Differentiated thymic epithelial cells adopt gene-expression and micro-environmental niches unique to the thymus 2310220

Abstract

The thymus contains a multitude of epithelial cell types that work in concert to educate immature T cells called thymocytes to distinguish self from non-self. A subset of thymic epithelial cells (TECs) express lineage defining transcription factors and differentiate into cell types -- such as muscle, neuroendocrine, and tuft cells -- that are typically found in peripheral tissues. However, the function and organization of these differentiated TECs especially in the human thymus are poorly understood. Specifically, much remains unknown about the gene regulation that enable their function, and their structural morphology and spatial localization in the thymus to ultimately orchestrate thymocyte education. To resolve the diversity of TECs at a single cell resolution, we simultaneously profiled the gene expression and chromatin accessibility of human thymus samples. We integrated our data with all available thymic single cell datasets to establish concordant cell annotations across studies. We leveraged the CELLxGENE database to identify unique gene signatures in the differentiated thymic TECs compared to their peripheral counterparts in 31 tissues. Informed by the gene expression of maturing thymic muscle cells, we used quantitative microscopy to evaluate their cellular morphology and spatial localization in the thymus. We show that differentiated TECs share substantial celltype restricted genes, yet take on a celltype specific identity, a phenomenon not shared by their peripheral counterparts. Narrowing in on the maturation of thymic muscle cells, we show that they have distinct cellular morphologies and thymic spatial localization as they differentiate. Differentiated thymic celltypes, while sharing similarity to their peripheral counterparts, take on a thymus specific identity. Furthermore, thymic muscle cells have distinct cell morphology and micro-environmental niche as they mature. NIH Computational and Systems Immunology (COMP)