ANTIBIOTIC RESISTANCE PATTERN OF ESCHERICHIA COLI DERIVED FROM RETAIL RAW MEAT IN NORTH SUMATERA,
INDONESIA
Rita Rosmala Dewi1), Karina Mia Berutu1), Juli Mutiara Sihombing1)
1) Faculty of Agriculture and Animal Husbandry, Tjut Nyak Dhien University, Medan, Sumatera Utara, Gg.
Rasmi No.28, Sei Sikambing C. II, Kec. Medan Helvetia, Kota Medan, Sumatera Utara 20123
*Corresponding Email: [email protected] Submitted 21 May 2023; Accepted 10 July 2023
ABSTRACT
Bacteria from animals raised for food that have developed antimicrobial resistance (AMR) may serve as a vehicle for its transmission from animal to human. Nevertheless, the antibiotic resistance profile of Escherichia coli from raw meat is scarcely reported, especially in North Sumatra. The aim of this investigation was to investigate the retail raw meat for the presence of E. coli and its antimicrobial resistance pattern. We purchased 80 packages of fresh meat products from four traditional markets located in Deli Serdang and Medan. Escherichia coli was isolated by an established microbiology test and a phenotypic antimicrobial susceptibility test was conducted by the method of disk diffusion. The data analysis of antibiotic resistance and multi-drug resistance (MDR) levels was performed by using WHONET 5.6. The antibiotic resistance dissimilarity between the two regencies was analyzed by using chi-square analysis.
This study observed about 19 E coli isolates (23.7%) were obtained from raw meat. Resistance toward the antibiotics listed as critically important for veterinary and human therapy is increasing concern for public health. The isolates were highly resistant to ampicillin and tetracycline. Meanwhile gentamycin is susceptible. The MDR level of E. coli in both regencies of North Sumatra was about 21.05%. This finding contribute essential information on AMR in food animals and can be used to improve local and regional plans for the administration of antibiotics to livestock.
Key words: Antimicrobial resistance (AMR); Escherichia coli; multidrug resistance (MDR)
INTRODUCTION
Antimicrobial resistance (AMR) is a health burden globally. AMR among human, animal, and zoonotic pathogens has emerged and disseminated, posing a serious threat to human health globally (Vidovic &
Vidovic, 2020). Illness involving AMR increases the risk of major medical condition and lengthy hospital stays, which in turn raises the cost of healthcare, the price of second-line medications, and the likelihood that treatments may fail (Dadgostar, 2019).
According to the recent data published by Murray et al., (2022), there were about 12.7 million fatalities in 2019 that were directly related to bacterial AMR out of an expected 495 million deaths linked to bacterial AMR worldwide. Antibiotic-resistant bacteria may spread to people through a variety of complicated and unpredictable routes. Food- producing animals become the drivers for the antimicrobial resistance of pathogen including E. coli through the food chain or direct contamination to human (Vidovic &
Vidovic, 2020).
Escherichia coli, a commensal bacterium of the intestinal flora of warm blood animals, is commonly used as indicator organisms for antimicrobial resistance (Moreno et al., 2000). This is due to their widespread distribution in the gut and ease with which they can acquire genes encoding antibiotic resistance as a result of their genomic plasticity (Azabo et al., 2022).
E. coli engages in the enterobacterial gene pool as a resistance gene donor and recipient, enabling it to both acquire and provide resistance genes to other bacteria.
(Poirel et al., 2018). Generally, antimicrobial resistance of E. coli is considered one of the important challenges
in both humans and animals at a global scale and may contribute as a real public health concern.
Contamination of antibiotic resistance bacteria in the food producing animal reported may due to the antibiotic application in the livestock. Resistance to particular antibiotics in commensal E. coli isolates from swine, poultry, and cattle is reported closely correlated with the level of use of these medications (Chantziaras et al., 2014). Antibiotics application in livestock is reported in the East Asia countries (Nhung et al., 2016) and worldwide (Van Boeckel et al., 2015). Indonesia is predicted among the five nations with the highest expected percentage elevates in consumption of antimicrobial by 2030 (Van Boeckel et al., 2015).
Furthermore, Indonesia, determined from 50 countries with the largest amounts of antibiotics applied in livestock in 2010, include Myanmar (205%), Indonesia (202%), Nigeria (163%), Peru (160%), and Vietnam (157%) (Van Boeckel et al., 2015).
The large production of cattle to meet Indonesia's strong demand for beef meat (Agus & Widi, 2018) results in a high usage of antibiotics among the country's livestock.
Farm animals including cattle has been shown to be a possible source of microorganisms resistant to antibiotics (Bitrus et al., 2019). Hence, the emergence of antibiotic resistance among pathogen from food-producing animals is a growing problem for veterinary medicine and public health.
In Indonesia, several investigations have been conducted the AMR in the food- producing animal product including raw meat in Surabaya (Effendi et al., 2020), poultry meat in Surabaya (Sudarmadi et al.,
*Corresponding author:
Rita Rosmala Dewi
Email: [email protected]
Faculty of Agriculture and Animal Husbandry, Tjut Nyak Dhien University, Medan, Sumatera Utara, Gg. Rasmi No.28, Sei Sikambing C. II, Kec. Medan Helvetia, Kota Medan, Sumatera Utara 20123
How to cite:
Dewi, R. R., Berutu, K. M., & Sihombing, J. M.
(2023). Antibiotic Resistance Pattern of Escherichia coli Derived from Retail Raw Meat in North Sumatera, Indonesia. Jurnal Ilmu dan Teknologi Hasil Ternak (JITEK), 18 (2), 87-99
2020) and Bogor (Januari et al., 2019).
Notwithstanding, there is dearth of information on antimicrobial residue from food-producing animal products (Arief &
Taufik, 2019) and none of them discuss about AMR pattern of bacteria E. coli observed from raw meat in Medan, North Sumatera. The Statistic Central Beraue of North Sumatera recorded the increased of production in beef cattle from 12,986,163 kg in 2020 to 13,286,017 kg in 2021 (BPS, 2022).
The high production of beef cattle may rise the high antibiotic usage in animal production. Then, the antibiotic consumption in livestock may disseminate the resistance bacteria the animal product from farm to fork. Hence, it calls the urgent necessity for antimicrobial resistance monitoring in livestock and the retail.
Furthermore, such information is needed by policymakers to regulate the antimicrobials prudent use in animal production.
MATERIALS AND METHODS
Study Area and Sampling
This study was carried out in two regencies, Medan and Deli Serdang, of North Sumatera, Indonesia. Sampling was carried out between January and March 2023. In all, 80 samples of beef meats were selected from four traditional markets and examined for the presence of E. coli and antibiotic sensitivity test (AST). The laboratory analysis was conducted in the Microbiology laboratory, Tjut Nyak Dhien University.
Isolation and Identification
E. coli was isolated in accordance with (Jang et al., 2008) and (Adzitey et al., 2021).
In total, 10 g of raw meat was pre-enriched in 90 mL of Peptone Buffered Water (Merck, Germany) and incubated at 37 C for 24 hours. The aliquots were streaked on Levine’s eosin-methylene blue agar (Merck, Germany) and incubated at 37 C for 24 hours. Biochemical tests were performed to identify E. coli using indole, Methyl
Red,Voges–Proskauer, and citrate utilization test (IMViC), and Triple Sugar Iron Agar (TSIA) (Merck, Germany).
Antibiotic Sensitivity Test
The antibiotics susceptibility of E. coli was examined for 5 antibiotics. These antibiotics were performed using disk diffusion (concentration in µg):
ciprofloxacin (5 µg), gentamycin (10 µg), chloramphenicol (30 µg), ampicillin (10 µg), and tetracycline (30 µg). The selection of antibiotics were according to WHO and OIE recommendation for the antimicrobials usage in human and farmed animals (OIE, 2015; WHO, 2019); The choice complied with Indonesia's Antimicrobial Resistance Integrated Surveillance (Suady, 2019). The method of disk diffusion for E coli was conducted in compliance with the Clinical and Laboratory Standards Institute (CLSI) guidelines (CLSI, 2018).
Data Analysis
Antimicrobial sensitivity test data of E. coli isolates from raw meat were analyzed separately in WHONET 5.6 (WHO, 2006a, 2006b). The MAR index was determined and interpreted by using the formula : a/b , where ‘a’ represent the antibiotics number to which an isolates was resistant and ‘b’
represent the antibiotic tested (Krumperman, 1983).
The phenotypic pattern of AMR and frequency of MDR were analyzed by WHONET 5.6 software. The chi-square test was performed to compare the discrepancies in the AMR pattern across the regencies of Medan and Deli Serdang. The MDR frequency to bacteria both Medan and Deli Serdang regency was sorted and compared.
SPSS was the software employed for the statistical analyses, with a significance level of α = 0.05.
RESULTS AND DISSCUSION
The E. coli Prevalence
Overall, E. coli prevalence in raw meat from traditional market from Sumatera
Utara was about 23.7%. Meanwhile, the prevalence of E coli from markets in two regencys including Medan and Deli Serdang was about 20% (95% CI = 12.2, 30.8) and 22.5% (95% CI = 14.6- 34.5) respectively (Table 1). This study also compared the E
coli contamination between two regencies at the retail stage. It revealed that there were no significant differences in E. coli proportion obtained from raw meat between traditional market in Medan and Deli Serdang (χ2 = 0.075 p = 0.785).
Table 1. Escherichia coli derived from raw meat in the traditional Market in Medan and Deli Serdang Regency, North Sumatera
Regency Total Prevalence (95%CI)
Medan 40 8(20; 12.2- 30.8)
Deli Serdang 40 11(27.5; 18.6- 40.5)
The contamination of E coli in animal products especially meat were also reported from Indonesia (Bahri et al., 2019; Bontong et al., 2012; Elsie, 2016) as well as worldwide (Adzitey et al., 2021). Even though this study showed the lower prevalence compare to other investigations from Egypt about 54% (Gwida et al., 2014) and Ghana about 80% (Adzitey et al., 2021).
Meanwhile, this investigation found to be higher compare to developed countries such as Europe (1.0%) as well as Italy (11.6%) (EFSA, 2018; Nobili et al., 2022) where there is a high premium placed on handling animals hygienically and processing them into meat and meat products.
Many aspects, including accuracy, the isolation and detection method used, the quantity of samples acquired, the type of samples analyzed, the period of sampling, the level of cleanliness maintained, and the location of sampling, may be highlighted by the stark disparities in E coli prevalence between nations. (Adzitey et al., 2020;
EFSA, 2018; Gwida et al., 2014; Nobili et al., 2022).
Most meats contain approximately high water activity (
a
w) about 0.99 which is preferable for the microbes growth (Enock et al., 2017). The presence of E. coli in the meat samples suggests that lapses take place throughout the transport, sale of the meat, and slaughter of the animals (Koutsoumanis et al., 2022). This is because a disease-free animal's muscle is unavoidably sterile. After the process of animal slaughtered, the exposed meat are vulnerable tocontamination by microbes (Adzitey et al., 2020). E. coli has been observed to flourish naturally in farm animals' digestive tracts.
(Bélanger et al., 2011).
Therefore, when the digestive tract ruptures during evisceration, the contaminated meats possibly become the reason of E coli contamination in meat samples. In addition, knives, tables and utensils that worn in the market were cross contaminated and found to be positive E coli (Adzitey et al., 2020). It has been established that E. coli serves as an indicator bacterium for indicating unsanitary conditions in the food processing chain (Martin et al., 2016).
Therefore, the occurrence of contamination raw meats in the markets from both regencies possibly derived from cross-contamination from food chain and meats handling at the retail stage. We found that there were no differences of E coli prevalence between the traditional market from Medan and Deli Serdang.
Hence, this study highlighted that the hygienic condition of the meat stalls in the traditional market between Medan and Deli Serdang is comparable. Since E. coli is considered an important bacteria from food- producing animals due to their ability to transmit the diseases through food chain of animal products (Heredia & García, 2018) as well as their resistant phenotype (Bitrus et al., 2019), then potential public health hazard from meat products sold in the traditional markets in the studied area is on the rise.
Antibiotic Susceptibility of E coli Bacteria Overall, 19 isolates comprising E. coli from Medan (n=8) and Deli Serdang (n=11) were tested to antibiotic susceptibility testing (AST). Figures 1. depicted the E. coli isolates antibiograms. Different levels of
resistance against the five antibiotics tested were demonstrated in the antimicrobial resistance profile of E. coli isolates from traditional markets in North Sumatera Province shown in Figure 1.
Figure 1. Antibiotic susceptibility pattern of E. coli isolates recovered from raw meat obtained from traditional market of North Sumatera against antimicrobials tested. R:
Resistant; I: Intermediate; S: Susceptible
Figure 2. Antibiotic susceptibility pattern of E. coli isolates recovered from raw meat obtained from traditional market of Medan Regency against antimicrobials tested. R:
Resistant; I: Intermediate; S: Susceptible
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Ampicillin Tetracycline Ciprofloxacin Chloramphenicol Gentamycin
R I S
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Ampicillin Tetracycline Ciprofloxacin Chloramphenicol Gentamycin
R I S
Figure 3. Antibiotic susceptibility pattern of E. coli isolates recovered from raw meat obtained from traditional market of Deli Serdang Regency against antimicrobials tested. R:
Resistant; I: Intermediate; S: Susceptible
The highest level of resistance was recovered for ampicillin (68.4%; 95% CI = 43.5-86.4) and tetracycline (42.1%; 21.1- 66.0). Varying levels of resistance to the five antibiotics tested have been observed in the antimicrobial resistance profile of E. coli obtained from raw meat in the traditional market of the Medan Regency (Figure 2).
The highest level of resistance is toward ampicillin (90.9%; 95% CI=57.1- 99.5) and tetracycline (36.4 %;12.4-68.4).
The profile of antibiotic resistance among E.
coli isolates from raw meat in traditional market of Deli Serdang Regency in Figure 3 illustrated varying levels of resistance against the five antibiotics tested. The highest level of resistance recorded for ampicillin (36.4%; 95% CI=10.2-74.1) and tetracycline (36.4%; 95% CI=10.2-74.1).
Many nations have designated the AMR surveillance involving food- producing animals a top priority, including Indonesia, due to the emergence of AMR in livestock and their products in the retail stage. The very high resistance prevalence to ampicillin and tetracycline supports the previous report of Indonesia surveillance of livestock by Suady, (2019). However slightly lower level of ciprofloxacin was reported in this study. The very high
resistance against ampicillin (100%) and tetracycline (89%) were also recorded from raw meat from traditional market in Surabaya (Effendi et al., 2020), which is in accordance with this findings.
The high resistance observed for tetracycline was in accordance with that reported in E. coli isolated from raw meat from Nepal (Saud et al., 2019) and Ghana (Adzitey et al., 2021). In contrast, the lower prevalence of chloramphenicol and sensitive to gentamycin was recorded in this study compare to aforementioned studies.
Improper handling of contaminated raw meat possibly caused the cross- contamination of resistant bacteria in the food chain (Aworh et al., 2021; Hammerum
& Heuer, 2009) or during the slaughter process (Alexander et al., 2010).
Moreover, the high level of tetracycline and ampicillin resistance recorded possibly indicate the high consumed of these antibiotics in the human and veterinary medicine, for instance Roth et al., (2019) reported that resistant E coli can be contaminate food animals from antibiotic usage in farm level. Tetracycline and ampicillin have been used extensively in the diseases therapy of human and animal infections (OIE, 2007). Additionally,
0%
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30%
40%
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60%
70%
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90%
100%
Ampicillin Tetracycline Ciprofloxacin Chloramphenicol Gentamycin
R I S
tetracycline is frequently used as growth promoters in animal feed at subtherapeutic concentrations (Chopra & Roberts, 2001).
Yusuf et al., (2018) also found that tetracycline is the most antibiotics used in Indonesia’s cattle based on their investigation through several provinces of Indonesia.
Furthermore, on the OIE antibiotic list, ampicillin and tetracycline are classified as veterinary critically important antibiotics (VCIA), which are crucial for treating diseases in animal production. (OIE, 2007).
Therefore, high resistance toward these antibiotics leading to a significant risk to human and animal health. Consumers may be at risk for health problems because meat and other animal sources have been demonstrated to be a significant route for extraintestinal MDR bacteria, particularly for Salmonella and E. coli (Xu et al., 2022;
Yamaji et al., 2018).
Disparities between Resistance Profile of E. coli Isolates from Traditional market in Medan and Deli Serdang
The pattern of antimicrobial resistance of E. coli isolated from raw meat collected from the traditional market of Medan and Deli Serdang are provided in Table 2. The majority of E. coli isolates were ampicillin (37.5 to 90.9%) and tetracycline (36.4 to 37.5%) resistant in both Medan and Deli
Serdang Traditional markets (Table 2). In comparison to Deli Serdang, E. coli isolates from Medan demonstrated higher prevalence of ampicillin resistance.
Meanwhile E coli isolates obtained from Deli Serdang demonstrated higher level resistance toward chloramphenicol, ciprofloxacin and tetracycline.
All tested antibiotics resistance patterns for E. coli from Medan and Deli Serdang regency are similar. Resistance was highest for tetracycline and ampicillin and susceptible is for gentamycin. Meanwhile, there were statistically significant variations between the level of AMR in E. coli obtained from Medan and Deli Serdang regency for ampicillin, while there were no statistically significant variations in proportion of MDR among E. coli isolated from Medan and Deli Serdang traditional market (χ2 = 3.074 p = 0.080). Significant discrepancies were observed only for ampicillin resistance. (Table 2). Microbes can exchange genes that give each other resistance when they are in close proximity to one another (Peterson & Kaur, 2018). In addition, E coli is reported acts as resistance genes donor and recipients then this allow them to acquire resistance genes from other bacteria and disseminate it to other bacteria (Cho et al., 2019). This ambience may lead about resemblance and divergence in their pattern of resistance.
Table 2. Antimicrobial Resistance Profile between E. coli isolates from Traditional market of Medan and Deli Serdang, North Sumatera.
Antimicrobial Agent Resistance % (95% CI)
Medan Deli Serdang
Ampicillin 90.9 (57.1-99.5) 37.5(10.2-74.1)*
Chloramphenicol 9.1 (0.5-42.9) 25 (4.5-64.4)
Ciprofloxacin 18.2 (3.2-52.3) 25 (4.5-64.4)
Gentamycin 0 (0.0-32.1) 0 (0.0-40.2)
Tetracycline 36.4 (12.4-68.4) 37.5 (10.2-74.1)
* Significant difference between E coli from Medan and Deli Serdang, P < 0.05.
Multidrug Resistance and MAR Index Table 3 depict the Multiple Antibiotics Resistance (MAR) index of E coli isolated from traditional market in North Sumatera. The identification if high- threat sources resistant faecal contamination
of food could be showed by the MAR indexing of bacteria, including E. coli (Ranasinghe et al., 2022). Up till now, no study has investigated the MAR index of meat-origin E. coli in North Sumatera. The average MAR index across 19 isolates was
0.33, with a range of 0 to 0.8. The combined antimicrobial agent patterns with the highest MAR value of 0.8 are as follows: Amp Cip Chl Te. Value of MAR greater than 0.2 denotes a high contamination risk where application of antibiotics frequently used.
This finding revealed 78.9% had indexes between 0.2-0.8 which is represent resistance to at least one or more antibiotics agents. Studies described by (Ranasinghe et al., 2022) and (Adzitey et al., 2021) showed the presence of high MAR in a relatively
similar level with study. The high prevalence demonstrates a significant adverse impact in usage of common antibiotic. High prevalence of ampicillin and tetracycline from raw meat possibly shows the frequent usage of common antibiotics (Ranasinghe et al., 2022). Due to the widespread imprudent use and out-of- date antimicrobial agents, the worldwide burden of MAR has increased to unacceptable proportions (Okeke et al., 2005; Ranasinghe et al., 2022).
Table 3. Antibiotic resistance profile and multiple antibiotic resistance index of individual Escherichia coli isolated from meat samples from Traditional market in North Sumatera
Serial Number Escherichia coli isolate Code Regency Antibiotic Resistance Profile MAR Index
1 P7 Medan Amp Cip Chl Te 0.8
2 P8 Medan Amp Cip Chl Te 0.8
3 K6 Deli Serdang Amp Chl Te 0.6
4 J16 Deli Serdang Amp Cip Te 0.6
5 K98 Deli Serdang Amp Cip 0.4
6 J25 Deli Serdang Amp Cip 0.4
7 P5 Medan Amp Te 0.4
8 K15 Deli Serdang Amp Te 0.4
9 P14 Medan Amp Te 0.4
10 J8 Deli Serdang Amp Te 0.4
11 J22 Deli Serdang Amp 0.2
12 K11 Deli Serdang Amp 0.2
13 K18 Deli Serdang Amp 0.2
14 K3 Deli Serdang Amp 0.2
15 K7 Deli Serdang Cip 0.2
16 P3 Medan 0
17 P4 Medan 0
18 P10 Medan 0
19 P13 Medan 0
MAR: Multiple Antibiotic resistance index, Amp: Ampicillin, Cip: Ciprofloxacin, Chl: Chloramphenicol, Te: Tetracycline
Figure 4. Multi-drug resistance of E. coli from raw meat recovered from traditional market on Medan and Deli Serdang regency. Numbers inside the brackets “()” denote the number of isolates; those on bars indicate percent isolates showing resistance; non- MDR = Resistant against only 1 or 2 classes of antibiotics; MDR=Multidrug resistance.
50,0%
25,0%
25,0%
0,0%
81,8%
18,2%
N O R E S I S T A N C E ( % ) N O N - M D R ( % ) M D R ( % )
Medan (8) Deli Serdang (11)
A high level of MDR (25%) was observed for E. coli from Medan, with another 25% resistant to one or two antibiotics agents tested (Figure 4). Overall, 18.2 % of E. coli isolated from raw meat in Deli Serdang traditional market was resistant to multiple classes of antibiotics;
81.8% was resistant to one or two antibiotic classes (Figure 4).
The relatively high MDR prevalence in food producing animal is steadily reported in multiple studies from Indonesia (Effendi et al., 2020), Nepal (Saud et al., 2019), and Ghana (Adzitey et al., 2021). Initially, MDR bacteria were associated with hospital- acquired infections (Bharadwaj et al., 2022).
However, the extensive application of antibiotics nowadays in the human and veterinary medicine elevate the emergence of MDR among bacteria (Caneschi et al., 2023). By accumulating genes that each code for resistance to a different agent on resistance plasmids or transposons, or by the actions of multidrug efflux pumps, each of which can release more than one drug type, bacteria can develop multidrug resistance (Nikaido, 2009). In addition, E. coli has an ability as the reservoir of resistance traits that can disseminates the multi-drug resistance genes among bacteria (Szmolka
& Nagy, 2013).
The high level of MDR revealed in this study may increase the awareness of MDR development in the food-producing animal products. The food industry is becoming increasingly concerned about the potential hazards of MDR due to the seriousness of the diseases that MDR zoonotic pathogens may cause, which could result in a deprivation of consumer confidence and, as a result, a decline in demand for animal origin foods (Pérez- Rodríguez & Mercanoglu Taban, 2019).
Therefore, surveillance and monitoring of antibiotics resistance in E coli and other public health significance bacteria from food of animal origin is essential to provide the information is needed by policymakers to regulate the antimicrobials prudent use in animal production.
CONCLUSION
This is the first report of AMR phenotypic, MDR and MAR index isolated from meat in North Sumatera. The resistant and MDR E. coli was observed in the raw meat isolated from traditional market in North Sumatera. This study highlighted high resistance toward ampicillin and tetracycline in both regencies of North Sumatera. Since these antibiotics listed under veterinary critically important antibiotics that are of particular importance in treating diseases in animal production as well as human, this may jeopardy the public health through animal products contamination of resistant E coli. Relatively High MDR among E coli isolates found in this study also rise the hazard for public health. The MAR result in this study concerning the traditional market may serve as the high-risk resistant bacteria contamination in the food chain. Therefore, for the future, the comprehensive data about AMR “from farm to fork” of North Sumatera is needed for better understanding regarding the dissemination of AMR in the food producing animal products.
ACKNOWLEDGMENT
The authors would like to thank to Ika Julianti from Faculty of Pharmacy, Tjut Nyak Dhien University for the laboratory assistance and Yunida Berliana, the Dean of Faculty of Agriculture and Animal Husbandry, Tjut Nyak Dhien University for the administration support during research.
REFERENCES
Adzitey, F., Assoah-Peprah, P., Teye, G. A., Somboro, A. M., Kumalo, H. M., &
Amoako, D. G. (2020). Prevalence and antimicrobial resistance of Escherichia coli isolated from various meat types in the tamale metropolis of Ghana. International Journal of Food Science, 2020. https://doi.org/10.1155 /2020/8877196
Adzitey, F., Huda, N., & Shariff, A. H. M.
(2021). Phenotypic antimicrobial susceptibility of Escherichia coli from raw meats, ready-to-eat meats, and their related samples in one health context. Microorganisms, 9(2), 1–11.
https://doi.org/10.3390/microorganis ms9020326
Agus, A., & Widi, T. S. M. (2018). Current situation and future prospects for beef cattle production in Indonesia - A review. Asian-Australasian Journal of Animal Sciences, 31(7), 976–983.
https://doi.org/10.5713/ajas.18.0233 Alexander, T. W., Inglis, G. D., Yanke, L.
J., Topp, E., Read, R. R., Reuter, T., &
McAllister, T. A. (2010). Farm-to- fork characterization of Escherichia coli associated with feedlot cattle with a known history of antimicrobial use.
International Journal of Food Microbiology, 137(1), 40–48.
https://doi.org/10.1016/j.ijfoodmicro.
2009.11.008
Arief, I. I., & Taufik, E. (2019). Analisis residu antibiotik serta kualitas daging dan hati ayam broiler Di Kabupaten Pidie Jaya Provinsi Aceh. Oktober, 07(3), 102–110.
Aworh, M. K., Kwaga, J. K. P., Hendriksen, R. S., Okolocha, E. C., & Thakur, S.
(2021). Genetic relatedness of multidrug resistant Escherichia coli isolated from humans, chickens and poultry environments. Antimicrobial Resistance and Infection Control, 10(1), 1–13. https://doi.org/10.1186/
s13756-021-00930-x
Azabo, R. R., Mshana, S. E., Matee, M. I.,
& Kimera, S. I. (2022). Antimicrobial resistance pattern of Escherichia coli isolates from small scale dairy cattle in Dar es Salaam, Tanzania. Animals, 12(14), 1–14. https://doi.org/10.3390 /ani12141853
Bahri, S., Rokhim, S., & Prasiska, Y. S.
(2019). Kontaminasi bakteri escherichia coli pada sampel daging.
Journal of Health Science and Prevention, 3(1), 62–67. https://doi.
org/10.29080/jhsp.v3i1.195
Bélanger, L., Garenaux, A., Harel, J., Boulianne, M., Nadeau, E., & Dozois, C. M. (2011). Escherichia coli from animal reservoirs as a potential source of human extraintestinal pathogenic E.
coli. FEMS Immunology and Medical Microbiology, 62(1), 1–10. https://doi.
org/10.1111/j.1574-695X.2011.00797.x Bharadwaj, A., Rastogi, A., Pandey, S.,
Gupta, S., & Sohal, J. S. (2022).
Multidrug-resistant bacteria: their mechanism of action and prophylaxis.
BioMed Research International, 2022.
https://doi.org/10.1155/2022/5419874 Bitrus, A. A., Mshelia, P. A., Kwoji, I. D., Goni, M. D., & Jajere, S. M. (2019).
Extended-spectrum beta-lactamase and ampicillin Class C beta- lactamase-producing Escherichia coli from food animals: A review.
International Journal of One Health, 5, 65–75. https://doi.org/10.14202/
IJOH.2019.65-75
Bontong, R. A., Mahatmi, H., & Suada, I. K.
(2012). Kontaminasi bakteri escherichia coli pada daging se’i sapi yang dipasarkan di Kota Kupang.
Indonesia Medicus Veterinus, 1(5), 699–711.
BPS. (2022). Produksi Daging Ternak Menurut Kabupaten/Kota dan Jenis Ternak (kg), 2020 dan 2021.
Caneschi, A., Bardhi, A., Barbarossa, A., &
Zaghini, A. (2023). The use of antibiotics and antimicrobial resistance in veterinary medicine, a complex phenomenon: a narrative review. Antibiotics, 12(3), 487. https://
doi.org/10.3390/antibiotics12030487 Chantziaras, I., Boyen, F., Callens, B., &
Dewulf, J. (2014). Correlation between veterinary antimicrobial use and antimicrobial resistance in food- producing animals: A report on seven countries. Journal of Antimicrobial Chemotherapy, 69(3), 827–834.
https://doi.org/10.1093/jac/dkt443 Cho, S., Nguyen, H. A. T., McDonald, J. M.,
Woodley, T. A., Hiott, L. M., Barrett,
J. B., Jackson, C. R., & Frye, J. G.
(2019). Genetic characterization of antimicrobial-resistant Escherichia coli isolated from a mixed-use watershed in northeast Georgia, USA.
International Journal of Environmental Research and Public Health, 16(19), 1–14. https://doi.org/
10.3390/ijerph16193761
Chopra, I., & Roberts, M. (2001).
Tetracycline Antibiotics: Mode of Action, Applications, Molecular Biology, and Epidemiology of Bacterial Resistance. Microbiology and Molecular Biology Reviews, 65(2), 232–260. https://doi.org/
10.1128/mmbr.65.2.232-260.2001 CLSI. (2018). Performance Standards for
Antimicrobial Disk and Dillution Susceptibility Test for Bacteria Isolated from Animals (5th ed.). CLSI Standard VET01. Wayne, PA:
Clinical and Laboratory Standards Institute.
Dadgostar, P. (2019). Antimicrobial resistance: implications and costs.
Infection and Drug Resistance, 12, 3903–3910. https://doi.org/10.2147/
IDR.S234610
Effendi, M. H., Cicilia, R., Rahmahani, J., &
Tyasningsih, W. (2020). Public Awareness for Antimicrobial Resistance from Escherichia coli Isolated from Beef Sold on Several Wet Market in Surabaya, Indone.
Indian Journal of Public Health, 11(9), 295–300.
EFSA. (2018). The European Union summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks in 2017. EFSA Journal, 16(12). https://doi.org/10.
2903/j.efsa.2018.5500
Elsie, I. H. (2016). Isolasi Escherichia coli Pada Daging Sapi Segar Yang Diperoleh Dari Beberapa Pasar Tradisional Di Pekanbaru Elsie, Israwati Harahap. Jurnal Photon, 7(1), 121–125.
Enock, D., Chama, O. N., & Emmanuel, A.
(2017). Effect of Animal Species on the Quality and Quantity of Kilishi Meat Products in Mubi North Local Government Area of Adamawa State.
International Journal of Rural Development, Environment and Health Research, 1(4), 13–20.
https://doi.org/10.22161/ijreh.1.4.3 Gwida, M., Hotzel, H., Geue, L., & Tomaso,
H. (2014). Occurrence of Enterobacteriaceae in Raw Meat and in Human Samples from Egyptian Retail Sellers . International Scholarly Research Notices, 2014(May 2013), 1–6. https://doi.org/10.1155/2014/56 5671
Hammerum, A. M., & Heuer, O. E. (2009).
Human health hazards from antimicrobial-resistant escherichia coli of animal origin. Clinical Infectious Diseases, 48(7), 916–921.
https://doi.org/10.1086/597292
Heredia, N., & García, S. (2018). Animals as sources of food-borne pathogens: A review. Animal Nutrition, 4(3), 250–
255. https://doi.org/10.1016/j.aninu.
2018.04.006
Jang, S., Biberstein, E., & Hirsh, D. (2008).
A Diagnostic: Manual of Veterinary Clinical Bacteriology and Mycology.
Iowa: University of California Davis County.
Januari, C., Sudarwanto, M. B., &
Purnawarman, T. (2019). Resistensi Antibiotik pada Escherichia coli yang Diisolasi dari Daging Ayam pada Pasar Tradisional di Kota Bogor (Antibiotic Resistance In Escherichia Coli Isolated From Chicken Meat Of Traditional Markets In The City Of Bogor). Jurnal Veteriner, 20(1), 125.
https://doi.org/10.19087/jveteriner.20 19.20.1.125
Koutsoumanis, K., Allende, A., Álvarez- Ordóñez, A., Bolton, D., Bover-Cid, S., Chemaly, M., Davies, R., De Cesare, A., Herman, L., Hilbert, F., Lindqvist, R., Nauta, M., Ru, G., Simmons, M., Skandamis, P., Suffredini, E., Argüello-Rodríguez,
H., Dohmen, W., Magistrali, C. F., Peixe, L. (2022). Transmission of antimicrobial resistance (AMR) during animal transport. EFSA Journal, 20(10). https://doi.org/10.29 03/j.efsa.2022.7586
Krumperman, P. H. (1983). Multiple Antibiotic Resistance Indexing of Escherichia coli to Identify High-Risk Sources of Fecal Contamination of Foodst. Applied and Enviromental Microbiology, 46(1), 165–170.
Martin, N. H., Trmcic, A., Hsieh, T. H., Boor, K. J., & Wiedmann, M. (2016).
The evolving role of coliforms as indicators of unhygienic processing conditions in dairy foods. Frontiers in Microbiology, 7(SEP), 1–8. https://
doi.org/10.3389/fmicb.2016.01549 Moreno, M. A., Domínguez, L., Teshager,
T., Herrero, I. A., & Porrero, M. C.
(2000). Antibiotic resistance monitoring: the Spanish programme.
The VAV Network. Red de Vigilancia de Resistencias Antibióticas en Bacterias de Origen Veterinario.
International Journal of Antimicrobial Agents, 14(4), 285–290.
Murray, C. J., Ikuta, K. S., Sharara, F., Swetschinski, L., Robles Aguilar, G., Gray, A., Han, C., Bisignano, C., Rao, P., Wool, E., Johnson, S. C., Browne, A. J., Chipeta, M. G., Fell, F., Hackett, S., Haines-Woodhouse, G., Kashef Hamadani, B. H., Kumaran, E. A. P., McManigal, B., Naghavi, M. (2022).
Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. The Lancet, 399(10325), 629–655. https://doi.org/
10.1016/S0140-6736(21)02724-0 Nhung, N. T., Cuong, N. V., Thwaites, G.,
& Carrique-Mas, J. (2016).
Antimicrobial usage and antimicrobial resistance in animal production in Southeast Asia: A review. Antibiotics, 5(4), 1–24. https://doi.org/10.3390/
antibiotics5040037
Nikaido, H. (2009). Multidrug Resistance in Bacteria. Annual Review Biochemical,
78, 119–146. https://doi.org/10.1146/
annurev.biochem.78.082907.145923.
Multidrug
Nobili, G., La Bella, G., Basanisi, M. G., Damato, A. M., Coppola, R., Migliorelli, R., Rondinone, V., Leekitcharoenphon, P., Bortolaia, V.,
& La Salandra, G. (2022). Occurrence and characterisation of colistin- resistant escherichia coli in raw meat in Southern Italy in 2018–2020.
Microorganisms, 10(9). https://doi.
org/10.3390/microorganisms10091805 OIE. (2007). OIE List of Antimicrobials of
Veterinary Importance.
OIE. (2015). OIE standards, guidelines and resolution on antimicrobial resistance and the use of antimicrobial agents.
World Organisation for Animal Health. www.oie.int
Okeke, I. N., Laxminarayan, R., Bhutta, Z.
A., Duse, A. G., Jenkins, P., Brien, T.
F. O., Pablos-Menddez, A., &
Klugman, K. P. (2005). Antimicrobial resistance in developing countries.
Part I: recent trends and current status.
Lancet Infectious Diseases, 19(5), 481–493.
Pérez-Rodríguez, F., & Mercanoglu Taban, B. (2019). A state-of-art review on multi-drug resistant pathogens in foods of animal origin: risk factors and mitigation strategies. Frontiers in Microbiology, 10(September). https://
doi.org/10.3389/fmicb.2019.02091 Peterson, E., & Kaur, P. (2018). Antibiotic
resistance mechanisms in bacteria:
Relationships between resistance determinants of antibiotic producers, environmental bacteria, and clinical pathogens. Frontiers in Microbiology, 9(NOV), 1–21. https://doi.org/10.33 89/fmicb.2018.02928
Poirel, L., Madec, J.-Y., Lupo, A., Schink, A.-K., Kieffer, N., Nordmann, P., &
Schwarz, S. (2018). Antimicrobial resistance in escherichia coli.
Microbiol Spectrum, 6(4).
https://doi.org/https://doi.org/10.1128 /microbiolspec.ARBA-0026-2017
Ranasinghe, R. A. S. S., Satharasinghe, D.
A., Anwarama, P. S., Parakatawella, P. M. S. D. K., Jayasooriya, L. J. P. A.
P., Ranasinghe, R. M. S. B. K., Rajapakse, R. P. V. J., Huat, J. T. Y., Rukayadi, Y., Nakaguchi, Y., Nishibuchi, M., Radu, S., &
Premarathne, J. M. K. J. K. (2022).
Prevalence and antimicrobial resistance of Escherichia coli in chicken meat and edible poultry organs collected from retail shops and supermarkets of North Western Province in Sri Lanka. Journal of Food Quality, 2022. https://doi.org/
10.1155/2022/8962698
Roth, N., Käsbohrer, A., Mayrhofer, S., Zitz, U., Hofacre, C., & Domig, K. J.
(2019). The application of antibiotics in broiler production and the resulting antibiotic resistance in Escherichia coli: A global overview. Poultry Science, 98(4), 1791–1804. https://
doi.org/10.3382/ps/pey539
Saud, B., Paudel, G., Khichaju, S., Bajracharya, D., Dhungana, G., Awasthi, M. S., & Shrestha, V.
(2019). Multidrug-resistant bacteria from raw meat of buffalo and chicken, Nepal. Veterinary Medicine International, 2019. https://doi.org/
10.1155/2019/7960268
Suady, I. (2019). AMU-AMR Surveillance System in Indonesia on Livestock and Animal Health Sector : approach &
findings Imron Suandy Poultry Population in Indonesia in 2013 - 2017.
Sudarmadi, A. A. M., Prajitno, S., &
Widodo, A. D. W. (2020). Antibiotic resistance in Escherichia coli and Staphylococcus aureus from retail chicken meat in Surabaya, Indonesia.
Biomolecular and Health Science Journal, 3(2), 80. https://doi.org/
10.20473/bhsj.v3i2.22170
Szmolka, A., & Nagy, B. (2013). Multidrug resistant commensal Escherichia coli in animals and its impact for public
health. Frontiers in Microbiology, 4(SEP), 1–13. https://doi.org/10.3389 /fmicb.2013.00258
Van Boeckel, T. P., Brower, C., Gilbert, M., Grenfell, B. T., Levin, S. A., Robinson, T. P., Teillant, A., &
Laxminarayan, R. (2015). Global trends in antimicrobial use in food animals. Proceedings of the National Academy of Sciences of the United States of America, 112(18), 5649–
5654. https://doi.org/10.1073/pnas.15 03141112
Vidovic, N., & Vidovic, S. (2020).
Antimicrobial resistance and food animals: Influence of livestock environment on the emergence and dissemination of antimicrobial resistance. Antibiotics, 9(2). https://
doi.org/10.3390/antibiotics9020052 WHO. (2006a). WHONET Tutorial Data
Analysis 1 for the Surveillance of Antimicrobial Resistance.
WHO. (2006b). WHONET Tutorial Data Analysis 2 for the Surveillance of Antimicrobial Resistance.
WHO. (2019). WHO | WHO list of Critically Important Antimicrobials (CIA) (6th ed.). WHO.
Xu, C., Kong, L., Gao, H., Cheng, X., &
Wang, X. (2022). A review of current bacterial resistance to antibiotics in food animals. Frontiers in Microbiology, 13(May). https://doi.
org/10.3389/fmicb.2022.822689 Yamaji, R., Friedman, C. R., Rubin, J., Suh,
J., Thys, E., Mcdermott, P., Hung-fan, M., & Riley, W. (2018). of Escherichia coli Isolates from Retail Meat and Suspected Cases of Urinary Tract Infections. 3(4), 1–12.
Yusuf, H., Idris, S., & Paul, M. (2018).
Antimicrobial usage surveillance of cattle in indonesia to address antimicrobial resistance. Advances in Social Science, Education and Humanities Research, 98(Icpsuas 2017), 355–359. https://doi.org/10.
2991/icpsuas-17.2018.77
