An N-methyltransferase from Ephedra sinica catalyzing the formation of ephedrine and pseudoephedrine enables microbial phenylalkylamine production
Bibliographic record
Abstract
Phenylalkylamines, such as the plant compounds ephedrine and pseudoephedrine and the animal neurotransmitters dopamine and adrenaline, compose a large class of natural and synthetic molecules with important physiological functions and pharmaceutically valuable bioactivities. The final steps of ephedrine and pseudoephedrine biosynthesis in members of the plant genus Ephedra involve N -methylation of norephedrine and norpseudoephedrine, respectively. Here, using a plant transcriptome screen, we report the isolation and characterization of an N -methyltransferase (NMT) from Ephedra sinica able to catalyze the formation of (pseudo)ephedrine and other naturally occurring phenylalkylamines, including N -methylcathinone and N -methyl(pseudo)ephedrine. Phenylalkylamine N -methyltransferase (PaNMT) shares substantial amino acid sequence identity with enzymes of the NMT family involved in benzylisoquinoline alkaloid (BIA) metabolism in members of the higher plant order Ranunculales, which includes opium poppy ( Papaver somniferum ). PaNMT accepted a broad range of substrates with phenylalkylamine, tryptamine, β-carboline, tetrahydroisoquinoline, and BIA structural scaffolds, which is in contrast to the specificity for BIA substrates of NMT enzymes within the Ranunculales. PaNMT transcript levels were highest in young shoots of E. sinica , which corresponded to the location of NMT activity yielding (pseudo)ephedrine, N -methylcathinone, and N -methyl(pseudo)ephedrine, and with in planta accumulation of phenylalkylamines. Co-expression of recombinant genes encoding PaNMT and an ω-transaminase (PP2799) from Pseudomonas putida in Escherichia coli enabled the conversion of exogenous ( R )-phenylacetylcarbinol (PAC) and ( S )-PAC to ephedrine and pseudoephedrine, respectively. Our work further demonstrates the utility of plant biochemical genomics for the isolation of key enzymes that facilitate microbial engineering for the production of medicinally important metabolites.
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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".