Disruption of chaperone-mediated autophagy-dependent degradation of MEF2A by oxidative stress-induced lysosome destabilization
Bibliographic record
Abstract
Oxidative stress has been implicated in both normal aging and various neurodegenerative disorders and it may be a major cause of neuronal death. Chaperone-mediated autophagy (CMA) targets selective cytoplasmic proteins for degradation by lysosomes and protects neurons against various extracellular stimuli including oxidative stress. MEF2A (myocyte enhancer factor 2A), a key transcription factor, protects primary neurons from oxidative stress-induced cell damage. However, the precise mechanisms of how the protein stability and the transcriptional activity of MEF2A are regulated under oxidative stress remain unknown. In this study, we report that MEF2A is physiologically degraded through the CMA pathway. In pathological conditions, mild oxidative stress (200 μM H 2O 2) enhances the degradation of MEF2A as well as its activity, whereas excessive oxidative stress (> 400 μM H 2O 2) disrupts its degradation process and leads to the accumulation of nonfunctional MEF2A. Under excessive oxidative stress, an N-terminal HDAC4 (histone deacetylase 4) cleavage product (HDAC4-NT), is significantly induced by lysosomal serine proteases released from ruptured lysosomes in a PRKACA (protein kinase, cAMP-dependent, catalytic, α)-independent manner. The production of HDAC4-NT, as a MEF2 repressor, may account for the reduced DNA-binding and transcriptional activity of MEF2A. Our work provides reliable evidence for the first time that MEF2A is targeted to lysosomes for CMA degradation; oxidative stress-induced lysosome destabilization leads to the disruption of MEF2A degradation as well as the dysregulation of its function. These findings may shed light on the underlying mechanisms of pathogenic processes of neuronal damage in various neurodegenerative-related diseases.
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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 | 0.000 |
| 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".