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The ImmGen consortium OpenSource T cell project

Nature Immunology volume 23, pages 643–644 (2022)Cite this article

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To the Editor — The ImmGen consortium is announcing the launch of ImmGen T (https://www.immgen.org/ImmGenT), a new open-source project that follows on from our previous effort in macrophages1 to comprehensively profile specific immune cell populations across different locations and activation states as a community project. The goal of this community project can again be defined simply: to coordinately profile every T cell, in every body location of the mouse, and in every state that immunologic challenges push T cells into. Profiling will be performed at the single-cell level, with the combined determination of mRNA, surface protein (CITE-seq2,3 (cellular indexing of transcriptomes and epitopes by sequencing)), and T cell receptor variable (TCR-V) sequence (two-chains). As with all ImmGen arms, the intent is to create a broad and homogenous dataset to serve as a general reference, and to enable integrative computational analyses (www.immgen.org).

T cells are richly heterogeneous, with a diversity of effector potentialities and phenotypes that relates directly to their protective abilities or their contributions to autoimmune diseases. A broadly and rigorously generated reference dataset will yield a useful framework and will allow cell states, and the fine regulatory modules that determine them, to be comparatively evaluated across a large array of immune responses. Tissue-specific atlases flourish (for example, Tabula Muris, Allen Brain Atlas and Human Cell Atlas), but these do not usually systematically assess T cells and may miss rare T cell states better represented elsewhere. We also know that the various frameworks for the classification of T cell subsets, derived from experimentation in vitro or from specific situations in vivo, tend to break down or become fuzzy when examined by single-cell genomics (for example, T helper 1 and 2 for CD4+ T cells, or activated, memory and exhausted CD8+ T cell classifications). From the cross-body and cross-stimulation landscape intended here, the community should be able to derive a common language to describe and classify all T cells. Generating information on cell-surface proteins will provide useful proteome and transcriptome correlates, possibly help in defining cell types, and flag markers usable for cell isolation. Finally, the bewildering complexity of TCR repertoires, and how they connect to phenotypic variation during immune responses, offers a whole new plane of investigation.

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References

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Authors and Affiliations

  1. Department of Immunology, Harvard Medical School, Boston, MA, USA

    David Zemmour & Christophe Benoist

  2. Department of Pathology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    David Zemmour

  3. Division of Biological Sciences, Molecular Biology Section, University of California San Diego, La Jolla, CA, USA

    Ananda Goldrath & Mitchell Kronenberg

  4. La Jolla Institute for Immunology, La Jolla, CA, USA

    Mitchell Kronenberg

  5. Department of Pathology, University of Massachusetts Medical School, Worcester, MA, USA

    Joonsoo Kang

Authors
  1. David Zemmour
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  2. Ananda Goldrath
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  3. Mitchell Kronenberg
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  4. Joonsoo Kang
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  5. Christophe Benoist
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Corresponding author

Correspondence to Christophe Benoist.

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The authors declare no competing interests.

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Zemmour, D., Goldrath, A., Kronenberg, M. et al. The ImmGen consortium OpenSource T cell project. Nat Immunol 23, 643–644 (2022). https://doi.org/10.1038/s41590-022-01197-z

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