Phytophthora infestans Cholinephosphotransferase with Substrate Specificity for Very-Long-Chain Polyunsaturated Fatty Acids
Bibliographic record
Abstract
The effective flux between phospholipids and neutral lipids is critical for a high level of biosynthesis and accumulation of very-long-chain polyunsaturated fatty acids (VLCPUFAs), such as arachidonic acid (ARA; 20:4n-6), eicosapentaenoic acid (EPA; 20:5n-3), and docosahexaenoic acid (DHA; 22:6n-3). Here we describe a cDNA (PiCPT1) from Phytophthora infestans, a VLCPUFA-producing oomycete, that may have a role in acyl trafficking between diacylglycerol (DAG) and phosphatidylcholine (PC) during the biosynthesis of VLCPUFAs. The cDNA encodes a polypeptide of 393 amino acids with a conserved CDP-alcohol phosphotransferase motif and approximately 27% amino acid identity to the Saccharomyces cerevisiae cholinephosphotransferase (ScCPT1). In vitro assays indicate that PiCPT1 has high cholinephosphotransferase (CPT) activity but no ethanolaminephosphotransferase (EPT) activity. Substrate specificity assays show that it prefers VLCPUFA-containing DAGs, such as ARA DAG and DHA DAG, as substrates. Real-time PCR analysis reveals that expression of PiCPT1 was upregulated in P. infestans organisms fed with exogenous VLCPUFAs. These results lead us to conclude that PiCPT1 is a VLCPUFA-specific CPT which may play an important role in shuffling VLCPUFAs from DAG to PC in the biosynthesis of VLCPUFAs in P. infestans.
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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) | 0.001 | 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".