Mutation frequency of <i>Escherichia coli</i> isolated from river water: potential role in the development of antimicrobial resistance
Bibliographic record
Abstract
Bacteria acquire genetic variations that help them to adapt to stressful environmental conditions, and these changes may be associated with the development of antimicrobial resistance. In this study, we investigated the mutation frequencies of 270 isolates of Escherichia coli from river water, which represents a relatively unstressful environment. As we predicted, mutation frequencies of the E. coli isolates ranged from <1 × 10−11 to 6.3 × 10−8 (median, 1.7 × 10−9), and a strong mutator (≥ 4 × 10−7) was not detected. To better understand the role of mutation frequency in the development of antimicrobial resistance, we assessed antimicrobial sensitivity after exposure of the E. coli isolates to subinhibitory concentrations of ciprofloxacin, as a surrogate for stress. We found that antimicrobial resistance increased in bacteria with a low mutation frequency after exposure, and the relative increase in antimicrobial resistance generally increased, depending on the mutation frequency. Thus, mutation frequency may contribute to the development of antimicrobial resistance of bacteria in natural environments.
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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 | 0.000 | 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 | 0.000 |
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".