Serogroup Diversity, Virulence Gene Distribution, and Antimicrobial Resistance Profiles of Intestinal Escherichia coli in Broilers

Serogroup Diversity, Virulence Gene Distribution, and Antimicrobial Resistance Profiles of Intestinal Escherichia coli in Broilers | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report Serogroup Diversity, Virulence Gene Distribution, and Antimicrobial Resistance Profiles of Intestinal Escherichia coli in Broilers Hongyan Sun, Ning Xu, Hongyan Liu, Jiyuan Yao, Shi Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9345958/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract This study investigated the serogroup distribution, virulence gene profiles, and antimicrobial resistance of avian pathogenic Escherichia coli ( APEC ) isolated from broiler farm environments in Changchun, China. A total of 690 samples, including cloacal swabs, fresh feces, and environmental swabs, were collected. E. coli isolates were identified through bacterial culture, IMViC tests, and 16S rDNA sequencing. Serogroups were determined using slide agglutination, ten virulence-associated genes were detected by PCR, and antimicrobial susceptibility to 16 antibiotics was assessed via the disk diffusion method.Among 70 isolated strains (isolation rate:10.14%), the predominant serogroups were O78(34.29%), O1(12.86%), and O18(4.29%), with 48.57% being untypeable. All isolates carried at least one virulence gene; iucD and hemolysin( HIY ) genes were most prevalent (94.29% each). All isolates displayed complete resistance (100%) to erythromycin, clindamycin, and spectinomycin/lincomycin, and were found to be multidrug resistant (MDR) to a minimum of six antibiotics.Resistance genes tetA (54.3%), tetG (51.4%), and sul1 (34.3%) were frequently detected. These findings highlight diverse serogroups, complex virulence profiles, and severe MDR in APEC from broiler farms, underscoring the need for enhanced surveillance and prudent antibiotic use. Broiler Avian pathogenic Escherichia coli (APEC) Serogroup Virulence gene Antimicrobial resistance Figures Figure 1 Figure 2 INTRODUCTION Escherichia coli is a common member of the intestinal microbiota in mammals and birds but can become pathogenic under certain conditions, leading to localized or systemic infections (Mageiros et al., 2021 ). Avian pathogenic Escherichia coli ( APEC ) is the main causative agent of avian colibacillosis, a disease that manifests as septicemia, pericarditis, perihepatitis, airsacculitis, and yolk sac infection, imposing considerable economic burdens on the global poultry industry (Palmieri, Apostolakos, Paudel, & Hess, 2023 ). Research has demonstrated that APEC impacts chickens of all age groups, with young chicks being particularly susceptible due to their immature immune systems, often leading to more severe disease and elevated mortality rates. The pathogenicity of APEC is closely associated with its array of virulence factors. These factors encompass adhesins, such as the P fimbriae‑associated protein PapC ; iron acquisition systems, including IucD and Irp2 ; serum survival factors like iss ; temperature‑sensitive hemagglutinin ( Tsh ); and hemolysins (Song et al., 2025 ). Acting synergistically, these factors enable the bacteria to survive, proliferate, and inflict pathological damage within the host's blood and tissues. It has been proposed that the presence of at least five specific virulence genes constitutes a key molecular characteristic of APEC strains (Subedi et al., 2018 ). Recent epidemiological studies on the virulence gene profiles of APEC have uncovered significant heterogeneity among strains isolated from diverse regions and under different rearing environments (Jonare et al., 2023 ). Apart from virulence factors, antimicrobial resistance (AMR) has become another significant challenge in APEC prevention and control. In intensive poultry farming, the widespread use of antibiotics—whether for disease prevention, treatment, or growth promotion—has facilitated the emergence and dissemination of drug‑resistant bacteria (Tian et al., 2021 ). APEC isolates have been shown to exhibit resistance to a wide range of antimicrobial agents, including tetracyclines, sulfonamides, penicillins, and certain fluoroquinolones (Liao et al., 2025 ). It is noteworthy that multidrug resistance (MDR) is prevalent in APEC isolates, defined as resistance to three or more classes of antimicrobials (Uddin et al., 2025 ). The horizontal transfer of resistance genes—such as tetA , tetG , and sul1 —among strains further accelerates the dissemination of antimicrobial resistance (Zhang et al., 2023 ), which has been recognized by the World Health Organization (WHO) and the World Organisation for Animal Health (WOAH) as one of the most urgent public health challenges of the 21st century, urging countries to strengthen resistance surveillance and antimicrobial stewardship within the livestock sector (European Food Safety et al., 2025 ). As a major broiler production hub in Jilin Province, Changchun features high‑density, intensive farming operations. Despite this, systematic data on the prevalence, serogroup distribution, virulence gene profiles, and antimicrobial resistance of APEC in the local broiler farm environment remain scarce. Existing studies have largely relied on samples collected from deceased birds during necropsy, with limited focus on environmental sources such as feces, housing surfaces, and cloacal swabs from live chickens. Given that environmental samples act as key reservoirs for drug‑resistant bacteria and resistance genes, they play a significant role in bacterial transmission and the dissemination of antimicrobial resistance. Thus, integrated investigations incorporating both environmental and biological samples are essential for a comprehensive understanding of the ecological distribution of APEC and its associated transmission risks. In this study, environmental samples (feces and environmental swabs) and biological samples (cloacal swabs) were collected from broiler farms around Changchun City. Through bacterial isolation and identification, serotyping, virulence gene detection, antimicrobial susceptibility testing, and resistance gene analysis, the prevalence of serogroups, virulence gene profiles, and antimicrobial resistance status of APEC in this region were systematically characterized. This research aims to provide a theoretical basis for the scientific prevention and control of avian colibacillosis and to support the rational use of antimicrobials in clinical practice. MATERIALS AND METHODS Study Area and Sample Collection This study was conducted from March to October 2025 at broiler farms in Dehui and Yongji counties, located near Changchun City, Jilin Province, China. A total of 690 samples were collected, including cloacal swabs from broilers (n = 130), environmental swabs from chicken houses (n = 430), and fresh fecal samples (n = 130). Isolation and Identification of E. coli Cloacal and environmental swabs were placed into sterile 1.5 mL microcentrifuge tubes and immediately transported to the laboratory for processing. Fecal samples (1 g) were mixed with 9 mL of sterile saline and thoroughly vortexed. All samples were then streaked onto MacConkey agar and eosin methylene blue (EMB) agar, followed by incubation at 37°C for 18–24 hours. Suspected colonies—characterized by pink, smooth, round morphology on MacConkey agar and purple-black coloration with a metallic sheen on EMB agar—were selected for purification. Purified isolates were identified by Gram staining and biochemical testing using the IMViC assays (indole, methyl red, Voges‑Proskauer, and citrate utilization). E. coli isolates were characterized as positive for indole and methyl red, and negative for Voges‑Proskauer and citrate (Shah et al., 2025 ). Bacterial genomic DNA was extracted using a commercial DNA extraction kit (Beijing Roadstar Technology Co., Ltd.) according to the manufacturer's instructions. The 16S rDNA gene was amplified by PCR using universal primers 27F (5′‑AGAGTTTGATCMTGGCTCAG‑3′) and 1492R (5′‑TACGGYTACCTTGTTACGACTT‑3′). Each 20 µL reaction mixture contained 10.0 µL of 2× Taq Plus Master Mix, 0.4 µL each of forward and reverse primers, 1.0 µL of DNA template, and deionized water (ddH₂O) to make up the final volume. The thermal cycling protocol consisted of an initial denaturation at 94°C for 2 min, followed by 30 cycles of denaturation at 94°C for 30 s, annealing at 50°C for 30 s, and extension at 72°C for 60 s, with a final extension at 72°C for 10 min. Amplified products were resolved by electrophoresis on a 1% agarose gel. Positive amplicons of approximately 1500 bp were sequenced by Sangon Biotech (Shanghai) Co., Ltd., and the resulting sequences were confirmed via BLAST search against the NCBI database. Serogrouping Identification of the O1, O18, and O78 serogroups was performed using PCR to target specific genes (gnd, wekO, wekS, wekW, wzx) (DebRoy, Fratamico, & Roberts, 2018 ; Runcharoon et al., 2025 ). Details of the primers are provided in Table 1. The O2 serogroup was not analyzed due to the lack of specific primers for this serogroup. Subsequently, traditional slide agglutination with O‑antigen‑specific antisera was employed to confirm the serogroup for all isolates (Boulbair et al., 2025 ). The PCR reaction mixture (20 µL) was prepared as detailed in section 2.2.3, utilizing the specific primers listed in Table 1 and maintaining consistent thermal cycling conditions. For agglutination testing, 10 mL of bacterial culture was centrifuged at 8000 × g for 5 minutes. The resulting pellet was resuspended in 5 mL of saline and autoclaved at 121°C for 2 hours to create the O‑antigen suspension. A mixture of 10 µL each of the O‑antigen suspension and polyvalent E. coli O‑antiserum was assessed for agglutination within 30 seconds on a glass slide. Positive reactions were further evaluated using monovalent antisera corresponding to the polyvalent serum to determine the specific O serogroup. A control consisting of O‑antigen suspension mixed with saline was included for each isolate to rule out autoagglutination. Detection of Virulence Genes Ten virulence‑associated genes ( aatA , papC , tsh , vat , cva/cvi , iss , iucD , irp2 , HIY , and aeA ) were detected by PCR using primers and conditions described previously (Table 2). Each 25 µL PCR reaction mixture was prepared according to the manufacturer's instructions. Amplification products were separated by electrophoresis on a 1% agarose gel. Positive control strains and negative controls were included to ensure accuracy. Antimicrobial Susceptibility Testing Antimicrobial susceptibility was determined using the Kirby‑Bauer disk diffusion method on Mueller‑Hinton agar, following the Clinical and Laboratory Standards Institute (CLSI) guidelines (Schiller, Young, Schulze, Tripepi, & Pohlschroder, 2022 ). The tested antimicrobial agents (Oxoid, UK) included ampicillin (10 µg), spectinomycin/lincomycin (20 µg), ciprofloxacin (5 µg), oxytetracycline hydrochloride (30 µg), florfenicol (30 µg), amikacin (30 µg), clindamycin (20 µg), gentamicin (10 µg), enrofloxacin (5 µg), norfloxacin (10 µg), colistin (polymyxin E, 15 µg), apramycin sulfate (20 µg), erythromycin (15 µg), amoxicillin (20 µg), cefazolin (30 µg), and neomycin sulfate (30 µg). For each E. coli isolate, colonies grown for 18‑24 h were suspended in sterile saline and adjusted to a 0.5 McFarland standard (approximately 1‑2 × 10⁸ CFU/mL). A sterile cotton swab was dipped into the suspension and used to evenly inoculate Mueller‑Hinton agar plates (4 mm thickness). After air‑drying for 5‑10 min at room temperature, antimicrobial disks were placed onto the agar surface using sterile forceps within 15 min. The plates were then inverted and incubated at 37°C for 18‑24 h. Inhibition zone diameters were measured and interpreted as susceptible (S), intermediate (I), or resistant (R) according to CLSI breakpoints. E. coli ATCC 25922 was used as the quality control strain. Detection of Resistance Genes Phenotypically resistant isolates were screened for resistance genes, including tetracycline resistance genes ( tetA , tetG ), the sulfonamide resistance gene ( sul1 ), aminoglycoside resistance genes ( strA , strB , gyrB ), β‑lactam resistance genes ( blaTEM , blaCTX‑M , blaCTX‑M‑1 , blaZX‑M ), the macrolide resistance gene ( ermB ), and quinolone resistance genes ( qnrS ) (Jacoby, Strahilevitz, & Hooper, 2014 ; Younis, Awad, & Mohamed, 2017 ). Primer sequences and expected amplicon sizes are listed in Table 3. PCR amplification was performed in a 20 µL reaction mixture containing 10.0 µL of 2× Taq Plus Master Mix, 0.4 µL of each forward and reverse primer, 1.0 µL of DNA template, and nuclease‑free water to make up the final volume. The thermal cycling protocol consisted of initial denaturation at 94°C for 2 min, followed by 30 cycles of denaturation at 94°C for 30 s, annealing at 50°C for 30 s, and extension at 72°C for 60 s, with a final extension at 72°C for 10 min. Amplified products were analyzed by 1% agarose gel electrophoresis. Positive amplicons were sequenced by Sangon Biotech (Shanghai) Co., Ltd., and the obtained sequences were confirmed by BLAST alignment against the NCBI database (Wang, Wang, Zhang, Qi, & Guo, 2009 ). Statistical Analysis Statistical analyses were conducted using SPSS version 27.0. Isolation rates, antimicrobial resistance rates, and other categorical variables were expressed as percentages. The chi‑square test was used to compare isolation rates among sample types. Co‑occurrence analysis of virulence genes was performed using Fisher's exact test. Antimicrobial resistance patterns were clustered using hierarchical clustering with Euclidean distance and complete linkage, and the results were visualized using a heatmap. A p‑value < 0.05 was considered statistically significant. RESULTS Isolation and Identification of E. coli A total of 70 E. coli strains were isolated and identified from 690 samples, yielding an overall isolation rate of 10.14%. Isolation rates varied among different sample types. The highest rate was observed in cloacal swabs (14.6%, 19/130), followed by fecal samples (13.1%, 17/130), while environmental swabs exhibited the lowest isolation rate (7.9%, 34/430) (Table 4). Following 16S rDNA PCR amplification, sequencing, and BLAST analysis, all isolates displayed greater than 99% homology with reference E. coli strains. Serogroup Distribution Serogrouping of the 70 E. coli isolates revealed three distinct serogroups. The predominant serogroup was O78, accounting for 34.29% (24/70) of the isolates, followed by O1 at 12.86% (9/70) and O18 at 4.29% (3/70). A substantial proportion of the isolates, specifically 48.57% (34/70), were untypeable (UT) with the antisera employed (Table 5). No significant differences in serogroup distribution were detected among isolates derived from various sample sources. Prevalence of Virulence Genes All 70 E. coli isolates exhibited the presence of at least one of the ten virulence genes screened, indicating potential pathogenicity (Table 6). The iucD gene and the hemolysin gene ( HIY ) were the most prevalent, each found in 94.29% (66/70) of the isolates. Following these, the irp2 and tsh genes were detected in 55.71% (39/70) of the isolates. The aatA gene was present in 47.14% (36/70) of the isolates. Lower detection rates were observed for cva/cvi (21.43%, 15/70), iss (12.86%, 12/70), vat (8.71%, 6/70), papC (8.57%, 6/70), and the pathogenicity island marker aeA (8.57%, 6/70). Co-occurrence analysis (Table 7) demonstrated varying degrees of association among different virulence genes. The highest co-occurrence rates were identified for the gene pairs iucD/HIY , tsh/HIY , cva/cvi/HIY , vat / HIY , and aeA / HIY , with 91.4% (64/70) of isolates harboring these gene pairs simultaneously. The irp2 gene co-occurred with tsh , iucD , cva/cvi , vat , and aeA in 54.3% of isolates. The aatA gene exhibited co-occurrence with tsh , iucD , cva/cvi , vat , and aeA in 51.4% of isolates. The iss gene co-occurred with these genes in 17.1% of isolates. Co-occurrence involving papC with the aforementioned genes was relatively low, at 8.6% (Fisher's exact test, P < 0.05 indicated significant co-occurrence). The co-occurrence patterns of virulence genes are visualized in Fig. 1 . Antimicrobial Susceptibility Profiles The antimicrobial resistance rates of the 70 E. coli isolates to 16 antibiotics are detailed in Table 8. The highest resistance rates were recorded for erythromycin, clindamycin, and spectinomycin/lincomycin, each exhibiting a resistance rate of 100.00% (70/70). This was followed by colistin (95.71%, 67/70), apramycin sulfate (91.43%, 64/70), amoxicillin (90.00%, 63/70), ampicillin (83.96%, 58/70), enrofloxacin (78.57%, 55/70), florfenicol (75.71%, 53/70), norfloxacin (74.26%, 52/70), cefazolin (70.00%, 49/70), neomycin sulfate (70.00%, 49/70), ciprofloxacin (67.14%, 47/70), oxytetracycline hydrochloride (44.29%, 31/70), and gentamicin (35.71%, 25/70). In contrast, the lowest resistance rate was noted for amikacin, which was only 2.86% (2/70). MDR analysis indicated that all isolates displayed multidrug resistance, demonstrating resistance to at least six antibiotics. A total of 16 distinct resistance patterns were identified among the isolates (Table 9). The most prevalent resistance pattern was Pattern K, which included resistance to AM, CZ, AMX, SPC, APr, NEO, FFC, E, CIP, NOR, ENY, CLN, OXY, and C, accounting for 14.3% (10/70) of the isolates. This was followed by Pattern M, which consisted of AM, AMX, GM, SPC, APr, NEO, FFC, E, CIP, NOR, ENY, CLN, OXY, and C, representing 11.4% (8/70) of the isolates. Pattern P, comprising AM, CZ, AMX, GM, SPC, APr, NEO, FFC, E, CIP, NOR, ENY, CLN, OXY, and C, also accounted for 11.4% (8/70) of the isolates. The broadest resistance profiles, represented by Patterns P, M, and L, exhibited resistance to 15 antibiotics and collectively accounted for 38.6% (27/70) of the isolates. Hierarchical clustering of resistance patterns is shown in Fig. 2 . Prevalence of Resistance Genes The prevalence of 14 resistance genes among 70 E. coli isolates was evaluated using PCR.This assessment included β-lactam resistance genes ( blaTEM , blaCTX-M , blacrX-M , blacrX-M-1 , blacrX-M-9 , blaZX-M ), aminoglycoside resistance genes ( strA , strB , gyrB ), quinolone resistance genes ( qnrS ), the sulfonamide resistance gene ( sul1 ), the macrolide resistance gene ( ermB ), and tetracycline resistance genes ( tetA , tetG ). The detection rates and the number of positive isolates for each gene are presented in Table 10. The results demonstrated that the strA gene had the highest detection rate at 65.7% (46/70), followed closely by gyrB at 62.9% (44/70) and blacrX-M at 51.4% (36/70). The detection rates for the other genes were as follows: blaTEM at 48.6% (34/70), qnrS at 47.1% (33/70), blaZX-M at 41.4% (29/70), blaCTX at 40.0% (28/70), strB at 38.6% (27/70), blacrX-M-1 at 37.1% (26/70), sul1 at 34.3% (24/70), blacrX-M-9 at 32.9% (23/70), ermB at 27.1% (19/70), tetA at 54.3% (38/70), and tetG at 51.4% (36/70). DISCUSSION In this study, the prevalence, serogroup distribution, virulence gene profiles, and antimicrobial resistance of APEC isolates from broiler farms in the Changchun region were systematically characterized. The overall isolation rate was 10.14% (70/690),which is lower than rates reported in studies using samples from deceased chickens (e.g., 28.6% in a previous study). This discrepancy likely reflects differences in sample sources, as our samples were primarily collected from healthy or subclinically infected flocks and farm environments, representing carriage rather than clinical disease (Idris et al., 2025 ). Among sample types, cloacal swabs yielded the highest isolation rate (14.6%), suggesting that cloacal sampling effectively reflects intestinal carriage, whereas environmental swabs exhibited the lowest rate (7.9%), potentially due to routine disinfection practices. Nonetheless, environmental samples remain important reservoirs for resistant bacteria and resistance genes (Liu et al., 2024 ). Serogrouping identified O78 as the predominant serogroup (34.29%), followed by O1 (12.86%) and O18 (4.29%), consistent with findings from most domestic and international studies. O78 is recognized as a globally dominant APEC serogroup frequently associated with colibacillosis outbreaks. Notably, 48.57% of isolates were untypeable (UT), a relatively high proportion that may be attributed to low antigen expression, the emergence of novel serogroups, or limitations inherent to traditional serotyping (Ingle et al., 2016 ). This finding underscores the need for molecular typing approaches, such as MLST or whole‑genome sequencing, in future investigations. All isolates carried at least one virulence gene, suggesting a potential for pathogenicity (Johnson and Nolan 2009 ; Jamali et al. 2024 ). The iucD and hemolysin genes exhibited the highest detection rates (94.29% each), followed by irp2 and tsh (55.71% each), and aatA (47.14%). As iron acquisition system genes, iucD and irp2 are critical for host adaptation and infection establishment (Schouler et al., 2012 ). Co‑occurrence analysis showed that HIY co‑occurred with iucD , tsh , cva/cvi , vat , and aeA at rates exceeding 90%, indicating that most isolates harbor multiple pathogenic mechanisms simultaneously, thereby enhancing their pathogenic potential. This pattern is consistent with the molecular characteristics of highly pathogenic APEC clones (Johnson & Nolan, 2009 ). Antimicrobial susceptibility testing showed that all isolates were multidrug‑resistant, exhibiting resistance to at least six antibiotics. Resistance rates were highest for erythromycin, clindamycin, and spectinomycin/lincomycin (100%), followed by colistin (95.71%), apramycin (91.43%), and amoxicillin (90.00%). This pattern is likely driven by the widespread use of these antimicrobials in livestock production (Elmarghani et al., 2025 ). Notably, the high resistance rate to colistin (95.71%) is of particular concern, as it is a last‑resort drug for treating multidrug‑resistant Gram‑negative infections in humans (Jeannot, Bolard, & Plésiat, 2017 ). In contrast, amikacin showed the lowest resistance rate (2.86%), and gentamicin remained relatively susceptible (35.71%), suggesting these agents may still represent viable treatment options (Xia et al., 2025 ). A total of 16 distinct resistance patterns were identified, among which Patterns P, M, and L exhibited the broadest resistance spectra (14‑15 antibiotics) and accounted for 38.6% of isolates, indicating complex dissemination and recombination of resistance genes (Petty et al., 2014 ). Resistance genes were detected at high frequencies, including strA (65.7%), gyrB (62.9%), blacrX‑M (51.4%), and blaTEM (48.6%), which is consistent with reports from other regions in China.The presence of tetA (54.3%), tetG (51.4%),and sul1 (34.3%) showed strong genotype‑phenotype concordance (Khalid et al., 2025 ; Subedi et al., 2018 ). Although no qnrA was detected among ciprofloxacin‑resistant isolates, suggesting that fluoroquinolone resistance in this region is primarily mediated by chromosomal mutations (e.g., gyrA or papC ) (Kareem et al., 2021 ), the detection of qnrS (47.1%) indicates that plasmid‑mediated mechanisms also contribute. CONCLUSIONS In conclusion, APEC strains isolated from broiler farms in the Changchun region displayed diverse serogroups, complex virulence gene profiles, and high levels of multidrug resistance. Environmental samples serve as reservoirs for resistant bacteria and resistance genes, thereby facilitating bacterial transmission and the spread of antimicrobial resistance (Bengtsson-Palme, Kristiansson, & Larsson, 2018 ). Enhanced biosecurity measures, prudent antimicrobial use, and the establishment of routine resistance surveillance programs are urgently needed. Declarations Author Contribution Conceptualization, Shi Li and Hongyan Sun; methodology, Ning Xu and hongyan Liu; formal analysis, Hongyan Sun and Ning Xu; investigation, hongyan Liu and Jiyuan Yao; writing—original draft preparation, Hongyan Sun; writing—review and editing, Shi Li; supervision, Shi Li; funding acquisition, Shi Li. All authors have read and agreed to the published version of the manuscript. Funding This work was supported by the Ministry of Agriculture and Rural Affairs Modern Agricultural Science and Technology Experimental Demonstration Base for Livestock and Poultry Breeding and Disease Prevention and Control (Dongfeng). Data Availability Statement The data presented in this study are available from the corresponding authors upon reasonable request. Acknowledgements We are grateful to the Ministry of Agriculture and Rural Affairs Modern Agricultural Science and Technology Experimental Demonstration Base for Livestock and Poultry Breeding and Disease Prevention and Control (Dongfeng) for its support, and to the laboratory members for their technical assistance and useful discussions. Conflicts of Interest The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Animal Ethics This study only involved sample collection from commercial broiler farms, and no animal experiments were conducted in this research. The sampling procedures were routine veterinary detection operations, which did not cause any pain or unnecessary harm to the broilers. All sampling activities were conducted with the full knowledge and consent of Jilin Agricultural University and the broiler farms. This study does not involve animal ethical issues that require additional ethical approval, and all operations comply with relevant animal welfare and ethical norms. References Bengtsson-Palme, J., Kristiansson, E., & Larsson, D. G. J. (2018). Environmental factors influencing the development and spread of antibiotic resistance. FEMS Microbiol Rev, 42 (1). doi:10.1093/femsre/fux053 Boulbair, I., Hu, J., Hammoudi, A., Zhang, B., Aissat, S., Wang, X., . . . Wang, S. (2025). 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(博士). 中国农业科学院, Retrieved from https://link.cnki.net/doi/10.27630/d.cnki.gznky.2025.000099 Available from Cnki Palmieri, N., Apostolakos, I., Paudel, S., & Hess, M. (2023). The genetic network underlying the evolution of pathogenicity in avian Escherichia coli. Front Vet Sci, 10 , 1195585. doi:10.3389/fvets.2023.1195585 Petty, N. K., Ben Zakour, N. L., Stanton-Cook, M., Skippington, E., Totsika, M., Forde, B. M., . . . Beatson, S. A. (2014). Global dissemination of a multidrug resistant Escherichia coli clone. Proc Natl Acad Sci U S A, 111 (15), 5694-5699. doi:10.1073/pnas.1322678111 Runcharoon, K., Garcia, B., Peterson, B. N., Young, M. M., Favro, M. E., Barbieri, N. L., . . . Logue, C. M. (2025). Longitudinal study of avian pathogenic Escherichia coli (APEC) serogroups associated with disease in Georgia poultry using molecular serology and virulence gene analysis. 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C., Rahman, A., Siddiquee, N. H., . . . Peas, T. (2025). Multidrug Resistance and Virulence Gene Profiles of E. coli in Broiler Chickens: A Study From Noakhali, Bangladesh. Vet Med Int, 2025 , 1157843. doi:10.1155/vmi/1157843 Wang, W., Wang, Y., Zhang, Q., Qi, Y., & Guo, D. (2009). Global characterization of Artemisia annua glandular trichome transcriptome using 454 pyrosequencing. BMC Genomics, 10 , 465. doi:10.1186/1471-2164-10-465 Xia, L., Wang, G., Chen, N., Qiao, D., Cao, J., & Bi, S. (2025). Genomic features, antimicrobial resistance and pathogenicity assessment of Escherichia coli serotype O177:H51 strain JS01 isolated from a diseased chicken. BMC Microbiol, 25 (1), 194. doi:10.1186/s12866-025-03925-5 Younis, G., Awad, A., & Mohamed, N. (2017). Phenotypic and genotypic characterization of antimicrobial susceptibility of avian pathogenic Escherichia coli isolated from broiler chickens. Vet World, 10 (10), 1167-1172. doi:10.14202/vetworld.2017.1167-1172 Zhang, H., Song, J., Zheng, Z., Li, T., Shi, N., Han, Y., . . . Fang, H. (2023). Fungicide exposure accelerated horizontal transfer of antibiotic resistance genes via plasmid-mediated conjugation. Water Res, 233 , 119789. doi:10.1016/j.watres.2023.119789 付新年, 马驰, 王鑫鑫, 马笑盈, 罗江焰, 郑盛, & 杨涓. (2025). 基于16SrDNA测序法分析大肠息肉患者肠道菌群的特征. 医学研究杂志, 54 (05), 93-98+165. Retrieved from https://kns.cnki.net/kcms2/article/abstract?v=Vs3rztogjcWqdShnwj8uedoP_EXAtMm0s42Z2LtvDs_HSY68eidPDjYD87RDq1Edxubo26ah569IeQqwv3Jah6FGUhmpcHvz3ExXXxNIWrIiP3xLqPYkYF7OQBLb6qAPjf8hc4SPqMsIXmuZgZ7g_32kWPZ-X4mQu7xP4NSyjo9xxU9vpjzdQ8W9OtVlr11J&uniplatform=NZKPT&language=CHS 贾雪波, 盛中伟, 肖芹, & 邹剑敏. (2016). 山东、安徽部分地区2016年禽致病性大肠杆菌的分子流行病学调查. 中国家禽, 38 (19), 71-74. doi:10.16372/j.issn.1004-6364.2016.19.017 孟庆美, 王少辉, 韩先干, 韩月, 丁铲, 戴建君, & 于圣青. (2014). 禽致病性大肠杆菌毒力基因多重PCR方法的建立和应用. 微生物学报, 54 (06), 696-702. doi:10.13343/j.cnki.wsxb.2014.06.013 王瑶, 张耀东, 易正飞, 信素华, 陶程琳, 李妍, . . . 王少辉. (2020). 禽致病性大肠杆菌血清型、进化分群及毒力基因的分子流行病学调查. 中国兽医科学, 50 (09), 1159-1166. doi:10.16656/j.issn.1673-4696.2020.0138 俞佳莉, 李欣, 钱懿青, 陈洪友, 乔雪飞, & 盛峰松. (2021). 溶藻弧菌脉冲场凝胶电泳分子分型方法的优化及应用. 中国卫生检验杂志, 31 (19), 2321-2326. Retrieved from https://kns.cnki.net/kcms2/article/abstract?v=Vs3rztogjcVr_TFlTD5dFkYCgIkDjG28zPkXfLs_ultdkUasCifKtkyJf4apJBlvi9g5CH8LGdltaAFhkD9k4Tt1XOjBR8IYrM9TNcoEIXs7OD_z7SWpjPgiLwiMpKGmgHYu1s9qhPRcHISLjKskcPOOLBHkr0tQP5nIZMY75uQQg5u8HdQNG4B9FLYLPXpJ&uniplatform=NZKPT&language=CHS 赵昶勋. (2022). 村镇易腐垃圾及其堆肥过程抗生素和抗性基因赋存状况分析. (硕士). 浙江大学, Retrieved from https://link.cnki.net/doi/10.27461/d.cnki.gzjdx.2022.003489 Available from Cnki Tables Tables 1 to 10 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Tables.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 24 Apr, 2026 Editor assigned by journal 23 Apr, 2026 Submission checks completed at journal 23 Apr, 2026 First submitted to journal 07 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9345958","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":628849329,"identity":"c23bfc7c-6085-43f1-9bbc-fde33de10b23","order_by":0,"name":"Hongyan Sun","email":"","orcid":"","institution":"Jilin Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Hongyan","middleName":"","lastName":"Sun","suffix":""},{"id":628849331,"identity":"ae73cfbf-74af-43fd-8382-c23c2ada0e9f","order_by":1,"name":"Ning Xu","email":"","orcid":"","institution":"Jilin Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Ning","middleName":"","lastName":"Xu","suffix":""},{"id":628849334,"identity":"42a3d123-80b9-40dc-b9c3-a5a629050743","order_by":2,"name":"Hongyan Liu","email":"","orcid":"","institution":"Jilin Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Hongyan","middleName":"","lastName":"Liu","suffix":""},{"id":628849336,"identity":"51705cf9-148f-4b69-ab40-8aa2d75a9a3a","order_by":3,"name":"Jiyuan Yao","email":"","orcid":"","institution":"Jilin Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Jiyuan","middleName":"","lastName":"Yao","suffix":""},{"id":628849339,"identity":"e72fe0db-89d0-4ade-92cb-8de5a774b2de","order_by":4,"name":"Shi Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYBACPmYGNoaECjYZMI+HGC1sYC1n2HhI0AJCjG0MpGhhZ3/24OE8Ph7+GQmMD962McibE3YYj7lB4jY2HokbCcyGc9sYDHc2ENbCJgHSwnAjgU2at40hweAAQS3szyQS57DxyN9IYP9NpBYGM4nEBjYeA6AtzERq4TGTSDjGxmN45mGz5JxzEoYbCGnh5z/+TPJHzTE5uePJBz+8KbORJ2gLFBwDYsYGICFBnHogqCFa5SgYBaNgFIxAAADnTTKADI0MNAAAAABJRU5ErkJggg==","orcid":"","institution":"Jilin Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Shi","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2026-04-07 13:39:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9345958/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9345958/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108878435,"identity":"c680bd66-d1b4-4849-b195-06c2871bd602","added_by":"auto","created_at":"2026-05-09 15:49:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":62243,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap illustrating the pairwise co-occurrence rates of 10 virulence-associated genes (\u003cem\u003eHIY\u003c/em\u003e, \u003cem\u003eirp2\u003c/em\u003e, \u003cem\u003etsh\u003c/em\u003e, \u003cem\u003eiucD\u003c/em\u003e, \u003cem\u003ecva/cvi\u003c/em\u003e, \u003cem\u003evat\u003c/em\u003e, \u003cem\u003eaeA\u003c/em\u003e, \u003cem\u003eiss\u003c/em\u003e, \u003cem\u003epapC\u003c/em\u003e, \u003cem\u003eaatA\u003c/em\u003e) among the bacterial isolates. The color intensity represents the percentage positivity of each gene pair co-occurring in the isolates, with darker blue indicating higher co-occurrence rates. Notably, the gene pairs \u003cem\u003eiucD\u003c/em\u003e and \u003cem\u003eHIY\u003c/em\u003e, \u003cem\u003etsh\u003c/em\u003e and \u003cem\u003eHIY\u003c/em\u003e, \u003cem\u003ecva/cvi\u003c/em\u003e and \u003cem\u003eHIY\u003c/em\u003e, \u003cem\u003evat\u003c/em\u003e and \u003cem\u003eHIY\u003c/em\u003e, as well as \u003cem\u003eaeA\u003c/em\u003e and \u003cem\u003eHIY\u003c/em\u003e exhibited the highest co-occurrence rate (91.4%). Blank cells along the diagonal represent self-comparisons of each gene and are not applicable for analysis.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9345958/v1/15eab0e64ea288447920b028.png"},{"id":108878436,"identity":"e0e501d7-f406-465f-a7c7-e3d8da56c75d","added_by":"auto","created_at":"2026-05-09 15:49:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":77474,"visible":true,"origin":"","legend":"\u003cp\u003eEach row represents one antimicrobial resistance pattern (A-P), and each column represents an antibiotic. Orange cells indicate resistance (value = 1). Hierarchical clustering (Euclidean distance, complete linkage method) was used to group the patterns. Patterns P, M, and L exhibited the broadest resistance profiles, whereas patterns A and B showed relatively narrower resistance spectra.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9345958/v1/b46ac6c0cf8fb07effa5c659.png"},{"id":108977660,"identity":"1d666846-1dc0-4ece-8bb5-d863c1c2f5e6","added_by":"auto","created_at":"2026-05-11 11:32:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":438720,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9345958/v1/6732c5db-452a-464b-af9f-3c980f490ea1.pdf"},{"id":108878434,"identity":"273b6b73-43fb-4d52-b991-1467e364ca25","added_by":"auto","created_at":"2026-05-09 15:49:17","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":49123,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-9345958/v1/89731fd898dc16b2e2c61e2f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Serogroup Diversity, Virulence Gene Distribution, and Antimicrobial Resistance Profiles of Intestinal Escherichia coli in Broilers","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003e \u003cem\u003eEscherichia coli\u003c/em\u003e is a common member of the intestinal microbiota in mammals and birds but can become pathogenic under certain conditions, leading to localized or systemic infections (Mageiros et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Avian pathogenic \u003cem\u003eEscherichia coli\u003c/em\u003e (\u003cem\u003eAPEC\u003c/em\u003e) is the main causative agent of avian colibacillosis, a disease that manifests as septicemia, pericarditis, perihepatitis, airsacculitis, and yolk sac infection, imposing considerable economic burdens on the global poultry industry (Palmieri, Apostolakos, Paudel, \u0026amp; Hess, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Research has demonstrated that \u003cem\u003eAPEC\u003c/em\u003e impacts chickens of all age groups, with young chicks being particularly susceptible due to their immature immune systems, often leading to more severe disease and elevated mortality rates.\u003c/p\u003e \u003cp\u003eThe pathogenicity of \u003cem\u003eAPEC\u003c/em\u003e is closely associated with its array of virulence factors. These factors encompass adhesins, such as the P fimbriae‑associated protein \u003cem\u003ePapC\u003c/em\u003e; iron acquisition systems, including \u003cem\u003eIucD\u003c/em\u003e and \u003cem\u003eIrp2\u003c/em\u003e; serum survival factors like \u003cem\u003eiss\u003c/em\u003e; temperature‑sensitive hemagglutinin (\u003cem\u003eTsh\u003c/em\u003e); and hemolysins (Song et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Acting synergistically, these factors enable the bacteria to survive, proliferate, and inflict pathological damage within the host's blood and tissues. It has been proposed that the presence of at least five specific virulence genes constitutes a key molecular characteristic of \u003cem\u003eAPEC\u003c/em\u003e strains (Subedi et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Recent epidemiological studies on the virulence gene profiles of \u003cem\u003eAPEC\u003c/em\u003e have uncovered significant heterogeneity among strains isolated from diverse regions and under different rearing environments (Jonare et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eApart from virulence factors, antimicrobial resistance (AMR) has become another significant challenge in \u003cem\u003eAPEC\u003c/em\u003e prevention and control. In intensive poultry farming, the widespread use of antibiotics\u0026mdash;whether for disease prevention, treatment, or growth promotion\u0026mdash;has facilitated the emergence and dissemination of drug‑resistant bacteria (Tian et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). \u003cem\u003eAPEC\u003c/em\u003e isolates have been shown to exhibit resistance to a wide range of antimicrobial agents, including tetracyclines, sulfonamides, penicillins, and certain fluoroquinolones (Liao et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). It is noteworthy that multidrug resistance (MDR) is prevalent in \u003cem\u003eAPEC\u003c/em\u003e isolates, defined as resistance to three or more classes of antimicrobials (Uddin et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The horizontal transfer of resistance genes\u0026mdash;such as \u003cem\u003etetA\u003c/em\u003e, \u003cem\u003etetG\u003c/em\u003e, and \u003cem\u003esul1\u003c/em\u003e\u0026mdash;among strains further accelerates the dissemination of antimicrobial resistance (Zhang et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), which has been recognized by the World Health Organization (WHO) and the World Organisation for Animal Health (WOAH) as one of the most urgent public health challenges of the 21st century, urging countries to strengthen resistance surveillance and antimicrobial stewardship within the livestock sector (European Food Safety et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs a major broiler production hub in Jilin Province, Changchun features high‑density, intensive farming operations. Despite this, systematic data on the prevalence, serogroup distribution, virulence gene profiles, and antimicrobial resistance of \u003cem\u003eAPEC\u003c/em\u003e in the local broiler farm environment remain scarce. Existing studies have largely relied on samples collected from deceased birds during necropsy, with limited focus on environmental sources such as feces, housing surfaces, and cloacal swabs from live chickens. Given that environmental samples act as key reservoirs for drug‑resistant bacteria and resistance genes, they play a significant role in bacterial transmission and the dissemination of antimicrobial resistance. Thus, integrated investigations incorporating both environmental and biological samples are essential for a comprehensive understanding of the ecological distribution of \u003cem\u003eAPEC\u003c/em\u003e and its associated transmission risks. In this study, environmental samples (feces and environmental swabs) and biological samples (cloacal swabs) were collected from broiler farms around Changchun City. Through bacterial isolation and identification, serotyping, virulence gene detection, antimicrobial susceptibility testing, and resistance gene analysis, the prevalence of serogroups, virulence gene profiles, and antimicrobial resistance status of \u003cem\u003eAPEC\u003c/em\u003e in this region were systematically characterized. This research aims to provide a theoretical basis for the scientific prevention and control of avian colibacillosis and to support the rational use of antimicrobials in clinical practice.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Area and Sample Collection\u003c/h2\u003e \u003cp\u003eThis study was conducted from March to October 2025 at broiler farms in Dehui and Yongji counties, located near Changchun City, Jilin Province, China. A total of 690 samples were collected, including cloacal swabs from broilers (n\u0026thinsp;=\u0026thinsp;130), environmental swabs from chicken houses (n\u0026thinsp;=\u0026thinsp;430), and fresh fecal samples (n\u0026thinsp;=\u0026thinsp;130).\u003c/p\u003e \u003cp\u003e \u003cb\u003eIsolation and Identification of\u003c/b\u003e \u003cb\u003eE. coli\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCloacal and environmental swabs were placed into sterile 1.5 mL microcentrifuge tubes and immediately transported to the laboratory for processing. Fecal samples (1 g) were mixed with 9 mL of sterile saline and thoroughly vortexed. All samples were then streaked onto MacConkey agar and eosin methylene blue (EMB) agar, followed by incubation at 37\u0026deg;C for 18\u0026ndash;24 hours. Suspected colonies\u0026mdash;characterized by pink, smooth, round morphology on MacConkey agar and purple-black coloration with a metallic sheen on EMB agar\u0026mdash;were selected for purification.\u003c/p\u003e \u003cp\u003ePurified isolates were identified by Gram staining and biochemical testing using the IMViC assays (indole, methyl red, Voges‑Proskauer, and citrate utilization). \u003cem\u003eE. coli\u003c/em\u003e isolates were characterized as positive for indole and methyl red, and negative for Voges‑Proskauer and citrate (Shah et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBacterial genomic DNA was extracted using a commercial DNA extraction kit (Beijing Roadstar Technology Co., Ltd.) according to the manufacturer's instructions. The 16S rDNA gene was amplified by PCR using universal primers 27F (5\u0026prime;‑AGAGTTTGATCMTGGCTCAG‑3\u0026prime;) and 1492R (5\u0026prime;‑TACGGYTACCTTGTTACGACTT‑3\u0026prime;). Each 20 \u0026micro;L reaction mixture contained 10.0 \u0026micro;L of 2\u0026times; Taq Plus Master Mix, 0.4 \u0026micro;L each of forward and reverse primers, 1.0 \u0026micro;L of DNA template, and deionized water (ddH₂O) to make up the final volume. The thermal cycling protocol consisted of an initial denaturation at 94\u0026deg;C for 2 min, followed by 30 cycles of denaturation at 94\u0026deg;C for 30 s, annealing at 50\u0026deg;C for 30 s, and extension at 72\u0026deg;C for 60 s, with a final extension at 72\u0026deg;C for 10 min. Amplified products were resolved by electrophoresis on a 1% agarose gel. Positive amplicons of approximately 1500 bp were sequenced by Sangon Biotech (Shanghai) Co., Ltd., and the resulting sequences were confirmed via BLAST search against the NCBI database.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSerogrouping\u003c/h3\u003e\n\u003cp\u003eIdentification of the O1, O18, and O78 serogroups was performed using PCR to target specific genes (gnd, wekO, wekS, wekW, wzx) (DebRoy, Fratamico, \u0026amp; Roberts, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Runcharoon et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Details of the primers are provided in Table\u0026nbsp;1. The O2 serogroup was not analyzed due to the lack of specific primers for this serogroup. Subsequently, traditional slide agglutination with O‑antigen‑specific antisera was employed to confirm the serogroup for all isolates (Boulbair et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The PCR reaction mixture (20 \u0026micro;L) was prepared as detailed in section 2.2.3, utilizing the specific primers listed in Table\u0026nbsp;1 and maintaining consistent thermal cycling conditions. For agglutination testing, 10 mL of bacterial culture was centrifuged at 8000 \u0026times; g for 5 minutes. The resulting pellet was resuspended in 5 mL of saline and autoclaved at 121\u0026deg;C for 2 hours to create the O‑antigen suspension. A mixture of 10 \u0026micro;L each of the O‑antigen suspension and polyvalent E. coli O‑antiserum was assessed for agglutination within 30 seconds on a glass slide. Positive reactions were further evaluated using monovalent antisera corresponding to the polyvalent serum to determine the specific O serogroup. A control consisting of O‑antigen suspension mixed with saline was included for each isolate to rule out autoagglutination.\u003c/p\u003e\n\u003ch3\u003eDetection of Virulence Genes\u003c/h3\u003e\n\u003cp\u003eTen virulence‑associated genes (\u003cem\u003eaatA\u003c/em\u003e, \u003cem\u003epapC\u003c/em\u003e, \u003cem\u003etsh\u003c/em\u003e, \u003cem\u003evat\u003c/em\u003e, \u003cem\u003ecva/cvi\u003c/em\u003e, \u003cem\u003eiss\u003c/em\u003e, \u003cem\u003eiucD\u003c/em\u003e, \u003cem\u003eirp2\u003c/em\u003e, \u003cem\u003eHIY\u003c/em\u003e, and \u003cem\u003eaeA\u003c/em\u003e) were detected by PCR using primers and conditions described previously (Table\u0026nbsp;2). Each 25 \u0026micro;L PCR reaction mixture was prepared according to the manufacturer's instructions. Amplification products were separated by electrophoresis on a 1% agarose gel. Positive control strains and negative controls were included to ensure accuracy.\u003c/p\u003e\n\u003ch3\u003eAntimicrobial Susceptibility Testing\u003c/h3\u003e\n\u003cp\u003eAntimicrobial susceptibility was determined using the Kirby‑Bauer disk diffusion method on Mueller‑Hinton agar, following the Clinical and Laboratory Standards Institute (CLSI) guidelines (Schiller, Young, Schulze, Tripepi, \u0026amp; Pohlschroder, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The tested antimicrobial agents (Oxoid, UK) included ampicillin (10 \u0026micro;g), spectinomycin/lincomycin (20 \u0026micro;g), ciprofloxacin (5 \u0026micro;g), oxytetracycline hydrochloride (30 \u0026micro;g), florfenicol (30 \u0026micro;g), amikacin (30 \u0026micro;g), clindamycin (20 \u0026micro;g), gentamicin (10 \u0026micro;g), enrofloxacin (5 \u0026micro;g), norfloxacin (10 \u0026micro;g), colistin (polymyxin E, 15 \u0026micro;g), apramycin sulfate (20 \u0026micro;g), erythromycin (15 \u0026micro;g), amoxicillin (20 \u0026micro;g), cefazolin (30 \u0026micro;g), and neomycin sulfate (30 \u0026micro;g).\u003c/p\u003e \u003cp\u003eFor each \u003cem\u003eE. coli\u003c/em\u003e isolate, colonies grown for 18‑24 h were suspended in sterile saline and adjusted to a 0.5 McFarland standard (approximately 1‑2 \u0026times; 10⁸ CFU/mL). A sterile cotton swab was dipped into the suspension and used to evenly inoculate Mueller‑Hinton agar plates (4 mm thickness). After air‑drying for 5‑10 min at room temperature, antimicrobial disks were placed onto the agar surface using sterile forceps within 15 min. The plates were then inverted and incubated at 37\u0026deg;C for 18‑24 h. Inhibition zone diameters were measured and interpreted as susceptible (S), intermediate (I), or resistant (R) according to CLSI breakpoints. \u003cem\u003eE. coli\u003c/em\u003e ATCC 25922 was used as the quality control strain.\u003c/p\u003e\n\u003ch3\u003eDetection of Resistance Genes\u003c/h3\u003e\n\u003cp\u003ePhenotypically resistant isolates were screened for resistance genes, including tetracycline resistance genes (\u003cem\u003etetA\u003c/em\u003e, \u003cem\u003etetG\u003c/em\u003e), the sulfonamide resistance gene (\u003cem\u003esul1\u003c/em\u003e), aminoglycoside resistance genes (\u003cem\u003estrA\u003c/em\u003e, \u003cem\u003estrB\u003c/em\u003e, \u003cem\u003egyrB\u003c/em\u003e), β‑lactam resistance genes (\u003cem\u003eblaTEM\u003c/em\u003e, \u003cem\u003eblaCTX‑M\u003c/em\u003e, \u003cem\u003eblaCTX‑M‑1\u003c/em\u003e, \u003cem\u003eblaZX‑M\u003c/em\u003e), the macrolide resistance gene (\u003cem\u003eermB\u003c/em\u003e), and quinolone resistance genes (\u003cem\u003eqnrS\u003c/em\u003e) (Jacoby, Strahilevitz, \u0026amp; Hooper, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Younis, Awad, \u0026amp; Mohamed, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Primer sequences and expected amplicon sizes are listed in Table\u0026nbsp;3.\u003c/p\u003e \u003cp\u003ePCR amplification was performed in a 20 \u0026micro;L reaction mixture containing 10.0 \u0026micro;L of 2\u0026times; Taq Plus Master Mix, 0.4 \u0026micro;L of each forward and reverse primer, 1.0 \u0026micro;L of DNA template, and nuclease‑free water to make up the final volume. The thermal cycling protocol consisted of initial denaturation at 94\u0026deg;C for 2 min, followed by 30 cycles of denaturation at 94\u0026deg;C for 30 s, annealing at 50\u0026deg;C for 30 s, and extension at 72\u0026deg;C for 60 s, with a final extension at 72\u0026deg;C for 10 min. Amplified products were analyzed by 1% agarose gel electrophoresis. Positive amplicons were sequenced by Sangon Biotech (Shanghai) Co., Ltd., and the obtained sequences were confirmed by BLAST alignment against the NCBI database (Wang, Wang, Zhang, Qi, \u0026amp; Guo, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were conducted using SPSS version 27.0. Isolation rates, antimicrobial resistance rates, and other categorical variables were expressed as percentages. The chi‑square test was used to compare isolation rates among sample types. Co‑occurrence analysis of virulence genes was performed using Fisher's exact test. Antimicrobial resistance patterns were clustered using hierarchical clustering with Euclidean distance and complete linkage, and the results were visualized using a heatmap. A p‑value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eIsolation and Identification of \u003cem\u003eE. coli\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eA total of 70 \u003cem\u003eE. coli\u003c/em\u003e strains were isolated and identified from 690 samples, yielding an overall isolation rate of 10.14%. Isolation rates varied among different sample types. The highest rate was observed in cloacal swabs (14.6%, 19/130), followed by fecal samples (13.1%, 17/130), while environmental swabs exhibited the lowest isolation rate (7.9%, 34/430) (Table\u0026nbsp;4). Following 16S rDNA PCR amplification, sequencing, and BLAST analysis, all isolates displayed greater than 99% homology with reference \u003cem\u003eE. coli\u003c/em\u003e strains.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSerogroup Distribution\u003c/h2\u003e \u003cp\u003eSerogrouping of the 70 \u003cem\u003eE. coli\u003c/em\u003e isolates revealed three distinct serogroups. The predominant serogroup was O78, accounting for 34.29% (24/70) of the isolates, followed by O1 at 12.86% (9/70) and O18 at 4.29% (3/70). A substantial proportion of the isolates, specifically 48.57% (34/70), were untypeable (UT) with the antisera employed (Table\u0026nbsp;5). No significant differences in serogroup distribution were detected among isolates derived from various sample sources.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of Virulence Genes\u003c/h2\u003e \u003cp\u003eAll 70 \u003cem\u003eE. coli\u003c/em\u003e isolates exhibited the presence of at least one of the ten virulence genes screened, indicating potential pathogenicity (Table\u0026nbsp;6). The \u003cem\u003eiucD\u003c/em\u003e gene and the hemolysin gene (\u003cem\u003eHIY\u003c/em\u003e) were the most prevalent, each found in 94.29% (66/70) of the isolates. Following these, the \u003cem\u003eirp2\u003c/em\u003e and \u003cem\u003etsh\u003c/em\u003e genes were detected in 55.71% (39/70) of the isolates. The \u003cem\u003eaatA\u003c/em\u003e gene was present in 47.14% (36/70) of the isolates. Lower detection rates were observed for \u003cem\u003ecva/cvi\u003c/em\u003e (21.43%, 15/70), \u003cem\u003eiss\u003c/em\u003e (12.86%, 12/70), \u003cem\u003evat\u003c/em\u003e (8.71%, 6/70), \u003cem\u003epapC\u003c/em\u003e (8.57%, 6/70), and the pathogenicity island marker \u003cem\u003eaeA\u003c/em\u003e (8.57%, 6/70).\u003c/p\u003e \u003cp\u003eCo-occurrence analysis (Table\u0026nbsp;7) demonstrated varying degrees of association among different virulence genes. The highest co-occurrence rates were identified for the gene pairs \u003cem\u003eiucD/HIY\u003c/em\u003e, \u003cem\u003etsh/HIY\u003c/em\u003e, \u003cem\u003ecva/cvi/HIY\u003c/em\u003e, \u003cem\u003evat\u003c/em\u003e/\u003cem\u003eHIY\u003c/em\u003e, and \u003cem\u003eaeA\u003c/em\u003e/\u003cem\u003eHIY\u003c/em\u003e, with 91.4% (64/70) of isolates harboring these gene pairs simultaneously. The \u003cem\u003eirp2\u003c/em\u003e gene co-occurred with \u003cem\u003etsh\u003c/em\u003e, \u003cem\u003eiucD\u003c/em\u003e, \u003cem\u003ecva/cvi\u003c/em\u003e, \u003cem\u003evat\u003c/em\u003e, and \u003cem\u003eaeA\u003c/em\u003e in 54.3% of isolates. The \u003cem\u003eaatA\u003c/em\u003e gene exhibited co-occurrence with \u003cem\u003etsh\u003c/em\u003e, \u003cem\u003eiucD\u003c/em\u003e, \u003cem\u003ecva/cvi\u003c/em\u003e, \u003cem\u003evat\u003c/em\u003e, and \u003cem\u003eaeA\u003c/em\u003e in 51.4% of isolates. The \u003cem\u003eiss\u003c/em\u003e gene co-occurred with these genes in 17.1% of isolates. Co-occurrence involving \u003cem\u003epapC\u003c/em\u003e with the aforementioned genes was relatively low, at 8.6% (Fisher's exact test, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicated significant co-occurrence). The co-occurrence patterns of virulence genes are visualized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAntimicrobial Susceptibility Profiles\u003c/h2\u003e \u003cp\u003eThe antimicrobial resistance rates of the 70 \u003cem\u003eE. coli\u003c/em\u003e isolates to 16 antibiotics are detailed in Table\u0026nbsp;8. The highest resistance rates were recorded for erythromycin, clindamycin, and spectinomycin/lincomycin, each exhibiting a resistance rate of 100.00% (70/70). This was followed by colistin (95.71%, 67/70), apramycin sulfate (91.43%, 64/70), amoxicillin (90.00%, 63/70), ampicillin (83.96%, 58/70), enrofloxacin (78.57%, 55/70), florfenicol (75.71%, 53/70), norfloxacin (74.26%, 52/70), cefazolin (70.00%, 49/70), neomycin sulfate (70.00%, 49/70), ciprofloxacin (67.14%, 47/70), oxytetracycline hydrochloride (44.29%, 31/70), and gentamicin (35.71%, 25/70). In contrast, the lowest resistance rate was noted for amikacin, which was only 2.86% (2/70).\u003c/p\u003e \u003cp\u003eMDR analysis indicated that all isolates displayed multidrug resistance, demonstrating resistance to at least six antibiotics. A total of 16 distinct resistance patterns were identified among the isolates (Table\u0026nbsp;9). The most prevalent resistance pattern was Pattern K, which included resistance to AM, CZ, AMX, SPC, APr, NEO, FFC, E, CIP, NOR, ENY, CLN, OXY, and C, accounting for 14.3% (10/70) of the isolates. This was followed by Pattern M, which consisted of AM, AMX, GM, SPC, APr, NEO, FFC, E, CIP, NOR, ENY, CLN, OXY, and C, representing 11.4% (8/70) of the isolates. Pattern P, comprising AM, CZ, AMX, GM, SPC, APr, NEO, FFC, E, CIP, NOR, ENY, CLN, OXY, and C, also accounted for 11.4% (8/70) of the isolates. The broadest resistance profiles, represented by Patterns P, M, and L, exhibited resistance to 15 antibiotics and collectively accounted for 38.6% (27/70) of the isolates. Hierarchical clustering of resistance patterns is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of Resistance Genes\u003c/h2\u003e \u003cp\u003eThe prevalence of 14 resistance genes among 70 \u003cem\u003eE. coli\u003c/em\u003e isolates was evaluated using PCR.This assessment included β-lactam resistance genes (\u003cem\u003eblaTEM\u003c/em\u003e, \u003cem\u003eblaCTX-M\u003c/em\u003e, \u003cem\u003eblacrX-M\u003c/em\u003e, \u003cem\u003eblacrX-M-1\u003c/em\u003e, \u003cem\u003eblacrX-M-9\u003c/em\u003e, \u003cem\u003eblaZX-M\u003c/em\u003e), aminoglycoside resistance genes (\u003cem\u003estrA\u003c/em\u003e, \u003cem\u003estrB\u003c/em\u003e, \u003cem\u003egyrB\u003c/em\u003e), quinolone resistance genes (\u003cem\u003eqnrS\u003c/em\u003e), the sulfonamide resistance gene (\u003cem\u003esul1\u003c/em\u003e), the macrolide resistance gene (\u003cem\u003eermB\u003c/em\u003e), and tetracycline resistance genes (\u003cem\u003etetA\u003c/em\u003e, \u003cem\u003etetG\u003c/em\u003e). The detection rates and the number of positive isolates for each gene are presented in Table\u0026nbsp;10.\u003c/p\u003e \u003cp\u003eThe results demonstrated that the \u003cem\u003estrA\u003c/em\u003e gene had the highest detection rate at 65.7% (46/70), followed closely by \u003cem\u003egyrB\u003c/em\u003e at 62.9% (44/70) and \u003cem\u003eblacrX-M\u003c/em\u003e at 51.4% (36/70). The detection rates for the other genes were as follows: \u003cem\u003eblaTEM\u003c/em\u003e at 48.6% (34/70), \u003cem\u003eqnrS\u003c/em\u003e at 47.1% (33/70), \u003cem\u003eblaZX-M\u003c/em\u003e at 41.4% (29/70), \u003cem\u003eblaCTX\u003c/em\u003e at 40.0% (28/70), \u003cem\u003estrB\u003c/em\u003e at 38.6% (27/70), \u003cem\u003eblacrX-M-1\u003c/em\u003e at 37.1% (26/70), \u003cem\u003esul1\u003c/em\u003e at 34.3% (24/70), \u003cem\u003eblacrX-M-9\u003c/em\u003e at 32.9% (23/70), \u003cem\u003eermB\u003c/em\u003e at 27.1% (19/70), \u003cem\u003etetA\u003c/em\u003e at 54.3% (38/70), and \u003cem\u003etetG\u003c/em\u003e at 51.4% (36/70).\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this study, the prevalence, serogroup distribution, virulence gene profiles, and antimicrobial resistance of \u003cem\u003eAPEC\u003c/em\u003e isolates from broiler farms in the Changchun region were systematically characterized. The overall isolation rate was 10.14% (70/690),which is lower than rates reported in studies using samples from deceased chickens (e.g., 28.6% in a previous study). This discrepancy likely reflects differences in sample sources, as our samples were primarily collected from healthy or subclinically infected flocks and farm environments, representing carriage rather than clinical disease (Idris et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Among sample types, cloacal swabs yielded the highest isolation rate (14.6%), suggesting that cloacal sampling effectively reflects intestinal carriage, whereas environmental swabs exhibited the lowest rate (7.9%), potentially due to routine disinfection practices. Nonetheless, environmental samples remain important reservoirs for resistant bacteria and resistance genes (Liu et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSerogrouping identified O78 as the predominant serogroup (34.29%), followed by O1 (12.86%) and O18 (4.29%), consistent with findings from most domestic and international studies. O78 is recognized as a globally dominant \u003cem\u003eAPEC\u003c/em\u003e serogroup frequently associated with colibacillosis outbreaks. Notably, 48.57% of isolates were untypeable (UT), a relatively high proportion that may be attributed to low antigen expression, the emergence of novel serogroups, or limitations inherent to traditional serotyping (Ingle et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This finding underscores the need for molecular typing approaches, such as MLST or whole‑genome sequencing, in future investigations.\u003c/p\u003e \u003cp\u003eAll isolates carried at least one virulence gene, suggesting a potential for pathogenicity (Johnson and Nolan \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Jamali et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The \u003cem\u003eiucD\u003c/em\u003e and hemolysin genes exhibited the highest detection rates (94.29% each), followed by \u003cem\u003eirp2\u003c/em\u003e and \u003cem\u003etsh\u003c/em\u003e (55.71% each), and \u003cem\u003eaatA\u003c/em\u003e (47.14%). As iron acquisition system genes, \u003cem\u003eiucD\u003c/em\u003e and \u003cem\u003eirp2\u003c/em\u003e are critical for host adaptation and infection establishment (Schouler et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Co‑occurrence analysis showed that \u003cem\u003eHIY\u003c/em\u003e co‑occurred with \u003cem\u003eiucD\u003c/em\u003e, \u003cem\u003etsh\u003c/em\u003e, \u003cem\u003ecva/cvi\u003c/em\u003e, \u003cem\u003evat\u003c/em\u003e, and \u003cem\u003eaeA\u003c/em\u003e at rates exceeding 90%, indicating that most isolates harbor multiple pathogenic mechanisms simultaneously, thereby enhancing their pathogenic potential. This pattern is consistent with the molecular characteristics of highly pathogenic \u003cem\u003eAPEC\u003c/em\u003e clones (Johnson \u0026amp; Nolan, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAntimicrobial susceptibility testing showed that all isolates were multidrug‑resistant, exhibiting resistance to at least six antibiotics. Resistance rates were highest for erythromycin, clindamycin, and spectinomycin/lincomycin (100%), followed by colistin (95.71%), apramycin (91.43%), and amoxicillin (90.00%). This pattern is likely driven by the widespread use of these antimicrobials in livestock production (Elmarghani et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Notably, the high resistance rate to colistin (95.71%) is of particular concern, as it is a last‑resort drug for treating multidrug‑resistant Gram‑negative infections in humans (Jeannot, Bolard, \u0026amp; Pl\u0026eacute;siat, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In contrast, amikacin showed the lowest resistance rate (2.86%), and gentamicin remained relatively susceptible (35.71%), suggesting these agents may still represent viable treatment options (Xia et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). A total of 16 distinct resistance patterns were identified, among which Patterns P, M, and L exhibited the broadest resistance spectra (14‑15 antibiotics) and accounted for 38.6% of isolates, indicating complex dissemination and recombination of resistance genes (Petty et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResistance genes were detected at high frequencies, including \u003cem\u003estrA\u003c/em\u003e (65.7%), \u003cem\u003egyrB\u003c/em\u003e (62.9%), \u003cem\u003eblacrX‑M\u003c/em\u003e (51.4%), and \u003cem\u003eblaTEM\u003c/em\u003e (48.6%), which is consistent with reports from other regions in China.The presence of \u003cem\u003etetA\u003c/em\u003e (54.3%), \u003cem\u003etetG\u003c/em\u003e (51.4%),and \u003cem\u003esul1\u003c/em\u003e (34.3%) showed strong genotype‑phenotype concordance (Khalid et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Subedi et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Although no qnrA was detected among ciprofloxacin‑resistant isolates, suggesting that fluoroquinolone resistance in this region is primarily mediated by chromosomal mutations (e.g., \u003cem\u003egyrA\u003c/em\u003e or \u003cem\u003epapC\u003c/em\u003e) (Kareem et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), the detection of \u003cem\u003eqnrS\u003c/em\u003e (47.1%) indicates that plasmid‑mediated mechanisms also contribute.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eIn conclusion, \u003cem\u003eAPEC\u003c/em\u003e strains isolated from broiler farms in the Changchun region displayed diverse serogroups, complex virulence gene profiles, and high levels of multidrug resistance. Environmental samples serve as reservoirs for resistant bacteria and resistance genes, thereby facilitating bacterial transmission and the spread of antimicrobial resistance (Bengtsson-Palme, Kristiansson, \u0026amp; Larsson, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Enhanced biosecurity measures, prudent antimicrobial use, and the establishment of routine resistance surveillance programs are urgently needed.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, Shi Li and Hongyan Sun; methodology, Ning Xu and hongyan Liu; formal analysis, Hongyan Sun and Ning Xu; investigation, hongyan Liu and Jiyuan Yao; writing—original draft preparation, Hongyan Sun; writing—review and editing, Shi Li; supervision, Shi Li; funding acquisition, Shi Li. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Ministry of Agriculture and Rural Affairs Modern Agricultural Science and Technology Experimental Demonstration Base for Livestock and Poultry Breeding and Disease Prevention and Control (Dongfeng).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data presented in this study are available from the corresponding authors upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to the Ministry of Agriculture and Rural Affairs Modern Agricultural Science and Technology Experimental Demonstration Base for Livestock and Poultry Breeding and Disease Prevention and Control (Dongfeng) for its support, and to the laboratory members for their technical assistance and useful discussions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimal Ethics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study only involved sample collection from commercial broiler farms, and no animal experiments were conducted in this research. The sampling procedures were routine veterinary detection operations, which did not cause any pain or unnecessary harm to the broilers. All sampling activities were conducted with the full knowledge and consent of Jilin Agricultural University and the broiler farms. This study does not involve animal ethical issues that require additional ethical approval, and all operations comply with relevant animal welfare and ethical norms.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBengtsson-Palme, J., Kristiansson, E., \u0026amp; Larsson, D. 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Retrieved from https://kns.cnki.net/kcms2/article/abstract?v=Vs3rztogjcWqdShnwj8uedoP_EXAtMm0s42Z2LtvDs_HSY68eidPDjYD87RDq1Edxubo26ah569IeQqwv3Jah6FGUhmpcHvz3ExXXxNIWrIiP3xLqPYkYF7OQBLb6qAPjf8hc4SPqMsIXmuZgZ7g_32kWPZ-X4mQu7xP4NSyjo9xxU9vpjzdQ8W9OtVlr11J\u0026amp;uniplatform=NZKPT\u0026amp;language=CHS\u003c/li\u003e\n\u003cli\u003e贾雪波, 盛中伟, 肖芹, \u0026amp; 邹剑敏. (2016). 山东、安徽部分地区2016年禽致病性大肠杆菌的分子流行病学调查. \u003cem\u003e中国家禽, 38\u003c/em\u003e(19), 71-74. doi:10.16372/j.issn.1004-6364.2016.19.017\u003c/li\u003e\n\u003cli\u003e孟庆美, 王少辉, 韩先干, 韩月, 丁铲, 戴建君, \u0026amp; 于圣青. (2014). 禽致病性大肠杆菌毒力基因多重PCR方法的建立和应用. \u003cem\u003e微生物学报, 54\u003c/em\u003e(06), 696-702. doi:10.13343/j.cnki.wsxb.2014.06.013\u003c/li\u003e\n\u003cli\u003e王瑶, 张耀东, 易正飞, 信素华, 陶程琳, 李妍, . . . 王少辉. (2020). 禽致病性大肠杆菌血清型、进化分群及毒力基因的分子流行病学调查. \u003cem\u003e中国兽医科学, 50\u003c/em\u003e(09), 1159-1166. doi:10.16656/j.issn.1673-4696.2020.0138\u003c/li\u003e\n\u003cli\u003e俞佳莉, 李欣, 钱懿青, 陈洪友, 乔雪飞, \u0026amp; 盛峰松. 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(2022). \u003cem\u003e村镇易腐垃圾及其堆肥过程抗生素和抗性基因赋存状况分析.\u003c/em\u003e (硕士). 浙江大学, Retrieved from https://link.cnki.net/doi/10.27461/d.cnki.gzjdx.2022.003489 Available from Cnki\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 10 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"veterinary-research-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"verc","sideBox":"Learn more about [Veterinary Research Communications](https://www.springer.com/journal/11259)","snPcode":"11259","submissionUrl":"https://submission.nature.com/new-submission/11259/3","title":"Veterinary Research Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Broiler, Avian pathogenic Escherichia coli (APEC), Serogroup, Virulence gene, Antimicrobial resistance","lastPublishedDoi":"10.21203/rs.3.rs-9345958/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9345958/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigated the serogroup distribution, virulence gene profiles, and antimicrobial resistance of avian pathogenic \u003cem\u003eEscherichia coli\u003c/em\u003e (\u003cem\u003eAPEC\u003c/em\u003e) isolated from broiler farm environments in Changchun, China. A total of 690 samples, including cloacal swabs, fresh feces, and environmental swabs, were collected. \u003cem\u003eE. coli\u003c/em\u003e isolates were identified through bacterial culture, IMViC tests, and 16S rDNA sequencing. Serogroups were determined using slide agglutination, ten virulence-associated genes were detected by PCR, and antimicrobial susceptibility to 16 antibiotics was assessed via the disk diffusion method.Among 70 isolated strains (isolation rate:10.14%), the predominant serogroups were O78(34.29%), O1(12.86%), and O18(4.29%), with 48.57% being untypeable. All isolates carried at least one virulence gene; \u003cem\u003eiucD\u003c/em\u003e and hemolysin(\u003cem\u003eHIY\u003c/em\u003e) genes were most prevalent (94.29% each). All isolates displayed complete resistance (100%) to erythromycin, clindamycin, and spectinomycin/lincomycin, and were found to be multidrug resistant (MDR) to a minimum of six antibiotics.Resistance genes \u003cem\u003etetA\u003c/em\u003e (54.3%), \u003cem\u003etetG\u003c/em\u003e (51.4%), and \u003cem\u003esul1\u003c/em\u003e(34.3%) were frequently detected. These findings highlight diverse serogroups, complex virulence profiles, and severe MDR in \u003cem\u003eAPEC\u003c/em\u003e from broiler farms, underscoring the need for enhanced surveillance and prudent antibiotic use.\u003c/p\u003e","manuscriptTitle":"Serogroup Diversity, Virulence Gene Distribution, and Antimicrobial Resistance Profiles of Intestinal Escherichia coli in Broilers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-09 15:49:07","doi":"10.21203/rs.3.rs-9345958/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-24T08:51:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-23T10:17:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-23T10:17:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"Veterinary Research Communications","date":"2026-04-07T13:27:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"veterinary-research-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"verc","sideBox":"Learn more about [Veterinary Research Communications](https://www.springer.com/journal/11259)","snPcode":"11259","submissionUrl":"https://submission.nature.com/new-submission/11259/3","title":"Veterinary Research Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1b5691c1-aa83-4201-a18b-261010af7f36","owner":[],"postedDate":"May 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-09T15:49:07+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-09 15:49:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9345958","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9345958","identity":"rs-9345958","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}