An autoantigen-ome from HS-Sultan B-Lymphoblasts offers a molecular map for investigating autoimmune sequelae of COVID-19

  1. Julia Y. Wang
  2. Wei Zhang
  3. Victor B. Roehrl
  4. Michael W. Roehrl
  5. Michael H. Roehrl

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Abstract

To understand how COVID-19 may induce autoimmune diseases, we have been compiling an atlas of COVID autoantigens (autoAgs). Using dermatan sulfate (DS) affinity enrichment of autoantigenic proteins extracted from HS-Sultan lymphoblasts, we identified 362 DS-affinity proteins, of which at least 201 (56%) are confirmed autoAgs. Comparison with available multi-omic COVID data shows that 315 (87%) of the 362 proteins are affected in SARS-CoV-2 infection via altered expression, interaction with viral components, or modification by phosphorylation or ubiquitination, at least 186 (59%) of which are known autoAgs. These proteins are associated with gene expression, mRNA processing, mRNA splicing, translation, protein folding, vesicles, and chromosome organization. Numerous nuclear autoAgs were identified, including both classical antinuclear antibodies (ANAs) and extractable nuclear antigens (ENAs) of systemic autoimmune diseases and unique autoAgs involved in the DNA replication fork, mitotic cell cycle, or telomerase maintenance. We also identified many uncommon autoAgs involved in nucleic acid and peptide biosynthesis and nucleocytoplasmic transport, such as aminoacyl-tRNA synthetases. In addition, this study found autoAgs that potentially interact with multiple SARS-CoV-2 Nsp and Orf components, including CCT/TriC chaperonin, insulin degrading enzyme, platelet-activating factor acetylhydrolase, and the ezrin-moesin-radixin family. Furthermore, B-cell-specific IgM-associated endoplasmic reticulum (ER) complex (including MBZ1, BiP, heat shock proteins, and protein disulfide-isomerases) is enriched by DS-affinity and up-regulated in B-cells of COVID-19 patients, and a similar IgH-associated ER complex was also identified in autoreactive pre-B1 cells in our previous study, which suggests a role of autoreactive B1 cells in COVID-19 that merits further investigation. In summary, this study demonstrates that virally infected cells are characterized by alterations of proteins with propensity to become autoAgs, thereby providing a possible explanation for infection-induced autoimmunity. The COVID autoantigen-ome provides a valuable molecular resource and map for investigation of COVID-related autoimmune sequelae and considerations for vaccine design.

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  1. Version published to 10.1071/ch22267
  2. ScreenIT

    SciScore for 10.1101/2021.04.05.438500: (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
    Protein network analysis: Protein-protein interactions were analyzed by STRING [49].
    STRING
    suggested: (STRING, RRID:SCR_005223)
    Pathways and processes enrichment were analyzed with Metascape [17], which utilize various ontology sources such as KEGG Pathway, GO Biological Process, Reactome Gene Sets,
    Metascape
    suggested: (Metascape, RRID:SCR_016620)
    KEGG
    suggested: (KEGG, RRID:SCR_012773)
    GO Biological
    suggested: None
    Autoantigen literature text mining: Every DS-affinity protein identified in this study was searched for specific autoantibodies reported in the PubMed literature.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Search keywords included the MeSH keyword “autoantibodies”, the protein name or its gene symbol, or alternative names and symbols.
    MeSH
    suggested: (MeSH, RRID:SCR_004750)

    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 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.

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  3. Version published to 10.1101/2021.04.05.438500v1 on bioRxiv