Genomic and Bioinformatic Insights into <i>Enterococcus faecalis</i> from Retail Meats in Nigeria
Bibliographic record
Abstract
Abstract Background Enterococcus faecalis (E. faecalis) is a commensal and opportunistic pathogen increasingly recognized for its antimicrobial resistance (AMR) and zoonotic potential. This study employs whole-genome sequencing (WGS) to characterize E. faecalis isolates from retail meat samples, focusing on antimicrobial resistance genes (ARGs), virulence determinants, mobile genetic elements, and phylogenomic relationships. Materials and Methods Fifty raw meat samples, including chicken (n=18), beef (n=17), and turkey (n=15), were collected from retail markets in Akungba-Akoko, Nigeria. E. faecalis isolates were identified using standard microbiological methods and subjected to antimicrobial susceptibility testing were further analysed using WGS. Results Ten E. faecalis isolates were recovered, with the highest prevalence in chicken (n=6), followed by beef (n=2) and turkey (n=2). All isolates were resistant to clindamycin, erythromycin, and tetracycline. Frequent ARGs included aac(6’)-aph(2’’) , ant(6)-Ia , lsa(A) , erm(B) , tet(M) , and tet(L) . Plasmid replicons rep9c and repUS43 showed ST-specific associations with ST477 and ST16, respectively. MGEs such as IS3 , IS6 , IS256 , and IS1380 co-localized with ARGs and virulence determinants. Phylogenomic analysis revealed two major lineages, with ST477 distributed across meat types and ST16 restricted to chicken. Comparative genomic analysis with publicly available African E. faecalis isolates revealed distinct clonal lineages and geographic clustering across the continent. Conclusion The co-occurrence of multidrug resistance, virulence factors, and MGEs in foodborne E. faecalis poses a public health concern due to the risk of horizontal gene transfer and zoonotic spread. These findings underscore the need for genomic surveillance and antimicrobial stewardship in food systems, particularly in low- and middle-income countries.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".