Single-cell RNA-sequencing resolves self-antigen expression during mTEC development

Abstract

The crucial capability of T cells for discrimination between self and non-self peptides is based on negative selection of developing thymocytes by medullary thymic epithelial cells (mTECs). The mTECs purge autoreactive T cells by expression of cell-type specific genes referred to as tissue-restricted antigens (TRAs). Although the autoimmune regulator (AIRE) protein is known to promote the expression of a subset of TRAs, its mechanism of action is still not fully understood. The expression of TRAs that are not under the control of AIRE also needs further characterization. Furthermore, expression patterns of TRA genes have been suggested to change over the course of mTEC development. Herein we have used single-cell RNA-sequencing to resolve patterns of TRA expression during mTEC development. Our data indicated that mTEC development consists of three distinct stages, correlating with previously described jTEC, mTEChi and mTEClo phenotypes. For each subpopulation, we have identified marker genes useful in future studies. Aire-induced TRAs were switched on during jTEC-mTEC transition and were expressed in genomic clusters, while otherwise the subsets expressed largely overlapping sets of TRAs. Moreover, population-level analysis of TRA expression frequencies suggested that such differences might not be necessary to achieve efficient thymocyte selection.

Biologically indeterminate yet ordered promiscuous gene expression in single medullary thymic epithelial cells

“…That being said, we were unable to explain membership to co-expression groups by any of the features we examined, including gene category, chromosome localisation, genomic distance, tissue specificity, autoimmune disease association, and inclusion in a specific biological pathway. The largely random distribution of genes in modules across the genome is in keeping with observations from previous studies (Meredith et al, 2015;Pinto et al, 2013;Miragaia et al, 2018). Our results are also consistent with previously published studies that concluded that PGE patterns in mTEC are dictated neither by expression patterns seen in differentiated peripheral cell types nor by coregulation by specific transcription factors (Meredith et al, 2015;Villaseñor et al, 2008;Pinto et al, 2013).…”

“…Cell-based clustering of our data supports previous observations that the mTEC compartment is heterogeneous (Bornstein et al, 2018;Miragaia et al, 2018), a notion supported by studies tracking TEC differentiation during organogenesis and regeneration (Gäbler et al, 2007;Yano et al, 2008;Wang et al, 2012;Metzger et al, 2013;Nishikawa et al, 2014;Ohigashi et al, 2013;Mayer et al, 2016;Ohigashi et al, 2015). These suggest that mTEC derive during embryogenesis from progenitors expressing claudins-3 and -4 and SSEA-1 (Hamazaki et al, 2007;Sekai et al, 2014), and postnatally from a population localised at the corticomedullary junction expressing podoplanin and CCL21 (Onder et al, 2015;Michel et al, 2017;Mayer et al, 2016).…”

“…Nevertheless, each of the conditions captured the transcriptomic diversity of the batch-corrected meta-experiment (Methods; Figure 2). The transition from TRA-to TRA+ mTEC surrounded by satellite clusters is additionally evident in our analysis of published single-cell TEC datasets ( Figure S3) (Sansom et al, 2014;Brennecke et al, 2015;Miragaia et al, 2018;Bornstein et al, 2018). We conclude that a non-random and robustly defined set of diverse mTEC subpopulations is reproducible across multiple distinct experiments using different mouse strains and single-cell experimental protocols and that TRG expression biases are apparent across subpopulations.…”

“…TEC can be broadly categorized into cortical (c-) and medullary (m-) lineages based on their structure, anatomical location, molecular characteristics and functions (Rodewald, 2008;Vaidya et al, 2016). Studies examining TEC development and diversity have further revealed considerable heterogeneity within the mTEC compartment reflecting both maturational stages and functionally distinct mTEC subpopulations (Nishikawa et al, 2010;Metzger et al, 2013;Miragaia et al, 2018;Bornstein et al, 2018). During intrathymic selection, cTEC positively select thymocytes that express T-cell receptors (TCRs) capable of recognising peptide:MHC complexes.…”

Extent, heritability, and functional relevance of single cell expression variability in highly homogeneous populations of human cells

“…This is because many micro-environmental perturbations and stochastic factors at the cellular level are known to change the scEV. These factors may include local cell density, cell size, shape and rate of proliferation, cell cycle, and so on (Snijder et al 2009;McDavid et al 2014;Kernfeld et al 2018;Miragaia et al 2018;Mitchell et al 2018). To work on the cell-to-cell variability, these confounding factors have to be controlled.…”