A CD4+ T cell reference map delineates subtype-specific adaptation during acute and chronic viral infections

  1. Massimo Andreatta
  2. Ariel Tjitropranoto
  3. Zachary Sherman
  4. Michael C Kelly
  5. Thomas Ciucci  Is a corresponding author
  6. Santiago J Carmona  Is a corresponding author
  1. University of Lausanne, Switzerland
  2. University of Rochester, United States
  3. Frederick National Laboratory for Cancer Research, United States

Abstract

CD4+ T cells are critical orchestrators of immune responses against a large variety of pathogens, including viruses. The multifaceted roles of CD4+ T cells, including their help to innate cells, CD8+ T and B cells and their support for long-lived immunity rely on a profound functional heterogeneity. 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. Taking advantage of single-cell transcriptomics, efficient computational methods, and robust animal models, we characterize the transcriptional landscape of CD4+ T cells responding to self-resolving and chronic viral infections. We build a comprehensive map of virus-specific CD4+ T cells and their evolution over time, and identify six major distinct cell states that are consistently observed in acute and chronic infections in mice. During the course of acute infections, T cell composition progressively changes from effector to memory states, with subtype-specific gene modules and kinetics. Conversely, T cells in persistent infections fail to transition from effector to memory states, and acquire distinct, chronicity-associated transcriptional programs. By single-cell T cell receptor (TCR) sequencing analysis, we characterize the clonal structure of virus-specific CD4+ T cells across individuals and T cell subtypes. We find that virus-specific CD4+ T cell responses are essentially private across individuals and that most T cells differentiate into both Tfh and Th1 subtypes irrespective of their TCR, in both acute and chronic infections. Finally, we show 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, available online at https://spica.unil.ch.

Data availability

Sequence data are deposited in the NCBI Gene Expression Omnibus under accession numbers GSE182320 and GSE200635. The new reference atlas can be downloaded (DOI: 10.6084/m9.figshare.16592693) or accessed via the web portal (https://spica.unil.ch/refs/viral-CD4-T). All code sources are available at https://github.com/carmonalab

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Massimo Andreatta

    Agora Cancer Research Center, University of Lausanne, Lausanne, Switzerland
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8036-2647
  2. Ariel Tjitropranoto

    Department of Microbiology and Immunology, University of Rochester, Rochester, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5525-5236
  3. Zachary Sherman

    Department of Microbiology and Immunology, University of Rochester, Rochester, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Michael C Kelly

    Frederick National Laboratory for Cancer Research, Fregerick, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0654-2778
  5. Thomas Ciucci

    Department of Microbiology and Immunology, University of Rochester, Rochester, United States
    For correspondence
    thomasciucci@icloud.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5828-0207
  6. Santiago J Carmona

    Agora Cancer Research Center, University of Lausanne, Lausanne, Switzerland
    For correspondence
    Santiago.Carmona@unil.ch
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2495-0671

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (PZ00P3_180010)

  • Santiago J Carmona

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: This study was performed under the protocol UCAR 2020-003 approved by the University of Rochester Committee on Animal Resources.

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

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  1. Massimo Andreatta
  2. Ariel Tjitropranoto
  3. Zachary Sherman
  4. Michael C Kelly
  5. Thomas Ciucci
  6. Santiago J Carmona
(2022)
A CD4+ T cell reference map delineates subtype-specific adaptation during acute and chronic viral infections
eLife 11:e76339.
https://doi.org/10.7554/eLife.76339

Share this article

https://doi.org/10.7554/eLife.76339

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