Clusters versus Affinity-Based Approaches in F. tularensis Whole Genome Search of CTL Epitopes

Deciphering the cellular immunome of a bacterial pathogen is challenging due to the enormous number of putative peptidic determinants. State-of-the-art prediction methods developed in recent years enable to significantly reduce the number of peptides to be screened, yet the number of remaining candidates for experimental evaluation is still in the range of ten-thousands, even for a limited coverage of MHC alleles. We have recently established a resource-efficient approach for down selection of candidates and enrichment of true positives, based on selection of predicted MHC binders located in high density “hotspots" of putative epitopes. This cluster-based approach was applied to an unbiased, whole genome search of Francisella tularensis CTL epitopes and was shown to yield a 17–25 fold higher level of responders as compared to randomly selected predicted epitopes tested in Kb/Db C57BL/6 mice. In the present study, we further evaluate the cluster-based approach (down to a lower density range) and compare this approach to the classical affinity-based approach by testing putative CTL epitopes with predicted IC50 values of <10 nM. We demonstrate that while the percent of responders achieved by both approaches is similar, the profile of responders is different, and the predicted binding affinity of most responders in the cluster-based approach is relatively low (geometric mean of 170 nM), rendering the two approaches complimentary. The cluster-based approach is further validated in BALB/c F. tularensis immunized mice belonging to another allelic restriction (Kd/Dd) group. To date, the cluster-based approach yielded over 200 novel F. tularensis peptides eliciting a cellular response, all were verified as MHC class I binders, thereby substantially increasing the F. tularensis dataset of known CTL epitopes. The generality and power of the high density cluster-based approach suggest that it can be a valuable tool for identification of novel CTLs in proteomes of other bacterial pathogens

Whole-Genome Immunoinformatic Analysis of F. tularensis: Predicted CTL Epitopes Clustered in Hotspots Are Prone to Elicit a T-Cell Response

The cellular arm of the immune response plays a central role in the defense against intracellular pathogens, such as F. tularensis. To date, whole genome immunoinformatic analyses were limited either to relatively small genomes (e.g. viral) or to preselected subsets of proteins in complex pathogens. Here we present, for the first time, an unbiased bacterial global immunoinformatic screen of the 1740 proteins of F. tularensis subs. holarctica (LVS), aiming at identification of immunogenic peptides eliciting a CTL response. The very large number of predicted MHC class I binders (about 100,000, IC50 of 1000 nM or less) required the design of a strategy for further down selection of CTL candidates. The approach developed focused on mapping clusters rich in overlapping predicted epitopes, and ranking these “hotspot” regions according to the density of putative binding epitopes. Limited by the experimental load, we selected to screen a library of 1240 putative MHC binders derived from 104 top-ranking highly dense clusters. Peptides were tested for their ability to stimulate IFNγ secretion from splenocytes isolated from LVS vaccinated C57BL/6 mice. The majority of the clusters contained one or more CTL responder peptides and altogether 127 novel epitopes were identified, of which 82 are non-redundant. Accordingly, the level of success in identification of positive CTL responders was 17–25 fold higher than that found for a randomly selected library of 500 predicted MHC binders (IC50 of 500 nM or less). Most proteins (ca. 2/3) harboring the highly dense hotspots are membrane-associated. The approach for enrichment of true positive CTL epitopes described in this study, which allowed for over 50% increase in the dataset of known T-cell epitopes of F. tularensis, could be applied in immunoinformatic analyses of many other complex pathogen genomes

Global analyses of TetR family transcriptional regulators in mycobacteria indicates conservation across species and diversity in regulated functions

BACKGROUND: Mycobacteria inhabit diverse niches and display high metabolic versatility. They can colonise both humans and animals and are also able to survive in the environment. In order to succeed, response to environmental cues via transcriptional regulation is required. In this study we focused on the TetR family of transcriptional regulators (TFTRs) in mycobacteria. RESULTS: We used InterPro to classify the entire complement of transcriptional regulators in 10 mycobacterial species and these analyses showed that TFTRs are the most abundant family of regulators in all species. We identified those TFTRs that are conserved across all species analysed and those that are unique to the pathogens included in the analysis. We examined genomic contexts of 663 of the conserved TFTRs and observed that the majority of TFTRs are separated by 200 bp or less from divergently oriented genes. Analyses of divergent genes indicated that the TFTRs control diverse biochemical functions not limited to efflux pumps. TFTRs typically bind to palindromic motifs and we identified 11 highly significant novel motifs in the upstream regions of divergently oriented TFTRs. The C-terminal ligand binding domain from the TFTR complement in M. tuberculosis showed great diversity in amino acid sequence but with an overall architecture common to other TFTRs. CONCLUSION: This study suggests that mycobacteria depend on TFTRs for the transcriptional control of a number of metabolic functions yet the physiological role of the majority of these regulators remain unknown. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1696-9) contains supplementary material, which is available to authorized users

A FAIR guide for data providers to maximise sharing of human genomic data

It is generally acknowledged that, for reproducibility and progress of human genomic research, data sharing is critical. For every sharing transaction, a successful data exchange is produced between a data consumer and a data provider. Providers of human genomic data (e.g., publicly or privately funded repositories and data archives) fulfil their social contract with data donors when their shareable data conforms to FAIR (findable, accessible, interoperable, reusable) principles. Based on our experiences via Repositive (https://repositive.io), a leading discovery platform cataloguing all shared human genomic datasets, we propose guidelines for data providers wishing to maximise their shared data’s FAIRness. Citation: Corpas M, Kovalevskaya NV, McMurray A, Niel

Time for T? Immunoinformatics addresses the challenges of vaccine design for neglected tropical and emerging infectious diseases

Vaccines have been invaluable for global health, saving lives and reducing healthcare costs, while also raising the quality of human life. However, newly emerging infectious diseases (EID) and more well-established tropical disease pathogens present complex challenges to vaccine developers; in particular, neglected tropical diseases, which are most prevalent among the world’s poorest, include many pathogens with large sizes, multistage life cycles and a variety of nonhuman vectors. EID such as MERS-CoV and H7N9 are highly pathogenic for humans. For many of these pathogens, while their genomes are available, immune correlates of protection are currently unknown. These complexities make developing vaccines for EID and neglected tropical diseases all the more difficult. In this review, we describe the implementation of an immunoinformatics-driven approach to systematically search for key determinants of immunity in newly available genome sequence data and design vaccines. This approach holds promise for the development of 21st century vaccines, improving human health everywhere

Simultaneous assessment of acidogenesis-mitigation and specific bacterial growth-inhibition by dentifrices

Dentifrices can augment oral hygiene by inactivating bacteria and at sub-lethal concentrations may affect bacterial metabolism, potentially inhibiting acidogenesis, the main cause of caries. Reported herein is the development of a rapid method to simultaneously measure group-specific bactericidal and acidogenesis-mitigation effects of dentifrices on oral bacteria. Saliva was incubated aerobically and anaerobically in Tryptone Soya Broth, Wilkins-Chalgren Broth with mucin, or artificial saliva and was exposed to dentifrices containing triclosan/copolymer (TD); sodium fluoride (FD); stannous fluoride and zinc lactate (SFD1); or stannous fluoride, zinc lactate and stannous chloride (SFD2). Minimum inhibitory concentrations (MIC) were determined turbidometrically whilst group-specific minimum bactericidal concentrations (MBC) were assessed using growth media and conditions selective for total aerobes, total anaerobes, streptococci and Gram-negative anaerobes. Minimum acid neutralization concentration (MNC) was defined as the lowest concentration of dentifrice at which acidification was inhibited. Differences between MIC and MNC were calculated and normalized with respect to MIC to derive the combined inhibitory and neutralizing capacity (CINC), a cumulative measure of acidogenesis-mitigation and growth inhibition. The overall rank order for growth inhibition potency (MIC) under aerobic and anaerobic conditions was: TD> SFD2> SFD1> FD. Acidogenesis-mitigation (MNC) was ordered; TD> FD> SFD2> SFD1. CINC was ordered TD> FD> SFD2> SFD1 aerobically and TD> FD> SFD1> SFD2 anaerobically. With respect to group-specific bactericidal activity, TD generally exhibited the greatest potency, particularly against total aerobes, total anaerobes and streptococci. This approach enables the rapid simultaneous evaluation of acidity mitigation, growth inhibition and specific antimicrobial activity by dentifrices

The clinical presentation of culture-positive and culture-negative, qPCR-attributable shigellosis in the Global Enteric Multicenter Study and derivation of a Shigella severity score: implications for pediatric Shigella vaccine trials

BACKGROUND: Shigella is a leading cause of childhood diarrhea and target for vaccine development. Microbiologic and clinical case definitions are needed for pediatric field vaccine efficacy trials. METHODS: We compared characteristics of moderate to severe diarrhea (MSD) cases in the Global Enteric Multicenter Study (GEMS) between children with culture positive Shigella to those with culture-negative, qPCR-attributable Shigella (defined by an ipaH gene cycle threshold <27.9). Among Shigella MSD cases, we determined risk factors for death and derived a clinical severity score. RESULTS: Compared to culture-positive Shigella MSD cases (n=745), culture-negative/qPCR-attributable Shigella cases (n=852) were more likely to be under 12 months, stunted, have a longer duration of diarrhea, and less likely to have high stool frequency or a fever. There was no difference in dehydration, hospitalization, or severe classification from a modified Vesikari score. Twenty-two (1.8%) Shigella MSD cases died within the 14-days after presentation to health facilities, and 59.1% of these deaths were in culture-negative cases. Age < 12 months, diarrhea duration prior to presentation, vomiting, stunting, wasting, and hospitalization were associated with mortality. A model-derived score assigned points for dehydration, hospital admission, and longer diarrhea duration but was not significantly better at predicting 14-day mortality than a modified Vesikari score. CONCLUSIONS: A composite severity score consistent with severe disease or dysentery may be a pragmatic clinical endpoint for severe shigellosis in vaccine trials. Reliance on culture for microbiologic confirmation may miss a substantial number of Shigella cases but is currently required to measure serotype specific immunity

A Detailed Analysis of the Murine TAP Transporter Substrate Specificity

The transporter associated with antigen processing (TAP) supplies cytosolic peptides into the endoplasmic reticulum for binding to major histocompatibility complex (MHC) class I molecules. Its specificity therefore influences the repertoire of peptides presented by MHC molecules. Compared to human TAP, murine TAP's binding specificity has not been characterized as well, even though murine systems are widely used for basic studies of antigen processing and presentation.We performed a detailed experimental analysis of murine TAP binding specificity by measuring the binding affinities of 323 peptides. Based on this experimental data, a computational model of murine TAP specificity was constructed. The model was compared to previously generated data on human and murine TAP specificities. In addition, the murine TAP specificities for known epitopes and random peptides were predicted and compared to assess the impact of murine TAP selectivity on epitope selection.Comparisons to a previously constructed model of human TAP specificity confirms the well-established differences for peptide substrates with positively charged C-termini. In addition these comparisons show that several residues at the N-terminus of peptides which strongly influence binding to human TAP showed little effect on binding to murine TAP, and that the overall influence of the aminoterminal residues on peptide affinity for murine TAP is much lower than for the human transporter. Murine TAP also partly prefers different hydrophobic amino acids than human TAP in the carboxyterminal position. These species-dependent differences in specificity determined in vitro are shown to correlate with the epitope repertoire recognized in vivo. The quantitative model of binding specificity of murine TAP developed herein should be useful for interpreting epitope mapping and immunogenicity data obtained in humanized mouse models

Reflections on the ethics of recruiting foreign-trained human resources for health

<p>Abstract</p> <p>Background</p> <p>Developed countries' gains in health human resources (HHR) from developing countries with significantly lower ratios of health workers have raised questions about the ethics or fairness of recruitment from such countries. By attracting and/or facilitating migration for foreign-trained HHR, notably those from poorer, less well-resourced nations, recruitment practices and policies may be compromising the ability of developing countries to meet the health care needs of their own populations. Little is known, however, about actual recruitment practices. In this study we focus on Canada (a country with a long reliance on internationally trained HHR) and recruiters working for Canadian health authorities.</p> <p>Methods</p> <p>We conducted interviews with health human resources recruiters employed by Canadian health authorities to describe their recruitment practices and perspectives and to determine whether and how they reflect ethical considerations.</p> <p>Results and discussion</p> <p>We describe the methods that recruiters used to recruit foreign-trained health professionals and the systemic challenges and policies that form the working context for recruiters and recruits. HHR recruiters' reflections on the global flow of health workers from poorer to richer countries mirror much of the content of global-level discourse with regard to HHR recruitment. A predominant market discourse related to shortages of HHR outweighed discussions of human rights and ethical approaches to recruitment policy and action that consider global health impacts.</p> <p>Conclusions</p> <p>We suggest that the concept of corporate social responsibility may provide a useful approach at the local organizational level for developing policies on ethical recruitment. Such local policies and subsequent practices may inform public debate on the health equity implications of the HHR flows from poorer to richer countries inherent in the global health worker labour market, which in turn could influence political choices at all government and health system levels.</p

Development and Validation of an Epitope Prediction Tool for Swine (PigMatrix) Based on the Pocket Profile Method

Background: T cell epitope prediction tools and associated vaccine design algorithms have accelerated the development of vaccines for humans. Predictive tools for swine and other food animals are not as well developed, primarily because the data required to develop the tools are lacking. Here, we overcome a lack of T cell epitope data to construct swine epitope predictors by systematically leveraging available human information. Applying the “pocket profile method”, we use sequence and structural similarities in the binding pockets of human and swine major histocompatibility complex proteins to infer Swine Leukocyte Antigen (SLA) peptide binding preferences. We developed epitope-prediction matrices (PigMatrices), for three SLA class I alleles (SLA-1*0401, 2*0401 and 3*0401) and one class II allele (SLA-DRB1*0201), based on the binding preferences of the best-matched Human Leukocyte Antigen (HLA) pocket for each SLA pocket. The contact residues involved in the binding pockets were defined for class I based on crystal structures of either SLA (SLA-specific contacts, Ssc) or HLA supertype alleles (HLA contacts, Hc); for class II, only Hc was possible. Different substitution matrices were evaluated (PAM and BLOSUM) for scoring pocket similarity and identifying the best human match. The accuracy of the PigMatrices was compared to available online swine epitope prediction tools such as PickPocket and NetMHCpan. Results: PigMatrices that used Ssc to define the pocket sequences and PAM30 to score pocket similarity demonstrated the best predictive performance and were able to accurately separate binders from random peptides. For SLA-1*0401 and 2*0401, PigMatrix achieved area under the receiver operating characteristic curves (AUC) of 0.78 and 0.73, respectively, which were equivalent or better than PickPocket (0.76 and 0.54) and NetMHCpan version 2.4 (0.41 and 0.51) and version 2.8 (0.72 and 0.71). In addition, we developed the first predictive SLA class II matrix, obtaining an AUC of 0.73 for existing SLA-DRB1*0201 epitopes. Notably, PigMatrix achieved this level of predictive power without training on SLA binding data. Conclusions: Overall, the pocket profile method combined with binding preferences from HLA binding data shows significant promise for developing T cell epitope prediction tools for pigs. When combined with existing vaccine design algorithms, PigMatrix will be useful for developing genome-derived vaccines for a range of pig pathogens for which no effective vaccines currently exist (e.g. porcine reproductive and respiratory syndrome, influenza and porcine epidemic diarrhea)