Mechanoresilience of lysosomes conferred by TMEM63A
Bibliographic record
Abstract
Abstract Lysosomes are subject to perturbations that can cause damage to their limiting membrane. Osmotic shifts, pore-forming toxins, and the growth of luminal polymers or pathogens all stand to increase lysosomal membrane tension and/or disrupt the bilayer. In some contexts, this leads to lysosomal rupture and cell death. Here we describe a mechanism that enables lysosomes to sense and respond to acute increases in tension of their limiting membrane. We report that the lysosome-resident non-selective cation channel, TMEM63A, can drive the directional flux of monovalent cations, major osmoticants, out of the lumen when gated by mechanical tension on the organelle. This results in the ability for lysosomes to relieve hydrostatic pressure and, proportionally, membrane tension, affording lysosomes the time to acquire additional lipids. Lysosomes without this mechanism −either because TMEM63A is deleted or in the case when cells express disease-causing variants of TMEM63A − are an order of magnitude more sensitive to lysis upon increases to their membrane tension when compared to their wildtype counterparts. These findings suggest that lysosomes are capable of regulating hydrostatic pressure and volume in response to high tension.
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".