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Updated: Sep 4, 2025

Author Spotlight: Elucidating the Pathways of TFH Cell Differentiation in Acute LCMV Challenges
Published on: April 26, 2024
A CD4+ T cell reference map delineates subtype-specific adaptation during acute and chronic viral infections
Massimo Andreatta1,2,3, Ariel Tjitropranoto4, Zachary Sherman4
1Department of Oncology, UNIL CHUV and Ludwig Institute for Cancer Research Lausanne, University of Lausanne, Lausanne, Switzerland.
None:
CD4+ T cells are critical orchestrators of immune responses against a large variety of pathogens, including viruses. While multiple CD4+ T cell subtypes and their key transcriptional regulators have been identified, there is a lack of consistent definition for CD4+ T cell transcriptional states. In addition, the progressive changes affecting CD4+ T cell subtypes during and after immune responses remain poorly defined. Using single-cell transcriptomics, we characterized the diversity of CD4+ T cells responding to self-resolving and chronic viral infections in mice. We built a comprehensive map of virus-specific CD4+ 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+ T cells across individuals. Virus-specific CD4+ 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+ 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+ T cells responding to viruses and provides a new computational resource for CD4+ T cell analysis.
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