Bimodal Activation of Acetyl-CoA Carboxylase by Glutamate
Bibliographic record
Abstract
Acetyl-CoA carboxylase (ACC) catalyzes the formation of malonyl-CoA, an essential substrate for fatty acid biosynthesis and a potent inhibitor of fatty acid oxidation. Here, we provide evidence that glutamate may be a physiologically relevant activator of ACC. Glutamate induced the activation of both major isoforms of ACC, prepared from rat liver, heart, or white adipose tissue. In agreement with previous studies, a type 2A protein phosphatase contributed to the effects of glutamate on ACC. However, the protein phosphatase inhibitor microcystin LR did not abolish the effects of glutamate on ACC activity. Moreover, glutamate directly activated purified preparations of ACC when protein phosphatase activity was excluded. Phosphatase-independent ACC activation by glutamate was also reflected by polymerization of the enzyme as judged by size-exclusion chromatography. The sensitivity of ACC to direct activation by glutamate was diminished by treatment in vitro with AMP-activated protein kinase or cAMP-dependent protein kinase or by beta-adrenergic stimulation of intact adipose tissue. We conclude that glutamate, an abundant intracellular amino acid, induces ACC activation through complementary actions as a phosphatase activator and as a direct allosteric ligand for dephosphorylated ACC. This study supports the general hypothesis that amino acids fulfill important roles as signal molecules as well as intermediates in carbon and nitrogen metabolism.
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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 | 0.000 |
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".