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The mutational landscape of SARS-CoV-2 variants diversifies T cell targets in an HLA supertype-dependent manner (preprint)
biorxiv; 2021.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2021.06.03.446959
ABSTRACT
The rapid, global dispersion of SARS-CoV-2 since its initial identification in December 2019 has led to the emergence of a diverse range of variants. The initial concerns regarding the virus were quickly compounded with concerns relating to the impact of its mutated forms on viral infectivity, pathogenicity and immunogenicity. To address the latter, we seek to understand how the mutational landscape of SARS-CoV-2 has shaped HLA-restricted T cell immunity at the population level during the first year of the pandemic, before mass vaccination. We analyzed a total of 330,246 high quality SARS-CoV-2 genome assemblies sampled across 143 countries and all major continents. Strikingly, we found that specific mutational patterns in SARS-CoV-2 diversify T cell epitopes in an HLA supertype-dependent manner. In fact, we observed that proline residues are preferentially removed from the proteome of prevalent mutants, leading to a predicted global loss of SARS-CoV-2 T cell epitopes in individuals expressing HLA-B alleles of the B7 supertype family. In addition, we show that this predicted global loss of epitopes is largely driven by a dominant C-to-U mutation type at the RNA level. These results indicate that B7 supertype-associated epitopes, including the most immunodominant ones, were more likely to escape CD8+ T cell immunosurveillance during the first year of the pandemic. Together, our study lays the foundation to help understand how SARS-CoV-2 mutants shape the repertoire of T cell targets and T cell immunity across human populations. The proposed theoretical framework has implications in viral evolution, disease severity, vaccine resistance and herd immunity.

Full text: Available Collection: Preprints Database: bioRxiv Language: English Year: 2021 Document Type: Preprint

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Full text: Available Collection: Preprints Database: bioRxiv Language: English Year: 2021 Document Type: Preprint