A transferase interactome that may facilitate channeling of polyunsaturated fatty acid moieties from phosphatidylcholine to triacylglycerol
Bibliographic record
Abstract
Polyunsaturated fatty acids (PUFAs) such as α-linolenic acid (ALA, 18:3Δ 9 cis ,12 cis ,15 cis ) have high nutritiol and industrial values. In oilseed crops, PUFAs are synthesized on phosphatidylcholine (PC) and accumulated in triacylglycerol (TAG). Therefore, exploring the mechanisms that route PC-derived PUFA to TAG is essential for understanding and improving PUFA production. The seed oil of flax ( Linum usitatissimum ) is enriched in ALA, and this plant has many lipid biosynthetic enzymes that prefer ALA-containing substrates. In this study, using membrane yeast two-hybrid and bimolecular fluorescence complementation assays, we probed recombint flax transferase enzymes, previously shown to contribute to PUFA enrichment of TAG, for physical interactions with each other under in vivo conditions. We found that diacylglycerol acyltransferases, which catalyze the fil reaction in acyl-CoA–dependent TAG biosynthesis, interact with the acyl-editing enzymes phosphatidylcholine: diacylglycerol cholinephosphotransferase, and lysophosphatidylcholine acyltransferase. Physical interactions among the acyl-editing enzymes were also identified. These findings reveal the presence of an assembly of interacting transferases that may facilitate the channeling of PUFA from PC to TAG in flax and possibly also in other oleaginous plants that produce seeds enriched in PC-modified fatty acids.
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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 | 0.001 |
| 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) | 0.004 | 0.002 |
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".