SARS-CoV-2 evolution in animals suggests mechanisms for rapid variant selection

  1. Laura Bashor
  2. Roderick B. Gagne
  3. Angela M. Bosco-Lauth
  4. Richard A. Bowen
  5. Mark Stenglein
  6. Sue VandeWoude

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Abstract

SARS-CoV-2 emerged because of viral spillover from animals to humans, and spillback to other animal species has been observed with accelerating frequency. Cross-species transmission generally results in the rapid adaptation of the virus to the new host, and repeated transmissions may hasten viral evolution and novel strain emergence. We report the surprisingly rapid selection of numerous SARS-CoV-2 variants in cell culture and following infection of nonhuman mammalian hosts, including dogs and cats. These molecular changes in SARS-CoV-2 provide insight into mechanisms of viral host adaptation, lay the groundwork for additional studies assessing dominant variant fitness and phenotype, and highlight the potential for human reinfection with new viral variants arising in species in close and frequent contact with humans.

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  1. Version published to 10.1073/pnas.2105253118
  2. ScreenIT

    SciScore for 10.1101/2021.03.05.434135: (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 culture passage in vitro: SARS-CoV-2 strain USA-WA1/2020 (Genbank MN985325.1) was obtained (15) and passaged in E6 Vero cells a total of three times.
    Vero
    suggested: CLS Cat# 605372/p622_VERO, RRID:CVCL_0059)
    SARS-CoV-2 strain USA-WA1/2020 was expanded in Vero E6 cells, and all four species were inoculated with the same “Passage 3” viral stock.
    Vero E6
    suggested: RRID:CVCL_XD71)
    Software and Algorithms
    SentencesResources
    Briefly, data were trimmed for adapters and low quality using Cutadapt (48), followed by aligning reads to the viral reference sequence.
    Cutadapt
    suggested: (cutadapt, RRID:SCR_011841)
    Data were pre-processed for quality with GATK (49) prior to calling single nucleotide and structural variants with LoFreq (50).
    GATK
    suggested: (GATK, RRID:SCR_001876)
    LoFreq
    suggested: (LoFreq, RRID:SCR_013054)
    SnpEff and SnpSift were used to annotate variants and predict their functional effects (51,52).
    SnpEff
    suggested: (SnpEff, RRID:SCR_005191)
    SnpSift
    suggested: (SnpSift, RRID:SCR_015624)
    All SARS-CoV-2 raw sequence data used in this study will be publicly available upon publication in the NCBI SRA database under BioProject PRJNA704947.
    NCBI SRA
    suggested: None
    BioProject
    suggested: (NCBI BioProject, RRID:SCR_004801)

    Results from OddPub: Thank you for sharing your code and 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.

    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.

  3. Version published to 10.1101/2021.03.05.434135v2 on bioRxiv
  4. Version published to 10.1101/2021.03.05.434135v1 on bioRxiv