Characterization of the diversification of phospholipid:diacylglycerol acyltransferases in the green lineage
Bibliographic record
Abstract
Triacylglycerols have important physiological roles in photosynthetic organisms, and are widely used as food, feed and industrial materials in our daily life. Phospholipid:diacylglycerol acyltransferase (PDAT) is the pivotal enzyme catalyzing the acyl-CoA-independent biosynthesis of triacylglycerols, which is unique in plants, algae and fungi, but not in animals, and has essential functions in plant and algal growth, development and stress responses. Currently, this enzyme has yet to be examined in an evolutionary context at the level of the green lineage. Some fundamental questions remain unanswered, such as how PDATs evolved in photosynthetic organisms and whether the evolution of terrestrial plant PDATs from a lineage of charophyte green algae diverges in enzyme function. As such, we used molecular evolutionary analysis and biochemical assays to address these questions. Our results indicated that PDAT underwent divergent evolution in the green lineage: PDATs exist in a wide range of plants and algae, but not in cyanobacteria. Although PDATs exhibit the conservation of several features, phylogenetic and selection-pressure analyses revealed that overall they evolved to be highly divergent, driven by different selection constraints. Positive selection, as one major driving force, may have resulted in enzymes with a higher functional importance in land plants than green algae. Further structural and mutagenesis analyses demonstrated that some amino acid sites under positive selection are critically important to PDAT structure and function, and may be central in lecithin:cholesterol acyltransferase family enzymes in general.
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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 | 0.001 | 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) | 0.001 | 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".