The Lipid Kinase PIKfyve Controls Lysosome Gene Transcription
Bibliographic record
Abstract
Lysosomes are degradative organelles responsible for molecular degradation, eliminating pathogens, digesting cellular debris and salvaging energy during autophagy. Upscaling of lysosome activity has been observed in autophagy where the transcription factor EB (TFEB), a master regulator of lysosome biogenesis, is stimulated to enhance lysosomal gene expression. The most well characterized regulator of TFEB is the mammalian target of rapamycin complex one (mTORC1). Under nutrient sufficiency, mTORC1 is active and phosphorylates TFEB, resulting in its cytosolic retention. During starvation, mTORC1 is inactivated, TFEB becomes dephosphorylated and it enters the nucleus, upregulating lysosomal gene transcription. Recently, mTORC1 was shown to be recruited by the lysosomal lipid phosphatidylinositol 3,5‐bisphosphate [PtdIns(3,5) P 2 ]. Therefore, we postulated that PtdIns(3,5) P 2 may help repress TFEB function by maintaining an active mTORC1. To do this, we used apilimod to inhibit PIKfyve, the enzyme that synthesizes PtdIns(3,5) P 2 . Depletion of PtdIns(3,5) P 2 caused TFEB‐GFP to translocate from the cytosol to the nucleus within 40 minutes and enhanced expression of various lysosomal genes, including cathepsin D. Additionally, apilimod treatment appeared to cause TFEB dephosphorylation similar to mTORC1 inhibition, judged by the faster TFEB gel mobility. However, and strikingly, mTORC1 remained active in apilimod‐treated cells as reported by phosphorylation of two downstream effectors, S6K and ULK. Thus, PtdIns(3,5) P 2 appears to control TFEB‐mediated lysosome gene expression, independently of mTORC1 activity. Currently, we are testing whether PtdIns(3,5) P 2 binds to and presents TFEB to mTORC1 on lysosomes. This work was funded by Canadian Research Chairs.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".