ILF and vReD pathways cooperate to control lysosomal transporter protein lifetimes
Bibliographic record
Abstract
Lysosomal nutrient transporter proteins move lumenal products of biomaterial catabolism to the cytoplasm for reuse by the cell. Two mechanisms control their lifetimes: the ILF (IntraLumenal Fragment) and vReD (Vacuole REcycling and Degradation) pathways. But it is not clear if they function independently. Using S. cerevisiae as a model, here we show that the ILF pathway mediates constitutive turnover of the lysine transporter Ypq1 and zinc transporter Cot1-known vReD client proteins-in vivo and in vitro. In contrast, the vReD pathway mediates constitutive degradation of the amino acid transporter Vba4. Activation of TOR with cycloheximide enhances their degradation by these pathways. However, misfolding by heat stress shunts all three into the ILF pathway. Thus, both pathways control individual transporter lifetimes, although only the ILF pathway mediates protein quality control. The pathway chosen depends on protein fate: degradation is imminent by the ILF pathway, whereas the vReD pathway permits reuse.
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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) | 0.001 | 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".