Mammalian acetyl‐CoA carboxylase polymerizes in association with tubulin
Bibliographic record
Abstract
Acetyl‐CoA carboxylase (ACC) catalyses the formation of malonyl‐CoA, an essential substrate for fatty acid synthase and a potent inhibitor of fatty acid oxidation. Control of ACC activity has important implications for overall energy metabolism and involves complex regulation via gene expression, allosteric mechanisms and multi‐site phosphorylation. A classic characteristic of ACC is allosteric activation by carboxylic acids, leading to the formation of filamentous polymers (up to 5–10‐MDa). Here, we test the hypothesis that ACC polymerization involves additional proteins. ACC polymers were purified by size fractionation and subjected to tandem mass spectrometry to identify associated proteins. Major ACC polymer‐associated proteins included tubulin and fatty acid synthase. The association between ACC and tubulin was validated by co‐immunoprecipitation and confocal microscopy. In reconstitution studies, purified tubulin and/or GTP had no direct effect on catalytic properties of ACC. However, based on immunocytochemical analysis, association with tubulin may be sensitive to the phosphorylation state of ACC. In conclusion, intracellular control of ACC involves complex protein‐protein interactions. These studies were supported by the Canadian Institutes for Health Research and by Scholarships from UBC and the Natural Sciences and Engineering Research Council (WML).
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".