Comparative genomics of Enterococcus spp. isolated from bovine feces
Bibliographic record
Abstract
BACKGROUND: Enterococcus is ubiquitous in nature and is a commensal of both the bovine and human gastrointestinal (GI) tract. It is also associated with clinical infections in humans. Subtherapeutic administration of antibiotics to cattle selects for antibiotic resistant enterococci in the bovine GI tract. Antibiotic resistance genes (ARGs) may be present in enterococci following antibiotic use in cattle. If located on mobile genetic elements (MGEs) their dissemination between Enterococcus species and to pathogenic bacteria may be promoted, reducing the efficacy of antibiotics. RESULTS: We present a comparative genomic analysis of twenty-one Enterococcus spp. isolated from bovine feces including Enterococcus hirae (n = 10), Enterococcus faecium (n = 3), Enterococcus villorum (n = 2), Enterococcus casseliflavus (n = 2), Enterococcus faecalis (n = 1), Enterococcus durans (n = 1), Enterococcus gallinarum (n = 1) and Enterococcus thailandicus (n = 1). The analysis revealed E. faecium and E. faecalis from bovine feces share features with human clinical isolates, including virulence factors. The Tn917 transposon conferring macrolide-lincosamide-streptogramin B resistance was identified in both E. faecium and E. hirae, suggesting dissemination of ARGs on MGEs may occur in the bovine GI tract. An E. faecium isolate was also identified with two integrative conjugative elements (ICEs) belonging to the Tn916 family of ICE, Tn916 and Tn5801, both conferring tetracycline resistance. CONCLUSIONS: This study confirms the presence of enterococci in the bovine GI tract possessing ARGs on MGEs, but the predominant species in cattle, E. hirae is not commonly associated with infections in humans. Analysis using additional complete genomes of E. faecium from the NCBI database demonstrated differential clustering of commensal and clinical isolates, suggesting that these strains may be specifically adapted to their respective environments.
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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 | 0.001 |
| 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) | 0.001 | 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".