Enhanced autophagic-lysosomal activity and increased BAG3-mediated selective macroautophagy as adaptive response of neuronal cells to chronic oxidative stress
Bibliographic record
Abstract
Oxidative stress and a disturbed cellular protein homeostasis (proteostasis) belong to the most important hallmarks of aging and of neurodegenerative disorders. The proteasomal and autophagic-lysosomal degradation pathways are key measures to maintain proteostasis. Here, we report that hippocampal cells selected for full adaptation and resistance to oxidative stress induced by hydrogen peroxide (oxidative stress-resistant cells, OxSR cells) showed a massive increase in the expression of components of the cellular autophagic-lysosomal network and a significantly higher overall autophagic activity. A comparative expression analysis revealed that distinct key regulators of autophagy are upregulated in OxSR cells. The observed adaptive autophagic response was found to be independent of the upstream autophagy regulator mTOR but is accompanied by a significant upregulation of further downstream components of the canonical autophagy network such as Beclin1, WIPI1 and the transmembrane ATG9 proteins. Interestingly, the expression of the HSP70 co-chaperone BAG3, mediator of BAG3-mediated selective macroautophagy and highly relevant for the clearance of aggregated proteins in cells, was found to be increased in OxSR cells that were consequently able to effectively overcome proteotoxic stress. Overexpression of BAG3 in oxidative stress-sensitive HT22 wildtype cells partly established the vesicular phenotype and the enhanced autophagic flux seen in OxSR cells suggesting that BAG3 takes over an important part in the adaptation process. A full proteome analysis demonstrated additional changes in the expression of mitochondrial proteins, metabolic enzymes and different pathway regulators in OxSR cells as consequence of the adaptation to oxidative stress in addition to autophagy-related proteins. Taken together, this analysis revealed a wide variety of pathways and players that act as adaptive response to chronic redox stress in neuronal cells.
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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".