Automated Organization Profile

Institute for Transplantation Diagnostics and Cell Therapeutics, University Hospital Düsseldorf, Düsseldorf, Germany

Current S-Index

3.5

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.2

Average Dataset Index per dataset

Total Datasets

3

Total datasets in this organization

Average FAIR Score

53.9%

Average FAIR Score per dataset

Total Citations

0

Total citations to the organization's datasets

Total Mentions

0

Total mentions of the organization's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Dissecting CD8+ T cell pathology of severe SARS-CoV-2 infection by single-cell immunoprofiling

SARS-CoV-2 infection results in varying disease severity, ranging from asymptomatic infection to severe illness. A detailed understanding of the immune response to SARS-CoV-2 is critical to unravel the causative factors underlying differences in disease severity and to develop optimal vaccines against new SARS-CoV-2 variants. We combined single-cell RNA and T cell receptor sequencing with CITE-seq antibodies to characterize the CD8+ T cell response to SARS-CoV-2 infection at high resolution and compared responses between mild and severe COVID-19. We observed a population of exhausted CD8+ T cells in severe SARS-CoV-2 infection and identified a population of NK-like, terminally differentiated CD8+ effector T cells characterized by expression of FCGR3A (encoding CD16). Further characterization of NK-like CD8+ T cells revealed heterogeneity among CD16+ NK-like CD8+ T cells and profound differences in cytotoxicity, exhaustion, and NK-like differentiation between mild and severe disease conditions. We propose a model in which differences in the surrounding inflammatory milieu lead to crucial differences in NK-like differentiation of CD8+ effector T cells, ultimately resulting in the appearance of NK-like CD8+ T cell populations of different functionality and pathogenicity. Our in-depth characterization of the CD8+ T cell-mediated response to SARS-CoV-2 infection provides a basis for further investigation of the importance of NK-like CD8+ T cells in COVID-19 severity.

Authors

  • Schreibing, Felix ;
  • Hannani, Monica T ;
  • Kim, Hyojin ;
  • Nagai, James S ;
  • Ticconi, Fabio ;
  • Fewings, Eleanor ;
  • Bleckwehl, Tore ;
  • Begemann, Matthias ;
  • Torow, Natalia ;
  • Kuppe, Christoph ;
  • Kurth, Ingo ;
  • Hornef, W Mathias ;
  • Kranz, Jennifer ;
  • Frank, Dario ;
  • Anslinger M Teresa ;
  • Ziegler, Patrick ;
  • Kraus, Thomas ;
  • Enczmann, Juergen ;
  • Balz, Vera ;
  • Windhofer, Frank ;
  • Balfanz, Paul ;
  • Kurts, Christian ;
  • Marx, Gernot ;
  • Dreher, Michael ;
  • Schneider, K Rebekka ;
  • Saez-Rodriguez, Julio ;
  • Costa, Ivan ;
  • Hayat, Sikander ;
  • Kramann, Rafael
0 Citations0 Mentions54% FAIR0.4 Dataset Index
10.5281/zenodo.71292292022

Dissecting CD8+ T cell pathology of severe SARS-CoV-2 infection by single-cell immunoprofiling

SARS-CoV-2 infection results in varying disease severity, ranging from asymptomatic infection to severe illness. A detailed understanding of the immune response to SARS-CoV-2 is critical to unravel the causative factors underlying differences in disease severity and to develop optimal vaccines against new SARS-CoV-2 variants. We combined single-cell RNA and T cell receptor sequencing with CITE-seq antibodies to characterize the CD8+ T cell response to SARS-CoV-2 infection at high resolution and compared responses between mild and severe COVID-19. We observed a population of exhausted CD8+ T cells in severe SARS-CoV-2 infection and identified a population of NK-like, terminally differentiated CD8+ effector T cells characterized by expression of FCGR3A (encoding CD16). Further characterization of NK-like CD8+ T cells revealed heterogeneity among CD16+ NK-like CD8+ T cells and profound differences in cytotoxicity, exhaustion, and NK-like differentiation between mild and severe disease conditions. We propose a model in which differences in the surrounding inflammatory milieu lead to crucial differences in NK-like differentiation of CD8+ effector T cells, ultimately resulting in the appearance of NK-like CD8+ T cell populations of different functionality and pathogenicity. Our in-depth characterization of the CD8+ T cell-mediated response to SARS-CoV-2 infection provides a basis for further investigation of the importance of NK-like CD8+ T cells in COVID-19 severity.

Authors

  • Schreibing, Felix ;
  • Hannani, Monica T ;
  • Kim, Hyojin ;
  • Nagai, James S ;
  • Ticconi, Fabio ;
  • Fewings, Eleanor ;
  • Bleckwehl, Tore ;
  • Begemann, Matthias ;
  • Torow, Natalia ;
  • Kuppe, Christoph ;
  • Kurth, Ingo ;
  • Hornef, W Mathias ;
  • Kranz, Jennifer ;
  • Frank, Dario ;
  • Anslinger M Teresa ;
  • Ziegler, Patrick ;
  • Kraus, Thomas ;
  • Enczmann, Juergen ;
  • Balz, Vera ;
  • Windhofer, Frank ;
  • Balfanz, Paul ;
  • Kurts, Christian ;
  • Marx, Gernot ;
  • Dreher, Michael ;
  • Schneider, K Rebekka ;
  • Saez-Rodriguez, Julio ;
  • Costa, Ivan ;
  • Hayat, Sikander ;
  • Kramann, Rafael
0 Citations0 Mentions54% FAIR0.4 Dataset Index
10.5281/zenodo.71292282022

Dissecting CD8+ T cell pathology of severe SARS-CoV-2 infection by single-cell epitope mapping (Version: 1.0)

We provide the R object of the scRNA-seq data of CD8+ T cells used in the study. An R markdown is provided to show the UMAP, antibody derived tag (ADT) derived data, TCR seq information, and binding of Dextramer reagents carrying SARS-CoV-2-derived epitopes.

Authors

  • Schreibing†, Felix ;
  • Hannani†, Monica ;
  • Ticconi, Fabio ;
  • Fewings, Eleanor ;
  • Nagai, James S ;
  • Begemann, Matthias ;
  • Kuppe, Christoph ;
  • Kurth, Ingo ;
  • Kranz, Jennifer ;
  • Frank, Dario ;
  • Anslinger, Teresa M ;
  • Ziegler, Patrick ;
  • Kraus, Thomas ;
  • Enczmann, Jürgen ;
  • Balz, Vera ;
  • Windhofer, Frank ;
  • Balfanz, Paul ;
  • Kurts, Christian ;
  • Marx, Gernot ;
  • Marx, Nikolaus ;
  • Dreher, Michael ;
  • Schneider, Rebekka K ;
  • Saez-Rodriguez, Julio ;
  • Costa†, Ivan ;
  • Kramann†, Rafael
0 Citations0 Mentions54% FAIR0.4 Dataset Index
10.5281/zenodo.45432572021