Interferon resistance of emerging SARS-CoV-2 variants

  1. Kejun Guo
  2. Bradley S. Barrett
  3. James H. Morrison
  4. Kaylee L. Mickens
  5. Eszter K. Vladar
  6. Kim J. Hasenkrug
  7. Eric M. Poeschla
  8. Mario L. Santiago

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Abstract

The emergence of SARS-CoV-2 variants with enhanced transmissibility, pathogenesis, and resistance to vaccines presents urgent challenges for curbing the COVID-19 pandemic. While Spike mutations that enhance virus infectivity or neutralizing antibody evasion may drive the emergence of these novel variants, studies documenting a critical role for interferon responses in the early control of SARS-CoV-2 infection, combined with the presence of viral genes that limit these responses, suggest that interferons may also influence SARS-CoV-2 evolution. Here, we compared the potency of 17 different human interferons against multiple viral lineages sampled during the course of the global outbreak, including ancestral and five major variants of concern that include the B.1.1.7 (alpha), B.1.351 (beta), P.1 (gamma), B.1.617.2 (delta), and B.1.1.529 (omicron) lineages. Our data reveal that relative to ancestral isolates, SARS-CoV-2 variants of concern exhibited increased interferon resistance, suggesting that evasion of innate immunity may be a significant, ongoing driving force for SARS-CoV-2 evolution. These findings have implications for the increased transmissibility and/or lethality of emerging variants and highlight the interferon subtypes that may be most successful in the treatment of early infections.

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  1. Version published to 10.1073/pnas.2203760119
  2. Version published to 10.1101/2021.03.20.436257v2 on bioRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.03.20.436257: (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.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Cell lines: A549 cells were obtained from the American Type Culture Collection (ATCC) and cultured in complete media containing F-12 Ham’s media (Corning), 10% fetal bovine serum (Atlanta Biologicals), 1% penicillin/streptomycin/glutamine (Corning) and maintained at 37°C 5% CO2.
    A549
    suggested: None
    To generate the A549-ACE2 stable cell line, 107 HEK293T (ATCC) cells in T-175 flasks were transiently co-transfected with 60 μg mixture of pBABE-puro-ACE2, pUMVC, and pCMV-VSV-G at a 10:9:1 ratio using a calcium phosphate method42.
    HEK293T
    suggested: None
    The contents of the entire vial (~0.5 ml) were inoculated into 3 T-75 flasks containing 3×106 A549-ACE2 cells, except for B.1.1.7 which was inoculated into 1 T-75 flask.
    A549-ACE2
    suggested: None
    Software and Algorithms
    SentencesResources
    Statistical analyses: Data were analyzed using GraphPad Prism 8.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2021.03.20.436257v1 on bioRxiv