Prevalence, antibiotic resistance, and virulence gene profiles of uropathogenic Escherichia coli (UPEC) isolated from raw milk: implications for public health

Prevalence, antibiotic resistance, and virulence gene profiles of uropathogenic Escherichia coli (UPEC) isolated from raw milk: implications for public health | 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 Research Article Prevalence, antibiotic resistance, and virulence gene profiles of uropathogenic Escherichia coli (UPEC) isolated from raw milk: implications for public health Aynur Akan, Seval Cing Yildirim, Cumhur Avsar, Zeynep Yegin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8060277/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Mar, 2026 Read the published version in Folia Microbiologica → Version 1 posted You are reading this latest preprint version Abstract Raw milk, while nutritionally valuable, may act as a reservoir for zoonotic and antibiotic-resistant microorganisms, creating a potential pathway for foodborne urinary tract infections (FUTIs). Among foodborne pathogens, Escherichia coli stands out as both a commensal and a versatile pathogen responsible for approximately 80% of uncomplicated urinary tract infections (UTIs). Increasing evidence suggests that foodborne E. coli strains carrying uropathogenic traits can contribute to community-acquired UTIs, yet this link remains insufficiently characterized. This study provides a comprehensive assessment of the prevalence, antibiotic resistance, and virulence gene profiles of E. coli isolates obtained from raw milk samples collected in rural areas of Malatya province, Türkiye. A total of 206 bacterial colonies were isolated, and 115 were confirmed as E. coli through phenotypic and biochemical tests. Antibiotic susceptibility analysis revealed complete resistance to cephalothin and variable resistance to several antibiotics, yielding a Multiple Antibiotic Resistance (MAR) index of 0.178, indicative of moderate antibiotic selection pressure. Molecular identification via 16S rRNA sequencing confirmed 51 of 69 isolates (73.91%) as E. coli with ≥ 99% similarity. Screening for ten virulence genes demonstrated that 34 of the confirmed isolates (66.60%) carried three or more virulence determinants, classifying them as potential uropathogenic E. coli (UPEC). These findings demonstrate that raw milk can serve not only as a route for E. coli contamination but also as a reservoir of multidrug-resistant and uropathogenic strains. The coexistence of antibiotic resistance and UPEC-associated virulence factors in foodborne isolates provides novel evidence linking the food chain to the emergence of FUTIs. Continuous microbiological surveillance, antibiotic stewardship, and strict hygiene protocols throughout the dairy production chain are essential to prevent foodborne urinary tract infections and protect public health. antibiotic resistance public health raw milk urinary tract infection (UTI) uropathogenic Escherichia coli (UPEC) virulence genes Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Milk proteins play a key role in tissue repair and immune system support. Regular milk consumption increases bone mineral density, thereby reducing the risk of osteoporosis, and contributes to healthy tooth development by enhancing calcium absorption (Heaney, 2000 ). Owing to its rich nutritional composition, milk supports a diverse microbial community (Quigley et al., 2013 ). Furthermore, milk intake has been associated with a lower risk of several chronic diseases, including cardiovascular disease, stroke, hypertension, colorectal cancer, metabolic syndrome, obesity, type 2 diabetes mellitus, and Alzheimer’s disease (Zhang et al., 2021 ). Despite these benefits, milk also provides a favorable environment for microbial growth, particularly for psychrotrophic bacteria; therefore, strict hygiene controls are essential during production and processing (Yalew et al., 2024 ). Among the bacterial contaminants, E. coli is one of the most frequently encountered foodborne pathogens, commonly linked to raw and undercooked meat, poultry, raw milk, and untreated water (Bielecki, 2003 ). E. coli represents a remarkable transition between commensalism and pathogenicity and, as a versatile pathogen, is responsible for more than two million human deaths annually through both intestinal and extraintestinal infections (Tenaillon et al., 2010 ). Beyond its presence in food, pathogenic E. coli is a zoonotic and versatile foodborne pathogen possessing numerous virulence genes that regulate diverse cellular processes and determine its pathogenic potential (Kaper et al., 2004 ; Li et al., 2022 ). Based on infection site, E. coli strains are broadly classified into two groups: intestinal pathogenic E. coli (IPEC), which cause gastrointestinal infections, and extraintestinal pathogenic E. coli (ExPEC), which cause infections outside the intestine. The ExPEC group includes several clinically important pathotypes, such as uropathogenic E. coli (UPEC), neonatal meningitis E. coli (NMEC), septicemia-associated E. coli (SEPEC), avian pathogenic E. coli (APEC), and mammary pathogenic E. coli (MPEC) (Sora et al., 2021 ). ExPEC strains are the predominant causative agents of urinary tract infections (UTIs), accounting for nearly 90% of community-acquired cases and most pyelonephritis episodes. Other urinary tract diseases, such as prostatitis and catheter-associated UTIs, are also frequently linked to ExPEC infections (Dale and Woodford, 2015 ; Sora et al., 2021 ). The majority of UTIs in young, otherwise healthy women are attributed to ExPEC (Poolman and Wacker, 2016 ). Since the early 2000s, ExPEC has also emerged as a major contributor to antibiotic resistance, particularly against cephalosporins and fluoroquinolones (Pitout, 2012 ). At the molecular level, Escherichia coli strains that cause urinary tract infections differ markedly from commensal isolates and are referred to as uropathogenic E. coli (UPEC) (Foxman and Brown, 2003 ). UPEC is the predominant etiological agent in both uncomplicated and complicated UTIs, and infection with UPEC increases the likelihood of recurrence within six months (Medina and Castillo-Pino, 2019 ). It accounts for approximately 75% of uncomplicated and more than half of complicated UTI cases, particularly affecting women and older adults (Zhou et al., 2023 ; Whelan et al., 2023 ). UPEC employs a broad repertoire of virulence and fitness determinants to colonize, survive, and disseminate within the urinary tract (Subashchandrabose and Mobley, 2015 ). These include fimbrial and non-fimbrial adhesins, flagella, toxins, lipopolysaccharides, polysaccharide capsules, outer-membrane vesicles, and iron-acquisition systems (Zhou et al., 2023 ). The primary target organs are the urethra, bladder, and kidneys, and severe infections may progress to bacteremia, septicemia, or urosepsis (Zhou et al., 2023 ). Biofilm formation by UPEC enhances bladder colonization and markedly increases antimicrobial resistance (Klein and Hultgren, 2020 ). UPEC-associated virulence factors can be classified by function: adherence-related (type 1, P, S, and F1C pili; Dr adhesins), toxins (HlyA, CNF1), immune-evasion factors (capsular antigens, CNF1, Yersiniabactin), and iron-uptake systems (Aerobactin, Enterobactin, Salmochelin, Yersiniabactin), as well as additional surface molecules such as Antigen 43 and flagella (Ulett et al., 2007 ; Schwan, 2008 ; Nielubowicz and Mobley, 2010 ; Chaturvedi et al., 2012 ; Flores-Mireles et al., 2015 ). Isolates carrying three or more virulence genes are generally defined as potential UPEC strains (Spurbeck et al., 2012 ; García-Meniño et al., 2022 ; García et al., 2023 ). Combinations of these genes influence infection severity, therapeutic response, and recurrence, although disease outcome also depends on host-related factors such as immune status, age, hormonal balance, and environmental conditions (Köves and Wullt, 2016 ). Foodborne urinary tract infections (FUTIs) represent a new paradigm distinct from classical foodborne illnesses, reflecting the potential role of the food chain as a reservoir for antibiotic-resistant Escherichia coli . Unlike conventional foodborne diseases, which primarily affect the gastrointestinal tract, FUTIs are characterized by urinary tract involvement without gastrointestinal symptoms. These infections are frequently caused by antibiotic-resistant E. coli strains and account for a notable proportion of community-acquired urinary tract infections. Consequently, FUTIs demand a different perspective in terms of infection dynamics and public health management (Jakobsen et al., 2010 ; Nordstrom et al., 2013 ). Increasing evidence indicates that the food chain contributes substantially to the growing prevalence of antibiotic-resistant UTIs in the community. Uropathogenic E. coli (UPEC) strains have been repeatedly detected in retail meat products, particularly poultry, suggesting a potential link between foodborne exposure and extraintestinal infections. The incidence of UTIs varies across regions depending on food production practices, antibiotic usage, and hygiene conditions, yet the overall trend reveals a continuous global increase (Priyanka et al., 2023 ). In the present study, a combination of microbiological and molecular techniques was employed to identify and characterize Escherichia coli strains isolated from raw milk samples. These complementary methods provided detailed information on species identity, phenotypic traits, antibiotic susceptibility, and virulence gene profiles. Colony morphology was first evaluated on selective and differential media, followed by biochemical confirmation using IMViC tests. Antimicrobial susceptibility was determined using the Kirby–Bauer disk diffusion method, while molecular tools—including PCR and 16S rRNA gene sequencing—were applied for accurate species identification and detection of virulence-associated genes. This integrated approach enabled a comprehensive assessment of E. coli prevalence, antibiotic resistance, and virulence characteristics, thereby supporting the identification of potential uropathogenic E. coli (UPEC) strains in raw milk. Unlike previous studies that focused solely on either antibiotic resistance or virulence profiling, our work combines both datasets to reveal the coexistence of multidrug resistance and UPEC-related virulence determinants in a food matrix. This provides novel evidence for the potential role of raw milk as a reservoir of foodborne uropathogens. By integrating molecular and phenotypic data, this study establishes a new framework for detecting and assessing uropathogenic E. coli in food matrices, emphasizing their relevance to antimicrobial resistance surveillance and public health monitoring, and providing a foundation for future risk assessment studies on foodborne uropathogens. Materials and Methods Collection of raw milk samples A total of 122 raw milk samples were collected from Malatya province between May 23, 2024- October 14, 2024. Milk samples were collected directly from the producer. The samples were obtained from rural settlements covering the Toygar, Hatunsuyu-Mahmutlu, Şahnahan, Yaka, and Eski Malatya regions (Fig. 1 ). Each ~ 50 mL milk sample was placed in sterile transport containers and transported to the Industrial Biotechnology Research Laboratory under cold chain conditions (4 ± 1°C). The samples were then subjected to pre-analysis preparation on the same day. Preliminary identification of E. coli by cultural methods Cultural methods are a fundamental step in the preliminary identification of bacteria. In this step, preliminary information about the possible presence of E. coli was obtained by evaluating the colony morphology of the bacteria on selective and/or differential media. McConkey (MAC) agar, Nutrient Agar (NA), and Eosin Methylene Blue (EMB) agar were used in this study; each medium allowed the differentiation of specific phenotypic characteristics of E. coli . MAC agar provided differentiation based on lactose fermentation, while NA was used for pure colony isolation. EMB agar, on the other hand, produced the characteristic metallic green highlights of E. coli , enabling its differentiation from other bacteria. Raw milk samples obtained from different geographical regions were delivered to the laboratory under cold chain conditions as quickly as possible. For enrichment, 1 mL of each raw milk sample was inoculated into 9 mL of sterile peptone water. This mixture was incubated at 37°C in a shaking incubator at 110 rpm for 18–24 hours. Additionally, 100 µL of raw milk samples were directly inoculated onto MAC medium using the spread plate method, and the plates were incubated at 37°C for 18–24 hours. At the end of incubation, serial dilutions were applied to enriched raw milk samples based on bacterial growth densities on the MAC agar medium. To determine the total bacterial count in the samples as individual colonies, sequential dilutions were prepared with 0.9% (w/v) physiological saline (PS) solution. For this purpose, 1 mL of each milk sample was mixed with 9 mL of PS at a 1:10 ratio, resulting in dilutions of 10⁻⁴, 10⁻⁵, 10⁻⁶, and 10⁻⁷. 0.1 mL of each dilution was taken and inoculated onto MAC agar using the spread plate method under sterile conditions. After inoculation, the plates were incubated at 37°C for 18–24 hours. Pink-red lactose-fermenting bacterial colonies observed on MAC agar were identified using a colony counter. The identified colonies were picked using a sterile needle and loop and inoculated onto EMB agar plates by streaking. The prepared plates were incubated at 37°C for 24 hours. On EMB agar, colonies with the characteristic metallic, bright green color of E. coli were observed. Samples from these metallic colonies were taken with a sterile loop and inoculated onto NA for single colony formation. The inoculated plates were incubated at 37°C for 18–24 hours to obtain pure colonies. After inoculation on NA, six of the individual colonies formed after 24–48 hours of incubation at 37°C were taken with a needle loop and inoculated onto EMB agar using the streak method for further testing of pure cultures. The inoculated plates were incubated at 37°C for 18–24 hours. This method allowed the characteristic colony morphology of bacteria to be observed more clearly on EMB agar. Isolates that reappeared on EMB agar were transferred into Brain Heart Infusion (BHI) broth prior to definitive confirmation by taking samples from three different bacterial colonies, a minimum of one and a maximum of three, from each milk sample. Characterization of E. coli isolates All stock cultures were removed from the − 80°C freezer and thawed in a container containing crushed ice to enable characterization of E. coli or other Enterobacteriacea members. Completely thawed samples (200 µL) were inoculated into 20 mL of previously prepared Mueller Hinton Broth (MHB). These cultures, prepared at approximately 1% (v/v), were incubated at 37°C and 110 rpm in a shaking incubator for 18–24 hours. Following the incubation period, Gram staining, catalase, oxidase, IMVIC, and TSI biochemical tests were performed to characterize isolates suspected of being E. coli . Antibiotic susceptibility testing Antibiogram test was performed on 120 different bacterial samples, which were identified as E. coli with biochemical tests. Kirby-Bauer disk diffusion test was used to determine the antibiotic susceptibility profiles of E. coli strains. Mueller-Hinton Agar (MHA) solid medium was used for testing cultures. 10% (v/v) culture was established by adding 200 µL of completely dissolved stock bacteria samples to 20 mL of prepared MHB. The prepared mixture was incubated at 37°C in a shaking incubator at 110 rpm for 18–24 hours. Following incubation, 100 µL of stock bacterial cultures diluted to a 0.5 McFarland standard were spread homogeneously onto the surface of the MHA using a Drigalski stick. A total of seven separate MHA plates were labeled for each bacterial culture. Three different antibiotic discs were placed on the first five of these plates, and two different antibiotic discs were placed on the remaining two plates, at distances adjusted according to CLSI (Clinical and Laboratory Standards Institute), 2022 standards. A total of 19 different antibiotics were used to determine the antibiotic susceptibility profile of each bacterial culture. Information of antibiotic discs used in this study is given in Table 1 . After the discs were placed, the plates were incubated at 37°C for 24 hours. After incubation, the inhibition zone diameters around the antibiotic discs were measured with an electronic caliper and evaluated according to CLSI, 2022 standards. Table 1 The properties of the antibiotics used in the study Antibiotic class Subclass Antibiotic name/Symbol Concentration of disc (µg) Penicillins Aminopenicillin Ampicillin (AMP/AM) 10 β-lactam/β-lactamase inhibitor combinations Piperacillin/tazobactam (PPT /TPZ) 100/10 Ampicillin/sulbactam (ASB/SAM) 10/10 Amoxicillin/clavulanic acid (AMC/AMC) 20/10 Cephems III Cefotaxime (CTX/CTX) 30 IV Cefepime (CPM/FEP) 30 II Cefuroxime (CRX/CXM) 30 Cephalosporin I Cephalotin (CFL/KF) 30 Cephalosporin III Ceftazidime (CAZ/CAZ) 30 Penems Carbapenem Ertapenem (ETP/ETP) 10 Carbapenem Meropenem (MER/MEM) 10 Aminoglycosides Gentamicin (GEN/CN) 10 Amikacin (AMI/AK) 30 Quinolones Quinolone I Nalidixic acid (NAL/NA) 30 Fluoroquinolone Norfloxacin (NOR/NOR) 10 Fluoroquinolone Ciprofloxacin (CIP/CIP) 5 Folate pathway inhibitors Trimethoprim/sulfamethoxazole (SUT/SXT) 1.25/23.75 Other antibiotics Fosfomycin (FOS/FF) 200 Nitrofuran Nitrofurantoin (NIT/F) 300 Genomic DNA isolation and identification of UPEC virulence genes with PCR For DNA isolation, stock bacterial cultures kept in 85% glycerol solution (v/v) were removed from the freezer and thawed in a container filled with crushed ice. Completely thawed samples (200 µL) were inoculated with 20 mL of previously prepared MHB. The culture prepared at 10% (v/v) was incubated at 37°C and 110 rpm for 18–24 hours. After incubation, DNA isolation of isolates suspected to be E. coli was performed using PureLink Genomic DNA Mini Kit (Thermo Fisher Scientific, Waltham, MA, USA). As shown in Online Resource 1 (Supplementary Figure S1 ), the uncropped gel image demonstrates the genomic DNA integrity of E. coli isolates prior to PCR amplification, confirming that the extracted DNA samples were intact and suitable for downstream molecular analyses. In order to evaluate the uropathogenic potential of E. coli isolates, PCR reactions of isolated bacterial genomic DNA samples were performed for the selected UPEC virulence genes. Based on the evaluation of bacterial samples' antibiogram test results according to CLSI standards, only 69 of 120 genomic DNA samples were screneed for UPEC virulence genes. Bacterial samples with similar inhibition zone values were excluded from further analysis. PCR reactions were performed using specific primers for target UPEC virulence genes. Analyzed UPEC virulence genes, primer sequences, and amplicon sizes are given in Table 2 . First, PCR amplification was performed for fimA virulence gene analysis. A total of 25 µl of PCR mixture included 2 mM MgCl 2 , 1x Taq buffer, 0.2 mM dNTP mix, 0.5 µM forward and reverse primer pair, 1.5 U Taq polymerase (Thermo Fisher Scientific, Waltham, MA, USA) and 1 µl E. coli DNA. Thermal cycler conditions were as follows: 35 cycles of 40 s at 94°C, annealing for 45 s at 60°C and extension for 60 s at 72°C. A predenaturation step for 6 min at 95°C and a final extension step for 12 min at 72°C were included. The similar PCR and thermal cycler conditions were used for the other investigated virulence genes with a difference in annealing temperatures. In PCR protocols, a 40-second annealing time at 60°C was applied for most of the investigated genes, but for iroN , kpsMII , agn43 and iutA genes, this temperature was optimized as 58°C. Fragments were run on 2.5% agarose gels stained with ethidium bromide by electrophoresis and analyzed with gel documentation system (SYNGENE Ingenius 3, England) to confirm the expected fragment sizes. 50bp DNA Ladder RTU (Ready-to-Use) (GeneDireX, Inc., Taiwan) was used in the experiments. Each DNA isolate was separately analyzed for the presence of 10 different targeted virulence genes. According to the widely accepted criterion stated in the introduction part, the status of UPEC was assigned to the isolates positive for ≥ 3 of the virulence genes. Table 2 UPEC virulence genes, primer sequences, and amplicon sizes Virulence gene Primer sequence Amplicon length (bp) hlyA F: AACAAGGATAAGCACTGTTCT R: ACCATATAAGCGGTCATTCCC 1177 papC F: GACGGCTGTACTGCAGGGTGTGGCG R: ATATCCTTTCTGCAGGGATGCAATA 328 cnf1 F: AAGATGGAGTTTCCTATGCAGGAG R: CATTCAGAGTCCTGCCCTCATTATT 498 fimA F: GTTGTTCTGTCGGCTCTGTC R: ATGGTGTTGGTTCCGTTATTC 447 fyuA F: TGATTAACCCCGCGACGGGAA R: CGCAGTAGGCACGATGTTGTA 785 vat F: AGAGACGAGACTGTATTTGC R: GTCAGGTCAGTAACGAGCAC 289 iroN F: AAGTCAAAGCAGGGGTTGCCCG R: GACGCCGACATTAAGACGCAG 667 kpsMII F: GCGCATTTGCTGATACTGTTG R: AGGTAGTTCAGACTCACACCT 578 agn43 F: CTGGAAACCGGTCTGCCCTT R: CCTGAACGCCCAGGGTGATA 433 iutA F: GGCTGGACATCATGGGAACTGG R: CGTCGGGAACGGGTAGAATCG 302 16S rRNA analysis The same number of bacterial genomic DNA samples (n = 69) analyzed for UPEC virulence genes were prepared for sequencing by applying PCR for 16S rRNA gene. PCR reaction was carried out in 50 µl total volume including 1x PCR buffer, 0.1 mM dNTP mix, 0.4 µM forward (27F: 5′-AGAGTTTGATCMTGGCTCAG-3’) and reverse (1492R: 5′-TACGGYTACCTTGTTACG ACTT-3’) universal primer pair, and 5 U Taq DNA polymerase (Thermo Fisher Scientific, Waltham, MA, USA). Thermal cycler (Techne TC-5000, California, USA) conditions for 16S rRNA analysis were as follows: 35 cycles of 60 s at 95°C, annealing for 60 s at 63°C and extension for 60 s at 72°C. A predenaturation step for 5 min at 95°C and a final extension step for 10 min at 72°C were included. PCR products were run on 1.5% agarose gels stained with ethidium bromide by electrophoresis and analyzed with gel documentation system (SYNGENE Ingenius 3, England). Amplicons that gave a single and dominant band with primers specific to the 16S rRNA gene were sent to the laboratory of AQUATAYF Biotechnology AR-GE Industry and Trade Ltd. Co. under cold chain conditions for sequence analysis. Statistical and bioinformatics analyses Correlation analysis between antibiogram and UPEC-associated genes was performed using the Past 4.03 statistical analysis program. For this purpose, resistance and intermediate susceptibility of the strains were assigned a value of '1', and susceptibility was assigned a value of '0'. Additionally, the presence of the relevant gene regions in the PCR screenings was evaluated as '1', and their absence was evaluated as '0'. Pearson correlation was applied for the analysis and significance levels were determined at p < 0.05 level. The 16S rRNA PCR products obtained in the study were sequenced by Sanger sequencing method and the obtained sequence data were compared with the NCBI database by BLAST (Basic Local Alignment Search Tool) analysis. The phylogenetic tree was constructed using the maximum likelihood method and the Tamura-Nei (1993) model. The tree with the highest log-likelihood value (-8.278.16) is presented. The starting tree for the heuristic search was selected by selecting the tree with the highest log-likelihood from among the trees obtained using the Neighbor-Joining (NJ) method (Saitou and Nei, 1987 ) and Maximum Parsimony (MP) methods. The NJ tree was constructed based on the pairwise distance matrix calculated using the Tamura-Nei (1993) model. The MP trees were selected as the tree with the shortest length among analyses conducted with 10 different random starting trees. The proportion of positions in the tree where at least one base could be unambiguously identified is indicated for each internal node. The analysis was performed with 101 nucleotide sequences covering 972 positions. Evolutionary analyses were conducted using the MEGA12 software, supporting up to 3 parallel threads (Kumar et al., 2024 ; Tamura and Nei, 1993 ; Saitou and Nei, 1987 ). Results Findings of identification of E. coli by cultural and biochemical methods A total of 122 raw milk samples were analyzed using culture-based microbiological methods. Samples were first inoculated on selective MAC agar medium. Red/pink colonies from MAC agar were transferred to EMB agar. After incubation, colonies that developed a characteristic metallic highlight on EMB agar were evaluated for preliminary identification of E. coli . Based on these preliminary evaluation criteria, a total of 206 colonies likely to be E. coli were obtained from 73 different milk samples. Pure cultures were established by selecting at least one and at most three colonies from each milk sample. Furthermore, 49 milk samples with colonies not displaying metallic highlights on EMB agar were excluded from further analysis since they did not meet the preliminary diagnostic criteria for E. coli . Based on the preliminary evaluation criteria, 59.8% of the collected milk samples were found to contain E. coli or other Enterobacter species. IMVIC tests and other basic biochemical tests were applied to 206 colonies isolated from 73 raw milk samples. According to the IMVIC test results, 115 colonies obtained from 47 milk samples showed the typical biochemical profile specific to E. coli (Indole: positive, Methyl Red: positive, Voges-Proskauer: negative, Citrate: negative). In addition, all isolates were determined to be catalase positive and oxidase negative. The TSI test revealed the typical acid/acid reaction and gas production in the isolates. Microscopic examinations using Gram staining determined that the isolates had Gram-negative rod morphology. These findings suggest that a significant portion of the bacteria isolated from raw milk samples are biochemically compatible with E. coli . The remaining 91 colonies showed incompatible results with this biochemical profile and they might belong to enteric bacteria other than E. coli . In our study, IMVIC positivity rate covers approximately 64% (47/73) of milk samples and 55.8% (115/206) of the colonies. Elimination of colonies which give negative IMVIC results before molecular identification increases the specificity of the test and reduces the likelihood of false-positive diagnoses. Antibiogram test results In the study, antibiotic resistance and susceptibility profiles of 115 isolates biochemically identified as E. coli were determined. Nineteen antibiotics were tested as previously mentioned in materials and methods section. All of the tested E. coli isolates were resistant to cephalothin. Varying degrees of resistance were observed to other antibiotics. The resistance rates were determined as follows: 0% (n = 0) norfloxacin, 0.86% (n = 1) fosfomycin, 1.73% (n = 2) cefepime, 2.6% (n = 3) piperacillin, 3.47% (n = 4) cefuroxime, 3.47% (n = 4) nitrofurantoin, 4.34% (n = 5) amikacin, 5.21% (n = 6) ciprofloxacin, 6.08% (n = 7) ertapenem, 6.08% (n = 7) amoxicillin, 6.08% (n = 7) gentamicin, 6.08% (n = 7) nalidixic acid, 6.95% (n = 8) cefotaxime, 8.69% (n = 10) sulfamethoxazole, 25.21% (n = 29) ampicillin. When antibiotic sensitivity rates were examined, it was found that the majority of the isolates showed high sensitivity to many antibiotics. The highest susceptibility rates were observed as follows: 99.13% (n = 114) fosfomycin, 96.52% (n = 111) ceftazidime and meropenem, 94.78% (n = 109) ampicillin, amikacin and cefuroxime, 93.91% (n = 108) ertapenem and ciprofloxacin, 93.04% (n = 107) amoxicillin and gentamicin, 91.3% (n = 105) nalidixic acid and sulfamethoxazole, 90.43% (n = 104) cefotaxime, 88.69% (n = 102) cefepime, 87.82% (n = 101) nitrofurantoin and norfloxacin, and 86.95% (n = 100) piperacillin. These data indicate that a significant portion of the isolates are still susceptible to broad-spectrum antibiotics. Resistance and susceptibility profiles of the isolates to various antibiotics are depicted in Table 3 . Table 3 Resistance and susceptibility profiles of the isolates to various antibiotics Antibiotic Sensitive Intermediate Resistant Positivity (%)* Negativity (%)* 1.AMP (AM-10) 85 1 29 73,9 25,21 2.AMI (AK-30) 109 1 5 94,78 4,34 3.AMC (AMC-30) 107 1 7 93,04 6,08 4.ASB (SAM-20) 109 3 3 94,78 2,6 5.CPM (FEP-30) 102 1 2 88,69 1,73 6.CTX (CTX-30) 104 3 8 90,43 6,95 7.CAZ (CAZ-30) 111 0 4 96,52 3,47 8.CRX (CXM-30) 109 2 4 94,78 3,47 9.CFL (KF-30) 0 0 115 0 100 10.CIP (CIP-5) 108 1 6 93,91 5,21 11.ETP (ETP-10) 108 0 7 93,91 6,08 12.FOS (FF-200) 114 0 1 99,13 0,86 13.GEN (CN-10) 107 1 7 93,04 6,08 14.MER (MEM-10) 111 2 2 96,52 1,73 15.NAL (NA-30) 105 3 7 91,3 6,08 16.NIT (F-300) 101 0 4 87,82 3,47 17.NOR (NOR-10) 101 4 0 87,82 0 18.PPT (TPZ-110) 100 2 3 86,95 2,6 19.SUT (SXT-25) 105 0 10 91,3 8,69 *The positivity rate represents the total percentage of isolates susceptible and intermediate to the antibiotic, while the negativity rate represents the percentage of the resistant isolates. These two rates provide a comparative analysis for evaluating antibiotic efficacy and determining the distribution of resistance. In the study, antibiotic susceptibility profiles of 115 E. coli isolates were also evaluated using descriptive statistics and ratio analysis (Fig. 2 ). The highest resistance rate was observed for the antibiotic cephalothin at 100%, followed by ampicillin at 25.21%. Resistance rates for other antibiotics were generally low and ranged from 0 to 9%. The combined report of both high resistance (25.21%) and high susceptibility (73.9%) for ampicillin may suggest heterogeneity among isolates. In particular, 100% resistance to cephalothin may indicate widespread and uncontrolled use of this antibiotic in veterinary field practice. The MAR index was calculated and interpreted according to Krumperman ( 1983 ) using the formula: a/b, where ‘a’ represents the number of antibiotics to which an isolate was resistant, and ‘b’ represents the total number of antibiotics tested (Fig. 3 ). In conclusion, the antibiogram results reveal that E. coli strains isolated from raw milk samples exhibit striking resistance profiles to some antibiotics, indicating that these bacteria may pose a potential zoonotic risk. Detection of UPEC virulence genes In the study, UPEC virulence factors were amplified by the PCR method, and their presence in E. coli isolates was evaluated. A total of ten different virulence genes were analyzed, including hlyA, papC, cnf1, fimA, fyuA, vat, iroN, kpsMII, agn43, and iutA. The PCR amplification patterns of these genes are presented in Online Resource 2 (Supplementary Figure S2), while representative amplification products from selected positive isolates are shown in Fig. 4 . Distinct amplification profiles confirmed the presence of key virulence determinants among potential UPEC isolates; however, the vat gene was not detected in all isolates. The amplification pattern of the fimA virulence gene, a major adhesion factor contributing to bacterial attachment and biofilm formation, is shown in Online Resource 3 (Supplementary Figure S3). The detection rates of UPEC virulence genes among the analyzed isolates are summarized in Table 4 . Table 4 Percentage of UPEC virulence genes in isolates Virulence gene Positive isolate (n) Percentage (%) fimA 68 98.55 fyuA 22 31.88 hlyA 18 26.09 papC 2 2.90 cnf1 3 4.35 iroN 6 8.70 kpsMII 8 11.59 agn43 66 95.65 iutA 18 26.09 vat 0 0.00 Correlation analysis between antibiogram and UPEC-associated genes When the Pearson correlation relationship between the antibiogram of the 69 tested strains and the genes screened for UPEC is examined, it is seen that many antibiotics show a positive correlation with each other at a significance level of p < 0.05. When the correlation between antibiotics and UPEC-related genes was analyzed, no significant relationship was found between fimA , fyuA , hlyA , agn43 , iutA , and vat genes and any antibiotics. In terms of correlation, very low negative or positive relationships were observed between these gene regions and antibiotics. A positive correlation was detected between papC and two antibiotics (ETP-10 and TPZ-110), cnf1 and two antibiotics (FEB-30 and FF-200), iroN and three antibiotics (AM-10, CIP-5, and NA-30), and finally kpsMII and one antibiotic (FF-200) at the p < 0.05 level. In addition, a positive correlation was found between fimA and agn43 , as well as hlyA and iroN and iutA at the p < 0.05 level (Fig. 5 ). Correlation analysis of antibiotic resistance and virulence genes In the study, we examined the relationships between antibiotic resistance profiles and some important virulence genes identified in UPEC strains, and very strong positive correlations were found (r > 0.8). The obtained correlation coefficients suggest that some virulence factors are co-carried on the same mobile genetic elements (e.g., plasmids, transposons) as resistance genes and spread together through co-selection. The correlation between amikacin (AK) and hlyA and cnf1 genes was determined as r = 0.939 and r = 0.878, respectively. Correlations between cefepime (FEP) and cefuroxime (CXM) and cnf1 were at r = 0.944 and r = 0.946, respectively, indicating that strains resistant to these two antibiotics carry the cnf1 gene at a high rate. A high correlation (r = 0.872) was also detected between cephalexin (KF) and iroN , an important component of the siderophore system. The correlation coefficient between temocillin (TPZ) and the kpsMII gene involved in capsule biosynthesis was r = 0.975, which is the strongest relationship obtained in this study. A strong correlation (r = 0.805) was also observed between meropenem (MEM), a carbapenem group antibiotic, and iroN . The correlation between fluoroquinolones norfloxacin (NOR) and iroN (r = 0.901) indicates that genes related to iron metabolism may be associated with resistance acquisition in association with mutations in DNA gyrase/topoisomerase IV, which is an antibiotic target. Molecular identification of isolates by 16S rRNA sequencing and BLAST analysis 16S rRNA gene region was amplified from genomic DNA samples of potential E. coli isolates and the amplification products were analyzed by 1.5% agarose gel electrophoresis. Dense, single bands approximately 1.500 bp in size were observed in each well of each sample. These results demonstrate that the universal primer sets used specifically amplified the targeted 16S rRNA gene region and that the PCR reactions were technically successful. 16S rRNA PCR products were sequenced using Sanger sequencing, and the resulting sequence data were compared with the NCBI database using Basic Local Alignment Search Tool (BLAST) analysis. The analyses revealed that the majority of the isolates matched reference strains of the E. coli species with high similarity rates (≥ 99%). In particular, ≥ 99% homology of the isolates with the 16S rRNA gene regions of E. coli strains allowed these microorganisms to be identified as E. coli at the species level. These results are consistent with the species identification threshold of 98% and above reported in the literature. Furthermore, the distribution of E. coli , Shigella sp., Citrobacter freundii , Stenotrophomonas maltophilia , and other species in the obtained matches was 74%, 6%, 6%, 1.4% and 13%, respectively (Fig. 6 ). Determination of UPEC potential by combined evaluation of sequencing and virulence gene analyses Sequencing analyses of the 16S rRNA gene revealed that the majority of the 69 isolates evaluated (n = 51) shared a high level of genetic similarity to Escherichia coli , ensuring species-level molecular identification accuracy. Simultaneous PCR analyses were conducted to investigate the presence of 10 UPEC-specific virulence genes, providing detailed molecular information regarding the potential pathogenicity of the isolates (Fig. 7 ). This two-stage molecular analysis strategy applied to the isolates not only provided taxonomic confirmation but also enabled the assessment of each isolate's uropathogenic potential. Based on the widely accepted criterion of carrying ≥ 3 virulence genes for UPEC diagnosis, 34 of the 51 E. coli isolates (66.60%) were classified as potential UPEC. The remaining 17 isolates were classified as non-UPEC due to inadequate virulence gene profiles. Discussion IMVIC test data demonstrate that they are an effective first-line assay for the differential diagnosis of E. coli . This is consistent with previous studies using similar sample types. For example, the classical (++--, IMVIC) profile was detected in nearly all E. coli strains isolated from raw milk samples in China, and the diagnostic accuracy of biochemical tests was reported to be high (Liu et al., 2021 ). In another study conducted in Egypt, the majority of E. coli strains obtained from milk and dairy products were found to have the classical IMVIC profile (Ombarak et al., 2016 ). In studies conducted in South Africa, PCR confirmation was performed after the suspicious strains were eliminated with IMVIC tests, and it was emphasized that biochemical tests provide significant time and resource savings (Caine et al., 2014 ). In our study, IMVIC positivity rate covered approximately 64% (47/73) of milk samples and 55.8% (115/206) of the colonies. In the study, IMVIC tests were used as an efficient method in the initial screening and differentiation phases; the exclusion of isolates showing biochemical incompatibility in the diagnosis of E. coli contributed to a specific diagnosis. However, the data obtained also demonstrate the limitations of IMVIC tests, and it should be noted that molecular confirmation methods are complementary to this process. The high overall antibiotic susceptibility rate (87–99%) found in this study is a significant finding demonstrating that E. coli strains originating from raw milk can still be effectively treated with many common antibiotics. However, comparison of resistance rates with the literature highlights regional differences. For example, another study reported higher resistance rates to ampicillin and sulfamethoxazole in broiler E. coli isolates (Jakobsen et al., 2010 ). This difference may be explained by variables such as geographic region, antibiotic use policies, and animal husbandry practices. Ten UPEC virulence genes ( hlyA , papC , cnf1 , fimA , fyuA , vat , iroN , kpsMII , agn43 , and iutA) were evaluated to determine potential UPEC isolates. FimA and papC , which are among the adhesin and colony-forming genes were the most frequent genes determined. FimA is one of the structural components of type 1 fimbriae and contributes to the bacterial infection capacity by enabling adhesion to bladder epithelial cells. This gene is commonly found in UPEC strains and was reported to play a significant role in lower urinary tract infections (Sarowska et al., 2019 ). papC is an adhesin gene involved in the formation of P fimbriae and has been associated with upper urinary tract infections, particularly pyelonephritis (Johnson, 1991 ). hlyA gene, responsible for hemolysin production, was detected in some strains. This gene targets the cell membrane and induces the production of alpha-hemolysin, which causes lysis. kpsMII gene, associated with capsule synthesis, is involved in the formation of capsular structures, which increase the bacterial resistance to phagocytosis. The presence of this gene, in particular, suppresses the immune response, allowing the bacteria to evade host defense mechanisms. Previous studies have reported that this gene is more frequently found in E. coli strains associated with severe clinical conditions such as sepsis and pyelonephritis (Roberts, 1996 ). Other important virulence factors identified in the study include the siderophore genes fyuA , iroN , and iutA , which mediate iron uptake. These genes enable the bacteria to efficiently utilize limited iron resources in host cells, providing an advantage during the infection process. It is reported in literature that these genes are highly prevalent in UPEC strains and their presence strongly correlate with virulence capacity (Johnson and Stell, 2000 ). Agn43 gene, responsible for autotransporter proteins, is associated with colony morphology, cell adhesion, and biofilm formation. The positivity of this gene in some strains supports the biofilm-forming potential of UPEC isolates (Zalewska-Pią Tek et al., 2015). The cytotoxic necrotizing factor 1 ( cnf1 ) gene disrupts epithelial cell morphology by affecting intracellular actin structures, facilitating bacterial invasion. The presence of this gene is generally associated with more severe and invasive infections. Previous studies have reported cnf1 positivity between 10% and 30% (Blanco et al., 2004 ) and our findings support this range. Vacuolating autotransporter toxin ( vat ) contributes to UPEC fitness during systemic infection (Subashchandrabose et al., 2013 ; Nichols et al., 2016 ). Positive PCR amplification of vat gene was not detected in any of the isolates evaluated in the study (0%). When all data are evaluated together, it is understood that more than one virulence gene can coexist in UPEC strains, increasing the pathogenic capacity of the bacteria. The most commonly detected gene in the virulence gene analysis was fimA . This gene was detected positive in all isolates (98.55%) except one. The second commonly detected gene was agn43 (95.65%). These genes were followed by the less commonly detected genes such as fyuA (31.88%), hlyA (26.09%) and iutA (26.09%). The prevalence of fimA in UPEC from UTI patients changed between 100% and 76% (Abdul Raheem Hasan, 2021; Zamani and Salehzadeh, 2018 ). The most frequent gene combination was reported as fimA - agn43 in Mexican unpasteurised fresh cheeses similar to our results (Guzman-Hernandez et al., 2016 ). fyuA gene was present between 60.1% and 77% of the UPEC clinical isolates (Habibi et al., 2017 ; Rezatofighi et al., 2021 ). hlyA prevalence changed between 10%- 67.5% in UPEC from clinical samples (Valadbeigi et al., 2019 ; Helmy et al., 2023 ). iutA prevalence changed between 100% and 62.2% in UPEC isolated from clinical samples (Munkhdelger et al., 2017 ; Arafa et al., 2022 ). In general, the majority of isolates carried between two and four virulence genes. One of the commonly used criteria for UPEC identification is the presence of at least three different virulence genes (Brons et al., 2020 ; Derakhshan et al., 2022 ). UPEC highlight the distinctiveness of the coexistence of gene clusters corresponding to key pathogenicity functions such as adhesion, toxicity, and iron uptake (Spurbeck et al., 2012 ). In this study, 51 of the 69 isolates evaluated in terms of sequencing and virulence gene analysis were determined to belong to the E. coli species, and 34 of these isolates (66.60%) could be considered potential UPEC. When the correlation analysis between antibiotics considered, strong positive correlations were observed between AMP and antibiotics such as AMC and CTX (dark blue ellipses). Based on these data, it may be predicted that all three antibiotics generally undergo the same resistance mechanism (e.g., beta-lactamase production) and may thus induce cross-resistance. Significant positive correlations were found between CIP, NAL, and NOR, suggesting cross-resistance, which is common among quinolones, and the effectiveness of shared targets (e.g., DNA gyrase). Since DNA gyrase is an enzyme found only in prokaryotes and is vital for bacterial growth, it may be considered as an ideal target for quinolone antibiotics (Fàbrega et al., 2009 ). In E. coli , mutations occurring in the gyrA gene can significantly increase nalidixic acid resistance, while other mutations occurring in the gyrA or topoisomerase IV gene regions additionally lead to the development of high-level resistance to fluoroquinolones (Hopkins et al., 2005 ). Quinolone resistance can negatively affect the treatment process, and the spread of resistance genes through horizontal gene transfer can make the control of infectious diseases more complex. Positive correlations were also found between aminoglycosides such as GEN and KAN. These correlations are expected to be strong because of their common target, protein synthesis inhibition. Though antibiotic resistance can not be considered a direct virulence factor, it can have determinative effects on the development and course of infection under certain biological and clinical conditions. In particular, the ability of an antibiotic-resistant bacterial strain to effectively colonize specific anatomical sites within the host may lead to increased pathogenicity and treatment failure (Beceiro et al., 2013 ). In terms of infection dynamics, antibiotic resistance and virulence are complex interacting properties rather than two completely independent phenomena. Therefore, evaluation of both features together is of critical significance in understanding infections and developing targeted treatment strategies. Correlation analysis of antibiotic resistance and virulence genes were emphasized in results section. The findings demonstrate statistically significant and biologically explainable relationships between antibiotic resistance profiles and specific virulence genes in UPEC strains. The predominance of genes such as cnf1 , hlyA , iroN , and kpsMII in strains with high resistance profiles suggests that these pathogens exhibit both treatment resistance and invasiveness. This poses a serious threat in hospital-acquired infections and should be considered in determining antimicrobial treatment strategies. UPEC potential was determined by combined evaluation of sequencing and virulence gene analyses as detailed results are presented in the article. Based on the widely accepted criterion of carrying ≥ 3 virulence genes for UPEC diagnosis, 34 of the 51 E. coli isolates (66.60%) were classified as potential UPEC. In our study, the high prevalence of UPEC in E. coli isolates (66.60%) from raw milk indicates that dairy products can be a serious vector not only for microbial contamination but also for potentially virulent zoonotic strains. This finding highlights the potential for UPEC strains to be transmitted to humans through the food chain and poses a significant public health threat to food safety. Conclusion The comprehensive investigation of raw milk samples from rural Malatya revealed critical insights into the public health risks posed by Escherichia coli contamination, antibiotic resistance, and uropathogenic potential. Using an integrative workflow that combined phenotypic identification, molecular verification, antibiogram testing, and virulence gene profiling, 206 bacterial colonies were isolated, of which 115 were confirmed as E. coli . Antibiotic susceptibility testing demonstrated universal resistance to cephalothin, highlighting uncontrolled antibiotic use in veterinary practice. The calculated Multiple Antibiotic Resistance (MAR) index of 0.178 reflected moderate antibiotic selection pressure among isolates. Species-level confirmation via 16S rRNA gene sequencing and BLAST analysis showed that 51 of 69 analyzed isolates (73.91%) shared ≥ 99% sequence homology with E. coli reference strains. Screening for 10 virulence genes revealed that 34 of the 51 confirmed isolates (66.60%) carried at least three virulence determinants, classifying them as potential uropathogenic E. coli (UPEC). These findings illustrate that raw milk may act not only as a carrier of E. coli contamination but also as a potential reservoir for multidrug-resistant and uropathogenic strains. Raw milk should therefore be recognized as both a valuable food source and a possible vector of infection when processing and hygiene standards are inadequate. Strengthening microbiological surveillance, promoting rational antibiotic use, and implementing rigorous hygiene measures throughout the dairy production chain—from milking to retail—are essential to reduce foodborne transmission risks. Scientific data–driven training and monitoring programs will play a pivotal role in preventing infections, particularly urinary tract infections, and safeguarding public health. Declarations Author contributions Seval Cing Yildirim: Conceptualization, Project administration, Supervision, Methodology, Investigation, Formal analysis, Writing – review & editing. Aynur Akan: Methodology, Investigation, Formal analysis, Writing – review & editing. Cumhur Avsar: Conceptualization, Methodology, Investigation, Formal analysis, Writing – review & editing. Zeynep Yegin: Conceptualization, Supervision, Methodology, Investigation, Formal analysis, Writing – original draft. All authors reviewed and accepted the final manuscript. Funding This work was supported by Inonu University Scientific Research Projects Coordination Unit (project ID: 3513). Clinical trial number: Not applicable. Data availability Data will be made available on request. Competing interests The authors declare no competing interests. References Abdul Raheem Hasan S, Sajid Al-Jubori S, Abdul Sattar Salman J. Molecular Analysis of fimA Operon Genes among UPEC Local Isolates in Baghdad City. 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Published 2023 Jun 23. doi:10.3390/ijms241310537 Additional Declarations No competing interests reported. Supplementary Files SupplementaryInformationFigures.docx Cite Share Download PDF Status: Published Journal Publication published 26 Mar, 2026 Read the published version in Folia Microbiologica → Version 1 posted 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-8060277","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":561871945,"identity":"4d92952a-2012-4709-9b65-dc2caeba9119","order_by":0,"name":"Aynur Akan","email":"","orcid":"","institution":"Inonu University","correspondingAuthor":false,"prefix":"","firstName":"Aynur","middleName":"","lastName":"Akan","suffix":""},{"id":561871946,"identity":"069688b5-94bd-42a4-8f79-7499a19b6b9e","order_by":1,"name":"Seval Cing 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13:10:03","extension":"xml","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":175734,"visible":true,"origin":"","legend":"","description":"","filename":"9e45d78a40ab4ad5ae2963f82b01a37c1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8060277/v1/c562096bf02beddf88b70bb1.xml"},{"id":98518941,"identity":"4ed9a3e6-4a78-4e32-9e7b-bcd08e07132f","added_by":"auto","created_at":"2025-12-18 13:10:04","extension":"html","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":188900,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8060277/v1/2f627cb323913cbef8d4e246.html"},{"id":98624777,"identity":"20057468-640f-460b-9d02-88dcaab4f780","added_by":"auto","created_at":"2025-12-19 17:08:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":266088,"visible":true,"origin":"","legend":"\u003cp\u003eGeographical locations of raw milk sampling from five selected regions of Malatya, Turkey.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8060277/v1/4ad82af10538c37714e45c65.png"},{"id":98518921,"identity":"c26de8fc-d1bb-42a1-9c28-eed0f1941378","added_by":"auto","created_at":"2025-12-18 13:10:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":27060,"visible":true,"origin":"","legend":"\u003cp\u003eResistance (red) and susceptibility (green) rates of \u003cem\u003eE. coli\u003c/em\u003e strains isolated from raw milk samples against different antibiotics. The graph shows the results of 115 isolates tested against 19 different antibiotic agents.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8060277/v1/6cb7d1b65d82eb1027f40f49.png"},{"id":98625457,"identity":"03613e2e-9910-443e-a2ab-703a1a2eb9d1","added_by":"auto","created_at":"2025-12-19 17:09:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":87677,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical representation of MAR index and MDR status of the isolates\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8060277/v1/733849adc538494df5b616c8.png"},{"id":98518932,"identity":"421ffe67-ee48-49e2-b893-9554e4a909f4","added_by":"auto","created_at":"2025-12-18 13:10:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":446996,"visible":true,"origin":"","legend":"\u003cp\u003eGel image of UPEC virulence genes. In the upper gel: strains positive for the \u003cem\u003efimA\u003c/em\u003e(1, 8, 17, 45, and 99); strains positive for \u003cem\u003ehlyA\u003c/em\u003e (3, 6, and 28); strains positive for \u003cem\u003ekpsMII\u003c/em\u003e (20, 30, and 44); strains positive for \u003cem\u003epapC \u003c/em\u003e(8 and 81); and in the lower gel: strains positive for \u003cem\u003efyuA\u003c/em\u003e (8, 10, and 49); strains positive for \u003cem\u003eiroN\u003c/em\u003e (46, 47, and 61); strains positive for \u003cem\u003eagn43\u003c/em\u003e (5, 6, and 33); strains positive for \u003cem\u003eiutA\u003c/em\u003e (1, 6, and 83); strains positive for \u003cem\u003ecnf1\u003c/em\u003e (99, 102, and 106), M: Marker (50 bp DNA Ladder RTU (Ready-to-Use), GeneDireX, Taiwan).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8060277/v1/d058e6fc3f1f7016094fbfec.png"},{"id":98518936,"identity":"63fe1586-978e-4e46-8945-63d33b56efb2","added_by":"auto","created_at":"2025-12-18 13:10:04","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":308602,"visible":true,"origin":"","legend":"\u003cp\u003eGraph showing the Pearson correlation between the antibiogram and UPEC-associated genes. Boxes indicate a significance level of p\u0026lt;0.05. Red dots indicate a negative correlation, while blue dots indicate a positive correlation (The size of the dots indicates the magnitude of the correlation).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8060277/v1/b12d7eaa29b78e6bddfc7282.png"},{"id":98518939,"identity":"56f07455-8b5e-4e42-94a4-0a410a0b13ce","added_by":"auto","created_at":"2025-12-18 13:10:04","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":221236,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic tree of the isolates analyzed in the study* Evolutionary analysis with maximum likelihood method\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8060277/v1/43bd5668eef978ceceddd03e.png"},{"id":98518935,"identity":"61b39825-cea4-4ac5-93b5-68404b64793a","added_by":"auto","created_at":"2025-12-18 13:10:04","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":100113,"visible":true,"origin":"","legend":"\u003cp\u003eSpecies distribution of isolates based on BLAST analysis\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8060277/v1/cac5b1b984089020c8c3babb.png"},{"id":105755161,"identity":"8682016d-bc58-4268-bde7-cb9a84d439f9","added_by":"auto","created_at":"2026-03-30 16:26:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2805974,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8060277/v1/d5a7ecec-fb56-4b5c-ad25-bc239b1a4ef8.pdf"},{"id":98518917,"identity":"3041c7d5-5921-4e29-bf80-e184f9bdd343","added_by":"auto","created_at":"2025-12-18 13:10:02","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":413862,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformationFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-8060277/v1/058ecb2971212e8e67b2a848.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence, antibiotic resistance, and virulence gene profiles of uropathogenic Escherichia coli (UPEC) isolated from raw milk: implications for public health","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMilk proteins play a key role in tissue repair and immune system support. Regular milk consumption increases bone mineral density, thereby reducing the risk of osteoporosis, and contributes to healthy tooth development by enhancing calcium absorption (Heaney, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Owing to its rich nutritional composition, milk supports a diverse microbial community (Quigley et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Furthermore, milk intake has been associated with a lower risk of several chronic diseases, including cardiovascular disease, stroke, hypertension, colorectal cancer, metabolic syndrome, obesity, type 2 diabetes mellitus, and Alzheimer\u0026rsquo;s disease (Zhang et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite these benefits, milk also provides a favorable environment for microbial growth, particularly for psychrotrophic bacteria; therefore, strict hygiene controls are essential during production and processing (Yalew et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Among the bacterial contaminants, \u003cem\u003eE. coli\u003c/em\u003e is one of the most frequently encountered foodborne pathogens, commonly linked to raw and undercooked meat, poultry, raw milk, and untreated water (Bielecki, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). \u003cem\u003eE. coli\u003c/em\u003e represents a remarkable transition between commensalism and pathogenicity and, as a versatile pathogen, is responsible for more than two million human deaths annually through both intestinal and extraintestinal infections (Tenaillon et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBeyond its presence in food, pathogenic \u003cem\u003eE. coli\u003c/em\u003e is a zoonotic and versatile foodborne pathogen possessing numerous virulence genes that regulate diverse cellular processes and determine its pathogenic potential (Kaper et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Based on infection site, \u003cem\u003eE. coli\u003c/em\u003e strains are broadly classified into two groups: intestinal pathogenic \u003cem\u003eE. coli\u003c/em\u003e (IPEC), which cause gastrointestinal infections, and extraintestinal pathogenic \u003cem\u003eE. coli\u003c/em\u003e (ExPEC), which cause infections outside the intestine. The ExPEC group includes several clinically important pathotypes, such as uropathogenic \u003cem\u003eE. coli\u003c/em\u003e (UPEC), neonatal meningitis \u003cem\u003eE. coli\u003c/em\u003e (NMEC), septicemia-associated \u003cem\u003eE. coli\u003c/em\u003e (SEPEC), avian pathogenic \u003cem\u003eE. coli\u003c/em\u003e (APEC), and mammary pathogenic \u003cem\u003eE. coli\u003c/em\u003e (MPEC) (Sora et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eExPEC strains are the predominant causative agents of urinary tract infections (UTIs), accounting for nearly 90% of community-acquired cases and most pyelonephritis episodes. Other urinary tract diseases, such as prostatitis and catheter-associated UTIs, are also frequently linked to ExPEC infections (Dale and Woodford, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sora et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The majority of UTIs in young, otherwise healthy women are attributed to ExPEC (Poolman and Wacker, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Since the early 2000s, ExPEC has also emerged as a major contributor to antibiotic resistance, particularly against cephalosporins and fluoroquinolones (Pitout, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAt the molecular level, \u003cem\u003eEscherichia coli\u003c/em\u003e strains that cause urinary tract infections differ markedly from commensal isolates and are referred to as uropathogenic \u003cem\u003eE. coli\u003c/em\u003e (UPEC) (Foxman and Brown, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). UPEC is the predominant etiological agent in both uncomplicated and complicated UTIs, and infection with UPEC increases the likelihood of recurrence within six months (Medina and Castillo-Pino, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). It accounts for approximately 75% of uncomplicated and more than half of complicated UTI cases, particularly affecting women and older adults (Zhou et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Whelan et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUPEC employs a broad repertoire of virulence and fitness determinants to colonize, survive, and disseminate within the urinary tract (Subashchandrabose and Mobley, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). These include fimbrial and non-fimbrial adhesins, flagella, toxins, lipopolysaccharides, polysaccharide capsules, outer-membrane vesicles, and iron-acquisition systems (Zhou et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The primary target organs are the urethra, bladder, and kidneys, and severe infections may progress to bacteremia, septicemia, or urosepsis (Zhou et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Biofilm formation by UPEC enhances bladder colonization and markedly increases antimicrobial resistance (Klein and Hultgren, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUPEC-associated virulence factors can be classified by function: adherence-related (type 1, P, S, and F1C pili; Dr adhesins), toxins (HlyA, CNF1), immune-evasion factors (capsular antigens, CNF1, Yersiniabactin), and iron-uptake systems (Aerobactin, Enterobactin, Salmochelin, Yersiniabactin), as well as additional surface molecules such as Antigen 43 and flagella (Ulett et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Schwan, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Nielubowicz and Mobley, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Chaturvedi et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Flores-Mireles et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Isolates carrying three or more virulence genes are generally defined as potential UPEC strains (Spurbeck et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Garc\u0026iacute;a-Meni\u0026ntilde;o et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Garc\u0026iacute;a et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Combinations of these genes influence infection severity, therapeutic response, and recurrence, although disease outcome also depends on host-related factors such as immune status, age, hormonal balance, and environmental conditions (K\u0026ouml;ves and Wullt, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFoodborne urinary tract infections (FUTIs) represent a new paradigm distinct from classical foodborne illnesses, reflecting the potential role of the food chain as a reservoir for antibiotic-resistant \u003cem\u003eEscherichia coli\u003c/em\u003e. Unlike conventional foodborne diseases, which primarily affect the gastrointestinal tract, FUTIs are characterized by urinary tract involvement without gastrointestinal symptoms. These infections are frequently caused by antibiotic-resistant \u003cem\u003eE. coli\u003c/em\u003e strains and account for a notable proportion of community-acquired urinary tract infections. Consequently, FUTIs demand a different perspective in terms of infection dynamics and public health management (Jakobsen et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Nordstrom et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIncreasing evidence indicates that the food chain contributes substantially to the growing prevalence of antibiotic-resistant UTIs in the community. Uropathogenic \u003cem\u003eE. coli\u003c/em\u003e (UPEC) strains have been repeatedly detected in retail meat products, particularly poultry, suggesting a potential link between foodborne exposure and extraintestinal infections. The incidence of UTIs varies across regions depending on food production practices, antibiotic usage, and hygiene conditions, yet the overall trend reveals a continuous global increase (Priyanka et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the present study, a combination of microbiological and molecular techniques was employed to identify and characterize \u003cem\u003eEscherichia coli\u003c/em\u003e strains isolated from raw milk samples. These complementary methods provided detailed information on species identity, phenotypic traits, antibiotic susceptibility, and virulence gene profiles. Colony morphology was first evaluated on selective and differential media, followed by biochemical confirmation using IMViC tests. Antimicrobial susceptibility was determined using the Kirby\u0026ndash;Bauer disk diffusion method, while molecular tools\u0026mdash;including PCR and 16S rRNA gene sequencing\u0026mdash;were applied for accurate species identification and detection of virulence-associated genes.\u003c/p\u003e \u003cp\u003eThis integrated approach enabled a comprehensive assessment of \u003cem\u003eE. coli\u003c/em\u003e prevalence, antibiotic resistance, and virulence characteristics, thereby supporting the identification of potential uropathogenic \u003cem\u003eE. coli\u003c/em\u003e (UPEC) strains in raw milk. Unlike previous studies that focused solely on either antibiotic resistance or virulence profiling, our work combines both datasets to reveal the coexistence of multidrug resistance and UPEC-related virulence determinants in a food matrix. This provides novel evidence for the potential role of raw milk as a reservoir of foodborne uropathogens. By integrating molecular and phenotypic data, this study establishes a new framework for detecting and assessing uropathogenic \u003cem\u003eE. coli\u003c/em\u003e in food matrices, emphasizing their relevance to antimicrobial resistance surveillance and public health monitoring, and providing a foundation for future risk assessment studies on foodborne uropathogens.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCollection of raw milk samples\u003c/h2\u003e \u003cp\u003eA total of 122 raw milk samples were collected from Malatya province between May 23, 2024- October 14, 2024. Milk samples were collected directly from the producer. The samples were obtained from rural settlements covering the Toygar, Hatunsuyu-Mahmutlu, Şahnahan, Yaka, and Eski Malatya regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Each ~\u0026thinsp;50 mL milk sample was placed in sterile transport containers and transported to the Industrial Biotechnology Research Laboratory under cold chain conditions (4\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C). The samples were then subjected to pre-analysis preparation on the same day.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ePreliminary identification of\u003c/b\u003e \u003cb\u003eE. coli\u003c/b\u003e \u003cb\u003eby cultural methods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCultural methods are a fundamental step in the preliminary identification of bacteria. In this step, preliminary information about the possible presence of \u003cem\u003eE. coli\u003c/em\u003e was obtained by evaluating the colony morphology of the bacteria on selective and/or differential media. McConkey (MAC) agar, Nutrient Agar (NA), and Eosin Methylene Blue (EMB) agar were used in this study; each medium allowed the differentiation of specific phenotypic characteristics of \u003cem\u003eE. coli\u003c/em\u003e. MAC agar provided differentiation based on lactose fermentation, while NA was used for pure colony isolation. EMB agar, on the other hand, produced the characteristic metallic green highlights of \u003cem\u003eE. coli\u003c/em\u003e, enabling its differentiation from other bacteria.\u003c/p\u003e \u003cp\u003eRaw milk samples obtained from different geographical regions were delivered to the laboratory under cold chain conditions as quickly as possible. For enrichment, 1 mL of each raw milk sample was inoculated into 9 mL of sterile peptone water. This mixture was incubated at 37\u0026deg;C in a shaking incubator at 110 rpm for 18\u0026ndash;24 hours. Additionally, 100 \u0026micro;L of raw milk samples were directly inoculated onto MAC medium using the spread plate method, and the plates were incubated at 37\u0026deg;C for 18\u0026ndash;24 hours. At the end of incubation, serial dilutions were applied to enriched raw milk samples based on bacterial growth densities on the MAC agar medium. To determine the total bacterial count in the samples as individual colonies, sequential dilutions were prepared with 0.9% (w/v) physiological saline (PS) solution. For this purpose, 1 mL of each milk sample was mixed with 9 mL of PS at a 1:10 ratio, resulting in dilutions of 10⁻⁴, 10⁻⁵, 10⁻⁶, and 10⁻⁷. 0.1 mL of each dilution was taken and inoculated onto MAC agar using the spread plate method under sterile conditions. After inoculation, the plates were incubated at 37\u0026deg;C for 18\u0026ndash;24 hours.\u003c/p\u003e \u003cp\u003ePink-red lactose-fermenting bacterial colonies observed on MAC agar were identified using a colony counter. The identified colonies were picked using a sterile needle and loop and inoculated onto EMB agar plates by streaking. The prepared plates were incubated at 37\u0026deg;C for 24 hours. On EMB agar, colonies with the characteristic metallic, bright green color of \u003cem\u003eE. coli\u003c/em\u003e were observed. Samples from these metallic colonies were taken with a sterile loop and inoculated onto NA for single colony formation. The inoculated plates were incubated at 37\u0026deg;C for 18\u0026ndash;24 hours to obtain pure colonies.\u003c/p\u003e \u003cp\u003eAfter inoculation on NA, six of the individual colonies formed after 24\u0026ndash;48 hours of incubation at 37\u0026deg;C were taken with a needle loop and inoculated onto EMB agar using the streak method for further testing of pure cultures. The inoculated plates were incubated at 37\u0026deg;C for 18\u0026ndash;24 hours. This method allowed the characteristic colony morphology of bacteria to be observed more clearly on EMB agar.\u003c/p\u003e \u003cp\u003eIsolates that reappeared on EMB agar were transferred into Brain Heart Infusion (BHI) broth prior to definitive confirmation by taking samples from three different bacterial colonies, a minimum of one and a maximum of three, from each milk sample.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCharacterization of\u003c/b\u003e \u003cb\u003eE. coli\u003c/b\u003e \u003cb\u003eisolates\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAll stock cultures were removed from the \u0026minus;\u0026thinsp;80\u0026deg;C freezer and thawed in a container containing crushed ice to enable characterization of \u003cem\u003eE. coli\u003c/em\u003e or other Enterobacteriacea members. Completely thawed samples (200 \u0026micro;L) were inoculated into 20 mL of previously prepared Mueller Hinton Broth (MHB). These cultures, prepared at approximately 1% (v/v), were incubated at 37\u0026deg;C and 110 rpm in a shaking incubator for 18\u0026ndash;24 hours. Following the incubation period, Gram staining, catalase, oxidase, IMVIC, and TSI biochemical tests were performed to characterize isolates suspected of being \u003cem\u003eE. coli\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAntibiotic susceptibility testing\u003c/h3\u003e\n\u003cp\u003eAntibiogram test was performed on 120 different bacterial samples, which were identified as \u003cem\u003eE. coli\u003c/em\u003e with biochemical tests. Kirby-Bauer disk diffusion test was used to determine the antibiotic susceptibility profiles of \u003cem\u003eE. coli\u003c/em\u003e strains. Mueller-Hinton Agar (MHA) solid medium was used for testing cultures. 10% (v/v) culture was established by adding 200 \u0026micro;L of completely dissolved stock bacteria samples to 20 mL of prepared MHB. The prepared mixture was incubated at 37\u0026deg;C in a shaking incubator at 110 rpm for 18\u0026ndash;24 hours. Following incubation, 100 \u0026micro;L of stock bacterial cultures diluted to a 0.5 McFarland standard were spread homogeneously onto the surface of the MHA using a Drigalski stick. A total of seven separate MHA plates were labeled for each bacterial culture. Three different antibiotic discs were placed on the first five of these plates, and two different antibiotic discs were placed on the remaining two plates, at distances adjusted according to CLSI (Clinical and Laboratory Standards Institute), 2022 standards. A total of 19 different antibiotics were used to determine the antibiotic susceptibility profile of each bacterial culture. Information of antibiotic discs used in this study is given in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. After the discs were placed, the plates were incubated at 37\u0026deg;C for 24 hours. After incubation, the inhibition zone diameters around the antibiotic discs were measured with an electronic caliper and evaluated according to CLSI, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e standards.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe properties of the antibiotics used in the study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntibiotic class\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubclass\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAntibiotic name/Symbol\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConcentration of disc (\u0026micro;g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePenicillins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAminopenicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmpicillin (AMP/AM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eβ-lactam/β-lactamase inhibitor combinations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePiperacillin/tazobactam\u003c/p\u003e \u003cp\u003e(PPT /TPZ)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100/10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmpicillin/sulbactam\u003c/p\u003e \u003cp\u003e(ASB/SAM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10/10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmoxicillin/clavulanic acid\u003c/p\u003e \u003cp\u003e(AMC/AMC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20/10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCephems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCefotaxime (CTX/CTX)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCefepime (CPM/FEP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCefuroxime (CRX/CXM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCephalosporin I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCephalotin (CFL/KF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCephalosporin III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCeftazidime (CAZ/CAZ)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePenems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarbapenem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eErtapenem (ETP/ETP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarbapenem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMeropenem (MER/MEM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAminoglycosides\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGentamicin (GEN/CN)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmikacin (AMI/AK)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuinolones\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuinolone I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNalidixic acid (NAL/NA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFluoroquinolone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNorfloxacin (NOR/NOR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFluoroquinolone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCiprofloxacin (CIP/CIP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFolate pathway inhibitors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTrimethoprim/sulfamethoxazole (SUT/SXT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.25/23.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther antibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFosfomycin (FOS/FF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNitrofuran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNitrofurantoin (NIT/F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eGenomic DNA isolation and identification of UPEC virulence genes with PCR\u003c/h3\u003e\n\u003cp\u003eFor DNA isolation, stock bacterial cultures kept in 85% glycerol solution (v/v) were removed from the freezer and thawed in a container filled with crushed ice. Completely thawed samples (200 \u0026micro;L) were inoculated with 20 mL of previously prepared MHB. The culture prepared at 10% (v/v) was incubated at 37\u0026deg;C and 110 rpm for 18\u0026ndash;24 hours. After incubation, DNA isolation of isolates suspected to be \u003cem\u003eE. coli\u003c/em\u003e was performed using PureLink Genomic DNA Mini Kit (Thermo Fisher Scientific, Waltham, MA, USA). As shown in Online Resource 1 (Supplementary Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), the uncropped gel image demonstrates the genomic DNA integrity of E. coli isolates prior to PCR amplification, confirming that the extracted DNA samples were intact and suitable for downstream molecular analyses.\u003c/p\u003e \u003cp\u003eIn order to evaluate the uropathogenic potential of \u003cem\u003eE. coli\u003c/em\u003e isolates, PCR reactions of isolated bacterial genomic DNA samples were performed for the selected UPEC virulence genes. Based on the evaluation of bacterial samples' antibiogram test results according to CLSI standards, only 69 of 120 genomic DNA samples were screneed for UPEC virulence genes. Bacterial samples with similar inhibition zone values were excluded from further analysis. PCR reactions were performed using specific primers for target UPEC virulence genes. Analyzed UPEC virulence genes, primer sequences, and amplicon sizes are given in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. First, PCR amplification was performed for \u003cem\u003efimA\u003c/em\u003e virulence gene analysis. A total of 25 \u0026micro;l of PCR mixture included 2 mM MgCl\u003csub\u003e2\u003c/sub\u003e, 1x Taq buffer, 0.2 mM dNTP mix, 0.5 \u0026micro;M forward and reverse primer pair, 1.5 U Taq polymerase (Thermo Fisher Scientific, Waltham, MA, USA) and 1 \u0026micro;l \u003cem\u003eE. coli\u003c/em\u003e DNA. Thermal cycler conditions were as follows: 35 cycles of 40 s at 94\u0026deg;C, annealing for 45 s at 60\u0026deg;C and extension for 60 s at 72\u0026deg;C. A predenaturation step for 6 min at 95\u0026deg;C and a final extension step for 12 min at 72\u0026deg;C were included. The similar PCR and thermal cycler conditions were used for the other investigated virulence genes with a difference in annealing temperatures. In PCR protocols, a 40-second annealing time at 60\u0026deg;C was applied for most of the investigated genes, but for \u003cem\u003eiroN\u003c/em\u003e, \u003cem\u003ekpsMII\u003c/em\u003e, \u003cem\u003eagn43\u003c/em\u003e and \u003cem\u003eiutA\u003c/em\u003e genes, this temperature was optimized as 58\u0026deg;C. Fragments were run on 2.5% agarose gels stained with ethidium bromide by electrophoresis and analyzed with gel documentation system (SYNGENE Ingenius 3, England) to confirm the expected fragment sizes. 50bp DNA Ladder RTU (Ready-to-Use) (GeneDireX, Inc., Taiwan) was used in the experiments. Each DNA isolate was separately analyzed for the presence of 10 different targeted virulence genes. According to the widely accepted criterion stated in the introduction part, the status of UPEC was assigned to the isolates positive for \u0026ge;\u0026thinsp;3 of the virulence genes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUPEC virulence genes, primer sequences, and amplicon sizes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVirulence gene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimer sequence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmplicon length (bp)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ehlyA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: AACAAGGATAAGCACTGTTCT\u003c/p\u003e \u003cp\u003eR: ACCATATAAGCGGTCATTCCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003epapC\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: GACGGCTGTACTGCAGGGTGTGGCG\u003c/p\u003e \u003cp\u003eR: ATATCCTTTCTGCAGGGATGCAATA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e328\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ecnf1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: AAGATGGAGTTTCCTATGCAGGAG\u003c/p\u003e \u003cp\u003eR: CATTCAGAGTCCTGCCCTCATTATT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e498\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003efimA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: GTTGTTCTGTCGGCTCTGTC\u003c/p\u003e \u003cp\u003eR: ATGGTGTTGGTTCCGTTATTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e447\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003efyuA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: TGATTAACCCCGCGACGGGAA\u003c/p\u003e \u003cp\u003eR: CGCAGTAGGCACGATGTTGTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e785\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003evat\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: AGAGACGAGACTGTATTTGC\u003c/p\u003e \u003cp\u003eR: GTCAGGTCAGTAACGAGCAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e289\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eiroN\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: AAGTCAAAGCAGGGGTTGCCCG\u003c/p\u003e \u003cp\u003eR: GACGCCGACATTAAGACGCAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ekpsMII\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: GCGCATTTGCTGATACTGTTG\u003c/p\u003e \u003cp\u003eR: AGGTAGTTCAGACTCACACCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e578\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eagn43\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: CTGGAAACCGGTCTGCCCTT\u003c/p\u003e \u003cp\u003eR: CCTGAACGCCCAGGGTGATA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e433\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eiutA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: GGCTGGACATCATGGGAACTGG\u003c/p\u003e \u003cp\u003eR: CGTCGGGAACGGGTAGAATCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e16S rRNA analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe same number of bacterial genomic DNA samples (n\u0026thinsp;=\u0026thinsp;69) analyzed for UPEC virulence genes were prepared for sequencing by applying PCR for 16S rRNA gene. PCR reaction was carried out in 50 \u0026micro;l total volume including 1x PCR buffer, 0.1 mM dNTP mix, 0.4 \u0026micro;M forward (27F: 5\u0026prime;-AGAGTTTGATCMTGGCTCAG-3\u0026rsquo;) and reverse (1492R: 5\u0026prime;-TACGGYTACCTTGTTACG ACTT-3\u0026rsquo;) universal primer pair, and 5 U Taq DNA polymerase (Thermo Fisher Scientific, Waltham, MA, USA). Thermal cycler (Techne TC-5000, California, USA) conditions for 16S rRNA analysis were as follows: 35 cycles of 60 s at 95\u0026deg;C, annealing for 60 s at 63\u0026deg;C and extension for 60 s at 72\u0026deg;C. A predenaturation step for 5 min at 95\u0026deg;C and a final extension step for 10 min at 72\u0026deg;C were included. PCR products were run on 1.5% agarose gels stained with ethidium bromide by electrophoresis and analyzed with gel documentation system (SYNGENE Ingenius 3, England). Amplicons that gave a single and dominant band with primers specific to the 16S rRNA gene were sent to the laboratory of AQUATAYF Biotechnology AR-GE Industry and Trade Ltd. Co. under cold chain conditions for sequence analysis.\u003c/p\u003e\n\u003ch3\u003eStatistical and bioinformatics analyses\u003c/h3\u003e\n\u003cp\u003eCorrelation analysis between antibiogram and UPEC-associated genes was performed using the Past 4.03 statistical analysis program. For this purpose, resistance and intermediate susceptibility of the strains were assigned a value of '1', and susceptibility was assigned a value of '0'. Additionally, the presence of the relevant gene regions in the PCR screenings was evaluated as '1', and their absence was evaluated as '0'. Pearson correlation was applied for the analysis and significance levels were determined at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 level.\u003c/p\u003e \u003cp\u003eThe 16S rRNA PCR products obtained in the study were sequenced by Sanger sequencing method and the obtained sequence data were compared with the NCBI database by BLAST (Basic Local Alignment Search Tool) analysis. The phylogenetic tree was constructed using the maximum likelihood method and the Tamura-Nei (1993) model. The tree with the highest log-likelihood value (-8.278.16) is presented. The starting tree for the heuristic search was selected by selecting the tree with the highest log-likelihood from among the trees obtained using the Neighbor-Joining (NJ) method (Saitou and Nei, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1987\u003c/span\u003e) and Maximum Parsimony (MP) methods. The NJ tree was constructed based on the pairwise distance matrix calculated using the Tamura-Nei (1993) model. The MP trees were selected as the tree with the shortest length among analyses conducted with 10 different random starting trees. The proportion of positions in the tree where at least one base could be unambiguously identified is indicated for each internal node. The analysis was performed with 101 nucleotide sequences covering 972 positions. Evolutionary analyses were conducted using the MEGA12 software, supporting up to 3 parallel threads (Kumar et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Tamura and Nei, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Saitou and Nei, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1987\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eFindings of identification of\u003c/b\u003e \u003cb\u003eE. coli\u003c/b\u003e \u003cb\u003eby cultural and biochemical methods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA total of 122 raw milk samples were analyzed using culture-based microbiological methods. Samples were first inoculated on selective MAC agar medium. Red/pink colonies from MAC agar were transferred to EMB agar. After incubation, colonies that developed a characteristic metallic highlight on EMB agar were evaluated for preliminary identification of \u003cem\u003eE. coli\u003c/em\u003e. Based on these preliminary evaluation criteria, a total of 206 colonies likely to be \u003cem\u003eE. coli\u003c/em\u003e were obtained from 73 different milk samples. Pure cultures were established by selecting at least one and at most three colonies from each milk sample. Furthermore, 49 milk samples with colonies not displaying metallic highlights on EMB agar were excluded from further analysis since they did not meet the preliminary diagnostic criteria for \u003cem\u003eE. coli\u003c/em\u003e. Based on the preliminary evaluation criteria, 59.8% of the collected milk samples were found to contain \u003cem\u003eE. coli\u003c/em\u003e or other \u003cem\u003eEnterobacter\u003c/em\u003e species.\u003c/p\u003e \u003cp\u003eIMVIC tests and other basic biochemical tests were applied to 206 colonies isolated from 73 raw milk samples. According to the IMVIC test results, 115 colonies obtained from 47 milk samples showed the typical biochemical profile specific to \u003cem\u003eE. coli\u003c/em\u003e (Indole: positive, Methyl Red: positive, Voges-Proskauer: negative, Citrate: negative). In addition, all isolates were determined to be catalase positive and oxidase negative. The TSI test revealed the typical acid/acid reaction and gas production in the isolates. Microscopic examinations using Gram staining determined that the isolates had Gram-negative rod morphology. These findings suggest that a significant portion of the bacteria isolated from raw milk samples are biochemically compatible with \u003cem\u003eE. coli\u003c/em\u003e. The remaining 91 colonies showed incompatible results with this biochemical profile and they might belong to enteric bacteria other than \u003cem\u003eE. coli\u003c/em\u003e. In our study, IMVIC positivity rate covers approximately 64% (47/73) of milk samples and 55.8% (115/206) of the colonies. Elimination of colonies which give negative IMVIC results before molecular identification increases the specificity of the test and reduces the likelihood of false-positive diagnoses.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAntibiogram test results\u003c/h2\u003e \u003cp\u003eIn the study, antibiotic resistance and susceptibility profiles of 115 isolates biochemically identified as \u003cem\u003eE. coli\u003c/em\u003e were determined. Nineteen antibiotics were tested as previously mentioned in materials and methods section. All of the tested \u003cem\u003eE. coli\u003c/em\u003e isolates were resistant to cephalothin. Varying degrees of resistance were observed to other antibiotics. The resistance rates were determined as follows: 0% (n\u0026thinsp;=\u0026thinsp;0) norfloxacin, 0.86% (n\u0026thinsp;=\u0026thinsp;1) fosfomycin, 1.73% (n\u0026thinsp;=\u0026thinsp;2) cefepime, 2.6% (n\u0026thinsp;=\u0026thinsp;3) piperacillin, 3.47% (n\u0026thinsp;=\u0026thinsp;4) cefuroxime, 3.47% (n\u0026thinsp;=\u0026thinsp;4) nitrofurantoin, 4.34% (n\u0026thinsp;=\u0026thinsp;5) amikacin, 5.21% (n\u0026thinsp;=\u0026thinsp;6) ciprofloxacin, 6.08% (n\u0026thinsp;=\u0026thinsp;7) ertapenem, 6.08% (n\u0026thinsp;=\u0026thinsp;7) amoxicillin, 6.08% (n\u0026thinsp;=\u0026thinsp;7) gentamicin, 6.08% (n\u0026thinsp;=\u0026thinsp;7) nalidixic acid, 6.95% (n\u0026thinsp;=\u0026thinsp;8) cefotaxime, 8.69% (n\u0026thinsp;=\u0026thinsp;10) sulfamethoxazole, 25.21% (n\u0026thinsp;=\u0026thinsp;29) ampicillin. When antibiotic sensitivity rates were examined, it was found that the majority of the isolates showed high sensitivity to many antibiotics. The highest susceptibility rates were observed as follows: 99.13% (n\u0026thinsp;=\u0026thinsp;114) fosfomycin, 96.52% (n\u0026thinsp;=\u0026thinsp;111) ceftazidime and meropenem, 94.78% (n\u0026thinsp;=\u0026thinsp;109) ampicillin, amikacin and cefuroxime, 93.91% (n\u0026thinsp;=\u0026thinsp;108) ertapenem and ciprofloxacin, 93.04% (n\u0026thinsp;=\u0026thinsp;107) amoxicillin and gentamicin, 91.3% (n\u0026thinsp;=\u0026thinsp;105) nalidixic acid and sulfamethoxazole, 90.43% (n\u0026thinsp;=\u0026thinsp;104) cefotaxime, 88.69% (n\u0026thinsp;=\u0026thinsp;102) cefepime, 87.82% (n\u0026thinsp;=\u0026thinsp;101) nitrofurantoin and norfloxacin, and 86.95% (n\u0026thinsp;=\u0026thinsp;100) piperacillin. These data indicate that a significant portion of the isolates are still susceptible to broad-spectrum antibiotics. Resistance and susceptibility profiles of the isolates to various antibiotics are depicted in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResistance and susceptibility profiles of the isolates to various antibiotics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntibiotic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eResistant\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePositivity (%)*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNegativity (%)*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.AMP (AM-10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e73,9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e25,21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.AMI (AK-30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94,78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4,34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.AMC (AMC-30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93,04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6,08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.ASB (SAM-20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94,78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.CPM (FEP-30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88,69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.CTX (CTX-30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90,43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6,95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7.CAZ (CAZ-30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e96,52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3,47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8.CRX (CXM-30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94,78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3,47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9.CFL (KF-30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10.CIP (CIP-5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93,91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5,21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11.ETP (ETP-10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93,91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6,08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12.FOS (FF-200)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99,13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13.GEN (CN-10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93,04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6,08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14.MER (MEM-10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e96,52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15.NAL (NA-30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e91,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6,08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16.NIT (F-300)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e87,82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3,47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17.NOR (NOR-10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e87,82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18.PPT (TPZ-110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e86,95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19.SUT (SXT-25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e91,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8,69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*The positivity rate represents the total percentage of isolates susceptible and intermediate to the antibiotic, while the negativity rate represents the percentage of the resistant isolates. These two rates provide a comparative analysis for evaluating antibiotic efficacy and determining the distribution of resistance.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the study, antibiotic susceptibility profiles of 115 \u003cem\u003eE. coli\u003c/em\u003e isolates were also evaluated using descriptive statistics and ratio analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The highest resistance rate was observed for the antibiotic cephalothin at 100%, followed by ampicillin at 25.21%. Resistance rates for other antibiotics were generally low and ranged from 0 to 9%. The combined report of both high resistance (25.21%) and high susceptibility (73.9%) for ampicillin may suggest heterogeneity among isolates. In particular, 100% resistance to cephalothin may indicate widespread and uncontrolled use of this antibiotic in veterinary field practice. The MAR index was calculated and interpreted according to Krumperman (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1983\u003c/span\u003e) using the formula: a/b, where \u0026lsquo;a\u0026rsquo; represents the number of antibiotics to which an isolate was resistant, and \u0026lsquo;b\u0026rsquo; represents the total number of antibiotics tested (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In conclusion, the antibiogram results reveal that \u003cem\u003eE. coli\u003c/em\u003e strains isolated from raw milk samples exhibit striking resistance profiles to some antibiotics, indicating that these bacteria may pose a potential zoonotic risk.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDetection of UPEC virulence genes\u003c/h3\u003e\n\u003cp\u003eIn the study, UPEC virulence factors were amplified by the PCR method, and their presence in E. coli isolates was evaluated. A total of ten different virulence genes were analyzed, including hlyA, papC, cnf1, fimA, fyuA, vat, iroN, kpsMII, agn43, and iutA. The PCR amplification patterns of these genes are presented in Online Resource 2 (Supplementary Figure S2), while representative amplification products from selected positive isolates are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Distinct amplification profiles confirmed the presence of key virulence determinants among potential UPEC isolates; however, the vat gene was not detected in all isolates. The amplification pattern of the fimA virulence gene, a major adhesion factor contributing to bacterial attachment and biofilm formation, is shown in Online Resource 3 (Supplementary Figure S3). The detection rates of UPEC virulence genes among the analyzed isolates are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePercentage of UPEC virulence genes in isolates\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVirulence gene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive isolate (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003efimA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e98.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003efyuA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ehlyA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003epapC\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ecnf1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eiroN\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ekpsMII\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eagn43\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eiutA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003evat\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eCorrelation analysis between antibiogram and UPEC-associated genes\u003c/h3\u003e\n\u003cp\u003eWhen the Pearson correlation relationship between the antibiogram of the 69 tested strains and the genes screened for UPEC is examined, it is seen that many antibiotics show a positive correlation with each other at a significance level of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. When the correlation between antibiotics and UPEC-related genes was analyzed, no significant relationship was found between \u003cem\u003efimA\u003c/em\u003e, \u003cem\u003efyuA\u003c/em\u003e, \u003cem\u003ehlyA\u003c/em\u003e, \u003cem\u003eagn43\u003c/em\u003e, \u003cem\u003eiutA\u003c/em\u003e, and \u003cem\u003evat\u003c/em\u003e genes and any antibiotics. In terms of correlation, very low negative or positive relationships were observed between these gene regions and antibiotics. A positive correlation was detected between \u003cem\u003epapC\u003c/em\u003e and two antibiotics (ETP-10 and TPZ-110), \u003cem\u003ecnf1\u003c/em\u003e and two antibiotics (FEB-30 and FF-200), \u003cem\u003eiroN\u003c/em\u003e and three antibiotics (AM-10, CIP-5, and NA-30), and finally \u003cem\u003ekpsMII\u003c/em\u003e and one antibiotic (FF-200) at the p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 level. In addition, a positive correlation was found between \u003cem\u003efimA\u003c/em\u003e and \u003cem\u003eagn43\u003c/em\u003e, as well as \u003cem\u003ehlyA\u003c/em\u003e and \u003cem\u003eiroN\u003c/em\u003e and \u003cem\u003eiutA\u003c/em\u003e at the p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 level (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation analysis of antibiotic resistance and virulence genes\u003c/h2\u003e \u003cp\u003eIn the study, we examined the relationships between antibiotic resistance profiles and some important virulence genes identified in UPEC strains, and very strong positive correlations were found (r\u0026thinsp;\u0026gt;\u0026thinsp;0.8). The obtained correlation coefficients suggest that some virulence factors are co-carried on the same mobile genetic elements (e.g., plasmids, transposons) as resistance genes and spread together through co-selection. The correlation between amikacin (AK) and \u003cem\u003ehlyA\u003c/em\u003e and \u003cem\u003ecnf1\u003c/em\u003e genes was determined as r\u0026thinsp;=\u0026thinsp;0.939 and r\u0026thinsp;=\u0026thinsp;0.878, respectively. Correlations between cefepime (FEP) and cefuroxime (CXM) and \u003cem\u003ecnf1\u003c/em\u003e were at r\u0026thinsp;=\u0026thinsp;0.944 and r\u0026thinsp;=\u0026thinsp;0.946, respectively, indicating that strains resistant to these two antibiotics carry the \u003cem\u003ecnf1\u003c/em\u003e gene at a high rate. A high correlation (r\u0026thinsp;=\u0026thinsp;0.872) was also detected between cephalexin (KF) and \u003cem\u003eiroN\u003c/em\u003e, an important component of the siderophore system. The correlation coefficient between temocillin (TPZ) and the \u003cem\u003ekpsMII\u003c/em\u003e gene involved in capsule biosynthesis was r\u0026thinsp;=\u0026thinsp;0.975, which is the strongest relationship obtained in this study. A strong correlation (r\u0026thinsp;=\u0026thinsp;0.805) was also observed between meropenem (MEM), a carbapenem group antibiotic, and \u003cem\u003eiroN\u003c/em\u003e. The correlation between fluoroquinolones norfloxacin (NOR) and \u003cem\u003eiroN\u003c/em\u003e (r\u0026thinsp;=\u0026thinsp;0.901) indicates that genes related to iron metabolism may be associated with resistance acquisition in association with mutations in DNA gyrase/topoisomerase IV, which is an antibiotic target.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMolecular identification of isolates by 16S rRNA sequencing and BLAST analysis\u003c/h2\u003e \u003cp\u003e16S rRNA gene region was amplified from genomic DNA samples of potential \u003cem\u003eE. coli\u003c/em\u003e isolates and the amplification products were analyzed by 1.5% agarose gel electrophoresis. Dense, single bands approximately 1.500 bp in size were observed in each well of each sample. These results demonstrate that the universal primer sets used specifically amplified the targeted 16S rRNA gene region and that the PCR reactions were technically successful.\u003c/p\u003e \u003cp\u003e16S rRNA PCR products were sequenced using Sanger sequencing, and the resulting sequence data were compared with the NCBI database using Basic Local Alignment Search Tool (BLAST) analysis. The analyses revealed that the majority of the isolates matched reference strains of the \u003cem\u003eE. coli\u003c/em\u003e species with high similarity rates (\u0026ge;\u0026thinsp;99%). In particular, \u0026ge;\u0026thinsp;99% homology of the isolates with the 16S rRNA gene regions of \u003cem\u003eE. coli\u003c/em\u003e strains allowed these microorganisms to be identified as \u003cem\u003eE. coli\u003c/em\u003e at the species level. These results are consistent with the species identification threshold of 98% and above reported in the literature. Furthermore, the distribution of \u003cem\u003eE. coli\u003c/em\u003e, \u003cem\u003eShigella\u003c/em\u003e sp., \u003cem\u003eCitrobacter freundii\u003c/em\u003e, \u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e, and other species in the obtained matches was 74%, 6%, 6%, 1.4% and 13%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDetermination of UPEC potential by combined evaluation of sequencing and virulence gene analyses\u003c/h2\u003e \u003cp\u003eSequencing analyses of the 16S rRNA gene revealed that the majority of the 69 isolates evaluated (n\u0026thinsp;=\u0026thinsp;51) shared a high level of genetic similarity to \u003cem\u003eEscherichia coli\u003c/em\u003e, ensuring species-level molecular identification accuracy. Simultaneous PCR analyses were conducted to investigate the presence of 10 UPEC-specific virulence genes, providing detailed molecular information regarding the potential pathogenicity of the isolates (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis two-stage molecular analysis strategy applied to the isolates not only provided taxonomic confirmation but also enabled the assessment of each isolate's uropathogenic potential. Based on the widely accepted criterion of carrying\u0026thinsp;\u0026ge;\u0026thinsp;3 virulence genes for UPEC diagnosis, 34 of the 51 \u003cem\u003eE. coli\u003c/em\u003e isolates (66.60%) were classified as potential UPEC. The remaining 17 isolates were classified as non-UPEC due to inadequate virulence gene profiles.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIMVIC test data demonstrate that they are an effective first-line assay for the differential diagnosis of \u003cem\u003eE. coli\u003c/em\u003e. This is consistent with previous studies using similar sample types. For example, the classical (++--, IMVIC) profile was detected in nearly all \u003cem\u003eE. coli\u003c/em\u003e strains isolated from raw milk samples in China, and the diagnostic accuracy of biochemical tests was reported to be high (Liu et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In another study conducted in Egypt, the majority of \u003cem\u003eE. coli\u003c/em\u003e strains obtained from milk and dairy products were found to have the classical IMVIC profile (Ombarak et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In studies conducted in South Africa, PCR confirmation was performed after the suspicious strains were eliminated with IMVIC tests, and it was emphasized that biochemical tests provide significant time and resource savings (Caine et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In our study, IMVIC positivity rate covered approximately 64% (47/73) of milk samples and 55.8% (115/206) of the colonies. In the study, IMVIC tests were used as an efficient method in the initial screening and differentiation phases; the exclusion of isolates showing biochemical incompatibility in the diagnosis of \u003cem\u003eE. coli\u003c/em\u003e contributed to a specific diagnosis. However, the data obtained also demonstrate the limitations of IMVIC tests, and it should be noted that molecular confirmation methods are complementary to this process.\u003c/p\u003e \u003cp\u003eThe high overall antibiotic susceptibility rate (87\u0026ndash;99%) found in this study is a significant finding demonstrating that \u003cem\u003eE. coli\u003c/em\u003e strains originating from raw milk can still be effectively treated with many common antibiotics. However, comparison of resistance rates with the literature highlights regional differences. For example, another study reported higher resistance rates to ampicillin and sulfamethoxazole in broiler \u003cem\u003eE. coli\u003c/em\u003e isolates (Jakobsen et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). This difference may be explained by variables such as geographic region, antibiotic use policies, and animal husbandry practices.\u003c/p\u003e \u003cp\u003eTen UPEC virulence genes (\u003cem\u003ehlyA\u003c/em\u003e, \u003cem\u003epapC\u003c/em\u003e, \u003cem\u003ecnf1\u003c/em\u003e, \u003cem\u003efimA\u003c/em\u003e, \u003cem\u003efyuA\u003c/em\u003e, \u003cem\u003evat\u003c/em\u003e, \u003cem\u003eiroN\u003c/em\u003e, \u003cem\u003ekpsMII\u003c/em\u003e, \u003cem\u003eagn43\u003c/em\u003e, and \u003cem\u003eiutA)\u003c/em\u003e were evaluated to determine potential UPEC isolates. \u003cem\u003eFimA\u003c/em\u003e and \u003cem\u003epapC\u003c/em\u003e, which are among the adhesin and colony-forming genes were the most frequent genes determined. \u003cem\u003eFimA\u003c/em\u003e is one of the structural components of type 1 fimbriae and contributes to the bacterial infection capacity by enabling adhesion to bladder epithelial cells. This gene is commonly found in UPEC strains and was reported to play a significant role in lower urinary tract infections (Sarowska et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). \u003cem\u003epapC\u003c/em\u003e is an adhesin gene involved in the formation of P fimbriae and has been associated with upper urinary tract infections, particularly pyelonephritis (Johnson, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). \u003cem\u003ehlyA\u003c/em\u003e gene, responsible for hemolysin production, was detected in some strains. This gene targets the cell membrane and induces the production of alpha-hemolysin, which causes lysis. \u003cem\u003ekpsMII\u003c/em\u003e gene, associated with capsule synthesis, is involved in the formation of capsular structures, which increase the bacterial resistance to phagocytosis. The presence of this gene, in particular, suppresses the immune response, allowing the bacteria to evade host defense mechanisms. Previous studies have reported that this gene is more frequently found in \u003cem\u003eE. coli\u003c/em\u003e strains associated with severe clinical conditions such as sepsis and pyelonephritis (Roberts, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). Other important virulence factors identified in the study include the siderophore genes \u003cem\u003efyuA\u003c/em\u003e, \u003cem\u003eiroN\u003c/em\u003e, and \u003cem\u003eiutA\u003c/em\u003e, which mediate iron uptake. These genes enable the bacteria to efficiently utilize limited iron resources in host cells, providing an advantage during the infection process. It is reported in literature that these genes are highly prevalent in UPEC strains and their presence strongly correlate with virulence capacity (Johnson and Stell, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). \u003cem\u003eAgn43\u003c/em\u003e gene, responsible for autotransporter proteins, is associated with colony morphology, cell adhesion, and biofilm formation. The positivity of this gene in some strains supports the biofilm-forming potential of UPEC isolates (Zalewska-Pią Tek et al., 2015). The cytotoxic necrotizing factor 1 (\u003cem\u003ecnf1\u003c/em\u003e) gene disrupts epithelial cell morphology by affecting intracellular actin structures, facilitating bacterial invasion. The presence of this gene is generally associated with more severe and invasive infections. Previous studies have reported \u003cem\u003ecnf1\u003c/em\u003e positivity between 10% and 30% (Blanco et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) and our findings support this range. Vacuolating autotransporter toxin (\u003cem\u003evat\u003c/em\u003e) contributes to UPEC fitness during systemic infection (Subashchandrabose et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Nichols et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Positive PCR amplification of \u003cem\u003evat\u003c/em\u003e gene was not detected in any of the isolates evaluated in the study (0%). When all data are evaluated together, it is understood that more than one virulence gene can coexist in UPEC strains, increasing the pathogenic capacity of the bacteria. The most commonly detected gene in the virulence gene analysis was \u003cem\u003efimA\u003c/em\u003e. This gene was detected positive in all isolates (98.55%) except one. The second commonly detected gene was \u003cem\u003eagn43\u003c/em\u003e (95.65%). These genes were followed by the less commonly detected genes such as \u003cem\u003efyuA\u003c/em\u003e (31.88%), \u003cem\u003ehlyA\u003c/em\u003e (26.09%) and \u003cem\u003eiutA\u003c/em\u003e (26.09%). The prevalence of \u003cem\u003efimA\u003c/em\u003e in UPEC from UTI patients changed between 100% and 76% (Abdul Raheem Hasan, 2021; Zamani and Salehzadeh, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The most frequent gene combination was reported as \u003cem\u003efimA\u003c/em\u003e-\u003cem\u003eagn43\u003c/em\u003e in Mexican unpasteurised fresh cheeses similar to our results (Guzman-Hernandez et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). \u003cem\u003efyuA\u003c/em\u003e gene was present between 60.1% and 77% of the UPEC clinical isolates (Habibi et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Rezatofighi et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). \u003cem\u003ehlyA\u003c/em\u003e prevalence changed between 10%- 67.5% in UPEC from clinical samples (Valadbeigi et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Helmy et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). \u003cem\u003eiutA\u003c/em\u003e prevalence changed between 100% and 62.2% in UPEC isolated from clinical samples (Munkhdelger et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Arafa et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In general, the majority of isolates carried between two and four virulence genes. One of the commonly used criteria for UPEC identification is the presence of at least three different virulence genes (Brons et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Derakhshan et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). UPEC highlight the distinctiveness of the coexistence of gene clusters corresponding to key pathogenicity functions such as adhesion, toxicity, and iron uptake (Spurbeck et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In this study, 51 of the 69 isolates evaluated in terms of sequencing and virulence gene analysis were determined to belong to the \u003cem\u003eE. coli\u003c/em\u003e species, and 34 of these isolates (66.60%) could be considered potential UPEC.\u003c/p\u003e \u003cp\u003eWhen the correlation analysis between antibiotics considered, strong positive correlations were observed between AMP and antibiotics such as AMC and CTX (dark blue ellipses). Based on these data, it may be predicted that all three antibiotics generally undergo the same resistance mechanism (e.g., beta-lactamase production) and may thus induce cross-resistance. Significant positive correlations were found between CIP, NAL, and NOR, suggesting cross-resistance, which is common among quinolones, and the effectiveness of shared targets (e.g., DNA gyrase). Since DNA gyrase is an enzyme found only in prokaryotes and is vital for bacterial growth, it may be considered as an ideal target for quinolone antibiotics (F\u0026agrave;brega et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). In \u003cem\u003eE. coli\u003c/em\u003e, mutations occurring in the \u003cem\u003egyrA\u003c/em\u003e gene can significantly increase nalidixic acid resistance, while other mutations occurring in the \u003cem\u003egyrA\u003c/em\u003e or \u003cem\u003etopoisomerase IV\u003c/em\u003e gene regions additionally lead to the development of high-level resistance to fluoroquinolones (Hopkins et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Quinolone resistance can negatively affect the treatment process, and the spread of resistance genes through horizontal gene transfer can make the control of infectious diseases more complex. Positive correlations were also found between aminoglycosides such as GEN and KAN. These correlations are expected to be strong because of their common target, protein synthesis inhibition. Though antibiotic resistance can not be considered a direct virulence factor, it can have determinative effects on the development and course of infection under certain biological and clinical conditions. In particular, the ability of an antibiotic-resistant bacterial strain to effectively colonize specific anatomical sites within the host may lead to increased pathogenicity and treatment failure (Beceiro et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In terms of infection dynamics, antibiotic resistance and virulence are complex interacting properties rather than two completely independent phenomena. Therefore, evaluation of both features together is of critical significance in understanding infections and developing targeted treatment strategies.\u003c/p\u003e \u003cp\u003eCorrelation analysis of antibiotic resistance and virulence genes were emphasized in results section. The findings demonstrate statistically significant and biologically explainable relationships between antibiotic resistance profiles and specific virulence genes in UPEC strains. The predominance of genes such as \u003cem\u003ecnf1\u003c/em\u003e, \u003cem\u003ehlyA\u003c/em\u003e, \u003cem\u003eiroN\u003c/em\u003e, and \u003cem\u003ekpsMII\u003c/em\u003e in strains with high resistance profiles suggests that these pathogens exhibit both treatment resistance and invasiveness. This poses a serious threat in hospital-acquired infections and should be considered in determining antimicrobial treatment strategies.\u003c/p\u003e \u003cp\u003eUPEC potential was determined by combined evaluation of sequencing and virulence gene analyses as detailed results are presented in the article. Based on the widely accepted criterion of carrying\u0026thinsp;\u0026ge;\u0026thinsp;3 virulence genes for UPEC diagnosis, 34 of the 51 \u003cem\u003eE. coli\u003c/em\u003e isolates (66.60%) were classified as potential UPEC. In our study, the high prevalence of UPEC in \u003cem\u003eE. coli\u003c/em\u003e isolates (66.60%) from raw milk indicates that dairy products can be a serious vector not only for microbial contamination but also for potentially virulent zoonotic strains. This finding highlights the potential for UPEC strains to be transmitted to humans through the food chain and poses a significant public health threat to food safety.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe comprehensive investigation of raw milk samples from rural Malatya revealed critical insights into the public health risks posed by \u003cem\u003eEscherichia coli\u003c/em\u003e contamination, antibiotic resistance, and uropathogenic potential. Using an integrative workflow that combined phenotypic identification, molecular verification, antibiogram testing, and virulence gene profiling, 206 bacterial colonies were isolated, of which 115 were confirmed as \u003cem\u003eE. coli\u003c/em\u003e. Antibiotic susceptibility testing demonstrated universal resistance to cephalothin, highlighting uncontrolled antibiotic use in veterinary practice. The calculated Multiple Antibiotic Resistance (MAR) index of 0.178 reflected moderate antibiotic selection pressure among isolates.\u003c/p\u003e \u003cp\u003eSpecies-level confirmation via 16S rRNA gene sequencing and BLAST analysis showed that 51 of 69 analyzed isolates (73.91%) shared\u0026thinsp;\u0026ge;\u0026thinsp;99% sequence homology with \u003cem\u003eE. coli\u003c/em\u003e reference strains. Screening for 10 virulence genes revealed that 34 of the 51 confirmed isolates (66.60%) carried at least three virulence determinants, classifying them as potential uropathogenic \u003cem\u003eE. coli\u003c/em\u003e (UPEC). These findings illustrate that raw milk may act not only as a carrier of \u003cem\u003eE. coli\u003c/em\u003e contamination but also as a potential reservoir for multidrug-resistant and uropathogenic strains.\u003c/p\u003e \u003cp\u003eRaw milk should therefore be recognized as both a valuable food source and a possible vector of infection when processing and hygiene standards are inadequate. Strengthening microbiological surveillance, promoting rational antibiotic use, and implementing rigorous hygiene measures throughout the dairy production chain\u0026mdash;from milking to retail\u0026mdash;are essential to reduce foodborne transmission risks. Scientific data\u0026ndash;driven training and monitoring programs will play a pivotal role in preventing infections, particularly urinary tract infections, and safeguarding public health.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSeval Cing Yildirim:\u0026nbsp;\u003c/strong\u003eConceptualization, Project administration, Supervision, \u0026nbsp; Methodology, Investigation, Formal analysis, Writing \u0026ndash; review \u0026amp; editing.\u003cstrong\u003e\u0026nbsp;Aynur Akan:\u0026nbsp;\u003c/strong\u003eMethodology, Investigation, Formal analysis, Writing \u0026ndash; review \u0026amp; editing. \u003cstrong\u003eCumhur Avsar:\u0026nbsp;\u003c/strong\u003eConceptualization, \u0026nbsp;Methodology, Investigation, Formal analysis, Writing \u0026ndash; review \u0026amp; editing.\u003cstrong\u003e\u0026nbsp;Zeynep Yegin:\u0026nbsp;\u003c/strong\u003eConceptualization, Supervision, \u0026nbsp;Methodology, Investigation, Formal analysis, \u0026nbsp;Writing \u0026ndash; original draft. All authors reviewed and accepted the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Inonu University Scientific Research Projects Coordination Unit (project ID: 3513).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Competing interests\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbdul Raheem Hasan S, Sajid Al-Jubori S, Abdul Sattar Salman J. Molecular Analysis of fimA Operon Genes among UPEC Local Isolates in Baghdad City. Arch Razi Inst. 2021;76(4):829-840. 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Published 2023 Jun 23. doi:10.3390/ijms241310537\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"antibiotic resistance, public health, raw milk, urinary tract infection (UTI), uropathogenic Escherichia coli (UPEC), virulence genes","lastPublishedDoi":"10.21203/rs.3.rs-8060277/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8060277/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRaw milk, while nutritionally valuable, may act as a reservoir for zoonotic and antibiotic-resistant microorganisms, creating a potential pathway for foodborne urinary tract infections (FUTIs). Among foodborne pathogens, \u003cem\u003eEscherichia coli\u003c/em\u003e stands out as both a commensal and a versatile pathogen responsible for approximately 80% of uncomplicated urinary tract infections (UTIs). Increasing evidence suggests that foodborne \u003cem\u003eE. coli\u003c/em\u003e strains carrying uropathogenic traits can contribute to community-acquired UTIs, yet this link remains insufficiently characterized.\u003c/p\u003e \u003cp\u003eThis study provides a comprehensive assessment of the prevalence, antibiotic resistance, and virulence gene profiles of \u003cem\u003eE. coli\u003c/em\u003e isolates obtained from raw milk samples collected in rural areas of Malatya province, T\u0026uuml;rkiye. A total of 206 bacterial colonies were isolated, and 115 were confirmed as \u003cem\u003eE. coli\u003c/em\u003e through phenotypic and biochemical tests. Antibiotic susceptibility analysis revealed complete resistance to cephalothin and variable resistance to several antibiotics, yielding a Multiple Antibiotic Resistance (MAR) index of 0.178, indicative of moderate antibiotic selection pressure. Molecular identification via 16S rRNA sequencing confirmed 51 of 69 isolates (73.91%) as \u003cem\u003eE. coli\u003c/em\u003e with \u0026ge;\u0026thinsp;99% similarity. Screening for ten virulence genes demonstrated that 34 of the confirmed isolates (66.60%) carried three or more virulence determinants, classifying them as potential uropathogenic \u003cem\u003eE. coli\u003c/em\u003e (UPEC).\u003c/p\u003e \u003cp\u003eThese findings demonstrate that raw milk can serve not only as a route for \u003cem\u003eE. coli\u003c/em\u003e contamination but also as a reservoir of multidrug-resistant and uropathogenic strains. The coexistence of antibiotic resistance and UPEC-associated virulence factors in foodborne isolates provides novel evidence linking the food chain to the emergence of FUTIs. Continuous microbiological surveillance, antibiotic stewardship, and strict hygiene protocols throughout the dairy production chain are essential to prevent foodborne urinary tract infections and protect public health.\u003c/p\u003e","manuscriptTitle":"Prevalence, antibiotic resistance, and virulence gene profiles of uropathogenic Escherichia coli (UPEC) isolated from raw milk: implications for public health","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-18 13:09:53","doi":"10.21203/rs.3.rs-8060277/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"19b4156c-b0e3-4121-8905-26f2bcc54cfd","owner":[],"postedDate":"December 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T16:21:27+00:00","versionOfRecord":{"articleIdentity":"rs-8060277","link":"https://doi.org/10.1007/s12223-026-01461-x","journal":{"identity":"folia-microbiologica","isVorOnly":false,"title":"Folia Microbiologica"},"publishedOn":"2026-03-26 16:10:16","publishedOnDateReadable":"March 26th, 2026"},"versionCreatedAt":"2025-12-18 13:09:53","video":"","vorDoi":"10.1007/s12223-026-01461-x","vorDoiUrl":"https://doi.org/10.1007/s12223-026-01461-x","workflowStages":[]},"version":"v1","identity":"rs-8060277","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8060277","identity":"rs-8060277","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}