Evasive Spike Variants Elucidate the Preservation of T Cell Immune Response to the SARS-CoV-2 Omicron Variant

Arnav Solanki, James Cornette, Julia Udell, George Vasmatzis, Marc Riedel

    Research output: Contribution to journalArticlepeer-review

    Abstract

    The Omicron variants boast the highest infectivity rates among all SARS-CoV-2 variants. Despite their lower disease severity, they can reinfect COVID-19 patients and infect vaccinated individuals as well. The high number of mutations in these variants render them resistant to antibodies that otherwise neutralize the spike protein of the original SARS-CoV-2 spike protein. Recent research has shown that despite its strong immune evasion, Omicron still induces strong T Cell responses similar to the original variant. This work investigates the molecular basis for this observation using the neural network tools NetMHCpan-4.1 and NetMHCiipan-4.0. The antigens presented through the MHC Class I and Class II pathways from all the notable SARS-CoV-2 variants were compared across numerous high frequency HLAs. All variants were observed to have equivalent T cell antigenicity. A novel positive control system was engineered in the form of spike variants that did evade T Cell responses, unlike Omicron. These evasive spike proteins were used to statistically confirm that the Omicron variants did not exhibit lower antigenicity in the MHC pathways. These results suggest that T Cell immunity mounts a strong defense against COVID-19 which is difficult for SARS-CoV-2 to overcome through mere evolution.

    Original languageEnglish (US)
    Pages (from-to)450-460
    Number of pages11
    JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
    Volume21
    Issue number3
    DOIs
    StatePublished - May 1 2024

    Bibliographical note

    Publisher Copyright:
    © 2004-2012 IEEE.

    Keywords

    • COVID-19
    • histocompatibility antigens Class I
    • histocompatibility antigens Class II
    • immunogenicity
    • spike glycoprotein

    PubMed: MeSH publication types

    • Journal Article
    • Research Support, U.S. Gov't, Non-P.H.S.

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