mTOR controls lysosome tubulation and antigen presentation in macrophages and dendritic cells
Bibliographic record
Abstract
Macrophages and dendritic cells exposed to lipopolysaccharide (LPS) convert their lysosomes from small, punctate organelles into a network of tubules. Tubular lysosomes have been implicated in phagosome maturation, retention of fluid phase, and antigen presentation. There is a growing appreciation that lysosomes act as sensors of stress and the metabolic state of the cell through the kinase mTOR. Here we show that LPS stimulates mTOR and that mTOR is required for LPS-induced lysosome tubulation and secretion of major histocompatibility complex II in macrophages and dendritic cells. Specifically, we show that the canonical phosphatidylinositol 3-kinase-Akt-mTOR signaling pathway regulates LPS-induced lysosome tubulation independently of IRAK1/4 and TBK. Of note, we find that LPS treatment augmented the levels of membrane-associated Arl8b, a lysosomal GTPase required for tubulation that promotes kinesin-dependent lysosome movement to the cell periphery, in an mTOR-dependent manner. This suggests that mTOR may interface with the Arl8b-kinesin machinery. To further support this notion, we show that mTOR antagonists can block outward movement of lysosomes in cells treated with acetate but have no effect in retrograde movement upon acetate removal. Overall our work provides tantalizing evidence that mTOR plays a role in controlling lysosome morphology and trafficking by modulating microtubule-based motor activity in leukocytes.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".