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Fischer, D.S. ; Ansari, M. ; Wagner, K.I.* ; Jarosch, S.* ; Huang, Y.* ; Mayr, C. ; Strunz, M. ; Lang, N.J. ; D'Ippolito, E.* ; Hammel, M.* ; Mateyka, L.* ; Weber, S.* ; Wolff, L.S.* ; Witter, K.* ; Fernandez, I.E.* ; Leuschner, G.* ; Milger, K.* ; Frankenberger, M. ; Nowak, L.* ; Heinig-Menhard, K.* ; Koch, I. ; Stoleriu, M.-G. ; Hilgendorff, A. ; Behr, J.* ; Pichlmair, A.* ; Schubert, B. ; Theis, F.J. ; Busch, D.H. ; Schiller, H. B. ; Schober, K.*

Single-cell RNA sequencing reveals ex vivo signatures of SARS-CoV-2-reactive T cells through 'reverse phenotyping'.

Nat. Commun. 12:4515 (2021)
Publ. Version/Full Text Research data DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
The in vivo phenotypic profile of T cells reactive to severe acute respiratory syndrome (SARS)-CoV-2 antigens remains poorly understood. Conventional methods to detect antigen-reactive T cells require in vitro antigenic re-stimulation or highly individualized peptide-human leukocyte antigen (pHLA) multimers. Here, we use single-cell RNA sequencing to identify and profile SARS-CoV-2-reactive T cells from Coronavirus Disease 2019 (COVID-19) patients. To do so, we induce transcriptional shifts by antigenic stimulation in vitro and take advantage of natural T cell receptor (TCR) sequences of clonally expanded T cells as barcodes for 'reverse phenotyping'. This allows identification of SARS-CoV-2-reactive TCRs and reveals phenotypic effects introduced by antigen-specific stimulation. We characterize transcriptional signatures of currently and previously activated SARS-CoV-2-reactive T cells, and show correspondence with phenotypes of T cells from the respiratory tract of patients with severe disease in the presence or absence of virus in independent cohorts. Reverse phenotyping is a powerful tool to provide an integrated insight into cellular states of SARS-CoV-2-reactive T cells across tissues and activation states.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Receptor; Lymphocytes; Expression; Epitopes; Distinct; Linking; Naive
Language english
Publication Year 2021
HGF-reported in Year 2021
ISSN (print) / ISBN 2041-1723
e-ISSN 2041-1723
Journal Nature Communications
Quellenangaben Volume: 12, Issue: 1, Pages: , Article Number: 4515 Supplement: ,
Publisher Nature Publishing Group
Publishing Place London
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)
Institute of Virology (VIRO)
German Center for Lung Research (DZL)
Institute of Lung Health and Immunity (LHI)
Helmholtz AI - HMGU (HAI - HMGU)
POF-Topic(s) 30205 - Bioengineering and Digital Health
30203 - Molecular Targets and Therapies
80000 - German Center for Lung Research
30202 - Environmental Health
Research field(s) Enabling and Novel Technologies
Immune Response and Infection
Lung Research
PSP Element(s) G-503800-001
G-502700-001
G-501800-810
G-501600-012
G-501600-001
G-552100-001
Grants Joachim Herz Stiftung
German Center for Infection Research (DZIF)
German Research Foundation (DFG)
German Center for Lung Research (DZL)
Helmholtz Association
BMBF project Single Cell Genomics Network Germany
European Union's Horizon 2020 research and innovation program
Chan Zuckerberg Initiative
BMBF
Helmholtz Association's Initiative and Networking Fund through Helmholtz AI
German research foundation (DFG) fellowship through the Graduate School of Quantitative Biosciences Munich (QBM)
German National Network of University Medicine of the Federal Ministry of Education and Research (BMBF)
DOI 10.1038/s41467-021-24730-4
WOS ID WOS:000678710800001
Scopus ID 85111243629
PubMed ID 34312385
Erfassungsdatum 2021-09-09
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