The Journal of ImmunologyGenomicsPeer-reviewed journal article
CD4+ Mucosal-associated Invariant T (MAIT) cells express highly diverse T cell receptors
Rimanpreet KauriD, Danielle XieiD, Atul PradhaniD, Nezar MehannaiD, Kelin LiiD, Jeffrey AubéiD, Barbara RosatiiD, David CarlsoniD, Christina Y. LeeiD, Charles Kyriakos VorkasiD
Abstract
Mucosal-associated invariant T cells are highly conserved innate-like T cells in mammals recognized for their high baseline frequency in human blood and cytotoxic effector functions during infectious diseases, autoimmunity, and cancer. While the majority of these cells express a conserved CD8{beta}+ TRAV1-2 T cell receptor recognizing microbially-derived Vitamin B2 intermediates presented by the evolutionarily conserved major histocompatibility complex I-related molecule, MR1, there is an emerging appreciation for diverse subsets that may be selected for in humans with distinct functions, including subpopulations that co-express CD4. Prior work has not examined T cell receptor (TCR) heterogeneity in CD4+ MAIT cells, largely due to bias of identifying human MAIT cells as CD8+ TRAV1-2+ cells. In this study, we adopted an unbiased single-cell TCR-sequencing approach of total MR1-5-OP-RU-tetramer-reactive T cells and discovered that CD4+ MAIT cells express highly diverse TRAV1-2 negative TCRs. To specifically characterize this TCR repertoire, we analyzed VDJ sequences of single MR1-5-OP-RU tetramer+ MAIT cells across two datasets and identified distinct TCR usage among CD4+ MAIT cells including TRAV21, TRAV8 (TRAV8-1, TRAV8-2, TRAV8-3), and TRAV12 families (TRAV12-2, TRAV12-3), as well as more variable J chain and CDR3 sequences. Non-TRAV1-2 MAIT cell TCRs were also enriched after in vitro expansion, including with Mycobacterial tuberculosis. These results indicate that mature human CD4+ MAIT cells adopt distinct TCR usage from the canonical TRAV1-2+ CD8+ subset and suggest that alternative MR1 ligands in addition to riboflavin intermediates may select them.
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
- 4
- FWCI
- 1.49
- Field percentile
- top 17%
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