Caspase 3 exhibits a yeast metacaspase proteostasis function that protects mitochondria from toxic TDP43 aggregates
Bibliographic record
Abstract
Caspase 3 activation is a hallmark of cell death and there is a strong correlation between elevated protease activity and evolving pathology in neurodegenerative disease, such as amyotrophic lateral sclerosis (ALS). At the cellular level, ALS is characterized by protein aggregates and inclusions, comprising the RNA binding protein TDP-43, which are hypothesized to trigger pathogenic activation of caspase 3. However, a growing body of evidence indicates this protease is essential for ensuring cell viability during growth, differentiation and adaptation to stress. Here, we explored whether caspase 3 acts to disperse toxic protein aggregates, a proteostasis activity first ascribed to the distantly related yeast metacaspase ScMCA1. We demonstrate that human caspase 3 can functionally substitute for the ScMCA1 and limit protein aggregation in yeast, including TDP-43 inclusions. Proteomic analysis revealed that disrupting caspase 3 in the same yeast substitution model resulted in detrimental TDP-43/mitochondrial protein associations. Similarly, suppression of caspase 3, in either murine or human skeletal muscle cells, led to accumulation of TDP-43 aggregates and impaired mitochondrial function. These results suggest that caspase 3 is not inherently pathogenic, but may act as a compensatory proteostasis factor, to limit TDP-43 protein inclusions and protect organelle function in aggregation related degenerative disease.
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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 | 0.001 |
| 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 | 0.000 |
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".