Has the Bacterial Biphenyl Catabolic Pathway Evolved Primarily To Degrade Biphenyl? The Diphenylmethane Case
Bibliographic record
Abstract
In this work, we have compared the ability of Pandoraea pnomenusa B356 and of Burkholderia xenovorans LB400 to metabolize diphenylmethane and benzophenone, two biphenyl analogs in which the phenyl rings are bonded to a single carbon. Both chemicals are of environmental concern. P. pnomenusa B356 grew well on diphenylmethane. On the basis of growth kinetics analyses, diphenylmethane and biphenyl were shown to induce the same catabolic pathway. The profile of metabolites produced during growth of strain B356 on diphenylmethane was the same as the one produced by isolated enzymes of the biphenyl catabolic pathway acting individually or in coupled reactions. The biphenyl dioxygenase oxidizes diphenylmethane to 3-benzylcyclohexa-3,5-diene-1,2-diol very efficiently, and ultimately this metabolite is transformed to phenylacetic acid, which is further metabolized by a lower pathway. Strain B356 was also able to cometabolize benzophenone through its biphenyl pathway, although in this case, this substrate was unable to induce the biphenyl catabolic pathway and the degradation was incomplete, with accumulation of 2-hydroxy-6,7-dioxo-7-phenylheptanoic acid. Unlike strain B356, B. xenovorans LB400 did not grow on diphenylmethane. Its biphenyl pathway enzymes metabolized diphenylmethane, but they poorly metabolize benzophenone. The fact that the biphenyl catabolic pathway of strain B356 metabolized diphenylmethane and benzophenone more efficiently than that of strain LB400 brings us to postulate that in strain B356, this pathway evolved divergently to serve other functions not related to biphenyl degradation.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".