Diacylglycerol acyltransferase 1 is activated by phosphatidate and inhibited by SnRK1‐catalyzed phosphorylation
Bibliographic record
Abstract
Diacylglycerol acyltransferase 1 (DGAT1) catalyzes the final and committed step in the Kennedy pathway for triacylglycerol (TAG) biosynthesis and, as such, elucidating its mode of regulation is critical to understand the fundamental aspects of carbon metabolism in oleaginous crops. In this study, purified Brassica napus diacylglycerol acyltransferase 1 (BnaDGAT1) in n-dodecyl-β-d-maltopyranoside micelles was lipidated to form mixed micelles and subjected to detailed biochemical analysis. The degree of mixed micelle fluidity appeared to influence acyltransferase activity. BnaDGAT1 exhibited a sigmoidal response and eventual substrate inhibition with respect to increasing concentrations of oleoyl-CoA. Phosphatidate (PA) was identified as a feed-forward activator of BnaDGAT1, enabling the final enzyme in the Kennedy pathway to adjust to the incoming flow of carbon leading to TAG. In the presence of PA, the oleoyl-CoA saturation plot became more hyperbolic and desensitized to substrate inhibition indicating that PA facilitates the transition of the enzyme into the more active state. PA may also relieve possible autoinhibition of BnaDGAT1 brought about by the N-terminal regulatory domain, which was shown to interact with PA. Indeed, PA is a key effector modulating lipid homeostasis, in addition to its well recognized role in lipid signaling. BnaDGAT1 was also shown to be a substrate of the sucrose non-fermenting-1-related kinase 1 (SnRK1), which catalyzed phosphorylation of the enzyme and converted it to a less active form. Thus, this known regulator of carbon metabolism directly influences TAG biosynthesis.
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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".