Differential T-Cell Reactivity to Endemic Coronaviruses and SARS-CoV-2 in Community and Health Care Workers

  1. Ricardo da Silva Antunes
  2. Suresh Pallikkuth
  3. Erin Williams
  4. Esther Dawen Yu
  5. Jose Mateus
  6. Lorenzo Quiambao
  7. Eric Wang
  8. Stephen A Rawlings
  9. Daniel Stadlbauer
  10. Kaijun Jiang
  11. Fatima Amanat
  12. David Arnold
  13. David Andrews
  14. Irma Fuego
  15. Jennifer M Dan
  16. Alba Grifoni
  17. Daniela Weiskopf
  18. Florian Krammer
  19. Shane Crotty
  20. Michael E Hoffer
  21. Savita G Pahwa
  22. Alessandro Sette

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Abstract

Herein we measured CD4+ T-cell responses against common cold coronaviruses (CCC) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in high-risk health care workers (HCW) and community controls. We observed higher levels of CCC-reactive T cells in SARS-CoV-2–seronegative HCW compared to community donors, consistent with potential higher occupational exposure of HCW to CCC. We further show that SARS-CoV-2 T-cell reactivity of seronegative HCW was higher than community controls and correlation between CCC and SARS-CoV-2 responses is consistent with cross-reactivity and not associated with recent in vivo activation. Surprisingly, CCC T-cell reactivity was decreased in SARS-CoV-2–infected HCW, suggesting that exposure to SARS-CoV-2 might interfere with CCC responses, either directly or indirectly. This result was unexpected, but consistently detected in independent cohorts derived from Miami and San Diego.

CD4+ T-cell responses against common cold coronaviruses (CCC) are elevated in SARS-CoV-2 seronegative high-risk health care workers (HCW) compared to COVID-19 convalescent HCW, suggesting that exposure to SARS-CoV-2 might interfere with CCC responses and/or cross-reactivity associated with a protective effect.

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  1. Version published to 10.1093/infdis/jiab176
  2. ScreenIT

    SciScore for 10.1101/2021.01.12.21249683: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: Human subjects selection process: Peripheral blood mononuclear cells (PBMC) and serum isolation and handling: For the Miami cohorts, peripheral venous blood was collected in EDTA vacutainer tubes after obtaining written informed consent from the participants.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Using the automatic plate washer, the plates were washed three times with PBS-T and 50 ul anti-human IgG (Fab-specific) horseradish peroxidase antibody (HRP, Sigma,
    anti-human IgG
    suggested: None
    Alternatively, ELISA kits (Epitope Diagnostics, Inc (EDI™, San Diego, CA, USA) were used on the SIP community controls for COVID-19 IgM and IgG antibody detection to the N-antigen.
    IgG
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    To investigate CCC CD4+ T cell responses, we performed prediction of peptides for HLA class II spanning the entire sequence of the 4 main CCC strains (HCoV-229E, HCoV-NL63, HCoV-HKU1 and HCoV-OC43).
    HCoV-NL63
    suggested: RRID:CVCL_RW88)
    Software and Algorithms
    SentencesResources
    The results were recorded in Microsoft Excel and the endpoint titers calculated using GraphPad Prism 8.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    All samples were acquired on a ZE5 Cell analyzer (Bio-rad laboratories), and analyzed with FlowJo software (Tree Star, San Carlos, CA).
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)

    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:
    Limitations of the present study: All recruited SARS-CoV-2 infected donors were associated with mild or asymptomatic disease, and therefore does not address another important aspect of research on CCC and SARS-CoV-2 interactions, namely whether levels of preexisting cross-reactive CCC T cell responses might influence disease severity (28, 30). Larger sample sizes will be required to analyze this issue in this type of cross-sectional design, but it is likely that a prospective longitudinal design might be necessary to firmly address this point based on evaluation of CCC reactivity in pre-infection samples, and its correlation with disease severity post SARS-CoV-2 infection. Additional limitations of this study are the relative small size of the cohorts investigated, and the unknown history of previous CCC exposure. Therefore, the results may not be necessarily generalizable to other situations with different patterns of prior exposure.

    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: Please consider improving the rainbow (“jet”) colormap(s) used on pages 38, 41, 44 and 30. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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 10.1101/2021.01.12.21249683v1 on medRxiv