Lysosomal ATP Transporter SLC17A9 Controls Cell Viability via Regulating Cathepsin D
Bibliographic record
Abstract
SLC17A9 (solute carrier family 17 member 9) functions as an ATP transporter in lysosomes as well as other secretory vesicles. SLC17A9 inhibition or silence leads to cell death. However, the molecular mechanisms causing cell death are unclear. In this study, we report that cell death induced by SLC17A9 deficiency is rescued by the transcription factor EB (TFEB), a master gene for lysosomal protein expression, suggesting that SLC17A9 deficiency may be the main cause of lysosome dysfunction, subsequently leading to cell death. Interestingly, Cathepsin D, a lysosomal aspartic protease, is inhibited by SLC17A9 deficiency. Heterologous expression of Cathepsin D successfully rescues lysosomal dysfunction and cell death induced by SLC17A9 deficiency. On the other hand, the activity of Cathepsin B, a lysosomal cysteine protease, is not altered by SLC17A9 deficiency, and Cathepsin B overexpression does not rescue lysosomal dysfunction and cell death induced by SLC17A9 deficiency. Our data suggest that lysosomal ATP and SLC17A9 play critical roles in lysosomal function and cell viability by regulating Cathepsin D activity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".