The Genome of <i>Polaromonas</i> sp. Strain JS666: Insights into the Evolution of a Hydrocarbon- and Xenobiotic-Degrading Bacterium, and Features of Relevance to Biotechnology
Bibliographic record
Abstract
Polaromonas sp. strain JS666 can grow on cis-1,2-dichloroethene (cDCE) as a sole carbon and energy source and may be useful for bioremediation of chlorinated solvent-contaminated sites. Analysis of the genome sequence of JS666 (5.9 Mb) shows a bacterium well adapted to pollution that carries many genes likely to be involved in hydrocarbon and xenobiotic catabolism and metal resistance. Clusters of genes coding for haloalkane, haloalkanoate, n-alkane, alicyclic acid, cyclic alcohol, and aromatic catabolism were analyzed in detail, and growth on acetate, catechol, chloroacetate, cyclohexane carboxylate, cyclohexanol, ferulate, heptane, 3-hydroxybenzoate, hydroxyquinol, gentisate, octane, protocatechuate, and salicylate was confirmed experimentally. Strain JS666 also harbors diverse putative mobile genetic elements, including retrons, inteins, a miniature inverted-repeat transposable element, insertion sequence transposases from 14 families, eight genomic islands, a Mu family bacteriophage, and two large (338- and 360-kb) plasmids. Both plasmids are likely to be self-transferable and carry genes for alkane, alcohol, aromatic, and haloacid metabolism. Overall, the JS666 genome sequence provides insights into the evolution of pollutant-degrading bacteria and provides a toolbox of catabolic genes with utility for biotechnology.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".