Polycyclic aromatic hydrocarbon degrading gene islands in five pyrene-degrading<i>Mycobacterium</i>isolates from different geographic locations
Bibliographic record
Abstract
Mycobacterium sp. strain KMS utilizes pyrene, a high-molecular weight polycyclic aromatic hydrocarbon (PAH), as a sole carbon source. Bioinformatic analysis of the genome of isolate KMS predicted 25 genes with the potential to encode 17 pyrene-induced proteins identified by proteomics; these genes were clustered on both the chromosome and a circular plasmid. RT-PCR analysis of total RNA isolated from KMS cells grown with or without pyrene showed that the presence of pyrene increased the transcript accumulation of 20 of the predicted chromosome- and plasmid-located genes encoding pyrene-induced proteins. The transcribed genes from both the chromosome and a circular plasmid were within larger regions containing genes required for PAH degradation constituting PAH-degrading gene islands. Genes encoding integrases and transposases were found within and outside the PAH-degrading gene islands. The lower GC content of the genes within the gene island (61%-64%) compared with the average genome content (68%) suggested that these mycobacteria initially acquired these genes by horizontal gene transfer. Synteny was detected for the PAH-degrading islands in the genomes of two additional Mycobacterium isolates from the same PAH-polluted site and of two other pyrene-degrading Mycobacterium from different sites in the United States of America. Consequently, the gene islands have been conserved from a common ancestral strain.
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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".