Structural and evolutionary characterization of phospholipid:diacylglycerol acyltransferase in photosynthetic organisms
Bibliographic record
Abstract
Phospholipid:diacylglycerol acyltransferase (PDAT) catalyzes the last step in acyl-CoA independent triacylglycerol biosynthesis in algae and higher plants. Although PDAT has been characterized in some algal and plant species, the evolution and structural properties of this important enzyme at the broad level of photosynthetic organisms is yet to be studied. In this study, a reliable fluorescence-based PDAT assay was first developed to replace the costly and lab-extensive radiolabelling method. The novel method, as well as various biotechnological and in silico analyses, were then used to explore the structural and evolutionary properties of PDATs. The results showed that functional divergence and positive selection present in the evolution of PDAT in green algae and plants. The identified positive selection sites are important in PDAT activity and thus would be candidate sites for modifying PDAT via protein engineering. In addition, PDAT evolved to be more important for plant metabolism and fitness than algae.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".