Ego3, a regulator of TORC1 signaling, is degraded by the \nintralumenal fragment pathway
Bibliographic record
Abstract
Target of rapamycin complex 1 (TORC1) is a conserved protein kinase complex whose activity controls metabolism in eukaryotic cells. To function, TORC1 and its regulators are localized to lysosome membranes. The mechanism(s) that control TOR complex protein lifetimes remain enigmatic. The IntraLumenal Fragment (ILF) pathway is a selective protein degradation pathway that involves lysosomes. Thus, I hypothesized that components of TORC1, EGO and SEA complexes may be degraded by this ILF pathway. \nUsing the yeast S. cerevisiae and its vacuolar lysosome (or vacuole) as models, I tested this hypothesis by first imaging live cells by fluorescence microscopy. I found that several subunits of TORC1, EGO and SEA complexes tagged with GFP are sorted into boundaries between docked vacuoles and accumulate within the vacuole lumen. However, when I isolated vacuoles from cells and repeated this experiment in vitro, I found that nearly all components re-localized to endosomes. The only exception was Ego3, a subunit that tethers the EGO complex to vacuole membranes. I then applied rapamycin, an inhibitor of TOR, to induce TOR protein downregulation and degradation. In vivo, I found that rapamycin stimulated sorting of TOR complex . Whereas, in vitro, rapamycin only enhanced sorting, internalization and degradation of Ego3. \nIn conclusion, many components of TOR signaling complexes seem to be degraded by the ILF pathway including Ego3. Thus, I speculate that the ILF pathway may play an important role in downregulating TOR activity.
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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) | 0.002 | 0.001 |
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".