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Record W4414248798 · doi:10.3390/antibiotics14090931

Phenotypic and Molecular Study of Multidrug-Resistant Escherichia coli Isolates Expressing Diverse Resistance and Virulence Genes from Broilers in Tunisia

2025· article· en· W4414248798 on OpenAlexafffund
Ghassan Tayh, Fatma Nsibi, Khaled M. Abdallah, Omar Abbes, Ismaı̈l Fliss, Lilia Messadi

Bibliographic record

VenueAntibiotics · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsUniversité Laval
FundersInternational Development Research Centre
KeywordsVirulenceGeneColistinAntibiotic resistanceEscherichia coliPhenotypeStreptomycinTrimethoprimPlasmid

Abstract

fetched live from OpenAlex

This study investigated the molecular and phenotypic characteristics of antimicrobial resistance in Escherichia coli isolates recovered from the ceca of healthy broilers in Tunisia. A total of 111 E. coli isolates were obtained from chicken samples collected at slaughterhouses and cultured on cefotaxime-supplemented MacConkey agar. All isolates exhibited a multidrug-resistant (MDR) phenotype, and 72.1% were confirmed as extended-spectrum β-lactamase (ESBL) producers. The most frequent β-lactamase gene was blaCTX-M-G1, followed by blaTEM and blaSHV. Carbapenem resistance genes (blaOXA-48 and blaIMP) were detected in 12.6% and 6.3% of isolates, respectively, while six isolates harbored the colistin resistance gene mcr-1. Among the tested virulence genes, fimH, traT, and iutA were the most prevalent, detected in over 70% of isolates. Class 1 integrons were present in 83% of isolates, and class 2 integrons in 39.6%, with gene cassettes encoding resistance to trimethoprim (dfrA) and streptomycin (aadA). These findings highlight the widespread presence of MDR and ESBL-producing E. coli strains with virulence traits and integrons in poultry, underscoring the risk of transmission to humans. This study provides essential data supporting the implementation of integrated surveillance strategies in line with the One Health approach.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.247
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes2
Has abstractyes

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