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bioRxiv · 10.1101/2024.05.03.592310

Reproducible single cell annotation of programs underlying T-cell subsets, activation states, and functions

Kotliar, D.·Curtis, M.·Agnew, R.·Weinand, K.·Nathan, A.·Baglaenko, Y.·Zhao, Y.·Sabeti, P. C.·Rao, D. A.·Raychaudhuri, S.
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Abstract

T-cells recognize antigens and induce specialized gene expression programs (GEPs) enabling functions including proliferation, cytotoxicity, and cytokine production. Traditionally, different classes of helper T-cells express mutually exclusive responses - for example, Th1, Th2, and Th17 programs. However, new single-cell RNA sequencing (scRNA-Seq) experiments have revealed a continuum of T-cell states without discrete clusters corresponding to these subsets, implying the need for new analytical frameworks. Here, we advance the characterization of T-cells with T-CellAnnoTator (TCAT), a pipeline that simultaneously quantifies pre-defined GEPs capturing activation states and cellular subsets. From 1,700,000 T-cells from 700 individuals across 38 tissues and five diverse disease contexts, we discover 46 reproducible GEPs reflecting the known core functions of T-cells including proliferation, cytotoxicity, exhaustion, and T helper effector states. We experimentally characterize several novel activation programs and apply TCAT to describe T-cell activation and exhaustion in Covid-19 and cancer, providing insight into T-cell function in these diseases.

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Kotliar, D., Curtis, M., Agnew, R., Weinand, K., Nathan, A., Baglaenko, Y., Zhao, Y., Sabeti, P. C., Rao, D. A., Raychaudhuri, S.. 2024-05-05. Reproducible single cell annotation of programs underlying T-cell subsets, activation states, and functions. https://doi.org/10.1101/2024.05.03.592310

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