Biphenyl Modulates the Expression and Function of Respiratory Oxidases in the Polychlorinated-Biphenyls Degrader Pseudomonas pseudoalcaligenes KF707
Bibliographic record
Abstract
Pseudomonas pseudoalcaligenes KF707 is a soil bacterium which is known for its capacity to aerobically degrade harmful organic compounds such as polychlorinated biphenyls (PCBs) using biphenyl as co-metabolite. Here we provide the first genetic and functional analysis of the KF707 respiratory terminal oxidases in cells grown with two different carbon sources: glucose and biphenyl. We identified five terminal oxidases in KF707: two c(c)aa3 type oxidases (Caa3 and Ccaa3), two cbb3 type oxidases (Cbb31 and Cbb32) and one bd type cyanide-insensitive quinol oxidase (CIO). While the activity and expression of both Cbb31 and Cbb32 oxidases was prevalent in glucose grown cells as compared to the other oxidases, the activity and expression of the Caa3 oxidase increased considerably only when biphenyl was used as carbon source in contrast to the Cbb32 oxidase which was repressed. Further, the respiratory activity and expression of CIO was up-regulated in a Cbb31 deletion strain as compared to W.T. whereas the CIO up-regulation was not present in Cbb32 and C(c)aa3 deletion mutants. These results, together, reveal that both function and expression of cbb3 and caa3 type oxidases in KF707 are modulated by biphenyl which is the co-metabolite needed for the activation of the PCBs-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".