High prevalence of antibiotic-resistant Escherichia coli harbouring extended-spectrum beta-lactamase (ESBL) in raw chicken meat sold at retail in Klang Valley, Malaysia

Abstract

Chicken is the most widely consumed meat in Malaysia as it is abundant, provides good nutrient and taste, and available at an affordable price. However, it is known to harbour various foodborne pathogens including faecal microorganism, Escherichia coli. There are various routes and factors that can cause contamination of E. coli in chicken. Furthermore, numerous reports have shown that over the past decades, the trends of antimicrobial resistance among foodborne pathogens have been increasing rapidly. Therefore, the present work aimed to assess the prevalence of E. coli contamination by examining various contributing factors and its antibiotic resistance in raw chicken meat sold in Klang Valley, Malaysia. Results showed that 74% of the samples were contaminated with E. coli with wet markets showing higher prevalence (17%) of E. coli than in hypermarkets. Univariate analysis within the same risk factor showed that packaging process, storage temperature, and antibiotics had significant effects on the prevalence of E. coli (∼ 6.097 log CFU/g). The E. coli loads were significantly influenced by market type and storage temperature as validated by Mann–Whitney tests. All E. coli isolates displayed multiple antibiotic resistance (MAR) index ranging from 0.33 to 1.00, and 35 E. coli isolates showed the highest MAR index (1.00), being resistant to 12 antibiotics. Furthermore, 90% of E. coli isolates contained extended-spectrum beta-lactamase genotypes that can subvert potent antibiotic, beta-lactam. The findings from the present work would help reduce the risk of foodborne illnesses by identifying the risk factors associated with E. coli prevalence in chicken and provide the basis to revise guidelines on antibiotic use in livestock to reduce antimicrobial resistance.

Introduction

Livestock animals are major carriers and sources of foodborne pathogens that contribute to foodborne illnesses. Poultry, especially chicken, is high in demand due to its nutritional quality, affordable price, and acceptability as compared to other types of meat (Barroeta 2007, Cavani et al. 2009). In Malaysia, poultry meat consumption per capita has consistently increased from 38.59 kg in 2007 to 46.1 kg in 2021 (DVS 2018, DOSM 2022), which is higher than beef, pork, and mutton. However, chicken meat is one major contributor that is frequently involved in food poisoning and outbreaks (Antunes et al. 2016, Wessels et al. 2021). In 2022, the incidence rate of food poisoning in Malaysia was reported at 44 cases per 100 000 people (MOH 2023). Various types of pathogenic and non-pathogenic microorganisms can be found in chicken meat, and monitoring each of these species would be challenging (Genca and Arslan 2012). Although Salmonella spp. have been commonly reported as one of the main contaminants in poultry products (Thung et al. 2016, Nidaullah et al. 2017, Sandrasaigaran et al. 2023), previous study have also reported the presence of Escherichia coli in chicken, and this has become major concerns because E. coli serves as an indicator for faecal contamination, and poses a serious health threat leading to severe foodborne illnesses (Ghafir et al. 2008, Rahman et al. 2020).

Escherichia coli is a common foodborne microorganism that resides in the intestines of humans and warm-blooded animals. Its presence in raw foods is often linked with faecal contamination (Rahman et al. 2020), and a sign of poor hygienic conditions in abattoirs, logistics, and trade and prepping areas (Mpundu et al. 2019). Furthermore, various types of E. coli strains (e.g. enteropathogenic E. coli, enterohaemorrhagic E. coli, enterotoxigenic E. coli, enteroaggregative E. coli, enteroinvasive E. coli, diffusely adherent E. coli, uropathogenic E. coli, neonatal meningitis E. coli, avian pathogenic E. coli, and mammary pathogenic E. coli) are known to be highly pathogenic to both humans and animals, causing foodborne illnesses (enteric), urinary tract infections, sepsis, and septic shock (Iredell et al. 2016, Armanullah et al. 2018, Sora et al. 2021). The rate of self-reported acute diarrhoea in a 4-week study among Malaysian population was 5%, which accounted for ∼13 million cases annually (Gurpreet et al. 2011). Foodborne illnesses have significantly affected the socioeconomic sector due to the loss of productivity, cost of medical treatment, hospitalization, and rate of mortality (Jeyaletchumi et al. 2010a).

The antibiotic treatment for foodborne illnesses is also becoming more complicated when the bacteria have evolved to be more virulent, and developed multiple antibiotic resistance (MAR), which poses a serious health threat (Chen et al. 2012). This may be attributed to the use of common or similar antibiotics, such as ampicillin, gentamicin, and tetracycline, in both livestock management and human treatment. In addition, recent reports have also shown the global spread of extended-spectrum beta-lactamase (ESBL)-producing E. coli in both humans and animals (Islam et al. 2022). Beta-lactam resistance in E. coli is typically mediated by the production of beta-lactamase, an enzyme that degrades beta-lactam antibiotics. The global emergence of ESBL resistance in E. coli poses a significant challenge in antibiotic selection as cephalosporins are the alternative class of beta-lactam antibiotics used in humans if the common antibiotic has been subdued. The World Health Organization (WHO) (2011) and The World Organization for Animal Health (OIE) (2007) classify these drugs as ‘critically important antimicrobials’. Although the use and administration of antibiotics in animal farming are efficient in controlling diseases and mortality, it also becomes one of the leading factors contributing to the emergence and development of antimicrobial resistance (AMR) (Haulisah et al. 2021).

It is essential to determine the prevalence and investigate the contributing factors of E. coli in raw chicken meat that could potentially provide solutions to minimize health risk, eliminate unwanted pathogenic outbreak, and undertake preventive steps. Therefore, the aims of the present work were to assess the prevalence of E. coli in raw chicken meat from selected markets in Klang Valley, Malaysia, and examine its associated risk factors including type of market, packaging, storage temperature, organic status, and antibiotic factor. In addition, the present work also determined the antibiotic resistance profile and the presence of ESBL genotypes from the isolated E. coli to further determine its risk and threats. The present work hypothesized that E. coli contaminations would be significantly influenced by numerous factors such as the type of market (wet market vs. hypermarket), packaging process, storage temperature, organic status, and antibiotic exposure, with E. coli isolates potentially harbouring high levels of MAR including ESBL genotypes. The present work would provide further insights into the prevalence and contributing measures of E. coli in raw chicken meat in Klang Valley, Malaysia. Additionally, it could also serve as a safety indicator for meat products, and a benchmark that can be applied in Hazard Analysis and Critical Control Points, as well as increase awareness on the hygienic level of poultry sold at every retail level.

Materials and methods

Sample collection

A total of 100 whole chicken samples were collected from 9 wet markets (n = 47) and 10 hypermarkets (n = 53) located around Klang Valley, Malaysia, covering both urban and rural populations. Sampling visits were conducted for 6 months (May 2022 to October 2022). On every sampling day, two samples were randomly selected from each location. A study on consumer behaviour in Malaysia revealed that most consumers purchased fresh meat only from either modern retail stores or traditional markets, with freshness being the primary physical attributes influencing the purchase decision (Chamhuri and Batt 2013). Given this preference for fresh meat based on reported statistics, frozen chicken (−18 to −20°C) was excluded from the present work. A wet market is an open market that sells fresh produce, whereas a modern hypermarket is a huge retail store that sells a wide range of general products and groceries. Each chicken sample was placed in a labelled zip lock bag and kept in an ice box containing ice during transportation from the time of the sampling until its arrival to the laboratory. The chicken samples were categorized as ‘pre-packed’ if they were packed in any kind of package (vacuum packed or polyethylene plastic) and ‘without packaging’ if no packaging and only displayed on the shelf on ice. The display temperatures of the chicken samples were categorized into three groups, ambient temperature (25°C), refrigerated (1–5°C), and on ice (0°C). These categories were determined by verifying the standard common temperatures after acquiring the samples as some retail market lacked temperature indicators. Chicken samples from hypermarket were also categorized according to their growth condition either ‘organic’ or ‘non-organic’ and ‘antibiotic’ or ‘non-antibiotic’ based on their labelling. All samples were immediately prepared, analysed, and stored (4 ± 2°C, if needed) upon arrival to the laboratory.

Prevalence of E. coli from chicken samples

The isolation of E. coli was adapted from a previous study (Choi et al. 2017). The whole chicken was deboned, and all parts of the meat were taken, covering all major parts including breast, wings, thigh, and drumettes, in approximate proportional weight of 50 g to represent the whole chicken. Next, 50 g of chicken from each sample was submerged in 450 ml of buffered peptone water (BPW; Oxoid, UK), and homogenized using a BagMixer 400P stomacher machine (Interscience, Saint-Nom-la-Bretèche, France). The suspension was serially diluted in Universal bottle containing BPW from 10^–2 to 10^–5. Then, 1 ml was inoculated onto a dry dehydrated Petrifilm™ E. coli Coliform count plate (3 M Microbiology, USA). The inoculated Petrifilm™ was incubated at 37°C for 24 h. Plates with 15–150 blue colonies with gas bubble formation were selected for colony counting (Petrifilm™ Interpretation Guide, 3 M, USA 2017), and expressed in colony-forming units per gram of chicken meat (CFU/g). One colony isolate was taken to represent each positive sample for subsequent analysis.

DNA extraction and PCR analysis for verification of E. coli strain

The blue colonies collected from the Petriflim™ were grown in tryptic soy broth (Merck, Germany) for 24 h at 37°C. All the tubes showing apparent growth were subjected to DNA extraction using the boiled cell method adapted from a previous study (Jeyaletchumi et al. 2010b). Polymerase chain reaction (PCR) on the DNA template from each E. coli isolates was conducted to amplify a 16S rRNA gene region at 544 bp for the identification and verification of E. coli. The sequences of the primer pair used for targeting 16S rRNA were ECA75F (5′-GGAAGAAGCTTGCTTCTTTGCTGAC-3′) and ECR619R (5′AGCCCGGGGATTTCACATCTGACTTA-3′), which were adapted from a previous study (Sabat et al. 2000). The PCR was performed following the manufacturer's protocol (Promega, USA). The PCR products were analysed through agarose gel electrophoresis to determine and validate the presence of E. coli (New et al. 2018).

Antibiotic resistance profile of E. coli

Disk diffusion method of Kirby–Bauer was used to determine the susceptibility of E. coli isolates against selected antibiotics of veterinary significance on Mueller Hinton agar. Twelve different antibiotics under the category of Critically Important Antimicrobial Agents were selected based on the OIE List of Antimicrobial Agents of Veterinary Importance (OIE 2007). The antibiotics with the following concentrations were used: ampicillin-sulbactam (Sam) (20 µg), ampicillin (Amp) (10 µg), gentamycin (Cn) (10 µg), kanamycin (K) (30 µg), streptomycin (S) (10 µg), cefazolin (Cz) (30 µg), ciprofloxacin (Cip) (5 µg), ofloxacin (Ofx) (5 µg), tetracycline (Tc) (30 µg), doxycycline (Dc) (30 µg), trimethoprim-sulfamethoxazole (Sxt) (25 µg), and trimethoprim (W) (5 µg). Zones of inhibition were measured to the nearest millimetre (mm) and reported either as susceptible (S), intermediate resistant (I), or resistant (R) on the basis set by the Clinical Standard Laboratory Institute (CLSI) guideline breakpoint (CLSI 2020). All antimicrobial susceptibility results that fell into the intermediate category were presumed to be resistant for the purposes of the present work (Wong et al. 2012, 2014). This approach was taken to ensure a conservative assessment of AMR, as intermediate susceptibility may not guarantee clinical efficacy. Each sample was analysed in triplicate, and the average value was calculated from the three independent measurements. The results obtained were analysed for MAR. Every isolate was allocated an MAR index, as defined by Krumperman (1983).

Detection of ESBL-producing E. coli

Three ESBL genotypes (bla_TEM, bla_SHV, and bla_CTX-M) were identified to determine the prevalence of ESBL-producing E. coli among the E. coli positive chicken samples. The respective genotypes were amplified by PCR individually using the DNA template extracted for E. coli verification. Table 1 shows the sequence of the PCR primers including its expected size that were designed based on previous studies for bla_TEM, bla_SHV, and bla_CTX-M (Zaniani et al. 2012, Jahantabi et al. 2020).The PCR was performed following the manufacturers protocol (Promega, USA): initial denaturation for 5 min at 95°C, then 35 cycles, each consisting of a denaturation at 94°C for 1 min, annealing at 57°C for 30 s, extension at 72°C for 1 min, and followed by a final extension hold at 72°C for 7 min. Then, the PCR products were analysed by agarose gels electrophoresis to verify the presence of ESBL genotypes.

Statistical analysis

All samples were analysed in triplicates, and the CFU/g was converted to log CFU/g. Statistical analyses were performed using the Minitab software (version 19; Pennsylvania, USA). A univariate analysis was performed within the same risk factor (in Table 2) using cross-tabulations and the Pearson's chi-squared test. The Mann–Whitney test was performed to ascertain significant differences in E. coli loads (log CFU/g) in chicken meat within the same risk factor (in Table 3), with 95% confidence interval (P < .05 was considered significant) for both tests.

Results and discussion

Prevalence and microbial load of E. coli

Tables 2 and 3 show the distribution and loads of E. coli in fresh raw chicken samples from various sources, respectively. All isolates that showed growth of E. coli from the Petrifilm™ were subjected to PCR analysis for further genotypic verification. Fig. 1A shows the PCR bands on agarose gel that verify E. coli based on the 16S rRNA amplicon. The expected band size (using the specific 16S rRNA primer) from E. coli ATCC 25922 as the reference strain was 544 bp. A total of 74% (n = 74/100) chicken samples showed the prevalence of E. coli. Wet markets (83.0%, n = 39/47) showed higher prevalence of E. coli than hypermarkets (66.0%, n = 35/53). This was likely due to faecal contamination on the chicken samples, possibly contributed by poor hygiene of the operators during handling in wet markets. This in turn could possibly have been due to less stringent or lack of proper Standard Operating Procedures (e.g. the chicken display temperature) in wet markets as compared to hypermarkets. Mishandling of chicken carcasses, cross-contamination from the soil, cutting equipment, use of contaminated water for washing purposes, or post-processing contamination could result in E. coli contamination of chicken meat products (Chang et al. 2013). However, chi-squared test comparing the types of markets and E. coli contamination in retailed chicken meat revealed no significant difference (P ≥ .05) between the markets. Despite the variations in operation, the findings showed that microbial contamination from all types of markets had comparable prevalence. This was corroborated by Vital et al. (2014). Nevertheless, it was apparent that the E. coli loads from wet market samples (average microbial load of 3.834 ± 1.271 log CFU/g) were significantly (P < .05) higher compared to hypermarket samples (average microbial load of 3.301 ± 0.915 log CFU/g). This might have been due to the higher environment temperature and humidity in the wet markets, as this place normally operates in open air space compared to hypermarkets that are well equipped with proper storage facilities and adequate temperature control for their fresh produce. According to Qiu et al. (2022), the combination of high temperature and high humidity all year-round in the wet markets contributes to the risk of temperature abuse which is ideal for bacterial development. The contamination level of E. coli in the wet markets (Table 3) showed range as low as 1.204 log CFU/g to 6.097 log CFU/g. The variation in contamination level within the same factor might be caused by location, food handlers' knowledge and practices, individual market setting, and cleanliness. The hands of food handlers could be the vector spreading harmful microorganisms through cross-contamination. This could occur if they ignore the importance of washing their hands, and did not abide by the proper hygiene practices throughout the process. Food handlers should have excellent hygiene practices to prevent or reduce cross-contamination (Abdul-Mutalib et al. 2012). Samsudin et al. (2020) reported that there were significant difference in knowledge, attitude, and practices (KAP) among workers in wet markets, and emphasized on importance and impact of KAP in preventing leptospirosis. Food handlers' knowledge on food safety also affects their attitudes and practices towards safe food handling (Sani and Siow 2014). Hence, it is highly possible that the variation in contamination level of E. coli was contributed by differences in knowledge, attitudes, and practices among workers.

Different types of packaging of the chicken meat also contributed to the prevalence of E. coli. Pre-packed chicken samples (84.8%, n = 39/46; wet market, n = 4/4; hypermarket, n = 35/42) had significantly higher rate of E. coli than those without packaging (64.8%, n = 35/54; wet market, n = 35/43; hypermarket, n = 0/11). The higher prevalence of E. coli in pre-packed chicken samples might have been due to the incidence of cross-contamination during the packing process. This in turn might have been due to the non-sterility of the packaging used, and adhesion and persistence ability of microorganisms to the surfaces of the packaging. Multiple studies have shown that various foodborne pathogens, such as E. coli, Staphylococcus aureus, and Campylobacter jejuni, can persist for hours or even days on packaging films, utensils, and equipment surfaces (Kusumaningrum et al. 2003, Wilks et al. 2005). However, the data in the present work showed that there was no significant difference between the E. coli loads (P ≥ .05). This suggested that the presence of the packaging was not able to inhibit E. coli growth and possibly provided more conducive environment for the pathogen to grow (Caleb et al. 2013). It has been reported that the air enclosed in the package might support the proliferation of aerobic bacteria. Lee and Baek (2008) reported that the level of E. coli on baby spinach increased in packaging with air. Similar results concerning the development of bacteria in meat with different packaging was reported by Bingol and Ergun (2011). Their investigation showed that E. coli loads increased during storage in all tested packaging environment.

The findings from the present work showed that the storage temperature had significant (P < .05) effects where 100% (n = 19/19) of the samples displayed in ambient temperature had E. coli, followed by 72.9% (n = 35/48) and 60.6% (n = 20/33) of the samples displayed in refrigerated temperature and on ice (meat counter), respectively. The ambient temperature showed the highest E. coli load (4.900 ± 0.650 log CFU/g) which was significantly higher (P < .05) as compared to refrigerated (3.301 ± 0.915 log CFU/g) and on ice (2.822 ± 0.786 log CFU/g) samples. This is because E. coli is a mesophilic bacterium that can thrive at temperatures ranging from 21 to 49°C, with an optimum of 37°C (Noor et al. 2013). The growth of E. coli cells is impaired at temperatures below 21°C and stops at 7.5°C (Ingraham and Marr 1966), which coincided with the limited growth of E. coli on the samples that were displayed on ice observed in the present work.

Beside post-slaughter factors, pre-slaughter factors such as growth environment (organic and non-organic) and the administration of antibiotics also affect the prevalence of E. coli in chicken meat samples. In Malaysia, the organic agriculture industry is recognized as a niche market. Nevertheless, in 2002, Malaysia has enacted legislation to regulate organic farming in the country which is known as the Malaysian Organic Certification Program (myOrganic). All phases of the organic food value chain, including production, processing, handling, labelling, and marketing, are governed by the certification standards under the Ministry of Agriculture and Food Security. The present work reported that significantly higher (P < .05) prevalence of E. coli was observed in organically farmed (100%, n = 11/11), non-organically farmed (70.8%, n = 63/89), non-antibiotic (100%, n = 22/22), and antibiotic (66.7%, n = 52/78) samples. The main factor affecting the high prevalence of bacteria in organically farmed and non-antibiotic samples was the limitation of protective mechanism to prevent the growth of pathogenic bacteria throughout the raising process. Chang et al. (2013) also reported a higher prevalence of E. coli:O157 in organic chicken compared to standard cage non-organic chicken. However, the comparison of E. coli loads within organic and non-organic chicken samples in the present work showed no significant difference (P ≥ .05), which was possibly due to the presence of AMR E. coli that had the capability to grow equally in both organic and non-organic chicken samples. This was consistent with Stuart et al. (2012) who discovered similar microbial loads of extended spectrum beta-lactamase (ESBL) E. coli in both conventional and organic chicken samples.

Antibiotic resistance profile

Table 4 shows the antibiotic susceptibility profiles of 74 E. coli isolates against six classes of antibiotics. Among all antibiotics, E. coli isolates showed the highest susceptibility against gentamycin, an antibiotic commonly administered to defend against bacterial infections in swine (DVS 2021). Approximately 69–95% of the E. coli isolates showed resistance against the selected antibiotics listed in Table 4. The results also indicated that all E. coli isolates were resistant to ciprofloxacin. This may be attributed to extensive application of fluoroquinolones like ciprofloxacin, enrofloxacin, and nalidixic acid in the treatment and prevention of diseases in poultry farms (Er et al. 2013). Majority of the isolates (>90%) were also found to be highly resistant towards ampicillin, kanamycin, streptomycin, cefazolin, ciprofloxacin, doxycycline, and trimethoprim-sulfamethoxazole. This might possibly be due to the administration of those antibiotics in livestock production, and potential horizontal acquirement of the resistance towards the respective antibiotics (Chopra and Roberts 2001; de Mesquita Souza Saraiva et al. 2022). Prudent use of antibiotics is part of the Good Veterinary and Good Animal Husbandry Practices, and the guidelines on the use of the antibiotics for poultry such as ampicillin, doxycycline, and trimethoprim-sulfamethoxazole were included (DVS 2021). For poultry, oral antibiotic treatment is often administered to groups of animals rather than individually. It can be added on top of the animal feed or by adding it to drinking water (DVS 2021).

Table 5 shows the MAR indices and the percentage of occurrence for 74 E. coli isolates from chicken samples. The antibiotic resistance profile of each E. coli isolates was found to have different MAR indices, ranging from 0.33 to 1.00. The MAR = 0.33 means that the E. coli isolates were resistance against at least three different classes of antibiotics, and would be categorized as multidrug resistant (MDR). Any MAR index of >0.20 indicates that the bacterial isolates originated from a high-risk environment where antibiotics are commonly administered, are easily transferred, and possibly high rate of faecal contamination (Krumperman 1983, Gufe et al. 2019). This was consistent with a previous study conducted in Malaysia where 90% of the E. coli isolated from livestock were resistant to at least four antibiotics tested (Haulisah et al. 2021). Another study also showed high percentage (100%) of MDR E. coli isolated from broiler farm in East Coast of Peninsular Malaysia (Ibrahim et al. 2021). Sukhumungoon et al. (2011) have also reported that 38.5% of E. coli O157:H7 that were isolated from beef from various market in Malaysia showed resistant to four different types of antibiotics. These also agreed with similar research conducted in various Asian countries. Usui et al. (2014) reported that 91.5% of the E. coli isolates obtained from selected poultry farm in Vietnam were resistant to more than two antibiotics. Among them were ampicillin, cefazolin, cefdopoxime, kanamycin, gentamicin, dihydrostreptomycin, oxytetracycline, chloramphenicol, nalidixic acid, and enrofloxacin. In Thailand, 100% of the E. coli isolates obtained from broiler farms showed MDR against tetracycline, ampicillin, and erythromycin (Mooljuntee et al. 2010), and 80.3% of E. coli which were isolated from selected poultry samples in China exhibited MDR (Dou et al. 2016). Furthermore, in the present work, there were 35 out of 74 E. coli isolates that displayed the highest MAR index of 1.00, being resistant to 12 antibiotics across all the six classes. The presence of E. coli with high MAR index and MDR in livestock or poultry farms evidently poses significant risks including zoonotic transmission to humans, which can result in severe diseases that are difficult to treat. In addition, this AMR capability can also be transferred (horizontal and vertical gene transfer) causing higher resistance in other bacterial populations. This would also pose a complex challenge for veterinary treatments and could drive the use of more potent antibiotics that could further promote AMR and put more stress to the livestock's host. Regulatory bodies should impose stricter regulations, increase food safety measures, and undertake constant surveillance to assess the level of exposure, and implement effective intervention strategies to protect public health and animal welfare.

Detection of ESBL-producing E. coli

Fig. 1B–D show the PCR bands on agarose gel that verify the presence of bla_CTX-M, bla_TEM, and bla_SHV for the ESBL genotypes, respectively. Table 6 shows the TEM, SHV, and CTX-M ESBL detected among the 74 E. coli isolates expressed by bla_TEM, bla_SHV, and bla_CTX-M, respectively. In total, there were 90.5% (n = 67/74) of E. coli isolates that harboured at least one ESBL genes isolated from retail chicken meat sample. The majority of ESBL genotype that was found in chicken meat was the combination of both TEM and CTX-M, accounting for 63.51% (n = 47/74), and the highest for single ESBL gene was for CTX-M at 17.57% (n = 13/74). As high as 73.13% (n = 49/74) of the E. coli isolates harboured at least two ESBL resistance genes. SHV was the least prevalent ESBL gene detected in all isolates. Only one strain (1.35%) was found to harbour all three ESBL genes (TEM + SHV + CTX-M), and this is highly concerning that such strain was detected in chicken meat sample. The high prevalence of ESBL genes in chicken meat was similar to previous study by Suryadevara et al. (2020) where it was reported that 72.7% of MDR E. coli isolated from chicken samples in Selangor, Malaysia were ESBL-producing strains. In another study, 37.5% of E. coli isolated from chicken samples in Kelantan, Malaysia were also identified as MDR, carrying multiple genes including bla_TEM, bla_OXA, bla_NDM, and mcr (Aklilu et al. 2022). On the other hand, researchers also reported that CTX-M was the most common type of ESBL observed in their studies besides bla_TEM (Ho et al. 2012). Similarity between drug resistance genes in humans and retail meats can be caused by several factors, which include transferring of drug-resistant strains from food (Overdevest et al. 2011). A study conducted in Thailand reported the presence of ESBL-producing E. coli in poultry farms and concluded the effects during raising process as potential contributors to emergence of MDR in E. coli strains (Tansawai et al. 2019). Smet et al. (2011) concluded that E. coli strains of poultry origin may become established within the human microbiome and have the potential to transfer their bla gene to commensal E. coli in humans. Their study also demonstrated that the administration of third-generation cephalosporins significantly enhanced the proliferation of ESBL-producing bacteria in the human gastrointestinal tract. This indicates that antibiotic use not only promotes the selection and growth of resistant bacterial populations but may also increase the chances of these bacteria to transfer their resistance genes. The spread of ESBL-producing bacteria reduces the effectiveness of broad-spectrum antibiotics and can negatively affect patient recovery or even cause even severe reactions.

Referring to the Feed (Prohibited Antibiotics, Hormones, and Other Chemicals) Regulations 2012, all the antibiotics tested in the present work are not banned for use in livestock animals in Malaysia. The Malaysian Ministry of Health, through the National Pharmaceutical Control Bureau and the Pharmacy Enforcement Division are collaborating with the Department of Veterinary Services (DVS) to regulate the use of antibiotics in animal feed and ensure the safety of the Malaysian consumers. Even so, the Feed Act 2009 does not provide specific procedures and withdrawal periods of the antibiotics for farmers before the slaughtering process. This might cause the presence of antibiotics’ residue in the meat of the treated animals which would be a public concern, and pose threat to human health (Saidin et al. 2018). This supports the emergence of antibiotic resistance in E. coli isolated from chicken bred and sold in Malaysia. This could be attributed to an improper planning and excessive administration of antibiotic agents by the farmers, which could be threatening to public health (Ibrahim et al. 2021). MDR bacteria could develop resistance to multiple antibiotics from different families, which can cause treatments to be challenging. Infections with MDR bacteria are hard to treat since few or even no treatment options are available. Resistance towards multiple antibiotic classes at the same time poses a major issue in animal and human health. Different antibiotic classes have different mechanisms of action (Chopra and Roberts 2001; Gleckman et al. 1981, Zeng and Lin 2013, Aldred et al. 2014, Krause et al. 2016), and MDR can affect their effectiveness against bacterial infections, and this would increase health and exposure risk. Given the capability of bacteria to transfer antibiotic resistance genes, it shows that chicken could serve as potential source of antibiotic resistance genes for human bacteria (de Mesquita Souza Saraiva et al. 2022). This risk is further amplified when Malaysia showed notable increase in chicken meat exports from 86 970 tonnes in 2016 to ∼94 854 tonnes in 2021 (DVS Annual Reports 2022), including to Singapore and the Middle East (Benalywa et al. 2019). By 2050, it is estimated that approximately more than 10 million lives will be at risk annually as a consequence of the rise in drug-resistant infections (O'Neill 2016). Therefore, it is crucial to prevent the release of these resistant strains to maintain the effectiveness of existing medical treatments. The results from the present work could be essential in providing crucial knowledge and current status of AMR in animal husbandry. This would then help policymakers and healthcare providers to develop guidelines for safe food handling and preparation or amend existing regulations accordingly.

Conclusion

A high prevalence of E. coli was detected in retail chicken samples purchased from wet markets and hypermarkets around Klang Valley, Malaysia. The presence of E. coli in animals and their products remains a major challenge due to difficulties in control and regulation. The present work accepted the hypothesis that factors such as packaging, storage temperature, organic farming, and absence of antibiotic residues contributed significantly to the prevalence of E. coli in retail chicken meat. All the assessed risk factors in the present work were associated with E. coli prevalence in chicken from both wet markets and hypermarkets. In addition, a high proportion of E. coli isolates were found to be ESBL-producers, which indicated a rapid increase in antibiotic-resistant E. coli.

Despite the rigorous methodology employed in the present work, several limitations must be acknowledged. First, the possibility of cross-contamination of E. coli across all samples cannot be entirely ruled out due to non-aseptic handling by poultry and market workers. Although variations in antimicrobial susceptibility testing results and ESBL genotyping suggest differences in the contaminating E. coli strains, cross-contamination remains a potential confounding factor. This study also did not trace ESBL-producing strains back to their origin (whether the chickens were sourced from wet markets or hypermarkets). This decision was based on the finding that the origin was not identified as a significant factor influencing the prevalence of E. coli. Therefore, further source tracking was not prioritized in the present work. In addition, the study also focused on a single geographic area (Klang Valley) rather than the whole Malaysia, which serve as limitation to obtain more in-depth analysis. Future studies could, therefore, cover other regions to validate these findings, and assess regional variations. In order to reduce the formation of AMR in Malaysia, control mechanisms and a strong monitoring system should be implemented by regulatory bodies. Immediate actions and effective interventions are essential to prevent contamination by foodborne pathogens that can cause outbreaks and diseases. Definitive rules, effective policies, and monitoring activities, combined with food safety training for vendors and consumers on hygiene practices, are needed to ensure safe and healthy food supplies.

Acknowledgements

The present work was technically supported by the Faculty of Food Science and Technology, Universiti Putra Malaysia.

Conflict of interest

All authors declare there is no conflict of interest.

References