Yeast Mitochondrial Protein–Protein Interactions Reveal Diverse Complexes and Disease-Relevant Functional Relationships
Bibliographic record
Abstract
Although detailed, focused, and mechanistic analyses of associations among mitochondrial proteins (MPs) have identified their importance in varied biological processes, a systematic understanding of how MPs function in concert both with one another and with extra-mitochondrial proteins remains incomplete. Consequently, many questions regarding the role of mitochondrial dysfunction in the development of human disease remain unanswered. To address this, we compiled all existing mitochondrial physical interaction data for over 1200 experimentally defined yeast MPs and, through bioinformatic analysis, identified hundreds of heteromeric MP complexes having extensive associations both within and outside the mitochondria. We provide support for these complexes through structure prediction analysis, morphological comparisons of deletion strains, and protein co-immunoprecipitation. The integration of these MP complexes with reported genetic interaction data reveals substantial crosstalk between MPs and non-MPs and identifies novel factors in endoplasmic reticulum-mitochondrial organization, membrane structure, and mitochondrial lipid homeostasis. More than one-third of these MP complexes are conserved in humans, with many containing members linked to clinical pathologies, enabling us to identify genes with putative disease function through guilt-by-association. Although still remaining incomplete, existing mitochondrial interaction data suggests that the relevant molecular machinery is modular, yet highly integrated with non-mitochondrial processes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| 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) | 0.000 | 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 teacher head, 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".