Identification of a Serine Hydrolase as a Key Determinant in the Microbial Degradation of Polychlorinated Biphenyls
Bibliographic record
Abstract
The ability of 2-hydroxy-6-oxo-6-phenylhexa-2,4-dienoate (HOPDA) hydrolase (BphD) of Burkholderia cepacia LB400 to hydrolyze polychlorinated biphenyl (PCB) metabolites was assessed by determining its specificity for monochlorinated HOPDAs. The relative specificities of BphD for HOPDAs bearing chlorine substituents on the phenyl moiety were 0.28, 0.38, and 1.1 for 8-Cl, 9-Cl, and 10-Cl HOPDA, respectively, versus HOPDA (100 mm phosphate, pH 7.5, 25 degrees C). In contrast, HOPDAs bearing chlorine substituents on the dienoate moiety were poor substrates for BphD, which hydrolyzed 3-Cl, 4-Cl, and 5-Cl HOPDA at relative maximal rates of 2.1 x 10(-3), 1.4 x 10(-4), and 0.36, respectively, versus HOPDA. The enzymatic transformation of 3-, 5-, 8-, 9-, and 10-Cl HOPDAs yielded stoichiometric quantities of the corresponding benzoate, indicating that BphD catalyzes the hydrolysis of these HOPDAs in the same manner as unchlorinated HOPDA. HOPDAs also underwent a nonenzymatic transformation to products that included acetophenone. In the case of 4-Cl HOPDA, this transformation proceeded via the formation of 4-OH HOPDA (t(12) = 2.8 h; 100 mm phosphate, pH 7.5, 25 degrees C). 3-Cl HOPDA (t(12) = 504 h) was almost 3 times more stable than 4-OH HOPDA. Finally, 3-Cl, 4-Cl and 4-OH HOPDAs competitively inhibited the BphD-catalyzed hydrolysis of HOPDA (K(ic) values of 0.57 +/- 0. 04, 3.6 +/- 0.2, and 0.95 +/- 0.04 microm, respectively). These results explain the accumulation of HOPDAs and chloroacetophenones in the microbial degradation of certain PCB congeners. More significantly, they indicate that in the degradation of PCB mixtures, BphD would be inhibited, thereby slowing the mineralization of all congeners. BphD is thus a key determinant in the aerobic microbial degradation of 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) | 0.000 | 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".