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Integrating Machine Learning-Enhanced Immunopeptidomics and SARS-CoV-2 Population-Scale Analyses Unveils Novel Antigenic Features for Next-Generation COVID-19 Vaccines

Title: Integrating Machine Learning-Enhanced Immunopeptidomics and SARS-CoV-2 Population-Scale Analyses Unveils Novel Antigenic Features for Next-Generation COVID-19 Vaccines
Authors: Caron, Etienne; Kovalchik, Kevin; Hamelin, David; Kubiniok, Peter; Bourdin, Benoite; Mostefai, Fatima; Poujol, Raphaël; Paré, Bastien; Simpson, Shawn; Sidney, John; Bonneil, Eric; Courcelles, Mathieu; Saini, Sunil Kumar; Kapoor, Saketh; Weitzen, Maya; Grenier, Jean-Christophe; Gharsallaoui, Bayrem; Maréchal, Loïze; Wu, Zhaoguan; Savoie, Christopher; Sette, Alessandro; Thibault, Pierre; Sirois, Isabelle; Smith, Martin; Decaluwe, Hélène; Hussin, Julie; Lavallée-Adam, Mathieu
Publisher Information: Springer Science and Business Media LLC
Publication Year: 2024
Description: Next-generation T-cell-directed vaccines for COVID-19 aim to induce durable T-cell immunity against circulating and future hypermutated SARS-CoV-2 variants. Mass Spectrometry (MS)-based immunopeptidomics holds promise for guiding vaccine design, but computational challenges impede the precise and unbiased identification of conserved T-cell epitopes crucial for vaccines against rapidly mutating viruses. We introduce a computational framework and analysis platform integrating a novel machine learning algorithm, immunopeptidomics, intra-host data, epitope immunogenicity, and geo-temporal CD8+ T-cell epitope conservation analyses. Central to our approach is MHCvalidator, a novel artificial neural network algorithm enhancing MS-based immunopeptidomics sensitivity by modeling antigen presentation and sequence features. MHCvalidator identified a novel nonconventional SARS-CoV-2 T-cell epitope presented by B7 supertype molecules, originating from a +1-frameshift in a truncated Spike (S) antigen, supported by ribo-seq data. Intra-host analysis of SARS-CoV-2 proteomes from ~100,000 COVID-19 patients revealed a prevalent S antigen truncation in ~51% of cases, exposing a rich source of frameshifted viral antigens. Our framework includes EpiTrack, a new computational pipeline tracking global mutational dynamics of MHCvalidator-identified SARS-CoV-2 CD8+ epitopes from vaccine BNT162b4. While most vaccine-encoded CD8+ epitopes exhibit global conservation from January 2020 to October 2023, a highly immunodominant A*01-associated epitope, especially in hospitalized patients, undergoes substantial mutations in Delta and Omicron variants. Our approach unveils unprecedented SARS-CoV-2 T-cell epitopes, elucidates novel antigenic features, and underscores mutational dynamics of vaccine-relevant epitopes. The analysis platform is applicable to any viruses, and underscores the need for continual vigilance in T-cell vaccine development against the evolving landscape of hypermutating SARS-CoV-2 variants.
Document Type: other/unknown material
Language: unknown
DOI: 10.21203/rs.3.rs-3914861/v1
Availability: http://dx.doi.org/10.21203/rs.3.rs-3914861/v1; https://www.researchsquare.com/article/rs-3914861/v1; https://www.researchsquare.com/article/rs-3914861/v1.html
Rights: https://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.39F69269
Database: BASE