Genomic characterization of pathotype diversity and drug resistance among generic <i>Escherichia coli</i> isolated from broiler chickens in Canada
Bibliographic record
Abstract
Escherichia coli is a Gram-negative bacterium that is ubiquitous in animals and humans, with some strains capable of causing disease. The aim of this study was to perform a comparative genomic analysis of 2732 generic E. coli isolates that were recovered from poultry samples collected from six regions in Canada as part of the National Microbiological Baseline study in Broiler Chicken. Isolates were subjected to whole genome sequencing and a subset (1122/2732) were tested for phenotypic resistance to 15 antimicrobials. These E. coli isolates were highly diverse, representing 376 serotypes, 236 sequence types and 21 pathotypes, of which 19 were hybrid pathotypes. A high concordance (>85%) between resistance phenotype and the presence of antimicrobial resistance genes and point mutations (resistance determinants) was observed for 13/15 antimicrobials. Over 95% of the β-lactam, fluoroquinolone, and phenicol resistance genes were predicted to be plasmid-borne. The number of resistance determinants per genome was highest in Quebec, while resistance genes associated with β-lactam resistance were more frequently detected in isolates from British Columbia. Generic E. coli in Canadian poultry are highly diverse, can carry pathotype-associated virulence factors and resistance determinants of clinical significance with a risk of emerging into pathogenic strains.
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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 | 0.002 |
| 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".