The ionophore resistance genes <i>narA</i> and <i>narB</i> are geographically widespread and linked to resistance to medically important antibiotics
Bibliographic record
Abstract
ABSTRACT Ionophores are a class of antibiotics used widely in animal production as anti-coccidials and for growth promotion. Since ionophores are not used in human medicine, it has largely been assumed that they do not contribute to medically important antimicrobial resistance (AMR). Nonetheless, there is increasing concern that ionophore usage could co-select for clinically relevant AMR, since the ionophore resistance genes narA and narB have been found in linkage with multiple AMR genes. We investigated the global distribution and AMR linkage of narA and narB using publicly available data. These ionophore resistance genes can be found worldwide, with >2,400 narAB -bearing isolates reported from 51 countries. Isolates were derived from a range of host species, including poultry, cattle, and humans. narAB was linked with an average of over 10 resistance determinants for AMR, including many medically important antibiotics. These observations indicate that we cannot assume that ionophore use is risk-free, with clear potential for co-selection for clinically relevant AMR. IMPORTANCE Ionophores are a type of antibiotic used to promote growth in cattle and pigs and to treat parasitic infections in poultry. It has been assumed that ionophore use in animals does not pose a risk for humans. However, growing evidence suggests that ionophore use may select for medically relevant antibiotic resistance. Using analyses of public data, we found that ionophore resistance is widespread and that it is usually linked to resistance genes for medically relevant drugs. There is thus clear potential for ionophore use to impact the presence of antibiotic resistance genes in the food supply.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 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".