Prevalence of antibiotic resistance in Escherichia coli strains simultaneously isolated from humans, animals, food, and the environment: a systematic review and meta-analysis
Received 12 January 2019
Accepted for publication 4 March 2019
Published 8 May 2019 Volume 2019:12 Pages 1181—1197
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 4
Editor who approved publication: Professor Suresh Antony
Ali Pormohammad,1 Mohammad Javad Nasiri,2 Taher Azimi2,3
1Student Research Committee, Department of Microbiology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran; 2Department of Microbiology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran; 3Department of Pathobiology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
Background: Antimicrobial resistance is a serious public health problem worldwide. We aimed to investigate the prevalence of antibiotic resistance in Escherichia coli strains simultaneously isolated from humans, animals, food, and the environment.
Methods: Studies on PubMed, Embase, and the Cochrane Library published from January 1, 2000 to January 1, 2018 were searched. The quality of the included studies was assessed by the modified critical appraisal checklist recommended by the Joanna Briggs Institute. All analyses were conducted using Biostat’s Comprehensive Meta-Analysis version 2.0. Depending on the heterogeneity test for each antibiotic, we used a random- or fixed-effect model for pooled prevalence of drug resistance. Studies were eligible if they had investigated and reported resistance in two or more isolation sources (human, animal, food, or environment). To decrease heterogeneity and bias, we excluded studies that had reported E. coli drug resistance isolated from one source only. We included publications that reported drug resistance with minimum inhibitory concentration or disk diffusion method (DDM) as antibiotic-susceptibility tests.
Results: Of the 39 included studies, 20 used the DDM and 19 minimum inhibitory concentration for their antibiotic-susceptibility testing. Colistin had the lowest prevalence, with 0.8% (95% CI 0.2%–3.8%) and amoxicillin the highest, with 70.5% (95% CI 57.5%–81%) in isolated human E. coli strains tested with the DDM. To assess historical changes in antimicrobial drug resistance, subgroup analysis from 2000 to 2018 showed a significant increase in ciprofloxacin resistance.
Conclusion: Monitoring and evaluating antibiotic-sensitivity patterns and preparation of reliable antibiotic strategies may lead to better outcomes for inhibition and control of E. coli infections in different regions of the world.
Keywords: antibiotic, drug resistance, Escherichia coli
Antimicrobial resistance is a serious public health problem worldwide.1–3 Inappropriate use of antibiotics by humans, factories, and farms, poor hygiene and sanitation, and inefficient prevention and control of infections in health-care settings are considered important reasons in the emergence and distribution of antibiotic-resistant bacteria.4,5 Extended-spectrum β-lactamases (ESBLs) are enzymes that confer resistance to most β-lactam antibiotics, including penicillins, cephalosporins, and the monobactam aztreonam. Infections with ESBL-producing organisms have been associated with poor outcomes.6 An important example of antibiotic resistance is multidrug-resistant (MDR) and ESBL-producing Escherichia coli, which can cause life-threatening infections.7 E. coli is the predominant facultative flora in the gastrointestinal tract of humans and animals.8 Some E. coli strains, however, have developed the ability to cause disease in the gastrointestinal, urinary, and central nervous systems.9,10 Prolonged exposure of E. coli to antibiotics contributes to the development of antibiotic resistance.11,12 Thus, antibiotic-resistant bacteria, including E. coli, in animals could serve as important reservoirs for colonization and infection in human beings.8 Research has indicated that drug-resistant E. coli can be transmitted to human beings from the environment through direct or indirect contact (eg, consumption of contaminated food and water).11 Therefore, assessing the prevalence of drug-resistant E. coli in different sources is critical for establishing guidelines in veterinary and human health care. To this end, we conducted a systematic review and meta-analysis to investigate the prevalence of antibiotic resistance in E. coli strains simultaneously isolated from humans, animals, food, and the environment.
Sources of information and search strategies
For papers from January 1, 2000 to January 1, 2018, PubMed, Embase, and the Cochrane Library were searched with the MeSH terms “Escherichia coli”, “drug resistance”, “antimicrobial resistance”, “animal”, “environment”, and “food”. These terms were combined with text searches that included “E. coli”, “antibiotic(s)”, “Gram-negative bacteria”, “Enterobacteriaceae”, “Escherichia”, “antibiotic resistance”, “antibacterial drug”, and “meat”. Contact was made with expert authors by mail to request any details not included in the original publications and unpublished work regarding our previous experiences.13–15 In addition, we searched related reviews and references for relevant studies. We conducted our study according to PRISMA guidelines.16
Two reviewers (TA and AP) independently carried out a review on titles and abstracts and chose those fitting the selection criteria for full-text evaluation. Discrepancies were discussed with a third reviewer (MJM). All original articles in the English language that simultaneously reported the prevalence of antibiotic resistance in E. coli strains isolated from humans, animals, the environment, and food with standard laboratory tests were included. Studies were eligible if they reported the prevalence of drug resistance in E. coli base on laboratory-standard guidelines. We considered all standard guidelines for inclusion in the study: Clinical and Laboratory Standards Institute (CLSI), National Committee for Clinical Laboratory Standards (NCCLS), Committee of the French Society of Microbiology, European Committee on Antimicrobial Susceptibility (EUCAST), British Standard for Antimicrobial Chemotherapy. However, only CLSI/NCCLS and EUCAST guidelines were used in all included studies.
Standard laboratory tests included disk diffusion method (DDM), minimum inhibitory concentration (MIC), andE. test. The aim of this study was to investigate the prevalence of drug-resistant E. coli strains from different sources and compare them with one another. As such, we included publications pursuing a common goal that reported the prevalence of drug resistance in E. coli from different sources. To decrease heterogeneity and bias, we excluded studies that reported E. coli drug resistance isolated from one source only. In this study, MDR strains were defined as resistant to three or more antimicrobial classes.
Data extraction and data collection
Data extracted were name of first author, publication date, sample size, time and location of study, total number of analyzed E. coli strains, and number of drug-resistant E. coli strains. Data were independently collected by two authors (AP and TA).
Articles excluded were those that had not used standard methods (according to guidelines) for detection of drug resistance, had not reported the sample size, or had inappropriate data. Due to limted papers, we excluded studies that reported with Vitek (n=2), plate/replicator (n=1), Isosensitest (n=1), and Trek Diagnostic Systems products (n=1) for prevention of methodological bias (Figure 1). Furthermore, to reduce any potential heterogeneity that might be caused by different laboratory producers and quality of antibiotics, studies that reported the prevalence of antibiotic resistance from different sources (human, animal and environment) separately were excluded.
Figure 1 Flow diagram of literature search and study selection.
Quality assessment of the studies were performed by two reviewers independently, according to the modified critical appraisal checklist recommended by the Joanna Briggs Institute.17 Disagreements were resolved by a consensus-based discussion. The checklist is composed of seven questions (question 4 has two scores) that reviewers answerfor each study. The “Yes” answer for each question receives 1 point. Final scores for each study can range from 0 to 8 (Table S1).
All statistical analyses were carried out with Comprehensive Meta-Analysis version 2.0 (Biostat, Englewood, NJ, USA). Determination of the heterogeneity of studies was carried out using both chi-squared (Cochran’s Q) and I2 tests to assess the appropriateness of pooling data. Depending on the heterogeneity test, we used a random- or fixed-effect model for the pooled prevalence of drug resistance. In cases of high heterogeneity (I2>50%), the random-effect model (Mantel–Haenszel
heterogeneity) was used, and for low heterogeneity (I2<50%), the fixed-effect model was used.18 Begg’s and Egger’s tests were used to assess publication bias. Point estimation of effect size, prevalence, and 95% CIs were measured for each study.
The was a systematic review, so ethical approval was not required.
Selection of studies
A total of 39 studies, selected from a total of 28,489 articles (0.137%, 39 of 28,489) found in the initial search, were included in the final analysis. The location of studies covered east to west and north to south of the world, with the majority of patients from the US, China, and India. Each assessment with more than one isolation source was treated as a separate study. Figure 1 shows the selection process. Characteristics of the selected articles are summarized in Table 1. Of the 39 included studies, 20 used the DDM, 15 agar dilution, and four broth microdilution as the antibiotic-susceptibility test. Some studies used agar dilution and broth dilution combined, referred to as MIC testing for the analysis. In the included studies, 20 studies simultaneously reported prevalence data in humans and animals, 13 in humans, animals, food, and theenvironment, five in animals, food, and the environment and one in human, food, and the environment.
Table 1 Characterization of included studies
Prevalence of antibiotic resistance in E. coli isolates using DDM
Table 2. Prevalence of antibiotic resistance in human, animal, food/environment E. coli isolates with Disk Diffusion method
Table 3. Prevalence of antibiotic resistance in human, animal, food/environment E. coli isolates with MIC method
Figure 2 Prevalence of antibiotic resistance in human, animal, food/environment E. coli isolates with disk diffusion method.
As shown in Table 2 and
Prevalence of antibiotic resistance in E. coli isolates using MIC
As shown in Figure 3, Table 3, and Figures S66–S87 and S89–S90, in E. coli strains isolated from humans, the lowest resistance rate was for imipenem (0.1%, 95% CI 0–0.3%) and the highest for amoxicillin (53.4%, 95% CI 22%–82.3%; Table 3 and
Figure 3 Prevalence of antibiotic resistance in human, animal, food/environment E. coli isolates with MIC method. Abbreviation: MIC, minimum inhibitory concentration.
Prevalence of ciprofloxacin resistance in E. coli strains isolated from human
Ciprofloxacin was the most reported antibiotic used for E. coli in the included studies, so we analyzed ciprofloxacin resistance in more detail. In studies that had used DDM or MIC, the prevalence of ciprofloxacin-resistant E. coli strains isolated from humans was higher than the isolated resistant strains from animals, food, and environmental sources. The prevalence of ciprofloxacin-resistant clinical human isolates among different countries included in these studies is shown in Figure 4. In the studied countries, Spain had the lowest prevalence of ciprofloxacin resistance (0.4%) and Iran the highest (52%) with the DDM. The US had the lowest prevalence of ciprofloxacin resistance (0.01%) and Thailand the highest (43%) on MIC. The prevalence of ciprofloxacin-resistant clinical (human) isolates in WHO regional offices with MIC is shown in Figure 5. Our analyses indicated that among WHO regional offices, America and Southeast Asia (0.008% and 43%, respectively) had the lowest and highest prevalence rates of ciprofloxacin resistance in human isolates using MIC . Overall, results showed that antibiotic resistance in American and European countries is lower than other regions of the world. Subgroup analysis from 2000 to 2018 also indicated a significant increase in ciprofloxacin resistance (Figures 6 and S88).
Figure 4 The global prevalence of ciprofloxacin-resistant clinical (human) isolates with DDM and MIC method.Abbreviations: MIC, minimum inhibitory concentration; DDM, disc diffusion method.
Figure 5 The prevalence of ciprofloxacin-resistant clinical (human) isolates in WHO regional offices with MIC method.
Figure 6 Subgroup analyses of ciprofloxacin-resistant clinical (human) isolates with the MIC method from 2000–2018.Abbreviation: MIC, minimum inhibitory concentration.
The prevalence of antibiotic resistance in E. coli strains simultaneously isolated from human, animal, food, and environment samples from 2000 to 2018 were assessed in this meta-analysis . To our knowledge, the present study is the first comprehensive systematic review on the prevalence of antimicrobial resistance in E. coli from different sources. We hope presenting these data helps to prevent the spread of antimicrobial resistance by giving an appropriate vision of E. coli drug-resistance patterns in different regions of the word. Based on the meta-analysis results in this study, overall MDR prevalence in human, environmental, and animal E. coli isolates was 22%, 31.3%, and 5.7%, respectively, using the DDM. MIC resultsshowed that rates of MDR E. coli isolates in humans and animals were 12.6% and 22.2%, respectively. Comparison of MDR E. coli strains isolated from different sources showed higher prevalence in animal and environmental sources than humans. The prevalence of ESBL-producing E. coli based on MIC in human, animal, and environmental/food isolates was 42.4%, 63.2%, and 28.6%, respectively. The prevalence of ESBL-producing E. coli based on the DDM in human, animal, and environmental/food isolates was 13%, 26.3%, and 25%, respectively. The prevalence of ESBL antibiotic resistance in animal isolates was higher than in human isolates. Furthermore, there was high pooled prevalence of ESBL-producing E. coli using MIC, but this was low using the DDM. The uncontrolled use of antibiotics in domestic animals, as well as dietary supplements, could be one of the main reasons for high antimicrobial resistance in animal isolates in some countries.19 In several countries, such as the Netherlands, nearly 300,000 kg of antibiotics are used every year in the treatment of animals, and this can be considered a possible reason for the emergence of extensive antimicrobial resistance.20 In addition, colonization of healthy adult workers with ESBL-producing E. coli may be related to consumption of food and water contaminated with ESBL-producing bacteria.5 However, Boonyasiri et al reported that ESBL-producing E. coli was found in the food from a market near a factory where stool samples were collected from workers.5 Leading antibiotic-resistance issues may include indiscriminate use of antibiotics, poor hygiene and other preventive measures in veterinary medicine, insufficient staff training, deficiencies in health centers and infection-control programs in hospitals, and lack of proper management steps in animal farms, which may lead to a high prevalence of ESBL-producing E. coli isolates in animal (63%) and human samples (42%).
The prevalence of ciprofloxacin-resistant E. coli strains isolated from human with both the DDM and MIC was higher than counterparts isolated from animals, food, or the environment. There was very low pooled prevalence of cefotaxime and ceftazidime resistance in all sample types when tested using MIC (0.5%–1% and 0.8%–1.3%, respectively), but cefotaxime and ceftazidime resistance were much higher with the DDM (31.2%–58% and 10%–57.4%, respectively). Moreover, the prevalence of amoxicillin resistance in animal samples with the DDM was very high (96%), but amoxicillin resistance was lower with MIC (30%).
The main limitation for the current review is the lack of comprehensive studies in different regions of the world. The limited number of studies reporting drug resistance from different sources was another restriction. Split meta-regression, subgroup, and sensitivity analyses to detect the sources of heterogeneity, publication bias, and heterogeneity must be considered when interpreting the outcomes reported here.
For future direction and supporting the practice of evidence-based medicine, more notifications on E. coli-resistance status isolated from different sources (human, animal, and environment or food specimens) are needed. Such studies could enhance our knowledge of antibiotic-resistance status for E. coli and help us to provide prevention protocols to reduce the occurrence of resistant strains.
Analyses showed prevalence of drug resistance in different sources and documented increase in E. coli drug resistance. Our data demonstrated the evolution of antibiotic resistance and helped to describe drug-resistance prevalence in modern E. coli strains. Moreover, the results showed that the prevalence of ESBL antibiotic resistance and MDR E. coli strains in animal isolates was higher than in human isolates. According to our findings, systematic surveillance of hospital-associated infections, proper monitoring of disposal processes in hospitals, monitoring the use of antibiotics in animals, monitoring and evaluation of antibiotic-sensitivity patterns, and preparation of reliable antibiotic strategies may ease more corrective actions for the inhibition and control of E. coli infections in different parts of the world.
TA conceived and designed the study, AP and TA performed the study, MJN analyzed the data, and AP, MJN and TA wrote the paper and participated in data analysis and manuscript editing..
We greatly appreciate the input from Professor Marc William Allard (Division of Microbiology, Office of Regular Science, Center for Food Safety and Applied Nutrition, US Food and Drug Administration, College Park, MD, USA) for his collaboration with us as an expert and native English speaker for revision of the manuscript and his helpful comments.
The authors report no conflicts of interest in this work.
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Table S1 Characterization of included studies
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