated in a series of five 2s shakes with increasing speed separated by a 5 min break during which fly behaviour was manually analysed for the fraction of aroused flies after each stimulus . Again , control flies showed a dynamic arousal threshold that was higher during the afternoon "siesta" as expected ( Fig 7C , S3 Movie ) , and a distinctly smaller percentage of aroused flies was observed for AstA34>TrpA1 flies at all time points and intensities . Strikingly , the percentage of aroused flies was steadily decreasing during the course of the day and was lowest at the time of the evening peak activity ( Fig 7C ) . Sleep and feeding are interconnected behaviours , and it is interesting to ask whether flies with activated AstA cells are prevented from eating more because their locomotor activity is reduced , leading to insufficient foraging activity although flies are "hungry" . Alternatively , flies with activated AstA cells may eat less because they need less energy intake since they move less , and thus are "satiated" . To find out which scenario applies , we monitored food intake in AstA1>TrpA1 and AstA34>TrpA1flies that prior to the CAFE assay at 22°C had been kept under assay conditions for one day at 22°C and then for two days at 29°C to activate AstA signalling . Under these conditions , both AstA1>TrpA1 and AstA34>TrpA1 flies showed no feeding rebound after release from thermogenetical activation of AstA signalling ( S15 Fig ) . This suggests that flies with activated AstA signalling are not in a hunger state , and further indicates that the observed feeding phenotype is not due to impaired locomotor ability . To test this further , we monitored the locomotor activity of fed ( agarose with sugar ) and starved ( agarose without sugar ) flies with thermogenetically activated AstA neurons . Wildtype flies respond to prolonged starvation with a phase of hyperactivity , interpreted as a hunger-driven food search [62 , 63] . Likewise , AstA34>TrpA1 flies on starvation medium increased locomotor activity/reduced sleep compared to flies on food ( Fig 7D ) . This provides further evidence that flies with activated AstA cells kept on food do not feel hungry . Off food , these flies become hungry as judged by their observed hyperactivity which argues against a general locomotor impairment in flies with activated AstA cells . The same phenotype was also seen with AstA1>TrpA1 flies ( S16 Fig ) . Obviously , the sleep-promoting effect of AstA neurons can at least partially be overcome by starvation , arguing against a direct dependence between the sleep-promoting and anorexic effect of AstA cells . So far , we could show that thermogenetic activation of AstA-signalling from PLP neurons and/or EECs inhibits feeding and promotes sleep . To distinguish between these AstA cell subsets , we next aimed to further restrict the thermogenetic activation to AstA EECs only , using panneuronal elav-Gal80 [64] . To our surprise , elav-Gal80 not only efficiently suppressed GFP expression in AstA neurons , but also in EECs ( see S16C and S16D Fig ) . Since elav was reported to be specifically expressed in neurons and glia [65 , 66] , we tested for elav expression in the midgut by immunostaining with an anti-ELAV monoclonal antibody which strongly and specifically stained EECs in the midgut ( S17A and S17B Fig ) . A similar pattern was found when expressing GFP with an elav-Gal4 driver line ( S17E Fig ) . This indicates that the widely used panneuronal elav-Gal4 drivers cannot be regarded as neuron/nervous system-specific , and suggests a role for elav in EEC differentiation . A second Gal80 line used to restrict Gal4 expression to the nervous system is nsyb-Gal80 [67] . We found no nsyb>GFP expression in EECs , and tried to restrict AstA34>GFP expression to the EECs by co-expression of nsyb-Gal80 . Co-expression of Gal80 inhibited the expression of GFP in AstA neurons , but to our surprise also in the midgut EECs . In line with that , nsyb-Gal80 completely suppressed the behavioural effects observed upon thermoactivation of the AstA34 cells ( S18 Fig ) . These results caution against the assumption that Gal80 patterns always fully replicate the respective Gal4 pattern . Prospero is a EEC-specific marker for the gut [68 , 69] , but expresses also broadly in the adult CNS [70] which prevented the use of prospero-Gal4 for thermogenetic activation . Thus , we were unable to further genetically differentiate between PLP neurons and AstA EECs . During our morphological analysis ( Fig 1 ) we noticed that the PLP neurites in the superior protocerebrum make branches in the same area as the PDF-expressing small ventral lateral neurons ( sLNvs ) , a main component of the central circadian clock . The neuropeptide PDF is a major synchronisation and output factor of the circadian clock [71] which affects the timing of sleep and feeding [18 , 72] . We therefore wanted to know whether the PLP neurons represent downstream targets of circadian PDF-signalling . Confocal microscopy first showed that indeed the projections of sLNvs and PLP neurons are overlapping in the superior protocerebrum ( Fig 8A and 8B ) . While the sLNv projections represent mainly output sites [73] , the PLP neurites seem to be postsynaptic as indicated by the expression of the postsynaptic marker DenMark:mcherry ( Fig 8A and 8B ) . Using live cAMP imaging , we next asked whether PLP neurons express functional PDF receptors . Synthetic PDF was bath-applied to acutely isolated brains that expressed the cAMP sensor Epac-camps in the AstA34 neurons . A similar approach had previously been very successful to demonstrate functional PDF receptors on clock neurons [74] . The PLP neurons reacted with a fast increase in intracellular cAMP upon 10 μM PDF ( Fig 8C and 8D ) , while control applications of saline had no effect . This PDF-mediated cAMP increase appeared to be by direct activation of PDF receptors on the PLP neurons since a similar cAMP increase was also seen after blocking neuronal conduction by tetrodotoxin ( TTX , Fig 8C and 8D ) . PDF application had no effect on the PLP neurons in a PDF receptor mutant background ( han5304 [75] , Fig 8C and 8D ) . We also found that the PDFR expression reporter pdfr-myc [76] is weakly but consistently expressed in the PLP neurons ( Fig 8E ) . Only very few further neurons in that area of the superior protocerebrum were weakly myc-positive; strongly myc-positive neurons comparable in staining intensity to the sLNvs were absent in that part of the brain . These results suggest that the PLP neurons represent downstream targets of circadian PDF signalling . To investigate the functional significance of PDF-PLP neuron signalling , we first aimed to down-regulate the expression of the PDF receptor by RNAi in AstA neurons . In preliminary test , however , none of the tested VDRC or Janelia PDFR RNAi-lines had an effect on circadian locomotor activity when expressed in PDF and other clock neurons ( Pamela Menegazzi , pers . commun . ) , indicating a general lack-of-effect in these lines . We therefore switched to constitutive activation of PDF signalling by expressing membrane-tethered PDF ( t-PDF ) in AstA34 cells . A similar approach has been successfully used to study the sleep effects of calcitonin gene-related peptide/DH31 [77] . t-PDF activated co-expressed PDFR in heterologous cell culture and rescued rhythmicity when specifically expressed in clock neurons in a pdf01 mutant background [78] When expressed in AstA34 cells , t-PDF induced a significant increase in total sleep compared to Gal4/UAS controls and flies expressing a scrambled non-functional version of t-PDF ( Fig 9A , 9B , 9D and 9E ) . In accordance , total activity in AstA34>t-PDF flies was significantly reduced to about half of that of controls ( S10B Fig ) . The effect of t-PDF expression , compared to Gal4/UAS controls , was most pronounced during the evening activity when no or little native PDF is released , and small during the peak time of native PDF release in the morning hours ( [79 , 80] , Fig 9A ) . Compared to flies expressing a scrambled version of PDFR , the effect of t-PDF expression was most pronounced during the light phase , and less pronounced during the dark phase when also the PDFR-SCR control flies slept most of the time ( Fig 9D and 9E ) . This suggests that t-PDF-induced PDFR signalling activates AstA34 cells , in line with the reported activating effect of t-PDF on sLNvs [81] and that this ectopic activation is most effective when native PDF release is absent . The timing of the activity peaks was unaltered . In addition , AstA34>t-PDF flies fed significantly less than the PDFR-SCR and UAS-TRPA1 control ( Fig 9C ) , again in line with the notion that t-PDF increases the activation of AstA34 cells . No significant difference , however , was detectable for the AstA34-Gal4 control . We note that for the t-PDF-SCR expressing flies the total amount of sleep and the sleep bout duration was considerably lower than for other controls ( Fig 9B ) , mostly due to a low amount of sleep during the day ( Fig 9A ) . The observed changes in sleep after expression of t-PDFR are considerably smaller but go in the same direction than the changes observed upon activation of AstA34 cells ( Fig 5 ) , suggesting that PDF positively modulates rather than strongly activates AstA34 cell activity . To test this assumption , we thermogenetically activated the PDF-expressing sLNvs using the R6-Gal4 driver line [82] . As expected if PDF activates AstA cells , activating sLNvs increased sleep and not activity . Yet , the effect was limited to the time of morning and evening peak activity and was -again- much smaller compared to thermogenetic activation of the AstA cells ( Fig 10A ) . Total sleep and sleep bout duration over the day was not significantly altered ( Fig 10A''' ) . We cannot exclude that this mild effect is at least in part caused by co-activation of one or two large LNvs which weakly express R6-Gal4 [83] and have been shown to promote arousal [72] . Based on these results and the anatomical and imaging data , we conclude that PDF from the sLNvs positively modulates PLP neurons without affecting the phase and general timing of AstA-regulated behaviours .
Our study shows that AstA cells via AstA signalling subserve an anorexigenic and sleep-promoting function in Drosophila . In mammals , a variety of neuropeptides and peptide hormones affect both sleep and feeding [4 , 5] , and our results provide evidence that also further such peptides exist in the fly besides sNPF and possibly NPF [21 , 24 , 25] . More specifically , our results with a new AstA34-Gal4 driver line show that activation of AstA-expressing PLP brain neurons or numerous EECs in the midgut strongly reduces food intake and promotes sleep . These behavioural effects are congruent with the anatomy of these cells . PLP interneurons are well positioned to modulate sleep as they widely arborise in the posterior superior protocerebrum , a projection area of sleep-relevant dopaminergic neurons [84 , 85] , superior ( dorsal ) fan-shaped body neurons [86–88] and neurons of the pars intercerebralis [89] . AstA EECs in Drosophila are “open type” EECs [31 , 32] , possessing apical extensions that reach the gut lumen and likely express gustatory receptors [90] . AstA-expressing EECs are thus potentially able to humorally signal nutritional information from the gut to brain centres regulating feeding and possibly also sleep and locomotor activity . If AstA is involved in inhibiting feeding and promoting sleep , one could expect AstA mutants to display decreased sleep and increased feeding in the absence of any other manipulation of AstA cells . We observed , however , that a functional loss of the AstA gene did neither affect feeding nor locomotor activity under the experimental conditions with unrestricted access to a food source . This may suggest that AstA signalling is not part of a core feeding network , but represents an extrinsic modulator which becomes activated under specific yet so far uncharacterised conditions . Alternatively , as suggested by the observed difference in effect of constitutive vs . conditional electrical silencing of AstA cells , flies may be able to genetically or neuronally compensate for a constitutive loss of AstA signalling during development . In larval Drosophila , AstA inhibits midgut peristalsis and affects K+ transport [35] in order to concentrate ingested food . Together with our finding of a sleep-promoting and feeding-inhibiting effect of AstA , we propose that pleiotropic AstA signalling serves to coordinate behaviour and gut physiology to allow for efficient digestion . After food intake , AstA from the PLP neurons or EECs cause inhibition of further feeding , and -as the need for food search behaviour is relieved and nutrients need to be taken up- promotes sleep and inhibits gut peristalsis . Based on the gut content , enteroendocrine AstA is released and hormonally activates DAR-2 on key metabolic centers to tune adipokinetic hormone and insulin signalling [91] , and -at least in other insects- stimulates digestive enzyme activity in the midgut [92 , 93] . The AstA receptors are homologues of the vertebrate galanin receptors [40–43] that have pleiotropic functions [44] . When activated in specific brain areas , galanin signalling has a strong orexigenic effect [45] and has also been implicated in the control of arousal and sleep in mammals [45] . In zebrafish , transgenic heat-shock induced expression of galanin decreased swimming activity , the latency to rest at night and decreased the responsiveness to various stimuli [94] . Furthermore , the allatostatin/galanin-like receptor NPR-9 inhibits local search behaviour on food in the nematode C . elegans [95] . Similar to AstA in Drosophila [35] , galanin modulates intestinal motility and ion transport [44] . Thus , in broad terms , the involvement of DARs/galanin receptors in modulating feeding , gut physiology and arousal/sleep appears to be evolutionarily conserved . The neuronal clock network in Drosophila is intrinsically and extrinsically modulated by a variety of peptides ( sNPF , NPF , calcitonin-gene related peptide/DH31 , ion transport peptide , myoinhibiting peptides and PDF ) , which all affect sleep and locomotor activity and in part also act as clock output factors [24 , 77 , 96–100] . Our imaging results and constitutive activation of the PDF signalling pathway by t-PDF now suggest that the PLP neurons are modulated by PDF originating from the sLNv clock neurons . Unlike the peptides above , AstA from PLP neurons is outside and downstream of the central clock and seems not to modulate the clock network . Due to their anatomy and position , PLP neurons thus appear well-suited candidate cells by which clock neurons could modulate the complex cross-regulatory network regulating sleep , locomotor activity and perhaps also feeding . The rather mild effects on sleep and feeding of either t-PDF expression in AstA cells or thermogenetic activation of the sLNvs implies that this pathway is not the major output target of the central clock ( if there is any ) to modulate feeding and locomotor activity/sleep . We found no shift in the circadian period or phase of feeding and locomotory activity/sleep upon AstA cell activation , suggesting that the main function of PDF-to-AstA cell signalling is not to time the respective behaviours but to modulate their amplitude . Similar non-timing functions of PDF have been demonstrated for other behaviours , including geotaxis and rival-induced mating duration [101 , 102] . At first sight , our data suggesting that PDF activates PLP neurons to promote sleep seem to contradict earlier findings [72] . Since pdf01 mutants show increased sleep during the photophase , the arousal effect appears to be the dominant effect of PDF which is due to signalling between ventral lateral clock neurons ( LNvs ) [72] , with a major contribution of the PDF-expressing large LNvs [103] . The PLP neurons are only contacted by the sLNvs , which upon activation induced a time-specific increase in sleep , but did not increase arousal . Thus , the sLNv-PLP pathway likely represents a sleep-promoting clock output branch . Besides PDF , the sLNvs but not the lLNvs also co-localise the sleep-promoting peptide sNPF [24] . A recent report shows that hormonal PDF released from abdominal PDF neurons serves to couple the central clock with a peripheral clock in the oenocytes [104] . Furthermore , the posterior midgut is innervated by the abdominal PDF neurons [32] , and PDFR is expressed in the midgut [105] . It is thus possible that the AstA-expressing EECs represent additional PDF targets and may contribute to the PDF-related effects of AstA cells . In conclusion , the lack of effect on feeding upon AstA cell silencing under non-restricted food availability and an unaltered circadian locomotor rhythmicity after AstA cell silencing suggests that AstA signalling is neither a primary signal in feeding regulation nor in the clock output pathway timing rhythmic behaviour . Rather—like mammalian galanin signalling [45]- it seems to be one out of several modulatory pathways that allow to adapt the intensity of feeding and locomotor activity/sleep to specific physiological or environmental conditions . For example , decreased locomotor activity to save energy and increased digestion efficiency to maximise energy uptake may be most important during restricted food conditions , at which AstA cell silencing leads to increased feeding [28] . While our results allow now to raise such speculations , it is clear that more research is needed to reveal the conditions at which AstA signalling is functional and the modulatory PDF input is strongest .
Following strains were used: w;AstA1-Gal4 [28] , kindly provided by D . Anderson , Caltech , CA , USA ) , w;tsh-Gal80/CyO ( kindly provided by J . Simpson ) , elav-Gal4 ( Bloomington Stock Center ) , elav-Gal80 [64] , kindly provided by LY and YN Jan ) , w;nsyb-Gal80 [67] , kindly provided by Stephen F . Goodwin—originally from J . Simpson ) , prospero-Gal4 ( kind gift of J . F . Ferveur ) , nsyb-Gal4 ( kindly provided by T . Langenhan ) , 386y-Gal4 and w;;Pdfr-myc ( [76 , 106] , kindly provided by Paul Taghert ) , UAS-Dcr-2 ( VDRC Stock #60007 ) UAS-AstA-RNAi ( VDRC Stock #103215 KK ) , w;UAS-DenMark [107] , kind gift of Bassem Hassan ) , UAS-Epac1camps [74] , 10xUAS-IVS-myr::GFP ( [108] , Bloomington Stock Center ) , UAS-tethered-PDF ( UAS-t-PDF-M6a containing one transgene copy , and control UAS-t-PDF-SCR A2 [78] , kindly provided by Joel Levine ) , w;UAS-TrpA1 ( Bloomington Stock Center ) , w;UAS-Kir2 . 1 ( [30] , w;;UAS-ΔOrk-ΔC1 and w;;UAS-ΔOrk-ΔNC1 ( [60] , Bloomington Stock center ) , UAS-tubGal80ts [53] han5304 ( [75]and Canton-S wildtype and w1118 for control crossings ( all from Bloomington Stock Center ) . Flies were kept on standard Drosophila medium ( Supplementary file 1 ) at a 12:12 h light-dark cycle ( LD , in which lights-on is defined as ZT0 and lights-off as ZT12 ) and 25°C , except for the crossings used in TrpA1 experiments , which were kept at 20 or 22°C . The putative D . melanogaster allatostatin A promoter region was amplified from genomic DNA by PCR using three different primer sets that amplified 1 . 03 kb , 2 . 05 kb and 2 . 74 kb upstream of the transcription initiation site ( see S1 Text ) . The resulting PCR products were cloned into pCR-TOPO . The inserts were digested with MunI and BamHI , gel purified and exchanged with the Akh promotoer in the pAkh-Gal4 vector [109] . The resulting P{pAstA-Gal4} plasmids were injected into Drosophila embryos by BestGene Inc . ( Chino Hills , CA , USA ) and at least 5 independent P-element transformant lines per construct were obtained . While the short 1 . 03 kb promoter fragment failed to direct GAL4 expression to AstA-immunoreactive ( IR ) cells , longer 2 . 05 and 2 . 74 kb promoter fragments lead to GAL4 expression in varying subsets of AstA-IR cells in the larval CNS and midgut ( S1 Fig ) . We chose the 2 . 74 kb promoter line AstA34-Gal4 for our experiments , since it showed the most restricted and AstA-specific cellular distribution among the different 2 . 74 kb promoter lines generated by P element transposition ( S1 Fig ) . The generation of AstA mutants by germline-specific expression of Cas9 and guide RNA ( gRNA ) transgenes [57] was already described [91] . Mutant stocks were established from two alleles , AstASK1 ( used by [91] ) and AstASK4 ( w1118;;AstASK4 used throughout this study ) , in which the start codon of the AstA gene is removed . Tissue of feeding 3rd instar larvae or adult flies ( approx . 1 week after eclosion at 25°C ) was dissected in HL3 . 1 solution [110] and fixed in 4% PFA/PBS ( pH 7 . 2 ) at room temperature for 45 min ( guts and larval CNS ) or 90 min ( adult CNS ) . After several washes with PBT ( = PBS with 0 . 3% Triton X ) followed by an overnight blocking step with PBT containing 10% normal goat serum at room temperature , the tissue was incubated in primary antibody solution on a shaker for 1d at 4°C , then several hours at room temperature . Primary antibodies were diluted in PBT containing 3% normal goat serum . 1d of washing steps with PBT followed , after which the samples were incubated with secondary antibodies diluted 1:300 in PBT containing 3% normal goat serum . Samples were again washed several times with PBT , then twice with PBS and finally mounted onto microscope slides using 80% glycerol/20% PBS . Images were acquired with a Leica TCS SPE or SP8 confocal microscope ( Leica , Wetzlar , Germany ) . Fiji [111] was applied for maximum intensity projection and contrast enhancement . Figures were generated with Adobe Photoshop CS2 . Primary antibodies used were a mouse anti-GFP IgG mAb ( 1:100 , A11120 , Invitrogen GmbH , Karslruhe , Germany ) , a rat anti-ELAV mAb ( 1:100 , 7E8A10 , developed by GM Rubin , obtained from the Developmental Studies Hybridoma Bank , University of Iowa , IA , USA ) , monoclonal rat anti-mCherry ( 1:1000 , Molecular Probes , Frederick MD , USA ) , mouse anti-Myc-tag mAb ( 1:1000 , 9B11 mouse , mAb New England Biolabs , Frankfurt , Germany ) and a polyclonal rabbit antiserum directed against Dippu-AstA-7 ( 1:2000 , [112] , Jena Bioscience GmbH , Germany ) which recognizes the C-terminal YXFGL-amide of AstA peptides including that of Drome-AstA-1–3 [113] . Alexa Fluor 532 and 647- or DyLight 488-conjugated IgG ( H+L ) secondary antibodies were purchased from Dianova GmbH , Hamburg , Germany . The CAFE protocol followed [47] . 4–5 old male or female flies were anesthetized on ice and transferred into 24-well plates ( 1 fly per well ) containing several small holes in each well to allow for air exchange . A piece of moist filter paper was added to each well to provide the flies with water separately from the food . Capillaries ( 5 μl glass capillary pipettes , Megro GmbH & Co . KG , Wesel , Germany ) were filled with liquid food and one capillary per well was inserted through a hole in the lid of the well plate so that the bottom was easily accessible to the fly . Food capillaries in wells without flies were used to control for evaporation . The amount of evaporated liquid in these control capillaries was substracted from the other capillaries in the capillary assays . The plates were put into an airtight , humid container and placed into an incubator with a 12:12 h LD at 22°C or 29°C . Liquid food was prepared fresh every day and contained: 5 . 4% sucrose , 3 . 6% yeast extract ( BioChemica , AppliChem , Darmstadt , Germany ) and 0 . 03% BPB ( Bromophenol blue sodium salt , electrophoresis grade , AppliChem , Darmstadt , Germany ) ( all m/v ) in ultrapure water . Capillaries were exchanged each day at the same time . Food consumption was not measured for the first day to give the flies some time to acclimatize to the change of environment and food . Values measured for day 2 and 3 ( descent of the meniscus ) were summed up for each fly . Four to five days old flies of each genotype were kept for 24h at 22°C on normal food , 29°C with normal food or at 29°C with water only . For each trial , 10 male flies were transferred to a 50ml falcon tube . These tubes were tapped gently on the table , and the number of flies which climbed over an 8 cm marker within 10 seconds was calculated . For each experiment , this was repeated 10 times . Drosophila Activity Monitors ( DAM , TriKinetics Inc . , Waltham , MA , USA ) were used to measure locomotor activity . 4–5 days old adult males or females were transferred to separate glass tubes containing an agar-sucrose food medium ( prepared from 2% agar and 4% sucrose in ultrapure water by brief boiling ) , after which the tubes were closed with foam plugs . The tubes were inserted into holes in the monitor and centered . As a fly walked back and forth within its tube , it interrupted an infrared beam that crossed the tube at its midpoint . Light beam interruptions were counted for individual flies at 1-min intervals as a measure of fly activity . Flies were monitored under a 12:12 h LD with 365 lux light intensity at 22°C and subsequently at 29°C; average minute-by-minute activities during the day were calculated for both conditions . Activity and sleep data was analysed using ActogramJ [114] and a custom-made Excel macro by Taishi Yoshii [115] . Flies were kept in a 29°C incubator , LD12:12 , for 3d prior to the experiments . Two different arousal setups were used , with flies kept in tubes or Petri dishes , respectively . Tube assay: During the assay , each fly was individually housed in a 65mm glass tube ( Trikinetics ) . For each experiment , we used 5 tubes for each genotype , which were laid on a loudspeaker ( VISATON WS 25E , 8Ω ) . On the 4th day from ZT1 to ZT12 , stimuli of increasing intensity between 0 . 4 and 2 . 0 volt ( steps of 0 . 4 Volt ) were consecutively delivered and behaviour was recorded by a camera ( PENTAX TV LENS 25mm 1:1 . 4 ) at 1 Hz using IC Capture 2 . 2 software . Stimuli were generated with a PHILIPS PM 5139 function generator coupled to a TAURUS A2100 stereo amplifier and a loudspeaker to generate a 5Hz sine wave to wake up the flies . The interval between the individual stimuli was between 5–8 min . Average walking velocity ( cm/s ) and stimulus-induced walking distance for a 2 min window after each stimulus was analysed with MetaMorph version 7 . 8 . 0 ( Molecular Devices , Sunnyvale , CA , USA ) from ZT1 to ZT 12 . Petri dish assay: 5 flies were housed in a Petri dish filled with 2% agarose containing 4% sucrose on a shaker ( Edmund Bühler KL-2 , Tübingen , Germany ) . On the 4th day from ZT1 to ZT 12 , five mechanical shakes with increasing speed ( 50 , 100 , 200 , 300 and 400 rpm ) were delivered for 2 seconds . The interval between the individual stimuli was between 5–8 min . Fly behaviour was recorded at 1 frame/s for 12h and locomotor activity was measured by eye , then arousal thresholds ( percentage of flies moving ) were calculated for each stimulus . The ratiometric cAMP sensor UAS-Epac1camps [116] was expressed under the control of the AstA34-Gal4 driver line . Homozygous 5–7 days old male w;UAS-Epac1camps;AstA34-Gal4 flies were freshly dissected in cold Hemolymph-like saline ( HL3 [117] ) and isolated brains were mounted with the posterior surface up on the bottom of a Petri-dish containing HL3 . Brains were allowed to recover from dissection for 15min prior to imaging . Live-imaging was conducted using an epifluorescent imaging setup ( Zeiss AxioExaminer D1 , Specta-X hybrid solid state LED source , or a VisiChrome High Speed Polychromator System with a ZEISS Axioskop2 FS plus , Visitron Systems GmbH , Puchheim , Germany ) equipped with a 40x dipping objective ( Zeiss 20x/1 , 0 DIC M27 ) . Central brain AstA neurons were brought into focus and regions of interest ( ROIs ) were defined on single cell bodies using the Visiview Software ( version 2 . 1 . 1 , Visitron Systems , Puchheim , Germany ) . Time lapse frames were imaged with 0 . 2Hz by exciting CFP . CFP and YFP emissions were separately recorded with sCMOS cameras ( pco . edge 4 . 2 . , PCO AG , Kelheim , Germany , connected via a Cairn TwinCam ) or with a CCD-camera ( Photometrics , CoolSNAP HQ , Visitron Systems GmbH using a beam splitter ) . After measuring baseline FRETs for 100s , substances were bath applied drop-wise between recording seconds 100 and 110 . PDF peptide was synthesized by Iris Biotech GmbH ( Marktredwitz , Germany ) and was applied in a concentration of 10μM in 0 . 1% DMSO in HL3 . The water-soluble forskolin derivate NKH477 served as positive control in a concentration of 10μM , while HL3 alone was applied as negative control . Both negative and positive controls also contained 0 . 1% DMSO . For tetrodotoxin ( TTX ) treatments , brains were incubated for 15min in 2μM TTX in HL3 prior to imaging and substances were coapplied together with 2μM TTX ( as described in [118] ) . Intensity data for CFP and YFP emissions of each ROI were exported into Excel and inverse FRET ( iFRET ) was calculated over time according to the following equation: iFRET = CFP/ ( YFP-CFP*0 . 357 ) [74] . Thereby , raw CFP and YFP emission data were first background corrected and YFP data were further corrected by subtracting the CFP spillover into the YFP signal , which was determined as 35 . 7% of the CFP signal . Individual neuronal traces were finally normalized to baseline and were averaged for each treatment . Maximum iFRET changes were quantified for each individual neuron , then averaged for each pharmacological treatment and statistically compared . Plotting and statistical analysis were performed using OriginPro 9 . 1G and the R environment ( http://www . r-project . org/ ) . One-way ANOVA with post-hoc Tukey's HSD tests were applied if criteria for normal distribution ( Shapiro-Wilk normality test , p > 0 . 05 ) and homogeneity of variances ( Levene's test , p > 0 . 05 ) were met , otherwise Kruskal-Wallis and post-hoc Mann-Whitney U tests ( with Holm correction ) were applied . Exceptions are stated in the figure legends .
|
Feeding and sleep are fundamental behaviours that are controlled by diverse neuropeptides . While feeding is associated with wake periods , sleep prevents feeding . Both feeding and sleep are timed to specific parts of the day by internal clocks , presumably to optimise behaviour and metabolic processes . We investigated the functions of Allatostatin A ( AstA ) peptides in the fruit fly . AstA is produced by neurons as well as by endocrine cells in the midgut epithelium . Thermogenetic activation of subsets of AstA-producing cells in the brain and midgut revealed that AstA affects both feeding and sleep in opposite directions: feeding is reduced by AstA signalling , while sleep is promoted . Others could previously show that insect AstA also inhibits gut motility and release of digestive enzymes from the gut . An attractive conclusion is that AstA signalling helps to put flies in a digestive energy-saving state . Interestingly , a set of six AstA-expressing PLP neurons are in close contact to neurons central to the circadian clock network , and express functional receptors for the clock output signal PDF . This opens the possibility that PLP neurons are at the interface between clock , feeding and sleep—a hypothesis that needs to be tested in the future .
|
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2016
|
Allatostatin A Signalling in Drosophila Regulates Feeding and Sleep and Is Modulated by PDF
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Seminoma is a subclass of human testicular germ cell tumors ( TGCT ) , the most frequently observed cancer in young men with a rising incidence . Here we describe the identification of a novel gene predisposing specifically to seminoma formation in a vertebrate model organism . Zebrafish carrying a heterozygous nonsense mutation in Leucine-Rich Repeat Containing protein 50 ( lrrc50 also called dnaaf1 ) , associated previously with ciliary function , are found to be highly susceptible to the formation of seminomas . Genotyping of these zebrafish tumors shows loss of heterozygosity ( LOH ) of the wild-type lrrc50 allele in 44 . 4% of tumor samples , correlating with tumor progression . In humans we identified heterozygous germline LRRC50 mutations in two different pedigrees with a family history of seminomas , resulting in a nonsense Arg488* change and a missense Thr590Met change , which show reduced expression of the wild-type allele in seminomas . Zebrafish in vivo complementation studies indicate the Thr590Met to be a loss-of-function mutation . Moreover , we show that a pathogenic Gln307Glu change is significantly enriched in individuals with seminoma tumors ( 13% of our cohort ) . Together , our study introduces an animal model for seminoma and suggests LRRC50 to be a novel tumor suppressor implicated in human seminoma pathogenesis .
Human testicular germ cell tumors ( TGCT ) [MIM 613190] affect 1 in 500 Caucasian men . Current clinical classification recognizes five main subcategories with diverse clinical manifestations , genomic constitution and pathology [1] . TGCTs have their origin in the oncogenic counterparts of cells derived from the embryonic stage of the germ lineage . So-called Type II TGCTs , which are the most predominant tumor types diagnosed in Caucasian men aged 20–40 , derive from primordial germ cells ( PGC ) /gonocytes that have become blocked in their maturation and form carcinoma in situ ( CIS ) cells [1] . Depending on incompletely understood factors these form the uniform pathology seminoma , which is considered the default tumor type developing from CIS . Alternatively , CIS cells can also develop into non-seminoma , a more mixed tumor spectrum that includes characteristics of undifferentiated stem cells , which are expected to arise in part through epigenetic reprogramming . An overview of the development of various TGCT subtypes is provided in Figure S1 [1] , [2] . The incidence for seminomas , representing the major component of TGCT type II , is rising [1]; nevertheless , there are sparse data describing genetic alterations functionally contributing to seminoma development , and previously described mammalian models did not have sufficient analogy to human seminoma [1] . In recent years , zebrafish have emerged as an established and tractable vertebrate animal model that contributes to current oncology research [3] . Many basic developmental processes are well conserved from fish to mammals , including germ line development [4] and earlier described TGCT isolated from zebrafish seem to resemble human TGCT characteristics [5] . We previously described a loss-of-function mutation in zebrafish lrrc50Hu255h , of which homozygous mutants display the ciliopathy phenotypes of primary ciliary dyskinesia ( PCD ) ( CILD1; MIM 244400 ) in humans [6] . An essential function in proper cilia function has now been attributed to LRRC50 across eukaryotic taxa in organisms ranging from Chlamydomonas and zebrafish to humans ( CILD13; MIM 613190 ) [6]–[9] . Here , we describe the susceptibility to tumor formation of heterozygous lrrc50Hu255h zebrafish and suggest a tumor suppressor role for LRRC50 ( alias DNAAF1; dynein assembly factor 1 ) in the specific development of the TGCT subtype seminoma in both zebrafish and man .
Whereas homozygous lrrc50 ( −/− ) mutants develop lethal defects during larval development due to severe ciliopathy phenotypes [6] , [10] , heterozygous lrrc50hu255h ( +/− ) zebrafish develop into adulthood without apparent defects . Noticeably , we observed unexpectedly high tumor prevalence in the male population ( n = 30 ) during the second and third year of life , with a penetrance exceeding 90% ( Figure 1A ) . Testes are the predominant tissue for tumor formation ( Figure 1B ) , although sporadically tumors were also observed in other tissues ( Figure 1A , and non-TGCT examples in Figure S2A , S2B ) . Histological analyses ( n = 11 ) indicate that females develop no gonadal abnormalities ( Figure S2C ) . The recovered tumors display uniform loss of macroscopic normal testicular architecture ( Figure 1C ) . The tumors are well encapsulated and do not appear to be metastatic; upon tumor isolation no abnormal visceral organs were observed . Analysis of 104 randomly selected age-matched male zebrafish ( 24–44 months old ) that had similarly been generated through N-ethyl-N-nitrosourea ( ENU ) mutagenesis showed a common background level ( 16 . 3% ) of TGCT formation ( Figure 1A ) . Wild-type zebrafish adult testes are composed of few SPG/gonocytes and large numbers of differentiated germ cells or mature sperm ( Figure 2A , high resolution image in Figure S3A ) [11] . The recovered tumors generally present severely reduced or total absence of end-stage differentiated germ cells and an increase of cells morphologically resembling early spermatogonial cells ( SPG ) ( Figure 2A ) . Three testes from fish without externally evident tumors ( Figure 1A ) morphologically contained increased numbers of both pre- and post-meiotic cells that most likely represents hyperplasia , but might additionally suggest that population expansion precedes tumorigenesis ( Figure S3B ) [12] . Differentiated spermatogonia typically remain interconnected through a stabilized intercellular bridge ( forming a syncytium ) , licensing unbound exchange of cytoplasmic components resulting in population synchronization [13] . Immunohistochemistry ( IHC ) with mitotic marker phospho-Histone H3 ( pH3 ) in wild-type testis occasionally stains single stem cells -the only germ cell type dividing as a single cell- and marks clutches of synchronously dividing differentiated cells , while the tumors are predominantly composed of single proliferating cells ( Figure 2B ) . Upon quantification ( Figure S4A ) , we observed significantly increased numbers of individual proliferating cells ( P = 0 . 0025 , non-parametric Mann-Whitney test ) , suggesting that these tumors are highly proliferative and enriched for single cells . The zebrafish tumors consist of a morphologically uniform tumor cell population , which is most analogous to human seminoma . A human seminoma-specific marker is HIWI [14] , whose zebrafish ortholog Ziwi is described [15] to have similar elevated expression in early germ cells and reduced diffuse expression in differentiated germ cells ( Figure 2C ) . Ziwi IHC on lrrc50Hu255h tumors shows strong staining in the majority of cells with the exception of somatic tissue . Staining with meiosis marker γ-H2Ax shows various stages of differentiated germ cells in wild-type , but almost complete absence in the tumors , indicating a pre-meiotic population of cells ( Figure 2D , 2E ) [16] . More in-depth studies would be useful to correlate the tumor characteristics of our zebrafish tumors with human seminomas , such as staining with the additional TGCT markers for early germ cells Nanog and Oct3/4 , in order to affirm a seminoma analogy more accurately . Nevertheless , the zebrafish tumors have a severe early germ cell differentiation defect , and based on both the morphology and the combination of the various histological analyses of lrrc50Hu255h tumors we suggest an initial specific classification as seminoma is supported . We next interrogated the somatic loss of the wild-type lrrc50 allele in zebrafish tumorigenesis by genotyping the Hu255h ( c . 263T>A/p . Lys88* ) nonsense mutation and LOH was found in 44 . 4% of tumors ( n = 4/9 ) ( Figure 2F ) ; direct sequencing of the coding regions of the lrrc50 locus revealed no additional mutations . Tumors lacking evident LOH could potentially reflect the presence of wild-type tissue and/or variable tumor progression . When tumor genotypes and tumor progression are compared based on morphology and Ziwi expression , LOH strongly correlates with samples where sperm content is relatively low and there is an abundance of early germ cells ( Figure S4B ) . Alternatively , undetected inactivating lesions ( e . g . promotor/intronic sequences , large chromosomal deletions ) , epigenetic alterations , or unrelated background tumors could obscure genotypic analysis . Although we cannot exclude an underlying haploinsufficient mechanism , we suggest that zebrafish lrrc50hu255h seminoma progression is consistent with biallelic inactivation . We next conducted LRRC50 mutational analysis in a collection of 30 human seminomas and five spermatocytic seminomas ( the latter as controls ) ( Table 1 ) . We identified one individual ( SE14 ) diagnosed with a stage-II seminoma and a contra-lateral stage I seminoma within a six-year interval; both tumors have a nonsense c . 1462C>T/p . Arg488* mutation in exon 8 ( Figure 3A , 3B , Table 1 ) . Corresponding peripheral blood ( PBL ) revealed a heterozygous germline c . 1462C>T/p . Arg488* ( TMP_ESP_16_84203896 ) LRRC50 mutation , which is extremely rare and identified in 0 . 008% ( 1/12 , 999 ) of chromosomes in the NHLBI Exome Variant Server ( NHLBI ESP , http://evs . gs . washington . edu/EVS/ ) . Both tumor DNA chromatograms show a consistently stronger mutant peak compared to PBL , indicating biallelic loss in at least a subset of tumor cells , or presence of non-tumorous cells ( somatic tissue , lymphocytes ) . Analysis of SNPs in closest proximity to the mutation , rs17856705 and rs2288020 , showed perfect heterozygosity in both seminomas and PBL , supportive of a localized LOH event . Accordingly , IHC staining of SE14-tumor sections with α-LRRC50 indicates no detectable protein expression , whereas IHC on rete testis ( non-tumorous normal control tissue ) from SE14 confirms presence of LRRC50 in ciliated somatic tissue and antibody specificity ( Figure 3C ) . In normal testis LRRC50 is expressed in SPG and spermatocytic cells and notably appears to localize to structures resembling cilia ( Figure 3C ) . Cilia have not previously been demonstrated in early germ cells . To investigate the cilia-like structures in more detail , immunofluorescent staining and confocal microscopy was performed on 6 normal testes obtained from autopsies of men ranging from 33–43 years of age . Not only did we observe cilia on spermatogonia upon staining for specific ciliary marker detyrosinated tubulin , but co-staining α-LRRC50 with another established cilia marker , acetylated-α-tubulin , confirms LCCR50 localization to the axoneme of the cilium . Furthermore , ciliary LRRC50 was observed in both somatic tissue cells of the seminiferous tubule ( red arrows and insert ) and germ cells lining the tubular epithelium ( white arrows and higher resolution images ) ( Figure 3D ) . Pedigree analysis of the proband SE14 ( Figure 3E ) revealed two first cousins who died of seminoma as teenagers ( samples unavailable ) , suggestive of an underlying genetic predisposition . The presence of familial TGCTs and previous diagnosis with seminoma are risk factors for the formation of contra-lateral TGCT [17] . Therefore , we screened LRRC50 sequences in 15 TGCTs with a known familial incidence ( Table 1 ) . We identified one sample ( fTGCT6 ) harboring a heterozygous c . 1769C>T/p . Thr590Met missense mutation ( Figure 3A , 3F , Table 1 ) , predicted to be damaging by PolyPhen-2 [18] . This is a rare SNP ( rs34777958 ) not detected in an ethnically matched male control group ( n = 100 ) , and is present in 1 . 15% ( 150/12 , 850 ) of chromosomes in the NHLBI ESP . Additionally , genotype data in dbSNP137 showed that Thr590Met is not present in homozygosity in the NHLBI ESP cohort suggesting that it is a deleterious change likely under purifying selection . Patient fTGCT6 and his monozygotic twin brother both developed seminoma . Again , the mutant chromatogram is stronger in the tumor than in PBL , suggesting LOH . In the total seminoma population ( n = 38 ) we identified a significantly enriched , heterozygous , conserved mutation , c . 919C>G/p . Gln307Glu ( n = 5 , 5/76 alleles , P = 0 . 0013 , Fisher's exact test ) , potentially associated with seminoma as it is absent in a healthy male control group ( n = 100 , 0/200 alleles ) ( Table 1 , Table 2 and Figure 3A , 3F ) . We sequenced the entire coding sequences of the LRRC50 gene ( primer sequences provided in Table S2 ) in these samples but observed no additional exonic mutations , apart from frequently occurring SNPs without predicted pathogenicity , excluding compound heterozygosity . The Gln307Glu allele is present 2 . 9% ( 375/12625 ) in the ESP cohort , however we cannot exclude the possibility that some ESP males may have been affected with seminomas . To test the functional consequences of Thr590Met and Gln307Glu on protein function , an in vivo complementation approach was employed in zebrafish . Since maternally-derived WT lrrc50 mRNA can still be detected in lrrc50hu255h mutants early in development [6] , we opted to use transient morpholino ( MO ) -induced suppression designed to block maternal and embryo-derived lrrc50 translation . We have previously shown that in addition to the PCD and renal cystic phenotypes of lrrc50 mutants , transient MO-induced suppression of lrrc50 gives rise to gastrulation phenotypes in mid-somitic embryos , which can be rescued by wild-type ( WT ) capped human LRRC50 mRNA ( Figure 4A , 4B , scoring shown in Table S1 ) [19] . Here , we test LRRC50 mRNA harboring either Thr590Met or Gln307Glu missense mutations to rescue MO-induced gastrulation defects . Whereas co-injection of WT message with MO results in a significant rescue in comparison to MO alone ( P<0 . 0001; c2 ) , embryo batches injected with either missense change resulted in no significant rescue suggesting that both variants are functional nulls in this assay ( Figure 4B , scoring shown in Table S1 ) . Importantly , mutant LRRC50 message injected alone did not produce a significantly different phenotype from that of WT mRNA . To corroborate these findings , two dimensional morphometric analysis of the gastrulation defects are conducted . We labeled anatomical landmarks of 9-somite stage embryos with a cocktail of krox20 , pax2 , and myoD riboprobes , and measured the ratio of the width spanning the fifth somite counted from the anterior end of the embryo versus the length from the first to the last appreciable somite ( Figure 4C , 4D , scoring shown in Table S1 ) . Consistent with the in vivo scoring data , the measurements capturing the gastrulation defects of lrrc50 morphants were statistically indistinguishable from those of either of the two mutant rescue batches ( n = 9–13 embryos/batch ) , substantiating further the notion that both changes are detrimental to protein function . Current knowledge of LRRC50 function is limited to ciliary motility and ciliogenesis [6]–[10] , [ 20] , but lacks molecular detail . We therefore used immunofluorescence ( IF ) and four polyclonal LRRC50 antibodies from different companies to characterize the protein . In serum-starved ciliated RPE-hTERT cells , we confirmed endogenous localization to the basal body ( Figure 5A ) [6] , [7] , [20] , [21] . Moreover , LRRC50 maintains centrosomal association throughout the cell cycle and temporarily localizes to the midbody ( Figure 5B , 5C ) . Midbody localization is manifested by multiple centrosome/basal body-related proteins [22]–[25] , and LRRC50 , structurally and dynamically , closely resembles a specific subset of LRR-proteins sharing multiple characteristics and cellular localization patterns ( Figure S5A ) [26] . Intriguingly , we observed that LRRC50 also associates with condensed chromosomes ( Figure 5D ) , reminiscent of the dynamic localization exhibited by perichromosomal sheath proteins ( Figure S5B ) [27] . Similarly , LRRC50 mRNA expression is subjected to a stringent cell cycle regulation ( Figure 5E , FACS profiles presented in S6A ) . Analysis of Lrrc50 mRNA expression in a mouse cDNA library of developing embryonic stages and adult tissues shows high expression levels in the ciliated tissues testis , lung and ovary , but also in highly proliferating intestinal tissue ( Figure 5F ) . In RPE-hTERT cells we observed increased LRRC50 expression upon serum starvation , which promotes cell cycle exit and initiation of ciliation [28] ( Figure S6B ) . Collectively , the expression and localization data confirms the ciliary role of LRRC50 , but suggests there may be additional functions other than cilia regulation ( Figure S6C , summarizing model in Figure S7 ) .
In this manuscript we characterize a novel vertebrate model for human seminoma associated with biallelic inactivation of lrrc50 in at least 44 . 4% of tumors tested . We translated this finding to humans and identified pathogenic germline LRRC50 mutations in two human seminoma pedigrees that had at least partially lost expression of the wild-type allele in their tumors . In addition , a significant enrichment of a pathogenic Gln307Glu change in sporadic seminomas ( 13% of cases ) was identified , which is absent from a healthy control population , and low in the general population . Although functional evidence indicates that Gln307Glu is detrimental to protein function , population frequency data suggests that in homozygosity , it is likely not sufficient to cause PCD when inherited in the germline ( 0 . 001% of the ESP cohort is homozygous for this change ) . However , in the context of seminoma , this change potentially represents a significant genetic risk factor . Wild-type zebrafish have been previously described to be susceptible to the formation of TGCTs upon advanced age [29] , [30] , however the etiology for this is undetermined . Similarly , zebrafish derived from genetic screens typically show seminoma development upon advanced age; one large-scale study including 10 , 000 zebrafish determined a background percentage of 5% in two year old zebrafish , of which nearly 50% were diagnosed as seminomas [31] . One other study of genetic instability ( gin ) zebrafish mutants between 30–34 months old identified a 28% tumor incidence compared to 5% in wild-type animals , and seminomas are observed in ∼20% of the gin mutants [12] . In line with these results , we identified a 16 . 3% background incidence of seminoma formation in 104 male zebrafish derived from N-ethyl-N-nitrosourea ( ENU ) -based mutagenesis screens ( Figure 1A ) . Of interest , genetic mutant zebrafish lines are typically more susceptible to develop a different tumor spectrum , most notable malignant peripheral nerve sheath tumors ( zMPNST ) ( Figure S2A ) , as has been described for p53 , ribosomal protein mutants and genomic instability mutants [32] , [33] . The recently described mutant Alk6b zebrafish are similarly predisposed to GCT formation; of interest , tumor formation occurs earlier in life in this genetic model . The introduced loss-of-function Alk6b mutation fails to activate BMP target genes through downstream nuclear p-SMAD1/5/8 . The authors suggest that haploinsufficiency is a likely mechanism for the observed tumor phenotype , which is consistent with the observed latency of heterozygous compared to homozygous mutants , but possible LOH events cannot be excluded [34] . Here , we observed a tumor penetrance exceeding 90% , which is considerably elevated from the control zebrafish assessed here , as well as in previously described studies [12] , [31] . Importantly , sequencing of zebrafish seminomas identified a subset of tumors showing LOH , which is likely correlated with advanced tumor progression in these samples ( Figure S4B ) . Both zebrafish tumors and human seminomas show biallelic loss in a subset of samples , but LOH is not evident in all samples . Despite the presence of wild type tissue , which may obscure our genetic LOH analysis in the remaining samples , we cannot rule out a potential haploinsufficient mechanism . All identified alleles we tested are loss-of-function mutations as determined by in vivo complementation studies and IHC , and do not show dominant negative phenotypes . The incidence for human seminoma is rising , however currently established risk factors remain poorly described and are limited to urological and testicular developmental abnormalities such as cryptorchidism and testicular atrophy and undetermined environmental factors [35] . Since LRRC50 mutations have been reported in PCD [8] , [9] , a multifaceted disease that includes infertility , we cannot exclude a correlation with impaired sperm motility , however , thus far no systematic association between PCD and seminoma has been described [36] . Of interest though , motile cilia protein DNAH9 ( MIM 603330 ) is frequently mutated in breast cancer ( MIM 114480 ) [37] , [38] and in line with this notion , ciliary frequencies are reduced on cells derived from breast tumors [39] . We hypothesize that the ciliary localization of LRRC50 in early germ cells ( Figure 3D ) and subsequent loss in tumor sections might suggest a role for this organelle in normal germ cell regulation . Loss of cilia potentially deregulates specific receptors essential for proper germ cell responses . Indeed , there is some circumferential support for this hypothesis . Somatostatin receptor 3 ( Sstr3 ) is an established ciliary localized receptor [40] that is known to be lost in seminomas [41] . Loss of Fgf8 and Fgfr1 expression in Xenopus reduces cilia length [42] and expression of the human orthologs is reduced in seminoma specifically when compared to other GCTs [43] . Another interesting correlation is the aberrant expression of a PDGFRα transcript in CIS cells [44] , and normal PDGF-AA signaling can signal through cilia , at least in fibroblasts [45] . The data presented in this manuscript would argue for an additional unique role of LRRC50 in primary cilia that is not related to its function in motile cilia: the gastrulation phenotypes described in MO-treated zebrafish are associated with primary cilia function and we have never observed these defects with PCD-associated genes previously tested . Furthermore , we have described that primary cilia formation is inhibited upon shRNA-mediated knockdown in mammalian cells [6] , and show increased LRRC50 mRNA expression upon primary cilia formation ( Figure S6B ) . It is under debate whether cilia could have a direct contribution to tumorigenesis , but it has rather been demonstrated that well-described tumor suppressors like VHL , APC , and members of the Shh and Wnt pathway connect to cilia function [46] , [47] , indicating that the cilium could be implicated in tumor development . Alternatively and moreover , the intracellular localizations observed for LRRC50 and cell-cycle dependent regulation could equally well reflect a cilia-independent putative tumor suppressor function . Further studies are required to unravel the apparent diverse molecular functions of LRRC50 . In what way the dysfunction or loss of LRRC50 affects autonomous early germ cell development , and whether it induces a block in maturation , deregulates differentiation or proliferation and systematically leads to seminoma development , remains elusive . The fundamental mechanisms underlying seminoma formation are incompletely understood , but in humans is known to involve erasure of genetic imprinting of PGC/gonocyte progenitor cells [48] . Although common characteristics have been extensively described to include aneuploidy and non-random gain and loss of chromosomes , of which gain of 12p appears important in metastatic tumors [48] , little information on early initiating events is available . Causal genetic factors to seminoma development are also limited as only 1 . 4% of TGCT are familial cancer syndromes . Nevertheless , the familial risk factor for inherited TGCT is estimated as more than double of other familial cancer syndromes [17] , appealing to the need for more genetic studies . Recent advances have implicated the KITLG/SPRY4/BAK1 and TGFβ/BMP-signaling ( BMPR1B ) pathways in germ cell tumor development , which include the control of differentiation , cell proliferation and apoptosis [34] , [49]–[51] . Mutations in both pathway components are identified in seminomas and non-seminomas , hence differentiating factors amongst these tumors remain unknown . Furthermore , N- and KRAS activation mutations and LOH of well-accepted tumor suppressors APC , p53 and CDH-1 have been identified in both seminomas and non-seminomas [52] , [53] . It is expected however , that the default pathway for CIS cell development is seminoma and that an additional event is required to induce a switch in pluripotency , leading to non-seminoma [48] . Our data identifies LRRC50 as a novel candidate and we suggest that a currently unknown tumor suppression mechanism ( Figure S7 ) specifically predisposes to zebrafish and human seminoma development .
All animal experiments were approved by the Animal Care Committee of the Royal Dutch Academy of Science according to the Dutch legal ethical guidelines or the Duke University Institutional Care and Use Committee . The human tumor samples used for this study were approved by an institutional review board ( MEC 02 . 981 ) . Samples were used according to the “Code for Proper Secondary Use of Human Tissue in the Netherlands , ” developed by the Dutch Federation of Medical Scientific Societies [54] . Heterozygote lrrc50Hu255h , vhl and randomly selected control zebrafish were isolated from a forward genetic N-ethyl-N-nitrosourea ( ENU ) -based mutagenesis screen as previously described and maintained according to standard protocols [6] , [55] . Founder lrrc50+/− fish were outcrossed three consecutives times to wild-type lines and incrossed once to maintain the line . Prior to tissue isolation , zebrafish were euthanized by overdose of MS222 . Fragments for immunohistochemistry were fixed overnight using a 4% paraformaldehyde solution containing 2% acetic acid , embedded in paraffin and sectioned at 6 µm . Fragments used for morphological analysis were fixed using 4% glutaraldehyde and embedded in glycol methacrylate ( Technovit 7100 , Hereaus Kulzer ) , sectioned at 4 µm and stained with toluidine blue . Images were captured using a Nikon Eclipse E800 equipped with a Nikon DXM1200 digital camera and Plan Apo 2×/0 . 1 , 10×/0 . 45 , 20×/0 . 75 and 40×/0 . 95 NA objectives . Human RPE-hTERT and T47D cells were cultured in DMEM/F12 supplemented with 10% fetal bovine serum ( Lonza ) , penicillin/streptomycin and ultra-glutamine ( 2 mM ) . T47D cells were subjected to a double thymidine block ( 10 mM , Sigma ) and released for indicated times . RPE-hTERT cells were ciliated by 48 hours of serum withdrawal . Mitotic RPE-hTERT cells were trapped in nocodazole ( Sigma ) : 1 µg/ml , collected using mitotic shake-off , swollen for 15 minutes in hypotonic ( 75 mM ) KCl solution at 37°C and prepared for imaging using cytospin . RPE-hTERT cells were transfected with Mybbp1a-RFP using Fugene6 ( Roche ) according to manufacturer recommendations . RNA isolation was performed according to manufacturers recommendations ( Qiagen , RNA isolation kit ) . mRNA probes; LRRC50 Hs00698399_m1 and RPL19 Hs01577060_gH , were purchased from Applied Biosystems . Real time PCR was performed in triplicate using the one-step RT-PCR kit and the 7500 system from Applied Biosystems . For mouse tissue LRRC50 expression profiling , Clontech RNA libraries of developing embryo's and adult tissues were used . Cells for FACS analysis were fixed in ice-cold 70% ethanol , DNA content and mitotic index determined using propidium iodide and phospho-HistoneH3 according to standard conditions . Cells are fixed in either ice-cold methanol or 4% PFA with 0 . 1% Triton-X-100 . All immuno-fluorescence stainings were performed in PBS containing 3% BSA and 5% goat serum and washed in 3% BSA in PBS . Coverslips were mounted using ProLong antifade ( Molecular Probes ) . Primary antibodies used are α-LRRC50 ( 1∶100 , Abcam; ab75163 , 1∶100 Aviva Systems Biology; ARP53359_P050 , 1∶100 Santa Cruz Biotechnology; sc-133762 , 1∶100 Sigma; SAB2101390 ) , α-acetylated α-tubulin ( 1∶10 . 000 , Sigma-Aldrich T6793; clone 6-11B-1 ) , α-CREST/ACA anti-sera ( 1∶10 . 000 , Fitzgerald Industry Int . ) , α-γ-tubulin ( 1∶500 , Sigma; clone GTU-88 , T6557 ) . Secondary antibodies ( alexa-488 , -568 and -647 , various species ) were obtained from Molecular Probes . Images were acquired using a Zeiss 510 Meta confocal microscope with a 63×1 . 3 N . A . objective and analyzed with the Zeiss LSM Meta 510 software and a Deltavision RT imaging system ( Applied Precision ) using 100× NA 1 . 4 UPlanSApo objective ( Olympus ) using SoftWorx software . For zebrafish immunohistochemistry , stainings were performed as described [15] , [34] . Primary antibodies used were α-phosphorylated-histone H3 ( 1∶1000 , Upstate; 06-570 ) , α-Ziwi ( 1∶100 , [15] ) and α-γ-H2Ax ( 1∶200 , Cell Signaling ) . Human testicular tissues isolated from autopsies performed at the University Medical Center Utrecht of 6 men ( 33–43 years of age ) were used . After deparaffination and rehydration , 4 µm sections were digested in protease XXIV ( Sigma , 0 . 02 mg/ml in PBS , pH 7 . 3 , 60 minutes at room temperature ) [56] . After washing and blocking in 1% BSA in PBS , primary antibodies ( mouse monoclonal acetylated-α-tubulin , clone 6-11B-1 Sigma 1∶12000 , rabbit polyclonal α-LRRC50 , ARP53359_P050 Aviva Systems Biology , 1∶50 , rabbit detyrosinated-tubulin , Millipore AB3201 1∶250 ) were incubated for 60 minutes at room temperature . After repeated washing in PBS , secondary antibodies are incubated for an additional 60 minutes at room temperature: goat-anti-mouse conjugated to Cy5 ( Millipore , 1∶100 ) and goat-anti-rabbit-Cy3 ( Life Technologies , 1∶100 ) . Sections were washed again repeatedly , incubated in DAPI ( diluted 1∶5000 in PBS ) for 15 minutes and after a final round of washes in PBS , mounted with Fluoromount G . Stained sections are stored in the dark at 4°C until confocal imaging with a Zeiss LSM700 63× objective . IHC section ( 3 µm ) are stained with α-LRRC50 ( 1∶200 , Abcam; ab75163 ) , secondary antibody used is powervision-HRP IgG ( 1∶200 , Immunologic ) and sections were counterstained with hematoxylin according to standard protocols . MO targeting lrrc50 was injected into wild-type embryos at the one to four cell stage , and rescued with capped human LRRC50 mRNA as described [19] . We used site-directed mutagenesis to introduce missense changes Thr590Met and Gln307Glu into the WT pCS2+ LRRC50 construct ( Quick-Change Site Directed Mutagenesis kit , Agilent ) and used linearized plasmid to transcribe mRNA ( SP6 mMessage mMachine kit , Ambion ) . Live embryo scoring , RNA ISH , morphometric analyses and statistics were conducted as described [57] . Analysis is detailed in Table S1 . To assess and compare the amount of proliferating spermatogonial stem cells between wild-type and tumor tissue , sections pH3-stainings were quantified . For analysis of the tumor samples , three photographs ( 20× magnification ) from three different sections are used ( 16–20 µm distance between sections ) to obtain a valid representation of various regions of the tumor . For the control samples , two sections were used given the smaller size of testis fragments . The protocol for quantification was adapted from ImageJ ( http://rsbweb . nih . gov/ij/ ) . Briefly , the difference in intensity between pH3-positive and pH3-negative background tissue was substantial enough to set the threshold by manually adjusting the background levels . Next , a binary image was created to calculate the percentage of total surface area covered with positive cells . Large clusters ( >3–4 cells ) of proliferating cells are removed manually to enrich for individual positive cells . To correlate the amount of proliferative spermatogonial stem cells to the total amount of tissue on a given image , the calculated surface area was set to 100% and the proliferation percentage was extrapolated . The percentage of proliferation per picture was averaged for each tissue fragment . Averages were calculated and results are represented in a box-plot . More details on the calculation are found in the statistical analysis section . DNA isolation , PCR and sequencing of tumor fragments and human samples were performed according to standard procedures . Human control samples were obtained from healthy blood donors that submitted material to the UMC Utrecht department of Medical Genetics . Primer sequences can be found in Table S2 . Sequence analysis was performed using polyphred software [6] and DNASTAR Lasergene Software ( http://www . dnastar . com/default . aspx ) . The number of tumors identified in the different groups ( Figure 1A ) were compared using a two-tailed Fisher's exact test in a 2×2 contingency table . Between 24 months and 44 months of age , male lrrc50Hu255h zebrafish ( TGCT tumors n = 24 , normal n = 0 ) compared controls ( TGCT tumors n = 17 , normal n = 87 ) . The quantifications of spermatogonial stem cell proliferation ( Figure S4A ) were subjected to statistical analysis . As input the following data was used; the tumor averages three quantified sections per sample; whereas vhl ( +/− ) and wild type control groups averaged two sections . A non parametric Mann-Whitney test at P<0 . 05 was used to compare whether the averages of two groups are different , the p-value between the tumor group ( n = 7 ) and normal wild type ( n = 5 ) or vhl ( +/− ) ( n = 4 ) was calculated . Wild type and the vhl ( +/− ) group are not significantly different ( P = 0 . 3095 , U = 7 . 000 ) , both are significantly ( P = 0 . 0025 , U = 0 . 0000 ) different from the tumor group . Results are represented in a box-plot . To calculate the putative overrepresentation of c . 919C>G/p . Gln307Glu in the seminoma cohort ( Figure 3F ) , a two-tailed Fisher's exact test in a 2×2 contingency table was used as the data is categorical and sample sizes are large . We used n = 100 and n = 0 for the control group and n = 33 and n = 5 for the seminoma group , and determined P = 0 . 0013 confirming a significant enrichment . Expression of mRNA as described in Figure 5E; Ct values obtained were normalized and used to calculate relative expression levels in n = 4 per condition . The standard deviation ( P = 0 . 05 ) was calculated . This was performed similarly for Figure 5F using n = 3 per condition .
|
Testicular Germ Cell Tumors are frequently occurring tumors , affecting 1 in 500 individuals . Of this diverse group , the subtype seminoma is most prevalent and is the most common tumor type found in men aged 20–40 years of age . In contrast to other frequently occurring tumor types , there is very little information on the genetic components that form risk factors for seminoma . In this study we describe the unexpected finding that zebrafish carrying a heterozygous mutation in the lrrc50/dnaaf1 gene have a high incidence for testicular germ cell tumor formation . Detailed analysis suggests that these tumors resemble human seminoma . We therefore analyzed this gene in a subset of human seminoma samples and recovered mutations that were subsequently demonstrated to prohibit protein function . Seminomas were also previously found in family members of these patients , suggesting that a genetic component is the underlying cause . We thus identified a novel gene that can be considered a risk factor for human seminoma , and we describe an animal model system that is valuable for further seminoma research .
|
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2013
|
Mutations in LRRC50 Predispose Zebrafish and Humans to Seminomas
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Lassa fever is a viral haemorrhagic fever caused by an arenavirus . The disease is endemic in West African countries , including Guinea . The rodents Mastomys natalensis and Mastomys erythroleucus have been identified as Lassa virus reservoirs in Guinea . In the absence of a vaccine , rodent control and human behavioural changes are the only options to prevent Lassa fever in highly endemic areas . We performed a 4 year intervention based on chemical rodent control , utilizing anticoagulant rodenticides in 3 villages and evaluating the rodent abundance before and after treatment . Three additional villages were investigated as controls . Analyses to assess the effectiveness of the intervention , bait consumption and rodent dynamics were performed . Anthropological investigations accompanied the intervention to integrate local understandings of human–rodent cohabitation and rodent control intervention . Patterns of bait consumption showed a peak at days 5–7 and no consumption at days 28–30 . There was no difference between Bromadiolone and Difenacoum bait consumption . The main rodent species found in the houses was M . natalensis . The abundance of M . natalensis , as measured by the trapping success , varied between 3 . 6 and 16 . 7% before treatment and decreased significantly to 1–2% after treatment . Individuals in treated villages welcomed the intervention and trapping because mice are generally regarded as a nuisance . Immediate benefits from controlling rodents included protection of food and belongings . Before the intervention , local awareness of Lassa fever was non-existent . Despite their appreciation for the intervention , local individuals noted its limits and the need for complementary actions . Our results demonstrate that chemical treatment provides an effective tool to control local rodent populations and can serve as part of an effective , holistic approach combining rodent trapping , use of local rodenticides , environmental hygiene , house repairs and rodent-proof storage . These actions should be developed in collaboration with local stakeholders and communities .
Lassa fever is a viral haemorrhagic fever caused by an arenavirus , which was first discovered in Nigeria in 1969 [1 , 2] . The disease is endemic in West African countries , including Sierra Leone , Liberia , Guinea , southern Mali , northern Cote d’Ivoire and Nigeria [3–6] . Lassa fever recently emerged in Benin and Togo [7–9] and affects between 200 , 000 and 300 , 000 people per year with up to 5 , 000 to 10 , 000 deaths annually [10] . The mortality rate is low ( 1–2% ) in communities in endemic areas but can be as high as 50% among hospitalized patients during outbreaks [11 , 12] . In general , most cases remain asymptomatic [13] . In Guinea , an epidemiological survey in human populations showed a high seroprevalence , up to 40% , in the south of the country near the border with Sierra Leone [14] . Acute cases have been reported in regional hospitals [15] . For many years , the Natal multimammate mouse , Mastomys natalensis , was considered to be the sole reservoir of the virus [16 , 17]; however , a recent study in Guinea and Nigeria showed that two other species , the Guinea multimammate mouse , Mastomys erythroleucus , and the African wood mouse , Hylomyscus pamfi , can also serve as reservoirs [18 , 19] . Humans can be infected by touching objects contaminated with rodent urine , breathing aerosolized particles , being bitten by rodents or consuming rodents [20–24] . Human-to-human transmission occurs in the community and in health care settings [10 , 25 , 26] . Treatment options are limited , with Ribavirin given early in the course of disease to improve survival in patients with Lassa fever [27] . In the absence of a vaccine , rodent control and human behavioural changes are currently the only options available to prevent Lassa fever in highly endemic areas . In Sierra Leone in 1983 , a team from the United States Centers for Disease Control and Prevention reported an experimental approach to reduce the incidence of Lassa fever by controlling the rodent population [28] . The experiment lasted 5 weeks and was spatially focused in a single township . The authors did not find any change in disease incidence between people living in houses with the intervention ( trapping ) and those in houses without the intervention . It is probable that the experiment was too short to adequately measure an effect on the disease incidence . Furthermore , treatment of only a few houses within a single village led to a rapid re-infestation from neighbouring houses . In light of these limitations , our aim was to perform rodent control on a larger scale and for a longer duration . To that end , we investigated a dozen villages in Faranah , in rural Upper Guinea , where Lassa Virus ( LASV ) is widely distributed [29] . Previous studies of rodent dynamics have shown that M . natalensis rodents aggregate in houses during the dry season and disperse into gardens and surrounding fields in the rainy season , where they forage in cultivated areas before the harvest [30] . We therefore planned rodent control interventions inside houses during the dry season only , which starts in November and finishes in April [30] . Studies on rat poison use and availability in Africa are rare , but some examples of acute poison or anticoagulant use and supply in Tanzania [31] , South Africa [32 , 33] and Sierra Leone show effectiveness in controlling rodent population for short periods of time . These examples also indicate that people primarily use anticoagulants and acute poisons ( zinc phosphide ) because they are easily accessible , cheap and less labour intensive than trapping . In some cases , the anti-inflammatory drug Indomethacin [34 , 35] may also be used instead of rodenticide . Whatever the substance used , the effects of rodent control are short-lived . Despite the noise and the loss of crops , people often adjust to living alongside the rodents . As in other studies on rodent control acceptability in Africa [33] we aimed to assess first the feasibility and acceptability of community rodent control activities before extending to an holistic approach including environmental sanitation , house repair and rodent proof containers . To evaluate the feasibility of rodent control in the Faranah region , we performed an intervention based on chemical rodent treatment in 3 villages , evaluating the rodent abundance before and after treatment . Three additional villages were investigated as controls for comparison with the treatment villages . This article discusses the rodent diversity , rodent abundance and sociocultural factors affecting the feasibility , efficacy and acceptability of chemical rodent control . Based on our experiences during 4 consecutive years in Upper Guinea , we discuss ideas for advancing sustainable rodent control .
Six villages were chosen in the surrounding area of Faranah; 3 to serve as controls and 3 to perform the intervention . The choice of villages was based on their remote location from a paved road , a size not exceeding 1000 inhabitants , less than 45 minutes driving time from Faranah and the presence of LASV ( see map in Fichet-Calvet et al . 2016 ) . We first sampled rodents in 10 villages in November-December 2013 . Of the 10 villages , 9 were positive , with a range of 1 to 10 LASV-positive M . natalensis rodents in each village . The villages were classified as either high or low prevalence and therefore allocated randomly to control and treated groups , leading to 3 villages in the control group with the following prevalence rates: 20 . 6% ( 7/34 ) in Sokourala , 19 . 6% ( 10/51 ) in Damania , and 2 . 1% ( 1/46 ) in Sonkonia . The 3 villages in the treated group had the following prevalence rates: 20 . 0% ( 8/40 ) in Dalafilani , 17 . 8% ( 8/45 ) in Yarawalia , and 3 . 8% ( 2/52 ) in Brissa . Thus , two villages with a high prevalence and one village with a low prevalence were included in each category ( control versus treatment ) . We planned to perform the treatment intervention during the dry season ( November-April ) , when the rodents are expected to aggregate inside . We employed a treatment using anticoagulant rodenticide baits , which we distributed in baiting stations ( Coral , Ensystex Europe ) to all open houses of the village . Rodent control is more effective when it is managed at the collective level rather than at the individual level [36] . Two baiting stations were distributed in each room , totalling 300–600 stations per village , according to their size . During the first three years , we purchased the anticoagulants locally available in Conakry . This treatment was a mixture of wheat and Bromadiolone , labelled at 0 . 01% , sold in small sealed bags ( S1 Fig ) . In these baits , Bromadiolone was titrated at 30 ppm , which corresponds to a concentration of 0 . 003% ( V . Lattard , pers . com . according to [37] ) . The concentration was therefore 3 times lower than that claimed on the label . During the last year , we used Difenacoum at 0 . 005% mixed with cereals and paraffin as bait in cubes weighing 50 g ( Rodenthor bloc , Ensystex Europe ) . The duration of chemical treatment was 10 days during the first 2 years and 30 days during the last 2 years ( S1 Table ) . In the villages with treatment , dead rodents found outside of their burrows were collected by the team and cremated in a special hole outside the village . This hole was also used to burn the contaminated waste produced by necropsies during the routine sampling of rodents for LASV testing . For comparison with the captured rodents , dead rodents were numbered and identified during years 3 and 4 . To verify whether rodents were eating the bait , we evaluated the consumption during the whole process of treatment during years 3 and 4 . On day 1 , the bait stations were weighed empty and filled with 50 g of bait before being set . On day 2 , each station was weighed and the value was recorded ( S2 Fig ) . The difference between day 1 and day 2 indicated the daily consumption for each bait station . The values were thereafter summed for all the stations set in the village . Checking and baiting were performed each day during the first 5 days and then every 2 or 3 days between days 6 and 30 . The reason for the more frequent checking at the beginning and less frequent checking at the end of the process was the decrease in the local rodent population due to the anticoagulant rodenticide activity . Typically , the highest rodent mortality occurs between 3 and 10 days after the first anticoagulant ingestion [38] . To measure the local rodent abundance , we set 120 traps along a transect crossing the villages . Two Sherman live traps ( Sherman Live Trap Co . , Tallahassee , FL , USA ) were set per room over 3 consecutive nights . The traps were checked by team members each morning , and the captured animals were immediately necropsied in situ according to a BSL3 procedure [39 , 40] . The animals were morphologically identified , and several biopsies were collected for further ecological and virological analysis . Morphological identification was facilitated from knowledge gained during 14 years of work with small mammal species in this area . Previous studies using both morphological and molecular identifications in the same geographical area have shown that M . natalensis was predominantly living in houses while M . erythroleucus was never found in houses [41] . The abundance was estimated by using the trapping success for each 3-night trapping session ( Σ trapped rodents during 3 days/360 trap-nights x 100 ) . A trapping session was performed twice in each treated village , i . e . , before and after treatment , and once in the control villages . In total , we analysed 14 , 394 trap nights . Data are available in DOI 10 . 6084/m9 . figshare . 5545267 . We applied several techniques to collect local perception regarding cohabitation with rodents and the intervention after the first treatment and throughout the 4 years . Qualitative investigations included focus group discussions with groups of women and men separately in each village ( 11 ) , in-depth interviews ( 39 ) , informal discussions and participant observation and photographs . Focus group discussions are used to collect views on a particular topic from specific groups of people with similar experiences . These discussions usually include approximately ten individuals and two moderators , one who asks questions and stimulates the discussion and another who takes notes . We used this technique to explore peoples’ views on the project activities and on why rodents live with them . In-depth interviews were conducted individually with people who could provide detailed information on the research topic . We conducted informal discussions with the team and people living in the villages regarding the intervention . Photographs documented the domestic space , the distribution of the houses , and building materials , among other inputs . In addition , we distributed a short quantitative questionnaire in August 2016 to evaluate the acceptance of our project by the villagers . We selected people in each village according to their availability , knowledge and willingness to participate [42] . Oral consent was obtained before distribution of the questionnaire . In total , 203 people were questioned regarding their views of the project and specifically whether rodents had disappeared from their houses and for how long this absence had persisted . All the discussions were facilitated by a translator in Malinke , Djallonke and French . We obtained permission from the local health authorities ( Directeur Régional de la Santé , Directeur Préfectoral de la Santé ) in Faranah and in each village from the local chief , elders and youth leaders before starting the research activities . During the Ebola Virus Disease ( EVD ) epidemic , lasting from March 2014 to January 2016 , we were not able to follow the original planned intervention . People refused the trapping in some villages due to the fear and mistrust generated by the EVD epidemic . In year 2 for example , a trapping delay of 6 months meant that we did not have time to perform 1 trapping session in 6 villages before treatment , 1 trapping session in 6 villages after treatment , nor elimination in 3 villages before the end of dry season in April . Furthermore , 2 of 3 control villages refused to adhere to the experiment . In year 3 , one control village was still reluctant to participate . In years 2 to 4 , we therefore reduced pre- and post-treatment trapping in treated villages only , and kept a single trapping in control villages where possible . Details are presented in a supplementary document ( S1 Text ) . A comparison of the daily consumption between the Bromadiolone grains and the Difenacoum blocks , and also between villages was evaluated through a linear model ( “lm” tool in R software , R Development Core Team , 2017 ) , with the quantity as a response variable , and molecule , village and days as explanatory variables . Rodent dynamics were analysed using the linear mixed effects model ( “lme” tool in R software ) , with the abundance of M . natalensis as a response variable , and treatment as an explanatory variable coded as a fixed effect . The village and the year were also entered in the model as random variables . The abundance of M . natalensis was here estimated through the number of trapped animals since the denominator of TS was always the same , i . e . 360 trapping nights . To analyse the possible trend of rodent abundance between year 1 and year 4 , a third model was implemented in R , with the abundance of M . natalensis as the response variable , and type of village ( treated vs control ) and year ( year1 , year4 ) as explanatory variables in a 2-ways interaction . To evaluate the relationship between rodent abundance and bait consumption , a simple regression was performed with 6 points ( 3 villages x 2 years ) .
In both year 3 and year 4 , the bait consumption at the beginning of the baiting period was low and then increased , reaching a maximum at day 5 or day 7 depending on the year ( Fig 1 ) . Subsequently , bait consumption gradually decreased to zero after days 25 or 28 , depending on the year . The bait consumption was similar regardless of the molecule ( p = 0 . 06 , df = 72 ) , Bromadiolone ( sum = 46 . 440; median = 0 . 940; IC95% = 0 . 723 . 8–1 . 340 . 2 kg ) or Difenacoum ( sum = 39 . 140; median = 0 . 930; IC95% = 0 . 682–1 . 057 kg ) . Village effect was evident , with a bait consumption higher in Brissa , than in Yarawalia ( p = 0 . 007 , df = 72 , estimate = -287 . 7 ) and Dalafilani ( p = 0 . 006 , df = 72 , estimate = -292 . 7 ) . The villages in our study were primarily inhabited by M . natalensis , which represented 94% ( 1047/1114 ) of the captured animals ( Table 1 ) . The dynamics of M . natalensis population changes in treated villages are shown in Fig 2 , where the values of trapping success ( TS ) are plotted according to the time schedule , either before or after treatment . After treatment , the population was significantly lower than before ( p<0 . 0001 , df = 11 ) . After 3 years of treatment , the treated villages had a significant lower abundance than the control villages ( significant interaction year 4 x treated villages , p = 0 . 03 , df = 8 , estimate = -19 . 7 , in Fig 3 ) . A simple regression between abundance and bait consumption during year 3 and 4 gives a significant coefficient of correlation ( r2 = 0 . 94 , df = 4 , p = 0 . 001 ) . The highest abundance observed in Brissa corresponded to the highest bait consumption . The most frequent building type is a round Sudanese-style mud hut with thatch roof; people use sleeping huts or rooms as storehouses; kitchens are adjacent buildings which follow the same construction style . Owners of concrete and metal-roofed buildings , which have several rooms , typically reserve one room as a store to protect harvest and seeds from fires ( Fig 4 ) . Granaries are rare in the region; many people stopped using granaries because they were unable to prevent fires and thefts . Women can preserve condiments , dry fish and leftover food in wooden boxes . Small quantities of rice remain freely available in rooms , especially in women’s rooms , for weekly family feeding . Before consumption , husk-rice is boiled , dried on the ground several times and pounded . During the drying process , rice can be transferred from the ground outside the house onto the floor inside the house or kitchen several times until the rice is dry . Rodent-proof containers for post-harvest storage are not available in the region beyond plastic bags and plastic and metallic containers with and without lids , which are also used to store water , local handmade condiments and other crops . Consequently , in certain villages , people highlighted the need for building food storage and making available rodent-proof containers in parallel with poisoning or trapping . Rodents are considered a nuisance because of their effects on food stocks and personal properties . Individuals believed that it would be impossible to kill ‘all’ rodents . For them , they live in rural areas , surrounded by fields and vegetation , and are therefore in permanent cohabitation with rodents . Persons living in the periphery , bordering the bush , complained that rodents come back sooner to these houses than to those in the middle of the village . Locally , preventive measures taken against rodents are very limited: acute poisons available on the market are used by individual owners in kitchens , stores and rooms before harvesting crops , when people are annoyed by rodent noise or when mice damage their belongings . Several people use Indomethacin , instead of poison because they want to prevent small children and domestic animals from accidental intoxication with poison . Adults may have cats , and the presence of cats was reported to result in fewer rodents in some houses . Children perform rodent trapping by hand when they find a nest in the house or have dogs with them to hunt rodents in the fields .
The consumption curves of the two compounds , Bromadiolone and Difenacoum , showed that both are effective and that after 28 days , no rodents were feeding . This complete lack of consumption at the end of the operation also showed that there was no resistance phenomenon . A resistance phenomenon is visible when the consumption curve makes a plateau , even peaks again after 15–20 days , due to resistant individuals , which continue to eat the bait . Despite a difference of amplitude between the two curves ( Bromadiolone vs Difenacoum ) , the pattern is similar and quantities of bait were equally eaten at the end of the process when the 3 villages are taken into account . Only one village ( Brissa ) showed a higher bait consumption , which corresponds to a larger rodent population in years 3 and 4 . The peak of Bromadiolone consumption observed during day 4–6 may be due to the behaviour of the rodents , which transport the wheat seeds to their burrows [43] . Paraffin blocks used in year 4 are generally recognized to have a lower palatability and consumption rate than whole cereals . The post-treatment trapping showed that the efficacy was similar between the 2 baits . Information collected from villagers indicated that the rodents returned very quickly . Similar observations were done by the population in Sierra Leone after using poison [44] . Increasing the treatment duration to 30 days caused the rodent population , according to local individuals’ observations , to remain low for a longer period of time , with treatment effects persisting for approximately 2 to 3 months . This period would correspond to a return to the carrying capacity of a M . natalensis population if 90% were initially eliminated ( calculation in [45] ) . Two months correspond also to the mean period for recovery of R . rattus populations after removal trapping in villages located in Uganda [46] . Assessment of trapping success after treatment was below 2% ( years 3 and 4 ) , which is comparable to an elimination performed with continuous trapping during one month [47] . As a consequence , the populations of M . natalensis oscillated from one year to the next , mimicking seasonal variations . The decline observed in our experiment , occurred however during the dry season when M . natalensis populations were expected to be abundant indoors , as shown by sampling during Year 1 in control villages after treatment ( Fig 3 ) or in longitudinal studies performed in 2 other villages in the same region ( Fichet-Calvet et al 2007 ) . In this study , the decline is therefore due to our experiment and not to a normal seasonal effect . A comparison of rodent abundance between year 1 and year 4 showed a slight decrease in the treated villages . This finding needs to be confirmed in a long-term study . Year 2 had a slightly different pattern , as the abundance was surprisingly low before treatment . The trapping before treatment in year 2 was conducted in March , not in November as usually performed . This shift towards the end of the dry season may explain the altered abundance of rodents indoors because they had begun to disperse outdoors [30] . However , the difference might also be due to human behaviour . We observed that villagers in Dalafilani used rodenticides and increased the number of cats between 2 trapping sessions , which may explain the similar trapping success rates measured after treatment in year 1 and before treatment in year 2 . This intensification of rodent control by villagers influenced the subsequent rodent abundance . After 4 years , however , we conclude that once-yearly treatment is not sufficient to maintain the low population abundance of M . natalensis . There are several reasons for the return of rodents 2 to 3 months after the end of operations: 1 ) the high proliferation of this species , whose mean litter size is 9 . 2 ( 3–14 in [48]; 2 ) the survival of a few animals in the fields surrounding the houses , which allows recolonization of the human habitat; 3 ) several closed houses in which we were not able to enter and deposit of the poisoned baits , which may have served as shelters from which the rodents could recolonize houses in the surrounding areas; 4 ) several very attractive foods available for rodents; 5 ) the porosity of the walls and roofs , allowing rodents to enter very easily; and 6 ) the low prevalence of predators , such as cats and dogs . Points 1 ) and 2 ) would be more difficult to change because animals’ inherent biological traits are not very easily influenced . Experiments concerning fertility control in rodents are rare because chemosterilization is difficult to practice in the field [49 , 50] . The surrounding fields are also the natural optimal habitat for M . natalensis , and it seems unrealistic to remove them from this habitat . Recent studies on M . natalensis movements in different microhabitats in the villages confirm the need to expand rodent control measures outside the house to nearby field and gardens [51] . However , points 3 ) to 6 ) could be modified more easily in collaboration with the residents taking advantage of the knowledge we are generating together . Based on our findings we present in the following lines some ideas for improvement and work towards a sustainable and holistic rodent control intervention .
Based on these findings and the acceptability of rodent control activities at community level , we aim to promote , in coordination with health and agricultural authorities , a more holistic approach [56] , including rodent trapping and poisoning , environmental hygiene , personal hygiene , house repairs and rodent-proof storage . The present scenario creates the potential to develop a research-based project and design a collective "one-health" action [57] for rodent management and Lassa fever control .
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In the absence of a Lassa fever vaccine , rodent control is the primary prevention option . An effective rodent control intervention must understand human behaviour towards the rodent such as: human–rodent interactions , cohabitation , and local rodent control measures . We conducted a rodent control intervention at community level in a Lassa Virus endemic area in Upper Guinea ( Guinea ) accompanied by an anthropological study on people’s perceptions and recommendations on the intervention . Based on our results we seek to broaden the rodent control intervention by including environmental hygiene , house repairs and rodent-proof storage . Chemical treatment has proven effective for rodent control but other factors involved in human-rodent interactions should also be addressed . Our findings highlight the need for Lassa fever prevention and rodent control initiatives to work in collaboration with communities and undertake a holistic approach towards rodent control .
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2018
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Rodent control to fight Lassa fever: Evaluation and lessons learned from a 4-year study in Upper Guinea
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Mutations in VAPB/ALS8 are associated with amyotrophic lateral sclerosis ( ALS ) and spinal muscular atrophy ( SMA ) , two motor neuron diseases that often include alterations in energy metabolism . We have shown that C . elegans and Drosophila neurons secrete a cleavage product of VAPB , the N-terminal major sperm protein domain ( vMSP ) . Secreted vMSPs signal through Roundabout and Lar-like receptors expressed on striated muscle . The muscle signaling pathway localizes mitochondria to myofilaments , alters their fission/fusion balance , and promotes energy production . Here , we show that neuronal loss of the C . elegans VAPB homolog triggers metabolic alterations that appear to compensate for muscle mitochondrial dysfunction . When vMSP levels drop , cytoskeletal or mitochondrial abnormalities in muscle induce elevated DAF-16 , the Forkhead Box O ( FoxO ) homolog , transcription factor activity . DAF-16 promotes muscle triacylglycerol accumulation , increases ATP levels in adults , and extends lifespan , despite reduced muscle mitochondria electron transport chain activity . Finally , Vapb knock-out mice exhibit abnormal muscular triacylglycerol levels and FoxO target gene transcriptional responses to fasting and refeeding . Our data indicate that impaired vMSP signaling to striated muscle alters FoxO activity , which affects energy metabolism . Abnormalities in energy metabolism of ALS patients may thus constitute a compensatory mechanism counterbalancing skeletal muscle mitochondrial dysfunction .
ALS is a lethal neurodegenerative disease characterized by the combined degeneration of lower and upper motor neurons [1] . Most ALS cases occur sporadically , but about 10% are familial . These genetic cases are caused by mutations in multiple genes , including in the Vapb ( VAMP/synaptobrevin-associated protein B ) gene . Mutations in Vapb lead to ALS8 that manifests as ALS or late-onset SMA , a motor neuron disease restricted to lower motor neurons [2]–[4] . While Vapb mutations are rare , reduced VAPB mRNA or protein levels have been reported in sporadic ALS patients , a mSOD1 ALS mouse model , and ALS8 patient motor neurons derived from induced pluripotent stem cells [5]–[7] . Hence , a loss of VAPB might be relevant in non-ALS8 patients . VAPB , and its paralog VAPA , are broadly expressed type II membrane proteins that are evolutionarily conserved . These VAPs have been implicated in regulating lipid transport and homeostasis at intracellular organelle contact sites , endoplasmic reticulum ( ER ) dynamics , and membrane trafficking [8]–[12] . In addition to these cell autonomous functions , the VAP vMSP is cleaved from the transmembrane domain in the cytoplasm and secreted in a cell-type specific fashion [13]–[15] . Secreted vMSPs antagonize Eph receptor signaling through a direct interaction with the extracellular domain [13] . More recently , we have shown in C . elegans and Drosophila that neurons secrete vMSPs to regulate mitochondrial localization and function in striated muscle [15] . vMSPs interact with muscle SAX-3 Roundabout and CLR-1 Lar-like protein-tyrosine phosphatase receptors to down-regulate CLR-1 signaling . VAP loss causes uncontrolled CLR-1 Lar-like receptor activation in body wall muscle . CLR-1 stimulates actin filament assembly in the muscle belly that requires the actin-related protein 2/3 ( Arp2/3 ) complex . These ectopic actin filaments displace mitochondria from I-bands , cause aberrant fission and fusion balance , and impair respiratory chain activity . Hence , vMSPs secreted by neurons promote muscle mitochondrial localization and function , perhaps in an effort to modulate energy homeostasis . vMSP signaling to muscle mitochondria might be relevant for the energy balance in ALS8 disease . Out of five ALS8 patients studied , five had increased cholesterol levels , four had reduced HDL , three had elevated triacylglycerol levels , and one was diabetic [16] . More generally , ALS is associated with a spectrum of abnormalities in energy metabolism , including mitochondrial defects in neurons and skeletal muscle , insulin resistance , dyslipidemia , and hypermetabolism [17] . These metabolic abnormalities are positively correlated with survival . For instance , increased prediagnostic body fat is associated with decreased risk of ALS mortality [18] and in some patient populations , higher LDL/HDL ratios correlate with increased survival time [19] , [20] . However , the cause ( s ) of the metabolic defects and their relationship to each other are not well understood . Here we show in C . elegans that loss of the VAP homolog VPR-1 causes triacylglycerol ( TAG ) accumulation in striated body wall muscle . Mosaic analysis and tissue-specific expression studies provide compelling evidence that VPR-1 acts in neurons , not muscles to regulate fat levels . Multiple lines of evidence support the model that impaired vMSP signaling from neurons to muscle increases TAG levels in muscle . We propose that this fat metabolism alteration is part of a compensatory response mediated by the DAF-16/FoxO transcription factor . FoxO promotes muscle fat accumulation , maintains ATP levels during aging , and extends lifespan without influencing muscle mitochondrial morphology , localization , or function . Finally , we provide evidence that skeletal muscle metabolism is abnormal in Vapb mutant mice . Our results support the model that disrupting vMSP signaling to muscle triggers a compensatory response involving FoxO transcription factors .
In our studies of vpr-1 ( tm1411 ) null mutant hermaphrodites , we noticed that body wall muscles often contain large lipid-like droplets not observed in wild-type controls . These apparent lipid-like droplets were visible in young adults ( 1–3 days post L4 stage ) by differential interference contrast ( DIC ) microscopy ( Figure 1A ) . In transgenic vpr-1 mutants expressing mitochondrial matrix-targeted GFP ( mitoGFP ) in muscle , droplets are observed in the muscle belly surrounded by mitochondria ( Figure S1 ) . The vast majority of visible droplets in peripheral tissues are found in muscle . Transmission electron microscopy ( TEM ) of vpr-1 ( tm1411 ) mutant muscle shows an expanded muscle belly filled with mitochondria , as previously reported [15] , and large droplets ( Figures 1B and S2 ) . The droplets are often found in close proximity to mitochondria and ER . Large muscle droplets were not observed in young adult wild-type muscle ( Figures 1B and S2 ) . However , muscle lipid droplets and abnormal mitochondria are observed in very old ( 18 day ) wild-type adults [21] , [22] . In these old worms , large lipid droplets accumulate in the muscle , intestine , and epidermis . We did not detect abnormally large droplets in young vpr-1 mutant intestinal and epidermal tissues by TEM . Instead , intestinal and epidermal tissues looked similar to wild-type controls , although it is difficult to assess minor differences ( Figure S2 ) . Hence , muscle droplets accumulate in aging vpr-1 mutant worms . To directly test whether these droplets contain lipid , we fed vpr-1 mutant worms E . coli incubated with Bodipy-conjugated fatty acids ( Bodipy-FAs ) . These fluorescent compounds can be used to directly visualize fat stores in live tissue [23] , [24] . In wild-type hermaphrodite controls , dietary Bodipy-FAs were observed primarily in the intestine with a few small droplets present in muscle . In contrast , muscles of vpr-1 ( tm1411 ) null mutants contained numerous large Bodipy-FA-stained droplets ( Figure 1C ) . The fluorescent droplets fully overlapped with those observed in muscle by DIC microscopy ( Figure 1D ) . Similar results are observed with Sudan Black B , which darkly stains neutral TAGs in fixed opaque worms ( Figure S3 ) . Bodipy-FAs are continuously transported from the diet , to the worm's intestinal cells , and then to the muscle , where they are tightly packed in membrane-bound vesicles . Bodipy-FAs are also incorporated into yolk lipoprotein complexes [23] , which are specifically endocytosed by oocytes [25] . Although yolk accumulates in the pseudocoelom of vpr-1 mutants ( due to defective oogenesis ) , it is not up-taken by muscle ( Figure S4 ) . Both Bodipy-FA and Sudan Black staining show a mild increase in intestinal fat content in vpr-1 mutants . Whether this apparent increase is due to fat accumulation or increased fat synthesis is not clear . We also performed mass spectrometry of lipid extracts to determine the lipid composition of wild-type and vpr-1 mutant adult hermaphrodites . Lipids were analyzed by electrospray ionization tandem mass spectrometry ( ESI-MS/MS ) . ESI-MS/MS analysis of the extracts detected a robust increase in TAGs in vpr-1 mutant extracts , but not in the membrane phospholipids phosphatidylethanolamine and phosphatidylcholine ( Figure 1E and data not shown ) . These data indicate that loss of vpr-1 causes TAG accumulation in muscle of adult hermaphrodite worms . VAP homologs have been implicated in ER stress pathways [13] , [26] , [27] , which can modulate lipid metabolism and homeostasis [28] . Furthermore , mitochondrial dysfunction is sometimes associated with ER stress . We considered the possibility that increased ER stress might cause the high muscle fat levels in vpr-1 mutants . Three lines of evidence argue against this possibility . First , an integrated hsp-4/BiPp::gfp ER stress reporter [29] did not show elevated stress levels in vpr-1 mutants ( Figure S5A ) . Second , vpr-1 mutants are not more sensitive than wild type to tunicamycin treatment , which induces ER stress ( Figure S5B ) . Third , RNA-mediated interference ( RNAi ) of xbp-1 , an ER stress-responsive transcription factor , in vpr-1 mutants had no effect on muscle fat levels in 3-day old adults ( 18 . 0±3 . 6 droplets/mm2 for vpr-1 ( tm1411 ) [n = 12] versus 17 . 3±3 . 6 droplets/mm2 for vpr-1 ( tm1411 ) xbp-1 RNAi [n = 10]; P = 0 . 28 ) . These data indicate that increased ER stress does not cause the muscle TAG defect in vpr-1 mutants . vpr-1 is ubiquitously expressed and its homologs have been implicated in regulating lipid dynamics via a cell autonomous mechanism [10] , [30]–[32] . To determine in which cell type ( s ) VPR-1 functions to regulate muscle fat , we first used genetic mosaic analysis . Transgenic vpr-1 ( tm1411 ) mutant hermaphrodites were generated containing the vpr-1 genomic locus and the lineage marker sur-5::GFP expressed from an extrachromosomal array [33] . In C . elegans , extrachromosomal arrays are spontaneously lost at low frequency during cell division , thereby generating mosaic worms . When these events occur early in development , mosaic worms can be generated with losses in neurons , body wall muscles , intestinal cells , and the germ line . Expressing the vpr-1 genomic locus in vpr-1 ( tm1411 ) null worms rescued the fat metabolism defect in muscle ( Figure 2 ) , as well as the muscle mitochondrial defects , sterility , slow growth , and other phenotypes . Body wall muscles are generated from multiple cell lineages , including the EMS lineage . Transgene array loss in the EMS lineage generates mosaic worms that have a subset of muscles lacking vpr-1 expression . These muscle cells exhibited low fat levels , identical to muscle cells that express vpr-1 ( Figure 2 ) . Therefore , VPR-1 is not required in body wall muscle for fat accumulation . Mosaic worms lacking vpr-1 in the E lineage , which generates the intestine , also did not exhibit elevated muscle fat droplets , indicating that vpr-1 is not required in the intestine . In contrast to muscle and intestine loss , vpr-1 loss in the AB lineage , which generates the neurons , did cause increased fat droplets in muscles ( Figure 2 ) . Unexpectedly , we also found that vpr-1 loss in the germ cell lineage causes muscle fat accumulation ( Figure 2 ) . These results indicate that VPR-1 acts cell nonautonomously in neurons and germ cells ( or their differentiation products ) to modulate fat levels in muscle . vpr-1 null mutants are sterile , due to a failure of germ cells to differentiate into sperm and oocytes . Sperm secrete signaling molecules , such as MSPs that may influence fat metabolism [14] . To test whether sperm affect fat levels , we mated sterile 1-day-old adult vpr-1 ( tm1411 ) hermaphrodites to wild-type males . Supplying sperm to the reproductive tract reduces muscle fat levels in vpr-1 ( tm1411 ) mutants , as visualized with Bodipy-FAs ( Figure S6A ) . Sperm did not rescue the sterility or muscle mitochondrial defects of vpr-1 mutants ( data not shown ) . However , preventing spermatogenesis in wild-type hermaphrodites using the fog-3 ( q443 ) null mutation causes mild muscle fat accumulation , as well as mild mitochondrial morphology defects ( Figure S6B ) , without affecting oxygen consumption [34] . These data indicate that the spermatogenesis defects in vpr-1 mutants contribute to muscle fat levels and perhaps mitochondrial defects . Two mechanisms appear to affect muscle fat levels , one mechanism involving neuronal vpr-1 and a second mechanism involving sperm , which can modify specific vpr-1-dependent pathways . Here , we focus on the neuronal mechanism . Genetic mosaics assess the effect of vpr-1 loss from cells within an otherwise vpr-1 ( + ) background . To test whether VPR-1 expression is sufficient in neurons , we expressed VPR-1 under the control of tissue-specific promoters in vpr-1 null mutants . Consistent with genetic mosaic analysis , VPR-1 expression using the myo-3 muscle-specific promoter or the ges-1 intestine-specific promoter did not influence muscle fat levels . In contrast , over-expressing the vpr-1 cDNA with the unc-119 pan-neuronal promoter completely rescued the muscle fat levels in approximately 30–40% of transgenic mutant worms ( Figures 3A and 3B ) . These rescued transgenic mutants were still sterile . The incomplete rescue appears to be due to the germ line defects ( i . e . lack of sperm ) and missing vpr-1 introns or 3′UTR in the transgene ( P . Cottee and M . Miller , unpublished ) . Consistent with these observations , driving neuronal expression of the vpr-1 genomic locus instead of the cDNA rescued several vpr-1 mutant phenotypes with increased efficiency . These results indicate that VPR-1 acts cell nonautonomously in neurons to regulate muscle fat levels . The VAPB P56S mutation acts as a dominant negative by inhibiting secretion of the wild-type and mutant vMSPs [13] , [15] . To test whether neuronal vMSP secretion affects muscle fat levels , we generated transgenic worms expressing P56S VPR-1 under the unc-119 neuronal promoter . P56S VPR-1 overexpression in wild-type worms causes increased muscle lipid droplets in most worms ( Figure 3A ) , suggesting that vMSP secretion from neurons influences muscle fat accumulation . vMSP signaling to muscle is transduced via muscle SAX-3 Robo and CLR-1 Lar-like receptors [15] . sax-3 mutations cause incompletely penetrant and variably expressed defects in muscle mitochondrial morphology [15] . Similarly , we observed incompletely penetrant defects in muscle fat accumulation by TEM and DIC microscopy ( Figure S2; 11 . 1±13 . 2 fat droplets/mm2 for sax-3 ( ky123 ) [n = 13] versus 0 . 9±1 . 8 droplets/mm2 for wild type [n = 8] ) . Impaired vMSP signaling causes uncontrolled CLR-1 Lar receptor activity and ectopic Arp2/3-dependent actin filaments in muscle . A reduction of clr-1 or arx-2 , which encodes Arp2 , rescues the muscle mitochondrial defects , but not the sterility in vpr-1 mutants [15] . To test whether excess CLR-1 Lar and Arp2/3 activities cause muscle lipid accumulation , we used RNAi to down-regulate their functions in vpr-1 mutants . clr-1 or arx-2 RNAi restored mitochondria to I-bands , as previously reported [15] , and reduced muscle fat droplets in vpr-1 ( tm1411 ) mutants when compared to the mutant control ( Figure 4; 18 . 0±3 . 6 droplets/mm2 for vpr-1 ( tm1411 ) [n = 12] versus 0 . 6±1 . 3 droplets/mm2 for vpr-1 ( tm1411 ) clr-1 RNAi [n = 9 , P<0 . 001] and 3 . 1±2 . 0 droplets/mm2 for vpr-1 ( tm1411 ) arx-2 RNAi [n = 6 , P<0 . 001] ) . Similar results were observed using TEM [15] . We also found that overexpressing arx-2/arp2 specifically in wild-type muscle causes mild mitochondrial morphology and fat accumulation defects ( Figure S7 ) . Taken together , the data strongly support the hypothesis that impaired vMSP signaling from neurons to muscle causes elevated fat levels in muscle . The elevated TAGs in vpr-1 mutants and continuous accumulation of dietary Bodipy-FAs in muscle suggested that fat metabolism and transport pathways are altered . Reduced energy production triggers enhanced activity of the DAF-16/FoxO transcription factor , which controls expression of genes involved in fat synthesis , fat transport , β-oxidation , and stress resistance [35]–[39] . We hypothesized that the muscle cytoskeletal or mitochondrial defects trigger elevated FoxO activity . To investigate if DAF-16 affects fat metabolism in vpr-1 mutants , we generated vpr-1 ( tm1411 ) daf-16 ( mu86 ) double mutants . Muscles of daf-16 ( mu86 ) null mutants contain few Bodipy-FA-stained droplets , similar to muscles of wild-type controls . However , muscle fat levels in the double mutants are also low , and strongly reduced when compared to those in vpr-1 ( tm1411 ) mutants alone ( Figure 5A ) . daf-16 loss did not affect food intake , assessed by measuring pharyngeal pumping rates ( Figure 5B; P>0 . 05 ) , muscle mitochondria ( see below ) , or sterility of vpr-1 ( tm1411 ) mutants . We conclude that the elevated fat levels in vpr-1 null mutants require DAF-16/FoxO activity . We next examined DAF-16/FoxO transcriptional activity using an integrated transgenic line that expresses GFP under the sod-3 promoter ( sod-3p::GFP ) , a direct DAF-16 target [35] , [40] . When worms were cultured under normal growth conditions , about 40–50% of 1-day-old adult vpr-1 ( tm1411 ) transgenic worms showed increased GFP expression relative to control transgenic animals ( Figure 5C ) . By day three of adulthood , most vpr-1 ( tm1411 ) mutants show broad GFP expression throughout the body , including the intestine , neurons , vulva muscles , and body wall muscles . The elevated GFP expression is due to DAF-16 because GFP expression is suppressed in transgenic vpr-1 ( tm1411 ) daf-16 ( mu86 ) double mutants ( Figure 5C ) . These data indicate that vpr-1 loss causes elevated DAF-16 activity in muscles and other cell types . To investigate the mechanism ( s ) by which VPR-1 controls DAF-16/FoxO , we analyzed DAF-16 subcellular localization in vpr-1 ( tm1411 ) mutants . An integrated and rescuing transgenic line was used to express DAF-16::GFP under its endogenous promoter . DAF-16::GFP translocates from cytoplasm to nucleus upon loss of insulin signaling , although other mechanisms exist that regulate nuclear DAF-16 activity independent of translocation [41] , [42] . Under normal growth conditions at 20°C , DAF-16::GFP in vpr-1 mutant and control transgenic strains was distributed throughout the cytoplasm and nucleus with no significant difference between the two strains ( Figures 6A and 6B ) . However , vpr-1 mutants appear more sensitive to higher temperatures that require increased metabolic activity ( Figures 6A and 6B ) . We conclude that VPR-1 does not have a strong effect on DAF-16 nuclear translocation under standard conditions . The results thus far strongly support the model that impaired vMSP signaling to muscle triggers DAF-16-dependent muscle fat accumulation . We hypothesized that cytoskeletal or mitochondrial abnormalities in vpr-1 mutant muscles induce elevated DAF-16 transcriptional activity . If this idea is correct , then inactivating the Arp2/3 complex in vpr-1 mutants should attenuate DAF-16 activity . To assess DAF-16 transcriptional activity , we used the integrated sod-3p::GFP transgenic reporter . arx-2/arp2 RNAi in vpr-1 ( tm1411 ) mutants causes a strong reduction in sod-3p::GFP expression in body wall muscle , the intestine , and other cells ( Figure 6C ) . arx-2 RNAi in wild-type worms has little effect on GFP expression . Therefore , the elevated DAF-16 activity in vpr-1 mutants is at least partially dependent on the Arp2/3 complex . One possibility is that DAF-16 causes the mitochondrial abnormalities in vpr-1 mutants . To test this model , we first evaluated mitochondria using the mitoGFP transgene expressed in body wall muscle . As previously documented [15] , wild-type muscles contain linear mitochondrial tubules positioned along I-bands . In contrast , vpr-1 ( tm1411 ) mutants contain disorganized and interconnected mitochondrial networks in the muscle belly ( Figure 7A ) . Loss of daf-16 in vpr-1 ( tm1411 ) mutants did not affect muscle mitochondrial morphology or localization ( Figure 7A ) . Next , we examined mitochondrial functional status using MitoTracker CMXRos , which accumulates in the mitochondrial matrix depending on membrane potential , and oxygen consumption of whole worms . DAF-16 loss did not affect the reduced MitoTracker CMXRos accumulation ( Figure 7B ) or the low oxygen consumption rates of vpr-1 mutants ( Figures 7C and 7D ) . We conclude that DAF-16 does not affect the muscle mitochondrial defects in vpr-1 mutants and likely acts downstream of Arp2/3 . As the intestine and epidermis are fat storage sites in C . elegans , we hypothesized that the increase in muscle fat is an attempt to provide fuel for energy production . Our previous studies showed that 1-day-old adult vpr-1 ( tm1411 ) mutants have reduced ATP levels when compared to controls [15] . However , the ATP levels in vpr-1 mutants did not decrease over the next two days , as observed in the wild type ( Figure 8A ) . 3-day-old adult vpr-1 ( tm1411 ) mutants had higher ATP levels than wild-type controls at the same age ( Figure 8A ) . Similar ATP dynamics have been observed in aging worms with mutations in the daf-2 insulin receptor or clk-1 , a mitochondrial protein involved in ubiquinone biosynthesis [43] , [44] . Hence , DAF-16 may help maintain ATP levels in these aging worms . To test whether DAF-16 affects the energy balance of vpr-1 mutants , we measured ATP levels in single and double mutant extracts . daf-16 loss did not influence ATP levels in 1-day-old adult vpr-1 ( tm1411 ) mutants ( Figure 8A ) . However , daf-16 is required for the high ATP concentration in 3-day old mutant adults ( Figure 8A; P<0 . 001 ) . ATP levels in daf-16 mutants are similar to wild-type controls ( data not shown ) , as previously shown [43] , [44] . These data indicate that DAF-16/FoxO helps vpr-1 mutants maintain ATP levels during aging . Based on the abnormalities in energy metabolism , we tested whether DAF-16 influences lifespan in vpr-1 mutants . Similar to other worm mutants with mild or tissue-specific reduction in mitochondrial function , vpr-1 ( tm1411 ) mutants have slightly extended adult lifespan compared to wild-type worms ( Figure 8B; mean adult lifespan ± SD of 12 . 9±4 . 4 days [n = 154] for vpr-1 ( tm1411 ) versus 10 . 5±2 . 1 days [n = 159] for wild type , P<0 . 001 ) . daf-16 loss in vpr-1 ( tm1411 ) mutants causes a strong reduction in lifespan relative to vpr-1 mutants and wild-type controls ( Figure 8B; 6 . 9±2 . 5 days for vpr-1 ( tm1411 ) daf-16 ( mu86 ) [n = 250]; P<0 . 001 ) . The lifespan of daf-16 single mutants was similar to wild type ( data not shown ) , as previously shown [38] , [45] . These data indicate that DAF-16/FoxO activity extends survival of vpr-1 mutants . The data thus far indicate that VPR-1 loss causes profound defects in muscle energy metabolism . We hypothesized that the regulatory function of vMSPs on energy metabolism was conserved in mammals , and studied energy metabolism of Vapb −/− mice [4] . In basal conditions , Vapb −/− mice do not exhibit overt defects in energy metabolism . In particular , body weight and glycemia appear normal with age ( L . Dupuis , unpublished results ) . However , an energy metabolism defect of Vapb deficient mice might be unmasked by modifying insulin supply through feeding and fasting paradigms . In worms and mice , fasting reduces insulin signaling and increases FoxO activity , resulting in altered metabolic gene expression . We used Vapb −/− mice of 2–6 months of age to avoid any confounding effect of the motor dysfunction observed at 18 months [4] . Mice were either fasted for 24 hours ( fasted group ) or fasted for 16 hours and refed for 8 hours to synchronize meals ( fed group ) . In +/+ mice , fasting decreased the TAG levels in the gastrocnemius ( GA ) muscle ( Figure 9A; P<0 . 05 ) . In contrast , TAG levels remained unchanged upon fasting in Vapb −/− GA and tibialis anterior ( TA ) muscles ( Figure 9A and data not shown ) . In liver , TAG levels were unchanged upon fasting and feeding in either +/+ or −/− mice ( Figure 9A ) . Thus , Vapb ablation increases the resistance of muscle lipid stores to fasting induced mobilization . We next looked at mRNA levels of metabolic genes by quantitative RT-PCR . In liver , Vapb ablation potentiated induction of the direct FoxO1 target gene phosphoenolpyruvate carboxykinase ( PEPCK ) in response to fasting , but had no effect on fasting induction of other FoxO1 targets such as glucose 6-phosphatase ( G6Pase ) and pyruvate dehydrogenase kinase ( PDK4 ) ( Figure 9B ) . FoxO1 and FoxO3 mRNA and proteins were similar in +/+ and −/− livers , and FoxO1 up-regulation by fasting appeared normal in −/− liver ( Figure 9B ) . We also examined putative FoxO1 and FoxO3 target genes in +/+ and mutant TA muscle . Feeding decreased expression of PEPCK , G6Pase , and lipoprotein lipase ( LPL ) , and increased expression of the lipogenic transcription factor SREBP1c ( Figure 9C ) . This regulation was lost in Vapb −/− muscles , as feeding did not modify expression of these four genes . Vapb genotype did not affect levels of PDK4 mRNA . FoxO1 and FoxO3 expression was down-regulated upon feeding in control TA muscles , but FoxO3 regulation was lost in −/− muscles ( Figure 9C ) . The expression of muscle FoxO3 targets LC3 and Atrogin1 was up-regulated in fed −/− mice , while another FoxO3 target , ATG12 , was unchanged . These results indicate that muscles of Vapb −/− mice are partially insensitive to fasting/feeding alterations in lipid mobilization and FoxO target gene expression . Hence , Vapb mutant worms and mice appear to have muscle energy metabolism alterations , at least in part involving FoxO targets . Whether the putative metabolic changes in mouse muscle are due to secreted vMSPs is not yet clear .
VAPs physically interact with multiple proteins involved in lipid binding and transport , such as oxysterol binding protein and ceramide-transfer protein [10] , [11] , [30] , [46] . Although the biological role of these interactions is not well understood , VAPs have been proposed to act in macromolecular complexes for transporting lipids between organelles at membrane contact sites . This mechanism depends on VAP function in the same cell in which lipid dynamics occur ( i . e . a cell autonomous function ) . Here we show in C . elegans that vpr-1/vap loss triggers a robust increase in striated muscle TAG levels . Unexpectedly , this function does not require VPR-1 in muscle . Genetic mosaic and cell-type specific expression studies demonstrate that VPR-1 acts in neurons , consistent with the signaling function . Indeed , muscle vMSP receptors and the downstream Arp2/3 complex mediate this lipid metabolism response . We also found that sperm presence can modulate striated muscle TAG metabolism . Neurons and sperm are two cell types capable of secreting MSP domains [15] , [47] . Our data do not exclude cell autonomous roles for VPR-1 in regulating lipid dynamics . Nevertheless , they highlight the importance of testing VAP autonomy when evaluating biological mechanism . We show that vpr-1/vap loss triggers elevated DAF-16/FoxO activity , resulting in muscle TAG accumulation . Inactivating the Arp2/3 complex largely suppresses these metabolic alterations , as well as the muscle mitochondrial defects . These data support the model that impaired vMSP signaling to muscle triggers elevated FoxO activity . Consistent with this model , over-expressing Arp2 specifically in wild-type muscle causes TAG accumulation and mitochondrial defects . Although we cannot eliminate the possibility that Arp2/3 acts in other tissues , it appears to be a muscle-specific suppressor of vpr-1 mutants . How might the Arp2/3 complex regulate FoxO ? One possibility is that vpr-1 mutants go into energy deficit as they age , as mitochondrial dysfunction is thought to increase FoxO activity [48]–[51] . An alternative possibility is that FoxO acts downstream of Arp2/3 , but in parallel to mitochondria . In either case , reduced insulin signaling could be involved . A strong reduction in insulin causes increased FoxO nuclear translocation , which is not observed in vpr-1 mutants under standard conditions . However , subtle changes can be more difficult to detect . Additional mechanisms could also modulate FoxO in vpr-1 mutants . The vMSP/ephrin receptor VAB-1 directly interacts with DAF-18/PTEN ( phosphatase and tensin homolog deleted on chromosome ten ) , which regulates FoxO activity [52] . VAB-1 is expressed throughout the adult nervous system and in the gonad [53] , [54] . Previous studies have shown that sperm presence can modulate DAF-16/FoxO translocation and transcriptional activity [55] , perhaps through secreted MSPs . Whether sperm act via the Arp2/3 complex is not clear . An interesting possibility is that global MSP signals from neurons and sperm are sensed through distinct mechanisms . These mechanisms might converge on muscle metabolic output to meet changes in energy requirements . In mammals , FoxO transcription factors are critical regulators of energy metabolism , particularly under fasting conditions . We show that Vapb ablation in mice renders muscle lipid stores resistant to fasting , a situation analogous to lipid accumulation in vpr-1 mutant worm muscles . Dysregulated lipid stores in mutant mice is associated with alterations in muscle gene expression consistent with abnormal FoxO1 and FoxO3 activity [56] . For instance , FoxO1 target gene mRNAs for PEPCK and G6Pase are clearly up-regulated in muscle of young Vapb −/− mice in the fed state ( i . e . in the presence of insulin that decreases FoxO1 activity ) . Similar results are observed for FoxO3 target genes LC3 and Atrogin-1 . These data suggest that FoxO1/3 are less sensitive to insulin inhibition in Vapb −/− mice . Not all FoxO target genes studied are sensitive to Vapb ablation . For instance , VAPB does not appear to influence PDK4 and ATG12 mRNAs . Additionally , some of the mRNAs studied showed uncoupling from circulating insulin levels , consistent with an insensitivity of FoxO1 to insulin . SREBP1c mRNA , which is negatively regulated by FoxO1 [57] , was increased by feeding in +/+ mice , but not in −/− mice . A similar , albeit mirror situation was observed for LPL , a gene positively regulated by FoxO1 [58] . Hence , FoxO1/3 might participate in the abnormal lipid mobilization in Vapb −/− mice , but other mechanisms are likely at work to avoid the major consequences of chronic muscle FoxO activation , such as muscle atrophy [59] . In summary , our findings show that VAPB is involved in modulating mouse muscle energy metabolism upon fasting and refeeding , possibly via altered FoxO activity . Whether this occurs through a cell autonomous or a cell nonautonomous mechanism , like in C . elegans and Drosophila , remains to be determined . A key finding in worms is that DAF-16/FoxO activity prolongs the adult lifespan of vpr-1 mutants from 6 . 9±2 . 5 to 12 . 9±4 . 4 days . This lifespan increase may be due to metabolic alterations that compensate for mitochondrial dysfunction . Consistent with this idea , FoxO extends the lifespan of C . elegans with reduced mitochondrial function [48] , [49] , [60] . The FoxO-dependent fat accumulation in vpr-1 mutant muscle may reflect an effort to increase energy production . We show that DAF-16 helps vpr-1 mutants maintain ATP levels in 3-day old adults . Among the numerous DAF-16 metabolic genes are those involved in fat synthesis and transport , β-oxidation , the glyoxylate cycle , and gluconeogenesis [37] . However , additional DAF-16 targets may also be involved , such as stress resistance enzymes [37] , [38] , [61] . vpr-1 mutants are more resistant than the wild type to reactive oxygen species and ER stress . Based on identified DAF-16 targets and vpr-1 mutant phenotypes , DAF-16 might increase energy substrate availability in muscle , stimulate anaerobic metabolism , increase oxidative metabolism in non-muscle cells , or decrease ATP consumption . Further studies are necessary to distinguish among these possibilities , as well as other models . Metabolic alterations in ALS patients and mouse models are hypothesized to compensate for mitochondrial dysfunction , particularly in skeletal muscle [17] , [19] , [62] , [63] . Differentially expressed gene networks involved in oxidative metabolism and the cytoskeleton , including up-regulated FoxO1 and FoxO3 mRNAs have been found in ALS patient skeletal muscles [64] , [65] . Our studies of VAPB in worms , flies , and mice are consistent with impaired vMSP signaling to muscle causing some of these alterations . Importantly , vpr-1 loss in worms , Vapb depletion in zebrafish , or Vapb loss in mice does not cause motor neuron degeneration [4] , [15] , providing strong evidence that mitochondrial and metabolic defects are not secondary consequences of neurodegeneration . These data contrast with a recent Drosophila study suggesting that Vapb loss causes neurodegeneration via increased phosphoinositides [66] . In humans , metabolic alterations caused by reduced VAPB function may not be sufficient to induce motor neuron degeneration , although they could strongly predispose to ALS . Redundancy could be an important consideration in the different models . The worm genome encodes a single vap homolog , but many genes with MSP domains . Vertebrate genomes typically encode VAPA and VAPB , which are approximately 60% identical . Vap mutant flies have the most severe developmental defects and the fewest MSP genes in the genome . In summary , our results support the model that striated muscle mitochondrial dysfunction alters FoxO activity , which in turn affects energy metabolism and promotes survival . It is possible that reduced vMSP signaling causes some of the mitochondrial and metabolic alterations in ALS patients . Perhaps vMSPs might protect against ALS via effects on skeletal muscle energy metabolism .
C . elegans Bristol N2 is the wild-type strain . Worms were grown on NGM plates with NA22 bacteria as the food source [67] . Strain construction and marker scoring were done as previously described [15] , [54] . The strains and genetic markers used or generated were as follows: CF1553 muIs84[pAD76 ( sod-3::GFP ) ] , CF1038 daf-16 ( mu86 ) I , vpr-1 ( tm1411 ) /hT2[bli-4 ( e937 ) let- ? ( q782 ) qIs48] I;III , SJ4005 zcIs4[hsp-4::GFP] , TJ356 zIs356[daf-16p::daf-16::GFP; rol-6] IV , fog-3 ( q443 ) I/hT2[bli-4 ( e937 ) let- ? ( q782 ) qIs48] I;III , CX3198 sax-3 ( ky123 ) X , and XM1004 vpr-1 ( tm1411 ) daf-16 ( mu86 ) /hT2[bli-4 ( e937 ) let- ? ( q782 ) qIs48] I;III . Transgenics expressing vit-2p::vit-2::gfp were generated by crossing into the pwIs23 integrated line . RNAi was performed using the feeding method starting at the L1 stage , as previously described [15] . arx-2 , clr-1 , and xbp-1 RNAi clones are from the genome-wide library [68] . Each clone was sequenced for confirmation . To generate transgenic C . elegans , the marker plasmids pRF4 [rol-6] ( 60 ng/µl ) or myo-3p::mito::GFP ( 30–60 ng/µl ) were mixed with myo-3p::vpr-1 ( 60 ng/µl ) , ges-1p::vpr-1 ( 60 ng/µl ) , unc-119p::vpr-1 ( 60 ng/µl ) , unc-119p::vpr-1 P56S ( 60 ng/µl ) , or myo-3p::arx-2::mCherry ( 60 ng/µl ) and microinjected into the gonads of young adult hermaphrodites . Injected worms were incubated for 24 hours , transferred to new NGM plates , and screened for transgenic progeny . Transgenic lines were selected based on the roller phenotype or GFP expression . Multiple independent transgenic lines were generated for all strains . To conduct genetic mosaic analysis , 10 ng/µl WRM06B28 fosmid DNA containing the vpr-1 genomic locus was mixed with 10 ng/µl pTG96 ( sur-5p::GFP ) plasmid and microinjected into the gonads of vpr-1 ( tm1411 ) /hT2 hermaphrodites . Transgenic lines were selected based on GFP expression . Transgenic lines were maintained as vpr-1 ( tm1411 ) homozygotes , as the fosmid rescued the sterility , mitochondria , fat metabolism , slow growth , and embryonic defects . For lineage scoring , approximately 15 , 000 worms were screened . Transgene loss in the AB lineage was scored by GFP loss in head and tail neurons , the nerve cords , and the excretory gland . Transgene loss in the P1 lineage was scored by GFP loss in the intestine , muscle , somatic gonad , and hyp11 . The P2 lineage was scored by GFP loss in numerous body wall muscle cells and hyp11 , the P3 lineage was scored by GFP loss in body wall muscle , and the P4 lineage was inferred by a sterile phenotype without GFP loss . Transgene loss in the EMS lineage was scored by GFP loss in the intestine and somatic gonad , while loss in the E lineage was score by exclusive GFP loss in the intestine . TEM was performed as previously described [15] . For the Bodipy-FA experiments , a 5 mM Bodipy-FA ( Molecular probe , U . S . A ) stock solution was prepared in DMSO and kept at −20°C . A 200 µM working solution diluted in distilled water was dropped onto seeded plates and allowed to dry . L4 stage worms were placed on the plates and incubated in the dark for 24 hours at 20°C . Bodipy-FAs can get trapped in intestinal gut granules that are not present in muscle . Sudan Black B staining was conducted as described in previous studies [15] . Briefly , synchronized 1-day-old adult worms were collected into microfuge tubes containing M9 solution . Worms were washed five times , incubated for 40 minutes at 20°C to remove intestinal bacteria , and fixed in 1% paraformaldehyde . The fixed worms were washed three times in cold M9 solution and dehydrated through a 25% , 50% , and 70% ethanol series . Sudan Black B solution was added to the worms and incubated for 1 hour . To remove excess stain , worms were washed five times with 70% ethanol . To normalize for staining variability among experiments , wild type and vpr-1 ( tm1411 ) mutants were processed in the same tube and identified based on gonad morphology . For the lipid analysis by ESI-MS/MS , lipids from equal masses of wild type and vpr-1 ( tm1411 ) mutant adults were extracted by chloroform-methanol following a modified Bligh/Dyer extraction [69] . A mixture of internal standards including T17:1 TAG was added to the chloroform-methanol phase before extraction . The extracted samples were concentrated to dryness under a nitrogen stream , reconstituted with methanol∶chloroform ( 1∶1 v/v ) and transferred to HPLC auto samplers . Lipids were analyzed by ESI-MS/MS using an API 4000 ( Applied Biosystems/MDS Sciex , Concord , Ontario , Canada ) triple quadrupole mass spectrometer . Extracted lipid samples ( 5 ml ) were infused into the mass spectrometer with a solvent mixture of chloroform-methanol ( 1∶2 , v/v ) containing 0 . 1% formic acid using a Shimadzu Prominence HPLC with a refrigerated auto sampler ( Shimadzu Scientific Instruments , Inc . Columbia , MD ) . Lipids were analyzed in positive ion mode using an API 4000 ( Applied Biosystems/MDS Sciex , Concord , Ontario , Canada ) triple quadruple mass spectrometer . Samples ( 5 µl ) were directly infused into the electrospray source using a Shimadzu Prominence HPLC with a refrigerated auto sampler ( Shimadzu Scientific Instruments , Inc . Columbia , MD ) . Neutral loss ( NL ) scanning ( 228 , 254 , 256 , 268 , 278 , 280 , 284 , and 304 ) of naturally occurring aliphatic chains ( i . e . building block of TAG molecular species ) were utilized to determine the identities of each molecular species . NL scanning of 141 was used for profiling phosphatidylethanolamine . The following analysis parameters were used: ion spray voltage 5000 V , de-clustering potential 40 V , temperature 300°C ( for TAG ) , collision energy 35 V , and collisionally activated dissociation 5 . To assess mitochondrial transmembrane potential , worms were stained using the MitoTracker CMXRos dye ( Molecular Probes , U . S . A ) , as previously described [15] . This lipophilic cationic fluorescent dye accumulates in mitochondria in a membrane potential-dependent manner [70] . L4 larval stage worms were placed on dried plates containing a 100 µM MitoTracker CMXRos dye solution ( dropped on bacteria ) . After 24 hours incubation in the dark , worms were transferred to a new NGM plate and incubated in the dark for 20 minutes to remove intestinal background . Worms were mounted on dried 2% agarose pads without anesthetic . Wild-type and vpr-1 ( tm1411 ) mutant hermaphrodites were cultured on the same plates . ATP concentration was measured as described previously , with slight modification [15] . Briefly , 150 worms were individually picked and placed into tubes containing M9 buffer , washed four times , and incubated at 20°C for 40 minutes to remove intestinal bacteria . These worms were then washed four times with TE solution ( 100 mM Tris–Cl , pH 7 . 6 , 4 mM EDTA ) and placed into microfuge tubes containing 300 µl TE solution . Worm extracts were prepared by a series of cycles including freezing , thawing , and sonicating . These extracts were boiled for 10 minutes to release ATP and block ATPase activity . Carcasses and insoluble material were pelleted in a microcentrifuge at 20 , 000×g for 10 minutes . The soluble extracts were diluted in a 1∶10 ratio using TE solution . ATP concentration in 60 µl of diluted extracts was measured using the ENLITEN ATP Assay System ( Promega , U . S . A ) , according to the manufacturer's instructions . A luminometer ( Berthold , Germany ) was used for quantification . Protein concentration was determined using the BCA protein assay ( Pierce , U . S . A ) . ATP measurements were repeated at least three times for each strain . Oxygen consumption rates were measured as previously described using the oxygraph system ( Hansatech , UK ) with minor modifications [15] . Worms were cultured at 20°C and synchronized to the 1-day-old adult stage . For each test , 1000 worms were individually picked and placed into a glass tube with 1 ml M9 buffer at 20°C . Collected worms were incubated for 40 min at 20°C to remove intestinal bacteria , carefully washed five times , and placed into 1 ml M9 buffer . The worm solution was loaded into the chamber equipped with a S1 Clark type polarographic oxygen electrode disc maintained at 20°C . Oxygen concentration was measured for 10 minutes . For normalization , worms were carefully collected from the chamber and protein content was measured using the BCA test kit ( Pierce , U . S . A . ) . Rates were normalized to either total protein content or number of worms . We performed at least three independent measurements per strain . To measure feeding rates , worms were cultured at 20°C and 1-day-old adult worms were placed on new NGM plates . Feeding behavior was recorded using a Zeiss Lumar stereomicroscope with AxioCam MRM digital camera . Measurements were conducted during a 30 second period at room temperature ( 22°C ) . The rhythmic contractions of the pharyngeal bulb were counted . For each strain , over 20 worms were counted . To determine lifespan of worms , L4 larval stage worms were placed on new NGM plates seeded with NA22 bacteria and cultured at 20°C . The L4 stage was used because a small percentage of vpr-1 mutants die during L1–L4 stages and vpr-1 mutants develop slowly . Worms were monitored every day and transferred to flesh NGM plates . Death was scored by failure to respond to touching with a platinum wire . Wild-type worms fed NA22 bacteria have slightly shorter lifespan than worms fed OP50 bacteria . To analyze ER homeostasis , worms were cultured on plates with tunicamycin ( Sigma , U . S . A ) from the embryonic stage to adulthood . NGM plates with 0 . 1% DMSO and 0 or 5 . 0 µg/ml tunicamycin were prepared . About 30 adult worms were placed on each tunicamycin plate and allowed to lay embryos for 30 minutes . Adult worms were then removed . Twelve hours later the number of hatched embryos was counted and compared with the number of worms that reached the adult stage within 96 hours . We performed at least three independent measurements for each strain . Mouse experiments were performed using the Institutional European Guidelines , under the supervision of an authorized investigator ( LD ) , and approved by the local ethical committee for animal experiments ( CREMEAS , agreement N° AL/01/08/02/13 ) . Vapb −/− mice were used and genotyped as described [4] . Mice ( 8–10 per group ) were either fasted for 24 hours from 5PM ( fasted group ) , or fasted from 5PM to 9AM and refed until sacrifice at 5PM . GA and TA muscle and liver tissues were collected , and rapidly frozen in liquid nitrogen for subsequent analyses of gene expression and TAG levels . The tissues were stored at −80°C until the time of analysis . For RT-qPCR , frozen liver and muscle tissues were placed into tubes containing 5 mm stainless steel beads ( Qiagen , Courtaboeuf , France ) and 1 ml of Trizol reagent ( Invitrogen , Paisley , UK ) and homogenized using a TissueLyser ( Qiagen ) . RNA was prepared from tissue homogenates following Trizol manufacturer's instructions . RNA reverse transcription and SYBR Green real-time PCR assays were performed using the Bio-Rad ( Biorad , Marnes la Coquette , France ) iCycler kits and protocols . PCR conditions were 3 min at 94°C , followed by 40 cycles of 45 s at 94°C and 10 s at 60°C . Primers are shown in Table S1 . For western blotting , liver and TA muscles were incubated in Lysis buffer containing complete protease and phosphatase inhibitor cocktails . Protein concentration was measured using BCA Protein Assay . Equal amount of protein ( 50 µg ) were separated by SDS-PAGE 10% and blotted onto nitrocellulose membrane . Membranes were saturated with 10% milk and then incubated with the primary antibodies FoxO1 ( Proteintech; 18592-1-AP ) , FoxO3a ( Cell signaling; #2497 ) , VAPB [4] and Histone H3 ( Cell signaling; #9715 ) , all diluted ( 1∶1000 ) followed by anti-rabbit secondary antibody , diluted 1∶5000 . For TAG analysis , tissue powder was homogenized in lysis buffer ( 250 mM Sucrose solution , 1 mM EDTA , 2% SDT , 1 mM DTT , 10 mM Tris HCl pH 7 . 4 ) containing protease inhibitors ( Sigma P8340 ) and phosphatase inhibitors ( Sigma 8345 ) , centrifuged at 12000×rpm for 15 minutes at room temperature . TAG concentration was determined in duplicate for each sample in 5 µl of supernatant , using the enzymatic method of analysis ( Randox Triglyceride Colorimetric Assay Kit , Randox Laboratories Limited , UK ) as described by the manufacturer . Lipid values were normalized to protein concentration .
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ALS patients often present with systemic alterations in energy metabolism , such as dyslipidemia and hypermetabolism of unknown origin . Reduction of Vapb function is thought to cause motor neuron disease in ALS8 patients and may predispose individuals to ALS , in general . We have shown that neurons secrete the N-terminal VAPB vMSP into the extracellular environment . The secreted vMSPs signal through Roundabout and Lar-like receptors on striated muscles . This neuron to muscle signaling pathway localizes mitochondria to myofilament I-bands and promotes mitochondrial function . Here we show that loss of VAPB in C . elegans neurons causes metabolic changes in muscles , including altered fat metabolism and elevated DAF-16 FoxO transcription factor activity . DAF-16 promotes muscle triacylglycerol accumulation , increases ATP levels , and prolongs survival in Vapb mutants . However , it does not influence muscle mitochondrial localization nor does it affect oxygen consumption . We also show that Vapb knockout mice exhibit disrupted muscular triacylglycerol and FoxO target gene transcriptional responses to fasting and refeeding . These data indicate that impaired vMSP signaling to muscle triggers an energy deficiency , which induces a protective metabolic response involving FoxO . Hence , some energy metabolism alterations observed in ALS patients might be a consequence of striated muscle mitochondrial dysfunction .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2013
|
VAPB/ALS8 MSP Ligands Regulate Striated Muscle Energy Metabolism Critical for Adult Survival in Caenorhabditis elegans
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The protozoan Trypanosoma cruzi is the causative agent of Chagas disease . There are no vaccines or effective treatment , especially in the chronic phase when most patients are diagnosed . There is a clear necessity to develop new drugs and strategies for the control and treatment of Chagas disease . Recent papers have suggested the ecto-nucleotidases ( from CD39 family ) from pathogenic agents as important virulence factors . In this study we evaluated the influence of Ecto-Nucleoside-Triphosphate-Diphosphohydrolase ( Ecto-NTPDase ) activity on infectivity and virulence of T . cruzi using both in vivo and in vitro models . We followed Ecto-NTPDase activities of Y strain infective forms ( trypomastigotes ) obtained during sequential sub-cultivation in mammalian cells . ATPase/ADPase activity ratios of cell-derived trypomastigotes decreased 3- to 6-fold and infectivity was substantially reduced during sequential sub-cultivation . Surprisingly , at third to fourth passages most of the cell-derived trypomastigotes could not penetrate mammalian cells and had differentiated into amastigote-like parasites that exhibited 3- to 4-fold lower levels of Ecto-NTPDase activities . To evidence the participation of T . cruzi Ecto-NTPDase1 in the infective process , we evaluated the effect of known Ecto-ATPDase inhibitors ( ARL 67156 , Gadolinium and Suramin ) , or anti-NTPDase-1 polyclonal antiserum on ATPase and ADPase hydrolytic activities in recombinant T . cruzi NTPDase-1 and in live trypomastigotes . All tests showed a partial inhibition of Ecto-ATPDase activities and a marked inhibition of trypomastigotes infectivity . Mice infections with Ecto-NTPDase-inhibited trypomastigotes produced lower levels of parasitemia and higher host survival than with non-inhibited control parasites . Our results suggest that Ecto-ATPDases act as facilitators of infection and virulence in vitro and in vivo and emerge as target candidates in chemotherapy of Chagas disease .
Trypanosoma cruzi is the etiologic agent of Chagas disease , an endemic zoonosis present in some countries of South and Central Americas . WHO estimates suggested that 100 million people remain at risk of acquiring this infection [1] . There are no vaccines or effective treatment for this disease , especially in the chronic phase [2] . Many compounds are potential candidates to be used in the treatment for Chagas disease , such as TAK-187 , D0870 , albaconazole and allopurinol [2] . In spite of these , there is a clear necessity to develop new drugs and strategies for the control and treatment of Chagas disease [2] . From this point of view , virulence biomolecules , in particular those secreted or ecto-localized at the parasite's plasma membrane seem to be good targets . The concentrations of extra cellular nucleotides and their derivative molecules , such as adenosine and inosine are linked to ecto-nucleotidase activities of cells [3] , [4] . The role of ecto-nucleotidases as the major biomolecules involved in the control of purinergic signaling were demonstrated in various models , such as the dominant role of CD39 in the modulation of inflammation and immune response in the Langerhans cells [5] and in cardioprotection and protective responses to hypoxia/ischemia in murine model [6] , [7] . ATP has been previously demonstrated as a “danger” extracellular signal induced by pathogen infection or injury , and it is able to trigger different cellular events such as proliferation , differentiation and chemotaxis , release of cytokines or lysosomal constituents , and generation of reactive oxygen or nitrogen species [4] . Some authors believe that a high ecto-ATPase activity of pathogen is an adaptive parasitic behavior that made these organisms more virulent because they interfere with extracellular ATP signals [8]–[11] . Members of Ecto-NTPDase family are nucleotidases able to hydrolyze 5′-nucleoside tri- and/or diphosphates; the main role of these enzymes is the termination of purinergic signaling [12] . NTPDases are ubiquitous and were previously shown in other parasites including the trypanosomatides of genus Leishmania and in T . brucei [13]–[16] . Recent papers have suggested the ecto-nucleotidases from pathogenic agents , including parasites , and in a special way the Ecto-NTPDases ( from CD39 family ) as important virulence factors [9] , [14] , [17]–[21] . This hypothesis was clearly evidenced in Toxoplasma gondii and Legionela pneumophila [8] , [11] , [22] . In T . gondii the NTPase , a member of CD39 family , is produced as a soluble low activity tetrameric enzyme in the parasitophorous vacuole . Activation of this enzyme by dithiol agent ( DTT ) leads to depletion of host ATP levels and rapid exit of intracellular parasites from infected cells [8] . These data support the idea that activation of NTPase is an event related with the end of one intracellular parasite life cycle and the start of another cellular infection . In other words , NTPase activity would act as a timer and is crucial to T . gondii infection . In addition , Naakar and coworkers showed that lowering the expression of NTPDase by RNA antisense technology inhibits T . gondii proliferation in in vitro infection [22] . In L . pneumophila it was demonstrated that an Ecto-NTPDase , similar to CD39 , is essential for intracellular bacterial multiplication . The authors showed that this pathogenic bacterium has two Ecto-NTPDases ( lpg0971 and lpg1905 ) , and only the product of lpg1905 is implicated with in vitro intracellular multiplication and mice virulence [11] , [23] . T . cruzi is another example of pathogenic agent in which Ecto-NTPDase was suggested as a virulence factor . The first evidence of an ecto-nucleotidase at the T . cruzi surface was the demonstration of an ecto-ATPase activity in intact parasites that was partially sensitive to 4 , 4′-diisothiocyanatestilbene-2 , 2′-disulfonic acid ( DIDs ) [24] . Subsequently , three papers showed evidence that surface T . cruzi ecto-ATPase could modulate parasite-host interaction [10] , [17] , [25] . Bisaggio and co-workers [10] showed that treatment with ecto-ATPase inhibitors ( Suramin and DIDs ) lead to inhibition of ATPase activity , adhesion and internalization of parasites in macrophage in vitro infection [10] . In addition , the over-expression of ecto-ATPase activity was followed by a dramatic increase in parasite adhesion to resident macrophages . In 2004 our group obtained the first biochemical characterization and immunolocalization of an Ecto-NTPDase on the T . cruzi surface [17] . In the same work we isolated a cDNA encoding an Ecto-NTPDase homologue to CD39 family enzymes . Because trypomastigotes presented higher levels of ecto-ATPase activity than epimastigotes and because the literature clearly pointed to ATP as a pro-inflammatory molecule we suggested that ecto-ATPase activity could be related with parasite virulence [17] . In the present work , we show that a high ratio of ecto-ATP/ADP hydrolysis is important to maintain the capacity of parasites to infect mammalian VERO cells . Additionally , Ecto-NTPDase inhibition modulates infectivity and virulence to mice , suggesting that NTPDase is a facilitator of T . cruzi infection .
Giemsa was purchased from Merck ( D-6100 Darmstadt , Germany ) . ARL67156 , Suramin , GdCl3 , ATP , ADP and AMP were purchased from Sigma Chemical Co . ( St . Louis , MO ) . Distilled water was deionized using a MilliQ system ( Millipore Corp . , Bedford , MA ) and was used in the preparation of all solutions . Different T . cruzi strains , Y , CL , Be-62 ( all from the T . cruzi II lineage ) and CL Brener ( a hybrid cloned strain ) were maintained for successive blood passages in mice . Vero cells lines ( carcinoma-derived African green monkey fibroblast cells ) were seeded in 75 cm2 flasks at a density of 5×104 and sustained in RPMI 1640 medium ( GIBCO BRL ) supplemented with 5% fetal calf serum ( FCS , from CULTILAB , Campinas , SP , Brazil ) and 1 mM L-glutamine ( Sigma Aldrich ) . After 48 h of plating , the cultures were infected with bloodstream Y strain trypomastigotes harvested from T . cruzi-infected Swiss mice by orbital venous sinus puncture on the day of peak parasitemia employing a parasite/host cell ratio of 10∶1 . After infection the cell cultures were maintained at 37°C in 5% CO2 atmosphere for 24 h for parasite internalization . After this time , cells were washed three times with phosphate buffered saline ( PBS ) solution , RPMI medium with 1% fetal calf serum ( 15 mL ) was added and cells were incubated at 33°C , 5% CO2 atmosphere , for completion of the intracellular cell cycle of parasites . Vero cell-derived trypomastigotes were isolated from culture supernatants of infected cells after centrifugation at 2500×g for 15 min . The recently released cell-derived trypomastigotes were used for infection of new cells grown in 75 cm2 flasks employing a parasite/host cell ratio of 10∶1 and maintained for four sub-cultivation passages in Vero cells . Parasites derived from cells infected with bloodstream trypomastigotes were called trypomastigotes of first cell passage ( P1 ) , and those obtained from the successive sub-inoculations performed with parasites derived from Vero cells were denominated trypomastigotes of 2nd , 3rd and 4th passages ( P2 , P3 , P4 ) . CL , Be-62 or CL-Brener parasites were recovered only after the first passage ( P1 ) , Y strain parasites were recovered in P1 for “in vitro” infectivity assays and in vivo infectivity and virulence determination using Swiss mice as experimental model . Afterwards the Y strain was maintained until the fourth passage in the continuous cultivation assay . Intact live parasites were washed twice in 0 . 9% NaCl and suspended ( 1 . 0×108 cells/ml ) in nucleotidase reaction medium without nucleotides ( 116 mM NaCl , 5 . 4 mM KCl , 5 . 6 mM D-glucose , 50 mM Hepes-Tris buffer , pH 7 . 2 ) . The assays were carried out in 125 µL total reaction volume . The reactions were started with the addition of 2 . 5 mM ATP or ADP , in the presence of 5 mM MgCl2 and were carried out as detailed elsewhere [14] . For the in vitro hydrolytic activity assays performed in the presence of specific ecto-ATPase inhibitors or polyclonal antiserum anti-NTPDase-1 , parasites were exposed during the entire experimental time to the concentrations described in the Results . The ecto-nucleotidase activities were determined by measurement of inorganic phosphate ( Pi ) released to the medium after 1 hour of incubation at 37°C [26] . The recombinant T . cruzi apyrase NTPDase-1 ( Accession No . AY540630 ) was expressed in bacterial heterologous system by transfer of the cDNA ( 1770 bp ) encoding the predicted soluble portion of T . cruzi NTPDase-1 to the expression vector pET21b ( Novagen ) . Cloning in the correct frame was confirmed by partial sequencing of recombinant plasmid , using T3 and T7 primers and BigDyeET-terminator kit in the MegaBace 500 apparatus , according to the manufacturer ( GE Amersham Biosciences ) . The cloned sequence excluded the portion encoding the previously predicted putative amino-terminal signal peptide [17] . The recombinant plasmid pET21b-Tc-NTPDase-1 was used for transforming Escherichia coli BL21 ( DE3 ) . This vector adds a hexa-histidine sequence ( Hexa-HIS ) at the carboxyl-terminal portion of the resulting fusion protein , a tag that was used as target for purification of recombinant protein using nickel affinity chromatography Ni-NTA-agarose ( GE-Amersham ) . Protein expression was induced with 1 mM IPTG during 1 hour at 37°C and 200 rpm . Purification and protein refolding were performed following previously described protocols [27] . The purified recombinant protein ( rNTPDase-1 ) was used for producing polyclonal antiserum by immunization of a female rabbit . Previous to the immunization a blood sample was obtained ( 3 mL ) from the ear marginal vein ( negative control ) . Purified recombinant NTPDase-1 ( 0 . 5 mg in 0 . 5 mL complete Freund's adjuvant- Sigma ) was inoculated by intradermal route . After three weeks , another dose was inoculated ( 0 . 5 mg NTPDase-1 in 0 . 5 mL incomplete Freund's adjuvant-Sigma ) . The immune serum was recovered after an interval of 15 days . Blood was collected by puncture of the ear marginal vein and centrifuged at 3000 rpm for 10 min at room temperature; the serum supernatant was distributed in 1 . 5 ml aliquots . The pre-immune serum and immune antiserum were used in western blotting analysis and only immune serum was able to recognize the recombinant NTPDase-1 ( data not shown ) . Both sera were treated for the complete inactivation of the complement system ( CS ) in order to be used in “in vitro” infectivity assays and NTPDase-1 inhibition assays . For this purpose , the pre-immune and immune sera were warmed to 56°C for 30 min . After CS inactivation these samples were stored in aliquots at −20°C . T . cruzi Y strain [28] was maintained cyclically in mice as described above . VERO cells were grown at 37°C in RPMI 1640 medium ( Sigma ) supplemented with 5% fetal calf serum , garamycin ( 10 mg/ml ) in a humidified 5% CO2 atmosphere . In vitro host cell invasion assays were carried out as detailed elsewhere [29] , using first passage trypomastigotes ( P1 ) . Briefly , 5×105 trypomastigotes from Y strain were placed in each well of 24-well plates containing 13-mm round glass cover slips coated with 5×104 Vero cells ( 10∶1 ) . After 24 h of infection , the cover slips were washed three times with 0 . 9% saline and stained with Giemsa ( Merck ) . The numbers of infected cells and amastigotes per infected cell were counted in at least 300 cells , in quadruplicate . In experiments using trypomastigotes treated with NTPDase inhibitors ( ARL67156 , GdCl3 , Suramin ) , parasites were recovered after one VERO cell passage , washed in sterilized saline solution and suspended in RPMI containing different concentrations of inhibitors . After 10 min of exposure to the inhibitor , parasites were recovered , suspended in new RPMI medium devoid of inhibitor and used for infecting VERO cells monolayer . The Vero cells were infected as described above . Samples of Y strain P1 trypomastigotes were produced using independent sets of mouse blood containing Y strain trypomastigotes . All procedures and experimental animal protocols were conducted in accordance with the COBEA ( Brazilian School of Animal Experimentation ) and behavior instructions for the use of animals in research . For in vivo assays , groups of ten mice were inoculated with 5×103 culture-derived P1-trypomastigotes of Y T . cruzi strain treated or not with ecto-nucleotidase inhibitors ARL67156 ( 300 µM ) , GdCl3 ( 300 µM ) or Suramin ( 100 µM and 1000 µM ) . A second confirmatory assay was performed using the same concentrations of ARL67156 ( 300 µM ) , GdCl3 ( 300 µM ) and only the most effective concentration of Suramin ( 1000 µM ) using groups of six mice . Treatment with inhibitors was performed using 2×105 parasites/ml during 10 min in MEM with 1% fetal calf serum and the respective ecto-nucleotidase inhibitors . After treatment parasites were recovered by centrifugation at 3500 rpm for 15 min , suspended in the same medium without inhibitors and used for infecting mice as described above . Parasitemia was evaluated by examination of fresh blood collected from the mouse-tail , starting from day 4th post infection . The number of parasites was calculated as previously described [30] . Curves were plotted using the mean of the parasitemia obtained from six mice . Mortality rate was cumulative and expressed as a percentage of deaths within the period of 120 days after inoculation . Except when mentioned , all hydrolytic activity experiments were performed in triplicate , with similar results obtained in at least three separate cell suspensions . Statistical significance was determined by Student's t test . Differences were considered significant at p<0 . 05 . Data were expressed as average±standard deviation .
Blood trypomastigotes from Y , Be-62 and CL strains and the clone CL-Brener were used for infecting VERO cell cultures . Parasites obtained after one passage ( P1 ) were used for measuring Ecto-ATPDase hydrolytic activity . The different strains exhibited distinct levels of ATP and ADP hydrolysis ( Figure 1 ) . Y strain presented the highest levels of ATP hydrolysis and lowest ADP hydrolysis and was chosen for further in vitro and in vivo infection assays . In order to establish a possible correlation with ecto-nucleotidase activity and infectivity capacity , we started a continuous in vitro cultivation of Y trypomastigotes in VERO cell cultures and analyzed Ecto-ATPDase activity . Each global exit of parasites to the culture supernatant after completion of the intracellular life cycle was named as “one passage ( P ) ” . Because Y is a polyclonal strain we observed two days of massive parasite exit from VERO cells; samples for each day of cell exit for the 1st and 3rd passages were collected and called PN-X , were N indicates the passage and X indicates the day from the beginning of cell exit in each passage . We detected a marked 3- to 6-fold decrease in the ATPase/ADPase ratio ( Figure 2A , inset ) and in the number of parasites that infected cells at the 3rd to 4th passage when compared to the 1st passage parasites ( Figures 2B , 2C ) . Because of this observed low infection from 3rd to 4th passage , we were unable to recover sufficient parasites to perform enzymatic assays for the 5th and later passages . Curiously , ecto-ATPase activity ranged from 1400 to 2800 nmol Pi . 108 parasites−1 . h−1 ( P1 , P3 , P4 ) and it did not decrease significantly in trypomastigotes that could complete infection and intra cellular cycle in all analyzed passages ( Figure 2A ) . On the other hand , ecto-ADPase activity increased from 50–100 nmol Pi . 108 parasites−1 . h−1 in the first passage to 300–1200 nmol Pi . 108 parasites−1 . h−1 in passages 3 and 4 ( Figure 2A ) , reflecting in a significantly decreased ecto-ATP/ADPase ratio ( Figure 2A , inset ) . We did not measure infectivity directly during passages cultivation , but it could be clearly observed that the number of parasites from the 3rd to 4th passage penetrating VERO cells was very low . The majority of parasites did not infect cells and differentiated to amastigote-like in the culture supernatant ( Figure 2B , 2C ) . We recovered these parasites and observed that the population was comprised of about 80% amastigote-like and 20% trypomastigotes that could not penetrate VERO cells . We compared the ecto-nucleotidase activity of these parasites ( indicated as Ama-like-P3 on Figure 2A ) with that of infective P4 trypomastigotes ( parasites that penetrated cells , concluded the cellular life cycle and were recovered from VERO cell culture supernatant ) . In Figure 2A ( inset ) we show that these non-penetrating amastigote-like parasites have an ecto-ATPase/ADPase ratio of 2 . 0 , which is 2 . 5-fold lower than infective P4-trypomastigotes ( ratio = 5 . 6 ) . Overall , these results suggested that a high ATPase/ADPase ratio ( in the range of 12 to 36 ) seems to be a requirement for internalization of parasites . We speculate that the absence of mammalian host factors in the culture medium could influence the differentiation process , generating non-infective amastigote-like parasites with reduced Ecto-ATPDase activity . In face of the above results , we decided to investigate the effect of known ecto-ATDPase inhibitors on T . cruzi infectivity and hydrolytic activity . We tested the action of Ecto-ATPDase inhibitors directly on live P1-trypomastigotes from Y strain . The inhibitors tested were: ARL67156 ( 6-N , N-Diethyl-β-γ-dibromomethylene-D-adenosine-5-triphosphate ) considered to be a selective inhibitor of ecto-ATPase [31]; Gadolinium , a lanthanide related with extra- and intracellular ATP action and able to inhibit Ecto-NTPDase from Torpedo electric organ [32] and Suramin , a polysulfonated naphthylurea compound that was previously demonstrated to inhibit T . cruzi Ecto-ATPDase [10] . Intact parasites were incubated for 10 min with different concentrations of the above inhibitors ( 0 , 100 , 300 , 500 µM ) and were subsequently recovered by centrifugation and suspended in fresh buffer free of inhibitors . These pre-treated parasites were used for in vivo Ecto-ATPDase hydrolysis assays and in experimental VERO cells infection . We observed that all drugs tested were able to partially inhibit ATPase and ADPase activities . Higher in vivo inhibition of T . cruzi ecto-ATPase ( approximately 75% ) was achieved with Suramin 100 µM ( Figure 3A ) . Gadolinium and ARL67156 inhibited only approximately 30% of this activity at 300 and 500 µM respectively ( Figure 3B and 3C ) . On the other hand ADPase activity was more effectively inhibited ( 60% ) by Suramin and Gadolinium at 500 µM; ARL 67156 inhibited about 50% of ADPase activity at 300 µM ( Figure 3A , 3B and 3C ) . Infectivity of parasites treated with ATPDase inhibitors ( 300 µM ARL 67156 , 300 µM Gadolinium or 100 µM Suramin ) were evaluated in VERO cells . P1 trypomastigotes ( Y strain ) were pre-treated during 10 min with the indicated inhibitor concentrations . Parasites were recovered by centrifugation , washed in appropriate medium and used for infecting VERO cell monolayers . After 24 hours of interaction ( parasites-cells ) the non-internalized parasites were discarded . The slides were covered with new growth medium and incubated during an additional 24 h . After staining , levels of cell infection and the number of intracellular amastigotes per infected cells were measured . Suramin was the most effective in vitro infectivity inhibitor , as revealed by a significant 71% reduction in the number of infected cells per 300 cells ( Table 1 ) , which is also visually documented in microphotographs of VERO cells exposed to control or Suramin pre-treated parasites ( Figures 4E and 4F , respectively ) . It should be noted that pre-treatment of parasites with Suramin caused an infectivity blockage while not affecting the intracellular survival of those parasites that managed to penetrate the cells , as evidenced by a similar number of parasites per infected cell detected in the experiment ( Table 1 ) . ARL 67156 and Gadolinium caused 42% and 65% infectivity inhibition , respectively ( Table 1 , Figure 4A , 4B , 4C , 4D ) . The results show that only Suramin and Gadolinium lead to significant decrements in T . cruzi infectivity . These observed effects resulted from a direct action of drugs on the parasite rather than derived from a response of VERO cells to the drugs , since the cells did not have direct contact with the drugs . Similar to Suramin , ARL 67156 pre-treatment did not affect the detected number of parasites per infected cell , whereas GdCl3 pre-treatment caused a significant decrement in the number of parasites per infected cell ( Table 1 ) . This latter observation could be related with the action of GdCl3 inhibitor upon target biomolecules involved with both infection and differentiation processes . We have only identified one T . cruzi NTP-diphosphohydrolase in the parasite genome , named NTPDase-1 [17] . In light of the results described in the previous sections , we decided to study if NTPDase-1 could be responsible for the Ecto-ATPDase activity correlated with parasite infectivity . We obtained the recombinant T . cruzi NTPDase-1 ( ∼66 kDa ) by heterologous expression , purified it by affinity chromatography ( Figure 5A ) and evaluated its ATPDase activity in presence or absence of the previously described Ecto-NTPDase inhibitors . The specific ATPase and ADPase activities were 24 . 0±8 . 4 and 14 . 3±6 . 9 nmol Pi . h−1 . µg Prot−1 , or 0 . 4 and 0 . 24 µmol Pi . min−1 . mgProt−1 . Specific activities are in the range of recombinant human enzymes [33] . Concerning only the average activity values the ATPase/ADPase ratio is 1 . 7 , similar to mouse ( 1 . 9 ) and human ( 1 . 9 ) NTPDase1 isoforms [33] . We show in Figure 5B that only Suramin caused significant levels of nucleotidase inhibition of this enzyme . The level of Suramin inhibition on recombinant purified NTPDase-1 ( 40 to 50% ) was very similar to the extent of Suramin inhibition of hydrolytic activity on live parasites ( Figure 3 ) , suggesting that Suramin blockage of trypomastigote infectivity ( Table 1 ) could be related with its effect on T . cruzi NTPDase-1 . On the other hand ARL 67156 and Gadolinium showed no effect on the activity of this recombinant enzyme , suggesting that other enzymes with NTPDase activity sensitive to these inhibitors may exist at the T . cruzi surface . We produced a polyclonal antiserum anti- T . cruzi NTPDase-1 using the purified recombinant protein as antigen for immunization of rabbits . This serum gives a strong signal in immuno-fluorescence experiments; in contrast no signal is obtained from the negative control pre-immune serum , thus clearly indicating that immunization of rabbits with the antigen has produced antibodies against NTPDase-1 ( Cunha et al . , manuscript in preparation ) . In vitro assays using the antiserum fail to produce any inhibitory action towards the recombinant protein enzymatic activity ( data not shown ) . This indicates that although the produced antibodies are able to bind to NTPDase-1 , they must target regions that are not essential for enzymatic activity . A complement system ( CS ) inhibition pre-treatment of the pre-immune and immune sera was performed as described in material and methods , before its use in infectivity assays . Y strain P1 trypomastigotes were submitted to pre-incubation with CS inactivated antisera , and parasites were used for infecting VERO cell monolayers . We observed that the antiserum assayed at 1∶50 and 1∶100 significantly inhibited the infectivity of parasites ( Table 2 ) . To confirm the results from experiments using VERO cells as model , we performed experimental in vivo infection assays in mice using P1 Y trypomastigotes pre-treated with the optimal concentration of Ecto-NTPDase inhibitors that blocked in vitro infection ( Table 1 and Figure 4 ) . A parallel negative control experiment was performed by omitting drug pre-treatment of parasites . All data are mostly related with the action of drugs directly on parasites rather than on mice , because parasites are pre-treated with inhibitors , washed and finally inoculated in the animals . Figures 6A and B show the parasitemia and mortality verified in the tested animals , respectively . Data clearly shows that pre-exposure of parasites to ARL 67156 ( 300 µM ) or Gadolinium ( 300 µM ) resulted in a decreased parasitemia and increased host animal's survival . The most effective drug was ARL 67156 , which resulted in about 60% mice survival when compared with mice infected with non-treated parasites ( control ) . Pre-treatment of parasites with Suramin at 100 µM ( data not shown ) and 300 µM ( Figure 6B ) did not result in significant protection , while pre-exposure of parasites to 1 mM Suramin resulted in a significant decrease in parasitemia as well as a prolonged time of survival of infected mice ( Figure 6A , 6B ) . A second confirmatory experiment was performed and gave similar results ( data not shown ) .
The present work shows evidence that continuing cultivation of trypomastigotes in VERO cells caused an infectivity decrease during cultivation and that only a small fraction of parasites was able to infect VERO cells and conclude another cellular cycle at the third to fourth passage . Parasites ( trypomastigotes ) that completed this passage presented 2 . 5-fold higher levels of ecto-ATPase activities when compared with amastigote-like parasites that could not penetrate into VERO cells . These data reinforce that a high ecto-ATPase activity is important for infectivity and suggest that the absence of host factors leads to loss of infectivity factors from T . cruzi . Similar suggestion was made by Bêrredo-Pinho et al . [14] when the ecto-ATPase activity was assayed on promastigotes from Leishmania amazonensis and showed that higher passages in acellular medium lead to low ecto-ATPase levels and avirulence [14] . However , as we have used a single strain ( Y ) in our experiments , verification of correlation between infectivity and Ecto-ATPDase activity in other strains may provide further support to our hypothesis . In order to evaluate the importance of Ecto-NTPDase activity in T . cruzi infectivity we performed experiments with three known enzyme inhibitors . Analyzing Ecto-ATPDase inhibitory effects of these compounds we observed that all were able to partially inhibit both ecto-ATPase and -ADPase on live parasites , but the effect of ARL67156 and Gadolinium on the ecto-ATPase was lower than that observed for Suramin . In parallel , we observed that P1 trypomastigotes treated with ecto-nucleotidase inhibitors showed significant decrements of in vitro infectivity ( Table 1 ) and in vivo virulence ( Figure 6 ) , suggesting the importance of Ecto-ATPDase activity in these processes . We cannot exclude the possibility that inhibitors used in this work had an additional action on other molecular targets . It has been shown that P2 receptors are susceptible to blockage by Suramin [34] , but even if that is the case our data would still point out the importance of the extracellular nucleotide metabolism for T . cruzi , as demonstrated for other parasites [35] . Further studies including the use of more selective ENTPDase inhibititors , such as Polyoxometalates [36] and anthraquinone derivatives from bromaminic acid [37] , are still necessary to determine the exact molecular mechanism inducing the loss of infectivity and virulence observed in our experiments . Parasites have been incubated with high concentrations of inhibitor , but the in vitro experiments were performed in drug-free medium after the centrifugation of parasites . The persistence of effects from drugs on the parasite even after their removal suggests that the drugs might have triggered persistent changes in the parasite's metabolism that had a very slow recovery rate . Considering the important roles of ATP , ADP and Adenosine as extracellular molecules in modulating the inflammatory process and platelet aggregation [5] , [38]–[40] and the proposed role of NTPDases in host pathogen interactions [41] , it is possible to speculate that some of the in vivo effects observed might be correlated to the impairment of the parasites' ability to modulate the levels of these nucleotides by inhibition of NTPDase . Further experiments are warranted to substantiate this hypothesis . The present work shows the first biochemical demonstration of recombinant T . cruzi Ecto-NTPDase-1 activity . Enzymatic inhibition of this recombinant protein in the presence of Suramin , suggests that the effects of this drug on intact parasites , namely blockage of cell infection may be due to targeting of this inhibitor to the Ecto-NTPDase-1 on their surface . Polyclonal antiserum to T . cruzi Ecto-NTPDase also blocked infection of the cells . It should be noted that the antibodies did not display any direct inhibitory effect on enzymatic activity of the recombinant NTPDase-1 , under controlled in vitro conditions . Considering that during the infection process the parasite will be exposed to diverse environmental conditions , it is possible that even though the antibody was not directly targeted to the NTPDase-1 active site , it might bind to modulatory regions preventing the response of the enzyme to certain stimuli . Alternatively , antibody binding might generate a steric hindrance at the parasite surface that prevents its adhesion to host cells . Structural studies of NTPDase-1 and its use for the rational design of inhibitors could be a relevant strategy for the development of new drugs to treat the disease . In addition , the observed effect of antibodies on the parasites suggests that an effective immune response from the host could be mounted based on vaccination using this antigen . Further immunization experiments using this protein are necessary to verify its potential as a protective antigen . In contrast , the observed ARL 67156 and Gadolinium inhibition of hydrolytic activities on live parasites could be related with another ecto-nucleotidase target , since they caused no inhibition of purified T . cruzi Ecto-NTPDase-1; this observation suggests the existence of other enzymes with Ecto-NTPDase activity at the parasite surface . We exhaustively searched for another apyrase/CD39 gene in the T . cruzi genome public database , including the in silico screening of 67 Mb of partial genome assembly [42] without any success . This indicates that targets for ARL 67156 and Gadolinium are either Ecto-NTPDases encoded by genes that are located in a portion of the genome not yet sequenced or are proteins with no detectable primary sequence similarity with Ecto-NTPDase . Alternatively , it is possible that Ecto-NTPDase-1 is in fact inhibited by these other compounds , but the recombinant version of this protein is insensitive due to alterations in its structure compared to the native form . This paper shows the correlation of Ecto-ATPDase activity with T . cruzi infectivity and virulence . In addition , inhibitors of such activity tested here appear to interfere with the parasite infection process and emerge as possible new clinical drugs to Chagas disease treatment . Because Suramin and Gadolinium are currently used in unrelated human chemotherapy these drugs have already been tried for safety and may provide prompt options for development and use in Chagas disease treatment . Suramin is a current drug used in the treatment of Human African trypanosomiasis [43] and exhibits toxic effects to T . cruzi [44] , [45] . Gadolinium is used as a contrast drug in magnetic resonance clinical imaging exams . ( Gd ) -based paramagnetic contrast agents are relatively safe when used in clinically recommended doses , however there is literature linking Gd-based paramagnetic contrast agents with nephrogenic systemic fibrosis ( NSF ) in patients with renal failure [46] . We believe that chemotherapy studies with these compounds and their association with the currently used drug Benznidazole in lower doses is warranted and may represent an alternative to treat Chagas patients .
|
The protozoan Trypanosoma cruzi is the causative agent of Chagas disease , an endemic zoonosis present in some countries of South and Central Americas . The World Health Organization estimates that 100 million people are at risk of acquiring this disease . The infection affects mainly muscle tissues in the heart and digestive tract . There are no vaccines or effective treatment , especially in the chronic phase when most patients are diagnosed , which makes a strong case for the development of new drugs to treat the disease . In this work we evaluate a family of proteins called Ecto-Nucleoside-Triphosphate-Diphosphohydrolase ( Ecto-NTPDase ) as new chemotherapy target to block T . cruzi infection in mammalian cells and in mice . We have used inhibitors and antibodies against this protein and demonstrated that T . cruzi Ecto-NTPDases act as facilitators of infection in mammalian cells and virulence factors in mice model . Two of the drugs used in this study ( Suramin and Gadolinium ) are currently used for other diseases in humans , supporting the possibility of their use in the treatment of Chagas disease .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"infectious",
"diseases/protozoal",
"infections",
"infectious",
"diseases/neglected",
"tropical",
"diseases",
"biochemistry",
"molecular",
"biology"
] |
2009
|
Influence of Ecto-Nucleoside Triphosphate Diphosphohydrolase Activity on Trypanosoma cruzi Infectivity and Virulence
|
Intercalated disks ( ICDs ) are substantial connections maintaining cardiac structures and mediating signal communications among cardiomyocytes . Deficiency in ICD components such as desmosomes , fascia adherens and gap junctions leads to heart dysfunction . Coxsackievirus B3 ( CVB3 ) infection induces cardiac failure but its pathogenic effect on ICDs is unclear . Here we show that CVB3-induced miR-21 expression affects ICD structure , i . e . , upregulated miR-21 targets YOD1 , a deubiquitinating enzyme , to enhance the K48-linked ubiquitination and degradation of desmin , resulting in disruption of desmosomes . Inhibition of miR-21 preserves desmin during CVB3 infection . Treatment with proteasome inhibitors blocks miR-21-mediated desmin degradation . Transfection of miR-21 or knockdown of YOD1 triggers co-localization of desmin with proteasomes . We also identified K108 and K406 as important sites for desmin ubiquintination and degradation . In addition , miR-21 directly targets vinculin , leading to disturbed fascia adherens evidenced by the suppression and disorientation of pan-cadherin and α-E-catenin proteins , two fascia adherens-components . Our findings suggest a new mechanism of miR-21 in modulating cell-cell interactions of cardiomyocytes during CVB3 infection .
microRNAs ( miRNAs ) are endogenous gene regulators functioning through targeting messenger RNAs ( mRNAs ) [1] . Their capability of targeting several genes simultaneously enables their vast involvement in physiological and pathological conditions [2] , including cardiac dysfunctions and viral infections [3] , [4] . Among these small RNAs , miR-21 is one of the most essential ones due to its wide involvement in development and diseases [5] . miR-21 acts as a pivotal pillar in controlling the pathogenesis of cardiovascular diseases [6] . This is evidenced by the fact that miR-21 is abundant in cardiovascular system and dramatically altered during the development of the diseases such as cardiac hypertrophy [7] , fibrosis [8] and myocardial infarction [9] . However , the functional role of miR-21 directly related to cardiomyocyte physiology , is controversial . Thum et al . showed that neither enhancement nor suppression of miR-21 affects the morphology , size or number of cardiomyocytes in primary culture [10] , while another group demonstrated that miR-21 induces cardiomyocyte outgrowth [7] . Cardioprotective roles of miR-21 have been suggested by several studies using hypertrophy [11] or ischemia models [12] in which miR-21 attenuates hypertrophic growth and inhibits the cardiomyocyte death but genetic knock-out experiments and locked nucleic acid-mediated inhibition of miR-21 expression suggest no essential role of miR-21 in pathological myocardium remodeling [13] . miR-21 is also actively involved in viral infections . Epstein-Barr virus ( EBV ) infection stimulates miR-21 expression , resulting in B-cell transformation [14] . Hepatitis C virus ( HCV ) induces miR-21 expression to evade host immune system [15] . Coxsackievirus B3 ( CVB3 ) is a major cause of myocarditis , an infectious heart diseases characterized by inflammation and damage of myocardium , accounting for ∼20% of sudden unexpected death in youth and infants [16] , [17] . We and others have shown that CVB3 infection induces significant changes in host miRNA expression profiles , which in turn modulate viral infection or contribute to the progression of the disease [18]–[21] . For miR-21 , its altered expression and functional role during CVB3 infection have been studied by a number of groups while the results on the altered expression are inconsistent . Jin He and co-workers found that miR-21 was downregulated in CVB3 infected mice , resulting in the upregulation of PDCD4 and cardiomyocyte apoptosis [15] . However , two other groups showed that CVB3 infection upregulates miR-21 in mice [19] , [22] . The latter one further indicated that miR-21 promotes the differentiation of Th-17 ( Helper T ) cells that produce interleukin-17 ( IL-17 ) , leading to inflammation while the detailed mechanism has not been identified [22] . Intercalated disks ( ICDs ) are essential cell-cell connections consisting of desmosomes , fascia adherens and gap junctions . They are critical components for cardiac functions and their disruption leads to heart dysfunction [23] . Desmosomes anchor the cell membranes to the intermediate filaments to maintain the proper cell-cell connections [24] . Adherens junctions link the cell membranes to cytoskeleton components like actin [25] . Gap junctions channel the electronic and metabolic signals among the cardiomyocytes [26] . Disorganization of these structures results in pathological heart conditions such as hypertrophy , dilated cardiomyopathy and arrhythmia , symptoms similar to CVB3 induced cardiac failure [23] , [27] . miR-21 enhances the gap junctions by targeting SPRY2 and triggering the redistribution of Connexin 43 and β-catenin [7] . However , whether and how miR-21 regulates desmosome or adherens junctions in cardiomyocytes is entirely unknown . To address these issues , we analyzed the miRNA expression profiles in CVB3 infected mouse hearts and cultured mouse and human cardiomyocytes , and found that miR-21 was robustly increased by CVB3 infection . Functional characterization found that virus-induced increase of miR-21 expression injures cardiomyocytes by two ways: i ) disturbing desmosome structures by targeting YOD1 , a deubiquitinating enzyme , to enhance the ubiquitin-mediated degradation of desmin proteins and ii ) interrupting fascia adherens organization by directly targeting VCL and suppressing its protein translation .
To identify miRNA candidates regulating CVB3-induced viral myocarditis , we performed microarray analysis of miRNA expression profiles using RNAs isolated from CVB3-infected mouse hearts , an established viral myocarditis model . We first confirmed the myocarditis occurrence by observing leukocyte infiltration and cardiomyocyte necrosis , which demonstrated that severe myocarditis appeared at both 4-day post infection ( 4 dpi ) and 7 dpi ( Figure S1A in Text S1 ) . VP-1 expression was detected as an indicator for successful infection ( Figure S1B in Text S1 ) . Based on these confirmations of infection and disease presence , total RNAs isolated from these tissues were employed to conduct microarray analysis . miRNAs with more than 2-fold changes compared with controls were selected as top miRNA candidates . As shown in the heat map in Figure 1A , 16 miRNAs were upregulated and 2 were downregulated at 4 dpi compared with the control group; while 15 miRNAs were increased and 8 were decreased at 7 dpi . Among all these miRNAs , eight appeared in the lists of miRNAs identified at both 4 and 7 dpi , indicating their potential functions in viral myocarditis . We also conducted quantitative reverse transcriptase PCR ( q-RT-PCR ) to confirm the alterations of some miRNA candidates including miR-21 , miR-203-3p , miR-222-3p and miR-574-3p ( Figure 1B , S1C in Text S1 ) . The results were consistent with the microarray analysis data . We chose miR-21 for further investigation due to its critical role in cardiac diseases . Both microarray and q-RT-PCR confirmed a 2–4 fold increase in CVB3 infected mouse hearts compared with the control ( Figure 1B ) . The q-RT-PCR results showed that the induction of miR-21 expression in CVB3 infected group is greater at 7 dpi than at 4 dpi; while such difference was not obvious in the microarray data , indicating that q-RT-PCR may be more sensitive than microarray analysis in this type of analysis . To further confirm the upregulation of miR-21 during CVB3 infection in vitro , HL-1 mouse cardiomyocytes and immortalized human cardiomyocytes were used to detect miR-21 expression levels after CVB3 infection by q-RT-PCR . Compared to sham-infected control , CVB3 infection triggered a 5–10 folds upregulation in the infected cells ( Figure 1C ) . We then infected HL-1 cells with UV-irradiated CVB3 to determine whether active viral replication is required for miR-21 upregulation . Q-PCR results showed that UV-inactivated CVB3 failed to stimulate miR-21 ( Figure S2 in Text S1 ) , indicating that viral replication is required for the induction of miR-21 . These data demonstrated that CVB3 infection induces upregulation of miR-21 expression in cardiomyocytes in vitro and in vivo . We first evaluated the effect of miR-21 on CVB3 replication . HL-1 cells and immortalized human cardiomyocytes were transfected with 10 nM of miR-21 mimics or 50 nM of miR-21 inhibitor ( 21-in ) . miR-CL , a miRNA mimic control with a scrambled sequence , was used as a negative control for miR-21 . We also transfected the cells with miR-362 , a non-relevant miRNA as another negative control . According to bioinformatic analysis using TargetScan [28] , miR-362 only shared 4 predicted targets with miR-21 in the total 110 potential targets and none of the 4 targets ( ARHGEF12 , BCL11A , PURB and TNRC6B ) were known to be involved in the signal pathways in this study . miRNA inhibitor control ( CL-in ) was used as a negative control for 21-in . As shown in Figure S3A in Text S1 , transfection of miR-21 mimics led to a ∼10-fold increase in miR-21 level compared with transfection of miR-CL . This increased level is similar to that induced by CVB3 infection . In addition , 21-in reduced miR-21 expression by ∼90% compared with the control . Viral replication levels were measured by detecting viral protein VP-1 and performing viral plaque assay . Neither miR-21 nor 21-in exhibited any effect on VP-1 level or viral plaque numbers in both HL-1 cells and human cardiomyocytes ( Figure S4 in Text S1 ) , indicating that miR-21 may not affect CVB3 replication . As mentioned above , miR-21 is involved in regulating cell-cell connections in cardiomyocytes , we thus further explored the effect of miR-21 upregulation on desmosome structure by detecting the expression of γ-catenin ( plakoglobin ) , a major intracellular component of desmosome , and desmin , the intermediate filaments closely associating with desmosomes to maintain its structure and function . In sham-infected controls , transfection of miR-21 mimics inhibited desmin expression by ∼70% ( from 1 . 00 to 0 . 29 ) while 21-in increased desmin expression by ∼90% ( from 1 . 00 to 1 . 87 ) . In the miR-CL transfected cells , a robust reduction ( ∼80% , from 1 . 00 to 0 . 21 ) in desmin expression was found in CVB3 infected cells compared with the sham-infected control . Transfection of miR-21 mimics enhanced virus-induced suppression of desmin expression while treatment of 21-in substantially attenuated the downregulation of desmin during CVB3 infection ( Figure 2A ) . On the contrary , miR-21 showed no significant influence on γ-catenin level . The decreased levels of desmin protein may affect desmosome formation and its structures . This speculation was verified by electronic microscopy ( EM ) . As shown in Figure 2B , in the control groups ( miR-CL and miR-362 ) , compact and well-organized desmosomes were observed with typical opposing electron dense plaques anchoring on the cell membranes . Multiple desmosomes were also found in some areas at the boundary of the cardiomyocytes . In contrast , most miR-21 mimic transfected cells demonstrated no apparent desmosomes despite multiple cell-cell contacts . In a few miR-21 mimic transfected cells , desmosome-like structures with much thinner and shorter electron dense plaques were identified . For the 100 cells analyzed in each group , 62 and 55 desmosomes were observed in miR-CL and miR-362 group , respectively; while only 17 desmosome-like structures were found in the miR-21 mimic transfected group . To confirm these findings , the distribution of γ-catenin was analyzed by immunofluorescence staining . Loss of γ-catenin at the cell-cell connection sites accompanied with increased intracellular localization was observed in miR-21 transfected cells compared with miR-CL and miR-362 groups ( Figure S5A in Text S1 ) . These data indicate that increased miR-21 level downregulates desmin expression and damages desmosome structures in cardiomyocytes . As shown in Figure 2A , even in control groups that were not transfected with miR-21 , CVB3 infection can also induce desmin downregulation . We then investigated the influence of CVB3 infection on desmosomes . EM data showed that CVB3 infection also resulted in fewer , thinner and shorter desmosomes in comparison to the sham controls ( Figure 3 ) . More importantly , inhibition of cellular miR-21 by 21-in partially rescued the desmosomes by maintaining the proper structures of some desmosomes and increasing the desmosome numbers . These observations were validated by detection of γ-catenin using immunofluorescence staining . Infection of CVB3 led to loss of γ-catenin in the cell-cell contact sites while 21-in partially alleviated such reduction ( Figure S5B in Text S1 ) . Together , our data suggest that miR-21 induced by CVB3 triggers desmosome destruction in the infected cardiomyocytes . To reveal the mechanism by which miR-21 suppresses desmin expression , we first evaluated it at the transcription level by q-RT-PCR . The results proved that neither CVB3 infection nor miR-21 transfection/inhibition could cause alterations in desmin mRNA levels ( Figure 4A ) . This suggests that the change of desmin expression occurs at the post-transcriptional level . We then performed bioinformatic prediction using the miRWalk software [29] to search for potential miR-21 targeting sites within desmin mRNA but no site was found in the 5′ untranslated region ( 5′UTR ) , coding region or the 3′UTR , indicating no direct targeting effect of miR-21 on desmin translation . Previous studies reported that desmin undergoes cleavage by protease such as cystein protease and caspase [30] , [31] . However , our western blot ( WB ) analysis showed no cleavage products despite a robust decrease in desmin protein levels in the miR-21 mimic transfected samples ( Figure 4B ) . Recently , it was reported that desmin is susceptible to degradation via ubiquitin-proteasome pathway [32] . We thus further determined whether miR-21 regulates desmin ubiquitination . To this end , desmin was pulled down by immunoprecipitation and the ubiquitinated desmin ( ubi-desmin ) was detected by an anti-ubiquitin antibody . We found that CVB3 infection or transfection of miR-21 mimics induced poly-ubiquitination of desmin while 21-in suppressed such process ( Figure 4C ) . In CVB3 infected cells , transfection of miR-21 mimics further intensified the ubiquitination of desmin while 21-in alleviated this process . To further confirm the involvement of ubiquitin-proteasome pathway in miR-21 mediated desmin degradation , we applied proteasome inhibitor MG132 to block this pathway . As shown in Figure 4D , compared with DMSO control , MG132 eliminated the effect of miR-21 on desmin downregulation . These data indicate that miR-21 promotes desmin degradation through the ubiquitin-proteasome pathway . To understand the mechanism by which miR-21 induces desmin ubiquitination , we performed a bioinformatic search for the potential target genes of miR-21 using the TargetScan software [28] . Among the top 10 predicted targets , YOD1 is a known mediator of the ubiquitin-proteasome pathway ( Table S1 in Text S1 ) . Two conserved targeting sites were identified on the 3′UTR of YOD1 mRNA ( Figure 5A ) . YOD1 is a deubiquitinating enzyme that removes ubiquitin residues from the ubiquitinated proteins , facilitating the dislocation of mis-folded proteins from the endoplasmic reticulum ( ER ) for further degradation [33] . It is however not clear whether YOD1 regulates the degradation of normal cytosolic protein . To verify whether YOD1 is a true target of miR-21 , we first measured the expression level of YOD1 in miR-21 mimic transfected cells without CVB3 infection . WB results showed that miR-21 mimic transfection led to a ∼40% ( from 1 . 00 to 0 . 62 ) reduction in YOD1 levels compared with miR-CL . Similar reduction of YOD1 by miR-21 was observed in CVB3-infected samples ( Figure 5B ) . We further used miR-21 inhibitors to knockdown the endogenous miR-21 and thus block the induction of miR-21 by CVB3 infection . A ∼40% ( from 1 . 00 to 1 . 41 ) increase in YOD1 was observed in 21-in transfected samples compared with CL-in in sham infected samples . Importantly , 21-in transfection attenuated the dowregulation of YOD1 during CVB3 infection , indicating that CVB3-induced miR-21 is responsible for the reduction of YOD1 ( Figure 5B ) . To validate the direct targeting effect of miR-21 on YOD1 3′UTR , we cloned one miR-21 targeting sites of YOD1 into a dual-luciferase reporter vector . We also constructed a mutated site by changing 4 base-pairs ( bp ) to disrupt the targeting effect of miR-21 . Luciferase reporter assay showed that miR-21 caused ∼40% reduction in the luciferase activity of the reporter harboring the wide type ( wt ) site but not the mutant ( mut ) one ( Figure 5C ) . These data demonstrate that miR-21 plays an essential role in downregulating YOD1 during CVB3 infection . zTo confirm that the YOD1 suppression by miR-21 leads to the degradation of desmin during CVB3 infection , we utilized small interference RNA ( siRNA ) to knockdown endogenous YOD1 , which mimicked the effect of miR-21 on YOD1 expression . As shown in Figure 6A , compared with the scrambled control siRNA ( si-Scr ) , YOD1 siRNA ( si-YOD1 ) successfully suppressed YOD1 expression in both sham- and CVB3-infected cells , and this suppression correlated well with each corresponding decrease of desmin protein . Particularly , in CVB3-infected samples , desmin was further downregulated compared to the sham-infected control , indicating the role of YOD1 in desmin degradation . We also found more ubiquitinated desmin proteins in si-YOD1 transfected cells than in the control group in both sham- and CVB3-infected samples ( Figure 6B ) . Application of MG132 blocked the degradation of desmin , which is consistent with the miR-21 mimic transfection results ( Figure 6C ) . To further confirm that YOD1 inhibition and desmin downregulation is mediated by miR-21 , we transfected cells with miR-362 as an additional non-specific control , which showed no effect on the expression levels of γ-catenin , desmin , YOD1 and ubiquitinated desmin ( Figure S6A–B in Text S1 ) . The above finding was further verified by ectopic expression of YOD1 in CVB3 infected or miR-21 transfected cells . The results showed that similar levels of desmin expression were found in sham- and CVB3-infected cells in the presence of a YOD1 expression plasmid while the empty vector failed to rescue the loss of desmin ( Figure 6D ) . The overexpression of YOD1 almost eliminated the effect of miR-21 on desmin degradation as evidenced by the equivalent levels of desmin in miR-CL and miR-21 transfected cells in the presence of a YOD1 expression plasmid . These data indicate that overexpression of YOD1 could counteract the effect of miR-21 on desmin degradation and that YOD1 is responsible for the miR-21 mediated degradation of desmin during CVB3 infection . Further , we examined the effect of YOD1 siRNA on desmosome structure in cardiomyocytes . EM data showed that silencing YOD1 resulted in substantial reduction of desmosome number and weakening of desmosome structure compared with the controls . These are evidenced by the thinner and shorter electron dense plaques and fewer desmosome-like structure ( 15/100 cells ) in YOD1 siRNA-transfected cells than in the control group ( 67/100 cells ) ( Figure 6E ) . This observation was supported by immunofluorescence staining of γ-catenin , showing loss of γ-catenin at the cell-cell contact area due to the knocking down of YOD1 ( Figure S6C in Text S1 ) . We then investigated the effect of miR-21 and YOD1 siRNA on the distribution of desmin protein in cardiomyocytes . Immunofluorescence staining data showed that in control groups ( miR-CL , si-Scr and sham ) , desmin was mainly localized along the cell borders where the cells contact with each other . On the contrary , transfection of miR-21 mimics , knocking down of YOD1 or infection of CVB3 induced more cytoplasmic distribution of desmin than the controls ( Figure 7 ) . More importantly , we found that the redistribution of desmin was accompanied by the increased ( 2–3 folds ) co-localization of desmin and proteasomes , which was verified by the Pearson's Correlation analysis ( Figure S7 in Text S1 ) . These results support our findings that miR-21-induced suppression of YOD1 promotes desmin degradation through the ubiquitin-proteasome pathway during CVB3 infection , which contributes to the damage of desmosomes . To test whether CVB3 infection in vivo regulates the YOD1-desmin cascade , we detected the expression levels of desmosome components and desmosome structures in the CVB3 infected mouse heart . Compared with the sham control , CVB3 infection downregulated the expression levels of γ-catenin , YOD1 and desmin ( Figure 8A ) , while increased the desmin ubiquitination level ( Figure 8B ) . More importantly , EM analysis demonstrated that CVB3 infection triggered the loss of normal dark and thick desmosomes between cardiomyocytes and resulted in shorter , thinner and smaller desmosomes ( Figure 8C ) , similar to the in vitro results . These data imply that CVB3 interrupts cardiomyocyte connections by modulating the YOD1-desmin cascade . The linkage between polyubiquitin chains and the target proteins can be mediated by lysine 48 ( K48 ) or 63 ( K63 ) which affects the fate of the ubiquitinated proteins [34] . We tested whether the desmin ubiquitination is linked by K48 or K63 . In cells treated with miR-21 , YOD1 siRNA or infected with CVB3 , the K48 linked rather than the K63-linked ubiquitination was increased compared with the control groups ( Figure 9 ) . Previous studies suggested that eleven lysine residues of the mouse desmin protein are involved in its ubiquitination [35] . Among them , K108 and K406 are conserved in the human desmin protein for ubiquitination [36] , [37] . We thus introduced point mutations into these two sites and studied the effect of these mutations on desmin ubiquitination and degradation . As shown in Figure 10 , single mutation at K108 or K406 ( K108R or K406R ) attenuated the ubiquitination and downregulation of desmin induced by miR-21 , YOD1 siRNA or CVB3 infection compared with the wt desmin . Such effect was enhanced by introducing a double mutation at both K108 and K406 ( K108R/K406R ) . These above data indicate that K48-linked polyubiquitination of desmin at K108 and K406 contributes to the miR-21 mediated desmin degradation during CVB3 infection . Among the top 10 miR-21 targets , another gene , VCL , is also closely related to the regulation of cell-cell connections and cardiac function . VCL is an essential component of fascia adherens that maintains cardiac structures [23] . Through bioinformatic prediction , we found one conserved targeting site of miR-21 in the VCL mRNA of both human and mice; while human VCL contains an additional miR-21 site ( Figure S8A in Text S1 ) . We first performed luciferase assay to evaluate the targeting effect of miR-21 on the conserved site . The results showed that miR-21 inhibited the luciferase activity of the reporter harboring the wt site but not the mutant one , indicating the specific recognition of this site by miR-21 ( Figure S8B in Text S1 ) . We then measured the expression of VCL in different human and mouse cell lines that transfected with miR-21 mimics . Interestingly , in all three human cell lines , immortalized human cardiomyocytes , HeLa cells and HEK 293T cells , miR-21 significantly inhibited VCL expression ( Figure S8C in Text S1 ) . In contrast , in the two mouse cell lines tested , NIH 3T3 and HL-1 cells , despite the successful transfection of miR-21 mimics as evidenced by q-RT-PCR results ( Figure S3B in Text S1 ) , only minimal inhibitory effect of miR-21 on VCL expression was observed ( Figure S8C in Text S1 ) . This indicates that the immortalized human cardiomyocytes would be a better cell line to study the role of miR-21 in fascia adherens . We thus transfected these cells either with miR-21 mimics to increase miR-21 level or with 21-in to suppress CVB3-induced expression of miR-21 . The two cellular proteins ( i . e . , pan-cadherin and α-E-catenin ) associated with fascia adherens were then detected by WB . The results showed that miR-21 silenced VCL expression , leading to downregulation of pan-cadherin and α-E-catenin compared with miR-CL and miR-362 ( Figure 11A , S9A in Text S1 ) . However , application of 21-in produced opposite results ( Figure 11A ) . Knocking down of VCL using siRNAs showed similar effect as that of miR-21 on the inhibition of pan-cadherin and α-E-catenin ( Figure S9B in Text S1 ) . We further analyzed the fascia adherens by investigating the distribution of pan-cadherin and α-E-catenin by using the immunofluorescence staining method . In control cells ( miR-CL , miR-362 and si-Scr ) , both signals were well aligned with the cell-cell connection border lines . However , when transfected with miR-21 mimics ( Figure 11B ) or VCL siRNAs ( Figure S9C in Text S1 ) , pan-cadherin and α-E-catenin were disorganized with the loss of clear cell contact sites . In addition , the irregular distribution of pan-cadherin and α-E-catenin was also observed in CVB3 infected cells , while inhibition of miR-21 could partially inhibit such phenomenon , particularly the localization of α-E-catenin ( Figure S10 in Text S1 ) . These data imply that miR-21 targets VCL and interrupts fascia adherens during CVB3 infection .
miRNAs are among the pivotal regulators of virus-host interactions . Several studies have reported the role of host miRNAs in regulating the replication of CVB3 and the activation of inflammatory process [18]–[20] , [22] . However , the research on the roles of miRNAs in cardiomyocyte pathology during the occurrence of viral myocarditis , particularly the regulation of cell-cell connections which are fundamental to cardiac structures and functions , is still missing . This study is the first to reveal the role of miR-21 in modulating ICDs in the cardiomyocytes during CVB3 infection . We identified two new targets , YOD1 and VCL , of miR-21 . Suppression of YOD1 by miR-21 promoted desmin degradation and desmosome disorganization . Targeting VCL by miR-21 directly triggered the reduction and disorientation of fascia adherens components including pan-cadherin and α-E-catenin . These findings provide a new perspective to understand the role of miRNAs in viral myocarditis . The differential expression of miR-21 caused by CVB3 infection is controversial . Both up- and down-regulation of miR-21 expression during CVB3 infection have been reported [15] , [19] , [22] . In our study , we found by microarray analysis that CVB3 infection induced miR-21 upregulation . We also further confirmed the results by q-RT-PCR using both the in vivo and in vitro models at different time points post infection . It is worth noting that different studies used different mouse strains including C3H , BALB/c and A/J and also employed distinct endogenous controls such as GAPDH and U6 . These may partially explain the inconsistency of the data . Considering that three independent groups including ours found that miR-21 is increased and that the transcriptional factors controlling miR-21 expression , such as activation protein 1 ( AP-1 ) [38] , STAT3 [39] and p38 [40] , are all activated by CVB3 infection [20] , [41] , [42] , we would argue that miR-21 is indeed upregulated by CVB3 infection in the heart . The two major cell types in adult murine hearts are cardiomyocytes ( ∼56% ) and cardiac fibroblasts ( 27% ) [43] . During CVB3 infection , about 30% of the cardiomyocytes are infected [44] . In our study , both mice and human cardiomyocytes showed 5–10 fold increase in miR-21 expression levels during CVB3 infection , suggesting the contribution of cardiomyocytes to overall miR-21 upregulation in CVB3-infected hearts . It has been reported that miR-21 is a central regulator for fibrosis [45] , indicating that cardiac fibroblasts may also associate with the miR-21 increase during CVB3 infection though further validation is still needed . The infiltrated CD45+ inflammatory cells account for 20–30% of the total cells in the infected heart during viral myocarditis [46] , [47] . It has recently been reported that miR-21 upregulation is a general feature of T-cell activation [48] , implying a likely involvement of immune cells in miR-21 induction in viral myocarditis . In addition , we showed that UV-irradiated CVB3 failed to induce miR-21 , suggesting that active replication of the virus is required for such induction . ICDs are composed of three major sub-units , desmosomes , fascia adherens and gap junctions [23] . They are the anchoring pillar to stabilize the cardiac structures and the bridging cable to transmit signals among cardiomyocytes . It is known that deficiency in ICDs causes both constitutional and functional damage to the myocardium . CVB3 infection has been found to affect endothelial tight junction [49] but its pathologic effect on cardiomyocyte ICDs is not clear . miR-21 has been identified as one of the most important miRNAs involved in heart diseases , particularly in cardiac hypertrophy [7] , [11] . However , its role in modulating ICD organization has been very limitedly investigated . Desmosomes are symmetrical protein complexes connecting adjacent cardiomyocytes . They are tightly linked by desmin , an intermediate filament facilitating the anchoring of desomosomal plaques [50] . Mutation or knockout of desmin frequently causes dilated cardiomyopathy [51] , [52] , a heart disease that often develops in the end stage of viral myocarditis [27] . Knockout of desmin also leads to fibrosis and ischemia injury in the heart with the loss of myocardium strength and integrity [53] . Cardiomyocytes lacking desmin show disorganized myofibrils which are separated from ICDs , resulting in a reduction in desmosome numbers [54] . In this study , we found that desmin levels were reduced by miR-21 mimic transfection and CVB3 infection . Silencing miR-21 could rescue the desmin levels during CVB3 infection , suggesting the regulatory role of miR-21 in desmin levels in CVB3-infected cardiomyocytes . Our results showed that miR-21 could not suppress desmin transcription . Further , we failed to observe any protease-mediated cleavage of desmin though it might be due to that the antibody we used could not recognize the cleavage products . Recent studies reported the loss of desmin due to ubiquitination by Trim32 during muscle atrophy [32] , indicating the important role of ubiquitin-proteasome system in modulating desmin levels . We found that CVB3 infection and/or miR-21 mimic transfection enhanced desmin ubiquitination while 21-in produced an opposite effect . Application of proteasome inhibitor suppressed the miR-21-mediated desmin degradation . These data suggest that CVB3-induced miR-21 expression causes desmin degradation through the ubiquitin-proteasome pathway . Importantly , we further demonstrated that the suppressed desmin levels eventually led to quantity reduction and structure disorganization of desmosomes . Inhibition of miR-21 during CVB3 infection hindered the desmosome loss and destruction . In search for the underlying mechanism by which miR-21 promotes desmin degradation , we identified YOD1 as a novel target of miR-21 . YOD1 is a deubiquitinating enzyme ( DUB ) in the ovarian tumor ( OTU ) family that removes ubiquitin residues from poly-ubiquitinated proteins [14] . It is involved in the degradation of misfolded proteins in ER . DUBs in OTU family have been found to be capable of stabilizing some cytosolic proteins . OTUB1 stabilizes c-IAP1 by counteracting its ubiquitination process [55] . It also enhances the stability of p53 by suppressing its ubiquitination [56] . The role of YOD1 in protein stabilization is unknown . By using siRNA to knock down YOD1 , enhanced desmin ubiquitination and degradation was observed . Treatment of proteasome inhibitor blocked the effect of YOD1 siRNAs on desmin suppression , suggesting that YOD1 is essential to stabilize desmin . YOD1 siRNAs also caused disruption of desmosomes . These results are in line with the role of miR-21 in promoting desmin degradation . Furthermore , overexpression of YOD1 attenuated the effect of CVB3 infection and/or miR-21 transfection on desmin degradation . Interestingly , both miR-21 and YOD1 siRNAs induced the re-distribution of desmin , resulting in increased co-localization of desmin and proteasomes . Additionally , our in vivo data also showed that CVB3 infection led to downregulation of YOD1 and ubiquitin-proteasome mediated desmin degradation , which causes subsequent desmosome destruction in the mouse heart . These findings suggest that YOD1 possesses a similar function to OTUB1 in stabilizing certain cellular proteins and that suppression of YOD1 expression during CVB3 infection is the cause of desmosome damage . Ubiquitin contains seven lysine residues ( K6 , K11 , K27 , K29 , K33 , K48 and K63 ) and a N-terminal methionine ( M1 ) which potentially contribute to the linkage of polyubiquitin chain to targeted proteins [57] . The canonical K48-linked polyubiquitin chains are frequently associated with the proteasome-mediated degradation of targeted substrates while the K63-linked ones are often involved in protein trafficking , DNA repair and inflammation processes [58] . In this study , we found that CVB3 , miR-21 or YOD1 siRNA stimulated K48- rather than K63-linked polyubiquitination , supporting that these treatments promote desmin degradation via the proteasome system . Further , we identified K108 and K406 located in the desmin protein as important sites for desmin ubiquitination and degradation . Mutation of these two sites inhibited desmin downregulation during CVB3 infection . Indeed , the introduction of mutation did not fully rescue the desmin level . There are several possible explanations . First , the detection of total desmin in the samples did not exclude endogenous wild type desmin which still can be regulated by miR-21 and CVB3 . This can be further tested with tagged desmin . Second , there may be other residues in desmin involved in its ubiquitination and degradation . Third , ubiquitination may not be the only mechanism for desmin downregulation , particularly during CVB3 infection which induces shut-off of host protein translation [59] . Further investigations may elucidate this mechanism . Another major component of ICD is fascia adherens . VCL is one of the major components of fascia adherens . Cardiomyocyte-specific excision of VCL results in dilated cardiomyopathy and sudden death in young mice [60] , both of which are typical consequences of CVB3-induced heart failure . We demonstrated that suppression of VCL by miR-21 led to the further inhibition of pan-cadherin and α-E-catenin , two cellular proteins associated with fascia adherens . This suppressed expression also caused disorientation of pan-cadherin and α-E-catenin in cell contact sites . The disappearance of distinct cell-cell connection sites supports the notion that VCL is essential for cell-cell contacts in cardiomyocytes . Inhibition of miR-21 attenuated the loss and redistribution of proteins in fascia adherens . Together , targeting of VCL by miR-21 yields a negative regulatory effect on fascia adherens during CVB3 infection . In conclusion , we revealed a novel role of miR-21 on controlling the integrity of cardiomyocyte ICDs through targeting YOD1 and VCL . The disorganization of desmosomes and fascia adherens by miR-21 expression during CVB3 infection may contribute to the pathogenesis of viral myocarditis ( Figure S11 in Text S1 ) . Based on the understanding of the underlying mechanism of miR-21 function , new strategies can be developed for drug targeting to protect the integrity of the myocardium , which can be use to prevent or treat viral myocarditis .
This study was carried out in strict accordance with the recommendations in the Guide to the Care and Use of Experimental Animals – Canadian Council on Animal Care . Alls protocols were approved by the Animal Care Committee of Faculty of Medicine , University of British Columbia ( protocol number: A11-0052 ) . Male A/J mice ( 4-week old ) were purchased from Jackson Laboratory . Mice were infected by intraperitoneally inoculation with 5×103 plaque-forming unit ( pfu ) of CVB3 or sham-infected with phosphate buffer saline ( PBS ) ( Sigma ) . HeLa , NIH 3T3 and HEK 293T cells were cultured in Dulbecco's modified Eagle's medium ( DMEM ) ( Lonza ) with 10% fetal bovine serum ( FBS ) ( Sigma ) . HL-1 cells were cultured in Claycomb medium ( Sigma ) with 10% FBS . Immortalized human cardiomyocytes were purchased from Applied Biological Materials and cultured in Prigrow I medium with 10% FBS . Viral infection of cells was conducted by incubation with viruses for 1 h in a serum free medium followed by switching to complete medium . Details are given in the Supporting Information . One mL of CVB3 stock was aliquoted to a 2 mL tube and kept on ice . UV irradiation was conducted in a UV Stratalinker 1800 ( Stratagene ) for 30 min with the virus tube kept 5-cm from the UV bulb . The viruses were then tested by infection of HeLa cells and WB detection of the absence of VP-1 to confirm the successful irradiation . The supernatants from CVB3 infected samples were collected and serially diluted . The diluted supernatants were added onto HeLa cells in 6-well plates ( 8×105 cells/well ) . Cells were washed with PBS after 1 h of incubation with the supernatants , supplemented with 0 . 75% soft agar in DMEM and 10% FBS , and incubated for 3 days . After incubation , cells were fixed with Carnoy's fixative for 30 min and stained with 1% crystal violet . The viral plaques were counted and the virus titers were calculated as the plaque forming units per mL ( pfu/mL ) . All the assays were conducted at least three times . Mouse heart and cellular RNAs were extracted using the miRCURY RNA Isolation Kits ( Exiqon ) according to the manufacturer's instructions . Part of the mouse heart RNAs ( 4 dpi and 7 dpi ) were submitted to Exiqon ( Denmark ) for miRNA microarray analysis as described previously [61] . The remaining heart RNAs and cellular RNAs were then reverse transcribed using a TaqMan MicroRNA Reverse Transcription Kit ( Life Technologies ) . Mature miRNA levels were detected by the TaqMan MicroRNA Assay ( Life Technologies ) using relative quantitative methods as described previously [18] . U6 RNA was detected as the endogenous control for data normalization . For desmin q-RT-PCR , the cellular total RNAs were reverse transcribed by using the superscript III first-strand synthesis system ( Life Technologies ) and detected using the QuantiTect SYBR Green PCR master mix ( Qiagen ) . GAPDH was detected as an endogenous control . Primers were listed in Table S2 in Text S1 . All q-RT-PCR experiments were repeated in triplicates with the no-template as a control . Mouse heart tissues and cultured cells were lysed with the RIPA lysis buffer . Proteins were separated by sodium dodecyl sulfate polyacrylamide gel electrophoresis ( SDS-PAGE ) , transferred to nitrocellulose membranes and identified by immunoassay . Protein levels were quantified by using ImageJ program . All the experiments were conducted at least three times . More details can be found in the Supporting Information . Cells cultured on glass cover slips ( Thermo Fisher ) were washed with PBS and fixed with methanol/acetone ( 1∶1 ) for 20 min at −20°C . Cells were then washed with TBS twice and blocked with 2 . 5% bovine serum albumin ( BSA ) ( Sigma ) in TBS for 1 h at room temperature followed by incubation with primary antibodies diluted in blocking buffer overnight at 4°C . Cells were then washed with TBS five times ( 5 min/time ) at room temperature . Secondary antibodies diluted in blocking buffer were then added into the samples and incubated for 1 h at room temperature . Samples were then washed with TBS five times at room temperature . The cover slips were stained with DAPI ( DAKO ) and mounted onto microscope glass slides ( Thermo Fisher ) with nail oil . Images were captured using a Leica AOBS SP2 confocal microscope ( Leica , Allendale , NJ ) and analyzed by using Volocity software . Details on the antibodies used are listed in the Supporting Information . Cultured cells or mouse heart sections were washed with 0 . 1M sodium cacodylate buffer and fixed in the primary fixing solution ( 2 . 5% glutaraldehyde ( Polysciences ) in 0 . 1 M sodium cacodylate buffer ) for 1 h . Cells were washed with 0 . 1 M sodium cacodylate buffer for 3×10 min and fixed with the secondary fixation solution ( 1% osmium tetroxide ( Polysciences ) and 1% potassium ferrocyanide in 0 . 1 M sodium cacodylate buffer ) for 1 h followed by 3×10 min washes with distilled water . Cells were then collected in 1 . 5 mL Eppendorf tubes and dehydrated by incubating with acetone ( 30% , 50% , 70% and 90% for 15 min each followed by 100% acetone ( 3×10 min ) ) . The samples were infiltrated with a mixture of acetone-Eponate 12 resin ( Epon ) ( Ted Pella ) ( 1∶1 ) for 1 . 5 h and then with acetone-Epon ( 2∶1 ) for overnight . The samples were further infiltrated with 100% Epon for 6 h , embedded in 100% Epon in a flat embedding mould and cut into thin sections of 60 nm thickness using a UC6 Ultramicrotome and viewed under a Tecnai 12 transmission electron microscope ( FEI Inc . ) For cultured HL-1 cells , 100 cells were analyzed for each sample to calculate the desmosome number . Desmin from the cultured cells was pulled down by desmin antibody ( Abcam ) using a Pierce Crosslink IP Kit ( Thermo Scientific ) following the manufacturer's instructions . The enriched desmin was then separated by 6% SDS-PAGE and immunoanalyzed by using an anti-ubiquitin antibody ( Thermo Scientific ) , K48-linkage specific polyubiquitin antibody ( Cell Signaling Technology ) or K63-linkage specific polyubiquitin antibody ( Cell Signaling Technology ) . The hearts were collected and fixed in 10% formalin . Tissues were then embedded in paraffin and sectioned for standard hematoxylin and eosin ( H&E ) staining to evaluate cardiac inflammation and damage using the methods described previously [62] . miRNA mimics ( Life Technologies ) , siRNAs ( Dharmacon ) and miRNA inhibitors ( Life Technologies ) were transfected into cells using the Lipofectamine RNAiMAX reagent ( Life Technologies ) according to the manufacturer's instructions . Cells were subjected to further infection or collected for analysis at 48 h post transfection . For more details , please refer to Supporting Information . Cells were transfected with miRNA mimics or siRNAs for 6 h and treated with proteasome inhibitor MG132 ( Santa Cruz ) or equal volume of DMSO ( Sigma ) at 10 µM for 24 h . Cellular proteins were then collected at 48 h post transfection for detection of reduced protein degradation by WB analysis . The wt and mut binding sites of miR-21 within the 3′UTR of YOD1 or VCL were synthesized by Integrated DNA Technologies . Oligomers were annealed and inserted into the pmirGLO Dual-Luciferase miRNA Target Expression Vector ( Promega ) according to the manufacturer's instructions . The oligonucleotides used for annealing are listed in Table S2 in Text S1 . Dual luciferase assays were conducted using Dual-Luciferase Reporter Assay System ( Promega ) . YOD1 expression plasmid and the corresponding empty vector were purchased from Origene and transfected at the concentration of 1 µg/well in 6-well plates using lipofectamine 2000 ( Life Technologies ) . A plasmid overexpressing wt mouse desmin was purchased from Origene and used for generating desmin mutants through the mutagenesis service from Topgenetech Inc . . These mutants include two single mutations ( K108R and K406R ) and one double mutation ( K108R/K406R ) . All the vectors were confirmed by sequencing . More details are provided in the Supporting Information . All experiments were repeated at least three times . The Student's t-test was used for the paired comparison among the samples . A p value<0 . 05 ( labeled with “*” ) in two-tailed tests was considered as statistically significant . “**” was used for labeling differences with p value<0 . 01 .
|
Coxsackievirus B3 ( CVB3 ) is one of most common causes of heart inflammation and failure . However , the mechanism by which CVB3 induces cardiac damage has not been fully elucidated . Particularly , the involvement of microRNAs ( miRNAs ) , a family of small RNAs controlling the progression of a wide range of diseases , in CVB3 infection is still unclear . These small RNAs are essential to understand the CVB3-caused heart muscle cell injury and have great potential to serve therapeutic purposes . Here , we systematically analyzed the miRNA changes during CVB3 infection and found that miR-21 is increased by viral infection . We further demonstrated that the CVB3-induced miR-21 triggers heart muscle cell damage by interfering with the cell-cell interactions . miR-21 suppresses the levels of components in cell-cell interactions by either promoting the degradation of those proteins or directly inhibiting the protein production . Inhibition of miR-21 can reduce the host injury caused by CVB3 infection . Our findings will shed new lights on the pathogenesis of CVB3-induced heart failure .
|
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2014
|
Coxsackievirus-Induced miR-21 Disrupts Cardiomyocyte Interactions via the Downregulation of Intercalated Disk Components
|
Neisseria meningitidis is a leading cause of sepsis and meningitis . The bacterium recruits factor H ( fH ) , a negative regulator of the complement system , to its surface via fH binding protein ( fHbp ) , providing a mechanism to avoid complement-mediated killing . fHbp is an important antigen that elicits protective immunity against the meningococcus and has been divided into three different variant groups , V1 , V2 and V3 , or families A and B . However , immunisation with fHbp V1 does not result in cross-protection against V2 and V3 and vice versa . Furthermore , high affinity binding of fH could impair immune responses against fHbp . Here , we investigate a homologue of fHbp in Neisseria gonorrhoeae , designated as Gonococcal homologue of fHbp ( Ghfp ) which we show is a promising vaccine candidate for N . meningitidis . We demonstrate that Gfhp is not expressed on the surface of the gonococcus and , despite its high level of identity with fHbp , does not bind fH . Substitution of only two amino acids in Ghfp is sufficient to confer fH binding , while the corresponding residues in V3 fHbp are essential for high affinity fH binding . Furthermore , immune responses against Ghfp recognise V1 , V2 and V3 fHbps expressed by a range of clinical isolates , and have serum bactericidal activity against N . meningitidis expressing fHbps from all variant groups .
The Gram negative bacterium Neisseria meningitidis is part of the normal human nasopharyngeal flora in up to 40% of healthy individuals [1] , [2] and a leading cause of sepsis and meningitis worldwide , with a case fatality rate from septicaemia of approximately 10% [3] , [4] . Because of the non-specific early symptoms and rapid progression of meningococcal disease , there is an urgent need to develop vaccines to protect individuals from this important infection [4] , [5] . N . meningitidis is classified into 12 different serogroups based on its polysaccharide capsule , although only six serogroups are responsible for the majority of disease . Currently there are vaccines based on the polysaccharide capsule of four of these serogroups ( i . e . A , C , W , and Y ) [5] . However , the capsule of serogroup B N . meningitidis ( MenB ) is structurally identical to a modification of a cell adhesion molecule present in the foetal brain , and is thus weakly immunogenic and could induce autoimmunity if used as a vaccine [6] . Vaccines based on outer membrane vesicles have proven to be effective against MenB but only in combating epidemic disease caused by a single clone [7]; the most effective approach to produce a broadly protective vaccine against all N . meningitidis serogroups ( including MenB ) will be the use of protein based vaccines [8] . Factor H binding protein ( fHbp ) of N . meningitidis is an important component of MenB vaccines currently under advanced clinical development [8] , [9] . Immunisation with fHbp elicits serum bactericidal antibodies [8] , [9] , a marker of protection , and the protein provides an important mechanism for immune evasion for the meningococcus by recruiting the negative complement regulator , factor H ( fH ) , thereby protecting N . meningitidis against complement-mediated lysis [10] , [11] . fHbp is a surface expressed lipoprotein consisting of two β barrels [12] , [13] . Based on sequence alignments , fHbp has been categorised into three different variant groups , V1 , V2 and V3 , or two families , A and B [8] , [9] . However , immunisation with V1 fHbp ( family B ) does not elicit bactericidal responses against V2 and V3 ( family A ) fHbp-expressing strains and vice versa [8] , [9] , [14] . In addition , immunisation with one V1 peptide does not provide cross-protection against all strains expressing V1 fHbps [14] . This suggests that a broadly protective vaccine should include multiple fHbps , or fHbps which elicit cross-protection . Current vaccines contain V1 . 1 fHbp together with other antigens , or a combination of V1 and V3 fHbps [8] , [9] . Although Neisseria gonorrhoeae binds fH to its surface , the receptor on the bacterium is Por1A which is not related to fHbp [15] . However , inspection of gonococcal genome reveals a homologue of fhbp ( annotated as ngo0033 in N . gonorrhoeae strain FA1090 ) ; we designated the predicted protein Gonococcal homologue of fHbp ( Ghfp ) , because it is approximately 90% identical to V3 fHbps . In contrast to meningococcal fHbp , Ghfp is highly conserved with three alleles described which only differ by one or two amino acids [16] . Furthermore , Ghfp is not predicted to contain a signal sequence or a lipid modification motif ( LXXC ) suggesting it is unlikely to be expressed on the bacterial surface [16] , [17] . Here , we investigate the location , the fH binding capacity and the vaccine potential of Ghfp .
Analysis of the genome sequence of N . gonorrhoeae strain FA1090 identified the presence of a fhbp homologue [16] , [17] which we designated Gonococcal homologue of fHbp , Ghfp . Sequence alignment of Ghfp with available fHbp sequences ( www . neisseria . org ) reveals that Ghfp has between 60–67% , 81–89% and 86–94% amino acid identity with V1 , V2 and V3 fHbps , respectively ( Supplementary Figure S1 ) . To investigate the cellular location of Ghfp , sera were raised against recombinant Ghfp from N . gonorrhoeae strain FA1090 . By Western blot analysis , sera recognised a protein with an estimated molecular weight of 30 kDa ( corresponding to Ghfp ) in lysates of N . gonorrhoeae strains FA1090 and F62; no protein was detected in lysates from F62Δghfp ( Figure 1A ) . Sera raised against Ghfp also recognise V3 . 28 fHbp expressed by N . meningitidis strain M1239 ( Figure 1A ) . Moreover , Ghfp was expressed by 20 clinical N . gonorrhoeae strains isolated in the UK ( Figure 1B and not shown ) . To determine whether Ghfp is surface located , we performed flow cytometry analysis with anti-Ghfp serum to detect Ghfp on the surface of N . gonorrhoeae F62 and F62Δghfp , and fHbp on N . meningitidis M1239 and M1239Δfhbp ( Figure 1C and 1D ) . Results demonstrate that anti-Ghfp serum recognises V3 . 28 fHbp on the surface of N . meningitidis , but there was no detectable Ghfp on the gonococcal surface . To exclude the possibility that the lack of detection of Ghfp by flow cytometry was due to low expression levels , we also exposed viable bacteria to proteinase K , and monitored the degradation of Ghfp , a surface protein i . e . the α-2 , 3-sialyltransferase , Lst [18] , and the cytoplasmic protein RecA by Western blot analysis . Ghfp and RecA were unaffected by exposing cells to proteinase K . The relative amounts of full length protein after incubation with reducing concentrations of proteinase K ( serial three-fold dilutions from 3 ng/ml , Figure 1E ) were: Ghfp , 94-90-89-100; RecA , 101-98-101-100 . In contrast , digestion of Lst was observed : the amount of Lst peptides with reducing concentrations of proteinase K were 214-158-128-100 ( Figure 1E ) . Recombinant Ghfp is cleaved by these concentrations of proteinase K ( data not shown ) demonstrating that Ghfp is susceptible to cleavage by this protease . In conclusion , our results demonstrate that Ghfp is expressed by N . gonorrhoeae but is not located on the bacterial surface , in keeping with previous predictions . Due to its high sequence identity with V3 fHbp , which binds fH with a KD in the nM range [13] , [14] , fH binding to Ghfp was tested by far Western analysis . Surprisingly , there was no detectable fH binding to Ghfp using normal human serum as the source of fH ( Figure 2A ) . Therefore , we compared the sequence of Ghfp with V2 and V3 fHbps that bind fH at high affinity , and identified five amino acids that are consistently different between Ghfp and V2/V3 fHbps i . e . R176 , D199 , D212 , R288 and D318 of Ghfp ( amino acid numbering according to fHbp V1 . 1 structure [12] , Supplementary data Figure S2 ) . Recent studies have shown that Ghfp is highly conserved [16] which we confirmed by sequencing Ghfp in a panel of 20 clinical isolates from the UK ( not shown ) . All three Ghfp polymorphisms in our isolates had been identified previously [16] and are also present in V2 and/or V3 fHbp , so do not include residues ( R176 , D199 , D212 , R288 and D318 ) that are unique to Ghfp . The amino acids R176 and D199 are located in the predicted N-terminal barrel of Ghfp and , similar to C-terminal β barrel residue D212 , are not located at the region of Ghfp corresponding to the interface of fHbp with fH [13] . In contrast , R288 is located in close proximity to the predicted fH:Ghfp interface , while D318 could be involved in interactions between the two predicted β barrels of Ghfp . To determine whether these five amino acid changes are responsible for the reduced fH binding to Ghfp , we modified these specific amino acids into the equivalent residues in the closely related V3 . 45 fHbp . Modification of all five residues in GhfpM1–5 ( i . e . R176Q , D199G , D212S , R288H and D318G ) was sufficient to enable Ghfp to bind fH by far Western analysis ( Figure 2B ) . Analysis of GhfpM1 ( R176Q ) , GhfpM1–2 ( R176Q and D199G ) , GhfpM1–3 ( R176Q , D199G and D212S ) and GhfpM1–4 ( R176Q , D199G , D212S and R288H ) demonstrated that these modifications did not restore fH binding . However the substitutions R288H and D318G in GhfpM4–5 are sufficient to confer fH binding to Ghfp by far Western analysis ( Figure 2C ) . To further analyse this interaction in more detail , the binding of Ghfp and V3 . 45 fHbp to fH6–7 was also investigated by Surface Plasmon Resonance ( SPR , Figures 2D and 2E ) . The dissociation constant of V3 . 45 fHbp and complement control protein ( CCP ) domains 6 and 7 of fH ( fH6–7 ) was 1±4 nM , similar to previous results for V3 fHbps [13] , [14] . Consistent with our far Western analysis , no fH binding was detected to Ghfp by SPR under these conditions . Moreover , no fH binding was observed to GhfpM5 ( D318G ) . There was fH binding detected to GhfpM4 ( R288H ) ( KD of 16±0 . 3 nM ) while the double substitution , GhfpM4–5 ( R288H and D318G ) , resulted in fH binding that was equivalent to fHbp ( KD i . e . of 2 nM ) . To exclude the possibility that Ghfp interacts with fH via CCP domains other than fH6–7 , we also examined fH binding by ELISA in which recombinant proteins were coated on the wells of plates and binding to purified full length fH was detected . Consistent with SPR , we observed fH binding to GhfpM4–5 , partial fH binding to GhfpM4 , and no fH binding to wild-type Ghfp or GhfpM5 ( Figures 2E ) . In conclusion , despite its high amino acid identity with V3 fHbp , Ghfp does not bind fH to any significant degree , and there are only two amino acids responsible for the striking difference in affinity compared with fHbp . Due to its high sequence identity with V3 fHbp , we were able to map the Ghfp sequence on our V3 fHbp structure [13] . Figure 2G shows the location of these two important amino acids , R288 ( altered in M4 ) and D318 ( M5 ) ; while R288 lies on the face of Ghfp which interacts with fH in fHbps , D318 may influence the interaction between the two β barrels of the protein . As the modifications R288H and D318G in Ghfp are sufficient to confer high affinity fH binding , we next investigated whether the corresponding residues in V3 . 45 fHbp are necessary for binding to fH . We generated V3 . 45 fHbp with H288R and G318D ( fHbpM4–5 ) ; these modifications were not included in our recent analysis of fH:V3 fHbp interactions which involved alanine substitution of fHbp [13] . Initially binding of fH was examined by far Western analysis ( Figure 3A ) and showed loss of detectable fH binding to fHbpM4 ( H288R ) , fHbpM5 ( G318D ) or fHbpM4–5 ( H288R and G318D ) . To verify these results , binding of fH6–7 to fHbp wild type and modified proteins was analysed by SPR ( Figure 3B ) . No detectable binding of fH was observed to fHbpM4 , fHbpM5 and fHbpM4–5 under these conditions , demonstrating that both of these residues are necessary for high affinity interactions with fH . To exclude the possibility that these modified fHbp molecules interact with fH via CCP domains other than fH6–7 , we examined binding to purified full length fH by ELISA . Consistent with SPR , we observed fH binding to fHbp V3 . 45 but no binding to fHbpM4 , fHbpM5 and fHbpM4–5 ( Figure 3C ) . Taken together , we conclude that the amino acids present at positions 288 and 318 are the basis for the profound difference in interactions with fH observed in the closely related proteins from the gonococcus and meningococcus . Next we investigated the vaccine potential of Ghfp by examining the ability of sera raised against this protein to recognise fHbps expressed by a range of N . meningitidis isolates . Immune sera not only recognise closely related V3 fHbps expressed in whole cell extracts of N . meningitidis but also V1 and V2 proteins ( Figure 4A ) . However , V2 . 23 fHbp expressed by N . meningitidis strain 5/99 was not detected by anti-Ghfp serum or by sera raised against V2 fHbp [19] , suggesting that this strain expresses little or no fHbp . Therefore , we examined whether anti-Ghfp serum recognises equivalent amounts of different recombinant fHbps by ELISA . Surprisingly , immune sera raised against Ghfp detected all V1 , V2 and V3 fHbps examined ( Figure 4B and C ) . Serum bactericidal activity ( SBA ) is an established correlate of protective immunity against serogroup C meningococcal infection [8] . To determine whether immunisation with Ghfp elicits functional immune responses , we evaluated the SBA of anti-Ghfp serum against several N . meningitidis strains expressing V1 , V2 and V3 fHbp ( Figure 4D ) . We found SBA against strains expressing V1 , V2 and V3 fHbps . SBA can be influenced by expression levels of fHbp or inherent serum resistance of the bacteria due to capsule expression [20] . To study the observed cross-protection of anti-Ghfp serum independent of these factors , we constructed isogenic strains of N . meningitidis MC58 each expressing one of the seven most prevalent fHbps ( i . e . V1 . 1 , V1 . 4 , V1 . 13 , V2 . 16 , V2 . 19 , V3 . 45 and V3 . 47 ) from disease isolates in England and Wales , accounting for 70% of cases [19] . To this end , we inactivated the wild-type copy of fHbp and introduced a single copy of the gene encoding each of the selected variants at an ectopic site under the control of an IPTG inducible promoter . Expression of the different fHbps was confirmed by Western blot analysis of whole cell extracts ( Figure 5A ) and surface expression verified by flow cytometry ( Figure 5B and C ) , showing higher expression levels compared to wild type fHbp expression . We determined the SBA of anti-Ghfp serum against the isogenic N . meningitidis strains and compared the findings with sera raised against V1 . 1 or V3 . 45 fHbp ( Figure 5D ) . We found that anti-Ghfp serum exhibited SBA against N . meningitidis expressing V1 . 1 , V1 . 4 , V2 . 16 , V2 . 19 , V3 . 45 and V3 . 47 . In contrast , anti-fHbp V1 . 1 serum only elicited SBA responses against V1 . 1 and V1 . 4 expressing strains , while anti-V3 . 45 fHbp serum had SBA against all V2 as well as the V3 . 45 expressing strains ( i . e . strains expressing family A proteins ) . No detectable SBA was measured with any sera against the isogenic MC58Δfhbp strain or using sera from mice receiving adjuvant alone ( data not shown ) . To examine this cross-protection in another genetic background , we constructed isogenic strains of N . meningitidis H44/76 in a similar way to express V1 . 1 , V2 . 16 or V3 . 47 , and observed similar cross-protective SBA responses ( Figure 5E ) . In conclusion , Ghfp can elicit SBA against V1 , V2 and V3 fHbp expressing N . meningitidis and is therefore a naturally occurring protein capable of providing cross-protection .
N . meningitidis and N . gonorrhoeae are two human specific , closely related pathogens that inhabit distinct niches in the body . N . gonorrhoeae causes sexually transmitted infections predominantly affecting the mucous membranes of the genito-urinary tract , while N . meningitidis colonises the nasopharynx [21] . Despite sharing many similarities of the genetic level , these bacteria employ entirely different mechanisms to evade immune responses , and in particular , to avoid complement activation on their surface [22] . For example , disease isolates of N . meningitidis express a polysaccharide capsule which is essential for high-level serum resistance [23] , while N . gonorrhoeae is not encapsulated . Instead sialylation of lipopolysaccharide markedly promotes complement resistance in the gonococcus [24] but this has less impact on N . meningitidis [25] . Both organisms have evolved to bind fH to their surface to prevent complement activation ( by down-regulating the alternative pathway ) but use different strategies . The gonococcus recruits fH via an exposed surface loop of Por1A ( loop 5 ) , an outer membrane porin often expressed by isolates recovered from patients [15] . fH can also bind to gonococci expressing Por1B albeit to a lesser degree , with this interaction facilitated by lipopolysaccharide sialylation [26] . Although meningococci express class 3 and class 2 porins ( which are related to Por1A and Por1B of N . gonorrhoeae , respectively ) , these are not involved in fH binding; loop 5 of the meningococcal porins lacks a region present in gonococcal Por1A , which probably accounts for its inability to bind fH [27] . Instead , the surface expressed lipoprotein fHbp mediates high affinity binding of fH by the meningococcus irrespective of variant group [13] . This interaction enhances bacterial survival in whole blood and prevents serum dependent killing [10] , [11] . It is not clear why the organisms have adopted alternative approaches to exploit the same human molecule , but it is likely to be influenced by the affinity of the interaction , the local availability of fH and the density of the bacterial receptor , as well as other factors conferring complement resistance . Without capsules , gonococci are largely reliant on their capacity to recruit fH and C4bp to survive in the human host [28] , [29] . Therefore the relatively low levels of fH in the genito-urinary tract may have favoured its recruitment by a highly abundant protein on the gonococcal surface , such as porin . Here , we show that Ghfp , the gonococcal homologue of the meningococcal fH receptor , does not bind fH to any detectable extent despite its high sequence identity with fHbp . Remarkably , only two amino acids in Ghfp ( R288 and D318 ) that differ from those in fHbp are responsible for this lack of interaction . Furthermore , the replacement of the equivalent amino acids in V3 . 45 fHbp ( i . e . H288R and G318D ) resulted in loss of fH binding . The H288R modification is located at the fH:fHbp interface; the side chain of fHbp H288 sits in a hydrophobic pocket in fH formed by H337 , Y353 and the methylene groups of the R341 . The extended side chain of Ghfp R288 is too long to fit into this pocket without remodelling the interface , and would also result in electrostatic repulsion with R341 of fH . The lack of fH binding to V3 . 45 fHbpM5 ( i . e . G318D ) is more difficult to explain as it is located away from the fH:fHbp interface , and is at the end of the final strand of the second β barrel . However , the register of this strand is such that the side chain of residue 318 points into the hydrophobic core of the barrel . Substitution of Gly with Asp is not possible without structural rearrangement due to steric clashes in the hydrophobic core as it is energetically unfavourable to place a negative charge in the hydrophobic environment . Given this final strand also makes crucial contacts with the first β barrel , this substitution could lead to structural rearrangements at interface between the two barrels and therefore alter the distal fH binding site ( which comprises both barrels ) . Recently , we identified several residues in V1 , V2 and V3 fHbps which are needed for high affinity interactions with fH through alanine scanning mutagenesis [13] . Here we found two further mutations that abolish fH:fHbp binding by analysing the binding characteristics of a natural protein . While fHbp is located on the surface of the meningococcus , we demonstrate that Ghfp is not on the external surface of the gonococcus , as suggested previously [17] . Examination of Ghfp also reveals the absence of a signal sequence for export so the protein is likely to remain intracellular and not secreted into the extracellular milieu . We can however not exclude the possibility that the location of Ghfp changes during infection . The function of Ghfp remains unknown , although due to its high level of identity to fHbp , we cannot exclude that Ghfp promotes survival in the presence of antimicrobial peptide LL-37 [30] or has a role in siderophore binding [31] . However , these are unlikely functions for Ghfp given the location of the protein . fHbp is a key component of protein sub-unit meningococcal vaccines under late phase clinical development [8] , [9] , [32]–[34] . Unfortunately , antibody responses against fHbp are thought to be largely variant/family specific . Therefore fHbp-based vaccines consisting of a single natural fHbp might be expected to have limited coverage . To overcome this issue , vaccines under development have included fHbp together with other antigens namely GNA2132 , NadA , GNA1030 , GNA2091 and a membrane vesicle [35] , or multiple fHbp variants [9] . Here , we show that anti-sera raised against Ghfp has the potential to recognize representative V1 , V2 and V3 fHbps , in contrast to sera raised against the widely used V1 . 1 fHbp and V3 . 45 fHbp [8] . More importantly , we showed that Ghfp has the potential to elicit SBA against wild-type N . meningitidis , and two different strains expressing the most common V1 , V2 and V3 fHbps . SBA of murine immune sera was assayed in the presence of rabbit complement . Although a heterologous non-human source , rabbit complement has been used to validate the immunogenicity of conjugate vaccines in pre-clinical and clinical studies [36] . Furthermore , V1 fHbps differ in their recognition by sera raised against Ghfp ( Figure 4A ) but this cannot be explained at the level of overall sequence identity as the proteins we examined are all approximately 60% identical to Ghfp . The advantage of using isogenic strains over naturally occurring isolates is that this approach allows analysis of the effect of diversity in protein sequence on cross-protective responses , while excluding strain-specific , confounding factors such as levels of expression and other mechanisms of immune escape [37] . This breadth of activity was an unexpected finding which has been seen with synthetic fHbp molecules containing epitopes from different fHbp variants [38] , [39] and is not the result of overexpression of fHbp in our isogenic strains; anti-sera raised against V1 . 1 only has SBA against V1 . 1 and V1 . 4 in line with previous results [14] , while our work showed that sera raised against V3 . 45 was able to elicit SBA against strains expressing V2 . 16 and V2 . 19 , again consistent with previous work demonstrating that raised anti-V3 . 45 fHbp serum does have SBA against some V2 fHbp expressing strains [14] . The mechanism underlying the broad protection of Ghfp is currently unknown . Based on the position of invariant amino acids in different fHbps , the protein has also been divided into five variable segments , designated as VA-VE . Using these five segments , fHbps can be categorized into six modular groups [40] . A closer inspection of the fHbps expressed in our isogenic strains reveals that all alleles and Ghfp harbour an identical variable segment D ( VD ) . However , this common sequence cannot be the basis of the cross-protection offered by Ghfp as fHbp V3 . 45 and V1 . 1 also harbour this region yet do not provide the same breadth of SBA . Another possibility is that the immunogenic properties of Ghfp are not solely dependent on its primary amino acid sequence but instead a result from its conformation . For instance , it is possible that due to D318 or other residues , the folding of Ghfp is altered compared with V3 . 45 , altering accessibility of certain regions of fHbp to B cell receptors and therefore inducing cross-protective responses . We also compared Ghfp and fHbp V3 . 45 with the rationally designed fHbp that showed broad cross-protection due to introduction of V2 and V3 epitopes into V1 . 1 fHbp [39] . However all the amino acids introduced into V1 . 1 to obtain the cross-protection are present in both Ghfp and fHbp V3 . 45 and so cannot explain the cross-protection we observed with Ghfp . In summary , Ghfp is a promising vaccine candidate against N . meningitidis since the protein not only offers a broad range of protection , but is also a naturally occurring non-fH binding molecule . There are potential drawbacks for the use of functional fHbps as a vaccine antigen due to its high affinity binding with fH . The extensive binding of fH to fHbp could shield immunogenic epitopes on the antigen resulting in less effective antibody responses [12] . Moreover , binding of fHbp to fH might reduce the immunogenicity at the site where antibody responses are initiated [41] or it could lead to formation of anti fH responses in the human host [42] . Indeed , non-functional fHbps have demonstrated non-inferior or enhanced immunogenicity compared with wild-type proteins in transgenic mice [13] , [43] , although any benefit of these antigens and Ghfp will need to be assessed in clinical trials .
The bacterial strains used in this work are shown in Table 1 and Table 2 . N . meningitidis was grown in the presence of 5% CO2 at 37°C on Brain Heart Infusion ( BHI , Oxoid , Basingstoke , United Kingdom ) plates with 5% ( vol . /vol . ) horse serum ( Oxoid ) or in BHI broth at 37°C . N . gonorrhoeae was grown in the presence of 5% CO2 at 37°C on GC agar ( Oxoid ) plates with Vitox ( Oxoid ) or in GC broth ( 15 g Protease peptone ( Oxoid ) , 4 g K2HPO4 , 1 g KH2PO4 , 5 g NaCl per litre ( Sigma Aldrich ) with 10 ml Kellogg's supplement ( 40 g glucose , 0 . 5 g glutamine , 50 mg Fe ( NO3 ) 9H2O , 1 ml 0 . 2% thiamine pyrophosphate per 100 ml , Sigma Aldrich ) . N . gonorrhoeae strains were obtained from across the UK in 2012 , and provided by the Sexually Transmitted Bacterial Reference Unit , Public Health England ( kind gift of Dr . Ison and Dr . Quaye ) . Escherichia coli was grown on LB agar plates or LB liquid at 37°C with appropriate antibiotics . Strain MC58Δfhbp [44] and H44/76Δfhbp ( constructed as MC58Δfhbp ) were complemented with pGCC4 [45] containing fhbp V1 . 1 , 1 . 4 , 1 . 13 , 2 . 16 , 2 . 16 , 3 . 45 and 3 . 47 . PCR to amplify fhbp was performed using genomic DNA from strains listed in Table 1 and using primers in Table 3 . PCR products were ligated into pGEMT ( Promega ) then pGCC4 . Transformation of N . meningitidis strain MC58ΔfHbp was performed as described previously [46] . M1239Δfhbp was constructed as MC58Δfhbp and F62Δghfp was a kind gift of Dr . M Pizza ( Novartis ) . N . meningitidis was grown overnight and re-suspended in phosphate buffered saline ( PBS ) . The concentration of bacteria was determined by measuring the O . D . at 260 nm of bacterial lysates in 1% SDS/0 . 1 M NaOH [46] and adjusted to 109 CFU per ml . Samples were mixed with an equal volume of 2× SDS-PAGE loading buffer and boiled for 10 minutes , then run on SDS-PAGE gels and transferred to Immobilon PVDF membranes ( Millipore ) . Membranes were blocked with 3% skimmed milk in 0 . 01% Tween in PBS ( PBS-T ) then incubated with primary ( immune sera at a 1∶10000 dilution ) and subsequently with secondary antibodies ( goat anti-mouse conjugated HRP IgG , Dako , 1∶20000 dilution ) all in PBS-T with 3% skimmed milk . fH binding to fHbp expressed by N . meningitidis or recombinant proteins was analysed by far Western blotting . Blots were incubated with normal human serum ( diluted 1∶100 ) for 45 minutes , then incubated with anti-fH ( Quidel 1∶1000 dilution ) , followed by rabbit anti-goat-HRP conjugated IgG ( Santa Cruz 1∶20000 dilution ) . Binding of secondary antibodies was detected using the ECL kit ( Amersham ) . Genes were amplified without their signal sequence by PCR with genomic DNA using primers described in Table 3 . PCR products were ligated into pGEMT then into pET28a ( Invitrogen , after digestion with BamHΙ and EcoRΙ ) or pET21b ( Invitrogen , using HindΙΙΙ and XhoΙ , or NdeΙ and XhoΙ ) . Proteins were expressed in E . coli and purified using Nickel affinity chromatography followed by a HiTrapQ HP column ( GE Healthcare ) [13] . Mutations were introduced into ghfp by overlapping PCR and into fHbp by QuikChange Site-Directed mutagenesis ( Agilent Technologies ) using primers described in Table 3 . SPR was performed using a Biacore 3000 ( GE Healthcare ) . Ghfp ( 50 µg/ml ) was first digested with 0 . 5 µg/ml trypsin for 2 hours at room temperature under constant shaking ( 300 rpm ) , then 0 . 1 mg/ml Pefabloc SC plus ( Roche ) was added and incubated for 10 minutes prior to dialysis against PBS . Recombinant proteins were immobilized on a CM5 sensor chip ( approximately 600–1000 RU ) ( GE Healthcare ) and increasing concentrations of fH6–7 ( 0 . 5 nM–32 nM ) were injected over the flow channels ( 40 µl/min ) . Dissociation was allowed for 300 seconds . BIAevaluation software was used to calculate the KD . Proteins ( 3 µg/ml , 50 µl per well ) were coated on the surface of wells ( F96 maxisorp , Nunc ) , and after blocking with 4% BSA in PBS-T , anti-Ghfp serum was added at different dilutions and detected with goat anti-mouse HRP antibody ( 1∶5000 diluted ) followed by substrate ( Becton Dickinson ) . To measure fH binding to Ghfp and fHbp , proteins were coated onto wells ( 3 µg/ml , 50 µl per well ) , then incubated with fH ( 1 µg/ml , Sigma ) and fH binding was detected using anti-fH poly clonal antibody ( Quidel , 1∶1000 dilution ) followed by an HRP-conjugated rabbit anti-goat IgG ( Dako , 1∶5000 dilution ) . Six female BALB/C mice ( 6–8 week old , Charles Rivers , Margate ) were immunised with antigens ( 20 µg ) absorbed to aluminium hydroxide ( final concentration 3 mg/ml ) , 10 mM Histidine-HCL , 2 M NaCl ( final concentration 9 mg/ml ) in ndistilled H2O and mixed overnight at 4°C . The antigens were given via the intraperitioneal route on days 0 , 21 and 35 . Sera were collected on day 49 by terminal anaesthesia and cardiac puncture . All procedures were conducted in accordance with Home Office guidelines . N . meningitidis was grown on BHI plates supplemented with 1 mM IPTG overnight and suspended in PBS supplemented with 0 . 1% glucose ( PBS-G ) to a final concentration of 5×104 CFU/ml . Bacteria were mixed with an equal volume of baby rabbit complement ( Cedarlane ) diluted 1∶10 in PBS-G . Heat inactivated serum , pooled from at least six mice was added to the wells . Control wells contained either no serum or no complement . Following incubation for 1 hour at 37°C in the presence of 5% CO2 , 10 µl from each well was plated onto BHI plates in duplicate and the number of surviving bacteria were determined . SBA was performed with two-fold dilutions of serum starting at 1∶32 . The bactericidal activity was expressed as the dilution of serum needed to kill more than 50% of bacteria in three independent experiments . Killing was calculated by comparing the number of surviving bacteria with those recovered from wells containing complement only . N . gonorrhoeae strain F62 was grown overnight in GC liquid at 37°C then diluted 1∶20 and grown for approximately six hours until an OD A600 of approximately 0 . 5 . An aliquot ( 1 ml ) of the bacterial culture was centrifuged at 13 , 000× g then re-suspended in 300 µl of 3 ng/ml Proteinase K ( Qiagen ) or 3 times dilutions from this . After incubation for 30 minutes at 37°C , Pefablock SC inhibitor ( Roche , final concentration 1 mM ) was added for 15 minutes at room temperature . Samples were then spun and suspended in 100 µl 1× sample buffer . Digestion was assessed by Western blot analysis with antibodies against Ghfp ( 1∶10000 diluted ) , RecA ( Abcam , 1∶5000 diluted ) , and α-Lst [18] ( 1∶20000 ) followed by goat anti-rabbit ( Santa Cruz Technology , 1∶20000 ) or goat anti-mouse HRP conjugated IgG ( Dako , 1∶20000 ) . The relative amounts of full length protein after incubation with reducing concentrations of proteinase K was measured using AIDA software . Bacteria ( 1×109 ) were fixed in 1 ml of 3% formaldehyde for two hours then washed with PBS . To measure fHbp expression , 5×107 bacteria were incubated with 50 µl anti-Ghfp serum ( diluted 1∶500 ) in PBS-T for 30 minutes at 4°C with shaking , washed in PBS-T then incubated with FITC conjugated goat anti-mouse antibody ( DAKO , diluted 1∶50 ) for 30 minutes . After washing , fHbp expression was measured by flow cytometry using the FACS calibur , calculating the mean FL1 of 10000 bacteria .
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Neisseria meningitidis is a major cause of sepsis and meningitis in young children and adolescents . Although vaccines are currently available against several serogroups , a broadly effective vaccine against serogroup B is still needed . Factor H binding protein ( fHbp ) can bind the human complement regulator factor H ( fH ) and is an important meningococcal immunogen . fHbp is divided into three variant groups ( V1 , V2 and V3 ) and immunisation with V1 fHbp does not elicit cross-protection against meningococcus expressing fHbp V2 or V3 , and vice versa . Here , we investigate a homologue of fHbp in Neisseria gonorrhoeae which we named Gonococcal homologue of factor H binding protein ( Ghfp ) . We show that in contrast to fHbp , Ghfp is not expressed on the bacterial surface and is unable to bind to factor H . Surprisingly , we found that antibodies raised against Ghfp have the capacity to mediate protective immunity against N . meningitidis expressing any of the three variant groups of fHbp , and could provide a broadly protective vaccine against N . meningitidis .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"biology"
] |
2013
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Distinct Binding and Immunogenic Properties of the Gonococcal Homologue of Meningococcal Factor H Binding Protein
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Neuropathies are neurodegenerative diseases affecting humans and other mammals . Many genetic causes have been identified so far , including mutations of genes encoding proteins involved in mitochondrial dynamics . Recently , the “Turning calves syndrome” , a novel sensorimotor polyneuropathy was described in the French Rouge-des-Prés cattle breed . In the present study , we determined that this hereditary disease resulted from a single nucleotide substitution in SLC25A46 , a gene encoding a protein of the mitochondrial carrier family . This mutation caused an apparent damaging amino-acid substitution . To better understand the function of this protein , we knocked out the Slc25a46 gene in a mouse model . This alteration affected not only the nervous system but also altered general metabolism , resulting in premature mortality . Based on optic microscopy examination , electron microscopy and on biochemical , metabolic and proteomic analyses , we showed that the Slc25a46 disruption caused a fusion/fission imbalance and an abnormal mitochondrial architecture that disturbed mitochondrial metabolism . These data extended the range of phenotypes associated with Slc25a46 dysfunction . Moreover , this Slc25a46 knock-out mouse model should be useful to further elucidate the role of SLC25A46 in mitochondrial dynamics .
Mitochondria are eukaryotic organelles with a wide range of functions . In addition to delivery of energy to cells via oxidative phosphorylation ( OXPHOS ) , they are involved in various other bioenergetic reactions , including Krebs cycle , β-oxidation of fatty acids and heme biosynthesis . Furthermore , they have roles in calcium signaling , stress response and apoptosis [1–3] . Consequently , they are a vital organelle . Not surprisingly , mitochondrial dysfunction is shown to be responsible for an increasing number of diseases , inherited or not [2 , 4] . To enable a variety of cells to respond to variable physiological conditions , particularly to adapt to varying energy demands , mitochondrial morphology is highly dynamic , with three main mechanisms: fusion , fission and cristae remodeling [5–7] . The balance between fusion and fission is particularly critical to regulate mitochondrial shape , size and number . In mammals , mitochondrial morphology is regulated by the following GTPase proteins: DRP1 ( Dynamin related protein 1 ) for fission , mitofusin MFN1 and MFN2 , and OPA1 ( Optic atrophy 1 ) for fusion . All these proteins are essential for development [8–10] and despite ubiquitous expression , their mutations primarily cause neurological diseases , as is common for proteins involved in mitochondrial dynamics [11–13] , probably due to neurons being energy-intensive cells [14] . Fusion proteins , for example , are involved in diverse syndromes . Dominant mutations of OPA1 cause Autosomal Dominant Optic Atrophy ( ADOA ) , affecting mitochondrial morphology ( aggregated and fragmented ) and content ( reduced content of mitochondrial DNA ( mtDNA ) and reduced ATP production ) [15–18] . Mutations in MFN2 cause Charcot-Marie-Tooth type 2A ( CMT2A ) disease in humans , a sensorimotor axonopathy with aggregated swollen mitochondria and altered structural integrity of inner and outer mitochondrial membranes [19 , 20] . Mutations of orthologous genes cause neurodegenerative diseases in other mammals , with for example , different mutations of MFN2 causing respectively an early axonopathy in Tyrolean Grey breed [21] and fetal-onset neuroaxonal dystrophy in dog [22] . Recently , human patients with combined ADOA and CMT2 phenotypes were identified as having recessive mutations in SLC25A46 [23] . This gene encodes a protein belonging to the mitochondrial carrier transporter family [24] , anchored on the outer mitochondrial membrane [23] . 53 proteins belong to this family . Most of them are responsible for the transport of a quantity of diverse metabolites across the inner mitochondrial membrane , which are necessary for all the metabolic pathways taking place in mitochondria [25–27] However , the observed phenotypes linked to SLC25A46 dysfunction suggested that SLC25A46 is rather involved in mitochondrial dynamics , and particularly may act as a pro-fission factor [23] . In cattle , due to massive inbreeding and bottlenecks effects in each selected breed , recessive mutations are likely to be transmitted to a large proportion of the population , leading to emergences of hereditary diseases [28] . In the late 2000’s , such an outbreak was described in the French Rouge-des-Prés breed with a new sensorimotor polyneuropathy named “Syndrome des veaux tourneurs” ( “Turning calves syndrome” ) because of a propensity of the affected calves to turn around themselves before falling down [29] . This neurodegenerative disease is characterized by an early onset of ataxia , especially of hindlimbs , and paraparesia affecting young calves ( 2–6 weeks old ) . Despite symptomatic care , nervous symptoms progress over the next months , leading to repetitive falls and ultimately resulting in permanent recumbency and inevitably euthanasia . Degenerative lesions involve both the general proprioceptive sensory and upper motor neuron motor systems [29] . The number of cases in this breed has rapidly increased in a few years ( based on statistics from the French National Observatory for Bovine Genetic Diseases ) , prompting a genetic study to identify the causal mutation . We identified herein by homozygosity mapping the 3Mb haplotype associated to this disease on bovine chromosome 7 . Further examination of this genetic interval allowed us to determine that this disease resulted from a single nucleotide polymorphism in the coding region of the SLC25A46 gene , leading to an apparently damaging amino acid substitution . The eradication of the “Turning calves syndrome” was undertaken , through the selection of non-carrier males so the number of reported affected calves rapidly dropped to zero . Therefore , a novel mouse knockout model of Slc25a46 was produced to elucidate the function of the encoded protein . The resulting phenotype described below included nervous symptoms but had more widespread effects , including alterations in mitochondrial dynamics and metabolism that caused premature death , thus extending the range of phenotypes associated with polymorphisms of this gene .
Calves from the Rouge-des-Prés breed presenting an ataxic gait and paraparesis of hindlimbs as described in [29] were examined by a veterinarian , and diagnosis was confirmed by histopathology . Pedigree analysis of 11 of them confirmed the autosomal recessive determinism of the “Turning calves syndrome” and the involvement of a predominant founder ancestor ( S1 Fig ) . This bull , born in 1973 , was a historical sire of the Rouge-des-Prés breed ( contributing 6% of the breed ) . Genotyping of 12 affected calves followed by homozygosity mapping identified a single 3 . 1 Mb homozygous interval at the telomeric end of bovine chromosome 7 ( S1 Table ) . This information was used to design a genetic indirect test , based on the haplotype associated to the disease , allowing to begin the selection against the “Turning calves syndrome” of the Rouge-des-Prés breed . To identify the causative mutation , whole-genome sequencing was performed on two affected cattle , one heterozygous carrier and one wild-type ( WT ) . The detected polymorphisms ( SNP and small indels ) were filtered in several steps . First , the genotype/phenotype correlation had to be perfect , i . e . affected cattle had to be homozygous for the polymorphism , and the WT and carrier cattle had to be homozygous or heterozygous , respectively , for the WT allele . Second , since this mutation is supposedly specific to the Rouge-des-Prés breed , with relatively recent emergence , polymorphisms were discarded if they were already present in the dbSNP database and/or in the Illumina SNP chip . Finally , polymorphisms were filtered according to their predicted effects on transcript and/or protein , based on the hypothesis that this mutation is very deleterious ( Table 1 ) . The two remaining putative causal SNPs were a single substitution in exon 15 of MAN2A1 gene and a single substitution in exon 4 of SLC25A46 gene ( Table 2 ) . These two polymorphisms were further tested ( Sanger sequencing and Taqman assay ) on an extended DNA multibreed panel , including 93 Rouge-des-Prés cattle , and 321 samples from 12 French cattle breeds . The MAN2A1 polymorphism was discarded because the genotype/phenotype association was not always found , and because it was present in other breeds . The SLC25A46 polymorphism had a perfect genotype/phenotype association . All the affected animals were homozygous for this mutation . All the proteins from the mitochondrial carrier family share a common structure with three tandemly repeated homologous domains about 100 amino acids long . Each domain contains two transmembrane alpha-helices forming a funnel-shaped cavity allowing the binding and the transport of the substrate from the intermembrane space to the matrix by a conformational transition [26 , 27 , 30] . The C/T SLC25A46 substitution leads to replacement of an arginine by a cysteine , in the first transmembrane helix of the protein ( Fig 1A–1C ) . This amino acid is highly conserved throughout evolution in SLC25A46 proteins ( Fig 1D ) . When compared to the other mitochondrial carriers , as described in [30] , it appears that this amino-acid is not conserved across this family . The most frequent amino-acid at this position is a threonine , and is shared by only 19 of the 53 mitochondrial carriers . This suggests a role more related to the specific biological function ( s ) of SLC25A46 . Based on SIFT software [31] , this substitution was expected to affect the function of SLC25A46 . The mutated protein was expressed normally in brain and liver of affected animals and was present in mitochondrial-enriched protein extracts , consistent with a typical mitochondrial localization ( Fig 1E ) . Affected calves have characteristic degenerative microscopic lesions in the central nervous system ( CNS ) and peripheral nervous system ( PNS ) , both in grey matter ( brain stem lateral vestibular nuclei and spinal cord thoracic nuclei ) and white matter ( dorsolateral and ventromedial funiculi of the spinal cord ) , in addition to demyelination in certain peripheral nerves [29] . Electron microscopy confirmed this neuropathy phenotype , with discrete lesions of demyelination and a few enlarged nodes of Ranvier ( Fig 1F ) . As mentioned above , selection against this disease in the affected breed was undertaken for obvious economic reasons as soon as the genetic test was commercially available . Thus , affected animals were rapidly unavailable , limiting the range of phenotypic investigations that could be performed to analysis of previously collected tissue samples . To better characterize the function of SLC25A46 , construction of mouse models was initiated . SLC25A46 mouse models were constructed , using TALEN ( Translation Activator-Like Effector Nuclease ) technology , by targeting mouse exon 3 , the exon homologous to the one mutated in the bovine gene . Following microinjection of the TALEN mRNA and screening of the resulting mice , two transgenic lines were established in a pure FVB/N genetic background: 1 ) Tg26 line with a 75 bp DNA deletion inducing exon 3 aberrant splicing and resulting in a truncated protein of 159 amino acids; and 2 ) Tg18 line with a 15 bp insertion / 3 bp deletion , causing replacement of 2 amino acids from the first transmembrane domain by six modified amino-acids ( Fig 2A , S2A Fig ) . Heterozygous mice were viable and appeared as fit as their WT counterparts ( they were monitored for at least 12 months ) . Transmission of the mutated allele followed Mendelian inheritance . In both lines , Slc25a46 was undetectable by western blot analysis , on both total protein and on protein extracts enriched for mitochondrial proteins ( Fig 2B and 2C ) . However , in Tg18 line , Slc25a46 mRNA levels were unchanged in homozygous mutant animals , except in peripheral nerves ( S2B Fig ) . It suggests that a repression of the translation of the Slc25a46 mRNA occurred in Tg18 mice and/or more likely that the mutated protein was not properly associated with the mitochondrial membrane and consequently was rapidly degraded . A degradation mechanism must also occur in Tg26 mice for the putatively translated truncated protein , in addition to a noticeable reduction in amount of Slc25a46 mRNA , probably due to mRNA decay ( S2C Fig ) . Thus , homozygous mutants from both lines were regarded as functional knock-outs and will now be referred to as Tg-/- mice . At birth , Tg-/- pups from the two lines were indistinguishable from each other and from their WT and heterozygous littermates , despite reported expression of the Slc25a46 gene early during mouse embryogenesis in various EST databases . However , their growth was reduced compared to the WT pups from the end of the 1st week of life , and from the 2nd week , they stopped gaining weight ( Fig 3A and 3B ) . The observed reduced growth rate started despite a normal feeding behavior during the first weeks , while the pups were still nursed by their mother , as evidenced by the presence of milk in their stomach ( Fig 3C ) and by a normal behavior in the cage ( i . e . all the pups were regularly seen under their mother , and none of them was left alone in the cage ) . Yet , at 3 weeks of age , intestinal tracts of Tg-/-mice were less filled than their WT counterparts , with reduced feces ( Fig 3D ) , consistent with their cachectic state . Furthermore , there were intestinal hemorrhages in the oldest Tg-/- animals ( Fig 3E ) . Intestinal length and diameter were smaller in Tg-/- than in WT mice . However , histological staining did not reveal any obvious change in the intestine from the Tg-/- mice which could explain their reduced growth ( S3A Fig ) . An ataxic gait was apparent from the 2nd week of life , especially on the hind limbs ( Fig 3F and 3G ) . Tg-/- mice walked on the tip of their toe , instead of putting the whole foot sole on the soil ( Fig 3F and 3G ) . This was evocative of a proprioception defect , as it is described in the “Turning calves syndrome” [29] . However , it did not evolve to permanent recumbency , perhaps due to the short lifespan of the Tg-/- mice ( see below ) . Moderate hyperreflexia was also evidenced on hindlimbs when pinching the mice’s toes . An epileptic-like phenotype was also noticed from the 2nd week of life ( S1 Movie ) . All Tg-/- mice died between the 3rd and 4th weeks of life , either spontaneously in the cage , or by euthanasia for evident ethic reasons ( Fig 3H ) . Post-mortem examination revealed that several other organs were affected in Tg-/-mice . Thymus and spleen were significantly smaller relatively to the body mass ( Fig 3I and 3J ) . This was expected as they are described as metabolic state sensors , with rapid atrophy in case of malnutrition [32] . Liver was also significantly smaller ( Fig 3I and 3J ) , and biochemical blood analyses showing increased biliary acids , bilirubin and cholesterol in Tg-/- mice were indicative of a cholestasis , and consistent with a stress of the liver ( Table 3 ) . Liver histology was nonetheless almost normal ( S3B Fig ) . Muscle damage was also suspected , based on a general decrease of muscle mass combined with increased creatine kinase and aspartate amino transferase ( Table 3 ) , but muscle histopathology was also unchanged in Tg-/- mice ( S3C Fig ) . Biochemical analysis revealed a highly-disturbed metabolism in Tg-/- mice , confirming the general alteration of their state ( Table 3 ) . Severe hypoglycemia was noted , which may be linked to the observed growth defect . Low plasma iron concentrations combined with high ferritin were indicative of defective iron metabolism and/or storage . Therefore , the phenotype of the Tg-/- mice was distinctly different from that of the above-mentioned bovine sensorimotor polyneuropathy , presenting a wider range of symptoms . Since Tg-/- mice displayed symptoms evocative of proprioception and motor involvement , investigations were then undertaken on the nervous system of Tg-/- mice . However , no major defect of the CNS was detected in Tg-/- mice ( based on HES and Luxol blue staining ) , with only minimal lesions consisting of rare vacuolated neurons in the lateral vestibular nuclei ( Fig 4A ) . Peripheral nerves lacked visible degenerative lesions , although the presence of macrophages containing lipid debris suggested a possible degenerative process ( Fig 4B ) . Axon diameters and myelin sheath thickness was comparable in both genotypes ( Fig 4C ) . Thus , even if it was not possible to exclude a peripheral neuropathy in Tg-/- mice , the fast evolution of the disease up to death may limit it to an early very mild form . Furthermore , the study of the optic nerve could not highlight any difference between WT and Tg-/- pups ( Fig 4D ) , nor degenerative lesions in the Tg-/- axons , an observation recalling the lack of reported vision defect in the “Turning calves” [29] but contrasting with consistency of this phenotype in recently reported human cases [23 , 33 , 34] . However , axons from CNS and PNS had abnormal round , small and aggregated mitochondria as evidenced in myelinated and non-myelinated fibers ( Fig 5A and 5B ) , indicating a fusion/fission imbalance , an observation also noticed in tissues from affected “Turning calves” ( Fig 5C ) . Moreover , most mitochondria in Tg-/- mice had abnormalities of their internal architecture , namely abnormal membranes and cristae . These abnormal mitochondria were also detected in the enteric nervous system of Tg-/- mice , in intestinal Auerbach plexus cells ( Fig 5D ) . In accordance with ubiquitous expression of Slc25a46 in mice ( S2B and S2C Fig ) , there were abnormal mitochondria in other organs from Tg-/- mice , indicating a generalized mitochondrial defect . Skeletal muscles also had numerous aggregated mitochondria , although their morphology generally remained normal ( Fig 5E ) , as well as muscular layers in the intestinal tract . Hepatocytes had numerous and smaller mitochondria with vesicular cristae , rarely attached to the inner mitochondrial membrane ( Fig 5F–5H ) . Since mitochondrial internal architecture and morphology were altered in several tissues , we searched for effects on mitochondrial metabolism . Regarding activity of each respiratory chain complex in mice , there were significant decreases for complexes I , III , and IV in brain and muscle from Tg-/- mice ( Fig 6A ) . However , there was an opposite trend in liver from Tg-/- mice , with a significant increase for complexes III and IV activities . This particular response could be explained by the specific effect of physiological stresses on the mitochondrial metabolism in various tissues and specifically the liver [35 , 36] . Krebs cycle enzymes , localized in the mitochondrial matrix , generally had no change in activities , except aconitase which was increased in muscles from Tg-/- mice , and fumarase which was increased in liver ( Fig 6B ) . Proper fusion/fission equilibrium is necessary to maintain a homogeneous and healthy population of mitochondria [37] . For example , several missense mutations of MFN2 causing autosomal dominant optic atrophy ‘plus’ phenotype induce a respiratory chain defect and mtDNA deletions and eventually mtDNA depletion in muscle cells [38 , 39] . Moreover , loss of mtDNA is also found in Ugo1p depleted cells , Ugo1p being SLC25A46’s homolog in yeast [40] . However , there was no significant mtDNA depletion or large deletion in liver , muscle or brain from homozygous mutant mice ( Fig 6C ) . Comparative MS-MS analysis was conducted in brain protein extracts after enrichment of mitochondrial proteins , in order to detect changes in protein expression induced by disruption of Slc25a46 in mouse . Amongst the detected proteins , only 26 were significantly up- or downregulated ( Table 4 ) . Interestingly , five downregulated proteins belonged to the Hsp70 ( 70 kDa Heat-shock protein ) family ( Grp78 , Hs71l , Hs71b , Hsp7c , Hs74 ) , as well as three others for which the p-value nearly reached the significance threshold ( Hsp72 , Grp75 , Hs90b ) . Such observations might suggest a role , direct or indirect , of Slc25a46 in the mitochondrial-Endoplasmic Reticulum ( ER ) contact sites ( see below ) . Alterations were also noted in mitochondrial membrane proteins associated with glucose transport ( Hk1 , Hk1-sb ) , and fatty acid metabolism ( Gpdm , Echa ) . Notably , hemoglobin subunits were significantly upregulated ( Hba , Hbb1 , Hbb2 ) . This upregulation may be linked to an iron dysregulation , as evidenced by biochemical analyses on Tg-/- mice . While this manuscript was first submitted , a paper was published , with evidence of interaction between SLC25A46 and fusion proteins MFN2 and OPA1 , and MIC60 and MIC19 proteins belonging to the MICOS complex [34] . Notably MS-MS results did not show any significant change of expression for these proteins , their level was then monitored by western blot on brain extracts ( S4A Fig ) . Tg-/- mice did not display significant expression level for these proteins . Thus the knock-out of Slc25a46 in mouse does not lead to a reduction of Mic60 and a potential disruption of the MICOS complex , contrary to the fibroblasts treated with siRNA , as described in [34] . Moreover , it is not compensated by a change in the expression of fusion proteins Opa1 and Mfn2 . Expression of OPA1 , MFN2 and MIC60 was also monitored by Western blot on bovine brain and liver protein extracts , but we could not infer a significant change in the expression of these proteins , especially because the number of biological samples was very low ( S4B Fig ) .
In the present study , we provided reliable evidence that the “Turning calves syndrome” , a recessive sensorimotor polyneuropathy reported in the French Rouge-des-Prés breed in the late 2000’s , was caused by a point mutation in SLC25A46 gene . The single amino acid substitution did not affect protein expression nor its proper location within the mitochondria ( based on western blot ) . However , it affected a highly conserved amino acid , in the first transmembrane helix of the protein . Amongst the mitochondrial carrier proteins , 14 are known to be associated to rare metabolic diseases [27 , 41] . Mutations are mostly located in functional domains of the proteins , including the substrate binding sites and the matrix and cytosolic gates ( which respectively open/close the carrier to the mitochondrial matrix and towards the cytosol ) [41] Interestingly , even the mutated amino-acid is not conserved amongst the mitochondrial carrier family , it is located just in the matrix gate area [30] , which is known to be critical for the conformational change . Electron microscopy confirmed axonal lesions in affected cattle and identified abnormal round and aggregated mitochondria in axons . This phenotype is reminiscent of mutations in mitochondrial fusion proteins such as MFN2 in CTM2A disease [20] , consistent with an fusion/fission imbalance . However , SLC25A46 function in fusion or fission remains elusive . Ugo1p , which is SLC25A46 homolog in yeast , plays a crucial role in fusion , in close interaction with Fzo1p and Mgm1p ( MFN1/2 and OPA1 homologs , respectively ) [40 , 42 , 43] . Ugo1p mutants had fragmented mitochondria , and a loss of mtDNA [40] . In humans , a pro-fission role of SLC25A46 was proposed , due to an increase of mitochondrial branching in fibroblasts derived from a patient carrying a homozygous missense mutation in the carrier domain of the protein [23] . In contrast , there was another report of a SLC25A46 mutation in a splice site , leading to a truncated transcript and perhaps to a knock-out [33] . In this case , the mitochondrial network was fragmented , suggesting a fusion role for SLC25A46 . To better understand SLC25A46 function , and because the selection against “Turning calves syndrome” made new biological material collection difficult in cattle , mouse knock-out models were constructed . In Tg-/- mice , nervous degenerative phenotypes ( ataxic gait and epilepsy ) were apparent from the 2nd week of life . Furthermore , Tg-/- mice also had pronounced weight loss and metabolic defects leading to premature death around weaning . Although histopathology did not account for this drastic phenotype , electron microscopy implicated involvement of mitochondria in several tissues . There was a fusion/fission imbalance ( similar to cattle ) , with numerous round aggregated mitochondria in the central and peripheral nervous systems , including the enteric nervous system . Abnormal mitochondria were present in Auerbach plexus cells . This may have contributed to dysmotility of the intestinal tract , and the subsequent observed weight loss , at least partially , as often described for multi-systemic mitochondrial diseases such as Mitochondrial Neurogastrointestinal Encephalopathy Syndrome . [44] These small and numerous mitochondria were also detected in muscle and liver . Clearly , effects of disruption of SLC25A46 were not restricted to the nervous system , consistent with ubiquitous expression of the gene . Mitochondria regulate their shape in accordance with the metabolic state of the cell . In case of starvation , mitochondrial length is increased , by phosphorylation of the fission protein Drp1 , leading to decreased fission [45] and/or by oligomerization of fusion protein OPA1 [46] . In mitochondrial fusion-incompetent cells , mitochondria cannot fuse and are degraded , leading to cell death . Tg-/- mice which experience weight loss , are in a metabolic state mimicking starvation . Consequently , the absence of elongated mitochondria suggests an impaired fusion in these animals . In addition to the fusion/fission imbalance , mitochondria from Tg-/- mice had disturbed internal architecture , with distorted and vesicular-like cristae , and cristae less frequently attached to the membrane . Cristae morphology is maintained and regulated mainly by OPA1 and by the MICOS complex [1 , 47] . This complex is composed of six subunits in yeast , with all of them inserted in the inner mitochondrial membrane [48] . Mutations in genes encoding these subunits result in an altered internal architecture , i . e . loss of cristae junctions , and cristae organized as membrane stacks [48–50] . MIC60 , also known as Mitofilin , is one of the key players of the MICOS complex . In yeast , the MIC60 homolog Fcj1p interacts with SLC25A46 homolog Ugo1p , forming close contact sites between outer and inner mitochondrial membranes [51] . The interaction between MIC60 and SLC25A46 has been recently documented in human [23 , 34] . In the report from Janer et al . , the absence of SLC25A46 resulted in a marked decrease in the steady-state level of MIC60 in studied human fibroblasts [34] . Based on abnormalities of mitochondrial architecture detected in Tg-/- mice , we inferred that Slc25a46 ( potentially in association with Mic60 ) , may contribute to establishment of a proper contact between outer and inner mitochondrial membranes in mammals . However , Mic60 was only marginally downregulated in Tg-/- mice ( MS/MS analysis ) , with the p-value nearly reaching the threshold of significance , and this downregulation could not be observed by Western blot analysis . Furthermore , MS/MS analysis did not highlight any downregulation of fusion factors interacting with Slc25a46 , such as OPA1 and MFN2 , nor did specific analysis of these proteins by Western blotting . These differences suggest either cell-type ( fibroblast vs brain cells ) and/or species’ specificities . Since cristae contain OXPHOS subunits ( i . e . respiratory complexes I to V ) , disorganization of cristae often decreases activity of OXPHOS subunits [49 , 52 , 53] and disturbs assembly of respiratory supercomplexes , with profound reduction in respiration efficiency [54] . Mitochondrial metabolism is indeed affected in Tg-/- mice , with a marked decrease in complexes I , III , IV activities in brain and muscle , and an increase in complexes III and IV activities in liver . This discrepancy is not unlikely , given the specificity of each tissue and each cell type in the response to physiological stresses [35 , 36] or to mutations [55 , 56] . Our proteomic analysis highlighted a potential interaction between Slc25a46 and Hsp70 proteins; eight of the latter were down-regulated in Tg-/- mice . These chaperone proteins , participate in the protein folding [57–59] and in the protein import across the outer mitochondrial membrane [60 , 61] in close interaction with Tom70 , which is also significantly downregulated . Thus , in Tg-/- mice , importation of proteins may be downregulated , either by a direct interaction between Slc25a46 and the import machinery ( interactions between Slc25a46 and Hsp90 , Grp75 and Grp78 were recently evidenced by immunoprecipitation [23] ) , or by a general alteration of the outer mitochondrial membrane structure . Interestingly , Grp78 also known as BiP , which is one of the most significantly downregulated protein in the Tg-/- mice , is considered as a major regulator of the ER , due to its multiple roles in the ER function [62] , and is shown to act at the ER-mitochondria interface under stress conditions [63 , 64] . The recent observation that SLC25A46 interacts with the Endoplasmic Reticulum Membrane Complex ( EMC ) and may participate to the regulation of the phospholipid flux between ER and mitochondria appears to support the pivotal role of SLC25A46 between ER and mitochondria [34] . Alternatively , since all these Hsp70 proteins function under the dependence of ATP , the affected mitochondrial metabolism may be insufficient to provide enough ATP , which could downregulate Hsp70 protein expression . Collectively , there was good evidence for a pivotal function of SLC25A46 between the outer and inner mitochondrial membranes . Disruption of Slc25a46 in mouse not only affected the subtle equilibrium between fusion and fission , but also disturbed the internal architecture and the link with a pool of Hsp70 chaperone proteins and potentially the mitochondrial-ER trafficking . Consequently , mitochondrial and general metabolisms were severely impacted , leading to premature death . This model seemed similar to an affected infant that died seven days after birth [33] . In contrast , in cattle affected by the “Turning calves syndrome” , the mutated protein was still present and we inferred that it retained a portion of its activity , as in humans carrying homozygous missense mutations . According to the localization of the mutations ( in cytosolic , transmembrane or inter mitochondrial membrane domains ) , interactions with various proteins could be disturbed , affecting only a part of SLC25A46’s functions . Furthermore , alteration of SLC25A46’s functions might also result in species-specific phenotype , as all human cases reported so far suffer from optic atrophy , which is not observed in the bovine [29] and mouse models reported here ( Table 5 ) . However , it should be mentioned that FVB/N mice carry two mutations which result in severe vision impairment: a mutation in the tyrosinase gene ( TyrC ) causing an albino phenotype and the retinal degeneration mutation ( Pde6brd/rd11 ) [65] . Consequently , FVB/N mice suffer from early onset retinal degeneration and blindness around weaning [66] which might interfere with the observation of the phenotype . Overall , our data in both models provided a basis for the wide range of human phenotypes described for SLC25A46 mutations . Furthermore , there was clear evidence that SLC25A46 should be added to the list of candidate genes causing premature neonatal death , with a potential link between early deaths and SLC25A46 mutations that result in the absence or in a drastic reduction of the amount of the protein ( see Table 5 ) . Finally , we produced the first Slc25a46 knock-out mouse model , which should be useful to further elucidate the function of SLC25A46 in mitochondrial dynamics .
All procedures involving animals conformed to the Guide for the Care and Use of Laboratory Animals ( NIH Publication No . 85-23 , revised 1996 ) . All efforts were made to minimize suffering . Blood samples were collected from cattle by veterinarians or by trained and licensed technicians during routine blood sampling for paternity testing , genomic selection or annual prophylaxis . Affected calves were euthanized for ethical reasons , due to the absence of effective treatment . All samples and data were obtained with permission of breeders or breed organizations . For mice , protocols were approved by the Animal Experimentation Ethics Committee and the French Ministry of Research ( APAFIS#1227–2015100516164803 v3 ) , and the Haut Conseil des Biotechnologies ( HCB n°6461 ) . Twelve affected calves were examined clinically and confirmed to have the disease [29] . Blood samples were collected from these calves and their parents , and DNA was extracted with a Genisol Maxi-Prep kit . Blood samples were also collected from control animals known to be unaffected based on our genotypes database . In total , 123 unaffected adult cattle , all of the Rouge-des-Prés breed , were selected ( including eight bulls used for artificial insemination and 115 cows from the La Greleraie INRA experimental facility ) . All of these cattle were genotyped by Labogena with the Bovine SNP50 Beadchip V1 ( Illumina ) . Mapping was carried out by homozygosity mapping with in-house HOMAP software , as described [28] . Whole genome sequencing was performed at the Get-PlaGe platform ( http://genomique . genotoul . fr/ ) on a HiSeq 2000 Illumina sequencer producing 100-bp long , paired end reads . Four animals had their entire genomic DNA sequence determined ( two affected , one carrier and one healthy ) . Reads were quality checked and mapped on the UMD3 . 1 reference genome using BWA aln software ( version 0 . 5 . 9-r16 ) . Alignments were filtered with a minimum MAPQ value of 30 . Reads that mapped to multiple localizations were removed . The target region was selected on each produced . bam file using Samtools ( Version 0 . 1 . 18 ) . Local indel realignment and base quality recalibration were applied using GATK toolkit . The SNPs were predicted with samtools mpileup and bcftools , and annotated with Ensembl Variant Effect Predictor tool and SNPs were filtered according to the animals’ phenotype-genotype correlation . A total of 93 living Rouge-des-Prés cattle were tested for SLC25A46 and MAN2A1 polymorphisms , including 27 with clinical symptoms of distal axonopathy ( with or without subsequent histopathological confirmation ) . In addition , 31 more historical Rouge-des-Prés animals were also tested , as well as 321 other cattle from 12 French breeds . For all of these , DNA was extracted from blood samples ( Genisol Maxi-Prep kit or QIAsymphony DNA Kit ( Qiagen ) ) . Sanger sequencing was performed using standard methods on the two potential polymorphisms identified after whole-genome sequencing , in SLC25A46 and MAN2A1 genes . Primers ( S2 Table ) were designed using Primer3 . The PCR products were amplified using 200 ng of DNA , with standard GoTaq PCR reagents ( Promega ) , on a Master Thermal Cycler ( Eppendorf ) . The SNP of SCL25A46 gene was genotyped using PCR-LAR ( Ligation Assay Reaction ) by Labogena . A pair of PCR primers ( Turn_F and Turn_R ) flanking the mutation was designed with Primer3 . vo4 software , based on the genomic sequence of the bovine gene SCL25A46 , according to the UMD3 . 1 assembly ( S3 Table ) . The PCR amplification was performed in a final volume of 10 μl using a Qiagen Multiplex PCR Kit , 10−50 ng of template DNA and 2 . 0 pmol of each primer . Reactions were run for 30 cycles in an MJ thermal cycler ( Model PTC-200 ) . The PCR amplification included an initial activation step at 95°C for 15 min , denaturation at 94°C for 30 s , primer annealing at 60°C for 90 s , extension at 72°C for 1 min , and final extension at 60°C for 30 min . The following tagged probes were designed for the ligation assay , Turn_LAR-M ending with the mutated nucleotide and Turn_LAR-S ending with the non-mutated nucleotide , and Turn_2p , a double-phosphorylated primer ( S3 Table ) . The PCR product ( 10 μl ) was used for allele discrimination using the Ligation Assay Reaction . The reaction contained 2 pmol of each probe , 1 . 5 U of Taq DNA Ligase and reaction buffer ( New ENGLAND BioLabs ) . Reactions were run in an MJ thermal cycler ( Model PTC-200 ) . The ligation reaction included an initial activation step at 95°C for 2 min and the following thermocycling profile was repeated 35 times: denaturation at 94°C for 30 s and probe annealing at 60°C for 3 min . Finally , the reacting solution was held at 99°C for 10 min to deactivate Taq DNA Ligase . Following the ligation reaction , an Applied Biosystems 3730xl DNA analyser with GeneMapper Analysis software ( Applied Biosystems ) was used to analyze fluorescently tagged fragments . Exon3 of mouse Slc25a46 gene was targeted at the site of the original mutation associated with phenotype ( chromosome:GRCm38:18:31604753:31606764:1 ( reverse complement ) ) . The target sequence was chosen with the ZiFiT Targeter program ( http://zifit . partners . org ) . A potential TALEN target sequence identified by the program was selected empirically with a preference for an 18-16-18 combination ( 16 bases for the spacer ) . The chosen sequences were TGTGCTGGCCCATCCTTG for the left TALEN and CAGTGTCAGGTAAATATA for the right . No homology with the targeted sequence was identified ( Blast NCBI ) at any other location in the genome that could represent a potential off-target site The TALEN kit used for TALE assembly was a gift from the Keith Joung laboratory ( Addgene kit # 1000000017 ) . The TALEN were constructed according the REAL ( Restriction Enzyme And Ligation ) assembly method , as described [67] . The left TALEN was constructed by assembling units of the kit in the following order: 9 , 15 , 19 , 22 , 30 , 14 , 19 , 22 , 27 , 12 , 16 , 25 , 27 , 12 , 20 , and 25 ( by groups of four units ) . The entire insert was subcloned into the final JDS74 plasmid opened at the bsmb1 sites . Similarly , the right TALEN was constructed by assembling of units of the kit in the following order: 6 , 15 , 16 , 25 , 30 , 15 , 16 , 22 , 27 , 15 , 19 , 21 , 27 , 11 , 17 , and 25 . The entire insert was then subcloned into the final JDS74 plasmid . All inserts of final plasmids were entirely sequenced with primers 2978 ( TTGAGGCGCTGCTGACTG ) and 2980 ( TTAATTCAATATATTCATGAGGCAC ) . To prepare RNA from each plasmid for microinjection , 5 μg of TALEN plasmid was linearized with 20 U of Age1 enzyme ( New England Biolabs , ) for 8 h at 37°C in 100 μl . The linearized fragment was purified by migration on an agarose gel and a Qiagen Gel extraction column kit ( Qiagen ) . Messenger RNA was produced on 1 μg of purified linearized plasmid with the ARCA T7 capRNA pol kit ( Cellscript , TEBUbio France ) and polyadenylated with the polyA polymerase tailing kit ( Epicentre ) according to the manufacturer's instructions . Messenger RNA was purified with a Qiagen RNEasy minikit ( Qiagen France ) , re-suspended in distilled water , and RNA concentration was estimated with a nanodrop photometer ( Thermoscientific ) . The concentrated RNA was then diluted ( 100 ng/μl ) in injection buffer ( Millipore , France ) and stored at -80°C until used . The day of injection , 5 ng/μl of each TALEN RNA were mixed ( final concentration , 10 ng/μl ) in injection buffer and microinjected into pronuclei of murine FVB/N embryos , which were transferred into pseudo-pregnant mice . Resulting offspring were genotyped by DNA analysis of tail biopsies . Transgenic mice were crossed with FVB/N mice to derive F1 offspring that were used to produce the mentioned transgenic FVB/N Tg18 and Tg26 lines . Transgenic mice were genotyped using a couple of primers ( S2 Table ) surrounding the TALEN restriction site . Since the AT content of the amplified fragment was high ( 71% ) , the PCR used KAPA2G Robust Taq ( Kapa Biosystems ) , with KAPA2G buffer A and KAPA Enhancer , in accordance with manufacturer’s recommendations . The PCR products were amplified on a Master Thermal Cycler ( Eppendorf ) including an initial activation step at 95°C for 3 min , 40 cycles of denaturation at 95°C for 15 s , primer annealing at 60°C for 15 s , extension at 72°C for 15 s and final extension at 72°C for 3 min , followed by electrophoresis on a 3% agarose gel . In accordance with their general condition , between 2 and 4 weeks of age , WT and Tg-/- mice were euthanized by cervical dislocation or anesthetic overdose ( ketamine-xylazine ) according to protocols approved by the Animal Experimentation Ethics Committee . Blood was collected ( heparinized tubes ) from the posterior vena cava [68] , centrifuged ( 10 min at 3500 rpm and 4°C ) , and plasma was removed and frozen ( -20°C ) pending analyses . Various tissues were dissected , and either frozen at -80°C for RNA/protein extraction , or rinsed in PBS and fixed overnight in 4% PFA/PBS , then processed in a TP1020-1-1 tissue processor ( Leica ) and embedded in paraffin ( EG 1160 Embedding Center; Leica ) . Affected calves were euthanized for ethical reasons by intravenous administration of euthanasia solution ( T-61 , embutramide 200 mg/mL , mebezonium iodure 50 mg/mL , tetracaine chlorhydrate 5 mg/mL , 1 dose of 0 . 1 mL/kg , Intervet , Angers , France ) . Tissue were dissected and frozen at -80°C for subsequent protein extraction . Plasma biochemical analyses were done at the Institut Clinique de la Souris ( ICS , Strasbourg ) , and at the Laboratoire de Biochimie ( Hôpital Bicêtre , Paris ) . Following parameters were measured: glucose , sodium , potassium , chloride , calcium , phosphorus , magnesium , urea , iron , ferritin , total proteins , albumin , total bilirubin , bile acids , total cholesterol , triglycerides , creatinine , beta hydroxybutyrate , lactate; as well as creatine kinase , aspartate aminotransferase and alanine aminotransferase . Fixed and embedded tissues from WT and Tg-/- ( n≥3 ) were sectioned ( 5 μm ) and stained ( Hemalun-Eosin-Saffron ) in a VV24/4 VARISTAIN automatic slide stainer ( Thermo Electron ) according to a standard protocol . After staining , slides were scanned on a 3DHISTECH scanner ( Sysmex ) . Total RNA was extracted from various tissues using Qiazol reagent ( Invitrogen ) and the RNeasy mini kit ( Qiagen ) with DNase I treatment . Then , 500 ng RNAs were reverse-transcribed using a RT-vilo kit ( Invitrogen ) , according to the manufacturer’s instructions . To sequence transcripts , cDNA were amplified by PCR with PCR primers for Slc25a46 and Rpl13 genes ( S4 Table ) . Following PCR reactions , products were electrophoresed on a 2% agarose gel and amplified cDNA fragments of Slc25a46 were sequenced . Frozen tissues were ground with an Ultra-Turrax either in Mitochondria Isolation kit for Tissue ( ThermoFisher ) for mitochondria-enriched protein extracts , or in 10 mM Tris solution ( pH 7 . 2 , 2 mM MgCl2 , 0 . 5% NP40 , 1 mM DTT , with Halt Protease Inhibitor Cocktail EDTA free; Roche Diagnostics ) for total protein extracts . Protein contents were assayed with the 2-D Quant kit ( GE Healthcare ) and 100 μg of proteins were separated on home cast 12 . 5% SDS-PAGE at 80 V for 20 min and 150 V for 50 min , with 10 μl of MW Marker ( Nippon Genetics ) added to the gel before electrophoresis . After separation , proteins were transferred on nitrocellulose membrane with a Trans-blot Turbo apparatus ( BioRad ) for 7 min at 2 . 5 A and 25 V . The membrane was rinsed twice , 5 min each , in MilliQ water and proteins were stained in 5X Rouge Ponceau solution for 5 min . Proteins were destained in TBS solution for 20 min and the membrane was blocked with 5% dry milk TBS-0 . 1% Tween20 solution for 1 h at room temperature . The membrane was incubated with polyclonal anti-SLC25A46 Novus antibody at a 1/1000 ratio in TBS-0 . 1% Tween20 solution for 1 h . The membrane was washed for 5 min and then twice for 15 min in fresh TBS-0 . 1% Tween20 solution . Thereafter , the membrane was incubated with goat anti-rabbit horseradish peroxydase-conjugated antibody ( Santa Cruz ) diluted at 1/10 000 in TBS-0 . 1% Tween20 for 1 h , and then washed as previously described . Bands were visualized by enhanced chemiluminescence ( ECL Prime , GE Healthcare ) and detected on ChemiDoc Touch ( BioRad ) in automatic mode . The membrane was washed 5 min in TBS solution , 2 x 10 min in TBS-0 . 1% Tween20 and then was incubated with MTCO2 polyclonal antibody ( ProteinTech ) against cytochrome c oxidase II protein ( COX2 ) at a 1/1000 ratio in TBS-0 . 1% Tween20 solution for 1 h , and then processed as described above . Additional western blots were performed with rabbit polyclonal anti-Mfn2 ( Santa Cruz ) antibody at a 1/200 ratio , mouse monoclonal anti-MIC60 ( Abcam ) antibody at a 1/500 ratio and anti-OPA1 ( Santa Cruz ) antibody at a 1/200 ratio . For incubation of mouse samples with mouse antibodies , a preliminary saturation of mouse IgG was performed with AffiniPure Fab Fragment Donkey anti-mouse IgG ( Jackson ImmunoResearch ) at a 30 μg/mL ratio in TBS/Tween20 0 . 1% solution . Successive steps were as described above with secondary goat respective anti-rabbit or anti-mouse horseradish peroxydase-conjugated antibody ( Santa Cruz ) diluted at 1/10 000 in TBS-0 . 1% Tween20 for 1 h . Mitochondria-enriched protein extracts were prepared as described in the above paragraph . Each lane of gel was cut into 20 gel pieces and analyzed separately , except the last two which were paired . After protein in-gel reduction ( 10 mM dithiothreitol ) , alkylation ( 50 mM iodoacetamide ) and trypsin digestion ( overnight incubation at 37°C with 100 ng of trypsin in 25 mM ammonium bicarbonate ) , the resulting peptides were extracted with 40% ACN/0 . 1% TFA ( v/v ) . Tryptic peptides were dried and re-suspended with 40 μL of 2% ACN/0 . 08% TFA ( v/v ) . Peptide analysis was performed on a nanoLC system ( Ultimate 3000 , Thermo Scientific ) coupled to an LTQ-Orbitrap Discovery mass spectrometer ( Thermo Scientific ) with a nanoelectrospray interface . The sample was loaded into a trap column ( PepMap100 , C18 , 300 μm i . d . × 5 mm , 5 μm , Thermo Scientific ) at a flow rate of 20 μl . min−1 for 3 min with 2% ACN/0 . 08% TFA ( v/v ) . Peptides were then separated on a reverse phase nanocolumn ( PepMap100 , C18 , 75 μm i . d . × 150 mm , 2 μm , Thermo Scientific ) with a two-step gradient from 1 to 25% B for 42 min and from 25 to 35% B for 5 min at 300 nl . min−1 at 40°C ( buffer A: 2% ACN/0 . 1% FA ( v/v ) , buffer B: 80% ACN/0 , 1% FA ( v/v ) ) . Ionization was performed in positive mode ( 1 . 4 kV ionization potential ) with a liquid junction and a sillica tip emitter ( 10 μm id , NewObjective ) . Peptide ions were analyzed using Xcalibur 2 . 0 . 7 with a data-dependent method including two steps: ( i ) full MS scan ( m/z 300–1 , 400 ) and ( ii ) MS/MS ( normalized collision energy fixed to 35% , dynamic exclusion time set to 45 s ) . The MS and MS/MS raw data were submitted for protein identification and quantification by spectral counting using the X ! TandemPipeline 3 . 3 . 4 ( version 2015 . 06 . 03 , http://pappso . inra . fr/bioinfo/xtandempipeline/ ) with X ! Tandem search engine ( version Piledriver , 2015 . 04 . 01 , http://www . thegpm . org/TANDEM ) and Uniprot SwissProt mus musculus database ( version 2015 . 10 . 14; 25248 entries ) . Search criteria used were trypsin digestion , carbamidomethyl ( C ) set as fixed modification and oxidation ( M ) set as variable modification , one missed cleavage allowed , mass accuracy of 10 ppm on the parent ion and 0 . 5 Da on the fragment ion . The final search results was filtered using multiple threshold filter: -4 . 0 protein log ( E-value ) identified with at least two different peptides with E-value < 0 . 01 . Differential analyses were performed using the Bioconductor Limma R package , with a voom transformation [69 , 70] and a Benjamini-Hochberg correction for multiple testing . Proteins with the lowest counts were removed using a threshold of 10 spectra for the sum over all replicates . Samples of central and peripheral nervous systems were fixed for 3 h in 2 . 5% glutaraldehyde in Sœrensen buffer and osmificated for 1 h in 1% OsO 4 , as described [71] . Afterwards , they were rinsed in Sœrensen buffer , dehydrated in graded acetone , and embedded in Epon . Semi-thin sections ( 1 μm ) were stained with toluidine blue . Ultra-thin sections were stained with uranyl acetate and lead citrate and viewed using a JEOL electron microscope . Liver was fixed with 2% glutaraldehyde in 0 . 1 M Na cacodylate buffer ( pH 7 . 2 ) , for 4 h at room temperature . Samples were then contrasted with 0 . 5% Oolong Tea Extract ( OTE ) in cacodylate buffer , postfixed with 1% osmium tetroxide containing 1 . 5% potassium cyanoferrate , gradually dehydrated in ethanol ( 30 to 100% ) and substituted gradually with a mixture of propylene oxyde-epon and embedded in Epon ( Delta Microscopie–Labège France ) . Thin sections ( 70 nm ) were collected onto 200 mesh cooper grids , and counterstained with lead citrate . Grids were examined with an Hitachi HT7700 electron microscope operated at 80kV ( Elexience–France ) , and images were acquired with a charge-coupled device camera ( AMT ) . Samples of brain , liver and muscle were transferred to ice-cold isolation buffer ( 20 mM Tris , 0 . 25 M sucrose , 40 mM KCl , 2 mM EGTA , and 1 mg/mL BSA; pH 7 . 2 ) and homogenized on ice by five strokes with a glass-Teflon potter homogenizer . Citrate synthase ( CS ) , complex I ( NADH-ubiquinone oxidoreductase ) ( CI ) , complex II ( succinate-ubiquinone oxidoreductase ) ( CII ) , complex III ( ubiquinone-cytochrome c oxidoreductase ) ( CIII ) , complex IV ( cytochrome c oxidase ) ( CIV ) , aconitase ( ACO ) , isocitrate dehydrogenase ( IDH ) , α-ketoglutarate dehydrogenase ( AKGDH ) and fumarate hydratase ( FH ) activities were spectrophotometrically measured at 37°C as described [72 , 73] . All enzymatic activities were expressed as nanomoles per minute and per milligram of protein . Total DNA was extracted from brain , liver and muscle homogenates using a standard procedure [74] . The mtDNA copy number per cell was measured by quantitative PCR based on the ratio of mtDNA ( MTCO2 gene ) to nDNA ( PPIB gene ) , as described [74] . Long-range PCR was performed to detect large mtDNA deletions with primers F1 ACGGGACTCAGCAGTGATAAAT;R1 GCTCCTTCTTCTTGATGTCTT ( expected size , 15144 bp ) .
|
Mitochondria are essential organelles , the site of numerous biochemical reactions , with a critical role in delivering energy to cells , particularly in the nervous system . Consequently , disrupted mitochondrial function often results in neurodegenerative diseases , in humans and in other mammals . Herein , we determined that the “Turning calves syndrome” , a new hereditary sensorimotor polyneuropathy in the French Rouge-des-Prés cattle breed was due to a single substitution in SLC25A46 , a gene encoding a protein of the mitochondrial carrier family . We created a mouse knock-out model and determined that disruption of this gene dramatically disturbed mitochondrial dynamics in various organs that resulted in altered metabolism and early death , indirectly confirming the gene identification in cattle . Moreover , our novel findings extended the range of phenotypes associated with polymorphisms of this gene and help to elucidate the role of SLC25A46 in mitochondrial function .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
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] |
2017
|
Bovine and murine models highlight novel roles for SLC25A46 in mitochondrial dynamics and metabolism, with implications for human and animal health
|
Circuitry mapping of metazoan neural systems is difficult because canonical neural regions ( regions containing one or more copies of all components ) are large , regional borders are uncertain , neuronal diversity is high , and potential network topologies so numerous that only anatomical ground truth can resolve them . Complete mapping of a specific network requires synaptic resolution , canonical region coverage , and robust neuronal classification . Though transmission electron microscopy ( TEM ) remains the optimal tool for network mapping , the process of building large serial section TEM ( ssTEM ) image volumes is rendered difficult by the need to precisely mosaic distorted image tiles and register distorted mosaics . Moreover , most molecular neuronal class markers are poorly compatible with optimal TEM imaging . Our objective was to build a complete framework for ultrastructural circuitry mapping . This framework combines strong TEM-compliant small molecule profiling with automated image tile mosaicking , automated slice-to-slice image registration , and gigabyte-scale image browsing for volume annotation . Specifically we show how ultrathin molecular profiling datasets and their resultant classification maps can be embedded into ssTEM datasets and how scripted acquisition tools ( SerialEM ) , mosaicking and registration ( ir-tools ) , and large slice viewers ( MosaicBuilder , Viking ) can be used to manage terabyte-scale volumes . These methods enable large-scale connectivity analyses of new and legacy data . In well-posed tasks ( e . g . , complete network mapping in retina ) , terabyte-scale image volumes that previously would require decades of assembly can now be completed in months . Perhaps more importantly , the fusion of molecular profiling , image acquisition by SerialEM , ir-tools volume assembly , and data viewers/annotators also allow ssTEM to be used as a prospective tool for discovery in nonneural systems and a practical screening methodology for neurogenetics . Finally , this framework provides a mechanism for parallelization of ssTEM imaging , volume assembly , and data analysis across an international user base , enhancing the productivity of a large cohort of electron microscopists .
Is ssTEM really necessary ? Why can't we deduce networks from physiology , confocal imaging , or behavior ? The answer is that potential network motifs derived by these methods are not unique . Diversity in potential network topologies is so high [17 , 26] that only anatomical ground truth can produce a valid connectome [17] . For example , mammalian retinas are simpler than those of most other vertebrates [27] , but even so , no fewer than 70 unique cell classes exist [28] . And though the flow of signals from cone photoreceptors to ganglion cells ( GCs ) involves stereotyped networks that seem simple [29] , a vast number of synaptic motifs can be produced from even a limited neuron set [17] . A small network of two different bipolar cells ( BCs ) driving two GC channels , interconnected by one amacrine cell ( AC ) class can be connected in 90 formal motifs and at least 40 of these are biologically tenable ( Figures 1 , S1 , and S2 ) . This is further compounded by unknown synaptic weights , molecular diversity of receptors and channels , gap junction display , and electrotonic constraints . With electrotonic constraints , the geometric locus of a synaptic contact matters [30–32] and the number of structural motifs possible in the simple five-element example extends to at least 640 ( Figure S1 ) . In stark contrast , we know that the outflow of signals from the mammalian retina is represented by only 15–20 GC classes , each representing a discrete filter channel [5 , 33 , 34] . An anatomical approach that unambiguously determines motifs is required . This is justified by the fact that the efficacy of anatomy discovering complex motifs is unrivaled . Mammalian night ( scotopic ) vision is a prime example . The main scotopic signal flow network is rod → rod BC → rod AC , which then bifurcates into two synaptic arms that reenter the ON- and OFF-cone BC pathways . This motif was reported in 1974 by Helga Kolb and E . V . Famiglietti Jr . using ssTEM [12] . Subsequent physiological and genetic analyses [35 , 36] provided correlative support for the anatomical model , but neither study would have uniquely yielded the correct topology . Moreover , both transmission electron microscopy ( TEM ) [12 , 37–40] and light microscopy ( LM ) imaging studies [41 , 42] reveal that this network is even more complex . There are , in fact , no physiological data that either explain or predict these network submotifs . And despite five decades of robust physiology of retinal rod signaling , the discovery of a second scotopic pathway was also based on ssTEM [43 , 44] . Finally , corruption of scotopic motifs in retinal disease was discovered by TEM [45] , again despite decades of electroretinographic analysis . It is unlikely that the day of ultrastructural discovery is past and we argue that it is just dawning . Manually acquiring even small maps by ssTEM requires Herculean effort and high technical skill [21] . The gold-standard for such mapping has long been the Caenorhabditis elegans ( C . elegans ) ssTEM reconstruction project [46–50] where over 300 neurons , over 6 , 000 synapses , and nearly 900 gap junctions were traced through several instances of 1 , 000–2 , 000 section series , initially aligned and manually marked-up using the cinematographic method of Levinthal and Ware [51] developed in the early 1970s . While the actual build and analysis times are not available , we will show that a typical vertebrate brain canonical volume ( see below ) involves one to three orders of magnitude more connections and vastly more complex topology , since most of the C . elegans sections involve tracing linear tracts . The brute force manual method is simply impractical for building CN maps of more complex neural systems . Three essential factors in building CN maps are ( 1 ) proper resolution , ( 2 ) statistical coverage , and ( 3 ) complete classification . Resolution must be sufficient to unambiguously identify synaptic contacts and gap junctions [21] but not so high as to be unmanageable: nominally 2 nm/pixel . This yields synaptic vesicles spanned by 8–10 pixels that are robust for circuitry tracing . Coverage scales with neuronal diversity and density: a canonical region must be sampled . We define two coverage units ( Figure 2 ) . A canonical tile is bounded by the Voronoi domain ( see Reese [11] ) of the rarest neuronal element in a cellular array . In retina , this might be the dopaminergic polyaxonal cell [52] or OFF α GCs [5] . A slightly larger element is the canonical field , bounded by three somas ( in planar systems such as retina ) or four somas ( in brain volumes ) of the sparsest neuronal class . This ensures inclusion of multiple somas of all element classes in the region . However , not all canonical fields are known a priori and , arguably , molecular and anatomic data are key prerequisites to defining such domains . As we will show , a canonical field of retina can be acquired and assembled in less than 5 mo . Cortex is more challenging . Using normal primate ocular dominance column dimensions ( >0 . 5 mm ) and assuming a canonical repeat of 0 . 25 mm , the acquisition of V1 visual cortex would take 12 y . Reducing resolution to 10 nm/pixel ( similar to bloc-face imaging ) reduces acquisition to less than 1 y and new high-throughput TEM configurations ( e . g . , the Harvard Connectome Project ) are allowing much larger capture fields , with as much as a 10× improvement in speed . Thus even canonical high-resolution cortical volumes are possible with ssTEM . Classification ( i . e . , neuronal phenotyping ) must be sufficiently robust to identify most major elements in a canonical field and may be the most effective way of identifying a field in the first instance [5] . It is not practical to decipher networks from large reconstructions when the number of classes of neurons is unknown . In general , panels of markers compatible with mapping networks are applied to or expressed in regions of interest [2 , 53] . In conjunction with serial section light microscopy ( ssLM ) , we use computational molecular phenotyping ( CMP , see Marc , Murry , and Basinger [54] and Marc and Jones [5] ) . CMP is a high-resolution optical imaging strategy that exploits sets of immunoglobulins ( IgGs ) targeting small molecules , precise multichannel image registration , and cluster analysis to extract defined neuronal classes in any tissue [5 , 27 , 54 , 55] . Small molecule optical CMP is compatible with ssTEM and enables classification of neuronal elements via direct multimodal image registration [17 , 56] . A tutorial on CMP is available in Protocol S1 . In summary , building a CN map of any neural region such as retina requires canonical field imaging , neuronal phenotyping , image mosaicking , image registration , and image annotation . In this paper we detail complementary applications that can be used with a variety of datasets to produce large , high-resolution , aligned mosaics .
Many TEM facilities lack automated montaging , but this does not mean that high quality imagery cannot be obtained . Standard TEM imaging with sufficient image overlap can be obtained manually and images scanned at high resolution and bit depth . We use magnifications ranging from 5 , 000× to 10 , 000× and a typical manual ssTEM project size would be 100 image tiles per section . Similarly , corresponding bounding or intercalated ssLM sections can be imaged manually and require only a few tiles even at high resolution . However , as the positions of each ssLM and ssTEM image tile in the original sections are often lost , software tools to provide precise mosaic alignments are necessary . Larger ssTEM datasets can be captured with automated imaging , exceeding 1 , 000 tiles . Such montaging requires robust control of stage position , camera behavior , metadata collection , and efficient use of resources . All of these are available through use of SerialEM software developed at the University of Colorado . SerialEM allows the use irregular capture patterns . No further user attention is required once all sections on a grid have been queued , which allows one to utilize the TEM during commonly idle night and weekend periods . In all regards we have found automated capture very resource efficient compared to manual approaches . Our current configuration captures 3 , 000 tiles in a day . The expanded capacity of ssTEM imaging requires a corresponding automation of ssLM tile collection . There are a number of commercial microscope tiling stages and our initial experience showed that the highest precision stages were essential to building mosaics of sufficient quality for CMP . However , the development of software tools for building mosaics informed by but not dependent upon stage metadata makes the X-Y precision of the stage less critical as long as overlap is adequate . There are several challenges in ssTEM or ssLM image mosaicking with manual tile acquisition . First , every section exhibits an unpredictable rotation when placed in the TEM or on a slide and the number of tiles in each scan-line will differ . Thus it is typically not known which tiles are neighbors in a section . We developed the ir-fft algorithm to deduce the tile ordering automatically . The next challenge is the correction of nonlinear warps introduced into each tile from variations in electron imaging quality ( Figure 4; also see Methods and Materials ) . Our solution finds pairs of overlapping tiles , computes their relative displacement , deduces a tile ordering , builds a layout of the mosaic without nonlinear warping , and refines the mosaic by applying nonlinear warps to each tile . Ultimately , it is more efficient to build ssLM and ssTEM mosaics when coordinate information is available in the image metadata and the tool ir-translate exploits this . Only overlapping tiles are matched using the Fourier shift method ( ir-fft ) . This reduces the complexity of the method from a quadratic to a linear function of the number of tiles . Next , we define a tension vector proportional to the offset between the approximate position , and the preferred position as found by matching . These tensions are relaxed by iteratively moving the tiles . Regardless of tile placement , most mosaics require some nonlinear warp refinement and this is accomplished with ir-refine-grid , an approach that places a course triangular mesh over each tile . Vertices are repositioned by registering their immediate neighborhood to overlapping tiles with the same matching algorithm utilized by ir-fft . Details of algorithm development are in Protocol S1 . Each tile is sampled onto a coarse uniform triangle mesh , and small neighborhoods are sampled from all of the tile neighbors in the mosaic and the best matches determined as in ir-fft . A simple example of the ability of ir-refine-grid to manage subtle distortions is shown in Figure 5 , where the TEM image tiles previously shown intractable under translation are readily aligned without user intervention . These are low resolution tiles: a worst-case scenario . Even when thousands of tiles are assembled , the alignment remains excellent . Figure 6 displays a randomly selected tile from a 275+ mosaic series of >1 , 000 tiles each , aligned with ir-translate . At the screen resolution used for synaptic markup , the tile edges are rarely visible . The error in alignment in this set of four overlapping tiles is extremely small , ranging from no detectable misalignment across three tiles to 7 . 8-nm shift in one tile: roughly one-third of a vesicle . Such errors are random rather than systematic through the volume , and do not accumulate . Together , ir-tools assemble superb mosaics . As an example , our Syncroscan system builds mosaics from arrays of LM tiles but invariably shows subtle misalignments or blurring at boundaries ( Figure 7A ) . Conversely , ir-tools perform beautifully on exactly the same image tiles , generating seamless mosaics ( Figure 7B ) . In truth , the Syncroscan errors are so small ( ≈200–2 , 000 nm ) that they are generally invisible when the full image is viewed , but a Laplacian transform ( Figure 7C ) shows that there are many of them . When multiple channels are registered for CMP , these errors are additive , resulting in corruption of classification and ssLM-ssTEM registration . The LM images mosaicked by ir-tools are essentially perfect . Both user-guided and automated image registration tools are needed for ssLM and ssTEM . User-guided applications are essential because some images ( e . g . , certain CMP imagery ) lack sufficient information to drive automation . Ir-tweak is an interactive , multithreaded , cross-platform application for manual slice-to-slice registration . As control points are placed by the user in one image , their locations in the other image are estimated by the current thin-plate spline transform parameters . When the user corrects the locations of estimated points in the second image , the transform parameters are updated . Figure 8 shows the ir-tweak interface where the operator places points in the fixed image , adjusts their locations on the moving target image , and observes the registration dynamically . While automated multimodal slice-to-slice registration remains an open challenge ( see http://prometheus . med . utah . edu/∼marclab/gallery_CS . html for publicly available test sets ) , such boundary or intercalated registrations are manageable with user-guided tools such as ir-tweak . Conversely , automated ssTEM slice-to-slice ( stos ) image registration is essential to building volumes , even when image metadata are unavailable . As any section may be distorted by stretching or electron-optical defects , stos registration is similar to ir-refine-grid , with two differences . Since the orientation of slice pairs is arbitrary , we cannot use image correlation to estimate image-to-image translation parameters . Instead , we first perform a brute force search ( ir-stos-brute ) for tile translation/rotation parameters by downscaling the section mosaics to 128 × 128 pixel thumbnails and preprocessing ( ir-blob ) to enhance large blob-like features , preventing feature washout when downscaling . These parameters are then used to initialize the mesh transform at a fine resolution ( ir-stos-grid ) and applied to a “moving” slice relative to a chosen fixed slice . Figure 9 is from a down-sampled QuickTime movie ( see Video S1 ) of a mouse retinal microneuroma ssTEM dataset acquired manually on film and automatically built into a volume of 45 auto-registered mosaics . This is a representative legacy dataset and is by far the most challenging type of data for automatic mosaicking and volume assembly due to lack of metadata and the presence of many section defects ( stain artifacts , folds , dirt , beam burns ) . Even so , the alignment is excellent and suggests that many legacy ssTEM datasets can be exploited . The availability of a large-format digital camera for TEM ( e . g . , the Gatan Ultrascan 4000 ) coupled with the most recent builds of SerialEM now make it possible to acquire large image fields at synaptic resolution from any specimen and begin assembling volumes automatically , such as the retinal circuitry volume for the rod BC layer in the mouse retina ( Figure 10; Video S2 ) . In this example , each slice was automatically mosaicked from 16 tiles ( 5 , 000× ) with ir-translate and ir-refine-grid and a volume of 20 slices automatically registered with ir-stos ( Figure 10A and 10B ) . Manually registering these datasets is impossible because of the many required distortion corrections among tiles and slices . With the ir-tools a year's manual work can be done in a day . Upon browsing the volume , characteristic connection motifs can be quickly extracted ( Figure 10C and 10D ) and graphically summarized ( Figure 10E ) from a text list of relations . Again , the goal is not to render 3D shapes , but rather browse and markup synaptic motifs . This volume readily detects characteristic reciprocal feedback , GABAergic local feedforward , and glycinergic long-range feedforward synaptic arrangements in the locale of the BC ( see Video S3 ) . Importantly , all regions are registered , not just the ones of local interest . We have similarly built volumes from 1 , 000-tile datasets of mouse retinal microneuromas ( see below ) and over 275 serial 1 , 000-tile mosaics from a 369-section series through the rabbit inner plexiform layer ( Figure 11 ) , with excellent automated alignment and without accumulating distortions . After automated registration through a volume of >100 sections ( 2 Tb ) , no error emerges from transforming all sections into the same volume space . While subtle slice-to-slice distortions exist due to physical deformation of sections , they do not accumulate and section-to-volume distortions are statistically indistinguishable from any those of any slice pair . Should such unlikely distortions emerge , our fast transform management method ( see “Visualization and Annotation” below ) allows the volume to be partitioned at any point and structures tracked across the parts . We can define break points and reference slices anywhere in the volume and rapidly create new series of transforms . This method is ideal for automated registration . CMP is a thin-section optical method that provides molecular signals for classification of cells and large processes . Ultrathin sections are immunoprobed for different small molecules , imaged optically , registered by ir-tools , and visualized as multichannel molecular signatures of different cell types . A tutorial on CMP is provided in Protocol S1 . All cells have small molecule signatures and these are most evident in the central nervous system [57 , 58] and retina [5 , 27 , 54 , 59] . A library of four to eight small molecules can segment retinal populations into 20 or more natural molecular cell classes [5 , 55] . CMP can also segment many cell processes into different functional classes with high fidelity [17 , 56] . Figure 12 displays a retinal microneuroma ssTEM ( Fig 12A ) , its bounding CMP ssLM images as multispectral overlays ( Figure 12B and 12C ) , and its corresponding theme map after K-means classification with CMPView ( Figure 12D ) . The four 90-nm sections preceding the ssTEM set were processed for CMP using IgGs targeting glutamate ( IgG E ) , glycine ( IgG G ) , taurine ( IgG τ ) , and GABA ( IgG γ ) and aligned with the initial ssTEM image with ir-tweak . After classification with these four signatures alone , we show that there are four superclasses of ACs ( γ1 , γ2 , G1 , G2 ) , two BC superclasses ( Eτ , EτG ) , two GC superclasses ( E , Eγ ) , the glial Müller cell class ( τQ ) , and the retinal pigmented epithelium class , similar to results in normal mouse , primate , and rabbit retinas . One critical feature of such theme maps is completeness: every cell in the TEM mosaic is classified into a known biological group and every process traced from it is similarly tagged . No other method has yet achieved this scale of functional coverage . On a larger scale , a 0 . 75-mm wide sample of the mouse inner plexiform layer was mosaicked and augmented with CMP at sufficient resolution to identify many synapses directly ( Figure 13 ) . An example of the value of CMP signatures in defining circuits is shown in Figure 13B , where an ON cone BC [59 , 60] is presynaptic to a class γ1 AC process , which also makes a reciprocal synapse back onto the BC . This is an archetypal feedback motif ( see Figure 10 ) , one of the most common in retina [17] . In addition a G1 glycinergic AC process is presynaptic to the BC . This illustrates the powerful segmentation possible with ssLM CMP , even at the ultrastructural scale , enabled by ir-tweak . But why isn't simply sampling random examples sufficient ? As shown by Marc and Liu [17] , one of the most common motifs in retinal signaling is the nested feedback synapse , yet its full topology is rarely observed without ssTEM reconstruction . Individual TEM mosaics can be many gigabytes in size , while final ssTEM volumes can be multiple terabytes . Exploring such large datasets requires new viewing tools . A single section can easily exceed the 32-bit limit ( 64 K × 64 K pixels ) of most contemporary image file formats . Even if we exported full resolution mosaics to an image file for use with conventional imaging tools , each 8-bit grayscale 1 , 000-tile mosaic would require 16 GB of memory . This size is not yet common on desktop computers . To enable real-time viewing of the completed mosaics we used the established technique ( e . g . , Google Earth ) of constructing an image pyramid for each tile and transforming them with the graphical processing unit . Only tiles visible on the screen are loaded and displayed at the needed resolution ( Figure 14; Video S3 ) . This technique makes the viewer memory footprint essentially volume-independent , providing several advantages . ( 1 ) Tile versions enhanced for contrast ( ir-clahe ) , features ( ir-blob ) , or any other processing can be substituted in real time by pointing the viewer at a different pyramid and using the same transforms . ( 2 ) Different transformations can be substituted to view results at each pipeline stage . ( 3 ) Reduced memory and bandwidth requirements of the pyramid-GPU approach make it possible for viewers to work over an HTTP connection . This is an important feature for collaborative annotation since the terabyte scale of the completed volume makes it difficult to relocate . ( 4 ) The transformations between volume and sections are known . Annotation loci can be moved from volume space back to section space for persistent storage , allowing one to update transforms or even reorder sections in the volume without losing the locations of established annotations . MosaicBuilder is our completed Mac OS X viewer for viewing single sections and was our first visualization/annotation tool . MosaicBuilder imports the images files and transformation definitions generated by the ir-tools and then creates a single project file containing the image pyramid for the section and any annotations . A single logical file allows the final mosaic to be easily moved and shared among colleagues . Viking is our web based volume viewer that allows the viewing of volumes over a reasonably fast internet connection . It uses the same image pyramid display strategy as Mosaic Builder , but instead of importing files into a single package , Viking reads an XML file containing HTTP links to all transforms and image files . Viking uses the slice-to-slice transforms ( ir-stos-grid ) to register all slices to a single reference section . The user can display any section in register with the volume and can easily page to adjacent sections to track structures . Viking also supports switching to view any grid transformation generated by the pipeline or alternate image pyramids generated by running image filters over the tiles . As tools for the framework were developed , we were faced with the option to blend the tools into a single integrated application with a rich user interface or preserve each algorithm as a separate executable in a library of tools . We chose the latter as it is more flexible for code refinement and enhancement . However , by scripting each stage of the pipeline as a separate function in a Python package , we can invoke them with additional short scripts , automating pipeline execution . This process allows building the entire volume starting from raw microscope output using a single command . Data can be driven from any source into any stage of the volume building process via addition of a new function . The current scripting approach for building volumes does have a higher barrier to entry for new users compared to a single application . Though Python is not nearly as technical as the C++ environment used to create the ir-tools , changing the pipeline ( e . g . , adding support for a new microscope platform ) does require some programming skill . The ir-tools have eliminated the most difficult technical challenges to volume construction , but the current state of the technology still mandates support from skilled programming personnel for the computational side of the reconstruction effort to be successful . Though sectioning and staining a 400+ section dataset is in itself a tour de force , it is well within the abilities of many ultrastructural laboratories and can be done in a few work days . And while even manual EM capture can take much longer than sectioning , multiplexing the task across several TEMs and operators also makes the task of acquiring ssTEM data practical . The image processing step has always been the real “show-stopper” when large scale ssTEM projects were conceived . Table 3 summarizes the canonical field , capture , and image processing parameters and timelines for a concrete project: a CN map of the rabbit retinal inner plexiform layer . This project specifies a resolution of 2 . 18 nm/pixel , which is sufficient to identify conventional/ribbon synapses and moderate scale gap junctions . In broad terms , an optimal canonical volume can be captured in about 3–5 mo with a complete volume build on a single machine .
The importance of molecular classification of neural data cannot be overstated . Without even partial classification , ssTEM reconstructions remain of limited value . This observation remains true even with the ability to nominally identify individual cells by stochastic , multivariate protein expression [2] . In contrast , small molecule CMP allows the categorization of class partners in networks before the network is built from ssTEM . Classification by post hoc unraveling of connectivity is undoubtedly the most unwieldy and statistically challenging way to identify synaptic partners . Our specific objective in developing these tools is retinal CN mapping . We have begun implementation of this process by developing a rabbit retinal preparation with strong image segmentation . As shown previously [5 , 60 , 67] , augmenting CMP libraries with the activity marker 1-amino-4-guanidobutane ( AGB ) generates a nearly complete neuronal classification . These signals are also fully compatible with ssTEM [56] . We have prepared a single retinal preparation with 16 patches each defined as a canonical field for CN mapping . These patches are being sectioned , stained , and captured with an estimated completion date of mid-March 2009 . The strategy uses horizontal serial sections ( sections in the plane of the retina ) beginning from either the AC or GC side of the inner plexiform layer ( Figure 15 ) . Those cellular layers are first classified as CMP bounding layers registered to the ssTEM set of >400 sections , with each section captured in mosaics of 950–1 , 100 tiles . Upon completion of each volume , it will be available for our own and community browsing and annotation , described as follows . Most of the example ssTEM volumes our group has produced so far have been collected with a single high-performance microscope . We can capture 3 , 000 tiles/day . However , the install base of manual TEM systems or film-based systems with montaging stages far exceeds those with high-resolution digital cameras . Further , the performance of film is still superior to any digital system and the potential for capturing high bit-depth scanned images manually augmented with positional metadata makes our ultrastructural framework even more practical . By fragmenting large projects into packets of grids that can be captured in parallel , it is possible to speed tile acquisition multiplicatively and then distribute tiles to a central resource for volume builds . The next phase of CN mapping is analysis: building a description of connectivity by tagging cells and processes and marking synapses . Our goal is not to render 3D ultrastructural images , but rather tabulate connections within the volume . While it is plausible to develop automated synapse and gap junction recognition tools ( perhaps augmented by molecular probes ) , those tools are in early development stages . Our experience is that analysts can perform excellent tagging and synapse markup with these tools . Furthermore , large datasets can be analyzed in parallel by large groups . A wonderful example of this is the www . galaxyzoo . org project to classify millions of galaxies imaged by various platforms such as the Sloan Digital Sky Survey ( www . sdss . org ) . Given the importance of mammalian central nervous system circuitry analysis in neurological disorders , the notion of a single lab performing cradle-to-grave processing on a system is increasingly impractical , as is the notion that computational pattern recognition can adequately screen data without missing important observations . Human eyes remain the best pattern recognition systems for ssTEM data . The value of our strategy to develop a scalable , web-compliant viewer for community markup lies in the fact that new , powerful acquisition platforms [23–25] and their descendants will soon create an additional deluge of high-quality data . Our next phases of development target six areas . ( 1 ) Auto-tracking: Computational techniques for segmenting and tracing individual neurons across a large number of ssTEM sections [68 , 69] are critical to speed network data collection . ( 2 ) Auto-markup: We are exploring a large library of identified synapses to train automate synapse markup and implement logical rules for synapse identification and signal polarity . These efforts will not replace human tracking and markup in the short term , but needn't be extremely efficient to accelerate analysis several-fold . ( 3 ) Enhanced pipeline speed: Even though we can speed mosaic and volume builds by using more machines , we still seek to vastly improve tool speed to accommodate larger canonical volumes . For example , a canonical volume in primary visual cortex spanning an ocular dominance column is several times larger than the retinal canonical volume . ( 4 ) Simplified pipeline integration: Our efforts to develop acquisition , classification , mosaicking , registration , browsing , and markup tools have originated with several developers using different platforms . How much multiplatform development is justified ? Certainly we argue for an open , platform neutral code base for future development . However , data transport across platforms is now so simple that it is not essential to spend development resources in replicating applications . Rather , improved pipeline scripts and interfaces will be our short-term focus . ( 5 ) Volume viewing with http compliance: We are creating a volume slice-by-slice viewer that enhances the speed of synapse tagging for building CN maps . While not essential to our framework , it offers the ability to lever current web protocols to facilitate community markup . ( 6 ) Enhanced CMP power: We are screening libraries of macromolecules ( e . g . , Marc et al . [70] and Micheva and Smith [7] ) for ssTEM-compliance to augment our CMP library . Finally , the informatics challenges deserve mention . We are hardly alone in this venture . Many groups have addressed the informatics of neuroscience data collections , especially the need to aggregate resources , e . g . , the Neuroscience Information Framework ( http://nif . nih . gov ) , soon to be transferred to the supervision of the National Center for Microscopy and Imaging Research at the University of California at San Diego ( http://www-ncmir . ucsd . edu/ ) , and the International Neuroinformatics Coordinating Facility ( http://incf . org ) . However , a key issue is a lack of multiresolution annotation tools and task administration for large-scale distributed , multiresolution datasets . Though large scale navigational tools have been built by the Allen Institute for Brain Science ( http://www . brain-map . org/ ) and Brain Maps developed by Ed Jones and colleagues at the University of California Davis ( http://brainmaps . org/ ) , robust tools for community markup that can navigate high resolution TEM datasets have yet to be created or validated . Ontologies for neural systems are under rapid development ( http://ccdb . ucsd . edu/CCDBWebSite/sao . html ) , which will be essential to building these markup tools . These and other groundbreaking efforts validate the need for next-generation software including rapid navigation of fused TEM-multivariate molecular data , true volumetric atlases , graph-theory based analyses , and dynamic ontology updating . High-performance ssTEM is a powerful technology coupled to traditionally artisanal data presentation and analysis methods . These are poorly adapted to large-scale collaborations or high-throughput screening . Many laboratories have attempted to develop stronger tools for ssTEM throughput , but most efforts were hampered by many barriers: code that did not scale , limited processor speed , expensive storage , and small canonical volumes . Our framework largely overcomes all computational barriers , providing highly standardized collaborative environments that enable ssTEM to serve as both a statistically practical CN mapping tool and an effective screening/phenotyping tool for modern neurogenetics .
All animal use including methods for anesthesia and euthanasia conformed to institutional animal care and use authorizations at the University of Utah and to the Association for Research in Vision and Ophthalmology Statement for the Use of Animals in Ophthalmic and Visual Research . Retinal samples were taken from Dutch Belted rabbits ( Oregon Rabbitry ) , C57Bl/6J mice ( The Jackson Laboratories ) , and TG9N transgenic mice that have an aggressive photoreceptor degeneration and neural remodeling defect [56] . Light-adapted adult male and female pigmented rabbits tranquilized with intramuscular ketamine/xylazine were deeply anesthetized with intraperitoneal urethane in saline , euthanized by thoracotomy in accord with University of Utah Institutional Animal Care and Use Committee guidelines , and the eyes immediately injected with 0 . 1 ml fixative and an additional 18-Ga needle pressure relief . Rabbit eyes were enucleated , hemisected , and fixed in 1% formaldehyde , 2 . 5% glutaraldehyde , 3% sucrose , 1 mM MgSO4 , in 0 . 1 M phosphate or cacodylate buffer , ( pH 7 . 4 ) . Light-adapted mice were rapidly euthanized with halothane or an isoflurane vaporizer . Mouse eyes were slit at the limbus and injected slowly with 0 . 1 ml fixative before enucleation and immersion fixation for 24 h . All tissues were osmicated 45–60 min in 0 . 5%–1% OsO4 in 0 . 1M cacodylate buffer , processed in maleate buffer for en bloc staining with uranyl acetate , and processed for resin embedding as described in Marc and Liu [17] . Specifically for CN maps , flat resin mounts of retina are remounted for serial sections in the horizontal plane through the inner plexiform layer [27 , 71] . Vertical sections of mouse retina were used to define normal C57Bl6/j and disordered TG9N mouse retinal circuitries . Serial sections were cut at 60–90 nm with various models of Leica ultramicrotomes onto carbon-coated Formvar films on gold slot grids and imaged at 80 KeV in either a Hitachi H-600 or JEOL JEM 1400 electron microscope at 5 , 000–10 , 000× magnification . Images were captured directly on film ( Kodak 4489 Electron Microscope Film ) and digitized at 16 bits grayscale on Ultramax or Creoscitex scanners , or captured digitally on a GATAN Ultrascan 4000 16 megapixel 16-bit camera . Creating the CN map of the retina requires digitizing each tissue section and registering it to its neighbors . Creating a volume of this scale is a significant undertaking: The CN map for the rabbit inner plexiform layer in the visual streak requires a volume delimited by a canonical field 250 μm in diameter × 30 μm high: roughly 1 . 47 × 106 μm3 . A cylindrical volume is a more efficient capture object than rhomboidal prisms that will have extremities clipped out as sections are rotated during registration . While the issue is irrelevant at small volumes [18] , it tremendously impacts beam time at canonical scales . In practice , at a magnification of 5 , 000× on the JEOL JEM-1400 , we capture 950–1 , 100 images or tiles/section and ≈333 sections at 70–90-nm thickness . Storage of unprocessed 16-bit images requires 10 . 4 terabytes . With a time of capture at roughly 30 s/frame , this requires some 70–100 calendar days on a single TEM , which argues for automated capture scripts and efficient capture geometries . To ensure the images can be positioned properly in the total mosaic , each image has 15% area overlap with its neighbors . With some of the software tools developed below , it is also evident that such tasks can be parallelized across microscopes and users . We capture ssTEM data using SerialEM software developed by D . Mastronarde at the University of Colorado at Boulder [72] . Though originally developed for TEM tomography , SerialEM is ideal for large-scale mosaicking . The most recent build version of SerialEM allows definition of multiple circular or polygonal regions of interest on a grid and automates stage drive and image capture within the regions of interest on the JEOL JEM 1400 TEM ( and other recent TEMs as well such as FEI Tecnais ) and , critically , stores stage position metadata for each tile . This greatly reduces the computational cost of the initial positioning of mosaic tiles from O ( n2 ) to O ( n ) . The program includes a scripting capability that provides the flexibility needed to optimize the acquisition strategy , for example , by focusing only on an appropriately spaced subset of the image tiles . While automated capture is ideal for the microscope's Gatan Ultrascan 4000 ( 4K × 4K ) camera , it can also serve on a smaller scale with film capture . We use the same software suite ( ir-tools ) to mosaic ssLM and ssTEM data . In an ideal setting , we have stage position metadata for both kinds of datasets ( from Syncroscan and SerialEM ) , which can be used by ir-translate to produce precise initial image mosaics . This is then followed by ir-refine grid to correct for image aberrations in each tile . However , some users may lack capture automation . In this more general case , an operator manually adjusts the position of each tile , aiming for a specified but often imprecise overlap between tiles . Even approximate coordinate information is often not recorded . Given a large number of tiles specified in no particular order , a mosaic must be constructed and individual tiles corrected for distortions , especially subtle electron-optical aberrations ( spherical aberrations , magnification astigmatism , local heating motions , charging motions , etc . ) that are often undetectable until precise alignment is attempted ( Figure 4 ) . It is rare that the magnification in the average TEM is exactly the same at the field center and edge . At a modest magnification yielding a 7 . 5-μm wide field ( about 5 , 000× ) , a 1% error in magnification at the edge of the field ( 4 , 950× ) yields a displacement of over three vesicles: potentially a massive misalignment in tracing circuits . A mosaicking scheme that addresses this general problem is ir-fft followed by ir-refine-grid . Slice-to-slice image registration is further complicated by differences in imaging modalities ( ssLM versus ssTEM ) , changing shapes of cells and processes , and physical distortions affecting individual sections ( folds , stretching ) . At the boundaries of or intercalated within the ssTEM volume , we collect ssLM data for CMP analysis . Similar to the multimodal alignment strategies used by Marc and colleagues [5 , 56] , ssLM images are operator-registered to adjacent ssTEM slices using ir-tweak . However , manually registering large ssTEM volumes is impractical and automated slice-to-slice tools are needed: ( ir-stos-brute , ir-stos-grid ) . CMP is a method to extract quantitative molecular signatures from cells or even cellular processes [5 , 54] and fuse molecular signature data with ssTEM datasets [17 , 56] . ssLM samples ( 40–90 nm ) are arrayed on 12-spot Teflon-coated slides ( Cel-Line; Erie Scientific Inc ) , fully sodium ethoxide etched , probed with IgGs targeting various molecules , and visualized with silver-intensified 1 . 4-nm gold granules conjugated to goat anti-rabbit or goat anti-mouse IgG ( Nanoprobes ) . Immunoreactivity in these samples is a pure surface phenomenon independent of section thickness [54] . The IgG library includes ( but is not limited to ) anti-L-aspartate ( IgG D ) , anti-L-glutamate ( IgG E ) , anti-glycine ( IgG G ) , anti-L-glutamine ( IgG Q ) , anti-taurine ( IgG τ ) , and anti-GABA ( IgG γ ) ( Signature Immunologics Inc . ) . All data were captured as 8-bit 1 , 388 pixel × 1 , 036-line frames under voltage-regulated tungsten halogen flux with a variation of 1 . 2 ± 0 . 6%/min ( mean ± SD ) . Image mosaic tiles were captured with a Peltier-cooled QImaging Fast 1394 QICAM ( QImaging ) and a Syncroscan montaging system ( Synoptics Inc . ) on a Scan 100 × 100 stage ( Märzhäuser Wetzlar GMBH & Co . ) . ssLM mosaics were prepared using various ir-tools and aligned using ir-tweak ( see below ) . CMP classification ( clustering , histogram analysis , PCA , etc . ) is performed on the CMP dataset using CMPView ( J . Anderson , 2008 ) to phenotype processes and cells . CMPview is built in MATLAB2008a . Clustering is based on the robust K-means and isodata algorithms ( see Marc et al . [5 , 54] ) , augmented with interactive histogram splitting tools . CMPView operates on either pixel-based or object-based images . The intermediate product of relevance for this paper is the production of a high-resolution theme map of cell classes that is then registered to ssTEM data [17 , 56] . Finally , image analysis for characterization of mosaicking and registration performance was performed using ImageJ [73] . Once large mosaics are built , it is essential to have tools to browse , annotate , and record annotations . Some mosaics are 15–30 GB datasets , which are unmanageable by most commercial imaging tools . We have developed two applications , MosaicBuilder ( Mac OS X ) and Viking ( Win ) , that allow single slices to be viewed , browsed , and annotated . By using image pyramids , these tools quickly navigate between low and high magnification views . Volumes are even more challenging , as they expand into terabyte size and Viking allows rapid paging through the build over an HTTP connection , enabling single image repositories to serve multiple users . This 12-stage framework requires significant user management and exceptional digital hygiene in data archiving , access , and revision control . Since each computational stage invokes a different program and occasional transitions between data formats we elected to use the Python scripting language and Python Imaging Library to bridge stages . The scripts perform tasks such as conversion from microscope-specific formats to the plain text “ . mosaic” format of ir-tools , image cropping , contrast enhancement , down-sampling , and launching multiple instances of single-threaded algorithms to ensure each CPU core is fully utilized . Pipeline automation improves throughput , eases integration , produces consistent results , and stabilizes performance .
|
Building an accurate neural network diagram of the vertebrate nervous system is a major challenge in neuroscience . Diverse groups of neurons that function together form complex patterns of connections often spanning large regions of brain tissue , with uncertain borders . Although serial-section transmission electron microscopy remains the optimal tool for fine anatomical analyses , the time and cost of the undertaking has been prohibitive . We have assembled a complete framework for ultrastructural mapping using conventional transmission electron microscopy that tremendously accelerates image analysis . This framework combines small-molecule profiling to classify cells , automated image acquisition , automated mosaic formation , automated slice-to-slice image registration , and large-scale image browsing for volume annotation . Terabyte-scale image volumes requiring decades or more to assemble manually can now be automatically built in a few months . This makes serial-section transmission electron microscopy practical for high-resolution exploration of all complex tissue systems ( neural or nonneural ) as well as for ultrastructural screening of genetic models .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"computer",
"science",
"cell",
"biology",
"neurological",
"disorders",
"ophthalmology",
"computational",
"biology",
"neuroscience"
] |
2009
|
A Computational Framework for Ultrastructural Mapping of Neural Circuitry
|
Orientation selectivity is a key property of primary visual cortex that contributes , downstream , to object recognition . The origin of orientation selectivity , however , has been debated for decades . It is known that on- and off-centre subcortical pathways converge onto single neurons in primary visual cortex , and that the spatial offset between these pathways gives rise to orientation selectivity . On- and off-centre pathways are intermingled , however , so it is unclear how their inputs to cortex come to be spatially segregated . We here describe a model in which the segregation occurs through Hebbian strengthening and weakening of geniculocortical synapses during the development of the visual system . Our findings include the following . 1 . Neighbouring on- and off-inputs to cortex largely cancelled each other at the start of development . At each receptive field location , the Hebbian process increased the strength of one input sign at the expense of the other sign , producing a spatial segregation of on- and off-inputs . 2 . The resulting orientation selectivity was precise in that the bandwidths of the orientation tuning functions fell within empirical estimates . 3 . The model produced maps of preferred orientation–complete with iso-orientation domains and pinwheels–similar to those found in real cortex . 4 . These maps did not originate in cortical processes , but from clustering of off-centre subcortical pathways and the relative location of neighbouring on-centre clusters . We conclude that a model with intermingled on- and off-pathways shaped by Hebbian synaptic plasticity can explain both the origin and development of orientation selectivity .
Response properties in the visual system undergo a remarkable change in the transition from subcortical pathways to cortex . Cortical neurons are selective for stimulus characteristics such as contour orientation , motion direction and depth . In primate and carnivore subcortical neurons , by contrast , these selectivities are weak or absent [1–3] . This change in neuronal tuning characteristics–from camera-like to one that supports object recognition [4]–depends on the geniculocortical synapse , where subcortical signals converge onto cortical neurons . Orientation selectivity is a clear example of the subcortical-to-cortical transformation . Many cortical neurons respond best to a contour with specific orientation ( for example , vertical ) and less well to other orientations . Orientation selectivity was first described by Hubel and Wiesel [5] , who also provided a model for its origin . They proposed that on-centre and off-centre subcortical channels converge on cortical neurons , that the two inputs are driven by separate locations in the visual field , and that the preferred orientation is approximately perpendicular to the displacement of the inputs . Parts of this model have survived the test of time . Simultaneous recording of cortical neurons and their subcortical inputs have demonstrated the convergence of on- and off-pathways [6–8] . These same studies have shown a pattern of convergence that is consistent with the measured orientation preference . The model has also been extended to the retinal level . Anatomical data shows that nearest neighbours in the retina are usually of opposite sign [9] . Soodak [10] proposed that the convergent pathways at the cortex originate in neighbouring retinal ganglion cells , and Ringach [11] showed that a model based on this idea fits well with several cortical properties . The Hubel and Wiesel model has also , however , encountered significant challenges . A recent study [12] has shown that the inputs to a cortical column do not neatly segregate into on- and off-dominated neurons as earlier envisaged [13] . Instead , there is substantial spatial overlap between the population of on- and off-inputs to a cortical column . How do these overlapping areas segregate into the on- and off-subfields of a cortical receptive field ? That is one of the questions we aim to answer with the modelling in the present paper . Another question concerns intracortical inhibition , which plays a major part in shaping cortical receptive fields [14]: what are the relative roles of subcortical convergence and intracortical inhibition in producing orientation preference ? A third challenge to the convergence model for orientation selectivity comes from response amplitude . In the Soodak [10] and Ringach [11] models , a cortical neuron linearly sums responses from a number of neighbouring subcortical neurons . But nearest retinal neighbours are almost always of opposite sign [9] , which will result in signal cancellation and very low response amplitudes in the cortex . Indeed , it has been shown that cells in the kitten’s primary visual cortex are insensitive compared to their mature counterparts [15] and that substantial areas of the orientation preference map in the immature ferret are noisy [16] . We therefore tested the idea that the same on/off segregation responsible for cortical receptive fields can raise response amplitudes . We find that responses in the mature cortex are an order of magnitude larger than before segregation . In this paper , we describe a signal-processing model that complies with known anatomy and physiology of the early visual pathways . On-centre and off-centre inputs to a cortical neuron are co-extensive; a Hebbian development process functionally segregates the two signs of input . Intracortical inhibition , which is assumed to derive from a widespread , slow-acting network that indiscriminately reduces membrane potential , contributes to orientation selectivity through the iceberg effect [17] . Our aim is to show how developmental refinement of geniculocortical connections can lead to cortical response characteristics–time courses , precise orientation tuning , and orientation preference maps–that match well with those seen in the laboratory . To make the modelling manageable , the scope of the model is limited in several ways . First , the model is designed to describe the cat’s visual pathway because the visual literature for this species is particularly rich ( including almost all the animal studies cited above ) . Second , the subcortical pathway is chosen to pass through the X-type retinal ganglion cell because of its relatively high acuity . Last , the model is restricted to monochromatic , monocular stimuli , and the input layers of primary visual cortex . The model builds on a previous one [18] by adding a retinal ganglion cell array , a development process and dynamic intracortical inhibition . Earlier accounts of this work have appeared in abstract form [19] , [20] .
A flow diagram of the model is shown in Fig 1A . There are multiple subcortical channels , each of which passes through either on-centre or off-centre neurons . Each channel consists of four neurons–photoreceptor , bipolar cell , retinal ganglion cell and relay cell in the dorsal lateral geniculate nucleus–in series . The input to each channel is a dot product of the stimulus with a Gaussian weighting function representing subcortical spatial spread . Apart from shared input , signals in each channel are assumed to be independent . Thus , the membrane potential p in neurons 1 , 2 , 3 and 4 for channel j is given by: τdpj1 ( t ) dt=−gjs ( x , y ) ⋅s ( t , x , y ) −pj1 ( t ) # τjdpj2 ( t ) dt=−njpj1 ( t ) −pj2 ( t ) # τjdpj3 ( t ) dt=pj2 ( t ) +ps−pj3 ( t ) # τjdpj4 ( t ) dt=h ( pj3 ( t ) ) −pj4 ( t ) # The derivation of these equations is provided in the Methods , along with definitions and values of the variables . Subcortical channels converge onto layer 4 and 6 neurons in primary visual cortex via a Gaussian convergence function . Cortical neurons are of two types , excitatory and inhibitory . They receive the same subcortical input , and inhibitory neurons therefore have receptive fields similar to those of excitatory neurons [8 , 21] . Inhibitory neurons differ from excitatory neurons in that they are split into two compartments . The first compartment , consisting of dendrites and soma , has fast dynamics corresponding to fast-spiking neurons [21] . Simple cells stimulated with flashed stimuli , however , have long-lasting inhibitory tails [22] , so we have included a second compartment–axon and terminals–with much slower dynamics . The axons converge on excitatory neurons with another Gaussian convergence function . The effect of this slower component is to provide a widespread , slow-acting inhibition to excitatory neurons [14 , 22] . Defining inhibitory somas , inhibitory axon terminals and excitatory neurons as stages 5 , 6 and 7 , the membrane potential in neuron k for each of these stages is given by: τdpk5 ( t ) dt=∑jgkc ( xj , yj ) wjkh ( pj4 ( t ) ) −pk5 ( t ) # τinhdpk6 ( t ) dt=h ( pk5 ( t ) ) −pk6 ( t ) # τdpk7 ( t ) dt=∑jgkc ( xj , yj ) wjkh ( pj4 ( t ) ) −∑lgke ( xl , yl ) pl6 ( t ) −pk7 ( t ) # Fig 1B illustrates signal processing in a typical neuron . The sum of the weighted synaptic inputs is integrated over time to produce a generator potential . This potential is rectified to produce action potential rate; the exceptions are the photoreceptors and bipolar cells , which do not produce action potentials . Fig 1C shows the signal processing in an inhibitory neuron . Subcortical inputs undergo temporal integration as they pass through the dendrites and soma . The rectification function is then applied to the sum . The resulting action potential is once again integrated within the axon and inhibitory network to produce the inhibitory input to excitatory cortical cells . Our aim in this paper is to describe a physiologically plausible model that reproduces key aspects of orientation selectivity . It has become increasingly clear over recent years that cortical properties depend heavily on the response characteristics of subcortical channels [10 , 11] and the way in which the cortex combines its subcortical inputs [12] . We therefore start by describing the spatial distribution of subcortical channels in the model and the process by which visual development weights the cortical inputs . Fig 2A shows all subcortical channels in a 6°×6° patch of visual field . Each channel is represented by a circle at the centre of its receptive field , red for on-centre channels and blue for off-centre . The calculation of the locations ensured that closest neighbours were almost always of opposite polarity , as required by anatomical measurements [9] . The weighting of each channel’s synapse with a cortical neuron is represented by circle diameter , and all weights are assumed equal at the start of the development process . Response-dependent development of the visual system is driven by intrinsic connections [23] and at least two stimulus sources: waves of activity traversing the retina [24] , and moving visual stimuli encountered after eye opening [25] . Neuronal responses in the model were therefore stimulated with a drifting sinusoidal grating over the full range of orientations . Each cycle in the development process then consisted of increasing the weight of all geniculocortical synapses for one randomly chosen subcortical channel . If the action potential rate of a cortical neuron increased as a result , the synapse between the channel and the cortical target remained strengthened . Otherwise , the synaptic weight was weakened to less than its original value . Fig 2B and 2C show the weights at intermediate steps of visual development for the excitatory cortical neuron at the middle of the visual field patch , and Fig 2D shows the final result . On-centre channels dominate off-centre channels in oval areas of visual field and off-centre channels dominate in other areas . The source of the on/off segregation is easy to understand . Neighbouring channels tend to have opposite sign so that their signals typically cancel each other when they sum at a cortical neuron . A strengthening of one channel and weakening of its opposite-sign neighbour will increase the cortical response , and the Hebbian development process preserves this bias . The channel sign that dominates a visual area will depend on the randomised process by which channel locations were assigned . Fig 3A and 3B show the start and end of development for the neuron in Fig 2 . Fig 3C shows synapse strength for a cortical neuron located at the position marked by the yellow dot . The on-off segregation is in much the same direction as that in part B of the figure , but the pattern is more odd- than even-symmetric . Part D of the figure shows synaptic strengths for a cortical neuron in a third location . In this case the orientation of on-off segregation differs from the other two locations , indicating that each cortical neuron has its own spatial pattern of inputs . All of these on-off segregations are suggestive of the receptive field patterns to which they could contribute: we will show receptive fields at the end of the results . Hebbian changes could potentially increase a synapse’s strength beyond the physiological limit . But the model includes intracortical inhibition which is driven by the same geniculocortical input as are the excitatory neurons . As synapses increase in strength so does inhibition: this limits excitatory responses in the cortex , preventing further synaptic strengthening . We now demonstrate this growth in inhibition during development and its effect on response time courses . Fig 4A shows the time course of two representative cortical neurons at the start of visual development . Responses to a 2 Hz drifting grating are shown . The blue curve indicates the somal generator potential of a geniculorecipient inhibitory neuron , the orange curve shows potential in the axonal terminal in the same neuron , and the red curve gives potential in an excitatory neuron with which the axon makes an inhibitory synapse . All response amplitudes are low due to the near-cancellation of neighbouring on- and off-channels . Fig 4B , obtained at the end of development , shows much larger amplitudes due to the functional segregation of on- and off-channels . The figure also shows that the mean potential of the inhibitory terminal has risen due to rectification at the axon initial segment , and that the excitatory cell’s mean potential has fallen as a consequence . The result is the iceberg effect [17] illustrated in Fig 4C . This shows action potential rate in the excitatory neuron for four steps in the development process . As the excitatory drive to this neuron rises so does inhibition , and only the peak of the underlying response is seen . We used Fourier analysis to compare the shape of this time course with that found in the published literature . The horizontal axis in Fig 4D shows relative modulation , defined as the ratio of the Fourier fundamental component of the impulse rate divided by mean rate . Dean and Tolhurst [26] showed that as the response becomes more peaked , and the peristimulus time histogram is reduced to a single bin , this ratio approaches 2 . A frequency histogram of the ratio is shown in Fig 4D for both Dean et al . ’s result and for the model . The mode of the histogram is close to 2 in both cases , indicating that the time course in the model is similar to that recorded in real cortex . To measure orientation tuning in the model we drifted a sinusoidal grating across the visual field at a variety of orientations . Fig 5A gives the result for the cortical neuron whose geniculocortical strengths are shown in Fig 3B . Early in the development process , response amplitudes are low and orientation tuning is weak . Later in development two tuning peaks appear , one for motion in one direction and the other for motion in the opposite direction . The preferred orientation matches that expected from the synaptic strengths . To check tuning precision , we fitted a curve to the response at each cortical location: Fig 5B shows the result of fitting the curve to the post-development data in part A of the figure . Tuning bandwidth was measured as the half width at half height of the fitted curve , as shown . Fig 5C shows tuning bandwidths as a function of peak response amplitude at four steps of development , where each circle represents one excitatory cortical neuron . Not surprisingly , bandwidths are large and scattered at the start of development . Bandwidths at the end of development , however , are tightly clustered and as low as 15° . To compare this result with real cortex we calculated the frequency histogram of bandwidth , as shown in Fig 5D . The histogram falls between two recent empirical estimates [27 , 28] , indicating that bandwidth estimates in the model are realistic . Previous work , particularly optical imaging , has shown that preferred orientation forms characteristic patterns across the cortical surface [29] . We next wished to determine whether our model reproduces such patterns . Preferred orientation , taken from the maximum of the motion direction tuning curve , is shown as a function of visual field location in Fig 6 . Part A of the figure shows that an orientation map exists even before development starts . This is as expected from the orientation tuning curve in Fig 5A , development cycle 0 , which shows a mature preferred orientation even though tuning is poor . Like the empirical work , the map at the end of development ( Fig 6B ) displays regions in which orientation changes little and other regions containing pinwheels , around which orientation varies across its whole range . The consistency of the map during development matches findings in ferret primary visual cortex [16] . The model provides us with a unique opportunity for exploring the source of these patterns . The first clue comes from comparing the pattern at the start and end of development ( Fig 6A and 6B ) . The patterns are very similar ( correlation coefficient = 0 . 97 , n = 6559 , p<round-off error , null hypothesis: maps are uncorrelated ) , indicating that the basic pattern is set prior to any developmental changes in the cortex . This suggests that the orientation maps are determined by the spatial layout of subcortical channels . We tested this idea by subtracting the map of off-centre channels from that for the on-channels . The result , in Fig 6C , shows areas clearly dominated by one or the other contrast polarity . To see whether this inhomogeneity could produce the orientation map we took the dot product of the map in C with Gabor functions varying in both spatial phase and orientation . The details of this calculation are provided in the Methods section . The result , in part D of the figure , shows clear similarities with the orientation map ( correlation coefficient = 0 . 88 , n = 6559 , p<round-off error ) . In a further six simulations , obtained by varying the randomisation seed ( and therefore the retinal ganglion cell array ) , the correlation coefficient was never less than 0 . 87 . It seems , therefore , that clumping of on-centre channels in one region and of off-channels in a nearby region can produce orientation preference maps that look much like those recorded in the laboratory . We compared the statistics of the map with published work by calculating its periodicity . Each orientation in Fig 6B was converted to a unit vector and a Fourier transform was calculated for the real and imaginary parts of the vector map , as shown in Fig 7 . The peak magnitudes of both transforms were at 0 . 63 cycles/deg from the origin , yielding a periodicity of 1 . 6 degrees of visual angle . Converting to distance , using the cortical magnification factor calculated in the Methods section , yielded a periodicity of 1 . 1 mm . This compares well with the estimates of Löwel et al . [30] and Diao et al . [31] who found values of 1–1 . 1 and 1 . 1 mm , respectively . We also counted pinwheels , as defined in the Methods . The result was 2 . 8 pinwheels per orientation hypercolumn , close to the mean value ( 3 . 1 ) found in three species by Kaschube et al . [32] and in four species , including the cat , by Schottdorf et al . [33] . We are therefore confident that the orientation preference map obtained from the model faithfully reproduces empirical data . What is the source of the periodicity in the orientation map ? Given that the map can be predicted from subcortical arrays , we looked at subcortical sources . Fig 8A shows an analysis like that in the previous figure except that here the analysed map is subcortical . Pulses representing off-centre ganglion cell locations were subtracted from on-centre pulses , the map was smoothed with the spatial profile of the geniculate centre mechanism , and the result was Fourier transformed . The maximum magnitude in this map is found at 0 . 60±0 . 05 cycles/deg from the origin ( mean±standard error , obtained from the standard and six other maps ) , representing a periodicity of 1 . 7° . This value is close to that found for the orientation map ( 1 . 6° ) , indicating that we should look subcortically for the source of the periodicity . One possibility is aliasing [34]: the on- and off-centre ganglion cells in our model have a density of 24 . 4 and 26 . 6 cells/deg2 , respectively . As described in the Methods , this results in a periodicity of 6 . 5° which is about four times the required value . Another possibility is shown in Fig 8B , the upper part of which shows the one-dimensional centre mechanism profiles of neighbouring on- and off-centre cells . The lower part of Fig 8B shows the difference between these two profiles to mimic the results of cortical convergence . The Fourier transform of this difference curve , shown in Fig 8C , has a peak 0 . 56 cycles/deg from the origin , which translates to a periodicity of 1 . 8° . This value is close to the periodicity of 1 . 6° found in the orientation map , strongly suggesting that the latter value is set by the differencing of on- and off-centre receptive field profiles . The geniculocortical weight maps in Fig 3 are reminiscent of simple cell receptive fields . We calculated receptive fields in the model with a sparse noise stimulus: squares of light or dark , as shown in Fig 9A , were briefly presented at a variety of visual field locations . Responses in excitatory cortical neurons were calculated and the peak impulse rate was recorded at each location . Contour plots of the responses to light and dark are shown in red and blue , respectively . Fig 9B , 9C and 9D show the resulting receptive fields for the neurons whose synaptic weights are given in Fig 3B , 3C and 3D , respectively . Stimulus locations far from the neuron produce a generator potential that fails to reach spike threshold , and the receptive fields are therefore smaller than the corresponding weight maps . In particular , the weight map in Fig 3B is nearly even-symmetric so that only the central subfield survives in the receptive field . Otherwise the synaptic weight patterns are faithfully represented in their receptive fields . Another feature of interest is the peak impulse rate shown next to each subfield . Responses to dark stimuli are clearly greater than to light stimuli with the same contrast magnitude , reflecting the dark dominance seen in real cortex [35 , 36] . Dark dominance in the model arises from two sources: off-centre ganglion cells outnumber on-centre cells , and off-centre geniculate responses are faster than their on-centre counterparts . Both of these asymmetries reflect empirical findings [9 , 37] .
A number of previous models have addressed issues such as orientation selectivity and cortical mapping . How do our results fit in with this previous work ? One of the earliest studies was by von der Malsburg [38] , whose model consisted of a retinal layer connected directly to a cortical layer . Retinocortical connections varied in strength through Hebbian plasticity , producing a cortical map of preferred orientation . The retina , however , consisted entirely of on-cells , limiting the orientation selectivity of cortical cells . Miller [39] described a model for the development of orientation selectivity , and showed that it could produce both receptive fields like those in simple cells , and cortical maps of orientation preference resembling laboratory observations . To do this Miller assumed that nearby like-sign subcortical neurons have positively correlated activity but that the correlation between more distant neurons is between those of opposite sign . We have not made any assumption about the statistics of subcortical activity . Instead , we have used the known statistics of subcortical receptive field locations [9] to calculate orientation selectivity: simple cell-like receptive fields result from spatial clustering of same-sign subcortical channels rather than from response correlations . Somers , Nelson and Sur [40] described a model in which subcortical inputs provide a mild orientation bias to cortical neurons , but the authors do not provide a mechanism by which such a bias might develop . Instead , they showed that the orientation tuning can be sharpened by connections between excitatory cortical cells , leading to positive feedback . These connections correspond to the prolific excitatory-to-excitatory synapses found in anatomical studies [41] . A more recent study [27] has also shown that mutual excitation can improve tuning sharpness . We have chosen to avoid recurrent connections from excitatory cells for simplicity and ease of interpretation . One of the advantages of the Somers et al . [40] model is that the units it uses , such as micrometres of cortical surface , correspond with those used in empirical studies . We have taken their approach even further by specifying spatiotemporal and response parameters with units of degrees of visual angle , seconds , millivolts and impulses/s . This aids comparison of the model with experimental observations . Another advantage of our model is that its stimulus can be any spatiotemporal pattern , provided that it is monocular and monochromatic . The model can therefore be tested with stimuli not described here . Previous work has shown that orientation preference maps are firmly established early in visual life , even though orientation tuning is weak . Chapman et al . [16] used optical imaging to measure maps in ferret cortex around the time of eye opening . They found that maps in each animal were geometrically stable over many weeks even though responses were weak in the earliest recordings . Our model provides a basis for this finding by proposing that the stability originates in the retinal ganglion cell array . Crair et al . [42] recorded orientation preference maps in both normal and binocularly deprived cats and found that the maps were present in animals without visual experience . This suggests that the stimuli we have used to drive Hebbian development are due to moving waves of subcortical activity rather than motion in the visual world . Later work , however , has introduced a new factor into this parsimonious picture . Smith et al . [23] used calcium imaging of spontaneous activity in ferret visual cortex to show correlated activity between widespread cortical patches . They found that correlated patches had similar orientation preferences when stimulated . The patchy correlations were evident before eye opening , at a time when orientation preference maps were still forming . How the subcortically driven maps that we have simulated fit in with the long-range cortical networks found by Smith et al . remains to be determined . Previous models have assumed that orientation selectivity depends on discrete lines of on- and off-centre cortical inputs [5 , 13] or on small numbers of nearest-neighbour retinal ganglion cells of opposite sign [10 , 11] . Both of these models now look impractical . Consider , for example , a visual field point that is 11° from the cat’s central area , as in the model we have described . According to the estimates in the Methods section , the density of X-type retinal ganglion cells at the corresponding retinal location is about 51 neurons/deg2 [43] . Given that each X-cell drives one or very few relay neurons in the lateral geniculate nucleus [44 , 45] , the densities of geniculocortical inputs will be similar . Those inputs produce a simple cell receptive field with a median area of 2 . 7 deg2 [46] . We can therefore expect that about 51×2 . 7 = 140 subcortical inputs converge on a simple cell . Reid and Alonso [7] estimated that a third of those inputs are functionally effective , while our estimate ( Fig 3B , which shows that one or other input sign dominates at each point ) is closer to one half . We therefore estimate that a simple cell is driven by 47 to 70 subcortical neurons , substantially higher than in the earlier models . A recent paper [47] modelled the contribution of retinal on/off pairs to cortical orientation preference maps . The authors concluded that paired interactions do not lead to realistic orientation preference maps . Our results provide an alternative model , namely that orientation preference arises from localised high densities of same-sign retinal neurons . In particular , orientation preference at a specific visual field location is determined by a retinal area in which on-centre neurons are more densely packed than are off-centre neurons , and a nearby area in which off-centre neurons are more densely packed ( Fig 6C ) . Whether our model reflects the seeding of real orientation preference maps remains to be tested in the laboratory . There are two sources of randomness in the model , both structural . The first is the random variation of a channel location about its node on a rectangular grid . This variation seeds the orientation map . The second source of random variation is the sequence in which channels are tested with an increase in geniculocortical strength . Changing this sequence has little effect on the results . We have chosen not to add noise to the membrane potential: all of the differential equations defining the model are deterministic . This choice comes with two disadvantages . First , two studies [48 , 49] have shown that membrane potential noise helps to preserve the precision of orientation tuning as contrast increases . Contrast invariance in our model may suffer from the lack of membrane potential noise . Second , the frequency histograms generated by the model are substantially narrower than those recorded in the laboratory ( Figs 4D and 5D ) . Membrane potential noise would broaden the model histograms . We have chosen , however , to exclude such noise from the model in order to make it simpler to interpret . We calculated impulse rate by thresholding membrane potential without considering random fluctuations in potential . There is strong empirical support for this approach . Carandini and Ferster [50] recorded membrane potential in primary visual cortical cells , low-pass filtered the potential and then applied a half-wave rectifier to predict impulse rate . The prediction worked well over a wide variety of conditions , including adaptation and a range of contrasts . Our model uses the relationship they measured between membrane potential and impulse rate , as shown in Eq 2 . Resting activity is a key component in our model . In keeping with subcortical measurements [51] we assume that X-cells have a substantial resting impulse rate , which helps to linearise their responses to stimuli of moderate contrast . This resting activity translates to an even higher impulse rate in the cortical inhibitory neurons , which corresponds with empirical findings [21] . In turn , the high firing rate in inhibitory neurons produces a resting hyperpolarisation in the cortical excitatory neurons . This matches the absolute contrast threshold found in simple cells [52] and the hyperpolarisation in intracellularly recorded simple cells [53] . All of these resting activities in the model result from a single parameter , the constant depolarisation added to the ganglion cell generator potential ( Eq 8 ) . While resting activity in the real visual system may derive from multiple sources , it is interesting that we have been able to construct an internally consistent model in which resting activities result from a single subcortical source .
Here we derive the equations describing the model . Each neuron is represented by a single nonlinear differential equation , and time courses are obtained by simultaneous numerical integration of the equations for all neurons . The difference between membrane potential at the initial segment of a neuron’s axon and action potential threshold determines the action potential rate . This difference is therefore called the generator potential , denoted by p ( t ) where t is time . The input to the neuron is a set of synaptic potentials , vi ( t ) , each of which is weighted by a gain , gi . The model assumes that the neuron is a low-pass filter that integrates the difference between the driving potential and generator potential: τdp ( t ) dt=∑igivi ( t ) −p ( t ) # ( 1 ) where τ is the time constant . The neuron’s action potential rate , a ( t ) , is obtained by rectifying the generator potential: a ( t ) =grecth ( p ( t ) ) whereh ( p ) ={p , p≥00 , p<0# ( 2 ) To complete Eq 1 we need to know how the activity in one processing stage , z , depends on that in the previous stage , z−1 . We assume that the postsynaptic potential , vi , is proportional to presynaptic impulse rate . The general equation for a model neuron is then: τdpz ( t ) dt=∑igih ( pi , z−1 ( t ) ) −pz ( t ) # ( 3 ) where proportionality constants have been absorbed into gain gi . The general equation requires modification for each stage of the model . The stage numbers are 1 to 7 representing , in order , photoreceptors , bipolar cells , ganglion cells , geniculate neurons , inhibitory neuron somas , inhibitory neuron axons , and excitatory cells . Fig 1 shows the signal-processing sequence . The photoreceptors receive their input from the visual stimulus rather than a presynaptic neuron , and do not produce action potentials: τdpj1 ( t ) dt=−gjs ( x , y ) ⋅s ( t , x , y ) −pj1 ( t ) # ( 4 ) where p represents the difference between membrane potential and resting potential rather than generator potential , j is channel number , the subscript s indicates subcortex , x and y give visual field location and s ( t , x , y ) is the stimulus . We use the ( ⋅ ) symbol to represent both vector and integral dot products . The gain is a Gaussian function of location representing subcortical spatial spread due to optical blurring and neural convergence: gjs ( x , y ) =gsπrs2exp ( − ( x−xj ) 2+ ( y−yj ) 2rs2 ) # ( 5 ) where gs and rs are the contrast sensitivity and radius of the centre mechanism ( the model does not include a surround mechanism ) and ( xj , yj ) is the spatial location of channel j . The dot symbol in Eq 4 represents the dot product: gjs ( x , y ) ⋅s ( t , x , y ) =∫y=−∞∞∫x=−∞∞gjs ( x , y ) s ( t , x , y ) dxdy# ( 6 ) The minus sign preceding the dot product in Eq 4 corresponds to photoreceptor hyperpolarisation by light . Bipolar cells do not produce action potentials and can be on- or off-centre: τjdpj2 ( t ) dt=−njpj1 ( t ) −pj2 ( t ) # ( 7 ) where τj and nj are the time constant and sign for channel j . Ganglion cells produce action potentials so p represents generator potential for these and subsequent neurons . Ganglion cells also have a resting impulse rate , which is implemented in the model by adding a constant depolarisation , ps , to the driving potential: τjdpj3 ( t ) dt=pj2 ( t ) +ps−pj3 ( t ) # ( 8 ) Relay cells in the dorsal lateral geniculate nucleus inherit the constant depolarisation from , and rectify , their input: τjdpj4 ( t ) dt=h ( pj3 ( t ) ) −pj4 ( t ) # ( 9 ) The input to inhibitory cortical neuron k is obtained by taking the dot product of the subcortical input with a Gaussian convergence function: τdpk5 ( t ) dt=∑jgkc ( xj , yj ) wjkh ( pj4 ( t ) ) −pk5 ( t ) # ( 10 ) where the convergence function gkc is obtained by subscript substitution into Eq 5 , c stands for cortex , and wjk is the strength of the synapse from subcortical input j . The generator potential in the inhibitory neuron initial segment is rectified and integrated by its axon and connection into the inhibitory network: τinhdpk6 ( t ) dt=h ( pk5 ( t ) ) −pk6 ( t ) # ( 11 ) Finally , excitatory cortical neuron k is driven by the sum of its subcortical and inhibitory inputs: τdpk7 ( t ) dt=∑jgkc ( xj , yj ) wjkh ( pj4 ( t ) ) −∑lgke ( xl , yl ) pl6 ( t ) −pk7 ( t ) # ( 12 ) where e stands for excitatory neuron . Eqs 4–12 together define the model . We transformed the model into the frequency domain for two reasons . First , we reduced the possibility of mathematical and computational errors by ensuring that the solutions in the temporal and frequency domains agreed to within round-off error . Second , we reduced computation time by performing most of the calculations in the frequency domain . The Fourier transform of Eq 4 is: iτωPj1 ( ω ) =−gjs ( x , y ) ⋅S ( ω , x , y ) −Pj1 ( ω ) # ( 13 ) where i=−1 , ω is temporal frequency , and Fourier transforms are shown in upper case . Thus: Pj1 ( ω ) =−gjs ( x , y ) ⋅S ( ω , x , y ) 1+iτω# ( 14 ) Similarly , the transforms for the following subcortical stages are: Pj2 ( ω ) =−njPj1 ( ω ) 1+iτjωPj3 ( ω ) =ps2πδ ( ω ) +Pj2 ( ω ) 1+iτjω#Pj4 ( ω ) =F ( h ( pj3 ( t ) ) 1+iτjω ( 15 ) where δ is the Dirac delta function and F is the Fourier transform . At the cortical level: Pk5 ( ω ) =∑jgkc ( xj , yj ) wjkF ( h ( pj4 ( t ) ) ) 1+iτωPk6 ( ω ) =F ( h ( pk5 ( t ) ) ) 1+iτinhω#Pk7 ( ω ) =∑jgkc ( xj , yj ) wjkF ( h ( pj4 ( t ) ) ) −∑lgke ( xl , yl ) Pl6 ( ω ) 1+iτω ( 16 ) Most of the simulations in the paper use a drifting grating as stimulus . We made these simulations faster by using the analytical solution for the dot product , Eq 6; the solution follows . There is no surround antagonism in the basic model . To compensate , stimuli are defined in terms of contrast rather than luminance . Contrast is obtained by finding the difference between local and background luminance , and dividing the difference by background luminance . The equation for a drifting grating is: sj ( t , u ) =ccos ( ψstim ( u+uj ) −ωstimt ) # ( 17 ) where c is the contrast , ψstim is the spatial frequency , ωstim is the temporal frequency , and u = cos ( θ ) x+sin ( θ ) y is the distance in the grating’s direction of motion , θ , with uj being the location of the jth channel . The dot product is then: gjs ( x , y ) ⋅s ( t , x , y ) =∬−∞∞gscπrs2exp ( −u2+v2rs2 ) cos ( ψstim ( u+uj ) −ωstimt ) dudv=gscexp ( −rs2ψstim24 ) cos ( ψstimuj−ωstimt ) # ( 18 ) ( where v is distance perpendicular to u ) which has transform gjs ( x , y ) ⋅S ( ω , x , y ) =πgscexp ( −rs2ψstim24 ) exp ( −iujψstim ) ( δ ( ω−ωstim ) +δ ( ω+ωstim ) ) # ( 19 ) A neuron’s location is defined in the model by the centre of the convergence function that weights its inputs . Off-centre subcortical channels were located at the nodes of a square grid aligned with the visual field patch , with a node at the centre of the patch . Each location was then perturbed with a Gaussian deviate in both the horizontal and vertical directions . Jang and Paik [54] provided evidence for developmental repulsion between on- and off-centre ganglion cells . Accordingly , on-centre channels were distributed similarly to off-centre channels except that the grid was offset: the four nodes closest to the centre of the visual field patch were equidistant from the centre . Cortical neurons were located on an unperturbed grid aligned with the patch , with the central node at the centre of the patch . Both an inhibitory and excitatory neuron were located at each grid node . The model used a retinal ganglion cell map based on the work of Wässle et al . [9] . Fig 10 illustrates two analyses designed to test whether the map we used accurately reproduces the statistics of measured maps . Part A shows the frequency histogram for the distance between nearest on- and off-centre neighbours on the left and right , respectively . Wässle et al . ’s data are shown in red and the model in blue . The widths of the measured and modelled histograms are similar , as required . Part B provides a test for whether the modelled on- and off-centre maps are statistically independent , as defined by Rodieck [55] . Each histogram shows the density of on-centre cells in annuli of the stated distance from reference off-centre cells . Histograms are provided for two random seeds used to generate the maps . For each seed , a linear regression performed on the data showed that there was no linear trend ( seed 1: F ( 1 , 18 ) = 1 . 12 , p = . 30; seed 2: F ( 1 , 18 ) = 0 . 23 , p = . 64 ) . Our modelled maps are therefore consistent with the conclusion of Eglen et al . [56] that on- and off-centre maps are independent outside a small inner area . The development process adjusted the strength of the synapse of each geniculate neuron onto each of its cortical targets . At the start of development all of these synapses were assigned a weight of 1 . For each development cycle a geniculate neuron was selected , with all neurons equally likely to be chosen . All synaptic weights for this neuron were increased by 0 . 2 and the model was stimulated with gratings drifting in 16 directions evenly distributed across the whole range . Each excitatory cortical neuron’s impulse rate was calculated , and if the maximum response increased relative to the previous cycle , the weight increase was retained for that neuron . Otherwise , the weight was reduced by 0 . 2 relative to its value on the previous cycle . Weights were restricted to lie between 0 and 2 . The number of development cycles was determined as follows . Each geniculocortical synapse needed five cycles to change from its starting value to its minimum or maximum . The number of cycles was therefore set at five times the number of geniculate neurons , 5×3281 = 16405 , and rounded to the nearest thousand , 16000 . Figs 2 and 4C show that synaptic strength and response amplitude , respectively , change very little between cycles 10666 and 16000 . Indeed , response amplitude changed by at most 2% between these two cycles . We therefore refer to cycle 16000 as “After development” . Previous work has shown that inhibitory connections mature during visual development [57] . We therefore increased the strength of the synapse of inhibitory neurons onto excitatory neurons during development . All of these synapses had equal strength , which increased linearly with development cycle from 1 to ge . Table 1 provides a glossary of model parameters and their values . The following text describes these parameters and explains how they were set . Fig 6D shows the orientation preference map calculated from the spatial map of subcortical channels . The calculation used the following steps . All simulations were performed in Matlab 2017b ( The MathWorks , Inc ) : the computer code is provided in the Supporting information . Computational errors were reduced by running the model in both the temporal and frequency domains and ensuring that the solutions matched to within round-off error . The model was simulated using an 8°×8° visual field patch but only 6°×6° is displayed , to reduce edge effects . There were 3281 subcortical channels and 6561 excitatory cortical neurons , and therefore 2 . 2×107 geniculocortical weights . The weights were calculated over 16 , 000 development cycles . This calculation , which took 176 machine hours , was performed on the University of Sydney’s high-performance computing cluster , Artemis . We thank the Sydney Informatics Hub for the use of this facility .
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Many neurons in mammalian primary visual cortex are highly selective for the orientation of visual contours and can therefore contribute to object recognition . Orientation selectivity depends on on- and off-centre retinal neurons that respond , respectively , to light and dark . We describe a signal-processing model that includes both subcortical pathways and cortical neurons . The model predicts the preferred orientation of a cortical neuron from the empirically determined spatial layout of retinal cells . Further , the subcortical-to-cortical connections change in strength during visual development , meaning that cortical neurons in the model have orientation selectivity just as precise as real neurons . Our model can therefore explain the origin of orientation selectivity and the way it develops during visual system maturation .
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2019
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A model for the origin and development of visual orientation selectivity
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Unbiased lipidomic approaches have identified impairments in glycerophosphocholine second messenger metabolism in patients with Alzheimer's disease . Specifically , we have shown that amyloid-β42 signals the intraneuronal accumulation of PC ( O-16:0/2:0 ) which is associated with neurotoxicity . Similar to neuronal cells , intracellular accumulation of PC ( O-16:0/2:0 ) is also toxic to Saccharomyces cerevisiae , making yeast an excellent model to decipher the pathological effects of this lipid . We previously reported that phospholipase D , a phosphatidylinositol-4 , 5-bisphosphate ( PtdIns ( 4 , 5 ) P2 ) -binding protein , was relocalized in response to PC ( O-16:0/2:0 ) , suggesting that this neurotoxic lipid may remodel lipid signaling networks . Here we show that PC ( O-16:0/2:0 ) regulates the distribution of the PtdIns ( 4 ) P 5-kinase Mss4 and its product PtdIns ( 4 , 5 ) P2 leading to the formation of invaginations at the plasma membrane ( PM ) . We further demonstrate that the effects of PC ( O-16:0/2:0 ) on the distribution of PM PtdIns ( 4 , 5 ) P2 pools are in part mediated by changes in the biosynthesis of long chain bases ( LCBs ) and ceramides . A combination of genetic , biochemical and cell imaging approaches revealed that PC ( O-16:0/2:0 ) is also a potent inhibitor of signaling through the Target of rampamycin complex 2 ( TORC2 ) . Together , these data provide mechanistic insight into how specific disruptions in phosphocholine second messenger metabolism associated with Alzheimer's disease may trigger larger network-wide disruptions in ceramide and phosphoinositide second messenger biosynthesis and signaling which have been previously implicated in disease progression .
Remodeling of lipid species is required for maintaining normal cellular function and disruptions in lipid homeostasis are believed to contribute to aberrant cellular processes and toxicity associated with specific diseases [1] . Although significant advances have been made in characterizing the changes in lipid composition that occur in pathological conditions , it has proven difficult to connect these changes with relevant signaling networks that regulate cellular growth and viability . This is especially true for Alzheimer's disease ( AD ) for which there is increasing evidence that lipid dyshomeostatsis is playing a central role in the disease progression [2] , [3] . Recent lipidomic studies on both post mortem brain tissue and AD mouse models have not only detected dramatic changes in lipid species of most of the major lipid subclasses including ceramides , cholesterols , sphingolipids , phosphatidic acids and glycerophospholipids , but have also reported the presence of distinct changes between regions of the brain [4] . Although these dramatic alterations in lipid homeostasis correlate with the disease , it is imperative to identify the specific subspecies that are critical in contributing to the AD pathology by identifying their impact on signaling networks , which contribute to cellular toxicity . One lipid metabolite with neurotoxic properties that is of particular interest in AD is 1-O-hexadecyl-2-acetyl-sn-glycerophosphocholine or PC ( O-16:0/2:0 ) , also known as C16:0 Platelet Activating Factor ( PAF ) . We have shown that amyloid-β42 signals the intraneuronal accumulation of PC ( O-16:0/2:0 ) in AD and that this lipid second messenger , in turn , signals tau-hyperphosphorylation and induces caspase-dependent cell death independently of the G-protein coupled PAF receptor ( PAFR ) [5]–[7] . However , the underlying signaling pathways mediating the receptor-independent toxicity of PC ( O-16:0/2:0 ) remain enigmatic . The budding yeast Saccharomyces cerevisiae has been a valuable tool for identifying basic elements of lipid signaling networks associated with diseases as many of the fundamental processes of lipid metabolism and signaling are remarkably well conserved with mammalian cells [8] . Previously we employed a chemical genomic screen to identify signaling networks involved in regulating the receptor independent toxicity of PC ( O-16:0/2:0 ) . Using this approach we identified a conserved role for phospholipase D ( PLD ) ( S . cerevisiae Spo14 ) in buffering against the toxicity of PC ( O-16:0/2:0 ) in both yeast and cultured neuronal cells [9] . We also reported relocalization of GFP-tagged Spo14 to distinct foci juxtaposed to the PM upon PC ( O-16:0/2:0 ) treatment . Since PLD activation and localization depends upon the binding to PtdIns ( 4 , 5 ) P2 [10]–[12] , our findings suggested that the toxic accumulation of PC ( O-16:0/2:0 ) may elicit effects upon signaling networks that regulate the PM distribution of PtdIns ( 4 , 5 ) P2 . Here we provide more precise mechanistic insights by showing that PC ( O-16:0/2:0 ) promotes the redistribution of the sole yeast PtdIns ( 4 ) P-5 kinase , Mss4 , which gives rise to the formation of large invaginations of the PM that we have called PtdIns ( 4 , 5 ) P2-enriched structures ( PES ) . We also show that PC ( O-16:0/2:0 ) remodeling of the PtdIns ( 4 , 5 ) P2 PM pool is associated with the potent inhibition of Tor2 signaling . Consistent with these findings we observed that the effects of PC ( O-16:0/2:0 ) upon Mss4 distribution and PES formation depend on the accumulation of LCBs and ceramides . Together these findings identify a novel signaling network wherein toxic levels of PC ( O-16:0/2:0 ) modulate LCBs and ceramide metabolism , which in turn promotes the redistribution of PM PtdIns ( 4 , 5 ) P2 and the inhibition of Tor2 signaling . Our work provides further information into how the toxic accumulation of PC ( O-16:0/2:0 ) , as observed in AD patients [6] , may impact other lipid signaling networks ( i . e . , ceramide , PtdIns ( 4 , 5 ) P2 ) which have previously been implicated in the progression of this disease [13]–[19] .
We had previously shown that PC ( O-16:0/2:0 ) exposure led to the redistribution of the yeast PLD Spo14 at the PM into discrete foci [9] . As PLD activity is required to buffer the toxic effects of this lipid in both budding yeast and murine N2A neuroblastoma cells [9] , we sought to discern the mechanism underlying the changes in PLD distribution . Since the localization of this enzyme to the PM is dependent upon interactions with PtdIns ( 4 , 5 ) P2 , we examined the effects of PC ( O-16:0/2:0 ) on the distribution of this lipid using a fluorescent probe for PtdIns ( 4 , 5 ) P2 , GFP-2×PHPLCδ ( Fig . 1A ) [12] , [20]–[22] . Similarly to Spo14 , growth in the presence of PC ( O-16:0/2:0 ) resulted in the relocalization of the GFP-tagged reporter construct to distinct membrane associated structures at the PM which we have termed PtdIns ( 4 , 5 ) P2 enriched structures ( PES ) ( Fig . 1A ) . The appearance of the PES was maximal after 15 min of treatment with PC ( O-16:0/2:0 ) and persisted for up to 90 min ( Figure S1 ) . This result was specific for PC ( O-16:0/2:0 ) as all other related lipids , chemicals and conditions examined did not result in PES formation ( Table S1 ) . Furthermore , the distribution of GFP-tagged probes with specificity for additional intracellular phosphoinositides , PtdIns4P ( PHFapp1 ) and PtdIns3P ( PH-FYVEEEA1 ) , were unaltered by PC ( O-16:0/2:0 ) treatment suggesting a specific effect of this lipid on PM PtdIns ( 4 , 5 ) P2 ( Fig . 1B and C ) [20] , [23] . The abundance of PtdIns ( 4 , 5 ) P2 depends upon the opposing actions of Mss4 and multiple PtdIns ( 4 , 5 ) P2 phosphatases including Inp51 , Inp52 and Inp54 ( reviewed in [24] ) . Similar to our previous findings with GFP-tagged Spo14 and GFP-2×PHPLCδ , PC ( O-16:0/2:0 ) treatment resulted in the relocalization of Mss4-GFP to distinct foci within the cell ( Fig . 2A ) . This result suggested that PC ( O-16:0/2:0 ) -induced PES formation requires Mss4 activity . To investigate this possibility , we assessed PC ( O-16:0/2:0 ) -induced PES formation in wild type cells and those carrying a thermosensitive allele of MSS4 ( mss4-102 ) [20] . The reduced levels of PtdIns ( 4 , 5 ) P2 in mss4-102 cells precluded the use of GFP-2×PHPLCδ [20]–[22] . Therefore , changes in the PM structure were visualized using the lipophillic probe FM4-64 , which co-localizes with GFP-2×PHPLCδ following PC ( O-16:0/2:0 ) treatment in wild type cells ( Fig . S2 ) . As expected , both wild type and mss4-102 cells grown at the permissive temperature ( 25 C ) exhibit similar FM4-64 labeling that was restricted to the PM and early endosomes in untreated cells ( Fig . 2B ) . Following treatment with PC ( O-16:0/2:0 ) , structures similar to the PES were observed to form in both strains ( Fig . 2B ) . Growth at the restrictive temperature did not impact PES formation in wild type cells as the formation of these structures was similar to previous results with maximal PES formation evident at 15 min and persisting for at least 60 min ( Fig . 2B and Fig . S2E ) . However , PES formation was reduced in mss4-102 cells at all examined time points ( Fig . 2B and Fig . S2E ) suggesting that Mss4 activity is involved in PES formation . To assess the significance of Mss4-dependent PtdIns ( 4 , 5 ) P2 synthesis in buffering against PC ( O-16:0/2:0 ) toxicity , we examined the growth of strains possessing temperature sensitive alleles of MSS4 ( i . e . mss4-102 ) and the PtdIns 4-kinase STT4 ( i . e . stt4-4 ) [20] , [25] . Both mutant strains displayed increased sensitivity to PC ( O-16:0/2:0 ) compared to the isogenic wild type control whereas overexpressing Mss4 reduced the growth inhibitory effects of PC ( O-16:0/2:0 ) in an otherwise wild type strain ( Fig . 2C and Fig . S2F ) . Furthermore , growth was also impacted by reducing or increasing the cellular PtdIns ( 4 , 5 ) P2 levels through overexpressing or deleting phosphoinositide phosphatases respectively ( Fig . 2D and Fig . S2G–H ) . In particular , overexpression of Inp51 and Inp54 resulted in reduced growth whereas deletion of Inp51 alone improved growth in the presence of PC ( O-16:0/2:0 ) ( Fig . 2D and Fig . S2G ) [24] . Together these results indicate that cellular PtdIns ( 4 , 5 ) P2 and PES formation are important for buffering against the toxic effects of PC ( O-16:0/2:0 ) . We next sought to investigate the cellular processes involved in PES formation . First , we examined the ultrastructure of the PES by electron microscopy ( EM ) . In contrast to those untreated , cells exposed to PC ( O-16:0/2:0 ) displayed large invaginations of the PM , which occasionally appeared as either a transversal cut of the PM invagination or potentially invaginations which have undergone scission and become cytoplasmic ( Fig . 3A–F and Fig . S3A ) . The large invaginations of the PM present in PC ( O-16:0/2:0 ) treated cells are reminiscent of the failed endocytic events that have previously been observed in inp51Δ inp52Δ cells [26]–[28] . The formation of these structures in the inp51Δ inp52Δ mutant is due to increased PtdIns ( 4 , 5 ) P2 levels as a result of reduced cellular PtdIns ( 4 ) P 5-phosphatase activity [28] . This phenomenon requires an intact actin cytoskeleton [28] . In contrast , pretreatment with Latrunculin A ( Lat A ) , an actin depolymerizing agent , did not inhibit PES formation ( Fig . 3G ) and surprisingly we found that PC ( O-16:0/2:0 ) treatment alone resulted in the disruption of the actin cytoskeleton ( Fig . 3H ) . Similarly , deletion of VRP1 , an actin associated protein required for cytoskeletal organization that suppresses the inp51Δ inp52Δ phenotype [29] , did not affect PES formation or PC ( O-16:0/2:0 ) toxicity ( Fig . S3B and C ) . Combined these results strongly suggest that the PC ( O-16:0/2:0 ) -dependent PES is distinct from the previously characterized PM invaginations seen in inp51Δ inp52Δ cells and that the PES formation occurs independently of the actin cytoskeleton . The actin-independency of PES formation could potentially be explained by an unregulated association of endocytic coat complex proteins or impaired exocytic vesicle fusion [30] . However , a RFP-fusion of Chc1 , which associates at the PM independently of actin at sites of clathrin-mediated endocytosis [31] , co-localized with GFP-2×PHPLCδ at the PES in only 3% of cells ( Fig . S3D ) . In addition , the localization of the exocyst component Exo70 was only modestly disrupted upon PC ( O-16:0/2:0 ) treatment ( Fig . S3E ) and both Exo70-GFP or Sec3-GFP exhibited minimal co-localization with the PES marked by FM4-64 ( Fig . S3F ) . These results indicate that the actin-independent events involved in PES formation likely do not involve the aberrant association of endocytic or exocytic proteins with the PM . These findings suggested that Mss4 relocalization is a principal factor in PES formation and that perturbations to PM PtdIns ( 4 , 5 ) P2 distribution are critically involved in regulating the toxic effects of PC ( O-16:0/2:0 ) . How might PC ( O-16:0/2:0 ) disrupt Mss4 localization ? The association of this protein with the PM occurs through poorly defined processes and may involve a combination of protein-protein and lipid-protein interactions [30] , [32] , [33] . Interestingly , the only reported lipid factors mediating Mss4 localization to the PM are PtdIns ( 4 ) P and the complex sphingolipid mannose-inositol-phosphoceramide ( MIPC ) [30] , [33] . Although the role of MIPC was not confirmed by a subsequent study [34] , Gallego and co-workers have shown that Mss4 can bind to dihydrosphingosine-1 phosphate ( DHS-1P ) in vitro and that an extended treatment with an inhibitor of sphingolipid biosynthesis ( myriocin , 2 h ) results in relocalization of Mss4-GFP [32] . These results suggest that changes in sphingolipid levels can impact Mss4 localization . Therefore , we postulated that the biological consequences of PC ( O-16:0/2:0 ) treatment may arise in response to the effects of PC ( O-16:0/2:0 ) on either sphingolipid biosynthesis or catabolism . In agreement with this hypothesis , we observed a global accumulation of LCBs precursors , their phosphorylated derivatives ( LCB-Ps ) , as well as immediate ceramide precursors and metabolites in cells treated with PC ( O-16:0/2:0 ) for 90 min ( Fig . 4A , Dataset 1 and Fig . S4B ) . Furthermore , a modest but significant increase in several unphosphorylated phytosphingosine ( PHS ) and dihydrosphingosine ( DHS ) species is evident at 15 min ( Fig . S4B ) . We also report that these increases were not associated with a decrease in the abundance of complex sphingolipids suggesting that PC ( O-16:0/2:0 ) does not induce their catabolism ( Fig . 4A , Fig . S4D and Dataset S1 ) . In addition , deletion of the S . cerevisiae enzyme required for catabolism of complex sphingolipids , ISC1 , did not impact the effects of PC ( O-16:0/2:0 ) upon cell growth , PES formation or sphingolipid levels indicating that PC ( O-16:0/2:0 ) does not stimulate the breakdown of sphingolipids ( Fig . S4B–D ) . Next , we sought to determine whether PC ( O-16:0/2:0 ) -induced elevation in LCBs and/or ceramide levels contributed to PES formation . First , we directly assessed the effects of ceramide upon PES formation by treating cells with the cell permeable ceramide , Cer ( d18:1/2:0 ) , or a biologically inactive analog , Cer ( d18:0/2:0 ) ( Fig . 4B ) . Treatment with Cer ( d18:1/2:0 ) , but not Cer ( d18:0/2:0 ) resulted in relocalization of PtdIns ( 4 , 5 ) P2 and depolarization of the actin cytoskeleton similar to what is observed upon exposure to PC ( O-16:0/2:0 ) suggesting that elevated ceramide levels are sufficient to induce PES formation ( Fig . 4B ) . To explore the role of PC ( O-16:0/2:0 ) -induced accumulation of LCB and ceramide further , we next investigated the effects of myriocin , an inhibitor of sphingolipid biosynthesis [35] ( Fig . S4A ) , on Mss4-GFP localization in PC ( O-16:0/2:0 ) treated cells ( Fig . 4C and S4A ) . To accomplish this , we first pretreated cells with myriocin for 30 minutes prior to exposing them to PC ( O-16:0/2:0 ) . Although longer exposure ( 2 h ) to myriocin has been reported to impact Mss4-GFP localization [32] , our short pretreatment with myriocin did not affect Mss4-GFP localization ( Fig . 4C ) . Pretreatment with myriocin for this time period was sufficient to inhibit the relocalization of Mss4-GFP and PES formation induced by PC ( O-16:0/2:0 ) ( Fig . 4C and Fig . S4F ) . Combined , these results support the notion that PC ( O-16:0/2:0 ) treatment promotes the accumulation of LCBs and ceramides , which in turn contribute to changes in the subcellular localization of Mss4-GFP , PtdIns ( 4 , 5 ) P2 and downstream signaling events including actin cytoskeleton polarization . We next sought to identify relevant signaling pathways which might be impacted by the effects of PC ( O-16:0/2:0 ) upon sphingolipid metabolism and PM PtdIns ( 4 , 5 ) P2 localization . The target of rapamycin complex 2 ( TORC2 ) was identified as a potential target because of its localization to the PM and the responsiveness of this signaling complex to changes in sphingolipid biosynthesis [36]–[38] . Furthermore , TORC2 has an established role in maintaining actin cytoskeleton polarization which is dependent upon the PM recruitment and phosphorylation of the homologous kinases Ypk1 and Ypk2 by the PtdIns ( 4 , 5 ) P2 binding proteins Slm1 and Slm2 [39] , [40] . Utilizing a phospho-specific antibody recognizing a TORC2-dependent phosphorylation site on Ypk1 ( T662 ) we determined that phosphorylation of endogenous Ypk1 was reduced in PC ( O-16:0/2:0 ) suggesting that TORC2 signaling is inhibited by PC ( O-16:0/2:0 ) ( Fig . 5A ) [37] . Similar to mammalian cells , two distinct multiprotein complexes containing Tor activity , i . e . TORC1 and TORC2 , are present in yeast . Unlike mammalian cells , however , yeast possess two TOR genes , TOR1 and TOR2 , with Tor1 nucleating the formation of TORC1 while Tor2 is able to nucleate both TORC1 and TORC2 [41] . Given that the phosphorylation of the TORC2 target Ypk1 is potently inhibited by PC ( O-16:0/2:0 ) , we next sought to determine whether Tor2 activity is required for preventing the growth inhibitory effects of PC ( O-16:0/2:0 ) . To assess the relative role of each Tor protein in buffering the growth inhibitory effects of PC ( O-16:0/2:0 ) , we made use of strains harboring the temperature sensitive tor2-21 and tor2-30 alleles alone or in combination with deletion of TOR1 [42] . Whereas deletion of TOR1 alone had no observable effect upon PC ( O-16:0/2:0 ) sensitivity ( Fig . 5B ) , the tor2-21 strain exhibited a significant reduction in growth in the presence of PC ( O-16:0/2:0 ) at a semi-permissive temperature . To further validate the role of TORC2 signaling in mediating PC ( O-16:0/2:0 ) sensitivity we examined the effect of overexpressing the downstream target YPK2 [40] . Consistent with a role for TORC2 in mediating the response to PC ( O-16:0/2:0 ) , we found that overexpression of a YPK2 hyperactive allele ( D239A ) , known to rescue lethality of TORC2 mutants [40] , was able to restore growth of the tor2-21 strain in the presence of PC ( O-16:0/2:0 ) . Comparatively , the wild type ( Ypk2 ) and the kinase dead ( K373A ) variants [40] were unable to restore growth in the presence of reduced Tor2 function ( Fig . 5C ) . Together , these results provide compelling evidence that TORC2 is inhibited in response to PC ( O-16:0/2:0 ) treatment and that a reduction in TORC2 signaling is associated with an increased sensitivity to PC ( O-16:0/2:0 ) . Since these results establish an important role for the TORC2-Ypk2 signaling in mediating the cellular response to PC ( O-16:0/2:0 ) , we investigated the potential mechanisms by which PC ( O-16:0/2:0 ) might act to inhibit TORC2-dependent phosphorylation of Ypk1/2 . The requirement for PtdIns ( 4 , 5 ) P2 , PLD and Tor signaling in mediating PC ( O-16:0/2:0 ) sensitivity presented the intriguing possibility that PLD-generated PA regulates Tor signaling in S . cerevisiae as previously reported for mTor [43]–[46] . However , deletion of SPO14 , did not have noticeable effected the phosphorylation of endogenous Ypk1 suggesting that Spo14 does not impact TORC2 function in S . cerevisiae ( Fig . 5A ) . Furthermore , knock out of SPO14 exhibited a synthetic interaction with the tor2-21 allele ( Fig . S5 ) . These results indicate that Spo14 and Tor2 likely act through parallel signaling pathways . Alternatively , the inhibition of Ypk1 phosphorylation in PC ( O-16:0/2:0 ) -treated cells may be due to the direct inhibition of Tor kinase activity as was previously reported for cells with elevated glycerophosphocholine levels [47] . PC ( O-16:0/2:0 ) , however , did not inhibit the phosphorylation of recombinant GST-Ypk2 by immunopurified TORC2 suggesting PC ( O-16:0/2:0 ) does not act as a direct inhibitor of Tor function in vitro and that a secondary mediator is required ( Fig . S6A ) . Given that Ypk1/2 and TORC2 are normally localized to distinct subcellular compartments , however , the in vitro kinase assay likely does not fully recapitulate the constraints present in vivo . For example , phosphorylation of Ypk1/2 requires relocalization from the cytosol to the PM by TORC2 adaptor proteins Slm1/2 [48] . Interestingly , localization of Slm1/2 at the PM is itself partly dependent upon interactions with PtdIns ( 4 , 5 ) P2 [21] , [34] , [48] . We observed that PC ( O-16:0/2:0 ) treatment disrupted the typical association of Slm1-GFP with eisosomes , a distinct spatially segregated compartment of the PM in S . cerevisiae [49] , as indicated by the reduction in co-localization of Slm1-GFP with a tagged eisosome protein , Lsp1-mCherry ( Fig . 6A ) . This redistribution of Slm1-GFP was not due to disruption of eisosome integrity but was associated with its appearance at the PES ( Fig . S6B–D ) . Furthermore overexpression of Slm1 from a high copy plasmid enhanced growth compared to vector alone suggesting that Slm1-dependent signaling events are critically involved in mediating the cellular response to PC ( O-16:0/2:0 ) ( Fig . S6E ) . The correlation of Slm1 relocalization with increased LCBs and ceramides ( Fig . 4 and S4 ) in PC ( O-16:0/2:0 ) -treated cells is complementary with a previous report describing the impact of inhibiting sphingolpid metabolism upon the subcellular localization of Slm1 and Ypk1 phosphorylation [37] . Therefore , we next sought to investigate whether the relocalization of Slm1-GFP in PC ( O-16:0/2:0 ) impaired the interaction of Ypk1 or TORC2 . However , we found that the association of Slm1-GFP with HA-tagged TORC2 component Avo3 or untagged Ypk1 was not affected by PC ( O-16:0/2:0 ) treatment suggesting the inhibition of TORC2 signaling does not require the redistribution of Slm1 to the PES ( Fig . 6B ) . To support this conclusion we next investigated whether PES formation was necessary for the PC ( O-16:0/2:0 ) -dependent inhibition of Ypk1 phosphorylation ( Fig . 6C ) . Although pretreatment with myriocin alone increased Ypk1 phosphorylation ∼2 . 3 fold we observed that phosphorylation was similarly reduced ( ∼50% ) in cells pretreated with either vehicle or myriocin upon treatment with PC ( O-16:0/2:0 ) ( Fig . 6C ) . Therefore , the inhibition of TORC2-dependent Ypk1 phosphorylation by PC ( O-16:0/2:0 ) likely does not require the recruitment of Slm1 to the PES or a reduced interaction of Ypk1 with Slm1 or Avo3 , indicating PC ( O-16:0/2:0 ) inhibiting TORC2 through an previously undescribed mechanism .
Aberrant glycerophosphocholine metabolism in AD leading to the intraneuronal accumulation of specific lipid second messengers , including PC ( O-16:0/2:0 ) is linked to neuronal dysfunction , neurotoxicity , and accelerated cognitive decline [6] , [50]–[52] . In this report we have used S . cerevisiae to further characterize the mechanisms underlying receptor-independent toxicity of PC ( O-16:0/2:0 ) . Our work suggests a model ( Fig . 7 ) wherein exposure to toxic concentrations of PC ( O-16:0/2:0 ) promotes the accumulation of LCBs and ceramides , which leads to changes in the subcellular localization of Mss4 and formation of PtdIns ( 4 , 5 ) P2 enriched invaginations of the PM . Ultimately the PC ( O-16:0/2:0 ) -dependent remodeling of PtdIns ( 4 , 5 ) P2 affects downstream PtdIns ( 4 , 5 ) P2-dependent cellular processes such as PLD localization , which is critical for buffering against the toxic effects of PC ( O-16:0/2:0 ) [9] . However , the inhibition of TORC2 by PC ( O-16:0/2:0 ) also suggests that the toxic properties of PC ( O-16:0/2:0 ) are only partly due to disruptions in PtdIns ( 4 , 5 ) P2 signaling and that this lipid impacts other signaling pathways through distinct second messengers that remain to be identified . Given that PtdIns ( 4 , 5 ) P2 and downstream signaling events buffer against PC ( O-16:0/2:0 ) toxicity , it was important to investigate the factors underlying the relocalization of Mss4-GFP and PES formation to elucidate potential endogenous mechanisms of neuroprotection . The molecular details that contribute to the localization of Mss4 into distinct phosphatidylinositol kinase or PIK patches in yeast are not completely understood . However , the availability of its substrate , PtdIns ( 4 ) P , a recently identified interacting partner Opy1 and sphingolipid biosynthesis have been implicated [30] , [32] , [33] . Our data suggests that the PC ( O-16:0/2:0 ) -induced accumulation of LCBs and ceramides ( precursor molecules in the sphingolipid biosynthetic pathway Fig . S4 ) are at least partly responsible for the changes in PM PtdIns ( 4 , 5 ) P2 distribution as treatment with myriocin , an inhibitor of sphingolipid biosynthesis , was sufficient to prevent the redistribution of Mss4-GFP and PES formation ( Fig . 4 and Fig . S4 ) . The mechanism by which the observed changes in LCBs and ceramide might regulate Mss4 PM localization are not clear but previous reports have suggested that both MIPC and dihydrosphingosine-1 phosphate ( DHS-1P ) can interact with Mss4 [32] , [33] . The relocalization of Mss4-GFP , however , is likely not due to interactions with MIPC as neither the total levels of this lipid nor the abundance of individual species was significantly impacted by PC ( O-16:0/2:0 ) at any time point ( Fig . 4 , Fig . S4 and Dataset 1 ) . In contrast , the accumulation of one DHS and two PHS species displayed similar kinetics to the PtdIns ( 4 , 5 ) P2 redistribution and PES formation suggesting that these lipids may be involved in mediating the observed changes ( Fig . S4B and Dataset 1 ) . Certainly , this observation must be interpreted with caution as the reported in vitro interaction between Mss4 and LCBs has not been evaluated in vivo [32] . Furthermore , the role of LCB-Ps in mediating Mss4 localization at the PM must also be reconciled with the fact that LCB-Ps do not appear to be trafficked to the PM under normal circumstances [53] . Whether PC ( O-16:0/2:0 ) -induced changes in Mss4-GFP localization are dependent upon the improper trafficking of LCB-Ps or another mechanism remains an open question in need of further study . The spatial distribution of PtdIns ( 4 , 5 ) P2 at the PM is critical for regulating the activity of downstream signaling pathways . Our biochemical , genetic and cell biology based-assays suggest that the inhibition of Tor signaling plays a critical role in mediating the sensitivity to the toxic effects of PC ( O-16:0/2:0 ) ( Fig . 5 and 6 ) . The results of our in vitro kinase assay do not identify PC ( O-16:0/2:0 ) as a direct inhibitor of Tor kinase activity and suggests that another mechanism is responsible for the inhibition of Tor signaling ( Fig . S6 ) . How else might PC ( O-16:0/2:0 ) inhibit Tor signaling ? Although the cellular inputs which impinge upon Tor signaling are still being identified and the molecular mechanisms which translate these stimuli into activation/inhibition of Tor signaling are not completely understood , the TORC2-dependent phosphorylation of Ypk1/2 is sensitive to changes in PM PtdIns ( 4 , 5 ) P2 levels [48] . Our work demonstrating the relocalization of Slm1-GFP to the PES in response to PC ( O-16:0/2:0 ) is consistent with previous reports describing the interactions of Slm proteins with PtdIns ( 4 , 5 ) P2 ( Fig . 6 and S6 ) [1] , [20] . Because our data indicate that relocalization of Slm1 , and presumably Slm2 , to the PES is not required for the inhibition of TORC2-dependent Ypk phosphorylation , they suggest that an additional mechanism ( s ) exists for the regulation of TORC2 signaling ( Fig . 6 ) . Collectively , our results provide insight into how a disruption in phosphocholine metabolism signals network-wide lipid metabolic disturbances that may play defining roles into how neurons respond to accumulating Aβ42 . Interestingly , accumulating evidence suggests that disruptions in both PtdIns ( 4 , 5 ) P2 signaling and ceramide metabolism are contributing factors in the neuronal cell dysfunction and death observed in AD [13]–[19] . Whether the disruptions in PtdIns ( 4 , 5 ) P2 signaling and ceramide metabolism homeostasis observed in neurons are dependent upon an increase in PC ( O-16:0/2:0 ) concentrations is an intriguing question in need of further investigation .
The yeast strains and plasmids used in this study are listed in Table S2 and S3 . Strains were generated by using a standard PCR-mediated gene insertion/deletion technique [54] . Cells were grown in standard YPD or SD medium supplemented with amino acids and all lipids were prepared by resuspending in either ethanol or methanol and storing under nitrogen gas . All strains were grown in YPD or minimal media supplemented with appropriate amino acids as required and treated with PC ( O-16:0/2:0 ) ( Enzo Life Sciences , BML-L100 or Avanti Polar Lipids , 878119P ) at 20 µM for 15 minutes unless indicated otherwise . Media was supplemented with rapamycin ( 200 ng/ml ) where indicated . Cells were grown in YPD or minimal media at 30 C to mid-log phase and resuspended to an OD600 of 0 . 1 . Dot assays were performed by spotting 4 µL of ten-fold serial dilutions ( OD600 = 0 . 1 , 0 . 01 , 0 . 001 , 0 . 0001 ) onto YPD or minimal media selection plates containing the specified concentrations of ethanol , PC ( O-16:0/2:0 ) or other chemical as indicated . For all microscopy experiments , overnight cultures grown at 30 C in YPD medium were re-suspended at a final OD600 of 0 . 2 and allowed to reach mid-log phase prior treatment and image acquisition . Live cell imaging was performed by briefly centrifuging the cells ( 800 g for 3 min ) , followed by resuspending in a minimal volume of growth media , spotting onto glass slides and coverslipping prior to imaging . All images were acquired using a Leica DMI 6000 florescent microscope ( Leica Microsystems GmbH , Wetzler Germany ) , equipped with a Sutter DG4 light source ( Sutter Instruments , California , USA ) , Ludl emission filter wheel with Chroma band pass emission filters ( Ludl Electronic Products Ltd . , NY , USA ) and Hamamatsu Orca AG camera ( Hamamatsu Photonics , Herrsching am Ammersee , Germany ) . Images were acquired at 0 . 2 µM steps using a 63× oil-immersion objective with a 1 . 4 numerical aperture . Deconvolution and analysis were performed using Velocity Software V4 ( Perkin Elmer ) . For most images , representative images of the middle section and compressed image stack are shown . Numerical insets represent the indicated quantifications of at least 100 cells from 2 to 3 independent experiments unless indicated otherwise . Early log phase cells were fixed by diluting 37% formaldehyde to a final concentration of 3 . 7% and incubating at 25 C for 10 minutes . Cells were subsequently pelleted ( 800 g for 3 min ) and resuspended in PBS containing 3 . 7% formaldehyde and incubated for 1 hour . Cells were subsequently washed three times in PBS prior to staining with Rhodamine-conjugated phalloidin diluted in PBS containing 0 . 1% Tween on ice ( 20 Units/ml , Invitrogen ) and cells were washed two times prior to imaging . For actin depolymerisation , Latrunculin A ( 5 µM , Tocris ) was added as indicated prior to fixation and cell staining . In all cases overnight cultures of yeast strains were diluted to an OD600 of 0 . 2 in YPD or appropriate minimal media and allowed to reach mid-log growth prior to harvesting . Cell pellets were resuspended in 200 µL of lysis buffer ( 20 mM HEPES , 150 mM NaCl , 2 mM EDTA with phosphatase and protease inhibitors and lysed by vortexing with glass beads . Ypk1 was examined in ethanol and PC ( O-16:0/2:0 ) treated cells prepared as previously described [37] . Briefly , ice cold acetone was added to mid log phase cells and incubate on ice for 5 min . Cells were pelleted and washed two times in 5% acetone in PBS . Supernatant was removed and the cells pellets were dried under vacuum prior to lysis in urea buffer . Processing for electron microscopy was performed as previously described [55] . TORC2 was purified from RL127-1c cells . The cultures were grown to an OD600 of 5 . 0 in YPD ( 125 mL per assay point ) , chilled on ice for 30 minutes , collected , and washed . The cells were put into liquid nitrogen and ground up using a mortar and pestle . The powder was then resuspended in lysis buffer ( 1× Roche protease inhibitor +EDTA , 1 mM PMSF , phosphatase inhibitors , 5 mM CHAPS , 50 mM HEPES pH 7 . 5 , 300 mM KCl ) , spun down , and 420 ul of prepared paramagnetic beads ( Dynabeads M-270 Epoxy , coated with rabbit IgG; Sigma ) were added to the cleared protein extracts . The tubes were subsequently rotated for 3 h at 4°C . Beads were collected by using a magnet and washed extensively with lysis buffer . The kinase reactions were performed in a final volume of 30 µl containing TORC2-coupled beads , 300 ng of Ypk2 , 25 mM Hepes pH 7 . 0 , 50 mM KCl , 4 mM MgCl2 , 10 mM DTT , 0 . 5% Tween20 , 1× Roche protease inhibitor-EDTA , 100 mM ATP , 5 mCi [γ-32P]-ATP and 1 µl of inhibitors at various concentrations . PAF was dissolved in EtOH and used at the indicated concentrations . Assays were started with addition of ATP , maintained at 30°C for 25 minutes and terminated by the addition of 7 . 5 µl of 5× SDS-PAGE buffer . Samples were heated at 65°C for 10 min; proteins were resolved in SDS-PAGE , stained with Sypro Ruby and analysed using a Bio-Rad Molecular Imager . GST-Ypk2 fusion proteins were expressed in S . cerevisiae from a pRS426 vector . Actively growing cells were induced for 3 hours with galactose ( final concentration of 2% ) , chilled on ice for 30 minutes , and collected . The cells were put into liquid nitrogen and ground up using a mortar and pestle . The powder was then resuspended in lysis buffer ( 10% glycerol , 1×PBS , 0 . 5% Tween , 1× Roche protease inhibitor +EDTA , 1 mM PMSF , and phosphatase inhibitors ) and the fusion protein was bound to and eluted from glutathione Sepharose 4B ( GE Healthcare ) following standard procedures . The supernatant was dialyzed against ( 50% glycerol , 1 mM DTT , 1 mM EDTA , 25 mM Tris pH 7 . 5 , 50 mM NaCl ) , aliquotted , and frozen at −20°C . Cells at 0 . 6 OD600 were treated with 20 µM PAF or ethanol as a control . At T = 15 min , 30 min , 60 min and 120 min , 7 . 5 OD600 were harvested in glass tubes , washed with water and the pellet was extracted 3×1 ml in water∶Ethanol∶Diethyl Ether∶Pyridine∶NH4OH ( 15∶15∶5∶1∶0 . 018 ) at 65°C for 15 min each time . Avanti Polar Lipid MS standards ( LM-6002 ) were added during the first extraction at 62 . 5 pmol/tube . The extracts were pooled and dried under N2 , redissolved in 1 ml Chloroform with bath sonication , 1 ml Butanol was added and phospholipids were hydrolyzed for 30 min at 37°C after the addition of 200 µL 1 M KOH ( in methanol ) . After hydrolysis , the extract was neutralized by the addition of 200 µL 1 M Acetic Acid ( in Methanol ) . 1 ml Butanol saturated water was added , centrifuged to separate the phases and the upper aqueous layer was removed by aspiration , being careful not to disrupt the precipitate at the interface . This was repeated two more times after which the remaining lower phase was dried under N2 . The dried lipid was redissolved in 0 . 5 ml LC/MS buffer A with bath sonication , spun to pellet insoluble material and the transferred to MS analysis vials . The samples were analyzed on a Supelco Discovery Bio Wide Pore C18 ( 5 cm×2 . 1 mm , 5 uM ) column at 40°C ( 50 mm ) using an Agilent 1200 Series HPLC coupled to ABSciex QTRAP 4000 MS . The LCB ( P ) s were eluted using a binary solvent gradient of 0% B for 1 min , 25% at 4 min , 100% at 4 . 5 min and held at 100%B for 1 . 5 min , 0%B at 7 min . The LCB ( P ) s were detected in MRM mode , MS buffer A: Tetrahydrofuran: Methanol: 10 mM Ammonium Formate ( 30∶20∶50 ) with 0 . 2% Formic Acid MS buffer B: Tetrahydrofuran: Methanol: 10 mM Ammonium Formate ( 70∶20∶10 ) with 0 . 2% Formic Acid
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Accelerated cognitive decline in Alzheimer's patients is associated with distinct changes in the abundance of choline-containing lipids belonging to the platelet activating factor family . In particular , PC ( O-16:0/2:0 ) or C16:0 platelet activating factor ( PAF ) , is specifically elevated in brains of Alzheimer's patients . Since elevated intraneuronal levels of PC ( O-16:0/2:0 ) are thought to contribute to the loss of neuronal cells it is imperative to identify the underlying mechanisms contributing to the toxic effects of PC ( O-16:0/2:0 ) . In this study , we have determined that elevated levels of PC ( O-16:0/2:0 ) has negative effects upon the distribution of phosphoinositides at the plasma membrane leading to a potent inhibition of target of rapamycin ( TOR ) signaling . We further show that the changes in phosphoinositide distribution are due to changes in ceramide metabolism . In conclusion , our study suggests that the toxicity associated with aberrant metabolism of glycerophosphocholine lipids species is likely due to the remodeling of phosphoinositide and ceramide metabolism and that therapeutic strategies which target these disruptions may be effective in ameliorating Alzheimer's Disease pathology .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"molecular",
"cell",
"biology",
"neuroscience",
"biochemistry",
"biology"
] |
2014
|
A Neurotoxic Glycerophosphocholine Impacts PtdIns-4, 5-Bisphosphate and TORC2 Signaling by Altering Ceramide Biosynthesis in Yeast
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The structure of the infectious prion protein ( PrPSc ) , which is responsible for Creutzfeldt-Jakob disease in humans and bovine spongiform encephalopathy , has escaped all attempts at elucidation due to its insolubility and propensity to aggregate . PrPSc replicates by converting the non-infectious , cellular prion protein ( PrPC ) into the misfolded , infectious conformer through an unknown mechanism . PrPSc and its N-terminally truncated variant , PrP 27–30 , aggregate into amorphous aggregates , 2D crystals , and amyloid fibrils . The structure of these infectious conformers is essential to understanding prion replication and the development of structure-based therapeutic interventions . Here we used the repetitive organization inherent to GPI-anchorless PrP 27–30 amyloid fibrils to analyze their structure via electron cryomicroscopy . Fourier-transform analyses of averaged fibril segments indicate a repeating unit of 19 . 1 Å . 3D reconstructions of these fibrils revealed two distinct protofilaments , and , together with a molecular volume of 18 , 990 Å3 , predicted the height of each PrP 27–30 molecule as ~17 . 7 Å . Together , the data indicate a four-rung β-solenoid structure as a key feature for the architecture of infectious mammalian prions . Furthermore , they allow to formulate a molecular mechanism for the replication of prions . Knowledge of the prion structure will provide important insights into the self-propagation mechanisms of protein misfolding .
Little is known about the structure of the infectious prion protein , the infectious agent causing prion diseases such as sheep and goat scrapie , bovine spongiform encephalopathy or “mad cow disease” , chronic wasting disease in cervids ( deer , elk , moose , and reindeer ) , and Creutzfeldt-Jakob disease in humans . The structure of these infectious conformers is essential to understanding prion replication and the development of structure-based therapeutic interventions . The non-infectious , cellular prion protein ( PrPC ) , which has its highest expression levels in neurons , is misfolded through a posttranslational process into an altered , infectious conformer termed PrPSc or prion [1] . The structure of recombinant PrP , which approximates the structure of PrPC , has been solved repeatedly by NMR spectroscopy [2] and X-ray crystallography [3] . PrPC consists of an unfolded N-terminal domain and a largely α-helical C-terminal domain , which contains three α-helices and a short , two-stranded ß-sheet [2 , 3] . In contrast , PrPSc has been found by a variety of methods to contain predominantly ß-sheet structure [4] . PrPSc and its N-terminally truncated variant , PrP 27–30 , are generally insoluble and prone to aggregation into an assortment of quaternary structures , such as amorphous aggregates , 2D crystals , and amyloid fibrils . None of these aggregation products are amenable to conventional structural analysis techniques such as X-ray crystallography or solution NMR spectroscopy . To overcome the paucity of experimental data on the structure of the infectious prion , molecular modeling has been used by a variety of researchers to predict its structure . Little agreement exists among the published molecular models regarding the nature of the infectious conformer and a large range of different folds have been put forward [5] , with the most recent entry proposing a parallel in-register ß-sheeted structure [6] . While none of the published models satisfy all experimental restraints [5] , a ß-helical architecture has been suggested as a likely candidate for the structure of the infectious prion [7 , 8] . To investigate the structure of the infectious prion , we used electron cryomicroscopy ( cryo-EM ) to record and analyze the structure of brain-derived , murine prion protein amyloid . Brain-derived PrPSc has a high level of molecular heterogeneity due to its GPI-anchor and N-linked carbohydrates , which increases the difficulty to analyze its structure considerably . On the other hand , brain-derived PrPSc , as the disease-relevant conformer , can provide insights into the infectious state , which the more well-behaved , recombinantly-derived PrP amyloid , cannot [9] . By using transgenic mice expressing a GPI-anchorless form of the prion protein , which is also substantially underglycosylated [10] , a more homogeneous version of the prion protein could be analyzed . GPI-anchorless PrPSc is deposited predominantly as large fibrillar amyloid plaques , which allows for a milder purification procedure compared to traditional purification approaches [11] . In prion-infected mice expressing GPI-anchorless PrP , PrPSc retains its full infectivity , while the neuropathology is similar to a cerebral amyloid angiopathy ( CAA ) as seen in Alzheimer’s disease [12] and hereditary prion protein amyloidosis [13 , 14] . This difference in apparent neuropathology is not surprising given that infectivity and toxicity of PrPSc are not unequivocally linked [15] . After all , GPI-anchorless PrPSc cannot attach to the cell membrane , and therefore exhibits a different cellular and tissue distribution . Nonetheless , the homogeneous preparation of GPI-anchorless , infectious prions facilitated novel insights into the structure of PrPSc by cryo-EM .
GPI-anchorless PrP 27–30 , which , for consistency , is named according to the molecular weight of GPI-anchored PrP 27–30 , was purified from the brains of transgenic mice expressing GPI-anchorless PrP that were infected with prions of the Rocky Mountain Laboratory ( RML ) strain [10 , 16] . The purification procedure took advantage of both the in vivo formed amyloid fibrils of GPI-anchorless PrPSc and their partial resistance against Proteinase K ( PK ) digestion . Limited proteolysis of GPI-anchorless PrPSc , similar to the digestion of GPI-anchored PrPSc , removes just the first ~66 N-terminal residues , leaving a ~17 kDa PK-resistant , GPI-anchorless , unglycosylated fragment , and a very modest amount of monoglycosylated protein [10 , 17 , 18] ( Fig 1A and 1B ) . To verify that the purified GPI-anchorless PrP 27–30 preparations were still infectious , as reported by others , we inoculated a cohort of wild-type mice with the purified prions . All animals developed the typical neurological signs of RML-prion disease . Furthermore , biochemical and histopathological analyses demonstrated that the brains of infected mice showed all hallmarks of pathogenic prion disease , for example partial PK-resistance , presence of vacuolation , gliosis , and PrPSc deposition in the brain tissue ( Figs 1B and 2 ) . The observed , moderately-extended incubation period compared to animals inoculated with untreated brain homogenate ( Fig 1C ) is compatible with the use of PK treatment , which is known to degrade PrPC and PK-sensitive forms of PrPSc , thereby reducing the apparent prion titer [19 , 20] . In addition , the highly aggregated nature of the purified prions is also known to lower the effective prion titer [21 , 22] . The cryo-EM images from GPI-anchorless PrP 27–30 fibrils were examined in detail . Images showed fibrils ~10 nm wide , composed by two intertwined , twisting protofilaments , with a space between them ( Figs 3 , 4 and S1 ) . A clearer view of the fibrils was obtained in 3D tomograms ( S1 Video and S2 Fig ) , which allowed a more facile visualization of individual fibrils . Separate fibrils were found to display either a left- or right-handed twist , or to be essentially straight . This apparent variability with respect to the fibril helicity of GPI-anchorless fibrils had been observed before in negatively stained sample preparations [17] . Reconstructed tomograms allowed measurement of fibril widths , which were confirmed to be 9 . 55 ± 1 . 15 nm ( standard deviation; n = 261 ) ( S1 Fig ) . The limited dispersion of the values is similar to that of other amyloids [24] . The raw images contain high-resolution information , as surmised from Fourier-transform analyses routinely showing a 4 . 8 Å cross-β signal for individual fibrils along their axis ( Fig 3 ) that can be readily interpreted as originating from β-strands running perpendicular to the fibril axis . It is notable that the orientation of the cross-β signal is strictly dependent on the orientation of the individual amyloid fibrils , which proves its origin ( Fig 3 , black and white arrows ) . Furthermore , Fourier-transform analyses of nearby empty areas of ice or carbon film never showed a 4 . 8 Å signal ( Fig 3 , dotted boxes ) , indicating that the 4 . 8 Å signal is indeed a cross-β signal similar to what was seen in X-ray fiber diffraction from PrP 27–30 [25] . In fact , to our knowledge , this is the first time that electron cryomicroscopy and the use of a second generation direct electron detector ( Falcon II ) has allowed to detect the 4 . 8 Å cross-β signal in Fourier-transform analyses of otherwise unprocessed cryo low-dose electron micrographs of individual amyloid fibrils or small bundles of fibrils . Encouraged by this , we set out to extract as much additional structural information from the images as possible . In particular , we aimed at identifying the individual PrP subunits stacked in each protofilament . Unfortunately , fibrils were highly aggregated and did not display a constant helical periodicity . This impeded the use of the iterative helical real-space reconstruction ( IHRSR ) algorithm , which has frequently been used to process electron micrographs of amyloid fibrils to obtain high-resolution structural information [26] . Instead , we applied two single particle approaches to analyze a large number of short fibril segments from high magnification electron micrographs . In the first single particle analysis approach , cryo-EM images were selected that presented clear Thon rings to enable correction of the contrast transfer function ( CTF ) . In total , we extracted 1305 non-overlapping isolated fibril segments that were then aligned , classified , and averaged ( S3 Fig ) . An averaged power spectrum of 1072 aligned segments showed a 4 . 8 Å intensity ( Figs 5A and S4 ) , characteristic of the cross-β structure of amyloid fibrils , also detected in many raw images ( vide supra ) . The arc-shape of the 4 . 8 Å signal was indicative of an imperfect alignment of the fibrils . To overcome this problem , we analyzed each of the protofilaments that make up the fibril individually , which revealed 19 . 1 Å and ~40 Å signals upon Fourier-transform analysis ( Figs 5A , S4 and S5 ) . These spacings correspond to 4 and 8 multiples of 4 . 8 Å β-strands , and indicate the existence of a structural subunit with a height of 4 β-strands , that associates vertically with another subunit to form a higher order dimeric structure . Another feature , the absence of a strong ~10 Å signal on the equator of the Fourier-transforms ( Figs 5A and S5 ) , is generally interpreted to indicate the presence of β-helical and β-solenoidal structures [25 , 27] . The ~10 Å signal is commonly seen with stacked β-sheet structures such as Aβ ( 1–40 ) amyloid [28] , and given the fact that our electron micrographs readily display the 4 . 8 Å cross-β signal in Fourier-transform analyses of individual fibrils ( Fig 3 ) , the ~10 Å signal could be expected if a stacked β-structure were present . Therefore , the most parsimonious explanation of this spacing hierarchy is the presence of a 4-rung β-solenoid as the basic subunit along the protofilament axis . In an alternative reference-free single particle approach , we selected 2725 fibril segments from individual protofilaments , and performed eigenvector data compression and unsupervised automatic classification ( Fig 5B ) . This analysis was performed without alignments and thereby avoiding reference bias ( see materials and method for details and S6 Fig ) . The average of the amplitude spectra of all 20 classes ( Fig 5B ) revealed peaks at ~20 Å and ~40 Å ( Fig 5D ) , in good agreement with the first approach . Furthermore , individual class averages ( Fig 5B ) showed distinct densities along the fibril axis with an average height of ~20 Å ( Fig 5C ) , corroborating the other measurements . Considering all this , we reasoned that the volumetric information provided by individual fibrils should provide an independent assessment of the conclusion that GPI-anchorless subunits are ~20 Å "tall" . We picked isolated fibrils with images clearly showing a crossover point and covering at least one half turn ( 180° ) without overlap to other fibrils . Given the already mentioned extensive clumping of the fibrils , which showed a high degree of lateral aggregation and , most of the times , overlapped with neighboring fibrils , only a few fibrils meeting these visual requirements were selected ( Figs 4 and S1 ) . Based on their morphology and dimensions , these fibrils are representative of the majority of specimens seen in the micrographs , and no bias , other than the mentioned selection requirements , took place to choose them . We then generated 3D reconstructions of these fibrils , taking advantage of the fact that the 2D image of a helical object contains rotated projections of its 3D surface . Thus , we segmented the isolated fibrils into overlapping boxes along the helical axis and analyzed the fibril segments as single objects . Each box is a different view of identically the same fibril rotated around and translated along the helical axis [29] . By measuring the helical repeat distance of the fibril ( images shown in Fig 4 ) we could estimate the angular orientation of each box in the set ( S7 and S8 Figs ) . The 3D reconstruction of one of these individual GPI-anchorless PrP 27–30 fibrils , with a maximum width of 9 . 1 nm and a crossover distance of 95 nm , showed two approximately 50 x 29 Å oval-shaped protofilaments ( Fig 6 ) . Fibril reconstruction statistics are listed in S1 Table . The density profile of the cross-section suggested several densities distributed within the core of the protofilament ( Fig 6F ) , compatible with a ß-helical or ß-solenoidal fold and similar to what has been seen in the cross-section of the fungal HET-s prion [30] . The 3D reconstructions of the other isolated GPI-anchorless PrP 27–30 fibrils also contained two protofilaments twisting about the fibril axis ( S9 Fig ) . While the general shape and features of protofilaments were remarkably consistent , the four fibrils were structurally heterogeneous with respect to the protofilament orientation ( Fig 7 ) , their widths ( 9 . 5 nm , 9 . 4 nm , and 8 . 7 nm ) and crossover distances ( 76 nm , 67 nm , and 98 nm ) , which is a common hallmark of amyloid fibrils [31 , 32] , but is also likely to be a reflection of analytical variability , indicating the resolution limitations of our approach . However , the level of resolution attained in these 3D reconstructions allowed us to calculate the average height of a GPI-anchorless PrP 27–30 monomer within each protofilament . The average protein density has been estimated to be 0 . 8129 Da/Å3 [31 , 33] . However , considering that a highly compact amyloid might have a slightly different density value , we calculated the density value of a HET-s monomer stacked in a HET-s prion fibril ( [30] PDB: EMD-2946 ) . The value obtained was of 0 . 903 Da/A3 . Based on a molecular mass of 17 , 148 Da [18] , the calculated molecular volume a GPI-anchorless monomer is 18 , 990 Å3 . Consequently , the average height per monomer came to 17 . 7 Å ( Table 1 ) . A similar calculation using the generic 0 . 8129 Da/Å3 protein density value would result in a monomer height of 19 . 7 Å . These height value calculations confirm that the ~20 Å spacings detected by our two independent single particle analyses originate from individual GPI-PrPSc subunits stacked along the protofilament axis , lending further support to the 4-rung β-solenoid interpretation for the structure of PrPSc . Together , these data support a model in which the structure of PrPSc and PrP 27–30 consists of a four-rung ß-solenoid with a central , ß-strand-rich core , which is also supported by results obtained with X-ray fiber diffraction [25] . Fig 8 shows a cartoon representing the key elements of the prion architecture surmised from the data obtained in the present studies . It needs to be emphasized that this is not an atomistic model , but a cartoon only—meant to visualize the overall architecture of a four-rung ß-solenoid configuration . In order to account for a molecular height of 19 . 2 Å ( 4 x 4 . 8 Å ) the approximately 144 residues of PrP 27–30 must adopt a coiled ß-sheet conformation ( Fig 8B ) . This ~19 Å constraint is particularly relevant because it was obtained across many class averages , i . e . it is not characteristic of just one particular fibril architecture , but rather , emerges as a universal feature of the majority of fibrils present in the preparation . These data agree very well with data obtained from X-ray fiber diffraction of preparations of purified PrPSc samples of different kinds [25] . Although the actual number of residues in ß-sheet conformation per coil remains unclear , hydrogen-deuterium exchange and limited proteolysis studies have shown that brain-derived PrPSc consists of several ß-strands connected by short turns and loops [4 , 18] . Likely , the location of proline residues and the cysteine disulphide bridge pose constraints to the threading of the solenoid , with these elements likely located at corners [31 , 34] .
Our cryo-EM images of GPI-anchorless PrPSc fibrils , and their subsequent analysis , show that they consist of two intertwined protofilaments , in agreement with a recent study of negatively stained PrPSc fibrils [35] . Each protofilament exhibits an approximately ellipsoidal cross-section with a linear volume of ~9 , 900 Å3/nm . Given the fact that cryo-EM preserves the native structure of specimens , this information sets a structural restraint for the conformation of GPI-anchorless PrPSc . One important implication is that PrPSc subunits can only fit into protofilaments with the observed dimensions ( Table 1 ) , if they are folded up onto themselves . Based on the routine observation of regular 4 . 8 Å cross-ß signals in individual GPI-anchorless PrP 27–30 fibrils ( Fig 3 ) , a ß-solenoid arrangement is the easiest way to accommodate the peptide into the available protofilament volume . This arrangement would result in 4 x 4 . 8 Å ( ~19 Å ) repeats along the protofilament axis , which is exactly what our two independent single particle analyses revealed ( Figs 5 and S5 ) , together with an additional ~40 Å signal that likely corresponds to a vertical pairing of two PrPSc subunits , as seen in HET-s prion fibrils [30] . Therefore , our cryo-EM data revealed a ß-solenoid architecture as the basic element for the structure of the mammalian prion GPI-anchorless PrPSc ( Fig 8 ) , which is in agreement with previous results obtained by X-ray fiber diffraction for other prions such as RML and Sc237 PrP 27–30 [25] . As an important corollary , our cryo-EM data are incompatible with models based on alternative architectures , such as the parallel in-register ß-sheet fold , which is based on a single , superpleated protofilament with a molecular height of only 4 . 8 Å [6] . It is noteworthy that a β-solenoidal architecture has been demonstrated , as already mentioned , for the HET-s prion [30 , 36] , and has been proposed for insulin [31] and SH3 amyloid [37] fibrils based on cryo-EM data . While important structural elements still need to be defined , such as which residues participate in the ß-strands that form each solenoid rung , and which ones are located in turns and connecting loops , what we have learned about the structure of GPI-anchorless PrP 27–30 and its four-rung ß-solenoid architecture , allows us to extrapolate about possible templating mechanisms that control the replication of infectious prions in vivo . In-phase stacking of identical residues along the peptide chain , as was proposed by the parallel in-register ß-sheet model [6] , can be ruled out , as mentioned above , due to the experimentally determined height constraints . Therefore an alternative templating mechanism must explain the replication of prions in general , and the fidelity required for transmitting distinct prion strains in particular [19] . Templating based on a four-rung ß-solenoid architecture must involve the upper- and lowermost ß-solenoid rungs . These edge strands are inherently aggregation-prone , as they are predestined to propagate their hydrogen-bonding pattern into any amyloidogenic peptide they encounter [38] . In fact , the ß-strands of native proteins that contain a ß-solenoid are capped by loops and other structures to block unregulated propagation of ß-sheets . Furthermore , the elimination of the capping structures results in edge-to-edge-driven oligomerization of the "de-capped" ß-solenoids [39] . Thus , it is easy to conceive that these upper and lower ß-solenoid rungs can template an incoming unfolded PrP molecule to create additional ß-solenoid rungs . It is noteworthy that the molecular forces responsible for the templating − hydrogen-bonding , charge and hydrophobic interactions , aromatic stacking , and steric constraints − are fundamentally similar to those operating during DNA replication . Obviously , the exquisite specificity of the A:T and G:C pairings is lacking and instead , a much more complex array of forces controls the pairing of the pre-existing and nascent ß-rungs . Once an additional ß-rung has formed , it creates a fresh "sticky" edge ready to continue templating until the incoming unfolded PrP molecule has been converted into another copy of the infectious conformer . Furthermore , the stacking of GPI-anchorless PrP 27–30 molecules into amyloid fibrils , or , in other words , the way in which templating occurs , is either based on a ) a head-to-tail orientation resulting in amyloid fibrils with intrinsic polarity ( Fig 8 ) , or b ) a head-to-head and tail-to-tail orientation , which would result in generally apolar amyloid fibrils . In the former case , templating of ß-sheets would involve direct contact between different parts of the molecule , i . e . heterotypic templating . In the latter case , the same protein stretches will come into contact principally , but homotypic templating would result in two PrPSc molecules with opposite handedness . Alternatively , a head-to-head arrangement could also rely on heterotypic templating , if different parts of the molecule interact with each other . Experimentally , we observed a ~40 Å signal in Fourier-transform analyses of the fibril segments ( Figs 5 , S4 and S5 ) that may originate from a dimeric arrangement . The presence of a distinct dimer signal supports a head-to-head and tail-to-tail arrangement , but , ultimately , higher resolution data are needed to distinguish between these dimer options . In summary , we present data based on cryo-EM analysis that strongly support the notion that GPI-anchorless PrPSc fibrils consist of stacks of four-rung ß-solenoids . Two of such protofilaments intertwine to form double fibrils , in agreement with a recent report based on tomography of negatively stained PrPSc samples [35] . The four-rung ß-solenoid architecture of GPI-anchorless PrPSc provides unique and novel insights into the molecular mechanism by which mammalian prions replicate .
Heterozygous GPI-anchorless PrP transgenic mice ( tg44+/- ) were developed by Dr . Bruce Chesebro ( NIH Rocky Mountain Laboratories , Hamilton , MT , USA ) [10] . The mice were crossed to generate homozygous GPI-anchorless PrP animals ( tg44+/+ ) [16] and genotyped by tail DNA analysis using the PCR protocol described in Chesebro et al . [10] . Homozygous GPI-anchorless PrP transgenic mice ( tg44+/+ ) [10 , 16] were inoculated intra-cerebrally ( IC ) in the right temporal lobe , at 6 weeks of age , with 20 μl of a 2% RML-infected mouse brain homogenate ( BH ) , prepared in 2X ( w/v ) PBS . After 365 days post inoculation , the asymptomatic mice were euthanized , the brains were harvested , rinsed in PBS , and stored at -80°C until use . For the bioassays two groups of six wild-type C57BL/6 mice were inoculated IC with either 20 μl of a 2% GPI-anchorless RML prion BH or with an equivalent amount of purified GPI-anchorless PrP 27–30 resuspended in 5% ( w/v ) glucose in 2X PBS . Also a new cohort of six wild-type mice was inoculated IC with 20 μl 2X PBS as negative control . Mice were monitored until the appearance of clinical signs , at which time they were euthanized and the brains were removed . Animal experiments were carried out in accordance with the European Union Council Directive 86/609/EEC , and were approved by the University of Santiago de Compostela Ethics Committee ( protocol 15005AE/12/FUN 01/PAT 05/JRR2 ) . The Kaplan-Meier plot survival analyses of the wild-type mouse groups inoculated with GPI-anchorless RML prion BH and purified GPI-anchorless PrP 27–30 were compared using the Gehan-Breslow-Wilcoxon test . Immediately after extraction , the brain was fixed in formalin and then sliced into four transversal sections by cutting the brain caudally and rostrally to the midbrain and at the level of the basal nuclei . The sections were dehydrated by immersion in solutions of progressively higher ethanol concentration and , finally , with xylene before being embedded in paraffin . Haematoxylin-eosin was used to stain 4 μm thick sections . Additional sections were mounted on 3-triethoxysilyl-propylamine-coated glass slides for immunohistochemical ( IHC ) studies . IHC for the detection of PrPSc was performed as follows . Deparaffinized sections were subjected to epitope unmasking treatments: Immersed in formic acid and boiled at low pH ( 6 . 15 ) in a pressure cooker and pre-treated with proteinase K . Endogenous peroxidases were blocked by immersion in a 3% H2O2 in methanol . Then , the sections were incubated overnight with anti-PrP mAb 2G11 primary antibody ( 1:100 , kindly supplied by Dr . Eoin Monks , University College Dublin , Ireland ) and subsequently visualized using the Dako EnVision system K400111/0 ( Dako , Glostrup , Denmark ) and 3 , 3’diaminobenzidine as the chromogenic substrate . Additional sections were incubated with a rabbit polyclonal antibody against glial fibrillary acidic protein Z0334 , 1:600 ( Dako , Glostrup , Denmark ) to visualize astrocytic activation . For the glial fibrillary acidic protein detection epitope unmasking treatments were omitted , but the same visualization system was used . As a background control , the incubation with the primary antibodies was omitted . GPI-anchorless PrP 27–30 was isolated using a slightly modified version of the method of Baron et al . [11] . During the purification , total PrPSc was treated with 10 μg/ml of proteinase K ( PK ) at 37°C for 1 h . PK treatment yielded a shortened , protease-resistant form termed PrP 27–30 , due to its similarity to GPI-anchored PrP 27–30 , which has an apparent molecular mass of 27–30 kDa [40] . The final GPI-anchorless PrP 27–30 pellet was resuspended in 100 μl of deionized water and treated with lipase ( porcine pancreas lipase , Sigma No . 62300 ) at 1 μg/ml for 2 h at 37°C . To trap the fatty acids released by the lipase , bovine serum albumin ( BSA ) was added to a final concentration of 10 mg/ml . The sample was centrifuged at 22 , 000 g for 20 min , twice , and the pellet containing the PrP 27–30 fibrils was resuspended in 100 μl of deionized water . Finally , fibrils were sonicated with three pulses at a 50% amplitude with a probe ultrasonic homogenizer ( Cole Parmer Instrument CO . , Chicago , IL , USA ) , and the purified protein was stored at 4°C or -80°C . The sample purity was assessed by SYPRO Ruby Protein Gel Stain . The yield of GPI-anchorless PrP 27–30 was ~35 μg per mouse brain ( BCA protein assay [41] ) . SDS-PAGE was performed in 15% polyacrylamide gels . For Sypro Ruby staining , the gel was washed with ultrapure water , fixed for 1 hour with 10% methanol and 7% acetic acid , followed by overnight incubation with Sypro Ruby solution ( Lonza , Rockland , ME , USA ) at room temperature with gentle agitation and protection from light . For immunoblotting , the gel was transferred to an Immobilon-P PVDF membrane ( Millipore , Billerica , MA , USA ) and probed with the 3F10 antibody ( recognizing residues 137–151 ) at a 1:5 , 000 dilution . Peroxidase-labeled anti-mouse antibody was used as the secondary antibody at a 1:5 , 000 dilution . Samples were prepared by pipetting a 3 μl sample , mixed with a gold fiducial solution ( 15 nm gold particle size ) , onto a freshly glow-discharged Lacey carbon grids ( Ted Pella Inc . , Redding , CA , USA ) . The grids were plunge-frozen in liquid ethane in a Vitrobot Mark IV ( FEI , Eindhoven , The Netherlands ) . Cryo-EM data were collected using a Titan Krios microscope equipped with Falcon II direct electron detector ( FEI , Eindhoven , The Netherlands ) , operated at 300 kV . Low-dose imaging conditions with 20 electrons per Å2 were applied . Images were collected at 1–3 μm underfocus . All micrographs were recorded at a pixel size of 1 . 34 Å per pixel . Tilt series data were obtained on a Titan Krios ( FEI , Eindhoven , The Netherlands ) , operated at 300 kV on a Falcon II direct electron detector ( FEI , Eindhoven , The Netherlands ) , under low-dose conditions with 50 electrons per Å2 . Tomograms of selected areas were obtained from -70 to +70 degrees with a 1 . 5° tilt increment . The defocus range of the data set was 5–8 μm , with a pixel size of 6 Å . The tilted images were aligned and reconstructed with both the FEI Inspect3D software ( FEI , Eindhoven , The Netherlands ) and with Tomo3D [42] and the SIRT reconstruction method ( 30 iterations ) . 261 fibril widths were obtained from 9 different reconstructed tomograms . Measurements were determined using ImageJ software , following the “Measuring distances between points” manual . Single particle analysis: Only cryo-EM images presenting clear Thon rings were used for processing . The CTF was determined by CTFFIND3 [43] and phases were corrected with Bsoft [44] . Straight fibril segments were extracted manually from 400 micrographs using EMAN’s boxer program [45] . A total of 1305 non-overlapping segments were picked with a box size of 200 x 200 pixels ( 26 . 8 x 26 . 8 nm ) . In order to align the segments along the y-axis , a symmetrized average from an iterative alignment using the straightest particle in the set as a reference , was used as a starting template . Subsequently , particles were classified by multivariate statistical analysis implemented in IMAGIC [46] . Also , the aligned particles were cut into single protofilaments , realigned and reclassified , resulting in a new data set of 2610 particles . Finally , the summed amplitude spectra of all class averages was calculated and further analyzed . Reference-free single particle analysis: Image processing was performed with the IMAGIC-4D software [47] . The same 400 selected micrographs ( 4096 x 4096 pixels ) were normalized by a posteriori camera correction to remove camera artifacts [48] ( S6 Fig ) . Amplitude spectra were used to determine the CTF parameters and perform CTF-correction by phase flipping ( using CTF2D-FIND and CTF2D-FLIP programs ) . The particles were picked from the best patches of normalized and band-pass filtered micrographs by the PICK-M-ALL program , using a single featureless rectangular reference created by smearing a filament along its length . From the selected patches containing clear fibrils , the best 2725 particles were selected based on standard statistical analyses ( averages , standard deviations , cross correlation coefficients ) . Multivariate eigenvector data compression was then applied , followed by automatic unsupervised classification , to create 20 classes . No alignments were applied to avoid reference bias . 3D fibril reconstruction: Suitable fibril images were selected from a set of 1284 cryo-EM images . An individual fibril , presenting at least half a helical turn ( 180° ) , was segmented along the helical axis using EMAN’s boxer program [45] into overlapping boxes of 300 x 300 pixels ( 40 . 2 x 40 . 2 nm ) . The boxes were centered and spaced 1–5 pixels apart along the helical axis . By measuring the repeat distance of the helical fibril , we could estimate the angular orientation of each box in the set . The underlying assumption was that each box represented a different view of identically the same fibril , where each view is rotated and translated according to the helical twist . By assigning the angles to each box in the set , a preliminary 3D reconstruction was generated by back projection . Two-fold symmetry was then imposed . The preliminary 3D reconstruction was refined against other 3D reconstructions generated from the same fibril using different step sizes [29] . SPIDER software was used for the reconstruction [49] . In order to remove the rippling artifact created by the overlapping segments , the procedure continued with a second stage , using IMAGIC software [46] . The refined 3D reconstruction was rotated 90° around its x-axis and sliced along the yz plane . The new set of cross-sectional projections was aligned , centered , and averaged . The averaged density was symmetrized , replicated along the fibril length , and in-plane rotation angles were assigned based on the helical twist . Finally , the collection of 2D projections was used to assemble the 3D volume . Reconstructions were visualized in UCSF Chimera [50] . The thresholds for the cryo-EM maps were fixed based on the fibril widths measured in the raw images . The monomer height calculation was accomplished by determining the cross-section area ( Å2 ) of each protofilament in Chimera [50] and then calculating the corresponding volume using an experimentally determined molecular mass for the GPI-anchorless PrP 27–30 of 17 , 148 Da [18] , and a mean protein density of 0 . 903 Da/Å3; calculated based on a HET-s monomer stacked in a HET-s prion fibril ( [30] PDB: EMD-2946 ) .
|
The structure of the infectious prion ( PrPSc ) , which is responsible for Creutzfeldt-Jakob disease in humans and bovine spongiform encephalopathy , has escaped all attempts at elucidation due to its propensity to aggregate . Here , we use the repetitive organization inherent in amyloid fibrils to analyze the structure of GPI-anchorless PrP 27–30 via electron cryomicroscopy . Fourier-transform analysis of averaged fibril segments indicates a repeating unit of 19 . 1 Å . In agreement with this observation , 3D reconstructions reveal that each fibril contains two distinct protofilaments and that the height of each PrP 27–30 molecule in these fibrils is ~17 . 7 Å . Together the data indicate a four-rung β-solenoid structure as a key feature for the architecture of infectious mammalian prions . The data conflict with all previous models for the structure of PrPSc and allow the formulation of a molecular mechanism for the replication of prions .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"and",
"health",
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"structure",
"condensed",
"matter",
"physics",
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"cryo-microscopy",
"animal",
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"animal",
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"crystallography",
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"infectious",
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"immunohistochemistry",
"techniques",
"macromolecular",
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"analysis",
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"physical",
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"histochemistry",
"and",
"cytochemistry",
"techniques",
"amyloid",
"proteins",
"prion",
"diseases"
] |
2016
|
The Structural Architecture of an Infectious Mammalian Prion Using Electron Cryomicroscopy
|
Determining the forces that conserve amino acid positions in proteins across species is a fundamental pursuit of molecular evolution . Evolutionary conservation is driven by either a protein's function or its thermodynamic stability . Highly conserved histone proteins offer a platform to evaluate these driving forces . While the conservation of histone H3 and H4 “tail” domains and surface residues are driven by functional importance , the driving force behind the conservation of buried histone residues has not been examined . Using a computational approach , we determined the thermodynamically preferred amino acids at each buried position in H3 and H4 . In agreement with what is normally observed in proteins , we find a significant correlation between thermodynamic stability and evolutionary conservation in the buried residues in H4 . In striking contrast , we find that thermodynamic stability of buried H3 residues does not correlate with evolutionary conservation . Given that these H3 residues are not post-translationally modified and only regulate H3-H3 and H3-H4 stabilizing interactions , our data imply an unknown function responsible for driving conservation of these buried H3 residues .
In eukaryotes , histone and non-histone proteins package genomic DNA into higher order chromatin structures . These higher order structures control the accessibility of genomic DNA to various cellular machineries that perform transcription , replication , repair and recombination . The fundamental unit of eukaryotic chromatin is the nucleosome , composed of ∼147 base pairs of DNA wrapped around the histone octamer [1] . The histone octamer comprises of two copies of each of the four histone proteins: H2A , H2B , H3 , and H4 . All these histone proteins are characterized by the “histone fold” , consisting of the alpha-helical and globular “handshake” motif in between the unstructured N- and C-terminal “tails” [2] . The “handshake” motif helps in stable dimerization of H2A-H2B and H3-H4 . ( H3-H4 ) 2 forms a stable tetramer , where two H3-H4 dimers are arranged symmetrically across an interface formed by adjacent H3 molecules ( H3 , H3′; Figure S1A , B ) . Similarly , the H2A-H2B dimer contacts the H3-H4 dimer through a beta-strand extension between H2A and H4 , which serves as the only region of contact between these dimers ( Figure S1C , D ) . Thus , the buried region of the histone octamer can be identified as either the buried residues of the dimers , or the residues that form the interfaces between the dimers while forming the tetramer and octamer . The amino acid sequences of histone proteins are highly conserved from yeast to humans: H3 and H4 feature more than 90% conservation across all their known sequences . Covalent modifications to the histone “tail” domains [3] , which regulate chromatin organization and function , drive their high sequence conservation , while the need to maintain interactions with genomic DNA may drive the sequence conservation of many residues on the surface of the histone octamer . Due to the lack of any other function , we could hypothesize that the conservation of buried and inter-histone interface residues ( see Figure S1 and Figure S2 ) is driven by the need to maintain inter-histone interactions and to preserve the histone fold [4] , [5] , [6] , [7] , [8] . In this study , we test this hypothesis by exploring the correlation between a residue's evolutionary conservation and its contribution to the thermodynamic stability of the histone octamer .
To test the hypothesis that thermodynamic stability drives evolutionary conservation of buried and interface residues in H3 and H4 , we calculated the energetic consequences of mutating each of these residues . The contribution of the H3 and H4 interface residues ( see Figure S1 ) to stability was determined by calculating the change in stability ( ΔΔG ) after mutating each of the histone interface residues in H3 ( H113 , A114 , L126 , A127 , I130 , and R131 ) and H4 ( T96 , L97 , Y98 , and G99 in H4 ) to all possible amino acids using Medusa [8] , [9] , a computational protein design toolkit . We then used the ΔΔG values to determine the propensity of each possible amino acid to be stabilizing at each of these positions . The amino acid with the lowest ΔΔG at a position has the highest propensity to be stabilizing at that position . We find that most of the residues present in the H3-H3′ interface ( residues 113 , 126 , 127 and 130 ) have a strong preference for the native amino acid or for conserved substitutions . Since evolutionary pressure is associated with survival fitness , we asked if engineered mutations that should result in thermodynamic destabilization of the histone octamer would lead to phenotypic consequences in the budding yeast Saccharomyces cerevisiae . We made three H3-H3′ interface mutations ( Table 1 ) that disrupted conserved interactions ( H113A , L126A and L130A ) and one interface mutation that introduced a non-preferred amino acid at that position ( A114Y ) . Based on our models ( Figure 1A , where the left panels represent WT interface and right panels represent the mutant interface ) , H113A disrupted hydrogen-bonding and hydrophobic interactions of H113 with a negatively charged pocket formed by the adjacent H3 surface . L126A and L130A each disrupted hydrophobic interactions with the adjacent H3 ( Figure 1B , D ) . Consistent with these mutations resulting in a significant destabilization of the H3-H3′ interactions in silico ( Table 1 ) , we found that these H3 mutations were lethal when engineered in budding yeast ( Figure 2A ) . Regarding H3A114 , our calculations predict the preference of small amino acids or aspartate at this position ( Figure 3A ) , as large amino acids at 114 would disrupt H3-H3′ interaction ( Figure 1C ) . Consistent with this idea , a A114Y mutation was also lethal in yeast ( Figure 2A ) . The interface residues in H4 on the other hand interact with V101-A104 of H2A primarily through backbone hydrogen bonds ( Figure S1C , D ) . The side chain of H4Y98 is embedded in a deep groove formed on the H2A surface , which makes the position suitable only for aromatic residues as revealed by our calculations . In contrast , H4G99 is placed in a position where any side chain would have significant steric clashes with the H2A surface , making the position amenable only to glycine ( Figure 3C ) . We thus find that the selected interface residues lining the H3-H3′ and the H4-H2A interfaces are important for nucleosome stability in silico and viability in vivo . To extend this comparison between residues needed for nucleosome stability and their effects on growth in yeast , we calculated the change in nucleosome stability of 62 mutations pertaining to buried/interface residues extracted from the HistoneHits database [10] . Overall , we observed that residues found to be essential for viability are often also associated with being required for nucleosome stability ( Figure 2B , Table S1 and Table S2 ) . The ΔΔG of lethal mutants is significantly higher than the ΔΔG of viable mutants: the probability that the ΔΔG of lethal and viable mutants are similar is 2 . 5×10−4 , indicating that the difference in destabilizition of lethal and viable mutants is statistically significant . These results imply that the lethality observed in these studies is due to thermodynamic destabilization of the nucleosome . Furthermore , if we use an arbitrary ΔΔG cut-off of +3 kcal/mol as a threshold to suggest a point where sufficient thermodynamic destabilization would lead to lethality , we are able to predict 74% of the lethal mutants and 71% of the viable mutants from the HistoneHits database ( Figure 2C , D ) . These data suggest that nucleosome stability , which is essential for viability , is a major driving force behind the sequence conservation of buried H3 and H4 residues . To explore the relationship between thermodynamic stability and sequence conservation of buried and interface histone residues , we compared the sequence entropies [4] ( see Methods for mathematical definition ) of these residues from our calculations to those observed in evolution . We use sequence entropy as a parameter to measure the degree of variability of amino acids at a given position across a wide range of species . Highest sequence entropy would indicate all twenty amino acids are equally probable in that position , while zero value entropy would indicate complete conservation of that position . We calculated the sequence entropy at each buried and interface position in H3 and H4 based on the ΔΔG of all possible amino acids at that position ( detailed in Methods ) , which we compared to the evolutionary sequence entropy obtained from the homology-derived secondary structure of proteins database [11] . There could be a possible bias for native amino-acid type in our calculations because we keep the backbone fixed . However , since the histone-fold is highly conserved ( the Cα root mean square deviation ( RMSD ) between the crystal structures of yeast [12] , drosophila [13] , xenopus [1] and human [14] nucleosomes range between 0 . 25–0 . 5 Å , indicating very high structural similarity ) , we expect this bias to be minimal . We found statistically significant correlation between Medusa and evolutionary entropy for buried and interface residues in histone H4 ( Figure 3D , r = 0 . 69 , p = 3 . 8×10−4 , Table S4 ) , while there is no correlation in the case of histone H3 ( Figure 3B , Table S3 ) . We observe that thermodynamically , native residues in H3 are preferred in 75% of the positions considered ( Figure 3A ) , as compared to 54 . 5% for H4 ( Figure 3C ) . Compared to 63 . 4% [8] and 57 . 1% [15] of native residues preferred in the buried region of other proteins , H3 has a highly optimized buried-core . However , even such high sequence recapitulation is not accompanied by correlation between Medusa sequence entropy and evolutionary entropy of H3 ( Figure 3B ) . To analyze the lack of correlation in H3 further , we divide the H3 residues that we consider into three sets ( Figure S3 ) . The first set corresponds to five positions that feature much higher evolutionary entropy compared to other positions ( Figure S3A ) . These five outliers are S95 , V96 , A110 , I124 and L130 . Evolutionarily , cysteine is the most conserved amino acid at position 110 , but we do not consider cysteine in our calculations , hence we do not analyze this position further . To explore functional constraints on the evolution of S95 , V96 , I124 and L130 , we analyzed their tree-based conservation . We observe that the conservation of S95 , V96 and L130 ( Figures S4 , Figure S5 and Figure S6 respectively; the organisms whose sequences were used to construct the tree are shown in Figure S7 ) is highly tree-determinant , implying increasing the stability of the nucleosome to not be a major driving force . The observed tree-dependent evolution implies a functional constraint for conservation in these positions . In the second set , we observe twelve positions whose stability seemingly correlates with evolutionary conservation ( Figure S3B , r = 0 . 64 , p = 0 . 025 ) . However , the low value of the slope of the linear fit ( 0 . 032 ) indicates that evolutionary conservation is higher than the conservation expected due to stability , even if it follows the same trend as stability . The third set corresponds to eleven positions that feature evolutionary conservation that is much higher than required for stability . Nine of these positions are buried ( Table S5 ) , while two belong to the interface . Many buried positions being conserved much more than required by stability indicates that thermodynamic stability is not a sufficient driving force for H3 conservation . The increased sequence conservation observed in the buried residues of H3 is only observed in other proteins when those residues are essential for a protein's function other than stability [8] . An indirect way to assess if these residues are implicated in function is through evolutionary analysis that picks coevolving residues . Coevolution of two residues that are spatially distant may point to evolutionary constraints due to functional roles [16] . To find such coevolving residues in H3 , we used multiple sequence alignment of H3 sequences from a wide range of species ( from yeast to human , 223 species in total ) to calculate the Z-score of normalized mutual information of any two positions in H3 . A Z-score higher than 4 indicates significant coevolution [17] . In H3 , we find that there are only ten pairs of coevolving residues with significant Z-scores . Of these ten pairs , nine pairs ( Table 2 ) have at least one buried/interface residue that we consider in this study and out of these nine pairs , five pairs form structural contacts either intramolecularly or across the H3-H3′ dimeric interface ( Figure 4 ) . Notable among these pairs of residues that are spatially proximal are the electrostatic interaction between H113 and E123 and the hydrophobic interaction between H113 and L126 , both of which occur across the dimeric H3-H3′ interface . Additionally , R116 and E123 , which form an inter-molecular salt-bridge are also found to coevolve . The disruption of salt-bridge between R116 and E123 by the mutation R116H has been identified as a sin mutant , which alleviates the requirement for nucleosome-remodeling factors in transcription activation [18] , [19] . Thus , our coevolution analysis identifies at least one functionally important coupling . The coevolving pairs of residues that do not form structural contacts could have coevolved due to i ) their involvement in the folding kinetics of H3 , ii ) due to negative design [20] , where control of interactions between these residues is required for elimination of non-native structures , or iii ) due to other functions that involve the residues in the identified pairs , implying a functional constraint on their evolutionary conservation .
Our data point to a force apart from thermodynamic stability that conserves buried and interface residues in H3 . This driving force of conservation found in buried H3 residues has not been observed or characterized in buried residues of other highly conserved proteins to our knowledge . Statistically significant correlation between Medusa derived sequence entropies and evolutionary entropies has been shown before in other proteins [8] , and in H4 in this study , implying stability as a driving force for conservation buried residues . Further , when we performed similar analysis on all buried positions of actin ( PDB ID 1J6Z ) and tubulin ( PDB ID 1Z5V ) , we observe statistically significant correlation between evolutionary and Medusa entropies ( Table 3 ) . Thus , there is correlation between thermodynamic stability and evolutionary conservation in the buried residues found in other highly conserved proteins , namely actin and tubulin . These results reveal H3 as the only protein known so far , whose conservation of core residues is not driven by stability alone . We therefore suggest there is a novel function associated with the buried and interface residues of H3 that is driving the unique level of conservation . What might be the function of the conserved buried residues in H3 ? Given these residues are not found to be post-translationally modified , and their strict conservation is independent of H3-H3′ and H3-H4 stability , it could be suggested that they may be playing a role in histone chaperone interactions and deposition . Asf1 is one such histone chaperone that facilitates the deposition of histones in chromatin during replication . Even though Asf1 binds and/or competes for the H3-H4 dimer by interacting with residues in the H3-H3′ interface [21] , it cannot account for the conservation of the residues it interacts with in H3 , as the interacting residues from Asf1 are not similarly conserved . In addition , Asf1 is not known to interact with the H3 buried residues we examined . We do not rule out the possibility that other histone chaperones or other histone interacting proteins interact with the buried and interface residues in H3/H4 for a functional purpose , but it is striking to note that even though most of these proteins may also interact with H4 , conservation of H4 can be accounted for by thermodynamic stability alone . Another possibility for the increased conservation of buried residues of H3 could be the need to tightly regulate and fine-tune the stability of nucleosomes during transcriptional regulation , as a slight increase or decrease of nucleosome stability could have profound effects on cellular processes like transcription . We find evidence for this hypothesis in the observation that H3 variants such as H3 . 3 function by modulating nucleosome stability [22] . Although the core of H3 . 3 differs from canonical H3 in humans at just three positions , the destabilization of H3 . 3 containing nucleosomes has been shown to be important in transcriptional regulation [22] . Thus , major changes in cellular function due to minor perturbations in H3 sequence suggest the need for tight control of nucleosome stability . Such control may explain why the core residues of H3 are so highly conserved . We conclude that an unknown set of factors is driving conservation of H3 to a degree that has not been found in any other protein to date . The significance of these residues outside of histone fold interactions awaits further discovery . Our finding of an unexpected level of sequence conservation , not demonstrated before in a protein to our knowledge , suggests the ability to predict functional roles of amino acid residues apart from imparting thermodynamic stability to a given protein .
The residues analyzed in this paper include 51 , 61 , 67 , 70 , 71 , 74 , 75 , 88 , 91 , 92 , 93 , 95 , 96 , 100 , 103 , 104 , 107 , 110 , 111 , 113 , 114 , 119 , 123 , 124 , 126 , 127 , 130 and 131 from H3 and 29 , 33 , 34 , 37 , 38 , 43 , 50 , 54 , 58 , 62 , 65 , 66 , 69 , 73 , 81 , 86 , 89 , 90 , 96 , 97 , 98 and 99 from H4 . The interface residues include 110 , 113 , 114 , 123 , 126 , 127 , 130 and 131 in H3 and 96 , 97 , 98 and 99 in H4 . We performed ΔΔG calculations on two types of residues in H3 and H4 , i ) residues in the interface of H3-H3′ and H4-H2A and ii ) residues that are buried in the histone octamer . We define buried residues as those that have less than 1 Å3 exposed solvent accessible surface area in the histone octamer . We calculate solvent accessible surface area using the method of LeGrand and Merz [23] , using 1024 dots on surface of each atom . We define interface residues ( lining H3-H3′ and H4-H2A ) as those that formed persistent contacts across these interfaces in our earlier simulations of the mono-nucleosome [24] . We used the coordinates of histone octamer , extracted from the crystal structure of the yeast nucleosome [12] ( PDB ID 1id3 ) to perform Medusa calculations . Since we consider only core residues of H3 and H4 that do not interact with DNA , we do not consider DNA in our calculations . Medusa calculations involve a Monte-Carlo based simulated annealing procedure that uses rotamer libraries of amino acids for fast minimization of its energy function while leaving the backbone fixed . For all the residue positions we considered in this study , ΔΔG was calculated for mutation of the native amino acids at that position to 17 other amino acids ( all natural amino acids except cysteines and prolines: we do not consider disulfide bonds in our model and prolines can also affect the protein backbone , which we hold fixed in our calculations ) . For each position , residues within 10 Å ( CA – CA distance ) were allowed to sample all available native rotamers , while rest of the residues were allowed to sample the sub-rotameric states of the starting rotamer . We averaged the free energy obtained from 100 Medusa calculations to obtain ΔΔG for each mutation . We define ΔΔG as:Where ΔGMut is the stability of the mutant and ΔGWT is the stability of the wild type . Thus , a destabilizing mutation would result in a positive ΔΔG . For buried residues , we calculated only the ΔΔG for each mutation . For the interface residues , we calculate the difference in binding energy between mutant nucleosome and the wild-type nucleosome; the difference in binding energy is positive if mutation results in a decrease in binding energy . For comparison between ΔΔG and viability , we calculated the change in nucleosome stability of 62 mutations pertaining to buried/interface residues extracted from the HistoneHits database [10] . The difference in between lethal and viable mutants were statistically tested using a two sample , one-tailed t-test ( sample size of lethal mutants = 27 and viable mutants = 35 ) which gives a p-value of 2 . 5×10−4 . We assume a Boltzmann distribution of amino acid residues in a given position , where the ratio of propensity of two amino acids can be calculated from the ΔΔG of mutating one of the amino acids to the other:where pi and pj are the propensities of amino acids i and j at a given position and ΔΔGij is the free energy change upon mutating i to j at that position obtained from Medusa calculations . Here , the temperature T refers to the physical temperature at which the protein exists and functions in the organism , and hence would vary in a narrow range . We use a temperature of 300 K to perform all calculations . These propensities are in turn used to calculate the sequence entropy at a given position:where H ( k ) is the sequence entropy at position k and pi is the propensity of amino acid i at position k . The positional sequence entropy thus calculated is compared to evolutionary entropy extracted from homology-derived secondary structure of proteins ( HSSP ) database entry for yeast nucleosome ( 1id3 . hssp ) [11] . We use mutual information as a measure of coevolution of two positions in either the same protein or across two proteins [25] . Mutual information is defined as:where MI ( i , j ) is the mutual information of positions i , j; H ( i ) is the sequence entropy at position i and H ( i , j ) is the joint entropy of positions i and j . Since MI by definition cannot be greater than Min ( H ( i ) , H ( j ) ) , it correlates with the individual and joint entropies . To remove dependence of MI ( i , j ) on H ( i ) or H ( j ) , we normalize MI ( i , j ) by dividing it by H ( i , j ) to compare positions with varying entropies . It was shown before that H ( i , j ) was the best normalizing factor compared to H ( i ) and H ( j ) [17] . We then calculate the Z-score for the normalized MI for a given protein or protein pair . Z-score is defined as:In the above equation , MIN ( i , j ) refers to normalized MI . To account for evolutionary noise in MIN ( i , j ) , we perform tree based shuffling of position j , while keeping position i constant as described by Noivirt et al . [26] . The probability of shuffling position j between sequence a and sequence b is given by:where d ( a , b ) is the genetic distance between sequence a and b and is obtained from Clustalw2 [27] . Clustalw2 calculates genetic distance based on the minimum number of substitutions required to convert one sequence into another ( with correction applied to allow multiple substitutions to have occurred [28] ) . We perform 100 iterations of 2000 shuffles for each pair of positions for which we observe significant Z-score . We construct a distribution of MIN ( i , j ) from these shuffles and then determine the probability of obtaining the evolutionarily observed MIN ( i , j ) from the distribution of MIN ( i , j ) determined through shuffles ( P-value ) . A P-value of less than 0 . 05 is considered statistically significant . Swissprot IDs for Histones H3 sequences from different species were obtained from its Interpro family ( Interpro accession ID: IPR000164; website: http://www . ebi . ac . uk/interpro/ ) . The sequences were pruned to remove duplicates and fragments . We then selected a unique sequence for each species in the remaining group of sequences and performed multiple sequence alignments using Clustalw2 [27] . For the analysis of mutual information , we used sequences from 223 species for H3 . We use Henikoff position-based weighting algorithm to remove bias due to phylogenetic proximity [29] . S . cerevisiae strains used in this study are summarized in Table S6 . Ycp50-copy II ( HHT2-HHF2 ) , a plasmid containing wild-type H3-H4-copy II alleles with their native promoters and a TRP selectable marker was used for the mutational analyses . Point mutations were generated using site-directed mutagenesis ( QuickChange II kit; Agilent Technologies ) . Oligonucleotide primers were designed using the wild-type S . cerevisiae gene sequence of H3 or H4 found in the Saccharomyces Genome Database sequence for HHT2 and HHF2 . Mutant plasmids were sequenced for accuracy prior to performing histone shuffling in the yeast strains WZY42 as described by Zhang et al . [30] To analyze the effects of these mutants on yeast growth and viability , wild type and mutant strains were grown to an optical density of 0 . 5 at 600 nm in SC-Trp media prior to performing ten-fold serial dilutions on SC-Trp and 5-FOA plates . Plates were incubated at 30°C for 48–72 hours before being photographed . To confirm that our results were not strain-specific , we analyzed the same H3 mutants in YBL574 strain background ( Table S5 ) and obtained identical results .
|
Most proteins fold to a well-defined , three-dimensional structure , which can be delineated into the protein surface and its buried core . When comparing amino acid sequences of the same protein from different organisms , we would expect to find certain residue positions conserved due to the importance of that position in either maintaining the protein's function or its three-dimensional structure . In this study , we looked at residues in the buried core domains of histone proteins H3 and H4 , which have no known function other than maintaining the three-dimensional structure of the protein . We find that perturbing protein stability ( which is a measure of maintenance of the protein's structure ) by mutating these residues compromises survival fitness in yeast . However , the stability conferred by buried amino acids of H3 alone cannot account for their evolutionary conservation , which is in striking contrast to other proteins where stability has been shown to be the driving force for sequence conservation . This conservation of H3 thus points to either new additional functions of H3 that have not been uncovered or a unique conservation mechanism that goes beyond survival pressure . These data therefore reveal a highly conserved domain that is distinct in its evolutionary conservation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biochemistry/molecular",
"evolution"
] |
2011
|
Thermodynamic Stability of Histone H3 Is a Necessary but not Sufficient Driving Force for its Evolutionary Conservation
|
In many species a fundamental feature of genetic diversity is that genetic similarity decays with geographic distance; however , this relationship is often complex , and may vary across space and time . Methods to uncover and visualize such relationships have widespread use for analyses in molecular ecology , conservation genetics , evolutionary genetics , and human genetics . While several frameworks exist , a promising approach is to infer maps of how migration rates vary across geographic space . Such maps could , in principle , be estimated across time to reveal the full complexity of population histories . Here , we take a step in this direction: we present a method to infer maps of population sizes and migration rates associated with different time periods from a matrix of genetic similarity between every pair of individuals . Specifically , genetic similarity is measured by counting the number of long segments of haplotype sharing ( also known as identity-by-descent tracts ) . By varying the length of these segments we obtain parameter estimates associated with different time periods . Using simulations , we show that the method can reveal time-varying migration rates and population sizes , including changes that are not detectable when using a similar method that ignores haplotypic structure . We apply the method to a dataset of contemporary European individuals ( POPRES ) , and provide an integrated analysis of recent population structure and growth over the last ∼3 , 000 years in Europe .
MAPS estimates demography using the number of Pairwise Shared Coalescence ( PSC ) segments of different lengths shared between individuals . We define a PSC segment between ( haploid ) individuals to be a genomic segment with a single coalescent time across its length ( Fig 1A ) . Long PSC ( lPSC ) segments tend to have a recent coalescent time , and so manifest themselves in genotype data as unusually long regions of high pairwise similarity , which can be detected by various software packages [26–29] . Because lPSC segments typically reflect recent coalescent events , counts of lPSC segments are especially informative for recent population structure [19 , 24 , 30] . And partitioning lPSC segments into different lengths bins ( e . g . 2-8cM , ≥8cM ) can help focus inference on different ( recent ) temporal scales . However , we caution that the historical signal that gives rise to the number of segments of in a certain length bin ( e . g . 2-8cM ) to strongly overlap with that has given rise to a numbers of segments subsequent length bin ( e . g . ≥8 ) . The MAPS model involves two components: i ) a likelihood function ( Eq ( 7 ) ) , which relates the observed data ( genetic similarities , as measured by sharing of lPSC segments ) to the underlying demographic parameters ( migration rates and population sizes ) ; and ii ) a prior distribution on the demographic parameters , which captures the idea that nearby locations will often have similar demographic parameters . The likelihood function comes from a coalescent-based “stepping-stone” model in which discrete populations ( demes ) arranged on a spatial grid exchange migrants with their neighbors ( Fig 1b ) . The parameters of this model are the migration rates between neighboring demes ( Mα , β ) and the population sizes within each deme ( Nα ) . The prior distribution is similar to that from [12] , and is based on partitioning the habitat into cells using Voronoi tesselations ( one for migration and one for population size ) , and assuming that migration rates ( or population sizes ) are constant in each cell . We use an MCMC scheme to sample from the posterior distribution on the model parameters ( migration rates , population sizes , and Voronoi cell configurations ) . We can summarize these results by surfaces showing the posterior means of demographic parameters across the habitat . The inferred migration rates and population sizes will depend on the density of the grid used . However , using ideas from [23] and [24] we convert them to corresponding parameters in continuous space , whose interpretation is independent of the grid for suitably dense grids . Specifically , we convert the migration rates to an effective spatial diffusion parameter σ ( x → ) , often referred to as the “root mean square dispersal distance” , which can be interpreted roughly as the expected distance an individual disperses in one generation ( Eq ( 18 ) ) ; and we convert the population sizes ( N → ) to an “effective population density” D e ( x → ) , which can roughly be interpreted as the number of individuals per square kilometer ( Eq ( 17 ) ) . These are deemed “effective” parameters because the spatial re-scaling assumes a simple approximation to the two dimensional coalescent process , see [23] . Similar to the original grid-based demographic parameters , we can summarize MAPS results by surfaces showing the posterior means of σ ( x → ) and D e ( x → ) across the habitat . Our MAPS approach is closely related to the EEMS method [12] , but there are some important differences . First , the MAPS likelihood is based on lPSC sharing , rather than a simple average genetic distance across markers . This was primarily motivated by the fact that , by considering lPSC segments in different length bins , MAPS can interrogate demographic parameters in recent time periods . However , this change also allows MAPS , in principle , to estimate absolute values for the parameters M and N → , whereas EEMS can estimate only “effective” parameters which represent the combined effects of M and N → . This ability of MAPS to estimate absolute values stems from its use of a known recombination map , which acts as an independent clock to calibrate the decay of PSC segments . Finally , MAPS uses a coalescent model , whereas EEMS uses a resistance distance approximation [12 , 31] .
We assess the performance of MAPS with several simulations , and compare and contrast the results with EEMS . We used the program MACS [32] to simulate data under a coalescent stepping stone model and refinedIBD [27 , 28] to identify lPSC segments . Alternatively , we could of inferred lPSC segments exactly using [32] or [33] , however we found the error from refinedIBD to be negligible in our simulations . All simulations involved twenty demes , each containing 10 , 000 diploid individuals , and each exchanging migrants with their neighbor with a per lineage migration rate equal to 0 . 01 per generation . We analyzed each simulated data set using PSC segments of length 2-6cM and ≥6cM , which correspond to time-scales of approximately 50 generations and 12 . 5 generations respectively ( see Lemma 5 . 3 in S1 Appendix ) , however these are only the mean coalescent times and considerable variation exists in distribution of coalescent times . Results for other length bins also reflect the change in migration due to barrier ( S1 & S2 Figs ) . To illustrate MAPS on real data , we analyze a genome-wide SNP dataset on individuals of European ancestry [25] . Previous analyses of these data have shown the strong influence of geography on patterns of genetic similarity [20 , 34 , 35] . In particular [20] analyzed spatial patterns in the sharing of PSC segments across Europe . To facilitate comparison with their results , we use their PSC segment calls , focusing on a subset of 2224 individuals after filtering ( see Methods ) . We applied MAPS to these data using three different PSC segment length bins: 1−5cM , 5−10cM , and > 10cM . The longer bins correspond to more recent demography because as PSC lengths increase , the average coalescent times decrease . Indeed , the average coalescent times for each of these three length bins is inferred to be 90 , 23 and 7 . 5 generations respectively , which roughly correspond to 2700 years , 675 years and 225 years if we assume 30 years per generation and a sufficiently large effective population size ( see S1 Appendix ) . Here , we caution that these are only the mean coalescent times: other analyses have shown that distribution on coalescent times can have a very wide distribution and are strongly affected by the demographic history , especially in expanding populations [20] . We note that the accuracy of called PSC segments will vary across these bins: based on simulations in [20] PSC segment calls in the smallest bin ( 1-5cM ) will likely suffer from both false positives and false negatives , whereas for the longer bins PSC calls should be very reliable . Nonetheless , even in the smallest bin , closely-related individuals will still tend to show higher PSC sharing , and so the estimated MAPS surfaces should provide a useful qualitative summary of spatial patterns of variation even if quantitative estimates may be less reliable .
We developed a method ( MAPS ) for inferring migration rates and population sizes across space and time periods from geo-referenced samples . Our method builds upon a previous method developed for estimating effective migration surfaces ( EEMS ) [12] . However there are several differences between MAPS and EEMS . Most fundamentally , MAPS draws inferences from observed levels of PSC sharing between samples , whereas EEMS draws inferences from the genetic distance . These two data summaries capture different information about the coalescent distributions: in essence , PSC sharing captures the frequency of recent coalescent events , whereas genetic distance captures the mean coalescent time . Consequently MAPS inferences largely reflect the recent past ( mean coalescent time ⪅ 2 , 250 years for PSC segments > 2cM ) , whereas EEMS inferences reflect demographic history on a longer timescale across which pairwise coalescence occurs ( 99% of events > 6000 years old , assuming diploid Ne of 10 , 000 for humans , exponential coalescent time distribution ) . Another consequence of modelling PSC sharing , rather than genetic distance , is that MAPS can separately estimate demographic parameters related to migration rates ( M ) and population sizes ( N → ) , as in Fig 3 for example . In essence MAPS does this by using the known recombination map as an additional piece of information to help calibrate inferences . In contrast , EEMS makes no use of recombination maps and cannot separate M and N → . Instead EEMS infers a compound parameter referred to as the “effective migration rate” , which is influenced by changes in both M and N →; see Fig 3 . In principle , if applied to sequence data instead of genotype data at ascertained SNPs , the genetic distances used by EEMS could perhaps also separately estimate M and N → by exploiting known mutation rates to calibrate inferences . However , this would require non-trivial additional changes to the current EEMS likelihood , which was designed to be applicable to ascertained SNPs and does not explicitly model variation in population sizes . ( The EEMS likelihood instead uses a “diversity rate” eq , which reflects within-deme heterozygosity but is not explicitly a population size parameter . ) An additional useful feature of PSC segments is that , by varying the lengths analyzed , one can infer parameter values across associated with different time periods . For example , our simulations show how by contrasting shorter and longer PSC segments , the method can reveal different gene flow patterns in scenarios with recent changes ( see Figs 2 and 3 ) . Further support comes from our empirical analysis of the POPRES data-set , where we found population sizes inferred from longer PSC segments to be more correlated with census sizes than sizes inferred from shorter segments ( e . g . Spearman’s ρ = 0 . 71 for 1−5cM and ρ = 0 . 84 for > 10cM; see Fig 5 and S5 Fig ) . Also , not surprisingly , PSC segments greatly outperform using heterozygosity as an indicator of census population size ( the Spearman’s correlation coefficient between heterozygosity and census size was insignificant , p-value = 0 . 25 ) . Our estimates of dispersal distances and population density from the POPRES data are among the first such estimates using a spatial model for Europe ( though see [30] ) . The features observed in the dispersal and population density surfaces are in principle discernible by careful inspection of the numbers of shared PSC segments between pairs of countries ( e . g . using average pairwise numbers of shared segments , S4b Fig , as in [20] ) . For example , high connectivity across the North Sea is reflected in the raw PSC calls: samples from the British Isles share a relatively high number of PSC segments with those from Sweden ( S4b Fig ) . Also the low estimated dispersal between Switzerland and Italy is consistent with Swiss samples sharing relatively few PSC segments with Italians given their close proximity ( S4b Fig ) . However , identifying interesting patterns directly from the PSC segment sharing data is not straightforward , and one goal of MAPS ( and EEMS ) is to produce visualizations that point to patterns in the data that suggest deviations from simple isolation by distance . The inferred population size surfaces for the POPRES data show a general increase in sizes through time , with small fluctuations across geography; In our results , the smallest inferred population sizes are in the Balkans and Eastern Europe more generally . This is in agreement with the signal seen previously [20]; however , taken at face value , our results suggest that high PSC sharing in these regions may be due more to consistently low population densities than to historical expansions ( such as the Slavic or Hunnic expansions ) . Although consistent with previous results , our estimates of dispersal and population sizes do not exactly agree with empirical estimates . For example , our estimates of population sizes are consistently lower than the census sizes ( S5 Fig ) . This is to be expected for several reasons . First , census sizes include non-breeding individuals ( juvenile and post-reproductive age ) that do not impact the formation of PSC segments . Second , MAPS is fitting a single population size per location , and in a growing population the best fit population size will be an under-estimate of contemporary size . Third , in a wide class of population genetic models , the effective size , even among reproductive age individuals , is lower than the census size because of factors that inflate the variance in offspring number . Fourth , some discrepancy is expected simply because the stepping-stone population genetic model used here is only a coarse approximation to the complex spatial dynamics of human populations . Finally , there is probably cryptic relatedness in the POPRES samples which can decrease population size estimates . Here , as in EEMS , we use a discrete stepping-stone model to approximate a process that might be more naturally modelled as continuously varying in space [12] . Recent work exploits continuous models to estimate dispersal and population density parameters from sharing of lPSC segments [24 , 30] . However , these methods assume that dispersal and population density are constant across space: extending them to allow these parameters to vary across space could be an interesting avenue for future work . Here , we infer demography given a PSC length bin . These PSC length bins correspond to very approximate time periods , and we report the mean age of the segment in the specified time period to give an idea of the approximate time period under an assumption of a large effective population size ( see Lemma 5 . 3 in S1 Appendix ) . However , as mentioned previously , the variance in the distribution of ages can be very large . A major advancement would be to infer demography explicitly as a function of time . In principle , our method allows for inference of demography across time by treating PSC segments as roughly approximating independent across length bins conditional on the demography , see S1 Appendix . However , this requires fitting multiple migration/population surfaces and is computationally unfeasible with our current MCMC routine . Other computational techniques ( e . g . Variational Bayes or fast optimization of the likelihood ) might make this goal possible .
For the empirical data analysis , we ran MAPS with 200 demes . The MAPS output was obtained by averaging over 20 independent replicates ( the number of MCMC iterations in each replicate was to set 5e6 , number of burn-in iterations set to 2e6 , and we thinned every 2000 iterations ) . We provide the the MAPS here: https://github . com/halasadi/MAPS , and the plotting scripts here: https://github . com/halasadi/plotmaps . Our pipeline to call PSC segments for simulations can be found here: https://github . com/halasadi/ibd_data_pipeline . We follow the recommendations of [27 , 28] and [20] by running BEAGLE multiple times and merging shorter segments . For the empirical data analysis , we use the PSC segments ( “IBD” ) calls from [20] , which can be found here: https://github . com/petrelharp/euroibd . The calls from [20] were obtained by running fastIBD ( implemetned in BEAGLE [27] ) and applying custom post-processing steps derived by simulation . We further applied a filter to retain countries with at least 5 sampled individuals , and removed Russian and Greek individuals to restrict the geographic region to a smaller spatial scale . MAPS assumes a population genetic model consisting of triangular grid of d demes ( or populations ) with symmetric migration . The density of the grid is pre-specified by the user with the consideration that the computational complexity is O ( d3 ) . We use Bayesian inference to estimate the MAPS parameters: the migration rates and coalescent rates M and q_ respectively . Its key components are the likelihood , which measures how well the parameters explain the observed data , and the prior , which captures the expectation that M and q_ have some spatial structure ( in particular , the idea that nearby edges will tend to have similar migration rates and nearby demes have similar coalescent rates ) . MAPS estimates the posterior distribution of Θ=M , q_ given the data . The data used for MAPS consists of a similarity matrix X R = { X i , j R } which denotes the number of PSC segments in a range R = [μ , ν] base-pairs shared between pairs of haploid individuals ( i , j ) ∈ {1 , ⋯ , n} × {1 , ⋯ , n} where n is the number of ( haploid ) individuals . Furthermore , a recombination rate map is required as input for MAPS . The likelihood is a function of the expected value of X i , j R ( E [ X i , j R ] ) . Below we describe the computation of E [ X i , j R ] and the other key components of the likelihood . Finally , we briefly describe the prior used and an MCMC scheme to sample from the posterior distribution of Θ .
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We introduce a novel statistical method to infer migration rates and population sizes across space in recent time periods . Our approach builds upon the previously developed EEMS method , which infers effective migration rates under a dense lattice . Similarly , we infer demographic parameters under a lattice and use a ( Voronoi ) prior to regularize parameters of the model . However , our method differs from EEMS in a few key respects . First , we use the coalescent model parameterized by migration rates and population sizes while EEMS uses a resistance model . As another key difference , our method uses haplotype data while EEMS uses the average genetic distance . A consequence of using haplotype data is that our method can separately estimate migration rates and population sizes , which in essence is done by using a recombination rate map to calibrate the decay of haplotypes over time . An additional useful feature of haplotype data is that , by varying the lengths analyzed , we can infer demography associated with different recent time periods . We call our method MAPS for estimating Migration And Population-size Surfaces . To illustrate MAPS on real data , we analyze a genome-wide SNP dataset on 2224 individuals of European ancestry .
|
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"Abstract",
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"Results",
"Discussion",
"Methods"
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2019
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Estimating recent migration and population-size surfaces
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Spicy foods elicit a pungent or hot and painful sensation that repels almost all mammals . Here , we observe that the tree shrew ( Tupaia belangeri chinensis ) , which possesses a close relationship with primates and can directly and actively consume spicy plants . Our genomic and functional analyses reveal that a single point mutation in the tree shrew’s transient receptor potential vanilloid type-1 ( TRPV1 ) ion channel ( tsV1 ) lowers its sensitivity to capsaicinoids , which enables the unique feeding behavior of tree shrews with regards to pungent plants . We show that strong selection for this residue in tsV1 might be driven by Piper boehmeriaefolium , a spicy plant that geographically overlaps with the tree shrew and produces Cap2 , a capsaicin analog , in abundance . We propose that the mutation in tsV1 is a part of evolutionary adaptation that enables the tree shrew to tolerate pungency , thus widening the range of its diet for better survival .
Many plants contain pungent chemicals that deter animals from consuming them . Particularly , the genus Capsicum encompasses 22 wild species and produces a capsaicinoid called capsaicin , which is a pungent substance [1 , 2] . One of these species , the chili pepper , is a low shrub with capsaicin-containing fruits that are readily accessible to mammals and birds . However , capsaicinoids in these plants repel animals by evoking a sharp and burning sensation through activation of the nociceptor transient receptor potential vanilloid type-1 ( TRPV1 ) ion channel [3–7] . Interestingly , birds are an exception due to two specific point mutations in their TRPV1 channels that render them insensitive to capsaicin [8 , 9] . This adaptation broadens the range of diet in birds and also confers an advantage to the plants , because their seeds can be widely distributed by the birds [10] . Humans have an acute sensitivity to spicy food , and many find it unbearable . Nonetheless , with training , some have learned to enjoy the burning sensation elicited by consuming spicy food [1] , which presumably also confers protection against bacterial and fungal infection in the human digestive system [11] . However , whether pungency tolerance exists in other mammals remains unexplored . The tree shrew ( Tupaia belangeri chinensis ) is a mammal closely related to primates . Genomic analysis suggests that the tree shrew has a high sequence similarity to human [12] . Surprisingly , we found that tree shrews actively fed on the chili pepper when it was provided to them . To understand the molecular mechanism responsible for this capsaicin insensitivity , we employed a combination of behavioral observation , genome scans , mutational analyses , and electrophysiology studies , and we also sought a plausible cause for the behavior change that could not be brought about by a need to consume the chili pepper , a plant that was geographically isolated until recent times . We identified an amino acid change in the tree shrew TRPV1 ( tsV1 ) at the residue that in the homologs of sensitive species forms a hydrogen bond with capsaicinoids and stabilizes the binding , and we show that this change renders tsV1 refractory to capsaicinoid-induced activation . Furthermore , we identified Cap2 , a capsaicin analogue , from Piper boehmeriaefolium [13] , which overlaps geographically with tree shrews . We speculate that Cap2 might act as a potential environmental pressure for positive selection of the molecular change in tsV1 that confers capsaicinoid tolerance .
Among mammals , humans are the only known species that deliberately seeks spicy sensation from food [1] . Fortuitously , we observed that , like humans , tree shrews also actively fed on the chili pepper ( Fig 1A and S1 Movie ) . Moreover , when capsaicin was added to the food , the food intake in mice was significantly reduced in a concentration-dependent manner , whereas we found no such change in tree shrews ( Fig 1B ) . These observations suggest that spiciness elicited by capsaicin is tolerated in tree shrews . To determine whether genomic changes or conditioning is responsible for capsaicin tolerance in tree shrews , we applied a genomic scan for positively selected genes ( PSGs ) among one-to-one orthologous genes in the tree shrew genome and 5 other phylogenetically closely related mammals: humans , chimpanzees , macaques , mice , and rats . The phylogenic relationship of these 6 species is shown in an established species tree ( Fig 1C ) . Three hundred seventy-three PSGs were retained after applying the False Discovery Rate correction to the PSGs ( S2 Data ) . Gene ontology ( GO ) enrichment analysis by Protein Analysis THrough Evolutionary Relationships ( PANTHER ) Overrepresentation Test of the 373 PSGs identified 71 over-represented GO terms ( S1 Table ) . Interestingly , there was a clear enrichment of chemosensory behavior–related genes ( GO: 0007635 , P = 0 . 0329 ) , including trpv1 , as being over-represented by PSGs . This observation suggested that spiciness tolerance in tree shrew may be due to a positive selection of trpv1 in the tree shrew . We took advantage of the capsaicin tolerance to probe the effects of positive selection on the tsV1 channel protein . We first analyzed capsaicin-induced activity in dissociated mouse and tree shrew dorsal root ganglia ( DRG ) neurons by calcium imaging . Consistent with observations in the behavioral tests , we found that tree shrew DRG neurons exhibited a much weaker response to capsaicin compared with mouse DRG neurons ( Fig 1D and 1E ) . This was not caused by a paucity of tsV1 expression , because immunohistochemical and quantitative analyses of tissue sections from tongue and DRG suggested similar levels of TRPV1 protein and mRNA between mouse and the tree shrew ( Fig 1F and 1G ) . In addition , using hematoxylin and eosin ( H&E ) staining , we observed that unlike in mice , capsaicin didn’t cause discernible tissue disruption in the tree shrew ( S1A Fig ) . Furthermore , capsaicin-induced acute pain behavior was absent in tree shrews , despite a high concentration of capsaicin used ( S1B Fig ) . To rule out that the absence of capsaicin-induced acute pain in tree shrews is due to any other defects in the pain sensation pathway , we investigated formalin-induced pain . In mice , local injection of formalin strongly elicited pain ( S1C Fig ) . In contrast to the tolerance to capsaicin , formalin elicited both acute and inflammatory pain in the tree shrew which is similar to mice ( S1C Fig ) . We also observed numerous inflammatory neutrophils and serious disruption of tissue structure in the formalin-injected hind paw of both mice and the tree shrew ( S1D Fig ) . These observations suggest that pain sensation is intact in the tree shrew and are consistent with the hypothesis of a reduced sensitivity of tsV1 to capsaicinoids such as capsaicin . To directly measure the capsaicin sensitivity of tsV1 , we expressed tsV1 in mammalian cells and performed whole-cell recording ( S2A Fig and Fig 2A ) . We observed that the concentration of capsaicin required to activate tsV1 ( EC50: 5 . 2 ± 0 . 13 μM , n = 5 ) is much higher than the concentrations required to activate mouse TRPV1 ( mV1 ) ( EC50: 0 . 2 ± 0 . 07 μM , n = 3 ) ( Fig 2A ) and other mammalian TRPV1 channels we tested ( Fig 2B ) . In contrast , tsV1 showed similar single-channel conductance and similar sensitivity to low pH and heat as the other mammalian TRPV1 channels ( S2B–S2D Fig and S3 Fig ) . Based on these results , we reasoned that capsaicin tolerance we observed was caused by the reduced tsV1 sensitivity to capsaicin . To understand the reduced sensitivity in tsV1 , we first examined the protein sequence of the channel . Significant positive selection signal was detected in tsV1 , and Bayes Empirical Bayes ( BEB ) testing identified 30 sites under positive selection ( Table 1 and S2 Table ) . Since these 30 sites are widely distributed in different structural elements of tsV1 , we constructed chimeric channels between tsV1 and mV1 to identify a region or regions in tsV1 that could cause a reduced binding affinity to capsaicin and thus result in capsaicin tolerance ( Fig 2C ) . We found that a swap of the transmembrane domain IV ( S4 ) including S3–S4 linker had a major impact on capsaicin sensitivity , whereas changing other domains did not have a significant effect ( Fig 2C ) . Based on a homology model of tsV1 ( S4A Fig ) , we found that among the 30 positively selected sites , three ( I561 , C569 , and M579 ) are located within the S4 domain and the S3–S4 linker , which are close to the capsaicin-binding pocket ( Fig 2D ) , suggesting that these residues are more likely to be responsible for the reduced capsaicin sensitivity . To test the functional properties of these three sites , we replaced them with the homologous residues in mV1 and compared their sensitivity to capsaicin with wild type tsV1 by whole-cell recording . M579 in tsV1 corresponds to T551 in mV1 , a site forming a hydrogen bond ( Fig 2E upper panel , dotted line in red ) with capsaicin that stabilizes the binding [14–16] , whereas M579 in tsV1 cannot make a hydrogen bond with capsaicin ( Fig 2E lower panel ) . When we replaced the methionine with a threonine ( M579T ) , which can form the hydrogen bond with capsaicin , the mutant became extremely sensitive to capsaicin with an EC50 value of 0 . 1 ± 0 . 26 μM , which is approximately 50-fold lower than the EC50 of tsV1 ( Fig 2F ) . Conversely , mutant mV1 with T551 replaced by a methionine or a valine which cannot form a hydrogen bond with capsaicin , capsaicin sensitivity was significantly reduced to about 10% of the wild type mV1 ( mV1_T551M , EC50 approximately 2 . 1 μM; mV1_T551V , EC50 approximately 1 . 5 μM , and wild-type mV1 , EC50 approximately 0 . 2 μM ) ( Fig 2G ) . These results suggest that the observed decrease in capsaicin sensitivity is caused by a structural change that reduces the binding affinity between tsV1 and capsaicin . We next explored a plausible environmental factor that could select for the structural change in tsV1 and behavioral change in the species . By sequencing TRPV1 fragments containing the 579 site in 155 wild tree shrews from 5 populations ( Genbank No . MF073026–MF073180 ) , we found that M579 is conserved in all sequenced individuals ( S4D Fig ) , suggesting that it has been fixed at the species level . This excludes the chili pepper , which had been geographically isolated from the tree shrew until it was introduced to South Asia only approximately 300 years ago [2] . Piper boehmeriaefolium ( Miq . ) C . DC . , a spicy Piper species , has a geographical distribution that overlaps that of the tree shrew [17] ( Fig 3A and 3B ) . We therefore investigated if the chemosensory behavior of the tree shrew is P . boehmeriaefolium-related . Video observation ( 48 hours in total ) revealed that wild tree shrews preferred P . boehmeriaefolium over other pungent plants , which was different from wild mice ( Fig 3C ) . Phytochemical investigation illustrated that P . boehmeriaefolium is spicy because it contains a chemical analog of capsaicin ( Fig 3D , we referred to Cap2 ) [13] , which possesses an additional carbon in the “neck” region of capsaicin as well as several small differences in the “tail” region ( Fig 3D ) . Therefore , we hypothesized that the changes in tsV1 have been evolutionarily selected by Cap2 in the Piper species . To test this hypothesis , we chemically synthesized Cap2 ( S4B and S4C Fig ) and added it into the food of tree shrews and mice in different concentrations . We observed that food intake in mice was significantly decreased with the increase in Cap2 concentration; in contrast , increasing Cap2 did not reduce but caused a slight increase in the food intake in tree shrews ( Fig 3E ) . In agreement with the food intake observation , we found that in whole-cell recordings tsV1 exhibited an EC50 of approximately 1 . 9 ± 0 . 03 mM , n = 5 , which was approximately 2 , 500-fold larger than the EC50 of mV1 ( 0 . 74 ± 0 . 05 μM , n = 5 ) and other mammalian TRPV1 ( Fig 3F and 3G ) . These results suggest that ability to feed on P . boehmeriaefolium may be the driver for the spread of tsV1 mutation in the tree shrew . We hypothesized that M579 in tsV1 can also account for the insensitivity to Cap2 because of the structural similarity between capsaicin and Cap2 ( Fig 3D ) . Indeed , when we restored the hydrogen bonding capability at M579 by mutating it to a threonine , the tsV1_M579T mutant became significantly more sensitive to Cap2 ( Fig 4A left panel ) with an EC50 of 2 . 34 ± 0 . 26 μM ( n = 5 ) , which was approximately 1 , 000-fold lower than the wild-type tsV1 ( Fig 4A right panel ) . In addition , mutating the homologous site 551 from threonine to methionine in mV1 dramatically reduced the sensitivity to Cap2 by approximately 1 , 000-fold ( Fig 4B ) . mV1_T551M also exhibited largely diminished calcium signal in response to Cap2 ( Fig 4C and 4D ) . These observations demonstrate that tsV1 M579 ( or mV1 T551 ) has a major impact on Cap2 sensitivity . As the hydroxyl group on the side chain of threonine is expected to form a hydrogen bond with Cap2 to stabilize its binding to the tsV1_M579T mutant , just like its interaction with capsaicin on mV1 , we next replaced M579 in tsV1 with four other amino acids , in addition to threonine , and compared the EC50 of Cap2 . None of the five mutants exhibited a concentration-response curve to the right of the wild-type tsV1; the two mutants—M579T and M579S—that can presumably form a hydrogen bond with capsaicin and Cap2 exhibited large shifts to the left ( Fig 4E ) . This result suggests that methionine at the 579 has been selected to maximally reduce the sensitivity to Cap2 . There are other chemicals that can also activate TRPV1 and elicit a spiciness sensation like capsaicin and Cap2 , such as piperine ( from black pepper ) and gingerol and shogaol ( from ginger ) [1] . To test whether these irritants also contribute to fixation of the M579 mutation , we investigated whether M579 is critical for the binding of these irritants . Although mutating this homologous site in both mV1 and tsV1 ( mV1_T551M or tsV1_M579T ) led to shifts in concentration-response curve of piperine , gingerol , and shogaol ( S5 Fig ) , change in the EC50 of Cap2 ( approximately 1 , 000-fold , Fig 4E ) was much larger than other irritants ( approximately 10-fold for capsaicin; approximately 2-fold for piperine; approximately 6-fold for gingerol; approximately 10-fold for shogaol ) . These results are consistent with our hypothesis that Cap2 , instead of capsaicin and other irritants , is the main driver for the M579 mutation in tsV1 ( Fig 4F ) . This is also consistent with our observation that tree shrews compared to mice preferred P . boehmeriaefolium over other tested pungent plants ( Fig 3C ) and indicates that the chili pepper is not the driver for the M579 in tsV1 ( Fig 4F ) . Our observations together favor the idea that feeding adaptation to P . boehmeriaefolium rich in Cap2 has positive selected for M579 in tsV1 .
In this study , we found that tree shrews can tolerate pungent plants such as the chili pepper and Piper boehmeriaefolium , which are avoided by most animals because of the pungent sensation they elicit . We show that M579 in tsV1 has been strongly and positively selected to render this tree shrew homolog of TRPV1 less sensitive to the pungent chemical Cap2 in P . boehmeriaefolium , a Piper species with an overlapping geographical distribution in South Asia , and we suggest a plausible driver for the functional change in tsV1 and the dietary change in the species ( Fig 4F ) . The TRPV1 channel has been the molecular target for selection in evolution [18 , 19] . For instance , in camels and squirrels , two point mutations occur in the N-terminal ankyrin-repeat domain of TRPV1 to enhance their heat tolerance [20] . In addition , avian TRPV1 with two specific point mutations shows low sensitivity to capsaicin as well , which is consistent with the observation that birds are favored as vectors for seed dispersal [10] . However , it is difficult to determine the contribution of environmental pressure because of the low degrees of sequence conservation between avian and mammalian TRPV1 . We show that the 579 site in tsV1 constitutes a critical molecular determinant; this site is occupied in the tree shrew by a methionine which , unlike the threonine in the TRPV1 of species intolerable to pungency , cannot form a hydrogen bond with capsaicinoid ligands ( Fig 2F and Fig 4 ) . Our suggestion that P . boehmeriaefolium , instead of ginger , black pepper , and chili pepper , is the main environmental stress responsible for the positive selection of M579 is supported by the observation that swapping methionine with threonine or vice versa at this position ( tsV1_M579T or mV1_T551M ) caused significantly more change in sensitivity to Cap2 from P . boehmeriaefolium ( approximately 1 , 000-fold ) than to other irritants , such as piperine , gingerol , and shogaol ( Fig 2F , Fig 4A–4D and S5 Fig ) . The feeding behavior described in Fig 3C also supports this interpretation . Furthermore , the cultivation history of chili peppers in South Asia is only approximately 300 years [2] , yet M579 has been fixed in the tree shrew ( S4D Fig ) , which diverged from humans about 90 . 0 million years ago ( Fig 1C ) . Therefore , feeding adaptation to P . boehmeriaefolium is the most likely explanation to the fixation of this mutation by positive selection , which enabled an expansion of the tree shrew’s dietary repertoire .
All the animal experiments were performed in accordance with recommendations in the Guide for the Care and Use of Laboratory Animals of Kunming Institute of Zoology , Chinese Academy of Sciences . Experimental protocols using animals in this study were approved by the Institutional Animal Care and Use Committees at Kunming Institute of Zoology , Chinese Academy of Sciences ( approval ID: SMKXLLWYH20120520-01 ) . There were 12 , 767 orthologous genes of humans , chimpanzees , macaques , mice , and rats identified by BioMart in the Ensembl public database . OrthMCL identified 13 , 333 one-to-one orthologous genes in humans and the tree shrew by using mRNA and protein sequences from Ensembl ( Human ) and TreeshrewDB ( tree shrew ) [21] . A total of 10 , 060 overlapped one-to-one orthologous genes were identified in all 6 species . For genes that have more than one transcript , only the longest transcripts were retained . For each pair of one-to-one orthologous genes , conserved codons among 6 species were extracted by using the Gblocks with default parameters after alignment by Prank [22] . After trimming , conserved well-aligned sequences shorter than 300 bp were discarded . All gaps ( “-” ) and unknown sites ( “N” ) were removed before positive selection tests by using the CODEML program involved in the PAML [23] package . The topology of the 6 species from Ensembl species tree was used as an input tree in the PAML test . The dN/dS ratios ( ω ) of the tree shrew branch for each orthologous gene were estimated by using free-ratios model . Orthologous genes with dS summed over all branches of the tree >0 . 5 were retained . Test 2 , by comparing the log likelihood ( lnL ) of positive detection model ( A model ) and the corresponding null model with ω2 = 1 fixed ( A null model ) , was used to detect PSGs on the tree shrew branch ( #1 ) . BEB method was used to identify the sites under positive selection . We conducted the False Discovery Rate ( FDR ) [24] method for multi-correction for all orthologous genes . Genes with FDR <0 . 01 were identified as PSGs . For each PSG , matched orthologous human Ensembl gene IDs were used in GO annotation and enrichment tests by using the PANTHER Overrepresentation Test ( http://pantherdb . org/ ) . Orthologous genes with dS summed over all branches on the tree >0 . 5 were used as background gene list . GO term was filtered as the standard: P value of GO term is smaller than 0 . 05 , at least two PSGs involved in one GO , PSGs involved in one GO term is more than the expected genes ( + ) , fold enrichment is greater than or equal to 2 . Only the first-level GO terms were retained . Longest CDS frames of trpv1 from another 17 mammal species were obtained from Ensembl and aligned by MEGA [25] ( see S2 Table ) . Polyphen-2 [26] was used to predict possible impact of amino acid substitutions from human to the tree shrew of 30 BEB sites detected in tree shrew TRPV1 . Piper boehmeriaefolium ( Miq . ) C . DC . ( Piperaceae ) was collected and identified by Dr . Tharanga Aluthwattha from Xishuangbanna Tropical Botanic Garden , Yunnan Province , People’s Republic of China . Wild mice ( Niviventer confucianus ) were identified and provided by Dr . Quan Li from State Key Laboratory of Genetic Resources and Evolution , Kunming Institute of Zoology , Chinese Academy of Sciences , Yunnan Province , People’s Republic of China . Wild tree shrews were provided by Kunming Primate Research Center , Chinese Academy of Sciences , Yunnan Province , People’s Republic of China . Cap2 was synthesized at Zhengzhou Phtdpeptides Pharmaceutical Technology Co . , Ltd . Characterization of Cap2 by NMR and MS matched with prior literature . Capsaicin ( Sigma-Aldrich , United States of America ) and piperine , gingerol , and shogaol ( MedChem Express , USA ) were purchased . The purity of all compounds was > 99% . Wild tree shrews ( both sexes , n = 5 ) or mice ( both sexes , n = 6 ) were captured . Each animal was maintained in an observation chamber ( 100 × 100 × 50 cm3 ) at 25–27 °C and allowed free access to food ( normal laboratory chow ) and tap water ad libitum for at least 5 days before the test . Diet options ( apple , Piper species , chili pepper , garlic , and ginger ) were offered with video recordings . After 48 hours , food intake was quantified . Different concentrations of vanilloid compound ( Cap2 or capsaicin ) in manufactured feeds were made as 100 nM , 1 μM , 10 μM , and 100 μM . Along with normally manufactured feeds , these options were offered respectively in food containers for BALB/c mice ( both sexes , n = 5 ) or clean tree shrews ( both sexes , n = 5 ) . After 24 hours , food intake was quantified . The tongue cDNA library of tree shrews was constructed by using SMART cDNA Library Construction Kit ( Clontech , USA ) , as previously reported [27] . A pair of primers ( 5′-ATGCTGAAGTCTAAGGACGGC-3′ and 5′-CTTCTCCCCTGAAGCCGGGGA-3′ ) was used to clone tsV1 cDNA from the tongue cDNA library of tree shrews . To promote identification of transfected cells , enhanced green fluorescence protein ( eGFP ) was genetically linked to the C terminus of tsV1 cDNA by homologous recombination method , as previously described [28] . Single point mutants of TRPV1 were obtained by using Fast Mutagenesis Kit V2 , ( SBS Genetech Co . , Ltd . , China ) which were sequenced to confirm that site-directed mutagenesis was made . HEK293T cells were cultured in Dulbecco's modified eagle medium ( DMEM ) plus 10% fetal bovine serum with 1% penicillin/streptomycin , incubated at 37 °C in 5% CO2 . Cells were transiently transfected with cDNA constructs by Lipofectamine 2000 ( Life technologies , USA ) following manufacturer's protocol . Patch-clamp recordings were performed 1–2 days after transfection . The macroscopic currents were recorded by employing a HEKA EPC10 amplifier with the PatchMaster software ( HEKA ) . Both pipette solution and bath solution contained 130 mM NaCl , 3 mM HEPES , and 0 . 2 mM EDTA ( pH 7 . 4 ) . The membrane potential was held at 0 mV , the currents were evoked from +80 mV ( 500 ms ) to −80 mV ( 500 ms ) . All recordings were performed at room temperature . The experimental set-up for rapidly heating cell membrane containing expressed TRPV1 channels was described in a previous report [29] . Briefly , a glass pipette was filled with a solution distinct from the bath solution and was centered at the end of the optical fiber . The laser driving power was adjusted to produce junction potential values matching those measured in the same solutions at different temperatures . Capsaicin induced acute pain model was constructed as previously described [28] . Briefly , the right hind paw BALB/c mice or tree shrew was injected with capsaicin ( 100 nM , 1 μM , 10 μM , and 100 μM ) . The time spent licking the injected paw by each animal was recorded ( within 10 minutes ) as soon as the capsaicin was injected . According to our previous study [30] , a formalin-induced inflammatory pain model was established by right hind paw injection of 20 μl 0 . 5% formalin . A digital video camera was used to revalue the time spent licking the injected paw during phase I ( 0–5 minutes post-injection ) and phase II ( 15–30 minutes post-injection ) . Animals were euthanized via CO2 inhalation followed by decapitation . Then , the injected ( capsaicin or formalin ) right hind paws and tongue tissues were cut off and fixed in 10% formalin solution for H&E stain assay . After fixation by 10% formalin and dehydration by an increasing concentration of alcohol , paw materials were embedded in paraffin and sectioned to a thickness of 5 μm using a histocut ( Leica , RM2235 , Germany ) . The same procedure was repeated for tongue tissues of both mouse and tree shrew . Sections of paw tissues were deparaffinized and rehydrated for H&E staining . Similarly , sections of tongue tissues were also deparaffinized and rehydrated for immunohistochemistry ( IHC ) analysis . For IHC analysis , sections were incubated with rabbit polyclonal TRPV1 antibodies ( Thermo Fisher , USA ) and 2% bovine serum albumin ( BSA ) at 37 °C for 1 hour . After washing in PBS , the sections were exposed to horseradish peroxidase labeled antirabbit IgG ( Thermo Fisher , USA ) for 1 hour at room temperature . Immunoreactivity was visualized by incubation with 0 . 05% DAB·4HCl . Stained sections were observed by light microscopy ( Olympus , X81 , Japan ) . Mouse or tree shrew DRG neurons or transiently transfected HEK 293 cells were fixed with 4% paraformaldehyde for 10 minutes . Fixed cells were incubated with rabbit polyclonal TRPV1 antibodies ( Thermo Fisher , USA ) and 2% bovine serum albumin ( BSA ) at 37 °C for 1 hour . After washing in PBS , the cells were incubated with Cy3 labeled antirabbit IgG secondary antibodies ( KPL , USA ) and 2% bovine serum albumin ( BSA ) at 37 °C for 1 hour . One μg/ml DAPI ( Roche Diagnostics , Switzerland ) was used to dye the nuclear DNA . Cy3 was detected with a main beam splitter at 550 nm and a 570-nm long pass emission filter . DAPI was detected with a main beam splitter at 359 nm and a 570-nm long pass emission filter . DAPI-stained cells were viewed under a confocal laser scanning microscope ( Olympus , FV1000 , Japan ) . Total RNA was isolated from DRG by using TRIzol reagent ( Invitrogen ) . cDNA was reverse transcribed from 1 μg of RNA by using M-MLV reverse transcriptase ( Promega ) . Quantitative real-time PCR ( qRT-PCR ) was performed on the Bio-Rad CFX-96 Touch Real-Time Detection System . Primer sequences are listed below . Protein extraction from isolated DRG . Western blotting was done as described previously [31] , and proteins were detected with appropriate primary ( Abcam , UK ) and secondary ( Cell Signaling Technology , USA ) antibodies . Mouse or tree shrew DRG neurons were acutely dissociated and maintained in a short-term primary culture according to procedures as previously described [28] . DRG neuron cells were loaded with Fluo-4 AM in 2 mM Ca2+ Ringer’s solution ( 140 mM NaCl , 5 mM KCl , 2 mM MgCl2 , 10 mM glucose , 2 mM CaCl2 , and 10 mM HEPES , pH 7 . 4 ) . Using ionomycin ( 1 mM ) as blanking control , fluorescence images of DRG neurons were acquired with an Olympus IX71 microscope with Hamamatsu R2 charge-coupled device camera controlled by the MetaFluor Software ( Molecular Devices ) . Fluo-4 was excited by a LED light source ( X-Cite 120LED , Lumen Dynamics ) with a 500/20-nm excitation filter , while fluorescence emission was detected with a 535/30-nm emission filter . Fluorescence images were acquired with automated routines written in MetaMorph software ( Molecular Devices ) and analyzed with Igor Pro ( Wavemetrics ) . tsV1 was modeled based on the cryo-EM structure of rat TRPV1 in capsaicin bound state ( PBD ID: 3J5R ) [32 , 33] . Briefly , the amino acid sequences of tree shrew and rat TRPV1 were first aligned by Clustal Omega [34 , 35] . Then , the homology model of tsV1 was built by the RosettaCM program [36] . Ten thousand models were generated , and the model with the lowest energy was chosen as the final model after being refined with the relax application within the Rosetta program [37] . Capsaicin or Cap2 molecule was docked into the ligand binding pocket of mouse and tree shrew TRPV1 channels as described before [14] . In brief , the RosettaLigand application within the Rosetta program [37 , 38] was used to perform docking . TRPV1 structures were first relaxed within Rosetta program and then the capsaicin was placed roughly in the center of the ligand binding pocket formed by S3 , S4 , S4–S5 linker , and S6 segments . Ten thousand models were generated , and the top 10 models with the lowest binding energy were selected . The model with lowest binding energy among the largest cluster of the top 10 models was used as the representative model . For association analysis , blood samples and extracted DNA were collected from 155 wild tree shrews using TIANamp Genomic DNA kit according to the manufacturer’s instructions . The primer was designed ( CATGGAGACTGCATGGGCAGAAGGGAGCAG ) and sequenced a 1 kb fragment covering the gene region of 579 amino acid site in trpv1 . The wild tree shrews were provided by Kunming Primate Research Center , Chinese Academy of Sciences .
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Most mammals cannot tolerate the pungent sensation , such as that evoked by eating chili peppers . Here , we show that unexpectedly , the tree shrew , a mammal closely related to primates , can consume pungent plants . We determined that this tolerance is caused by an amino acid change in the tree shrew’s transient receptor potential vanilloid type-1 ( TRPV1 ) ion channel , which lowers the channel’s sensitivity to capsaicinoids—the substances that make plants spicy . We attribute the strong selection for this amino acid to an adaptation to consuming Piper boehmeriaefolium , a spicy plant that geographically overlaps with the tree shrew and produces Cap2 , a substance similar to capsaicin , the pungent agent found in chili peppers . Our study suggests an evolutionary and molecular mechanism adopted by the tree shrew to expand its nutritional repertoire .
|
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2018
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Molecular mechanism of the tree shrew’s insensitivity to spiciness
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In December of 2013 , chikungunya virus ( CHIKV ) , an alphavirus in the family Togaviridae , was introduced to the island of Saint Martin in the Caribbean , resulting in the first autochthonous cases reported in the Americas . As of January 2015 , local and imported CHIKV has been reported in 50 American countries with over 1 . 1 million suspected cases . CHIKV causes a severe arthralgic disease for which there are no approved vaccines or therapeutics . Furthermore , the lack of a commercially available , sensitive , and affordable diagnostic assay limits surveillance and control efforts . To address this issue , we utilized an insect-specific alphavirus , Eilat virus ( EILV ) , to develop a diagnostic antigen that does not require biosafety containment facilities to produce . We demonstrated that EILV/CHIKV replicates to high titers in insect cells and can be applied directly in enzyme-linked immunosorbent assays without inactivation , resulting in highly sensitive detection of recent and past CHIKV infection , and outperforming traditional antigen preparations .
The genus Alphavirus in the family Togaviridae is comprised of small , enveloped viruses with single-stranded , positive-sense RNA genomes 11–12 kb in length [1] . The genus includes 31 recognized species classified into eleven complexes based on antigenic and/or genetic similarities [2–4] , with most utilizing mosquitoes as vectors [1–7] . Mosquito-borne alphaviruses can infect mosquito species encompassing at least eight genera as well as many vertebrate taxa [8–12] . This ability to infect vertebrates and mosquitoes enables the maintenance of alphaviruses in endemic cycles with sporadic spillover events into human populations . Infections by Old World alphaviruses including chikungunya ( CHIKV ) , o'nyong-nyong , Sindbis , and Ross River viruses can produce rash and debilitating arthralgia [13] . In contrast , New World alphaviruses such as western ( WEEV ) , eastern , and Venezuelan equine encephalitis ( VEEV ) viruses can cause fatal encephalitis [13] . In 2004 , CHIKV reemerged from Africa and spread to the Indian Ocean Basin , Asia , and Europe causing explosive epidemics affecting millions of people [14–20] . Chikungunya fever ( CHIKF ) is characterized by severe , debilitating , and often chronic arthralgia that can persist for years , resulting in major economic as well as public health impacts [18 , 20–22] . Additionally , CHIKF is not easily diagnosed due to the overlap in initial signs and symptoms with dengue , malaria and other acute febrile illnesses , as well as the lack of high quality , affordable , commercially-available diagnostic assays [23 , 24] . In October of 2013 , CHIKV arrived in the Caribbean from Asia or Oceania and spread to South , Central and North America , resulting in over 1 . 1 million suspected cases as of February 2015 [Pan American Health Organization ( PAHO ) data] . Over 2 , 000 imported CHIKF cases have been detected in the U . S . and transmission in Florida has resulted in 11 autochthonous cases . Transmission in other parts of the U . S . is expected as CHIKV moves northward through Mexico . The large populations of both urban mosquito vectors ( Aedes aegypti and A . albopictus ) throughout most of the Americas , large populations of naive people , and its history in Southeast Asia indicate that CHIKV is likely to remain epidemic and endemic in the Americas for the foreseeable future [25] . Recently , a related alphavirus , Eilat virus ( EILV ) , isolated from Anopheles coustani s . I . mosquitoes was described [26] . EILV groups phylogenetically within the mosquito-borne clade of alphaviruses as a sister to the WEE complex . Although EILV , like other alphaviruses , can replicate to high titers ( >108 PFU/mL ) in mosquito cells , it is unable to replicate in vertebrate cells with blocks at both attachment/entry as well as viral RNA replication levels [27] . These unique EILV characteristics as well as the genetic tractability of alphaviruses provide an opportunity to safely develop antigens that , in contrast to traditional methods , do not require inactivation or expensive containment facilities to produce . Here , we report the development of an EILV/CHIKV chimera and its use as a diagnostic reagent to detect CHIKV infection in humans .
C7/10 cells ( American Type Culture Collection , Rockville , MD ) , derived from A . albopictus mosquitoes , were propagated at 28°C with 5% CO2 in Dulbecco’s minimal essential medium ( DMEM ) containing 10% ( V/V ) fetal bovine serum ( FBS ) , sodium pyruvate ( 1 mM ) , penicillin ( 100 U/mL ) , streptomycin ( 100 μg/mL ) , and 1% ( v/v ) tryptose phosphate broth ( Sigma , St . Louis , MO ) . An infectious cDNA clone encoding the EILV genome was chimerized by replacing its structural polyprotein open reading frame with that of a human CHIKV isolate from the British Virgin Islands ( strain-99659 ) [26 , 28] . The chimera was cloned and rescued as previously described [27] . Briefly , the CHIKV structural polyprotein open reading frame ( ORF ) was reverse transcribed from extracted RNA and PCR-amplified in three fragments between AvrII , Bsu36I , NcoI , and NotI restriction sites . These fragments were then digested and ligated into an infectious clone of EILV described previously [26] between AvrII and NotI sites , replacing the structural polyprotein ORF of EILV . The EILV/CHIKV chimera was amplified by infection of C7/10 cells at a multiplicity ( MOI ) of 0 . 1 PFU/cell and at 48 hours post-infection ( hpi ) , supernatants were harvested and clarified by centrifugation for 10 min at 3 , 000 × g . To generate serum-free EILV/CHIKV for use in indirect enzyme-linked immunosorbent assays ( ELISAs ) , C7/10 monolayers were washed with PBS 6 hours post-infection , and VP-SFM medium ( GIBCO , Grand Island , NY ) containing penicillin ( 100 U/mL ) , streptomycin ( 100 μg/mL ) , and 1% ( v/v ) tryptose phosphate broth ( Sigma ) was added . Cells were incubated for an additional 42 hours and supernatants were harvested and stored at -80°C . To compare EILV/CHIKV as antigen to a traditional antigen preparation , CHIKV ( strain LR2006 OPY1 ) , obtained from the World Reference Center for Emerging Viruses and Arboviruses ( WRCEVA ) at the University of Texas Medical Branch , was amplified by infection of confluent BHK-21 cells , and cell-lysate antigen ( CLA ) was prepared as previously described [29] . Briefly , infected cells were pelleted , washed with ice-cold borate saline buffer , and resuspended in an SDS/Triton X-100 buffer for sonication , followed by clarification by centrifugation and inactivation with 0 . 3% ( v/v ) β-propiolactone . Mouse immune ascitic fluids ( MIAFs ) against CHIKV strain Ross T-36059 , and Gamboa virus strain T-34953 , a bunyavirus used as a negative control , were obtained from the WRCEVA . Mouse immune serum ( MIS ) raised against mosquito salivary proteins was generated as previously described [30] . Briefly , adult CD1 mice were naturally exposed to approximately 20 A . albopictus mosquito bites twice weekly for 4 weeks , at which point serum was collected for use in an ELISA . A mouse IgG monoclonal antibody ( mAb ) against CHIKV , CHK-175 , was used as a quantitative benchmark [31] . For IgM ELISA positive controls , a panel of five IgM/ELISA- and PRNT-positive convalescent sera obtained from patients diagnosed by reverse transcriptase-PCR with CHIKV infection was used . Eight human serum samples positive for either dengue virus ( DENV ) or VEEV but negative for CHIKV by hemagglutination inhibition ( HI ) [32] were used as negative controls . To validate IgM ELISAs , a panel of acute serum samples collected from patients in Mexico with suspected CHIKV infection , based on clinical guidelines set forth by the Centers for Disease Control and Prevention ( CDC ) and PAHO [33] , were characterized by plaque reduction neutralization test ( PRNT ) as described previously [32] . Thirty-two CHIKV PRNT-positive samples were then selected for comparative IgM ELISA . For IgG ELISAs , 32 CHIKV PRNT-positive samples from Bangladesh , collected for a seroprevalence study from healthy individuals , were used . To determine a statistically robust cut-off value for human antibody-capture ELISAs , a panel of 34 human serum samples from Bangladesh , negative for CHIKV by PRNT , was utilized in addition to the 8 negative control samples described above . Immulon 2HB 96-well plates ( Fisher Scientific , Pittsburgh , PA ) were coated with serum-free EILV/CHIKV culture supernatants diluted in PBS , to a final concentration of 5 x 104 PFU per well or with CLA at a 1:400 dilution and incubated overnight at 4°C . These antigen dilutions were optimized in titration experiments against polyclonal sera . Plates were blocked with 100 μL of InBlock buffer ( InBios , Inc . , Seattle , WA ) for 1 h at room temperature ( RT ) and washed 5 times with 300 μL of 0 . 1% Tween-20 in PBS using an automatic plate washer ( BIO-RAD , Model 1575 ImmunoWash , Hercules , CA ) . Serum samples were diluted 1:100 in EB-C sample dilution buffer ( SDB; InBios ) and 2-fold serial dilutions were added to plates followed by incubation for 1 h at RT . Plates were washed as described above , and 50 μL of biotin-conjugated goat anti-mouse IgG ( Jackson ImmunoResearch Laboratories , West Grove , PA ) were added at a dilution of 1:10 , 000 in SDB and plates were incubated for 1 h at RT . Then , plates were washed , and 50 μL streptavidin-conjugated horseradish peroxidase ( HRP ) ( Roche Diagnostics , Indianapolis , IN ) were added at a dilution of 1:10 , 000 in SDB , and plates were incubated for 1 h at RT . Plates were washed and 75 μL of 3 , 3’ , 5 , 5’-tetramethylbenzidine substrate ( TMB; Sigma ) were added , incubated for 10 min at RT , and the reaction was stopped with 50 μL of 0 . 5M sulfuric acid . Absorbance values were read at 450 nm on a VERSAmax tunable microplate reader ( Molecular Devices , Sunnyvale , CA ) . Human serum samples , diluted 1:100 in SDB , were added to human IgM- or IgG-capture 96-well microtiter plates ( InBios ) in 50 μL volumes . After 1 h incubation at 37°C , plates were washed as described above . Cell supernatant containing EILV/CHIKV diluted in 1% BSA in PBS to a concentration of 2 . 5X107 PFU/well was then added and incubated for 1 h at 37°C . A panel of eight anti-CHIKV mouse mAbs was tested independently or in combinations for activity in a capture ELISA . CHK-175 antibody produced the highest signal-to-noise ratio at an optimal concentration of 100 ng/well and was selected for further use as the detecting antibody . CHK-175 diluted in SDB to 100 ng/well was added and incubated for 1 h at 37°C . Plates were washed , 50 μL of goat anti-mouse IgG-HRP conjugated antibody ( Southern Biotech , Birmingham , AL ) diluted 1:5 , 000 in conjugate dilution buffer ( InBios ) were added , and plates were incubated for 1 h at 37°C . Plates were then washed , 75 μL of TMB was added , incubated for 10 min at RT , and the reaction was stopped by the addition of 50 μL 0 . 5M sulfuric acid . The absorbance values were read at 450 nm . Commercially available anti-CHIKV IgM ( ab177848 , Lot: GR195090-3 , Abcam , Cambridge , MA ) and anti-CHIKV IgG Human ELISA Kits ( ab177835 , Lot: GR148047-1 , Abcam ) were used according to manufacturer’s instructions . The stability of EILV/CHIKV was assessed as described previously [34] . EILV/CHIKV was diluted 1:2 in PBS with 1% BSA , TRIS with 1% BSA , or SDB and incubated at 37°C . Antigen was sampled at 0 , 3 , 7 , or 10 days post-incubation and the antigen stability was assessed in IgM-capture ELISA described above . The stability was compared to a 4°C control of EILV/CHIKV and percent of original activity was calculated . Pregnant CD1 mice were obtained from Charles River ( Wilmington , MA ) . Seven-day-old suckling mice were pooled and randomly distributed into three groups of 13 mice each and inoculated intracranially ( IC ) with either 8 log10PFU of EILV/CHIKV , 4 log10PFU of live-attenuated CHIKV strain 181/25 [35] as a positive control for replication and neurovirulence , or mock-infected with PBS . Animals were observed daily for 28 days and sacrificed when they became moribund . Three mice per group were sacrificed on 0 , 3 , 7 , and 14 days post-infection and brain tissue was collected to determine infectious virus content via plaque assay on C7/10 cells as previously described [26] . To compare the activities of EILV/CHIKV versus CLA in indirect ELISAs , and the effects of the EILV/CHIKV and Abcam methods on absorbance values and signal-to-noise ratios , a 2-way ANOVA using a Bonferroni post-hoc test was performed . To compare the effects of different buffer preparations on EILV/CHIKV stability and activity differences between high- , medium- , and low-positive serum groups tested using either EILV/CHIKV or Abcam ELISA , a 2-way ANOVA using Tukey’s multiple comparisons test was performed . All statistical calculations were performed in Prism 6 ( GraphPad Software , Inc . , La Jolla , CA ) . A cut-off absorbance value for CHIKV-positive human samples was calculated as 5 standard deviations above the mean absorbance value of 42 PRNT-negative human serum samples . Deidentified , excess diagnostic serum samples , from Mexico and Bangladesh , were tested under a University of Texas Medical Branch institutional review board-approved protocol with no informed consent required . Animal studies were approved by the UTMB Institutional Animal Care and Use Committee under protocol 02-09-068 . The euthanasia method employed was carbon dioxide exposure followed by decapitation .
The utility of the EILV/CHIKV chimeric virus as a diagnostic antigen was first tested in an indirect ELISA . Plates were coated with EILV/CHIKV at 5 x 104 PFU per well and antigen was detected by both polyclonal and monoclonal antibodies with dilutions from 1:50 to 1:51 , 200 . EB-C sample dilution buffer , anti-Gamboa MIAF , and MIS raised against mosquito salivary proteins were utilized as negative controls . No cross-reactivity with mosquito-sensitized mouse sera was observed and optical density ( OD ) values of all of the negative controls were ≤ 0 . 07 ( Fig 1A ) . In contrast , the mouse anti-CHIKV polyclonal antisera and CHK-175 monoclonal antibody readily detected antigen at all dilutions with OD values from 1 . 1–3 . 2 and 0 . 2–2 . 7 , respectively . Signal-to-noise ratios ranged from ~16–46:1 and ~3–39:1 for polyclonal and monoclonal antibodies , respectively . As antigen was detected at all serum dilutions , an estimated quantitative sensitivity of the EILV/CHIKV ELISA was determined by titrating CHK-175 antibody from 100 μg/mL to 98 ng/mL . The lowest concentration of 98ng/mL was capable of detecting antigen , indicating a very high sensitivity of the assay . In contrast to the results obtained with EILV/CHIKV , CLA could only be detected by the polyclonal sera ( Fig 1B ) . In addition , the OD values obtained with polyclonal sera ranged from 0 . 1–2 . 7 and were significantly lower at all dilutions ( p<0 . 05 ) . EILV/CHIKV antigen was assessed as a diagnostic reagent in a capture ELISA format . IgM- and IgG-capture ELISAs were performed with acute serum samples collected 8 days post-fever onset from patients with RT-PCR-confirmed CHIKV infection . Samples positive for DENV or VEEV ( IAB subtype ) but negative for CHIKV by HI were utilized as negative controls . Serum samples were diluted from 1:50 to 1:51 , 200 and added to IgM- or IgG-capture plates followed by the addition of EILV/CHIKV . Antigen was detected with mouse CHK-175 mAb . Anti-CHIKV IgM was readily detected with OD values ranging from 0 . 23–3 . 0 , whereas the negative controls yielded a mean OD value of 0 . 09 ( Fig 2A ) . Signal-to-noise ratios ranged from 2–45:1 for all dilutions except 1:51 , 200 . Anti-CHIKV IgG was also readily detected with OD values ranging from 1 . 6–2 . 6 , with negative controls yielding a mean OD value of 0 . 09 ( Fig 2B ) . Signal-to-noise ratios ranged from 24–39:1 . No cross-reactivity was observed in either IgM- or IgG-capture ELISAs with anti-VEEV or-DENV human serum . Next , we compared the IgM- and IgG-capture ELISAs utilizing EILV/CHIKV antigen to commercial human IgM- or IgG-capture ELISA Kits ( Abcam ) . A panel of human serum samples from suspected CHIKV-infected individuals in Mexico was screened by PRNT50 and 32 positive samples were selected for IgM ELISAs . A PRNT50 was utilized , instead of PRNT80 , to increase the dynamic range of the assay to allow for more sensitive detection of anti-CHIKV antibodies in the acute phase of disease . For IgG ELISAs , 32 PRNT80-positive samples from Bangladesh , collected from healthy individuals , were selected . Serum samples , 4 positive and 8 negative , used above were selected as controls for both IgM and IgG ELISAs . The negative controls were confirmed CHIKV-negative by HI , and some were positive for either DENV or VEEV by HI . To determine a cut-off value for the IgM and IgG ELISAs , 42 human serum samples negative by CHIKV PRNT80 were utilized ( S1 Table ) . The OD values ranged from 0 . 06–0 . 16 and 0 . 08–0 . 12 for IgM and IgG ELISAs , respectively , and cut-off values of 0 . 18 and 0 . 13 were determined as 5 standard deviations above the mean absorbance value . For the Abcam IgM and IgG kits , positive samples were determined as per the manufacturer’s protocol . The EILV/CHIKV IgM ELISA detected all 32 PRNT50-positive serum samples ( 100% sensitivity ) , whereas the Abcam kit yielded positive results for only 13 ( 41% sensitivity ) , 11 of which had PRNT50 titers >640 ( Table 1 ) . An additional 12 of the 32 samples were inconclusive as per instructions provided with the Abcam kit . The 24 samples with PRNT50 >640 yielded the highest OD values in EILV/CHIKV IgM ELISA ranging from 1 . 0–3 . 3 , and signal-to-noise ratios were 11–36:1 . In contrast , the OD values of 11 samples positive with the Abcam kit ranged from 0 . 54–0 . 7 , with signal-to-noise ratios of 2 . 7–3 . 5:1 . Additionally , the EILV/CHIKV IgM ELISA distinguished between samples with PRNT50 > 640 versus ≤ 320 , whereas no differences could be discerned with the Abcam kit , which detected only 2 of 8 samples with PRNT50 ≤ 320 ( Fig 3A and 3B ) . The EILV/CHIKV IgG ELISA detected all 32 PRNT80-positive serum samples ( 100% sensitivity ) , whereas the Abcam kit detected only 23 ( 72% sensitivity ) ( Table 2 ) . The Abcam kit detected all 12 samples with PRNT80 >640 , whereas it could only detect 7 out of 10 , and 4 out of 10 samples with PRNT80 160–320 , and <80 , respectively . Additionally , 3 samples were inconclusive as per the manufacturer’s instructions , and one of the negative controls tested positive with the Abcam kit . The positive samples produced similar OD values in both kits; however differences in OD values of negative controls were observed with OD values ranging from 0 . 09–0 . 12 in the EILV/CHIKV ELISA compared to 0 . 14–0 . 49 in the Abcam ELISA . Consequently , significant differences in signal-to-noise ratios between EILV/CHIKV and Abcam ELISAs for high ( p<0 . 0001 ) and medium ( p<0 . 05 ) PRNT80 groups were observed . For high-positive samples with PRNT80 >640 , EILV/CHIKV ELISA ratios ranged from 7–17:1 and 2–5:1 in the Abcam ELISA ( Fig 4A and 4B ) . For medium-positive samples with PRNT80 160–320 , the ratios ranged from 3–8:1 in the EILV/CHIKV ELISA and 1–3:1 in the Abcam ELISA . No differences between EILV/CHIKV and Abcam ELISAs were observed in signal-to-noise ratios of samples with PRNT80 <80 . Using the accelerated decay methodology [34] , EILV/CHIKV was tested for its stability in three different buffers . EILV/CHIKV antigen was relatively stable in IgM-capture ELISA , with mean activity values , relative to initial activity , of 90% at 3 days , 87% at 7 days , and 82% at 10 days at 37°C in PBS-based buffer containing 1% BSA ( Fig 5 ) . In contrast , commercial kits generally provide antigen in lyophilized form and , upon reconstitution in buffer , as stated in their protocol , the antigen remains stable for up to 24 hours at 2–8°C . While there was no difference in ELISA activity for EILV/CHIKV stored in PBS ( 1% BSA ) versus SDB at the later time points of 7 and 10 days at 37°C , antigen stored in TRIS ( 1% BSA ) was less stable than that stored in the other two buffers at all time points . Infant mice inoculated IC with 8 log10PFU of EILV/CHIKV showed no signs of disease while those infected with a 10 , 000-fold lower dose of live-attenuated vaccine strain 181/25 did show signs of disease , including hind limb paralysis , hunched posture , and ruffled fur ( Fig 6A ) . In terms of replication , infectious titer of EILV/CHIKV dropped from a mean titer of 1 . 7X107 PFU/mL at day 0 to 1 . 3X102 PFU/mL at day 3 , and could not be detected on day 7 . As expected , positive control strain 181/25 replicated from a mean titer of 9 . 3X102 PFU/mL on day 0 to 3 . 1X107 PFU/mL on day 3 ( Fig 6B ) .
Our results indicate that EILV/CHIKV serves as a cost effective ELISA antigen for serological detection of CHIKV infection . In mosquito cells , this chimera replicates to exceptionally high titers ( 1010 PFU/mL ) , including in serum-free medium . Using a highly sensitive , newborn mouse model , we have demonstrated the replication-incompetence and safety of EILV/CHIKV following IC inoculation . The safety characteristics of EILV/CHIKV eliminate the need for high-level biosafety containment facilities for antigen production , and chemical or physical inactivation , thus maximally preserving native antigens . When applied either in capture- or indirect-ELISA formats using control MIAFs and acute and convalescent human serum samples from the Caribbean and Bangladesh , respectively , we determined that the EILV/CHIKV-based assay provides extremely sensitive indication of infection , outperforming traditional antigens with very high signal-to-noise ratios . While there are no licensed antiviral treatments available for CHIKV infection , early diagnosis is nevertheless important . Currently , patients lacking a laboratory-confirmed diagnosis are often empirically treated with antibiotics or antimalarials due to similar clinical presentations [40] . This can contribute to antimicrobial resistance and unnecessary side effects . In terms of surveillance , early and simple detection of CHIKV infection in resource-poor regions can better inform vector control measures , limiting epidemic spread of disease . Also , distinguishing dengue , which can be life threatening , from CHIKV infection can be important for case management . To detect recent CHIKV infections , IgM ELISAs are effective due to the prompt production following infection ( usually within 4–7 days ) of virus-specific IgM [16] . Additionally , IgM tends to be less cross-reactive among alphaviruses than IgG , resulting in high specificity [36] . Although RT-PCR is effective for diagnosing CHIKF soon after infection , its utility diminishes with time after the onset of signs and symptoms . Typically , by day 5 after symptoms appear , viral RNA levels in serum or plasma fall below detection limits [16] . Several commercial kits are available for the detection of anti-CHIKV IgM antibodies . However , their lack of specificity and sensitivity limits their clinical use [36] . Current PAHO , World Health Organization , and CDC guidelines recommend that in-house IgM ELISAs be implemented for accurate CHIKF diagnostics , and the use of whole virus antigen as opposed to recombinant subunits is recommended [33] . Of the commercial kits , Abcam’s Anti-CHIKV IgM Human ELISA kit is reported to produce comparable results to the CDC IgM ELISA [33] . In our comparative analysis , the EILV/CHIKV IgM ELISA demonstrated improved sensitivity with a maximum signal-to-noise ratio of 35:1 compared to a maximum ratio of 4:1 for the Abcam kit . Overall , the signal-to-noise ratios of the EILV/CHIKV IgM ELISAs were consistently higher than those produced by the Abcam kit . In laboratories that lack access to plate readers to quantify optical density , high signal-to-noise ratios can aid in the differentiation of positive and negative samples by simple visual observation . Of the 32 positive controls that we tested , 6 were collected between 4 and 5 days after the onset of symptoms . Of those , 5 had signal-to-noise ratios of 12–35:1 , allowing for confident identification of CHIKV IgM-positivity without the need for a plate reader . Samples collected less than 4 days after onset would require the use of a plate reader . For reliable detection of acute CHIKV-infection , EILV/CHIKV IgM-capture ELISA can be used alone , or in conjunction with , reverse transcriptase-PCR testing . Traditional approaches to antigen production for alphaviruses require infection of cell cultures or mouse brains in biosafety facilities , followed by time-consuming and expensive procedures to purify , concentrate , and inactivate the virus [37] . Manipulations such as these also have the potential to adversely affect the antigen , resulting in loss of epitopes . For instance , our mouse anti-CHIKV mAb readily detected EILV/CHIKV-derived antigen but not that derived from CLA ( Fig 1 ) . Recently , it was reported that complete CHIKV inactivation while retaining acceptable ELISA activity requires gamma-irradiation , followed by β-propiolactone-inactivation [38] . Furthermore , such preparations are unstable at 4°C , requiring that the antigen be lyophilized for storage longer than 24 hours [38] . As a result , the cost of antigen production from CHIKV cultures can be high and many of the commercially available ELISA kits are prohibitively expensive for clinical laboratories in developing countries endemic for alphaviruses . Recombinant protein antigens , derived from cloning and expressing partial viral genomes , can sometimes be missing critical conformational epitopes or may not fold correctly during production , resulting in serologic reduced sensitivity . Virus-like particle antigens , on the other hand , should contain conformational epitopes , but concentration and purification steps can complicate production [41] . Using the EILV chimeric platform , the cost of production can be reduced by eliminating the need for containment , purification , concentration , and inactivation . EILV/CHIKV also displays remarkable stability in liquid buffer , with an estimated shelf life at 4°C of >1 year . These qualities suggest that EILV-based chimeras are superior to traditional inactivated virus antigens for alphavirus diagnostics . While we have shown the utility of an EILV-based chimera as an ELISA antigen , further testing and evaluation is needed to define parameters for the clear discrimination between positive and negative results . We have shown that our anti-CHIKV IgM and IgG ELISAs can distinguish between human infections caused by CHIKV and VEEV or DENV with a high degree of signal separation . However , because other closely related alphaviruses co-circulate in most if not all CHIKF-endemic regions ( e . g . Mayaro virus in South America [39] ) , more extensive testing is needed to rule out false positives due to cross-reactivity with antibodies elicited by other alphaviruses , and thus determine the specificity of this assay . Also , while we have performed accelerated-decay studies to evaluate the stability of EILV/CHIKV in liquid storage , real-time stability studies need to be performed to determine the long-term stability of the antigen at 4°C .
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We have developed an innovative approach to production of alphavirus antigens for use in diagnostic assays that results in reduced production complexity as well as improved sensitivity in application . By generating recombinant viruses that contain the structural protein genes of pathogenic alphaviruses and the nonstructural protein genes of an insect-specific alphavirus , Eilat virus , we have been able to produce insect-restricted viruses that are antigenically identical to their pathogenic counterparts . The insect-specific nature of these chimeric viruses yields an advantageous safety profile and allows for safe handling of the antigen at the bench top . Traditional antigens , produced from wild-type virus , require extensive processing , from growth at biosafety level 3 to concentration and inactivation , followed by lyophilization , which often compromises antigen reactivity and is financially costly . Furthermore , current inactivation methods are imperfect processes that have historically resulted in residual live virus and subsequent breach of containment when used in a diagnostic setting . Other approaches , such as recombinant antigens generated from viral particle subunits , are missing conformational epitopes and their application results in reduced sensitivity . Here we describe the development of a diagnostic assay using this technology for the detection of chikungunya infection in humans .
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[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
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Utilization of an Eilat Virus-Based Chimera for Serological Detection of Chikungunya Infection
|
The adherens junctions between epithelial cells involve a protein complex formed by E-cadherin , β-catenin , α-catenin and F-actin . The stability of this complex was a puzzle for many years , since in vitro studies could reconstitute various stable subsets of the individual proteins , but never the entirety . The missing ingredient turned out to be mechanical tension: a recent experiment that applied physiological forces to the complex with an optical tweezer dramatically increased its lifetime , a phenomenon known as catch bonding . However , in the absence of a crystal structure for the full complex , the microscopic details of the catch bond mechanism remain mysterious . Building on structural clues that point to α-catenin as the force transducer , we present a quantitative theoretical model for how the catch bond arises , fully accounting for the experimental lifetime distributions . The underlying hypothesis is that force induces a rotational transition between two conformations of α-catenin , overcoming a significant energy barrier due to a network of salt bridges . This transition allosterically regulates the energies at the interface between α-catenin and F-actin . The model allows us to predict these energetic changes , as well as highlighting the importance of the salt bridge rotational barrier . By stabilizing one of the α-catenin states , this barrier could play a role in how the complex responds to additional in vivo binding partners like vinculin . Since significant conformational energy barriers are a common feature of other adhesion systems that exhibit catch bonds , our model can be adapted into a general theoretical framework for integrating structure and function in a variety of force-regulated protein complexes .
The development and maintenance of tissues in multicellular organisms requires a diverse array of structural elements that link cells to each other and to the extracellular matrix [1 , 2] . For epithelial tissues the main players in cell-cell adhesion are the proteins of the adherens junction complex: transmembrane cadherins and their binding partners that connect the actin cytoskletons of neighboring cells . To understand both healthy tissue architecture and abnormalities that lead to weakening of adhesion in epithelial tumors [3] , it is necessary to decipher the underlying molecular mechanisms that regulate the stability of the junctions . Identifying the binding partners of cadherin , their functional roles and interplay under varying environmental conditions , has been a major research goal over the last three decades [2] . The great challenge in achieving this goal is that binding between proteins is not a simple sum of pairwise interactions: the strength of adhesion between any two partners can be allosterically regulated by the presence or absence of other proteins in the complex , as well as conformational changes induced by external factors like mechanical tension [4] . For example , early studies established that the cytoplasmic domain of E-cadherin can bind to β-catenin [5 , 6] , and β-catenin can in turn bind to αE-catenin [7] . Since the latter was known to independently bind F-actin [8] , naively one would assume that αE-catenin would be the bridge linking E-cadherin/β-catenin to F-actin , forming a minimal recipe for an adherens junction complex ( see the schematic model in Fig 1 ) . However subsequent in vitro experiments with purified proteins cast doubts on this model , showing that while E-cadherin/β-catenin/αE-catenin formed a stable complex , it had significantly lower affinity for F-actin than αE-catenin alone [9 , 10] . This puzzling result was only clarified three years ago , when Buckley et al . added one more ingredient into the mix: applying physiological ( pN-level ) forces to the entire cadherin-catenin-actin ( CCA ) system in an optical tweezer [11] . Such external forces mimic the mechanical loads which the complex would feel in vivo , and thus would be a more realistic context to study complex formation than the earlier experiments in the absence of load . The results were dramatic: the mean lifetime of the CCA complex increased by a factor of 20 as force was increased from 0 to 10 pN , an unusual force-induced strengthening known as catch bonding [12] . The lifetime then fell off exponentially at higher forces , the conventional slip bond decay expected for most biological bonds under tension . The minimal CCA model of the adherens junction gained a new dimension of dynamic complexity: under the right amount of external load , the bond with actin is stabilized up to lifetimes of ∼1 s , perhaps long enough for vinculin , an additional binding partner between αE-catenin and actin to attach and strengthen the junction [13 , 14] . Catch bonding has now been observed in a variety of adhesion and receptor proteins complexed with particular ligands , among them selectins [12] , integrins [15] , bacterial FimH [16] , and the αβ T-cell receptor [17] . The phenomenon is not limited to protein-ligand complexes , but can occur even in single knotted proteins [18] , α-helices [19] , and force-sensitive functional groups in polymeric materials [20] . One of the most recent observations has been in vinculin [14] binding to actin , where the degree of strengthening under load also depends on the direction of the force . While all these examples highlight the crucial role of tension in regulating interactions , many of them also share the common feature that the structural and energetic details of how this regulation occurs at the molecular level remain largely a mystery . The force spectroscopy experiments that demonstrate protein-ligand catch bonding reveal only the distributions of unbinding times at different forces . We know from very general theoretical considerations that the underlying free energy landscape of a catch bond must necessarily be complex: a simple landscape with a single bound state energy well , and an end-to-end extension that increases monotonically with force , will always yield slip bond behavior [21] . Thus the most likely scenario for catch bonding is a landscape with heterogeneous bound states [22] , corresponding to different molecular conformations that can dynamically interconvert under force . But for any specific catch bond system , like CCA , this hypothesis leads to a host of difficult questions: what are the structural differences between the different conformational states ? What are the energy barriers between those states ? For each state , what are the associated changes in the interaction energies at the bond interface , which are ultimately responsible for the catch bond behavior ? Modeling can assist in tackling these issues , but all current theoretical approaches , despite their various strengths , fall short of being able to directly answer the above questions . The most widely used descriptions of catch bonds are phenomenological [23–27] , typically based on a kinetic network of strongly and weakly bound states [24 , 28] , with force biasing the system toward the strong state . While these models can fit experimental data and capture the essential conceptual basis of catch bonding—conformational heterogeneity—they are expressed in terms of transition rates between states . There is no direct connection between the fitted parameters and the structural features of those states , no way of estimating energy barriers , and no ability to rationalize or predict the results of mutation experiments on the bond lifetimes . Atomistic molecular dynamics simulations give important structural insights [29–32] , but have their own limitations: conformational transitions and bond breaking in adhesion complexes at physiological forces typically occur on timescales ( ms—s ) many orders of magnitude larger than those accessible by all-atom simulations , precluding direct comparison to force spectroscopy experiments . Thus a compromise is needed , an approach that is able to fit experimental data , but with results that also have a concrete structural interpretation . A recent study on the catch bonding in P- and L-selectin adhesion proteins pointed to a possible solution to this problem , introducing a novel , structure-based theory [33] . It provided an analytically solvable model for the mean bond lifetime , whose parameters could be directly linked to the energetics of the interface between the selectin protein and its ligand , as well as structural length scales in the complex . All the fitted parameters were physically reasonable , and in particular the extracted energies were consistent with available crystal structure data on the hydrogen bonding network at the interface . Such a model could for the first time rationalize how particular interfacial energy changes due to mutations would affect the observable bond dynamics . Unfortunately even this approach has an important shortcoming: it assumes the structural transition that occurs under force ( in this case the rotation of two selectin domains with respect to each other ) does not involve a significant energy barrier . In other words , the transition occurs on timescales much shorter than the mean bond lifetime . At any given force , the model thus yields a probability distribution of lifetimes ( also known as a bond survival probability ) that is single-exponential . While the selectin-ligand and other systems [25 , 34 , 35] considered in Ref . [33] do exhibit single-exponential survival probabilities experimentally , the majority of adhesion systems where data is available do not , including CCA [11 , 15 , 36–39] . Thus there is a need for a model that is structure-based , analytically tractable , and which can account for the full complexity of bond survival probabilities observed empirically . The theory developed in the current work fulfills all these criteria . It reproduces the experimental lifetime distributions of CCA , and also links them to existing structural information on the conformations of αE-catenin . It provides the first estimates of the energy barrier height between these conformations as the complex remodels under force , as well as the resulting energetic changes at the actin interface . These predictions allow us to suggest a future set of experiments to validate the model . They also give insights into the role of the catenin energy barrier in physiological contexts , where a specific conformation of CCA may be required for efficient binding of vinculin to further stabilize the complex [14] . While our focus is on a single system , the theory framework itself is quite general , and can be be readily adapted to other cases . It subsumes earlier models of bond dynamics as special cases in certain limits , including both the barrier-less selectin model and the conventional Bell model for slip bonds . It thus has the potential to provide a unified analytical formalism for interpreting data from the entire spectrum of force-regulated adhesion complexes seen in nature .
The key structural hypothesis underlying our theory is that conformational changes in the CCA complex induced by force allosterically regulate the interaction strength between F-actin and the C-terminal F-actin binding domain ( FABD ) [8] of αE-catenin ( see schematic model in Fig 1 ) . In the absence of a crystal structure of the FABD-actin interface , many questions remain about its molecular details [40 , 41] , and among the goals of our approach is to elucidate the overall actin-FABD bond energy and how it varies between different CCA conformations . The precise nature of the conformational changes that occur under tension is also not definitively established , though various lines of evidence point to the central role played by αE-catenin as the force transducer [42 , 43] , including recent dynamic FRET visualization of reversible conformational changes in the central domains of αE-catenin in a CCA complex under tension in living cells [44] . Fragmentary crystal structures of these central domains [43] suggest the potential of two alpha-helical bundles known as M2 and M3 ( residues 396-506 and 507-631 respectively ) to adopt different angles with respect to each other . The angle between the bundles ( denoted by α in Fig 1 ) is likely to alter under applied tension , and thus the rotation of M3 with respect to M2 is a natural candidate for the main force-sensitive conformational change [32 , 43] . For a catch bond to exist , conformations with small α should be associated with weaker FABD-actin binding , and those with larger α with stronger FABD-actin binding . As applied tension biases the system toward the latter conformations , this will lead to a regime where the effective bond lifetime increases with force . This rotation mechanism of catch-bond formation , where the relative orientation between two protein domains is coupled to the bond strength , has proven successful in explaining both experimentally and theoretically the catch bonds in several selectin systems [33 , 45] , and has recently been suggested as the underlying mechanism in catch bonds between the Notch receptor and certain ligands [36] . One important complication for αE-catenin , not present in the selectin cases , is the existence of a significant energy barrier to rotation: crystal structures [41 , 43] and molecular dynamics simulations [32] highlight a number of salt bridges among the M-domains that stabilize the small-α orientation of M2 and M3 . This will prove a crucial ingredient in explaining the dynamics and functional role of the bond , as we will discuss in more detail later . Synthesizing all these structural considerations into an analytically tractable model , we will posit a minimal Hamiltonian U ( r , θ ) for the FABD-actin bond . The conformation-dependence of the bond is encoded in two structural variables ( see Fig 1 ) : i ) the magnitude r = |r| of the vector r between the rotation pivot point ( i . e . the junction of the M2 and M3 domains ) and the FABD-actin interface; ii ) the angle θ between r and the applied force F z ^ acting on the bond through the actin . The overall geometry of αE-catenin relative to actin in Fig 1 mimics the optical tweezer experimental setup of Ref . [11] , whose bond lifetime results we will analyze . That setup was in turn inspired by electron tomographic images showing the organization of actin filaments near the membrane relative to CCA complexes . Fixing z ^ as the actin direction , the M2 domain could have an offset angle ϕ relative to z , making the relationship between the M2-M3 domain angle α and θ have the form: α = π − θ − ϕ . ( As discussed in the next section on parameter estimation , the Ref . [11] experimental data was consistent with ϕ ≈ 0° to within a few degrees . ) Because of steric effects between the domains and the nature of their junction , we assume the angle α can only take on values in some range αmin ≤ α ≤ αmax , which means θ is restricted to the corresponding range θmax ≥ θ ≥ θmin , where θmax ( min ) ≡ π − αmin ( max ) − ϕ . The Hamiltonian U ( r , θ ) has the form: U ( r , θ ) = 1 2 k ( θ ) ( r - r 0 ) 2 - F r cos θ + C ( θ ) ( 1 ) where k ( θ ) = k 0 + k 1 ( 1 + cos θ ) , C ( θ ) = { H ( cos θ - cos θ max ) cos θ c - cos θ max , θ ≥ θ c ( H - G ) ( cos θ - cos θ min ) cos θ c - cos θ min + G , θ < θ c . ( 2 ) Let us consider each of the terms in Eq ( 1 ) in turn . The first term in the Hamiltonian U is an effective bond elastic energy with angle-dependent spring constant k ( θ ) and natural bond length r0 . The distance r serves as an effective reaction coordinate for the bond , with bond rupture occurring if r > r0 + d , where d is the transition state distance . Thus the free energy barrier to bond rupture is k ( θ ) d2/2 , which depends on the conformation through k ( θ ) . Any angular function k ( θ ) can be expanded in Legendre polynomials Pl ( cos θ ) , and for our purposes it is sufficient to keep the two lowest-order terms ( l = 0 , 1 ) in the expansion , k ( θ ) = k0 + k1 ( 1 + cos θ ) , with coefficients k0 , k1 > 0 . This function describes the key feature of the allosteric coupling between the αE-catenin conformation and the bond strength: as θ decreases under force , k ( θ ) increases , leading to a higher energy barrier to rupture . The extent of the bond strengthening is determined by the magnitude of k1 . In analyzing the bond energetics later , it will be useful to express the role of k0 , k1 equivalently through two energy parameters E0 , E1 that have simpler physical interpretations . E0 is the free energy barrier to rupture at α = αmin when F = 0 , given by E0 = ( k0 + k1 ( 1 + cos θmax ) ) d2/2 , and E0 + E1 is the free energy barrier to rupture at α = αmax when F = 0 . The difference in barrier heights from αmin to αmax ( responsible for the bond strengthening ) is E1 = k1 ( cos θmin − cos θmax ) d2/2 . The second term in U describes the coupling of the Hamiltonian to the external applied force of magnitude F . It tilts the energy landscape toward larger r ( increasing the chances of rupture at a given θ ) and smaller θ ( or equivalently larger α ) . The final term C ( θ ) in U describes a free energy barrier between the angular conformational states located at a particular transition angle αc = π − θc − ϕ . This effectively subdivides the angular conformational space into two basins: a small inter-domain angle region ( α ≤ αc or θ ≥ θc ) and a large inter-domain angle region ( α > αc or θ < θc ) . The barrier passing from small to large α has height H , and the barrier returning from large to small α has height H–G , with a possible free energy offset G between the two basins . As in the case of k ( θ ) , we keep only terms up to linear order in cos θ , and make the barrier between the two regions cusp-like for analytical convenience . Using a more complicated form of C ( θ ) , with a smooth rather than cusp-like barrier , would not significantly alter the results of the model ( i . e . it would only lead to small corrections ∼kBT in the fitted results for the energy barriers , where kB is the Boltzmann constant and T the temperature ) . A representative energy landscape for U at F = 0 is drawn in Fig 2 in terms of r and α , showing the two wells corresponding to the small α and large α conformational states . The dynamics on this landscape is assumed to be described by diffusion of the vector r obeying a Fokker-Planck equation with potential U and diffusivity D = kBT/6πηr0 , since the motion corresponds to a rearrangement of a protein domain with characteristic size r0 . Here η is the viscosity of water , and for simplicity we ignore any prefactor due to the details of the domain shape in the diffusivity . The corrections due to such a prefactor are small , since it contributes only logarithmically to the fitted energies [33] . Reflecting boundary conditions are assumed at θmin and θmax . The two main dynamical quantities of experimental interest are: ( i ) the mean bond lifetime τ ( F ) , defined as the average time it takes to reach bond rupture , r = r0 + d , after the onset of an applied force of magnitude F . Prior to the force onset , the system is assumed to have equilibrated at zero force , in accordance with the experimental analysis in Ref . [11]; ( ii ) the survival probability distribution ΣF ( t ) , defined as the probability that a bond has not yet ruptured by time t for a given F . The two quantities are related through τ ( F ) = ∫ 0 ∞ d t Σ F ( t ) . Calculating either τ ( F ) or ΣF ( t ) analytically is non-trivial for a multi-dimensional potential like U , but we can take advantage of the double-well structure of the energy landscape . As shown in detail in the S1 Appendix , we first find approximate analytical expressions for four individual transition rates: crossing the barrier from the small to large α well , the reverse transition , bond rupture directly from the small α well , and bond rupture directly from the large α well . We then combine these expressions into analytical results for τ ( F ) and ΣF ( t ) in terms of the Hamiltonian parameters . The final expressions for τ ( F ) and ΣF ( t ) in the S1 Appendix are rather complex . But as described in the next section , ΣF ( t ) can be readily incorporated into a maximum likelihood estimation approach to find best-fit Hamiltonian parameters given an experimental data set , i . e . measurements of bond lifetimes at various forces . Moreover τ ( F ) reduces to earlier , simpler models of bond dynamics in certain limits . When H = G = 0 , θmin = 0 , θmax = π , we exactly recover the expression for τ ( F ) in the absence of an angular barrier ( and a corresponding ΣF ( t ) which is approximately single-exponential ) , used to describe selectin-ligand catch bonds in Ref . [33] ( see details in the S1 Appendix ) . If in addition we set k1 = 0 , so that k ( θ ) = k0 becomes independent of θ , we do not have any force-enhancement of the bond lifetime . In this limit τ ( F ) ∝ exp ( −Fd/kB T ) , the classic Bell model for conventional slip bonds [46] . The fact that we can smoothly interpolate between different regimes in parameter space , describing qualitatively different modes of force regulation , is one of the strengths of our approach . This allows us , for example , to make predictions for possible mutation experiments that alter the system parameters , and see to what extent the dynamics are robust to such changes .
To estimate the Hamiltonian parameters and gain insights into the structural mechanisms of catch bonding in the CCA complex , we fit the model to the raw data from the optical tweezer force spectroscopy experiment in Ref . [11] . This data consists of 803 measurements of the bond lifetime under varying force conditions from F = 0 . 7–33 pN , the same dataset whose histogram is depicted in Fig . 4A of Ref . [11] . For a given parameter set and force F , the probability to observe a bond lifetime between t and t + dt is −dt dΣF ( t ) /dt . We could thus construct an overall likelihood function for the data set given the parameters ( details in the S1 Appendix ) , and maximize it to find the best estimate for the parameters . For numerical convenience , it was useful to do the fitting in two stages: in the first stage we fixed values for the minimum M2-M3 inter-domain angle αmin and angle offset ϕ , and then maximized the likelihood function over the remaining parameters for these fixed values . In the second stage we then repeated this procedure for different choices of αmin and ϕ , to find the overall optimum . The largest likelihoods occurred in the range αmin = 40–50° and ϕ = −5 to 5° , yielding results for the remaining parameters identical to within error bars . The best-fit values reported in Table 1 are for αmin = 48° and ϕ = 0° . The predicted αmin range is consistent with available structural information . Though the experiment [11] was done using monomeric zebrafish αE-catenin , for which there is no crystal structure , we can compare to known homologous structures from other species and computational structure prediction results . 47° was the smallest angle observed in an analysis of available crystal structure fragments of the M2-M3 domains from mouse and human αE-catenin [43] , and 48° is the M2-M3 angle observed in the individual monomers of the full-length human αE-catenin homodimer ( PDB: 4IGG ) [41] . Plugging the zebrafish αE-catenin sequence into the I-TASSER structure prediction server [47 , 48] yields an M2-M3 angle of 45 ± 1° among the five best structures . The theoretical mean bond lifetime τ ( F ) is compared to the experimental results from Ref . [11] in Fig 3 , and the analogous comparison for the survival probabilities ΣF ( t ) at different F is shown in Fig 4 . The agreement between theory and experiment is excellent , with the model capturing not only the catch bond trend in τ ( F ) , but also the clear double-exponential behavior in ΣF ( t ) . As we will discuss in more detail below , the observation of two exponential regimes is closely connected to the presence of a significant energy barrier between the small α and large α conformations . The value of the model comes not just from the fact that it can fit the experimental data , but that its parameters have a direct physical interpretation that illuminates the structural mechanism of the CCA catch bond . The energy barrier at the transition angle αc = 53° divides the parameter space into two basins: a narrow basin between αmin = 48° to αc , and a much wider basin between αc and αmax = 169° . The narrow range suggests the M3 domain is held rigidly in place relative to M2 in the small α case , with limited rotational mobility , but once the stabilizing interactions at the hinge between M2 and M3 are broken , M3 can swing out to a larger angle . Of course the idea of solid body rotation about a hinge is a simplification: the protein domains are plastic objects that can continuously deform under tension , but picturing an overall rotation is still a useful first approximation . The parameter r0 = 1 . 7 nm , the distance between the hinge and the FABD-actin interface in the simple picture , can more accurately be interpreted as the effective size of the protein regions undergoing reorientation under force . The strength of the interactions in the hinge region is reflected in the angular energy barrier height H = 25 kBT , whose full significance we will explore below . The existence of this barrier is supported by corroborating evidence from a crystal structure [41] of αE-catenin ( PDB: 4IGG ) , which shows five inter-domain salt bridges in the hinge region where the M1 , M2 , and M3 domains meet ( Fig 5 ) . If each salt bridge roughly contributes 4–8 kBT to the overall barrier [49] , this is consistent with the magnitude of H . Molecular dynamics simulations also point to the stabilizing role of the salt bridges . Li et al . [32] compared trajectories measuring the M2-M3 angle for the wild-type structure , initially starting in the small α state , to trajectories of mutants where one of the salt bridges is disrupted ( i . e . E521A or R551A ) . The latter show the system venturing more readily to larger angles relative to the wild-type , as expected for a smaller barrier H . Having two conformational states at small and large α in itself does not guarantee catch bond behavior . What leads to lifetime enhancement under force is the fact that these states are allosterically coupled to the strength of the FABD-actin bond , which changes from E0 = 21 . 8 kBT at small α to E0 + E1 = 27 . 6 kBT at large α . Though we do not have any crystal structure of the FABD-actin interface , it is instructive to compare the value of E0 + E1 to a different catch bond system: the P-selectin complex with the ligand PSGL-1 , where E0 + E1 = 27 kBT [33] in the extended state favored at larger forces . The peak bond lifetime in P-selectin/PSGL-1 ( ∼1 . 1 s ) is also very similar to CCA ( ∼1 . 1 s in Fig 3 ) . Conveniently we do have the crystal structure of P-selectin-PSGL-1 in the extended conformation ( PDB: 1G1S ) [50] , showing that 20 hydrogen bonds contribute to E0 + E1 , consistent with a contribution of 1 . 2–1 . 5 kBT per hydrogen bond , typical for hydrogen bonds in proteins [51] . We thus predict a similar number of hydrogen bonds at the FABD-actin interface in the large angle state ( or fewer if salt bridges are involved ) . The allosteric change between the angular states translates into an interface energy difference of E1 = 5 . 8 kBT , about 4-5 hydrogen bonds or one salt bridge . The energy offset parameter G = 5 kBT plays the important role of biasing the system toward small α when the force is small . The equilibrium probability p S 0 of having α < αc at F = 0 is p S 0 = 0 . 77 ( see S1 Appendix for the derivation ) . As F is increased , the energy landscape is tilted toward higher α , and the barrier to FABD-actin bond rupture shifts from E0 to E0 + E1 , causing the lifetime enhancement . But the fact that the system is equilibrated at F = 0 before the application of force means that both large and small angle conformations are initially populated . The significant angular barrier H and the finite bond lifetime means that these populations do not necessarily have a chance to fully re-equilibrate once F > 0 is applied , during the time before rupture occurs . These two populations , one with a smaller barrier to rupture than the other , explain the distinct double-exponential behavior of ΣF ( t ) ( Fig 4; see also Fig . S2C of the SI ) . To understand this more concretely , a useful quantity is the probability of being in the small α state at the moment of rupture , the so-called splitting probability πS ( details given in the S1 Appendix ) . In the hypothetical scenario of arbitrarily long-lived bonds , where there is time for many transitions between the small and large α states , πS ≈ pS , the equilibrium probability of being in the small α state . But in many cases the bond lifetime is too short for equilibration , and πS may be very different from pS . For example at F = 15 . 1 pN ( the last panel in Fig 4 ) , pS = 10−4 , but πS = 0 . 47 . The tiny value of pS means that , given enough time , the initial fraction , p S 0 = 0 . 77 , of systems that start at small α should eventually transition to the large α state preferred at high forces , and almost never return . If that were actually the case , the survival probability at F = 15 . 1 pN would have been to very good approximation a single exponential , since rupture would occur almost entirely from the large α state . In reality , because of the barrier H slowing down angular transitions , the majority of those small α systems do not have enough time to transition . They thus stay in the small α state until rupture , giving a sizable πS . This leads to a short lifetime exponential regime in ΣF ( t ) , in addition to the longer lifetime exponential regime corresponding to ruptures from large α . The final parameter in the model , the transition state distance d = 0 . 56 nm , represents how much the FABD-actin bond interface can be deformed before rupture . The value is within the range expected of most proteins ( <2 nm ) [52] . Putting everything together , we thus see that the fitted model parameters are all within physically realistic ranges , and consistent with all the available evidence both from the Buckley et al . experiment and earlier studies .
Disrupting the stability of the hinge region ( Fig 5 ) with mutations at the M2-M3 interface ( R551A ) or M1-M3 interface ( E521A ) has been experimentally investigated to probe the role of the hinge in vinculin binding [43] . The underlying presumption is that the large α conformation , which is more accessible when the hinge is destabilized , exposes the vinculin binding site in the M1 domain . This would explain the enhanced binding affinity of the R551A and E521A mutants to the D1 domain of vinculin seen in the experiments . Of course in nature , access to the large α conformation is controlled not by mutations to the hinge , but by application of force , leading to the speculation that the αE-catenin system acts like a force-dependent “switch” [43] , with tension favoring a large α conformation , which in turn enhances both vinculin and F-actin bond strengths . In the context of the model , there are two scenarios for what might occur when the salt-bridge network at the hinge is disrupted: ( i ) the angular barrier energy H is decreased , since this is the parameter most directly related to the stability of the hinge , but other parameters in the model remain unaffected; ( ii ) the decrease of H is allosterically coupled to changes in the FABD-actin interfaces energies E0 , E1 or other structural parameters . The latter would be reminiscent of the case of L-selectin , where experimental mutations at the hinge between the lectin and EGF domains [25] led to allosteric changes in energies at the ligand-binding interface [33] . The possibility of scenario ( ii ) will have to await future experimental data , but we can explore scenario ( i ) theoretically . This also allows us to investigate the biological significance of the angular barrier H . Fig 6A shows what happens to the mean bond lifetime τ ( F ) when H is decreased from its wild-type value of 25 kBT in increments of 5 kBT ( roughly corresponding to removal of individual salt bridges ) , while all other parameters are fixed at their Table 1 values . The catch bond behavior is preserved , but with opposite trends at small and large forces: at small forces τ ( F ) generally decreases with decreasing H , while at larger forces it initially increases by about a factor of two at the maximum , and then decreases gradually . These changes are due to the fact that transitions between the small and large α states become easier with decreasing barrier heights . At smaller forces , where the weaker small α states are preferred , some fraction of systems that would have ruptured from the stronger large α state can now transition to small α before rupturing . The converse is true at larger forces , where we now allow more small α states to transition to the preferred large α state before rupture . Consistent with this , the lifetimes within each angular domain are drastically affected by the mutation . Fig 6B shows τL ( F ) , the mean duration of the large α state ( from initial entry into the state until either rupture occurs or a transition to small α; see S1 Appendix for details ) . For the wild-type value H = 25 kBT , there is a broad force region , F ≈ 4–18 pN , where the large angle state survives for macroscopic times comparable to the maximum bond lifetime , τL ( F ) > 1 s . When H = 20 kBT this region is decreased to F ≈ 12–18 pN , and then vanishes entirely at smaller H . With a decreasing barrier , the time spent at large α becomes significantly briefer , reduced by 4-6 orders of magnitude at H = 0 . At H = 25 kBT a typical system trajectory may have involved zero or one transition across the angular barrier , and then rupture . In contrast at smaller H the system makes a large number of angular transitions before the bond breaks . The result is that the double-well nature of the energy landscape is averaged out , and the survival probability ΣF ( t ) switches from double-exponential at H = 25 kBT to mainly single-exponential at H ≤ 20 kBT , as seen in Fig 6C . Thus while the presence of a large H barrier is not necessary for catch bonding , it is necessary to stabilize the large α conformational state so that it persists for long durations . A larger τL ( F ) over a wide force range comes at the price of a somewhat smaller maximum τ ( F ) . But this may be biologically preferred if the macroscopic duration of the large α state is necessary to allow time for additional binding partners ( like vinculin ) to dock before rupture or the transition to small α . Indeed two potentially fruitful future lines of experimental inquiry would be: a ) to first study the CCA catch bond under different mutations to the αE-catenin hinge region . The mutations would have a clear signature of their effect on H by the change in the nature of the survival probability distribution [Fig 6C] . Whether the response of τ ( F ) would follow the trend in Fig 6A would determine if scenario ( i ) were true , or whether additional allosteric effects like in scenario ( ii ) are also present; b ) to study the binding affinity or bond lifetime of vinculin to the CCA complex under these same mutations . This would elucidate whether the increased lifetime of the large α state , facilitated by the angular barrier , is also required for effective vinculin binding . One can also imagine an alternative vinculin binding mechanism like induced fit , where its affinity might be independent of the lifetimes or relative populations of the αE-catenin conformational states . The model presented here is the first quantitative , structural model for the catch bond in the cadherin-catenin-actin complex . It provides a full interpretation of the force spectroscopy data from the Buckley et al . experiment [11] , highlighting the central role of αE-catenin as a force-transducing conformational switch [42–44] . The switch mechanism , based on small and large angle catenin conformations with different FABD-actin bond strengths , is to date the most plausible molecular explanation of the CCA catch bond . Force induces a small-to-large angle transition over a substantial energy barrier resulting from a network of salt bridges . This transition in turn allosterically modifies the strength of the catenin-actin interface , resulting in the catch bond behavior . The energy barrier , captured in the parameter H in our model , leads to the double-exponential survival probabilities seen experimentally . Additionally , once the system transitions to the large α conformation , the barrier allows it to remain there a significant fraction of the bond lifetime , perhaps facilitating the binding of other proteins like vinculin which play major roles in the physiological complex . While the model parameters are consistent with all the available evidence , including structural information about the αE-catenin hinge region , full corroboration of the mechanism will require further experiments to check whether alterations in the αE-catenin conformational stability have the posited effects on bond observables . Moreover , future crystal structures of the FABD-actin interface would allow verification of the E0 and E0 + E1 energy scales predicted by our approach . Of course it is always possible that an alternative conformational mechanism will emerge for the CCA catch bond . Any competing explanation will still have to include a conformational change whose dynamics are slowed down by an energy barrier ≫ kBT , since this is the only way to have a catch bond with double-exponential survival probabilities . One of the attractive features of our model is that it can be readily adapted for such an eventuality . The current Hamiltonian is expressed in terms of bond distance and inter-domain angle , but analogous Hamiltonians can be formulated , replacing the angle with another conformational coordinate . The model can even generalize to more than two conformational basins in the energy landscape , separated by different barriers , if the structural evidence points in that direction . The basic approach stays the same , and analytical expressions for the bond lifetimes and distributions can always be derived to fit to experimental data . Given the ubiquity of multi-exponential lifetime distributions in catch bonding systems [11 , 15 , 36–39] , implicating conformational transitions with non-trivial energy barriers , our approach thus might provide a universal framework for structural modeling of catch bonding . And it is not only limited to multi-exponential distributions , since single-exponential behaviors ( for both catch and slip bonding ) are just special cases of the model parameters . The usefulness of our theory starts at the cadherin-catenin-actin system , but hopefully will not end there .
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Epithelial cells that line the surface of cavities in the human body are held together by groups of proteins known as adherens junctions . The cells are always under some level of mechanical tension , and the resulting forces can play a major role in determining junction stability . Our work provides a theoretical model to account for an intriguing recent experiment , where force was found to enhance the lifetime of the bonds between adherens junction proteins . This counter-intuitive strengthening of biological bonds under tension is known as catch bonding . Though observed in a wide variety of proteins responsible for adhesion between cells , the microscopic biophysical origins of this phenomenon are poorly understood . For the case of the adherens junction , our model allows us to use the experimental data to infer a number of previously unknown details , like the energies at the protein interfaces , and the associated protein structural rearrangements . Since the building blocks of the model—bond energy changes induced by protein domain rotations—are common to many adhesion protein systems that exhibit catch bonds our approach can be readily generalized to intepret experimental data in other cases .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"chemical",
"bonding",
"crystal",
"structure",
"absorption",
"spectroscopy",
"condensed",
"matter",
"physics",
"crystallography",
"thermodynamics",
"hydrogen",
"bonding",
"selectins",
"physical",
"chemistry",
"research",
"and",
"analysis",
"methods",
"contractile",
"proteins",
"actins",
"solid",
"state",
"physics",
"proteins",
"cell",
"adhesion",
"salt",
"bridges",
"chemistry",
"free",
"energy",
"physics",
"biochemistry",
"cytoskeletal",
"proteins",
"electrochemistry",
"cell",
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] |
2018
|
Unraveling the mechanism of the cadherin-catenin-actin catch bond
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Schistosomiasis is a parasitic disease infecting hundreds of millions of people worldwide . Treatment depends on a single drug , praziquantel , which kills the Schistosoma spp . parasite only at the adult stage . HDAC inhibitors ( HDACi ) such as Trichostatin A ( TSA ) induce parasite mortality in vitro ( schistosomula and adult worms ) , however the downstream effects of histone hyperacetylation on the parasite are not known . TSA treatment of adult worms in vitro increased histone acetylation at H3K9ac and H3K14ac , which are transcription activation marks , not affecting the unrelated transcription repression mark H3K27me3 . We investigated the effect of TSA HDACi on schistosomula gene expression at three different time points , finding a marked genome-wide change in the transcriptome profile . Gene transcription activity was correlated with changes on the chromatin acetylation mark at gene promoter regions . Moreover , combining expression data with ChIP-Seq public data for schistosomula , we found that differentially expressed genes having the H3K4me3 mark at their promoter region in general showed transcription activation upon HDACi treatment , compared with those without the mark , which showed transcription down-regulation . Affected genes are enriched for DNA replication processes , most of them being up-regulated . Twenty out of 22 genes encoding proteins involved in reducing reactive oxygen species accumulation were down-regulated . Dozens of genes encoding proteins with histone reader motifs were changed , including SmEED from the PRC2 complex . We targeted SmEZH2 methyltransferase PRC2 component with a new EZH2 inhibitor ( GSK343 ) and showed a synergistic effect with TSA , significantly increasing schistosomula mortality . Genome-wide gene expression analyses have identified important pathways and cellular functions that were affected and may explain the schistosomicidal effect of TSA HDACi . The change in expression of dozens of histone reader genes involved in regulation of the epigenetic program in S . mansoni can be used as a starting point to look for possible novel schistosomicidal targets .
It has been widely recognized in recent years that epigenetic effectors of chromatin remodeling are promising targets for therapeutic intervention , because they play a key role in epigenetic regulation of gene expression in all eukaryotes [1 , 2] . For schistosomiasis , new therapeutic interventions are highly desirable [3] because it is a parasitic disease that affects over 250 million individuals worldwide [4 , 5] , praziquantel is the only approved drug available for treatment [6] and resistant isolates of the Schistosoma mansoni parasite have been identified [7 , 8] . Chromatin is a complex structure of DNA packed into strings of nucleosomes , which are comprised of histone proteins that compact the eukaryotic genome and also regulate DNA accessibility to transcription , recombination , DNA repair and replication [9] . A range of modifications on the amino-terminal tail of histones , such as acetylation , methylation , ubiquitination , phosphorylation and sumoylation , are involved in chromatin remodeling and transcription regulation . These histone modifications are dynamically laid down and removed by histone modifying enzymes ( HMEs ) [10] . Two antagonistic enzyme families act to control the dynamics of histone acetylation , namely histone acetyltransferases ( HATs ) and histone deacetylases ( HDACs ) [11] , thus regulating many cellular processes such as nucleosome assembly , folding of chromatin and gene transcription [12] . In the past decade , HDACs have emerged as promising targets for epigenetic-based therapies intended to reverse aberrant epigenetic states associated with cancer; similar to the large majority of anticancer drugs , HDAC inhibitors ( HDACi ) induce tumor cell death [13 , 14] . Schistosome HDACs were characterized and studied in recent years as potential new drug targets , with the strategy of testing known HDAC-inhibiting anti-cancer drugs to kill schistosomes [15–17] . The rationale of the approach is based on the fact that the parasite shares some of the characteristics of malignant cells , such as high levels of metabolic activity and of cell division , an effective host immune evasion , and an intense oxidative metabolism [18] . In fact , it is already known that all HDAC classes can be inhibited by Trichostatin A ( TSA ) in human cells [1] , and that the parasite treatment with TSA leads to epigenetic changes in the chromatin and guides the parasite to apoptosis [15] . Also , in vitro assays have identified new compounds that inhibit SmHDAC8 ( class I ) [17] and SmSirtuins ( class III ) [19] deacetylases . In addition , in silico analyses [20] have pointed to a large number of S . mansoni histone binding partners potentially involved in the regulation of gene expression , DNA replication , cell death , cellular growth and proliferation [20] , thus suggesting that drug-induced histone modifications could affect these cellular processes in the parasite . In the present study , we report the histone acetylation status and the large-scale gene expression transition promoted by TSA HDACi , and confirm the chromatin acetylation changes in some of the gene loci with altered levels of transcription . Further , our gene expression analyses have pointed to the Polycomb Repressive Complex 2 ( PRC2 ) as being significantly affected by TSA , and this led us to test GSK343 [21] , an inhibitor of EZH2 , the histone methyltransferase component of PRC2 , as a possible schistosomicidal compound . Indeed , we found that the GSK343 EZH2 inhibitor was active in vitro against S . mansoni and acted synergistically with TSA , significantly increasing parasite death .
Animal experimentation was conducted in accordance with the Ethical Principles in Animal Research adopted by the Brazilian College of Animal Experimentation ( COBEA ) , and the protocol/experiments have been approved by the Ethics Committee for Animal Experimentation of Instituto Butantan ( CEUAIB n° 4704040515 ) . S . mansoni is maintained in the laboratory using the intermediate snail host Biomphalaria glabrata and as definitive host the golden hamster ( Mesocricetus auratus ) . Cercariae were released from infected snails and mechanically transformed to obtain schistosomula in vitro [22] . Newly transformed schistosomula were maintained for 12 h in M169 ( Vitrocell ) medium supplemented with 2% fetal bovine serum ( FBS ) ( Vitrocell ) , 1 μM serotonin , 0 . 5 μM hypoxanthine , 1 μM hydrocortisone , 0 . 2 μM triiodothyronine , penicillin/streptomycin , amphotericin , gentamicin ( Vitrocell ) at 37°C and 5% CO2 [23] , after which time the drug treatment was initiated , as described below . Adult worms were obtained from 7-week infected hamsters by left ventricular perfusion , and release of worms from the hepatic portal vein . Paired worms were maintained in RPMI medium ( Gibco ) supplemented with 10% fetal bovine serum ( FBS ) ( Vitrocell ) , penicillin/streptomycin , amphotericin ( Vitrocell ) at 37°C and 5% CO2 . The parasites were treated with 1 μM Trichostatin A ( Cayman Chemical ) , a concentration that has been shown by Dubois et al . [15] to be sub-lethal , and the negative controls with an equivalent amount of ethanol ( vehicle of TSA ) , for 12 , 24 and 48 h for microarray experiments , and for 12 h for ChIP-qPCR and western-blotting experiments . The microarray platform 4x180k was designed by our group and printed by Agilent , and it contains probes to the S . mansoni predicted genes ( "Smp genes" ) that were annotated by the genome-sequencing project in the ASM23792v2 version of the genome [24]; the probes covered Smp genes as follows: 12 mitochondrial Smp genes , 9255 sense predicted Smp genes , in addition to probes to the opposite strand of 9079 out of the Smp 9255 predicted genes . A total of 1517 additional Smp genes predicted in the genome could not be represented by unique probes , given the recommended parameters for probe design of the Agilent microarray platform . Positive and negative control probes as well as probes for spike-in RNAs were included as recommended by the Agilent expression array design instructions ( Agilent eArray ) . The microarray platform design along with gene annotation names was deposited at NCBI gene expression omnibus ( GEO ) under accession number GPL22001 , and the dataset series under accession numbers GSE83208 , GSE83209 , GSE83210 , GSE83211 . For each time point , total RNA from three biological replicates of schistosomula ( treated or control ) was extracted and purified using RNeasy Mini Kit ( QIAGEN ) according to the manufacturer’s instructions . 100 ng of each RNA sample were labeled with Cy3 or Cy5 using Low Input Quick Amp Labeling Kit ( Agilent ) ; the amplification method that is part of the protocol used to generate labeled cRNA is strand-specific and does preserve the strandedness of the labeled transcripts . Hybridizations were performed according to the Agilent protocols for two-color microarrays with dye-swap for technical replicates . After hybridizations and washings , microarrays were scanned with the SureScan Microarray Scanner ( Agilent ) . For quantitative RT-PCR , complementary DNAs were obtained by reverse transcription of 100 ng schistosomula total RNA using 6-mer random primers and SuperScriptIII Reverse Transcriptase ( Invitrogen ) and the qPCR amplification was done with SYBR Green Master Mix ( Life Technologies ) and specific primer pairs with the Applied 7500 PCR System ( Applied Biosystems ) . Primer pairs were designed for specific S . mansoni genes by Primer3 online software ( S1 Table ) . The results were analyzed by comparative Ct method and the statistical significance was calculated with the t-test . House-keeping gene PSMD Smp_000740 was chosen according to [25] . Feature Extraction Software ( Agilent ) was used to calculate the intensity of each spot from scanned microarray images . Raw intensity data was deposited at GEO under accession number GSE83211 . The low intensity spots were filtered out from the data by applying the IsPosAndSignif flag from the Feature Extraction Software , a Boolean flag , established via a 2-sided t-test , indicating if the mean signal of a spot is greater than the corresponding background . Total intensity data were normalized by Trimmed Mean method ( 40% ) , excluding positive and negative external controls present in the platform . The log2 ratio between treated and control sample intensities was calculated for each spot in the array . For genes that were represented in the array by multiple probes mapping along the gene , the mean intensity signal was calculated . Pearson correlation among biological replicates and time points were calculated revealing correlation coefficients in the range 0 . 75 to 0 . 88 ( Fig A in S1 Text ) . Significance Analysis of Microarray ( SAM ) [26] was used as the statistical test , applied individually for each time point using one-class approach [26] . Genes were considered as differentially expressed with q-value ≤ 0 . 05 . Gene Ontology terms for S . mansoni genes were downloaded from the Metazoa Mart database ( http://metazoa . ensembl . org/biomart/martview/ ) with a total of 6165 genes , and GO enrichment was calculated using Ontologizer tool [27] applying Parent-Child test with the Benjamini-Hochberg correction method [28] . To identify enriched gene networks among differentially expressed genes , QIAGEN’s Ingenuity Pathway Analysis software ( IPA , QIAGEN Redwood City , www . qiagen . com/ingenuity ) was used , considering 4758 S . mansoni genes encoding putative homologs to human proteins , as determined with BLASTP [29] ( coverage > 20% and amino acids similarity > 40% ) ( S2 Table ) . We assessed the H3K4me3 ChIP-Seq data by Roquis et al . [30] that was generated from schistosomula obtained 21 h after transformation of cercariae; we downloaded their raw data SRX1113460 , mapped them to the S . mansoni genome version ASM23792v2 using the HOMER pipeline [31] , which employs Bowtie2 to perform reads mapping and calculates significantly enriched peaks by requiring that each significant peak read density should be at least 4-fold higher than the peaks density in the surrounding 10 kb region [31] . The genomic coordinates of significant H3K4me3 peaks were associated with the genomic coordinates of the transcription start site ( TSS ) for known Smp genes using BedTools [32] within a window of ± 500 bp , as we have previously described [33]; in this way we were able to associate the presence of significant H3K4me3 marks to 4525 Smp genes in their promoter regions ( ± 500 bp of Smp gene 5´-end ) ( S2 Table ) . We tested whether the genes showing differential expression in the presence of TSA and having the H3K4me3 transcription start site mark at their TSS region had a higher mean fold-change in expression compared with the genes without the presence of this mark . For this purpose , we compared the mean fold-change ( treated/control ) between the two groups , namely differentially expressed genes that had a significantly enriched H3K4me3 mark at their TSS and differentially expressed genes that had no H3K4me3 mark , and applied the statistical t-test ( p-value < 0 . 05 ) . We used reader histone motifs from the Conserved Domains Database ( CDD ) ( https://www . ncbi . nlm . nih . gov/cdd ) to identify all S . mansoni proteins that would be predicted to recognize lysine and arginine modified by methylation and acetylation , and serine modified by phosphorylation . For this approach , we used Blastp ( https://www . ncbi . nlm . nih . gov/blast ) with parasite proteins as query and CDD files as subject , applying a 1e-10 cutoff of significance of alignment . S2 Table exhibits Smps with histone reader motif found in this analysis . Adult worms ( treated or control ) were used to prepare histone acid extracts . 50 worm pairs were soft lysed with 500 μl lysis buffer ( PBS containing 0 . 5% Triton X-10 , 0 . 02% NaN3 and Mini Protease Inhibitor Cocktail—Complete from Roche ) in a glass Potter homogenizer . The samples were centrifuged ( 10 min , 2000 g at 4°C ) and pellets containing the nuclear material were washed once in 200 μl lysis buffer then centrifuged again [15] . Histones were extracted from the nuclear fraction by suspending the pellet in 400 μl 0 . 25 M HCl with protease inhibitor and the solution was incubated overnight at 4°C in order to precipitate acid proteins [34] . The samples were centrifuged ( 60 min , 16000 g at 4°C ) and the supernatants ( with histone proteins ) were concentrated with trichloroacetic acid 33% [35] . The final pellet with histones was eluted in MilliQ water with protease inhibitors and protein concentration was determined with the Micro BCA Protein Assay kit ( Pierce Biotechnology ) . Of each sample , 10 μg of histone enriched extract was loaded on 15% SDS-Polyacrylamide gels , and after protein separation , transferred to a nitrocellulose membrane ( Amersham ) . Briefly , membranes were blocked with Tris-buffered saline ( TBS ) containing 0 . 1% Tween 20 and 5% skimmed milk ( TBST/5% milk ) , and then probed overnight with primary antibodies in TBS/2% BSA . Membranes were washed with TBST and incubated for 1 h in TBST/5% milk with secondary antibody conjugated with IRDye ( IRDye 800CW goat anti-rabbit and IRDye 700CW goat anti-mouse from Licor Biosciences ) . After washing the membranes in TBST , the bands were visualized and quantified with the Odyssey Infrared Imaging System ( Licor Biosciences ) . Acetylation of histones was measured with specific monoclonal antibodies to the following lysine modifications: Histone H3 acetyl K9 C5B11 ( Cell Signaling ) ( 1:1000 ) , Histone H3 acetyl K14 ab52946 ( Abcam ) ( 1:1000 ) , Histone H3 tri methyl K27 ab6002 ( Abcam ) ( 1:1000 ) and to normalize the samples anti-Histone H3 ab24834 ( Abcam ) ( 1:1000 ) was used . The ChIP protocol for crosslinking and sonication of schistosomula was based on a protocol described elsewhere [36] . The parasite suspension was sonicated using Epishear ( Active Motif ) with a 3 mm microprobe with 20% amplitude , 10 pulses of 30 s each , shearing the DNA into 100–1000 bp . The immunoprecipitation was performed with EZ-Magna ChIP Chromatin Immunoprecipitation kit ( Millipore ) with the following antibodies: Anti-Histone H3 ( Abcam ) , Histone H3 acetyl K9 C5B11 ( Cell Signaling ) , Histone H3 acetyl K14 ab52946 ( Abcam ) , Histone H3 tri methyl K27 ab6002 ( Abcam ) , Normal mouse IgG 12-371B ( Millipore ) and Normal Rabbit IgG PP64B ( Millipore ) . The recovered DNA in the precipitates was detected by qPCR with SYBR Advantage qPCR Premix ( Clontech ) and primers designed to specific gene promoter regions of interest ( S1 Table ) . We targeted these primers to approximately 500 bp upstream of the coding sequence , based on the fact that the H3K4me3 ChIP-Seq data for schistosomula from Roquis et al . [30] , when mapped to the S . mansoni genome as previously described [33] , falls within 500 bp of the transcription start site ( TSS ) of transcripts detected by RNA-Seq [33] . Primers were designed to non-repetitive regions within the promoter region of the selected set of genes indicated in the figure , with only one exception , Smp_174840 ( SmCBX5 ) , a gene for which the genomic upstream TSS region is highly repetitive; in this case , we designed primers at the first exon of the SmCBX5 gene . As a qPCR normalizer control we used the gene promoter region for the SmVal19 gene ( Smp_123090 ) , which was not expressed either in the HDACi- or the vehicle-treated schistosomula assays , and has no histone acetylation and methylation marks at its promoter region , as seen in the public ChIP-Seq datasets from [37] available at the Schistosoma genome browser ( http://schistosoma . usp . br ) . Schistosomula were equally distributed in 96-well microtiter plates ( 300 larvae per well ) , and the drugs ( TSA , GSK343 or a combination of the two ) or the corresponding vehicle ( control ) were added , as indicated in the legends to the figures . At each time point indicated in the figures , the parasites ( from a given set of wells in the plate ) were stained with 2 μg/mL propidium iodide ( PI ) and visualized at 10 x magnification using a Nikon Eclipse fluorescent inverted microscope . Dead parasites become stained with PI and were detected with a rhodamine filter ( 536 nm ) , and total parasites inside the well were counted using light optical microscopy [38] . For each time point a new set of wells was used , because the staining procedure was lethal to the parasites . The number of biological replicates that were assayed , as well as the number of parasites that were counted per replicate , is stated in the legends to the figures . For the LD50 assay , incubation with GSK343 was maintained for 96 h before counting . For the assay of synergy between TSA and GSK343 , parasites viability was measured each day along 4 days . Data were analyzed with Origin software ( OriginLab , Northampton , MA ) . The amino acid sequence of SmEZH2 ( Smp_078900 ) was used for the identification of template structures of SET domain using Blast algorithm at RCSB Protein Data Bank ( PDB ) [39] . Two PDB structures of human EZH2 SET domain , 4MI0 and 4MI5 , showed 63 . 8% and 64 . 9% amino acid sequence identity and 90 . 9% and 91 . 8% coverage , respectively , when compared with SmEZH2 SET domain ( from amino acids 746 to 978 ) using the EMBOSS Needle tool ( http://www . ebi . ac . uk/Tools/psa/emboss_needle/ ) . UCSF Chimera [40] was used to generate a superimposed model from the two PDB structures with the MatchMaker tool and Needleman-Wunsch algorithm . The sequence of SmEZH2 SET domain was aligned with the model using Clustal Omega . This sequence alignment was used to obtain twenty virtual structural models with Modeller 9v10 [41] , from which we selected the one with the lowest normalized DOPE-score ( zDOPE , Z-score of Discrete Optimized Protein Energy ) . The software SCWRL4 . 0 [42] was applied to the selected virtual model to improve protein side-chain conformations and KobaMIM [43] was used to refine the structure . Finally the virtual model of SmEZH2 SET domain was analyzed with Molprobity [44] and ERRAT [45] . To perform molecular docking we used the previous knowledge of amino acids of hEZH2 that interact with SAM cofactor [46] to set a grid box of 30x30x30 Å around this region , in the virtual model of SmEHZ2 , using the AutoDock Vina software [47] . We used the 3D ligand structures of GSK343 ( CID: 71268957 ) , GSK926 ( CID: 67466175 ) and SAM cofactor ( CID: 34756 ) from PubChem ( https://pubchem . ncbi . nlm . nih . gov ) to simulate the protein-ligand complex and obtain binding energies . This process consisted of 10 docking simulations using the following parameters: number of binding modes equal to 20 ( to maximize binding free energy calculations ) , search exhaustiveness of 50 and 3 kcal/mol of maximum energy difference , also receptors were considered as rigid and ligands as flexible . Binding energies are shown as mean ± S . D . calculated from the 10 docking simulations . Pymol ( PyMOL Molecular Graphics System , Version 1 . 8 Schrödinger , LLC ) was used for visualization of the three dimensional virtual model of SmEZH2 SET domain . Visualization of the two-dimensional diagram summarizing the molecular interactions between ligands and EZH2 was prepared using LigPlot program [48] .
The extent of histone acetylation in S . mansoni adult worms under the effect of the HDACi TSA was investigated after 24 h of parasite exposure to the drug . Histone marks H3K9ac and H3K14ac , associated with transcriptional activation , were studied by western blotting with monoclonal antibodies against the specific acetylated lysine 9 ( K9 ) and lysine 14 ( K14 ) residues of histone H3 . Histone hyperacetylation was detected both at H3K9ac and H3K14ac ( Fig 1A and 1B ) ; three independent biological replicates showed a statistically significant ( p-value ≤ 0 . 05 ) increase in acetylation . In parallel , the H3K27me3 histone mark , a non-related mark of transcription repression , was assayed as a control and found not to be affected by the TSA treatment ( Fig 1C ) ; this also suggests that no overall changes in histone modification had been triggered as a consequence of histone hyperacetylation . To explore the effect of HDACi on gene expression , three independent biological replicates of schistosomula were exposed in vitro to TSA or drug vehicle and large-scale gene expression changes were accessed by microarrays . Three different time points after drug exposure were analyzed ( 12 , 24 and 48 h ) . Our custom designed strand-specific Agilent microarray platform has probes for 9255 S . mansoni protein-coding gene transcripts; in addition , probes for the opposite complementary strand are present on the microarray , to detect an eventual antisense transcription for 9079 out of the 9255 gene loci . The number of genes affected by exposure to the HDACi , compared with vehicle at each time point , is shown in Table 1 . Note that the fraction of affected genes increased along the time of drug exposure and reached 54% within 48 h of treatment ( Fig 2A , Table 1 ) . It is interesting to note that at 24 h there was a predominant up-regulation of 2719 genes in the presence of the drug compared to vehicle , and only 1129 genes were down-regulated ( Table 1 , Fig 2A ) , while at 48 h of treatment just one quarter of the affected genes were up-regulated , greatly increasing the fraction of down-regulated genes . Venn diagrams for the subsets of up-regulated and down-regulated genes ( Fig B in S1 Text ) show that a large set of genes are affected exclusively at just one of the three time points analyzed . It is noteworthy that 1781 genes were affected in common at the three time points analyzed ( Fig 2B and Fig C in S1 Text ) . Overall , the data indicate a modification of the parasite’s gene transcription program along the time course of drug exposure . The strand-specific cRNA labeling protocol that was used here allowed the detection of transcriptional activity antisense to protein-coding genes , and indeed we detected that TSA treatment did affect antisense RNA ( asRNA ) transcription . Similar to the mRNAs , the fraction of affected asRNAs increased along the time of drug exposure and reached 45% of all expressed asRNAs within 48 h of treatment ( Table 1 ) ; the majority of them were up-regulated in the presence of TSA ( Table 1 ) . Considering the mRNA and the asRNA from the same locus , we found that at each time point there were over 700 loci where the pattern of expression change with drug was the same for both strands , namely both mRNA and asRNA were simultaneously up-regulated or both were down-regulated ( Table A in S1 Text ) upon TSA exposure . In addition , at each time point we detected over 400 loci where only the asRNA was differentially expressed by exposure of schistosomula to TSA ( most of them up-regulated ) , and the sense protein-coding mRNA of the same locus was not affected by the drug treatment ( Table A in S1 Text ) . Knowing that the H3K4me3 histone mark is related to transcriptionally active chromatin , we collected the H3K4me3 ChIP-Seq data for schistosomula from Roquis et al . [30] , mapped them to the S . mansoni genome as previously described [33] , and asked if the genomic positions having significantly enriched H3K4me3 marks would correspond to the positions of genes that would be more susceptible to changes in expression due to HDAC inhibition by TSA . For this analysis , we categorized the differentially expressed genes according to the presence or the absence of a significantly enriched H3K4me3 mark at their promoters ( see Methods ) , and computed the distribution of gene expression fold-change for each group at 12 , 24 and 48 h after treatment of schistosomula with TSA ( Fig 3A ) . Interestingly , we found that at 12 h after TSA treatment ( Fig 3A ) , genes that have the H3K4me3 histone mark at their promoters showed a median log2 fold-change ( treated/control ) of 0 . 55 , i . e . , on average they showed a median 1 . 5-fold activation in the presence of TSA relative to control . On the contrary , genes without the H3K4me3 mark at their promoters showed a median log2 fold-change of -0 . 61 , i . e . , on average they showed a median 1 . 5-fold inhibition in the presence of TSA relative to control ( Fig 3A ) , a significantly different pattern from that of genes with the H3K4me3 mark ( p-value < 1 x 10−7 ) . The differences in the pattern of expression change between the two groups were still observed after 24 h of TSA ( p-value < 1 x 10−7 ) and vanished at 48 h ( Fig 3A ) ; such a persistent difference at 24 h in the pattern of expression change between the genes with and without the H3K4me3 mark can be further appreciated with the cumulative distribution plot of Fig D in S1 Text , where the cumulative curve for genes with the mark is clearly shifted to the right , indicating a larger change in gene expression for the genes with the mark compared with the ones without . Also , the Kolmogorov-Smirnov test showed a significant difference ( p-value ≤ 0 . 0001 ) in the distribution profiles of log2 fold-change ( treated/control ) between the two groups of genes with or without the H3K4me3 mark , at each of the two early time points . Fig 3B shows an example of genomic distribution pattern of H3K4me3 marks along chromosome 4 for all significant differentially expressed genes at 12 h . It can be seen that a great number of differentially expressed genes are associated with the presence of the H3K4me3 mark at their promoters ( Fig 3B ) . Fig 3B also illustrates how the pattern of activation/inhibition of the genes in chromosome 4 changed at 24 h compared with the pattern at 12 h , nevertheless most of the expression changes persisted at 24 h . Gene Ontology analysis pointed to distinct enriched categories for up- and down- regulated genes in schistosomula at each of the three analyzed time points after HDACi treatment ( Tables 2–4 ) . Categories associated with ATP metabolism , such as ATP catabolic process ( GO:0006200 ) , ATP binding ( GO:0005524 ) and Purine nucleotide binding ( GO: 0017076 ) were enriched among the up-regulated genes after 12 , 24 and 48 h treatment respectively . The category of phosphorus metabolic process ( GO:0006793 ) was enriched among the up-regulated genes at 12 and 24 h . Many interesting categories are involved with regulation of DNA and chromatin , such as DNA replication ( GO:0006260 ) among the up-regulated genes at 24 and 48 h , and minichromosome maintenance ( MCM ) complex ( GO:0042555 ) among the up-regulated genes after 48 h treatment . Interestingly , the nucleosome category ( GO:0000786 ) was enriched among down-regulated genes after 48 h treatment . Genes affected in common at the three time points of TSA treatment ( 1781 genes ) were separated into two subsets of up-regulated or down-regulated genes ( Fig C in S1 Text ) and were classified into a number of enriched GO categories ( Table 5 ) , including the GO associated with DNA replication processes , which was also detected as enriched in the GO analyses of individual time points . A set of 48 genes ( out of the 1781 genes ) were affected in common at all three time points , but not with a consistent direction of expression change at all time points ( Fig C in S1 Text ) , thus not being included in the GO enrichment analysis . The vast majority of the 1781 genes exhibited a sustained gene expression change all along the HDACi treatment period , being either sustainably up- or down-regulated across the three time points ( 12 , 24 and 48 h ) ( Fig C in S1 Text ) . S3 Table gives the list of genes in each enriched GO category present in this analysis . Consistent with the GO analysis , Ingenuity Pathway Analysis ( IPA ) also pointed to an enriched network of genes from the DNA replication mechanism , with most of them detected as up-regulated by the HDACi treatment after 24 h ( Fig 4 ) . It is interesting to note the presence of a set of genes encoding DNA polymerases , pre-replication complex organization , GINS complex and minichromosome maintenance ( MCM ) proteins; all these proteins are closely involved in the initiation , regulation and progression of DNA replication . Upon longer exposure to HDACi ( 48 h treatment ) , two different enriched gene networks were detected , with most of the genes being down regulated , and being involved in cell movement of smooth muscle cells ( Fig 5A ) and in the production of reactive oxygen species ( Fig 5B ) . A set of differentially expressed genes was selected for RT-qPCR validation of the microarray results ( six up-regulated genes , four down-regulated genes ) ; selection was based on the following criteria: genes involved in signaling pathways such as SmChk1 , SmHistK , SmTyrK and SmSGPL , and also genes that encode proteins participating in chromatin remodeling such as SmCBX5 , SmEED , SmSET , SmSirt2 , SmWD40 and SmWD-repeat . A statistically significant change of expression was detected by RT-qPCR for all selected genes at all three time-points of TSA treatment under analysis ( Fig 6 ) . The same fold-change pattern was detected both by qPCR and microarray , corresponding to a Pearson correlation greater than 0 . 95 for 12 , 24 and 48 h . As a control , SmEZH2 histone methyl-transferase , not differentially expressed in the microarray , was also included in the RT-qPCR ( Fig 6 , rightmost bars ) . The overall increased acetylation of histones and the genome-wide gene expression regulation that were observed , led us to investigate the possible increased occupation by acetylated histone of the promoter region upstream of genes that were detected as up-regulated upon HDACi exposure . For this , we performed chromatin immunoprecipitation ( ChIP ) with antibodies against the histone marks related to transcription activation , namely H3K9ac , H3K14ac and H3K4me3 followed by qPCR using primers targeting the specific genomic DNA sequences of promoter regions of a set of selected genes that were up-regulated by TSA after 12 h treatment . We detected a significant increase of the H3K9ac mark at the promoter region of four out of eight chosen genes in schistosomula treated with TSA ( Fig 7A ) ; this result is corroborated by the fact that the total histone H3 occupancy at the promoter regions for all eight tested genes is not affected by TSA treatment ( Fig 7B ) . H3K14ac did not show an increased occupancy at any of the promoter regions tested ( Fig E in S1 Text ) . Also , the unrelated transcription repression histone mark H3K27me3 ( Fig E in S1 Text ) was not found enriched in any of the tested genes as expected , corroborating with western blotting assay where no change in this histone mark was detected . Using the Blastp tool we searched for S . mansoni genes encoding proteins with histone reader motifs , and we identified 195 histone readers among the parasite expressed genes . Interestingly , many of them were detected as differentially expressed ( q-value ≤ 0 . 05 ) after 12 h treatment ( 73 genes ) , 24 h ( 89 genes ) and 48 h treatment ( 85 genes ) ( Table 1 ) , although the number of affected genes was not sufficient to cause the class of histone readers to be significantly enriched . Most of these differentially expressed histone reader genes have the histone reader domain recognizing histone methyl-lysine , such as Ankyrin , WD40 and PHD domains ( S2 Table ) . These genes encode key proteins in the regulation of chromatin remodeling complexes recruiting proteins with the ability of writing or erasing histone modifications . Notably , among the differentially down-regulated genes we found SmEED ( Smp_165220 ) , which encodes a component of the Polycomb Repressor Complex 2 ( PRC2 ) and contains 7 repeat-units of WD40 motifs that are necessary for EED to recognize histone H3K27me3 [49] . EED is responsible for the regulation of EZH2 methyl-transferase activity of PRC2 , which inserts the H3K27me3 histone mark that determines transcription inhibition [49] . Having found that SmEED , an activator of EZH2 , was down-regulated in the presence of TSA , we hypothesized that a small molecule inhibitor of SmEZH2 methyltransferase might increase parasite mortality when given simultaneously with TSA . To evaluate SmEZH2 as a possible new anti-parasite epigenetic target , we tested GSK343 , a compound identified in human cancer cells as a highly potent , selective EZH2 inhibitor [21] . We assayed the in vitro effect of GSK343 on the viability of schistosomula after 4 days exposure and found that LD50 was 24 . 5 μM ( Fig F in S1 Text ) . Next , we followed schistosomula viability along 4 days of treatment with GSK343 ( Fig 8 ) and found zero viability of parasites at 50 μM GSK343 already after two days of treatment ( Fig 8 ) . At 20 μM GSK343 , a concentration below LD50 , 85% of schistosomula remained viable on day 4 ( Fig 8 ) . To test for the possible synergistic effect of both histone modifying enzyme inhibitors , we first exposed the parasites to a low dose of 1 μM TSA alone , a drug concentration which has previously been shown to cause very low mortality of schistosomula [15] . Indeed , we found that essentially 100% of schistosomula remained viable at day 4 of treatment with 1 μM TSA ( Fig 8 ) . Simultaneous exposure of schistosomula to 1 μM TSA plus 20 μM GSK343 caused a significant decrease in schistosomula viability to 70% after four days treatment , compared with 85% viability of schistosomula with 20 μM GSK343 alone ( p-value ≤ 0 . 001 two-way ANOVA test ) ( Fig 8 ) . The enhanced mortality of schistosomula caused by GSK343 in the presence of TSA compared with GSK343 alone is a clear indication of the synergistic effect of the two drugs . Noting that GSK343 appears as an interesting compound with a schistosomicidal effect , we performed the homology modeling of the potential drug target SmEZH2 and computed the predicted binding energy between the compound and the enzyme . As a template we used hEZH2 which has 746 amino acids; just the methyltransferase SET domain ( comprised of 233 amino acids ) has the crystal structure solved [50] . The SmEZH2 gene ( Smp_078900 ) , in turn , encodes a protein with 1026 amino acids with a conserved SET domain , with 64% identity and 91% coverage to the hEZH2 SET domain . Alignment of the sequences comprising the SET domain from human EZH2 , for which the structures with atomic resolution of 2 Å are available ( 4MI0 and 4MI5 ) with the sequence of S . mansoni EZH2 SET domain ( Fig G in S1 Text ) showed an identity higher than 60% , allowing the homology modeling of the SmEZH2 SET domain ( Fig 9A and 9B ) . The obtained refined homology model evaluated by Molprobity [44] exhibited in Ramachandran plots 95 . 7% of its residues in favored regions and 99 . 1% in allowed regions with two outliers ( Fig H in S1 Text ) , and ERRAT plots showed an overall quality factor of 93% for the SmEZH2 model structure . SmEZH2 presents an insertion of 19 amino acids at the SET domain compared to the hEZH2 ( Fig G in S1 Text ) , which could not be modeled and possibly this fact has reduced the overall resolution of the achieved model; this insertion appears in the SmEZH2 model as a loop external to the region involved in catalysis ( Fig 9A ) . In fact , SmHDAC8 insertions in the catalytic domain correspond to external solvent exposed loops that are not involved in catalysis as shown by X-ray crystallography [17] and the same is probably true of SmEZH2 . Using previous information of which amino acids interact with the cofactor SAM at the hEZH2 SET domain [46] , we defined the region at SmEZH2 to be used in the predictions of docking of SAM to SmEZH2 , that were computed with AutoDock Vina [47] , also taking into consideration the competitive mode of inhibition of cofactor SAM and compound GSK343 in hEZH2 , as shown in the literature [21] . This region is highly conserved between SmEZH2 and hEZH2 sequences , diverging only at V904I and Y908T . Compound GSK343 and SAM were predicted by the docking analyses to bind to the same protein region of SmEZH2 ( Fig 9C and 9D ) , sharing common amino acids ( Arg901 , Asp906 , Met909 , Ser911 , Leu913 , Asp923 and Thr925 ) at a binding distance of 3 . 5 Å as indicated in Fig 9C and 9D , thus suggesting that GSK343 could act as a competitive inhibitor of SAM in SmEZH2 . The interaction between cofactor SAM and hEZH2 ( Fig I in S1 Text ) occurs at the same protein region as that predicted for SAM interaction with SmEZH2 ( Fig 9D ) , and despite the conservation of sequence between hEZH2 and SmEZH2 in this region , just two amino acids predicted to be in close proximity to the SAM cofactor are in common , comparing SmEZH2 ( Ser911 and Leu913 , Fig 9D ) and hEZH2 ( Ser669 and Leu671 , Fig I in S1 Text ) . The predicted binding energies of cofactor SAM to hEZH2 and SmEZH2 were similar ( -6 . 3 ± 0 . 05 and -6 . 8 ± 0 . 27 kcal/mol ) . Notably , the predicted binding energies of inhibitor GSK343 to the models were more negative compared to the cofactor; GSK343 had a predicted binding energy of -7 . 83 ± 0 . 09 kcal/mol with SmEZH2 , and for hEZH2 the binding energy was -8 . 1 ± 0 . 22 kcal/mol .
We explored the effect of HDACi TSA on schistosomula gene expression , showing a large number of affected genes specifically related to different cellular functions . Remarkably , genes encoding proteins with activity at the DNA replication fork were up regulated , mainly after 24 h treatment , such as the genes responsible for Replication Complex organization ( ORC1 , ORC2 , ORC3 , CDC6 , CDT1 , MCM3 , MCM4 , MCM5 , MCM6 , MCM7 , HBO1 , FACT and RFC1-5 ) ( Fig 10A ) . Acetylation of histones is closely associated with DNA replication , stimulating the replication activity at the origin , which is recognized by the origin recognition complex ( ORC ) –heterohexamer with DNA-dependent ATPase activity [51] . After ORC binds to the origin , factors CDC6 ( cell division cycle 6 ) and CDT1 ( DNA replication factor ) are recruited and facilitate the loading of the MCM complex ( minichromosome maintenance protein complex MCM2-7 ) with helicase activity , forming a ring around the replication origin , encircling the pre-replication complex ( Pre-RC ) [52] . CDT1 recruits a histone acetyltransferase ( HBO1 ) to Pre-RC , which preferentially targets the histone H4 residues K5 , K8 and K12 , enhancing MCM2-7 loading through a mechanism requiring its acetyltransferase activity [53] . Further to this known mechanism involving a HAT , the replication fork also commits the histone chaperone FACT ( facilitates chromatin transcription ) that interacts with histones H2A-H2B and H3-H4 dimers promoting nucleosome disassembly and assembly [54] . We suggest that all this balanced mechanism of chromatin replication is being activated by HDAC inhibition , due to the increased gene expression of all the genes involved in the replication machinery . Also , the increased expression of genes encoding proteins from the replisome component , responsible for the replication initiation origin , fork progression and histone dynamics , as well the hyperacetylation of histones , suggests a genome-wide open chromatin status in the parasite due to the treatment with HDACi . The mechanism of chromatin deacetylation is important for the maturation of nascent chromatin , and is required for fork progression and stability . In line with this , disruption of HDAC functions by HDACi directly affects replication and generates a reduction in the rate of replication fork progression [55] . We observed important genes with increased expression related to this process such as replication factor c ( RFC1-5 ) and its downstream partner , PCNA ( Fig 10B ) . As a central fork component , the heterotrimeric clamp PCNA , besides orchestrating DNA synthesis and stimulating DNA polymerases activity and nucleosome assembly , also recruits HDACs to chromatin maturation , as well as other maturation factors [52] . The up-regulation of PCNA , Pol alpha , and Pol delta with TSA treatment possibly affects the cohesin rings upon fork passage . We suggest that the increased expression of components of the replication machinery may cause a replication stress as a result of HDAC inhibition , creating the possibility for DNA damage , a process that has been shown to occur upon hyperacetylation of histones [55] . An important cellular function , namely control of the quantity of reactive oxygen species ( ROS ) appears to be decreased by TSA HDACi , because 20 out of 22 genes that encode proteins responsible for reducing free radicals generation are down-regulated in schistosomula upon TSA treatment , and 2 out of 4 genes that increase ROS are up-regulated . In fact , in human cancer cells HDACi are thought to cause apoptosis through the induction of DNA damage and genomic instability as a result of the generation of ROS [56] . Recently , it was shown that depletion of SmCBP1 ( Smp_105910 ) , an HAT , resulted in an increase of neoblast proliferation [57] , and in our data this gene is down regulated after 12 and 48 h treatment . In line with this finding , neoblast genes such as FGF receptor gene ( Smp_175590 ) and Ago2 ( Smp_179320 ) [58] are up-regulated after 24 h treatment , so we suggest that under the stress of a sub-lethal dose of TSA the parasite is promoting the proliferation of its somatic stem cells . In fact , stem cell proliferation for tissue regeneration is induced by apoptosis after tissue injury [59] , and HDAC activity is an essential regulator of tissue regeneration in model organisms under the effect of HDACi [60 , 61] . We found that up to about half of the gene loci in S . mansoni showed antisense transcription and that 33 to 45% of total expressed antisense RNAs were differentially expressed upon TSA treatment ( Table 1 ) . Recently , a report on S . japonicum genes differentially expressed between genders has shown that a total of 685 and 430 genes were detected in males and females , respectively , as having significant fold-change values ≥ 2 simultaneously in the forward and the reverse strand [62] . Our results confirm that also in S . mansoni , a large number of genes exhibit antisense transcription , and that frequently the antisense transcripts show significant differential expression . Further experiments are needed to understand the role of these antisense messages in the parasite biology . The epigenome of S . mansoni has been recently explored , associating the gene expression levels with chromatin modifications [30 , 37] , or identifying chromatin epigenetic marks at the transcript start sites ( TSSs ) of genes [33] . Here we observed that on average the genes with a significantly enriched H3K4me3 mark at their TSSs showed an activation of transcription upon HDAC inhibition , whereas those genes without the mark showed on average an inhibition of transcription in the presence of TSA . In humans , it has already been described that the presence of the H3K4me3 mark at a gene TSS is often coupled with histone acetylation marks in the promoter region and gene body , allowing chromatin opening and transcription elongation [63] . Our results suggest that there is also a coupling between these two marks in S . mansoni . However , it should be noted that changes in transcription might not always be directly associated with hyperacetylation , for example when hyperacetylation affects the expression of a transcription factor ( TF ) that will in turn modify the expression of the TF target genes , regardless of whether the promoters of the latter are hyperacetylated or not . TSA treatment affected the expression of dozens of histone reader genes . Histone readers are important components of the chromatin remodeling complexes , and are able to precisely recognize histone post-translational modifications and recruit components responsible for regulating transcription , DNA replication , DNA damage and chromatin remodeling [64] . Our observed change in expression of SmEED , a histone reader from the Polycomb Repressor Complex 2 ( PRC2 ) , caused by a sub-lethal dose of TSA , suggested that another component of PRC2 , the EZH2 methyltransferase could be tested as target for inhibition . We therefore tested GSK343 , an EZH2 inhibitor [21] , and found that GSK343 was active in vitro against S . mansoni and acted synergistically with TSA , significantly increasing parasite death . This approach opens the perspective of using the information gathered here about the change in expression of the dozens of histone reader genes involved in regulation of the epigenetic program in S . mansoni as a starting point to look for possible novel schistosomicidal targets .
We have shown that the TSA HDAC inhibitor , a known schistosomicidal drug , causes a wide range of gene expression changes in S . mansoni , and we were able to point to a number of cellular functions that were affected in the parasite , such as DNA replication and control of reactive oxygen species . A new epigenetic enzyme SmEZH2 emerged as a novel potential drug target to be studied with schistosomicidal activity , with its inhibition having a synergistic anti-parasitic effect along with HDAC inhibition .
|
Human schistosomiasis is a disease caused by the parasite Schistosoma spp . that affects over 230 million people worldwide . Treatment depends on a single drug , praziquantel , and the search for new drugs calls for exploiting strategies that are successful for other pathologies such as cancer , including the test of inhibitors targeting chromatin enzymes responsible for modifying histone proteins associated with DNA . Histone modifications regulate cellular gene expression . Inhibitors targeting an important class of these histone-modifying enzymes , namely Histone Deacetylases ( HDACs ) , are known to induce in vitro mortality of the parasite ( at the schistosomula and adult worm stages ) , however the molecular changes caused in the parasite were not known . In this scenario , we studied the effect of the HDAC inhibitor Trichostatin A on the parasite genome-wide gene expression , on histone modifications at gene promoter regions and on the chromatin acetylation status , and found important affected gene pathways . In addition , this approach showed affected genes associated with other histone modifications , which led us to test and identify a synergistic schistosomicidal agent , GSK343 , an EZH2 histone methyltransferase inhibitor . Our work points to the class of histone methyltransferase modifying enzyme as a novel drug target to be explored in the future for parasitosis treatment .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion",
"Conclusions"
] |
[
"schistosoma",
"invertebrates",
"schistosoma",
"mansoni",
"helminths",
"gene",
"regulation",
"dna-binding",
"proteins",
"animals",
"dna",
"transcription",
"dna",
"replication",
"genome",
"analysis",
"dna",
"epigenetics",
"chromatin",
"promoter",
"regions",
"genomics",
"chromosome",
"biology",
"proteins",
"gene",
"expression",
"histones",
"gene",
"ontologies",
"biochemistry",
"cell",
"biology",
"nucleic",
"acids",
"genetics",
"biology",
"and",
"life",
"sciences",
"computational",
"biology",
"organisms"
] |
2017
|
Histone deacetylase inhibition modulates histone acetylation at gene promoter regions and affects genome-wide gene transcription in Schistosoma mansoni
|
The biological function of chaperone complexes is to assist the folding of non-native proteins . The widely studied GroEL chaperonin is a double-barreled complex that can trap non-native proteins in one of its two barrels . The ATP-driven binding of a GroES cap then results in a major structural change of the chamber where the substrate is trapped and initiates a refolding attempt . The two barrels operate anti-synchronously . The central region between the two barrels contains a high concentration of disordered protein chains , the role of which was thus far unclear . In this work we report a combination of atomistic and coarse-grained simulations that probe the structure and dynamics of the equatorial region of the GroEL/GroES chaperonin complex . Surprisingly , our simulations show that the equatorial region provides a translocation channel that will block the passage of folded proteins but allows the passage of secondary units with the diameter of an alpha-helix . We compute the free-energy barrier that has to be overcome during translocation and find that it can easily be crossed under the influence of thermal fluctuations . Hence , strongly non-native proteins can be squeezed like toothpaste from one barrel to the next where they will refold . Proteins that are already fairly close to the native state will not translocate but can refold in the chamber where they were trapped . Several experimental results are compatible with this scenario , and in the case of the experiments of Martin and Hartl , intra chaperonin translocation could explain why under physiological crowding conditions the chaperonin does not release the substrate protein .
Proteins that have not yet folded to their native state may interfere with the machinery of the cell . For this reason , prokaryotic and eukaryotic cells have evolved special macro-molecular “chaperone” complexes that capture and refold partially folded proteins , thereby preventing them from indulging in cellular mischief [1] , [2] , [3 , ] . An important class of chaperone complexes are the cage chaperones or chaperonins . These complexes can efficiently trap partially folded proteins in a cavity that is barely larger than the target protein , and assist in the folding of an entire class of proteins with different amino acid sequences . Hence , the chaperonin is able to distinguish partly folded states from the native state , independently of the specific amino-acid sequence . It is important to stress that in the presence of molecular crowding ( similar to the one present in a cell ) the chaperonin complex has been demonstrated to not release the substrate protein before it reaches the native state [4] . Below , we report a detailed numerical study of protein dynamics inside the so-called GroEL-GroES chaperone complex . The GroEL complex consists of two barrel-shaped protein complexes joined at the bottom ( see Figure 1 ) . Non-native proteins can be captured in an open GroEL “barrel” . The GroES “lid” can then cap a protein-containing barrel , thereby initiating the refolding process . After about 15 seconds and several refolding cycles , the GroES cap is released and the other barrel is capped ( if it contains a protein ) . A single “cycle” of the GroEL-GroES chaperone hydrolyses seven ATPs [5] . This energy is presumably used to compress the protein in a smaller , more hydrophilic GroEL cavity , thus increasing the thermodynamic driving force to expel this protein . Recently we reported simulations of the kinetics of chaperone-induced protein refolding , using a lattice model for the GroEL-GroES complex [6] . This study suggested that proteins may refold either inside the cavity in which it has been captured or , surprisingly , by translocating from one barrel of the GroEL dimer to the other ( see Figure 2 ) . This second route is unexpected because it is generally believed that proteins cannot cross the equatorial plane that separates the joined GroEL barrels [7] , [8] , [9] . In the present paper we use atomistic and mesoscopic simulations to test whether such a translocation scenario is compatible with the available structural information on the GroEL complex . Our simulation studies focus on the equatorial regime of the GroEL complex that might be expected to act as a barrier against translocation . Crystallographic studies indicate that most protein units in the chaperonin complex have a fairly rigid structure both in the open and closed configurations [5] . However , low-resolution small-angle neutron scattering experiments [7] and cryo-electron microscopy [8] , [9] indicate the presence of disordered residues in a central cavity of the equatorial region . These chains do not show up in the X-ray crystallographic structure of the GroEL complex . The presence of disordered protein chains in the pore that joins the two GroEL chambers will certainly affect the permeability of the equatorial plane , but they need not block translocation . There are , in fact , examples [10] where disordered protein chains near a pore act to enhance the selectivity of the translocation process . Interestingly , the chemical composition of the disordered chains in the GroEL complex is similar to that of chains in known translocation channels in the nuclear pore complex .
We start by considering a very naive estimate that has the advantage that it is based on the fully atomistic simulations . From these simulations , we know the density profile of Cα atoms in the trans ring ( see Figure 4 ) . If , in the spirit of the Flory model , we assume that the density fluctuations of independent polymer Kuhn segments are Poisson distributed , we can estimate the probability P0 that a tube with the diameter of an α-helix contains no Cα atoms at all . This would lead us to an estimate of the free energy barrier that is equal to −kTlnP0 . Using the density profile of Figure 4 and an estimate [14] for the persistence length of a protein filament , we obtain a translocation barrier of approximately 4 kBT . If we make the ( unrealistic ) assumption that all Cα's in a single chain are fully correlated , then we estimate the barrier height to be only 1 kBT , which should be a significant underestimate . To see whether such a rough estimate is at all reasonable , we can repeat the same procedure for the coarse-grained model where we can also perform direct free-energy calculations . To be consistent with the previous case , we assume that the there are only excluded-volume interactions between the ( mainly Gly ) chains and the helix residues . In terms of the interaction matrix of [15] this is equivalent to assuming that the helix consist entirely of Thr residues . Assuming all Kuhn segments fluctuate independently , we estimate the barrier to be 4 kBT , and the assumption of fully correlated fluctuations will again yield an estimate of order 1 kBT . The good agreement between the fully atomistic and coarse grained estimates is , of course , somewhat fortuitous , in view of the fact that the two density distributions are not identical . However , it suggests that the coarse-grained model may be of practical use . Next , we compute the free energy barrier for the coarse-grained model system using the MC method described in the Methods . First we considered the case of pure steric interactions between both the chains and the helix . In Figure 5 we plot the free energy F ( QS ) as a function of the reaction coordinate QS that measures the number of Cα's that have entered the pore region . The plot shows a symmetric barrier with a height of approximately 2 kBT , which is surprisingly close to the estimate obtained assuming fully correlated fluctuations of protein segments . In other words: the chains tend to move as a whole in an out of the central area of the pore . This picture is supported by the snapshot of the pore region ( Figure S4 ) . The main conclusion that we can draw from the coarse-grained free-energy calculations is that the presence of seven protein chains in the central core region of the trans ring is not enough to obstruct translocation on steric grounds alone . Of course , the interaction between a typical translocation protein segment and the ring chains is not purely steric . To consider the effect of both attractive and repulsive interactions , we consider the two cases separately . As the chains consist predominantly of Gly , we consider the scenarios that the interactions between the filament residues and the Cα atoms of the helix are all equal to the twice the average of all attractive ( resp . repulsive ) interaction energies of Gly in the Betancourt-Thirumalai interaction matrix [15] ( −0 . 1kBT and +0 . 1kBT , respectively ) . The strength of attractive/repulsive interactions between the Cα's of the helix and the filament is therefore −0 . 2kBT ( resp +0 . 2kBT ) . By taking an interaction that is double the average attractive/repulsive interaction strength , we are presumably modeling rather extreme cases that should put bounds on the actual translocation barrier . Figure 5 shows the computed free-energy barriers for translocation in the case of attractive ( resp . repulsive ) interactions . The translocation barrier is appreciably lower when the chains attract the α helix ( 2 kBT ) than in the opposite limit ( 4 . 5 kBT ) . However , the most striking observation is that the barrier is quite small in either case - a barrier of 4 . 5 kBT can easily be crossed due to the action of thermal fluctuations . In fact , in the case of attractive interactions , there is virtually no barrier for translocation . This absence of a barrier may provide a rationale for the experimental observation that Krueger et al . observed in their SANS experiments [13] that a non-native protein ( DPJ-9 ) was partially sucked into isolated trans rings . If proteins can indeed translocate through the GroEL equatorial plane then this may also be relevant for the mechanism by which the GroEL/GroES chaperonin can help the refolding of proteins that are too big to be encapsulated . In such cases , portions of the protein could be attracted to the inside of the pore and perform either a complete or a partial translocation ( Figure S5 ) . According to [6] either process can enhance the refolding efficiency . The translocation of encapsulated non-native proteins is most likely in cases where the initial structure is far native . The reason is two fold: first of all , for such conformation there should be a low free-energy cost associated with partial unfolding—a necessary first step in translocation . Secondly , non-native chains that are trapped in a hydrophilic cage tend to be compressed . They can lower their free energy by translocating out of the cage . The simulations of [6] suggest that the driving force for such translocation can be as much as 0 . 5 kBT per amino-acid residue . Such a free-energy gradient is enough to completely remove a small free-energy barrier that might oppose translocation ( Figure S6 ) .
In conclusion , our simulation results are not compatible with the assumption that the disordered protein chains in the cis or trans rings provide an effective barrier against translocation . The present findings may help explain a puzzling experimental finding concerning refolding experiments in the presence of crowding agents [4] . The experiments of [4] demonstrated that , under physiological crowding conditions , the substrate protein does not escape from the chaperonin until it has reached its native state . This phenomenon is difficult to reconcile with the standard scenario where a protein ( folded or not ) is expelled from the cis-chamber as another non-native protein binds to the ATP-trans chamber . However , if it is not another protein that binds to the hydrophobic rim of the trans chamber , but the original protein that has translocated from the cis-chamber ( see Figure 2 ) , then it becomes clear why non-native proteins are unlikely to escape . We stress that the present findings do not rule out the possibility that non-native proteins fold into the native state without translocation [16]—translocation is simply an added route for protein folding . Such a route maybe very important for proteins that folds co-translationally , where confinement in a optimal size tunnel is crucial for efficiently reaching the native state [17] . Our simulations suggest that it would be interesting to carry out refolding experiments on GroEL with mutated chains that would strongly stick to each other ( or that could be cross-linked ) . Such mutation would impede the translocation and should thereby reduce the efficiency of the GroEL/GroES complex .
The flexible nature of this region prevented accurate X-ray determination of the chains filling the interconnecting pore . To obtain a full-atomistic model , the program MODELLER [18] has been used to generate a starting configuration of the chains missing in the X-ray structure ( PDB code: 1AON ) of the GroEL/GroES complex loaded with ADP . The reconstructed fragments ( sequence KNDAADLGAAGGMGGMGGMGGM ) are added at the C-term extremity of each monomeric building block of the chambers . In order to avoid steric clashes between the chains , the procedure has taken into account of the quaternary assembly of the chains . After the generation of the chains structures , three steepest-descent minimisations were performed , using the program GROMACS [11] ( energy minimisation tolerance: 0 . 1 , 0 . 05 and 0 . 01 kJ/mol−1nm−1 ) . Molecular Dynamics ( MD ) simulations were subsequently performed with the GROMACS [11] package by using GROMOS96 force field with an integration time step of 2 fs . Non-bonded interactions were accounted for by using the particle-mesh Ewald method ( grid spacing 0 . 12 nm ) [19] for the electrostatic contribution and cut-off distances of 1 . 4 nm for Van der Waals terms . Bonds were constrained by LINCS [20] algorithm . The system was simulated in the NPT ensemble by keeping constant the temperature ( 300 K ) and pressure ( 1 atm ) ; a weak coupling [21] to external heat and pressure baths was applied with relaxation times of 0 . 1 ps and 0 . 5 ps , respectively . As we intended to simulate a solution at a pH-value of 7 the protonation states of pH sensitive residues were assigned as follow: Arg and Lys were positively charged , Asp and Glu were negatively charged and His was neutral . The protein's net charge was neutralised by the addition of Cl− and Na+ ions . It would have been prohibitively expensive to simulate the entire chaperonin plus surrounding water . However , this was not necessary , as our aim was to study the structure and dynamics of the strongly fluctuating the equatorial rings , rather than the relatively rigid remainder of the GroEL “chamber” . We therefore immobilised the chamber atoms that are not directly connected to the pore chains . Of course , the equatorial chains were free to move and relax in the pore . In order to further reduce the number of degrees of freedom treated , we only considered water molecules ( SPCE [22] ) inside the GroEL chamber . We achieved this by imposing a strong repulsive external potential outside the GroEL chamber . Ignoring the water outside the cage is not an unreasonable simplification , as we found that the disordered chains were completely solvated by water molecules and never moved outside the atoms of the internal surface of the chamber . We assumed periodic boundary conditions only along the symmetry axis of the GroEL complex ( “z-axis” ) . The Caterpillar model is a modification of the tube model of Maritan and co-workers [14] , [23] , [24] . The main differences are that we treat the structure of the backbone in more detail and that our scheme to account for self avoidance by means of bulky side groups is computationally cheaper than the approach of Maritan et al . who introduced a three-body interaction to achieve the same . The interaction between amino acids with different side chain ECA is given by the following expression ( 1 ) where is the distance between nonadjacent Cα atoms in the protein and rmax is the distance at which the potential has reaches half ε . For ε we use the 20×20 matrix derived with the method of Betancourt and Thirumalai [15] . Although these interaction energies are strictly speaking neither energies nor free energies , they do provide a reasonable representation of the heterogeneity in the interactions between different amino acids . We modeled the hydrogen bonds between the hydrogen and the oxygen of the backbone with a 10-12 Lennard-Jones potential: ( 2 ) where the minimum is at σ = 2 . 0 Å and ELJ = 3 . 1 kBT . The directionality of the hydrogen bond was taken into account by multiplying the Lennard-Jones potential by a pre-factor ( 3 ) where θ1 and θ2 are the angles between the atoms COH and OHN respectively . The large hard spheres centered on the Cα atoms ensure that the orientation factor is maximum only for angles close to π . Apart from rotations around the dihedral angles φ1 and φ2 ( Figure S3 ) , the backbone is rigid . We have verified that this model can indeed reproduce typical protein motifs such as alpha helices and beta sheets , depending on the amino-acid sequence . To sample the conformations of the protein chains anchored on the trans ring , we use two basic Monte-Carlo moves: branch rotation and an improved version of the biased Gaussian step [25] , while for the translocating alpha helix we allow only translation moves and rotation around the center of mass .
|
Chaperonin complexes capture proteins that have not yet reached their functional ( “native” ) state . Non-native proteins cannot perform their function correctly and threaten the survival of the cell . The chaperonins help these proteins to reach their native state . The prokaryotic GroEL-GroES chaperonin is an ellipsoidal protein complex that is approximately 16 nm long . It consists of two chambers that are joined at the bottom . Interestingly , protein repair by this chaperonin is not a one-step process . Typically , several capture and release steps are needed before the target protein reaches its native state . It is commonly assumed that substrate proteins cannot translocate , i . e . , move inside the complex from one chamber to the other . In the absence of translocation , proteins that have not yet reached their functional conformation have to be released into the cytosol before being recaptured by a chaperonin . We present multi-scale simulations that show that it is , in fact , surprisingly easy for substrate proteins to translocate between the two chambers via an axial pore that is filled with disordered protein filaments . This finding suggests that non-native proteins can be squeezed like toothpaste from one chamber to the other: the incorrect structure of the protein is broken up during translocation and the protein has an increased probability to find its native state when it reaches the other chamber . The possibility for intra-chaperonin translocation obviates the need for a potentially dangerous release of non-native proteins .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biophysics/macromolecular",
"assemblies",
"and",
"machines",
"biophysics/theory",
"and",
"simulation",
"biophysics/protein",
"folding"
] |
2008
|
Multi-Scale Simulations Provide Supporting Evidence for the Hypothesis of Intramolecular Protein Translocation in GroEL/GroES Complexes
|
Currently , there are mounting data suggesting that HIV-1 acquisition in women can be affected by the use of certain hormonal contraceptives . However , in non-human primate models , endogenous or exogenous progestin-dominant states are shown to increase acquisition . To gain mechanistic insights into this increased acquisition , we studied how mucosal barrier function and CD4+ T-cell and CD68+ macrophage density and localization changed in the presence of natural progestins or after injection with high-dose DMPA . The presence of natural or injected progestins increased virus penetration of the columnar epithelium and the infiltration of susceptible cells into a thinned squamous epithelium of the vaginal vault , increasing the likelihood of potential virus interactions with target cells . These data suggest that increasing either endogenous or exogenous progestin can alter female reproductive tract barrier properties and provide plausible mechanisms for increased HIV-1 acquisition risk in the presence of increased progestin levels .
Globally , male-to-female mucosal transmission accounts for the majority of recent HIV-1 infections ( 60% ) [1] . Numerous factors may increase HIV-1 acquisition risk in women , including stage of HIV-1 infection and viral load of the partner , co-infections with sexually transmitted infections , cervical ectopy , and age [2 , 3] . A consensus is now building that hormonal fluctuations and changes in the mucosal barriers of the female reproductive tract ( FRT ) are significant risk factors for HIV-1 acquisition . [4–11] . The underlying mechanisms behind increased acquisition remains to be elucidated . During the menstrual cycle in both women and macaques , mucosal barriers of mucus and epithelium are altered by hormonal fluctuation . Mucus is the first barrier encountered by HIV-1 in the FRT and is known to change in both levels and consistency during the menstrual cycle and in the presence of hormonal contraceptives [12] . The thickness of the squamous epithelial barriers of the vaginal vault fluctuates greatly in response to hormones in the macaque model [13 , 14] . For example , an increase in progestin levels during the luteal phase of the menstrual cycle , and after high-dose injection of the contraceptive depot-medroxyprogesterone acetate ( DMPA ) , leads to a thinning of the squamous epithelial barrier [15 , 16] . Whether similar changes take place in women is less clear and currently debated [17–21] . In the macaque model , DMPA treatment induces a progestin dominant state that is known to increase the efficiency of SIV acquisition after vaginal exposure [16 , 22] . Recent studies in pigtail macaques have also illustrated increased virus acquisition risk during the late-luteal progesterone-dominant and menses phases of the menstrual cycle [23 , 24] . Until recently , studies in women were less definitive and there was much debate on this issue [5 , 7 , 8 , 25–27] . However , there is now recent and compelling meta-analytical evidence from two separate studies , suggesting that DMPA increases HIV-1 acquisition [28 , 29] . It is important for the field to gain mechanistic insights into why there may be an increase in viral acquisition during progestin dominant states . Here , we utilize two macaque vaginal challenge models to characterize changes occurring in the FRT mucosal barriers over the menstrual cycle and after DMPA treatment . Our first model utilizes reproductive tissues from terminal necropsies of rhesus macaques , during the rhesus macaque anovulatory season , that were either DMPA-treated or untreated . Our second model assesses reproductive tissues from the pigtail macaques either through necropsied SHIV ( SF162p3 ) -infected animals during various phases of the menstrual cycle or SHIV-infected and non-infected vaginal biopsies taken from macaques after DMPA administration . Additionally , nine SHIV-negative pigtail macaque animals were utilized for mucus transport assays . We believe that the comparison of these two widely utilized models is a strength of this study as it identifies similarities in hormonal impact and allows the results obtained here to facilitate the interpretation of the vast majority of macaque research studies to understand vaginal acquisition of SIV/HIV-1 . The centerpiece of our study is the ability to follow viral particles interacting with mucosal barriers by utilizing capabilities to detect fluorescent HIV-1 particles in tissue , thereby allowing the direct observation of how changes in the mucosal barriers influence viral entry paths . [30] . By comparing the barrier function and resident target cell populations of the FRT , we can detect conditions during the progestin-dominant state that could increase the possibility of virus reaching target cells within the lumen . Additionally , by obtaining pigtail macaque cervical mucus and conducting mucus transport assays , we are able to assess how DMPA treatment affects mucus permissiveness for HIV-1 mobility . These mechanistic insights from both macaque models can increase our understanding of how hormonal changes might increase HIV-1 acquisition risk in women .
It is known that the thickness of the squamous epithelial barriers of the vaginal vault of macaque models can vary greatly in response to hormonal signals [13 , 31] . Preliminary studies have revealed that changes in epithelial thickness were primarily a consequence of alterations in the thickness of the stratum corneum ( SC ) equivalent of this non-keratinized squamous epithelium . Therefore , we determined the thickness of this layer by defining the boundary of the spinosum-granulosum after immunofluorescent staining with an anti-adherens antibody to E-cadherin . Through the distribution of these cellular junctions we could distinguish the non-viable SC from the nucleated strata and measure the thickness of this SC to the lumen using previously reported algorithms [21 , 32] . When comparing high-dose DMPA-treated ( 30 mg ) with untreated rhesus macaques , the majority of treated animals exhibited an absence of an ectocervical SC layer and a large decrease in vaginal SC thickness ( Fig 1A and 1B ) . Exceptions to this were two DMPA-treated rhesus macaques , HG60 and N195 . Both macaques retained thicker ectocervical SC , while N195 also possessed a thick vaginal SC ( Fig 1A and 1B ) . Likewise , in pigtail macaques during the progestin dominant luteal phase , or after DMPA treatment , obvious reductions in the ectocervical and vaginal SC thickness were observed ( Fig 1C–1G . In the luteal phase of pigtail macaques , regions without any apparent SC were visible and after DMPA treatment the spinosum-granulosum could be as thin as 2–3 cell layers ( Fig 1F ) . During initial analysis , we noticed an increase in the density of CD4+ T-cells within the squamous epithelium of DMPA treated rhesus macaques , results that were unexpected . Following , we quantified the density of CD68+ and CD4+ target cells located within the stratum malpighii of the ectocervical and vaginal squamous epithelium ( Fig 2 , S1 Fig , S2 Fig ) . In high-dose DMPA-treated rhesus macaques , higher densities of CD4+ and CD68+ target cells were found within the epidermis of the ectocervix ( both P≤0 . 001 ) and vagina ( P = 0 . 034 and P≤0 . 001 , respectively ) , compared to untreated macaques ( Fig 2A and 2B ) . This difference of CD4+ and CD68+ target cell infiltration was also evident within vaginal biopsy samples , indicating that intra-epithelial cell migration was not a product of PA-GFP HIV-1 administration ( both P≤0 . 001 ) . In high-dose DMPA-treated pigtails , ectocervical and vaginal samples contained more intra-epithelial CD4+ and CD68+ target cells than were found during the follicular and mid-cycle phases , regardless of SHIV infection status ( all P<0 . 001 ) . Similarly , macaques sacrificed in the late-luteal phase contained more ectocervical and vaginal intra-epithelial CD4+ and CD68+ target cells than found during the follicular and mid-cycle phases ( both P≤0 . 001 ) ( Fig 2C , S1 Fig , S2 Fig ) . This analysis revealed that all macaques in a progestin-dominant state had a statistically significant higher density of CD4+ and CD68+ target cells in the ectocervical squamous epithelium . A significant increase in the density of CD4+ and CD68+ target cells in the vaginal tissue of the pigtail macaques was also observed in the late-luteal phase and after high-dose DMPA treatment , in both SHIV and non-infected animals ( Fig 2C , S1 Fig , S2 Fig ) . In contrast , examination of the CD4+ and CD68+ target cell density in the superficial aspects of the endocervix showed no statistically significant difference over the menstrual cycle in these same animals ( S3 Fig ) . Next we determined differences in virus particle and nanobead diffusion in FRT mucus collected from pigtail macaques before , during , and after injection with DMPA ( Fig 3 ) . Tracking the time-dependent trajectory of individual particles allowed the determination of the mean squared displacement ( MSD ) for HIV and pegylated nanobead . MSD provides information relating to the diffusion constant of particles under different conditions . For beads , the estimated MSD was greatest after DMPA treatment ( 7 . 30 μm2 ) when compared to before ( 5 . 24 μm2 , P = 0 . 030 ) and during treatment ( 5 . 32 μm2 , P = 0 . 033 ) ( Fig 3A ) . Additionally , the estimated MSD of HIV-1 during DMPA treatment was significantly higher ( 4 . 20 μm2 , P = 0 . 04 ) when compared to HIV before treatment ( 2 . 31 μm2 ) . These results reveal that the virus can move through mucus of FRT more easily during the progestin-dominant state induced by high-dose DMPA treatment . To better characterize the nature of particle mobility , we fit the MSD as a function of lag-time ( Δt ) to a power law and obtained alpha ( α ) , the diffusion exponent . Again , estimated means and standard errors were calculated for α values for both particle types in each sample collected before , during and after DMPA treatment . An α value equal to 1 indicates free diffusion while a lower α signifies increased obstruction of particle motion . Bead mobility remained nearly unhindered across all conditions such that the calculated estimated means were 0 . 90 , 0 . 94 and 0 . 94 for the before , during and after DMPA treatment conditions , respectively . In contrast , HIV-1 mobility was significantly freer during DMPA treatment ( 0 . 80 ) when compared to before ( 0 . 59 , P = 0 . 008 ) and after ( 0 . 59 , P = 0 . 003 ) ( Fig 3B ) . These results demonstrate that DMPA treatment increases mucus permissiveness for HIV-1 mobility over timescales of 1 . 5s . In order to assess in vivo viral tissue association , all macaques except DMPA-treated pigtail macaques , were intravaginally inoculated with high titer PA-GFP HIV-1 and euthanized 4 hours post-inoculation . In these tissues , the majority of samples from both DMPA treated and untreated rhesus macaques and cycling pigtail macaques exhibited PA-GFP virions associated with each tissue type , between epithelial cells , and penetrating the squamous and columnar epithelial barriers up to depths of 50um , potentially within reach of target cell populations ( Table 1 , Fig 4 , S4 Fig , S5 Fig ) . Differences in virus tissue association were observed between DMPA treated and untreated rhesus macaques ( Table 1 ) . In the ectocervix of untreated rhesus macaques , analysis of 505 z-stack images revealed 356 PA-GFP HIV-1 particles associated with the tissue . In DMPA treated macaques , analysis of 1006 z-stack images illustrated only 343 PA-GFP HIV-1 particles interacting with the tissue . Although there were no differences in PA-GFP HIV-1 penetration between untreated and DMPA treated macaques ( P = 0 . 997 ) , there was slight increase in the number of virions associated with the surface of the ectocervical stratum corneum in untreated animals ( P = 0 . 296 ) , although not statistically significant . Similarly , in the vagina , there was a slight increase in virion association with the squamous epithelium ( P = 0 . 127 ) . After analyzing 1067 z-stacks , 1109 virions were found to interact with the squamous epithelium in untreated rhesus macaques , compared to 294 virions in 1058 z-stacks in DMPA treated macaques . However , unlike what was noted in with the ectocervix , there was a significant increase in the number of penetrating virions per z-scan in untreated macaques when compared to those animals that were DMPA treated ( P<0 . 001 ) , results suggesting that the tissues of the ectocervix and vagina may not be as similar as previously posited . Inversely , DMPA-treated macaques depicted a significant increase in the number of virions entering the endocervical canal and interacting with the simple columnar tissue , compared to untreated macaques ( P = 0 . 003 ) , although there was no difference in the number of penetrating virions between the two groups ( P = 0 . 212 ) . To extend this work to address natural hormonal changes over the menstrual cycle , we conducted complementary studies using PA-GFP HIV-1 in the in vivo pigtail macaque model . However , one caveat to this particular study was that we were only able to gain access to a small number of SHIV ( SF162p3 ) -infected animals . This small sample size of animals thereby impeded statistical analysis and has been described in more detail in the materials and methods . Regardless , similar to rhesus macaques that received exogenous progestin , pigtail macaques in the high progestin , late-luteal phase of the menstrual cycle exhibited more virions associated with the epithelium of the endocervical canal ( Fig 4B–4E , Table 1 ) . Of 495 images , 62 virions were associated with the simple columnar , of which 57% ( n = 35 ) were penetrating ( Fig 4D ) . However , of 315 images , no virions were seen penetrating the simple columnar of the progesterone-low follicular stage . Interestingly , during the mid-cycle period , when progesterone begins to rise , 37 virions amongst 517 images were located within the canal . Of these , 54% ( n = 20 ) penetrated the simple columnar ( Fig 4D ) . Most of these penetrating virions were seen in a single animal . Moreover , much like the DMPA-treated rhesus macaques , there were also fewer virions associated with the squamous epithelia of the ectocervix and vagina during the late-luteal phase . In contrast , more virions interacted with the squamous epithelium of the ectocervix and vagina of those macaques in the progesterone-low follicular and mid-cycle stages . In the follicular phase , 66% ( n = 62 ) of identified virions penetrated the ectocervical epithelium ( Fig 4B ) and 72% ( n = 101 ) penetrated the vaginal epithelium ( Fig 4C ) . During mid-cycle , 75% ( n = 64 ) of identified virions penetrated the ectocervical epithelium ( Fig 4B ) and 60% ( n = 86 ) penetrated the vaginal epithelium ( Fig 4C ) .
The studies presented here were designed to gain mechanistic insights into increased HIV-1 acquisition associated with vaginal challenge in macaque models . The FRT is a hormonally sensitive mucosal environment with dynamic changes in mucosal barrier function . Macaque models have revealed that progestin-dominant hormonal states , both endogenous and exogenous , can increase the efficiency of SIV/SHIV acquisition after vaginal challenge [16] . HIV-1 transmission requires that the virus in the inoculum reach a susceptible target cell in the mucosal tissue . We observed two progestin-dominant state changes in the mucosal barriers of macaques that would increase the likelihood of HIV-1 interacting with tissue resident target cells compared to during low-progestin states: increased viral entry into the endocervical canal and increased proximity of virus to target cells infiltrating the squamous epithelium . Utilizing the live pigtail macaque challenge model , we found that a paucity of virus associated with the columnar epithelium during the follicular phase of the menstrual cycle . The same held true for rhesus macaques that were out-of-season and non-cycling , a state also defined by minimal progestin levels . In contrast , after vaginal challenge during progestin-dominant states we observed an increase in virions able to reach the endocervical columnar epithelial barrier . This was noted , after high-dose DMPA treatment , for both rhesus and pigtail macaques as they entered the menstrual cycle luteal phase . The ability of the virus to better reach the endocervical columnar epithelium during progestin dominant states might be due to anatomical changes , alterations in mucus function , or a combination of the two [33 , 34] . Progestin-based hormonal contraceptives , such as DMPA , influence mucus by drastically reducing volume production and increasing viscosity to prevent sperm access to the cervical canal [35] . The direct analysis of HIV-1 mobility in pigtail macaque FRT mucus revealed that the ability of HIV-1 to diffuse through FRT mucus was increased relative to the diffusion of the pegylated nanobeads during DMPA treatment ( Fig 3 ) . The pegylated nanobeads are believed to be resistant to charge-based interactions with mucins ( muco-adhesion ) , and instead measure mucus pore size [36] . Consistent with hormonal changes influencing the muco-adhesion of the viral particles , we see minimal influence of the hormonal treatment on the mobility of the beads , which are non-muco-adhesive and of a similar size to the viral particles . These observations do not point to mucus inhibition of HIV-1 mobility by simple changes in pore size but suggest a virus-specific impediment for HIV-1 that is significantly abrogated in the presence of exogenous progestin . We have previously detected this type of activity in human cervicovaginal mucus [37] . The reported influence of pH on virus mobility further supports the potential role of muco-adhesion in this system [38–40] . The results presented in Fig 3 support the hormonal regulation of this muco-adhesion . During hormone treatment there is a significant increase in the MSD and α of HIV-1 in the absence of any change in the bead mobility . Further support for hormonal influence is seen during the washout period where the MSD of the beads increases significantly while the MSD and α of HIV-1 is decreased . It is known that mucins are highly glycosylated and alterations in these glycosylations are hormonally regulated , which may be responsible for anchoring pathogens to mucus [41–43] . For example , DMPA has been shown to reduce expression of negatively charged sialic acid carbohydrates on these proteins; therefore , there may be natural repulsion that occurs between HIV-1 and these carbohydrates in mucus , providing favorable conditions for HIV-1 transport . [43] . Importantly , the increased HIV-1 diffusion through mucus observed after DMPA treatment was associated with increased virus entry into the endocervical canal during the progestin-dominant state . This increased ability of virus to enter the endocervical canal and reach the columnar epithelial barrier is likely part of the mechanism by which HIV-1 acquisition may be increased during high-progestin environments ( Fig 5 ) . Changes in the squamous epithelium of the vaginal vault during progestin-dominant states also increased the likelihood that virus might encounter and potentially infect tissue resident target cells . The most obvious change in the squamous epithelium was the decrease in the epithelial barrier thickness of the vaginal vault during the natural or induced progestin-dominant state ( Fig 1 ) [13–15 , 44] . The ability of HIV-1 to penetrate the squamous epithelium did not appear to be associated with a decrease in epithelial thickness , but rather was more readily observed in thicker SC [30] . This phenomenon can be especially noted within the ectocervix of HG60 and the ectocervix and vagina of N195; two DMPA-treated rhesus macaques that retained a thick SC and exhibited a large number of penetrating HIV-1 virions ( Fig 1 , S5 Fig ) . However , in the case where virus can enter the non-viable pseudo-keratinized layer found in untreated animals , there were no target cells within this non-viable layer . Therefore , when progestin influence was minimal , the thick SC offered a partial barrier to HIV-1 transmission by increasing the distance that virions must traverse to reach viable target cells . The decreased thickness of the squamous epithelial barrier during the progestin-dominant state was associated with an increase in the number of CD4+ T-cells and CD68+ macrophages within the squamous epithelium . Previous studies have suggested no difference in target cell distribution in progesterone-treated macaques or during different menstrual cycle phases [45 , 46] . However , unlike the studies here , they did not strictly focus on the epidermis or only looked at CD3+ cells [47] . Here we focused on target cell density within the squamous epithelium and observed a significant increase in intra-epithelial CD4+ T-cells and CD68+ macrophages during the natural and DMPA-induced progestin-dominant state . Additionally , in DMPA-treated pigtail macaques , there were significant increases in intra-epithelial target cells regardless of macaque SHIV status , results that suggest that target cell infiltration is a product of a high-progesterone environment and not lentiviral infection ( Fig 2C ) . Interestingly , we observed two rhesus macaques ( HG60 and N195 ) that exhibited characteristics similar to both untreated and DMPA-treated rhesus macaques . Although both animals were treated with DMPA , the SC of the ectocervical ( HG60 and N195 ) and vaginal squamous epithelium ( N195 only ) remained present and thick , akin to untreated macaques . Furthermore , in those tissues where the SC remained thick , both rhesus macaques displayed a large number of virions “stuck” within the SC of the squamous epithelium and a decreased density of intraepithelial target cells results that also mirrored the untreated group and affected the overall statistics of the combined DMPA-treated animals ( S1 and S5 Figs ) . However , these macaques also illustrated viral association with the endocervical simple columnar epithelium similar to what was observed in DMPA-treated macaques ( S5 Fig ) . These data suggest two conclusions: 1 ) it is the epithelial physiology , which can be manifested in a variety of ways ( thinning , cellular junction alteration , etc . ) , and not progesterone directly , that affects intraepithelial target cell infiltration , and 2 ) progesterone can still affect mucus permeability properties . This would indicate there are different progestin-influenced pathways in the FRT for changes in mucus function versus alterations in epithelial physiology . It is notable that infiltration of target cells into the stratum malpighii would bring them closer to the lumen . Target cells close to the lumen were prominent in the squamous epithelium during the progestin-dominant state . Interestingly , when comparing DMPA-treated to untreated rhesus macaques , virus penetration was less apparent within the squamous tissues during the progestin-dominant state . Whether this is due to virus clearing by accessible target cells or being endocytosed by live keratinocytes of the stratum malpighii is not known . However , this situation , where the potential target cells are coming to where the virus is located , is potentially a mechanism for the increased acquisition observed in the progestin-dominant state . In the macaque model , CD4+ T-cells and CD68+ macrophage distribution , and virus penetration were dependent on epithelial thickness , suggesting HIV-1 interactions with the FRT may differ in the luteal and follicular stages of the menstrual cycle or with the use of progesterone-only contraceptives ( Fig 5 ) . Overall , the results presented here reveal that the high-dose DMPA models and the natural luteal phase in the pigtail macaque model show general similarity . How these observations in both macaque models relate to potential hormonal influences of increased acquisition in women remain to be elucidated . For example , it is clear that the standard high-dose DMPA treatment used here is much higher than the levels utilized in women . It has recently been reported that DMPA doses in the pigtail macaque model similar to the dose for women results in much smaller effects on epithelial thickness [47] . Previous studies of squamous epithelial thickness suggest that there is little to no variability in FRT epithelial thickness in women with exogenous or endogenous progestin exposure [48 , 49] . However , other studies suggest that differences in epithelial thickness can be detected [21] . Similar discrepant results have been obtained relating to target cell density in the squamous epithelium . Some clinical studies in women suggest that target cell density does not change [18 , 49–51] , while other studies have suggested that the vaginal CD4+ T-cell and CD68+ macrophage populations increased significantly amongst women receiving DMPA injections [48 , 52] . Likely , differences in analytical methods and sampling times account for these differences . If we extrapolate the macaque studies to HIV-1 acquisition in women , it suggests that HIV-1 acquisition can be influenced by menstrual cycle and hormonal contraceptives . To this end it should be possible to study the epithelial thickness , target cell localization , and mucus barrier function in women over the menstrual cycle and during the use of hormonal contraceptives . Considering the building consensus that DMPA can increase HIV-1 acquisition in women , it seems likely that some of the mechanisms identified here are associated with higher acquisition risk , including increased virus association with the endocervical columnar barrier and the infiltration of target cells into the squamous epithelium during the progestin dominant state . These studies provide mechanistic insight into the changes of physiological parameters of the FRT under various hormonal conditions associated with increased risk of acquisition and should be considered in the development of novel HIV-1 prevention technologies .
We received access to 8 pigtail macaques ( Centers for Disease Control and Prevention ) infected with the non-pathogenic SHIV strain SF162p3 and examined animals in an exploratory study in three distinct stages of the menstrual cycle . The study was descriptive and therefore not powered . Animal handlers and laboratory staff performing assays were aware of each animal’s phase in the menstrual cycle , but the samples were shipped to the Hope Laboratory for evaluation in blinded manner . The tissues for all SHIV ( SF162p3 ) -infected cycling animals were examined for epithelial thickness , virus penetration , and target cell density . Likewise , four SHIV ( SF162p3 ) -infected pigtail macaques were pre-treated with intramuscular injections of 30 mg Depo-provera/DMPA 4–5 weeks ( 28–33 days ) prior to sacrifice . These samples , along with vaginal biopsies from 2 DMPA-treated non-infected pigtail macaques were also assessed for epithelial thickness and target cell density . Complementary studies were done in 10 rhesus macaques ( Tulane National Primate Research Center ) comparing DMPA treated and control animals . Additionally , mucus studies in 9 , SHIV-negative , pigtail macaques were also conducted; focusing on virus particle and nanobead mobility in DMPA treated and untreated animals . All animal experiments were conducted in accordance with each facility’s respective Institutional Animal Care & Use Committee ( IACUC ) guidelines . No animals were excluded from analyses . All R5-HIV-1Ba-L PA-GFP-Vpr viral stocks were created and characterized as previously described [30] . All macaques were housed at the Tulane National Primate Research Center ( TNPRC ) ( Macaca mulatta ) or the Centers for Disease Control and Prevention ( CDC ) ( Macaca nemestrina ) , both in accordance with the Association for Assessment and Accreditation of Laboratory Animal Care International standards . All rhesus macaque studies were reviewed and approved by the Tulane University Institutional Animal Care and Use Committee under protocol number P0153 . Additionally , all pigtail macaque studies were reviewed and approved by the Institutional Animal Care and Use Committee of the Centers for Disease Control and Prevention under protocols 2445 , 2009 , and 2423 . All animal housing and studies were carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health ( NIH , AAALAC #000594 ) ( TNPRC ) or the National Research Council ( U . S . ) Committee for the Update of the Guide for the Care and Use of Laboratory Animals Institute for Laboratory Animal Research ( U . S . ) , National Academies Press ( U . S . ) , Guide for the care and use of laboratory animals . 8th ed . Washington , D . C . : National Academies Press , 2011 ( CDC ) , both with the recommendations of the Weatherall report; “The use of non-human primates in research” . Rhesus macaques were provided ad libitum with Monkey chow ( Lab Fiber Plus Primate diet-DT , PMI Nutrition International , St . Louis , MO ) and supplemented with fruits , vitamins and Noyes’ treats ( Research Diets , New Brunswick , NJ ) . Pigtail macaques were provided with an assortment of food selections such as fruits , vegetables , or seeds . All clinical procedures were carried out under the direction of a laboratory animal veterinarian . All procedures were performed under anesthesia using ketamine , often in combination with telazol , and all efforts were made to minimize stress , improve housing conditions , and to provide enrichment opportunities ( e . g . , objects to manipulate in cage , varied food supplements , foraging and task-oriented feeding methods , interaction with caregivers and research staff ) . Euthanasia of all macaques were performed in a humane manner ( intravenous pentobarbital ) as recommended by the American Veterinary Medical Association Guidelines on Euthanasia , 2013 , and in accordance with the euthanasia policies of each institution . Six rhesus macaques were pre-treated with intramuscular injections of 30 mg depo-medroxyprogesterone acetate ( Depo-provera/DMPA ) 28–33 days prior to virus exposure , leaving 4 macaques untreated . Approximately , 4mL of high titer PA-GFP HIV-1 was intravaginally applied to all anaesthetized animals that were subsequently returned to their cages for 4 hours . Likewise , four SHIV ( SF162p3 ) -infected and two non-infected pigtail macaques were pre-treated with intramuscular injections of 30 mg Depo-provera /DMPA 4–5 weeks ( 28–33 days ) prior to sacrifice or prior to vaginal biopsy acquisition , respectively . SHIV ( SF162p3 ) is a nonpathogenic virus that results in a very low viral load , and does not cause a permanent decrease in CD4+ T-cell populations . For menstrual cycle-related studies , eight SHIV ( SF162p3 ) -infected pigtail macaques were visually inspected for perineal tumescence and menses onset and progesterone measurements taken , as previously described , to determine the approximate day of menstrual cycle prior to HIV-1 exposure [24 , 53] . 1mL of PA-GFP HIV-1 was intravaginally applied at pre-determined days/phases of the menstrual cycle . Phases were designated as follicular ( day 1 of menstruation until day 14 ) , midcycle ( days 14–16 ) , or luteal ( days 17 to day prior to menstruation ) . All macaques were euthanized and PA-GFP HIV-1 inoculated reproductive tracts were removed for analysis . Multiple 1cm3 samples were harvested from the ectocervix , endocervix , and vagina . Tissue samples were preserved in optimal cutting temperature ( OCT ) and stored at -80°C . To assess the effects of contraceptives on HIV-1 transport in mucus , nine additional SHIV-negative pigtail macaque animals were utilized [54] . During the entirety of the study , all mucus samples were collected once weekly for all animals . To establish a baseline , mucus was collected for 4–6 weeks prior to intramuscular DMPA administration , thereby comprising the “before” condition . Macaques were divided into 3 groups of n = 3 and received either a 0 . 5 , 1 . 5 or 2 . 5mg/kg dose of DMPA once every 4 weeks for 2 months . Mucus was collected weekly , to up to 4 months after the final DMPA injection . Samples collected from first injection up to one month after the final injection made up the “during” condition . The after condition consisted of all sample collections occurring one month after final DMPA injection until the end of the study ( ~2 months ) For analysis , animals receiving different DMPA doses were pooled . During collection , the cervix was exposed using a vaginal speculum and cervical mucus was collected using a sterile Aspirette ( Cooper Surgical ) by insertion into the cervical os , approximately 1 . 5 cm or less with applied negative pressure . Cervical secretions were then expelled into a sterile 1 . 5ml Eppendorf O-ring tube ( Fischer Scientific ) and placed on ice until imaging the next day after shipment to Chicago , IL . Particle diffusion mucus transport assays were performed in accordance with established protocols as previously described [37] . Concentrated R9 BaL Gag-cherry ( HIV-1 ) and fluorescent polystyrene 200nm nanobeads were mixed in equal concentration [37] . Aliquots of aspirated macaque vaginal mucus ( 5μL ) were pipetted onto glass slides with affixed double-sided adhesive single-well spacers . To the mucus aliquot center , 0 . 5μL of HIV-1/beads mixture was added and gently pipetted until uniformity was achieved . Coverslips were placed over the mucus and secured with nail polish . Movies of both particle types were imaged inside of a temperature-controlled chamber maintained at 37°C with an EMCCD camera , attached to a deconvolution microscope . Imaging occurred 30μm away from the coverslip and no less than 100 particles of each type were imaged every 150ms for one minute . Individual particle positions for each particle type were analyzed using two-dimensional custom-based algorithmic particle tracking software . The collective population mobility was measured by calculating the time-averaged ensemble mean squared displacement ( MSD ) over timescales of 1 . 5 seconds ( Δt of 1 . 5s ) using custom-based particle tracking software to determine the individual particle positions for HIV and the muco-inert nanobeads [37 , 55] . Sectioned tissues were fixed in 3 . 7% formaldehyde in PIPES buffer and blocked with normal donkey serum prior to staining . For adherens junction identification in macaque tissues , HECD1 ( a gift from the laboratory of Dr . Kathy Green at Northwestern University ) was utilized . To identify target cells , rhesus macaque tissue was stained with MCD1 ( Santa Cruz ) CD4 ( Cell Marque ) and CD68 for macrophages ( DakoCytomation ) . Additional antibodies revealed cytokeratin-7 ( DakoCytomation ) staining in simple columnar tissue . To confirm that all PA-GFP fluorescence was associated with viral proteins , p24 ( AG3 . 0 National Institutes of Health AIDS Research and Reference Reagent Program; Jonathon Allan ) , and p17 ( Capricorn ) antibodies were used [56] . Secondary antibodies , Rhodamine RedX ( Jackson ImmunoResearch ) and Cy5 ( Jackson ImmunoResearch ) , were also utilized . Antibody specificity was determined by negative results with respective isotype control antibodies . Hoechst DAPI ( Invitrogen ) was used for DNA staining and wheat germ agglutinin ( Invitrogen ) highlighted cellular glycoproteins . After staining , mounting medium ( DakoCytomation ) and coverslips were applied and sealed with nail polish . Images were obtained by deconvolution microscopy on a DeltaVision RT system collected on a digital camera ( CoolSNAP HQ; Photometrics ) using a 40x or 100x oil objective . To assess epithelial thickness in rhesus and pigtail macaques , we took ten measurements of each tissue type per macaque . By utilizing an anti-adherens antibody , we distinguished the stratum corneum of each sample from the viable layers of the squamous epithelium . Using IDL and specifically created algorithms we measured the stratum corneum thickness , as previously described [21] . For virus penetration analyses , 100x Z-scan stacks were collected over 15μm for each image field and image analysis was performed with the softWoRx software ( Applied Precision ) . Several criteria were developed to assure the visualization of photoactivated virions , including a minimum of 2-fold increase in intensity post-photoactivation . Post-photoactivation GFP signal intensity was measured using softWoRx line profiling software . Penetrating virions were defined as virions entering more than one micron into the squamous or columnar epithelium and were determined with the measuring tool supplied by the softWoRx software . We use the cut off of 1 micron due to the resolution of our system . With a measurement less than 1 micron , we cannot be sure if the virion is in the tissue or on the surface of the tissue; therefore , 1 micron and beyond ensures that the detected virion is indeed penetrating . For each tissue block , 20 images were obtained with locations chosen randomly from multiple tissue sections . All combined tissue blocks encompassed the entire cervix and vaginal vault of each animal ensuring that any variability in installation would not be problematic and also allowing us to detect viral particles in each tissue type . Regions imaged were 60μm wide and 12μm thick . To determine target cell density in macaques , we took ten measurements , across multiple tissue blocks , of each tissue type per macaque . Panel images were acquired to include the epithelium and lamina propria . Each image consisted of a stitched panel comprised of three 40x images across the lumen and n 40x images to the basal layer , n being dependent on the epidermal thickness of each sample . Using the SoftWorX software we calculated areas of robust epithelial adherens junctions and determined target cell densities for each sample . To calculate density , the number of target cells in each sample was divided by the average HECD-1 area . The softWoRx software measuring tool was used to measure the shortest distance of intraepithelial target cells to the lumen . All virus penetration data were analyzed using data per image or per virion and included three models . The three models were; a negative binomial generalized estimating equation ( GEE ) modeling of the count per image of virions present on the tissue ( all observations per image ) , a binomial GEE with logit link modeling of the proportion per image of virions that penetrate the tissue ( observations with at least 1 virion present per image ) , and a gamma GEE modeling of the depth of penetration per virion . This approach was applied to two datasets: 1 ) rhesus macaque in vivo examining the covariates DMPA treatment and tissue type ( n = 8 , 4218 images ) and 2 ) pigtail macaque in vivo ( n = 8 , 4420 images ) examining the covariates menstrual stage and tissue type . Unfortunately , with the pigtail macaque samples , the data were too sparse to calculate the model with the main effects of tissue type ( ectocervix , endocervix , and vagina ) , along with menstrual cycle phase ( follicular , midcycle , and luteal ) and the interaction of the two variables . Overall , the GEE model was over saturated and the generalized Hessian matrix was not positive definite; therefore , the model would not run . All comparisons between multiple groups for target cell density analysis were performed . The initial datasets examined intraepithelial cell count for DMPA and untreated rhesus macaques . Later datasets included pigtail macaque data and examined in detail intraepithelial target cell density based on hormonal environment: DMPA treated and phases of the menstrual cycle . All data sets were stratified by tissue type . Target cell count per unit of area was examined in each dataset using negative binomial or zero-inflated negative binomial GEE where appropriate . Gamma GEE models were performed to assess the relationship between particle dispersion ( MSD ) and time . Time consists of before , during , and after treatment with repeated measures across days within each time period . The ‘before DMPA’ condition is represented by sample collections occurring four to six weeks before initial DMPA injection . One week after the initial injection and up to one month after the final injection make up the ‘during DMPA’ condition . The final condition , ‘after DMPA’ is comprised of all samples that occurred one month after the final DMPA injection . The models were performed separately for beads and virus particles . The underlying distribution of the outcome was assumed to be a gamma , accounting for repeated measures within monkey . All analysis were performed using SAS 9 . 4 and all limits of statistical significance were set at p < 0 . 05 .
|
Sexual transmission accounts for over 80% of all HIV-1 infections , with half of new infections occurring in women . Epidemiological studies suggest that certain hormonal contraceptives may be associated with increased HIV-1 acquisition . A hormonal influence of vaginal HIV acquisition is supported by studies utilizing various non-human primate models , which reveal that susceptibility to vaginal transmission is affected by the menstrual cycle or exogenous hormonal treatment . However , the mechanism of increased susceptibility remains unknown . Here , utilizing a variety of techniques and non-human primates , we illustrate that progestin-based contraceptives , such as Depo-Provera , and the natural menses luteal phase have a very similar impact in these models systems . Both increase virus influx into the endocervix and stimulate target cell infiltration of the squamous epithelium . The shedding of the superficial dead layers of the squamous epithelium in the progestin dominant state put the tissue resident cells in close proximity with virus in the lumen increasing the possibility of interactions and infection . A better understanding of vaginal SIV/SHIV acquisition in these widely utilized models is essential to interpret the results of ongoing clinical trials of HIV-1 acquisition during hormonal contraceptives use . An increased understanding of the mechanisms of HIV acquisition should contribute to vaccine development .
|
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2016
|
Increases in Endogenous or Exogenous Progestins Promote Virus-Target Cell Interactions within the Non-human Primate Female Reproductive Tract
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Echinococcus granulosus infections are a major public health problem in livestock-raising regions around the world . The life cycle of this tapeworm is sustained between dogs ( definitive host , canine echinococcosis ) , and herbivores ( intermediary host , cystic hydatid disease ) . Humans may also develop cystic hydatid disease . Echinococcosis is endemic in rural areas of Peru; nevertheless , its presence or the extension of the problem in urban areas is basically unknown . Migration into Lima , an 8-million habitant's metropolis , creates peripheral areas where animals brought from endemic areas are slaughtered without veterinary supervision . We identified eight informal , unlicensed abattoirs in a peripheral district of Lima and performed a cross-sectional study in to assess the prevalence of canine echinococcosis , evaluated by coproELISA followed by PCR evaluation and arecoline purge . Eight of 22 dogs ( 36% ) were positive to coproELISA , and four ( 18% ) were confirmed to be infected with E . granulosus tapeworms either by PCR or direct observation ( purge ) . Later evaluation of the human population living in these abattoirs using abdominal ultrasound , chest X-rays and serology , found 3 out of 32 ( 9 . 3% ) subjects with echinococcal cysts in the liver ( two viable , one calcified ) , one of whom had also lung involvement and a strongly positive antibody response . Autochthonous transmission of E . granulosus is present in Lima . Informal , unlicensed abattoirs may be sources of infection to neighbouring people in this urban environment .
Canine echinococcosis is caused by the adult stage of the tapeworm Echinococcus granulosus; infected dogs are the source of infection for human cystic hydatid disease ( CHD ) , a serious public health problem in farming regions around the world [1] , [2] . In the domestic life cycle of E . granulosus dogs harbor the intestinal adult tapeworm stage , spreading the parasite' eggs into the environment through their feces . Ruminants ( intermediary hosts ) , ingest infective eggs and develop cysts in their internal organs . Feeding dogs with raw viscera of infected animals contributes to perpetuating this cycle [3] , [4] . Humans get infected by accidental ingestion of eggs from tapeworm-infected dogs and develop cystic lesions , principally in liver and lungs , after several years [5] . Both canine echinococcosis and CHD are commonly found in rural farming communities , though there are some reports of human and dog infection in urban areas [6] , [7] , [8] , [9] , [10] , [11] . In a non-endemic coastal urban city in Peru , a study on abattoir workers and stray dogs from the same areas found 6 . 25% of canine echinococcosis by examination of the intestinal contents of stray dogs and 12% of human CHD [12] . Lima , the capital of Peru , with a population burgeoning on 8 million people , is assumed to be non-endemic for canine echinococcosis and CHD; the last reported prevalence of canine echinococosis was 0 . 003% [13] . However , 21% of lung CE patients in a hospital in Lima between 1980 and 1986 were born in the same city and had not spent more than one month in endemic regions [14] . Lima's unique migratory patterns have created regions in the periphery of this city where poor populations bring animals from endemic areas and slaughter them without veterinary supervision . We assessed the prevalence of canine echinococcosis in dogs living in informal , unlicensed abattoirs located in a peripheral district of Lima , and of CHD in the individuals living in the same dwellings .
The protocol and written informed consents were approved by the Animal and Human Ethics Committees of the Universidad Peruana Cayetano Heredia . All subjects older than eighteen years old provided written inform consent; and in the case of children , they provided written inform assent and their parents/guardians provided written consent for them . Animal ethical committee reviewed and approved the protocol according to international guidelines provided by The Office of Laboratory Animal Welfare ( A5146-01 ) . Cross-sectional study to determine the presence of canine echinococcosis and human CHD in informal urban abattoirs in Lima , Peru . The district of Puente Piedra is one of 49 districts composing metropolitan Lima . Located in the north of Lima , it covers an area of 71 . 18 km2 and has a population density of 3281 . 35 inhabitants per km2 [15] . Based on information collected through interviews to residents of Puente Piedra , we identified ten informal , unlicensed abattoirs where people raise and slaughter cattle and sheep , which are principally brought from endemic areas of the Peruvian highlands . In each abattoir center we evaluated all dogs older than 2 months that had been living ( sleeping and being fed ) there for at least 2 months before the visit , excluding dogs recently de-wormed or those that were pregnant . Dog stool samples were evaluated by coproparasitoscopy and coproELISA . Samples positive in coproELISA were evaluated by PCR and the dog had an arecoline bromhydrate purge ( Figure 1 ) . A positive dog was defined as any dog with a positive coproELISA , independently of the results of the other evaluations ( dogs without a coproELISA evaluation were not included in the analysis ) . After obtaining the results , praziquantel ( one 5 mg/kg dose ) was administered to all dogs belonging to abattoir centers where at least one dog was positive by any method . The methods used for each evaluation are briefly described below: We invited to all subjects older than 3 years olds who were living in the informal abattoirs to be evaluated by abdominal ultrasound ( US ) and/or chest X-Ray , in addition we offered serological evaluation by Enzyme-linked immunoelectrotransfer blot ( EITB ) . After the evaluations , individuals with abnormal radiological findings were referred to a local health center to be treated . US exams were performed using a Sonosite plus 3 . 5-MHz portable machine . Each evaluation was video-recorded and sent to a second , different observer to confirm or rule out the diagnosis of CE and its categorization according to the WHO US classification [20] . There were no discrepancies between observers . Posterior-anterior chest x-Rays were taken at a local health center facility and read by a trained radiologist . Human blood samples were obtained by venipuncture and taken to the Center for Global Health laboratories of the Universidad Cayetano Heredia in Lima . EITB was performed as previously described , using purified hydatid cyst fluid [21] . The presence of reactions to one or more of three known antigens ( 8 , 16 , and 21 kD ) was defined as a positive assay . χ2 tests were used to compare the frequencies of discrete variables . Continuous measurements were presented as median values and compared using Mann-Whitney test . A simple logistic regression ( SLR ) analysis followed by a multiple logistic regression ( MLR ) analysis were performed to evaluate the association between individual characteristics and the odds of being infected . A p-value of <0 . 05 was taken to indicate statistical significance . All analyses were conducted using Stata version 10 ( StataCorp LP College Station , TX , USA ) .
The owners of 8 out of 10 informal abattoirs in Puente Piedra agreed to participate . From 31 dogs in these abattoir centers , 9 were not evaluated: one was pregnant and for 8 animals fecal samples could not be obtained or were insufficient . Therefore , we analyzed data on 22/31 dogs . Characteristics of evaluated dogs and abattoir centers are presented in table 1 . The dogs had a median age of 30 months ( range: 4–120 ) , and median weight 16 . 5 kg ( 4 to 35 ) . Twelve dogs ( 54 . 6% ) were male , and only for 4 dogs ( 18 . 2% ) owners reported feeding them with viscera . Twelve dogs ( 54 . 6% ) belonged to abattoir centers next to the river . Using the above described cut-off , 8 of 22 dogs ( 36 . 4%; 95% CI:17 . 2%–59 . 3% ) were ELISA positive . The lowest OD value was 0 . 14 , and this dog had a negative PCR but expelled two E . granulosus worms after purge ( Table 2 ) ; in the remaining 7 , two were PCR positive ( purge was not performed in these two dogs ) . From the remaining 5 dogs ( all PCR negative ) , only 3 of them had arecoline purge and one dog expelled E . granulosus worms . Considering only those dogs with either demonstrated worms after purge ( n = 2 ) or a positive PCR ( n = 2 ) , the minimal prevalence of canine echinococcosis in this population is 4/22 ( 18%; CI:5 . 2%–40 . 3% ) ( Figure 1 ) . Positive dogs ( n = 8 ) belonged to 3 abattoir centers: Site A , 1/6 ( 17% ) ; Site F , 2/4 ( 50% ) ; and Site G , 5/10 ( 50% ) ( Site Map , Figure 2 ) . Related to the analysis of characteristics of dogs and the abattoir location , ( Table 3 ) , in both univariate and multivariate logistic regression analysis the only factor with a positive association with infection was the abattoir location . Dogs from abattoirs close to the river were 36 times more likely to be infected than those from abattoir centers slaughtering animals inside a home ( OR = 36; 95%CI: 1 . 37–934 . 80; p<0 . 05 ) . Coproparasitoscopy was performed in 25 fecal samples including 21 that were evaluated by coproELISA: 3 dogs ( 12% ) presented Taenia sp . Eggs . From these , one was not evaluated by coproELISA , one was ELISA negative , and one was ELISA positive . Additionally we found Toxocara sp . in 16 samples ( 64% ) , followed by Ancylostoma in 7 ( 28% ) , Isoospora in 7 ( 28% ) and Dipilidium sp . in only 3 ( 12% ) of the samples . In 6 out of the 8 studied abbattoirs , family members accepted to be evaluated for hydatid infection . From 39 family members in these abattoir centers , 7 were not evaluated ( mostly because they were not present at the days of evaluation ) . Therefore , we analyzed data from 32/39 subjects . Their median age was 24 . 5 years ( range: 3–76 ) , and 16 of them ( 50% ) were male . Ultrasound evaluation found images compatible with CE in 3/32 ( 9 . 3%; 95% CI: 2–25; two CE1 cases and 1 CE4 case ) ( Figure 3 ) . Chest X–rays were performed in 18/32 subjects , and only one ( also positive on liver US ) , had a image compatible with a complicated lung cyst ( Figure 3 ) . Finally , serum EITB was performed in 23/32 , and only one ( the one positive to both liver US and chest X-rays ) was seropositive . Therefore the prevalence of human CE among this population was 9 . 3% ( 95% CI: 2–25 ) . The three infected individuals were asymptomatic and none presented a history of residence in an endemic area . Two out of these three human cases belonged to abattoir centers where at least one dog was positive ( Site A and Site F ) ( Figure 2 ) .
This study found a high prevalence of canine echinococcosis by coproELISA ( 8/22 , 36% ) , and also of CHD ( 9 . 3% , 3/22 ) , demonstrating autochthonous transmission of E . granulosus in Lima , a large metropolis supposedly non-endemic [13] . These findings also confirm the risk of informal , unlicensed abattoirs for urban hydatid disease transmission [6] , [12] . Using interviews with the owners of abattoir dogs , we explored putatively associated risk factors reported by other studies such age , sex , and whether dogs were fed viscera [4] , [12] [22] . We found no association between these factors and the likelihood of a dog being infected . However , regarding feeding dogs with viscera , we could not directly observe owners' habits so as to verify the information provided during interviews . Additionally , we explored the effect of abattoir location and found that this was the only factor with a positive association with dogs being infected . A tentative explanation is that dogs in abattoirs slaughtering animals close to the river may have more access to infected viscera ( people who work in these abattoirs could be using the rivers to discard contaminated viscera ) . The association between inappropriately discarding viscera and an elevated risk of E . granulosus dog infection was previously reported in a study performed among stray dogs that were captured close to abattoirs; authors of that work noted that the high prevalence observed ( 6% ) was associated with the dogs' behavior of scavenging rubbish close to abattoirs [12] . We used primarily the coproELISA results to define infected cases since it is a technique that has some technical and logistic advantages in relation to other techniques e . g . the way to collect sample ( in arecoline purge sample collection is laborious and risky ) ; also , coproELISA is faster to perform and requires fewer personnel than the cumbersome , furthermore despite coproELISA performance can be affected due to cross-reaction with antigens of Taenia sp . and other helminthes ( specificity range 88 to 96% ) [16] , [17] , [22] , [23] . , the reported sensitivity of coproELISA varies between 76 and 83% [1] , [22] , [23] . This variation related to the parasite load found in the dog's intestines , with a moderate to high load ( >100 parasites ) corresponding to a high test result . Additionally; sensitivity of coproPCR seems lower , in a previous study in experimentally infected dogs coproPCR detected 25 . 9% of E . granulosus infected dogs and produced no false positive reactions , while arecoline purgation was 100% specific with a sensitivity of only 64% [18] . Therefore we cannot exclude further cases of dog infection in the copro-ELISA negative animals . On the other hand , from the most conservative standpoint , a minimum of 4 dogs ( 4/22 , 18%; two PCR positive and two purge positive ) were infected . We could not calculate the sensitivity of the purge and PCR because of the lack of a gold standard test . Dogs located near abattoirs are , as any other dogs , usually treated as pets and kept in close contact with families and workers , exposing them to the risk of being infected and developing CHD . Informal , unlicensed abattoirs in urban areas of endemic countries should be a target for control interventions to prevent the appearance of autochthonous cases .
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Echinococcus granulosus infections are a major public health problem in livestock-raising regions around the world . This parasite is transmitted by dogs , and humans could be accidentally infected , developing cystic lesions in internal organs after several years of infection . The risk of infection has been widely described in Peruvian rural areas; nevertheless the extension of the problem in urban areas is basically unknown . Migration into Lima , an 8-million habitant's metropolis , creates peripheral areas where animals brought from endemic areas are slaughtered without veterinary supervision . In our study , we assess the number of infected dogs , which were living in eight informal , unlicensed abattoirs in a peripheral district of Lima , by evaluation of dog faeces using different techniques . We identified that 4 of 22 dogs were infected with E . granulosus worm . Later evaluation of the human population living in these abattoirs using abdominal ultrasound , chest X-rays and serology , found 3 of 32 subjects had echinococcal cysts in the liver , one of whom had also a cyst in lung and a positive serological test . This work demonstrates that autochthonous transmission of E . granulosus is present in Lima and that informal , unlicensed abattoirs may be sources of infection to neighbouring people in this urban environment .
|
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"Introduction",
"Materials",
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2012
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Human and Canine Echinococcosis Infection in Informal, Unlicensed Abattoirs in Lima, Peru
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Infectious diseases result in millions of deaths each year . Mechanisms of infection have been studied in detail for many pathogens . However , many questions are relatively unexplored . What are the properties of human proteins that interact with pathogens ? Do pathogens interact with certain functional classes of human proteins ? Which infection mechanisms and pathways are commonly triggered by multiple pathogens ? In this paper , to our knowledge , we provide the first study of the landscape of human proteins interacting with pathogens . We integrate human–pathogen protein–protein interactions ( PPIs ) for 190 pathogen strains from seven public databases . Nearly all of the 10 , 477 human-pathogen PPIs are for viral systems ( 98 . 3% ) , with the majority belonging to the human–HIV system ( 77 . 9% ) . We find that both viral and bacterial pathogens tend to interact with hubs ( proteins with many interacting partners ) and bottlenecks ( proteins that are central to many paths in the network ) in the human PPI network . We construct separate sets of human proteins interacting with bacterial pathogens , viral pathogens , and those interacting with multiple bacteria and with multiple viruses . Gene Ontology functions enriched in these sets reveal a number of processes , such as cell cycle regulation , nuclear transport , and immune response that participate in interactions with different pathogens . Our results provide the first global view of strategies used by pathogens to subvert human cellular processes and infect human cells . Supplementary data accompanying this paper is available at http://staff . vbi . vt . edu/dyermd/publications/dyer2008a . html .
Infectious diseases result in millions of deaths each year . Millions of dollars are spent annually to better understand how pathogens infect their hosts and to identify potential targets for therapeutics . An important aspect of any host-pathogen system is the mechanism by which a pathogen is able to invade a host cell . Within these complex systems , protein-protein interactions ( PPIs ) between surface proteins form the foundation of communication between a host and a pathogen and play a vital role in initiating infection [1] . PPI-mediated mechanisms of infection have been studied in detail for many pathogens [2–7] . However , many questions are relatively unexplored . What are the properties of human proteins that interact with pathogens ? Do pathogens interact with certain functional classes of human proteins ? Which infection mechanisms and pathways are commonly triggered by multiple pathogens ? A significant hurdle to such global cross-pathogen comparisons has been the shortage of large-scale datasets of interactions between host and pathogen proteins . High-throughput experimental screens have been primarily used to identify intraspecies PPIs [8–16] . However , recent efforts to include host-pathogen PPIs in public databases have made it easier to acquire the data needed to address these important questions . In this paper , we integrate experimentally verified human-pathogen PPIs for 190 pathogen strains from seven public databases [17–23] . We partition the strains into 54 different pathogen groups , where each group is made up of taxonomically related strains . We analyze the intraspecies network of PPIs between the 1 , 233 unique human proteins spanned by the host-pathogen PPIs , and find that pathogens , both viral and bacterial , tend to interact with hubs ( proteins with many interacting partners ) and bottlenecks ( proteins that are central to many paths in the network ) in the human PPI network . We pay special attention to two networks of PPIs between human proteins: the proteins that interact with at least two viral pathogen groups ( see Figure 1 ) and the proteins that interact with at least two bacterial pathogen groups ( see Figure 2 , noting that the figure also contains human proteins targeted by only one bacterial pathogen group ) . We used the Cerebral plugin [24] for Cytoscape [25] to render these images . We compute the Gene Ontology ( GO ) [26] functions enriched in each of these two sets of human proteins . Such enriched functions highlight human pathways that may be involved in infection mechanisms that are common to multiple pathogens . Examples of such processes and components include cell cycle regulation , I-κB kinase/NF-κB cascade , and the nuclear membrane . These functions shed light on a number of features shared by different pathogens: interacting with human transcription factors and key proteins that control the cell cycle; transport of genetic material through the nuclear membrane ( in the case of viruses ) to subvert the host's transcriptional machinery; triggering an immune response via toll-like receptors; and activation of NF-κB signaling . We discuss in detail the importance of these and other enriched functions , as well as the proteins they annotate and the pathogens they interact with . Overall , these results provide the first global view of aspects of human cellular processes that are controlled by and respond to pathogens . Our results should be interpreted with caution since no single pathogen may target all the proteins and PPIs we analyze . In addition , data for bacterial pathogens are scarce . However , we suggest that piecing together targeted human proteins across multiple pathogens has the potential to provide insights into common molecular mechanisms of infection and proliferation used by different pathogens .
Researchers have argued that the degree distribution of PPI networks is scale-free and follows the power law , i . e . , the fraction of proteins in the network interacting with k other proteins is proportional to k−γ , for some γ greater than zero , typically between two and three [27 , 28] . One feature of such networks is that they are robust in the face of attacks on random nodes . For instance , the removal of random subsets of nodes increases the diameter of the network only gradually [29 , 30] . In this context , the diameter is defined as the average length of the shortest paths between all pairs of proteins . However , the selective removal of even a small number of nodes of high degree can dramatically change the topology of the network [29 , 30] . There is considerable debate on the origins of the scale-free property and whether this property is an artifact of experimental biases and errors [31–33] . Notwithstanding this debate , we reasoned that pathogens may have evolved to interact with human proteins that are hubs ( those involved in many interactions ) or bottlenecks ( those central to many pathways ) [34] to disrupt key proteins in complexes and pathways . ( See Methods for a precise definition of “bottleneck . ” ) Our results support this hypothesis . Figure 3A displays the cumulative log-log plot of the degree distribution of four sets of proteins in the human PPI network: ( i ) all proteins , ( ii ) “Viral” set , the subset of proteins interacting with at least one viral pathogen group , ( iii ) “Bacterial” set , the subset of proteins interacting with at least one bacterial pathogen group , and ( iv ) “Multiviral” set , the subset of proteins interacting with at least two viral pathogen groups . We did not include the “Multibacterial” set of human proteins interacting with two or more bacterial pathogen groups in this analysis since there are only 20 such proteins . These plots show that across almost the entire range of degrees , proteins interacting with viral and bacterial pathogen groups tend to have higher degrees than human proteins not interacting with pathogens . Further , proteins interacting with at least two viral pathogens have higher degrees than proteins interacting with one or more viral pathogens . The betweenness centrality results display the same trend ( see Figure 3B ) . Across the entire range of values , proteins interacting with viral and bacterial pathogens have higher betweenness centrality . These results suggest that pathogens may have evolved to interact with human hub and bottleneck proteins , perhaps because these proteins control critical processes in the host cell . We used Gene Set Enrichment Analysis ( GSEA ) [35] to test whether the gaps we observed in Figure 3 are statistically significant . GSEA is a method developed to assess the significance of the differential expression of a pre-defined gene set in two phenotypes of interest [35] . GSEA ranks all genes by a suitable measure of differential expression ( e . g . , the t-statistic ) and uses a modified Kolmogorov-Smirnov test to assess if the genes in the given set have surprisingly high or low ranks . Since distributions of the t-statistics of differentially expressed genes have been observed to follow a power-law distribution [36] , we reasoned that GSEA may be appropriate to test whether the human proteins interacting with pathogens have surprisingly high degree or betweenness centrality . Our GSEA results support the conclusions we draw from Figure 3 that pathogens preferentially interact with human protein hubs and bottlenecks: for each of the three sets of proteins plotted in Figure 3 , GSEA yields a p-value of at most 3 × 10−5 ( degree ) and 2 . 3 × 10−4 ( centrality ) . To alleviate the concern that the observed patterns may be artifacts of experimental biases or errors in the human PPI network , we repeated each of the analyses using two subsets of the human PPI network: a network composed of 13 , 324 PPIs detected only by high-throughput studies [14 , 15 , 37] and a network with 59 , 396 PPIs constructed using only manually curated interactions [20 , 23] . The top half of Table 1 summarizes these results . For all three networks , the viral set , the bacterial set , and the multiviral set are significant at the 0 . 05 level for both degree and centrality , with the exception of the multiviral set in the high-throughput network . Since 77 . 9% of the human-pathogen PPIs are for the human-HIV system , we repeated these analyses for each network after removing all human-HIV PPIs and obtained similar results ( see the bottom half of Table 1 ) . In Text S1 , we discuss three analyses that show that the consistency in the GSEA results for degree and for centrality are unlikely to result from any correlation that may exist between a protein's degree and its centrality ( Figure S1 and Table S1 accompany the discussion in Text S1 ) . We note that Tables S2 and S3 of the supplementary data contain detailed information on the GSEA results for the groups in Figure 3 and for individual pathogen groups . We computed over-represented GO terms in 58 sets of human proteins: the bacterial set , the viral set , the multibacterial set , the multiviral set , and the 54 sets of human proteins interacting with each of the 54 pathogen groups . Overall , we found 404 unique GO terms enriched in these sets . A complete list of enriched GO terms with images of the sub-networks spanned by the human proteins annotated with each term is available on the supplementary website . We identified at least one enriched function in 21 pathogen groups . Analysis of these data identified 91 biclusters ( see Methods for details ) , each containing between two and seven pathogen groups and between two and 40 enriched GO functions . We focus on two of the biclusters below . The biclusters demonstrate that our analysis can group different enriched functions together even if the effects of the interactions on the host cell or the participating host proteins are different . Our first example is a bicluster spanning the three pathogen groups Adenovirus , HIV , and Papillomavirus and 23 GO functions . GO biological processes in the bicluster include “cell cycle process” and “regulation of cellular process . ” GO cellular components in the bicluster include “membrane-enclosed lumen” and “pore complex . ” The membrane-enclosed lumen is the space within a sealed membrane or between two sealed membranes . Proteins annotated with these functions include KPNA2 , a karyopherin , the histone deacetylases HDAC1 and HDAC2 , and a number of Transcription Factors ( TFs ) . KPNA2 plays an important role in both the import and export of material through the nuclear membrane . Interactions with KPNA2 enable a virus to enter the nucleus and take over the host's transcriptional machinery [38–41] . HDACs play an important role in silencing gene expression by removing acetyl groups from histones , thus causing them to wrap more tightly around DNA and block the binding of TFs . The role played by pathogen-HDAC interactions varies among pathogen groups . In the case of Adenovirus , it has been suggested that the pathogen protein E1B interacts with HDAC1/SIN3 to produce an enzymatically active complex that may be capable of repressing the transcriptional activity of the human TP53 protein in order to block apoptosis [42] . In contrast , the E7 Papillomavirus protein binds to the HDAC complex to promote cell growth , eventually leading to cervical cancer [43] . The second example is a bicluster containing a virus ( HIV ) and three bacteria ( Chlamydia , Neisseria , and Escherichia coli ) . This bicluster contains 11 GO functions including the biological processes “immune response , ” “response to stimulus , ” and “cytokine production . ” Although these four groups of pathogens interact with proteins belonging to the same pathways , the functions of the interactions are different . In the case of the bacteria , these functions annotate such proteins as toll-like receptors ( TLRs ) and interleukin receptor-associated kinases ( IRAKs ) , which are special classes of host proteins responsible for recognizing foreign material and activating an immune response . There are no reported interactions with these proteins and HIV , although some researchers suggest that the single-stranded RNA of HIV-1 may encode many TLR7/TLR8 ligands [44] . In contrast to the bacteria in the bicluster , HIV uses host proteins involved in immune response such as CD4 , CCR5 , and CXCR4 to gain entrance to the cell . HIV attaches to the host protein CD4 , a T cell glycoprotein , and subsequently to host chemokine receptors CCR5 and CXCR4 . These binding events cause conformational changes to host proteins that allow the membrane of the virus to fuse to the host cell membrane [1] . The biclustering analysis of the previous section suggests that specific sets of pathogen groups might trigger or target the same human pathways and processes . Encouraged by these data , we asked if there are infection pathways commonly targeted or triggered by at least two viral or bacterial pathogen groups . To answer this question , we constructed two networks of human proteins: one where every protein interacts with at least two viral pathogen groups and the other where every protein interacts with at least two bacterial pathogen groups . In each network , we included every PPI connecting two proteins in the network . Figures 1 and 2 display these networks . ( Note that Figure 2 also contains human proteins that interact with only one bacterial pathogen group . ) We computed the enriched GO functions in these two networks . We group and highlight some of the enriched functions and relevant sub-networks below . Throughout our discussion , we will refer to the localization of proteins in the four main regions of Figures 1 and 2: extracellular , the cell membrane , the cytoplasm , and the nucleus . For every GO function that we discuss , we mention its p-value and rank in the sorted list of all functions enriched in the corresponding network . Our analysis highlights a number of important mechanisms that viral pathogens use to manipulate the human cell: ( i ) control the host cell cycle program to ensure the transcription of viral genetic material; ( ii ) utilize human TFs to promote the transcription of viral genetic material; ( iii ) target key human proteins that regulate critical cellular processes such as apoptosis; and ( iv ) subvert host machinery for transporting material across the nuclear membrane . Although the number of human-bacteria PPIs gathered in this study is small ( only 174 ) , our methods identified an important subset of human proteins enriched for functions involved in immune response and interacting with multiple bacterial pathogen groups . Figure 6 displays a subset of the multibacterial set that is enriched in four GO functions: “immune system process” ( p-value 1 . 397 × 10−9 , rank 1/28 ) , “response to wounding” ( p-value 3 . 93 × 10−4 , rank 8/28 ) , “immune response” ( p-value 0 . 002 , rank 14/28 ) , and “I-κB kinase/NF-κB cascade” ( p-value 0 . 012 , rank 18/28 ) . The proteins contained in this image are located in the top-right corner of Figure 2 . These functions are tied together by the Toll-Like Receptors ( TLRs ) and the protein IRAK1 found in the network in Figure 6 . TLRs are a special class of cell-surface proteins that play a role in recognizing the presence of a pathogen and activating an immune response against the pathogen . The TLR/IRAK complex stimulates the activity of NF-κB [86–88] , a complex of proteins that act as a TF for activating the production of a set of proteins in response to stimuli such as stress , cytokines , and bacterial or viral antigens . The human TLRs and IRAK1 protein interact with the pathogen proteins FLIC ( E . coli ) , HSP60 ( Chlamydia ) , and PIB ( Neisseria ) [20] . FLIC is a flagellin protein . TLR4 and TLR5 contain a specific innate immune receptor for recognizing bacterial flagella [5 , 89] . HSP60 is a heat-shock protein that stimulates an immune response via TLR2 and TLR4 [90] . PIB is an outer membrane protein that is known to be recognized by TLR2 , TLR4 , and TLR9 [7] . Another human protein included in this network is HLA-DRA , which is part of the major histocompatibility complex ( MHC ) . The MHC plays an important role in the immune system . HLA-DRA belongs to the class II MHC; proteins in this class belong to the lysosomal compartment of the cell , which contains digestive enzymes that kill engulfed foreign particles such as viruses or bacteria . The two bacterial partners for HLA-DRA are Mycoplasma and Staphylococcus [91 , 92] . In the case of Mycoplasma , the interacting partner is the MAM superantigen , which is known to contribute to autoimmune disease by activating proinflammatory monokines such as interleukin 1β and the tumor necrosis factor α [93] . The networks in Figures 1 and 2 contain a number of other human proteins targeted by more than two pathogen groups . We discuss two of these proteins—STAT1 and EP300 . Viral pathogens also interact with other human proteins involved in immune response pathways that are not included in the network in Figure 6 . An example is the human protein STAT1 . When the cell recognizes the presence of foreign material , it activates an immune response as a defense mechanism to either remove the foreign material or cause the cell to undergo apoptosis . During this process , STAT1 is tyrosine- and serine-phosphorylated and forms a homodimer known as IFN-γ-activated factor ( GAF ) . GAF migrates to the nucleus where it binds to specific cis-elements to drive the cell to produce interferons , agents that inhibit viral replication within other cells of the body [94] . STAT1 interacts with Adenovirus , HIV , and Hepatitis [95–97] . Hepatitis POLG is part of the pathogen core complex that allows the virus to avert host antiviral response by binding to host STAT1 and inhibiting its activity [98] . Within the nucleus , we see pathogens target the human protein EP300 , a histone acetyltrans-ferase that regulates transcription via chromatin remodeling . EP300 interacts with Adenovirus , HIV , Papillomavirus , and Polyomavirus [99–102] . The pathogen Adenovirus targets human EP300 via E1A . E1A is an oncoprotein that stimulates cell growth and inhibits differentiation by binding to the EP300/CBP complex and deregulating cellular transcription programs [103] . Papillomavirus protein VE7 shares many functional and structural similarities with E1A and is an interacting partner of human EP300 . The disruption of normal growth conditions brought about by the E1A-EP300 interaction leads to the development of cervical cancer [104] . In the case of HIV , the viral TAT protein targets human EP300 . The resulting complex regulates TAT transactivating activity and may assist in the integration of viral genetic material into human DNA [105] . We have provided a general overview of the landscape of human proteins interacting with pathogens and demonstrated that pathogens preferentially interact with two classes of human proteins: hubs ( i . e . , proteins that interact with many other human proteins ) and bottlenecks ( i . e . , proteins that lie on many shortest paths ) in the human PPI network . We identified GO functions over-represented in human proteins interacting with pathogens . Biclustering analysis demonstrated that many sets of pathogen groups target the same processes in the human cell , even if they interact with different proteins . We constructed networks of PPIs between human proteins that interact with at least two viral pathogen groups and with at least two bacterial pathogen groups . Consideration of the GO functions enriched in these networks provided insights into numerous pathways targeted or triggered by multiple pathogens: control and deregulation of the cell cycle; import of pathogen proteins into the nucleus in an attempt to subvert the host's DNA replication and transcription machinery; manipulation of host cellular programs such as apoptosis; immune response and activation of NF-κB pathways via the TLR/IRAK complex . A striking aspect of this network is that human proteins that mediate pathogen effects are often proteins in cancer pathways ( e . g . , RB1 , TP53 , and STAT1 ) . We note that only some of the pathogens targeting such proteins are known to cause cancer themselves ( e . g . , Herpesvirus and Papillomavirus ) . In fact , a number of parallels are becoming evident between infection and cancer; for instance , in the part that TLRs play in angiogenesis and their potential as targets for therapeutics [106 , 107] and the role that viruses may play in the development of inflammatory diseases and cancer [108] . Cell cycle regulators and many TFs have been extensively studied in the context of mediating tumor formation . Our observation that they are also communication vehicles for pathogens suggests that the link between pathogen infection and cancer may be worthy of further experimental studies . An important outcome of such a comparative study is the identification of human proteins to target experimentally for developing therapeutics . We provide a file on the supplementary website that contains the degree , centrality , the number of pathogen interactors , and the most specific annotations in each of the three GO hierarchies for each human protein that interacts with at least one pathogen protein . We provide this data as a resource for researchers interested in prioritizing antiviral and antibacterial targets . We reiterate that our results should be interpreted with caution since no single pathogen may target all the proteins we analyze . As interactions between host and pathogen molecules are discovered on genome-wide scales [109] , computational analyses such as those presented in this paper may provide a more detailed understanding of the landscape of host pathways and processes that pathogens target .
We downloaded all datasets used in this study in August 2007 . We gathered 10 , 477 experimentally detected and manually curated protein-protein interactions ( PPIs ) between human and pathogen proteins and 75 , 457 experimentally verified PPIs between human proteins from primary literature [109] and seven databases: the Biomolecular Interaction Network Database [21] , the Database of Interacting Proteins [19] , the Human Protein Reference Database [23] , IntAct [18] , the Molecular INTeraction database [17] , the Munich Information Center for Protein Sequences [22] , and Reactome [20] . Table 2 contains statistics on the experimental methods that yielded these PPIs and the literature support for the PPIs . These interactions cover 190 different pathogen strains . Two pathogens—HIV and Hepatitis—account for 88 . 4% ( 9 , 268 ) of the human-pathogen PPIs . To mitigate this bias , we merged pathogen strains into 54 groups based on taxonomic similarity: each group contains pathogens belonging to the same genus , or , in the case of viruses , the same family . The 54 pathogen groups contain 35 viral , 17 bacterial , and two protozoan groups . We constructed lists of unique human proteins interacting with each group . Table 3 summarizes the number of interactions acquired for each pathogen group . For some analyses , we consider a human PPI network assembled from unbiased high-throughput experiments [14 , 15 , 37] and a network constructed from only manually curated human PPIs [20 , 23] . These networks contain 13 , 324 and 59 , 396 interactions , respectively . We obtained functional annotations from the Gene Ontology ( GO ) [26] . We represent the set of known interactions between human proteins as an undirected graph G ( V , E ) , where V is the set of nodes ( proteins ) and E is the set of edges ( interactions ) . Let M be the set of pathogen groups . We say that a pathogen group P interacts with a human protein s if s interacts with a protein in P . For a pathogen group P ∈ M , we define VP ⊆ V to be the set of human proteins that interact with P . Let T = ∪P∈M be the set of proteins that interact with at least one pathogen . Let TV ( respectively , TB ) be the set of human proteins that interact with at least one viral ( respectively , one bacterial ) group . Let T ( k ) V ⊆ TV ( respectively , T ( k ) B ⊆ TB ) be the set of human proteins that interact with at least k viral ( respectively , k bacterial ) pathogen groups; by definition , T ( 1 ) V ≡ TV and T ( 1 ) B ≡ TB . We now describe in detail the tests we use to analyze TB , TV , T ( 2 ) B , T ( 2 ) V , and the 54 VP sets . The degree of a protein in a graph is the number of interactions in which it participates , not including self-interactions . We plot distributions of the degrees of four sets of proteins in G: ( i ) V , the set of all proteins in G; ( ii ) TB , the set of all human proteins interacting with at least one bacterial pathogen group; ( iii ) TV , the set of all human proteins interacting with at least one viral pathogen group; and ( iv ) T ( 2 ) V , the set of human proteins interacting with at least two viral pathogen groups . In this analysis , we ignore T ( 2 ) B since it contains only 20 proteins . If the distributions of TB and TV are more biased towards high degree proteins than the distribution for V , then we hypothesize that viral and bacterial pathogens have evolved to interact with hub proteins in the human PPI network . The degree of a protein captures only its local connectivity . Centrality captures both global and local features of a protein's importance in a network . In this paper , we use the notion of a protein's betweenness centrality [110] . A protein with high betweenness centrality is characteristic of a bottleneck in an interaction network ( i . e . , there are many paths that pass through this protein ) [34] . We define the betweenness centrality bc ( v ) of a protein v as the fraction of shortest paths in G between all protein pairs ( u , w ) that pass through the protein v . Given u , v , w ∈ V , let σuw denote the number of shortest paths between proteins u and w . There may be multiple equally long paths between u and w that are shorter than any other path between u and w . Let σuw ( v ) denote the number of these that pass through v . Then the betweenness centrality of v is In our analysis , we divide bc ( v ) by the number of pairs of nodes in G , yielding a quantity between 0 and 1 . We use the algorithm devised by Brandes [111] to compute the betweenness centrality of all nodes in G . This algorithm runs in time proportional to the product of the number of nodes in G and the number of edges in G . As with the degree analysis , we plot distributions of the betweenness centrality for V , TB , TV , and T ( 2 ) V . If the distributions for TB , TV , and T ( 2 ) V are biased toward higher values of centrality than the distribution for V , we hypothesize that pathogens have evolved to interact with bottlenecks in the human PPI network . Let L be the ranked list of the proteins in V , where we rank the proteins either by degree or by betweenness centrality . Given L and a predefined set S of proteins of interest ( e . g . , those interacting with HIV ) , we use GSEA to determine whether the proteins contained in S are randomly distributed throughout L or concentrated at the top . In the ranked list L , let li be the value ( of degree or centrality ) at index i; 1 ≤ i ≤ |L| . We abuse notation and say that an index i is an element of S if the protein whose rank is i belongs to S . First , we compute m = Σi∈Lli , the sum of all the values in L . Next , for each index i in L , we compute two values: Thus , Phit ( S , i ) measures the weighted fraction of proteins with index at most i that are in S and Pmiss ( S , i ) measures the fraction of proteins with index at most i that are not in S . We handle multiple ranks with identical values by computing these two values only at the largest rank for each unique value in L . Finally , we define the enrichment score as the largest positive value of Phit ( S , i ) - Pmiss ( S , i ) , i . e . , A large positive value of es ( S , L ) indicates that the proteins in S have high degree or high betweenness centrality . Note that our modification of the original definition of the enrichment score [35] ensures that if S mainly contains proteins with low degree or betweenness centrality , then the score will be close to 0 , since Phit ( S , i ) − Pmiss ( S , i ) will be negative for most indices . We record the rank i that yields es ( S , L ) ; the column titled “#proteins contributing” in Table S1 of the supplementary data displays these numbers . To compute p-values for an observed enrichment scores , we generate a null distribution of scores by repeatedly selecting |S| random nodes in L and computing the score for each random subset of nodes . We repeat this process 1 , 000 , 000 times and estimate the p-value for s as the fraction of random sets whose score is at least as large as s . We obtain our results by testing each of 57 sets: TB , TV , T ( 2 ) V , and the sets VP corresponding to each of the 54 pathogen groups . We isolate functionally coherent subsets of human proteins among the sets TB , TV , T ( 2 ) B , T ( 2 ) V , and the sets VP corresponding to each of the 54 pathogen groups using a test for functional enrichment . Given the hierarchical structure of the Gene Ontology ( GO ) [26] , we account for dependencies between annotations by using the method proposed by Grossman et al . [112] . Let S be a set of proteins of interest ( e . g . , the set of proteins interacting with HIV ) . We aim to compute GO functions that annotate a surprisingly large number of proteins in S . To this end , for each function f in GO , we count sf , the number of proteins in S annotated with f and spa ( f ) , the number of proteins in S annotated by at least one parent of f . We also compute vf and vpa ( f ) , the number of proteins in V annotated by f and by at least one parent of f , respectively . With these four counts in hand , we use the hypergeometric distribution to compute the probability pf ( S , V ) of drawing sf or more proteins from a set of vf marked proteins when we select spa ( f ) proteins at random from a universe of vpa ( f ) proteins: We account for multiple hypothesis testing using the method of Benjamini and Hochberg [113] . We consider only functions enriched with a p-value of at most 0 . 05 . Note that different enriched functions may annotate identical sets of human proteins . In each such case , we group the functions and associate the most enriched function ( and its p-value ) with the group . To report enrichment ranks , we sort the groups in increasing order of p-value . Although not discussed in this paper we repeat this analysis using T ( rather than V ) as the universe of proteins . With T as the universe , we expect to find functions that distinguish between the pathogens . The results with T as universe are available on our supplementary website . We compute enriched functions in each of the 54 sets of human proteins interacting with each pathogen group . We construct a binary matrix whose rows are enriched functions and whose columns are pathogen groups . An entry is one in this matrix if and only if the function is enriched with a p-value of at most 0 . 05 in the pathogen . In this binary matrix , we define a bicluster to be a subset R of rows and a subset C of columns such that each row-column pair in R × C contains a one . We also require a bicluster to be closed , i . e . , each row not in R ( respectively , column not in C ) contains a zero in at least one column in C ( respectively , row in R ) . We use the Bimax algorithm to compute all closed biclusters in this binary matrix [114] .
Table 4 contains a list of all the proteins discussed in this paper and their corresponding UniProt ids and descriptions .
|
Many pathogens , such as viruses and bacteria , cause disease in humans . Pathogen infections result in illness and death for millions of people each year . Pathogens communicate with human cells through physical interactions with various human proteins on the surface of the cell and within the interior of the cell . These interactions allow the pathogen to enter the host cell , manipulate important cellular processes , multiply , and invade other cells . In this paper , we compare interactions between human and pathogen proteins from 190 different pathogens to provide important insights into strategies used by pathogens to infect human cells . We show that both viral and bacterial proteins interact with human proteins that themselves interact with many human proteins or with human proteins that lie on many communication channels between other human proteins . Pathogens may have evolved to interact with these human proteins since they may control critical human cellular process . We also demonstrate that many viruses share common infection strategies , e . g . , lengthening particular stages of the cell cycle , controlling programmed cell death , and interacting with the nuclear membrane to transfer viral genetic material into and out of the nucleus . Such studies may help us better understand the process of infection and identify better strategies to prevent or cure infection .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Methods",
"Supporting",
"Information"
] |
[
"viruses",
"infectious",
"diseases",
"computational",
"biology",
"homo",
"(human)",
"eubacteria"
] |
2008
|
The Landscape of Human Proteins Interacting with Viruses and Other Pathogens
|
Conflict between the sexes over reproductive interests can drive rapid evolution of reproductive traits and promote speciation . Here we show that inter-species mating between Caenorhabditis nematodes sterilizes maternal individuals . The principal effectors of male-induced harm are sperm cells , which induce sterility and shorten lifespan by displacing conspecific sperm , invading the ovary , and sometimes breaching the gonad to infiltrate other tissues . This sperm-mediated harm is pervasive across species , but idiosyncrasies in its magnitude implicate both independent histories of sexually antagonistic coevolution within species and differences in reproductive mode ( self-fertilizing hermaphrodites versus females ) in determining its severity . Consistent with this conclusion , in androdioecious species the hermaphrodites are more vulnerable , the males more benign , or both . Patterns of assortative mating and a low incidence of invasive sperm occurring with conspecific mating are indicative of ongoing intra-specific sexual conflict that results in inter-species reproductive incompatibility .
Rarely do reproductive interests of males and females perfectly align . Sexual selection can accelerate the evolution of the traits and molecules mediating reproductive encounters , and this can lead to sexual conflict [1] , [2] . Components of the reproductive system that mediate male-female interactions , such as reproductive tract morphology , sperm and egg traits , and molecular components of seminal fluid all diverge rapidly between many species [3] , [4] . The particularly forceful process of sexual antagonism drives co-evolutionary arms races between sex-limited traits that exact or counteract harmful , but self-serving , effects on the other sex [2] , [4] , [5] . Ongoing sexually antagonistic coevolution that operates within a species might generate mismatched interactions between gametes or other reproductive tract components when mating occurs between species . When such mismatches interfere with normal conspecific reproduction [6] , [7] , they have the potential to instigate or magnify reproductive isolation between species [8] , [9] . Selection for traits that prevent the deleterious consequences of inter-species mating for the parents or hybrid offspring may result in further trait evolution [10] . Though pre-mating reinforcement behaviours have received much attention and debate [10]–[12] , post-mating mechanisms of gametic isolation , such as conspecific sperm precedence , also can play key roles in pre-zygotic reproductive isolation [13] , [14] . The prevailing view of gametic isolation between species is that fertilization precedence of conspecific sperm can provide a potent reproductive barrier , mediated by cryptic female choice , sperm competition , or incompatibilities between female reproductive tracts and heterospecific ejaculates [15]–[18] . Conspecific sperm precedence occurs both in species with internal and external fertilization , governed by a broad variety of proximate mechanisms [14] , [19] , [20] . Alternatively , Drosophila provide examples of inter-species mating harm , for example , owing to an overly engorged “insemination reaction mass” that exacts a fitness cost on females [6] , [7] , and female Carabus beetles suffer ruptured reproductive tracts from physical damage upon inter-species matings [21] . Within species , male seminal proteins can manipulate female physiology in a manner sub-optimal for females but beneficial to males [22] . While coevolution between the sexes may obscure the traces of such sexual antagonism ( as for other forms of genetic conflict [23] ) , interactions between divergent populations and species can unmask the underlying conflicts by revealing mismatched male and female traits [8] . Caenorhabditis nematodes provide a powerful system to examine both sexual antagonism and its modulation by reproductive mode . Males , females , and hermaphrodites will mate readily and promiscuously in lab culture , and mechanical harm incurred from multiple mating reduces longevity and survival in C . elegans hermaphrodites [24] and C . remanei females [25] . Male-derived chemical cues also are thought to accelerate female and hermaphrodite aging [26] . Following copulation , C . elegans hermaphrodites can expel male ejaculates [27] , and males deposit copulatory plugs that inhibit re-mating [28] , [29] and induce larger brood sizes in their partners [30] . In response to experimentally elevated sperm competition , C . elegans evolve larger sperm [31] . Though anatomical evolution in Caenorhabditis is conservative , these intra-specific dynamics suggest there may be substantial inter-species divergence in cryptic reproductive traits . Evolutionary transitions in reproductive mode from highly outbreeding to highly self-fertilizing are expected to reduce intra- and inter-sexual conflict [32] , [33] . Three species of Caenorhabditis have independently evolved androdioecy ( hermaphrodites and males ) from dioecy ( females and males ) , such that hermaphrodites are capable of self-fertilization in addition to being fertilized by males [34] . These androdioecious species manifest a “selfing syndrome” analogous to plants that includes reduced sperm size and low mating vigor [35] , [36] . Hermaphrodites from such species with relaxed sexual selection might be particularly susceptible to adverse effects of mating to vigorous males from closely related species that have a recent history of strong sexual selection ( the “weak inbreeder , strong outbreeder” or WISO hypothesis [33] , [37] ) . Despite the generally limited understanding of Caenorhabditis ecology and inter-species interactions in their rotting fruit and vegetal habitats , some species are sympatric [34] , [38] , putting them at risk for inter-species encounters . Species readily mate with one another in the laboratory , and the animals' transparent bodies provide literal windows into postmating-prezygotic , and postzygotic , reproductive interactions and barriers [39]–[41] . Here we describe an unprecedented postmating-prezygotic reproductive barrier in Caenorhabditis nematodes , induced directly by sperm cells , that imposes potent fitness costs to females and hermaphrodites . Theory predicts species with selfing hermaphrodites to be more susceptible to inter-species harm and less capable of inducing harm [33] , [37] . Theory also predicts that rapid divergence in sexually selected traits will produce heterogeneity in harmful effects between species pairs and consequently may fail to yield phylogenetic signal in the magnitudes of effect [2] , [4] . In this counterpoint to mechanisms of conspecific sperm precedence , we affirm a potent role for sexual conflict as a pre-zygotic isolating barrier between species .
In no-choice mating arenas , Caenorhabditis copulate repeatedly ( Figure S1; Text S1 ) , and will readily mate with different species [41]–[43] . We first examined the impact of mating the self-fertile hermaphrodites of C . briggsae , C . elegans , and C . tropicalis [44] with males of other species ( Figure 1A–1C; Text S1 ) . Despite the presence of abundant self-sperm , offspring production was invariably compromised . By contrast , mating to conspecific males leads to increased reproductive output , because hermaphrodite sperm stores are supplemented by the male sperm ( Figure S2 ) [45] . The extremity of reduced reproductive output upon inter-species mating , however , depends in part on the identity of maternal and paternal partners . For example , C . briggsae and C . elegans hermaphrodites produced <5% and <30% of their normal brood , respectively , when mated with any of seven dioecious species of Caenorhabditis tested ( Figure 1A and 1B ) . C . tropicalis hermaphrodites , however , showed similarly striking sensitivity to males of C . brenneri , but were resistant or less sensitive to males of other species ( Figure 1C ) . In crosses between C . briggsae hermaphrodites and C . nigoni males , a single heterospecific mating event is sufficient to strongly depress reproductive output ( Figure 1D ) , and prolonged exposure accelerates hermaphrodite mortality beyond that seen in conspecific or reciprocal crosses ( Figure 1G ) . Increasing the abundance of conspecific sperm in hermaphrodites by mating them with conspecific males immediately before or after the heterospecific matings was insufficient to prevent or rescue sterilization of C . briggsae hermaphrodites by C . nigoni males ( Figure S2 ) . Males from androdioecious species of both C . elegans and C . briggsae were markedly less able to reduce the reproductive output of heterospecific hermaphrodites compared to the effect of dioecious males ( Figure 1E and 1F ) . However , there is no clear association between degree of sterilization and phylogenetic distance ( Figure S3A ) , although notably C . tropicalis is most sensitive to males of its closest tested relative , C . brenneri . The above observations demonstrate that ( i ) hermaphrodites of all three self-fertile species are susceptible to adverse effects of mating with males of at least some other species and ( ii ) males of all species are capable of adversely affecting the reproductive output of hermaphrodites of at least some species . Such disparities among species in gametic isolation are predicted to be a common outcome of sexual selection on sperm competition [37] . Consistent with intense intra-species sperm competition , multiple mating is readily observed in laboratory populations of outbreeding species ( Figure S1; Text S1 ) , while the rarity of males in self-fertile populations [46] , [47] suggests that multiple mating in these lineages is rare . Additionally , males from highly selfing species are less harmful to heterospecific mates , consistent with weak inbreeder , strong outbreeder ( WISO ) dynamics [33] , [37] . To assess the generality of heterospecific sterilization , we also examined male effects on females of dioecious species ( Figure 2 ) . Despite their similar sperm sizes [48] , [49] , heterospecific mating of dioecious males from C . remanei , C . nigoni , and C . brenneri reduced the reproductive output of females of C . remanei and C . nigoni ( Figure 2A and 2B ) . However , males from highly selfing species lacked the capacity to compromise the fecundity of heterospecific females ( Figure 2A and 2B ) . In Drosophila , different levels of sexual antagonism can lead to reduced female survivorship in inter-strain matings [50] . To explore whether heterospecific Caenorhabditis matings exert negative effects beyond reproductive output , we quantified maternal survival in the four cross combinations involving C . briggsae and its outbreeding sister species , C . nigoni . Mating with C . nigoni males significantly reduced the lifespan of C . briggsae hermaphrodites relative to conspecific mating ( Figure 1G ) , but did not adversely affect conspecific C . nigoni female survival in our assay ( Figure 2C ) , consistent with additional harmful effects of heterospecific mating beyond sterilization . Matings between another closely related selfer-outbreeder pair produced a different pattern , in which males from the selfing C . tropicalis exerted a much weaker effect on C . wallacei female longevity than did the other three cross combinations ( Figure S4A ) . Matings between dioecious species yielded heterogeneous impacts on maternal survival . C . nigoni and C . sp . 5 males produced no significant reduction in female survival beyond that seen for conspecific matings ( Figure S4B ) , whereas C . nigoni asymmetrically harmed C . remanei survival ( Figure S4C ) . Similar to sterilization , then , inter-species mating affects maternal survival with species-pair dependencies in both outbreeding and selfing species . This observation is consistent with distinct evolutionary resolutions of sexual conflicts in different lineages . Additionally , we see a compelling effect of reproductive mode: in selfing species , hermaphrodites are more vulnerable , the males more benign , or both ( as for C . briggsae ) . One possible mechanism of reduced female fitness is competitive displacement of conspecific sperm by heterospecific sperm . Hermaphrodite Caenorhabditis make relatively small sperm that compete poorly with even conspecific male sperm , and their conspecific males make sperm that are smaller than those of dioecious species' males [31] , [48] , [49] , [51] . Thus , the sterilization of hermaphrodites could result from the displacement of self-sperm by larger , yet ineffectual , heterospecific sperm [41] . To address this issue , we labeled C . elegans and C . nigoni males with vital dyes , mated them to phenotypically female C . elegans fog-2 animals , and observed the transferred sperm from each male in live animals . Indeed , within a few hours of mating , we observed strong displacement of the smaller C . elegans male sperm from the spermathecae by the larger C . nigoni sperm ( Figures 3A and S6C ) . However , sperm displacement does not explain the adverse effects of heterospecific mating on survivorship nor does it account for the seeming irreversibility of sterility induced by males upon their mating partners . C . briggsae hermaphrodites mated to C . nigoni males display striking germ line abnormalities , including disorganized proximal germ cells and ectopic , distally localized diakinesis-stage oocytes ( Figure 3C ) . In addition , embryos often formed distal to the oviduct ( Figure 3D ) , and , more rarely , we observed egg-laying defects ( Figures 3G and S5 ) . The proximal mass of disorganized germ cells is reminiscent of ovulation-defective mutant phenotypes in C . elegans [45] , [52] , [53] . Consistent with this , DNA staining of C . briggsae hermaphrodites revealed extensive endomitotic oocyte accumulation after one day of mating with C . nigoni males ( 54% , n = 78; Figure 3F ) , which increased further after a second day ( 91% , n = 70 ) . No endomitotic oocytes were observed among C . briggsae hermaphrodites mated to conspecific males ( n = 51; Figure 3B ) , indicating that C . nigoni males promote oocyte maturation defects in C . briggsae hermaphrodites . Males transfer both sperm and seminal fluid components to mates , and in principle , either might negatively affect their partner's reproduction and lifespan after heterospecific matings . To distinguish these possible mechanisms , we again applied a fluorescent vital dye to males , mated them to conspecific or heterospecific individuals , and observed transferred sperm in live animals . After six hours of mating to C . briggsae hermaphrodites , conspecific male sperm had localized to the spermathecae and uterus in all animals ( n = 52 ) , as expected ( Figure 4A; Movie S1 ) . In a striking contrast , we found that 90% of C . briggsae hermaphrodites mated heterospecifically to C . nigoni males had sperm present in ectopic locations in the distal and proximal gonad , whereas only 10% of animals had sperm properly localized exclusively to the spermathecae or uterus ( n = 188; Figures 4F and S6A; Movies S1 and S2 ) . This appears to begin when many sperm penetrate the distal spermathecal valve , which normally separates maturing oocytes from sperm . Further , 7% of the hermaphrodites showed invasion of sperm into the body cavity ( n = 159; Figure 4F; see Movie S1 ) . Sperm of C . nigoni males also commonly invaded the gonad past the spermatheca when mated to other species ( C . elegans and C . remanei; Figures S5 , S6A–S6C ) , but the effect was most extreme in C . briggsae hermaphrodites , consistent with its pronounced deficits in reproductive output . Just three hours after mating , more than 50% ( n = 72 ) of C . briggsae hermaphrodites had C . nigoni sperm in the distal gonad ( cf . 90% six hours post mating; Figure S6A and S6D ) , whereas ∼20% ( n = 39 ) of C . elegans and 2 . 9% ( n = 35 ) of C . tropicalis hermaphrodites were similarly afflicted ( Figure S6B ) . Ectopic sperm also were very rarely observed in C . tropicalis hermaphrodites mated heterospecifically to C . brenneri and C . remanei ( 0 . 9% , n = 111 and 0% , n = 18 , respectively; Figure S6B ) , consistent with the infrequency of sterilization observed for this species . The ability of C . nigoni sperm to overrun the spermatheca is greater than that of other species tested . C . remanei sperm were rarely found in ectopic locations in C . nigoni females ( 5% , n = 100; Figure S6A ) , and ectopic sperm originating from C . briggsae males were never observed ( n = 70; Figure 4A and 4E ) . Notably , the distinctly stronger sterilization of C . tropicalis by males of C . brenneri than C . nigoni occurs in the face of similar sperm localization patterns three hours post-mating ( Figures 1B and S6C ) , further supporting the idea that factors other than sperm displacement are important in heterospecific sterilization . Intriguingly , in conspecific matings with C . nigoni and C . remanei , 5%–8% of females had small numbers of sperm in ectopic gonad locations ( Figures 4C , 4D , and S6A ) . This low but detectable incidence of mislocalized sperm in conspecific matings is indicative of ongoing sperm-driven sexual conflict within dioecious species . Negative effects of seminal components contributed by somatic glands can potentially trigger harmful reactions in females and hermaphrodites [54]–[56] . We therefore tested for a direct role of sperm in causing harm to C . briggsae hermaphrodites by feminizing the germ line of C . nigoni males via fog-3 ( RNAi ) ( Figure 5A and 5B ) [57] . Treated males have a normal somatic testis , mate normally , and can deposit seminal components including the copulatory plug , but transfer no sperm . The reproductive output ( Figure 5C ) and survival ( Figure 5D ) of C . briggsae hermaphrodites mated to spermless C . nigoni fog-3 ( RNAi ) males is strikingly higher than that of animals mated to wild-type C . nigoni males . These observations implicate sperm infiltration into the gonad arms ( and potentially into the body cavity ) as the principal cause of male-induced permanent harm in heterospecific matings . The extreme fitness costs to inter-species mating might select for behaviours that promote assortative mating [10] , [12] , [14] , [19] . We first examined female avoidance of heterospecific males because Caenorhabditis males mate indiscriminately when given the opportunity , and mating pheromones produced by virgin females are strongly attractive to males across species [43] , [58]; tests for assortative mating in choice experiments have not been reported previously between Caenorhabditis species . We created assay populations with an equal mixture of females from each of two species and males from one of them ( reciprocally ) , and then quantified the incidence of avoidance behaviour and of mating success of each species , as evidenced by copulatory plugs placed onto the vulva . This assay design presumes that dioecious males mate indiscriminately [43] and thus that female and hermaphrodite behaviour will dominate mating outcomes ( Text S1 ) . Owing to their aggressive sperm , we first focused on copulatory responses to C . nigoni males . Overall , we observed that C . nigoni females exhibit a conspecific mating bias ( Figure 6A–6C ) . We introduced C . nigoni females and males to either C . briggsae hermaphrodites ( Figure 6A ) , C . elegans hermaphrodites ( Figure 6B ) , or C . remanei females ( Figure 6C ) . C . nigoni males were favoured by conspecific females over all heterospecific mating partners . When C . remanei and C . nigoni females ( Figure 6C ) were presented with C . remanei males , the females of both species showed no mating biases and were equally likely to mate with the males . This contrasts with the conspecific mating bias we observed when these females were presented with C . nigoni males ( Figure 6C ) . This discrepancy suggests stronger assortative mating bias in favour of conspecifics by C . nigoni females compared to C . remanei females . We also tested C . nigoni females in the presence of either C . brigggsae hermaphrodites and males ( Figure 6A ) or C . elegans hermaphrodites and males ( Figure 6B ) . Interestingly , C . nigoni females mated more readily with the heterospecific males than did the hermaphrodites to males of their own species ( Figure 6A and 6B ) . The insensitivity of C . nigoni female reproductive output to having mated with androdioecious males ( Figure 2A ) could partially contribute to a lack of mate avoidance towards this class of heterospecific males ( Figure 6A and 6B ) , although female sex pheromones [58] and hermaphrodite mating avoidance behaviours [43] also could contribute to this outcome . In addition to the mating outcomes , C . briggsae hermaphrodites were distinct in that they crawled away from the mating area when in the presence of C . nigoni males ( t = −2 . 449 , degree of freedom [df] = 44 . 672 , p = 0 . 018 ) . We interpret leaving the mating area as avoiding copulatory attempts by males .
Here we show that sperm transferred from matings between species of Caenorhabditis nematodes induce severe damage to females , compromising their reproduction and longevity . This phenomenon is the antithesis of the conspecific sperm precedence observed in diverse organisms , but still yields a form of gametic isolation owing to sperm displacement and ectopic sperm migration by heterospecific sperm . Caenorhabditis females commonly mate with multiple males ( Figure S1; Text S1 ) , and sperm competition selects for more aggressive sperm within species [31] . Attracted to oocyte-secreted chemical cues , sperm must repeatedly crawl to the spermatheca ( the site of fertilization ) as embryos push them into the uterus ( Figure 7 ) [45] , [59] . We propose that intra-specific sperm competition between males within the reproductive tracts of multiply mated females acts to select for aggressive sperm in an evolutionary intra-species arms race . Sperm migration into distal portions of the gonad would represent a byproduct of sperm competition with harmful consequences for females , that in turn leads to counter-selection for female resistance [4] , [60] , [61] . While co-evolution within a species largely keeps these interactions matched , male and female changes can fail to complement one another in an inter-species context . Although such divergence need not have precipitated the initial isolating events , they nevertheless contribute to extant reproductive isolation among species . It remains to be tested whether heterospecific sterilization by sperm could also be co-opted as a weapon in inter-species resource competition when multiple Caenorhabditis species inhabit the same resource patch . This model of sperm competition ( Figure 7D ) and sexual conflict predicts sexual antagonism as an ongoing selective pressure within species of Caenorhabditis . We find evidence supporting this idea in the low incidence of ectopic sperm migration observed in conspecific matings for C . remanei and C . nigoni ( Figure S6A ) . This model also could explain fertility patterns reported for crosses between parthenogenic and amphimictic Aphelenchus nematodes [62] , suggesting applicability of this mode of gametic isolation across diverse taxa . Interactions between species with overlapping geographic ranges , as occurs for some Caenorhabditis including C . briggsae with C . nigoni [34] and C . tropicalis with several species [38] , could select for behavioural or gametic strengthening of species boundaries or yield reproductive character displacement [10] , [63] , consistent with some patterns of assortative mating and sperm migration observed in our experiments ( Figures 6 , S6A , and S6B ) . However , further tests comparing sympatric and allopatric genotypes are needed [10] , [14] . This model further predicts the evolution of distinct cellular and molecular mechanisms mediating male sperm vigor and female resistance in different species , and relaxation of selection in some highly self-fertilizing hermaphrodite species [33] , [37] . Consistent with what we observe empirically , differences among species in the mechanisms of evolutionary response to intra-species sexual conflict will create phylogenetic heterogeneity in how strongly the inter-species mismatches manifest as harm to females and hermaphrodites . We addressed several other potential mechanisms that could contribute to the compromised maternal fecundity and longevity upon inter-species mating . ( i ) Trauma through copulation may occur in Caenorhabditis [24] , and repeated matings in Drosophila melanogaster can induce female sterility and mortality [54] . We can rule out this possibility because germline-feminized males with normal copulatory behaviours do not affect maternal reproductive output or longevity ( Figure 5C and 5D ) . We also exclude repeated matings as an explanation for reduced reproduction because a single inter-species mating event also severely diminishes hermaphrodite reproductive output ( Figure 1D ) . ( ii ) We can rule out insufficient sperm or oocytes as the cause of sterilization , as hermaphrodites cease laying embryos despite the abundance of oocytes and sperm in the reproductive tract ( Figure 3 ) [40] . ( iii ) The reduction in progeny production after heterospecific mating could result from superior fertilization capability of heterospecific sperm , leading to mortality of hybrid embryos , as post-zygotic reproductive isolation is nearly complete between most species studied here . However , we and others have observed insufficient numbers of dead eggs to account for the overall reduction in reproductive output [40]–[42] . ( iv ) Larger sperm from males of another species also could potentially outcompete and displace the conspecific sperm from the spermatheca , yielding fewer progeny [64] . Indeed , such displacement occurs initially following heterospecific matings to males of a species with larger sperm ( Figure 3A ) . However , hermaphrodite sperm for C . briggsae , C . elegans , and C . tropicalis all are similarly small [48] , [49] , and yet these species differ starkly in susceptibility to the negative effects of mating to heterospecific males ( Figure 1A–1C ) . Likewise , the disparity in sperm size of males from different dioecious species does not correlate with the extremity of reduced progeny production ( Figure S3 ) , and would not be expected to shorten lifespan . These observations reinforce the direct effects of sperm mislocalization in the maternal reproductive tract as the primary mechanism of male-induced permanent harm in inter-species matings . Although our experiments demonstrate the key role of sperm cells in heterospecific harm upon mating , non-sperm components also could contribute . For example , upon maturation , C . elegans sperm cells release by exocytosis the contents of their lysosome-like membranous organelles ( MOs ) [65] , and it is conceivable that molecules from this sperm cell-derived component of the seminal fluid could interact with female tissues . Indeed , the nematode major sperm proteins ( MSPs ) act as hormone-like signaling molecules to oocytes and gonad sheath cells , delivered in sperm-derived vesicles , in addition to MSP performing cytoskeletal functions [66] , [67] . Additionally , components of the seminal fluid that derive from cells of the male somatic gonad play important roles in reproduction [28] , [68] . Such seminal factors might compromise female tissue in some way that makes it more susceptible to adverse effects of heterospecific sperm , perhaps by inducing dilation of the gonadal sheath cells bordering the distal end of the spermatheca . In C . elegans , gst-4 and daf-2 mutants show defects in dilation of the spermathecal valve [69] and many proteins affect sheath contraction [59] , suggesting potential pathway targets for compounds transferred by males during mating . In C . elegans , oocyte-derived chemical cues guide sperm migration to the spermathecae [59] . The attractant comprises a complex mixture of F-series prostaglandins derived from poly-unsaturated fatty acid ( PUFA ) precursors , whose synthesis and modulation depends on a suite of fatty acid desaturases , glutathione S-transferases , cytochrome P450s , insulin-like signaling , and communication between the somatic gonad and germ cells [69]–[72] . In C . elegans mutants of these genes , conspecific sperm fail to localize efficiently to the spermathecae , instead occurring more readily in the uterus [69] , [70] . Heterospecific sperm migrate to the spermathecae efficiently in C . elegans and C . briggsae hermaphrodite reproductive tracts ( Figure S6A–S6D ) [41] , indicating conservation of the sperm attractants and their detection between species . The high density of aggressive heterospecific sperm in their spermathecae then sets the stage for invasion of sperm into ectopic locations . However , sperm localization patterns for C . tropicalis suggests that its oocytes might secrete a sperm cue that is only weakly attractive , or a chemical mixture that attracts sperm efficiently only for some species ( Figure S6B ) . Consequently , heterospecific sperm occur with lower density in the spermathecae , with correspondingly reduced likelihood of invasion into the distal gonad ( Figure S6B ) . This hypothesis could underlie the limited adverse effects of heterospecific mating on C . tropicalis hermaphrodites . It might even implicate the weak sperm attractants as an evolutionary response through gametic reinforcement [20] if negative effects of inter-species mating in sympatry occurred in C . tropicalis' past [38] . Finally , it is conceivable that differences among species in sperm attraction to distinct prostaglandins , or other compounds , coupled with secretion of them by more distally developing oocytes could encourage ectopic sperm migration . The mechanism by which sperm migrate ectopically past the spermathecal boundary remains a key unsolved problem . Moreover , the breaching of the ovary basement membrane and migration of sperm into the body cavity through amoeboid movement , bearing a striking resemblance to features of metastasis in cancer [73]–[75] , motivates further investigation of the molecular basis of tissue integrity and resistance to cellular invasion [76] .
Animals were maintained according to standard C . elegans procedures [77] , with the exception of increased agar concentration in NGM plates to 2 . 2% in order to discourage animals from burrowing underneath the surface of the plate . Cultures were maintained at 20°C and 25°C . See Text S1 for strains of each species used for experiments: C . afra ( sp . 7 ) , C . brenneri , C . briggsae , C . elegans , C . latens ( sp . 23 ) , C . nigoni ( sp . 9 ) , C . portoensis ( sp . 6 ) , C . remanei , C . tropicalis ( sp . 11 ) , C . wallacei ( sp . 16 ) , C . sp . 5 [44] . Crosses consisted of placing one hermaphrodite at the fourth larval stage ( L4 , penultimate stage of development ) with six heterospecific males overnight ( 18–24 hours ) on a 35 mm diameter Petri dish with a 10 mm diameter bacteria spot ( E . coli OP50 ) . Hermaphrodites ( Figure 1A–1F ) that successfully mated ( presence of a copulatory plug ) were transferred daily and we measured reproductive output as the yield of viable adult progeny from two days of egg laying following the final mating event ( representing >90% of lifetime brood size ) . Control hermaphrodites were individuals allowed to produce self-progeny . For matings involving females ( Figure 2A and 2B ) , we first mated them to conspecific males overnight and the subsequent day we mated treatment females to heterospecific males . In all cases except one ( C . briggsae×C . nigoni ) , matings are incapable of yielding viable hybrid progeny ( few hybrids are produced by C . briggsae×C . nigoni [40] , [78] ) . Therefore , reproductive output measures the number of conspecific progeny of females ( or , equivalently , self-progeny of hermaphrodites ) . The single mating treatment ( Figure 1D ) consisted of placing ten young adult hermaphrodites ( C . briggsae ) with 40 young adult males ( C . nigoni ) on a 35 mm Petri dish with a 10 mm diameter bacteria spot . After an hour , mated hermaphrodites were isolated to individual 35 mm diameter Petri dishes , transferred daily , and allowed to lay eggs in order to measure progeny production . In situations when both female and hermaphrodites are used , they will be referred to as XX animals as they both have two X chromosomes . Seven L4 XX animals , depending on the species , were placed with ten heterospecific or conspecific males per plate and left overnight . The next day , XX animals were assayed for mortality by being touched on the head with an eyebrow hair glued to a toothpick . If the animal performed a backwards locomotive response to the touch , it was scored as alive . If it did not , it was scored as dead . This was performed every day for at least seven days . Every two days , XX animals and males were transferred to new plates in order to prevent the confusion of progeny with parents . Additionally , in these assays , XX animals were kept under continuous mating conditions: when males died or crawled off the plate , they were replaced with new males . XX animals that crawled off the plate were excluded from the lifespan measurements . The nuclei of animals were visualized using Hoechst 33258 staining . Seven XX animals were mated with ten heterospecific or conspecific males per plate for 1–3 days , and then XX animals were fixed in 100% methanol overnight at 4°C . The animals were then washed three times in M9 buffer and incubated in 1 µg/ml Hoechst in M9 buffer for 5 minutes , followed by mounting for fluorescent microscopy and imaging . Male sperm were fluorescently labeled in vivo with MitoTracker Red CMXRos ( Invitrogen ) [71] . Males were incubated in 1 mM dye for 2–3 hours , and then left on a plate to recover overnight . Subsequently , these males were mated with virgin young adult XX animals for 1–4 hours ( matings with C . elegans males were allowed to run overnight ) . Virginity was assured by isolating XX L4 animals from males before reaching adulthood . Mated XX animals were then mounted on 10% agarose pads [79] or 2% agarose pads and immobilized with 50 mM sodium azide for differential interference contrast ( DIC ) and fluorescence imaging . Automated time-lapse photography ( 1–10 frames per second ) was performed with the Open Lab software package and a Zeiss Axioskop 2 equipped with DIC and fluorescence microscopy . A 929 base pair fragment including coding sequence homologous to fog-3 was PCR amplified from C . nigoni genomic DNA using primers flanked with 5′ T7 promoters . The reaction was gel purified using the QIAquick kit ( Qiagen ) , and the resultant template was then used for in vitro transcription using the MAXIscript kit ( Ambion ) to make dsRNA . The dsRNA was recovered using phenol-chloroform extraction and isopropanol precipitation , and the dsRNA was then introduced into the animals via maternal microinjection . The male progeny of injected animals were scored for the feminization of germline ( Fog ) phenotype using DIC microscopy via standard methods [77] . The worms were mounted on 2% agarose pads and immobilized with 50 mM sodium azide . Only males with clearly defined oocytes and no observable sperm were used for sterilization and lethality experiments . Fog males were allowed to recover for 30 minutes on a plate in a drop of M9 buffer . These males were capable of performing the mating behaviour and of depositing copulatory plugs ( and presumably other seminal fluids ) . These males were then assayed for their ability to sterilize and prematurely kill C . briggsae hermaphrodites . These males were then used for experiments as described above . Control wild-type males were mounted , immobilized , and allowed to recover for the same amount of time in order to remove these as confounding factors . We focused our assortative mating assays on C . nigoni males , as their aggressive sperm results in sterility and increased mortality ( Figure 1 ) . We expect males to mate indiscriminately [41] , [43]; therefore , XX animal behaviours ( preference or avoidance ) should account for the majority of mating biases observed . Assortative mating assays consisted of placing ten virgin C . nigoni males with ten virgin conspecific and/or heterospecific mating partners on a 35 mm diameter Petri dish . The three treatments involved presenting males to ( i ) ten conspecific , ( ii ) ten heterospecific ( C . remanei , C . elegans , or C . briggsae ) , or ( iii ) a mixture of five conspecific and five heterospecific mating partners . See Text S1 for results of ( i ) conspecific and ( ii ) heterospecific treatment . Control assays consisted of males ( C . remanei , C . elegans , or C . briggsae ) following the same treatments as above with C . nigoni females as the heterospecific species . We recorded successful mating by the presence of a copulatory plug deposited by a male onto an XX animal's vulva . We also recorded whether any XX animals left the 3 mm diameter ( 5 µl ) bacterial spot mating area , which , we reasoned , was effective in avoiding copulation . We limited the mating period to 10 minutes to ensure males only mated once ( male∶female ratio >1 was used to more easily observe successful copulations with inefficient males of androdioecious species ) . This 10 minute mating period was determined by preliminary experiments with a male placed with multiple conspecific females . In order to visually distinguish the two female/hermaphrodite species from one another , strains with pharyngially expressed GFP ( C . briggsae PS9391 ) or RFP ( C . nigoni VX0092 ) markers were used , which we presume exerts no direct effect on mate choice . See Text S1 for observed mating frequencies . All statistical analyses were performed using IBM SPSS Statistics v . 20 , unless otherwise noted . We conducted non-parametric tests for measures of reproductive output , owing to non-normal distributions and heterogeneous variances . To assess the effect of heterospecific matings on reproductive output ( i . e . , extent of sterilization ) , we compared the control ( selfing for hermaphrodites and conspecific matings for females ) to each treatment ( heterospecific mating ) using Mann-Whitney U tests with Bonferroni correction for multiple testing . We used Kaplan-Meier survival analysis to test for an effect of mating on survival of females or hermaphrodites . The survival analyses were performed with the OASIS online application [80] and SPSS . In experiments that explored assortative mating with a mixed species treatment ( five conspecific and five heterospecific mating partners; Figure 6 ) , an index of mating bias was calculated as the difference between the number of mated C . nigoni females and the number of mated individuals of the other maternal species present in the arena , divided by the number of C . nigoni females present in the arena ( five ) . Positive values indicate a mating bias towards C . nigoni females over the female ( or hermaphrodite ) species that they were paired with , negative values indicate the reciprocal , and a value of zero indicates no mating bias ( a lack of preference or avoidance ) . Negative values were not observed in our experiments . We then tested for a significant difference from zero with two-tailed one sample t-tests .
|
The sexes have divergent reproductive interests , and conflict arising from this disparity can drive the rapid evolution of reproductive traits and promote speciation . Here we describe a unique reproductive barrier in Caenorhabditis nematodes that is induced by sperm . We found that mating between species can sterilize maternal worms and even cause premature death , and we were able to attribute this phenomenon directly to the sperm themselves . Sperm from other species can displace sperm from the same species and , in some cases , can invade inappropriate parts of the maternal reproductive system and even their non-reproductive tissues . We find that mating to males of another species harms females far more than does within-species mating . Overall , our observations are consistent with ongoing sexual conflict between the sexes within species , arising as a byproduct of sperm competition among the gametes of different males . Finally , patterns of assortative mating indicate that mating behaviours that reduce the likelihood of costly inter-species mating have evolved in this group of animals . These findings support an important role of sexual selection and gametic interactions contributing to reproductive boundaries between species , as predicted by evolutionary theory .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"physiological",
"processes",
"developmental",
"biology",
"reproductive",
"system",
"anatomy",
"fertilization",
"ecology",
"natural",
"selection",
"sexual",
"selection",
"sexual",
"conflict",
"speciation",
"physiology",
"biology",
"and",
"life",
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"reproduction",
"evolutionary",
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"evolutionary",
"processes",
"behavioral",
"ecology"
] |
2014
|
Intense Sperm-Mediated Sexual Conflict Promotes Reproductive Isolation in Caenorhabditis Nematodes
|
Leptospirosis is a bacterial zoonosis caused by pathogenic Leptospira for which rats are considered as the main reservoir . Disease incidence is higher in tropical countries , especially in insular ecosystems . Our objectives were to determine the current burden of leptospirosis in Seychelles , a country ranking first worldwide according to historical data , to establish epidemiological links between animal reservoirs and human disease , and to identify drivers of transmission . A total of 223 patients with acute febrile symptoms of unknown origin were enrolled in a 12-months prospective study and tested for leptospirosis through real-time PCR , IgM ELISA and MAT . In addition , 739 rats trapped throughout the main island were investigated for Leptospira renal carriage . All molecularly confirmed positive samples were further genotyped . A total of 51 patients fulfilled the biological criteria of acute leptospirosis , corresponding to an annual incidence of 54 . 6 ( 95% CI 40 . 7–71 . 8 ) per 100 , 000 inhabitants . Leptospira carriage in Rattus spp . was overall low ( 7 . 7% ) but dramatically higher in Rattus norvegicus ( 52 . 9% ) than in Rattus rattus ( 4 . 4% ) . Leptospira interrogans was the only detected species in both humans and rats , and was represented by three distinct Sequence Types ( STs ) . Two were novel STs identified in two thirds of acute human cases while noteworthily absent from rats . This study shows that human leptospirosis still represents a heavy disease burden in Seychelles . Genotype data suggests that rats are actually not the main reservoir for human disease . We highlight a rather limited efficacy of preventive measures so far implemented in Seychelles . This could result from ineffective control measures of excreting animal populations , possibly due to a misidentification of the main contaminating reservoir ( s ) . Altogether , presented data stimulate the exploration of alternative reservoir animal hosts .
Zoonoses are known to contribute to approximately 60% of human infectious diseases and represent 75% of emerging diseases [1] . Among them , leptospirosis is considered as one of the most prevalent bacterial zoonotic disease worldwide [2] , as well as a ( re ) emerging disease [3] . It is considered by the WHO as being amongst the world’s neglected tropical diseases with epidemic-prone potential causing significant public health impact [4 , 5] . Leptospirosis affects 1 . 03 million persons annually causing nearly 60 , 000 deaths [6] . This zoonosis is transmitted to humans and domestic animals through direct or indirect contact with infected urine excreted by reservoir/carrier hosts [7] . Leptospirosis prevalence is higher in tropical environments where conditions may be more conducive to Leptospira survival [8] . Prevalence is maximal in tropical islands for unknown reasons , although reduced species diversity typical of insular ecosystems may boost pathogen transmission [9 , 10] . In the South West Indian Ocean islands ( SWIO ) , human leptospirosis shows a contrasting epidemiology in terms of incidence , mortality and diversity of leptospires . In Reunion , a French administered island , the incidence of human leptospirosis is the lowest recorded in the region ( 8 . 2 cases per 100 , 000 ) and the disease is caused by two Leptospira species ( L . interrogans and , to a much lesser extent , L . borgpetersenii ) , with Icterohaemorrhagiae serogroup being overwhelmingly dominant [11] . The higher incidence ( 74 . 5 cases per 100 , 000 ) in Mayotte [12] , also administered by France and sharing a common health surveillance system with Reunion island , is compounded by a much higher diversity of bacterial species ( L . interrogans , L . borgpetersenii , L . kirschneri and L . mayottensis ) and serogroups [13 , 14] . Noteworthily in Mayotte , Icterohaemorrhagiae serogroup was not diagnosed through Microscopic Agglutination Test ( MAT ) since the implementation of active surveillance in 2008 [15] . In the Union of the Comoros , no human leptospirosis has been reported recently , but according to a recent study , the serological profile of Leptospira infecting humans is likely similar to that encountered in the neighboring Mayotte [16] , the fourth island of the Comorian archipelago . In Madagascar , a considerable diversity of pathogenic Leptospira has been detected in bats and terrestrial small mammals [17–19] , despite limited reports of human cases [20 , 21] . The Republic of Seychelles is an archipelago consisting of 155 granitic or coralline islands located between 4 and 10 degrees south of the equator and lying between 480 km and 1 , 600 km east of the African continent in the SWIO . The climate of Seychelles is of the warm , humid tropical type , and divided into two main seasons: the Northwest Monsoon , period of higher rainfall from December to March , and the Southeast Monsoon from May to October , separated by two relatively short Inter-Monsoonal periods [22] . The mid-year population estimate of Seychelles as at August 2015 is 93 , 419 [23] , of which almost 90% live on Mahé island . In reference studies on humans in Seychelles conducted up to 25 years ago [24–27] , Seychelles has been reported as ranking first worldwide for leptospirosis incidence [8] , and several serogroups have been identified by Microscopic Agglutination Test ( MAT ) [25 , 27] . However , in the absence of published molecular data , the Leptospira species of medical concern in Seychelles remains unknown . Rats have been considered as the main animal reservoir of Leptospira in Seychelles and have been the target of active population control; eradication of invasive rodents , including black rats ( Rattus rattus ) and Norway rats ( Rattus norvegicus ) , have been a continuous activity of both the Public Health Authority and the Environment department in Seychelles [28] . However , the role of suspected animal reservoirs has never been properly investigated , and the only mention of Leptospira prevalence in rats is an anecdotal study where 24% of sampled rats ( n = 25 ) were reported to be MAT seropositive for Icterohaemmorhagiae serogroup [25] . Hence , from a public health perspective , there is still a significant lack of information regarding a zoonosis considered as the most important infectious disease in the country , based on local surveillance data collected over the past three to four decades . The context of insular countries , such as Seychelles , which inherently have limited geographical distribution and diversity of vectors/reservoirs , represents an opportune small-scale environmental setup for the investigation of disease ecology [29] . Such studies have a direct beneficial impact in providing concrete evidence-based data that may guide public health interventions implemented to control the transmission of zoonotic pathogens to humans . Hence , we carried out a comprehensive survey aiming at ( i ) determining the present incidence of human leptospirosis in Seychelles and compare it to the Yersin et al . ( 1998 ) study published almost twenty years ago , ( ii ) characterizing at the specific and infraspecific levels the Leptospira infecting humans and animal reservoirs in order to identify transmission chains , and ( iii ) identifying biotic and abiotic variables having a major impact on the epidemiology of the disease in Seychelles .
The Health Research and Ethics Committee of the Ministry of Health of Seychelles approved the study protocol for humans ( Research Proposal 1405 ) . Signed consent forms were obtained from participants enrolled in the study before questionnaires were administered and samples taken . Written informed consent was sought from parents of minors included in the study . The Seychelles Bureau of Standards gave the approval for the trapping and investigation of rats ( A0157 ) . All animal procedures carried out on rats were performed in accordance with the European Union legislation for the protection of animals used for scientific purposes ( Directive 2010/63/EU ) . The research protocol’s ethical terms were defined under accreditation 03387 ( FEDER POCT LeptOI 32913 research program ) and were approved by the CYROI Institutional Animal Care and Use Committee ( Comiteé d’Ethique du CYROI n° 114 , IACUC certified by the French Ministry of Higher Education and Research ) . Veterinarians of the Veterinary Services of the Seychelles Agricultural Agency , Ministry of Agriculture and Fisheries , carried out sampling of dogs and cats . A national leptospirosis surveillance program was launched in Seychelles in December 2014 . The study was designed as a prospective population-based survey conducted for one year from the 1st December 2014 to the 30th November 2015 on all acute febrile cases of unknown origin in Seychelles . Physicians were requested to refer all cases more than 13 years of age with acute fever of unknown origin and meeting the case definition ( Box 1 ) to the reference leptospirosis clinic established at the Seychelles Hospital . Patients below 13 years were not included , in view of the larger spectrum of non-specific acute fever cases affecting this age group and the low prevalence of leptospirosis among this young age class based on local surveillance data . Referred patients were enrolled in the study after providing informed consent , and were assessed for severity and admitted to hospital if required as per established criteria . Demographic data i . e . age , sex and residential address were collected on all enrolled patients , as well as the outcome of clinical intervention , and a questionnaire was administered . Biological samples were collected to conduct an array of standard laboratory tests: 3 to 5 ml of whole blood was collected in tubes with and without anti-coagulant . Rats were trapped throughout Mahé at 12 sampling sites representing a spread over seven regions ( Victoria , Victoria periphery , North , Centre , East , West and South ) ; habitats were defined by descriptions of the sampling sites ( S1 Table ) . Two trapping missions were conducted , one during the Southeast monsoonal season in June-July 2013 , and the other in the Northwest monsoonal season in February-March 2014 . All information including GPS coordinates and habitat types are provided as supplementary material ( S1 Table ) . Trapping was conducted following a standard protocol [30] using wire cage traps baited with roasted coconuts . At each sampling site , 40 to 80 traps were placed 15 meters apart in line . Trapped animals were collected the following morning and brought back to a laboratory facility of the Ministry of Health . Animals were euthanized by cervical dislocation , blood collected by cardiac puncture , and dissected organs ( kidney , liver , lung , spleen ) were stored immediately in liquid nitrogen . Grinded fragments of fresh kidney tissue were immediately inoculated to culture medium ( see below ) . Rattus species were identified using morphological characters [31] and animals identified as R . rattus were further sequenced at the cytochrome b ( cytb ) locus in order to avoid misdiagnosis within the R . rattus complex [32] . Dr . Jimmy Mélanie and Dr . Maria Tirant , respectively Principal Veterinary Officer and Veterinary Officer at the Seychelles Veterinary Section of the Seychelles Agricultural Agency in the Ministry of Environment and Agriculture , collected over a period of 4 months ( December 2015 to March 2016 ) kidneys from healthy dogs and cats that were to be euthanized as part of the routine practice , i . e . from owners who wished to dispose of their unwanted animals . These kidney samples were stored in 70% ethanol at –80°C until shipment using dry ice . Total nucleic acids were extracted from a pool of kidney , lung and spleen tissues collected from rats . Organs were dissected on ice , thin slices of approximately 20 mg of each tissue were pooled in 750 μL of DMEM ( PAN-Biotech GmbH , Aidenbach , Germany ) and grinded using a tissue lyser ( QIAGEN , Les Ulis , France ) and two 3 mm tungsten beads agitated at 25 Hz for 1 min . The resulting homogenate was centrifuged for 5 min at 10 , 000 rpm and 200 μL of the resulting supernatant was added to 200 μL of AVL buffer for subsequent extraction . In addition , 5 μL of bacteriophage MS2 ( final concentration of 5μM ) was added to one sample of every batch run and used as internal extraction control as previously described [33] . Extraction was performed on an EZ1 Advanced XL robot ( QIAGEN , Les Ulis , France ) using EZ1 virus extraction kit following the manufacturer’s instructions and using a final elution volume of 60 μL [18 , 19] . Nucleic acids were extracted from human serum samples either manually or using a QIAcube robot ( QIAGEN , Les Ulis , France ) as per manufacturer’s instructions using QIAGEN Viral minikit . A reverse transcription step was performed on 10 μL of the eluted total nucleic acids from human and animal origin using a GoScript reverse transcriptase ( RT ) kit ( Promega , Charbonnières-les-Bains , France ) , by adding 1 . 25 μL of random primer hexamers , incubating at 80°C for 3 min and then holding at 4°C . To this mix was then added 4 μL of Buffer 5X , 2 μL of MgCl2 ( 25 mM ) , 1 μL of dNTPs ( 10 mM ) , 1 μL of RT ( 200 U/mL ) , 0 . 05 μL of RNAse inhibitor , and 0 . 7 μL of RNAse free H2O . Reverse transcriptions were carried out using the following conditions: 25°C for 5 min , 42°C for 60 min , 70°C for 15 min and then held at 17°C . As dog and cat kidneys were preserved in 70% ethanol , samples were first rehydrated overnight in osmosis water before carrying out DNA extraction using DNeasy Blood and Tissue extraction kit ( QIAGEN ) following manufacturer’s instructions . Reverse transcriptions were also carried out on these samples following the conditions mentioned above . All produced cDNAs were stored at –80°C until PCR detection . The screening of cDNA using a probe-based real-time PCR ( Polymerase Chain Reaction ) for pathogenic Leptospira spp . was done adapting Smythe’s protocol to target the rrs ( 16S ) gene [34] . Amplifications were performed in 25 μL containing 12 . 5 μL of Absolute Blue real-time PCR Low Rox Mix ( Thermo Scientific , Waltham , MA , USA ) , 0 . 5 μL ( 10 μM ) ( initial stock concentrations shown ) of each primer , 0 . 4 μL ( 10 μM ) probe and 6 . 1 μL of nuclease free water . The PCR conditions were 95°C for 15 min , followed by 45 cycles at 94°C for 30 sec and 60°C for 1 min . For human samples detection , a cut-off criterion was set at Cycle threshold ( Ct ) <35 for positivity following Ahmed et al . [35] . Leptospira interrogans DNA serially diluted and leading to a Ct of 30 was used as a positive control for RT and end-point PCRs . A minimum of three distinct negative ( water ) controls were performed for each RT-PCR run and one single negative ( water ) control for each end-point PCR . PCR detection was first performed in triplicates and samples producing at least two positive reactions were considered positive , while samples producing a single positive reaction were submitted to an additional triplicated PCR . Moreover , samples with amplification at only one or two out of six real-time PCR runs were not considered positive unless a Leptospira sequence was achieved . Additionally , samples that had 35<Ct<40 for more than two replicates out of six were considered positive . Animal samples were submitted to a single real-time PCR with a cut off criterion set at Ct<45 . Genotyping of positive samples was carried out through Multi Locus Sequence Typing ( MLST ) scheme#3 ( http://pubmlst . org [36] ) . This scheme was chosen instead of two other available schemes as a number of investigations on other islands of the SWIO region have been carried out using this same MLST scheme . The amplification of adk , icdA , lipL32 , lipL41 , rrs2 and secY genes was performed using generic primers [36] . In case of PCR failure , samples were submitted to an alternative PCR using degenerated primers [18] and/or to an alternative amplification of rrs2 gene using previously published LA/LB primers [37] . All amplicons were sequenced on both strands ( GenoScreen , Lille , France ) and sequences were edited using Geneious 9 . 1 . 3 [38] . Original sequence types ( STs ) were deposited on the pubMLST database . DNA sequences were deposited on GenBank and accession numbers are listed on S2 Table . Kidneys from freshly dissected rats were aseptically sectioned and finely minced with a blade before inoculating three distinct media: ( i ) Ellinghausen-McCullough-Johnson-Harris ( EMJH ) liquid basal medium ( Difco , Detroit , MI , USA ) supplemented with Albumin Fatty Acid Supplement ( AFAS , purchased at OIE and National Collaborating Centre for Reference and Research on Leptospirosis Academic Medical Center , Department of Medical Microbiology , Amsterdam ) [39 , 40]; ( ii ) EMJH liquid basal medium supplemented with AFAS , rabbit serum and foetal calf serum ( 1% each ) ; and ( iii ) semisolid Fletcher medium ( Difco , Detroit , MI , USA ) supplemented with rabbit serum ( 8% ) . All media were supplemented with 5-fluorouracil ( 5-FU ) at a final concentration of 200 μg . mL-1 . Cultures were incubated at 28°C , visually checked for the presence of Leptospira using a dark field microscope once a week for four months , and positive cultures were further sub-cultured in fresh EMJH liquid basal medium supplemented with AFAS but deprived of 5-FU . A detailed protocol is available at http://dx . doi . org/10 . 17504/protocols . io . ifccbiw . All acute human sera were screened through an in-house IgM ELISA test using 96-well Immulon 1B polystyrene plates coated with Leptospira biflexa serogroup Patoc antigen ( already prepared at 11×108 leptospires/mL from cultures and stored at 4°C ) . The antigen preparation was used at a dilution of 1:30 to test all 223 human sera on ETI-Max 3000 ( DiaSorin , Saluggia , Italy ) at the GHSR-CHU ( Groupe Hospitalier Sud Réunion-Centre Hospitalier Universitaire ) hospital of Saint Pierre in Reunion Island . Absorbances were read at 450/620 nm . MAT was based on a panel of twenty Leptospira strains ( see S3 Table ) allowing detecting most serogroups that have been previously reported in humans [13 , 14 , 25 , 41] and animals [42] in the SWIO islands . All patients enrolled in the prospective study were tested by MAT using the initial blood sample ( acute phase ) to measure the prevalence of antibodies to Leptospira in the cohort ( reflecting either ongoing , recent or old infections ) . For 46 patients of the cohort , we could obtain a second blood sample at least four weeks after the onset of the first signs and symptoms ( convalescent phase ) and these 46 paired sera were tittered with MAT . Sera were tested at dilutions ranging from 1:50 to 1:3200 . A MAT titer of more than or equal to 1:100 ( cut off value of the test ) indicated a seropositive sample and the reactive serogroup as the one allowing agglutination at two titer orders more than the other coagglutinins . MAT serology was diagnostic of acute leptospirosis only if the MAT titer was ≥ 1:400 on the acute phase sample and/or demonstrated a four-fold increase in titer ( i . e . seroconversion ) on paired sera . Since Icterohaemorrhagiae was the serogroup previously reported as most prevalent in human acute cases [25] and as Patoc cross-reacts with most serogroups , we carried out MAT in two steps . First , a screen at 1:100 using Patoc and Icterohaemorrhagiae serogroups allowed highlighting putative positive samples . Second , all the samples reactive against Patoc and/or Icterohaemorrhagiae were serially diluted , up to a titer of 1:3200 and submitted to MAT using the full panel listed in S3 Table . Overall , a patient was considered positive for leptospirosis if one of the following conditions was fulfilled: ( i ) MAT titer of acute serum ≥1:400; ( ii ) evidence of seroconversion on paired sera attested by a fourfold increase of MAT titers; ( iii ) real-time PCR with Ct<35 for at least two replicates out of six; ( iv ) real-time PCR with 35<Ct<40 for at least 3 replicates out of six; ( v ) real-time PCR with Ct<40 on one or two attempts and simultaneously positive for IgM by ELISA; ( vi ) real-time PCR with 35<Ct<40 and with at least a sequence achieved on one of MLST loci . Samples that were positive for IgM ELISA only were considered negative due to the possibility of rheumatoid factors giving a false positivity [43] and also for the well-known long-term persistence of anti-Leptospira IgM antibodies months and years after acute infection [44 , 45] . Georeferencing and mapping of human cases and Leptospira positive Rattus spp . was carried out using QGIS v2 . 18 . 0 “Las Palmas” , [46] freely available at http://www . qgis . org/en/site/ . We investigated the effects of different variables on the infection status of rats: host “Species” ( R . norvegicus vs R . rattus ) and “Maturity” ( juvenile vs adult ) , “Seasons” ( wet vs dry ) , as well as environmentally variables such as “UrbanOrRural” ( representing the type of habitat , urban or rural ) , and “Region” ( Victoria , Victoria periphery , North , Centre , East , West and South ) . Variable “UrbanOrRural” was determined in accordance to descriptions recorded during sampling at each site ( refer S1 Table ) : “urban” habitats are built or heavily disturbed habitats while “rural” sites are residential , mixed-agricultural or natural habitats . Pairs of variables were compared using Fisher’s exact test for count data . Generalized linear models including “Species” , “Maturity” , “Seasons” , “UrbanOrRural” , and “Region” as explicative variables were performed using a binomial distribution and logit link function ( log-likelihood type 1 test ) . Analyses were conducted using “R” software [47] . A minimum-spanning tree ( MST ) was built using goeBURST Full MST algorithm ( PHYLOViZ 1 . 1 , 2014 ) , by concatenating six MLST gene markers ( adk , icdA , lipL32 , lipL41 , rrs2 and secY; fused in that order ) and comparing with previously published STs found in various hosts worldwide .
Overall , 225 patients out of 226 presenting with acute fever of unknown origin were enrolled in the study ( one patient refused to participate ) . Two patients for whom no sample could be obtained were excluded , leaving a total of 223 patients effectively investigated for acute leptospirosis . There were 23 females and 198 males ( gender information was missing for two patients ) with a mean age of 33 years old ( range 13 years– 60 years ) and a median of 34 years old . A total of 51 patients ( 49 males and 2 females ) were diagnosed with leptospirosis ( see below ) of whom 6 patients ( 5 males and 1 female ) died of their disease , leading to a case fatality rate for leptospirosis of 11 . 8% . There was a moderate agreement ( 44 . 5% ) between MAT and real-time PCR results: out of 46-paired sera ( representing 20 . 6% of all patients ) , 11 were MAT positive out of which six were also real-time PCR positive . Of the 35 paired samples that were MAT negative , 88 . 6% were also negative by real-time PCR . Agreement by Cohen’s Kappa ( Table 1 ) between confirmed positives as defined by the diagnostic criteria and the different performed tests were categorized as: good for PCR ( 87 . 8% ) and MAT ( 81 . 4% ) , and moderate for IgM by ELISA ( 45 . 7% ) . A flow chart of the tests conducted and the positive and negative results are shown in Fig 1 . Altogether , 51 patients fulfilled the diagnostic criteria of acute leptospirosis either by real-time PCR ( n = 30 ) ( as per criteria ( iii ) and ( iv ) ) IgM ELISA with PCR ( n = 9 ) ( as per criteria ( v ) ) and confirmed MAT ( n = 19 ) ( as per criteria ( i ) and ( ii ) ) , as well as the aforementioned sample for which a sequence was produced ( diagnostic criteria ( vi ) ) . Considering the current population of Seychelles [23] , incidence of human leptospirosis was evaluated to be 54 . 6 ( 95% CI 40 . 7–71 . 8 ) per 100 , 000 . Temporal analysis of the prevalence of cases over the one-year period from December 2014 to December 2015 shows a decreasing trend from the January to March period , corresponding to the humid Northwest monsoon , towards the usually dry season , where fewer cases were reported ( Fig 2 ) . There is some seasonality depicted by a high number of cases after a period of high rainfall , although not as sharp as that reported in other insular ecosystems of the region ( see Discussion ) . In order to identify the most prevalent serogroups , we carried out MAT screening of all patients enrolled in the study using the blood sample collected at inclusion ( acute phase serum samples ) . Forty-five acute phase sera out of 223 tested seropositive by MAT ( i . e . titer > 100 ) at inclusion . Among the seropositives , the serogroup Icterohaemorrhagiae was dominant ( n = 8 ) , followed by Autumnalis ( n = 5 ) , Hurstbridge ( n = 4 ) , Australis ( n = 4 ) , Djasiman ( n = 3 ) and Sejroe ( n = 1 ) . The serogroups Ballum and Canicola , previously reported in Seychelles [25] , were not detected in our sample while the previously identified serogroup Louisiana was not included in our panel . We did have two sera that were Patoc positive but did not agglutinate with any of the 20 reference strains of our panel . As a significantly large number ( n = 18 ) of sera in our sample set displayed cross-agglutination , we identified the infective serogroup as the one allowing agglutination at two titer orders more than the other coagglutinins . According to this criterion , the distribution of major cross-agglutinating serogroups , in decreasing order , were Icterohaemorrhagiae ( n = 18 ) , Autumnalis ( n = 8 ) and Hurstbridge ( n = 8 ) . A single sample displayed equal cross-agglutination to Pomona and Hardjobovis serogroups ( see S4 Table for tabulated MAT results ) . MLST sequences were produced for 24 out of the 32 real-time PCR positive patients , distributed for the six gene loci as follows: adk ( n = 21 ) , icdA ( n = 19 ) , lipL32 ( n = 22 ) , lipL41 ( n = 21 ) , rrs2 ( n = 22 ) and secY ( n = 20 ) . Leptospira sequences that were obtained from these 24 patients were all identified as Leptospira interrogans . Complete six-loci MLST was achieved for 18 patients leading to three different STs: one was identified in pubMLST database as ST02 , whereas two STs were not previously reported/registered in the database and thus considered as novel . These two STs were submitted to the pubMLST database and consequently assigned as ST142 and ST143 . Thus ST02 ( n = 4 ) , ST142 ( n = 11 ) and ST143 ( n = 3 ) represented 22 . 2% , 61 . 1% and 16 . 7% of positive human samples with full MLST , respectively . In order to use the whole sequence data , we arbitrarily assigned an ST to those samples for which only partial genotyping was achieved . For this , after establishing that all alleles or combination of alleles were compatible with ST02 , ST142 or ST143 , we included in the analysis those human samples for which the obtained sequences allowed unambiguous ST assignation . This allowed us to assign an ST to 21 out of the 24 fully or partially sequenced human samples . With this dataset , ST02 ( n = 7 ) , ST142 ( n = 11 ) and ST143 ( n = 3 ) were found in 33 . 3% , 52 . 4% and 14 . 3% of human samples , respectively . Altogether 739 rats were sampled and screened for Leptospira carriage , leading to an overall prevalence of 7 . 7% . Genotyping provided sequences for 34 out of the 57 positive animals ( see S1 Table ) distributed as follows: 24 sequences for adk gene , 18 sequences for icdA , 21 sequences for lipL32 , 20 sequences for lipL41 , 29 sequences for rrs2 and 27 sequences for secY . Additionally , 13 sequences were achieved for rrs2 gene using LA/LB primers [37] revealing sequences for two additional samples which were not successfully genotyped using MLST scheme#3 [36] . Full MLST was obtained from all 12 Leptospira positive cultures attempted from 74 rat fresh kidney tissues as well as from three uncultured tissue samples . Full genotyping of these 15 samples revealed the exclusive presence of L . interrogans ST02 . Following the same procedure as that used for human samples analyses , we arbitrarily assigned an ST to those samples for which only partial genotyping was achieved . The allelic profiles of these remaining samples were all compatible with ST02 , ST142 or ST143 but only nine allowed unambiguous ST assignation and were all indicative of ST02 . A minimum-spanning tree presented in Fig 3 shows alleles differences between all three STs in fully genotyped human and rat samples . Overall , Leptospira prevalence was significantly higher ( p-value < 0 . 0001 ) in R . norvegicus ( 52 . 9% , n = 51 ) than in R . rattus ( 4 . 4% , n = 688 ) . Several biotic and abiotic variables affected the prevalence of Leptospira renal carriage in rats , we describe hereafter the influence of each analysed variable . Infection prevalence appeared significantly affected by the sampling season . Prevalence of Leptospira carriage was 5 . 4% ( n = 464 ) during the dry season vs . 11 . 6% ( n = 275 ) during the wet season ( Fig 4 ) ( p-value = 0 . 003 ) . An analysis of urban versus rural habitats irrespective of rat species and season showed that there was also a significantly higher positivity rate in urban ( 18 . 7%; n = 230 ) than in rural ( 2 . 8%; n = 509 ) habitats ( p-value < 0 . 0001; see Fig 4 ) . When each rat species was analysed separately , the difference in infection prevalence was not significant for R . norvegicus ( 55 . 8% in urban vs . 37 . 5% in rural ) but remained significant for R . rattus ( 10 . 2% in urban vs . 2 . 2% in rural , p-value < 0 . 0001 ) . The higher prevalence in urban habitat was still significant when each season was analyzed independently: Leptospira carriage in rats was 13% ( n = 138 ) in urban and 2 . 2% ( n = 326 ) in rural habitats during the dry season ( p-value <0 . 0001 ) while during the humid season , infection reached 27% ( n = 92 ) and 3 . 8% ( n = 183 ) in urban and rural habitats ( p-value = 0 . 009 ) , respectively . When infection prevalence was compared for each season independently , it appeared that R . norvegicus was still significantly more infected than R . rattus during both wet ( 64% vs 6 . 4%; p-value < 0 . 0001 ) and dry seasons ( 42 . 3% vs 3 . 2%; p-value < 0 . 0001 ) . Leptospira carriage was also significantly higher in R . norvegicus than in R . rattus whether animals were trapped in urban ( 55 . 8% vs 10 . 2%; p-value < 0 . 0001 ) or rural habitats ( 37 . 5% vs 2 . 2%; p-value < 0 . 0001 ) . Overall , 4 . 5% ( n = 5 ) of juvenile rats ( n = 110 ) were carriers of Leptospira , representing 0 . 7% of the total rats sampled . Conversely 8 . 3% of adult rats ( n = 629 ) were carriers of Leptospira representing 7% of total rats sampled . An analysis of maturity status of Rattus species in relation to Leptospira carriage showed that adult R . norvegicus were more infected ( 56 . 3% , n = 48 ) than adult R . rattus ( 4 . 3% , n = 581; p-value < 0 . 0001 ) ; whereas there was no significant difference detected amongst juveniles , possibly due to the very low number of caught R . norvegicus juveniles ( n = 3 ) . Both adult ( p-value < 0 . 0001 ) and juvenile rats ( p-value = 0 . 005 ) were more infected in the urban than in the rural habitats , adult rats being more infected in the wet ( 11 . 7% , n = 248 ) than in the dry ( 6 . 0% , n = 381 ) season ( p-value = 0 . 017 ) . We tested the distribution of Rattus spp . in urban vs . rural habitats , showing that both rat species were unevenly distributed ( see Fig 4 ) , R . norvegicus colonizing preferentially urbanized habitats ( 84 . 3% of sampled rats , n = 51 ) while R . rattus was dominant in rural settings ( 72 . 8% of sampled rats , n = 688; p-value < 0 . 0001 ) . Hence , the observed significant distribution of infected rats may be indirectly related to the uneven spatial distribution of Rattus spp . We addressed this hypothesis by performing a generalized linear model ( glm ) including all variables ( i . e . “Species” , “Seasons” , “UrbanOrRural” , “Maturity” and “Region” ) acting alone or in interaction . Using this model , the effect of Leptospira carriage amongst rats showed a borderline effect of season ( Wet > Dry; p-value < 0 . 1 ) , whereas increasingly significant differences of Leptospira carriage were observed for habitat ( urban > rural; p-value < 0 . 05 ) and Rattus species ( R . norvegicus > R . rattus; p-value < 0 . 001 ) . Performing a glm with “Species” and “Region” as explicative variables highlighted significant Leptospira infection in R . norvegicus ( p < 0 . 0001 ) in the East region ( p < 0 . 005 ) of Mahé . No other effect was highlighted for “Maturity” and “Region” variables . Further analyses of the interactions of variables “Species” , “Seasons” , “UrbanOrRural” , “Region” and “Maturity” did not highlight any significant interaction between these variables when taken together . A stratified general linear model analysis based on host species ( i . e . by R . norvegicus and R . rattus separately ) against all the other variables did not reveal any significant interaction between variables either . Following the investigation of rats and humans , it appeared that rats were likely not the only reservoir involved in human leptospirosis , as two thirds of PCR confirmed human cases were infected with a L . interrogans ST that was virtually absent from our genotyped rats sample . In an attempt to explore other possible reservoirs , we collected kidney samples from 12 cats and 24 dogs . One cat ( C13; Ct = 40 ) and one dog ( D18; Ct = 39 ) were diagnosed as infected with Leptospira by real-time PCR . Only the dog sample allowed the production of sequences for adk , lipL32 and lipL41 . Although no complete MLST could be achieved , the allelic profile obtained using the three sequenced loci was consistent with the novel ST142 , representing the most common ST found in human leptospirosis cases .
From a biogeographic perspective , the present study not only completes previous studies carried out in Seychelles but also brings in original data showing that the South Western Indian Ocean islands actually shelter distinct epidemiological situations . Some oceanic islands such as Seychelles and Reunion Island [49] host a narrow diversity of cosmopolitan pathogenic Leptospira possibly of recent introduction , while other territories such as Mayotte [13 , 14] and Madagascar [17 , 18 , 19] are host to a much higher Leptospira diversity , including endemic lineages of medical importance [50] . Altogether , the presented data further confirms that insular ecosystems facilitate the exploration of infectious diseases , as these environmental settings are home to peculiar species assemblages that are in turn involved in unique transmission pathways . This study has completed previously sparse information regarding human leptospirosis in Seychelles , which can still be considered as one of the countries with highest incidence worldwide . Presented results may guide the public health intervention strategies in the prevention of human leptospirosis and the control of animal reservoirs in Seychelles . The patterns of environmental exposure revealed herein support rat control efforts targeting the urban areas of Seychelles as they are expected to have a significant impact in reducing the risk of leptospirosis transmission and hence reducing the overall incidence in humans . However , genotyping of Leptospira from animals and human acute cases reveals that rats are potentially involved in less than a third of human infections . The insignificant change in mortality caused by leptospirosis together with a persistent high incidence of the disease in humans , highlights undetectable improvement in management of acute cases in humans worsened by a limited efficiency of preventive measures . This may result from insufficient rodent control measures or , as suggested by our study , from a misidentification of the main reservoir ( s ) still to be identified and controlled .
|
Leptospirosis is an emerging environmental infectious disease caused by corkscrew shaped bacteria called Leptospira . Humans usually get infected during recreational or work-related outdoor activities through contact with urine excreted by animal reservoirs . As a zoonotic disease , leptospirosis is a good example of the One Health concept for it links humans , animals and ecosystems in a web of pathogen maintenance and transmission . This zoonosis is highly prevalent in the tropics and especially in tropical islands . Seychelles archipelago has been reported as the country with highest human incidence worldwide , although figures are based on dated studies and/or poorly specific tests . The presented investigation aimed at providing an updated information on human leptospirosis burden in Seychelles and exploring the transmission chains in their environmental aspects . Presented data confirms that the disease still heavily impacts the country . Genotyping of pathogenic Leptospira in human acute cases reveals that three distinct Sequence Types ( STs ) are involved in the disease . However , rats typically considered as the main reservoir in Seychelles , harbor only one of these STs , found only in a minority of human cases . Hence , it appears that rats are likely not the main reservoir of leptospirosis in Seychelles , which has important consequences in terms of preventive measures to be implemented for a better control of human leptospirosis .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
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"medicine",
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"disease",
"epidemiology",
"pathogens",
"tropical",
"diseases",
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"geographical",
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"vertebrates",
"seychelles",
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] |
2017
|
Human leptospirosis in Seychelles: A prospective study confirms the heavy burden of the disease but suggests that rats are not the main reservoir
|
Sustained or repeated exposure to sedating drugs , such as alcohol , triggers homeostatic adaptations in the brain that lead to the development of drug tolerance and dependence . These adaptations involve long-term changes in the transcription of drug-responsive genes as well as an epigenetic restructuring of chromosomal regions that is thought to signal and maintain the altered transcriptional state . Alcohol-induced epigenetic changes have been shown to be important in the long-term adaptation that leads to alcohol tolerance and dependence endophenotypes . A major constraint impeding progress is that alcohol produces a surfeit of changes in gene expression , most of which may not make any meaningful contribution to the ethanol response under study . Here we used a novel genomic epigenetic approach to find genes relevant for functional alcohol tolerance by exploiting the commonalities of two chemically distinct alcohols . In Drosophila melanogaster , ethanol and benzyl alcohol induce mutual cross-tolerance , indicating that they share a common mechanism for producing tolerance . We surveyed the genome-wide changes in histone acetylation that occur in response to these drugs . Each drug induces modifications in a large number of genes . The genes that respond similarly to either treatment , however , represent a subgroup enriched for genes important for the common tolerance response . Genes were functionally tested for behavioral tolerance to the sedative effects of ethanol and benzyl alcohol using mutant and inducible RNAi stocks . We identified a network of genes that are essential for the development of tolerance to sedation by alcohol .
Drug tolerance and dependence are two key components in the development of drug addiction . These drug responses are believed to arise from common homeostatic adaptations in the brain that oppose the effects of the drug [1] , [2] . Tolerance in particular is a reduction in drug sensitivity in response to prior drug exposure . While this adaptation ameliorates the effects of intoxication , it often outlives the intoxicated state to produce symptoms of withdrawal . Not only are these symptoms indicative of physiological dependence but also both tolerance and withdrawal appear to act in a feed-forward kindling-like manner to deepen the addicted state [3] . Therefore , understanding the mechanisms that underlie tolerance to alcohol is of central importance for understanding alcoholism . Modulation of gene expression has emerged as an important mechanism in the development of brain adaptations that produce drug-induced changes in behavior [4] . In particular , epigenetic histone modifications have become central to our understanding of drug abuse . They serve as a molecular memory of previous drug experiences that leads to altered responsivity during future drug exposures . Drug-induced changes in histone acetylation , for example , have been shown to be a major component in the long-term adaptation that leads to tolerance to alcohols in both Drosophila and mammals [5] , [6] . Therefore , a genomic survey of histone acetylation may be instrumental in identifying genes whose coordinate regulation mediates drug-induced adaptations . While high-throughput expression studies have proven successful for the discovery of differences in gene expression that define cell types , the same methods have been less successful in the identification of genes that underlie drug-induced changes in behavior [7] . We believe that the major constraint impeding progress is that genes important for a specific drug response are obscured by the overwhelming abundance of changes in gene expression observed in response to drug exposure . Most of these changes may not produce any meaningful contribution to the behavior under study . This limitation has led the field to focus largely on meta-analysis of genomic data , but even extensive meta-analysis can result in an unwieldy number of gene candidates [8] . To circumvent this problem , we used a novel genomics-based epigenetic approach to specifically identify genes that underlie functional tolerance to alcohol sedation in Drosophila . This approach is based on the observation that some chemically distinct alcohols produce mutual cross-tolerance in a mechanistically related manner . We reasoned that the genes that show related patterns of histone acetylation in response to both drugs are likely to be involved in producing the common behavioral response , while genes that are unimportant for the shared behavior are unlikely to display similar histone acetylation profiles in response to these chemically distinct drugs . In Drosophila , tolerance to ethanol and to the solvent anesthetic benzyl alcohol has been shown to develop after a single exposure to the either drug [9]–[11] . Furthermore , both drugs were shown to induce cross-tolerance to each other , indicating that they share a common mechanism for the development of tolerance [12] . Using genetic analysis , we have previously demonstrated that the mechanism of tolerance to these drugs involves a drug-induced upregulation of the BK-type Ca2+-activated K+ channel encoded by the slo gene . We showed that in the nervous system , the Drosophila slo gene responds to solvent intoxication with a programmed transcriptional response whose progression is mediated by a dynamic increase in histone H4 acetylation [5] , [13] . In turn , increased slo gene expression acts as a neural excitant that , upon subsequent exposure , counters the sedating effect of the drug to produce tolerance . However , after drug clearance , the persistent increase in channel activity reduces the animal's seizure threshold , giving rise to a withdrawal phenotype [14] , [15] . In order to identify new genes that are co-regulated with slo and , like slo , participate in the neuroadaptations behind the development of drug tolerance , we conducted genome-wide surveys of histone acetylation changes produced in response to either ethanol or benzyl alcohol . A subset of the genes with similar responses to both drugs was evaluated by mutant analysis to functionally test their role in producing alcohol tolerance . Here we report the identification of a highly correlated network of genes with direct roles in the modulation of neural activity that are essential for the development of tolerance to sedation by alcohol .
To measure histone acetylation across the fly genome , we performed genomic surveys of histone H4 acetylation ( H4Ac ) using the chromatin-immunoprecipitation assay ( ChIP–chip ) . Anti-H4Ac immunoprecipitated chromatin and the corresponding “input” chromatin were hybridized to NimbleGen two-color Drosophila DNA tiling arrays . A representative snapshot of the acetylation profile of a 30 Kb region of chromosome 3R ( 3R:1 , 406 , 00 . . 1 , 436 , 000 ) obtained from an untreated control sample is shown in Figure 1 . Genes in this region are shown in figure 1A while the respective acetylation profile across the same region is shown in figure 1B . Peaks demarcate highly acetylated regions . In most cases , acetylation peaks overlapped the transcriptional start site of annotated genes , sometimes covering the entire coding region of genes . The histone H4 acetylation “landscape” closely resembled the histone H4 acetylation patterns reported by the modENCODE project , even though we used adult heads instead of whole flies . The veracity of the ChIP–chip data was further confirmed by real-time PCR for 10 unique loci across the fly genome from three independent control chromatin samples ( Supporting Figure S1 ) . We chose to survey histone acetylation as a way to monitor gene activation rather than directly measuring changes in mRNA abundance because we wanted to have a strong focus of transcriptional regulation . Changes in mRNA abundance are often produced by the specific regulation of message stability . However , changes in histone acetylation are the direct products of transcription co-factors such as histone acetyl-transferases ( HATs ) or histone deacetylases ( HDACs ) that often associate with transcription factors to initiate or prevent transcription . Hence histone acetylation more directly reflects transcription activation state . To specifically identify drug-induced changes in H4Ac , we hybridized anti-H4Ac immunoprecipitated chromatin from the heads of drug-treated and mock-treated flies in a single two-color Drosophila DNA tiling array . With this approach , changes in the magnitude of H4 acetylation between the control and drug-treated animals generate difference peaks . Figures 1C and 1D show the difference peaks generated by benzyl alcohol or ethanol , respectively , for the same region of chromosome 3R . Statistically significant peaks in the difference plots , from two biological replicates , were identified by statistical comparison to a randomized sample using a FDR cutoff <0 . 05 ( Supporting Figure S2 ) . Genes associated with each peak were subsequently identified by proximity after mapping the peaks to the annotated Drosophila genome . While each drug produced significant changes in over 1500 gene loci , only a subset of 144 genes ( ∼10% ) were found in common between the two drugs ( Figure 1E ) . We hypothesized that this intersection will be highly enriched for genes important for functional tolerance , a shared response to both drugs . To reduce the complexity of the analysis , only genes that increase acetylation were examined in this study . A complete list of these genes , including full gene ontology information , is displayed in the accompanying supporting material ( Supporting Datasets S1 and S2 ) . An attractive hypothesis is that the genes identified here are co-regulated in an activity-dependent manner and are involved in common processes in the cell . One way to determine similarities between groups of genes is to perform gene annotation clustering analysis , which is based on molecular function or biological process . However , this analysis does not take into account correlated transcriptional activity between the genes . To overcome this limitation , we performed a gene-expression profile analysis to enhance the gene ontology analysis . To identify co-regulated groups within the 144 candidate genes , we first organized them into groups with similar patterns of expression . Gene-expression profiles produced by exposing Drosophila melanogaster to various chemicals or subjecting them to temperature shock were obtained from the “Transcriptional Profiling of Compound-based treatments of D . melanogaster using Illumina poly ( A ) + RNA-Seq” data set ( collected by the Brenton Graveley laboratory at the University of Connecticut Health Center to the modENCODE Drosophila Transcriptome project [16] ) . This data set contains gene-expression profiles from different fly populations treated with four different temperature-shock protocols , eight different heavy-metal diets , exposures to three different ethanol concentrations , three different caffeine-treatment protocols , and four different treatments with oxidative stress agents . Gene-expression profiles of the 144 candidates were subjected to unsupervised hierarchical clustering based on Pearson correlation coefficients [17] . We found that the genes segregated into seven distinct clusters . However , only four of these clusters were highly correlated ( r>0 . 65 ) . Figure 2 shows the 144 genes after gene-expression clustering and the members of each highly correlated gene cluster . The similar response to a variety of unrelated treatments suggests that these genes are co-regulated . Because the genes in each cluster share highly correlated gene-expression patterns , it is expected that genes within each cluster also share common functional roles . To determine if the genes in each Gene-Expression Cluster have related function , we gathered gene ontology information for each gene . We performed gene annotation clustering within the gene groups shown in Figure 2 using the Database for Annotation , Visualization and Integrated Discovery ( DAVID ) tool [18] . A high percentage of genes within each Gene-Expression Cluster have common molecular functions and/or participate in a common biological process . The top terms in each DAVID cluster ( Fisher Exact/EASE Score p-value<0 . 05 ) are listed in Table 1 . We found Gene-Expression Cluster #1 to be highly enriched for genes associated with transcription regulation , chromatin regulation , and small regulatory proteins ( phosphorylation and GTPase activity ) amongst others . Gene-Expression Cluster #2 is enriched in adenyl nucleotide binding and microtubule cytoskeleton genes . Gene-Expression Cluster #4 is highly enriched for genes associated with ion channel activity and synaptic membrane proteins . Gene-Expression Cluster #3 did not display significant enrichment for any gene ontology category . Full gene ontology annotation information for all clusters can be found in Supporting Dataset S2 . To validate the efficiency of this approach in identifying genes involved in the development of tolerance to sedation , we chose a sample of 19 genes to test by mutant and RNAi knockdown analysis . Gene-Expression Cluster #4 contained the slo gene , which has previously been shown to play a role in the production of ethanol tolerance . Based on the hypothesis that the Gene-Expression Clusters represent co-regulated genes and were therefore more likely to be involved in the same process , we focused our analysis on this cluster . In addition , Cluster #4 is highly enriched for genes associated with ion channel activity and synaptic membrane proteins and thus has the potential of modulating neural activity in response to drugs . Eleven candidates ( out of thirteen cluster members ) were selected from Gene-Expression Cluster #4 for mutant analysis . We also examined eight other candidates ( five from Gene-Expression Cluster #1 , one from Gene-Expression Cluster #2 , and two that did not fall within any of the highly correlated clusters ) . The genes sampled were not chosen randomly but were selected based on the ease with which genetic tools could be obtained to test their function , whether or not the identity of the encoded protein was known , whether the gene was expressed in the nervous system , and prior information concerning the function of the gene ( e . g . pum is a known activity-dependent regulator of neural activity [19] ) . This collection of genes consisted of four ion channel genes , three ion channel accessory genes , five transcription modulator genes , two protein kinase genes , one phosphatase gene , two cell adhesion genes , and two genes associated with cellular house-keeping ( Table 2 ) . To test the role of the candidate genes in alcohol tolerance , we used different gene knock-out/knockdown approaches . When possible , we used available loss-of-function null mutations , but in cases where the homozygous null mutations compromised viability of the stock , we used either hypomorphic alleles , null heterozygotes , or a transgene that carries a Gal4-inducible RNAi of the gene . Expression of the RNAi transgene was induced by crossing the RNAi stocks with either the ubiquitous αTub84B-Gal4 driver or , if this combination proved lethal , the more restricted pan-neural elav-Gal4 driver was used . These distinct methods perturb gene expression in different ways and amounts , thereby increasing the chances of obtaining a viable adult . For the nineteen candidate genes , we used loss-of-function null alleles in three cases ( slo4 , so1 , nAChRa-30DDAS1 ) , hypomorphic alleles in two cases ( pum13 , eag1 ) , and a heterozygous loss-of-function allele in one case ( nej3/FM7 ) . In addition , we used ubiquitously expressed RNAi alleles for six genes ( Act57B , Ack-like , Teh2 , Ptp99A , Ten-a , kn ) and neurally restricted RNAi alleles for another six ( brp , msn , trr , unc-104 , mam , Dscam ) . Only one gene candidate was lethal under both RNAi induction protocols and thus could not be behaviorally tested ( para ) . For the purpose of convenience , in the remainder of the manuscript the word mutant will refer to all of the allele types used . For each mutant stock , the animals were subjected to a two-day alcohol tolerance assay . In this assay , a population of female flies was divided into two groups . On the first day , one group ( experimental ) was sedated with either benzyl alcohol or ethanol vapor , whereas the second group was left untreated ( control ) . On the second day , both groups were sedated with the alcohol vapor and the time of recovery monitored . If the experimental group recovered faster than the control group , the strain was said to be capable of acquiring tolerance . The magnitude of tolerance ( i . e . the change in recovery time between experimental and control groups ) was determined for each strain and statistically compared to the appropriate wild-type controls . The magnitude of benzyl alcohol tolerance for each strain is plotted in Figure 3A . Mutations in eleven of the eighteen genes tested significantly blocked or reduced tolerance to benzyl alcohol , while for the remaining seven genes , the mutation did not significantly affect benzyl alcohol tolerance . To determine if these mutations disrupt ethanol tolerance , all alleles were subjected to an equivalent two-day ethanol tolerance assay . Of the eleven alleles that significantly disrupted benzyl alcohol tolerance , ten also disrupted ethanol tolerance , and the remaining eight did not affect ethanol tolerance ( Figure 3B ) . These results reflect a validation rate of approximately 55% success for alcohol tolerance . Most importantly within Cluster #4 , the success rate is even higher —80% behavioral validation . Moreover , only one of the genes tested affected tolerance to one of the drugs but not both ( the mutation in msn significantly reduced benzyl alcohol tolerance but failed to affect ethanol tolerance significantly ) . Together , these data confirm our central hypothesis , that similarities in the histone modification profiles between benzyl alcohol- and ethanol-sedated flies is a useful way to identify genes that are involved in the acquisition of functional tolerance . During mutant analysis , we confirmed that each iteration of the treatment protocol produced tolerance by performing the tolerance test with the Canton-S ( CS ) strain—a common wild-type control used in the community . For each of the RNAi knockdown experiments , we used the progeny of the cross between the respective Gal4-driver strain and the w1118 strain as genetic controls . The w1118 strain carries the same genetic background as all the RNAi lines tested and therefore represents an appropriate genetic control for the progeny of the induced lines . The RNAi transgenic inserts are carried in two different chromosomal sites . The insertion site of the RNAi transgenes obtained from the TRiP Transgenic RNAi Project are all inserted into an engineered attP2 site at position 3L:11 , 063 , 638 ( chromosome 3 ) , while the insertion site of the RNAi transgene in lines obtained from the Vienna Drosophila RNAi Center are inserted at position 2L:22 , 019 , 296 ( chromosome 2 ) . It is possible that insertions at these positions disrupt expression of a gene important for tolerance . This has been ruled out by the fact that not all of the RNAi inserts at these position affect tolerance . Two additional RNAi lines had inserts at unmapped locations; however , neither of these affected tolerance . Changes in histone acetylation are known to be associated with changes in transcriptional activity of genes . Because the genes validated here were first identified through alcohol-induced changes in histone acetylation , one would expect that the transcriptional activity of these genes would also be modulated by alcohol exposure . To examine if these genes display alcohol-induced changes in gene expression , we performed quantitative RT-PCR analysis of mRNA abundance for a set of the candidate genes in response to either ethanol or benzyl alcohol . The genes tested here include eag , brp , Teh2 , pum , nej , and para . As shown in Figure 4 , we confirmed that all candidate genes tested increase mRNA expression in response to both ethanol and benzyl alcohol . While there are a few individual instances in which the message upregulation does not reach statistical significance , the overall effect of alcohol treatment is statistically significant amongst the six genes ( P = 0 . 0013 , by Two-way ANOVA ) . For individual cases , the genes eag and para showed significant upregulation after both ethanol and benzyl alcohol . The genes brp and Teh2 show a significant upregulation only after ethanol treatment , while pum showed upregulation only after benzyl alcohol treatment . Previous studies have shown that slo is slightly induced by both benzyl alcohol and ethanol sedation [10] , [12] . The nej gene may be upregulated by both drugs , albeit the changes reported here did not reach statistical significance . However , this might be a consequence of assaying for changes in gene expression at only the 6 h post-sedation time point . We expect that a time course analysis following alcohol exposure will be required to authoritatively assess the transcriptional dynamics of each gene's response to alcohol sedation .
Because many histone modifications are a direct molecular consequence of transcription factor/co-factor activity , they represent a reliable indicator of alterations in gene activity [20] . Patterns of histone modifications can be used to identify genes that are coordinately regulated and to identify the position of enhancers that mediate gene induction [21] , [22] . The histone H4 acetylation changes produced by benzyl alcohol and ethanol are grossly different , even though these drugs generate mutual cross-tolerance that has overlapping molecular origins [12] . However , we reasoned that the intersection between the benzyl alcohol pattern and the ethanol would be enriched for genes that underlie common adaptive tolerance response . Because , alcohol tolerance and dependence are thought to arise from common homeostatic mechanisms [23] , we believe that some ( but not all ) of the genes identified here are also likely to have a role in the development of alcohol dependence . We identified a cohort of 144 genes whose histone H4 acetylation state increases with either drug . To further organize the candidates into functionally-related groups we performed cluster analysis based on the transcriptional responses to a variety of different treatments . Because the expression of each subgroup is highly correlated , the genes in a group are likely to be coordinately regulated . This analysis was combined with Gene Ontology Term Clustering to generate subgroups enriched for genes that share both common transcriptional responses and participate in common biological processes . Of the eighteen genes tested for tolerance , ten were validated by mutant analysis . Although , mutant analysis in flies is faster than in mammals , the tolerance assay is sufficiently time consuming to make an unbiased genetic screen unattractive . However , this analysis shows that prescreening with this method reduces the number of candidates to be tested to a manageable number . We expect that analysis of the remaining 125 genes will continue to identify new tolerance genes , although as we move deeper into the rank-ordered list the success rate may decline . The genes implicated in producing ethanol tolerance have striking interrelationships linked to specific cellular processes . All ten validated genes have previously been associated with the regulation of neural physiology , neural development or synaptic plasticity , implicating a role for coordinate regulation of neural activity as a means to achieve long-term adaptations to alcohol . While it is intuitively obvious that functional tolerance to these drugs would involve adaptations affecting neural activity , our screen implicates specific genes . Historically , Drosophila has been an excellent model system for describing the cascades of interacting genes [14] that underlie a specific response . However , the first step in this process is the identification of a collection of mutations that specifically affect the response being studied . We believe that we have described an excellent method for enriching for tolerance genes . One gene identified by our unbiased enrichment procedure is the slowpoke ( slo ) BK-type K+ channel gene . This represents a key validating result because this gene has previously been shown to be important for ethanol and benzyl alcohol tolerance in Drosophila [2] , [12] and has also been shown to play a central role in the development of alcohol tolerance in C . elegans and mammals [24] , [25] . The slo gene encodes the pore forming subunit of the BK-type Ca2+-activated K+ channel , a pre-synaptic channel directly involved in the regulation of action potential shape and neurotransmitter release [26]–[28] . In Drosophila , an alcohol-induced increase in slo expression has been shown to enhance neural capacity for repetitive firing , resulting in enhanced resistance to the sedative effects of alcohol ( tolerance ) , and increased susceptibility to alcohol withdrawal seizures—a symptom of alcohol dependence [14] , [15] . The mammalian homolog of slo is KCNMA1 [29] . A second gene validated as being required for functional tolerance is the eag K+ channel gene . This is intriguing because the eag gene genetically interacts with the slo gene . In Drosophila , eag has been proposed to contribute subunits to ion channels ostensibly considered to be products of other ion channel genes , including BK channels [30] , [31] . This claim is buttressed by the recent finding that , in C . elegans , the eag and slo homologs genetically interact [32] . On a related note , heterologous expression studies in mammalian cells show evidence that abused drugs such as ethanol and cocaine significantly block channels produced by the human eag homolog [33] , [34] . The mammalian homologs of eag are members of the ERG/KCNH family of delayed rectifier voltage gated K+ channel genes [35] . The pum and Teh2 genes encode proteins that interact with the para voltage-gated Na+ channel , which also appears in our list . The gene pumilio ( pum ) encodes an RNA-binding protein that regulates translation and mRNA stability by binding to the 3′-UTR of mRNAs [36]–[38] . In addition to roles in germline development and embryogenesis , pum has been directly linked to the activity dependent regulation of neuronal excitability , pre-synaptic morphology , and long-term memory [19] , [39] , [40] . In neurons , the Pum protein regulates the translation of para mRNA in an activity-dependent manner [41] and therefore is a prime candidate for modulation of ethanol response that contributes to tolerance . Furthermore , a previous mutant screen had identified pum among a collection of learning and memory mutants as being involved in the development of rapid tolerance to alcohol [42] . The Teh2 gene encodes a member of a structurally conserved family of ion channel β-subunits . Teh2 has been functionally shown to act as β-subunit of the Para voltage-gated Na+ channel whose presence alters channel activity [43] . We have not yet properly evaluated whether the mutations in para itself would interfere with tolerance . The temperature sensitive parats1 allele does not block tolerance at permissive temperatures [44] , [45] , but animals carrying this temperature-sensitive mutation are essentially normal at the permissive temperature and completely paralyzed at the restrictive temperature . Unfortunately , induction of para RNAi with both Gal4 drivers used in this study resulted in lethality ( para is an essential gene ) . Nevertheless , the identification of both Teh2 ( a Para voltage-gated Na+ channel auxiliary subunit ) and pum ( a translational repressor of para mRNA ) strongly implicate Para Na+ channels as playing an important role in alcohol tolerance . This hypothesis can eventually be tested by collecting and testing hypomorphic para alleles . Surprisingly , the Teh2 protein also shows strong topological homology to the human slo BK channel β subunit , and it has been postulated ( but not yet proven ) that it could also act as a β-subunit for slo BK channels in flies [43] . The expression profile of Teh2 is very similar to the expression profile of slo [46] , suggesting that both proteins are expressed in the same cells . In mammals , both NaV and BK channel β-subunits serve as key regulators of their respective α subunits [47] , [48] . Furthermore in mammals , modulation of BK channels by β-subunits plays a role in the regulation of the molecular and behavioral responses to alcohol [49] , [50] . Further work is required to determine whether Drosophila Teh2 and BK channels interact . The gene brp encodes a pre-synaptic active zone component with significant sequence homology to a neural isoform of the vertebrate ELKS/CAST/ERC family . The Brp protein has been shown to be a critical player in the assembly of active zones and the regulation of evoked neurotransmitter release at chemical synapses [51] . Because of its physical interaction with pre-synaptic Ca2+ channels , Brp is thought to play an important role in clustering Ca2+ channels and vesicles to allow efficient transmitter release and synaptic plasticity [52] , [53] . Although there are no previous reports of interactions with drugs of abuse , brp is a key candidate for the control of synaptic homeostasis at the pre-synaptic active zone [54] , [55] . A number of genes identified in this study encode proteins involved in synaptic growth and axon guidance . For instance , the gene Ptp99A , a transmembrane receptor protein tyrosine phosphatase [56] , is involved in motor neuron axon guidance [57] and defasciculation of motor neuron axon [58] . The gene Ten-a encodes a protein with unknown function . However mutant phenotypes indicate it is important in synaptic target recognition , attraction and growth [59]–[61] . Meanwhile , the gene knot/collier ( kn/col ) is a sequence-specific DNA binding transcription factor involved in dendrite morphogenesis [62] and plays roles in the innate immune response [63] . Interestingly , the innate immune response has recently been linked with alcohol phenotypes in both flies and mammals [64] , [65] . However , the mechanisms by which immune factors contribute to behavioral changes associated with alcohol exposure remain unclear . Based on the gene-expression similarities with the myriad of synaptic genes found here , the gene kn could link the neuroimmune response to alcohol-induced behavioral changes . In addition to synaptic and neurogenic factors , two other transcription modulators were identified . The gene nej , which encodes the Drosophila homolog of the mammalian transcriptional co-activator CREB-binding protein ( CBP ) [66] , was also found in this study . CBP is recruited to DNA sites by a number of transcription factors , including CREB and cFos , and acts as a histone acetyl-transferase ( HAT ) , and thus , it is associated with activation of gene expression [67]–[69] . While most studies of Drosophila CBP have focused on its role during development [69]–[71] , a significant contribution of CBP to the regulation of pre-synaptic function has also been reported [72] . Furthermore , several lines of evidence indicate that through its interactions with CREB , CBP plays a critical role in the activity-dependent regulation of neural excitability and synaptic plasticity [73] , [74] . In Drosophila , CREB has already been shown to be involved in producing tolerance through the regulation of slo transcription [13] , and in this role CREB probably employs CBP . In mammals , CBP has been shown to modulate both ethanol and cocaine associated behaviors through the acetylation of histones [6] , [75] , [76] . Finally , the gene mastermind ( mam ) is a transcription factor co-activator that has been involved in nervous system development [77]–[79] . In mammals , Mam has been shown to directly associate with the histone acetyl transferase CBP/p300 with which it mediates chromatin-specific transcription . Furthermore , Mam induces phosphorylation and localization of CBP/p300 proteins to nuclear foci [80] . We have now implicated both mam and nej ( which encodes CBP ) in mediating tolerance to alcohol and believe that this same transcriptional regulating complex may be a central regulator of other neuroadaptations to alcohol . Ion channels and synaptic proteins work together to fine-tune cell excitability and synaptic communication . It is expected that environmental insults that affect neural activity will precipitate compensatory mechanisms that homeostatically regulate neural excitability . This may involve the coordinate modulation of a network of genes . Elucidating the networks of proteins that work together in regulating neural adaptation to alcohol provides a powerful way to understand the integrative mechanisms that lead to addiction . Here we have come a step closer by identifying a small network of neural genes with the potential of regulating neural activity in the development of an addiction phenotype: tolerance . As a summary , Figure 5 shows a schematic representation of the genes identified here within a representative neuron . Possible regulatory interactions between many of these genes become immediately apparent . At the transcriptional level for instance , CBP ( encoded by the gene nej ) has a direct role in histone acetylation of chromosomal regions through its interactions with the Transcription factor CREB [67] . The CBP/CREB assembly has being extensively involved in the transcriptional regulation of gene targets and is particularly associated with the activity-dependent regulation of synaptic plasticity [72] , [73] . Furthermore , the transcription co-activator Mam , which associates with CBP , may serve as a modulator of the transcriptional response of target genes [80] . At the translational level , a direct interaction between the translational repressor Pum and the Para voltage-gated Na+ channel has also been reported in neurons [41] . Meanwhile at the protein level , many known interactions also exist . For example , the putative ion-channel β subunit Teh2 is known to modulate the activity the para voltage-gated Na+ channel , and has also been postulated to interact with the BK channel encoded by slo [43] . In turn , BK channels can modulate the activity of voltage-gated K+ channels such as Eag and vise-versa [30] , [81] , as well as the release of neurotransmitter through its interactions with voltage-gated Ca2+ channels . The active zone component Brp is also thought to play an important role in the regulation of transmitter release through its interactions with Ca2+ channels and the synaptic vesicles complex [52] , [53] . Altogether , coordinately increasing the expression of all of these proteins could have a strong effect on synaptic activity . A previous genome-wide gene-expression study in flies showed that two hours after ethanol exposure there are changes in the expression of a suite of genes encoding chemosensory receptors , detoxification enzymes , and metabolic enzymes [82] . Changes in the expression of these genes may represent sensory and metabolic adaptation to ethanol . However , only few of these genes were tested for a role in functional tolerance and examining each of the genes identified by mutant analysis would be a lengthy endeavor . Instead , the same group surveyed a large collection of wild-derived inbred lines of Drosophila for differences in gene expression that correlated with the magnitude of tolerance induced by a single ethanol exposure [83] . In this study , the authors linked a module ( cluster ) of synaptic genes to the capacity to generate tolerance . The module included Synapsin , comt ( a gene that encodes the NSF protein that mediates ATP-dependent synaptic vesicle release ) , the soluble NSF attachment protein gene Snap , and the SNAP receptor genes Snap25 and Syx16 ( amongst others ) . Single gene mutant analysis has identified several additional synaptic genes as being required for alcohol tolerance . These genes encode the pre-synaptic proteins Dynamin , Syntaxin 1A , and Synapsin [44] , [45] , [84]; the transmembrane cell adhesion integrin subunit βPS and αPS3 [85]; the postsynaptic GABAB receptor [86]; and the post-synaptic scaffolding protein Homer [87] . However , none of these genes appear in our list of genes that show similar benzyl alcohol and ethanol-induced histone acetylation patterns . While there is very little overlap of our candidate genes with those described above , there is a strong overlap in biological function . One possible reason for the lack of overlap is that the distinct methodologies used offer unique glimpses into the mechanism of tolerance . For instance , mRNA abundance can be altered by regulated control of mRNA stability and protein activity can also be regulated post transcriptionally–both of which would not be visible in a ChIP-chip assay . The ChIP-chip assay should visualize changes in chromatin preferentially associated with transcription . On the other hand , the inbred line approach might best work for identifying genes that alter the predisposition for alcohol tolerance but may not flag those genes that change expression in order to implement the tolerance response . We are searching for genes that mediate the plastic changes that implement tolerance . We believe that the coincidence between benzyl alcohol- and ethanol-induced histone acetylation acts as a filter that helps enrich for tolerance genes by removing genomic responses irrelevant to the shared behavioral effects of the drugs . Combining this with co-expression network analysis and gene ontology clustering results in a highly effective enrichment procedure . We are convinced that together with the genes identified in previous studies , the genes identified here will help complete the puzzle of a very complex response . There is strong conservation of gene regulatory networks between Drosophila and mammals and a remarkable evolutionary concordance in the genes that underlie drug tolerance [88] , [89] . The gene networks identified here will be immediately useful for the identification of genes and regulatory events important for tolerance , dependence , or addiction in mammals . Drosophila still has an important role to play in that it is an ideal model organism for deciphering how this large collection of genes interact to produce an ethanol-induced response . The effectiveness of the technique used here relies primarily on the combinatorial approach , as the genomic-level ChIP data was of relatively low power ( N = 2/group ) and yet the combined approach was remarkably successful . This approach may be useful for characterizing other types of complex polygenic responses .
Drosophila stocks were raised on standard cornmeal agar medium in a 12/12 h light/dark cycle . For all assays , newly eclosed flies were collected over a two-day interval and studied 3 to 5 days after collection . The wild-type stock Canton S ( CS ) ; the mutants stocks eag1 , nej3/FM7 , pum13 , so1 , nAcRα-30DDAS1; the RNAi lines brpJF01932 , paraJF01469 , unc-104HM05162 , KnJF02206 , Ten-aJF03375 , Ptp99AJF01858 , DscamJF03307 , mamJF02881; and the Gal4 drivers elav[C155]-Gal4;UAS-Dcr2 and tubP-Gal4; were all obtained from the Bloomington Drosophila Stock Center at Indiana University ( Bloomington , IN ) . The UAS-RNAi lines Act57BGD6854 , trrGD4501 , Teh2KK112449 , Ack-likeKK105138 , msnKK108948 and the isogenic host strain for the RNAi library w1118 , were obtained from the Vienna Drosophila RNAi Center ( VDRC ) [90] . For RNAi induction , each RNAi lines was crossed to the tubP-Gal4 line or the elav[C155]-Gal4;UAS-Dcr2 , and the progeny tested . The wild type stocks used for comparisons were CS for all the mutant lines , and the progeny of the cross between w1118 and the respective Gal4 driver line for the RNAi stocks . The slo4 mutant was obtained from the Atkinson Lab collection . Approximately 500 age-matched wild-type CS flies were collected for exposure to either ethanol , benzyl alcohol , or for use as the respective untreated controls . For benzyl alcohol , the insides of a 180 ml glass tube were coated with 500 ul of a 0 . 4% benzyl alcohol solution in acetone . The tube was continuously rotated for 30 minutes at room temperature to evaporate the acetone , leaving a thin coat of evenly distributed benzyl alcohol . For the untreated control , a similar acetone-only tube was prepared . Flies were placed in each tube and exposed until the benzyl alcohol group was completely sedated ( approximately 15 minutes ) [10] . Flies were then transferred to fresh-food bottles for recovery . For ethanol exposure , flies were placed in a perforated 500 ml plastic bottle chamber . Humidified air saturated with ethanol vapor was delivered to flies in the chamber using an ethanol vapor inebriator set to 15 ml air per minute . For the untreated control , ethanol free humidified air was delivered to the chamber . Flies were placed in each chamber and exposed until the ethanol group was completely sedated ( approximately 15 minutes ) [11] . Flies were then transferred to fresh-food bottles for recovery . Chromatin extraction and immunoprecipitation were performed as described previously by [5] . In brief , formaldehyde cross-linked chromatin was extracted from 500 fly heads of drug treated and control flies ( mix of males and females ) , 6 hours after treatment and fragmented by sonication to ∼500 bp length . Chromatin samples ( 2 ug ) were immunoprecipitated using a 1∶200 dilution of ChIP grade antibody against acetylated histone H4 at lysine 5 , 8 , 12 and 16 ( catalog # 06-866; EMD Millipore , Billerica , MA ) . A fraction ( 1/10 ) of the chromatin sample was left unprecipitated for use as input control . DNA from immunoprecipitated ( ChIP ) and input samples was washed , reversed cross-linked , and purified and subsequently amplified using the GenomePlex Complete Whole Genome Amplification Kit ( Sigma-Aldrich , St . Louis , MO ) following the manufacturer's protocol . Approximately 1 ug of amplified ChIP and input DNA from each sample was sent to NimbleGen ( Roche NimbleGen , Madison , WI ) for two-color hybridization to Drosophila ChIP-chip 2 . 1M Whole-Genome Tiling Arrays . Each array consisted of 2 . 1 million 50–75 mer probes , with a 55 bp median probe spacing that cover the entire Drosophila genome ( UCSC Drosophila genome build DM3 ) . For measurements of control baseline H4 acetylation profiles , control ChIP and input DNA samples were labeled with Cy3 and Cy5 fluorescent dye , respectively , and co-hybridized to the same microarray . ChIP acetylation signals were reported as normalized Log2 ChIP ( control ) /Input ( control ) ratios . For measurements of drug-induced changes in acetylation , the control and drug-treated ChIP DNA samples were labeled with Cy3 and Cy5 fluorescent dye , respectively , and co-hybridized to the same microarray . The difference in acetylation signals were reported as normalized log2 ChIP ( drug-treated ) /ChIP ( control ) ratios . Each ChIP-chip experiment was repeated two times from independent biological samples . For each experiment , raw signals of corresponding experimental replicates were normalized using the ‘vsn’ package for R [91] and signal ratios from replicates were averaged using R/Bioconductor ( www . R-project . org; www . bioconductor . org ) [92] , [93] according to an online protocol ( http://epigenesys . eu/images/stories/protocols/pdf/20111025114444_p43 . pdf ) . Only arrays with normally distributed log-transformed signals were used , and signal normalization between arrays was performed against matched samples . Signal ratio peaks with enrichment score above 50% and a false discovery rate ( FDR ) of <0 . 05 and mapped to the annotated Drosophila genome ( UCSC , build DM3 ) using NimbleGen SignalMap software following default parameters . Peaks were assigned to the nearest gene using a bidirectional distance cut off of 500 bp beyond the annotated gene region defined by the 5′-most transcriptional start site to the end of the 3′ UTR . This analysis produced approximately 1500 associated genes for each drug . Genes were rank ordered with respect to peak magnitude . The genes mapped to peaks produced by benzyl alcohol and ethanol treatment were compared for common entries using Microsoft Excel for Mac software ( Microsoft , Redmond , WA ) . The raw and processed data from the ChIP-chip data described in this manuscript have been deposited in the public functional genomics data repository from NCBI: Gene Expression Omnibus ( GEO ) . Data can be found on the GEO website ( http://www . ncbi . nlm . nih . gov/geo/ ) using accession number GSE48449 . All essential sample annotation and experimental design information including sample data relationships have been included in the repository according to the Minimum Information About a Microarray Experiment ( MIAME ) guidelines [94] . For all tolerance assays , 5 to 7 day old age-matched female offspring from each line tested were collected and sorted into replicate vials under light CO2 anesthesia . To test for benzyl alcohol tolerance , flies were divided into 2 equal groups: the control group and the experimental group . Each group consisted of three vials with 12 flies each . On the first day , flies from each vial of the experimental group were sedated using a custom build benzyl alcohol vapor chamber for 15 minute , while the control group was mock sedated [14] . After sedation , the animals were returned to food vials for 24 hours allowed to recover . On the second day , both groups were sedated in tandem using the same benzyl alcohol vapor chambers . This time , flies were transferred on to small plastic Petri dishes immediately after sedation and their recovery period monitored . Flies were said to have recovered from sedation once they regain postural control . Sedation recovery was quantified by counting the number of flies recovered from sedation in each vial at 5-minute intervals . Recovery scores for each vial were plotted as the percentage of flies recovered from sedation over time . For ethanol , tolerance was assayed as previously described [45] . In brief , flies were divided into 2 groups of equal numbers: the control group and the experimental group . Each group consisted of six vials with 10 flies each . On the first day , the experimental group was sedated using an ethanol-saturated air stream , while the control group was mock sedated . After sedation , the animals were allowed to recover in a fresh air environment and then returned to food vials for 24 hours . On the second day , both groups were sedated in tandem using the same ethanol-saturated air stream method . Again , after sedation , the ethanol vapor was replaced with fresh air , and their recovery period monitored . Flies were said to have recovered from sedation once they regain postural control . Sedation recovery was quantified by counting the number of flies recovered from sedation in each vial at 2-minute intervals . Recovery scores for each vial were plotted as the percentage of flies recovered from sedation over time . For both benzyl alcohol and ethanol , tolerance was determined by comparing the 50% recovery time from sedation between the control and experimental groups . The 50% recovery time ( and the associated SEM ) for each treatment group was calculated by performing a Richard's five parameter non-linear regression curve fit on the respective recovery curves using GraphPad Prism for Mac software ( GraphPad Software , La Jolla , CA ) . The relative change in recovery time ( magnitude of tolerance ) between the experimental and control groups was determined by calculating the difference in the 50% recovery time between the groups and compared to the magnitude of tolerance of the respective control lines . Statistical significance was determined using one-way ANOVA followed by Dunnett's multiple-comparison post hoc test . Gene-expression data for the 144 genes identified in this study was obtained from the Drosophila database FlyBase [95] . This data was collected by the modENCODE project [16] from RNA-Seq analysis performed on poly ( A ) + RNA from Drosophila treated with various chemicals through feeding or subjected to temperature shock . Total RNA isolation , poly ( A ) + RNA purification and strand-specific library construction were performed in the Brenton Graveley and Peter Cherbas groups . Libraries were subjected to paired-end RNA sequencing ( 2×76+ nt ) on the GAIIx and HiSeq platforms ( Celniker , Gingeras , and Graveley groups ) . Fastq files were generated using pipeline version 1 . 5 . Treatment conditions are listed in Supporting Table S1 . Gene clustering analysis based on treatment co-expression profiles was performed by the Cluster 3 . 0 for Mac OSX program [96] . For this , gene-expression data was prepared for Cluster by importing the 21 RNA-Seq expression datasets of the fly populations exposed to distinct external treatment conditions for the 144 genes identified from common acetylation changes . First , a self-organizing map ( SOM ) was made using default parameters ( 10 clusters ) based on Pearson's correlation ( centered ) similarity matrix of each gene-expression profiles . The resulting SOM file was then used to perform complete-linkage hierarchical clustering of the normalized gene-expression profiles . For genes expression normalization Cluster 3 . 0 multiplies all values in each row of data to a scale factor S to so that the sum of the squares of the values is in each row is 1 . 0 ( a separate S is computed for each row ) . Hierarchical clustering was applied to both rows and columns . For heat-map visualization , the output file was exported to JavaTreeview [97] . Pearson's Correlation coefficients of the gene-expression data from D . melanogaster exposed to the various conditions for each pair of the 13 tested genes was performed using GraphPad Prism for Mac software ( GraphPad Software , La Jolla , CA ) . For gene ontology annotation search and clustering , significant gene categories for each cluster were identified using DAVID web-accessible version 6 . 7 [18] with default parameters ( High , 3 , 0 . 85 , 3 , 3 , 0 . 5 ) and official gene symbols as input . To test the validity of the genome-wide arrays for accurately reporting significant acetylation peaks we used quantitative real-time PCR ( qPCR ) to measure representative acetylation signals ( ChIP/Input ) from independent chromatin samples . Primer sets were designed for 10 unique loci across the genome . These loci mapped to the promoter region of 8 different genes ( Creb2 , CrebA , Cyc , dbi , gpdh , pdf , per and Rdl ) . Primer sequences are displayed in Supporting Table S2 . Real-time PCR analysis of ChIP DNA was performed using the SYBR Green PCR Master Mix ( Applied Biosystems/Life technologies , Carlsbad , CA ) in an ABI Prism 7300 Sequence Detection System ( Applied Biosystems , Carlsbad , CA ) as described previously by [5] . ChIP/Input ratios reported for each primer set are averages and SEM of three chromatin samples ( Supporting Figure S1A ) . For comparison , signal peaks of the same genomic loci were extracted from one of the NimbleGen ChIP-chip data sets . For this , ChIP/Inputs ratio signals from 7 consecutive probes spanning the center of the region defined by each primer set used in the qPCR experiment were grouped an the average and SEM signal calculated ( Supporting Figure S1B ) . Correlation analysis of the signal ratio profile generated by the ChIP-chip and ChIP-qPCR data across the 10 unique regions was performed using Pearson's correlation coefficient analysis . The ChIP-qPCR and the genome-wide ChIP-chip signals display a very high correlation coefficient ( r = 0 . 849 , P value = 0 . 0019 ) . Total RNA was extracted from heads of groups of 100 flies ( mix of males and females ) 6 hours after treatment with either ethanol or benzyl alcohol , and from untreated controls , using a single-step RNA isolation protocol [98] . Residual genomic DNA was digested by incubating the RNA samples at 37°C for 30 min with RNase free DNase I ( Ambion , Austin , TX ) and further purified by acid phenol/chloroform extraction ( Ambion , Austin , TX ) and ethanol precipitation . RNA quality was determined by agarose gel electrophoresis and quantified using a NanoDrop Spectrophotometer ( NanoDrop Technologies , Wilmington , DE ) . First-strand cDNA was synthesized from 50 ng of total RNA using the SuperScript VILO cDNA Synthesis Kit ( Invitrogen/Life technologies , Carlsbad , CA ) . The cDNAs were amplified by real-time PCR using the SYBR Green PCR Master Mix ( Applied Biosystems/Life technologies , Carlsbad , CA ) in an ABI Prism 7300 Sequence Detection System ( Applied Biosystems , Carlsbad , CA ) following the manufacturer's protocols . Quantification of the starting mRNA for each gene was determined relative to the Cyp1 mRNA using the ΔΔCt method . Primer sequences for the genes tested are displayed in Supporting Table S3 . A total of 8 replicate RT-PCR reactions were performed from independent RNA samples , and the yields thereof were expressed as an average . Statistical significance was calculated using the One-way ANOVA for each gene with Dunnett's post-hoc test for comparisons to the untreated controls . Statistical significance for the effects of alcohol treatment on gene expression for the group of genes was determined by Two-way ANOVA .
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Alcoholism is a complex condition of compulsive alcohol use that results in devastating physical and social consequences . The development of this affliction is believed to arise in part by homeostatic adaptations in the brain that lead to the development of alcohol tolerance and dependence . These adaptations are strongly influenced by a great number of genetic and environmental conditions . Identifying the relevant factors that define alcohol tolerance and dependence has been a major objective of neurobiology research for many decades . Here we use a novel genomic approach that exploits the analysis of epigenetic modifications and the power of Drosophila genetics to identify a network of genes with a potential role in the neuroadaptations that lead to alcohol tolerance . Gene-expression profiling and subsequent gene ontology analysis revealed that the group of genes identified here is highly enriched with genes involved in the activity-dependent modulation of synaptic transmission . Because of the strong conservation of regulatory gene networks between Drosophila and mammals , we believe that the network identified here will serve as a powerful guide for the identification of the regulatory events that lead to human alcohol tolerance .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2013
|
Alcohol-Induced Histone Acetylation Reveals a Gene Network Involved in Alcohol Tolerance
|
Scaffold proteins are ubiquitous chaperones that promote efficient interactions between partners of multi-enzymatic protein complexes; although they are well studied in eukaryotes , their role in prokaryotic systems is poorly understood . Bacterial membranes have functional membrane microdomains ( FMM ) , a structure homologous to eukaryotic lipid rafts . Similar to their eukaryotic counterparts , bacterial FMM harbor a scaffold protein termed flotillin that is thought to promote interactions between proteins spatially confined to the FMM . Here we used biochemical approaches to define the scaffold activity of the flotillin homolog FloA of the human pathogen Staphylococcus aureus , using assembly of interacting protein partners of the type VII secretion system ( T7SS ) as a case study . Staphylococcus aureus cells that lacked FloA showed reduced T7SS function , and thus reduced secretion of T7SS-related effectors , probably due to the supporting scaffold activity of flotillin . We found that the presence of flotillin mediates intermolecular interactions of T7SS proteins . We tested several small molecules that interfere with flotillin scaffold activity , which perturbed T7SS activity in vitro and in vivo . Our results suggest that flotillin assists in the assembly of S . aureus membrane components that participate in infection and influences the infective potential of this pathogen .
Scaffold proteins , which are responsible for tethering proteins and facilitating multi-enzymatic biological reactions [1–3] , are found ubiquitously in eukaryotic and prokaryotic cells . These proteins were first identified in eukaryotic cells , where they have been traditionally studied . They play an important role in numerous signaling cascades , as they increase the interaction efficiency of signaling proteins by concentrating them locally and positioning kinases near their substrates [4 , 5] . Biological reactions are more efficient if scaffold proteins tether protein partners and facilitate interactions . This scaffold role might apply to both eukaryotic and prokaryotic cells , although the precise function in prokaryotes is not well understood . Several scaffold proteins have nonetheless been described in bacteria and their molecular mechanisms characterized . For instance , the scaffold UspC regulates the K+ uptake signaling cascade in Escherichia coli [6] , and GraX is a scaffold that participates in a signaling transduction cascade in response to antibiotics in the Gram-positive bacterium S . aureus [7 , 8] . A new type of scaffold protein was recently found in association with bacterial cell membranes . These proteins are homologs of the so-called flotillin proteins that localize preferentially to membrane lipid rafts in eukaryotic cells [9–14] . Bacterial flotillins are found in discrete membrane regions termed functional membrane microdomains ( FMM ) , which differ in lipid composition from the rest of the membrane and spatially confine several proteins involved in signal transduction ( sensor kinases ) , protein trafficking ( ABC transporters and protein secretion machineries ) and other multi-protein enzymatic reactions [15 , 16] . FMM thus resemble the lipid rafts of eukaryotic cells in certain organizational and functional aspects [17] . Flotillin scaffold activity in eukaryotic lipid rafts centers on recruiting raft-associated proteins to the rafts and catalyzing more efficient interaction or oligomerization [18–22] . Bacterial flotillins probably have a similar role , and their scaffold activity might also facilitate more efficient interactions and oligomerization of protein partners within FMM [3 , 23] . The biological significance of bacterial flotillins is nonetheless incompletely understood [24 , 25] . The Gram-positive bacterium Bacillus subtilis is currently the best-established model for study of the physiological relevance of flotillins and FMM [9–14] . B . subtilis FMM contain two flotillin-like proteins , FloT and FloA , which interact physically and recruit various proteins to the FMM . Strains lacking both of these flotillins show altered function of FMM-associated protein complexes , such as sensor kinase dimerization [25] , FtsH-mediated protease activity [13] , and protein secretion via Sec machinery [9] . Current research links flotillin activity and correct function of virulence-related cell processes in Gram-positive and -negative bacteria . The Gram-positive pathogen Bacillus anthracis expresses a flotillin homolog , FlotP , that is structurally similar to B . subtilis FloT ( ~65% identity ) [26] . Subcellular FlotP localization is associated with membrane integrity , and alteration of its distribution correlates with a decrease in toxin secretion . In Gram-negative pathogens , a flotillin-defective Campylobacter jejuni strain is unable to adhere to or be internalized by epithelial cells , resulting in impaired virulence [27]; experiments in mice showed that this mutant did not cause campylobacteriosis [28] . Despite the number of examples that correlate flotillin activity with correct function of cell processes in bacteria , a precise molecular description of how flotillin contributes to the activation of these processes has yet to be elucidated . The flotillin of the human pathogen S . aureus is 84% identical to B . subtilis FloA [12] . Inhibition of flotillin activity interferes with oligomerization of FMM-associated proteins in other bacterial models , and flotillin-lacking pathogenic strains show attenuated virulence . Such inhibition could thus be a strategy by which to disable virulence-related protein complexes in S . aureus , which is currently a major problem in both clinical and community settings [29] . MRSA ( methicillin-resistant S . aureus ) invasive infections are difficult to treat and have a ~20% mortality rate in clinical contexts [30] . The ESAT-6 or type VII secretion system ( T7SS ) is a membrane-bound protein complex with a role in S . aureus virulence [31–33] . This system mediates formation of persistent abscesses , modulates immune responses and is involved in interspecies competition [31–35] . It consists of four membrane-bound proteins ( EsaA , EssA , EssB , EssC ) , a cytosolic regulator ( EsaB ) and several secreted effectors [31–34 , 36] ( Fig 1A ) : EsaE , D and G encode a toxin-antitoxin system [34 , 35] , and EsxA-EsxD are small secreted proteins ( up to 15 kDa ) with roles in pneumonia and abscess development , probably through interference with the host apoptosis pathway [31–35 , 37 , 38] . Successful translocation of these T7SS substrates through the membrane requires the four membrane proteins EsaA , EssA-EssC [31 , 33] . While little is known of the molecular function of EsaA or EssA , available crystal structures of EssB and EssC suggest that EssB is a single-pass transmembrane protein that forms a conditional dimer with large extra- and intracellular domains [39–41] . EssC is a FtsK/SpoIIIE homolog with several ATPase domains , probably to provide energy for translocation [42–44] . The oligomerization state of the S . aureus T7SS is currently debated . The homologous secretion system from mycobacteria typically forms membrane-bound complexes >1 MDa [45–50] and similarly sized complexes have recently been purified from S . aureus [51] . This is in contrast to a recent report showing that T7SS membrane proteins form only homo-oligomers and might not interact with one another [52]; these proteins might not form large oligomers , at difference from other bacterial T7SS . Structural analyses of EssB and EssC in S . aureus nonetheless identified distinct domains that act as hubs for protein-protein interactions ( the EssC FHA domain or the EssB pseudokinase fold ) , which suggests that multimerization is an important feature of this protein machinery [40 , 42 , 43 , 51] . Here we identified the T7SS as a complex associated with the FMM in S . aureus . We studied its functional dependence on FMM-harbored scaffold protein FloA and show that intact FMM are crucial for full T7SS activity in vitro and in vivo . We demonstrate that microdomain dissociation by genetic depletion of the FloA scaffold leads to decreased T7SS activity , probably due to less efficient T7SS membrane protein interaction . FMM dispersal by small anti-FMM molecule inhibitors and concomitant reduction of FloA scaffold activity similarly leads to reduced T7SS activity .
To identify new FMM-associated protein complex candidates , we quantified proteomes of detergent-sensitive ( DSM ) and -resistant ( DRM ) membrane fractions using a biochemical approach designed to purify eukaryotic raft-associated proteins [53 , 54] . This approach is based on the ability of rafts to resist disaggregation by treatment with non-ionic detergent ( Triton X-100 , Brij , CHAPS ) . Differences in lipid composition make rafts more compact than the remainder of the cell membrane and more resistant to detergent disaggregation [53 , 54] . After detergent treatment , large hydrophobic membrane fragments enriched in FMM can be concentrated in a DRM fraction using a phase separation approach . This allows comparison to a DSM fraction that is sensitive to detergent disaggregation , as it is comprised mainly of phospholipids and does not concentrate to the hydrophobic phase during phase separation [6] . As FloA expression is higher and its activity possibly more important , we used stationary cultures of S . aureus cells to isolate DRM and DSM fractions and quantify the proteins by label-free quantification ( LFQ ) mass spectrometry [55] . We plotted LFQ intensities of DRM fraction proteins against those of the DSM fraction , which led to separation into four protein populations ( I-IV; S1A Fig ) . The first population ( I ) consisted of proteins detected exclusively in the DSM fraction; population II and III proteins were found in both DRM and DSM , with greater abundance in the DSM ( II ) or DRM fraction ( III ) . Population IV was associated exclusively with the DRM fraction ( S1A Fig ) . Most of the proteins we associated with DRM fractions were histidine kinases , lipoproteins , transporters , or components of protein complexes; we identified 12 of 13 known membrane-bound histidine kinases and more than 85% of all identified components of S . aureus membrane transporters ( ABC transporters; ion , nutrient and metabolite transporters ) in DRM-associated populations ( III , IV ) ( S1B Fig ) . Proteins involved in division , like FtsA , FtsY or FtsI , were generally detected in DSM populations ( S1B and S1D Fig ) . Nonetheless , sequence analysis of the DRM and DSM proteins categorized by this approach did not lead to the identification of any common features within each protein population ( I-IV ) ( S1C Fig ) ; all proteins identified for each population are listed in S1 Table . These findings are consistent with the hypothesis that FMM , which are very concentrated in the DRM fractions , mainly contain proteins that require protein-protein interaction or form part of protein complexes . During our data analysis , we detected several proteins of the S . aureus T7SS , significantly enriched in the DRM fraction ( Fig 1B ) ; these included membrane proteins EsaA , EssA , EssB , which suggested that S . aureus T7SS is physically and functionally associated to FMM . We used purified DRM and DSM fractions to measure T7SS membrane proteins EsaA , EssA , EssB and EssC by immunodetection , using polyclonal antibodies to EsaA , EssB or EssC [33] . EssA was fused to the codon-optimized RFP variant MARS and detected with polyclonal anti-mCherry antibodies [56] . Western blot analyses confirmed EsaA , EssA and EssB enrichment in the DRM fraction ( Fig 1C ) . Signals attributable to EssB and EsaA were enriched in the DRM fraction ( ~10- and 2-fold , respectively ) , and immunodetection of EssA-MARS showed most of the signal associated with this fraction . EssC was also detected in the DRM fraction , although it was not markedly enriched in this fraction compared to the DSM . These data are consistent with the LFQ mass spectrometry findings and correlate T7SS and DRM in S . aureus . Based on these results , we hypothesized that T7SS proteins are associated with the S . aureus FMM , probably in a transient manner , as we did not detect all T7SS membrane-associated proteins exclusively in the DRM fraction . The FMM are specific membrane regions that probably act as oligomerization platforms . They spatially confine interacting protein partners and promote efficient interaction/oligomerization of multiprotein complexes [23 , 25 , 57] . The membrane-bound scaffold protein flotillin localizes preferentially to the FMM . Flotillin probably has an important role in tethering interacting proteins and facilitates oligomerization , similar to its function in eukaryotic lipid rafts [19 , 22 , 23] . To determine whether the T7SS-related membrane proteins in the DRM fractions are among the flotillin-tethered protein partners , we used a bacterial two-hybrid assay in a heterologous E . coli system , in which S . aureus flotillin ( FloA ) and T7SS membrane proteins were tagged with T25 or T18 fragments of an adenylate cyclase . After flotillin interaction with T7SS proteins , the enzyme is reconstituted , produces cAMP and triggers expression of a measurable cAMP-inducible lacZ reporter [58] . We detected strong interaction between FloA and EssB ( >2000 Miller Units; a 700 Miller Unit threshold defines positive and negative interaction signals ) , with no consistent interactions between FloA and EsaA , EssA or EssC ( Fig 1D and S2 Fig ) . Our protein-protein interaction analyses in a heterologous system thus suggest interaction between flotillin and the membrane-bound T7SS protein EssB from S . aureus T7SS . We extended the FloA-EssB interaction analyses to S . aureus cells and performed pulldown experiments to identify interaction between FloA and EssB , using a FLAG-EssB , FloA-His double-labeled strain . FloA-His is a functional construct used in previous studies [59] . The FLAG-EssB construct was functional when expressed in a ΔessB genetic background , as immunodetection experiments of the EsxC substrate in culture supernatants showed that this complemented strain rescued the ΔessB mutant secretion defect ( S3 Fig ) [31 , 33 , 39] . A purified membrane fraction of this FLAG-EssB , FloA-His double-labeled strain was loaded on a column of Ni-NTA/His-tag resin selective for proteins that bind directly or indirectly to FloA-His . Eluted proteins were resolved by SDS-PAGE and FLAG-EssB was detected by immunoblotting using monoclonal anti-FLAG antibodies . A FLAG-EssB signal was detected in the eluted sample of the double-labeled strain , suggesting that EssB co-eluted with FloA ( Fig 2A ) . In contrast , the elution fraction of FloA-His and FLAG-EssB single-labeled strains showed no signal , which implies that EssB retention on the column was FloA-dependent . We used stimulated emission depletion ( STED ) microscopy to examine EssB and FloA signal colocalization in S . aureus cells . STED microscopy is a super-resolution technique previously used in B . subtilis to demonstrate partial colocalization of FMM-associated proteins with the scaffold protein FloA [24] . Pull-down experiments or BN-PAGE coupled to immunoblotting have shown that flotillin interacts directly or indirectly with these FMM-associated proteins , and that this interaction contributes to FMM-associated complex oligomerization [9 , 57] . Partial colocalization of FloA with FloA-interacting FMM protein cargo is likely because flotillin does not form part of these oligomeric complexes and is thus not strictly necessary for their activity . The role of flotillin could be transient , to facilitate oligomerization of multimeric complexes that then act in a flotillin-independent manner . This is consistent with the role of FMM as oligomerization platforms , to promote efficient interaction between protein partners . To study FloA and EssB colocalization , we immunodetected these proteins in S . aureus cells , using specific antibodies . Subcellular signal localization in double-labeled samples was examined using STED microscopy ( Fig 2B , top panel ) . Traditional colocalization studies focus on 1:1 ratios of red- and green-labeled proteins , resulting in a merged yellow signal . Proteins abundant at different ratios still colocalize , but are falsely disregarded using this approach . We determined protein colocalization independent of the relative FloA and EssB abundance , and present the results in a white colocalization map ( Fig 2B , bottom ) . The flotillin signal was distributed in 1–6 fluorescent foci per cell , whereas the EssB signal formed 1–4 membrane foci . Using this method , we determined that 27% of the total EssB signal showed an overlap with FloA fluorescent signal . Thus , 73% of the EssB did not overlap with FloA and 68% of FloA did not overlap with EssB ( Fig 2C ) . This partial colocalization indicates biochemical interactions of EssB and FloA and suggests that this EssB and FloA interaction occurs in a transient manner , similar to previous flotillin-associated interactions . Having determined that EssB is enriched in the DRM fraction and interacts with FloA , we analyzed FloA influence on T7SS activity; this is an important aspect of S . aureus virulence , since EssB is essential for secretion of T7SS effectors during infection [31 , 33 , 39] . We compared the levels of the T7SS substrates EsxA and EsxB and of EsxC in wild type or FloA-defective cells in culture supernatants . EsxA and EsxB were C-terminally labeled with a FLAG-tag and expressed under the control of a constitutive promoter . Culture supernatant proteins were concentrated by trichloroacetic acid ( TCA ) precipitation , and EsxA- and EsxB-FLAG were immunodetected with monoclonal anti-FLAG antibodies and EsxC with EsxC-specific polyclonal antibodies [33] . The ΔfloA mutation might alter other secretory protein complexes in S . aureus , like the Sec system defect in a B . subtilis flotillin-deficient strain [9] . To normalize total ΔfloA mutant-to-wild type secreted protein in immunoblot analyses , we normalized cell culture optical density and added a defined concentration of an unrelated protein to supernatants . We added purified denatured YtnP lactonase ( 25 μg/ml ) from B . subtilis [60] to supernatants before TCA precipitation , and we used polyclonal anti-YtnP antibodies to trace YtnP concentration and thus ensure comparable concentration of the supernatant . In this system , EsxA-FLAG and EsxB-FLAG showed a marked decrease in supernatants from the ΔfloA mutant compared to wild type ( Fig 3 ) ; EsxC substrate was also decreased in ΔfloA compared to wild type supernatants , which implied an important flotillin role in T7SS activity . Quantitative differences in T7SS substrates in the supernatant are probably due to reduced T7SS secretion efficiency rather than reduced abundance of its components , as immunodetection indicated similar EsaA , EssA , EssB and EssC protein levels in wild type and ΔfloA mutant whole cell extracts ( S4 Fig ) . The most direct hypothesis as to how flotillin influences T7SS activity is that its scaffold activity promotes T7SS stability or assembly by tethering interacting proteins [3] . In the absence of FloA , EssB might oligomerize less efficiently and negatively affect correct T7SS organization . We thus used fluorescence microscopy to analyze EssB subcellular distribution in wild type and ΔfloA mutant cells labeled with a GFP-EssB translational fusion . We constructed a GFP-EssB ΔessB complemented strain and confirmed its function as above ( S3 Fig ) . Compared to the punctate GFP-EssB pattern on a wild type background , EssB foci were undetectable in ΔfloA mutants , and the GFP-EssB signal was distributed uniformly over large portions of the membrane ( Fig 4A , left ) whereas protein abundance was unaffected ( Fig 4A , right ) . This suggests that flotillin determines correct subcellular localization of EssB . EssB oligomerizes in vitro and forms conditional dimers [39–41] , although in vivo homo- or hetero-oligomerization has not been detected [52] . We thus tested whether FloA scaffold activity affects EssB oligomerization directly . FLAG-EssB-labeled S . aureus was cultured to stationary growth phase and membrane protein extracts ( 0 . 25% DDM , 4°C ) ( S5A Fig ) were resolved by 3-12% gradient Blue-Native ( BN ) -PAGE , which allows separation of membrane protein complexes into their natural oligomeric states ( 30–10 , 000 kDa ) [61–63] . FLAG-EssB was immunodetected using specific anti-FLAG antibodies . We observed a signal attributable to EssB at >250 kDa , which indicates that EssB forms stable oligomers in vivo ( S5B Fig ) . Protein samples crosslinked using DSP ( dithiobis ( succinimidyl propionate ) ) prior to cell lysis showed EssB-containing oligomers >1 MDa ( S5B Fig ) , which indicated the existence of large EssB-containing complexes in S . aureus cells . We applied this experimental approach using anti-FLAG epitope antibodies to compare FLAG-EssB-labeled wild type and ΔfloA mutant membrane fractions ( Fig 4B ) . Wild type cells usually showed two signals that corresponded to distinct EssB oligomeric states ( >1 MDa ) , whereas ΔfloA mutant showed one >1 MDa signal that did not coincide with either wild type band ( Fig 4B ) . In addition to these differences , we detected an intensity increase in a low molecular weight signal ( ~250 kDa ) in the ΔfloA mutant compared to the wild type strain ( Fig 4B , right , bottom arrow ) . These results suggest an important role for FloA in formation of EssB-containing high molecular weight complexes in S . aureus . To ascertain whether these very large protein complexes are EssB homo-oligomers or are constituted by other T7SS proteins , we analyzed FLAG-EssB in a pulldown analysis using FLAG-capture beads . Beads captured FLAG-EssB as well as EssB-associated proteins , which were eluted , resolved in SDS-PAGE , and immunoblotted , which indicated EssA , EssC and an EsaA fragment ( Fig 4C ) . The polyclonal EsaA antibody did not detect full-length EsaA in the pull-down assay , but showed fragmented EsaA , which is also detected in membrane fractions . Similar fragmentation is reported for the B . subtilis EsaA homolog [64] . The wild type and ΔfloA eluted fractions showed EssC and the EsaA fragment in comparable amounts , but no EssA was detected in the ΔfloA fraction ( Fig 4C ) . These data suggest that flotillin mediates the EssB-EssA interaction . To better understand the flotillin effect on the EssB-EssA interaction , we used a bacterial three-hybrid assay [25 , 57] to measure EssB-EssA oligomerization efficiency , alone or with FloA ( Fig 4D ) . A bacterial two-hybrid assay in which EssB and EssA were tagged respectively with the T25 and T18 catalytic domains , was complemented with a modular vector [65] that expressed floA . Whereas there was no EssB-EssA interaction in the absence of FloA , the EssB-EssA interaction signal was increased when FloA was present ( Fig 4D ) . FloA did not affect the EssB interaction with other T7SS membrane proteins ( EsaA or EssC ) ( S6 Fig ) , which implied that FloA scaffold activity is specific to the EssB-EssA interaction . This finding indicates the importance of FloA expression in T7SS protein-protein interactions and supports the hypothesis that flotillin acts as a scaffold to promote EssB-EssA interaction . To determine whether this FloA activity is sufficient to promote T7SS protein oligomerization , we genetically engineered an orthogonal T7SS system in E . coli , in which the T7SS membrane proteins EsaA , EssA , EssB and EssC were isolated from their native complex oligomerization network , and thus free from interference by potential staphylococcal oligomerization inputs . EsaA , EssA , EssB and EssC proteins were expressed alone ( -FloA ) or in the presence of FloA ( +FloA ) . Solubilized membrane fractions were purified , proteins extracted and their oligomerization states identified by BN-PAGE and immunoblotting using anti-EssB antibody . In the absence of FloA ( -FloA ) , EssB signals were observed in the 200-400 kDa range ( Fig 5A ) , similar to EssB oligomers detected in uncrosslinked staphylococcal membranes ( see Fig 4B and S5B Fig ) . In the presence of FloA ( +FloA ) , EssB oligomeric species shifted towards higher molecular weight complexes ( Fig 5A ) , indicating that FloA affects EssB oligomerization and potentially other T7SS complex components in the orthogonal biosystem . To ascertain whether FloA exclusively affects EssB oligomerization or influences oligomerization of additional T7SS proteins in this system , we purified E . coli membrane fractions , extracted proteins and identified their oligomerization states by size-exclusion chromatography . We used immunoblot to analyze 1 ml fractions of the column volumes in an 8–21 ml range to detect FloA , EsaA , EssB and EssC ( Fig 5B ) . In -FloA fractions , EsaA , EssB and EssC signals were detected in later-eluting fractions of 10–16 ml , corresponding to a 1-0 . 4 MDa range . In +FloA samples , the signal was detected in early-eluting fractions and concentrated in the 9 ml fraction , which corresponds to high molecular weight complexes >1 MDa ( Fig 5B ) . These results suggest that flotillin affects T7SS membrane protein oligomerization in this orthogonal system , and further highlights the importance of this scaffold protein for S . aureus T7SS . Targeting of flotillin scaffold activity could be an appropriate strategy for fighting bacterial infection by perturbing oligomerization of multiple virulence-related protein complexes such as T7SS . In mice , the T7SS Esx substrates participate in formation of persistent abscesses , probably due to the virulence of EsxA , EsxB , EsxC and EsxD secreted proteins [31 , 32 , 37 , 38 , 66] . In addition , EsxC is an immunogenic substrate , and kidney abscesses are associated with the generation of anti-EsxC antibodies [32] . In a murine infection model similar to that of Burts et al . [32] , we evaluated the link between FloA inactivation and reduced S . aureus virulence mediated by low T7SS activity by measuring EsxC immunoreactivity . Cohorts of 3-week-old BALB/c mice received intravenous injections of sublethal doses of staphylococcal wild type , ΔfloA mutant and ΔT7SS mutant strains . The humoral immune response was boosted by Staphylococcus challenge on days 14 and 28 [67] . After 40 days , mice were sacrificed and serum collected to determine anti-EsxC immunoglobulin titers by indirect ELISA ( Fig 6A ) . We observed significantly lower IgM antibody titers against EsxC in a ΔfloA mutant compared to wild type , consistent with in vitro experiments lowering EsxC secretion in the ΔfloA mutant ( Fig 6B ) . As control , we detected antibodies to the unrelated staphylococcal cell wall protein IsaA [68] , which showed that all mice established an S . aureus infection ( S7 Fig ) . These data indicate the importance of FMM integrity in T7SS-mediated virulence phenotypes in an in vivo infection . To target flotillin activity exogenously and develop alternative strategies against staphylococcal infections , we tested several small molecules known to interfere with FMM organization in S . aureus [59] . The small molecule zaragozic acid ( ZA ) is a potential inhibitor of flotillin activity [12] , as it blocks S . aureus squalene synthase [69] , which is needed to produce the polyisoprenoid lipids that stabilize flotillin in the FMM . When bacteria are exposed to micromolar ZA concentrations , flotillin organizes in a smaller number of membrane foci , concomitant with a reduction in its chaperone activity [12] . Similar to ZA , the cholesterol-lowering drug simvastatin used to treat patients with hypercholesterolemia , inhibits the same polyisoprenoid lipid production pathways in S . aureus . Simvastatin is a competitive inhibitor of HMG-CoA reductase , an enzyme upstream of squalene synthase in the constituent lipid biosynthesis pathway [70] . We included the small molecule 5-DSA ( 5-doxyl-stearic acid ) , a lipid probe that accumulates in biological membranes and is used to monitor membrane fluidity in lipid raft organization studies in eukaryotic cells [71 , 72] . In addition , 5-DSA is reported to displace certain membrane lipids and alter the function of various membrane-associated proteins [73 , 74] . Wild type S . aureus strains were grown in liquid TSB medium with different concentrations of simvastatin , 5-DSA and ZA to define the highest concentrations that did not affect S . aureus growth ( 20 μM simvastatin , 150 μM 5-DSA , 50 μM ZA; Fig 7A ) . We used fluorescence microscopy to monitor anti-FMM activity by evaluating FloA subcellular distribution . We quantified the number of fluorescent foci of a FloA-MARS strain grown with simvastatin , 5-DSA or ZA . Most untreated cells showed one , two or three fluorescent foci; occasional cells had no fluorescent foci or had four or more foci . Treatment with 20 μM simvastatin or 50 μM ZA reduced the number of fluorescent FloA foci per cell , and 150 μM 5-DSA treatment showed a drastic reduction in the number of foci per cell ( Fig 7B , S8 Fig ) . The altered subcellular localization of FloA-MARS in the presence of anti-FMM molecules was not a result of decreased flotillin in the cell membrane or its displacement to the cytosol , as shown by immunoblot analysis of fractionated cells after anti-FMM treatment ( Fig 7C ) . We thus suggest that these molecules severely alter FMM organization and probably affect associated processes . To determine whether 5-DSA , simvastatin or ZA also affected T7SS assembly and organization , we repeated BN-PAGE analysis as above . Without crosslinking , the FloA-interacting protein EssB only formed oligomers at ~250 kDa; high molecular weight protein complexes were not detected ( Fig 8A , left ) . DSP treatment before cell lysis allowed stabilization of high molecular weight complexes , and 5-DSA , simvastatin , and ZA treatment led to a decrease in the high molecular weight signal in wild type cells ( Fig 8A , center ) . This was consistent with the increase in low molecular weight species detected in 5-DSA- , simvastatin- , or ZA-treated samples compared to wild type ( Fig 8A , right , bottom arrow ) . BN-PAGE analysis thus suggested that 5-DSA , simvastatin , or ZA treatments interfere with correct T7SS assembly or organization , probably by inhibiting FloA scaffolding activity . We tested whether 5-DSA , simvastatin or ZA treatments also inhibit T7SS secretion in vitro . To define this , we monitored secretion of the T7SS substrates EsxA , EsxB and EsxC in stationary phase cultures . Concentrated proteins from supernatants of untreated and simvastatin- , 5-DSA- and ZA-treated cultures were resolved by SDS-PAGE and analyzed in immunoblot . Simvastatin- , 5-DSA- and ZA-treated cultures showed a notable reduction in secreted EsxA , EsxB and EsxC , particularly marked in ZA-treated cells , for which no signals were detected ( Fig 8B ) . To determine the localization of the T7SS substrates , we analyzed cell extracts by immunoblot , which showed EsxA , EsxB and EsxC signals in the cytoplasmic fraction of treated cultures . Simvastatin , 5-DSA and ZA in S . aureus cultures thus compromised T7SS activity and reduced T7SS substrate secretion ( Fig 8B ) . While treatment of S . aureus cultures probably affects T7SS organization and assembly , simvastatin , 5-DSA or ZA addition did not alter EsaA , EssB or EssC concentrations in cell extracts ( S9 Fig ) . The ZA inhibitory effect on T7SS activity via FMM perturbation led us to test ZA-mediated T7SS inhibition in vivo in the murine infection model . We administered 20 mg/kg ZA to a cohort of BALB/c mice via intraperitoneal injection , followed by challenge with sublethal doses of S . aureus . This procedure was repeated twice ( days 14 and 28 ) ; after 40 days mice were sacrificed and serum was collected for ELISA determination of immunoglobulin titers to EsxA , EsxB , EsxC and EsxD substrates . IgM antibody titers against all T7SS Esx substrates decreased for all T7SS Esx substrates , which was statistically significant for EsxB , EsxC and EsxD compared to levels in infected untreated mice ( Fig 8C ) . These results indicate that ZA inhibits secretion of T7SS-related substrates in vivo , probably by reducing secretion efficiency . This observation makes ZA an attractive molecule for development as an alternative antimicrobial therapy in S . aureus infections .
The role of scaffold proteins in prokaryotic cells is being studied for a number of bacterial species . These proteins are thought to have a central role in regulating assembly of protein-protein interactions; their activity is thus important for correct function of many biological reactions [2 , 3 , 75] . We show that the scaffold protein flotillin ( FloA ) promotes more efficient interaction in a multimeric complex involved in staphylococcal virulence . Here we used FloA-mediated T7SS secretion as a case study to evaluate FloA scaffold activity , although FloA might also contribute to oligomerization of other DRM fraction multimeric complexes with a role in S . aureus virulence . Lack of FloA causes a reduction in T7SS substrate secretion in vitro and in vivo , which implies an important FloA function in T7SS oligomerization . Additional possibilities for the role of flotillin in T7SS oligomerization should also be considered , for instance , that lack of flotillin causes changes in membrane stiffness [9] , which might affect T7SS oligomerization indirectly . We nonetheless found that FloA interacts with the T7SS membrane component EssB , thus facilitating its interaction with EssA and probably with other T7SS protein components; this highlights the importance of FloA for T7SS oligomerization , although T7SS organization remains unclear . Whereas FloA scaffold activity assists oligomerization of complexes such as T7SS , FloA is not a T7SS structural protein; it probably contributes to more efficient complex assembly , although FloA activity is not absolutely essential for the activity of these complexes [76] . In fact , some T7SS oligomerization and secretion of T7SS effectors are detectable in the absence of FloA . Bacterial flotillin might thus have a transient role , acting as a scaffold for oligomerization of membrane-associated protein complexes , whose subsequent activity is flotillin-independent . Flotillin might contribute to organizing FMM membrane microdomains , which are specialized in confining specific protein complexes , and to promoting their efficient oligomerization; these complexes will be excluded from the FMM once oligomerized . Bacterial FMM appear to facilitate efficient oligomerization of FMM-associated protein complexes ( FMM act as “oligomerization factories” ) [12] , and flotillin scaffold activity has a key role in facilitating interaction of FMM-associated membrane protein partners . Biochemical approaches such as pull-down experiments or BN-PAGE coupled with immunodetection demonstrated flotillin interaction with FMM-associated proteins , as well as its importance for correct oligomerization of protein partners in various bacterial species [9 , 14 , 25 , 55 , 57 , 77] . FMM are dynamic structures and move across the bacterial membrane in milliseconds . STED fluorescence microscopy was used to show partial flotillin colocalization ( milliseconds ) with various FMM protein partners such as FtsH and SecA [24] , previously identified in pull-down studies as flotillin interactors [9 , 13] . In the STED study , partial FloA colocalization with FtsH and SecA contrasted with full flotillin colocalization with NfeD , which implies that partial colocalization was not due to experimental factors [24] . The structural FMM proteins FloA and NfeD form part of the same operon , are expressed at similar levels , and are thus present in an equal ratio . When one is green- and one is red-labeled , colocalization is detected as a merged yellow signal . Most FMM cargo proteins are not expressed at the same ratio as FloA , however , and this approach can lead to false negative results due to differences in protein levels/signal intensities . To overcome these drawbacks , we studied FloA colocalization with FMM cargo proteins using a method that focuses on the signal , independent of its intensity [78] . Colocalization of proteins in unequal ratios can be detected using high-resolution microscopy images . Full colocalization of cargo proteins with flotilin would not be anticipated , as flotillin is not a structural component of these complexes . Protein interaction with FloA in pull-down experiments , and partial colocalization using STED microscopy support the hypothesis that FMM act as oligomerization platforms , in which flotillin and probably other structural proteins like NfeD assist FMM organization . The NfeD/FloA interaction is stable and would help maintain correct FMM architecture . In contrast , flotillin interaction with the FMM protein cargo is probably transient , as this interaction facilitates efficient oligomerization of protein partners . Protein complexes will thus dissociate from flotillin once oligomerized and will abandon FMM . Using a number of biochemical approaches , we detected FloA interaction with EssB , and showed partial FloA/EssB colocalization using STED microscopy . We thus propose a model to explore the role of FMM and FloA in T7SS organization , as illustrated in Fig 9 . The FloA interaction with EssB facilitates EssB-EssA binding; as EssB and EssA are significantly enriched in the DRM , this binding probably takes place in FMM . In contrast , FloA does not influence EssB interaction with other T7SS proteins ( EsaA , EssC ) , since EsaA and EssC are detected in pull-down experiments in a ΔfloA mutant background . We hypothesize the formation of an EssC-EsaA-EssB pre-complex , and EssA incorporation via FloA scaffold activity to generate T7SS in a flotillin-dependent manner . Although our data indicate a large T7SS hetero-oligomer , the nature of T7SS assembly is currently debated . Some reports argue that T7SS assembly in S . aureus resembles that in mycobacteria [46 , 48 , 50 , 51] , but there are also experimental evidences that interactions between T7SS protein components in S . aureus cells are exclusively homomeric [52] . Based on our results , we consider that both hypotheses are probably correct and are not necessarily mutually exclusive . T7SS assembly is influenced by the activity of proteins that catalyze T7SS oligomerization , such as flotillin . It is possible that T7SS assembly is transient during the bacterium lifespan , and is regulated by the activity of scaffold proteins expressed at a specific time during growth or in response to a specific signal . These signals are likely to be produced during an infection in which T7SS activity is necessary , which impedes reproduction of these conditions in the laboratory . In addition , laboratory conditions might affect results for T7SS assembly; the choice of detergent and its concentration for membrane proteins solubilization is critical for an appropriate balance between membrane disaggregation and extraction of membrane proteins in their natural oligomeric states , and subtle variations in detergent use can affect results notably [79] . During an infection in a murine model , the S . aureus T7SS is critical for abscess development [31 , 32] . Using a variety of virulence factors , S . aureus is able to evade immune mechanisms and eventually disseminate into peripheral organs to establish the formation of a purulent abscess [80] . Secretion of the T7SS substrates EsxA and EsxB is important in kidney and liver abscess formation [31] . EsxC is crucial for maturation of these abscesses over a prolonged period , leading to establishment of persistent infection during which EsxC continues to be produced , since infected mice generate antibody responses against EsxC [32] . Although the actual host cell targets are unknown , one can speculate that Esx substrates interfere with several immune mechanisms ( apoptosis , cytokine responses ) , similar to T7SS substrates of Mycobacterium tuberculosis , to generate a severe persistent infection [38 , 81 , 82] . Targeting the activity of bacterial scaffold proteins could thus be an innovative antimicrobial strategy that could reduce the virulence potential of S . aureus during a persistent infection . Here we show the potential antimicrobial effect of simvastatin , 5-DSA and ZA by their ability to perturb FMM organization , reduce T7SS function , and thus inhibit T7SS-mediated secretion of the EsxA , EsxB and EsxC substrates . Treated cells showed reduced extracellular EsxA , EsxB and EsxC levels , both in vitro and in an in vivo mouse infection model . Anti-FMM compounds could be a promising anti-microbial strategy to interfere simultaneously with molecular pathways that contribute to the virulence potential of S . aureus , toward eliminating hard-to-treat S . aureus infections . Such infections are considered endemic in hospitals , and their ~20% mortality rate in invasive MRSA infections makes them a leading cause of death by a single infectious agent [30] .
Strains used in this study were Staphylococcus aureus RN4220 [29] and S . aureus USA300_TCH1516 [83] . Escherichia coli DH5α and XL-1 Blue were used for cloning , and BL-21 Gold for recombinant protein expression . E . coli strains and S . aureus were propagated on LB and TSB media , respectively . Selective LB plates for E . coli were prepared using ampicillin ( 100 μg/ml ) , chloramphenicol ( 25 μg/ml ) , kanamycin ( 50 μg/ml ) and gentamycin ( 2 μg/ml ) . S . aureus was selected on TSB plates containing spectinomycin ( 600 μg/ml ) or erythromycin ( 2 μg/ml for RN4220 isolates and 100 μg/ml for the USA300_TCH1516 isolate , which bears an erythromycin resistance gene ) . For blue/white screenings , X-Gal ( 5-bromo-4-chloro-3-indolyl-β-D-galactopyranoside ) was added to the plates ( final concentration 50 μg/ml ) . If proteins were controlled by inducible promoters and induction was required , IPTG ( isopropyl-β-thiogalactopyranoside ) or xylose was added at 1 mM or 1% ( v/v ) , respectively . The anti-FMM molecules 5-doxyl-stearic acid and simvastatin were purchased from Sigma-Aldrich and zaragozic acid from Santa Cruz . Simvastatin and zaragozic acid were dissolved in DMSO to a 10 mg/ml stock solution and 5-doxyl-stearic acid was dissolved in methanol to 75 mM stock solution . Compounds were added to cultures at specified concentrations . All strains and plasmids were generated according to standard molecular biology techniques [84] . A complete list of strains , plasmids and primers used can be found in S2 and S3 Tables . For protein tagging ( with GFPmut2 , RFPMars or FLAG-Tag ) , the CDS of the protein of interest was fused to the respective tag via LFH ( long flanking homology ) -PCR [85]; the PCR fragment was subsequently cloned into target plasmids using suitable restriction enzymes . If the native promoter was required , a 500 bp fragment upstream of the corresponding operon was fused upstream to the CDS by LFH-PCR . For gene deletion and ectopic gene expression in S . aureus , we used the pMAD plasmid and its derivatives pAmy and pLac [86 , 87] . pMAD plasmids were constructed and maintained in E . coli and then transformed in S . aureus RN4220 via electroporation . After successful integration of the entire plasmid into the genome ( first recombination ) , constructs were shuttled to USA300 via ϕ11-phage transduction and selected for blue color and erythromycin resistance . To eliminate the pMAD plasmid backbone ( containing the erythromycin resistance gene and β-galactosidase ) , strains were grown at 42°C , plated on TSB X-Gal and white colonies were screened for loss of plasmid and presence of target construct by colony PCR ( second recombination ) . The flotillin deletion mutant ( ΔfloA::spc ) was constructed previously [59] and transferred into the USA300_TCH1516 isolate by ϕ11-phage transduction . The MARS-fluorescent protein fusion to FloA was generated by replacing the CDS of floA-yfp with floA-mars in a pCel plasmid created previously [59] . For analysis of protein-protein interaction via bacterial two- and three-hybrid systems [25 , 57 , 58] , the coding sequences of the corresponding gene without the stop codon were cloned in-frame into each of the bacterial two-hybrid vectors ( pKT25 , pKNT25 , pUT18 , pUT18C ) . For bacterial three-hybrid analysis , the CDS of flotillin controlled by an IPTG-inducible Plac promoter was introduced into plasmid pSEVA631 of the SEVA system [59 , 65] . For recombinant expression of EsxA , EsxB , EsxC and EsxD , we used the plasmid pET20b ( + ) , which allows tagging with a hexahistidine tag for purification . The plasmid also contains a periplasm-targeting sequence that was removed by cloning the inserts in-frame with NdeI and XhoI . For recombinant expression of FloA and EssB , the CDS were cloned into pASK-IBA3 using reverse PCR to linearize the vector bearing a C-terminal StrepII-tag . The construct to express recombinant T7SS structural genes EsaA , EssA , EssB and EssC was from GenScript . The genes are codon-optimized for E . coli and contain a ribosome-binding site between each gene to ensure translation of all components . The esaAessABC-CDS was cloned into the pBAD-HisB vector by in-fusion PCR , excluding the hexahistidine-tag encoded in the vector . For antibody production , pASK-IBA3C-essB was transformed in E . coli TOP10 ( Life Technologies ) and a single colony used to inoculate an overnight pre-culture . The pre-culture was diluted 1:100 and grown at 37°C to an optical density of OD600 = 0 . 4–0 . 6 . EssB was expressed by adding 2 . 5 mM anhydrotetracycline ( 24 h , 18°C ) . Cells were harvested by centrifugation ( 6000 xg , 20 min , 4°C ) and resuspended in 300 mM NaCl , 50 mM Tris pH 8 . 0 . Cells were lysed by two rounds of French press-mediated lysis ( 10 , 000 psi ) and the membrane fraction of cleared lysate was collected by ultracentrifugation ( 185 , 000 xg , 1 h , 4°C ) . Membrane proteins were then extracted in 300 mM NaCl , 50 mM Tris pH 8 . 0 , 1% DDM ( 1 h , 4°C ) . Insoluble proteins were removed by ultracentrifugation ( 185 , 000 xg , 1 h , 4°C ) . Membrane proteins were loaded on a pre-equilibrated 2x 1 ml StrepTrap HP column ( GE Healthcare ) and eluted with 2 . 5 mM desthiobiotin . Peak fractions were concentrated with a 10 kDa concentrator and further purified on an S200 size exclusion chromatography column . For antibody generation , protein was diluted in 1x PBS + 0 . 05% DDM ( final concentration 0 . 3 mg/ml ) . Rabbit immunization and antibody production were performed by ImmunoGlobe GmbH ( Himmelstadt , Germany ) . For label-free quantification , protein samples were reduced in 1x Laemmli buffer ( BioRad ) containing 50 mM dithiothreitol ( DTT , Thermo Scientific; 5 min , 95°C ) . Proteins were alkylated with 120 mM iodoacetamide ( 20 min , room temperature , light-protected ) then precipitated and washed three times in ice-cold acetone . Protein pellets were dissolved in 100 mM ammonium bicarbonate containing 0 . 5% ( w/v ) sodium deoxycholate ( Sigma-Aldrich ) . Digestions were performed with the lysyl endopeptidase LysC ( Wako; 1 h , 30°C ) , followed by treatment with trypsin ( Promega; overnight , 37°C ) . Sodium deoxycholate was removed by ethylacetate extraction [88] and samples were dried using a vacuum concentrator . Peptides were desalted using C18 stage tips with five C18 Empore SPE disks ( 3M ) and eluted with 60% ( v/v ) acetonitrile/0 . 1% ( v/v ) formic acid . NanoLC-MS/MS analyses were performed on an Orbitrap Fusion instrument equipped with an EASY-Spray Ion Source coupled to an EASY-nLC 1000 ( Thermo Scientific ) . Peptides were loaded on a trapping column ( 2 cm x 75 μm ID , PepMap C18 , 3 μm particles , 100 Å pore size ) and separated on an EASY-Spray column ( 25 cm x 75 μm ID , PepMap C18 , 2 μm particles , 100 Å pore size ) with a 120 min linear gradient from 3 to 32% acetonitrile and 0 . 1% formic acid . MS scans were acquired in the Orbitrap analyzer at 120 , 000 resolution at m/z 200 . Data-dependent MS/MS scans were measured by a Top Speed method ( cycle time 3 s in the ion trap analyzer , with rapid scan rate and HCD fragmentation with 35% normalized collision ) . Dynamic exclusion was applied for 60 s; isotopes , singly charged precursors and charge states >7 were excluded from selection . Minimum signal threshold for precursor selection was 1 x 104 . Predictive AGC was used with a target value of 2 x 105 for MS scans . For MS/MS scans , recommended universal method settings were applied ( AGC target 3 x 103 , max . injection time 0 . 25 s , injection of ions for all available parallelizable time ) . EASY-IC was used for internal calibration . Data analysis was performed using MaxQuant v1 . 5 . 3 . 30 . Bacterial two- and three-hybrid assays were performed using a kit ( Euromedex ) and screened as reported [25 , 57] . Briefly , plasmids were transformed in the BTH101 strain and selected on LB plates containing ampicillin and kanamycin . Single colonies were picked and grown at 30°C in liquid LB medium with antibiotics . After overnight growth , 2 μl were spotted on LB plates with ampicillin , kanamycin , 0 . 5 mM IPTG and 40 μg/ml X-Gal and incubated ( 48 h , 30°C ) . For quantification of interactions , single transformants were picked and grown in 1 ml LB medium ( 48 h , 30°C ) with antibiotics and inducer ( 0 . 5 mM IPTG ) , and β-galactosidase activity was determined in Miller Units , as described [89] . For recombinant expression of Esx-proteins ( EsxA-EsxD ) and YtnP , the pET20b ( + ) vector containing the respective His-tagged protein was transformed in E . coli BL-21 DE3 Gold ( Stratagene ) . Cells were grown to an optical density of OD600 = ~0 . 6 and expression of recombinant proteins was induced with 1 mM IPTG ( 4–5 h , 37°C ) . Cell pellets were resuspended in 50 mM Tris-HCl pH 7 . 5 , 500 mM NaCl , 20 mM imidazole , 10% ( v/v ) glycerol , 1% ( v/v ) Tween-20 and 0 . 2 μg/ml lysozyme ( Sigma-Aldrich; 10 min , 37°C ) , then lysed mechanically in a fast-prep shaker ( two times , 45 s each , 6 . 5 m/s ) and lysate was cleared by centrifugation ( 10 , 000 xg , 10 min , 4°C ) . Lysates were mixed with pre-equilibrated Ni-NTA resin ( Qiagen ) and incubated ( 30 min , 4°C with mild agitation ) . The resin was washed twice in 50 mM Tris-HCl pH 7 . 5 , 500 mM NaCl , 10% ( v/v ) glycerol and 1 mM PMSF ( phenylmethylsulfonylfluoride; Sigma-Aldrich ) with increasing imidazole concentrations from 20 to 50 mM . His-tagged proteins were eluted from the resin with 50 mM Tris-HCl pH 7 . 5 , 500 mM NaCl , 1 M imidazole , 10% ( v/v ) glycerol and 1 mM PMSF . Imidazole was removed using PD-10 desalting columns ( GE Healthcare ) . Proteins were supplemented with 20% ( v/v ) glycerol and stored at -80°C . pBAD-esaAessABC was transformed in E . coli One Shot TOP10 expression strain ( Life-Technologies ) and if necessary , pASK-IBA3C-floA was co-transformed . Cells were grown at 37°C in liquid LB medium to an optical density of OD600 = ~0 . 8 and expression induced with 0 . 2% ( w/v ) L-arabinose ( for pBAD plasmid ) and 0 . 2 μg/ml anhydrotetracycline ( for pASK-IBA3C ) ( 24 h , 18°C ) . Cell pellets were resuspended in 50 mM Tris-HCl pH 8 . 0 , 300 mM NaCl , 20 mM MgCl2 and 1 mM DTT and lysed in a French-press ( 3 cycles at 10 , 000 psi ) . The lysate was clarified by centrifugation ( 10 , 000 xg , 20 min , 4°C ) and membrane fractions collected by ultracentrifugation ( 185 , 000 xg , 1 h , 4°C ) . Membranes were homogenized and solubilized in 50 mM Tris-HCl pH 8 . 0 , 50 mM NaCl , 10 mM MgCl2 , 1 mM EDTA , 1 mM DTT , 0 . 25% ( w/v ) n-tetradecyl β-D-maltoside ( TeDM ) ( Anatrace ) . Membrane proteins were clarified by ultracentrifugation ( 100 , 000 xg 1 h , 4°C ) . The supernatant was loaded onto a Superose 6 10/300 column ( GE Healthcare ) equilibrated with 50 mM Tris-HCl pH 8 . 0 , 50 mM NaCl , 10 mM MgCl2 and 0 . 00002% ( w/v ) TeDM . Eluted fractions were collected and analyzed by western blot . For analysis of whole cell extracts by immunoblot , cells were grown to the stated growth phase . Cells equivalent to 1 ml at optical density OD600 = 1 . 5 were collected by centrifugation ( 9000 xg , 3 min ) and suspended in 50 μl lysis buffer ( 10 mM EDTA , 50 mM Tris-HCl pH 7 . 5 ) supplemented with 50 μg/ml lysostaphin ( Ambi Products ) and 1 mM PMSF . After incubation ( 37°C , 30 min ) , 50 μl 2x Laemmli buffer were added and samples boiled ( 10 min , 95°C ) . Depending on protein , 5–20 μl were loaded on an SDS-PAGE gel for subsequent immunoblot analysis . Culture supernatants were filter-sterilized with 0 . 25 μm syringe filters and precipitated with 5% trichloroacetic acid ( overnight , 4°C ) , washed with ice-cold acetone , and resuspended in 1x Laemmli buffer . Samples were boiled ( 10 min , 95°C ) and proteins equivalent to 0 . 4 ml ( for YtnP detection ) , 0 . 6 ml ( for EsxC ) or 1 . 6 ml culture supernatant ( for FLAG ) were resolved on 18% SDS-PAGE gels with a Tris-Tricine buffer system . Western blot was performed using standard protocols for semi-dry and wet-blot methods . Proteins were transferred to a PVDF membrane , blocked with 5% ( w/v ) non-fat dried milk powder in TBS-T , incubated with primary antibodies overnight , followed by 1 h incubation with secondary antibodies . Antibodies were used as follows: anti-mCherry ( 1:5000; BioVision ) , -GFP ( 1:5000; Takara ) , -FLAG ( 1:1000; Sigma-Aldrich ) , -EsxC ( 1:2000; [33] ) , -EssC ( 1:10 , 000; [33] ) , -EsaA ( 1:10 , 000; [33] ) , -EssB ( 1:4000 ) , -YtnP ( 1:1000; [60] ) , -GroEL ( 1:5000 , Sigma-Aldrich ) , -FloA ( 1:10000; [55] ) , chicken IgY-HRP ( 1:2 , 500; Life Technologies ) , -mouse IgG-HRP ( 1:10 , 000; Life Technologies ) and -rabbit IgG-HRP ( 1:20 , 000; Bio-Rad ) . Polyclonal antibodies to EsxC , EsaA and EssC were a kind gift of Tracy Palmer ( School of Life Science , University of Dundee , Scotland ) . Image processing was performed using ImageJ software [90] . Signals were quantified with the ImageJ Gel-Analyzing tool . For isolation of the crude membrane fraction , cells were grown in 50 ml liquid TSB medium overnight with vigorous agitation . Cells were collected by centrifugation ( 4000 xg , 15 min ) and washed in PBS . If required , cells were chemically crosslinked using amine-reactive crosslinker DSP ( dithiobis ( succinimidyl propionate ) ; Thermo Scientific ) prior to lysis . For crosslinking , cells were resuspended in 10 ml PBS supplemented with 1 mM DSP and incubated on ice for 2 h . Crosslinking reaction was quenched by adding Tris-HCl pH 7 . 5 to a final concentration of 20 mM ( on ice , 15 min ) . Cells were then collected and resuspended in 10 ml PBS lysis buffer ( PBS , 250 mM sucrose , 1 mM EDTA ) supplemented with 50 μg/ml lysostaphin , 1 mM PMSF followed by incubation ( 37°C , 10 min ) . Cells were lysed mechanically with glass beads in a fast-prep shaker ( twice 45 s each with 6 . 5 m/s ) ; debris and unbroken cells were removed by centrifugation ( 11 , 000 xg , 10 min , 4°C ) . The supernatant containing cytosolic and membrane proteins was ultracentrifuged ( 100 , 000 xg , 1 h , 4°C ) . Pelleted membrane proteins were resuspended in PBS + 250 mM sucrose and 10% ( v/v ) glycerol , flash-frozen in liquid nitrogen and stored at -80°C . To isolate detergent-resistant and -sensitive membrane ( DRM and DSM ) fractions , we used the Cellytic MEM protein extraction kit ( Sigma-Aldrich ) according to manufacturer’s protocols with minor modifications . Briefly , the crude membrane fraction was isolated as above and 1 μg total protein was mixed with kit lysis and separation buffer . After separating DRM from DSM proteins , DRM was washed three times and fractions precipitated with acetone , air-dried ( 5 min ) , suspended in 200 μl Laemmli buffer , and 10-20 μl loaded on an SDS-PAGE gel . His- or FLAG-tagged proteins were co-immunoprecipitated with Ni-NTA resin ( Qiagen ) or M2 FLAG-capture beads ( Sigma-Aldrich ) , respectively . For immunoprecipitation with His-tagged FloA , crude membrane fractions were isolated as above , solubilized in His-binding buffer ( 50 mM Tris-HCl pH 7 . 5 , 500 mM NaCl , 20 mM imidazole , 10% ( v/v ) glycerol , 1% ( v/v ) Tween-20 ) containing 0 . 25% DDM . Insoluble material was removed by centrifugation ( 100 , 000 xg , 1 h , 4°C ) . Solubilized protein ( 1 mg ) was incubated with 150 μl Ni-NTA resin and rotated ( 2 h , 4°C ) , washed twice in buffer W1 ( 50 mM Tris-HCl pH 7 . 5 , 500 mM NaCl , 20 mM imidazole , 10% ( v/v ) glycerol ) , twice in buffer W2 ( 50 mM Tris-HCl pH 7 . 5 , 500 mM NaCl , 50 mM imidazole , 10% ( v/v ) glycerol ) , and eluted with 200 μl elution buffer ( 50 mM Tris-HCl pH 7 . 5 , 500 mM NaCl , 1 M imidazole , 10% ( v/v ) glycerol ) . The eluted fraction was concentrated by TCA precipitation before SDS-PAGE and immunoblot . To capture FLAG-tagged proteins , crude membrane fractions were solubilized in 50 mM Tris-HCl pH 7 . 5 , 50 mM NaCl supplemented with 0 . 25% DDM . After removal of insoluble material ( 100 , 000 xg , 1 h , 4°C ) , a total of 4 mg protein was mixed with 20 μl pre-equilibrated beads . After rotation ( 2 h , 4°C ) , beads were washed four times in 50 mM Tris-HCl pH 7 . 5 , 50 mM NaCl with decreasing amounts of detergent ( two washes with 0 . 125% DDM , two washes with 0 . 02% DDM ) . Captured FLAG-tagged proteins were eluted by boiling beads in 50 μl Laemmli buffer , followed by SDS-PAGE and immunoblot . Blue Native PAGE ( BN-PAGE ) was performed with the Novex NativePAGE Bis-Tris system ( Life Technologies ) , used according to manufacturer’s protocols with minor modification . Briefly , crude membrane fractions were isolated as described above and solubilized ( overnight , 4°C ) in 1x Native PAGE sample buffer with 0 . 25% DDM . Insoluble material was removed by centrifugation ( 20 , 000 xg , 30 min , 4°C ) and 150 μg solubilized membranes were loaded on 3–12% gradient gels . After electrophoresis and blotting , PVDF membranes were fixed ( 15 min , 8% acetic acid ) , air-dried and rewetted in methanol before blocking and antibody incubation . For microscopy analysis , cells were harvested from liquid TSB culture , washed twice with PBS and fixed with 4% paraformaldehyde ( 5 min ) . After two additional washes in PBS , cells were spotted on an agarose pad ( 0 . 8% agarose in PBS ) to immobilize them for image acquisition . Epifluorescence microscopy was performed using a Leica DMI6000B microscope , equipped with a Leica CRT 60000 illumination system and DFC630FX camera . Raw images were processed and deconvoluted using image processing software Leica LAS AF v3 . 7 . For super-resolution stimulated emission depletion ( STED ) microscopy , immunofluorescent staining of the samples was guided by [91] . Δspa mutant cells were grown to mid-exponential phase and fixed with 4% paraformaldehyde for 30 min . After washing with PBS , cells were resuspended in GTE buffer ( 50 mM glucose , 20 mM Tris-HCl pH 7 . 5 , 10 mM EDTA pH 8 ) and mounted on 0 . 1% poly-L-lysine-coated coverslips . Samples were treated with 10 μg/ml lysostaphin in GTE for 5 min , washed with PBS and incubated in 70% EtOH for 10 min . Coverslips were air dried and blocked with 5% BSA for 30 min . Blocking solution was removed and the primary antibody ( anti-EssB 1:25 and anti-FloA 1:100 ) was incubated overnight in 0 . 5% BSA at 4°C . For each experiment a negative control was incubated without the primary antibody . Coverslips were washed with PBS and the Alexa conjugated secondary antibody was incubated for 2 h in the dark at room temperature ( anti-rabbit-Alexa546 1:250 , anti-chicken-Alexa488 1:500 , ThermoFisher ) . After washing with PBS , coverslips were air dried and mounted on microscope slides with 3 μl of Prolong Gold Antifade Mountant ( ThermoFisher ) . Slides were incubated in the dark overnight and images taken with a Leica SP8 TCS STED 3X system . Dual channel images were obtained exciting Alexa 546 and Alexa 488 at 561 nm and 488 nm respectively , with a pulsed white light laser depleting at 660 nm and 592 nm , respectively . Deconvolution of z-stacks was obtained with the software Huygens Professional and colocalization analysis was performed with the Costes’ threshold function of the JACoP Plugin for ImageJ [78 , 92] . Cohorts of 3-week-old BALB/c mice ( n = 6 ) were infected intravenously with 100 μl of suspension containing 106 CFU staphylococci in PBS . For anti-FMM treatment , 20 mg/kg zaragozic acid ( in PBS ) was administered intraperitoneally 30 min prior to challenge with staphylococci . The procedure was repeated twice ( days 14 and 28 ) . Mice were sacrificed after 40 days and blood samples collected by cardiac puncture . Serum EsxA-D and IsaA antibody titers were examined by ELISA . Briefly , recombinant His-tagged Esx proteins and IsaA were purified as above , diluted in PBS to 10 μg/ml final concentration and coated on 96-well plates ( Nunc , MaxiSorp ) . Plates were incubated ( overnight , 4°C ) and blocked with 5% BSA ( bovine serum albumin ) in PBS . Serum samples were diluted ( 1:50 in PBS ) , incubated on plates ( 1 h , 37°C ) ; plates were washed with PBS-T ( PBS + 0 . 05% Tween ) and incubated with anti-mouse IgM antibodies ( 1:5000; Life Technologies; 1 h , 37°C ) . After a final wash with PBS-T , 100 μl TMB ( 3 , 3’ , 5 , 5’-tetramethylbenzidine; Life Technologies ) was used to develop the reaction , which was terminated with 100 μl 1 N NaOH and absorbance measured at 450 nm . All experimental animal studies were approved by the Committee on the Ethics of Animal Experiments of the government of Lower Franconia ( 55 . 2-2532-2-57 ) and were in strict accordance with the guidelines for animal care and experimentation of German Animal Protection Law and EU Directive 2010/63/EU . Mice were housed in cages in standardized lighting conditions and had ad libitum access to food and water . All efforts were made to minimize suffering and animals were sacrificed at the end of the experiment by CO2 inhalation . Statistical analysis was performed with GraphPad Prism ( GraphPad software , version 7 ) using appropriate statistical methods as indicated in the figure legends . P-values ≤0 . 05 were considered significant . Pairwise comparisons were assessed using unpaired Student’s t-test . Analysis of variance ( ANOVA ) was performed to determine whether a group of means was significantly different from each other .
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The recently discovered functional membrane microdomains ( FMM ) of prokaryotic cells contain a protein homologous to the scaffold protein flotillin found in eukaryotic lipid rafts . It remains to be elucidated whether , like their eukaryotic counterparts , flotillin homolog proteins have a scaffold function in bacteria . Here we show that the Staphylococcus aureus flotillin FloA acts as a scaffold protein , to promote more efficient assembly of membrane-associated protein interacting partners of multi-enzyme complexes . In a case study , we provide biochemical evidence that FloA participates in assembly of the Type VII secretion system and thus contributes to S . aureus infective potential . Targeted dispersion of FMM-related processes using anti-FMM molecules opens up new perspectives for microbial therapies to treat persistent S . aureus infections .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
[
"medicine",
"and",
"health",
"sciences",
"enzyme-linked",
"immunoassays",
"protein",
"interactions",
"pathology",
"and",
"laboratory",
"medicine",
"eukaryotic",
"membrane",
"proteins",
"pathogens",
"microbiology",
"staphylococcus",
"aureus",
"membrane",
"proteins",
"physiological",
"processes",
"immunologic",
"techniques",
"cellular",
"structures",
"and",
"organelles",
"bacteria",
"bacterial",
"pathogens",
"research",
"and",
"analysis",
"methods",
"staphylococcus",
"medical",
"microbiology",
"proteins",
"microbial",
"pathogens",
"immunoassays",
"cell",
"membranes",
"biochemistry",
"protein",
"complexes",
"cell",
"biology",
"physiology",
"secretion",
"biology",
"and",
"life",
"sciences",
"organisms"
] |
2017
|
Flotillin scaffold activity contributes to type VII secretion system assembly in Staphylococcus aureus
|
Combinatorial therapy is a promising strategy for combating complex disorders due to improved efficacy and reduced side effects . However , screening new drug combinations exhaustively is impractical considering all possible combinations between drugs . Here , we present a novel computational approach to predict drug combinations by integrating molecular and pharmacological data . Specifically , drugs are represented by a set of their properties , such as their targets or indications . By integrating several of these features , we show that feature patterns enriched in approved drug combinations are not only predictive for new drug combinations but also provide insights into mechanisms underlying combinatorial therapy . Further analysis confirmed that among our top ranked predictions of effective combinations , 69% are supported by literature , while the others represent novel potential drug combinations . We believe that our proposed approach can help to limit the search space of drug combinations and provide a new way to effectively utilize existing drugs for new purposes .
In the past decades , targeted therapies modulating specific targets were considerably successful . However , recently , the rate of new drug approvals is slowing down despite increasing research budgets for drug discovery . One reason for this is that most human diseases are caused by complex biological processes that are redundant and robust to drug perturbations of a single molecular target . Therefore , the ‘one-drug-one-gene’ approach is unlikely to treat these diseases effectively [1] . Drug combinations can potentially overcome these limitations: they consist of multiple agents , each of which has generally been used as a single effective drug in clinic . Since the agents in drug combinations can modulate the activity of distinct proteins , drug combinations can help to improve therapeutic efficacy by overcoming the redundancy underlying pathogenic processes . In addition , some drug combinations were found to be more selective compared to single agents [2] , thereby reducing toxicity and side effects . Nowadays , drug combinatorial therapy is becoming a promising strategy for multifactorial complex diseases . For example , thiazide diuretics cause hypokalaemia when used to treat hypertension , while this side effect can be prevented by angiotensin-converting enzyme ( ACE ) inhibitors when they are used concurrently [3] . Saracatinib can overcome the resistance of breast cancer to trastuzumab when both drugs are used together , thereby improving the efficacy of trastuzumab [4] . Both glyburide and metformin are indicated for type 2 diabetes but work in different ways: glyburide reduces insulin resistance while metformin increases insulin secretion , and therefore the combination of these two drugs can improve therapeutic efficacy due to their complementary mechanisms [5] . Despite the increasing number of drug combinations in use , many of them were found in the clinic by experience and were not designed as such; the molecular mechanisms underlying these drug combinations are often not clear , which makes it difficult to propose new drug combinations . High-throughput screening was found to be useful to identify possible drug combinations [6]; however , it is impractical to screen all possible drug combinations for all possible indications since it leads to an exponential explosion as the number of drugs increases . Therefore , similarly to drug-target predictions [7] , [8] , [9] , [10] , a number of computational methods for predicting drug combinations have recently been developed . For example , stochastic search techniques were used to identify optimal combinations within a large parameter space [11] in an iterative way , but they only work on small drug sets due to the computational and experimental cost . Mathematical modeling was used to determine synergistic combinations by comparing dose-response profiles of single agents against those of drug combinations [12] , but it cannot explain the molecular mechanisms that underlie the drug combinations . Recently , in systems biology , both quantitative [13] and qualitative [14] models were introduced to investigate drug combinations based on the molecular networks or pathways possibly affected by the drugs . Although network analysis , in principle , can provide insights into the molecular mechanisms of drug actions [15] , the incompleteness of molecular networks and the scarceness of the corresponding kinetic parameters limit the application of such approaches to drug combinations considerably . In general , drugs are combined based on their mechanisms of action , which is characterized by the properties of drugs , such as their targets and pharmacology [16] , [17] . Taking this into account , we present here a novel concept for the prediction of drug combinations that integrates both molecular and pharmacological features associated with drugs . We treated drug combinations as combinations of their corresponding features , including their target proteins , therapeutic effects , and indication areas . Analysis on the drug combinations approved by the US Food and Drug Administration ( FDA ) demonstrates that there are some feature patterns enriched in known combinatorial therapies that are both predictive of new drug combinations and provide insights into the mechanisms underlying combinatorial therapy . We consequently predict new drug combinations based on feature patterns enriched in approved drug combinations . Subsequent targeted literature survey revealed that 69% of our predictions were previously reported as effective combinations although they are not approved yet , corroborating the predictive power of our proposed method . In addition , we identify several novel potential drug combinations . For example , we predict a novel combination of promethazine and ibuprofen that could be used as decongestant . Although experimental validation of each individual prediction needs to be provided in the future , we believe that our proposed approach can guide the selection of drug combinations to be tested experimentally .
In order to predict potential drug combinations , we first identified properties of approved pairwise drug combinations . A total of 184 pairwise drug combinations ( involving 238 drugs ) were approved by the FDA until November 2010 ( see Table S1 ) . We collected the molecular and pharmacological information associated with these drugs , including their target proteins and corresponding downstream pathways , medical indication areas , therapeutic effects as represented in the Anatomical Therapeutic Chemical ( ATC ) Classification System , and side effects . Here , each such property of a drug is called a feature , and a feature pair means two feature variables respectively associated with two different drugs . Therefore , a drug pair can be represented as a vector composed of feature pairs . For example , in case of the feature ‘target protein’ , drug 1 binds two proteins {p1 , p2} , drug 2 binds three proteins {p3 , p4 , p5} , the combination of drug 1 and drug 2 can be represented as following feature pairs: { ( p1 , p3 ) , ( p1 , p4 ) , ( p1 , p5 ) , ( p2 , p3 ) , ( p2 , p4 ) , ( p2 , p5 ) } , and similarly for other features . The numbers of drug combinations with available features are shown in Figure 1 ( drug combinations with pathway annotations are not shown because they are a subset of those with target annotations ) . Focusing on the ‘target protein’ feature , we investigated the drug combinations approved each year between 1984 and 2010 and observed that protein pairs targeted by newly approved combinations have often already been the targets of previous drug combinations . In total , 117 drug pairs approved as effective combinations until November 2010 have specific targets , when metabolizing enzymes and unspecific protein binders are excluded [16] . With the 16 drug combinations approved until 1983 as baseline , we found that as many as 76% ( 77/101 ) of drug combinations approved during 1984 and 2010 are directed against 6039 unique protein pairs ( 418 proteins ) that had been targeted previously by other combinations ( Figure 2 ( a ) ) . According to annotations from Gene Ontology [18] , we investigated the molecular functions of these 418 repeatedly used proteins ( Figure 2 ( b ) ) , and found that these target proteins cover a broad range of functions , which implies that drug combinations are not biased towards specific classes of protein targets . The above observations indicate that there are some target protein patterns enriched in previously approved drug combinations , which can be used to predict new drug combinations . Encouraged by the enrichment of certain protein patterns in approved drug combinations , we investigated the possibility to use the five drug features described above for predicting drug combinations . For this , each feature pair was assigned a score by comparing its frequency in effective drug combinations with that in the background ( see Materials and Methods , Eq . 1 ) , which consists of all possible pairs of drugs involved in effective combinations . The detailed scores for each feature pair can be found in Tables S2 , S3 , S4 . To evaluate the predictive ability of these features , we performed 5-fold cross-validation on the 184 drug combinations extracted from FDA orange book [19] ( see Materials and Methods ) . Figure 3 shows the receiver operating characteristics ( ROC ) curves obtained for different features , where the 5-fold cross-validation was repeated 10 times and the average was used as the final result ( detailed results can be found in Table S5 ) . Note that the performance of our method may be underestimated here because there are no true negative samples that are verified as invalid combinations . Furthermore , Figure 3 shows that all the features perform better than a random predictor , which implies that these properties can indeed help to predict new drug combinations . Among the features , the pathway feature was only weakly predictive , maybe because the simple association between drugs and pathways through target proteins does not sufficiently reflect the physiological context in which drugs work . One possible explanation for the observed poor predictive ability of the side-effect feature is that there are some common side effects associated with most drugs , thereby introducing much background noise . The performance of side effects may be improved if we consider only severe side effects associated with drugs . However , currently information on side-effect severity is unfortunately rarely available . The therapy information denoted by ATC code was found to be most predictive , probably due to the pharmacological information captured in the ATC code . Given the incomplete coverage of drug combinations by different features ( cf . Figure 1 ) , we integrated the three most predictive features ( i . e . therapy , target and indication area ) for predicting new combinations hereinafter ( see Materials and Methods , Eq . 3 ) . A correlation analysis of feature similarities shows that some correlations between features exist ( Figure S1 ) . However , distinct data sources complement each other in the prediction of drug combinations since the coverage of each feature is incomplete and the overlap between different features is low as shown in Figure 1 . By aggregating the three features where available , we aimed at improving the coverage of drug combinations compared with single features . For example , in 5-fold cross-validation , there are about 37 drug combinations in the validation set , among which 24 have ATC annotations while data integration by aggregating the three features can cover 34 drug combinations . In addition , the threshold above which data integration achieves the highest F1 score in cross-validation was used to make future predictions ( see Materials and Methods for details ) . Hereinafter , we set the threshold to 0 . 4 , corresponding to an F1 score of 0 . 17 . If a new drug pair has an integration score above this threshold , it will be treated as a putative combination . Note that here we choose to use a simple method ( maximization of the F1 score ) to predict whether a drug pair is an effective combination instead of other classifiers ( e . g . support vector machine or Bayesian classifier ) . The advantage of this method is that it is easy to interpret and avoids overfitting when dealing with small sample sizes and an imbalance between positive and negative examples ( i . e . all possible drug pairs except approved combinations ) in our datasets . By aggregating the three features that have been shown to be most informative above , we then predict possible effective combinations between marketed drugs . For this , pairwise drug combinations from the FDA orange book were used as training set to assign an enrichment score for each feature pair , and the integration of these features was used to screen all possible combinations between drugs involved in known combinations . To identify novel combinations , we excluded pairs already known to be valid combinations . In our dataset , we found that the mechanisms of drug combinations indicated for hypertension and contraception are relatively well studied . The drugs involved in combinations for hypertension mainly include thiazide diuretics , ACE inhibitors , angiotensin II antagonists , and beta-blocking agents , while the majority of available combinations are diuretic-based [20] . In the case of drug combinations for contraception , estrogen is mainly combined with hormonal contraceptives or progestogens . Therefore , the drugs involved in these two kinds of combinations were not considered here while making new predictions . As a result , we predict 16 possible drug combinations with confidence scores above the threshold of 0 . 4 ( see Benchmarking ) ( Table 1 ) ; the detailed feature patterns and their corresponding scores involved in predictions can be found in Table S6 . A literature survey showed that 11 out of our 16 predictions have already been reported to be effective in the literature ( Table 1 ) although they have not yet been approved by the FDA . For example , metformin and glimepiride are being explored as a combinatorial treatment for type 2 diabetes with different but complementary mechanisms , and have shown promising results [21] , [22] , [23] . Some of our 11 predictions are also supported by other sources beyond the scientific literature . For example , ciprofloxacin and loteprednol etabonate have been patented as an effective combinatorial treatment ( United States Patent 6359016 ) . In summary , the large overlap ( 69% ) between our predictions and those reported demonstrates that our proposed method effectively predicts new potential drug combinations . For the remaining 5 combinations , no literature support was found , implying that they are novel potential combination therapies . For example , we propose the combination of promethazine hydrochloride and ibuprofen based on the target combination ( HRH3 and ALOX12 ) to relieve nasal blockage . In our training dataset , ibuprofen is combined with three drugs , i . e . diphenhydramine , phenylephrine , and pseudoephedrine . However , promethazine share neither chemical similarity nor therapeutic effects with any of these three drugs . Promethazine is known as histamine receptor H1 antagonist and used as an anesthetic agent . Ibuprofen is a nonsteroidal anti-inflammatory drug ( NSAID ) used for relief of symptoms of arthritis and pain . These two drugs are predicted to be an effective combination mainly based on the inhibition of histamine receptor H3 ( HRH3 ) and arachidonate 12-lipoxygenase ( ALOX12 ) by promethazine and ibuprofen respectively . Promethazine inhibits histamine that in turn increases human airway epithelial paracellular permeability [24] , while 12-lipoxygenase deficiency was found to protect mice from allergic airway inflammation [25] . Based on their target information , we thus propose that promethazine and ibuprofen can be combined as decongestant . Furthermore , ciprofloxacin and budesonide were predicted to be combinable because of the therapeutic effect combination between anti-inflammatory agents ( coded as A07E ) and antibacterials ( coded by J01M ) . Ciprofloxacin is a synthetic antibiotic inhibiting DNA gyrase that is necessary to separate bacterial DNA , thereby blocking synthesis of bacterial DNA . Budesonide is an anti-inflammatory glucocorticoid steroid and is used to treat asthma . Recently , the composition of microbiota from the bronchial epithelium was found to be associated with asthma pathogenesis [26] . Therefore , a therapy that combines anti-inflammatory agents ( such as budenoside ) and antibacterials ( such as ciprofloxacin ) appears promising for treating asthma . In addition , fluticasone propionate was also predicted to be combinable with ciprofloxacin based on the therapeutic effect combination between corticosteroids ( coded by D07A ) and antibacterials ( coded by J01M ) . Fluticasone propionate is a synthetic corticosteroid and is indicated for asthma and allergic rhinitis . Based on their respective therapeutic information , the combination of these two drugs appears promising for the treatment of asthma . To gain more insights into the mechanisms of drug combinations , we investigated the enriched protein and therapy patterns that contribute to the integration score above the threshold of 0 . 4 as described above . For this , we constructed two drug-feature networks: a drug-protein network and a drug-therapy network for drug combinations that contain these enriched patterns . In these networks , two drugs were linked if they were documented as an effective combination and each drug was additionally linked to its features . The drug-protein network ( Figure 4 ) involving 59 drug combinations that contain enriched protein pairs shows that most of the drug pairs in the same combinations belong to the same general therapeutic category ( the first level of the ATC code ) , and the detailed network can be found in Dataset S1 . For two drugs that are found in approved combinations with a common third drug , we observed that they tend to share target proteins . Among 281 such pairs of drugs , 100 share target proteins - a significantly higher proportion than expected by chance ( p-value of 10−5 , Fisher's exact test ) . This phenomenon is more obvious for drugs sharing main targets . For example , five angiotensin II receptor antagonists - irbesartan , olmesartan medoxomil , valsartan , eprosartan mesylate and telmisartan - have type 1 angiotensin II receptor ( AG2S ) as main target , and all these five drugs can be combined with hydrochlorothiazide , a thiazide agent . This observation is not surprising since drugs that share the same target protein generally have similar pharmacology , thereby tending to be interchangeable with each other when combined with another drug for similar purposes . Furthermore , we ruled out the possibility that our identified protein patterns are a trivial consequence of high chemical similarity between drugs , which would in turn imply increased likelihood of targeting the same proteins [8] as well as similar pharmacology . By investigating the pairs of drugs in approved combinations with a third common drug , we found that only few of them have similar chemical structures . Among the 281 drug pairs , only 14 have chemical similarity larger than 0 . 6 , indicating that our approach captures much richer descriptions of drug combinations than chemical structure similarity alone . Furthermore , the feature patterns we identified here can help to explain the mechanisms of action of drug combinations . For example , hydrochlorothiazide , a diuretic drug , and methyldopa , an alpha-adrenergic agonist , are combined for the treatment of hypertension . Hydrochlorothiazide is very commonly combined with other drugs ( Figure 4 ) for lowering blood pressure by reducing the kidney's ability to retain water , thereby resulting in reduced blood volume . At the molecular level , hydrochlorothiazide inhibits carbonic anhydrase 2 ( CA2 ) , a member of an enzyme family that catalyzes the release of water molecules from carbonic acid . Methyldopa is an agonist of alpha-2 adrenergic receptors ( ADRA2A ) that mediates the sympathetic nerve activity , which in turn leads to reduced renin activity and lower blood pressure [27] . With knowledge about the physiological roles of drug targets , protein feature pairs are indeed helpful for explaining the mechanism underlying the combination therapies . The drug-therapy network ( Figure 5 ) constructed for 55 drug combinations containing enriched therapy patterns ( third level of the ATC code ) reveals that drugs in combinations do not necessarily have therapeutic effects in common ( the detailed network can be found in Dataset S2 ) . In fact , only 9 out of 55 drug combinations share therapeutic effects , indicating that the agents in the same combination tend to complement each other with respect to their specific therapeutic effects although they belong to the same general therapeutic category . Furthermore , we found that two drugs that are in approved combinations with a common third drug tend to have similar therapeutic effects . Among the drugs shown in Figure 5 , there are 205 such drug pairs , 77 of which share therapeutic effects indicating a significant enrichment ( p-value<10−6 , Fisher's exact test ) . For example , both lovastatin and simvastin can be combined with niacin for the treatment of dyslipidemia , where lovastatin and simvastin are peripheral vasodilators ( ATC code C04A ) and niacin is a lipid-modifying agent ( ATC code C10A ) . Analysis of the two drug-feature networks shown above demonstrates that our identified drug feature patterns can indeed provide insights into the mechanisms of action that underlie drug combinations . Our approach to predict drug combinations by representing drug combinations as combinations of their molecular and pharmacological features , including target proteins , therapies , and indication areas , not only led to the proposal of new drug combinations but also allowed mechanistic insights into existing ones . The overlap between our predictions and those reported in the literature demonstrate that this approach can effectively identify new drug combinations with the enriched feature patterns as an indicator for the mode of action underlying both marketed and predicted drug combinations . A limitation of this method is that it relies on the feature patterns enriched in approved drug combinations , which limits our predictions to those combinations that are similar to existing ones to some extent . Nevertheless , the new combinations are far from being obvious given the vast space of possible solutions . We believe that the methods proposed here can limit the search space of possible drug combinations as a guide for experimental screens and provide an alternative starting point towards repurposing old drugs .
All drug combinations were parsed from the FDA orange book [19] ( up to November , 2010 ) , and only pairwise combinations of prescription and over-the-counter ( OTC ) drugs were considered here . In total , our data set contains 184 drug combinations and 238 drugs . For drug target annotations , we used the compound-protein interactions from STITCH ( version 2 ) database [28] , requiring a confidence score higher than 0 . 7 and supported by either database or experiments . Furthermore , we combined this information with data collected from DrugBank ( version 3 ) [29] and therapeutic target database ( TTD , November , 2010 ) [30] . In particular , the targets from the TTD database were treated as main targets because they are annotated as primary therapeutic targets of drugs . We further investigated the pathways possibly affected by a drug through its target ( s ) , where pathway information was retrieved from the KEGG database [31] . For drug-pathway associations , each drug was associated with the pathways in which its target proteins are found . Drug indications were extracted from drug package inserts . Due to different names and synonyms associated with a disease , we mapped all disease names to Medical Subject Headings ( MeSH ) [32] terms by exact match , considering only the diseases branch and the psychiatry and psychology branch . Drug side effect information was retrieved from the SIDER database [33] . Drug therapy information was extracted from both STITCH and DrugBank , where the therapy information is represented as Anatomical Therapeutic Chemical ( ATC ) Classification System . Specifically , the third level of the ATC code was used here to represent the therapy information for each drug . Chemical similarity was calculated as the two-dimensional Tanimoto chemical similarity score with the Chemistry Development Kit [34] . The drug-protein network was constructed for drug combinations that contain enriched protein patterns , where two drugs were linked if they are an effective combination and each drug was also linked to its targets , and the same for the drug-therapy network . The networks were visualized with Cytoscape [35] . For each drug , the information extracted above can be used to describe the drug , including targets , indications , pathways , therapies encoded by ATC code , and side effects . For a drug pair and a feature F ( e . g . drug target ) , is associated with and is associated with , where and . Therefore , drug pair can be represented as feature pair . For each feature pair , a score is calculated as follows . ( 1 ) where is the number of times that feature pair occurs in effective drug combinations , and is the number of times that feature pair occurs in the background set of all possible pairwise combinations between drugs involved in known drug combinations . In this way , all the feature pairs can be ranked based on their scores and those ranked top are the feature pairs most strongly enriched in drug combinations . After getting the feature pairs for each drug combination , we used 5-fold cross-validation to evaluate their performance . In the 5-fold cross-validation , all the drug combinations were randomly split into five groups with similar size without overlap , four of which were used as training set and used to calculate the enrichment score for each feature pair while the remaining group was used as the validation set to evaluate the performance of the feature pairs , and the procedure was repeated for five times . The F1 score defined below was adopted as performance index . ( 2 ) where precision is the ratio of true positives in predicted positives and recall is the ratio of true positives that can be predicted correctly . The threshold above which the highest F1 score was achieved in cross-validation was used to make future prediction . We predict a drug pair as an effective combination if its score is above the threshold . Since the annotations from different data sources are incomplete , the feature pairs from distinct data sources were aggregated to calculate a confidence score about whether two drugs can be combined with the hope that information from distinct data sources can complement each other . For a drug pair , the confidence score is defined as follows . ( 3 ) where is the confidence or probability of drug combining with drug , is the confidence that drug can be combined with drug based on feature pairs from data source k ( e . g . target ) , and if the drug pair have no corresponding information from data source k . The feature confidence is defined as follows . ( 4 ) where is the precision obtained with feature pairs whose scores ( ) are larger than that of feature pair , and the maximum is used because there are possibly multiple feature pairs for one drug pair from data source .
|
The combination of distinct drugs in combinatorial therapy can help to improve therapeutic efficacy by overcoming the redundancy and robustness of pathogenic processes , or by lowering the risk of side effects . However , identification of effective drug combinations is cumbersome , considering the possible search space with respect to the large number of drugs that could potentially be combined . In this work , we explore various molecular and pharmacological features of drugs , and show that by utilizing combinations of such features it is possible to predict new drug combinations . Benchmarking the approach using approved drug combinations demonstrates that these feature combinations are indeed predictive and can propose promising new drug combinations . In addition , the enriched feature patterns provide insights into the mechanisms underlying drug combinations . For example , they suggest that if two drugs share targets or therapeutic effects , they can be independently combined with a third common drug . The ability to efficiently predict drug combinations should facilitate the development of more efficient drug therapies for a broader range of indications including hard-to-treat complex diseases .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] |
[
"biology",
"computational",
"biology"
] |
2011
|
Prediction of Drug Combinations by Integrating Molecular and Pharmacological Data
|
Unlike many wild grasses , domesticated rice cultivars have uniform culm height and panicle size among tillers and the main shoot , which is an important trait for grain yield . However , the genetic basis of this trait remains unknown . Here , we report that DWARF TILLER1 ( DWT1 ) controls the developmental uniformity of the main shoot and tillers in rice ( Oryza sativa ) . Most dwt1 mutant plants develop main shoots with normal height and larger panicles , but dwarf tillers bearing smaller panicles compared with those of the wild type . In addition , dwt1 tillers have shorter internodes with fewer and un-elongated cells compared with the wild type , indicating that DWT1 affects cell division and cell elongation . Map-based cloning revealed that DWT1 encodes a WUSCHEL-related homeobox ( WOX ) transcription factor homologous to the Arabidopsis WOX8 and WOX9 . The DWT1 gene is highly expressed in young panicles , but undetectable in the internodes , suggesting that DWT1 expression is spatially or temporally separated from its effect on the internode growth . Transcriptomic analysis revealed altered expression of genes involved in cell division and cell elongation , cytokinin/gibberellin homeostasis and signaling in dwt1 shorter internodes . Moreover , the non-elongating internodes of dwt1 are insensitive to exogenous gibberellin ( GA ) treatment , and some of the slender rice1 ( slr1 ) dwt1 double mutant exhibits defective internodes similar to the dwt1 single mutant , suggesting that the DWT1 activity in the internode elongation is directly or indirectly associated with GA signaling . This study reveals a genetic pathway synchronizing the development of tillers and the main shoot , and a new function of WOX genes in balancing branch growth in rice .
Rice is one of the most important crops in the world and feeds more than half of the world population . Thousands of years of domestication and breeding have selected many desirable traits in rice , including a plant architecture optimized for grain yield and quality . A mature rice plant has a main shoot and several lateral branches ( tillers ) , with each bearing an inflorescence ( panicle ) at the apex . Despite their differences in bud initiation time , the main shoot and all tillers grow to a uniform height and flower at the same time [1] . This is in contrast to its wild progenitor ( Oryza rufipogon ) and most wild grasses , which have dominant main shoot growth . The uniform growth of tillers and the main shoot in many cultivated cereal crops , such as rice , wheat , barley , is an important agricultural trait because it ensures not only uniform grain size , but also synchronized maturation time and a uniform panicle layer which facilitates harvesting [2] . However , the genetic basis underlying the uniform development of tillers and the main shoot in these crops remains unknown . The height of the rice culm is mainly determined by the length of the uppermost four or five internodes , which elongate rapidly after the initiation of reproductive growth . Internode elongation involves cell division in the intercalary meristem and subsequent cell elongation in the upper elongation zone [3] . Dwarf and semi-dwarf traits have increased rice yield by improving the harvest index and reducing lodging . Previous studies have demonstrated that gibberellin ( GA ) and brassinosteroid ( BR ) are two major hormones that promote internode elongation [4] , [5] . However , none of the previously isolated rice mutants disrupt the uniform growth of the main shoot and tillers . Members of the WOX8/9 subclade of homeobox ( WOX ) gene family have been shown to play important roles in region-specific transcription programs during many developmental processes . STIMPY/WOX9 and STIP-LIKE ( STPL , WOX8 ) are indispensable for embryonic patterning , shoot apical meristem maintenance , and cell proliferation during embryonic and post-embryonic development , mutants of WOX8/9 display reduced cell division and lethality during embryo and seedling developmental stages in Arabidopsis [6]–[8] . Homologs of WOX8/9 in petunia and tomato plants were reported to play important roles in shaping inflorescence architecture by promoting the separation of lateral inflorescence meristems from the apical floral meristem [9] , [10] . Here , we show that DWT1 , a homolog of Arabidopsis WOX8/9 , is required for the balanced growth of tillers and the main shoot in rice . The dwt1 mutant exhibits an altered architecture with reduced height of tillers and over-growth of the main shoot panicle . Functional analysis revealed that DWT1 acts through a non-cell-autonomous mechanism to promote tiller growth downstream of SLR1 . This finding reveals a DWT1-mediated genetic pathway synchronizing the development of tillers and the main shoot in rice .
We recently identified a mutant , dwarf tiller1 ( dwt1 ) , which exhibits disruption of the synchronized growth of tillers and the main shoot at maturity [11] . Genetic analysis showed that the dwt1 mutant is a recessive allele based on the observations that the F1 progeny of backcross displays the wild-type phenotype and F2 plants segregate about 3∶1 for normal and mutant plants [11] . Unlike wild-type plants , all dwt1 tillers form shorter culm and smaller panicles ( Fig . 1A ) , but most dwt1 main shoots exhibit similar height at maturity as the wild type ( Fig . 1B , E ) . Although all the dwt1 main shoots exhibited a normal height at maturity , 26% of the main shoots had defects in the second internode elongation and about 7% of the main shoots had shorter length of both the second and third internodes compared with the wild type ( Fig . 1B , E ) . However a compensatory elongation of the other internodes , especially the first internode retained the same height of the dwt1 main stem as wild-type plants ( Fig . 1B , right 1 ) . The degree of dwarfism varied among the tillers of the same dwt1 plant ( Fig . 1 C ) . About 15% of dwt1 tillers displayed a shorter length for only the second internode ( 22/143 ) ( dm-type , Fig . 1C , D and E ) . About 36% of the tillers ( 51/143 ) had a shorter length for both the second and third internodes ( Fig . 1C , D , and E ) , and 37% of the tillers ( 53/143 ) had a shorter length for the second , third and fourth internodes ( d6-type , Fig . 1C , D and E ) [12] . Even though the tiller height is dramatically reduced , the tiller number is not obviously affected in the dwt1 mutant , and both the wild type and dwt1 plants have about eight tillers . In addition , the short internodes appear twisted and distorted in the dwt1 mutant at the mature developmental stage ( Fig . 1D ) . In contrast to the defective internode development , the dwt1 main shoot develops a larger and denser panicle compared with that of the wild type ( Fig . 1F ) . The average number of primary branches and secondary branches on dwt1 main shoot panicles increases by 119% and 193% , respectively , compared to the wild-type main shoot ( Table S1 ) . Consequently , the average number of spikelets in dwt1 main shoots increases by about 162% compared to the wild type , and the weight of 1000 grains from the dwt1 main shoot increases by approximately 107% compared to that of the wild-type main shoot ( Table S1 ) . On the other hand , the seed weight of 1000 grains from the dwt1 tillers decreases compared with that of wild-type tillers ( Table S1 ) . These observations suggest that dwt1 has defects in growth uniformity between the main shoot and tillers , and its main shoot appears to be dominant compared to tillers . Suppression of lateral branches by the apex of the main shoot is a common phenomenon in plants , known as apical dominance . Elimination of apical dominance by decapitation usually promotes axillary bud outgrowth [13] . To determine whether the dwt1 phenotype is related to apical dominance , the main shoot and each tiller of dwt1 at the vegetative stage were separated and replanted individually in the paddy field . Each of the regenerated plants from the main shoot or tillers of dwt1 plants developed an architecture similar to dwt1 exhibiting dwarf tillers but a normal main shoot ( Fig . 2A and B ) . In addition , when the main shoot of the dwt1 plant was removed before flowering transition , the first formed tiller became a dominant shoot while subsequent tillers still remained dwarf . However , decapitation after the initiation of reproductive stage did not reestablish the main shoot dominance . Therefore we conclude that dwt1 mutant plants have a characteristic main shoot dominance , which can be partially released by removing the developed main shoot during vegetative growth . Rice internode elongation involves cell division followed by cell elongation [3] . Because the un-elongated internodes in dwt1 mutants are dramatically shorter ( 0 . 4±0 . 2 cm , n = 30 ) compared with wild-type plants ( 14 . 1±1 . 0 cm , n = 30 ) ( Fig . 3A and B ) , we performed longitudinal sections of the second internodes which display obvious defective elongation in the mutant . The results show that the cells in the wild type are slender and elongated , with a cell length of about 172 . 6±36 . 2 µm ( n = 30 ) ( Fig . 3C and E ) . However , dwt1 cells in the shorter internodes appear flat with a longitudinal length of about 20 . 9±3 . 7 µm ( n = 30 ) ( Fig . 3D and E ) . Furthermore , the dwt1 second un-elongated internode had a dramatic reduction in cell number per internode ( 247±35 , n = 5 ) in the longitudinal direction compared with the wild type ( 1077±90 , n = 5 ) ( Fig . 3F ) , suggesting that dwt1 has defects in both cell proliferation and cell elongation along the longitudinal direction in the tiller internodes . On the other hand , the transverse size of the un-elongated internodes in dwt1 is abnormally larger than that of the wild type ( Fig . S1 ) . The transverse section of wild-type internodes appeared a round shape with a perimeter of about 9 . 8±0 . 2 mm ( n = 10 ) ; however , the dwt1 un-elongated internodes exhibited an elliptic shape with a perimeter of about 11 . 2±0 . 3 mm ( n = 10 ) . The increase of the width in dwt1 results from the increase of both the cell number and cell size in radial direction . The radial cell number in un-elongated internodes of dwt1 was about 62 cells along the major axis and 45 cells along minor axis , which is more than that in the wild type ( 40 cells , n = 10 ) . To identify the DWT1 gene , we mapped the dwt1 locus to a 22 kilo-base ( kb ) region on the BAC clone OSJNBb0063G05 ( Fig . 4A ) [11] . Three annotated open reading frames in this region were sequenced , and a single base pair deletion was observed in one of the genes , LOC_Os01g47710 ( Fig . 4B ) , which was predicted to encode a putative WUSCHEL-like homeobox ( WOX ) protein [14] . This deletion results in a frame shift that replaces the C-terminal 279 residues with 162 new amino acids , downstream of the homeobox domain ( Fig . 4B ) . We transformed dwt1 plants with a 6 . 7-kb genomic sequence of LOC_Os01g47710 . All nine transformed plants exhibited a wild-type appearance with normally elongated internodes and uniform panicle size ( Fig . 4C , D ) , confirming that the loss-of-function mutation of this gene is responsible for the dwt1 phenotype . Furthermore , the DWT1 protein fused with yellow fluorescent protein ( YFP ) is localized in the nucleus when transformed into tobacco leaves ( Fig . 4E–H ) , consistent with the prediction of a transcription factor of WOX protein [15] . The transcribed region of the DWT1 gene was revealed by comparing the genomic sequence with the released EST clone ( OSIGCFA219G01 ) from the Rice Indica cDNA Database ( RICD , http://www . ncgr . ac . cn/ricd/ ) , and with sequences of our reverse transcription ( RT ) -PCR products . The predicted wild-type DWT1 protein is 533 amino acids in length and contains a conserved WUSCHEL ( WUS ) -like homeobox domain ( amino acids 65 to 132 Fig . S2 ) , which shares the highest sequence similarity with WOX8 and WOX9 proteins in Arabidopsis [14] . In addition to the homeobox domain , DWT1 also shares conserved N-terminal and C-terminal domains with WOX8/9-related proteins , but not with WUS ( Fig . S2 ) . Previous studies showed that the C-terminal domain might contribute to the dimerization of WUS proteins in Arabidopsis and snapdragon [16] , [17] . The C-terminal deletion of DWT1 protein might disturb the dimerization of the DWT1 protein . Phylogenetic analysis showed that the WOX8/9 subfamily of dicots and monocots are divided into two clades , and this subfamily is believed to be generated by gene duplication after the evolutionary separation of dicots and monocots ( Fig . S3 ) [18] . In dicot plants , WOX8 and WOX9 proteins apparently arose by gene duplication from an ancestral gene . The EVERGREEN ( EVG ) and SISTER OF EVERGREEN ( SOE ) from petunia [9] , and COMPOUND INFLORESCENCE in tomato [10] are more similar to STIP than STPL of Arabidopsis . In rice , there are three predicted WOX9 homologs , DWT1 , DWT-LIKE 1 ( DWL1 , LOC_Os07g34880 ) and DWT-LIKE 2 ( DWL2 , LOC_Os05g48990 ) . DWT1 and DWL1 are separated from DWL2 in two subclades with homologs of maize . These gene duplications suggest that after the divergence of monocots and eudicots , these subgroups in the WOX8/9 clade have been expanded , possibly with functional diversification ( Fig . S3 ) . To understand the evolutionary role of DWT1 , we did sequence analysis of DWT1 in cultivated rice and wild rice strains . Investigation of the SNP dataset of 508 indica and 341 temperate japonica rice cultivars [19] revealed 14 SNPs in the non-coding sequence and no SNP in the coding sequence of a 4 . 3-Kb DWT1genomic region . By contrast , we observed 4 nucleotide variations between these cultivated rice and 11 wild rice strains in the coding region . A 2-bp nucleotide change in exon 2 , CA ( 1284–1285 ) in cultivated rice changed to GC in 11 wild rice strains ( 6 Oryza . rufipogon and 5 Oryza . nivara strains ) , causing the amino acid change from glutamine to alanine ( Fig . S4 ) . Whether this sequence variation causes rice morphological difference between cultivated rice and wild rice remains to be elucidated . Quantitative reverse transcription ( qRT ) -PCR analysis revealed the expression of DWT1 mRNA in the callus , young panicle , young embryo , root tip and coleoptile , but not in the mature leaves , and mature spikelets ( Fig . 5A ) . A higher expression level of DWT1 was observed in panicles of tillers than that of the main shoot ( Fig . 5B ) . Notably , no obvious expression signal of DWT1 was detectable in the wild-type internodes where the dwt1 mutation causes the most severe phenotype ( Fig . 5A ) . Furthermore , in situ hybridization confirmed no detectable expression of DWT1 in the elongating internode ( Fig . 5C ) , but high DWT1 expression in the panicle meristem including the primordia of primary and secondary branches , floral meristem , and leaf primordia surrounding these meristems ( Fig . 5E–G ) . Consistent with qRT-PCR results , DWT1 transcripts were observed in the young embryo 10 days after fertilization ( Fig . 5I ) , and in the endodermis and exodermis layers of the elongation zone in root tip ( Fig . 5K ) . To further understand the function of the rice WOX8/9 clade , we analyzed the tissue-specific expression pattern of two DWT1 homologs . According to rice microarray data ( http://bar . utoronto . ca/efprice/cgi-bin/efpWeb . cgi ) , DWL2 has high expression level in the inflorescence meristem and embryo , but not in the internode . qRT-PCR analysis confirmed the expression of DWL1 and DWL2 in the panicle meristem but not in the internode , and no significant expression change in the dwt1 mutant ( Fig . S5 ) . The overlapping expression pattern of DWT1 and its two homologs suggest that the three rice WOX8/9 homologs may have similar function as DWT1 . Both qRT-PCR and in situ hybridization did not detect the transcripts of DWT1 in the internode , strongly suggesting a non-cell-autonomous manner of DWT1 function . One possibility is that DWT1 acts as a mobile protein signal , moving from the panicle meristem to the underneath internode . Alternatively , DWT1 may promote the production of a mobile signal in the panicle meristem . To test these possibilities , we detected the DWT1 protein localization in the transgenic plants harboring DWT1 protein fused with YFP ( yellow fluorescence protein ) , driven by the native DWT1 promoter . We could only observe the DWT1 protein in the young panicle but not in elongating internodes ( Fig . 5M–R ) . Consistently , western-blot only detected DWT1 proteins in panicle meristem tissues ( Fig . 5S ) , suggesting that DWT1 may regulate the internode elongation by producing a mobile signal in the panicle . To understand the molecular mechanism of DWT1 in regulating rice internode development , we analyzed gene expression changes of the un-elongated second internode of dwt1 tillers during the elongation stage using the Affymetrix rice genomic arrays . Compared with the wild type , a total of 476 genes were up-regulated and 499 genes down-regulated in dwt1 after statistical analysis ( >threefold change; P<0 . 001; Table S2 ) . Functional analysis by gene ontology ( GO ) enrichment showed that eleven GO categories were enriched from the differential expressed genes ( Fig . 6A , Table S3 ) . The most enriched one was “microtubule-based movement” , which contains genes encoding kinesins , tubulins and other cytoskeleton related proteins . Kinesins belong to a class of microtubule-associated proteins with a motor domain for binding and moving along the microtubules . Some of these kinesin members , including AtKINESIN5 ( ATK5 ) , PHRAGMOPLAST ORIENTING KINESIN 1 and 2 ( POK1 , POK2 ) , KCA1 and KCA2 are implicated in multiple mitosis-related processes , such as spindle formation , phragmoplast formation and cell plate formation [20]–[22] . Moreover , most of tubulin proteins differentially expressed are beta-tubulins , among which OsTUB6 was previously reported as a component of the spindle skeleton in mitosis [23] . In addition , the enriched GO categories “DNA replication initiation” , “DNA metabolic process” and “cell cycle” from dwt1 microarray data are directly related to cell division ( Fig . 6A ) . Furthermore , reduced expression of OsCYCA3;1 , CYCLINB2;2 ( CYCB2;Os2 ) , CYCLIN-DEPENDENT KINASE B2;1 ( CDKB2;1/CDC2OS3 ) , homologs of CELL DIVISION CONTROL 6 ( CDC6 ) , MINI CHROMOSOME MAINTENANCE ( MCM3 ) and E2 PROMOTER-BINDING FACTOR ( E2F ) , OsEXPA16 and OsXTH28 were confirmed by qRT-PCR in dwt1 ( Fig . 6 B ) , which closely correlates with the microarray data ( Pearson correlation = 0 . 96 ) ( Table S2 , S4 ) . CDC6 and MCM3 are involved in the DNA replication under the control of the E2F transcription factor in Arabidopsis [24] , [25] . OsCYCA3;1 encodes a type-A cyclin , a homolog of tobacco Nicta;CYCA3;2 , CYCB2;Os2 encodes a type-B cyclin , and CDKB2;1/CDC2OS3 encodes a cyclin-dependent kinase , which are implicated in cell cycle control [26] , [27] . OsEXPA16 encodes a α-expansin protein known to increase cell wall extensibility [28] , and OsXTH28 encodes a homolog of XTH28 , a xyloglucan endotransglycosylase involved in cell growth in stamen filament development in Arabidopsis [29] . In plants , cytokinin plays a central role in promoting cell division . Cytokinin response is positively regulated by the cytokinin-inducible type-B Response Regulators ( RRs ) but negatively regulated by the type-A RRs [30] . Three type-A RRs: OsRR6 , OsRR9 , OsRR10 , were upregulated in the shortened internode of dwt1 ( Table S5 , Fig . S6 ) . In addition , the expression of OsCYTOKININ OXIDASE 4 ( OsCKX4 ) and OsCKX9 encoding cytokinin-inactivating enzymes was elevated in dwt1 ( Fig . S6 ) . These results suggest that altered cytokinin signaling and reduced amount of active cytokinin may contribute to the reduced activity of cell division in dwt1 . Gibberellin ( GA ) is a crucial phytohormone in promoting the stem elongation in rice [31] , [32] . We observed that the expression level of OsENT-COPALYL DIPHOSPHATE SYNTHETASE 1 ( OsCPS1 ) encoding a GA biosynthetic enzyme was reduced , and that of OsGIBBERELLIN 2-OXIDASE 1 ( OsGA2OX1 ) encoding a GA-deactivating enzyme was upregulated in the un-elongated internode of dwt1 ( Table S5 ) . In addition , four genes encoding GA20-oxidases ( OsGA20OX1 , OsGA20OX2 , OsGA20OX3 , and OsGA20OX4 ) , which are feedback inhibited by GA signaling , displayed increased expression in dwt1 ( Fig . 7 ) . Therefore the developmental defects of dwt1 internodes may be associated with altered GA homeostasis or signaling To further test whether dwt1 has a defect in GA synthesis or signaling , we treated the wild-type and dwt1 mutant plants with active GA3 after the transition to the reproductive stage . Unlike the normal response to GA of the wild-type internodes and the normal internodes in dwt1 , the defective internodes of dwt1 showed little response to GA ( Fig . 8A , B and C , Fig . S7 ) . Consistent with the reduced morphological response , the expression levels of OsGA20OX1 , OsGA20OX2 , OsGA20OX3 , and OsGA20OX4 were less responsive to GA treatment in dwt1 un-elongated internodes than normal ones of the wild type ( Fig . 8D ) , suggesting a defect in GA signaling in these internodes . SLENDER RICE1 ( SLR1 ) is a nuclear-localized DELLA-domain protein that functions as a central suppressor of GA signaling in rice [33] , [34] . Compared with the wild type , slr1 mutants display a quick elongation of the basal internode at the seedling stage because of the constitutively activated GA response . To determine the genetic relationship between SLR1 and DWT1 , we crossed dwt1 with slr1 , and identified the double mutant by genotyping ( see methods ) . The slr1 dwt1 double mutant showed a subset of twisted and shorter internodes similar to dwt1 plants ( Fig . 8E , Fig . S8 C , F ) , while other internodes elongated as those of slr1 mutant ( Fig . S8 A , B , D , E ) , suggesting that the DWT1-dependent activity is required for the internode elongation in the absence of SLR1 .
The WOX genes form a plant specific clade of the homeobox transcription factor superfamily . Studies in dicot plants indicate that the WOX8/9 subclade genes play important roles in a wide range of developmental processes , such as embryonic patterning , stem-cell maintenance , inflorescence architecture development and organ formation [8] , [9] , [10] , [15] , [36] . Rice has three WOX members within the WOX8/9 subclade , and these members were assumed to be generated by duplication after the divergence of monocots from dicots [14] . Based on the functional analysis of DWT1 in this study , we hypothesize that DWT1 plays a key role in controlling the developmental uniformity of main shoot and tillers and may have been selected during rice domestication . The activated tiller buds develop their own adventitious roots , and thus gain a certain degree of independence from the main shoot . It is not clear whether the tiller development is also under the control of the main shoot after this transition . The dwt1 mutant shows not only dwarfed tillers bearing smaller panicles , but also an enhanced growth of the panicle on the main shoot , suggesting an enhanced apical dominance . It is also possible that a defect in tiller growth reduces the competition against the main shoot , resulting in quicker main shoot growth compared to wild type . The individual dwt1 tiller separated from the main shoot is able to grow into a whole rice plant with a near normal main shoot and dwarf tillers , suggesting that DWT1 suppresses the apical dominance in rice . Alternatively , the higher expression level of DWT1 in tiller panicles than the main shoot panicle may provide an enhanced growth vigor to the tillers , or a higher level of growth-promoting signal to the tiller internodes , which is essential for successful competition against the main shoot . It has been demonstrated that TEOSINTE BRANCHED 1 ( TB1 ) is the major contributor to the enhanced apical dominance during the domestication of maize . One tb1 allele with a transposon inserted in the regulatory region was selected from the maize wild ancestor teosinte . The inserted retro-element causes a two-fold increase in TB1 expression , which is strong enough for the transformation of a highly branched architecture of teosinte to the modern maize architecture [37] . It is not clear whether DWT1 is a key target being selected during the domestication of rice . Sequence analysis revealed an amino acid variation in the C-terminus of DWT1 coding region between cultivated rice and wild rice strains ( Fig . S4 ) . The C-terminal domain may be required for the homo- or heterodimerization of the DWT1 protein . The effect of this sequence variation on DWT1 function remains to be elucidated . Lateral branch development involves bud formation , bud outgrowth and branch growth . In most plants , the early events of lateral bud formation and outgrowth are inhibited by the apex of the main shoot , due to the apical dominance . How growth vigor of the branch is influenced by the main shoot is less understood . Apical dominance is mediated by the biosynthesis and transport of the phytohormone auxin [38] . Auxin is transported basipetally from the apical bud and inhibits the outgrowth of lateral buds . It is proposed that the repressive effect of auxin is mediated by secondary messengers . Strigolactone is synthesized in both the roots and the shoots and transported acropetally , and it plays an important role in repressing bud growth in several species , such as pea , petunia , Arabidopsis and rice , possibly by reducing auxin transport in the main shoot [39] . Cytokinin , mostly synthesized in the root and transported acropetally , is able to initiate the outgrowth of lateral buds [40]–[43] . Several WOX genes , including the DWT1 homologs in Arabidopsis , have been shown to be able to directly regulate genes involved in auxin and cytokinin biosynthesis , homeostasis , transportation and signaling . But none of them have been reported to be required for the main shoot dominance . The dwt1 mutant does not show an obvious difference in tiller number compared with the wild type , indicating that the initiation and outgrowth of tiller buds are not affected . Accordingly , no significant expression change of genes related to strigolactone biosynthesis and signaling pathway was observed in the leaf , root and basal shoot of dwt1 ( Fig . S9 ) . In addition , the expression levels of cytokinin-related genes , OsRR6 , OsRR9 , OsRR10 , OsCKX4 and OsCKX9 , are altered in the internodes , but not in the root or basal shoot of dwt1 ( Fig . S10 ) , suggesting that dwt1 does not have a defect in cytokinin signaling during lateral branch initiation and outgrowth . Thus , we propose that DWT1 enhances tiller growth vigor at late stages after the outgrowth of tiller buds . The higher expression level of DWT1 and more severe phenotypes in tillers than in main stem suggest that the differential DWT1 activity counter balance the weaker growth vigor of the tillers . The main shoot enters reproductive growth a bit earlier than tillers , thus may gain growth priority over tillers . The observation that removal of main shoot releases suppression of the next tiller in dwt1 suggests that DWT1 provides a competitive advantage to the younger tillers . The low percentage of un-elongated internodes observed in dwt1 main shoot suggests a minor but also positive function of DWT1 in promoting internode elongation in the main shoot , consistent with the lower level of DWT1 expression in main shoot panicles compared to tillers . It is likely that DWT1 is required for promoting internode growth and the higher level of DWT1 expression in tillers enhances the growth vigor to overcome the main shoot dominance . In addition , there may be an as yet unknown main shoot factor specifically responsible for establishing the main shoot dominance independent of DWT1 function , as a compensatory elongation of other internodes was observed in main shoots with an un-elongated internode . The phenotype of reduced internodes of dwt1 tillers seems similar to the dwarfism of mutants with defective synthesis or signaling of GA or brassinosteroids ( BRs ) [44]–[48] . However , no obvious expression change of genes relative to BR biosynthesis , metabolism and signaling pathways was seen in dwt1 ( Table . S4 ) . In addition , BR related mutants display dark green , rugose , and erect leaves [45]–[47] , which are not observed in dwt1 . In addition , none of the previously reported BR-related mutants have distorted internodes or a distinction between main shoot and tillers , suggesting that the elongation defect of dwt1 internodes is unlikely due to BR deficiency . On the other hand , the un-elongated internodes and expression of GA20OX genes showed insensitivity to GA treatment in dwt1 , suggesting a defect in GA response . The slr1 mutation was unable to suppress the dwarf-tiller phenotype of dwt1 , indicating that the action of DWT1 on internode elongation , possibly mediated by a mobile signal , is downstream , or independent of SLR1 . The dwarfed tillers of dwt1 show reduced cell division and cell elongation . In the shorter internode of dwt1 mutant , not surprisingly , a set of cell cycle related genes were observed to have decreased expression , while the expression of the negative regulators of cytokinin signaling and some cytokinin-inactivating enzymes were increased . Both type-A RR genes and CKX genes have been shown to function as negative regulators in cytokinin signaling and cell division [49] . OsWOX11 directly represses one of the type-A RR genes , RR2 , leading to enhanced cytokinin signaling and crown root development in rice [50] . WUS directly represses the transcription of several ARABIDOPSIS RESPONSE REGULATOR ( ARR ) genes to positively regulate stem cells in Arabidopsis [51] . As no DWT1 expression was detectable in the elongating internode , it is quite possible that the DWT1 may indirectly repress the expression of type-A RRs by promoting a mobile signal from the apical region where DWT1 is expressed . Alternatively , given the repressing effect of GA on the expression of type-A ARR genes and activation of type-A gene ARR5 by GA response inhibitor SPINDLY ( SPY ) in Arabidopsis [52] , the change of cytokinin pathway in dwt1 mutant may result from the secondary effect of abnormal GA signaling . DWT1 is expressed in the panicle meristem at stages when the 2nd , 3rd and 4th internodes start to elongate [53] . Consistently , only the elongation of internodes at these positions is affected in the dwt1 mutant , suggesting that DWT1 has a spatiotemporal specific function . The frequency of un-elongated internodes inversely correlated with the distance from the apical meristem . The loss of the function of the apically expressed DWT1 leads to elongation defects in 92% of the second internodes , 75% of the third internodes and only 39% of the fourth internodes . It is clear that internodes closest to the apical meristem were most affected , while internodes far away were less affected , implicating a signal gradient emanating from the apical meristem which determines the cell division and elongation potential of internodes underneath . The activation of DWT1 at early reproductive stage may be required for preventing the production of a mobile growth inhibitor , which prevents the premature elongation of the internodes , or may promote the production of a growth promotion signal . Such alteration may enhance the responsiveness of cells in the upper internodes to GA or cytokinin . A function in inter-organ coordination has recently been shown for a receptor-like kinase homologous to Arabidopsis CLAVATA1 , named HYPERNODULATION ABERRANT ROOT FORMATION1 ( HAR1 ) . HAR1 is an important regulator of shoot-to-root communication during root nodulation in Lotus japonicas . It was proposed that HAR1 negatively regulates nodulation by promoting the production and transportation of a putative shoot-derived inhibitor [54] , [55] . As a homolog of the CLAVATA1 downstream component WUS , DWT1 may regulate intra-panicle uniformity also by controlling long-distance coordination between the panicle and internodes or between main shoot and tillers . The nature of the mobile signal , if involved , and the molecular mechanism by which DWT1 ensures uniform tiller growth in rice require further study . Nevertheless , our study establishes DWT1 as a key genetic component responsible for uniform tiller growth in domesticated rice . Whether DWT1 is responsible for this trait during rice domestication and whether it can provide or improve tiller uniformity in other crops are also outstanding questions for future study .
All plants ( Oryza sativa ) were grown in the paddy field of Shanghai Jiao Tong University . The 11 wild rice strains ( Table S6 ) were ordered from International Rice Research Institute . For GA treatment , wild type and dwt1 mutants were grown in the paddy field , and at internodes elongation stage , GA3 ( 100 µM ) was sprayed to the plant for 3 times at a 2-day interval within 6 days . For the control , 1 mL of 95% alcohol was added to 1L sterilized water . The length of culm and the internode was measured 6 days after treatment , and the final elongation pattern were counted after heading ( 20 days after treatment ) . The Nicotiana benthamiana ( tobacco ) plants were grown in the green house under 16 hours light-long day conditions . Five normal wild-type elongated second internodes and five un-elongated second internodes in the mutant were harvested from different individual plants to count the total longitudinal cell number . The wild type internodes which were separated into 10–15 pieces and the un-elongated dwt1 internodes at the corresponding stages based on the size of wild-type internodes were embedded into the paraffin and sectioned longitudinally . The cell number of each piece in the longitudinal direction between two vascular bundles were counted under microscope ( Motic B3 ) and calculated . The statistical tests were performed by Student's t-test , and the variation is expressed as standard deviation ( SD ) . The dwt1 mutant was crossed with the slr1 mutant . dwt1-like and slr1-like mutants in F2 generation were genotyped by sequencing . The genotyping fragments for SLR ( nucleotides 569–1325 of the coding sequence ) and DWT1 ( nucleotides 508–1662 of the coding sequence ) were amplified by PCR , and sequenced . Three dwt1slr1 double mutants were identified from 17 slr1-like plants in 100 F2 plants . The genotyping primers are listed in Table S7 . The F2 mapping population was generated from a cross between dwt1 mutant ( Oryza sativa ssp . japonica ) and Longtepu B ( Oryza sativa ssp . indica ) . A 6 . 7-kb genomic fragment containing the open reading frame , 2 . 5-kb upstream and 0 . 6-kb downstream sequences of the DWT1 , was obtained by PCR from BAC clone OSJNBb0063G05 . The genomic fragment was inserted into a binary vector pCAMBIA1301 , then was introduced into the dwt1 mutant by the Agrobacterium-mediated transformation method [56] . The pDWT1: DWT-YFP was constructed by fusing an YFP to the C-terminal of DWT1 cDNA , which was driven by the native DWT1 promoter . This fragment was then inserted to the binary vector pCAMBIA1301 and transformed into the wild type . The SNP dataset was obtained from Rice Genome Knowledgebase ( RGKbase , http://rgkbase . big . ac . cn/RGKbase/index . php ) [57] . SNP sites within a specific region in the genome were extracted using customary Perl script according to gene feature file ( GFF ) of MSU 6 . 1 annotation . ( ftp://ftp . plantbiology . msu . edu/pub/data/Eukaryotic_Projects/o_sativa/annotation_dbs/pseudomolecules/version_6 . 1/ ) . The amino acid sequences were aligned using MUSCLE 3 . 6 with the default settings [58] , and then adjusted manually using GeneDoc ( version 2 . 6 . 002 ) software ( Pittsburgh Supercomputing Center; http://www . psc . edu/biomed/genedoc/ ) . Using the MEGAsoftware ( version 3 . 1; http://www . megasoftware . net/index . html ) and based on full-length protein sequences , midpoint-rooted neighbor-joining trees were constructed with the following parameters: Poisson correction , pairwise deletion , and bootstrap ( 1000 replicates; random seed ) [59] . The accession numbers are list in Table S8 . The 35S::DWT1-YFP vector was transformed into Agrobacterium tumefaciens strain GV3101 , and the cultured bacteria were infiltrated into young leaves of 4-week-old tobacco plants . YFP fluorescence was visualized with a confocal scanning microscope ( Leica TCS SP5 II ) 40–48 hours after infiltration [60] . Total RNA was extracted from different tissues of wide type and dwt1 mutant . The first-strand cDNAs were synthesized using MLV reverse transcriptase ( Ferments ) . Quantitative real-time PCR analyses were performed on a CFX96 ( Biorad , US ) using a SYBR green detection protocol according to the manufacturer's instructions . The RT-PCR was repeated at least three times for separately harvested samples . The primers used in this article are listed in Table S7 . Total proteins were extracted from internodes , leaves and panicles of wild type with 2× SDS loading buffer , separated on SDS/PAGE gels , transferred to a nitrocellulose membrane , and hybridized with anti-DWT1 antibody . The DWT1 antibody was prepared by Shanghai ImmunoGen Biological Technology and used at 1∶1000 dilution in the immunoblot analysis . Anti-β-tubulin was purchased from Santa Cruz Biotechnology and was used at 1∶1 , 000 dilution in the experiment . Total RNA were isolated from elongating internodes ( Length = 1 . 0 cm ) of dwt1 mutant and wild-type plants using TRIzol ( Invitrogen ) . Using the standard Affymetrix protocol , three biological repeats of the microarray experiment were performed with Affymetrix rice genome array by Gene Tech Biotechnology Company , which contains probe sets to detect transcripts from all of the high-quality expressed sequence from the entire rice genome . Significance analysis of microarray was used to identify differentially expressed genes . Genes with at least a threefold change in expression ( P values<0 . 001 ) were chosen for additional analysis . GO annotations of Microarray genes were downloaded from NCBI ( http://www . ncbi . nlm . nih . gov/ ) , UniProt ( http://www . uniprot . org/ ) , TIGR ( rice . plantbiology . msu . edu/ ) and the Gene Ontology ( http://www . geneontology . org/ ) . The “elim Fisher” algorithm was used to do GO enrichment test [61] . Gene ontology categories with an adjust p-value<0 . 05 were reported . DWT1-specific fragment ( nucleotides 1458–1701 of the coding sequence ) was amplified by PCR from the cDNA clone and then inserted into pBluescript SK ( + ) ( Stratagene ) . Preparation of probes and the in situ hybridization were performed according to the previous description [62] .
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Plant architecture is important for crop yield . In most plants , branches grow smaller than the main shoot , largely due to the ‘apical dominance’ . However , in several cereal crops , including rice , wheat , and barley , the branches ( tillers ) have a height and size indistinguishable from the main shoot . The genetic basis of uniform tiller growth has remained elusive . We identified DWARF TILLER1 , a WUSCHEL-related homeobox ( WOX ) transcription factor , as a positive regulator of tiller growth . Most dwt1 mutant plants show normal main shoot but dwarf tillers and reduced panicle size . Tiller growth in dwt1 appears to be inhibited by the main shoot , as removal of the main shoot releases the first tiller . The non-elongating internodes in dwt1 show reduced cell number and cell size , while DWT1 was mainly expressed in the panicles but not internodes , suggesting that DWT1 plays a long distance regulatory role in promoting internode elongation . Genome-wide expression analysis revealed that the expression of genes related to cell division and elongation , as well as to homeostasis and signaling of cytokinin and gibberellin were affected in dwt1 un-elongated internodes . This study reveals that a WOX transcription factor controls the growth uniformity of tillers and the main shoot in rice .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology",
"plant",
"science",
"rice",
"cereals",
"plant",
"growth",
"and",
"development",
"crops",
"genetics",
"plant",
"genetics",
"biology",
"crop",
"genetics",
"morphogenesis",
"agriculture"
] |
2014
|
DWARF TILLER1, a WUSCHEL-Related Homeobox Transcription Factor, Is Required for Tiller Growth in Rice
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We combined gene divergence data , classical genetics , and phylogenetics to study the evolution of the mating-type chromosome in the filamentous ascomycete Neurospora tetrasperma . In this species , a large non-recombining region of the mating-type chromosome is associated with a unique fungal life cycle where self-fertility is enforced by maintenance of a constant state of heterokaryosis . Sequence divergence between alleles of 35 genes from the two single mating-type component strains ( i . e . the homokaryotic mat A or mat a-strains ) , derived from one N . tetrasperma heterokaryon ( mat A+mat a ) , was analyzed . By this approach we were able to identify the boundaries and size of the non-recombining region , and reveal insight into the history of recombination cessation . The non-recombining region covers almost 7 Mbp , over 75% of the chromosome , and we hypothesize that the evolution of the mating-type chromosome in this lineage involved two successive events . The first event was contemporaneous with the split of N . tetrasperma from a common ancestor with its outcrossing relative N . crassa and suppressed recombination over at least 6 . 6 Mbp , and the second was confined to a smaller region in which recombination ceased more recently . In spite of the early origin of the first “evolutionary stratum” , genealogies of five genes from strains belonging to an additional N . tetrasperma lineage indicate independent initiations of suppressed recombination in different phylogenetic lineages . This study highlights the shared features between the sex chromosomes found in the animal and plant kingdoms and the fungal mating-type chromosome , despite fungi having no separate sexes . As is often found in sex chromosomes of plants and animals , recombination suppression of the mating-type chromosome of N . tetrasperma involved more than one evolutionary event , covers the majority of the mating-type chromosome and is flanked by distal regions with obligate crossovers .
Many diverse systems for sex determination have evolved in plants and animals [1]–[3] . One involves physically distinct sex chromosomes , a system thought to have evolved independently many times by suppression of recombination around the sex determination genes , followed by differentiation and degeneration of the non-recombining chromosome [4] . In the fungal kingdom , there is no dichotomy of individuals into sexes bearing different gametes , but instead mating-type identity is determined by inheritance of alleles at mating-type loci . Nevertheless , chromosomal regions controlling mating-type identity in fungi share features with the more complex sex chromosomes of algae , plants and animals [5] . Although mating-type loci consist of one to a few linked genes , and are thus limited to a small genomic region , alleles at the mating-type loci of fungi often differ to the extent that there is no sequence similarity between them [e . g . 6] , [7] . Furthermore , complete recombination cessation in the region around the mating-type loci have been reported from several fungal taxa [7]–[9] . However , fungi generally have much smaller regions of suppressed recombination than animal dimorphic chromosomal regions . For example , in Cryptococcus neoformans recombination is suppressed on only 6% of a 1 . 8 Mb chromosome , or ca . 100 kb [8] . The filamentous ascomycete Neurospora tetrasperma constitutes an exception in which recombination is blocked over the majority of the chromosome containing the mating-type loci , referred to as the mating-type ( mat ) chromosome . Moreover , the non-recombining region is flanked by distal regions where obligate crossovers are observed [10] , [11] . In this species , the large non-recombining region is associated with a uniquely fungal life cycle , called pseudohomothallism , where self-fertility is enforced by maintenance of a constant state of heterokaryosis , normally only observed post-fertilization in this group of fungi . Modified programs of meiosis and sexual spore development lead to the packaging of two haploid nuclei of opposite mating-type ( mat A and mat a ) into each N . tetrasperma ascospore progeny [12] , [13] . The species maintains its ability to outcross by the occasional production of homokaryotic , self-sterile ( mat A or mat a ) propagules , both asexual and sexual , which may be isolated to obtain single mating-type component strains . A key feature of meiosis in N . tetrasperma is suppressed crossing over on the mating-type bivalent , ensuring that mat A and mat a will segregate in the first division of meiosis . Although suppressed recombination between mat and the centromere would suffice to provide the mechanism for segregation of mating type , the non-recombining region covers a much larger area of the chromosome [10] . The mating-type chromosomes of N . tetrasperma therefore resemble the sex chromosomes of animals and plants both in failing to recombine over the majority of their length and having obligate crossovers at the flanking “pseudoautosomal” regions . However , the mechanism initiating the divergence of mating-type chromosomes in N . tetrasperma differs from that of animal and plant sex chromosomes , where initiation is suggested to be due to selection for linkage between primary sex-determining alleles and other interacting genes . Such interactions involve alleles with beneficial effects in one sex , but which reduce the fitness of the other sex ( e . g . sexually antagonistic genes , [4] and references therein ) . Two factors have been suggested to affect recombination between evolving sex chromosomes: the spread of genetic modifiers of recombination rates [14] , and chromosomal rearrangements causing chromosome heteromorphism [4] . Both these factors have been suggested to be responsible for the blocked recombination in N . tetrasperma . Reciprocal introgression of the mating-type chromosomes between N . tetrasperma and its close relative N . crassa indicate that both autosomal genes and structural heterozygosity affect recombination in this species [11] . By investigating nucleotide sequence divergence of genes shared between homologous non-recombining chromosomes , insight can be gained into when and how recombination ceased between them , assuming they have been evolving independently since recombination was disrupted . This approach has been used for several systems , including X–Y gametologs of humans [15] , mouse [16] , dioecious plants [17] , W–Z gametologs of chicken [18] , and genes located on the mating-type chromosomes of the basidiomycete Cryptococcus [19] . All of these systems exhibit “evolutionary strata” , the term initially introduced by Lahn and Page [15] to represent different sequential steps whereby recombination become arrested between the proto-sex chromosomes . In this study , we compared the level of divergence between alleles on mat A and mat a-chromosomes from a single wild-type N . tetrasperma heterokaryon and found that evolution of the mating-type chromosome in this lineage involved two successive events . The first suppressed recombination over a very large region-at least 6 . 6 Mbp , or 75% of the chromosome , and was contemporaneous with the split of N . tetrasperma from a common ancestor with the outcrossing relative N . crassa . The second was confined to a smaller region in which recombination ceased more recently . In spite of the early origin of the first stratum , genealogies of five genes located in this region from strains belonging to an additional N . tetrasperma phylogenetic lineage indicate totally independent initiations of recombination suppression in the two lineages . We hypothesize that pseudohomothallism in N . tetrasperma evolved in a stepwise manner , and that the steps required to block recombination along the mat-chromosome occurred independently in the different lineages in order to facilitate a more efficient first division meiotic segregation of mating type .
In order to relate the divergence and evolutionary constraints of alleles within a heterokaryon to the location in the genome , the synonymous ( dS ) and non-synonymous to synonymous ( dN/dS ) nucleotide divergence values were estimated for 35 allele pairs of genes of the single mating-type component strains ( i . e . homokaryotic mat A or mat a-strains ) originating from the heterokaryotic ( mat A+mat a ) strain P581 of N . tetrasperma ( Table 1 ) . In addition , divergence values ( dS and dN/dS ) were estimated between each N . tetrasperma allele and the homologous allele of N . crassa ( http://www . broad . mit . edu/annotation/genome/neurospora/ ) . Because of the self-fertilizing nature of the species , genes outside of the regions of blocked recombination are expected to be largely identical between single mating-type component strains isolated from wild heterokaryons . Accordingly , no sequence divergence was found between allele pairs from the single mating-type component strains ( i . e . dS = 0 ) of eight genes located at both ends of mat chromosome , indicating homogenization of genes in these two distal regions by recombination ( Table 2 ) . The region between mus-42 and lys-3 , which will hereafter be referred to as the non-recombining part of the mat chromosome , in contrast contained 15 divergent allele pairs with dS-values ranging from 0 . 013 to 0 . 082 . No divergence was found for two additional genes in this region ( rid and cys-5 ) . The dS-values of the genes in the non-recombining region , but on either side of mat , were found to be significantly different ( Mann-Whitney test , p<0 . 0015 ) ; to the right of mat , dS ranged from 0 . 047 to 0 . 082 , while dS ranged from 0 to 0 . 04 on the left side of mat ( Table 2 ) . This difference was significant even when excluding the two non-divergent genes on the left flank ( rid and cys-5; Mann-Whitney test , p<0 . 0058 ) . Taken together , our data indicate that the evolution of the mating-type chromosome in this lineage involved at least two events , dividing recombination suppression into two strata . The first , larger Stratum 1 includes mat , the centromere and the majority of the right arm of the chromosome , and the second , smaller Stratum 2 is restricted to the area left of mat ( Figure 1A ) . The divergence ( dS ) between alleles of the N . tetrasperma heterokaryon in the first stratum did not differ significantly from the divergence between alleles of N . tetrasperma and N . crassa ( Table 2 ) . Thus , the data suggest that the event creating Stratum 1 was close to the time of the split of N . tetrasperma from a common ancestor with N . crassa . The ratio of non-synonymous to synonymous substitutions per site ( dN/dS ) did not differ between alleles of the two mat chromosomes and between any of these and N . crassa , and no difference in dN/dS was found between N . tetrasperma and N . crassa when comparing the region of blocked recombination with the other genes of the genome ( Table 2 ) . To establish the left flank boundary of the non-recombining region , allelic segregation of mus-42 was scored in 152 heterokaryotic ( mat A and mat a ) progeny of the selfed cross of P581 . The marker mus-42 was heteroallelic in all 152 progeny , confirming no crossovers between mat and mus-42 during meiosis . Given a crossover-rate of above 1 . 95% in this interval in N . crassa , we calculate an over 95% probability of detecting a crossover event in 152 offspring ( estimated as 1- the probability of finding one crossover in 152 offspring ) . Thus , mus-42 is genetically linked to the region of blocked recombination , and our data strongly indicate that the boundary of the non-recombining region is located left of mus-42 . The N . crassa genome sequence ( http://www . broad . mit . edu/annotation/genome/neurospora/ ) was used to estimate the physical size of the non-recombining region in N . tetrasperma strain P581 , assuming that the mat a-chromosome is collinear with N . crassa [11] . The entire region of blocked recombination occupies about 6 . 9 Mbp ( 78 . 4% of the total chromosomal length ) , but the size of each stratum within the block differs: the older Stratum 1 is 6 . 6 Mbp ( 75% ) , while the more recent Stratum 2 is 0 . 3 Mbp ( 3 . 4% ) ( Figure 1A ) . An altered gene order in the mat a-chromosome of strain P581 could explain the lack of divergence in rid and cys-5 . A cross between two strains of N . crassa , one of which contained an introgressed mat a-chromosome originating from P581 ( referred to as mat aT ) was used to infer gene order by crossover frequencies between mat chromosome loci ( Supporting Information , Table S1 ) . The small number of crossovers among markers in the 83 scored progeny and the lack of double crossovers show tight linkage of the genes , as is known in N . crassa , but cannot be used to conclude a definitive gene order . However , all possible orders of these tightly linked genes place them well within the region of blocked recombination . The evolutionary history of mat chromosome strata may vary among the divergent lineages known within N . tetrasperma [20] . To test this possibility , five genes within Stratum 1 were sequenced from single mating-type components of six heterokaryons , representing two phylogenetic lineages of N . tetrasperma . The sequences of these genes from the mat chromosome were identical for the mat A-component strains of each lineage . The mat a-component strains of each lineage also had identical gene sequences , except for one intron polymorphism that was found in upr-1 between mat a-component of strain P2361 ( FGSC 4372 ) and the two other mat a-component strains of Lineage 1 . Synonymous sequence divergence values between allele pairs of the heterokaryons are shown in Table 3 . One most parsimonious tree for each of the genes upr-1 , eth-1 , lys-4 , ad-9 and lys-3 , and bootstrap support for branches , are shown in Figure 1B . Both synonymous divergence data and genealogies confirm that the alleles located on the mat A and mat a-chromosomes within heterokaryons of all five genes of Lineage 1 diverged early . In contrast , a more recent split of the alleles within heterokaryons are found in Lineage 2 ( Table 3; Mann-Whitney test , p<0 . 0119 ) . Although no synonymous divergence was found for ad-9 and lys-3 of Lineage 2 ( Table 3 ) , the presence of one non-synonymous change in lys-3 indicates that recombination is suppressed in this whole region in both lineages ( Figure 1B ) . The genes sequenced here were limited to Stratum 1 , and although alleles in this stratum are assumed to have started to diverge in the early evolution of the species ( see above ) , our data imply different evolutionary histories of this part of the mat chromosome in the two lineages of N . tetrasperma . The Kimura 2-parameter genetic distance between N . crassa and N . tetrasperma , based on intron-data from autosomal genes ( i . e . genes located on chromosomes other than the mating-type chromosome; Table 2 ) , was found to be 0 . 0533 . Assuming a divergence time of Eurotiomycetes and Sordariomycetes between 400 to 670 MYA and using the Langley Fitch algorithm to calculate substitution-rate [21] , we estimate that N . tetrasperma diverged from a common ancestor with N . crassa between 3 . 5 and 5 . 8 MYA .
Although fungi have no differentiated sexes , i . e . female/male dichotomy of individuals carrying gametes of different sizes , the data presented here confirms that similar mechanisms drive the evolution of sex chromosomes found in the animal and plant kingdoms and the fungal mating-type chromosomes in Neurospora tetrasperma . First , the mating-type chromosomes in the pseudohomothallic N . tetrasperma fail to recombine over the majority of its length; here we establish that in strain P581 the non-recombining region covers almost 7 Mbp , over 75% of the mating-type chromosome . Previous studies , using the same fungal strain , have shown suppressed recombination of a large portion of the mating-type chromosomes of N . tetrasperma [9]–[11] . This study was able to more precisely identify the boundaries and size of the non-recombining region . Notably , the left arm of the non-recombining region is shorter than previously reported [22]; the earlier suggestion that the non-recombining region begins around nit-2 was not supported here . Instead , the left boundary appears located close to mus-42 ( Figure 1A ) . Furthermore , in analogy to systems of sex chromosomes representing all three kingdoms [15]–[19] , our data revealed that the evolutionary events leading to the suppression of recombination involved two successive events , resulting in two evolutionary strata , 6 . 6 Mbp and 0 . 3 Mbp in size , respectively . Thus , the data suggest that in this fungus stepwise cessation of recombination can take place over a vast genomic region up to 6 . 6Mbp in size . The event ( s ) that suppressed recombination are unknown . In the absence of a single , large structural change we may expect a more gradual change in divergence along the chromosome . The simplest possible hypothesis is that Stratum 1 correlates with one large inversion . However , when such a pericentric inversion has been observed on the mating-type chromosome of N . crassa , an inversion loop appears to be formed during meiosis , allowing both pairing and crossing over of the inverted region as well as the formation of inviable and unstable progeny [23] . Since such an inversion loop or crossovers do not occur in N . tetrasperma , multiple mechanisms for blocking recombination along the mating-type chromosome are likely to be involved . With the upcoming availability of the genome sequence of N . tetrasperma ( http://www . jgi . doe . gov/ ) we should be able to disentangle what factor resulted in ceased recombination in this region . Interestingly , the non-recombining region extends over the majority of the chromosome , although a shorter non-recombining region between mat and the centromere would itself be sufficient for the first division meiotic segregation of mating-type that is needed for pseudohomothallism [13] . If one event caused the large Stratum 1 , as indicated by our data , it could be the reason for the apparently unnecessary large size . In this context , the reason for the more recent Stratum 2 is obscure . In an earlier study of C . neoformans Fraser and co-workers hypothesized that the accumulation of transposable elements would explain the pattern of a gradually growing non-homologous region between the two mating-type chromosomes [19] . Testing the transposon-mediated chromosomal rearrangement hypothesis in N . tetrasperma would require further investigation , again possible with the sequenced genome . A small number of genes showed sequence divergence ( dS ) that deviated slightly from the other genes located within the same stratum . For example , in Stratum 2 , rid and cys-5 showed no sequence divergence in exons between corresponding alleles ( dS = 0 ) . In these two genes , no introns are present to support homogenization or divergence between the alleles . However , the mapping data indicate conserved order of nine markers ( including rid and cys-5 ) located between ro-10 and mat ( Supporting Information , Table S1 ) , suggesting that they are not translocated in N . tetrasperma . For eth-1 , located in Stratum 1 , we found a ds-value of 0 . 029 , which is roughly half the value found for alleles of the other genes in that stratum . As the actual mapping location of eth-1 was not investigated , the possibility should not be excluded that this gene was recently translocated from the younger evolutionary stratum . Studies from a diverse range of systems have revealed that lack of recombination per se is sufficient for genetic degeneration of a chromosome such as gene loss and null-mutations at protein coding genes , and for transposable element accumulation [4] , [24] . The heterokaryotic life-style of N . tetrasperma , in which cells during the whole life-cycle carry two nuclei of separate mating-types , would be expected to further favor the erosion of a gene located on these chromosomes , since maintaining function requires an active counterpart on only one of the chromosomes . However , we found no evidence for relaxed selective constraints , as judged from the dN/dS comparisons between genes on the mating-type chromosomes and the autosomes , or gene loss in the mating-type chromosomes of N . tetrasperma . This observation could be due to the very young age of the system . Alternatively , an occasional homokaryotic part of the life cycle [25] , would unmask recessive deleterious mutations and purge these from the population . The accumulation of repetitive elements along the mating-type chromosome remains an interesting target for future research , because these are found to be very early colonizers of non-recombining chromosomes of animal and plant systems [26]–[29] . Multiple phylogenetic lineages exist within N . tetrasperma , all of them being pseudohomothallic [20] . The transition from heterothallism to pseudohomothallism in N . tetrasperma is associated with loss of mating-type heterokaryon incompatibility . This loss of heterokaryon incompatibility is required to maintain pseudohomothallism and may explain the sexual dysfunction observed when single mating-type strains are outcrossed in the laboratory [30] . The existence of eight-spored outbreeding sister-species to N . tetrasperma [i . e . ( N . crassa ( N . tetrasperma , PS1 , N . sitophila ) ) see [31]; Jeremy Dettman and John Taylor , personal communication] indicate that the non-recombining region formed at or after the split of N . tetrasperma from N . crassa . We found that Stratum 1 was contemporaneous with the split of N . tetrasperma from a common ancestor with N . crassa , estimated to be between 3 . 5 to 5 . 8 MYA . Assuming that the non-recombining region is a prerequisite for pseudohomothallism would suggest that all lineages of N . tetrasperma should share Stratum 1 of the mat-chromosome . In contrast , the divergence data and genealogies of five genes located in Stratum 1 suggest that the two different N . tetrasperma lineages share a non-recombining region on the mating-type chromosome due to convergent evolutionary events . We hypothesize that pseudohomothallism evolved in a stepwise manner , and that in the early evolution of pseudohomothallism in N . tetrasperma there was no recombination block , but that it evolved independently in the different lineages as a selective response for a more efficient pseudohomothallism with absolute first division meiotic segregation of mating type . Elucidating mechanisms by which sex chromosomes evolve from autosomes has been accelerated by the revolution in genomic science . Considerable insight into plants and animals can be gained through the study of alternative systems , such as N . tetrasperma , in which the genomic consequences of reduced recombination per se can be disentangled from sex-biased evolutionary forces such as male-biased mutation and dispersal [32] , [33] . Thus , the system presented here has the potential to contribute significantly to the general understanding of the forces shaping sex chromosomes , as well as general insights into how levels of polymorphism vary among different regions of the genome .
N . tetrasperma strains used in this study were obtained from the Fungal Genetics Stock Center ( FGSC ) , Kansas City , KS , or from the Perkins collection at Stanford University , and are listed in Table 1 . The Perkins collection is now curated and available from the FGSC . The single mating-type component strains of each heterokaryon ( i . e . the homokaryotic mat A or mat a-strains ) were originally obtained through the isolation of homokaryotic sexual or asexual spores occasionally produced by the heterokaryon . The identity of the mating type was confirmed by PCR using allele specific primers [34] . Crosses were made using standard methods on synthetic cross ( SC ) medium [35] at 25°C . Strains for DNA extraction were grown in minimal medium broth [36] with 1% sucrose for 3 days at 37°C . DNA was extracted from fungal vegetative tissue using methods previously described [37] . PCR reactions were performed using the Expand High Fidelity PCR System ( Roche Diagnostics , Mannheim , Germany ) according to the manufacturer's recommendations , using an Eppendorf epgradient S thermocycler ( Eppendorf , Hamburg , Germany ) . PCR products were purified using ExoSap-IT ( Amersham Biosciences , Little Chalfont , UK ) , and sequencing was performed by Macrogen Inc . , Seoul , Korea , utilizing ABI 3730 XL automated sequencers ( Applied Biosystems , Foster City , CA ) . Raw sequence data were analyzed using the SeqMan version 5 . 01 software from DNASTAR package ( DNASTAR , Madison , WI ) and BioEdit version 7 . 0 . 5 . 2 [38] . Exon sequences from 25 genes located on the mating-type chromosome ( also referred to as Linkage Group I: LGI ) and ten genes located on autosomes ( LGV and LGVI ) were chosen for analysis ( Table 2 ) . Primers for amplification of nuclear genes were designed from the N . crassa genome sequence ( http://www . broad . mit . edu/annotation/genome/neurospora/Home . html ) by using the PrimerSelect version 5 . 01 software of the DNASTAR package ( DNASTAR , Madison , WI ) . Primer sequences and information is found in Supporting Information , Table S2 . Sequences were PCR-amplified from the separate , homokaryotic , single-mating-type component strains of the wild-type heterokaryon P581: mat A ( FGSC 2508 ) and mat a ( FGSC 2509 ) ( Table 1 ) . Synonymous and non-synonymous nucleotide divergence values ( dS and dN , respectively ) were estimated between alleles using DNAsp version 4 . 10 . 9 [39] . Comparisons were made between N . tetrasperma alleles from the different single-mating-type component strains , as well as between the N . tetrasperma alleles and the N . crassa genome sequence . To establish the boundary of the non-recombining region on the left flank of LGI of strain P581 , recombination was assessed in individual sexual progeny originating from a selfed cross of the heterokaryotic mycelia . Hetero- or homoallelism of mus-42 , located at the leftmost side of the non-recombining region , was scored in 152 heterokaryotic ( mat A+mat a ) progeny , by digesting PCR products obtained by primers TF1 and TR1 ( Supporting Information , Table S2 ) with the restriction enzyme NmuCI ( Fermentas Life Sciences , Germany ) , according to the manufacturer's recommendations . NmuCI has an additional recognition site in the mus-42 allele from the mat A-chromosome of P581 , as compared to that of mat a , making it possible to separate the two alleles with agarose gel electrophoresis subsequent to amplification and digestion . A recombination event between mat and mus-42 would result in homoallelism of mus-42 and heteroallelism of mat found in a single sexual progeny . Jacobson [11] suggested that the mat a-chromosome of N . tetrasperma ( mat aT ) is collinear with the N . crassa mat a ( mat aC ) chromosome . In order to further establish the location of the genes investigated in this study , we carried out a finer scale linkage analysis of the mat aT chromosome of strain P581 by crossing a fifth backcross progeny of mat aT of P581 introgressed into the N . crassa background ( DJ1544-2a ) [11] and N . crassa ( FGSC 3789A ) ( Table 1 ) . First , by DNA sequencing , we confirmed that the parental strain DJ1544-2a contained exclusively N . tetrasperma alleles at the genes between mus-42 and mat , allowing for normal linkage testing in this region . Subsequently , the molecular markers mus-42 , rid , leu-4 , cys-5 , ser-3 and tef-1 , and the genetic markers ro-10 , mep and mat , were scored for 83 progeny from the cross DJ1544-2a×FGSC 3789A . For mus-42 , rid , leu-4 , cys-5 , ser-3 and tef-1 we scored N . tetrasperma and N . crassa alleles by PCR-amplification and amplicon digestion using the primer pairs and restriction enzymes TF1 & TR1 ( NmuCI ) , rid-1F2 & rid-1R2 ( NmuCI ) , leu-4F1 & leu-4R1 ( EheI ) , cys-5F & cys-5R ( FspBI ) , ser-3F & ser-3R ( HincII ) and ef-1aF1 & ef-1aR1 ( SmuI ) , respectively . Primers sequences are found in online Supporting Information , Table S2 , enzymes were obtained from Fermentas Life Sciences , Germany , and digestion was performed according to the manufacturer's recommendations . Genetic markers were scored as described previously [11] . Recombination frequencies between the markers were compared to those expected for wild-type N . crassa . The genes upr-1 , eth-1 , lys-4 , ad-9 and lys-3 of the homokaryotic , single mating-type components of six N . tetrasperma heterokaryotic strains , belonging to either of two well-supported phylogenetic lineages of N . tetrasperma ( Table 1 ) , were PCR-amplified and sequenced using primers pairs upr-1F1 & upr-1R1 , eth-1F1 & ethR1 , lys-4F1 & lys-4R1 , ad-9F & ad-9R and lys-3F1 & lys-3R1 ( Supporting Information , Table S2 ) , respectively . Sequences were aligned for each gene using the Clustal W algorithm of BioEdit version 7 . 0 . 5 . 2 and alignments are available from TreeBASE ( study accession no . S1960; matrixes M3612-M3616 ) . Synonymous divergence values ( dS ) were estimated between the pairs of alleles of the single mating-type components originating from each of the six heterokaryotic strains of N . tetrasperma , as well as between these alleles and the N . crassa genome sequence , as described above . Phylogenetic analyses were carried out in PAUP 4 . 0b [40] . For each gene , we identified maximum parsimony ( MP ) trees by heuristic searches using the tree bisection-reconnection ( TBR ) branch-swapping algorithm using N . crassa as outgroup . All characters were of equal weight and unordered , and statistical support for phylogenetic grouping was assessed by bootstrap analysis using 1000 replicate datasets with the random addition of sequences during each heuristic search .
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In fungi , mating occurs between individuals of alternative mating-types and there is no dichotomy of individuals into two morphologically different sexes . Nevertheless , in this paper we show that chromosomal regions controlling mating-type identity in fungi share features with the more complex sex chromosomes found in the other eukaryote kingdoms . We have specifically studied the mating-type chromosome in an emerging model-species of filamentous ascomycetes , Neurospora tetrasperma , and show that it resembles the sex chromosomes of animals and plants both in failing to recombine with its homologous chromosome over the majority of its length , and having obligate crossovers at the flanking “pseudoautosomal” regions . Furthermore , our data indicate that the evolution of the mating-type chromosome in this species involved more than one successive evolutionary event , each defining an “evolutionary stratum” , a term initially introduced by to represent different sequential steps whereby recombination became arrested between the proto-sex chromosomes in humans . We argue that insight into the evolution of chromosomal sex determination can be gained through the study of alternative , simple , systems , such as N . tetrasperma , in which the genomic consequences of reduced recombination per se can be disentangled from sex-biased evolutionary forces such as male-biased mutation and dispersal .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"evolutionary",
"biology",
"evolutionary",
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2008
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The Mating-Type Chromosome in the Filamentous Ascomycete Neurospora tetrasperma Represents a Model for Early Evolution of Sex Chromosomes
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In sub-Saharan Africa , where there is the scarcity of proper diagnostic tools , febrile illness related symptoms are often misdiagnosed as malaria . Information on causative agents of febrile illness related symptoms among pastoral communities in Ethiopia have rarely been described . In this a community based cross-sectional survey , we assessed the prevalence of typhoid fever , typhus , brucellosis and malaria among individuals with a set of given symptoms in Amibara district , Afar Region , Ethiopia . Blood samples were collected from 650 study participants , and examined by Widal and Weilfelix direct card agglutination test ( DCAT ) as well as test tube based titration test for Salmonella enterica serotype Typhi ( S . Typhi ) and Rickettsia infections . Rose Bengal Plate Test ( RBPT ) and Complement Fixation Test ( CFT ) were used to screen Brucella infection . Thin and thick blood smears were used to diagnosis malaria . Out of 630 sera screened by DCAT , 83 ( 13 . 2% ) were reactive to H and/or O antigens for S . Typhi infection . Among these , 46 ( 55 . 4% ) were reactive by the titration test at the cut off value ≥ 1:80 . The combined sero-prevalence for S . Typhi by the two tests was 7 . 3% ( 46/630 ) . The seroprevalence for Rickettsia infection was 26 . 2% ( 165/630 ) by DCAT and 53 . 3% ( 88/165 ) by the titration test at the cut off value ≥ 1:80 . The combined sero-prevalence for Rickettsia infection by the two tests was 14 . 0% ( 88/630 ) . The sero-prevalence for Brucella infection was 12 . 7% ( 80/630 ) by RBPT , of which 28/80 ( 35% ) were positive by CFT . The combined sero-prevalence for Brucella infection by the two tests was 4 . 4% ( 28/630 ) . Out 650 suspected individuals for malaria , 16 ( 2 . 5% ) were found positive for P . falciparum infection . In this study , typhoid fever , typhus , brucellosis and malaria were observed among symptomatic individuals . The study also highlighted that brucellosis cases can be misdiagnosed as malaria or other disease based solely on clinical diagnosis . Therefore , efforts are needed to improve disease awareness and laboratory services for the diagnosis of brucellosis and other zoonotic diseases to identify other causes of febrile illness in this pastoral setting .
Sub-Saharan Africa is plagued by a myriad of infectious diseases posing significant public health and economic challenges . In addition , the often non-specific clinical signs of these diseases and the scarcity of proper diagnostic tools are the major challenges for health professionals in properly diagnosing and treating adequately patients [1 , 2] . Studies showed that symptoms such as fever , headache , joint pain and back pain are often misdiagnosed as malaria , especially until the introduction of rapid diagnostics for malaria though these symptoms are not only specific to malaria [3–5] . Many studies have shown that diseases such as typhoid fever , rickettsioses , brucellosis , Q fever , and leptospirosis are the leading causes for febrile illness with symptoms such as fever , headache , joint pain and back pain [6–9] . For instance , typhoid fever due to S . Typhi has been reported as the leading cause of over 21 million febrile cases and over 200 , 000 deaths each year in many low- and middle-income countries [7–9] . Brucellosis has been considered as an important zoonotic disease worldwide and is responsible for big economic losses as it causes abortion in livestock [10 , 11] . It also causes a considerable human morbidity and spontaneous abortion among pregnant women in endemic areas [12–15] . Although many malarious countries including Ethiopia are scaling up malaria intervention programs towards elimination , the disease remains one of the worst health problems with an estimated 216 million cases and 445 000 deaths globally in 2016 , while most of the cases and deaths occurred in African [16] . Hence , in low- and middle-income countries where there is a shortage of effective routine diagnostic tools to identify a wide range of infectious diseases that manifest similar symptoms and where there is also a low awareness among community members and health professionals about the common causative agents of such illnesses , a community-based approach epidemiological survey would help health professionals to improve clinical diagnosis and provide appropriate treatment [1 , 2] . In Ethiopia , there have been few health facilities based studies to determine the prevalence of typhoid fever , typhus , malaria and brucellosis among individuals presented with febrile illness related symptoms [17–19] . Communities based epidemiological data on the causative agents of common febrile illness related symptoms is generally lacking in the pastoralists areas due to the remoteness of sites and pastoralists way of life . Moreover , in the present study area , health professionals had no clear information on the magnitude of brucellosis , and its clinical based diagnosis might not be even considered . Hence , we assessed the prevalence of typhoid fever , typhus , brucellosis and malaria in individuals who were complaining of symptoms such as fever , headache , joint pain and back pain in the pastoral community of the Amibara district , Afar Region , Ethiopia .
The study was conducted in the pastoral community of Amibara district in the Afar Region of Ethiopia , around 260 km from Addis Ababa . The majority of the study population are pastoralists , depending on livestock for their livelihoods , while some started to practice agro-pastoralism and growing crops along river Awash . The study area and the population has been previously described in detail [20 , 21] . A community based cross-sectional survey was carried out between September and December 2016 to determine the prevalence of typhoid fever , typhus , brucellosis and malaria among individuals who were complaining of a range of symptoms . The result of previous health facilities based sero-prevalence of brucellosis ( 34% ) in other pastoral community areas of Ethiopia was used to estimate the sample size [17] for the study on brucellosis . Using this information , a sample size of 380 individuals ( 95% confidence level , 5% degree of accuracy and 10% compensation for refusal of blood sample ) was initially considered . According to the information from Melka Worer health center 50% of patients with symptoms like fever , headache and joint pain often diagnosed as positive for typhoid , typhus or malaria . Based on this supplementary information , sample size was increased to 422 individuals ( 95% confidence level , 5% degree of accuracy and 10% compensation for refusal of blood sample ) . However , during the survey period all eligible individuals who came for diagnosis were considered and the sample size was increased to 650 . In this study , six accessible pastoral kebeles of the district were conveniently selected , and a house-to-house survey of all households in the selected kebeles was conducted by community health workers under the supervision of the research team . The heads of the households ( husband or wife ) or individuals over 18 years were asked if there was any family member ( age ≥ 2 years ) who manifested symptoms such as fever , fatigue , headache , joint pain , and back pain for short or long periods of time . The individuals were asked to come to the nearest health post , and they were interviewed in their local language ( Afar language ) using a structured questionnaire that captured common signs/symptoms they felt , onset of illness , treatment sought , and information on socio-demographic characteristics of the individuals . Body temperature was also recorded using a digital thermometer . All individuals equal or older than 2 years , who reported the above symptoms , came for examination and willing to provide blood , and gave informed consent and/or assents were included in the study . Three ml venous blood sample was collected into plain vacutainer test tube and transported to Melka Werer Health Center . Serum was separated and tested for typhoid fever , typhus and malaria on the same days . The remaining serum was stored at -20°C until transported to the laboratory of Aklilu Lemma Institute of Pathobiology , Addis Ababa University and tested for brucellosis and also tested for typhoid and typhus by test tube based titration method . Anemic individuals and pregnant women were included in the malaria study and provided only finger prick blood sample . Widal and Weilfelix direct card agglutination tests ( DCAT ) were used for the serological screening of S . Typhi and Rickettsia infections , respectively following the manufacturer’s instructions ( Rapid Labs Ltd , Hall Farm Business Centre , UK ) , and as previously described [22 , 23] . A test tube based titration test was performed for all samples that were found to be reactive by the DCAT and for other 25 randomly selected samples which were found non-reactive as previously described [24] . Rose Bengal Plate Test ( RBPT ) was used to screen for Brucella infection as previously described [25] . All sera which tested positive by the RBPT and other randomly selected 68 negative samples were further tested using Complement Fixation Test ( CFT ) following the guidelines of OIE 2008 [26] . The guideline of Ministry of Health ( MOH ) was followed for the diagnosis of malaria and identification of Plasmodium species at the Health center [27] . Data was entered into EpiData 3 . 1 and analyzed with Stata/SE 11 . 0 . Descriptive analysis was used to summarize the data in the form of frequencies and percentages of variables . Pearson chi-square test was used to evaluate the statistically significant difference in the level of prevalence of typhoid fever , typhus , brucellosis and malaria between male and female study participants and according to the reported clinical features . Bivariable and multivariable logistic regression analyses were performed to explore associations of socio-demographic characteristics of the study participants with increased odds of having higher prevalence of typhoid fever , typhus , brucellosis and malaria . P-value below 5% was considered as indicator of statistical significance . This study received ethical clearance from the Institutional Review Board of Aklilu Lemma Institute of Pathobiology , Addis Ababa University ( ALIPB/IRB/005/2015/16 ) ) . Permission was obtained from Amibara Health Office . Participants’ information sheet which contains the objective of the study , inclusion/exclusion criteria , the required data and methods of data collection as well as informed consent document were prepared in Amharic the national language of the country . Then , the elements of participants’ information sheet initially were orally translated to the local language and described to community leaders and to each of the study participant or parent in case of children under 18 years by trained local health personnel . Informed written consent was obtained from illiterate participants and/or assent in children aged between 12 and 18 years by signing with their finger . Blood sample was collected under aseptic condition by experienced laboratory technicians . Study participants who were found positive for the investigated diseases were treated accordingly as per physician recommendation .
A total of 657 individuals who were complaining various symptoms such as headache , joint pain fever and back pain appeared for clinical examination . However , seven individuals were not volunteers to consent to provide blood sample and they were excluded . Out of the 650 study participants , 630 provided venous blood and 20 provided finger prick blood sample due to anemia and/or pregnancy . The participants’ age ranged from 2 to 80 years with mean age 34 . 25 ±17 . 38 years . The majority were illiterate ( 75 . 2% ) and pastoralists ( 78 . 8% ) ( Table 1 ) . Table 2 shows the clinical signs , duration of the illness and treatment history as reported by the study participants . Headache ( 74 . 8% ) , joint pain ( 74 . 8% ) , and general malaise ( 24 . 9% ) were the frequently reported symptoms . The duration of the illness reported by the participants ranged between 2 and 7300 days , with a median duration of 257 days . A total of 159 individuals ( 24 . 5% ) reported that they sought treatment at various health facilities for their or their family member current illness . Among them , 68/159 ( 42 . 8% ) were examined and treated for malaria , typhus or typhoid fever , while others ( 91 participants ) reported that they and their families received a treatment though they did not get adequate information for which disease they were treated . The remaining 491 ( 75 . 5% ) individuals did not seek treatment because of various reasons like distance from health facility , the intermittent nature of the illness or lack of money . History of abortion was reported by 116/325 ( 35 . 7% ) women and the majority ( 70 . 7% ) of them didn’t know the cause of the abortion . Out of 630 sera screened by the DCAT , 83 ( 13 . 2% ) were reactive for S . Typhi infection either against flagella ( H ) antigen ( 18/83 , 21 . 7% ) or against somatic ( O ) antigen ( 41/83 , 49 . 4% ) or against both H and O antigens ( 24/83 , 28 . 9% ) . Among the reactive sera to O antigen , 17 ( 19 . 54% ) , 8 ( 9 . 20% ) , 1 ( 1 . 2% ) and 1 ( 1 . 2% ) were reactive at the titration of 1:80 , 1:160 , 1:320 and 1:640 , respectively . Among the reactive sera to H antigen , 15 ( 22 . 73% ) , 9 ( 13 . 64% ) and 1 ( 1 . 52% ) were reactive at the titration of 1:80 , 1:160 and 1:320 , respectively . Thus , the overall sero-prevalence of current infection with S . Typhi as indicated either by H and/or O antigen was considered as 7 . 3% ( 46/630 ) at the cut off value ≥ 1:80 . The cases were more common among females than among males ( 17 . 2% vs 6 . 9% , X2 = 14 . 06 , P<0 . 001 ) as detected by DCAT and by the titration test ( 9 . 4% vs . 4 . 1% , X2 = 6 . 35 , P = 0 . 012 ) . All the randomly selected 25 samples which were non-reactive by DCAT were also found non- reactive by the titration test . In multivariable regression analyses , being female ( AOR = 2 . 21 , 95%CI: 1 . 01–4 . 83 , P = 0 . 047 ) and duration of illness above a month ( AOR = 2 . 70 , 95%CI: 1 . 02–7 . 18 , P = 0 . 046 ) were found to be associated with a high sero-positivity for S . Typhi infection ( Table 3 ) . Of the 630 sera screened for Rickettsia infection by DCAT , 165 ( 26 . 2% ) were reactive . Out of these sera , 41 ( 21 . 8% ) , 33 ( 17 . 6% ) , 9 ( 4 . 8% ) and 5 ( 2 . 7% ) were reactive at the titration of 1:80 , 1:160 , 1:320 and 1:640 , respectively . Hence , 88 ( 53 . 3% ) samples were reactive by the titration test at the cut off value ≥ 1:80 . The combined sero-prevalence for Rickettsia infection by the two tests was 14 . 0% ( 88/630 ) . The sero- prevalence was frequent among females compared to males ( 32 . 9% vs 15 . 8% , X2 = 22 . 74 , P<0 . 001 ) by DCAT , as well as by titration test ( 18 . 5% vs . 6 . 9% , X2 = 16 . 83 , P<0 . 001 ) . It was also higher among those individuals who reported headache compared to who did not ( 28 . 3% vs 20 . 0% , X2 = 4 . 18 , P = 0 . 041 ) by DCAT and ( 16 . 5% vs . 6 . 5% , X2 = 9 . 81 , P = 0 . 002 ) by titration test . All the 25 samples which were non-reactive by DCAT were also non-reactive by titration test . In multivariable regression analyses , being female ( AOR = 3 . 10 , 95%CI: 1 . 67–5 . 77 , P <0 . 001 ) and reporting headache ( AOR = 2 . 80 , 95%CI: 1 . 26–6 . 22 , P = 0 . 011 ) were significantly associated with sero-positivity for Rickettsia infection ( Table 4 ) . The sero-prevalence for Brucella infection among the study participants was 12 . 7% ( 80/630 ) by RBPT and 35% ( 28/80 ) by CFT . The combined sero-prevalence for Brucella infection by the two tests was 4 . 4% ( 28/630 ) . The sero-prevalence for Brucella infection was relatively high in the age group between 2–14 and 15–24 ( Table 5 ) . The sero-prevalence was also relatively high among individuals who reported drinking raw milk from aborted animals ( 13 . 0% vs . 6 . 9% ) by RBPT and ( 20 . 6% vs 6 . 7% ) by CFT . Among the study participants , 569 ( 90 . 7% ) reported drinking raw milk from aborted animals , 566 ( 90 . 3% ) touched aborted fetus/discharges from aborted animals without protection and 562 ( 90 . 1% ) responded that they had no clear information about a disease that causes abortion in their animals . In the univariable logistic regression analysis; being children ( COR = 3 . 43 , 95%CI:1 . 40–8 . 40 , P = 0 . 007 ) was found to be associated with high seropositivity for Brucella infection . On the other hand , age 45 and above was found to be associated with a low risk for Brucella infection ( COR = 0 . 22 , 95%CI: 0 . 06–0 . 75 , P = 0 . 015 ) . In multivariable logistic regression analysis , agropastoralism by occupation was associated with a high risk ( AOR = 9 . 51 , 95%CI: 2 . 30–39 . 34 , P = 0 . 002 ) for Brucella infection . None of the 68 samples which were negative by RBPT was found positive by CFT . The sero-prevalence of Brucella infection was not significantly associated with clinical symptoms reported by the study participants ( Table 6 ) . Of the 650 suspected individuals for malaria , 16 ( 2 . 5% ) were found positive for P . falciparum malaria infection microscopically , and P . falciparum was the only species detected . P . falciparum malaria cases were more common among males than among females ( 4 . 4% vs 1 . 3% , X2 = 6 . 14 , p = 0 . 013 ) . The case was also high in the age group between 2–14 years ( 8 . 8% , X2 = 25 . 13 , p < 0 . 001 ) and among individuals with body temperature ≥ 37 . 5°C ( 18 . 8% vs 1 . 6% , X2 = 35 . 80 , p < 0 . 001 ) . It was also high among individuals felt the illness for a week or less ( 4 . 4% , X2 = 6 . 59 , p = 0 . 037 ) . Multivariable regression analysis showed that being a male ( AOR = 4 . 47 , 95% CI:1 . 24–16 . 14 , P = 0 . 022 ) and having fever ≥ 37 . 5 °C ( AOR = 9 . 17 , 95%CI: 1 . 96–42 . 84 , P = 0 . 005 ) were independently associated with increased odds of having P . falciparum malaria infection ( Table 7 ) . Among the total 650 study participants who were tested for S . Typhi , Rickettsial , Brucella and/or Plasmodium infections , 344 ( 52 . 9% ) were found to be positive for one or more of the infectious agents by the screening tests ( Widal and Weilfelix direct card agglutination , Rose Bengal Plate Test and blood films ) . However , only 24 . 6% ( 160/650 ) were found to be positive for one or more of the infectious agents by the confirmatory tests ( titration test for S . Typhi and Rickettsia infections , and Complement Fixation Test for Brucella infection ) .
In this study , typhoid fever , typhus , brucellosis and malaria were observed among symptomatic individuals . The study also highlighted that brucellosis cases can be misdiagnosed as malaria or other disease based solely on clinical diagnosis . Therefore , efforts are needed to improve disease awareness and laboratory services for the diagnosis of brucellosis , which should be considered in the routine differential clinical diagnosis of febrile illness in the study area . Only a quarter of the study participants ( 24 . 6% ) were diagnosed for one or more of the above mentioned diseases . In the majority ( 75 . 4% ) of the symptomatic individuals , the cause of their illness remained unknown . In addition , a high prevalence of unexplained abortions in women ( 35 . 7% ) was observed . Hence , further community based studies on other zoonotic diseases like leptospirosis and Q fever are warranted to identify other causes of febrile illness in this pastoral setting .
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Many diseases such as typhoid fever , typhus , brucellosis and malaria show common symptoms such as fever , headache , joint pain and back pain . Hence , in countries where there is a problem of appropriate laboratory based diagnostic tools , health workers cannot properly diagnose these diseases and provide appropriate treatment . A community- based studies of the causative agents of the above mentioned illness would provide important information for health workers about some of the common causative agents in that particular area . In this study , we assessed the prevalence of typhoid fever , typhus , brucellosis and malaria among individuals who were complaining illnesses such fever , headache , joint pain and back pain in the pastoral of the Amibara district , Afar Region , Ethiopia . Among 650 individuals who were complaining symptoms , 46 ( 7 . 3% ) , 88 ( 14 . 0% ) , 28 ( 4 . 4% ) and 16 ( 2 . 5% ) were diagnosed for typhoid fever , typhus , brucellosis and malaria in that order . However , for the majority of the participants ( 75 . 4% ) , the cause of their illness remained unknown , and further investigations on the causative agents of febrile illness related symptoms is important in the present study area .
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"methods",
"Results",
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2018
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Community-based prevalence of typhoid fever, typhus, brucellosis and malaria among symptomatic individuals in Afar Region, Ethiopia
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Two species with similar resource requirements respond in a characteristic way to variations in their habitat—their abundances rise and fall in concert . We use this idea to learn how bacterial populations in the microbiota respond to habitat conditions that vary from person-to-person across the human population . Our mathematical framework shows that habitat fluctuations are sufficient for explaining intra-bodysite correlations in relative species abundances from the Human Microbiome Project . We explicitly show that the relative abundances of closely related species are positively correlated and can be predicted from taxonomic relationships . We identify a small set of functional pathways related to metabolism and maintenance of the cell wall that form the basis of a common resource sharing niche space of the human microbiota .
Species in an ecosystem interact with each other and with their environment . Both types of interactions leave an imprint on the composition and diversity of a community . Two species competing for exactly the same resources engage in a struggle for existence [1] . In the end , one species will win the competition by driving the other to extinction . As a result , one might expect that closely related species rarely occupy the same habitat where they would risk being drawn into competition . On the other hand , species that survive in the same habitat must share many common features [2] . Thus , the rise and fall of a common resource may cause the abundances of similar species to rise and fall in concert . These opposing ecological forces simultaneously push and pull on species abundances to shape the composition of a community . Ecological processes operate on the thousands of microbial species that inhabit the human body [3–6] just as they operate on the Amazon rainforest . Technological advances have recently made it possible to study the human microbiota using 16S ribosomal RNA tag-sequencing and whole genome ‘shotgun’ metagenomics [7] . Variability in the composition of the microbiota can be studied in two ways . Longitudinal studies follow the relative abundances of the species in a single bodysite of a particular person over time [8] . Cross-sectional studies examine the relative abundances of the species in a single bodysite across a sample of many different people [9] . These studies have demonstrated that the composition of the human microbiota exhibits three qualitative scales of variation [10 , 11]: there are small-scale fluctuations in relative species abundances through time , there are medium-scale variations in species composition from person-to-person , and there are large-scale differences in species composition between different bodysites . In this work we quantitatively explore the idea that variations in species abundances between different sites can be explained mainly through the local variations in resource availability . Concretely , we reanalyze data from the Human Microbiome Project ( HMP ) [3–5 , 12] on the species composition of different bodysites ( i . e . , gut , skin , vagina , and oral cavity; Fig 1 ) . To develop the analysis method , we start from a theoretical model that assumes maximal diversity of species and derives a relationship between species abundance and resource availability . We then use the results of this model to guide the joint analysis of the datasets from different body sites in the HMP project , introducing a new Common Component Analysis ( CoCA ) method . The general idea is that if the same species exist in different body sites , the same resources must also be present at these body sites . We find that this intuition is correct by showing that the covariance of species abundances at specific body sites can be simultaneously projected into the same basis that describes the availability of effective resources . This means that the abundances of species at different body sites are driven by the same set of resources , just different resources are of varying importance at different body sites . These results cannot be reproduced from randomized data and reflect an underlying global set of ecological resources shared between body sites . Our method identifies species that share common resources . To understand the source of this sharing , we look for similarities between the species . We find that species that share common resources are also closely related taxonomically , suggesting that evolution is constrained by ecology . We further back this observation by identifying specific metabolic pathways that are conserved between species identified as close using our resource sharing analysis . The goal of this work is three-fold . First , we introduce a new analysis technique that identifies covariations among components in different subsets that are driven by the same process ( CoCA ) . Second , by successfully applying the CoCA analysis technique to HMP data , we show that the diversity of the microbiome at different body sites is shaped by common biological processes . Third , in the case of the specific problem of species at different ecological sites , we make the biological point that microbiome species that share the same resources are also closely related taxonomically and we back this fact by identifying shared pathways . The methodological developments are presented in the “Theory” subsection of the Results and the biological results in the“Analysis” subsection . For readers predominantly interested in the biological results the “Analysis” subsection can be read independently of the “Theory” subsection . In addition to presenting statistical evidence for the observations described above , we formulate a hypothesis ( in the form of a mathematical model ) that explains their origin . Our model is inspired by MacArthur’s famous model of competition [1 , 13–15] , but is adapted to account for the compositional nature of metagenomic survey data . We demonstrate that habitat variability is sufficient to explain the medium-scale variations in species composition observed in a cross-sectional study of the human microbiota . As a result , the relative abundances of closely related species are positively correlated—they rise and fall in concert as habitat conditions vary from person-to-person . Therefore , cross-sectional studies allow us to extract a wealth of information about the influence of species traits and habitat properties on community composition using advanced statistical techniques .
Although we have stated the maximum diversity hypothesis as a generative model of species composition , we rarely know , and generally cannot measure , all of the effective resources in a community . Therefore , we treat the mathematical model as an inverse problem with the goal of inferring the effective resources from observations of species composition across many individuals and bodysites . The inverse problem can be solved because , by construction , the model imposes that the inferred effective resources correspond to directions with high intra-bodysite variability ( Fig 2A–2C ) . We exploit this feature to developed a technique we called CoCA that infers the characteristics of the species and habitats from observed correlations ( S1 Text ) . Like other techniques for simultaneous matrix diagonalization [19–21 , 28] , CoCA aims to find a single set of directions that simultaneously explain variation within each of the bodysites . Moreover , CoCA has a theoretical interpretation derived from the maximum diversity hypothesis and properly accounts for the compositional nature of genomic survey data . Our statistical analysis of the data from the Human Microbiome Project ( HMP ) centers on three observations: The first point is a validation of our mathematical model , whereas points 2 and 3 demonstrate that the results obtained by CoCA have biologically reasonable interpretations . Point 3 is a corollary of point 2; if taxonomy explains species relationships in the common basis then it follows that there will also be a relationship with characteristics that vary by taxonomy ( e . g . , metabolic pathways ) . Nevertheless , it is important to check that the pathways that are selected make biological sense . We compare the CoCA results to PCA , as well as to the results of the CoCA algorithm applied to randomized data ( S1 Text ) . Previous studies have revealed that bacteria exhibit tremendous genomic and functional diversity due , in part , to high rates of horizontal gene transfer ( HGT ) [36] . As a result , the ability of sequence-based or taxonomic classification of bacteria to capture ecological relationships has been called into question [37–40] . Nevertheless , we found that genetically related species respond to fluctuating habitat conditions in the same way , implying that they occupy similar ecological niches . Thus , current taxonomic groupings of bacteria are largely sufficient for explaining cross-sectional correlations in relative species abundances over the healthy human population . This result is not at odds with high rates of HGT; it simply implies ecologically derived constraints on evolution . We introduced CoCA , a theory-driven data analysis technique that can be applied to any cross-sectional study with labeled metadata , including studies with populations corresponding to healthy and unhealthy individuals . Although the effective resources identified by CoCA are derived entirely from data on relative species abundances across a population , they reflect indirect ecological relationships between species that are mediated through resources and form the basis of a common resource sharing niche space of the human microbiota . Future analyses of larger , and more diverse , datasets will further elucidate the relationship between this underlying niche space and the functional properties of the organisms in the microbiota . Given that CoCA identifies features that separate the bodysites with high fidelity , we believe that it is a useful technique for identifying microbiota based biomarkers that discriminate between host phenotypes . Extending our results to include data from unhealthy subjects will be an important avenue for future work . A recent paper by Bashan et al [41] developed an approach to analyzing microbial dynamics based on a Dissimilarity-Overlap Curve . They found that communities with a high overlap in the species that were present also have a low dissimilarity in their relative abundance profiles . They argue that this relationship is evidence of “universality” where interspecies interactions are essentially the same across a population of human subjects . Our model is also based on the assumption that the underlying drivers of variation in the microbiota are the same across subjects and across bodysites , and it is only the relative importance of these factors that leads to differences between groups . However , we focused only on variation in the relative abundances of highly abundant species that are present across all four major bodysites in the Human Microbiome Project rather than variation in species assemblages . The successful application of CoCA to HMP data from four different body sites implies that the processes that shape the variation in species abundances are shared between bodysites , and only changes in the specific contribution of various effective resources differentiate bodysites . CoCA uses simultaneous diagonalization to identify processes that are shared between communities . Covariance matrices from communities without shared drivers of variation cannot be simultaneously diagonalized , as we showed with randomized data . Consequently , we would expect that CoCA would fail on datasets from clearly different ecological environments ( e . g . , hot springs compared to body sites ) . In this case , failure is not a bad thing: it can be easily diagnosed from the poor agreement between the predicted and observed covariances and it provides an ecologically meaningful result be ruling out the hypothesis that the environments have shared drivers of variation . CoCA does not explain 100% of the variation in the HMP data , nor do taxonomic relationships explain 100% of the variation in the inferred resource utilizations . The additional variation is likely do to other types of interactions between species in the human microbiota that cannot be captured using effective resources that are shared across bodysites . Moreover , effective resources are only defined by a statistical model and , therefore , do not have obvious relationships to measurable environmental variables . Here , we attempted to explain the inferred effective resources in terms of metabolic processes inferred through KEGG pathways but it is likely that other factors , such as resilience to temperature or pH ranges , contribute to the effective resources in ways that our analysis with KEGG pathways could not uncover . Our study also has other limitations that should be addressed in future work . We have based our analyses on relative species abundances derived from OTUs constructed using data from the HMP . These data are likely to be noisy , but the degree of uncertainty is difficult to quantify . Moreover , the use of OTUs defined by 97% sequence identity , and subsequent reduction of the communities to 100 highly abundant species , leads to a coarse grained representation that may smooth out relevant features . It will be important to revisit our analyses on additional datasets , and with additional tools for generating highly accurate pictures of community composition . On the theoretical side , it will be important to examine the validity of the maximum diversity hypothesis across communities with different properties .
We analyzed data from the Human Microbiome Project ( HMP ) on person-to-person variability in relative species abundances in four bodysites ( gut , oral cavity , vagina , and skin; Fig 1A ) [3–5 , 12] . The species-level relative abundances derived from the HMP whole genome sequencing data were obtained from MG-RAST ( Project 385 ) through the MR-RAST API [42] . Only the processed data as provided on the MG-RAST server were extracted . Thus , these species counts were constructed using the default MG-RAST pipeline [43] . Briefly , this pipeline identifies putative rRNA fragments and clusters them at 97% identity to define operational taxonomic units , which are assigned species labels using a search against the M5rna database [44] . We eliminated any lowly abundant species and selected for further study 100 species ( Fig 3A ) that were highly abundant across all bodysites , as described in S1 Text . The final dataset ( consisting of the counts of the 100 selected species in each of the samples ) is available in the Supporting Information ( S1 Code ) and at https://sites . google . com/site/charleskennethfisher/home/programs-and-data along with the source code . Log-ratio transformations are obtained using y = G log x , where x is an N dimensional vector of relative abundances , G is an N − 1 × N matrix with G1 = 0 , and y is an N − 1 dimensional vector of transformed relative abundances . We use a G that implements an additive log-ratio ( or ALR ) transform , but the choice of G is not critical for our analyses and some other possible choices are discussed further in the S1 Text . Applying a log-ratio transformation to Eq 2 gives y = G V λ = V ˜ λ . Here , V is an N × N − 1 dimensional matrix whereas V ˜ = G V is an N − 1 × N − 1 dimensional matrix . Once again , the use of relative abundances shows up as a loss of information . The matrix V that contains the information about all N species that we would like to obtain can only be recovered from V ˜ using some assumptions . The use of compositional transformations with CoCA requires an extra step to recover the N × N − 1 dimensional matrix V from the N − 1 × N − 1 dimensional matrix V ˜ = G V . Unfortunately , the matrix G is not invertible . But , if we assume that V is sparse then it is possible to determine V from V ˜ . In the context of the model , this assumption means that any individual consumer species is unlikely to be able to utilize every effective resource . To recover V from V ˜ , we solve the problem: min | | V | | 1 subject to G V = V ˜ ( 5 ) where ||V||1 = ∑iμ |Viμ| . Using the ALR transform , all of the solutions to this problem are all of the form V i μ = z μ + V ˜ ( i - 1 ) , μ ( 1 - δ i 1 ) for i = 1 , … , N , where zμ can , in principle , take on any real value . Because we want the solution with a minimum L1 norm , it is sufficient to test zμ = 0 and z μ ∈ { - V ˜ i , μ } i = 1 N - 1 ( the only sparse solutions ) and to choose the one with minimum norm . This is a tractable search over N ( N − 1 ) possibilities in the worst case and can be done easily for reasonable system sizes . Each row of the matrix V = G V ˜ ( here , G is a matrix that arises from the log-ratio transform—see details ) describes how one of the species responds to changes in the latent variables . Thus , the ith row of V is a mathematical representation of species i . The distance between species i and j in the inferred basis can be calculated by computing the distance between the ith and jth rows of V with each column ( i . e . , latent variable ) weighted by its variance ( S1 Text ) . Distances between species computed from the common components were regressed against the distances computed from KEGG pathways ( S1 Text ) . To select relevant pathways , we compute posterior probabilities for each regression coefficient to be non-zero using the Bayesian Ising Approximation ( BIA ) [34 , 35] . The BIA approximates the posterior distribution of a vector indicator variables with si = +1 if pathway i relevant and si = − 1 if pathway i is not relevant . The posterior distribution is approximately an Ising model described by: log P λ ( s | y ) ≃ n 2 4 λ ∑ i h i ( λ ) s i + 1 2 ∑ i , j ; i ≠ j J i j ( λ ) s i s j ( 6 ) where the external fields ( hi ) and couplings ( Jij ) are defined as: h i ( λ ) = r 2 ( y , x i ) - 1 n + ∑ j J i j ( λ ) ( 7 ) J i j ( λ ) = λ - 1 r 2 ( x i , x j ) - n λ r ( x i , x j ) r ( y , x i ) r ( y , x j ) - 1 2 r 2 ( y , x i ) r 2 ( y , x j ) ( 8 ) and λ is the inverse variance of the prior distribution . Here , r ( z1 , z2 ) is the Pearson correlation coefficient between variables z1 and z2 . The BIA approximation is based on a series expansion that is valid as long as: λ ≥ λ * = n ( 1 + p r ) . ( 9 ) where r = p - 1 ( p - 1 ) - 1 ∑ i ≠ j r 2 ( X i , X j ) is the root mean square correlation between features . To perform feature selection , we are interested in computing marginal probabilities Pλ ( sj = 1|y ) ≃ ( 1 + mj ( λ ) ) /2 , where we have defined the magnetizations mj ( λ ) = 〈sj〉 . While there are many techniques for calculating the magnetizations of an Ising model , we focus on the mean field approximation which leads to a self-consistent equation: This mean field approximation provides a computationally efficient tool that approximates Bayesian feature selection for linear regression .
|
The human body is inhabited by a vast number of microorganisms comprising the human microbiota . The species composition of the microbiota varies considerably from person-to-person and the relative abundances of some species rise and fall in concert . We introduce a mathematical model where differences in habitat conditions cause most of the variability of the microbiota . A statistical analysis shows that variable habitat conditions are sufficient for explaining the patterns of variation observed across a healthy human population and , as a result , the correlation between the relative abundances of two species reflects how closely related they are rather than how they directly interact with each other .
|
[
"Abstract",
"Introduction",
"Results",
"and",
"discussion",
"Methods"
] |
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2017
|
Variable habitat conditions drive species covariation in the human microbiota
|
In the natural environment , animals often encounter multiple sensory cues that are simultaneously present . The nervous system integrates the relevant sensory information to generate behavioral responses that have adaptive values . However , the neuronal basis and the modulators that regulate integrated behavioral response to multiple sensory cues are not well defined . Here , we address this question using a behavioral decision in C . elegans when the animal is presented with an attractive food source together with a repulsive odorant . We identify specific sensory neurons , interneurons and neuromodulators that orchestrate the decision-making process , suggesting that various states and contexts may modulate the multisensory integration . Among these modulators , we characterize a new function of a conserved TGF-β pathway that regulates the integrated decision by inhibiting the signaling from a set of central neurons . Interestingly , we find that a common set of modulators , including the TGF-β pathway , regulate the integrated response to the pairing of different foods and repellents . Together , our results provide mechanistic insights into the modulatory signals regulating multisensory integration .
An environment is often represented by numerous sensory cues . In order to better survive , an animal often needs to detect and process simultaneously present sensory cues to make a behavioral decision [1–8] . Because integrating multiple sensory cues generates a more accurate evaluation of the environment , it provides important adaptive values . Multisensory integration is widely observed in both vertebrate and invertebrate animals . Previous studies using behavioral and psychophysical approaches show that humans and other organisms can integrate an array of sensory stimuli to generate decisions in every-day life [9–11] . One common characteristic of multisensory behavioral responses and decision-making processes is their ability to be modulated by various internal states and contexts , including arousal , sleepiness versus wakefulness , the motivational or nutritional state of the organism , or the level of the reward paired with the stimuli . Neurotransmitters , such as dopamine , serotonin , glutamate , and neuropeptides , mediate many of these neurological effects on decision-making . In addition , patients of several neurological diseases , including autism spectrum disorder and schizophrenia share deficits associated with sensory processing or decision-making when encountering multiple sensory stimuli [3 , 4 , 12–20] . Together , these studies reveal multisensory integration as a common neuronal and behavioral process modulated by multiple contexts across the animal kingdom . Despite the importance of multisensory integration in animal behavior , our understanding of the underlying mechanisms remains preliminary . The nematode C . elegans provides an opportunity to address the question . C . elegans feeds on bacteria . A bacteria lawn provides various types of sensory information , including olfactory , gustatory , mechanical , and gaseous cues . The small nervous system ( 302 neurons ) of C . elegans hermaphrodite generates sensorimotor responses to these modalities [21–32] and many of the responses can be shaped by external and internal contexts that modulate neural activities [4 , 33–37] . The C . elegans genome encodes the homologues of about 50% of the molecules expressed in the mammalian brains [38] , which in combination with a well-defined wiring diagram of the nervous system [39] allows characterization of the molecular and circuit basis for multisensory integration during decision-making . Here , we show that C . elegans integrates the information from an attractive food lawn and a simultaneously present repellent to generate a decision on leaving . We show that the decision to leave the lawn depends on the attractiveness of the lawn and the concentration of the repellent . We identify specific neurons and modulatory molecules that promote or suppress the food-repellant integration underlying the lawn-leaving decision . We further demonstrate that several modulatory molecules and neurons act as common modulators to regulate integrated decisions on different foods paired with different repellents . These findings identify conserved neuronal signals that modulate multisensory processing during decision-making and reveal a modulatory basis for multisensory integration .
To establish a behavioral assay for multisensory integration in C . elegans , we presented a repulsive odorant , 2-nonanone , to the animals on a small lawn of the E . coli strain OP50 ( Fig 1A and Experimental Procedures ) and assessed the decision of the animals to stay on or leave the lawn over time . Because the OP50 lawn serves as a food source for the worm , under the standard condition C . elegans stays on the lawn and leaves only at a low frequency [40 , 41] . Meanwhile , 2-nonanone strongly repels C . elegans at concentrations ranging from 10% to 100% . The olfactory sensory neurons AWB detect and mediate the avoidance of 2-nonanone [42–44] . We first presented a drop of 10% 2-nonanone close to the edge of an OP50 lawn , on which 15–25 young adults acclimatized for one hour ( Fig 1A ) . We found that within a few minutes the animals migrated to the side of the bacterial lawn away from 2-nonanone , stayed on the edge of the lawn before dispersing throughout the lawn without leaving ( Fig 1B ) . This result indicates that C . elegans is able to detect and avoid 10% 2-nonanone even on the food lawn , but the repulsion is not strong enough to suppress the retention of the worm by the food lawn . In contrast , when we presented a drop of higher concentration of 2-nonanone to the worms in the same configuration , the worms migrated to the side of the lawn , started to leave the food lawn in a few minutes , and continued to migrate to the edge of the plate away from the repellent within the one-hour time window of the assay ( Fig 1B and 1C and S1 Movie ) . The food-leaving behavior was robustly evoked with 100% 2-nonanone ( Fig 1B–1E ) , under which condition a significant number of worms already left the lawn after 2-nonanone was presented to the worms for 15 minutes ( Fig 1C ) . In addition , it took a similar amount of time for the worms to reach the edge of the lawn that was paired with either 10% or 100% 2-nonanone ( Fig 1D ) . These results show that C . elegans integrates the attraction of a food lawn with the repulsion of 2-nonanone to generate a behavioral decision and that increasing concentration of 2-nonanone enhances lawn leaving ( Fig 1B and 1C ) . These findings are consistent with the general rule that governs multisensory integration , where increasing the reliability of a sensory cue , such as increasing the concentration of 2-nonanone , strengthens the weight of the cue in integration [45] . To characterize the regulatory mechanisms underlying multisensory integration , we used 100% 2-nonanone as the repellent for the rest of the study unless otherwise described . We quantified the percentage of the worm outside the OP50 lawn 15 minutes after the assay began unless otherwise described , because it was an early time point when wild type started to show a robust leaving decision . To characterize how the nervous system regulates the integrated response to the attractive OP50 lawn and the repulsive odorant 2-nonanone , we first probed the amphidal sensory neurons AWB , which mediate avoidance of 2-nonanone via the function of the cGMP-gated channel subunit tax-2 [42] . Exposure to 2-nonanone suppresses the intracellular calcium transients of AWB [43 , 44] . Consistently , we found that the transgenic animals that selectively expressed a hyperactive form of an amiloride-sensitive sodium channel MEC-4 that generated necrosis of AWB [42 , 46] did not leave the OP50 lawn when 2-nonanone was present ( Fig 2A ) and that many of the worms remained diffusely distributed on the food lawn by the end of the assay . These transgenic animals were defective in avoiding 2-nonanone in the standard chemotaxis assay ( Table 1 and S1 Fig ) , consistent with previous findings [42] . AWB-killed animals also spent more time to reach the edge of the OP50 lawn when 2-nonanone was present ( Table 2 ) , consistent with the role of AWB in mediating the avoidance of 2-nonanone . Meanwhile , the transgenic animals with genetically killed AWB stayed on OP50 lawn similarly as wild type when 2-nonanone was not present ( Table 3 ) . Together , these results show that AWB regulate the integrated response by mediating the response to the unisensory repellent 2-nonanone . Next , we sought additional sensory neurons that regulated the integrated behavioral decision . Previous studies identify several sensory neurons that respond to the smell of the E . coli strain OP50 or mediate the behavioral response to the presence or removal of food [21 , 43 , 47–50] . To examine the potential role of these sensory neurons in our multisensory integration paradigm , we first tested a null mutation ky4 in odr-7 , which encodes a putative DNA-binding nuclear receptor that specifies the function of the AWA sensory neurons [51] , a null mutation p680 in che-1 , which encodes a zinc finger transcription factor required for the development and function of the ASE sensory neurons [52] , transgenic animals that selectively express a cell-death activator EGL-1 [53] in the AQR , PQR and URX neurons or the CO2-sensing BAG sensory neurons [27–29 , 54–56] . We also tested transgenic animals selectively expressing a cell-death inducing caspase , or twk-18 ( gf ) that encodes a constitutively active form of the potassium channel TWK-18 [57] , or tetanus toxin that eliminates the synaptic release [58] in the ASI , AWC , ASJ , ADL or ASK neurons [48 , 54 , 59–63] . We found that all except three of the tested strains were normal . The transgenic animals that contained genetically-killed ASK left the OP50 lawn significantly faster than wild type , and the transgenic animals that contained genetically-killed ASI or expressed the tetanus toxin in ADL left the OP50 lawn significantly more slowly than wild type ( Fig 2B–2D and Table 4 ) . Because the transgenic animals defective in the function of ASK or ASI or ADL are not deficient in avoiding 2-nonanone in our standard chemotaxis assay , in their ability to remain on OP50 lawn when 2-nonanone is not present , as well as in moving to the edge of the OP50 lawn with the presence of 2-nonanone ( Tables 1–3 ) , these results together indicate that the sensory neurons ASK , ASI and ADL modulate how rapidly the behavioral decision to leave the repellent-paired food lawn is made . To characterize the mechanisms underlying multisensory integration of food and 2-nonanone , we examined mutants that were defective in biosynthesis of neurotransmitters . We tested effects of mutating tph-1 that encodes tryptophan hydroxylase required for the production of serotonin [64] , cat-2 that encodes tyrosine hydroxylase needed for the synthesis of dopamine [65] , tdc-1 that encodes tyrosine decarboxylase required for the synthesis of tyramine and octopamine , or tbh-1 that encodes tyramine beta hydroxylase required for the production of octopamine [66] . Interestingly , all of these mutants exhibited wild-type behavioral decision when they were exposed to 2-nonanone on an OP50 food lawn ( Figs 3A–3D and S2 ) . These results show that serotonin , dopamine , tyramine or octopamine are not required for 2-nonanone-dependent food leaving , although these neurotransmitters regulate many food-dependent sensorimotor responses ( [31] and references therein ) . Next , we examined the function of neuropeptide-encoding genes . We first found that mutations in the kpc-1 ( gk8 ) and egl-3 ( n150 ) , which disable two of the four known peptide pre-processing enzymes in C . elegans [67–69] , delayed the decision to leave the food lawn paired with 2-nonanone ( Fig 3E and 3F ) , suggesting the modulatory role of peptides or growth factors in promoting the integrated decision . Next , we screened many mutations in genes encoding peptides or growth factors . We focused on the available mutations that did not generate any gross defect in either development or locomotion and identified three mutations that significantly altered the wild-type decision . The canonical mutations , e1372 , or a deletion , ok3125 , in daf-7 that encodes a TGF-β ligand that regulated development , metabolism and host-pathogen recognition [70–72] , significantly delayed the decision to leave the OP50 lawn paired with 2-nonanone ( Fig 3G and 3J ) . A deletion mutation tm2984 in nlp-7 , which encodes a neuropeptide-like protein that regulates stress response , egg-laying , life span and modulation of aversive responses to noxious stimuli [73–76] , similarly delayed the decision to leave the lawn ( Fig 3H ) . However , the mutations in daf-7 or nlp-7 did not generate any detectable defect in the chemotactic response to 2-nonanone alone , or the tendency to leave the OP50 lawn when no repellent was present , or the ability to move to the edge of the lawn when 2-nonanone was present ( Tables 1–3 ) . In addition , expressing the genomic fragment containing the regulatory and coding regions of daf-7 or nlp-7 rescued the defect of the respective mutant animals in making the decision to leave the lawn that was paired with 2-nonanone ( Fig 3I and 3J ) . Together , these results indicate that TGF-β/DAF-7 and NLP-7 promote the food-leaving decision when 2-nonanone is present . The C . elegans TGF-β/DAF-7 regulates several physiological processes through the conserved type I and type II TGF-β receptor , DAF-1 and DAF-4 , respectively [77 , 78] . DAF-7 is found in the sensory neurons OLQ , ADE and ASI , all of which are implicated in sensing bacteria [22 , 70 , 71 , 79 , 80] . DAF-7 produced by ASI regulates the satiety-induced quiescence , the entry into an alternative developmental stage under the environmental stress , and the modulation of the lifespan by dietary restriction , and responds to the abundance of food [71 , 79–82] . The expression of daf-7 is induced in the sensory neurons ASJ upon exposure to pathogenic bacteria and DAF-7 in ASJ regulates the avoidance of the pathogen through DAF-1 and DAF-4 receptors [70] . In addition , through DAF-1 and DAF-4 , DAF-7 regulates metabolism and fat accumulation [72] . Here , we showed that mutating daf-7 delayed the decision to leave the food lawn when 2-nonanone was present ( Fig 3G ) . To identify the source of the DAF-7 signal regulating multisensory integration , we tested the transgenic animals that selectively expressed a wild-type daf-7 cDNA in subsets of daf-7-expressing neurons in daf-7 mutant animals for potential rescuing effects . We found that expressing daf-7 selectively in ASI ( Pstr-3::daf-7 [70] ) did not rescue the defects in the integrated response; but expressing daf-7 in ADE ( Pcat-2::daf-7 ) or OLQ ( Pocr-4::daf-7 ) sensory neurons using cell-selective promoters [83–85] rescued the delayed leaving phenotype in the daf-7 ( e1372 ) mutant animals ( Fig 3K–3M ) . In addition , we found that the canonical mutation in the type I and type II TGF-β receptor , daf-1 ( m40 ) , similarly delayed the decision to leave the OP50 lawn paired with 2-nonanone ( Fig 4A ) . Expressing either the genomic DNA fragment of daf-1 or the daf-1 cDNA selectively in the interneurons RIM and RIC ( Pdaf-1::daf-1 or pRIM/RIC::daf-1; [70 , 72] ) fully rescued the defect in the daf-1 ( m40 ) mutant animals ( Fig 4B and 4C ) , while expressing daf-1 in sensory neurons ( Pbbs-1::daf-1 or Posm-6::daf-1; [70] ) was not sufficient to rescue ( Figs 4D and S3 ) . Together , these results indicate that the TGF-β/DAF-7 signal produced by the ADE or the OLQ sensory neurons acts through the type I TGF-β receptor DAF-1 in RIM and/or RIC neurons to promote repellent-dependent leaving of a food lawn . To further interrogate the role of the RIM/RIC neurons in multisensory integration , we examined the transgenic animals that expressed a histamine-gated chloride channel in the RIM and RIC neurons under the histamine-treated condition [86] or the transgenic animals that expressed tetanus toxin [58] in RIM and RIC . We found that these transgenic animals were normal in leaving the OP50 lawn when 2-nonanone was present ( Fig 4E and 4F ) . Since neither the tdc-1 ( n3419 ) mutant animals that lack tyramine and octopamine nor the tbh-1 ( n3247 ) mutant animals that lack octopamine are defective in their decisions to leave the OP50 lawn paired with 2-nanone ( Fig 3 ) , together , our results suggest that RIM/RIC and the release of the neurotransmitter tyramine and octopamine from these neurons may be suppressed during the integrated response to the simultaneously present food lawn and 2-nonanone . To further interrogate the role of tyramine or octopamine signaling in the daf-7- and daf-1-dependent integrated response , we tested how removing tyramine and/or octopamine affects the delayed food leaving in the daf-7 ( e1372 ) or daf-1 ( m40 ) mutant animals . Interestingly , both of the daf-1 ( m40 ) ; tbh-1 ( ok1196 ) and the daf-7 ( e1372 ) ; tbh-1 ( ok1196 ) double mutant animals [72] behaved like the daf-1 ( m40 ) and the daf-7 ( e1372 ) single mutants , respectively ( Fig 4G ) . In contrast , the mutation in tdc-1 ( ok914 ) strongly suppressed the delayed decision phenotype in both daf-7 ( e1372 ) and daf-1 ( m40 ) mutant animals ( Fig 4H and 4I ) . While TDC-1 is needed for the production of tyramine and octopamine in both RIM and RIC , TBH-1 is only needed for the biosynthesis of octopamine in RIC [66] . Together , these results show that the TGF-β/DAF-7 regulates the decision between staying on a food lawn versus avoiding a repellent through the canonical signaling pathway and that the DAF-7 signal produced from ADE or OLQ inhibits the tyramine neurotransmission of RIM and/or RIC to promote the decision to leave the food-lawn that is paired with 2-nonanone . To better characterize the neural circuits underlying multisensory integration , we probed the potential interneurons that regulated the decision between staying on the food lawn versus avoiding 2-nonanone . We focused on the interneurons AIY , AIB , and the command interneurons , all of which regulate locomotion [21 , 87] . AIY and AIB are also the major interneurons postsynaptic to the sensory neurons that respond to the bacteria food or the repellent 2-nonanone [39] . To disrupt the function of AIY , we selectively expressed in AIY a gain-of-function isoform of a potassium channel TWK-18 [57] to inhibit the activity of AIY ( Pttx-3::twk-18 ( gf ) ) or the tetanus toxin ( Pttx-3::TeTx ) to block the synaptic release . We also tested the ttx-3 ( mg158 ) mutants that fail to develop AIY interneurons [88] . All three mutations delayed the decision to leave the lawn ( Fig 5A–5C ) . However , these manipulations do not disrupt the ability to reach the edge of the food lawn during 2-nonanone-dependent food leaving , to avoid 2-nonanone alone , or to stay on OP50 lawn when no repellent was present ( Tables 1–3 ) . In contrast , selectively expressing the tetanus toxin in the AIB interneurons or treating the transgenic animals expressing the histamine-gated chloride channel in AIB with histamine did not significantly alter the decision to leave the OP50 lawn that was paired with 2-nanonone ( Fig 5D and 5E ) . Together , these results indicate that the activity and the synaptic output of the AIY interneurons promote the decision to leave the food lawn paired with 2-nonanone , while AIB are dispensable for the decision-making . Next , we examined transgenic animals that expressed the tetanus toxin with the nmr-1 promoter or the glr-1 promoter . The nmr-1 promoter is expressed in a few command interneurons including AVA , AVB , AVD , AVE and PVC , while the glr-1 promoter is expressed in several head motor neurons in addition to the nmr-1-expressing interneurons [89] . Interestingly , both transgenic lines left the 2-nonanone paired food lawn more than wild type ( Fig 5F and 5G ) . However , these transgenic animals are normal in 2-nonanone avoidance in the absence of food or spontaneous food leaving . They also do not reach the edge of the lawn more rapidly than wild type ( Tables 1–3 ) . Together , these results show that different downstream neurons modulate the decision to leave the food lawn paired with a repellent in opposite ways by promoting or inhibiting the decision-making process . These neurons may act as the convergent sites to process multiple sensory signals in order to generate specific behavioral outputs . Next , we asked whether the molecular and circuit mechanisms underlying the integrated response to the OP50 food lawn paired with 2-nonanone were shared by the integrated responses to different pairing of attractive foods and repulsive odorants . We paired the OP50 lawn with various repellents , including 100% 1-octanol and 100% benzaldehyde . While benzaldehyde is attractive at low concentrations [23] , 100% benzaldehyde strongly repels C . elegans in a way that is dependent on the function of the sensory neurons AWB [90–92] . We found that a drop of 100% benzaldehyde first repelled the animals to the edge of the OP50 food lawn and then in about 10–15 minutes started to repel the animals off the food lawn ( Fig 6A and S2 Movie ) . This decision to leave depends on the function of the sensory neurons AWB ( Fig 6B ) . Interestingly , 1-octanol failed to stimulate food leaving under our experimental conditions ( Fig 6A ) . We also paired a lawn of Comamonas sp with 100% 2-nonanone . Comamonas is an attractive food source for C . elegans [40] . We found that pairing a Comamonas bacteria lawn with 100% 2-nonanone repelled C . elegans off the lawn similarly as the OP50 lawn paired with 2-nonanone ( Fig 7A ) . Interestingly , we found that several modulators , particularly TGF-β/DAF-7 , the TGF-β receptor DAF-1 , and the sensory neurons ASK , that regulated the integrated response to an OP50 lawn paired with 100% 2-nonanone also similarly regulated the integrated response to OP50 lawn paired with 100% benzaldehyde and the integrated response to the Comamonas lawn paired with 100% 2-nonanone ( Figs 6 and 7 ) . Together , these results indicate that a common set of modulators and signaling mechanisms regulates the integrated behavioral decisions on whether to leave or stay on an attractive food lawn paired with an odorant repellent . For freely feeding animals , such as C . elegans , appropriate behavioral responses to food sources paired with other sensory cues are critical for survival , because food can be easily found in close proximity to toxins . It is conceivable that a common set of modulators represent the contexts where the worm needs to evaluate the opposing values provided by a source of nutrients and a potential threat to generate a behavioral decision .
One potential mechanism to regulate a coherent behavioral response to multiple simultaneously present sensory cues is to utilize sensory neurons that are capable of perceiving some or all of the cues . These types of sensory responses can involve either the activation or the inhibition of certain sensory neurons that detect distinct stimuli . Worms are capable of sensing both food signals and a range of repulsive cues ( [31] and the references therein ) using a variety of sensory neurons . Here , we confirm the requirement of the AWB sensory neurons that are known to sense repellents , including 2-nonanone and 100% benzaldehyde [42 , 44 , 90] . AWB also respond to bacteria food [43 , 50] . Previous studies identify the role of AWB in promoting food leaving under malnourished conditions [93] , suggesting the involvement of AWB in integrating the nutritional state with the food signals . Thus , AWB may regulate the integrated response by simultaneously processing food smells and repulsive odorants . Interestingly , we also uncover a critical and specific role of three sensory neurons , ASK , ADL and ASI , in modulating the decision to leave a food paired with a repulsive odorant . Previous studies show that ASK and ASI sensory neurons respond to E . coli OP50 [50 , 94] . Both ASI and ASK are involved in evaluating the properties of the food in the environment [49] . ASI also mediate the balance between food intake and fat storage , as well as experience-dependent changes in food response [36 , 72 , 79–81 , 95] . ASK regulate the responses to the pheromones and mediate food leaving in animals that are significantly food-deprived [62 , 63 , 93] . Thus , it is possible that ASI and ASK neurons sense the olfactory signal of food and/or the satiety signal to regulate the multisensory integration . The ADL sensory neurons have been shown to regulate the responses to the repellent octanol , the pheromones and the preference for certain food odors [42 , 63 , 76 , 96] . Therefore , it is conceivable that ADL regulate the multisensory integration by mediating the response to the repulsive odorants . How neuromodulators regulate a behavioral decision that integrates cues of opposing values is not well understood . Previous studies in C . elegans have implicated neuropeptides and growth factors in the context-dependent modulation of several sensorimotor responses [3 , 33 , 76 , 95 , 97 , 98] . Here , we show that the NLP-7 peptide and TGF-β/DAF-7 modulate the decision to leave a food lawn paired with a repulsive odorant . nlp-7 is expressed in several amphidial sensory neurons that respond to contextual cues and NLP-7 delays the acute avoidance of a noxious stimulus , 1-octanol [73–76 , 99] . This effect is in contrast with that of mutating nlp-7 in the integrated behavioral response , where NLP-7 promotes the decision to leave the food in order to avoid the repulsive odorant . These results together characterize distinct functions of the NLP-7 neuropeptide in regulating multisensory integration versus context-dependent avoidance of noxious stimuli . The TGF-β/DAF-7 pathway regulates multiple behavioral and physiological events , including dauer formation , food intake , fat storage , as well as avoidance of pathogenic bacteria after prolonged exposure . The functions of DAF-7 in these physiological events depend on its expression in the sensory neurons ASI and/or ASJ [70–72] . Here , we show that DAF-7 promotes the decision to leave the food lawn paired with a repulsive odorant via its expression in either the ADE or the OLQ sensory neurons . Our results are the first to characterize the function of daf-7 produced by ADE or OLQ . ADE produce dopamine [100] . However , we did not see any phenotype in the cat-2 mutants that were defective in dopamine synthesis ( Fig 3 and Table 4 ) , suggesting that the function of ADE in regulating the integrated response to food and repellent is independent of dopamine . These results distinguish the role of daf-7 in the aforementioned food-associated behaviors from its function in the 2-nonanone-dependent lawn-leaving . Although DAF-7 likely functions in a way that is independent of synaptic connections , the cell-specific function of DAF-7 in different behaviors may result from the functions of different daf-7-expressing sensory neurons in detecting and responding to different environmental conditions . Previous studies show that the daf-7 expression level in ASJ increases rapidly after incubation on the pathogenic bacteria PA14 [70] . It will be informative to examine whether the daf-7 expression similarly changes during the first several-minute simultaneous exposure to the food and 2-nonanone and whether the potential change causally links with the lawn-leaving behavior . ADE and OLQ have been previously implicated in mechanosensation [22 , 30 , 101] . Thus , we propose that ADE and OLQ regulate the integrated response to a food lawn paired with a repellent by representing the mechanical stimulus that a worm senses from the food lawn . Further studies to characterize the function of these neurons using in vivo calcium imaging and by manipulating their activity or the signal release and testing the resulting behavioral effect will be informative for understanding their roles in regulating multisensory integration . We further show that the canonical TGF-β receptor DAF-1 acts in the interneurons RIM and RIC to regulate the decision to leave the food lawn paired with a repulsive odorant by inhibiting the tyramine signaling from these interneurons . This regulatory mechanism of DAF-7 is reminiscent of that in feeding , where DAF-7 promotes the pumping rate by inhibiting the output from the RIM and/or RIC neurons [72] . The RIM and RIC neurons have been previously implicated in various sensorimotor responses , as well as the context-dependent locomotory and feeding behaviors [66 , 72 , 86 , 99 , 102] . Our results further reveal RIM/RIC as one of the central sites where different sensory signals converge to generate appropriate behavioral outputs . The members in the large TGF-β family have been implicated in various neuronal functions , including learning and memory , synaptic plasticity , synaptogenesis , dendritic development , and regulation of the function of the neural-muscular junctions [103–106] . Defects in the TGF-β pathways have been implicated in the pathology of neurological disorders , such as schizophrenia , depression , anxiety and Alzheimer’s disease [107–109] . Our work reveals a new role for TGF-β signals in regulating decision-making , when sensory cues of opposing valance are simultaneously present . Interestingly , in contrast to the critical role of the NLP-7 peptide and the DAF-7 in the multisensory integration , none of the mutants that lack the major neurotransmitters is defective in the 2-nonanone-dependent lawn-leaving . Previously , several food-associated behaviors have been studied in C . elegans , some of which are regulated by the neurotransmitters . For example , the worm avoids octanol within several seconds upon the exposure to the repellent . The presence of food or serotonin modulates the latency of the response [96] . In addition , the worm spontaneously leaves a food lawn at a very low frequency ( < 0 . 05 leaving event/min ) and the rate of leaving is modulated by tyramine and/or octopamine [41] . In our assay , the majority of the worms leave the lawn several minutes after the addition of a repellent to the side of the lawn . The dynamics and the time scale of this repellent-dependent lawn-leaving are different from the food-modulated avoidance of octanol or the spontaneous lawn-leaving . The behavior in this study is also different from the lawn-leaving behavior that is driven by the depletion of the lawn , which occurs over a course of several hours [48] , or from leaving a lawn of pathogenic bacteria , in which the worms start to leave the lawn after feeding on the lawn for a few hours due to the pathogenesis of the bacteria [70] . Thus , it is conceivable that the lawn-leaving behavior that our assay analyzes is regulated by mechanisms that are different from those important for the other food-associated behaviors . The ability to integrate multiple types of sensory stimuli requires not only the responses across peripheral sensory areas , but also the signal processing in downstream network of interneurons [1 , 3 , 5–8 , 110] . In C . elegans , a number of sensorimotor responses are modulated by specific contexts via the functions of several interneurons [33 , 97 , 99 , 111] . However , how interneurons mediate decision-making during multisensory behavior is not fully characterized . Here , we find that the AIY interneurons play a modulatory role in 2-nonanone-dependent food leaving . The AIY interneurons receive synaptic inputs from the sensory neurons that detect olfactory , gustatory and thermal information . Previous studies implicate AIY in integrating simultaneously present aversive and attractive cues in olfactory plasticity and in food and serotonin-dependent modulation of sensorimotor responses [33 , 111–113] . We propose that AIY may act as an integrating site that receives and processes signals from the food and the repellent 2-nonanone during multisensory integration . Future studies that examine the activity of AIY in response to the simultaneous stimulation of the repellent and the food , as well as to each stimulus alone will further reveal the role of AIY in the multisensory integration . Our study also implicates the glr-1- and nmr-1-expressing neurons in regulating the repellent-dependent food leaving . It is conceivable that some of these command interneurons or head motor neurons may serve as the downstream-modulated targets for the integrated behavioral response .
C . elegans strains were cultivated under the standard conditions [114] . Hermaphrodites were used in this study . The strains that were used in the study include: PR680 che-1 ( p680 ) I , CX14394 npr-5 ( ok1583 ) V , MT15434 tph-1 ( mg280 ) II , CB1112 cat-2 ( e1112 ) II , MT9455 tbh-1 ( n3247 ) X , RB1161 tbh-1 ( ok1196 ) X , RB993 tdc-1 ( ok914 ) II , MT13113 tdc-1 ( n3419 ) II , DR40 daf-1 ( m40 ) IV , PR691 tax-2 ( p691 ) I , PR671 tax-2 ( p671 ) I , RB859 daf-22 ( ok693 ) II , OH8 ttx-3 ( mg158 ) X , MT150 egl-3 ( n150 ) V , CX4 odr-7 ( ky4 ) X , CX03572 nlp-9 ( tm3579 ) V , ZC2685 npr-2 ( ok419 ) IV , VC48 kpc-1 ( gk8 ) I , RB1341 nlp-1 ( ok1470 ) X , RB1289 npr-18 ( ok1388 ) X , CB1372 daf-7 ( e1372 ) III , ZC2673 gcy-33 ( ok232 ) V , SM2322 daf-7 ( ok3125 ) III , AX1295 gcy-35 ( ok769 ) I , QZ81 ins-6 ( tm2416 ) II , QZ126 ins-7 ( tm2001 ) IV , FX02105 nlp-24 ( tm2105 ) V , RB1902 flp-19 ( ok2460 ) x , CX10 osm-9 ( ky10 ) IV , FX02984 nlp-7 ( tm2984 ) X , RB1161 tbh-1 ( ok1196 ) X , RB993 tdc-1 ( ok914 ) II , KQ361 tdc-1 ( ok914 ) II; daf-7 ( e1372 ) III , KQ363 tdc-1 ( ok914 ) II; daf-1 ( m40 ) IV , KQ364 daf-1 ( m40 ) IV; tbh-1 ( ok1196 ) X , KQ362 daf-7 ( e1372 ) III; tbh-1 ( ok1196 ) X , ZC1952 yxIs25[Pttx-3::TeTx::mCherry; Punc-122::gfp] , KQ280 daf-1 ( m40 ) IV; ftEx98[Pdaf-1::daf-1::gfp; Podr-1::dsRed] , KQ380 daf-1 ( m40 ) IV; ftEx205[Ptdc-1::daf-1::gfp; Podr-1::dsRed] , KQ252 daf-1 ( m40 ) IV; ftEx70[Pbbs-1::daf-1::gfp; Podr-1::dsRed] , ZD736 daf-7 ( ok3125 ) III;qdEx44[Pstr-3p::daf-7; Pges-1::gfp] , ZD729 daf-7 ( ok3125 ) III;qdEx37[Pdaf-7::daf-7; Pges-1::gfp] , PY7502 yxIs34[Pceh-36∇::TU813; Pceh-36∇::TU814; Psrtx-1::gfp; Punc-122::dsRed] , ZC2393 yxEx1248 [Pttx-3::twk-18 ( gf ) ::mCherry; Punc-122::RFP] , CX14848 kyEx4866[Pinx-1::HisCl1::SL2mCherry; Punc-122::dsRed] , CX16040 kyEx5464[Ptdc-1::HisCl1::SL2mCherry] , ZC1451 yxEx699[Pnmr-1::TeTx::mCherry; Punc-122::dsRED]; QS4 qrIs2[Psra-9::mCasp1; Psra-9::gfp; Pelt-2::gfp] , PS6025 qrIs2[Psra-9::mCasp1; Psra-9::gfp; Pelt-2::gfp]; ZC1552 yxEx749[Pglr-1::TeTx::mCherry; Punc-122::gfp] , PY7505 oyls84[Pgpa-4::TU813; Pgcy-27::TU814; Pgcy-27::gfp; Punc-122::dsRed] , CX3830 kyIs102V; kyIs104[Pstr-1::mec-4 ( d ) ; Pstr-1::gfp]; CX14637 kyEx4779[Pinx-1::TeTx::mCherry; Punc-122::gfp] , CX14993 kyEx4962[Ptdc-1::TeTx::mCherry] , AX2051 Ex[Pgcy-33::egl-1; Punc-122::dsRed] , CX12330 Ex[Psre-1::TeTx::mCherry; Punc-122:RFP] , CX7102 lin-15B ( n765 ) X; qaIs2241[Pgcy-36::egl-1; Pgcy-35::gfp; lin-15 ( + ) ] , ZC2752 nlp-7 ( tm2984 ) X; yxEx1420[Pnlp-7::nlp-7; Punc-122::gfp] , ZC2731 daf-7 ( e1372 ) III; yxEx1409[Pcat-2::daf-7; Punc-122::gfp]; ZC2734 daf-7 ( e1372 ) III , yxEx1412[Pocr-4::daf-7; Punc-122::gfp] On a 5 cm-diameter NGM ( Nematode Growth Medium , 2 . 5g/L Bacto Peptone , 3 . 0g/L NaCl , 1mM CaCl2 , 1mM MgSO4 , 25mM KPO4 pH6 . 0 ) plate , 15–25 young adult worms were placed on a small 1 cm-diameter round-shaped bacteria lawn to acclimatize for 1 hour . The lawn was made by putting a drop of freshly prepared E . coli OP50 culture on the NGM plate and letting the plate stand on the bench for 2 hours . Next , a drop of 1 μl 2-nonanone ( Sigma Aldrich , Cat # 821-55-6 ) , either 10% ( v/v in 100% ethanol ) or 100% , was placed on the right-hand side of the lawn and 1–3 mm away from the lawn . The number of worms on the lawn was counted every 5 minutes for a total of 60 minutes , and the percentage of worms outside the lawn was calculated ( Fig 1A and 1B ) . In some assays , 1 μl of 100% benzaldehyde ( Sigma Aldrich , Cat # 100-52-7 ) was used , instead of 2-nonanone . The OP50 culture was prepared freshly each day by culturing at 27°C for 12–15 hours in NGM medium . For assays using Comamonas sp for the food lawn , the experiments were performed in the same way , except that the bacteria strain was cultured with Luria Broth . To determine the time taken to reach the edge of the food lawn , the food lawn was divided into 5 columns with each being 2 mm wide ( S1 Fig ) . The time taken for 90% of the worms to crawl into the column furthest away from the repellent was recorded . The percentage of worms that leave the repellent-paired food lawn quantified on different days may vary . The main source of the variability is likely the variability of the food-lawn , which is made by the bacteria culture freshly prepared every day . Although the bacteria culture is prepared using the same method each time , we may not be able to control all aspects of the bacteria growth , which can generate difference in the assay conditions , such as the thickness of the lawn and the amount of the bacterially derived metabolites present in the lawn . These variables may affect the dynamics of the behavior . However , the effects of these variations were minimized , because we always compared mutants with wild type tested in parallel , and compared transgenic animals with non-transgenic siblings or wild-type animals tested in parallel on the same days . The bar graphs in the figures report the percentage of worms outside the lawn 15 minutes after the start of the assay , unless otherwise noted . We used this time point , because it was often when a significant difference was first observed . To generate a nlp-7 genomic rescue fragment , a 4 . 7 kb PCR product was amplified from genomic DNA that included 2 . 5 kb 5’ upstream sequence , the nlp-7 coding region , and 1 kb 3’ downstream sequence ( NLP-7F: 5’-CATGTTTTTGATCATTTTCGAAC-‘3 and NLP-7R3’UTR: 5’-AATATCGTATGCCAACTTGAAC-‘3 ) . The nlp-7 genomic PCR product was injected into the nlp-7 ( tm2984 ) animals . To generate the construct expressing a wild-type daf-7 cDNA in the OLQ or ADE sensory neurons , the daf-7 cDNA was amplified from PJM016 ( Gift from Dr . Dennis Kim and Dr . Joshua Meisel [70] ) . The daf-7 cDNA product was cloned into a gateway destination vector that contained an unc-54 3’UTR using the Nhe-1 and Kpn-1 sites . Both the promoter regions of ocr-4 ( 4 . 0 kb promoter for expression in OLQ ) and cat-2 ( 1 . 1 kb promoter for expression in ADE ) were amplified from genomic DNA ( CAT-2F: CTAGCAGGCCCAATCTTTTCTG and CAT-2R: TCCTCTTCCAATTTTTCAAGGGGT/OCR-4F: 5’-TTCTAATATTGCTCCATCAAC-‘3 and OCR-4R: 5’-TAATACAAGTTAGATTCAGAGAATA-‘3 ) and cloned into the entry-TOPO vector PCR8 ( Invitrogen ) . The expression clones , Pcat-2::daf-7 and Pocr-4::daf-7 , were generated using LR recombination reactions ( Invitrogen ) . Each transgene was injected at 30–50 ng/μl with the co-injection marker as previously described [115] . Lawn-leaving assay was performed and analyzed similarly as the assay for multisensory integration , except that no repulsive chemical was present . Briefly , animals were placed on a 1 cm-diameter round-shaped bacteria lawn of OP50 and left for 10 minutes to acclimatize before examining food leaving over a period of one hour by counting the number of worms that were present on the food lawn every 5 minutes for a total of 60 minutes . To examine the avoidance of 2-nonanone , chemotaxis assays were performed essentially as previously described [42] . Briefly , animals were placed in the center of a square plate with a side of ~ 9 cm that was divided into sectors A—F and 2 drops of 1 μl of 2-nonanone was added to one side and 2 drops of 1 μl ethanol was added to the opposite side of the plate as control . Approximately 100 worms were used in each assay . Chemotactic avoidance was analyzed by counting the number of worms in the sectors A-B , C-D and E-F with E-F being furthest away from the 2-nonanone point sources ( S1 Fig ) . The avoidance index was calculated as the number of animals in sectors A and B minus the number of animals in the sectors E and F and normalized with the total number of animals in all 6 sectors on plate .
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The present study characterizes the modulation of a behavioral decision in C . elegans when the worm is presented with a food lawn that is paired with a repulsive smell . We show that multiple specific sensory neurons and interneurons play roles in making the decision . We also identify several modulatory molecules that are essential for the integrated decision when the animal faces a choice between the cues of opposing valence . We further show that many of these factors , which often represent different states and contexts , are common for behavioral decisions that integrate sensory information from different types of foods and repellents . Overall , our results reveal the molecular and cellular basis for integration of simultaneously present attractive and repulsive cues to fine-tune decision-making .
|
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"Methods"
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2019
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Molecular and cellular modulators for multisensory integration in C. elegans
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Congenital diaphragmatic hernia ( CDH ) is a severe birth defect that is often accompanied by other congenital anomalies . Previous exome sequencing studies for CDH have supported a role of de novo damaging variants but did not identify any recurrently mutated genes . To investigate further the genetics of CDH , we analyzed de novo coding variants in 362 proband-parent trios including 271 new trios reported in this study . We identified four unrelated individuals with damaging de novo variants in MYRF ( P = 5 . 3x10-8 ) , including one likely gene-disrupting ( LGD ) and three deleterious missense ( D-mis ) variants . Eight additional individuals with de novo LGD or missense variants were identified from our other genetic studies or from the literature . Common phenotypes of MYRF de novo variant carriers include CDH , congenital heart disease and genitourinary abnormalities , suggesting that it represents a novel syndrome . MYRF is a membrane associated transcriptional factor highly expressed in developing diaphragm and is depleted of LGD variants in the general population . All de novo missense variants aggregated in two functional protein domains . Analyzing the transcriptome of patient-derived diaphragm fibroblast cells suggest that disease associated variants abolish the transcription factor activity . Furthermore , we showed that the remaining genes with damaging variants in CDH significantly overlap with genes implicated in other developmental disorders . Gene expression patterns and patient phenotypes support pleiotropic effects of damaging variants in these genes on CDH and other developmental disorders . Finally , functional enrichment analysis implicates the disruption of regulation of gene expression , kinase activities , intra-cellular signaling , and cytoskeleton organization as pathogenic mechanisms in CDH .
Congenital diaphragmatic hernia ( CDH ) is a severe developmental disorder affecting 1 in 3000 live births [1 , 2] . It is characterized by defects in diaphragm that allow the abdominal viscera to move into the thoracic cavity and is associated with pulmonary hypoplasia and in some cases pulmonary hypertension . CDH can be isolated ( 50–60% ) or associated with anomalies in other organs including the heart , brain , kidneys and genitalia [3 , 4] . Despite advances in treatment , mortality rate remains high [5 , 6] . A better understanding of the causative factors for CDH may inform disease prevention and treatment . The genetic contribution to CDH has been established by familial aggregation [7] , rare monogenic disorders associated with CDH in humans [8] , chromosome abnormalities [9] , copy number variations [10–12] , and mouse models [13] . However , our understanding of the genetic basis of CDH is still rudimentary . The historically low reproductive fitness of individuals with CDH led to the hypothesis that de novo variants with large effect sizes may explain a fraction of CDH patients as in other developmental disorders [14 , 15] . We and others have previously reported an enrichment of damaging variants in sporadic CDH patients [16 , 17] . However , no recurrently mutated gene was identified in our genome wide analyses due to the limited sample size . To continue the search for new CDH genes , we performed whole exome ( WES ) or whole genome sequencing ( WGS ) of 271 new trios . Combined with previously published WES data [16 , 17] , we analyzed all 362 trios . We confirmed the overall burden of damaging de novo variants and identified a new disease gene recurrently mutated in cases with similar syndromic features . To prioritize additional risk genes , we analyzed cross-disorder overlap and pathway enrichment . The results provide insights into the genetic architecture of CDH and suggest additional candidate genes .
Patients were recruited from the multicenter , longitudinal DHREAMS ( Diaphragmatic Hernia Research & Exploration; Advancing Molecular Science ) study [11] . We excluded patients with known genetic causes from clinical karyotype or chromosome microarray or with a family history of CDH . WES was performed on 118 proband-parents trios , a subset ( 39 ) of whom were published previously [17] . WGS was performed on 192 trios including 27 without damaging variants from the previous study [17] . On average , 91% of coding regions in WES samples and 98% in WGS samples were covered by 10 or more unique reads ( S1 Fig ) . WGS showed more uniform distribution of sequencing depth that contributes to higher power in detecting coding variants [18 , 19] . For the 27 overlapping samples , 12 additional de novo coding variants were identified in WGS including 10 not included in the exome targets or with low depth of coverage and two that failed stringent QC filters in our previous study . Combined with trios collected by Boston Children’s Hospital/Massachusetts General Hospital ( BCH/MGH ) [16] , we analyzed a total 362 unique trios ( S1 Table ) . Clinical and demographic information of patients are given in S1 Data . In the combined cohort , there were 212 ( 58 . 6% ) male and 150 ( 41 . 4% ) female patients . The male-to-female ratio ( 1 . 4:1 ) was consistent with published retrospective and prospective cohorts [20 , 21] . The most common type of CDH was left-sided Bochdalek; rare forms of CDH or atypical lesion sides were also included ( Table 1 ) . A total 149 ( 41 . 2% ) cases had additional congenital anomalies or neurodevelopmental disorders ( NDD ) at the time of last follow up and were classified as complex cases; and 209 ( 57 . 7% ) patients had no additional anomalies at last contact were classified as isolated cases . The most frequent comorbidity among complex cases was cardiovascular anomalies ( 44 . 3% ) . NDD , skeletal malformations , and genitourinary defects were also observed in complex cases ( Table 1 ) . We identified 471 coding de novo variants in 264 ( 72 . 9% ) cases including 430 single nucleotide variants ( SNV ) and 41 indels . Transition-to-transversion ratio of de novo SNVs was 2 . 64 . The number of de novo coding variants per proband closely followed a Poisson distribution , with an average of 1 . 32 in WGS trios and 1 . 28 in combined WES trios ( S2 Fig ) . Variants that were likely gene disrupting ( LGD ) or predicted deleterious missense ( “D-mis” defined by CADD score [22] ≥25 ) were considered as damaging . A total of 193 damaging variants ( 57 LGD and 138 D-mis ) were identified in 150 ( 41 . 4% ) cases , including 38 ( 10 . 5% ) cases harboring two or more such variants . Compared with the baseline expectations ( Material and methods ) [23] , both de novo LGD variants ( 0 . 16 per case ) and D-mis variants ( 0 . 38 per case ) were significantly enriched in cases ( fold enrichment ( FE ) = 1 . 73 , P = 8 . 6x10-5 by one-sided Poisson test for LGD; FE = 1 . 5 , P = 1 . 1x10-6 for D-mis ) while the frequency of silent variants closely matched the expectation ( 0 . 30 per case , FE = 1 . 01 , P = 0 . 48 by one-sided Poisson test ) . Consistent with the previous study [16] , damaging variants showed a higher enrichment in complex cases than isolated cases ( FE = 1 . 70 vs 1 . 64 for LGD , 1 . 61 vs 1 . 38 for D-mis; S2 Table ) ; and the proportion of complex cases who carried damaging variants was higher than isolated cases ( 43 . 6% vs . 39 . 4% ) . Burden of damaging variants was also higher in female than male cases ( FE = 2 . 09 vs 1 . 47 for LGD , 1 . 63 vs 1 . 36 for D-mis; S2 Table ) , supporting a “female protective model” similar to autism and other NDD with male bias [24 , 25] . Recent studies highlighting the use of large population reference sequencing data in interpreting LGD variants has demonstrated that genes depleted of LGD variants in the general population were more likely associated with disorders with reduced reproductive fitness[26] . We defined constrained genes by the estimated probability of loss-of-function intolerance ( pLI ) [27] ≥0 . 5 and found the burden of LGD variants was largely explained constrained genes ( Table 2 ) . D-mis also showed a higher enrichment in constrained genes ( Table 2 ) . We identified eight genes affected by more than one de novo LGD or missense variant ( S3 Table ) . The top ranked gene , MYRF , has one frameshift insertion and three damaging missense variants , all of which were validated by Sanger sequencing . It is the only constrained gene in the list . By comparing with baseline expectations , only MYRF reaches genome-wide significance after Bonferroni correction of ~20000 coding genes ( P = 5 . 3x10-8 <0 . 01/20000 , by one-sided Poisson test ) . Notably , all four patients with MYRF variants also had congenital heart disease ( CHD ) , and three of them had genital anomalies including blind-ending vagina in a female and ambiguous genitalia or undescended testes in two male cases ( Table 3 ) . By screening another 220 CDH trios collected by the DHREAMS study , we identified another patient harboring a de novo splice acceptor site variant . The female patient had a diagnosis of Scimitar syndrome ( a complex form CHD ) . She also had a monozygotic twin sister with hypoplastic left heart syndrome who also carried the same variant but no known CDH . Given the strong association of MYRF variants with CHD , we then searched for de novo variants from a recently published study of CHD conducted by Pediatric Cardiac Genomics Consortium ( PCGC ) [29] and identified three additional de novo missense variants in MYRF from 2645 trios . All CHD patients also had genitourinary anomalies , including a patient with Swyer syndrome ( 46XY karyotype with female reproductive organs ) . One CHD patient with the Q403H variant had hemidiaphragm eventration . Recently , Pinz et al . [30] and Chitayat et al [31] reported three additional cases with complex CHD who carried de novo LGD variants in MYRF . All cases had genital defects , and one had CDH and the other two had pulmonary hypoplasia . Furthermore , from clinical WES , we also identified a Swyer syndrome patient with a stop-gain variant in MYRF who had dextrocardia and pulmonary hypoplasia . In total , we identified 13 patients harboring 12 different de novo functional variants in MYRF ( 6 LGD and 6 missense variants; Fig 1A ) . All patients had CHD; and excluding those who died in infancy and had incomplete phenotypic information , all patients also had genitourinary anomalies . CDH was present in 7 out of 12 patients , and diaphragm defects were not systematically evaluated in cases without reported CDH . There was no clear phenotypic difference between patients with LGD variants and those with missense variants ( Table 3 ) . Taken together , the unique association of CDH and similar non-diaphragm defects including CHD , Scimitar syndrome , genitourinal anomalies and sex reversal in 46XY patients with de novo variants in MYRF establish it as a new syndromic CDH gene . MYRF is a highly constrained gene in the population ( pLI = 1 ) . By examining both public databases ( ExAC and gnomAD ) and our own cohort , we only identified two rare LGD variants that affect all functional isoforms , yet their functional consequences were not clear ( S5 Table ) . We also searched for inherited variants in 362 CDH trios and 2645 CHD trios from PCGC but did not find any inherited LGD variants in probands . Enrichment for de novo LGD variants associated with CDH and near complete absence of loss-of-function variants in the general population suggest that variants causing loss of MYRF function are likely fully penetrant for one or more aspects of this syndrome . All six de novo missense variants identified patients were also absent from the public databases , consistent with their high penetrance as LGD variants in this gene . MYRF is a membrane-associated transcription factor that plays a pivotal role in oligodendrocyte differentiation and myelination [32 , 33] . Although it has not previously been implicated in diaphragm or cardiac development , its expression level was ranked at the top 21% of genes expressed in mouse developing diaphragm at E11 . 5 [34] and top 14% in developing heart at E14 . 5 [35] . The MYRF protein has two functional isoforms . Both isoforms contain a N-terminal proline-rich region followed by a DNA binding domain ( DBD ) , which can be cleaved from the membrane by a region called intramolecular chaperon auto-processing ( ICA ) domain . All frameshift and stop gained variants resulted in truncated protein products in both functional isoforms and may trigger non-sense mediated decay . The precise functional effects of splice site variants were not evaluated , but are predicted to cause exon skipping , intron retention or activation of cryptic splice site and also result in a truncated protein . All six missense variants aggregated in the two DBD and ICA functional domains ( Fig 1a ) . The missense variants were predicted as deleterious by a majority of bioinformatics tools ( S4 Table ) . Most of the affected amino acid residues are highly conserved across species ( S3 Fig ) . MYRF DBD is homologous to yeast transcriptional factor Ndt80 but MYRF can only function as a trimer [36] . All missense variants in this domain are located in a region depleted of missense variants in the population ( observed/expected = 0 . 31; Fig 1A ) and have high MPC scores [37] ( S4 Table ) . Protein structure modeling predicted that those variants may affect DNA binding affinity ( F387S ) , change surface charge distribution ( Q403H ) , or destabilize the protein structure ( G435R and L479R ) ( S4 Fig ) . Previous studies also showed that full length MYRF forms a trimer before cleavage , and trimerization is required for auto-cleavage and subsequent activation [38] . The ICA domain which is distantly related to bacteriophage’s tailspike protein was believed to play an essential role in MYRF trimerization . Two missense variants ( V679A , R695H ) are located at the C-terminal end of the ICA domain where the triplet helix bundle is formed [39] . V679 is one of the critical residues in ICA that is fully conserved from human to bacteriophage ( S3 Fig ) . Structure modeling predicted that the variant R695H may destabilize the trimer structure ( S4 Fig ) and would fail to produce functional MYRF DBD trimers by trimerization-dependent auto-proteolysis . To evaluate the effect of MYRF variants on gene expression , we performed RNA-seq on diaphragm fibroblast cell cultures from neonatal patients . After removing outlier samples ( S5 Fig ) , we obtained transcriptome data of 31 patients including three with a de novo MYRF variant ( one frameshift insertion and two missense variants in the ICA domain ) . Most patients ( 27/31 , 87% ) included in the RNA-seq analysis were self-reported non-Hispanic White . Additionally , we identified 74 putative MYRF target genes from a previous study of rat oligodendrocyte progenitor cells ( S3 Data ) [40] . Gene expression levels were quantified as TPM ( transcripts per million mapped reads ) . The z-scores of expression levels of putative MYRF target genes were systematically shifted down in MYRF mutant cells ( P = 2 . 4E-7 by Kolmogorov-Smirnov test; Fig 1B ) , consistent with the reduced transcription factor activities caused by the damaging variants . We quantified differential expression ( DE ) of genes between samples with and without de novo MYRF variants by a shrinkage estimator of fold change [41] . Selected DE genes were validated by quantitative polymerase chain reaction ( qPCR ) on the same cell cultures ( S7 Fig ) . Using gene set enrichment analysis [42] of genes ranked by the fold changes , putative MYRF target genes are significantly enriched among the down-regulated genes ( normalized enrichment score ( NES ) = -2 . 10 , P<5 . 0E-4; Fig 1C ) . Since all MYRF mutation carriers were males , we repeated the analysis using only males and found the results are similar as using all samples ( NES = -1 . 95 , P<5 . 0E-4 ) , suggesting that sex is not a confounding factor . The patient with the MYRF frameshift variant was the only MYRF mutation carriers whose ethnicity was not self-reported White . The enrichment of MYRF target genes is also observed in genes down-regulated in the two samples with missense variants ( S6 Fig ) , suggesting that the result was not driven by the LGD variant or ethnicity . Manual inspection of top DE genes ( S4 Data ) revealed that GATA4 , a known CHD gene that has also been implicated in familial and sporadic CDH [43] , was significantly down-regulated in cases with de novo MYRF variants ( estimated fold change = 0 . 54 , q-value = 0 . 03 ) . Interestingly , we observed that expression trajectories of MYRF and GATA4 were similar in mouse developing diaphragm and lung ( S8 Fig ) suggesting that they play similar functional roles during diaphragm and pulmonary development . Besides MYRF , we estimated there were 64 ( 95% CI: 38–93 ) genes with de novo variants implicated in CDH based on the overall burden analysis . Most of those genes have only one damaging variant in the cohort . To prioritize among all the genes with de novo damaging variants , we took two approaches . We noted that CHD was the most common non-diaphragm defect in complex cases ( Table 1 ) . Damaging mutations in MYRF have been identified in a previous CHD study but the gene did not reach genome-wide significance [29] . The identification of the MYRF syndrome suggested that the comorbidity of CHD and CDH in some cases can be explained by the same genetic factors , many of which remain to be discovered . CDH is also part of the phenotype spectrum of several rare Mendelian disorders [8] . Recently discovered genes for developmental disorders are often pleiotropic and implicated in multiple diseases [15 , 29 , 44] . Thus , the finding of MYRF motivated us to assess the genetic overlap between CDH and other developmental disorders , especially CHD , to help us prioritize additional CDH genes with pleiotropic effects . To this end , we curated genes that were known or implicated in CHD and other developmental disorders ( S5 Data; Materials and Methods ) . Hereafter we refer to these known or candidate genes as CHD or DD genes . In addition to MYRF , we identified a total of 26 DD/CHD genes with damaging de novo variants in 25 CDH patients ( Fig 2A ) . Using a simulation approach that accounted for the number of variants , gene size , and sequence context ( Materials and Methods ) , we found that damaging variants in CDH were significantly enriched in the DD and CHD genes ( Fig 2B ) . For example , we observed 6 CHD genes with de novo LGD variants in CDH which was 4 . 7-fold higher than expected ( P = 1 . 7x10-3 ) ; the number of DD genes with de novo LGD variants ( 8 ) was 3 . 4 folder higher than expected ( P = 2 . 3x10-3 ) . Among CHD genes with at least one damaging variant in CDH , haploinsufficiency of WT1 is a known cause of several syndromic forms of CDH [8]; ZFPM2 and GATA6 have already been established as CDH genes by previous studies [45 , 46] . However , the enrichment of damaging variants and especially LGD variants remained significant after excluding known or candidate CDH genes [47] ( S9 Fig ) . Furthermore , the enrichment cannot fully be explained by the over-representation of constrained genes , because the enrichment persisted after conditioning on all constrained genes and remained significant for LGD variants ( S9 Fig ) . The cross-disease overlap suggests that pleiotropic effects of variants in the genes associated with other developmental disorders are also associated with CDH in a fraction of cases . Since CHD genes were curated based on the damaging mutations in CHD patients and DD genes were mostly implicated in other developmental disorders , the genes that appear in both sets were more likely to participate in a broader range of developmental process . Accordingly , the enrichment in genes found exclusively in one set was significantly reduced ( Fig 2B , S9 Fig ) . We reviewed the most recent medical records of those patients ( S7 Table ) and identified six complex cases with CHD and/or NDD compatible with the initial reported phenotypes for these genes . Two additional cases were found to have non-CHD cardiovascular defects like two-vessel cord or dilated aortic root; and another four had mild-to-moderate developmental delay/intellectual disability at latest evaluation . Four patients who carried LGD variants in known DD genes ( POGZ , ARID1B , FOXP1 , and SIN3A ) and one patient who carried a known activating variant in the Noonan syndrome gene PTPN11 were considered pathogenic variants by the American College of Medical Genetics and Genomics guidelines [48] . Pleiotropy was further supported by the gene expression data . The majority of the 26 DD/CHD genes with damaging de novo variants in CDH were not only highly expressed in mouse developing diaphragm but also in developing heart or brain ( Fig 2C ) . Indeed , over all coding genes , expression ranks in the three developing organs were highly correlated ( Spearman rank correlation r = 0 . 74 between diaphragm and heart , 0 . 74 between diaphragm and brain ) . Therefore , high diaphragm expression can be a proxy for a pleiotropic effect . Consistent with this , we found that all damaging de novo variants in complex cases , presumed to enrich causative variants affecting multiple organs , were greatly enriched in genes at the top quartile of expression in developing diaphragm ( FE = 4 . 6 , P = 7 . 9x10-7 by one-sided Poisson test for LGD; FE = 2 . 4 , P = 1 . 8x10-4 for D-mis ) . By contrast , in isolated cases , the enrichment of damaging variants was distributed in genes across a broad range of expression ( Fig 3 ) . As a second approach to prioritize CDH genes , we hypothesized that different CDH genes converge onto a small number of pathways , and novel genes in the enriched pathways could be candidates for new disease genes . We evaluated functional enrichment of genes affected by damaging de novo variants to identify biological processes involved in CDH . To boost the signal , only constrained genes or known haploinsufficient genes were included in the pathway analysis ( Materials and Methods ) . A total of 63 Gene Ontology Biological Process gene sets were enriched at a false discovery rate ( FDR ) of 0 . 1 ( S6 Data ) . To remove the redundancies between gene sets , we used a similarity score to organize functionally related gene sets into a network . The resulting network was annotated and visualized as a functional enrichment map ( Fig 4A ) . Eleven functional groups were identified that recapitulated our current knowledge about the molecular genetic basis of CDH [49] . They were supported by 48 genes including 27 novel genes ( Fig 4B ) . Transcription factor haploinsufficiency is an established cause of CDH [50] and other birth defects [51] . Recently , disruption of epigenetic machinery was also found to underlie many developmental disorders [35 , 44 , 52] . The majority of DD/CHD genes directly or indirectly regulate gene expression which formed a highly connected cluster of enriched gene sets , some of the transcription factors are involved in the development of heart , lung and reproductive organs . We identified nine novel genes encoding transcription factors or histone modifiers . Proper cell migration is critical during diaphragm development . Initially , mesenchymal precursor cells migrate from mesoderm to form the primordial diaphragm . After that , pleuroperitoneal folds of the primordial diaphragm become the targets of migration of muscle progenitors , where they undergo myogenesis and morphogenesis [53] . Several related pathways were implicated including cellular response to growth factors or stress events that initiate directional migration [54] , actin cytoskeletal organization and cell-cell junction assembly that drive and fine tune cell movement [55 , 56] . Gene sets in protein phosphorylation and JUN-MAPK ( mitogen-activated protein kinase ) cascades were also enriched but not entirely due to three Noonan syndrome genes ( PTPN11 , BRAF , RAF1 ) . The enrichment in kinase activity related pathways was supported by six novel kinase genes that overlapped with intracellular signaling functions . One kinase gene , MAPK8IP3 , has been implicated in lung development in a mouse model [57] .
In this study , by analyzing de novo coding variants in CDH , we confirmed the overall enrichment of damaging de novo variants and identified MYRF as a new syndromic CDH gene . All our CDH cases with MYRF mutations also had CHD and most of them had genitourinary defects . The striking phenotypic similarities among the cases suggest that damaging de novo variants of MYRF disrupt the function of progenitor cells of developing diaphragm , heart and reproductive organs . In this novel MYRF syndrome , all cases with disease associated variants had CHD including three with Scimitar syndrome , whereas penetrance CDH was incomplete . It suggests that the manifestation of CDH in this syndrome depends on other genetic , environmental , or stochastic factors . The monozygotic twin case discordant for CDH supports that stochastic developmental events are involved . MYRF is well known for its function in regulating myelination of the central nervous system [32] . A mouse model with conditional deletion of MYRF in oligodendrocyte precursors has abnormal motor skill [58] . Recently , an inherited missense variant in MYRF ( Q403R ) has been reported as the cause of encephalopathy with reversible myelin vacuolization in a Japanese pedigree [59] . This variant is located at the same residue as the de novo missense variant in one of the PCGC cases but with a different substutition ( Q403H ) . No other congenital defects were reported for the variant carriers in that family . The Q403R variant has been experimentally shown to diminish the transcription activity of a target gene [59] , similar to our finding in two other missense variants ( S6 Fig ) . Why the two different substitutions at the same amino acid position result in different phenotypes remains to be elucidated in the future . Among patients with de novo damaging variants in MYRF , one individual with the R695H variant also had intellectual disability and delayed motor skills ( Table 3 ) . We identified 25 other individuals harboring damaging de novo variants in known or candidate DD/CHD genes , most of which have not been reported to be associated with CDH before . The significant enrichment of damaging variants among DD/CHD genes strongly suggest their causative role for majority of these cases . Similar to the case of MYRF , many DD/CHD genes have yet to be established as known disease genes . The enrichment of CDH damaging variants support their possible involvement in a broader range of developmental abnormalities which should be further evaluated in additional case cohorts with other congenital anomalies . Some recent studies of other congenital anomalies and developmental disorders have already provided further evidence for a few putative DD/CHD genes . For example , a damaging missense variant in LAMA5 , a gene that plays a role in the maintenance and function of the extracellular matrix critical for pattern formation during development [60] , was associated with multi-system syndrome in an Italian family [61] . Duplication of STAG2 , which encodes a subunit of cohesin complex , was associated with intellectual disability and behavioral problems [62] . MEIS2 was previously nominated as a potential CDH candidate by transcriptome analysis [34] and encodes an interaction partner of transcription factor gene PBX1 , haploinsufficieny of which has recently been associated with multiple developmental defects including CDH [63] . Since our knowledge of DD/CHD genes is incomplete , it is possible that this observed genetic overlap represents only the tip of an iceberg . Our pathway analysis not only captured general biological process during developmental , but also identified pathways that are closely related to diaphragm development . Some novel genes prioritized by the pathway analysis have also been supported by new genetic data in other disorders . For example , de novo copy number loss or missense variants in TAOK2 , one of the kinase gene implicated by the enriched gene sets of the kinase activity and MAPK signaling , has been demonstrated to cause autism and other NDD [64] . Because CDH is a relatively uncommon and lethal condition as are many other rare congenital anomalies , it is difficult to recruit large numbers of patients for genetic studies . The findings from this and other studies [15] suggest that cross-disorder analysis can be a powerful strategy for future gene discovery . The genetic overlap between CDH and other disorders is consistent with pleiotropy among developmental disorder genes and is further supported by the highly correlated gene expression levels in multiple developing organs . We also showed that different enrichment patterns of de novo damaging variants between complex and isolated CDH cases is consistent with the hypothesis that variants in complex cases affect genes with more pleiotropic effects . The pleiotropic effects of genes during development also suggest that our current classification of “isolated” cases may understate their non-diaphram abnormalities . A limitation of our study is the lack of long term clinical outcome data on many of the patients since our cohort is still relatively young . Examining the most recent medical records of patients with variants in DD/CHD genes revealed mild-to-moderate cadiovascular or NDD symptoms in several cases initially classified as isolated at birth ( S7 Table ) . The medical records were often incomplete for patients who died at early infancy or were lost to follow-up ( Table 1 ) , and it is likely that NDD outcome in many isolated patients were underestimated [65 , 66] . Furthermore , almost all isolated cases also had pulmonary hypoplasia . Traditionally it was assumed that lung defects were caused by the mechanical compression by the herniated visceral , but it is clear now that development of lung and diaphargm are two intricatelly connected developmental processes [67] , and lung defects may share common etiologies with CDH [68] . Among MYRF variant carriers , four patients who did not have diaphragm defects developed pulmonary hypoplasia ( Table 3 ) , further supporting common genetic control of these two processes . Larger cohorts with more detailed neurodevelopmental and long term outcomes will enhance our ability to identify additional CDH genes and provide accurate prognostic information to families to allow for future clinical diagnosis of these conditions . In summary , our analysis of de novo coding variants in 362 CDH trios identified a new disease gene MYRF , revealed genetic overlap with other developmental disorders , and identified biological processes important for diaphragm development . Future studies will beneifit from larger sample sizes , analyzing different types of genetic variants , leveraging the information from other developmental disorders , and integrating functional genomic data .
Study subjects were enrolled by the DHREAMS study ( http://www . cdhgenetics . com/ ) . Neonates , children and fetal cases with a diagnosis of diaphragm defects were eligible for DHREAMS . Clinical data were collected from the medical records by study personnel at each of 16 clinical sites . A complete family history of diaphragm defects and major malformations was collected on all patients by a genetic counsellor . A blood , saliva , and/or skin/diaphragm tissue sample was collected from the patient and both parents . All studies were approved by local institutional review boards , and all participants or their parents provided signed informed consent . Cases without known pathogenic chromosome abnormalities or copy number variations [11] were selected for exome or whole-genome sequencing . A total of 283 trios with no family history of CDH with three generation and not born to consanguineous marriages were included in the current study . De novo coding variants on a subset trios ( n = 39 ) have been described in our previous study [17] . In Neonates cohort , longitudinal follow-up data including Bayley III and Vineland II developmental assessments since discharge at 2 years and/or 5 years of age were gathered . Patients were evaluated to have developmental delay if at least one of the composite scores was 2 standard deviations below population average . Patients with additional birth defects or developmental delay or other neuropsychatric phenotypes at last contact were classified as complex , and otherwise as isolated . Pulmonary hypoplasia , cardiac displacement and intestinal herniation were considered to be part of the diaphragm defect sequence and were not considered to be additional birth defects . Subjects of BCH/MGH cohort were enrolled in “Gene Mutation and Rescue in Human Diaphragmatic Hernia” study as described previously [16] . Among 87 trios from BCH/MGH cohort , 8 trios were found to be duplicates with DHREAMS trios and were excluded from the analysis . Exome sequencing was performed in 79 trios that were not published before . Eleven trios were processed at the New York Genome Center . The DNA libraries were prepared using the Illumina TruSeq Sample Prep Kit ( Illumina ) . The coding exons were captured using Agilent SureSelect Human All Exon Kit v2 ( Agilent Technologies ) . Samples were multiplexed and sequenced with paired-end 75bp reads on Illumina HiSeq 2500 platform according to the manufacturer’s instructions . Sixty-eight trios processed at University of Washington Northwest Genome Center were captured using NimbleGen SeqCap EZ Human Exome V2 kit ( Roche NimbleGen ) , and sequeced on HiSeq 4000 in 75 bp paired-end reads . Another 192 trios were processed at Baylor College of Medicine Human Genome Sequencing Center using whole genome sequencing as part of the Gabriella Miller Kids First Pediatric Research Program . Among these , 27 trios were included in the previous exome study [17] but had no damaging de novo variants . Genomic libraries were prepared by the Illumina TruSeq DNA PCR-Free Library Prep Kit ( Illumina ) with average fragment length about 350 bp , and sequenced as paired-end reads of 150-bp on Illumina HiSeq X platform . Exome and whole-genome sequencing data were processed using an inhouse pipeline implementing GATK Best Practice ( version 3 ) . Briefly , reads were mapped to human genome reference ( GRCh37 ) using BWA-mem ( version 0 . 7 . 10 ) ; duplicated reads were marked using Picard ( version 1 . 67 ) ; variants were called using GATK ( version 3 . 3–0 ) HaplotypCaller to generate gVCF files for joint genotyping . All samples within the same batch were jointly genotyped and variant quality score recalibration ( VQSR ) was performed using GATK . Common SNP genotypes within exome regions were used to valid parent-offspring relationships using KING ( version 2 . 0 ) [69] . A variant that was presented in the offspring and had homozygous reference genotypes in both parents was considered to be a potential de novo variant . We used a series of stringent filters to identify de novo variants as described previously[70] . Briefly , we first kept variants that passed VQSR filter ( tranche≤99 . 8 for SNVs and ≤99 . 0 for indels ) and had GATK’s Fisher Strand≤25 , quality by depth≥2 . Then we required the candidate de novo variants in proband to have ≥5 reads supporting alternative allele , ≥20% alternative allele fraction , Phread-scaled genotype likelihood ≥60 ( GQ ) , and population allele frequency ≤0 . 1% in ExAC; and required both parents to have > = 10 reference reads , <5% alternative allele fraction , and GQ≥30 . We used ANNOVAR [71] to annotate functional consequence of de novo variants on GENCODE ( v19 ) protein coding genes . All coding de novo variants were manually inspected in the Integrated Genomics Viewer ( http://software . broadinstitute . org/software/igv ) . A total of 169 variants were selected for validation using Sanger sequencing; all of them were confirmed as de novo variant . The number of coding de novo variants per proband was compared with expectations under Possion distribution . All coding variants were classified as silent , missense , inframe , and likely-gene-disrupting ( LGD , which includes frameshift indels , canonical splice site , or nonsense variants ) . The most severe functional effect was assigned to each variant . We defined deleterious missense variants ( D-mis ) by phred-scaled CADD ( version 1 . 3 ) [22] score≥25 . Baseline rate for different classes of de novo variants in each GENCODE coding gene were using a previously described mutation model [23 , 70] . Briefly , the tri-nucleotide sequence context was used to determine the probability of each base in mutating to each other possible base ( precomputed rates are available at: https://github . com/jeremymcrae/denovonear/blob/master/denovonear/data/rates . txt ) . Then , the mutation rate of each functional class of point mutations in gene was calculated by adding up point mutation rates in the longest transcript . The rate of frameshift indels was presumed to be 1 . 1 times the nonsense mutation rate . The expected number of variants in different gene sets were calculated by summing up the class-specific variant rate in each gene in the gene set mutiplied by twice the number of patients ( and if the gene is located on the non-pseudoautosomal region of chromsome X , further adjusted for female-to-male ratio [14] ) . The observed number of variants in each gene set and case group was then compared with the baseline expectation using Poisson test . In burden analysis , constrained genes were defined by pLI metrics [27] ≥0 . 5 which include a total of 5451 GENCODE genes , and all remaining genes were treated as other genes . We used a less stringent pLI threshold than previously suggested [27] for defining constrained genes , because it captured more known haploinsufficient genes important for heart and diaphragm development . Genes were also grouped by their expression levels in mouse developing diaphragm . Microarray expression profile of mouse pleuroperitoneal folds at E11 . 5 was taken from a previous study [34] . Normalized gene expression levels were converted to rank percentiles with smaller values corresponding to higher expression . Human orthologs of mouse genes were identified using annotations from MGI database ( http://www . informatics . jax . org/ ) . When a human gene mapped to multiple mouse genes , the highest expression level was assigned to the human gene . Fibroblasts were obtained from diaphragm biopies at the time of diaphragm repair from 36 CDH neonatal cases most of whom carried damaging de novo variants , including three cases carrying MYRF variants ( p . G81Wfs*45 , V679A , and R695H ) . Cells were cultured in Dulbecco's Modified Eagle's Medium supplemented with 10% heat-inactivated fetal bovine serum and 1x Antibiotic/antimycotic ( Gibco; Life Technologies ) , following standard conditions . Cells were cultured in parallel in successive passes until optimal confluence was reached , and were collected with 2 . 5% Trypsin ( Gibco; Life Technologies ) and harvested by centrifugation 5 minutes at 1200rpm . Total RNA was extracted from the cell pellet of each subject using RNeasy LipidTissue mini Kit ( QIAGEN ) according to manufacturer's protocol . The quality and quantity of RNA were assayed using a Qubit RNA Assay Kit in a Qubit 2 . 0 Fluorometer ( Life Technologies ) and RNA Nano 6000 Assays on a Bioanalyzer 2100 system ( Agilent Technologies ) . cDNA libraries were prepared with the TruSeq Stranded Total RNA Sample Preparation kit ( Illumina ) , following the manufacturer instructions . And the purified products were evaluated with an Agilent Bioanalyzer ( Agilent Technologies ) . The library was sequenced on Illumina HiSeq 2000 platform in 100-bp paired-end reads . RNA-seq reads were mapped to the human reference genome ( GRCh37 ) using STAR ( version 2 . 5 . 2b ) [72] . Gene expression levels were quantified as TPM from the output of FeatureCounts ( 2015–05 version ) [73] . Only protein coding genes were kept for analysis and genes with no mapped reads in at least half of the samples were filter out . All sequenced samples had >20 million mapped read pairs with >90% mapping rate . Principle component ( PC ) analysis of gene expression profile showed that five samples were separated from others on the first two PC axes ( S5 Fig ) . The outlier samples were likely due to different number of passages in cell culture , and were removed from analysis . Differential expressed genes ( DEG ) between cases with MYRF variants and others were identified using DESeq2 package [41] . DEG were selected using following criteria: adjusted p-value < 0 . 5 and adjusted fold change > 0 . 5 or < -0 . 5 . We noted that all three MYRF de novo variant carriers were male . To avoid confounding effect of gender , DEG analysis was also performed by comparing male samples with or without MYRF variants . The full DEG list is given in S4 Data . To evaluate the consequence of MYRF damaging variants on patients’ transcriptome , we tested if putative MYRF target genes were systematically down-regulated in the fibroblast cells with MYRF variants using gene set enrichment analysis ( GSEA ) . The MYRF target genes as oligodendrocyte-specific genes that had at least one MYRF ChIP-seq binding peaks with 100kb of transcription start site [40] . We then identified corresponding human orthologs using biomaRt package [74] . A total of 74 human genes were defined as putative target genes for GSEA . We selected six genes from differentially expressed genes between MYRF mutation carriers and other cases , including four down-regulated ( GATA4 , DBNDD2 , MYO1D and NFASC ) and two up-regulated ( H3F3C and SEMA3A ) in MYRF mutant cells . First-strand cDNA was synthesized from the total RNA ( 500ng~1 µg ) using the RNA to cDNA EcoDry Premix ( Random Hexamers ) kit ( TaKaRa ) according to manufacturer's instructions . Primers for the selected genes ( S6 Table ) were synthesized by IdtDNA . All qPCR reactions were performed in a total of 10 µl volume , comprising 5 µl 2x SYBR Green I Master Mix ( Promega ) , 1 µl 10nM of each primer and 2 µl of 1:20 diluted cDNA in 96-well plates using CFX Connect Real-Time PCR Detection System ( Bio-Rad ) . All reactions were performed in triplicate and the conditions were 5 minutes at 95°C , then 40 cycles of 95°C at 15 seconds and 60°C at 30 seconds . The relative expression levels were calculated using the standard curve method relative to the β-actin housekeeping gene . Five-serial 4-fold dilutions of cDNA samples were used to construct the standard curves for each primer . To assess the genetic overlap with other developmental disorders and especially CHD , we tested if the de novo damaging variants in CDH cases were enriched in known and putative CHD and DD genes . DD genes were extracted from DDG2P database [75] ( accessed on Jan 11 , 2018 ) and filtered to keep “allelic requirement” as monoallelic , X-linked dominant or hemizygous , and required “organ specificity list” to include brain , heart or not specific to any organ . A total 508 DD genes were identified , including 460 confirmed DD genes . CHD genes were collected based on a recent exome study of 2645 trios [29] . CHD genes included high heart expressed genes ( HHE; ranked at top 25% ) or known human CHD genes that were affected by more than one damaging de novo variants ( LGD or D-mis defined by meta-SVM [76] as the original publication on CHD [29] ) or constrained ( pLI≥0 . 5 ) HHE genes affected by only one damaing variants from the same study . A total 200 CHD genes were identified , 57 of which overlapped with DD genes . To assess if the exome-wide de novo damaging variants in CDH were enriched in CHD and DD genes , simulations were done to randomly place variants to the coding regions in a way that keeps the number of variants , tri-nucleotide context , functional effect , and deleteriouness prediction the same as that of the observed data [77] . Here the coding region was defined as coding sequences and canonical splice sites of all GENCODE v19 coding genes . For damaging mutations identified from WES data , the coding regions were restricted to the regions that have at >10X coverage in least 80% samples . Empirical p-value was calculated as the chance when there were more simulated damaging variants than observed in the given gene set . We ran 50 , 000 simulations to evaluate the significance . And the expected number of variants in a gene set was the average number of randomly generated variants in a gene set over all simulations . To evaluate the functional convergence of genes affected by damaging variants , we extracted 89 genes that included 86 constrained genes ( pLI≥0 . 5 ) , two known candidates for CDH ( GATA6 , WT1 ) , and a known haploinsufficient gene ( KDM5B ) . Gene sets were derived from Gene Ontology Biological Process ( GO-BP , accessed Feb 1st , 2018 ) . The GO-BO categories that were statistically over-represented in the gene list ( FDR<0 . 1 ) were identified using hyper-geometric test implemented by BINGO [78] . Terms annotating more than 750 or less than 25 genes were discarded , because large gene-sets usually represent broad categories without specific biological meaning . Small gene sets on the other hand are not likely to produce statistically significant results . Enriched gene sets were graphically visualized as a network , in which each gene set is a node and edges represent overlap between sets . The Cytoscape software [79] and EnrichmentMap plugin [80] were used to construct the network . The color gradient of nodes reflects the enrichment p-values . Node size is proportional to the number of genes in the gene set . Edge thickness is proportional to the similarity score between gene sets which is defined by the average of Jaccard coefficient and overlap coefficient [80] . Enriched gene sets with highly overlapping genes ( S6 Data ) were grouped together and annotated manually .
|
Congenital diaphragmatic hernia ( CDH ) is a life-threatening condition affecting about 1 every 3000 newborns . Although the role of genetics in the pathogenesis of CDH has been well established , only a handful of disease genes have been identified so far . We and other have previously shown that de novo variants , those carried by the cases but not inherited from parents , are enriched in sporadic CDH cases consistent with their negative effects on reproductive fitness . To further investigate the genetics of CDH , we analyzed de novo variants in 362 proband-father-mother trios from whole exome or genome sequencing data and identified four patients carrying damaging variants in MYRF , a membrane associated transcription factor that is highly expressed in developing diaphragm and heart . We then ascertained a total of 12 patients with MYRF de novo variants , and found they shared common phenotype characteristics including congenital abnormalities in diaphragm , heart and reproductive organs . The high rate of recurrence and similar phenotypic manifestations suggest that de novo variants of MYRF have pleiotropic effects and cause a novel syndrome . The identified new gene is reminiscent of previously identified CDH genes ( e . g . , GATA4 , GATA6 , NR2F2 , ZFPM2 , and WT1 ) that are also associated with other developmental disorders . Indeed , we found in our cohort more than 20 damaging de novo variants in genes implicated in other developmental disorders but not previously linked to CDH . The overlap was unlikely to occur by chance and can be best explained by their pleiotropic effects . We also showed that , despite the shared genetic basis with other disorders , damaging de novo variants in CDH as a whole were enriched in specific functional pathways that recapitulated our current knowledge about diaphragm development . So additional candidate genes can be prioritized based on the genetic pleiotropy and functional specificity . The findings have general implications in design and analysis in genetic studies of rare birth defects .
|
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"Abstract",
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"Discussion",
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"and",
"methods"
] |
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2018
|
De novo variants in congenital diaphragmatic hernia identify MYRF as a new syndrome and reveal genetic overlaps with other developmental disorders
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Tegumentary Leishmaniasis ( TL ) is a neglected disease with worldwide distribution and considered a public health problem , especially in Latin America . In Colombia , the governmental epidemiological surveillance system ( SIVIGILA ) is responsible for collecting information on the presentation of cases of TL from each of the municipalities and departments . In absence of a study compiling and analyzing currently available metadata of TL in Colombia , this study describes the geospatial-temporal distribution of TL and identifies the regions of the country on which prevention measures should be established in order to control the disease . This is an exploratory descriptive analysis of the distribution of TL in Colombia . Information was collected on new cases of the disease during the years 2007–2016 from the Colombian reporting system ( SIVIGILA ) . Incidence calculations were made based on population estimates by departments and biogeographical regions . Time evolution is shown in biennial maps . A 10-year series was analyzed , showing that the Amazon region is the most affected in terms of incidence , while the Andean region has the highest number of cases with a high variability among the departments that make it up . In those departments where there is a greater reported diversity of vector species , a large number of cases was observed . Transmission dynamics of TL in Colombia in the past 10 years have been variable , with a greater concentration of cases in the central and southern departments . The present study contributes to improve the understanding of the patterns of distribution of TL in Colombia and can be a basis for future studies of impact evaluation of Health policies in the country and the region .
Leishmaniasis , considered one of the most neglected diseases worldwide , is a grouping of parasitic pathologies caused by protozoans of the Leishmania genus , and transmitted to humans primarily by insects of the Psychodidae family [1] . Leishmaniasis displays a wide range of manifestations and clinical forms of which the most common , both worldwide and in the American continent , is Cutaneous Leishmaniasis ( CL ) characterized by ulcerative skin lesions [1–3] . CL is considered a widespread public health issue with an elevated prevalence , considered endemic in 98 countries , adding up to a population at risk of over 350 million people . Meanwhile , Mucocutaneous Leishmaniasis ( ML ) affects a smaller percentage of the population , producing disfiguring lesions which compromise both the oral and nasal mucosae [1 , 2 , 4] . In the clinical practice , CL and ML are known as Tegumentary Leishmaniasis ( TL ) . The American continent constitutes a special scenario for TL , given that the biological and clinical complexity of the disease is compounded by the presence of sociodemographic variability , geographical diversity , and the presence of internal armed conflicts in different countries . These features facilitate the parasite’s spread in the Americas , now present in 20 countries , of which 18 are endemic with a yearly average of 56 , 262 cases between 2001 and 2015 . Seventy percent of the cases reported in 2015 were found in just three countries: Brazil , Colombia and Peru [3 , 5 , 6] . Colombia is one of the 6 countries that account for over two thirds of TL cases worldwide [7] . This clustering of the disease has been associated with various circumstances , including the presence of armed conflict , which leads to internal displacement and increases the probability of contact between vectors , reservoirs and hosts . This occurs in both the civilian and military populations . Additionally , social inequality , the absence of preventive measures in rural areas , deforestation , and geographical diversity allow the circulation of a wide array of species of both vector and parasite in up to 30 of the 32 departments in the country [3 , 6 , 8] . It is worth noting that Colombia is the country with the greatest number of circulating species in the world , 10 in total ( L . panamensis , L . braziliensis , L . guyanensis , L . infantum chagasi , L . mexicana , L . lainsoni , L . amazonensis , L . colombiensis , L . equatoriensis , L . naiffi ) , and that the most prevalent species exhibit high genetic diversity [9–11] . This set of conditions conspires to produce an incidence of 33 . 6 per 100 , 000 inhabitants in 2015 , leading to the categorization of the country as one of Intense Transmission by the Panamerican Health Organization ( PAHO ) according to its Leishmaniasis Compound Index [3] . Considering the particular characteristics found in the country , it is important that robust epidemiological surveillance models be implemented , which can detect and categorize cases not only by geographical location , but also by species . These models would allow for the execution of prevention and control strategies in order to gradually reduce the burden of disease in the country . Currently , public health authorities in Colombia collect data on various diseases by means of a system called SIVIGILA , which gathers data on a variety of illnesses that are of public health concern [12] . In spite of the existence of this system , it is presumed that inadequate reporting is the norm in rural areas with no direct access to information systems . Likewise , and in response to the challenges around surveillance and control of leishmaniasis throughout the continent , the Regional Leishmaniasis program of the PAHO , along with representatives from six endemic countries , created a regional information system called SisLeish . The program gathers data from the epidemiological surveillance systems in each country , continually evaluating the disease’s distribution and producing regional indicators [13] . Despite the existence of information systems which compile data on TL , the geospatial and temporal distribution of the disease throughout the Colombian territory has not yet been studied . The trends and changes in TL’s distribution for recent years remains unknown . Therefore , this study aimed to analyze the spatiotemporal distribution of TL in Colombia between the years 2007 and 2016 , providing a quantitative characterization of the disease’s behavior and spread in the country . Using the current available information , we also constructed a descriptive model which estimates the standardized incidence ratio in each of the departments and regions in each time period . This analysis allows us to formulate hypotheses regarding the areas most in need of attention from public health authorities .
We report a geospatial analysis of TL data in Colombia . The data were readily obtained from existing public access databases ( SIVIGILA ) . Hence , there are no specific ethical considerations . The governmental surveillance system in Colombia is carried out by the National Public Health Surveillance System ( SIVIGILA ) , regulated in 2006 by the office of the President of the Republic of Colombia , which is tasked with the information collection from Primary Data Generating Units ( UPGD ) . These units correspond to Institutions Providing medical Services ( IPS ) in which cases of the various diseases that require mandatory reporting ( Common source and transmissible events , Non transmissible prevalent diseases and Avoidable mortality events ) are detected [12 , 14] . Mandatory reporting events are logged in SIVIGILA’s website , and the data for TL was used to construct summary tables by municipality and department for every year from 2007 to 2016 . These tables were then complimented with demographic data from the national statistical service ( DANE ) presented in the “Estimación y proyección de población nacional , departamental y municipal total por área 1985–2020” report [15] . The data was organized with the Microsoft Excel software in its 2016 version . The data for each geographical unit was collated both annually and biennially . Additionally , departments were grouped by geographical regions ( Andean , Amazon , Caribbean , Pacific , Orinoco , and Insular ) ( See S1 Text for more information about geographical regions ) . Then , inferences were conducted regarding the geospatial distribution . The data collection and analysis process are depicted in Fig 1 . Descriptive statistics were used to summarize the data . Preliminarily , the crude incidence ( Io ) was calculated by dividing the number of cases by the projected population for each of the scales and each one of the years considered . The data were then grouped , and Io was calculated for biennial periods . Io by department was split in quartiles and graphed , using a different color for each quartile . Maps depicting incidence quartile for each department were generated from an aggregation of data from biennial periods from 2007 to 2016 . Administrative polygons for Colombia were obtained from the Global Administrative Areas database , managed by the University of California Berkeley [16] . Regional polygons were constructed using R version 1 . 0 . 136 [17] , and packages sp and rgdal [18 , 19] . The maps were generated using QGIS version 2 . 18 . 7 Las Palmas [20] . Standardized Incidence Ratios ( SIR ) were calculated from the total number of cases in Colombia for the period considered using Empirical Bayes smoothing method described by Clayton and Kaldor [21] . In order to visualize the detail of the annual tendencies for each of the studied regions , a time series graphic was generated and smoothed by means of Lowess ( Locally-Weighted Scatterplot Smoother , 0 . 3 degrees , 2 steps ) using Minitab v . 18 . Additionally to visualize cases and vector distributions , total case data was overlaid with vector species data reported by Ferro et al . [8] on which accumulated cases in all study periods were added . The map was constructed displaying the number of cases detected in each department for all the periods , with circles centered on each department’s centroid and radii proportional to the number of cases .
Generally , it was observed that TL has had a stable behavior in the country in the past few years , with a stable incidence between 9 . 99 and 34 . 17 cases per 100 , 000 inhabitants . Closer examination of TL behavior by geographical region shows that the Amazon region exhibits the highest incidence rates for all observed periods . Incidence in this region varies from 76 . 75 to 240 . 93 cases per 100 , 000 inhabitants . The region with the lowest incidence is the Insular region , in which only one case occurred during the periods examined . Likewise , the Caribbean region displayed incidences between 5 . 11 and 13 . 64 cases per 100 , 000 inhabitants . The Andean region had the highest number of cases for all periods , reaching a total of 12 , 847 cases between 2009 and 2010 . The Orinoco region displayed the lowest case number , with 1031 cases for the 2007–2008 period ( S1 Table ) . The behavior of TL by departments was highly variable . The Antioquia department presented a highest number of cases in all the time periods , registering 20 , 951 in total across all years studied , with an average between 1000 and 3000 cases each year . The Meta department displayed the second highest number of TL cases in the country , reaching a peak of 4019 cases in 2009 , this considered as the highest number of cases in a single department in any of the studied periods . The departments with the fewest cases were Bogotá with 37 cases and San Andrés with 1 case in all the periods ( S2 Table ) . Fig 2 shows intraregional and interdepartmental variations in annual incidence . Across the study periods , high Io’s ( >51 . 6 cases per 100 , 000 inhabitants ) occurred in departments of the Amazon and Orinoco regions . Despite presenting high Io’s at the starting and ending periods , the departments in the Andean region presented mostly high to intermediate incidences ( 15 . 4–51 . 6 cases per 100 , 000 inhabitants ) . Departments in the Pacific and Caribbean regions displayed intermediate Io’s in 8 out of the 10 years considered . The Caribbean region displayed a greater frequency of low Io’s ( <3 . 92 cases per 100 , 000 inhabitants ) in later time points . Departmentally , Putumayo , Guaviare , Guainía , Caquetá , Vaupés , Meta , Chocó , and Vichada showed high Io’s for most periods considered ( Fig 2 ) . Maps in Fig 3 display biennial incidence divided in quartiles across departments in a choropleth format . Departments in the Amazon and Orinoco regions overall display the highest incidences , with values above the third quartile . The segmentation of the data by quartiles shows that the largest values are extreme , with a much larger range in the last group of incidences . Some departments in the Andean region , such as Antioquia , Santander , and Tolima , showed intermediate to high incidences for all time periods , while departments such as Valle and Quindío showed intermediate to low incidences . SIR showed high incidences in departments belonging to the Orinoco and Amazon regions in all the time periods . The Caribbean region displays the lowest SIRs across all time periods . Centrally-located departments show stable incidences across time periods , with the notable exceptions of Norte de Santander and Tolima , which trend towards higher values ( Fig 4 ) . Superposition of vector species and leishmaniasis cases shows that departments with greater reported vector diversity tend to display an elevated number of cases , particularly in the departments belonging to the Andean and Orinoco regions ( Fig 5 ) . Lutzomyia gomezi and Psychodopygus panamensis are present in 21 departments each , considered the most widely spread species in the country . They are followed by Psathyromyia shannoni and Nyssomyia trapidoi , which are present in 16 and 11 departments , respectively . Antioquia showed the highest number of vector species , 11 overall , followed by Meta , Caldas , Boyacá , and Amazonas , with 9 species each . Yearly tendency of TL varied according to the region under study , showing a stable pattern in the Andean , Caribbean and Insular regions . The Amazon , Orinoco , and Pacific regions displayed a progressive increase in incidence up to the year 2010 , followed by a stable behavior , mainly in the Amazon and Orinoco regions , and finally decreasing from the year 2014 to 2016 . Case behavior in relation to Io backs the likely influence of the population base in the annual tendency of the event ( Fig 6 ) .
TL remains a public health issue in Colombia and worldwide . This study , shows that the disease trends have been stable in the past decade , particularly in the Caribbean and Insular regions ( Figs 2–4 and 6 ) . Both regions are adjacent to the Caribbean sea , with high average temperatures , and frequent droughts , which inhibit vector spread [8] . The Andean region showed an increasing tendency , which might be due to a variety of factors , including outbreaks , and changes which facilitate the infection’s permanence , urbanization , and deforestation [22–26] . The Orinoco , Amazon and Pacific regions displayed an increasing tendency during the first years considered , with a decrease in incidence in the later years ( Fig 6 ) . The initial tendency coincides with the inception of the epidemiological vigilance system , which could have altered the behavior artificially . Additionally , the geographical characteristics in these regions allow for the optimal development of vectors , thus facilitating the disease’s transmission and permanence [8] . On an intraregional level , we observed highly fluctuating incidences , mainly in the inner Andean Region and the Orinoco region , where low incidences in departments such as Huila , Quindío , Arauca and Casanare can be contrasted with the high incidences found in Santander , Tolima , Meta , and Vichada ( Figs 2–4 ) . These large differences among departments belonging to the same regions , some of which are contiguous , shows that individual departmental characteristics modify disease burden . The Andean region , which gathers over 50% of the country’s population , shows great socioeconomic diversity and highly variable geography [27] . These features have been studied extensively in previous investigations , and have demonstrated a strong influence on disease presentation , particularly in those region in which the biogeographical and social conditions allow not only for vector development , but also for its propagation due to deforestation and urbanization [28 , 29] . Another important aspect is the degree of sophistication of the individual departmental reporting systems , which has a direct impact not only on diagnosis , but also on the disease’s treatment . This can ultimately result in an increase in risk to all the population , since some of the population inhabits distant areas where it is difficult to diagnose and treat them , thus becoming reservoirs and perpetuating the disease’s cycle [28] . On the other hand , the Amazon region demands special attention , not only from Colombia , but also from other countries in the region , due to its connections with countries as Brazil and Peru , which allow for the continued transit of potentially infected humans , and the continuity across borders of vector habitats [3] . This was one of the most affected areas by the disease , with high incidences across all study periods . This can be attributed to the wealth of vector species and of mammals that serve as disease reservoirs , which helps maintain the epidemiological circuit and , in turn , transmission rates [8] . The population in this region is relatively low , when compared with other regions with similar transmission rates ( S1 Table ) , due in part to the large percentage of the territory occupied by tropical rainforest . The opposite situation is seen in the Andean region , which is made up of the 11 departments that make up the majority of the country’s population , in which the large number of cases does not result in elevated incidences ( Figs 1 and 5; S1 Table ) . Some of the factors that may have produced these population concentrations are the armed conflict that was active during the studied periods , and a lack of public policies that favored the agricultural economic sector , which combined led to a reduction in rural population growth , mass displacement from rural to urban areas and an increase in internal migration [30 , 31] . It is worth noting that some departments in the Orinoco and Amazon regions , have shown high transmission rates and prevalence in independent studies [9 , 32] . These same departments report fewer cases to the central surveillance system than departments in other regions with more robust healthcare infrastructure . These same areas are often the most accessible to research groups , which strengthens the surveillance network , particularly in the Andean region . Likewise , the great diversity of circulating Leishmania species in Colombia plays a fundamental role in the permanence and propagation of the disease , given that neither epidemiological surveillance , nor treatment , take this variable into account . This assumes that all species are equally susceptible to treatment , which has been refuted in multiple studies [4 , 11 , 33–35] . The presence of some vectors in over half of the departments in Colombia ( Fig 5 ) shows the importance of this factor in the perpetuation of the epidemiological cycle . This underlines the need to address this issue in order to control Leishmaniasis in the country [8 , 36] . Likewise , the superposition of the vector species with the TL cases is observed most often in zones with high incidences , reinforcing the importance of the vector’s role ( Fig 6 ) . Studies carried out on vectors in Mexico and Spain have shown similar behaviors to those herein presented and have highlighted the need to analyze not only the distributions of the species , but also the bio-climatic and sociodemographic factors as transcendental elements in the transmission of the disease [37 , 38] . Likewise , studies conducted in Brazil have associated factors such as urbanization and poor sanitary conditions with the adaptation and maintenance of the vector life cycle [39 , 40] . This highlights the importance of complementing the epidemiological surveillance with the phlebotominae analysis , more when Ferro et al . , shows through predictive analysis the possible dispersion of each of the species of the vectors involved in the transmission , where it is evident that almost throughout of all the Colombian territory and especially in bordering zones , there can be presence of diverse species of sandfly vectors [8] . The above , denotes the priority that the strengthening of the Epidemiological Surveillance System should have , not only at a national level , but also at a regional level , since the joint analysis of the different elements that make up the epidemiological circuit of the disease will allow not only a better understanding of the system , but also establish more efficient prevention and control measures . Despite the multiple efforts undertaken by governmental agencies to control the disease , many characteristics of the surveillance system must be expanded on to be able to formulate public policies that lead to a reduction in case presentation . Retrospective studies play a significant role in this process , since trends can be identified , and then prevention and control measures can be formulated . Of note , studies in Brazil and Iran have evaluated the spatial distribution and epidemiological characteristics of leishmaniasis , becoming the starting point for a more effective allocation of resources , guiding national and regional public health policy [41 , 42] . Despite the existence of a reporting system , underreporting is common in the most remote rural areas . These areas coincide with areas highly affected by armed conflict , which makes it challenging to estimate the real number of cases with certainty . It is expected that the signing of the peace accords in Colombia will lead to a more sustained and widespread governmental presence in these areas , allowing for more reliable information gathering in both the civilian population and in the population belonging to illegal armed groups . The weaknesses of the national epidemiological surveillance system have direct repercussions over the Regional SisLeish system [13] , which collates data from all countries in the Americas in order to guide the efforts of the PAHO . Non-adherence to the surveillance system and delays in reporting have been detected in the SisLeish system , and can be traced back directly to local systems [13] . The data presented here differ significantly from those reported by Maia-Elkhoury et al . [43] with regards to incidence . This is due to differences in the definition of the population at risk . This study considered the entire population of the department as being at risk , instead of just accounting for the population of municipalities in which cases were reported . Given that underreporting is a major hurdle to analysis , we considered that the totality of the population should be considered at risk , instead of the population of the few municipalities which report cases to the national system . The case of the Amazonas department is illustrative , where some of the municipalities report significant numbers of cases for some years , and none for others ( Fig 2 ) . The population cannot be considered as not having been at risk during the years when no cases were reported . Differences may also have arisen due to base populations being different . The base populations considered in our analysis were extrapolated from census projections of 2005 , since current population dynamics are unknown . The SIR model allows us to highlight departments that are at particularly high risk , and which merit increased attention from the authorities . Although more sophisticated modeling techniques were attempted , high interdepartmental variability in the occurrence of cases resulted in inadequate fits . Geo-political changes introduced further variability , which could correspond to a high rate of internal migration . It should be noted that the highest rates of internal migration during the period studied were found in the departments of Boyacá , Cundinamarca , Meta , and the Orinoco and Amazon regions , which would reflect the displacement of potentially infected populations to urban areas [29 , 44–46] . It is important to note that variables that could aid in modelling , like deforestation and socioeconomic characteristics , are not reported directly by SIVIGILA , and can have dramatic effects on disease occurrence [25 , 38] . Disease dynamics may change significantly in the future due to historical transitions that are underway . The resolution of the armed conflict with the FARC guerrilla , and the establishment of rural transitional zones , will likely lead to many former combatants to be detected by the epidemiological surveillance system . Public health agencies should prepare not only for a significant increase in the number of resources required for diagnosis and treatment , but also for the redistribution of TL cases in the country , which will require changes in resource allocation . This abrupt change may lead to case number spikes in some areas previously considered as low transmission rate areas , which do not correspond to outbreaks , but which will be detected as such by the current system . In spite of SIVIGILA’s shortcomings , it is worthwhile noting that the system must be strengthened and extended , since the data collected by the system are the basis for the analysis of the country’s health situation , giving birth to all of the national public health initiatives . In conclusion , to our knowledge , this is the first study analyzing the TL epidemiological situation for a 10-year period in Colombia , accounting for all geographical subdivisions , and vector species distribution in the country . The Andean , Amazon , and Orinoco regions account for over 75% of the cases of TL in Colombia , so that public health efforts should be extended there , particularly away from urban areas . Enhanced control can be achieved through the implementation of disease vigilance and control systems , and the strengthening of public health networks that could reduce the disease’s impact on the population . Adequate geospatial modelling of the disease could be achieved by means of a more extensive case description which includes socioeconomical and biogeographical data . This information would be required in order to develop predictive models that could more accurately guide public health efforts towards this neglected disease .
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Colombia is among the countries with the highest number of Tegumentary Leishmaniasis cases worldwide . Despite public health efforts , and the existence of a national epidemiological surveillance system , articulated with the regional SisLeish system , the trends followed by the disease’s prevalence and incidence have not been explored . This work presents a retrospective analysis of Tegumentary Leishmaniasis in Colombia between the years 2007 and 2016 , depicting the spatiotemporal distribution of the disease throughout the Colombian territory . The results show a sustained transmission rate , especially in the Amazon and Orinoco regions , and high intraregional variability that could be attributed to each region’s characteristics ( vector species diversity and low adherence to preventive measures ) . The Amazon region is of particular importance due to its direct connection to other endemic countries such as Peru and Brazil . This connection highlights the need to prioritize the implementation of control and prevention strategies in this region . The surveillance system displays multiple flaws , which contribute to under-reporting and have a direct impact on the regional system . Strengthening the system should become a key public health objective in the country . The results of this research can contribute to the understanding of the transmission dynamics of Leishmaniasis in Colombia , as well as to the bolstering of public policy efforts in towards prevention and control of the disease .
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2018
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Geospatial-temporal distribution of Tegumentary Leishmaniasis in Colombia (2007–2016)
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