Machine learning-enhanced immunopeptidomics applied to T-cell epitope discovery for COVID-19 vaccines
Kevin A. Kovalchik, David Hamelin, Peter Kubiniok, Benoîte Bourdin, Fatima Mostefai, Raphaël Poujol, Bastien Paré, Shawn M. Simpson, John Sidney, Éric Bonneil, Mathieu Courcelles, Sunil Kumar Saini, Mohammad Shahbazy, Saketh Kapoor, Vigneshwar Rajesh, Maya Weitzen, Jean‐Christophe Grenier, Bayrem Gharsallaoui, Loïze Maréchal, Zhaoguan Wu, Christopher J. Savoie, Alessandro Sette, Pierre Thibault, Isabelle Sirois, Martin A. Smith, Hélène Decaluwe, Julie Hussin, Mathieu Lavallée‐Adam, Étienne Caron
Abstract
Next-generation T-cell-directed vaccines for COVID-19 focus on establishing lasting T-cell immunity against current and emerging SARS-CoV-2 variants. Precise identification of conserved T-cell epitopes is critical for designing effective vaccines. Here we introduce a comprehensive computational framework incorporating a machine learning algorithm—MHCvalidator—to enhance mass spectrometry-based immunopeptidomics sensitivity. MHCvalidator identifies unique T-cell epitopes presented by the B7 supertype, including an epitope from a + 1-frameshift in a truncated Spike antigen, supported by ribosome profiling. Analysis of 100,512 COVID-19 patient proteomes shows Spike antigen truncation in 0.85% of cases, revealing frameshifted viral antigens at the population level. Our EpiTrack pipeline tracks global mutations of MHCvalidator-identified CD8 + T-cell epitopes from the BNT162b4 vaccine. While most vaccine epitopes remain globally conserved, an immunodominant A*01-associated epitope mutates in Delta and Omicron variants. This work highlights SARS-CoV-2 antigenic features and emphasizes the importance of continuous adaptation in T-cell vaccine development. The identification of T cell epitopes is a critical step in understanding the immune response to infection and in designing vaccine based approaches. Here the authors introduce a frame work of antigen discovery called MHCvalidator and Epitrack to identify new antigenic features for T-cell COVID-19 vaccines and characterise a novel non-canonical epitope from a truncated Spike variant and mutation of an immunodominant epitope in the BNT162b4 vaccine.