Identification and characterization of an efficient acyl-CoA: diacylglycerol acyltransferase 1 (DGAT1) gene from the microalga Chlorella ellipsoidea
Bibliographic record
Abstract
BACKGROUND: Oil in the form of triacylglycerols (TAGs) is quantitatively the most important storage form of energy for eukaryotic cells. Diacylglycerol acyltransferase (DGAT) is considered the rate-limiting enzyme for TAG accumulation. Chlorella, a unicellular eukaryotic green alga, has attracted much attention as a potential feedstock for renewable energy production. However, the function of DGAT1 in Chlorella has not been reported. RESULTS: A full-length cDNA encoding a putative diacylglycerol acyltransferase 1 (DGAT1, EC 2.3.1.20) was obtained from Chlorella ellipsoidea. The 2,142 bp open reading frame of this cDNA, designated CeDGAT1, encodes a protein of 713 amino acids showing no more than 40% identity with DGAT1s of higher plants. Transcript analysis showed that the expression level of CeDGAT1 markedly increased under nitrogen starvation, which led to significant triacylglycerol (TAG) accumulation. CeDGAT1 activity was confirmed in the yeast quadruple mutant strain H1246 by restoring its ability to produce TAG. Upon expression of CeDGAT1, the total fatty acid content in wild-type yeast (INVSc1) increased by 142%, significantly higher than that transformed with DGAT1s from higher plants, including even the oil crop soybean. The over-expression of CeDGAT1 under the NOS promoter in wild-type Arabidopsis thaliana and Brassica napus var. Westar significantly increased the oil content by 8-37% and 12-18% and the average 1,000-seed weight by 9-15% and 6-29%, respectively, but did not alter the fatty acid composition of the seed oil. The net increase in the 1,000-seed total lipid content was up to 25-50% in both transgenic Arabidopsis and B. napus. CONCLUSIONS: We identified a gene encoding DGAT1 in C. ellipsoidea and confirmed that it plays an important role in TAG accumulation. This is the first functional analysis of DGAT1 in Chlorella. This information is important for understanding lipid synthesis and accumulation in Chlorella and for genetic engineering to enhance oil production in microalgae and oil plants.
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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) | 0.001 | 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 | 0.001 |
| 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".