Elucidating the enzyme network driving <i>Amaryllidaceae</i> alkaloids biosynthesis in <i>Leucojum aestivum</i>
Bibliographic record
Abstract
Amaryllidaceae alkaloids (AAs) are diverse bioactive metabolites with significant pharmaceutical potential, derived from 4'-O-methylnorbelladine (4'OM). The biosynthesis of these compounds involves the condensation of tyramine and 3,4-dihydroxybenzaldehyde by norbelladine synthase (NBS) and/or noroxomaritidine/norcraugsodine reductase (NR), followed by O-methylation. Cytochrome P450 enzymes, particularly the CYP96T family, introduce further structural diversity through C-C couplings, resulting in lycorine, galanthamine and crinine cores. Despite their importance, the exact biosynthetic pathways remain poorly defined. In this study, we describe key enzymes from Leucojum aestivum (La), providing crucial insight into AA biosynthesis. Transient expression in Nicotiana benthamiana demonstrated that LaNBS and LaNRII catalyse the conversion of tyramine and 3,4-dihydroxybenzaldehyde to norbelladine, which is subsequently O-methylated by a norbelladine-4'-O-methyltransferase (LaN4'OMT) in planta. Co-agroinfiltration of LaNBS, LaNRII, LaN4'OMT and LaCYP96T1 resulted in the production of various phenol-coupled products, with lycorine as the predominant compound, alongside haemanthamine, crinine/vittatine and norgalanthamine. This study identifies LaCYP96T1 and LaCYP96T2 as the first monocot enzymes capable of catalysing all three regioselective C-C phenol couplings and also highlights the substrate promiscuity of LaNRII. The findings not only elucidate critical steps in AA biosynthesis but also open new avenues for biotechnological application in producing valuable alkaloids, offering potential for novel drug development.
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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".