A negative feedback regulation of MTORC1 activity by the lysosomal Ca <sup>2+</sup> channel MCOLN1 (mucolipin 1) using a CALM (calmodulin)-dependent mechanism
Bibliographic record
Abstract
Macroautophagy/autophagy is an evolutionarily conserved pathway that is required for cellular homeostasis, growth and survival. The lysosome plays an essential role in autophagy regulation. For example, the activity of MTORC1, a master regulator of autophagy, is regulated by nutrients within the lysosome. Starvation inhibits MTORC1 causing autophagy induction. Given that MTORC1 is critical for protein synthesis and cellular homeostasis, a feedback regulatory mechanism must exist to restore MTORC1 during starvation. However, the molecular mechanism underlying this feedback regulation is unclear. In this study, we report that starvation activates the lysosomal Ca2+ release channel MCOLN1 (mucolipin 1) by relieving MTORC1's inhibition of the channel. Activated MCOLN1 in turn facilitates MTORC1 activity that requires CALM (calmodulin). Moreover, both MCOLN1 and CALM are necessary for MTORC1 reactivation during prolonged starvation. Our data suggest that lysosomal Ca2+ signaling is an essential component of the canonical MTORC1-dependent autophagy pathway and MCOLN1 provides a negative feedback regulation of MTORC1 to prevent excessive loss of MTORC1 function during starvation. The feedback regulation may be important for maintaining cellular homeostasis during starvation, as well as many other stressful or disease conditions.
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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 | 0.000 |
| 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".