Mechanistic Connections between Endoplasmic Reticulum (ER) Redox Control and Mitochondrial Metabolism
Bibliographic record
Abstract
The past decade has seen the emergence of endoplasmic reticulum (ER) chaperones as key determinants of contact formation between mitochondria and the ER on the mitochondria-associated membrane (MAM). Despite the known roles of ER–mitochondria tethering factors like PACS-2 and mitofusin-2, it is not yet entirely clear how they mechanistically interact with the ER environment to determine mitochondrial metabolism. In this article, we review the mechanisms used to communicate ER redox and folding conditions to the mitochondria, presumably with the goal of controlling mitochondrial metabolism at the Krebs cycle and at the electron transport chain, leading to oxidative phosphorylation (OXPHOS). To achieve this goal, redox nanodomains in the ER and the interorganellar cleft influence the activities of ER chaperones and Ca2+-handling proteins to signal to mitochondria. This mechanism, based on ER chaperones like calnexin and ER oxidoreductases like Ero1α, controls reactive oxygen production within the ER, which can chemically modify the proteins controlling ER–mitochondria tethering, or mitochondrial membrane dynamics. It can also lead to the expression of apoptotic or metabolic transcription factors. The link between mitochondrial metabolism and ER homeostasis is evident from the specific functions of mitochondria–ER contact site (MERC)-localized Ire1 and PERK. These functions allow these two transmembrane proteins to act as mitochondria-preserving guardians, a function that is apparently unrelated to their functions in the unfolded protein response (UPR). In scenarios where ER stress cannot be resolved via the activation of mitochondrial OXPHOS, MAM-localized autophagosome formation acts to remove defective portions of the ER. ER chaperones such as calnexin are again critical regulators of this MERC readout.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".