Nutrient and Stress-Induced Mitochondrial Hyperfusion Regulates Cell Death Pathways
Bibliographic record
Abstract
Mitochondria undergo constant cycles of remodelling to sustain normal cell function. As the major cellular metabolic hub, mitochondria are understood to require a precise balance of membrane fission and fusion to maintain mitochondrial genome integrity and levels of oxidative phosphorylation. Mitochondria have been shown to shift the balance of these two opposing pathways to drive a hyperfusion response following proteostasis stress conditions to avoid apoptosis. Importantly, in response to amino acid starvation, mitochondria have been reported to undergo fusion to form elongated structures that avoid degradation via mitophagy. Here, we aimed to study the signals controlling nutrient-dependent mitochondrial fusion and we attempted to reverse the elongation by supplementing three regulatory amino acids, glutamine, leucine, and arginine. Surprisingly, the addback of amino acids did not reverse the elongation, rather, led to stronger mitochondrial hyperfusion. The mechanisms regulating amino-acid dependent mitochondrial hyperfusion response were unknown. We confirmed that addback of amino acids led to metabolic reprogramming that upregulated nucleotide biosynthesis pathways, independent of mTORC1. Additionally, we found the loss of fumarate hydratase prevented amino acid induced mitochondrial hyperfusion, which suggested that amino acid metabolism via the TCA cycle mediates the mitochondrial hyperfusion response. Furthermore, enzymatic inhibition of inosine monophosphate dehydrogenase further blocked this hyperfusion response, indicating a key role of purine biosynthesis in mitochondrial remodelling. The functional role of mitochondrial hyperfusion has been linked to a pro-survival response and we also observed a similar suppression of programmed cell death upon amino acid-induced mitochondrial hyperfusion. These results suggest a novel metabolic mechanism is responsible for sensing cellular amino acids to regulate mitochondrial fusion and cell survival.
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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 | 0.001 | 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".