Plant Acyl-CoA:Lysophosphatidylcholine Acyltransferases (LPCATs) Have Different Specificities in Their Forward and Reverse Reactions
Bibliographic record
Abstract
Acyl-CoA:lysophosphatidylcholine acyltransferase (LPCAT) enzymes have central roles in acyl editing of phosphatidylcholine (PC). Plant LPCAT genes were expressed in yeast and characterized biochemically in microsomal preparations of the cells. Specificities for different acyl-CoAs were similar for seven LPCATs from five different species, including species accumulating hydroxylated acyl groups in their seed oil, with a preference for C18-unsaturated acyl-CoA and low activity with palmitoyl-CoA and ricinoleoyl (12-hydroxyoctadec-9-enoyl)-CoA. We showed that Arabidopsis LPCAT1 and LPCAT2 enzymes catalyzed the acylation and de-acylation of both sn positions of PC, with a preference for the sn-2 position. When acyl specificities of the Arabidopsis LPCATs were measured in the reverse reaction, sn-2-bound oleoyl, linoleoyl, and linolenoyl groups from PC were transferred to acyl-CoA to a similar extent. However, a ricinoleoyl group at the sn-2-position of PC was removed 4-6-fold faster than an oleoyl group in the reverse reaction, despite poor utilization in the forward reaction. The data presented, taken together with earlier published reports on in vivo lipid metabolism, support the hypothesis that plant LPCAT enzymes play an important role in regulating the acyl-CoA composition in plant cells by transferring polyunsaturated and hydroxy fatty acids produced on PC directly to the acyl-CoA pool for further metabolism or catabolism.
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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 | 0.001 | 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".