The ATLAS™ screening assay reveals distinct CD4 + and CD8 + SARS-CoV-2 antigen response profiles which have implications to Omicron cellular immunity

  1. James J. Foti
  2. Kevin Lema
  3. Justin Strickland
  4. Emily Tjon
  5. Adrienne Li
  6. Amalia Rivera
  7. Crystal Cabral
  8. Laura Cormier
  9. Louisa Dowal
  10. Sudhir Rao
  11. Vijetha Vemulapalli
  12. Jessica B. Flechtner

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Abstract

The emergence of SARS-CoV-2 variants are a persistent threat to the efficacy of currently developed prophylactic vaccines and therapeutic antibodies. These variants accumulate mutations in the spike protein which encodes the epitopes necessary for neutralizing antibody binding. Moreover, emerging evidence suggest that robust antibody responses are insufficient to prevent severe disease and long-lasting viral immunity requires T cells. Thus, understanding how the T cell antigen landscape evolves in the context of these emerging variants remains crucial. T cells responses are durable and recognize a wider breadth of epitopes reducing the possibility of immune escape through mutation. Here, we deploy the ATLAS™ assay which identifies CD4 + and CD8 + T cell antigens by utilizing the endogenous HLA class-I and class-II peptide processing pathways. Profiling of T cells from exposed and unexposed donors revealed rich and complex patterns which highlighted the breadth of antigenic potential encoded in SARS-CoV-2. ATLAS revealed several common or frequent antigenic regions as well as an abundance of responses in the unexposed cohort potentially the result of pre-exposure to related coronaviruses. ORF10 was a common CD4 + response in the unexposed cohort while spike was identified as a common and frequent target in both cohorts. Moreover, the spike response profiles allowed us to accurately predict the impact of Omicron spike mutations. This analysis could thus be applied to study the impact of future emerging VOCs.

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  1. ScreenIT

    SciScore for 10.1101/2022.05.17.491668: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    RandomizationClones with confirmed expression of SARS-CoV-2 and positive control polypeptides were randomly re-arrayed in duplicate along with multiple replicates of the NG negative control into 384-well plates.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Recombinant DNA
    SentencesResources
    Design of the SARS-CoV-2 Plasmid Library: To generate a SARS-CoV-2 plasmid library for use in the ATLAS assay (described below and Fig 1), a consensus sequence was derived by aligning 1676 sequences available on NCBI as of May 2020 to the SARS-CoV-2 reference sequence (NC_045512) using the Geneious Prime software (Biomatters).
    SARS-CoV-2
    suggested: RRID:Addgene_164583)

    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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

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

    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.

  2. Version published to 10.1101/2022.05.17.491668v1 on bioRxiv