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

Characterization of HIV-Specific CD4+T Cell Responses against Peptides Selected with Broad Population and Pathogen Coverage

CD4+ T cells orchestrate immunity against viral infections, but their importance in HIV infection remains controversial. Nevertheless, comprehensive studies have associated increase in breadth and functional characteristics of HIV-specific CD4+ T cells with decreased viral load. A major challenge for the identification of HIV-specific CD4+ T cells targeting broadly reactive epitopes in populations with diverse ethnic background stems from the vast genomic variation of HIV and the diversity of the host cellular immune system. Here, we describe a novel epitope selection strategy, PopCover, that aims to resolve this challenge, and identify a set of potential HLA class II-restricted HIV epitopes that in concert will provide optimal viral and host coverage. Using this selection strategy, we identified 64 putative epitopes (peptides) located in the Gag, Nef, Env, Pol and Tat protein regions of HIV. In total, 73% of the predicted peptides were found to induce HIV-specific CD4+ T cell responses. The Gag and Nef peptides induced most responses. The vast majority of the peptides (93%) had predicted restriction to the patient’s HLA alleles. Interestingly, the viral load in viremic patients was inversely correlated to the number of targeted Gag peptides. In addition, the predicted Gag peptides were found to induce broader polyfunctional CD4+ T cell responses compared to the commonly used Gag-p55 peptide pool. These results demonstrate the power of the PopCover method for the identification of broadly recognized HLA class II-restricted epitopes. All together, selection strategies, such as PopCover, might with success be used for the evaluation of antigen-specific CD4+ T cell responses and design of future vaccines

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

Simple Metals at High Pressure

In this lecture we review high-pressure phase transition sequences exhibited by simple elements, looking at the examples of the main group I, II, IV, V, and VI elements. General trends are established by analyzing the changes in coordination number on compression. Experimentally found phase transitions and crystal structures are discussed with a brief description of the present theoretical picture.Comment: 22 pages, 4 figures, lecture notes for the lecture given at the Erice course on High-Pressure Crystallography in June 2009, Sicily, Ital

Proteome Sampling by the HLA Class I Antigen Processing Pathway

The peptide repertoire that is presented by the set of HLA class I molecules of an individual is formed by the different players of the antigen processing pathway and the stringent binding environment of the HLA class I molecules. Peptide elution studies have shown that only a subset of the human proteome is sampled by the antigen processing machinery and represented on the cell surface. In our study, we quantified the role of each factor relevant in shaping the HLA class I peptide repertoire by combining peptide elution data, in silico predictions of antigen processing and presentation, and data on gene expression and protein abundance. Our results indicate that gene expression level, protein abundance, and rate of potential binding peptides per protein have a clear impact on sampling probability. Furthermore, once a protein is available for the antigen processing machinery in sufficient amounts, C-terminal processing efficiency and binding affinity to the HLA class I molecule determine the identity of the presented peptides. Having studied the impact of each of these factors separately, we subsequently combined all factors in a logistic regression model in order to quantify their relative impact. This model demonstrated the superiority of protein abundance over gene expression level in predicting sampling probability. Being able to discriminate between sampled and non-sampled proteins to a significant degree, our approach can potentially be used to predict the sampling probability of self proteins and of pathogen-derived proteins, which is of importance for the identification of autoimmune antigens and vaccination targets

Allergen-specific IgG+ memory B cells are temporally linked to IgE memory responses

BACKGROUND: Immunoglobulin E (IgE) are least abundant, tightly regulated and IgE producing B cells are rare. The cellular origin and evolution of IgE responses are poorly understood. OBJECTIVE: To investigate the cellular and clonal origin of IgE memory responses following mucosal allergen exposure by sublingual immunotherapy (SLIT). METHODS: In a randomized double-blind, placebo-controlled, time-course SLIT study, peripheral blood mononuclear cells (PBMCs) and nasal biopsies were collected from forty adults with seasonal allergic rhinitis at baseline, 4, 8, 16, 28 and 52 weeks. RNA was extracted from PBMCs, sorted B cells and nasal biopsies for VH repertoire sequencing. Moreover, monoclonal antibodies were derived from single B cell transcriptomes. RESULTS: Combining VH repertoire sequencing and single cell transcriptomics yielded direct evidence of a parallel boost of two clonally and functionally related B cell subsets of short-lived IgE+ plasmablasts and IgG+ memory B cells (termed IgGE). Mucosal grass pollen allergen exposure by SLIT resulted in highly diverse IgE and IgGE repertoires. These were extensively mutated and appeared relative stable as per heavy chain isotype, somatic hypermutations and clonal composition. Single IgGE + memory B cell and IgE+ pre-plasmablast transcriptomes encoded antibodies that were specific for major grass pollen allergens and were able to elicit basophil activation at very low allergen concentrations. CONCLUSION: For the first time, we have shown that upon mucosal allergen exposure, human IgE memory resides in allergen-specific IgG+ memory B cells. These rapidly switch isotype and expand into short-lived IgE+ plasmablasts and serve as a potential target for therapeutic intervention