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A key component of pathogen-specific adaptive immunity in vertebrates is the presentation of pathogen-derived antigenic peptides by major histocompatibility complex (MHC) molecules. The excessive polymorphism observed at MHC genes is widely presumed to result from the need to recognize diverse pathogens, a process called pathogen-driven balancing selection. This process assumes that pathogens differ in their peptidomes—the pool of short peptides derived from the pathogen’s proteome—so that different pathogens select for different MHC variants with distinct peptide-binding properties. Here, we tested this assumption in a comprehensive data set of 51.9 Mio peptides, derived from the peptidomes of 36 representative human pathogens. Strikingly, we found that 39.7% of the 630 pairwise comparisons among pathogens yielded not a single shared peptide and only 1.8% of pathogen pairs shared more than 1% of their peptides. Indeed, 98.8% of all peptides were unique to a single pathogen species. Using computational binding prediction to characterize the binding specificities of 321 common human MHC class-I variants, we investigated quantitative differences among MHC variants with regard to binding peptides from distinct pathogens. Our analysis showed signatures of specialization toward specific pathogens especially by MHC variants with narrow peptide-binding repertoires. This supports the hypothesis that such fastidious MHC variants might be maintained in the population because they provide an advantage against particular pathogens. Overall, our results establish a key selection factor for the excessive allelic diversity at MHC genes observed in natural populations and illuminate the evolution of variable peptide-binding repertoires among MHC variants.

Tuberculosis (TB), caused by (MTB), remains a significant global health concern. The existing vaccine, Bacillus Calmette-Guérin (BCG), provides inconsistent protection, highlighting the pressing need for a more effective vaccine. We aimed to identify novel antigens and assess their protective efficacy as TB vaccine candidates. Using immunopeptidomics, we identified 64 and 80 unique mycobacterial antigens derived from BCG and MTB, respectively. We prioritised antigens based on HLA allele coverage through an immunoinformatics approach. The candidates, , , and , delivered as DNA vaccines, were evaluated for efficacy in mice using the ex vivo Mycobacterial Growth Inhibition Assay (MGIA) and was identified as a promising candidate. In vivo murine challenge experiments confirmed the protective efficacy conferred by when formulated as recombinant protein with AS01™ or AddaS03™ adjuvants, compared to the naïve group. The immunogenic profiles of formulated in the two different adjuvants differed, with -AS01™ inducing antigen-specific IFN-γ, TNF-α, IL-2, IL-17, IgG1 and IgG2a-c, while -AddaS03™ induced TNF-α, IL-2, IL-17, IL-4, IgM, IgG1, IgG2b. Our findings highlight as a promising protective antigen for future TB vaccine development.

The Human Leukocyte Antigen (HLA) locus associates with a variety of complex diseases, particularly autoimmune and inflammatory conditions. The HLA-DR15 haplotype, for example, confers the major risk for developing Multiple Sclerosis in Caucasians, pinpointing an important role in the etiology of this chronic inflammatory disease of the central nervous system. In addition to the protein-coding variants that shape the functional HLA-antigen-T cell interaction, recent studies suggest that the levels of HLA molecule expression, that are epigenetically controlled, also play a role in disease development. However, deciphering the exact molecular mechanisms of the HLA association has been hampered by the tremendous genetic complexity of the locus and a lack of robust approaches to investigate it. Here, we developed a method to specifically enrich the genomic DNA from the HLA class II locus (chr6:32,426,802-34,167,129) and proximal promoters of 2,157 immune-relevant genes, utilizing the Agilent RNA-based SureSelect Methyl-Seq Capture related method, followed by sequencing to detect genetic and epigenetic variation. We demonstrated successful simultaneous detection of the genetic variation and quantification of DNA methylation levels in HLA locus. Moreover, by the detection of differentially methylated positions in promoters of immune-related genes, we identified relevant pathways following stimulation of cells. Taken together, we present a method that can be utilized to study the interplay between genetic variance and epigenetic regulation in the HLA class II region, potentially, in a wide disease context.

In light of the tremendous amount of cellular, molecular, and genetic information identifying key aspects of autoimmune diseases, it is arguably apparent that the manifestation of autoimmune disease is governed by the acquisition of multiple immune-compromising traits. These traits increase susceptibility and drive disease. To identify critical traits, or hallmarks, of autoimmune diseases, we asked what hallmarks were shared among three kidney autoimmune diseases: Anti-glomerular basement membrane (anti-GBM) disease, systemic lupus erythematosus (SLE) nephritis, and anti-neutrophil cytoplasmic-autoantibody (ANCA) pauci-immune small vessel vasculitis. At least six hallmarks emerged: (1) autoreactive cells evade deletion, (2) presence of asymptomatic autoantibodies, (3) hyperactivity of Fc–FcR pathway, (4) susceptibility to environmental impact, (5) antigenic modifications of self proteins, (6) microbial infections. We propose that these hallmarks, in spite of the mechanism through which they arise, are shared by most, if not all, autoantibody-mediated diseases.