Evolution of Diterpene Metabolism: Sitka Spruce CYP720B4 Catalyzes Multiple Oxidations in Resin Acid Biosynthesis of Conifer Defense against Insects
Bibliographic record
Abstract
Diterpene resin acids (DRAs) are specialized (secondary) metabolites of the oleoresin defense of conifers produced by diterpene synthases and cytochrome P450s of the CYP720B family. The evolution of DRA metabolism shares common origins with the biosynthesis of ent-kaurenoic acid, which is highly conserved in general (primary) metabolism of gibberellin biosynthesis. Transcriptome mining in species of spruce (Picea) and pine (Pinus) revealed CYP720Bs of four distinct clades. We cloned a comprehensive set of 12 different Sitka spruce (Picea sitchensis) CYP720Bs as full-length cDNAs. Spatial expression profiles, methyl jasmonate induction, and transcript enrichment in terpenoid-producing resin ducts suggested a role of CYP720B4 in DRA biosynthesis. CYP720B4 was characterized as a multisubstrate, multifunctional enzyme by the formation of oxygenated diterpenoids in metabolically engineered yeast, yeast in vivo transformation of diterpene substrates, in vitro assays with CYP720B4 protein produced in Escherichia coli, and alteration of DRA profiles in RNA interference-suppressed spruce seedlings. CYP720B4 was active with 24 different diterpenoid substrates, catalyzing consecutive C-18 oxidations in the biosynthesis of an array of diterpene alcohols, aldehydes, and acids. CYP720B4 was most active in the formation of dehydroabietic acid, a compound associated with insect resistance of Sitka spruce. We identified patterns of convergent evolution of CYP720B4 in DRA metabolism and ent-kaurene oxidase CYP701 in gibberellin metabolism and revealed differences in the evolution of specialized and general diterpene metabolism in a gymnosperm. The genomic and functional characterization of the gymnosperm CYP720B family highlights that the evolution of specialized metabolism involves substantial diversification relative to conserved, general metabolism.
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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 | 0.001 |
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".