Prevalence and Genetic Basis of Antimicrobial Resistance in Non-aureus Staphylococci Isolated from Canadian Dairy Herds
Bibliographic record
Abstract
Emergence and spread of antimicrobial resistance is a major concern for the dairy industry worldwide. Objectives were to determine: 1) phenotypic and genotypic prevalence of drug-specific resistance for 25 species of non-aureus staphylococci, and 2) associations between presence of resistance determinants and antimicrobial resistance. Broth micro-dilution was used to determine resistance profiles for 1,702 isolates from 89 dairy herds. Additionally, 405 isolates were sequenced to screen for resistance determinants. Antimicrobial resistance was clearly species-dependent. Resistance to quinupristin/dalfopristin was common in Staphylococcus gallinarum (prevalence of 98%), whereas S. cohnii and S. arlettae were frequently resistant to erythromycin (prevalence of 63 and 100%, respectively). Prevalence of resistance was 10% against beta-lactams and tetracyclines. In contrast, resistance to antimicrobials critically important for human medicine, namely vancomycin, fluoroquinolones, linezolid and daptomycin, was uncommon (<1%). Genes encoding multidrug-resistance efflux pumps and resistance-associated residues in deducted amino acid sequences of the folP gene were the most frequent mechanisms of resistance, regardless of species. The estimated prevalence of the mecA gene was 17% for S. epidermidis. Several genes, including blaZ, mecA, fexA, erm, mphC, msrA and tet were associated with drug-specific resistance, whereas other elements were not. There were specific residues in gyrB for all isolates of species intrinsically resistant to novobiocin. This study provided consensus protein sequences of key elements previously associated with resistance for 25 species of non-aureus staphylococci from dairy cattle. These results will be important for evaluating effects of interventions in antimicrobial use in Canadian dairy herds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 teacher head, 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".