CD8+ T cell cross-reactivity against SARS-CoV-2 conferred by other coronavirus strains and influenza virus

  1. Chloe H. Lee
  2. Mariana Pereira Pinho
  3. Paul Buckley
  4. Isaac Woodhouse
  5. Graham Ogg
  6. Alison Simmons
  7. Giorgio Napolitani
  8. Hashem Koohy

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Abstract

While individuals infected with coronavirus disease 2019 (COVID-19) manifested a broad range in susceptibility and severity to the disease, the pre-existing immune memory of related pathogens can influence the disease outcome. Here, we investigated the potential extent of T cell cross-reactivity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that can be conferred by other coronaviruses and influenza virus, and generated a map of public and private predicted CD8+ T cell epitopes between coronaviruses. Moreover, to assess the potential risk of self-reactivity and/or diminished T cell response for peptides identical or highly similar to the host, we identified predicted epitopes with high sequence similarity with human proteome. Lastly, we compared predicted epitopes from coronaviruses with epitopes from influenza virus deposited in IEDB to support vaccine development against different virus strains. We believe the comprehensive in silico profile of private and public predicted epitopes across coronaviruses and influenza viruses will facilitate design of vaccines capable of protecting against various viral infections.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.20.107292: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The Repitope package was retrieved from GitHub repository (https://github.com/masato-ogishi/Repitope.git).
    Repitope
    suggested: None
    Visualization of private and public peptides: The conservation of peptides across coronavirus strains before and after MHC binding and immunogenicity prediction were visualized by ‘venn’ function from R venn v1.9 package and upset function from R UpSetR v1.4.0 package.
    R UpSetR
    suggested: None
    To identify shared peptides with up to two amino acid tolerance, the best matching peptides were identified by ‘pairwiseAlignment’ from Biostrings v2.40.2 package using BLOSUM62 matrix, gapOpening of 100 and gapExtension of 100, followed by hamming distance to filter only peptide pairs with less than or equal to two amino acid difference.
    Biostrings
    suggested: (Biostrings, RRID:SCR_016949)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    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.

    About SciScore

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  2. Version published to 10.1101/2020.05.20.107292 on bioRxiv