In silico genomic insights into bacteriophages infecting ESBL-producing Escherichia coli from human, animal, and environmental sources
Bibliographic record
Abstract
Abstract Background The emergence of antimicrobial resistance (AMR) in Escherichia coli , particularly extended-spectrum beta-lactamase-producing E. coli (ESBL-EC), is a global public health concern. Bacteriophages (phages) play a significant role in bacterial evolution and the spread of antibiotic resistance genes (ARGs). This study investigates prophages integrated within ESBL-EC genomes to assess their diversity, gene content, and potential contributions to ESBL-EC persistence across human, animal, and environmental reservoirs. Between May and December 2020, a cross-sectional study was conducted in Abuja and Lagos, collecting 448 stool, cecal, and environmental samples from abattoir workers, slaughtered cattle, and the abattoir environment. ESBL-EC genomes from these samples, obtained in an earlier study, were analyzed for phage regions using PHASTER. Intact prophages were analyzed in silico using computational tools to detect ARGs, ESBL genes, virulence factors, and heavy metal resistance. Their genomic relationships were examined with statistical significance of p < 0.05. Results Out of 448 s amples, ESBL-EC prevalence was 21.7% (97/448). Among 97 ESBL-EC isolates, 646 prophage regions were detected, with 30% (194/646) classified as intact phages. Among the 158 phages with genus assignments, Punavirus was the most prevalent (60.1%). Escherichia was the most frequent predicted host (308/646), particularly in cattle ( n = 143) and human ( n = 124) sources. Among ESBL-EC genomes, 83.5% (81/97) with intact phages carried phage-associated ARGs, 76.3% (74/97) carried phage-associated ESBL genes, 18.6% (18/97) harbored phage-associated virulence factors, 15.5% (15/97) contained phage-associated plasmids, and 10.3% (10/97) had heavy metal resistance. The most prevalent phage-associated ARGs detected were qnrS1 (73/81) and bla CTX-M-15 (72/81) . Two isolates recovered from abattoir workers carried two phage-like plasmids, each harboring either tet(A) or bla CTX-M-55 gene. The predominant phage lifestyles were temperate ( n = 182), mainly in the Peduoviridae family, and lytic ( n = 12) in the Punavirus genus. Conclusion This is the first study in Nigeria to characterize phages in ESBL-EC isolates at the One Health interface. The presence of intact phages in humans, animals, and the environment underscores the complex interactions shaping phage ecology. The discovery of ARGs, virulence genes, and heavy metal resistance within prophages suggests a potential role in AMR dissemination. Future research should focus on elucidating mechanisms of ARG transfer mediated by phages in One Health settings.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".