Single-cell transcriptomics of human T cells reveals tissue and activation signatures in health and disease

Abstract

Human T cells coordinate adaptive immunity in diverse anatomic compartments through production of cytokines and effector molecules, but it is unclear how tissue site influences T cell persistence and function. Here, we use single cell RNA-sequencing (scRNA-seq) to define the heterogeneity of human T cells isolated from lungs, lymph nodes, bone marrow and blood, and their functional responses following stimulation. Through analysis of >50,000 resting and activated T cells, we reveal tissue T cell signatures in mucosal and lymphoid sites, and lineage-specific activation states across all sites including distinct effector states for CD8+ T cells and an interferon-response state for CD4+ T cells. Comparing scRNA-seq profiles of tumor-associated T cells to our dataset reveals predominant activated CD8+ compared to CD4+ T cell states within multiple tumor types. Our results therefore establish a high dimensional reference map of human T cell activation in health for analyzing T cells in disease.

Three-dimensional genome structure and chromatin accessibility reorganization during in vivo induction of human T cell tolerance

“…The genes of CD4, interleukin 2 receptor subunit alpha (IL-2RA), and OX40 (also called tumor necrosis factor receptor superfamily member 4, TNFSF4) are specifically expressed in the CD4 + T ss cells, whereas CD8A, CD8B, and KLRD1 are expressed in the CD8 + T ss cells (Figure 1C and 1D). These observations confirmed a difference in gene expression between the CD4 + lineage and CD8 + lineage (Kioussis and Ellmeier, 2002; Mingueneau et al, 2013; Monaco et al, 2019; Satpathy et al, 2018; Szabo et al, 2019). The TF Foxp3, a key regulatory gene for the development of Tregs, is highly expressed in CD4 + T ss (Figure 1C) (Hori et al, 2003).…”

CReSCENT: CanceR Single Cell ExpressioN Toolkit

“…Other DEGs within cluster 3 include CST7, NKG7, KLDR1, GNLY, and GZMH, several of which have been previously associated with cytotoxic T cell function (27). This coincides with the analysis from the original authors of this dataset (26), who identified cells belonging to cluster 3 enriched for CD8+ effector memory CD45RA (CD8 TEMRA ) cells ( Figure 2D) and expression of CCL5 ( Figure 2E), which is a marker of CD8+ TEM cells (26,28). Together, this demonstrates the ability of the CReSCENT framework to recapitulate findings from original publications and support reproducible single-cell science.…”

“…To show how CReSCENT may be used for the analysis of scRNA-seq data, we performed an analysis of a publicly available human tumour-associated T cell scRNA-seq data set, containing data from the blood, lymph nodes, lungs and bone marrow from two donors, with or without CD3/CD28 T Cell Activator stimulation (26). Using one of the samples from this dataset, from the bone marrow of one donor, with CD3/CD28 T cell activation, we performed multiple runs of the CReSCENT pipeline, each with a different cell clustering resolution (1.0 [default], 0.7 and 0.3).…”

Deconvolution of Cell Type-Specific Drug Responses in Human Tumor Tissue with Single-Cell RNA-seq

“…We projected drug-treated cells onto vehicle-treated cells with UMAP in Fig. 2 as described in Szabo et al (code available at www.github.com/simslab/umap_projection) 29 .…”