Poultry-associated nitrofurantoin-resistant and pre-resistant Escherichia coli clones are found in multiple countries and one-health compartments
Bibliographic record
Abstract
Escherichia coli is the most common cause of urinary tract infection (UTI) in humans. The nitrofuran-class antibacterial drug nitrofurantoin is a frequent UTI therapy, with resistance rarely observed. Here we show that nitrofurantoin resistant (NFT-R) E. coli are sometimes excreted by dogs fed a raw meat diet in the city of Bristol, United Kingdom, and that NFT-R and pre-resistant (one mutation away from NFT-R) E. coli can be found contaminating chicken meat sold for human consumption and chicken-based raw dog food in the same city. Using whole genome sequencing, we identified multiple NFT-R or pre-resistant E. coli clones spanning several phylogroups. These clones were dominated by isolates from poultry farms and poultry meat in Europe, Canada, the United States and Japan, and we identified instances where closely related NFT-R and pre-resistant isolates have colonised humans and caused UTIs. The origins of these poultry-associated NFT-R and pre-resistant E. coli clones are uncertain, but nitrofuran-class antibacterials (particularly furazolidone, furaltadone, and nitrofurazone) were used in poultry production during the 1970s and 80s, though this practice has been banned since the 1990s. It is possible, therefore, that this caused an initial selective pressure for the emergence of NFT-R and pre-resistant E. coli clones on poultry farms. Our findings have potentially important implications for domestic hygiene, particularly among people receiving nitrofurantoin therapy.
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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) | 0.002 | 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".