Distinct evolutionary trajectories of SARS-CoV-2-interacting proteins in bats and primates identify important host determinants of COVID-19

  1. Marie Cariou
  2. Léa Picard
  3. Laurent Guéguen
  4. Stéphanie Jacquet
  5. Andrea Cimarelli
  6. Oliver I. Fregoso
  7. Antoine Molaro
  8. Vincent Navratil
  9. Lucie Etienne

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Abstract

The coronavirus disease 19 (COVID-19) pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a coronavirus that spilled over from the bat reservoir. Despite numerous clinical trials and vaccines, the burden remains immense, and the host determinants of SARS-CoV-2 susceptibility and COVID-19 severity remain largely unknown. Signatures of positive selection detected by comparative functional genetic analyses in primate and bat genomes can uncover important and specific adaptations that occurred at virus–host interfaces. We performed high-throughput evolutionary analyses of 334 SARS-CoV-2-interacting proteins to identify SARS-CoV adaptive loci and uncover functional differences between modern humans, primates, and bats. Using DGINN (Detection of Genetic INNovation), we identified 38 bat and 81 primate proteins with marks of positive selection. Seventeen genes, including the ACE2 receptor, present adaptive marks in both mammalian orders, suggesting common virus–host interfaces and past epidemics of coronaviruses shaping their genomes. Yet, 84 genes presented distinct adaptations in bats and primates. Notably, residues involved in ubiquitination and phosphorylation of the inflammatory RIPK1 have rapidly evolved in bats but not primates, suggesting different inflammation regulation versus humans. Furthermore, we discovered residues with typical virus–host arms race marks in primates, such as in the entry factor TMPRSS2 or the autophagy adaptor FYCO1, pointing to host-specific in vivo interfaces that may be drug targets. Finally, we found that FYCO1 sites under adaptation in primates are those associated with severe COVID-19, supporting their importance in pathogenesis and replication. Overall, we identified adaptations involved in SARS-CoV-2 infection in bats and primates, enlightening modern genetic determinants of virus susceptibility and severity.

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  1. Version published to 10.1073/pnas.2206610119
  2. ScreenIT

    SciScore for 10.1101/2022.04.07.487460: (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
    Initial codon alignments and phylogenetic trees were obtained using DGINN with default parameters (prank -F -codon; version 150803, HKY+G+I model (Löytynoja and Goldman, 2008); PhyML v3.2 (Guindon et al., 2010)).
    PhyML
    suggested: (PhyML, RRID:SCR_014629)
    Recombination events were detected through the use of GARD (Kosakovsky Pond et al., 2006) from the HyPhy suite as implemented in DGINN.
    HyPhy
    suggested: (HyPhy, RRID:SCR_016162)
    Positive selection analyses were then run using models from BUSTED and MEME from the HyPhy suite (Murrell et al., 2012, 2015; Pond et al., 2005) and codon substitution models from PAML codeml (
    PAML
    suggested: (PAML, RRID:SCR_014932)
    To obtain a maximum number of species along primate and bat phylogenies, further sequences were retrieved from NCBI databases using BLASTn.
    NCBI
    suggested: (NCBI, RRID:SCR_006472)
    BLASTn
    suggested: (BLASTN, RRID:SCR_001598)
    Final codon alignments were then made using PRANK (Löytynoja and Goldman, 2008) or Muscle Translate (Edgar, 2004), and phylogenetic trees were built using PhyML with HKY+I+G model and aLRT for branch support (Guindon et al., 2010).
    PRANK
    suggested: (prank, RRID:SCR_017228)
    , M1, M2, M7, M8, M8a) and Bio++ (M0, M1NS, M2NS, M7NS, M8NS, M8aNS) (references in “DGINN screen”).
    Bio++
    suggested: (Bio++, RRID:SCR_016055)
    Interactors of RIPK1 were retrieved using the Reactome FIV plugin in Cytoscape (Gillespie et al., 2022)
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)
    Since no crystal structure is available for TMPRSS2 protease, the 3D structure of TMPRSS2 was predicted using the Iterative-Threading ASSEmbly Refinement (I-TASSER) server (Yang and Zhang, 2015).
    I-TASSER
    suggested: (I-TASSER, RRID:SCR_014627)
    Sequence logo generation: The amino acid sequence logos of TMPRSS2 were generated using WebLogo (V. 2.8.2, (Crooks et al., 2004)), based on an alignment of the positively sites from mammalian species reported as naturally susceptible and/or experimentally permissive to SARS-COV2, SARS-COV and MERS-COV. Code and Data availability: All codes are available in: https://gitbio.ens-lyon.fr/ciri/ps_sars-cov-2/2021_dginn_covid19, and the DGINN pipeline is available at: http://bioweb.me/DGINN-github.
    WebLogo
    suggested: (WEBLOGO, RRID:SCR_010236)

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

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    With the caveats that no functional studies exist on bat RIPK1, the extrapolation of the functions ascribed to the corresponding residues in human RIPK1 suggests that positive selection in bat RIPK1 may result from an advantageous decrease of RIPK1-driven inflammation in bats. This is analogous to the loss of S358 phosphorylation site in bat STING that participates in a dampened inflammation response in bats (Xie et al., 2018), and supports a model where hosts that are more tolerant to viral infection contribute to the establishment of a host reservoir, such as hypothesized for bats (Ahn et al., 2019; De La Cruz-Rivera et al., 2018; Irving; Pavlovich et al., 2018; Prescott et al.; Xie et al., 2018; Zhang et al., 2013). It is also possible that there are fewer signatures of adaptation in SARS-CoV interacting proteins in bats over primates, because coronaviruses may have been less pathogenic in the former host, and therefore less selective (Emerman and Malik, 2010; Irving). However, evidence of strong positive selection in the bat ACE2 receptor driven by ancient pathogenic SARS-CoVs (this study, and (Demogines et al., 2012; Frank et al., 2020)) supports a model in which past SARS-CoV epidemics have been sufficiently potent to shape bat genomes. Our work also tries to bridge studies of ancient and recent evolution of genes, which can help us better understand past epidemics and adaptive genes, and ultimately develop evolutionary medicine. This study over millions of years of evo...

    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.

    Results from scite Reference Check: We found no unreliable references.

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  3. Version published to 10.1101/2022.04.07.487460v1 on bioRxiv