Functional Characterization of Lysophosphatidylcholine: Acyl-CoA Acyltransferase Genes From Sunflower (Helianthus annuus L.)
Bibliographic record
Abstract
Lysophosphatidylcholine acyltransferase (LPCAT, EC 2.3.1.23) is an evolutionarily conserved key enzyme in the Lands cycle that catalyses acylation of lysophosphatidylcholine (LPC) to produce phosphatidylcholine (PC), the main phospholipid in cellular membranes. In this study, three LPCAT genes from sunflower were identified and the corresponding proteins characterized. These HaLPCAT genes encoded functionally active enzymes that were able to complement a deficient yeast mutant. Moreover, enzymatic assays were carried out using microsomal preparations of the yeast cells. When acyl specificities were measured in the forward reaction, these enzymes exhibited a substrate preference for unsaturated acyl-CoAs, especially for linolenoyl-CoA, while in the reverse reaction linoleoyl or linolenoyl acyl groups were transferred from PC to acyl-CoA to a similar extent. Expression levels of LPCAT genes were studied revealing distinct tissue-specific expression patterns. In summary, this study suggests that the combined forward and reverse reactions catalysed by sunflower LPCATs facilitate acyl-exchange between the sn-2 position of PC and the acyl-CoA pool. Sunflower LPCATs displayed different characteristics, which could point to different functionalities, favouring the enrichment of seed triacylglycerols with polyunsaturated fatty acid.
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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".