Antigenic Evolution on a Global Scale Reveals the Potential Natural Selection of Severe Acute Respiratory Syndrome-Coronavirus 2 by Pre-existing Cross-Reactive T-Cell Immunity

  1. Chengdong Zhang
  2. Xuanxuan Jin
  3. Xianyang Chen
  4. Li Qiu
  5. Qibin Leng
  6. Tianyi Qiu

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Abstract

The mutation pattern of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) has changed constantly during worldwide community transmission of this virus. However, the reasons for the changes in mutation patterns are still unclear. Accordingly, in this study, we present a comprehensive analysis of over 300 million peptides derived from 13,432 SARS-CoV-2 strains harboring 4,420 amino acid mutations to analyze the potential selective pressure of the host immune system and reveal the driver of mutations in circulating SARS-CoV-2 isolates. The results showed that the nonstructural protein ORF1ab and the structural protein Spike were most susceptible to mutations. Furthermore, mutations in cross-reactive T-cell epitopes between SARS-CoV-2 and seasonal human coronavirus may help SARS-CoV-2 to escape cellular immunity under long-term and large-scale community transmission. Additionally, through homology modeling and protein docking, mutations in Spike protein may enhance the ability of SARS-CoV-2 to invade host cells and escape antibody-mediated B-cell immunity. Our research provided insights into the potential mutation patterns of SARS-CoV-2 under natural selection, improved our understanding of the evolution of the virus, and established important guidance for potential vaccine design.

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  1. Version published to 10.3389/fmicb.2021.599562
  2. ScreenIT

    SciScore for 10.1101/2020.06.16.154591: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

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  3. Version published to 10.1101/2020.06.16.154591v1 on bioRxiv