Single phosphorylation sites in Acc1 and Acc2 regulate lipid homeostasis and the insulin-sensitizing effects of metformin
Bibliographic record
Abstract
Metformin is one of the most widely prescribed therapeutics for type 2 diabetes. But exactly how it works is still unclear. Gregory Steinberg and colleagues now show that it does so by activation of the enzyme AMP-activated protein kinase (Ampk) and Ampk's obligate targeting of two key enzymes involved in lipid homeostasis. The obesity epidemic has led to an increased incidence of nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes. AMP-activated protein kinase (Ampk) regulates energy homeostasis and is activated by cellular stress, hormones and the widely prescribed type 2 diabetes drug metformin1,2. Ampk phosphorylates mouse acetyl-CoA carboxylase 1 (Acc1; refs. 3,4) at Ser79 and Acc2 at Ser212, inhibiting the conversion of acetyl-CoA to malonyl-CoA. The latter metabolite is a precursor in fatty acid synthesis5 and an allosteric inhibitor of fatty acid transport into mitochondria for oxidation6. To test the physiological impact of these phosphorylation events, we generated mice with alanine knock-in mutations in both Acc1 (at Ser79) and Acc2 (at Ser212) (Acc double knock-in, AccDKI). Compared to wild-type mice, these mice have elevated lipogenesis and lower fatty acid oxidation, which contribute to the progression of insulin resistance, glucose intolerance and NAFLD, but not obesity. Notably, AccDKI mice made obese by high-fat feeding are refractory to the lipid-lowering and insulin-sensitizing effects of metformin. These findings establish that inhibitory phosphorylation of Acc by Ampk is essential for the control of lipid metabolism and, in the setting of obesity, for metformin-induced improvements in insulin action.
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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) | 0.002 | 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".