SARS-CoV-2-reactive T cells in healthy donors and patients with COVID-19
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Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the rapidly unfolding coronavirus disease 2019 (COVID-19) pandemic 1,2. Clinical manifestations of COVID-19 vary, ranging from asymptomatic infection to respiratory failure. The mechanisms that determine such variable outcomes remain unresolved. Here we investigated CD4+ T cells that are reactive against the spike glycoprotein of SARS-CoV-2 in the peripheral blood of patients with COVID-19 and SARS-CoV-2-unexposed healthy donors. We detected spike-reactive CD4+ T cells not only in 83% of patients with COVID-19 but also in 35% of healthy donors. Spike-reactive CD4+ T cells in healthy donors were primarily active against C-terminal epitopes in the spike protein, which show a higher homology to spike glycoproteins of human endemic coronaviruses, compared with N-terminal epitopes. Spike-protein-reactive T cell lines generated from SARS-CoV-2-naive healthy donors responded similarly to the C-terminal region of the spike proteins of the human endemic coronaviruses 229E and OC43, as well as that of SARS-CoV-2. This results indicate that spike-protein cross-reactive T cells are present, which were probably generated during previous encounters with endemic coronaviruses. The effect of pre-existing SARS-CoV-2 cross-reactive T cells on clinical outcomes remains to be determined in larger cohorts. However, the presence of spike-protein cross-reactive T cells in a considerable fraction of the general population may affect the dynamics of the current pandemic, and has important implications for the design and analysis of upcoming trials investigating COVID-19 vaccines.
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This cross-reactivity largely originates from previous exposure to circulating common cold coronaviruses.
“This cross-reactivity largely originates from previous exposure to circulating common cold coronaviruses [110-116].”
From Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition) (2021) · cites this paper as [114]
The Discussion says pre-existing spike-reactive CD4+ T cells in SARS-CoV-2-unexposed healthy donors were probably acquired through earlier infections with endemic common-cold coronaviruses. The cross-reactivity section (p. 273) reports responses to endemic coronavirus peptides but describes the proposed origin as a suggestion. It does not establish that this is the origin of cross-reactivity generally, or quantify it as 'largely' responsible. (LLM, conf=0.86)
Experimental — accuracy not yet measuredLymphocytes from 20% to 50% of unexposed donors display significant reactivity to SARS-CoV-2 Ag peptide pools.
“lymphocytes from 20% to 50% of unexposed donors display significant reactivity to SARS-CoV-2 Ag peptide pools (Figure 6).”
From Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition) (2021) · cites this paper as [114]
T cell responses against SARS-CoV-2 are highly multi-antigenic and multi-specific, with tens of different epitopes recognized by CD4+ and CD8+ T cells in a given individual.
“the T cell responses against SARS-CoV-2 are highly multi-antigenic and multi-specific, with tens of different epitopes recognized by CD4+ and CD8+ T cells in a given individual.”
From Impact of SARS-CoV-2 variants on the total CD4+ and CD8+ T cell reactivity in infected or vaccinated individuals (2021) · cites this paper as [52]
The dominant cytokine produced by SARS-CoV-2-specific CD4+ T cells from COVID-19 patients is IFNγ, with a Th1 signature including TNF and IL-2.
“The dominant cytokine produced by SARS-CoV-2-specific CD4+ T cells from COVID-19 patients is IFNγ (Braun et al., 2020; Grifoni et al., 2020; Rydyznski Moderbacher et al., 2020; Weiskopf et al., 2020), with a clear IFNγ, tumor necrosis factor (TNF), IL-2 protein signature of canonical Th1 cells (Braun et al., 2020; Rydyznski Moderbacher et al., 2020; Peng et al., 2020; Sekine et al., 2020).”
From Adaptive immunity to SARS-CoV-2 and COVID-19 (2021) · cites this paper as Braun et al., 2020
An extended absence of SARS-CoV-2-specific CD4+ T cells is associated with severe or fatal COVID-19.
“In contrast, the strikingly extended absence of SARS-CoV-2-specific CD4+ T cells was associated with severe or fatal COVID-19 (>day 22 PSO in some cases) (Braun et al., 2020; Rydyznski Moderbacher et al., 2020; Tan et al., 2020a).”
From Adaptive immunity to SARS-CoV-2 and COVID-19 (2021) · cites this paper as Braun et al., 2020
Substantial cross-reactive T cell memory has been reported, measurable in approximately 28%-50% of people depending on the study.
“In contrast, substantial cross-reactive T cell memory has been reported, measurable in ∼28%–50% of people, depending on the study (Le Bert et al., 2020; Braun et al., 2020; Grifoni et al., 2020).”
From Adaptive immunity to SARS-CoV-2 and COVID-19 (2021) · cites this paper as Braun et al., 2020
SARS-CoV-2 infection elicits a Th1 CD4+ T cell response, with IFNγ and IL-2 as the main cytokines produced and some TNFα as well.
“SARS-CoV-2 infection elicits a Th1 CD4+ T cell response, with IFNγ and IL-2 being the primary cytokines produced by these cells and some TNFα production as well112,126-129.”
From SARS-CoV-2, COVID-19 and the aging immune system (2021) · cites this paper as [128]
Compared with mild COVID-19, severe COVID-19 patients generate a weaker T cell response to the N-terminal portion of the SARS-CoV-2 S protein, including the receptor-binding domain.
“Specifically, when compared to those with mild COVID-19, patients with severe disease generated a weaker T cell response to the N-terminal portion of the SARS-CoV-2 S protein, a region that includes the critical receptor-binding domain (RBD)128.”
From SARS-CoV-2, COVID-19 and the aging immune system (2021) · cites this paper as [128]
Many individuals have existing memory T cells generated from endemic human coronavirus infections that can cross-react with SARS-CoV-2 epitopes.
“Therefore, many individuals have existing memory T cells that were generated from endemic human coronavirus infections and can cross-react with SARS-CoV-2 epitopes, known as SARS-CoV-2 cross-reactive memory T cells128.”
From SARS-CoV-2, COVID-19 and the aging immune system (2021) · cites this paper as [128]
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- Authors
- Braun, J., Loyal, L., Frentsch, M., Wendisch, D., Georg, P., Kurth, F., Hippenstiel, S., Dingeldey, M., Kruse, B., Fauchere, F., Baysal, E., Mangold, M., Henze, L., Lauster, R., Mall, M. A., Beyer, K., Röhmel, J., Voigt, S., Schmitz, J., Miltenyi, S., Demuth, I., Müller, M. A., Hocke, A., Witzenrath, M., Suttorp, N., Kern, F., Reimer, U., Wenschuh, H., Drosten, C., Corman, V. M., Giesecke-Thiel, C., Sander, L. E., & Thiel, A.
- Affiliations
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE)
- Charité – Universitätsmedizin Berlin (DE)
- University Medical Center Hamburg-Eppendorf (DE)
- Technische Universität Berlin (DE)
- Robert Koch Institute (DE)
- Miltenyi Biotec (Germany) (DE)
- Brighton and Sussex Medical School (GB)
- JPT Peptide Technologies (Germany) (DE)
- Corresponding author
- Sander, Leif Erik
- Thiel, Andreas
- ORCID
- Braun, Julian
- Loyal, Lucie
- Frentsch, Marco
- Wendisch, Daniel
- Georg, Philipp
- Kurth, Florian
- Hippenstiel, Stefan
- Dingeldey, Manuela
- Fauchere, Florent
- Baysal, Emre
- Mangold, Maike
- Henze, Larissa
- Mall, Marcus A.
- Beyer, Kirsten
- Voigt, Sebastian
- Demuth, Ilja
- Müller, Marcel A.
- Hocke, Andreas
- Witzenrath, Martin
- Suttorp, Norbert
- Kern, Florian
- Reimer, Ulf
- Drosten, Christian
- Corman, Victor M.
- Giesecke-Thiel, Claudia
- Sander, Leif Erik
- Thiel, Andreas
- Venue
- Nature
- Published
- 2020-07-29
- Volume
- 587
- Issue
- 7833
- Pages
- 270-274
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W3045971896
- Cited by
- 1,310
- References
- 41
- Citations by year
- 2026: 16 · 2025: 37 · 2024: 91 · 2023: 143 · 2022: 283 · 2021: 480 · 2020: 259 · 2014: 1
- FWCI
- 38.31
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Nature (publishedVersion)
- medRxiv (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Figshare (submittedVersion, cc-by)
- Sussex Research Online (University of Sussex) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- Funders
- Deutsche Forschungsgemeinschaft (KFO 339, SFB‐TR84)
- Bundesministerium für Bildung und Forschung
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Keywords
- SARS-CoV-2, COVID-19 pandemic, CD4+ T cells, spike protein, cross-reactive T cells, HCoV-229E, HCoV-OC43, C-terminal epitope, T cell immunity, COVID-19 vaccine design, healthy donors
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, Adult, Aged, Aged, 80 and over, Cell Line, Cross Reactions, Female, Humans, Lymphocyte Activation, Male, Middle Aged, Pneumonia, Viral, CD4-Positive T-Lymphocytes, Coronavirus Infections, Epitopes, T-Lymphocyte, Coronavirus 229E, Human, Coronavirus OC43, Human, Pandemics, Coronavirus NL63, Human, Healthy Volunteers, Spike Glycoprotein, Coronavirus
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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