Antibiotic-induced Recombination in <i>Escherichia coli</i> Requires the Formation of DNA Double-Strand Breaks
Bibliographic record
Abstract
Abstract Recombination is an essential process in bacterial drug resistance evolution. Fluoroquinolones, an important class of antibiotics, are known to stimulate recombination in Escherichia coli . When bacteria are exposed to antibiotics other than fluoroquinolones, including strong up-regulators of recombination pathways, there is no detectable change in the recombination level. Here we explore why fluoroquinolones, but not other antimicrobials, increase recombination rates. Fluoroquinolones, in contrast to other antibiotics, generate DNA double-strand breaks (DSBs). We tested whether other drugs that also cause double-strand breaks, such as mitomycin C and bleomycin, also affect bacterial recombination rates with consistent increases in recombination. A positive correlation between the number of DSBs and the recombination frequency was found. The manipulation of the level of DSBs directly impacted the recombination frequency. Our results highlight that only antibiotics that induce DNA double-strand breaks are more probable to increase genetic diversity via recombination. The stimulation of recombination by DSB-causing antimicrobials is an additional factor leading to the risk of antibiotic resistance evolution.
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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) | 0.002 | 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".