Characterization of Phosphatidylcholine:Diacylglycerol Cholinephosphotransferases from Soybean (<i>Glycine max</i>)
Bibliographic record
Abstract
Plant oils in the form of triacylglycerols (TAGs) have important food and industrial applications. The fatty acid composition of TAGs, especially their degree of unsaturation, affects the oil value and applications. Phosphatidylcholine:Diacylglycerol Cholinephosphotransferase (PDCT) facilitates the exchange of fatty acids between phosphatidylcholine and diacylglycerol, influencing the degree of fatty acid unsaturation. In this study, we identified and characterized two PDCT isoforms from soybean ( Glycine max ). Phylogenetic and structural analyses revealed that PDCTs are widely conserved across Embryophyta and share key sequence and structural features among species. Subcellular localization assays using transient expression of fluorescent protein-tagged GmPDCTs in Nicotiana benthamiana leaves confirmed their localization to the endoplasmic reticulum. Expression of GmPDCT s in yeast altered lipid unsaturation, while in vitro enzyme assays using yeast microsomal fractions confirmed that both GmPDCTs are catalytically active, preferring unsaturated substrates. Further structural analysis and mutagenesis revealed that the N-terminus and several amino acids within/near the predicted catalytic domains are critical to the PDCT function. Lastly, stable overexpression of GmPDCT s in Arabidopsis thaliana rod1 ( pdct ) mutant plants successfully restored a wildtype lipid phenotype, providing evidence that these genes encode functional PDCTs. Together, these findings provide new insights into PDCT structure–function relationships, offering potential targets for bioengineering strategies aimed at optimizing oil composition.
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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".