Acyl-CoA:diacylglycerol acyltransferase: Properties, physiological roles, metabolic engineering and intentional control
Bibliographic record
Abstract
Acyl-CoA:diacylglycerol acyltransferase (DGAT, EC 2.3.1.20) catalyzes the last reaction in the acyl-CoA-dependent biosynthesis of triacylglycerol (TAG). DGAT activity resides mainly in DGAT1 and DGAT2 in eukaryotes and bifunctional wax ester synthase-diacylglycerol acyltransferase (WSD) in bacteria, which are all membrane-bound proteins but exhibit no sequence homology to each other. Recent studies also identified other DGAT enzymes such as the soluble DGAT3 and diacylglycerol acetyltransferase (EaDAcT), as well as enzymes with DGAT activities including defective in cuticular ridges (DCR) and steryl and phytyl ester synthases (PESs). This review comprehensively discusses research advances on DGATs in prokaryotes and eukaryotes with a focus on their biochemical properties, physiological roles, and biotechnological and therapeutic applications. The review begins with a discussion of DGAT assay methods, followed by a systematic discussion of TAG biosynthesis and the properties and physiological role of DGATs. Thereafter, the review discusses the three-dimensional structure and insights into mechanism of action of human DGAT1, and the modeled DGAT1 from Brassica napus. The review then examines metabolic engineering strategies involving manipulation of DGAT, followed by a discussion of its therapeutic applications. DGAT in relation to improvement of traits of farmed animals is also discussed along with DGATs in various other eukaryotic organisms.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".