Prevalence of antibiotic resistance genes in bacterial communities associated with <i>Cladophora glomerata</i> mats along the nearshore of Lake Ontario
Bibliographic record
Abstract
The alga Cladophora glomerata can erupt in nuisance blooms throughout the lower Great Lakes. Since bacterial abundance increases with the emergence and decay of Cladophora, we investigated the prevalence of antibiotic resistance (ABR) in Cladophora-associated bacterial communities up-gradient and down-gradient from a large sewage treatment plant (STP) on Lake Ontario. Although STPs are well-known sources of ABR, we also expected detectable ABR from up-gradient wetland communities, since they receive surface run-off from urban and agricultural sources. Statistically significant differences in aquatic bacterial abundance and ABR were found between down-gradient beach samples and up-gradient coastal wetland samples (ANOVA, Holm-Sidak test, p < 0.05). Decaying and free-floating Cladophora sampled near the STP had the highest bacterial densities overall, including on ampicillin- and vancomycin-treated plates. However, quantitative polymerase chain reaction analysis of the ABR genes ampC, tetA, tetB, and vanA from environmental communities showed a different pattern. Some of the highest ABR gene levels occurred at the 2 coastal wetland sites (vanA). Overall, bacterial ABR profiles from environmental samples were distinguishable between living and decaying Cladophora, inferring that Cladophora may control bacterial ABR depending on its life-cycle stage. Our results also show how spatially and temporally dynamic ABR is in nearshore aquatic bacteria, which warrants further research.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".