Expression of bacterial biphenyl‐chlorobiphenyl dioxygenase genes in tobacco plants
Bibliographic record
Abstract
Optimized plant-microbe bioremediation processes in which the plant initiates the metabolism of xenobiotics and releases the metabolites in the rhizosphere to be further degraded by the rhizobacteria is a promising alternative to restore contaminated sites in situ. However, such processes require that plants produce the metabolites that bacteria can readily oxidize. The biphenyl dioxygenase is the first enzyme of the bacterial catabolic pathway involved in the degradation of polychlorinated biphenyls. This enzyme consists of three components: the two sub-unit oxygenase (BphAE) containing a Rieske-type iron-sulfur cluster and a mononuclear iron center, the Rieske-type ferredoxin (BphF), and the FAD-containing ferredoxin reductase (BphG). In this work, based on analyses with Nicotiana benthamiana plants transiently expressing the biphenyl dioxygenase genes from Burkholderia xenovorans LB400 and transgenic Nicotiana tabacum plants transformed with each of these four genes, we have shown that each of the three biphenyl dioxygenase components can be produced individually as active protein in tobacco plants. Therefore, when BphAE, BphF, and BphG purified from plant were used to catalyze the oxygenation of 4-chlorobiphenyl, detectable amounts of 2,3-dihydro-2, 3-dihydroxy-4'-chlorobiphenyl were produced. This suggests that creating transgenic plants expressing simultaneously all four genes required to produce active biphenyl dioxygenase is feasible.
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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 | 0.001 |
| 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".