Human phospho-signaling networks of SARS-CoV-2 infection are rewired by population genetic variants

  1. Diogo Pellegrina
  2. Alexander T. Bahcheli
  3. Michal Krassowski
  4. Jüri Reimand

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Abstract

SARS-CoV-2 infection hijacks signaling pathways and induces protein-protein interactions between human and viral proteins. Human genetic variation may impact SARS-CoV-2 infection and COVID-19 pathology; however, the role of genetic variation in these signaling networks remains uncharacterized. We studied human single nucleotide variants (SNVs) affecting phosphorylation sites modulated by SARS-CoV-2 infection, using machine learning to identify amino acid changes altering kinase-bound sequence motifs. We found 2033 infrequent phosphorylation-associated SNVs (pSNVs) that are enriched in sequence motif alterations, potentially reflecting the evolution of signaling networks regulating host defenses. Proteins with pSNVs are involved in viral life cycle processes and host responses, including regulators of RNA splicing and interferon response, as well as glucose homeostasis pathways with potential associations with COVID-19 co-morbidities. Certain pSNVs disrupt CDK and MAPK substrate motifs and replace these with motifs recognized by Tank Binding Kinase 1 (TBK1) involved in innate immune responses, indicating consistent rewiring of infection signaling networks. Our analysis highlights potential genetic factors contributing to the variation of SARS-CoV-2 infection and COVID-19 and suggests leads for mechanistic and translational studies.

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  1. ScreenIT

    SciScore for 10.1101/2021.11.22.21266712: (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

    Recombinant DNA
    SentencesResources
    In the cases where multiple adjacent phosphosites were found to match a pSNV, the highest-impact phosphosite was used.
    pSNV
    suggested: None
    Software and Algorithms
    SentencesResources
    ELM 61, HPRD 62).
    HPRD
    suggested: None
    The ANNOVAR software 63 was used to annotate the SNVs in protein-coding genes.
    ANNOVAR
    suggested: (ANNOVAR, RRID:SCR_012821)
    Gene sets were retrieved from the g:Profiler web server 67 (Mar 25th, 2021).
    g:Profiler
    suggested: (G:Profiler, RRID:SCR_006809)
    Human-human and human-virus PPIs were retrieved from the BioGRID database 43 (V 4.4.199, downloaded on June 29th, 2021).
    BioGRID
    suggested: (BioGrid Australia, RRID:SCR_006334)
    The PPI network was visualized using the Cytoscape software 69.
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)
    Disease annotations of pSNVs were then reviewed manually using the ClinVar website (data retrieved on Oct 6th, 2021).
    ClinVar
    suggested: (ClinVar, RRID:SCR_006169)

    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: We detected the following sentences addressing limitations in the study:
    Our study has important limitations. We currently have no statistical or clinical evidence of pSNVs associating with SARS-CoV-2 infection, COVID-19 risk or comorbidities, as most pSNVs are infrequent in human populations and remain unmapped in genome-wide association studies. The phosphosites we studied reflect an early post-infection timepoint in cell culture, limiting our analysis of signaling pathways activated further downstream of SARS-CoV-2 infection in human tissues and the immune system. On the one hand, our analysis may overestimate the extent of network rewiring because our sequence-based pSNV impact analysis does not account for co-expression and localization of kinases and substrates. On the other hand, the number of motif-rewiring pSNVs may be underestimated, because many motifs bound by kinases and other phospho-enzymes remain unknown. The known landscape of functional protein-coding SNVs may be extended by analyzing other types of PTMs. Our integrative proteogenomic analysis of pSNVs affecting signaling networks of SARS-CoV-2 enables further studies of viral infection, disease mechanisms and potential translation. Analysis of whole-genome sequencing datasets with matched clinical profiles of COVID-19 information is needed to associate our functional predictions of infrequent pSNVs with patient risk and co-morbidities, and to enable the development of prognostic and predictive biomarkers. The candidate genes, pathways, and kinases identified in this study enable...

    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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  2. Version published to 10.1101/2021.11.22.21266712v1 on medRxiv