A Highly Specific Assay for the Detection of SARS-CoV-2–Reactive CD4+ and CD8+ T Cells in COVID-19 Patients

  1. Henning Zelba
  2. David Worbs
  3. Johannes Harter
  4. Natalia Pieper
  5. Christina Kyzirakos-Feger
  6. Simone Kayser
  7. Marcel Seibold
  8. Oliver Bartsch
  9. Jiri Ködding
  10. Saskia Biskup

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Abstract

Gaining detailed insights into the role of host immune responses in viral clearance is critical for understanding COVID-19 pathogenesis and future treatment strategies. Although studies analyzing humoral immune responses against SARS-CoV-2 were available rather early during the pandemic, cellular immunity came into focus of investigations just recently. For the present work, we have adapted a protocol designed for the detection of rare neoantigen-specific memory T cells in cancer patients for studying cellular immune responses against SARS-CoV-2. Both CD4+ and CD8+ T cells were detected after 6 d of in vitro expansion using overlapping peptide libraries representing the whole viral protein. The assay readout was an intracellular cytokine staining and flow cytometric analysis detecting four functional markers simultaneously (CD154, TNF, IL-2, and IFN-γ). We were able to detect SARS-CoV-2–specific T cells in 10 of 10 COVID-19 patients with mild symptoms. All patients had reactive T cells against at least 1 of 12 analyzed viral Ags, and all patients had Spike-specific T cells. Although some Ags were detected by CD4+ and CD8+ T cells, VME1 was mainly recognized by CD4+ T cells. Strikingly, we were not able to detect SARS-CoV-2–specific T cells in 18 unexposed healthy individuals. When we stimulated the same samples overnight, we measured significant numbers of cytokine-producing cells even in unexposed individuals. Our comparison showed that the stimulation conditions can profoundly impact the activation readout in unexposed individuals. We are presenting a highly specific diagnostic tool for the detection of SARS-CoV-2–reactive T cells.

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  1. Version published to 10.4049/jimmunol.2000811
  2. ScreenIT

    SciScore for 10.1101/2020.08.10.20150060: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: All participants provided written informed consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    All patients showed Spike (S1 domain) specific IgG antibodies using ELISA.
    S1 domain) specific IgG
    suggested: None
    After cultivation, cells were washed twice followed by extracellular staining with fluorochrome- conjugated antibodies titrated to their optimal concentrations: CD3-BV785 (clone UCHT1; BioLegend), CD4-FITC (clone RPA-T4; BioLegend), CD8-APC/Cyanine (clone SK1; BioLegend), Zombi Aqua Dye (BioLegend).
    CD4-FITC
    suggested: None
    CD8-APC/Cyanine
    suggested: None
    After extracellular staining, cells were fixed and permeabilized (BD biosciences), followed by an intracellular staining with the following antibodies: IFN-BV421 (clone 4S.B3; BioLegend), TNF-AlexaFluor700 (clone MAb11; BioLegend), IL-2-PE/Cy7 (clone MQ1- 17H12; BioLegend) and CD154 - BV711 (clone 24-31; BioLegend).
    CD154
    suggested: (BioLegend Cat# 310837, RRID:AB_2563844)
    BV711
    suggested: (BioLegend Cat# 310837, RRID:AB_2563844)
    Software and Algorithms
    SentencesResources
    Statistics: Data were analyzed using FlowJo version 10.5.3 (FlowJo LLC).
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Frequencies of IFN-γ+ T cells within COVID-19 patients and unexposed individuals was compared with unpaired Mann-Whitney test using Prism 8.4.2 (Graphpad Software).
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    Graphpad
    suggested: (GraphPad, RRID:SCR_000306)

    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: Please consider improving the rainbow (“jet”) colormap(s) used on page 15. 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 10.1101/2020.08.10.20150060 on medRxiv