Oxidosqualene cyclases involved in the biosynthesis of triterpenoids in Quercus suber cork
Bibliographic record
Abstract
Cork is a water-impermeable, suberin-based material harboring lignin, (hemi)cellulose, and extractable small molecules (primarily triterpenoids). Extractables strongly influence the properties of suberin-based materials. Though these previous findings suggest a key role for triterpenoids in cork material quality, directly testing this idea is hindered in part because it is not known which genes control cork triterpenoid biosynthesis. Here, we used gas chromatography and mass spectrometry to determine that the majority (>85%) of non-polar extractables from cork were pentacyclic triterpenoids, primarily betulinic acid, friedelin, and hydroxy-friedelin. In other plants, triterpenoids are generated by oxidosqualene cyclases (OSCs). Accordingly, we mined Quercus suber EST libraries for OSC fragments to use in a RACE PCR-based approach and cloned three full-length OSC transcripts from cork (QsOSC1-3). Heterologous expression in Saccharomyces cerevisiae revealed that QsOSC1-3 respectively encoded enzymes with lupeol synthase, mixed α- and β-amyrin synthase, and mixed β-amyrin and friedelin synthase activities. These activities together account for the backbone structures of the major cork triterpenoids. Finally, we analyzed the sequences of QsOSC1-3 and other plant OSCs to identify residues associated with specific OSC activities, then combined this with analyses of Q. suber transcriptomic and genomic data to evaluate potential redundancies in cork triterpenoid biosynthesis.
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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 | 0.000 |
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".