In vitro transduction of antimicrobial resistance genes into <i>Escherichia coli</i> isolates from backyard poultry in Mexico
Bibliographic record
Abstract
The transmission of multidrug-resistant pathogens and antimicrobial resistance genes is an emerging problem involving multiple factors (humans, domestic animals, wildlife). The aim of this study was to investigate the presence of Escherichia coli isolates with different antimicrobial resistance genes from backyard poultry and to demonstrate the in vitro transduction phenomenon of these genes between phages from migratory wild birds and poultry E. coli isolates. We collected 197 E. coli isolates from chickens, turkeys, and ducks in backyard production units (northern region of the State of Mexico). Isolates were resistant to ampicillin (80.7%), tetracycline (64.4%), carbenicillin (56.3%), and nalidixic acid and trimethoprim–sulfamethoxazole (both, 26.9%). Moreover, the genes blaTEM (56.3%), tetB (20.8%), tetA (19.2%), sulI (7.6%), sulII (10.1%), qnrA (9.6%), and qnrB (5.5%) were found. In vitro transduction using phages from migratory wild birds sampled in the wetland Chimaliapan (State of Mexico) was successfully achieved. It was possible to transduce qnrA, tetB, blaTEM, and sulII genes to E. coli isolates from poultry. This is the first report that describes the transduction of antimicrobial resistance genes from phages of migratory wild birds to poultry and suggests the possible transmission in backyard production units.
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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) | 0.000 | 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".