Catalytic Plasticity of Germacrene A Oxidase Underlies Sesquiterpene Lactone Diversification
Bibliographic record
Abstract
Adaptive evolution of enzymes benefits from catalytic promiscuity. Sesquiterpene lactones (STLs) have diverged extensively in the Asteraceae, and studies of the enzymes for two representative STLs, costunolide and artemisinin, could provide an insight into the adaptive evolution of enzymes. Costunolide appeared early in Asteraceae evolution and is widespread, whereas artemisinin is a unique STL appearing in a single Asteraceae species, Artemisia annua. Therefore, costunolide is a ubiquitous STL, while artemisinin is a specialized one. In costunolide biosynthesis, germacrene A oxidase (GAO) synthesizes germacrene A acid from germacrene A. Similarly, in artemisinin biosynthesis, amorphadiene oxidase (AMO) synthesizes artemisinic acid from amorphadiene. GAO promiscuity is suggested to drive the diversification of STLs. To examine the degree of GAO promiscuity, we expressed six sesquiterpene synthases from cotton (Gossypium arboretum), goldenrod (Solidago canadensis), valerian (Valeriana officinalis), agarwood (Aquilaria crassna), tobacco (Nicotiana tabacum), and orange (Citrus sinensis) in yeast to produce seven distinct sesquiterpene substrates (germacrene D, 5-epi-aristolochene, valencene, δ-cadinene, α- and δ-guaienes, and valerenadiene). GAO or AMO was coexpressed in these yeasts to evaluate the promiscuities of GAO and AMO. Remarkably, all sesquiterpenes tested were oxidized to sesquiterpene acids by GAO, but negligible activities were found from AMO. Hence, GAO apparently has catalytic potential to evolve into different enzymes for synthesizing distinct STLs, while the recently specialized AMO demonstrates rigid substrate specificity. Mutant GAOs implanted with active site residues of AMO showed substantially reduced stability, but their per enzyme activities to produce artemisinic acid increased by 9-fold. Collectively, these results suggest promiscuous GAOs can be developed as novel catalysts for synthesizing unique sesquiterpene derivatives.
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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".