A Novel Assay of DGAT Activity Based on High Temperature GC/MS of Triacylglycerol
Bibliographic record
Abstract
Diacylglycerol acyltransferase (DGAT) catalyzes the final step in the acyl-CoA-dependent biosynthesis of triacylglycerol (TAG), a high-energy compound composed of three fatty acids esterified to a glycerol backbone. In vitro DGAT assays, which are usually conducted with radiolabeled substrate using microsomal fractions, have been useful in identifying compounds and genetic modifications that affect DGAT activity. Here, we describe a high-temperature gas chromatography (GC)/mass spectrometry (MS)-based method for monitoring molecular species of TAG produced by the catalytic action of microsomal DGAT. This method circumvents the need for radiolabeled or modified substrates, and only requires a simple lipid extraction prior to GC. The utility of the method is demonstrated using a recombinant type-1 Brassica napus DGAT produced in a strain of Saccharomyces cerevisae that is deficient in TAG synthesis. The GC/MS-based assay of DGAT activity was strongly correlated with the typical in vitro assay of the enzyme using [1-(14)C] acyl-CoA as an acyl donor. In addition to determining DGAT activity, the method is also useful for determining substrate specificity and selectivity properties of the enzyme.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".