Characterization of a C—C Bond Hydrolase from<i>Sphingomonas wittichii</i>RW1 with Novel Specificities towards Polychlorinated Biphenyl Metabolites
Bibliographic record
Abstract
Sphingomonas wittichii RW1 degrades chlorinated dibenzofurans and dibenzo-p-dioxins via meta cleavage. We used inverse PCR to amplify dxnB2, a gene encoding one of three meta-cleavage product (MCP) hydrolases identified in the organism that are homologues of BphD involved in biphenyl catabolism. Purified DxnB2 catalyzed the hydrolysis of 8-OH 2-hydroxy-6-oxo-6-phenylhexa-2,4-dienoate (HOPDA) approximately six times faster than for HOPDA at saturating substrate concentrations. Moreover, the specificity of DxnB2 for HOPDA (k(cat)/K(m) = 1.2 x 10(7) M(-1) s(-1)) was about half that of the BphDs of Burkholderia xenovorans LB400 and Rhodococcus globerulus P6, two potent polychlorinated biphenyl (PCB)-degrading strains. Interestingly, DxnB2 transformed 3-Cl and 4-OH HOPDAs, compounds that inhibit the BphDs and limit PCB degradation. DxnB2 had a higher specificity for 9-Cl HOPDA than for HOPDA but a lower specificity for 8-Cl HOPDA (k(cat)/K(m) = 1.7 x 10(6) M(-1) s(-1)), the chlorinated analog of 8-OH HOPDA produced during dibenzofuran catabolism. Phylogenetic analyses based on structure-guided sequence alignment revealed that DxnB2 belongs to a previously unrecognized class of MCP hydrolases, evolutionarily divergent from the BphDs although the physiological substrates of both enzyme types are HOPDAs. However, both classes of enzymes have mainly small hydrophobic residues lining the subsite that binds the C-6 phenyl of HOPDA, in contrast to the bulky hydrophobic residues (Phe106, Phe135, Trp150, and Phe197) found in the class II enzymes that prefer substrates possessing a C-6 alkyl. Thr196 and/or Asn203 appears to be an important determinant of specificity for DxnB2, potentially forming hydrogen bonds with the 8-OH substituent. This study demonstrates that the substrate specificities of evolutionarily divergent hydrolases may be useful for degrading mixtures of pollutants, such as PCBs.
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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) | 0.001 | 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".