A CD4<sup>+</sup> T cell reference map delineates subtype-specific adaptation during acute and chronic viral infections.

Details

Serval ID
serval:BIB_0B25A9B1D7B9
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
A CD4<sup>+</sup> T cell reference map delineates subtype-specific adaptation during acute and chronic viral infections.
Journal
eLife
Author(s)
Andreatta M., Tjitropranoto A., Sherman Z., Kelly M.C., Ciucci T., Carmona S.J.
ISSN
2050-084X (Electronic)
ISSN-L
2050-084X
Publication state
Published
Issued date
13/07/2022
Peer-reviewed
Oui
Volume
11
Pages
e76339
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
CD4 <sup>+</sup> T cells are critical orchestrators of immune responses against a large variety of pathogens, including viruses. While multiple CD4 <sup>+</sup> T cell subtypes and their key transcriptional regulators have been identified, there is a lack of consistent definition for CD4 <sup>+</sup> T cell transcriptional states. In addition, the progressive changes affecting CD4 <sup>+</sup> T cell subtypes during and after immune responses remain poorly defined. Using single-cell transcriptomics, we characterized the diversity of CD4 <sup>+</sup> T cells responding to self-resolving and chronic viral infections in mice. We built a comprehensive map of virus-specific CD4 <sup>+</sup> T cells and their evolution over time, and identified six major cell states consistently observed in acute and chronic infections. During the course of acute infections, T cell composition progressively changed from effector to memory states, with subtype-specific gene modules and kinetics. Conversely, in persistent infections T cells acquired distinct, chronicity-associated programs. By single-cell T cell receptor (TCR) analysis, we characterized the clonal structure of virus-specific CD4 <sup>+</sup> T cells across individuals. Virus-specific CD4 <sup>+</sup> T cell responses were essentially private across individuals and most T cells differentiated into both Tfh and Th1 subtypes irrespective of their TCR. Finally, we showed that our CD4 <sup>+</sup> T cell map can be used as a reference to accurately interpret cell states in external single-cell datasets across tissues and disease models. Overall, this study describes a previously unappreciated level of adaptation of the transcriptional states of CD4 <sup>+</sup> T cells responding to viruses and provides a new computational resource for CD4 <sup>+</sup> T cell analysis.
Keywords
Animals, CD4-Positive T-Lymphocytes, Mice, Receptors, Antigen, T-Cell/genetics, T-Lymphocytes, Virus Diseases, CD4 T cells, exhaustion, gene expression, immunology, inflammation, mouse, single-cell data science, single-cell transcriptomics, viral infection
Pubmed
Open Access
Yes
Create date
18/07/2022 9:55
Last modification date
04/08/2022 6:38
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