Functional Heterogeneity and Antimycobacterial Effects of Mouse Mucosal-Associated Invariant T Cells Specific for Riboflavin Metabolites
Bibliographic record
Abstract
Mucosal-associated invariant T (MAIT) cells have a semi-invariant TCR Vα-chain, and their optimal development is dependent upon commensal flora and expression of the nonpolymorphic MHC class I-like molecule MR1. MAIT cells are activated in an MR1-restricted manner by diverse strains of bacteria and yeast, suggesting a widely shared Ag. Recently, human and mouse MR1 were found to bind bacterial riboflavin metabolites (ribityllumazine [RL] Ags) capable of activating MAIT cells. In this study, we used MR1/RL tetramers to study MR1 dependency, subset heterogeneity, and protective effector functions important for tuberculosis immunity. Although tetramer(+) cells were detected in both MR1(+/+) and MR1(-/-) TCR Vα19i-transgenic (Tg) mice, MR1 expression resulted in significantly increased tetramer(+) cells coexpressing TCR Vβ6/8, NK1.1, CD44, and CD69 that displayed more robust in vitro responses to IL-12 plus IL-18 and RL Ag, indicating that MR1 is necessary for the optimal development of the classic murine MAIT cell memory/effector subset. In addition, tetramer(+) MAIT cells expressing CD4, CD8, or neither developing in MR1(+/+) Vα19i-Tg mice had disparate cytokine profiles in response to RL Ag. Therefore, murine MAIT cells are considerably more heterogeneous than previously thought. Most notably, after mycobacterial pulmonary infection, heterogeneous subsets of tetramer(+) Vα19i-Tg MAIT cells expressing CXCR3 and α4β1 were recruited into the lungs and afforded early protection. In addition, Vα19iCα(-/-)MR(+/+) mice were significantly better protected than were Vα19iCα(-/-)MR1(-/-), wild-type, and MR1(-/-) non-Tg mice. Overall, we demonstrate considerable functional diversity of MAIT cell responses, as well as that MR1-restricted MAIT cells are important for tuberculosis protective immunity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".