Characterization of cinnamate 4-hydroxylase (CYP73A) and p-coumaroyl 3′-hydroxylase (CYP98A) from Leucojum aestivum, a source of Amaryllidaceae alkaloids
Bibliographic record
Abstract
Biosynthesis of Amaryllidaceae alkaloids (AA) starts with the condensation of tyramine with 3,4-dihydroxybenzaldehyde. The latter derives from the phenylpropanoid pathway that involves modifications of trans-cinnamic acid, p-coumaric acid, caffeic acid, and possibly 4-hydroxybenzaldehyde, all potentially catalyzed by hydroxylase enzymes. Leveraging bioinformatics, molecular biology techniques, and cell biology tools, this research identifies and characterizes key enzymes from the phenylpropanoid pathway in Leucojum aestivum. Notably, we focused our work on trans-cinnamate 4-hydroxylase (LaeC4H) and p-coumaroyl shikimate/quinate 3'-hydroxylase (LaeC3'H), two key cytochrome P450 enzymes, and on the ascorbate peroxidase/4-coumarate 3-hydroxylase (LaeAPX/C3H). Although LaeAPX/C3H consumed p-coumaric acid, it did not result in the production of caffeic acid. Yeasts expressing LaeC4H converted trans-cinnamate to p-coumaric acid, whereas LaeC3'H catalyzed specifically the 3-hydroxylation of p-coumaroyl shikimate, rather than of free p-coumaric acid or 4-hydroxybenzaldehyde. In vivo assays conducted in planta in this study provided further evidence for the contribution of these enzymes to the phenylpropanoid pathway. Both enzymes demonstrated typical endoplasmic reticulum membrane localization in Nicotiana benthamiana adding spatial context to their functions. Tissue-specific gene expression analysis revealed roots as hotspots for phenylpropanoid-related transcripts and bulbs as hubs for AA biosynthetic genes, aligning with the highest AAs concentration. This investigation adds valuable insights into the phenylpropanoid pathway within Amaryllidaceae, laying the foundation for the development of sustainable production platforms for AAs and other bioactive compounds with diverse applications.
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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".