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Article

Occurrence and Molecular Characterization of Extended-Spectrum Beta-Lactamase (ESBL)-Producing Escherichia coli in Broilers in Indonesia

by
Nur Hidayatullah
1,2,†,
Imron Suandy
3,†,
Montira Intanon
1,4,
Thomas Alter
5,
Oli Susanti
6,
Ajeng Herpianti
6,
Sani Susanty
6,
Riska Desitania
6 and
Nattakarn Awaiwanont
1,4,*
1
Veterinary Public Health and Food Safety Centre for Asia Pacific (VPHCAP), Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai 50100, Thailand
2
Department of Plantation and Livestock of West Kalimantan Province, Ministry of Agriculture, Jalan M. Hambal No. 3, Pontianak 76121, West Kalimantan, Indonesia
3
Center of Veterinary Denpasar, Ministry of Agriculture, Jalan Raya Sesetan No. 266, Denpasar Selatan, Denpasar 80223, Bali, Indonesia
4
Research Center of Producing and Development of Products and Innovations for Animal Health and Production, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai 50100, Thailand
5
School of Veterinary Medicine, Institute of Food Safety and Food Hygiene, Freie Universität Berlin, 14163 Berlin, Germany
6
National Laboratory of Veterinary Public Health, Ministry of Agriculture, Jalan Pemuda No. 29A, Tanah Sereal, Bogor 16161, Jawa Barat, Indonesia
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Antibiotics 2025, 14(10), 1030; https://doi.org/10.3390/antibiotics14101030
Submission received: 22 August 2025 / Revised: 10 October 2025 / Accepted: 11 October 2025 / Published: 15 October 2025
(This article belongs to the Special Issue Antimicrobial Resistance: Epidemiology and Implications for Veterinary Medicine)
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Abstract

Extended-spectrum β-lactamase-producing Escherichia coli (ESBL-E. coli) are widespread in the food chain, but nationwide surveillance in Indonesian broiler production is limited. This study investigated the occurrence, antimicrobial resistance, phylogenetic diversity, and molecular characteristics of ESBL-E. coli from broilers in Indonesia. A total of 2182 E. coli isolates from broiler cecal samples across three regions during the period 2018–2020 were analyzed. Antimicrobial susceptibility testing and ESBL phenotyping were performed following the CLSI guidelines. ESBL resistance genes and phylogenetic groups were detected using multiplex/quadruplex PCR. ESBL-E. coli (9.9%) was most frequently observed in the western (15.2%) region, followed by the central (8.0%) and eastern (7.2%) regions. A total of 85 resistance patterns were identified, with 98.5% exhibiting multidrug resistance. The blaCTX-M gene was detected in 97.5% of isolates, predominantly blaCTX-M-1 (97.5%), while blaCTX-M-9 was found in 2.5%. The blaTEM gene was present in 33.0% of ESBL isolates; however, blaSHV and blaOXA-1 were absent. Phylogenetic group A predominated (42.0%), followed by E (22.5%), B1 (20.5%), F (10.5%), C (2.5%), and D (2.0%). This study demonstrates a significant occurrence of ESBL-E. coli in Indonesian broilers with regional variation and blaCTX-M predominance. The high rate of multidrug resistance poses a serious public health concern, emphasizing the urgent need for antimicrobial stewardship and enhanced surveillance programs.

1. Introduction

Chicken meat is a primary source of animal protein globally [1]. In Indonesia, poultry plays a pivotal role in the national diet, supplying over 65% of the animal protein consumed by its population of 275 million. As of 2023, the nation’s approximately 310 broiler establishments produced about 4.12 million metric tons of chicken meat annually, a figure expected to rise with population growth and consumer demand. However, the intensive nature of Indonesian poultry farming has generated conditions favorable for the development of antimicrobial resistance (AMR), posing significant risks to both animal health and public health [2,3]. This high production is often associated with widespread antimicrobial use, such as for prophylaxis, treatment, and even unauthorized growth promoters. The use of antimicrobials in poultry has accelerated the emergence of resistant pathogens, and many of these antimicrobials are critically important for treating human infections.
The primary pathogens requiring management in Indonesian broiler systems include Escherichia coli, Salmonella, Clostridium perfringens, and respiratory pathogens such as Mycoplasma gallisepticum. Of particular concern is extended-spectrum beta-lactamase-producing Escherichia coli (ESBL-E. coli), which can hydrolyze β-lactam antibiotics, leading to treatment failure. ESBL enzyme production is primarily encoded by three major gene families: blaTEM, blaSHV, and blaCTX-M, with CTX-M-type β-lactamases being the most prevalent worldwide [4,5]. These resistance genes are often carried on mobile genetic elements such as plasmids and transposons, facilitating their horizontal transfer between bacterial species and contributing to the rapid dissemination of antimicrobial resistance across different bacterial populations [6]. The blaCTX-M gene family is further subdivided into groups, with the CTX-M-1 and CTX-M-9 groups being among the most commonly detected in both clinical and veterinary isolates globally [7,8].
Surveillance of these resistant pathogens in food-producing animals is essential for understanding transmission dynamics and informing antimicrobial stewardship programs [9,10,11]. The importance of this surveillance extends beyond veterinary medicine, as ESBL-E. coli from poultry can directly impact human health through foodborne transmission, environmental contamination, and occupational exposure among farm workers and slaughterhouse personnel [12,13,14]. ESBL-E. coli infections are linked to increased morbidity, mortality, and healthcare costs [15].
Spatial variations in ESBL-E. coli prevalence are significant worldwide. Studies in Southeast Asia have shown varying prevalence rates, while European studies demonstrate considerable regional differences [16,17]. While studies have reported the presence of ESBL-E. coli in Indonesian poultry, these investigations are geographically limited and lack comprehensive national coverage, resulting in gaps that impede informed policy development [18,19,20]. Therefore, the objective of this study was to conduct a comprehensive nationwide investigation into the prevalence and molecular characteristics of ESBL-E. coli in broiler chickens across Indonesia. The findings provide essential baseline data to inform the country’s antimicrobial resistance surveillance and public health strategies.

2. Results

2.1. Third-Generation Cephalosporin-Resistant E. coli and ESBL-E. coli

Overall, out of 2182 E. coli isolates, 584 (26.8%) isolates were resistant to cefotaxime and/or ceftazidime. The highest percentage was observed in the western region (32.9%), followed by the central (28.2%) and eastern (20.7%) regions. In the analysis of ESBL phenotypic confirmation, 2023 isolates could be included. Among this subset, 425 isolates (21.0%) were resistant to cefotaxime and/or ceftazidime. ESBL-positive status was confirmed in 9.9% of the isolates tested. The prevalence of ESBL-E. coli was significantly higher in the western region than in the central (p < 0.001) and eastern (p < 0.001) regions. In contrast, there was no statistically significant difference in prevalence between the central and eastern regions (p = 0.844) (Table 1).

2.2. Antimicrobial Resistance of ESBL-E. coli

ESBL-E. coli isolates showed high rates of resistance to most antimicrobials tested (Table 2). The highest resistance rate was observed against cefotaxime, followed by ampicillin, sulfamethoxazole, trimethoprim, and gentamicin. Similar resistance rates were observed for the two quinolones: ciprofloxacin and nalidixic acid. Conversely, tigecycline and meropenem exhibited the lowest resistance rates.
Antimicrobial susceptibility testing revealed that the majority of ESBL-E. coli isolates (98.5%, 197/200) were multidrug-resistant (MDR), defined as exhibiting resistance to at least three antimicrobial classes. The most common profile was resistance to six antimicrobial classes (31.0%, 62/200), although some isolates (3.0%, 6/200) demonstrated resistance to as many as nine classes (Table 3).
The analysis of 200 ESBL-E. coli isolates revealed extensive phenotypic diversity, with 85 distinct antimicrobial resistance patterns (Table S1). The most prevalent resistance patterns demonstrated complex multidrug resistance involving eight–nine antimicrobial classes. The three most frequent patterns accounted for 23% of all isolates: (1) SMX+TMP+CIP+NAL+AZI+TET+CTX+AMP+GEN (8.0%, n = 16), (2) SMX+TMP+CIP+NAL+AZI+CAZ+CTX+AMP+GEN (7.5%, n = 15), and (3) SMX+TMP+CIP+NAL+AZI+TET+CAZ+CTX+AMP+GEN (7.5%, n = 15). Isolates with the most common resistance pattern were distributed across the western (n = 7), eastern (n = 6), and central (n = 3) regions. Notably, one isolate (0.5%) exhibited an extensively antimicrobial-resistant phenotype, with resistance to 13 antimicrobial agents (SMX+TMP+CIP+NAL+MER+AZI+CHL+TET+TGC+CAZ+CTX+AMP+GEN).

2.3. Antimicrobial Resistance Level of ESBL-E. coli

The MIC50 and MIC90 values revealed high levels of resistance to most antibiotics tested (Table 4). Resistance to beta-lactams was extensive, with cefotaxime showing an MIC50 of 4 μg/mL and MIC90 of >4 μg/mL, while ceftazidime showed an MIC50 of >8 μg/mL and MIC90 of >8 μg/mL. These high MIC values confirmed that over 90% of ESBL-E. coli isolates were resistant to third-generation cephalosporins, strongly reflecting active ESBL production, capable of hydrolyzing these antibiotics. Similarly, quinolone and fluoroquinolone resistance were extremely high, with ciprofloxacin having an MIC50 of 8 μg/mL and an MIC90 > 8 μg/mL, while nalidixic acid had an MIC50 of 128 μg/mL and an MIC90 > 128 μg/mL. This pattern demonstrated nearly complete resistance among isolates to this critical class of antibiotics. Resistance to sulfonamides was pronounced, with sulfamethoxazole showing an MIC50 > 1024 μg/mL and MIC90 > 1024 μg/mL, while trimethoprim exhibited an MIC50 of 32 μg/mL and MIC90 > 32 μg/mL. Additionally, high-level ampicillin resistance was observed across all isolates, with MIC50 and MIC90 values of 64 μg/mL and >64 μg/mL, respectively. Emergent colistin resistance was observed, with an MIC90 of 8 μg/mL; nevertheless, the majority of ESBL-E. coli isolates (85.5%) remained within the susceptible range. Among the tested agents, only meropenem and tigecycline demonstrated consistent effectiveness, with MIC90 values below established breakpoints; however, their application in poultry is limited.
A statistical analysis revealed significant regional differences in the geometric mean MICs for tetracycline and chloramphenicol (Table 5). The geometric mean MIC for tetracycline was significantly higher in the eastern region compared to the western region (p = 0.048). Furthermore, resistance to chloramphenicol was significantly higher in the western region than in both the eastern (p = 0.009) and central (p = 0.014) regions. For the other antibiotics, no statistically significant differences in geometric mean MICs were found among the regions (p > 0.05).

2.4. ESBL Resistance Genes of ESBL-E. coli Isolates from Broilers

All 200 ESBL-E. coli isolates were analyzed with specific primers for the presence of specific ESBL resistance genes. The most prevalent gene was blaCTX-M, including blaCTX-M-1 and blaCTX-M-9, followed by blaTEM (Table 6). blaSHV and blaOXA-1 were not detected in any of the isolates. blaCTX-M, specifically blaCTX-M-1, was the most dominant ESBL resistance gene across all regions. There were no statistically significant differences in the percentages of ESBL resistance genes between regions (p > 0.05).
Five ESBL resistance gene patterns of ESBL-E. coli isolates were identified. The most frequently observed was single blaCTX-M-1 (67.0%, 134/200), followed by blaCTX-M-1 + blaTEM (28.0%, 56/200), single blaTEM (2.5%, 5/200), blaCTX-M-9 + blaTEM (1.5%, 3/200), and blaCTX-M-1 + blaCTX-M-9 + blaTEM (1.0%, 2/200).

2.5. Phylogenetic Group

A phylogenetic analysis detected all E. coli phylogroups except for group B2 (Table 7). The most common phylogenetic group was group A, followed by E, B1, F, C, and D. The eastern and central regions exhibited similar phylogenetic distributions, with group A being the most frequent, followed by groups E and B1. In the western region, group A was also the most prevalent phylogroup, followed by groups B1, F, and E. In addition, phylogroup D was detected only in isolates from the western region. Although group C was found in all regions, it was only in a very small fraction. The only statistically significant difference among regions was for phylogroup E, which was found in a significantly higher proportion in the eastern region compared to the western region (p = 0.0003).
The distribution of ESBL resistance genes varied by phylogenetic group. While the blaCTX-M1 gene was highly prevalent (>95.0%) across all phylogroups, blaTEM showed a more varied distribution, occurring most frequently in group A (51.5%), followed by groups B1 (21.2%), E (18.2%), F (6.1%), and C (3.0%). Detection of the blaCTX-M-9 gene was restricted exclusively to phylogroups A (60.0%), B1 (20.0%), and C (20.0%).

3. Discussion

This study provides the first and most geographically comprehensive surveillance of ESBL-E. coli in Indonesian broiler production, establishing a unique region-specific national baseline. This nationwide surveillance revealed a 9.9% ESBL-E. coli prevalence across Indonesian broiler production, with significant regional variation. These findings contrast with previous localized studies in Indonesia reporting higher rates: 28.8% in West Java cloacal swabs and 25.0% in Bogor City feces [18,19]. Additionally, the prevalence in our study was significantly lower than that reported in Germany. That study reported 56.9% ESBL-E. coli from 51 cecal samples collected at slaughterhouses. These differences suggest regional variation in antimicrobial use patterns [21]. The lower percentage of ESBL-E. coli observed in this study when compared to other studies may be attributed to differences in sample size, geographic locations, sampling periods, and laboratory techniques [7,11,22]. The present study included more than 2000 E. coli isolates from different regions of Indonesia to reflect the ESBL-E. coli situation at the national level, while most other studies included smaller sample sizes and fewer E. coli isolates. A larger sample size improves the accuracy and reliability of ESBL-E. coli prevalence estimates. A small sample may not reflect the diversity of farm types, regions, or practices. The WHO report emphasizes that robust surveillance, including adequate sample sizes, is essential for accurately detecting antimicrobial resistance trends and informing public health interventions [23]. While most of the previous studies usually concentrate on one location or region, our study uses a collection of ESBL-E. coli isolates across three key geographical regions to establish a robust and essential national baseline. Antimicrobial resistance is usually dynamic; thus, collecting samples from different timeframes would also lead to differences in observed prevalences [24,25,26]. For screening of ESBL-E. coli, a recent study recommends utilizing MacConkey agar supplemented with 1 mg/L cefotaxime to improve both the sensitivity and specificity of ESBL-E. coli detection [27]. Therefore, further studies are suggested that employ cefotaxime-supplemented agar.
The results of this study highlight significant geographical disparities in ESBL-E. coli prevalence across Indonesia, with the western region showing a significantly higher prevalence of ESBL-E. coli compared to the central and eastern regions. This variation is likely attributable to differences in broiler production characteristics and practices, such as antimicrobial usage, farming practices, and biosecurity measures. Indonesia’s broiler population is heavily concentrated in its western and central regions, with significantly lower numbers in the eastern region [28]. Western Indonesia’s higher prevalence aligns with its concentration of intensive commercial farms using high stocking densities and rapid flock turnover. Such conditions can compromise biosecurity and encourage antimicrobial use, creating selective pressure for resistant bacteria. The higher population density and industrial activity in the west may also contribute to environmental reservoirs of resistant strains, while the movement of personnel like veterinarians and technicians between farms can facilitate their spread [29]. In contrast, the central region’s lower prevalence may be linked to moderately intensive farming and better farmer attitudes toward antimicrobial usage [24]. The eastern region exhibited the lowest prevalence, a finding attributed to its smaller and less concentrated broiler population, which consists mainly of small-scale, independent farms [25]. Although biosecurity in these eastern farms may not be ideal, the low underlying incidence of ESBL-E. coli in both broilers and humans limits the overall opportunity for transmission [26]. Thus, the structure of the regional broiler industry is one of the main drivers of ESBL-E. coli. This suggests that control efforts must be tailored by region, for example, reducing antibiotic dependency in the west and proactively protecting the central and eastern regions’ low-risk environment.
The extremely high prevalence of multidrug resistance (98.5%) among ESBL-E. coli isolates represents one of the most concerning findings in this study. This extensive MDR prevalence indicates severe resistance selection pressure within Indonesian broiler systems. The diversity of resistance patterns, with 85 distinct profiles identified, suggests widespread circulation of multiple-resistance plasmids and mobile genetic elements rather than clonal expansion of single resistant strains. The predominant pattern involving nine antimicrobial classes (SMX+TMP+CIP+NAL+AZI+TET+CTX+AMP+GEN) demonstrates the complexity of co-resistance mechanisms operating in Indonesian poultry production. High resistance rates to critically important antimicrobials pose significant therapeutic challenges. Third-generation cephalosporin resistance (cefotaxime 98.5%, ceftazidime 51.1%) confirms active ESBL production, capable of hydrolyzing these antibiotics, while extensive quinolone resistance (ciprofloxacin 72.0%, nalidixic acid 71.5%) threatens treatment options for human infections. These rates substantially exceed those reported in European studies: ciprofloxacin resistance reached only 10% in the Netherlands and 38% in Spain compared to our 72% [30,31,32]. Studies demonstrate that E. coli from quinolone-treated broilers exhibit significantly higher resistance levels than untreated ones [33], with poultry isolates showing greater ciprofloxacin resistance than those from pigs or humans due to more intensive quinolone use in poultry [22,34].
The Indonesian context reveals concerning antimicrobial usage patterns. According to 2017 data, approximately 80% of broiler farmers employ antimicrobials prophylactically, potentially driving bacterial resistance increases [35]. Sulfadiazine + trimethoprim represents the most widely used combination in broiler chickens [36], which correlates with sulfonamide resistance ranking among the top five classes in this study (86.0% for sulfamethoxazole, 84.0% for trimethoprim). Additionally, 96.9% of farmers utilize unauthorized commercial feeds containing antimicrobial growth promoters (penicillin, kanamycin, erythromycin, and oxytetracycline), further contributing to resistance development [37].
Colistin resistance emergence (14.5%) presents particularly alarming implications given its status as a last-resort antibiotic for multidrug-resistant Gram-negative infections. Although most isolates (85.5%) remained susceptible, detecting resistance genes warrants immediate enhanced surveillance. Among available treatment options, carbapenems such as meropenem remain the most reliable for ESBL-E. coli infections, while tigecycline demonstrates beneficial in vitro activity but its use should be limited to scenarios when carbapenems are unsuitable [38,39]. Minimal resistance to meropenem (3.0%) and tigecycline (2.5%) provides limited therapeutic alternatives, though their application in poultry remains restricted.
A minimum inhibitory concentration analysis revealed marked reductions in antimicrobial susceptibility, demonstrated by extremely elevated MIC50 and MIC90 values across important antimicrobial classes, including sulfonamides, quinolones, cephalosporins, penicillin, and aminoglycosides. The absence of significant regional differences in the geometric mean MICs for most antimicrobials tested suggests that nationwide resistance patterns are driven by common selective pressures. However, regional variation was observed for certain agents: tetracycline resistance was significantly higher in the east than in the west, whereas chloramphenicol resistance was more pronounced in the west compared to central and eastern regions. These findings imply that local factors, such as regional variation in antibiotic usage and the potential clonal spread of resistant strains, may underlie the distinct resistance profiles observed.
High co-resistance between fluoroquinolones (ciprofloxacin, nalidixic acid) and folate pathway inhibitors (sulfamethoxazole, trimethoprim) suggests clustered resistance genes [40,41]. These highly resistant strains in broiler production highlight the food chain as a significant vehicle for disseminating clinically important resistance to the public. Antimicrobial-resistant bacteria can spread through environmental contamination [42]. Enhanced biosecurity measures in livestock operations represent the most effective prevention strategy against multidrug-resistant bacterial contamination.
The molecular analysis revealed similar patterns in ESBL gene distribution across Indonesian broiler production. While blaCTX-M genes dominated in all regions, the eastern region showed universal prevalence (100%), while the central (94.2%), and western (97.8%) regions demonstrated slightly lower prevalences. This regional uniformity differs from previous Indonesian findings, where blaCTX-M was detected in only 6.0% of West Java samples, suggesting our larger sample size captured broader genetic diversity [43]. International comparisons reveal higher detection rates than the United Kingdom (15.6%), indicating Indonesia’s more widespread blaCTX-M dissemination [35]. The predominance of blaCTX-M-1 variants (97.5%) over blaCTX-M-9 (2.5%) reflects global trends, where CTX-M-1 group enzymes have become increasingly prevalent. This shift from historical patterns where blaTEM and blaSHV predominated suggests that third-generation cephalosporin usage in Indonesian poultry has driven selective pressure favoring CTX-M-1 evolution. The absence of blaSHV and blaOXA-1 genes distinguishes Indonesian broiler isolates from global patterns, where these genes commonly co-occur with blaCTX-M variants.
The regional variation in blaTEM prevalence (central: 38.5% vs. west: 27.0%) indicates different co-resistance patterns. As one of the earliest ESBL determinants described, blaTEM continues to circulate widely in Enterobacteriaceae, often co-occurring with newer ESBL genes [44]. The co-existence of blaTEM and blaCTX-M on conjugative plasmids enhances multidrug resistance phenotypes and facilitates rapid horizontal gene transfer, with higher blaTEM prevalence in central regions potentially correlating with penicillin usage patterns that favor ampicillin resistance mechanisms [26,45].
This molecular epidemiology pattern suggests established horizontal gene transfer networks across Indonesian broiler production, with conjugative plasmids, integrons, and transposons facilitating ESBL gene dissemination [46,47,48]. This combination of blaCTX-M-1 dominance with persistent blaTEM circulation indicates that Indonesian ESBL evolution follows a distinct route, potentially reflecting specific antimicrobial selection pressures in local production systems. These findings underscore the importance of targeted molecular surveillance combined with antimicrobial usage monitoring to design effective stewardship interventions addressing the full spectrum of ESBL mechanisms in Indonesian poultry.
A phylogenetic analysis revealed diversity patterns, with important clinical implications. Group A’s predominance (42.0%) aligns with global broiler-associated studies, contrasting markedly with Brazilian livestock systems, where Group B1 dominated (57.0%) [49]. This difference suggests host-specific phylogenetic adaptation in Indonesian poultry systems. The detection of phylogroup F across all regions (east: 1.8%, central: 15.4%, west: 12.9%) represents a novel finding with significant public health implications. Unlike commensal groups A and B1, phylogroup D and F isolates possess enhanced virulence factors regardless of host origin, potentially facilitating zoonotic transmission and extraintestinal infections [50,51,52,53]. The higher prevalence in western regions correlates with increased production intensity, suggesting industrial farming practices may select for virulent lineages.
The detection of phylogroup D at low frequency in western regions (4.3%) demands immediate attention due to its correlation with significant human pathogenicity, suggesting potential environmental contamination sources that require improved biosecurity protocols in western production facilities. This molecular epidemiology pattern shows that Indonesian broiler production has developed a unique combination of resistance and virulence. This indicates that surveillance and intervention strategies need to be focused on both antimicrobial resistance and pathogenic potential.
This study has some limitations. First, the data, collected from 2018 to 2020, establish a critical national baseline but may not reflect current resistance dynamics. Second, our slaughterhouse-based sampling design precluded the collection of farm-level data, such as biosecurity, antimicrobial usage, and management practices, preventing the analysis of specific risk factors for regional variations. Finally, the use of whole-genome sequencing (WGS) would have offered more comprehensive insights into the resistance mechanisms. Therefore, we recommend that future surveillance studies incorporate longitudinal surveillance, on-farm data collection, and WGS to track resistance evolution and identify its drivers.

4. Materials and Methods

4.1. E. coli Isolation

A total of 2182 E. coli isolates were obtained from the National Antimicrobial Resistance Surveillance Program in Indonesia. Briefly, broiler caecum samples were collected from slaughterhouses located across three major regions of Indonesia: West, central, and east, during the years 2018–2020 (Figure 1). Each cecum sample was randomly collected from one individual bird after the slaughtering procedure, thereby ensuring that each sample originated from a distinct farm source. The process of collecting samples was repeated every two weeks. E. coli isolation and identification were conducted in eight regional animal laboratories. Each individual cecal sample was streaked directly onto MacConkey agar and incubated at 37 °C for 18–24 h. Indole, methyl red, Voges–Proskauer, and citrate (IMViC) biochemical tests were conducted to verify the bacterial species. The E. coli colonies were cultivated on tryptic soy broth for 24 h and thereafter stored at a temperature of −20 °C in a supplement with 5% glycerol.

4.2. Antimicrobial Susceptibility Test

One phenotypically E. coli isolate per sample was sent to the National Quality Laboratory for Livestock Products, Bogor, Indonesia, and subjected to an antimicrobial susceptibility test using the SensititreTM Complete Automated AST System (Thermo ScientificTM, Waltham, MA, USA). A total of 14 types of antimicrobial agents among 10 antimicrobial classes were included: ampicillin (AMP), azithromycin (AZI), cefotaxime (CTX), ceftazidime (CAZ), chloramphenicol (CHL), ciprofloxacin (CIP), colistin (COL), gentamicin (GEN), meropenem (MER), nalidixic acid (NAL), sulfamethoxazole (SMX), tetracycline (TET), tigecycline (TGC), and trimethoprim (TMP). The results were interpreted according to the CLSI guidelines [54], with the exception of tigecycline, for which the EUCAST breakpoint was applied [55].
The isolates were classified as multidrug resistant (MDR) when resistant to at least one agent in three or more antimicrobial classes. The minimum inhibitory concentration (MIC) was recorded, and MIC50 and MIC90 were identified [56].

4.3. Phenotypic confirmation of ESBL-E. coli

E. coli isolates that showed resistance to third-generation cephalosporins (cefotaxime and/or ceftazidime) were evaluated for the production of the ESBL enzyme. According to the Clinical Laboratory Standards Institute’s (CLSI) standard, the double-disk diffusion test was used to phenotypically characterize ESBL-producing isolates [54]. In brief, cefotaxime (30 µg) and ceftazidime (30 µg), both alone and in combination with clavulanic acid (10 µg), were used. A bacterial cell suspension in 0.85% normal saline solution was made, and the turbidity was adjusted to match with a 0.5 McFarland standard. Subsequently, a sterile cotton swab was employed to put the suspension onto Mueller–Hinton agar (MHA) plates. Following the drying process, a cefotaxime (30 µg) antimicrobial disk and a clavulanic acid–cefotaxime (10 µg/30 µg) antimicrobial disk were placed on one cultured MHA plate. On an identical MHA plate, a ceftazidime (30 µg) antimicrobial disk and clavulanic acid–ceftazidime (10 µg/30 µg) antimicrobial disks were placed. The plates were incubated at 37 °C for 18–24 h [57]. The circular zones of inhibition around the antibiotic disks were measured according to the CLSI guidelines [54].
ESBL production was determined by a zone diameter > 5 mm for either antimicrobial agent when tested in combination with clavulanic acid compared to testing alone. K. pneumoniae ATCC 700603 and E. coli ATCC 25922 were used as quality control strains. Only ESBL-E. coli isolates were considered in the analysis of ESBL resistance genes, E. coli phylogenetic groups, and antimicrobial resistance patterns.

4.4. Determination of ESBL Resistance Genes

All of the ESBL-E. coli isolates were evaluated for the presence of ESBL resistance genes, blaTEM, blaSHV, blaOXA-1, blaCTX-M-1, blaCTX-M-9, and blaCTX-M, using the polymerase chain reaction (PCR) method. The genomic DNA of the E. coli isolate was extracted using a boiling method. Briefly, the E. coli isolates were cultured in 3 mL of Tryptone Soya Broth (Oxoid) supplemented with 1 mg/mL cefotaxime (Himedia) and incubated at 37 °C for 18–24 h. A volume of 1 mL of the culture was transferred to a 2 mL microcentrifuge tube, then centrifuged at 10,000× g for 5 min, and the supernatant was discarded. The pellet was suspended in 270 µL of nuclease-free water and heated at 99 °C for 10 min. The debris cell was discarded by centrifugation at 13,000× g for 2 min. The supernatant was collected. The genomic DNA was kept at −20 °C for further analysis.
Multiplex PCR was carried out to identify the blaTEM, blaSHV, blaOXA-1, blaCTX-M-1, and blaCTX-M-9 genes as previously described; all the primers used are listed in Table 8 [58,59]. The PCR reaction was performed under the following conditions: initial denaturation at 94 °C for 10 min, followed by 30 cycles of 30 s at 94 °C, 35 s at 61 °C, and 1 min at 72 °C, with a final 9 min extension at 72 °C. Amplicons (800 bp for blaTEM, 713 bp for blaSHV, 655 bp for blaCTX-M-1, 564 bp for blaOXA-1, and 518 bp for blaCTX-M-9) were visualized under UV light after electrophoresis through 2.5% agarose gel at 90 volts for 90 min.
The detection of blaCTX-M genes was investigated using singleplex PCR as previously described [61]. The PCR reaction was performed under the following conditions: initial denaturation at 94 °C for 10 min, followed by 30 cycles of 30 s at 94 °C, 35 s at 60 °C, and 1 min at 72 °C, with a final 9 min extension at 72 °C. The amplicon (585 bp) was visualized under UV light after electrophoresis through 1.5% agarose gel at 100 volts for 30 min. Positive amplicons from each gene were purified using the gel extraction kit (PureDireX, Bio-Helix Co., Ltd., New Taipei city, Taiwan) and subjected to Sanger sequencing (ATGC, Co., Ltd., Pathum Thani, Thailand). The obtained sequences were evaluated using the Benchling version 2025.5 (Benchling Inc., San Francisco, CA, USA) and were compared with the reference sequences at GenBank.

4.5. Determination of E. coli Phylogenetic Group

The phylogenetic group (A, B1, B2, C, D, E, and F) was determined using a quadruplex phylogroup assignment method, as previously described by Clermont, Christenson et al. [62].

4.6. Statistical Analysis

To determine if the observed differences in percentages between the three regions were statistically significant, a chi-square test of independence was performed, and Tukey’s honestly significant difference (HSD) test was conducted as a post hoc analysis to identify the differences between each region. The MIC50, MIC90, MIC ranges, and geometric means of the MICs were calculated for each antibiotic, and a one-way analysis of variance (ANOVA) was performed to determine if there were statistically significant differences between regions; a more detailed statistical analysis using pairwise t-tests was conducted. The t-tests were performed on the log-transformed MIC values. Statistical analyses were performed by using the SAS statistical software (SAS. 2018. SAS University Edition: Statistics, 6th ed.), results were considered statistically significant if p < 0.05.

5. Conclusions

This study reveals a low occurrence of ESBL-E. coli in Indonesian broilers from 2018 to 2020, providing crucial nationwide data on its prevalence and regional gene distribution. These findings serve as a reference for government and stakeholders to develop strategies aimed at preventing the spread of antimicrobial resistance from poultry to humans and the environment. Future surveillance efforts should prioritize temporal trend analysis to monitor changes in ESBL-E. coli prevalence and evaluate the effectiveness of antimicrobial stewardship interventions. This should be complemented by comprehensive risk factor analysis to identify key transmission drivers. Furthermore, whole-genome sequencing should be employed to provide deeper insights into the molecular epidemiology, genetic relatedness, and transmission dynamics of these resistant strains across different regions and production systems.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/antibiotics14101030/s1, Table S1: Antimicrobial resistance patterns of ESBL-E. coli.

Author Contributions

Conceptualization, N.A.; methodology, N.A., I.S., M.I. and T.A.; investigation, N.H., O.S., A.H., S.S. and R.D.; data curation, N.A., M.I., N.H. and I.S.; writing—original draft preparation, N.H.; writing—review and editing, N.A., M.I. and T.A.; visualization, N.H.; supervision, N.A., M.I., T.A. and I.S.; project administration, N.A. and N.H.; funding acquisition, N.A. and I.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Materials.

Acknowledgments

This research was partially supported by the Veterinary Public Health and Food Safety Centre for Asia Pacific and Chiang Mai University. Nur Hidayatullah completed a Master’s thesis as part of the Master of Science Program in Veterinary Public Health, Faculty of Veterinary Medicine, Chiang Mai University, under the CMU Presidential Scholarship.

Conflicts of Interest

The authors declare no conflicts of interest.

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Antibiotics 14 01030 g001
Figure 1. A map of the regions in Indonesia.
Figure 1. A map of the regions in Indonesia.
Antibiotics 14 01030 g001
Table 1. Number and percentage of ESBL-E. coli in different regions.
Table 1. Number and percentage of ESBL-E. coli in different regions.
RegionCefotaxime and/or Ceftazidime-Resistant
E. coli		ESBL-E. coli
N Positive (%) 95% CI p-Value for
Regions
Differences 		N Positive (%) 95% CI p-Value for
Regions
Differences
East808167 (20.7) a18.1–23.6<0.00176755 (7.2) a5.5–9.2<0.001
Central742209 (28.2) b25.1–31.564652 (8.0) a6.2–10.4
West632208 (32.9) b29.4–36.761093 (15.2) b12.6–18.3
Total2182584 (26.8) 2023200 (9.9)
CI = confidence interval; within columns, percentages with different superscript letters indicate significant differences (p-value < 0.05).
Table 2. The rates of antimicrobial resistance of ESBL-E. coli..
Table 2. The rates of antimicrobial resistance of ESBL-E. coli..
AntibioticResistance Status (%)
RIS
Cefotaxime98.50.01.5
Ampicillin97.50.52.0
Sulfamethoxazole86.00.014.0
Trimethoprim84.00.016.0
Gentamicin84.00.515.5
Ciprofloxacin72.016.012.0
Nalidixic acid71.50.028.5
Azithromycin62.50.037.5
Tetracycline55.01.543.5
Ceftazidime51.134.015.0
Chloramphenicol17.54.578.0
Colistin14.585.50.0
Meropenem3.00.596.5
Tigecycline2.50.097.5
R = resistant, I = intermediate, S = susceptible.
Table 3. Percentages of ESBL-E. coli resistance to different numbers of antimicrobial classes.
Table 3. Percentages of ESBL-E. coli resistance to different numbers of antimicrobial classes.
No. of Antimicrobial ClassesNo. of ESBL-E. coli IsolatesPercentage
231.5%
342.0%
4168.0%
53919.5%
66231.0%
75628.0%
8147.0%
963.0%
Total200100%
Table 4. MIC50 (µg/mL) and MIC90 (µg/mL) values of ESBL-E. coli across Indonesia.
Table 4. MIC50 (µg/mL) and MIC90 (µg/mL) values of ESBL-E. coli across Indonesia.
AntibioticClassMIC50
(µg/mL)		MIC90
(µg/mL)		GM
(µg/mL)		MIC
Range		MIC Breakpoint (µg/mL)
SulfamethoxazoleSulfonamides>1024>1024576.0≤8–>1024≥512
TrimethoprimSulfonamides32>3215.6≤0.25–>32≥16
CiprofloxacinQuinolones8>82.50.03–>8≥1
Nalidixic AcidQuinolones128>12856.7≤4–>128≥32
ColistinPolymyxins181.4≤1–>16≥4
MeropenemCarbapenems0.030.060.041≤0.03–>16≥4
AzithromycinMacrolides326422.6≤2–>64≥32
TetracyclineTetracyclines32>6413.4≤2–>64≥16
ChloramphenicolPhenicols812812.5≤8–>128≥32
TigecyclineTetracyclines0.250.50.282≤0.25–4>0.5
CeftazidimeCephalosporins>8>86.9≤0.5–>8≥16
CefotaximeCephalosporins4>43.8≤0.25–>4≥4
AmpicillinPenicillins64>6459.31–>64≥32
GentamicinAminoglycosides32>3218.3≤0.5–>32≥16
GM = geometric mean.
Table 5. MICs of antibiotics against ESBL-E. coli in broilers in different regions of Indonesia.
Table 5. MICs of antibiotics against ESBL-E. coli in broilers in different regions of Indonesia.
AntibioticRegionNMIC50 (µg/mL)MIC90 (µg/mL)GM (µg/mL)p-Value
SulfamethoxazoleEast5510241024667.10.721
Central5210241024600.8
West9310241024515.8
TrimethoprimEast55323217.90.712
Central52323215.6
West93323214.3
CiprofloxacinEast55883.00.051
Central52281.8
West93882.8
Nalidixic AcidEast5512812851.70.270
Central5212812848.4
West9312812865.4
ColistinEast5511.61.30.614
Central5213.81.3
West93181.6
MeropenemEast550.030.1620.0510.095
Central520.030.060.037
West930.030.030.037
AzithromycinEast55326428.60.085
Central52326419.0
West93326421.7
TetracyclineEast55646417.9 a0.044
Central52646415.8 ab
West9386410.3 b
ChloramphenicolEast5583210.4 a 0.036
Central52815.210.4 a
West93812815.4 b
TigecyclineEast550.250.50.3020.629
Central520.250.4750.271
West930.250.250.277
CeftazidimeEast55887.10.607
Central52886.7
West93886.8
CefotaximeEast55443.40.064
Central52444.0
West93443.9
AmpicillinEast55646456.40.528
Central52646459.1
West93646461.2
GentamicinEast55323216.40.570
Central52323219.8
West93323218.7
GM = geometric mean; different superscript letters indicate significant differences (p-value < 0.05).
Table 6. Distribution of ESBL resistance genes among ESBL-E. coli from broilers.
Table 6. Distribution of ESBL resistance genes among ESBL-E. coli from broilers.
RegionNESBL Resistance Genes
blaCTX-MblaCTX-M-1blaCTX-M-9blaTEMblaSHVblaOXA-1
East5555 (100%)55 (100%)1 (1.8%)19 (34.5%)00
Central5249 (94.2%)49 (94.2%)3 (5.8%)20 (38.5%)00
West9391 (97.8%)91 (97.8%)1 (1.1%)27 (29.0%)00
Total200195 (97.5%)195 (97.5%)5 (2.5%)66 (33.0%)00
Table 7. Phylogenetic group of ESBL-E. coli from broilers in different regions of Indonesia.
Table 7. Phylogenetic group of ESBL-E. coli from broilers in different regions of Indonesia.
RegionPhylogenetic GroupTotal
AB1B2CDEF
East24
(43.6%) a		7
(12.7%) a		0
(0.0%) a		2
(3.6%) a		0
(0.0%) a		21
(38.2%) a		1
(1.8%) a		55
Central17
(32.7%) a		12
(23.1%) a		0
(0.0%) a		1
(1.9%) a		0
(0.0%) a		14
(26.9%) a,b		8
(15.4%) a		52
West43
(46.2%) a		22
(23.7%) a		0
(0.0%) a		2
(2.2%) a		4
(4.3%) a		10
(10.8%) b		12
(12.9%) a		93
Total84
(42.0%)		41
(20.5%)		0
(0.0%)		5
(2.5%)		4
(2.0%)		45
(22.5%)		21
(10.5%)		200
Within columns, percentages with different superscript letters indicate significant differences (p-value < 0.05).
Table 8. Primers used for detection of ESBL resistance genes.
Table 8. Primers used for detection of ESBL resistance genes.
Gene TargetedSequence (5′-3′)Amplicon Size (bp)PurposeReference
blaTEMCATTTCCGTGTCGCCCTTATTC
CGTTCATCCATAGTTGCCTGAC		800Multiplex PCR[60]
blaSHVAGCCGCTTGAGCAAATTAAAC
ATCCCGCAGATAAATCACCAC		713Multiplex PCR[60]
blaOXA-1GGCACCAGATTCAACTTTCAAG
GACCCCAAGTTTCCTGTAAGTG		564Multiplex PCR[60]
blaCTX-M-1TTAGGAAGTGTGCCGCTGTA
CGGTTTTATCCCCCACAAC		655Multiplex PCR[59]
blaCTX-M-9GGTGATGAACGCTTTCCAAT
TTATCACCTGCAGTCCACGA		518Multiplex PCR[59]
blaCTX-MCGATGTGCAGTACCAGTAA
TTAGTGACCAGAATCAGCGG		585Singleplex PCR[61]
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Hidayatullah, N.; Suandy, I.; Intanon, M.; Alter, T.; Susanti, O.; Herpianti, A.; Susanty, S.; Desitania, R.; Awaiwanont, N. Occurrence and Molecular Characterization of Extended-Spectrum Beta-Lactamase (ESBL)-Producing Escherichia coli in Broilers in Indonesia. Antibiotics 2025, 14, 1030. https://doi.org/10.3390/antibiotics14101030

AMA Style

Hidayatullah N, Suandy I, Intanon M, Alter T, Susanti O, Herpianti A, Susanty S, Desitania R, Awaiwanont N. Occurrence and Molecular Characterization of Extended-Spectrum Beta-Lactamase (ESBL)-Producing Escherichia coli in Broilers in Indonesia. Antibiotics. 2025; 14(10):1030. https://doi.org/10.3390/antibiotics14101030

Chicago/Turabian Style

Hidayatullah, Nur, Imron Suandy, Montira Intanon, Thomas Alter, Oli Susanti, Ajeng Herpianti, Sani Susanty, Riska Desitania, and Nattakarn Awaiwanont. 2025. "Occurrence and Molecular Characterization of Extended-Spectrum Beta-Lactamase (ESBL)-Producing Escherichia coli in Broilers in Indonesia" Antibiotics 14, no. 10: 1030. https://doi.org/10.3390/antibiotics14101030

APA Style

Hidayatullah, N., Suandy, I., Intanon, M., Alter, T., Susanti, O., Herpianti, A., Susanty, S., Desitania, R., & Awaiwanont, N. (2025). Occurrence and Molecular Characterization of Extended-Spectrum Beta-Lactamase (ESBL)-Producing Escherichia coli in Broilers in Indonesia. Antibiotics, 14(10), 1030. https://doi.org/10.3390/antibiotics14101030

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