A divergent transcriptional landscape underpins the development and functional branching of MAIT cells.

MR1-restricted mucosal-associated invariant T (MAIT) cells play a unique role in the immune system. These cells develop intrathymically through a three-stage process, but the events that regulate this are largely unknown. Here, using bulk and single-cell RNA sequencing-based transcriptomic analysis in mice and humans, we studied the changing transcriptional landscape that accompanies transition through each stage. Many transcripts were sharply modulated during MAIT cell development, including SLAM (signaling lymphocytic activation molecule) family members, chemokine receptors, and transcription factors. We also demonstrate that stage 3 "mature" MAIT cells comprise distinct subpopulations including newly arrived transitional stage 3 cells, interferon-γ-producing MAIT1 cells and interleukin-17-producing MAIT17 cells. Moreover, the validity and importance of several transcripts detected in this study are directly demonstrated using specific mutant mice. For example, MAIT cell intrathymic maturation was found to be halted in SLAM-associated protein (SAP)-deficient and CXCR6-deficient mouse models, providing clear evidence for their role in modulating MAIT cell development. These data underpin a model that maps the changing transcriptional landscape and identifies key factors that regulate the process of MAIT cell differentiation, with many parallels between mice and humans.

Switching to IgG3, IgG2b, and IgA is division linked and independent, revealing a stochastic framework for describing differentiation.

LPS was used to induce switching of B cells to IgG3 and, in the presence of TGF-beta, to IgG2b and IgA. Switching to all three isotypes increased with division number according to a consistent relationship that was independent of time in culture. The mode of activation altered the relationship with division, as CD40 ligand increased switching to IgA and decreased switching to IgG2b and IgG3 when measured per division. This division-linked switching behavior could be described by Gaussian probability distributions centered around a mean division number. The divisions at which switching to IgG3 and IgG2b occurred overlapped, raising the possibility that the two switching mechanisms were linked. However, when IgG3+ and IgG3- B cells were sorted and placed back in culture, they switched to IgG2b at an equivalent rate, indicating that alternative switching decisions were made independently within a single cell. As a consequence, isotype switching could be predicted at the population level by standard probability laws. Therefore, division number provides a framework for a stochastic description of differentiation that may be widely applicable.