Distinct Roles for Two CYP226 Family Cytochromes P450 in Abietane Diterpenoid Catabolism by <i>Burkholderia xenovorans</i> LB400
Bibliographic record
Abstract
The 80-kb dit cluster of Burkholderia xenovorans LB400 encodes the catabolism of abietane diterpenoids. This cluster includes ditQ and ditU, predicted to encode cytochromes P450 (P450s) belonging to the poorly characterized CYP226A subfamily. Using proteomics, we identified 16 dit-encoded proteins that were significantly more abundant in LB400 cells grown on dehydroabietic acid (DhA) or abietic acid (AbA) than in succinate-grown cells. A key difference in the catabolism of DhA and AbA lies in the differential expression of the P450s; DitU was detected only in the AbA-grown cells, whereas DitQ was expressed both during growth on DhA and during growth on AbA. Analyses of insertion mutants showed that ditQ was required for growth on DhA, ditU was required for growth on AbA, and neither gene was required for growth on the central intermediate, 7-oxo-DhA. In cell suspension assays, patterns of substrate removal and metabolite accumulation confirmed the role of DitU in AbA transformation and the role of DitQ in DhA transformation. Spectral assays revealed that DitQ binds both DhA (dissociation constant, 0.98 +/- 0.01 microM) and palustric acid. Finally, DitQ transformed DhA to 7-hydroxy-DhA in vitro. These results demonstrate the distinct roles of the P450s DitQ and DitU in the transformation of DhA and AbA, respectively, to 7-oxo-DhA in a convergent degradation pathway.
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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".