Single-cell RNA sequencing reveals ex vivo signatures of SARS-CoV-2-reactive T cells through ‘reverse phenotyping

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. Researchers from Helmholtz Zentrum and the Technical University of Munich used single-cell RNA sequencing to identify and profile SARS-CoV-2-reactive T cells from Coronavirus Disease 2019 (COVID-19) patients. To do so, they induced transcriptional shifts by antigenic stimulation in vitro and took 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. The researchers characterized 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.

Single-cell RNA sequencing allows detection of transcriptional shifts induced
by antigen-specific stimulation in TCR-barcoded clonotypes

Fig. 1

a Experimental setup; cells from tracheal aspirates and peripheral blood T cells (flow cytometry-sorted for CD4 or CD8 positivity) of intensive care unit (ICU) patients with COVID-19 were profiled by single-cell RNA sequencing (scRNA seq). Before scRNA seq, peripheral blood T cells were stimulated with SARS-CoV-2 spike protein–peptide mix or left untreated. b Uniform manifold approximation and projection (UMAP) of Leiden clusters (left panel), CD4 and CD8 T cells (middle panel), and stimulated and unstimulated T cells (right panel) (n = 11,460 cells in total). c IFNG expression, IFN response score, proliferation score, cytotoxic score, and cytokine score (from top to bottom) in unstimulated (left panels; stimulated cells shown in gray) or stimulated (right panels; unstimulated cells shown in gray) T cells (n = 11,460 cells in total). d Stimulated CD4 and CD8 T cells with highlighted pseudotime after defining the endpoint of pseudotime at the tip of cluster 29 (n = 11,460 cells in total). e IFNG expression in unstimulated or stimulated T cells for four representative clonotypes. For each clonotype, cells belonging to that clonotype are shown in an individual panel pair (cells from the unstimulated condition in left panels, cells from the stimulated condition in right panels), while cells not belonging to that clonotype are shown in gray (n = 11,460 cells in total, 43 cells for CD4 clonotype 19, 8 for CD4 clonotype 574, 61 for CD8 clonotype 244, 165 for CD8 clonotype 13). Data are shown for patient GT_3.

Fischer DS, Ansari M, Wagner KI, Jarosch S, Huang Y, Mayr CH, Strunz M, Lang NJ, D’Ippolito E, Hammel M, Mateyka L, Weber S, Wolff LS, Witter K, Fernandez IE, Leuschner G, Milger K, Frankenberger M, Nowak L, Heinig-Menhard K, Koch I, Stoleriu MG, Hilgendorff A, Behr J, Pichlmair A, Schubert B, Theis FJ, Busch DH, Schiller HB, Schober K. (2021) Single-cell RNA sequencing reveals ex vivo signatures of SARS-CoV-2-reactive T cells through ‘reverse phenotyping’. Nat Commun 12(1):4515. [article]

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