Missense variants in ACE2 are predicted to encourage and inhibit interaction with SARS-CoV-2 Spike and contribute to genetic risk in COVID-19

  1. Stuart A. MacGowan
  2. Geoffrey J. Barton

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Abstract

SARS-CoV-2 invades host cells via an endocytic pathway that begins with the interaction of the SARS-CoV-2 Spike glycoprotein (S-protein) and human Angiotensin-converting enzyme 2 (ACE2). Genetic variability in ACE2 may be one factor that mediates the broad-spectrum severity of SARS-CoV-2 infection and COVID-19 outcomes. We investigated the capacity of ACE2 variation to influence SARS-CoV-2 infection with a focus on predicting the effect of missense variants on the ACE2 SARS-CoV-2 S-protein interaction. We validated the mCSM-PPI2 variant effect prediction algorithm with 26 published ACE2 mutant SARS-CoV S-protein binding assays and found it performed well in this closely related system (True Positive Rate = 0.7, True Negative Rate = 1). Application of mCSM-PPI2 to ACE2 missense variants from the Genome Aggregation Consortium Database (gnomAD) identified three that are predicted to strongly inhibit or abolish the S-protein ACE2 interaction altogether (p.Glu37Lys, p.Gly352Val and p.Asp355Asn) and one that is predicted to promote the interaction (p.Gly326Glu). The S-protein ACE2 inhibitory variants are expected to confer a high degree of resistance to SARS-CoV-2 infection whilst the S-protein ACE2 affinity enhancing variant may lead to additional susceptibility and severity. We also performed in silico saturation mutagenesis of the S-protein ACE2 interface and identified a further 38 potential missense mutations that could strongly inhibit binding and one more that is likely to enhance binding (Thr27Arg). A conservative estimate places the prevalence of the strongly protective variants between 12-70 per 100,000 population but there is the possibility of higher prevalence in local populations or those underrepresented in gnomAD. The probable interplay between these ACE2 affinity variants and ACE2 expression polymorphisms is highlighted as well as gender differences in penetrance arising from ACE2’s situation on the X-chromosome. It is also described how our data can help power future genetic association studies of COVID-19 phenotypes and how the saturation mutant predictions can help design a mutant ACE2 with tailored S-protein affinity, which may be an improvement over a current recombinant ACE2 that is undergoing clinical trial.

Key results

  • 1 ACE2 gnomAD missense variant (p.Gly326Glu) and one unobserved missense mutation (Thr27Arg) are predicted to enhance ACE2 binding with SARS-CoV-2 Spike protein, which could result in increased susceptibility and severity of COVID-19

  • 3 ACE2 missense variants in gnomAD plus another 38 unobserved missense mutations are predicted to inhibit Spike binding, these are expected to confer a high degree of resistance to infection

  • The prevalence of the strongly protective variants is estimated between 12-70 per 100,000 population but higher prevalence may exist in local populations or those underrepresented in gnomAD

  • A strategy to design a recombinant ACE2 with tailored affinity towards Spike and its potential therapeutic value is presented

  • The predictions were extensively validated against published ACE2 mutant binding assays for SARS-CoV Spike protein

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  1. ScreenIT

    SciScore for 10.1101/2020.05.03.074781: (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

    Antibodies
    SentencesResources
    Although values greater than 100% were observed in the experimental binding assay (and are valid)10, the assay is bounded above by an unknown quantity that in our estimation should correspond to the inverse of the ratio of immunoprecipitated ACE2 by the C-terminal tag antibody to the total amount of ACE2 in the sample.
    C-terminal tag
    suggested: None
    Software and Algorithms
    SentencesResources
    The average overlap per residue was pulled into Jalview as features from Chimera with the Fetch Chimera attributes function.
    Jalview
    suggested: (Jalview, RRID:SCR_006459)
    Quantitative results were extracted from figures in Li et al.10 with WebPlotDigitizer 4.240.
    WebPlotDigitizer
    suggested: (WebPlotDigitizer, RRID:SCR_013996)
    We transcribed data for additional mutants from Li et al.10 that were not reported in UniProt.
    UniProt
    suggested: (UniProtKB, RRID:SCR_004426)
    The wild-type and mutant models were downloaded from the server as PyMol sessions and detailed structural comparisons were conducted with PyMol20.
    PyMol
    suggested: (PyMOL, RRID:SCR_000305)
    Enumerating possible ACE2 missense SNPs: The ACE2 gene (ENSG00000130234) was retrieved from Ensembl in Jalview14.
    Ensembl
    suggested: (Ensembl, RRID:SCR_002344)
    Biopython was used to process sequence data.
    Biopython
    suggested: (Biopython, RRID:SCR_007173)
    Data analyses were coded in Python in Jupyter Notebooks.
    Python
    suggested: (IPython, RRID:SCR_001658)
    Numpy, Pandas and Scipy were used for data analysis.
    Numpy
    suggested: (NumPy, RRID:SCR_008633)
    Scipy
    suggested: (SciPy, RRID:SCR_008058)
    Matplotlib and Seaborn were used to plot data.
    Matplotlib
    suggested: (MatPlotLib, RRID:SCR_008624)

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

    IdentifierStatusTitle
    NCT04287686WithdrawnRecombinant Human Angiotensin-converting Enzyme 2 (rhACE2) a…

    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.
    • Thank you for including a protocol registration statement.

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  2. Version published to 10.1101/2020.05.03.074781 on bioRxiv