Comparative metagenomics reveals limited differences in antimicrobial resistance gene abundance across conventional and natural livestock production systems
Bibliographic record
Abstract
The livestock industry has been a source of concern in terms of antimicrobial resistance (AMR) development and spread, especially from a One Health perspective. Raising livestock without antimicrobials, so called natural (NAT) production, is an increasingly popular practice. This study used metagenomics to compare this practice to conventional (CONV) antimicrobial use (AMU) on the microbiome and resistome in the feces of beef cattle and swine and the cecal contents of broiler chickens. In cattle, Bacteroidetes, Euryarchaeota, and Spirochaetes were more abundant ( q < 0.01) in CONV than NAT systems, with no differences ( q > 0.05) in bacterial profiles in either swine or chickens. Classes of antimicrobial resistant genes (ARG) were not impacted regardless of AMU in any of the livestock species. However, many tetracycline resistance genes were more abundant in CONV as compared to NAT swine ( q < 0.05), but this difference was not observed in cattle or chickens. This study confirmed that elimination of AMU does not necessarily result in an immediate decline in the abundance or diversity of ARGs within a single livestock production cycle.
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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 | 0.001 |
| 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".