Proximity‐Dependent Sensors Reveal New Mechanisms of mTORC1 Activation by Amino Acids
Bibliographic record
Abstract
The mechanistic Target of Rapamycin Complex 1 (mTORC1) is potently activated by amino acids (AAs), which may be acquired exogenously through cell surface transporters, or derived through lysosomal degradation of exogenous protein. In highly lethal Ras‐driven cancers, macropinocytosis and lysosomal degradation of exogenous protein has been shown to fuel cancer growth through unclear mechanisms. Both exogenous and lysosome‐derived AAs activate mTORC1 on the lysosome surface. We hypothesized that detailed characterization of late endosome and lysosome organelle proteomes would reveal the functional organization of mTORC1 regulatory machinery, offering potential insight into mTORC1 activation by distinct sources of AAs. Using proximity‐dependent biotinylation and mass spectrometry (BioID), we designed organelle ‘sensors’ with which we revealed the surface proteomes of late endosomes and lysosomes. By combining BioID ‘sensors’ with systematic gene ablation using CRISPR‐Cas9 (a technique we call KO‐BioID) we were able to further define the functional organization of key proteins and complexes within the late endocytic system. Our results demonstrated that mTORC1 regulatory machinery is targeted to a specific subdomain of the late endocytic system that is defined by the HOPS complex. Functionally, we demonstrated that mTORC1 activation by lysosome‐derived AAs operates through a Rag GTPase‐independent pathway, which is inhibited by activation of the GATOR‐Rag GTPase AA‐sensing pathway. In summary, our work shows that distinct but functionally opposed mechanisms exist to activate mTORC1 in response to different AA sources. These results may reveal mechanistic insight into how lysosome‐derived nutrients fuel growth of Ras‐driven cancers.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".