CD4+ teff cell heterogeneity: the perspective from single-cell transcriptomics. (April 2020)

• Record Type: Journal Article
• Authors: Zemmour, David; Kiner, Evgeny; Benoist, Christophe
• Is Part Of: Current opinion in immunology. Volume 63(2020)
• Page Start: 61
• Page End: 67
• Publication Date: 2020-04
• Subjects: Immunology -- Periodicals; Allergy -- Periodicals; Immunology -- Abstracts -- Periodicals; Allergy -- Abstracts -- Periodicals; 616.079
• DOI: 10.1016/j.coi.2020.02.004
• Languages: English
• ISSNs: 0952-7915

Abstract

Highlights: Single-cell transcriptomics can reveal unrecognized heterogeneity and CD4 T subsets. An unexpected CD4+ T population with high levels of IFN-I responsive transcripts. Previously defined CD4 subsets more complex than anticipated. The end of Thx: continuous, rather than discrete, distribution of key cytokines. Phenotypes are driven by TCR signals, but not solely. Abstract : Single-cell transcriptomics (scRNAseq) holds the promise to generate definitive atlases of cell types. We review scRNAseq studies of conventional CD4 + αβ T cells performed in a variety of challenged contexts (infection, tumor, allergy) that aimed to parse the complexity and representativity of previously defined CD4 + T cell types, lineages, and cosmologies. With a few years' experience, the field has realized the difficulties and pitfalls of scRNAseq. With the very high-dimensionality of scRNAseq data, subset definitions based on low-dimensionality marker combinations tend to fade or blur: cell types prove more complex than expected; transcripts of key defining transcripts (cytokines, chemokines) are distributed as broad and partially overlapping continua; boundaries with innate lymphocytes are blurred. Tissue location and activation, either cytokine-driven or TCR-driven, determine Teff heterogeneity in sometimes unexpected ways. Emerging techniques for lineage and trajectory tracing, and RNA-protein connections, will further help define the space of differentiated CD4 + T cell heterogeneity.