SARS-CoV-2 reactive T cells in uninfected individuals are likely expanded by beta-coronaviruses

  1. Ulrik Stervbo
  2. Sven Rahmann
  3. Toralf Roch
  4. Timm H. Westhof
  5. Nina Babel

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Abstract

The current pandemic is caused by the SARS-CoV-2 virus and large progress in understanding the pathology of the virus has been made since its emergence in late 2019. Several reports indicate short lasting immunity against endemic coronaviruses, which contrasts repeated reports that biobanked venous blood contains SARS-CoV-2 reactive T cells even before the outbreak in Wuhan. This suggests there exists a preformed T cell memory in individuals not exposed to the pandemic virus. Given the similarity of SARS-CoV-2 to other members of the Coronaviridae family, the endemic coronaviruses appear likely candidates to generate this T cell memory. However, given the apparent poor immunological memory created by the endemic coronaviruses, other immunity against other common pathogens might offer an alternative explanation. Here, we utilize a combination of epitope prediction and similarity to common human pathogens to identify potential sources of the SARS-CoV-2 T cell memory. We find that no common human virus, other than beta-coronaviruses, can explain the pre-existing SARS-CoV-2 reactive T cells in uninfected individuals. Our study suggests OC43 and HKU1 are the most likely pathogens giving rise to SARS-CoV-2 preformed immunity.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.01.182741: (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
    The SARS-CoV2 protein sequences were downloaded from ViralZone (33; https://viralzone.expasy.org/89966), accessed May
    ViralZone
    suggested: (ViralZone, RRID:SCR_006563)
    The extraction was per pathogen name, as stored in the Taxonomy database.
    Taxonomy
    suggested: (Taxonomy, RRID:SCR_004299)
    (35; http://www.allelefrequencies.net, June 1, 2020).
    http://www.allelefrequencies.net
    suggested: (Allele Frequencies in Worldwide Populations, RRID:SCR_007259)

    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:
    One limitation to the study is that we do not consider the frequency of pathogens nor the potential expression level of the proteins and accessibility for the immune system. Both arguably have an effect on the likelihood that an epitope can raise a robust immune response. However, both variables can only be assessed with great uncertainty. Another limitation to the study is the reliance on sequence similarity; although related epitopes are likely to interact with the same T cell receptor, this is not guaranteed (32). The finding that the beta-coronaviruses OC43 and HKU1 are the most likely pathogens to give rise to SARS-CoV-2 preformed immunity means that the endemic coronaviruses must be able to generally raise a long lasting T cells response. Otherwise the epitopes recognized by the cross reactive T cells share no high degree of similarity. In conclusion, we conjecture that other beta-coronaviruses are the source for SARS-CoV-2 cross reactive T cells.

    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.

    About SciScore

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  2. Version published to 10.1101/2020.07.01.182741v1 on bioRxiv