mTORC1 regulates mannose-6-phosphate receptor transport and T-cell vulnerability to regulatory T cells by controlling kinesin KIF13A
Bibliographic record
Abstract
Abstract Mannose-6-phosphate receptor (M6PR) that facilitates cellular uptake of M6P-bearing proteins, including serine-protease granzyme-B (Gzm-B) has an important role in T-cell activation, migration and contraction. However, molecular mechanisms controlling M6PR expression in T cells remain poorly understood. Here, we show that M6PR expression on T cells is distinctively controlled by two common γ-chain cytokines interleukin-2 (IL-2) and IL-7, and the differential M6PR expression is not caused by an altered synthesis of M6PR protein, but is a result of distinct regulation of kinesin-3 motor-protein KIF13A that transport M6PR onto cell surfaces. Using signaling pathway-specific inhibitors, we determine that IL-2 and IL-7 distinctly regulate KIF13A and β1-adaptin and cell-surface M6PR by controlling a kinase mammalian target of rapamycin complex-1 (mTORC1). Inflammatory cytokine IL-2 and prosurvival cytokine IL-7 induce strong and weak activation of mTORC1, leading to up- and downregulation of motor-protein KIF13A and KIF13A-motorized M6PR on T cells, and formation of IL-2 and IL-7 effectors with M6PRhigh and M6PRlow cell-surface expression, respectively. Inhibition of mTORC1 by rapamycin reduces T-cell expression of KIF13A and cell-surface M6PR, and increases T-cell survival in Listeria monocytogenes-infected mice. Using regulatory T (Treg)-cell-enriched mouse tumor model, we determine that M6PRhigh IL-2 effectors but not M6PRlow IL-7 effectors adoptively transferred into tumors are vulnerable to Treg Gzm-B-mediated cell apoptosis. Inhibition of mTORC1 or small interfering RNA-mediated knockdown of KIF13A or M6PR renders IL-2 effectors refractory to Treg Gzm-B lethal hit. Overall, our data offer novel mechanistic insights into T-cell M6PR regulation, and Treg-resistant/Treg-susceptible phenomenon. Furthermore, regulation of T-cell fate vis-à-vis Treg suppression via the mTORC1-KIF13A-M6PR axis provides a proof of concept for therapeutic strategies to target cancer, infectious and autoimmune diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".