Integron Gene Cassettes and Degradation of Compounds Associated with Industrial Waste: The Case of the Sydney Tar Ponds
Bibliographic record
Abstract
Integrons are genetic platforms that accelerate lateral gene transfer (LGT) among bacteria. They were first detected on plasmids bearing single and multiple drug resistance determinants in human pathogens, and it is abundantly clear that integrons have played a major role in the evolution of this public health menace. Similar genetic elements can be found in nonpathogenic environmental bacteria and in metagenomic environmental DNA samples, and it is reasonable to suppose that integrons have facilitated microbial adaptation through LGT in niches outside infectious disease wards. Here we show that a heavily impacted estuary, exposed for almost a century to products of coal and steel industries, has developed a rich and unique cassette metagenome, containing genes likely to aid in the catabolism of compounds associated with industrial waste found there. In addition, we report that the most abundant cassette recovered in this study is one that encodes a putative LysR protein. This autoregulatory transcriptional regulator is known to activate transcription of linked target genes or unlinked regulons encoding diverse functions including chlorocatechol and dichlorophenol catabolism. Finally, only class 1 integrase genes were amplified in this study despite using different primer sets, and it may be that the cassettes present in the Tar Ponds will prove to be associated with class 1 integrase genes. Nevertheless, our cassette library provides a snapshot of a complex evolutionary process involving integron-meditated LGT likely to be important in natural bioremediation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".