Evolutionary Arms Race between Virus and Host Drives Genetic Diversity in Bat Severe Acute Respiratory Syndrome-Related Coronavirus Spike Genes

  1. Hua Guo
  2. Bing-Jie Hu
  3. Xing-Lou Yang
  4. Lei-Ping Zeng
  5. Bei Li
  6. Songying Ouyang
  7. Zheng-Li Shi

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Abstract

Evolutionary arms race dynamics shape the diversity of viruses and their receptors. Identification of key residues which are involved in interspecies transmission is important to predict potential pathogen spillover from wildlife to humans. Previously, we have identified genetically diverse SARSr-CoVs in Chinese horseshoe bats. Here, we show the highly polymorphic ACE2 in Chinese horseshoe bat populations. These ACE2 variants support SARS-CoV and SARSr-CoV infection but with different binding affinities to different spike proteins. The higher binding affinity of SARSr-CoV spike to human ACE2 suggests that these viruses have the capacity for spillover to humans. The positive selection of residues at the interface between ACE2 and SARSr-CoV spike protein suggests long-term and ongoing coevolutionary dynamics between them. Continued surveillance of this group of viruses in bats is necessary for the prevention of the next SARS-like disease.

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  1. Version published to 10.1128/jvi.00902-20
  2. ScreenIT

    SciScore for 10.1101/2020.05.13.093658: (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

    Antibodies
    SentencesResources
    ACE2 expression was detected using mouse anti-S-tag monoclonal antibody (Kyab Biotech Co. Ltd., Wuhan, China), followed by FITC-labelled goat anti-mouse IgG H&L (Abcam, Cambridge Biomedical Campus, Cambridge, UK).
    anti-S-tag
    suggested: None
    anti-mouse IgG
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Vero E6, HeLa, and HEK 293T/17 cells (ATCC) were maintained in Dulbecco’s modified Eagle medium (DMEM) supplemented with 10% fetal bovine serum (FBS).
    HEK 293T/17
    suggested: ATCC Cat# CRL-11268, RRID:CVCL_1926)
    Titers of all viruses used in this study were determined by plaque assays on Vero E6 cells, as previously described (17).
    Vero E6
    suggested: RRID:CVCL_XD71)
    HeLa cells were transfected with the same amount of human or R.
    HeLa
    suggested: CLS Cat# 300194/p772_HeLa, RRID:CVCL_0030)
    Software and Algorithms
    SentencesResources
    Phylogenetic trees were built by the maximum likelihood method implemented in RAxML program in CIPRES Science Gateway (https://www.phylo.org/).
    RAxML
    suggested: (RAxML, RRID:SCR_006086)

    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 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 10.1101/2020.05.13.093658v1 on bioRxiv