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Single cell multiomic analysis of T cell exhaustion in vitro

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NIAID Data Ecosystem2026-03-12 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP317907
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T cell activation is a key step in the amplification of an immune response. Over the course of an immune response, cells may be chronically stimulated, with some proportion becoming exhausted; an enormous number of molecules are involved in this process. There remain a number of questions about the process, namely: what degree of heterogeneity and plasticity do T-cells exhibit during stimulation? how many unique cell states define chronic stimulation? what markers discriminate activated from exhausted cells? We addressed these questions by performing single cell multiomic analysis to simultaneously measure expression of 38 proteins and 399 genes in human T cells expanded in vitro. This approach allowed us to study how T cells change over the course of chronic stimulation. Comprehensive immunophenotypic and transcriptomic analysis at day 0 enabled a refined characterization of T cell maturational states and the identification of a donor-specific subset of terminally differentiated T cells that would have been otherwise overlooked using canonical cell classification schema. As expected, activation downregulated naive-cell markers and upregulated effector molecules, proliferation regulators, co-inhibitory and co-stimulatory receptors. Our deep kinetic analysis further revealed clusters of proteins and genes identifying unique states of activation, defined by markers temporarily expressed upon 3 days of stimulation (PD-1, CD69, LTA), markers constitutively expressed throughout chronic activation (CD25, GITR, LGALS1), and markers uniquely up-regulated upon 14 days of stimulation (CD39, ENTPD1, TNFDF10); expression of these markers could be associated with the emergence of short-lived cell types. Notably, different ratios of cells expressing activation or exhaustion markers were measured at each time point. These data reveal the high heterogeneity and plasticity of chronically stimulated T cells. Our study demonstrates the power of a single-cell multiomic approach to comprehensively characterize T cells and to precisely monitor changes in differentiation, activation, and exhaustion signatures during cell stimulation.
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2021-05-01
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