Mitochondrial electron-transport-chain inhibitors of complexes I and II induce autophagic cell death mediated by reactive oxygen species
Bibliographic record
Abstract
Autophagy is a self-digestion process important for cell survival during starvation. It has also been described as a form of programmed cell death. Mitochondria are important regulators of autophagy-induced cell death and damaged mitochondria are often degraded by autophagosomes. Inhibition of the mitochondrial electron transport chain (mETC) induces cell death through generating reactive oxygen species (ROS). The role of mETC inhibitors in autophagy-induced cell death is unknown. Herein, we determined that inhibitors of complex I (rotenone) and complex II (TTFA) induce cell death and autophagy in the transformed cell line HEK 293, and in cancer cell lines U87 and HeLa. Blocking the expression of autophagic genes (beclin 1 and ATG5) by siRNAs or using the autophagy inhibitor 3-methyladenine (3-MA) decreased cell death that was induced by rotenone or TTFA. Rotenone and TTFA induce ROS production, and the ROS scavenger tiron decreased autophagy and cell death induced by rotenone and TTFA. Overexpression of manganese-superoxide dismutase (SOD2) in HeLa cells decreased autophagy and cell death induced by rotenone and TTFA. Furthermore, blocking SOD2 expression by siRNA in HeLa cells increased ROS generation, autophagy and cell death induced by rotenone and TTFA. Rotenone- and TTFA-induced ROS generation was not affected by 3-MA, or by beclin 1 and ATG5 siRNAs. By contrast, treatment of non-transformed primary mouse astrocytes with rotenone or TTFA failed to significantly increase levels of ROS or autophagy. These results indicate that targeting mETC complex I and II selectively induces autophagic cell death through a ROS-mediated mechanism.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".