UPR <sup>mt</sup> scales mitochondrial network expansion with protein synthesis via mitochondrial import
Bibliographic record
Abstract
Abstract As organisms develop, individual cells generate mitochondria to fulfill physiologic requirements. However, it remains unknown how mitochondrial network expansion is scaled to cell growth and impacted by environmental cues. The mitochondrial unfolded protein response (UPR mt ) is a signaling pathway mediated by the transcription factor ATFS-1 which harbors a mitochondrial targeting sequence (MTS) 1 . Here, we demonstrate that ATFS-1 mediates an adaptable mitochondrial expansion program that is active throughout normal development. Developmental mitochondrial network expansion required the relatively inefficient MTS 2 in ATFS-1, which allowed the transcription factor to be responsive to parameters that impact protein import capacity of the entire mitochondrial network. Increasing the strength of the ATFS-1 MTS impaired UPR mt activity throughout development due to increased accumulation within mitochondria. The insulin-like signaling-TORC1 3 and AMPK pathways affected UPR mt activation 4,5 in a manner that correlated with protein synthesis. Manipulation to increase protein synthesis caused UPR mt activation. Alternatively, S6 kinase inhibition had the opposite effect due to increased mitochondrial accumulation of ATFS-1. However, ATFS-1 with a dysfunctional MTS 6 constitutively increased UPR mt activity independent of TORC1 function. Lastly, expression of a single protein with a strong MTS, was sufficient to expand the muscle cell mitochondrial network in an ATFS-1-dependent manner. We propose that mitochondrial network expansion during development is an emergent property of the synthesis of highly expressed mitochondrial proteins that exclude ATFS-1 from mitochondrial import, causing UPR mt activation. Mitochondrial network expansion is attenuated once ATFS-1 can be imported.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".