In vitro selection of Remdesivir resistance suggests evolutionary predictability of SARS-CoV-2

  1. Agnieszka M. Szemiel
  2. Andres Merits
  3. Richard J. Orton
  4. Oscar A. MacLean
  5. Rute Maria Pinto
  6. Arthur Wickenhagen
  7. Gauthier Lieber
  8. Matthew L. Turnbull
  9. Sainan Wang
  10. Wilhelm Furnon
  11. Nicolas M. Suarez
  12. Daniel Mair
  13. Ana da Silva Filipe
  14. Brian J. Willett
  15. Sam J. Wilson
  16. Arvind H. Patel
  17. Emma C. Thomson
  18. Massimo Palmarini
  19. Alain Kohl
  20. Meredith E. Stewart

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Remdesivir (RDV), a broadly acting nucleoside analogue, is the only FDA approved small molecule antiviral for the treatment of COVID-19 patients. To date, there are no reports identifying SARS-CoV-2 RDV resistance in patients, animal models or in vitro . Here, we selected drug-resistant viral populations by serially passaging SARS-CoV-2 in vitro in the presence of RDV. Using high throughput sequencing, we identified a single mutation in RNA-dependent RNA polymerase (NSP12) at a residue conserved among all coronaviruses in two independently evolved populations displaying decreased RDV sensitivity. Introduction of the NSP12 E802D mutation into our SARS-CoV-2 reverse genetics backbone confirmed its role in decreasing RDV sensitivity in vitro . Substitution of E802 did not affect viral replication or activity of an alternate nucleoside analogue (EIDD2801) but did affect virus fitness in a competition assay. Analysis of the globally circulating SARS-CoV-2 variants (>800,000 sequences) showed no evidence of widespread transmission of RDV-resistant mutants. Surprisingly, we observed an excess of substitutions in spike at corresponding sites identified in the emerging SARS-CoV-2 variants of concern (i.e., H69, E484, N501, H655) indicating that they can arise in vitro in the absence of immune selection. The identification and characterisation of a drug resistant signature within the SARS-CoV-2 genome has implications for clinical management and virus surveillance.

Article activity feed

  1. Version published to 10.1371/journal.ppat.1009929
  2. ScreenIT

    SciScore for 10.1101/2021.02.01.429199: (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

    Software and Algorithms
    SentencesResources
    Consensus sequences and raw FASTQ files have been uploaded to GenBank under BioProject number PRJNA692078 and will be released upon publication.
    BioProject
    suggested: (NCBI BioProject, RRID:SCR_004801)

    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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 10.1101/2021.02.01.429199v2 on bioRxiv
  4. Version published to 10.1101/2021.02.01.429199v1 on bioRxiv