Molecular Characterization of Plasmid-Mediated Fluoroquinolone Resistance Genes (qnr, oqxAB, aac(6′)-Ib-cr, qepA) in Avian Pathogenic Escherichia coli from Broiler Flocks with Colibacillosis in Northern Iran

Introduction

Colibacillosis, caused by avian pathogenic Escherichia coli (APEC), is one of the most impactful bacterial problems in modern poultry production. It drives mortality, carcass condemnation, poor weight gain, and feed efficiency, as well as sustained treatment costs that erode margins in broiler operations (1, 2). Beyond economics, APEC and the mobile resistance elements it can carry raise clear One Health concerns because extraintestinal Escherichia coli lineages and their plasmids may circulate among birds, farms, and people who work with poultry or handle poultry products (3, 4).

Over the last two decades, fluoroquinolones have been widely used in poultry, sometimes for both metaphylaxis and treatment. That use has created strong selection pressure and has been accompanied by higher rates of non-susceptibility in Escherichia coli recovered from broilers and other birds across several regions (5, 6). Surveys from commercial flocks, retail meat, and wildlife that interface with poultry production repeatedly document this trend, indicating that resistance is not confined to a single point in the production cycle (7, 8). Although classical quinolone resistance is driven by chromosomal mutations in the quinolone resistance-determining regions of gyrA/gyrB and parC/parE, these mutations alone do not explain the speed or breadth of spread seen in poultry systems (9-11).

Plasmid-mediated quinolone resistance (PMQR) fills that gap. PMQR includes (i) target protection proteins encoded by qnr alleles (qnrA, qnrB, qnrS) that shield DNA gyrase and topoisomerase IV, (ii) the aminoglycoside acetyltransferase variant aac(6′)-Ib-cr that partially inactivates ciprofloxacin and norfloxacin, and (iii) efflux determinants such as qepA (MFS) and oqxAB (RND) that reduce intracellular drug levels (12-14). On their own, these mechanisms often confer modest increases in MICs but facilitate stepwise selection of high-level chromosomal resistance and frequently travel with β-lactamases on conjugative plasmids (15). Poultry studies from multiple regions report these determinants alone and in combination, often on epidemic plasmid backbones (16-21). Consistent with this breadth of evidence, Iranian broiler data further underscore the local relevance of PMQR within national production systems (22-24).

Mazandaran Province in northern Iran hosts a dense, economically important broiler industry yet remains underrepresented in integrated assessments of the main PMQR classes within clinical colibacillosis. To inform stewardship and surveillance, we conducted a regional molecular investigation of APEC isolates from broiler flocks with necropsy-supported diagnoses of colibacillosis in Mazandaran. This study aimed to characterize, within a single study framework, the prevalence and distribution of target-protection genes (qnrA, qnrB, qnrS) along with the principal efflux and drug-modifying determinants (oqxAB, qepA, aac(6′)-Ib-cr), using sequencing confirmation of representative amplicons for specificity. We interpret our findings in the context of the poultry literature from Asia, Europe, and beyond, and highlight practical implications for Iranian broiler production and regional One Health priorities.

Materials and Methods

Study design and sampling strategy

This molecular study was conducted in Mazandaran Province, northern Iran, from 2023 to 2024. Mazandaran was selected because it is a major broiler-producing region with frequent veterinary reports of colibacillosis, making it an appropriate setting for baseline surveillance of plasmid-mediated fluoroquinolone resistance (PMQR) in Escherichia coli (25).

Consecutive, non-duplicate diagnostic submissions were obtained from commercial broiler farms where field veterinarians observed clinical signs and necropsy lesions consistent with colibacillosis. A "suspect case" was defined as a flock with increased mortality and typical gross lesions at necropsy, including fibrinous pericarditis. From 106 suspect farm submissions (one per farm), pericardial exudate and sterile swabs of fibrinous pericarditis lesions were aseptically collected at necropsy, placed in transport medium, and processed the same day under biosafety level-2 conditions. To minimize clonality bias, a single Escherichia coli isolate per submission was advanced to downstream analyses. Planning targeted estimation of a single proportion (PMQR carriage) with 95% confidence. Assuming an anticipated prevalence of 30–60% and using the conservative worst-case scenario (p=0.50), ~80 isolates yield an approximate half-width of ±11% (26). To accommodate submissions that did not yield APEC, we aimed to enroll at least 100 suspect farm submissions.

Identification of Escherichia coli

Pericardial material was streaked onto eosin methylene blue (EMB) agar and aerobically incubated at 37°C for 18-24 hours. Lactose-fermenting colonies with a metallic-green sheen were subcultured to purity and examined as Gram-negative rods. Presumptive isolates were confirmed as Escherichia coli by the IMViC panel (Indole positive, Methyl Red positive, Voges-Proskauer negative, Simmons citrate negative). Only biochemically confirmed Escherichia coli were used for molecular assays (27).

Fluoroquinolone susceptibility testing

Fluoroquinolone susceptibility was evaluated using the Kirby–Bauer disk diffusion method on Mueller–Hinton agar: overnight cultures of confirmed Escherichia coli were adjusted to a 0.5 McFarland standard, plates were uniformly inoculated, five µg ciprofloxacin, 10 µg norfloxacin, five µg enrofloxacin, and 30 µg nalidixic acid disks were applied, incubation proceeded at 37 °C for 18 h, and inhibition zone diameters were measured in millimeters with a digital caliper; quantitative zone diameters are reported for all isolates and analyzed in relation to PMQR genotype (28).

DNA extraction and PCR detection of PMQR genes

Template DNA was prepared from overnight cultures by boiling lysis (95 to 100 °C), followed by rapid chilling and centrifugation. The supernatant was then used as the template. Conventional PCR assays targeted plasmid-mediated quinolone resistance determinants, including target-protection genes (qnrA, qnrB, qnrS), the drug-modifying enzyme gene aac(6′)-Ib-cr, and the efflux determinants qepA and oqxAB. Primer sequences, expected amplicon sizes, and gene-specific annealing temperatures are provided in Table 1. Each 25 µL reaction contained 1× PCR buffer with MgCl₂, 200 µM of each dNTP, 0.3 µM of each primer, 1 U Taq DNA polymerase, nuclease-free water, and 1–2 µL of template DNA. PCRs were run on a SensoQuest thermocycler (Germany) using Taq DNA Polymerase 2x Master Mix RED as the reaction master mix.

Thermocycling for the qnrA/B/S assays consisted of an initial denaturation at 95 °C for 5 min; 35 cycles of 95 °C for 45 s, 53 °C for 45 s, and 72 °C for 60 s; a final extension at 72 °C for 10 min; and a hold at 4 °C. For oqxAB, qepA, and aac(6′)-Ib-cr, cycling consisted of an initial denaturation at 95 °C for 15 min; 30 cycles of 94 °C for 30 s, 63 °C for 30 s, and 72 °C for 90 s; a final extension at 72 °C for 10 min; and a hold at 4 °C.

Each PCR run included a no-template negative control (NTC) to monitor reagent and workflow contamination. Amplicons were resolved on 1.5% Merck agarose in 1× TAE, run at approximately 100 V for 45–60 min, stained with ethidium bromide or SYBR-Safe, and visualized under UV/blue light. A 100-bp DNA ladder was used for sizing; bands at the expected sizes were interpreted as positive.

Sequencing confirmation

A representative subset of positives for each target was purified (Silica column) and subjected to Sanger sequencing. Chromatograms were quality-checked and trimmed in Chromas; bidirectional reads were assembled when available. Consensus sequences were queried against the NCBI database using BLASTn; matches with high coverage and ≥ 99% identity to the corresponding PMQR references were accepted as confirmatory (16, 17).

Statistical analysis

The isolate served as the unit of analysis. For each plasmid-mediated quinolone resistance determinant (qnrA, qnrB, qnrS, oqxAB, qepA, aac(6′)-Ib-cr), prevalence was calculated as the proportion of PCR-positive isolates among those tested for that determinant and is reported as a percentage with two-sided 95% confidence intervals computed by the exact (Clopper–Pearson) method. Statistical summaries were generated in IBM SPSS Statistics version 26.0, and percentages were reported to one decimal place.

Results

Bacterial isolation, identification, and fluoroquinolone susceptibility

A total of 106 diagnostic submissions from commercial broiler flocks with necropsy lesions compatible with colibacillosis were processed, of which 81 yielded Escherichia coli. Isolation was based on growth of lactose-fermenting colonies with a metallic green sheen on EMB agar, followed by biochemical confirmation using the IMViC scheme, namely Indole positive, Methyl Red positive, Voges–Proskauer negative, and Simmons citrate negative, which is consistent with Escherichia coli and was used as the entry criterion for molecular analysis.

Fluoroquinolone susceptibility testing by disk diffusion (ciprofloxacin five µg, enrofloxacin five µg, norfloxacin 10 µg, nalidixic acid 30 µg) is summarized in Table 2. Overall non-susceptibility (I+R) was highest for enrofloxacin (76.5%) and nalidixic acid (60.5%), moderate for norfloxacin (35.8%), and lowest for ciprofloxacin (23.5%).

Detection of plasmid-mediated quinolone resistance determinants

All 81 Escherichia coli isolates were assayed for the predefined plasmid-mediated quinolone resistance targets. Among target-protection genes, qnrA was 0/81 (0.0%; 95% CI, 0.0 to 4.5), qnrB was 4/81 (4.9%; 95% CI, 1.4 to 12.2), and qnrS was 28/81 (34.6%; 95% CI, 24.3 to 46.0). Among efflux and drug-modifying determinants, qepA was 0/81 (0.0%; 95% CI, 0.0 to 4.5), oqxAB was 43/81 (53.1%; 95% CI, 41.7 to 64.3), and aac(6′)-Ib-cr was 11/81 (13.6%; 95% CI, 7.0 to 23.0). These findings indicate that oqxAB was the most frequently detected marker in this cohort, that qnrS accounted for roughly one-third of isolates, that aac(6′)-Ib-cr and qnrB were detected at lower frequencies, and that qnrA and qepA were not detected under the conditions of this study. Per-gene prevalence with exact 95% confidence intervals is shown in Figure 1.

PMQR genotypes and their relationship with fluoroquinolone susceptibility

Overall, 43/81 (53.1%) isolates carried at least one PMQR determinant (the “PMQR-positive set”). At the isolate level (Table 3), PMQR-positive strains were enriched among non-susceptible categories, particularly for enrofloxacin and nalidixic acid, mirroring the cohort-level antibiogram. Genotype–phenotype discordance was observed in both directions. Five PMQR-positive isolates harbored one or more determinants yet remained fully susceptible to all four fluoroquinolones by disk diffusion. Conversely, nine isolates showed non-susceptibility to ≥1 fluoroquinolone but were negative for all screened PMQR genes, consistent with alternative mechanisms such as gyrA/parC mutations or other efflux systems beyond oqxAB. Detailed isolate-level gene profiles and corresponding resistance patterns appear in Table 3.

Sequencing confirmation

For analytical specificity, one representative amplicon from each positive target (qnrB, qnrS, oqxAB, and aac(6′)-Ib-cr) was purified and subjected to Sanger sequencing. All sequences showed ≥99% identity to their respective reference targets on BLASTn, confirming the identity of each assay's amplification product.

Discussion

In this regional analysis of Escherichia coli from broiler flocks with necropsy-confirmed colibacillosis in Mazandaran, northern Iran, oqxAB and qnrS were the predominant plasmid-mediated quinolone resistance markers, while aac(6′)-Ib-cr and qnrB occurred at lower levels, and qnrA/qepA were absent. This distribution is consistent with reports from commercial poultry systems, where oqxAB and qnrS are frequently detected. Studies from China and Korea have documented widespread oqxAB and substantial qnr carriage across birds, retail meat, and farm environments (1, 29). The absence of qepA and the low rate of qnrB in animal-origin surveys, where these genes are uncommon, contrasts with qnrS, which is typically the most frequent target-protection allele in avian isolates. (6, 13, 16). Our PMQR is broadly consistent with recent poultry cohorts in Europe and Asia, where oqxAB and qnrS are recurrent and qnrA/qepA remain infrequent (19, 21).

The predominance of oqxAB has practical implications because this RND-family efflux system can reduce intracellular levels of multiple agents beyond fluoroquinolones. It may also be co-selected by non-antibiotic pressures encountered in poultry production, broadening the ecological niches that favor persistence (5). The substantial qnrS signal indicates that target protection remains a significant contributor to decreased quinolone susceptibility in clinical broiler isolates, and the presence of aac(6′)-Ib-cr in a smaller subset suggests additional modification of ciprofloxacin and norfloxacin in the population (9, 12, 30). These patterns are consistent with the elevated non-susceptibility we observed for enrofloxacin and nalidixic acid, supporting the view that PMQR provides a low-level scaffold that facilitates selection of high-level chromosomal resistance under repeated drug exposure (31). Although we did not characterize β-lactam resistance, prior work has shown that PMQR genes can share plasmids with extended-spectrum β-lactamases, creating opportunities for co-selection under either antibiotic class and compounding the stewardship challenge in integrated operations (15).

Our findings add province-specific context to the growing Iranian literature on PMQR in broiler systems. The detection of PMQR determinants in commercial broilers from Semnan has already established a national signal, and the current data from Mazandaran indicate that efflux, dominated by oqxAB, and target protection via qnrS are also prominent in northern production, which argues for broader inter-provincial monitoring within a single analytic framework (22, 23). The concurrent phenotypic data also highlight that some isolates lacking detectable PMQR genes still exhibit fluoroquinolone non-susceptibility, indicating an additional contribution from chromosomal gyrA/parC mutations. The study’s strengths include a uniform diagnostic case definition based on necropsy findings, a single analytical unit per farm to limit clonality bias, standardized PCR conditions across all isolates, and sequencing confirmation of representative amplicons for specificity. The cross-sectional design, lack of species-specific PCR and APEC virulence-gene screening, absence of positive controls for qnrA/qepA, and no sequencing of quinolone–resistance–determining regions limit the inference on chromosomal backgrounds and clinical interpretation. The single-province scope may also constrain generalizability to settings with different antimicrobial-use practices. These limitations define priorities for future work, yet do not alter the core description of PMQR distribution in clinical Escherichia coli from broiler colibacillosis cases in Mazandaran (32).

From a One Health perspective, the coexistence of robust oqxAB and substantial qnrS detection in broiler colibacillosis isolates supports targeted stewardship that limits empirical fluoroquinolone use, prioritizes diagnostics and susceptibility testing, and strengthens biosecurity and vaccination strategies that reduce the need for antimicrobial therapy (5, 29). In our work, genotype–phenotype mismatches (five PMQR-positive but fully susceptible isolates and nine non-susceptible isolates lacking the screened PMQR genes) further support the coupling of routine antibiograms with molecular assays and periodic MIC testing to capture chromosomal mechanisms, such as gyrA/parC and non-oqxAB efflux activity. Given evidence of PMQR within birds, farm environments, and along retail pathways in several regions, a provincial surveillance program that pairs PMQR screening with ESBL markers, plasmid typing, and periodic whole-genome sequencing would provide early warning for emerging plasmid backgrounds and help align farm-level interventions (for example, indication-based prescribing, withdrawal-interval adherence, and litter/manure management) with public health priorities (3, 4).

Conclusion

Clinical Escherichia coli from broiler colibacillosis in Mazandaran, northern Iran, showed a PMQR profile dominated by oqxAB and qnrS, with lower detection of aac(6′)-Ib-cr and qnrB, and no detection of qnrA or qepA. This distribution aligns with recent poultry reports from Asia and Europe and complements Iranian data from Semnan, indicating that PMQR determinants are now entrenched in national broiler production. The findings underscore the importance of prudent fluoroquinolone use, enhanced farm-level prevention, and coordinated surveillance that links PMQR with plasmid and β-lactam resistance markers to inform effective antimicrobial stewardship and One Health interventions in the poultry sector.

Ethical Considerations

All procedures involving animals were reviewed and approved by the Islamic Azad University of Babol under approval code IR.IAU.AMOL.REC.1403.176. Samples consisted of post-mortem diagnostic submissions from commercial broilers; no live animal procedures were conducted.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Authors’ Contributions

The authors confirm sole responsibility for the following: study conception and design, data collection, analysis and interpretation of results, and manuscript preparation. S.S. and M.A. conceived and designed the study; K.T.G. coordinated field sampling and bacteriology; H.M.A. performed molecular assays and sequencing; M.B. curated data and performed the statistical analysis, also drafted the manuscript; all authors critically revised the text, approved the final version, and agree to be accountable for all aspects of the work.

Conflict of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

We thank Dr. Habibipour for his assistance with sampling and diagnosis. We are grateful to colleagues who provided helpful comments during manuscript preparation.

Transparency Statement

Data underlying the findings of this study are available from the corresponding author upon reasonable request.

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