<i>tfdA</i> -Like Genes in 2,4-Dichlorophenoxyacetic Acid-Degrading Bacteria Belonging to the <i>Bradyrhizobium-Agromonas-Nitrobacter-Afipia</i> Cluster in α- <i>Proteobacteria</i>
Bibliographic record
Abstract
The 2,4-dichlorophenoxyacetate (2,4-D)/alpha-ketoglutarate dioxygenase gene (tfdA) homolog designated tfdAalpha was cloned and characterized from 2,4-D-degrading bacterial strain RD5-C2. This Japanese upland soil isolate belongs to the Bradyrhizobium-Agromonas-Nitrobacter-Afipia cluster in the alpha subdivision of the class Proteobacteria on the basis of its 16S ribosomal DNA sequence. Sequence analysis showed 56 to 60% identity of tfdAalpha to representative tfdA genes. A MalE-TfdAalpha fusion protein expressed in Escherichia coli exhibited about 10 times greater activity for phenoxyacetate than 2,4-D in an alpha-ketoglutarate- and Fe(II)-dependent reaction. The deduced amino acid sequence of TfdAalpha revealed a conserved His-X-Asp-X(146)-His-X(14)-Arg motif characteristic of the active site of group II alpha-ketoglutarate-dependent dioxygenases. The tfdAalpha genes were also detected in 2,4-D-degrading alpha-Proteobacteria previously isolated from pristine environments in Hawaii and in Saskatchewan, Canada (Y. Kamagata, R. R. Fulthorpe, K. Tamura, H. Takami, L. J. Forney, and J. M. Tiedje, Appl. Environ. Microbiol. 63:2266-2272, 1997). These findings indicate that the tfdA genes in beta- and gamma-Proteobacteria and the tfdAalpha genes in alpha-Proteobacteria arose by divergent evolution from a common ancestor.
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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".