Enantioselective microbial synthesis of the indigenous natural product (−)-α-bisabolol by a sesquiterpene synthase from chamomile (<i>Matricaria recutita</i>)
Bibliographic record
Abstract
(-)-α-Bisabolol, a sesquiterpene alcohol, is a major ingredient in the essential oil of chamomile (Matricaria recutita) and is used in many health products. The current supply of (-)-α-bisabolol is mainly dependent on the Brazilian candeia tree (Eremanthus erythropappus) by distillation or by chemical synthesis. However, the distillation method using the candeia tree is not sustainable, and chemical synthesis suffers from impurities arising from undesirable α-bisabolol isomers. Therefore enzymatic synthesis of (-)-α-bisabolol is a viable alternative. In the present study, a cDNA encoding (-)-α-bisabolol synthase (MrBBS) was identified from chamomile and used for enantioselective (-)-α-bisabolol synthesis in yeast. Chamomile MrBBS was identified by Illumina and 454 sequencing, followed by activity screening in yeast. When MrBBS was expressed in yeast, 8 mg of α-bisabolol was synthesized de novo per litre of culture. The structure of purified α-bisabolol was elucidated as (S,S)-α-bisabolol [or (-)-α-bisabolol]. Although MrBBS possesses a putative chloroplast-targeting peptide, it was localized in the cytosol, and a deletion of its N-terminal 23 amino acids significantly reduced its stability and activity. Recombinant MrBBS showed kinetic properties comparable with those of other sesquiterpene synthases. These data provide compelling evidence that chamomile MrBBS synthesizes enantiopure (-)-α-bisabolol as a single sesquiterpene product, opening a biotechnological opportunity to produce (-)-α-bisabolol.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 | 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 teacher head, 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".