Characterization of a Type‐2 Diacylglycerol Acyltransferase from <i>Haematococcus pluvialis</i> Reveals Possible Allostery of the Recombinant Enzyme
Bibliographic record
Abstract
Haematococcus pluvialis is a green microalga used in the algal biotechnology industry that can accumulate considerable amounts of storage triacylglycerol (TAG) and astaxanthin, which is a high-value carotenoid with strong antioxidant activity, under stress conditions. Diacylglycerol acyltransferase (DGAT) catalyzes the last step of the acyl-CoA-dependent TAG biosynthesis and appears to represent a bottleneck in algal TAG formation. In this study, putative H. pluvialis DGAT2 cDNA (HpDGAT2A, B, D and E) were identified from a transcriptome database and were subjected to sequence-based in silico analyses. The coding sequences of HpDGAT2B, D, and E were then isolated and characterized through heterologous expression in a TAG-deficient Saccharomyces cerevisiae strain H1246. The expression of HpDGAT2D allowed the recovery of TAG biosynthesis in this yeast mutant, and further in vitro enzymatic assays confirmed that the recombinant HpDGAT2D possessed strong DGAT activity. Interestingly, the recombinant HpDGAT2D displayed sigmoidal kinetics in response to increasing acyl-CoA concentrations, which has not been reported in plant or algal DGAT2 in previous studies.
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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) | 0.000 | 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".