Loss of spatacsin impairs cholesterol trafficking and calcium homeostasis
Bibliographic record
Abstract
Abstract Mutations in SPG11, leading to loss of spatacsin function, impair the formation of membrane tubules in lysosomes and cause the accumulation of lipids in lysosome compartment. However, the full nature of lipids accumulating in lysosomes and the physiological consequences of such accumulation are not known. Here we show that loss of spatacsin, but also downregulation of clathrin, inhibited the formation of tubules on late endosomes/lysosomes and prevented the clearance of cholesterol from this subcellular compartment. Using spatacsin-deficient cells, we evaluated the consequences of impaired cholesterol clearance from late endosomes/lysosomes. The accumulation of cholesterol in late endosomes/lysosomes led to lower cholesterol levels in the plasma membrane, enhancing the entry of extracellular calcium by store-operated calcium entry and increasing resting cytosolic calcium levels. Higher cytosolic calcium levels promoted the nuclear translocation of the master regulator of lysosomes TFEB. Downregulation of TFEB or decrease in resting calcium levels in absence of spatacsin partially corrected the formation of tubules and the accumulation of cholesterol in lysosomes, suggesting that spatacsin could be indirectly implicated in the formation of tubules. Our work reveals a homeostatic balance between cholesterol trafficking and cytosolic calcium levels and shows that loss of spatacsin impairs this homeostatic equilibrium.
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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 | 0.001 | 0.001 |
| 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".