Benchmarking evolutionary tinkering underlying human–viral molecular mimicry shows multiple host pulmonary–arterial peptides mimicked by SARS-CoV-2

  1. A. J. Venkatakrishnan
  2. Nikhil Kayal
  3. Praveen Anand
  4. Andrew D. Badley
  5. George M. Church
  6. Venky Soundararajan

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Abstract

The hand of molecular mimicry in shaping SARS-CoV-2 evolution and immune evasion remains to be deciphered. Here, we report 33 distinct 8-mer/9-mer peptides that are identical between SARS-CoV-2 and the human reference proteome. We benchmark this observation against other viral–human 8-mer/9-mer peptide identity, which suggests generally similar extents of molecular mimicry for SARS-CoV-2 and many other human viruses. Interestingly, 20 novel human peptides mimicked by SARS-CoV-2 have not been observed in any previous coronavirus strains (HCoV, SARS-CoV, and MERS). Furthermore, four of the human 8-mer/9-mer peptides mimicked by SARS-CoV-2 map onto HLA-B*40:01, HLA-B*40:02, and HLA-B*35:01 binding peptides from human PAM, ANXA7, PGD, and ALOX5AP proteins. This mimicry of multiple human proteins by SARS-CoV-2 is made salient by single-cell RNA-seq (scRNA-seq) analysis that shows the targeted genes significantly expressed in human lungs and arteries; tissues implicated in COVID-19 pathogenesis. Finally, HLA-A*03 restricted 8-mer peptides are found to be shared broadly by human and coronaviridae helicases in functional hotspots, with potential implications for nucleic acid unwinding upon initial infection. This study presents the first scan of human peptide mimicry by SARS-CoV-2, and via its benchmarking against human–viral mimicry more broadly, presents a computational framework for follow-up studies to assay how evolutionary tinkering may relate to zoonosis and herd immunity.

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  1. Version published to 10.1038/s41420-020-00321-y
  2. Version published to 10.1101/2020.06.19.161620v2 on bioRxiv
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    SciScore for 10.1101/2020.06.19.161620: (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
    For comparison, we analyzed the protein sequences from 9434 viral species (taxons) from NCBI RefSeq (see Methods).
    RefSeq
    suggested: (RefSeq, RRID:SCR_003496)
    The UniProt database was used to download the 15 protein reference sequences for SARS-CoV.
    UniProt
    suggested: (UniProtKB, RRID:SCR_004426)

    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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

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  4. Version published to 10.1101/2020.06.19.161620v1 on bioRxiv