Global Genomic Analysis of SARS-CoV-2 RNA Dependent RNA Polymerase Evolution and Antiviral Drug Resistance

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

A variety of antiviral treatments for COVID-19 have been investigated, involving many repurposed drugs. Currently, the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp, encoded by nsp12-nsp7-nsp8) has been targeted by numerous inhibitors, e.g., remdesivir, the only provisionally approved treatment to-date, although the clinical impact of these interventions remains inconclusive. However, the potential emergence of antiviral resistance poses a threat to the efficacy of any successful therapies on a wide scale. Here, we propose a framework to monitor the emergence of antiviral resistance, and as a proof of concept, we address the interaction between RdRp and remdesivir. We show that SARS-CoV-2 RdRp is under purifying selection, that potential escape mutations are rare in circulating lineages, and that those mutations, where present, do not destabilise RdRp. In more than 56,000 viral genomes from 105 countries from the first pandemic wave, we found negative selective pressure affecting nsp12 (Tajima’s D = −2.62), with potential antiviral escape mutations in only 0.3% of sequenced genomes. Potential escape mutations included known key residues, such as Nsp12:Val473 and Nsp12:Arg555. Of the potential escape mutations involved globally, in silico structural models found that they were unlikely to be associated with loss of stability in RdRp. No potential escape mutation was found in a local cohort of remdesivir treated patients. Collectively, these findings indicate that RdRp is a suitable drug target, and that remdesivir does not seem to exert high selective pressure. We anticipate our framework to be the starting point of a larger effort for a global monitoring of drug resistance throughout the COVID-19 pandemic.

Article activity feed

  1. SciScore for 10.1101/2020.12.28.20248663: (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
    Whole-genome consensus sequences were aligned against NCBI Refseq sequence Wuhan-Hu-1 NC_045512.2 using MAFFT v7.467 (method FFT-NS-fragment; options --reorder --keeplength --mapout -- kimura 1 -- addfragments --auto)34.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    To infer the selection pressure that is acting on the entire nsp12 gene region, we calculated Tajimas’s D statistic35,36 using MEGA version 737 to test for neutral selection for the entire coding sequence.
    MEGA
    suggested: (Mega BLAST, RRID:SCR_011920)
    Data mining and structuring was performed through the R packages: tidyr v1.1.2, dplyr v1.0.2, reshape2 v1.4.443, BiocGenerics v0.32.044, IRanges v2.20.245, Biostrings v2.54.0, XVector v0.26.0, S4Vectors v0.24.4, shapefiles v0.7, foreign v0.8-76.
    tidyr
    suggested: (tidyr, RRID:SCR_017102)
    BiocGenerics
    suggested: None
    IRanges
    suggested: (IRanges, RRID:SCR_006420)
    Biostrings
    suggested: (Biostrings, RRID:SCR_016949)
    Plots were drafted using R packages: ggpubr v0.4.0, ggExtra v0.9, cowplot v1.1.0, lubridate v1.7.946, rgeos v0.5-5, rnaturalearth v0.1.0, rnaturalearthdata v0.1.0, sf v0.9-5, sp v1.4-2, maps v3.3.0, ggspatial v1.1.4, ggplot2 v3.3.247.
    ggExtra
    suggested: None
    cowplot
    suggested: (cowplot, RRID:SCR_018081)
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    To distinguish genuine stability predictions from noise, we filtered the results based on the reported standard deviations of FoldX energy calculations as described in Buss et al53.
    FoldX
    suggested: (FoldX, RRID:SCR_008522)

    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: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04323761Approved for marketingExpanded Access Treatment Protocol: Remdesivir (RDV; GS-5734…
    NCT04351503RecruitingA Systems Approach to Predict the Outcome of SARS-CoV-2 in t…
    NCT04351503RecruitingA Systems Approach to Predict the Outcome of SARS-CoV-2 in t…


    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.