A Longitudinal Study of Antimicrobial Resistance in <i>Enterococcus</i> spp. Isolated from a Beef Processing Plant and Retail Ground Beef
Bibliographic record
Abstract
ABSTRACT Antimicrobial use in food-producing animals has come under increasing scrutiny due to its potential association with antimicrobial resistance (AMR). Monitoring of AMR in indicator microorganisms such as Enterococcus spp. in meat production facilities and retail meat products can provide important information on the dynamics and prevalence of AMR in these environments. In this study, swabs or samples were obtained from various locations in a commercial beef packing operation (n = 600 total) and from retail ground beef (n = 60) over a 19-month period. All samples/swabs were enriched for Enterococcus spp. and suspected enterococci isolates were identified using species-specific PCR primers. Enterococcus faecalis was the most frequently isolated species followed by Enterococcus hirae, which was found mostly on hides and ground beef. Enterococcus faecium (n = 9) and E . faecalis (n = 120) isolates were further characterized for antimicrobial resistance and resistant genes due to the clinical significance of these species. Twenty-one unique AMR profiles were identified, with 90% of isolates resistant to at least two antimicrobials, and two that were resistant to nine antimicrobials. Tetracycline resistance was observed most often in E . faecalis (28.8%) and was likely mediated by tet (M). Genomic analysis of selected E . faecalis and E . faecium isolates revealed that many of the isolates in this study clustered with other publicly available genomes from ground beef, suggesting that these strains are well adapted to the beef packaging environment. IMPORTANCE Antimicrobial resistance (AMR) is a serious challenge facing the agricultural industry. Understanding the flow of antimicrobial resistant-bacteria through the beef fabrication process and into ground beef is an important step in identifying intervention points for reducing AMR. In this study we used enterococci as indicator bacteria for monitoring AMR in a commercial beef packaging facility and in retail ground beef over a 19-month period. Although washing of carcasses post-hide removal reduced the isolation frequency of Enterococcus spp., a number of antimicrobial resistant- Enterococcus faecalis isolates were recovered from ground beef produced in the packaging plant. Genome analysis showed that several E . faecalis isolates were genetically similar to publicly available isolates recovered from retail ground beef in the United States.
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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 | 0.001 | 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 | 0.000 |
| 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".