Peptide Presentation to T Cells: Solving the Immunogenic Puzzle: Systems Immunology Profiling of Antigen Presentation for Prediction of CD8+ T Cell Immunogenicity

Benchmarking bioinformatics pipelines in data-independent acquisition mass spectrometry for immunopeptidomics

Immunopeptidomes are the peptide repertoires bound by the molecules encoded by the major histocompatibility complex (MHC) (human leukocyte antigen (HLA) in humans). These HLA-peptide complexes are presented on the cell surface for immune T-cell recognition. Immunopeptidomics denotes the utilization of tandem mass spectrometry (MS/MS) to identify and quantify peptides bound to HLA molecules. Data-independent acquisition (DIA) has emerged as a powerful strategy for quantitative proteomics and deep proteome-wide identification; however, DIA application to immunopeptidomics analyses has so far seen limited use. Further, of the many DIA data processing tools currently available, there is no consensus in the immunopeptidomics community on the most appropriate pipeline(s) for in-depth and accurate HLA peptide identification. Herein, we benchmarked four commonly used spectral library-based DIA pipelines developed for proteomics applications (Skyline, Spectronaut, DIA-NN, and PEAKS) for their ability to perform immunopeptidome quantification. We validated and assessed the capability of each tool to identify and quantify HLA-bound peptides. Generally, DIA-NN and PEAKS provided higher immunopeptidome coverage with more reproducible results. Skyline and Spectronaut conferred more accurate peptide identification with lower experimental false-positive rates. All tools demonstrated reasonable correlations in quantifying precursors of HLA-bound peptides. Our benchmarking study suggests a combined strategy of applying at least two complementary DIA software tools to achieve the greatest degree of confidence and in-depth coverage of immunopeptidome data.

The HLA Ligandome Comprises a Limited Repertoire of O-GlcNAcylated Antigens Preferentially Associated With HLA-B*07:02

Mass-spectrometry based immunopeptidomics has provided unprecedented insights into antigen presentation, not only charting an enormous ligandome of self-antigens, but also cancer neoantigens and peptide antigens harbouring post-translational modifications. Here we concentrate on the latter, focusing on the small subset of HLA Class I peptides (less than 1%) that has been observed to be post-translationally modified (PTM) by a O-linked N-acetylglucosamine (GlcNAc). Just like neoantigens these modified antigens may have specific immunomodulatory functions. Here we compiled from literature, and a new dataset originating from the JY B cell lymphoblastoid cell line, a concise albeit comprehensive list of O-GlcNAcylated HLA class I peptides. This cumulative list of O-GlcNAcylated HLA peptides were derived from normal and cancerous origin, as well as tissue specimen. Remarkably, the overlap in detected O-GlcNAcylated HLA peptides as well as their source proteins is strikingly high. Most of the O-GlcNAcylated HLA peptides originate from nuclear proteins, notably transcription factors. From this list, we extract that O-GlcNAcylated HLA Class I peptides are preferentially presented by the HLA-B*07:02 allele. This allele loads peptides with a Proline residue anchor at position 2, and features a binding groove that can accommodate well the recently proposed consensus sequence for O-GlcNAcylation, P(V/A/T/S)g(S/T), essentially explaining why HLA-B*07:02 is a favoured binding allele. The observations drawn from the compiled list, may assist in the prediction of novel O-GlcNAcylated HLA antigens, which will be best presented by patients harbouring HLA-B*07:02 or related alleles that use Proline as anchoring residue.

Thermostability profiling of MHC-bound peptides: a new dimension in immunopeptidomics and aid for immunotherapy design

The features of peptide antigens that contribute to their immunogenicity are not well understood. Although the stability of peptide-MHC (pMHC) is known to be important, current assays assess this interaction only for peptides in isolation and not in the context of natural antigen processing and presentation. Here, we present a method that provides a comprehensive and unbiased measure of pMHC stability for thousands of individual ligands detected simultaneously by mass spectrometry (MS). The method allows rapid assessment of intra-allelic and inter-allelic differences in pMHC stability and reveals profiles of stability that are broader than previously appreciated. The additional dimensionality of the data facilitated the training of a model which improves the prediction of peptide immunogenicity, specifically of cancer neoepitopes. This assay can be applied to any cells bearing MHC or MHC-like molecules, offering insight into not only the endogenous immunopeptidome, but also that of neoepitopes and pathogen-derived sequences.