Next Article in Journal
Colonization of Group B Streptococcus in Pregnant Women and Their Neonates from a Sri Lankan Hospital
Previous Article in Journal
Metabolic Response to Tick-Borne Encephalitis Virus Infection and Bacterial Co-Infections
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Pathogens
Volume 11
Issue 4
10.3390/pathogens11040385
pathogens-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Antimicrobial Resistance, Pathogenic, and Molecular Characterization of Escherichia coli from Diarrheal Patients in South Korea

by
Seong Bin Park
1,
Yon Kyoung Park
2,
Min Woo Ha
3,
Kim D. Thompson
4 and
Tae Sung Jung
5,*
1
Coastal Research & Extension Center, Mississippi State University, Pascagoula, MS 39567, USA
2
Microbiology Division, Busan Institute of Health and Environment, Busan 616-100, Korea
3
Jeju Research Institute of Pharmaceutical Sciences, Jeju National University, Jeju 690-756, Korea
4
Moredun Research Institute, Pentlands Science Park, Bush Loan, Penicuik EH26 0PZ, UK
5
Laboratory of Aquatic Animal Diseases, Research Institute of Life Science, College of Veterinary Medicine, Gyeongsang National University, Jinju 660-701, Korea
*
Author to whom correspondence should be addressed.
Pathogens 2022, 11(4), 385; https://doi.org/10.3390/pathogens11040385
Submission received: 22 February 2022 / Revised: 18 March 2022 / Accepted: 21 March 2022 / Published: 23 March 2022
Browse Figures
Review Reports Versions Notes

Abstract

:
Diarrheal diseases due to foodborne Escherichia coli are the leading cause of illness in humans. Here, we performed pathogenic typing, molecular typing, and antimicrobial susceptibility tests on seventy-five isolates of E. coli isolated from stool samples of patients suffering from foodborne diseases in Busan, South Korea. All the isolates were identified as E. coli by both biochemical analysis (API 20E system) and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS). The bacteria displayed entero-pathogenic E. coli (EPEC) (47.0%), entero-aggregative E. coli (EAEC) (33.3%), entero-toxigenic E. coli (ETEC) (6.6%), ETEC and EPEC (6.6%), EPEC and EAEC (4%), and ETEC and EAEC (2.7%) characteristics. The E. coli isolates were highly resistant to nalidixic acid (44.0%), tetracycline (41.3%), ampicillin (40%), ticarcillin (38.7%), and trimethoprim/sulfamethoxazole (34.7%); however, they were highly susceptible to imipenem (98.6%), cefotetan (98.6%), cefepime (94.6%), and chloramphenicol (94.6%). Although 52 strains (69.3%) showed resistance against at least 1 of the 16 antibiotics tested, 23 strains (30.7%) were susceptible to all the antibiotics. Nine different serotypes (O166, O8, O20, O25, O119, O159, O28ac, O127a, and O18), five genotypes (I to V, random-amplified polymorphic DNA), and four phenotypes (A to D, MALDI-TOF MS) were identified, showing the high level of heterogeneity between the E. coli isolates recovered from diarrheal patients in South Korea.

1. Introduction

Foodborne illnesses or foodborne diarrheal diseases affect the global population [1,2]. In the US alone, over 211 million cases of diarrheal disease are reported annually, resulting in more than 900,000 hospitalizations and 6000 deaths [2]. Foodborne diseases are categorized into foodborne infections or foodborne poisoning, and these are subdivided further according to the etiological agent involved, such as viruses, bacteria, fungi, parasites, or chemicals [3]. Escherichia coli is one of the most common bacterial agents of foodborne diarrheal disease [4]. E. coli is a Gram-negative, facultative anaerobic and rod-shaped bacterium, and is a common commensal bacterium in the large intestine of mammals [5]. However, some E. coli strains can cause serious food poisoning or infection by the ingestion of contaminated food [4]. Well-known strains of pathogenic E. coli include entero-toxigenic E. coli (ETEC), entero-invasive E. coli (EIEC), entero-pathogenic E. coli (EPEC), entero-aggregative E. coli (EAEC), Shiga toxin-producing E. coli (STEC), and entero-hemorrhagic E. coli (EHEC) based on the presence of virulence genes [6,7]. In South Korea during the period 2010–2018, pathogenic E. coli were responsible for the highest number of foodborne disease cases (1784–2754 cases) recorded, followed by Norovirus (739-1994 cases), non-typhoidal Salmonella (147–3516 cases), Clostridium perfringens (171–1689 cases) Campylobacter (380–831 cases), and Staphylococcus aureus (4–372 cases) [1].
To diagnose E. coli-related diseases, stool specimens are collected from patients displaying typical symptoms of E. coli infection, such as weakness, fever, and watery or bloody diarrhea, and cultured on selective agar or nutrient agar. Conventional biochemical tests (API or Vitek systems) and/or matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) are then performed on isolated bacteria for their identification [8,9,10,11]. It is also essential to establish the correct antibiotic treatment for the patient, especially because of the emergence of multidrug resistant (MDR) E. coli [12]. MDR is defined as resistance acquired against at least one antimicrobial agent in three or more antibiotic categories. MDR E. coli are now recognized as one of the biggest challenges in public health worldwide [13].
Current molecular typing methods enable the differentiation between isolates of the same genus and species based on their phenotypic and genotypic characteristics [14]. Two representative molecular typing methods are used to determine the epidemiology of bacterial infections. One includes phenotyping-based methods such as O-serotyping, bacteriophage typing, and MALDI-TOF MS; while the other includes genotype-based methods such as restriction fragment length polymorphism (RFLP), amplified fragment length polymorphism (AFLP), random amplified polymorphic DNA (RAPD), pulse field gel electrophoresis (PFGE), and multi-locus sequence typing (MLST) [9,10,15,16,17,18,19,20,21].
In the present study, pathotyping (identification of pathogenic genes), phenotyping (O-serotyping and spectral analysis using MALDI-TOF MS), genotyping (clustal analysis using RAPDs), and antimicrobial susceptibility tests were conducted to investigate the characteristics of E. coli isolated from stool samples from foodborne diarrheal patients in Busan, South Korea.

2. Results

2.1. Identification and Pathogenic Properties of E. coli

A total of seventy-five bacterial isolates, obtained from diarrheal stool samples from foodborne diarrheal patients, were identified as E coli using API 20 E typing and MALDI-TOF MS using both bacterial colonies and extracted bacteria (log scores, ≥2.3; identification of species level). Thirty-six of the isolates (48%) were not assigned to any serotypes, while thirty-nine of the isolates (52%) belonged to only one E. coli O-serotype, i.e., O166 (8.0%, n = 6), O25 (5.3%, n = 4), O20 (5.3%, n = 4), O8 (5.3%, n = 4), O119 (4.0%, n = 3), O159 (4.0%, n = 3), O28ac (4.0%, n = 3), O127a (2.7%, n = 2), and O18 (2.7%, n = 2) (Table 1, Supplementary Table S4).
St, eaeA, bfpA, and aggR genes were amplified in all seventy-five E. coli isolates, while lt, stx1, stx2, and ial genes were not amplified (Table 1, Supplementary Tables S2 and S4). All the isolates encoded at least one pathogenic gene, such as eaeA (35 isolates; EPEC pathotype), aggR (30 isolates; EAEC pathotype), st (12 isolates; ETEC pathotype), and bfpA (11 isolates; EPEC pathotype), but no genes for E. coli pathotypes EIEC, STEC, and EHEC were amplified. EPEC was the most prevalent pathotype (35 isolates; 47%), followed by pathotype EAEC (25 isolates; 33.3%), pathotype ETEC (5 isolates; 6.6%), pathotype ETEC and EPEC (5 isolates; 6.6%), pathotype EPEC and EAEC (3 isolates; 4%), and pathotype ETEC and EAEC (2 isolates; 2.7%). Of these, twelve isolates contained more than one virulence gene, while one isolate contained three virulence genes: st, eaeA, and bfpA (Table 1).

2.2. Antimicrobial Susceptibility

Antimicrobial susceptibility was examined in all seventy-five E.coli isolates based on the standard CLSI protocol (Supplementary Table S3). Resistance was observed in all sixteen antibiotics examined (Table 2). The highest prevalence of resistance was to nalidixic acid with 44.0% of the isolates showing resistance (n = 33) followed by tetracycline at 41.3% (n = 31), ampicillin at 40.0% (n = 30), ticarcillin at 38.7% (n = 29), and trimethoprim/sulfamethoxazole at 34.7% (n = 26). Conversely, E. coli isolates were found to be most susceptible to imipenem at 98.6% (n = 74) and cefotetan at 98.6% (n = 74), followed by cefepime at 94.6% (n = 71), chloramphenicol at 94.6% (n = 71), cefazolin at 92% (n = 69), cefotaxime at 92% (n = 69), and amikacin at 92% (n = 69).
Twenty-three isolates (30.7%) were susceptible to all the antibiotics, while fifty-two isolates (69.3%) showed resistance against at least one of the sixteen antibiotics tested (Table 3). Thirty-four isolates (45.3%) showed MDR, with resistance to at least one in three or more of the antibiotic categories examined, of which two isolates were resistant to eleven antibiotics (Table 3).

2.3. Molecular Typing Using RAPD and MALDI-TOF MS

RAPD analysis was performed on the seventy-five isolates of E. coli using RAPD primer 5 of the Ready-To-Go-RAPD Analysis kit. This primer was chosen from the six primers provided in the kit because it generates clear and diverse amplification patterns. The same amplification patterns were observed in three independent experiments. RAPD analysis with primer 5 resulted in nine to nineteen clear bands, except for two isolates, which were not amplified (Figure 1). Five major clusters (I–V) were generated by primer 5, with a 76% similarity value between the clusters. Cluster I contained nine isolates (12%), and more than half of the isolates (n = 45) belonged to cluster II (60%, p < 0.05). Cluster III, IV, and V contained ten (13.3%), six (8%), and three (4%) isolates, respectively.
A dendrogram was generated based on the protein spectral fingerprints of the seventy-five E.coli isolates (Figure 2). The MALDI-TOF MS cluster analysis was performed using the integrated pattern-matching algorithm software exhibited, which divided the E. coli isolates into four major clusters (A to D) at a distance level of 500. Most isolates (68.0%, n = 51, p < 0.05) were classified into cluster D. Clusters A and B contained twelve (16.0%) and seven (9.3%) isolates, respectively. Five isolates were classified into cluster C (6.6%), which showed a close relative distance to cluster D at a distance level of 600.
The correlation analysis (Table 4) indicated that cluster D (68.0%, n = 51) from the RAPD analysis has a significant association with cluster III (60%, n = 45) from MALDI-TOF MS, since both clusters were the most dominant cluster of each molecular typing method (54.6%, n = 41).

3. Discussion

Characterization of pathogenic E. coli is performed using a variety of methods, including serotyping, genotyping, pathotyping, and phenotyping with various samples from human stools, dairy products, and meat from different countries [10,15,17,18,20,22,23]. Of these, the most well-known method for differentiating E. coli is serotyping based on 186 O antigens and 53 H antigens [6]. In general, an EHEC strain, O157:H7, is regarded as the major agent responsible for foodborne outbreaks since its shiga toxin (Stx) is essential for hemorrhagic colitis and hemolytic uremic syndrome in humans [24]. However, numerous studies have indicated that another fourteen non-O157 serotypes (O15, O26, O45, O55, O91, O103, O104, O111, O113, O118, O121, O128, O145, and O153) are becoming of public concern [24,25,26,27,28]. In this study, nine O-serotypes were identified in the E. coli collection, including O166, O8, O20, O25, O119, O159, O28ac, O127a, and O18, while no virulent STEC/EHEC O-serotypes were found. Interestingly, 48% of the isolates did not react with the 8 polyvalent and 43 monovalent serotyping sera that were used. Similarly, of the 101 E. coli isolated from chickens in South Korea in another study, only twenty-eight isolates (27.7%) could be serotyped, i.e., O1 (2%), O18 (3%), O20 (1%), O78 (19.7%), and O115 (2%) [23]. Similarly, of the 226 E. coli isolated from chickens in the Philippines, only five isolates (2.1%) could be O-serotyped [29]. In concurrence with these studies, our results showed the phenotyping of E. coli isolates, based on O-serotypes, to have a low discriminatory power because of the low number of isolates that could be assigned to a specific serotype. Conventional O-serotyping still plays a crucial role in confirming the pathogenic O-serotype in foodborne E. coli outbreaks, such as O157:H7 and other virulent O-serotypes.
Many research groups have focused on developing multiplex PCRs that are able to detect important pathogenic genes simultaneously because O-serotyping methods do not always indicate the exact pathogenicity of E. coli [10,15,16,17,19,21]. Based on these multiplex PCRs, some pathotypes have been found to be dominant in certain foods, hosts, and geographical regions. For example, of the 64 strains (22.9%) identified as diarrheagenic E. coli from a collection of 240 samples obtained from Tanzania, the most predominant pathotype was EAEC (14.6%), followed by EPEC (4.6%) and ETEC (3.6%), while EHEC and EIEC were not detected [30]. Similarly, in our study, EPEC (47.0%) was found to be the most abundant pathotype, followed by EAEC (33.3%) and ETEC (6.6%), while STEC, EHEC and EIEC were not found. Moreover, some strains were found to have genes encoding both pathogenicity islands, such as ETEC and EAEC (6.6%), ETEC and EPEC (4%), or EPEC and EAEC (2.7%), similar to a previous study that also demonstrated that several strains possessed two pathotypes [30]. It is reported that ETEC produces a heat-labile toxin (LT), with a sequence, antigenicity, and function similar to the cholera toxin, which is responsible for food poisoning in humans [31]. Some EPEC strains can colonize the small intestine and adhere to the mucosa causing effacement of microvilli, since a plasmid-encoding protein EPEC adherence factor (EAF) plays a key role in the pathogenesis of EPEC [32]. The distinctive characteristics of EAEC are the attachment of the E. coli to epithelial cells and the aggregation of the cells without penetration and replication [22,33]. In this study, our multiplex PCR showed that all seventy-five E. coli isolates possessed at least one pathogenic gene (EPEC, EAEC, and/or ETEC), which might be responsible for the disease seen in the diarrheal patients in South Korea. Moreover, all the isolates were divided into six groups (EPEC, EAEC, ETEC, ETEC and EAEC, ETEC and EPEC, and EPEC and EAEC) based on their pathogenic genes, which were further compared with two molecular typing analysis, RAPD (genotyping) and MALDI-TOF MS (phenotyping), to understand the correlation among the isolates.
To trace the source of foodborne illness and/or linking potential sources to the infection, studies using several molecular typing methods including RAPD, RFLP, PFGE, bacteriophage typing, and MALDI-TOF MS [9,15,16,17,18] have been used to classify the E. coli isolates involved. In this study, we conducted both a phenotyping analysis using mass spectrum profiles from MALDI-TOF MS and a genotyping analysis using RAPD fingerprinting. One study suggested that RAPD typing has great potential to identify the transmission of a particular bacterial species between different hosts and sources [34]. From the RAPD analysis, we detected genetic polymorphism among the 75 E. coli isolates, which were classified into five groups using primer 5 (I to V, Figure 1). Similarly, in a previous study analyzing 187 isolated from patients in an Iranian city from 2010 to 2016 using RAPD analysis, the E. coli isolates were associated with 32 different clusters, highlighting the amount of genetic diversity between the E. coli isolates from these patients [35]. On the other hand, several studies have indicated that MALDI-TOF MS analysis is able to discriminate between bacteria not only from various hosts and geographical origins, but also from the same host and region [36,37,38]. In this study, a dendrogram generated from MALDI-TOF MS indicated that E. coli strains showed heterogeneity in the phenotypes since they were divided into four clusters at the distance level of 500 (A to D, Figure 2). In a previous study, the dendrogram generated from MALDI-TOF MS failed to show any correlation between pathotypes, serotypes, and multilocus sequence types among the 136 E.coli strains examined [9]. Interestingly, they found that O157:H7 EHEC strains were relatively homogenous; however, the other pathotypes such as UPEC, EAEC, EIEC, DAEC, ETEC, and EPEC showed a variety of spectral patterns [9]. The current study demonstrated that pathotyping using pathogenic genes did not show any distinct distribution within the genotyping of RAPD clustering or within the phenotyping of MALDI-TOF MS clustering [39]. We concluded that the E. coli isolates recovered from human patients in the South Korea city of Busan were very heterogeneous with respect to pathotypes, genotypes, and phenotypes, based on the results of the O-serotyping, virulent gene amplification, and RAPD and MALDI-TOF MS analysis.
The present E. coli isolates were highly resistant to nalidixic acid, tetracycline, ampicillin, ticarcillin, and trimethoprim/sulfamethoxazole as well as highly susceptible to imipenem, cefotetan, cefepime, and chloramphenicol. They showed resistance to all sixteen antibiotics tested in this study. Drug-resistant E. coli has attracted great concern in relation to public health worldwide due to the abuse of antibiotics [40,41]. A previous study in South Africa demonstrated a high level of antibiotic resistance among E. coli isolates recovered from patients having foodborne diseases: cephalothin, 95%; streptomycin, 76%; ampicillin, 53%; amoxicillin-clavulanic acid, 5%; cefotaxime and kanamycin, 45%; sulfonamides and sulfa-trimethoprim, 21%; colistin, 16%; tetracycline, 13%; and ceftazidime and gentamicin, 8%. None of the isolates were resistant to chloramphenicol, ciprofloxacin, enrofloxacin, or nalidixic acid [42]. In a study from India, the resistance rates for E. coli isolates recovered from children were reported to be above 90% for cefotaxime, ceftazidime, cefepime, sulfamethoxazole, and co-trimoxazole. The isolates were highly susceptible for only two antibiotics: colistin and tigecycline [43]. However, in another study from Michigan in the United States, E. coli isolates (n = 353) from hospitalized patients during 2010–2014 were shown to have MDR to ampicillin (7.4%), trimethoprim/sulfamethoxazole (SXT) (4.0%), and ciprofloxacin (0.3%) [44], which are lower than the MDR levels mentioned above from South Africa [42], India [43], and Korea (in the present study). Taken together with the previous studies, our results suggest that E. coli isolated from patients from different countries may have different antibiotic susceptibilities, and therefore different strategies may be required to prevent and control the spread of MDR in foodborne pathogenic E. coli.

4. Materials and Methods

4.1. E. coli Isolates

Stool samples were collected from patients suffering from foodborne diarrheal diseases in Busan, South Korea, between 2014 and 2016, from which seventy-five isolates of E. coli were obtained. The stool samples were cultured on MacConkey (MAC; MERCK, Darmstadt, Germany) agar at 35 °C overnight, from which lactose-fermenting (pink) colonies were selected and cultured on triple sugar iron (TSI, Oxoid, Basingstoke, UK) slopes and tryptone soya agar (TSA, Oxoid, Basingstoke, UK). After Gram staining, the Gram-negative colonies showing gas production on TSI were cultured on TSA for identification using the API 20E typing system (BioMerieux, Durham, NC, USA).

4.2. O-Serotyping

O-serotypes were determined based on plate agglutination tests with O-antisera (DENKA SEIKEN, Tokyo, Japan). Briefly, bacterial colonies were suspended in 1 mL saline and incubated at 100 °C for 1 h followed by centrifugation at 900× g for 20 min. The pellet was resuspended in 0.5 mL saline and used as antigen for agglutination test. A total of 10 μL of antigenic suspension was mixed with the same volume of antisera or normal saline (as control for autoagglutination) on the slide glass. Agglutination was observed by tilting the glass slide backwards and forwards. If a specimen showed positive agglutination with the polyvalent serum, the O-serotype was then confirmed using the monovalent serum (shown in Supplementary Table S1) by observing agglutination with the bacteria within 1 min.

4.3. Characterization of Pathogenic Properties of E. coli by PCR

Genes associated with pathogenic properties of E. coli were determined by multiplex PCRs with minor modification [30,45,46,47,48,49]. The isolates were cultured in TSB at 35 °C for 24 h, and their DNA was extracted by boiling 50 μL of the culture with 450 μL of sterile distilled water for 20 min. Samples were then centrifuged at 14,000× g for 10 min, and supernatants were stored at −20 °C until used. Primer sets to amplify genes associated with pathogenic strains were used for multiplex PCR (Supplementary Table S2). Briefly, the mixture for multiplex PCRs included 2.5 units of i-StarMAXTM DNA polymerase (INTRON, Seongnam-Si, Korea), 10 mM dNTP (2.5 mM each), 1 × PCR buffer, 2 μL of primer set (10 pmol), and 2 μL of bacterial DNA. The final volume was adjusted to 20 μL with distilled water. PCR was performed using T-100 thermal controller (Bio-Rad, Hercules, CA, USA) with the condition of 94 °C for 5 min, followed by 30 cycles of 94 °C for 1 min, 55 °C for 1 min, and 72 °C for 1 min, followed by a final extension at 72 °C for 5 min. The amplified PCR product was visualized on 1.5% TAE agarose gel containing 0.5 μg/mL ethidium bromide.

4.4. Antimicrobial Susceptibility Test

The antibiotic resistance of the isolates was determined using the disk diffusion method based on the standard procedure outlined by the Clinical and Laboratory Standards Institute (CLSI) [50,51]. E. coli isolates were spread on TSA and cultured at 35 °C for 24 h. A bacterial colony was suspended in 3 mL of Mueller–Hinton broth (MHB, Oxoid, Basingstoke, UK), and the concentration of the suspension was adjusted to 0.5 McFarland (BioMerieux, Durham, NC, USA). The bacterial suspension was evenly spread on Mueller–Hinton agar (Oxoid, Basingstoke, UK), and each antimicrobial disk (BD, Franklin Lakes, NJ, USA) was placed on the agar. The antimicrobial susceptibility of the E. coli isolates was assessed for 16 antimicrobial agents (BD, USA), including ampicillin (10 μg), amikacin (30 μg), chloramphenicol (30 μg), cephalothin (30 μg), ciprofloxacin (5 μg), cefotetan (30 μg), cefotaxime (30 μg), cefazolin (30 μg), cefepime (30 μg), gentamicin (10 μg), imipenem (10 μg), nalidixic acid (10 U), ampicillin/sulbactam (10 μg /10 μg), trimethoprim/sulfamethoxazole (1.25 μg /23.75 μg), tetracycline (30 μg), and ticarcillin (30 μg). After culturing the agar plates at 35 °C for 24 h, the diameter of the clear zones was determined using a digital caliper (Fisher Scientific, Hampton, NH, USA) to measure the growth inhibition of the isolates against the antimicrobial agents. The susceptibility of the isolates was determined according to CLSI (Supplementary Table S3). E. coli ATCC 25922 and S. aureus ATCC 29213 were used as quality control strains (data not shown).

4.5. Sample Preparation and Measurement of MALDI-TOF MS

Fresh bacterial colonies were applied directly onto the MSP 96 target polished steel plate (Bruker Daltonik, Bremen, Germany) and left to dry at room temperature. Thereafter, 1 μL of HCCA matrix solution (saturated solution of α-cyano-4-hydroxy-cinnamic acid in 50% acetonitrile and 2.5% trifluoroacetic acid) was added onto the samples and allowed to dry. For the standard extraction method, the bacterial colonies were suspended in 300 μL of distilled water and 900 μL absolute ethanol was added. After vortexing, the sample was centrifuged at 16,000× g for 2 min and the supernatant was discarded. The pellet was resuspended in 20 μL of 70% formic acid and mixed thoroughly by pipetting, followed by the addition of the same volume of acetonitrile. After centrifugation at 16,000× g for 2 min, 1 μL of supernatant was targeted onto the MSP 96 target polished steel plate and dried at room temperature before the addition of 1 μL of HCCA matrix solution to crystallize the sample.
The mass spectra were acquired using Microflex LT mass spectrometry (Bruker Daltonik, Bremen, Germany) under the control of Flexcontrol software (Version 3.0; Bruker Daltonik). Positive ions were extruded with an accelerating voltage of 20 kV, and the spectra were analyzed within a mass/charge (m/z) ratio of 2000 to 20,000 in the positive linear mode. Each spectrum was calibrated with a bacterial test standard (BTS 255343, Bruker Daltonik). For bacterial identification, the generated spectra were automatically matched with the reference library and scored using the integrated pattern-matching algorithm software (MALDI Biotyper RTC, Bruker Daltonik). A logarithmic score of 0 to 3 was assigned by MALDI Biotyper 3.0 according to spectra peak matching patterns. Scores of 0 to 1.699 indicated no reliable identification; 1.700 to 1.999 indicated a probable genus identification; 2.000 to 2.299 indicated a secure genus identification and probable species identification; and scores of 2.300 to 3.000 indicated highly probable species identification. In addition, MSP dendrograms were generated using MALDI Biotyper 3.0, and the distance level in the dendrograms was set at a maximal value of 1000 following the manufacturer’s recommendation.

4.6. Random Amplified Polymorphic DNA (RAPD) Analysis

Genomic DNA was extracted from E. coli isolates using the Accuprep genomic DNA extraction kit (Bioneer, Daejeon, Korea) following the manufacturer’s protocol. Random amplified polymorphic DNA (RAPD) analysis was performed with Ready-To-Go RAPD Analysis Beads (GE Healthcare, Piscataway, NJ, USA) following the manufacturer’s instructions. Briefly, each 25 μL reaction volume contained 10 ng of bacterial DNA and 25 pmol of a single RAPD primer. RAPD analysis primer 5 (5′-d[AACGCGCAAC]-3′) was applied to generate unique banding patterns. Amplification was performed using a PT-100 thermal cycler (MJ research, Watertown, MA, USA), and the protocol was 1 cycle at 95 °C for 5 min followed by 45 cycles of 95 °C for 1 min, 36 °C for 1 min, and 72 °C for 2 min. Visualization of PCR products was carried out as described above. The results were analyzed using Bionumerics software (Applied Maths, Austin, TX, USA) to generate a cluster analysis.

4.7. Statistical Analysis

Statistical analysis was performed using Graphpad Prism version 9.2.0. (GraphPad, San Diego, CA, USA). Significant differences were determined by the Chi-squared test or one-way ANOVA. The difference was considered statistically significant at p < 0.05.

5. Conclusions

The present study aimed to investigate the characteristics of E. coli isolated from stool samples of diarrheal patients in Busan, South Korea. The E. coli isolates demonstrated nine serotypes (O166, O8, O20, O25, O119, O159, O28ac, O127a, and O18), six pathotypes (EPEC, EAEC, ETEC, ETEC and EAEC, ETEC and EPEC, and EPEC and EAEC), five genotypes (I to V, RAPD), and four phenotypes (A to D, MALDI-TOF MS) with high antimicrobial resistances to sixteen antibiotics. This study helps to highlight the prevalence, phylogroups, and antimicrobial susceptibility of foodborne pathogenic E. coli isolated from South Korea.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/pathogens11040385/s1, Table S1: O antisera used for the determination of E. coli serotypes.; Table S2: Primer pairs used for the determination of the pathotypes of E. coli.; Table S3: Determination of susceptible, intermediate, and resistant bacteria to antimicrobial agents based on the standard set by CLSI.; Table S4: Pathotyping by virulence gene, O-serotyping, and molecular typing by RAPD and MALDI TOF of E. coli isolates.

Author Contributions

Conceptualization, M.W.H., Y.K.P. and S.B.P.; methodology, S.B.P. and Y.K.P.; software, S.B.P.; validation, T.S.J.; formal analysis, K.D.T.; investigation, Y.K.P.; resources, Y.K.P.; data curation, M.W.H. and Y.K.P.; writing—original draft preparation, Y.K.P. and S.B.P.; writing—review and editing, T.S.J. and K.D.T.; visualization, S.B.P.; supervision, T.S.J. and S.B.P.; project administration, T.S.J.; funding acquisition, T.S.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Korea Research Foundation, grant number NRF-2021R1A2B5B02002220.

Institutional Review Board Statement

The Ethical Committee of the Gyeongsang National University confirmed that ethical review and approval were not needed since the study deals with a non-invasive diagnostic tool used according to standard indications in a specific subset of patients, and the clinical information of patients was collected anonymously (patient consent was not obtained; names, addresses, or codes identifying an individual were not obtained).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Lee, H.; Yoon, Y. Etiological agents implicated in foodborne illness world wide. Food Sci. Anim. Resour. 2021, 41, 1. [Google Scholar] [CrossRef] [PubMed]
  2. Scallan, E.; Hoekstra, R.M.; Angulo, F.J.; Tauxe, R.V.; Widdowson, M.-A.; Roy, S.L.; Jones, J.L.; Griffin, P.M. Foodborne illness acquired in the United States—Major pathogens. Emerg. Infect. Dis. 2011, 17, 7. [Google Scholar] [CrossRef] [PubMed]
  3. Bari, M.L.; Yeasmin, S. Foodborne diseases and responsible agents. In Food Safety and Preservation; Elsevier: Cambridge, MA, USA, 2018; pp. 195–229. [Google Scholar]
  4. Wang, J.; Song, F.; Walia, K.; Farber, J.; Dara, R. Using convolutional neural networks to extract keywords and keyphrases: A case study for foodborne illnesses. In Proceedings of the 2019 18th IEEE International Conference on Machine Learning and Applications (ICMLA), Boca Raton, FL, USA, 16–19 December 2019; pp. 1398–1403. [Google Scholar]
  5. Alizade, H.; Teshnizi, S.H.; Azad, M.; Shojae, S.; Gouklani, H.; Davoodian, P.; Ghanbarpour, R. An overview of diarrheagenic Escherichia coli in Iran: A systematic review and meta-analysis. J. Res. Med. Sci. Off. J. Isfahan Univ. Med. Sci. 2019, 24, 23. [Google Scholar]
  6. Fratamico, P.M.; DebRoy, C.; Liu, Y.; Needleman, D.S.; Baranzoni, G.M.; Feng, P. Advances in molecular serotyping and subtyping of Escherichia coli. Front. Microbiol. 2016, 7, 644. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Valilis, E.; Ramsey, A.; Sidiq, S.; DuPont, H.L. Non-O157 Shiga toxin-producing Escherichia coli—A poorly appreciated enteric pathogen: Systematic review. Int. J. Infect. Dis. 2018, 76, 82–87. [Google Scholar] [CrossRef] [Green Version]
  8. Amaretti, A.; Righini, L.; Candeliere, F.; Musmeci, E.; Bonvicini, F.; Gentilomi, G.A.; Rossi, M.; Raimondi, S. Antibiotic resistance, virulence factors, phenotyping, and genotyping of non-Escherichia coli Enterobacterales from the gut microbiota of healthy subjects. Int. J. Mol. Sci. 2020, 21, 1847. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  9. Clark, C.G.; Kruczkiewicz, P.; Guan, C.; McCorrister, S.J.; Chong, P.; Wylie, J.; van Caeseele, P.; Tabor, H.A.; Snarr, P.; Gilmour, M.W. Evaluation of MALDI-TOF mass spectroscopy methods for determination of Escherichia coli pathotypes. J. Microbiol. Methods 2013, 94, 180–191. [Google Scholar] [CrossRef]
  10. El-Badawy, M.F.; Tawakol, W.M.; Maghrabi, I.A.; Mansy, M.S.; Shohayeb, M.M.; Ashour, M.S. Iodometric and molecular detection of ESBL production among clinical isolates of E. coli fingerprinted by ERIC-PCR: The first Egyptian report declares the emergence of E. coli O25b-ST131clone harboring bla GES. Microb. Drug Resist. 2017, 23, 703–717. [Google Scholar] [CrossRef]
  11. Książczyk, M.; Kuczkowski, M.; Dudek, B.; Korzekwa, K.; Tobiasz, A.; Korzeniowska-Kowal, A.; Paluch, E.; Wieliczko, A.; Bugla-Płoskońska, G. Application of routine diagnostic procedure, VITEK 2 compact, MALDI-TOF MS, and PCR assays in identification procedure of bacterial strain with ambiguous phenotype. Curr. Microbiol. 2016, 72, 570–582. [Google Scholar] [CrossRef]
  12. Pormohammad, A.; Nasiri, M.J.; Azimi, T. Prevalence of antibiotic resistance in Escherichia coli strains simultaneously isolated from humans, animals, food, and the environment: A systematic review and meta-analysis. Infect. Drug Resist. 2019, 12, 1181. [Google Scholar] [CrossRef] [Green Version]
  13. Magiorakos, A.; Srinivasan, A.; Carey, R.; Carmeli, Y.; Falagas, M.; Giske, C.; Harbarth, S.; Hinndler, J. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: An international expert proposal for interim standard definitions for acquired resistance. Clin. Microbiol. Infect. 2020, 2012, 268–281. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Farber, J. An introduction to the hows and whys of molecular typing. J. Food Prot. 1996, 59, 1091–1101. [Google Scholar] [CrossRef] [PubMed]
  15. Darkazanli, M.; Kiseleva, I.; Darkazanli, K. Genetic Diversity of E. coli O157: H7 Isolated from Some Leafy Greens, Irrigated by Aleppo River, Using Random Amplified Polymorphic DNA (RAPD) Marker. Russ. Agric. Sci. 2018, 44, 146–152. [Google Scholar]
  16. de Lagarde, M.; Vanier, G.; Desmarais, G.; Kohan-Ghadr, H.R.; Arsenault, J.; Fairbrother, J. A new multidrug-resistant enterotoxigenic Escherichia coli pulsed-field gel electrophoresis cluster associated with enrofloxacin non-susceptibility in diseased pigs. J. Appl. Microbiol. 2021, 130, 707–721. [Google Scholar] [CrossRef] [PubMed]
  17. Jazeela, K.; Chakraborty, G.; Shetty, S.S.; Rohit, A.; Karunasagar, I.; Vijaya Kumar, D. Comparison of mismatch amplification mutation assay PCR and PCR-restriction fragment length polymorphism for detection of major mutations in gyrA and parC of Escherichia coli associated with fluoroquinolone resistance. Microb. Drug Resist. 2019, 25, 23–31. [Google Scholar] [CrossRef] [PubMed]
  18. Kazibwe, G.; Katami, P.; Alinaitwe, R.; Alafi, S.; Nanteza, A.; Nakavuma, J.L. Bacteriophage activity against and characterisation of avian pathogenic Escherichia coli isolated from colibacillosis cases in Uganda. PLoS ONE 2020, 15, e0239107. [Google Scholar] [CrossRef] [PubMed]
  19. Kotłowski, R.; Grecka, K.; Kot, B.; Szweda, P. New approaches for Escherichia coli Genotyping. Pathogens 2020, 9, 73. [Google Scholar] [CrossRef] [Green Version]
  20. Liu, B.; Furevi, A.; Perepelov, A.V.; Guo, X.; Cao, H.; Wang, Q.; Reeves, P.R.; Knirel, Y.A.; Wang, L.; Widmalm, G. Structure and genetics of Escherichia coli O antigens. FEMS Microbiol. Rev. 2020, 44, 655–683. [Google Scholar] [CrossRef] [Green Version]
  21. Nakamura, A.; Takahashi, H.; Arai, M.; Tsuchiya, T.; Wada, S.; Fujimoto, Y.; Shimabara, Y.; Kuda, T.; Kimura, B. Molecular subtyping for source tracking of Escherichia coli using core genome multilocus sequence typing at a food manufacturing plant. PLoS ONE 2021, 16, e0261352. [Google Scholar] [CrossRef]
  22. Govindarajan, D.K.; Viswalingam, N.; Meganathan, Y.; Kandaswamy, K. Adherence patterns of Escherichia coli in the intestine and its role in pathogenesis. Med. Microecol. 2020, 5, 100025. [Google Scholar] [CrossRef]
  23. Jeong, Y.-W.; Kim, T.-E.; Kim, J.-H.; Kwon, H.-J. Pathotyping avian pathogenic Escherichia coli strains in Korea. J. Vet. Sci. 2012, 13, 145–152. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Ağbaş, A.; Göknar, N.; Akıncı, N.; Yıldırım, Z.Y.; Taşdemir, M.; Benzer, M.; Gökçe, İ.; Candan, C.; Küçük, N.; Uzuner, S. Outbreak of Shiga toxin-producing Escherichia coli-associated hemolytic uremic syndrome in Istanbul in 2015: Outcome and experience with eculizumab. Pediatric. Nephrol. 2018, 33, 2371–2381. [Google Scholar] [CrossRef] [PubMed]
  25. DebRoy, C.; Roberts, E.; Valadez, A.M.; Dudley, E.G.; Cutter, C.N. Detection of Shiga toxin–producing Escherichia coli O26, O45, O103, O111, O113, O121, O145, and O157 serogroups by multiplex polymerase chain reaction of the wzx gene of the O-antigen gene cluster. Foodborne Pathog. Dis. 2011, 8, 651–652. [Google Scholar] [CrossRef]
  26. Fratamico, P.M.; Bagi, L.K.; Cray, W.C., Jr.; Narang, N.; Yan, X.; Medina, M.; Liu, Y. Detection by multiplex real-time polymerase chain reaction assays and isolation of Shiga toxin–producing Escherichia coli serogroups O26, O45, O103, O111, O121, and O145 in ground beef. Foodborne Pathog. Dis. 2011, 8, 601–607. [Google Scholar] [CrossRef] [Green Version]
  27. Perelle, S.; Dilasser, F.; Grout, J.; Fach, P. Screening food raw materials for the presence of the world’s most frequent clinical cases of Shiga toxin-encoding Escherichia coli O26, O103, O111, O145 and O157. Int. J. Food Microbiol. 2007, 113, 284–288. [Google Scholar] [CrossRef]
  28. Tzschoppe, M.; Martin, A.; Beutin, L. A rapid procedure for the detection and isolation of enterohaemorrhagic Escherichia coli (EHEC) serogroup O26, O103, O111, O118, O121, O145 and O157 strains and the aggregative EHEC O104: H4 strain from ready-to-eat vegetables. Int. J. Food Microbiol. 2012, 152, 19–30. [Google Scholar] [CrossRef] [PubMed]
  29. Bautista, V.A.L.M.; Mendoza, B.C. Serogroup, pathotype and multiple drug resistance of Escherichia coli strains isolated from the cloaca of layer chickens in San Jose, Batangas, Philippines. Philipp. Sci. Lett. 2018, 11, 69–77. [Google Scholar]
  30. Moyo, S.J.; Maselle, S.Y.; Matee, M.I.; Langeland, N.; Mylvaganam, H. Identification of diarrheagenic Escherichia coli isolated from infants and children in Dar es Salaam, Tanzania. BMC Infect. Dis. 2007, 7, 92. [Google Scholar] [CrossRef] [Green Version]
  31. Dubreuil, J.D.; Isaacson, R.E.; Schifferli, D.M. Animal enterotoxigenic Escherichia coli. EcoSal Plus 2016, 7, 1. [Google Scholar] [CrossRef] [Green Version]
  32. Mare, A.D.; Ciurea, C.N.; Man, A.; Tudor, B.; Moldovan, V.; Decean, L.; Toma, F. Enteropathogenic Escherichia coli—A Summary of the Literature. Gastroenterol. Insights 2021, 12, 28–40. [Google Scholar] [CrossRef]
  33. Liu, L.; Saitz-Rojas, W.; Smith, R.; Gonyar, L.; In, J.G.; Kovbasnjuk, O.; Zachos, N.C.; Donowitz, M.; Nataro, J.P.; Ruiz-Perez, F. Mucus layer modeling of human colonoids during infection with enteroaggragative E. coli. Sci. Rep. 2020, 10, 10533. [Google Scholar] [CrossRef] [PubMed]
  34. Zare, S.; Derakhshandeh, A.; Haghkhah, M.; Naziri, Z.; Broujeni, A.M. Molecular typing of Staphylococcus aureus from different sources by RAPD-PCR analysis. Heliyon 2019, 5, e02231. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Faraji, Z.; Khasheii, B.; Ghaemi, E.A.; Anvari, S.; Rajabnia, R.; Jamali, A. Molecular Typing of Uropathogenic Escherichia coli Strains Isolated from Patients by Random Amplified Polymorphic DNA-PCR (RAPD-PCR). Arch. Med. Lab. Sci. 2021, 7, e17. [Google Scholar] [CrossRef]
  36. Albesharat, R.; Ehrmann, M.A.; Korakli, M.; Yazaji, S.; Vogel, R.F. Phenotypic and genotypic analyses of lactic acid bacteria in local fermented food, breast milk and faeces of mothers and their babies. Syst. Appl. Microbiol. 2011, 34, 148–155. [Google Scholar] [CrossRef]
  37. Firacative, C.; Trilles, L.; Meyer, W. MALDI-TOF MS enables the rapid identification of the major molecular types within the Cryptococcus neoformans/C. gattii species complex. PLoS ONE 2012, 7, e37566. [Google Scholar] [CrossRef] [Green Version]
  38. Simmon, K.E.; Fang, D.C.; Tesic, V.; Khot, P.D.; Giangeruso, E.; Bolesta, E.S.; Wagner-Reiss, K.M.; Fisher, M.A.; Petti, C.A.; Han, X.Y. Isolation and characterization of “Pseudomonas andersonii” from four cases of pulmonary granulomas and emended species description. J. Clin. Microbiol. 2011, 49, 1518–1523. [Google Scholar] [CrossRef] [Green Version]
  39. Lindenstrauß, A.G.; Pavlovic, M.; Bringmann, A.; Behr, J.; Ehrmann, M.A.; Vogel, R.F. Comparison of genotypic and phenotypic cluster analyses of virulence determinants and possible role of CRISPR elements towards their incidence in Enterococcus faecalis and Enterococcus faecium. Syst. Appl. Microbiol. 2011, 34, 553–560. [Google Scholar] [CrossRef]
  40. More, S.J. European perspectives on efforts to reduce antimicrobial usage in food animal production. Ir. Vet. J. 2020, 73, 2. [Google Scholar] [CrossRef] [Green Version]
  41. Pokharel, S.; Shrestha, P.; Adhikari, B. Antimicrobial use in food animals and human health: Time to implement ‘One Health’ approach. Antimicrob. Resist. Infect. Control 2020, 9, 181. [Google Scholar] [CrossRef]
  42. Karama, M.; Cenci-Goga, B.T.; Malahlela, M.; Smith, A.M.; Keddy, K.H.; El-Ashram, S.; Kabiru, L.M.; Kalake, A. Virulence characteristics and antimicrobial resistance profiles of shiga toxin-producing Escherichia coli isolates from humans in South Africa: 2006–2013. Toxins 2019, 11, 424. [Google Scholar] [CrossRef] [Green Version]
  43. Eltai, N.O.; Al Thani, A.A.; Al Hadidi, S.H.; Al Ansari, K.; Yassine, H.M. Antibiotic resistance and virulence patterns of pathogenic Escherichia coli strains associated with acute gastroenteritis among children in Qatar. BMC Microbiol. 2020, 20, 54. [Google Scholar] [CrossRef] [PubMed]
  44. Mukherjee, S.; Mosci, R.E.; Anderson, C.M.; Snyder, B.A.; Collins, J.; Rudrik, J.T.; Manning, S.D. Antimicrobial drug–resistant Shiga toxin–producing Escherichia coli infections, Michigan, USA. Emerg. Infect. Dis. 2017, 23, 1609. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Aranda, K.R.; Fabbricotti, S.H.; Fagundes-Neto, U.; Scaletsky, I.C. Single multiplex assay to identify simultaneously enteropathogenic, enteroaggregative, enterotoxigenic, enteroinvasive and Shiga toxin-producing Escherichia coli strains in Brazilian children. FEMS Microbiol. Lett. 2007, 267, 145–150. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Blanco, M.; Blanco, J.; Mora, A.; Rey, J.; Alonso, J.; Hermoso, M.; Hermoso, J.; Alonso, M.; Dahbi, G.; González, E. Serotypes, virulence genes, and intimin types of Shiga toxin (verotoxin)-producing Escherichia coli isolates from healthy sheep in Spain. J. Clin. Microbiol. 2003, 41, 1351–1356. [Google Scholar] [CrossRef] [Green Version]
  47. Cho, S.-H.; Kim, J.-H.; Kim, J.-C.; Shin, H.-H.; Kang, Y.-H.; Lee, B.-K. Surveillance of bacterial pathogens associated with acute diarrheal disease in the Republic of Korea during one year, 2003. J. Microbiol. 2006, 44, 327–335. [Google Scholar]
  48. Jenssen, G.R.; Veneti, L.; Lange, H.; Vold, L.; Naseer, U.; Brandal, L.T. Implementation of multiplex PCR diagnostics for gastrointestinal pathogens linked to increase of notified Shiga toxin-producing Escherichia coli cases in Norway, 2007–2017. Eur. J. Clin. Microbiol. Infect. Dis. 2019, 38, 801–809. [Google Scholar] [CrossRef] [Green Version]
  49. López-Saucedo, C.; Cerna, J.F.; Villegas-Sepulveda, N.; Thompson, R.; Velazquez, F.R.; Torres, J.; Tarr, P.I.; Estrada-García, T. Single multiplex polymerase chain reaction to detect diverse loci associated with diarrheagenic Escherichia coli. Emerg. Infect. Dis. 2003, 9, 127. [Google Scholar] [CrossRef]
  50. Wayne, P. Clinical and laboratory standards institute. Performance standards for antimicrobial susceptibility testing. Inform. Suppl. 2011, 31, 100–121. [Google Scholar]
  51. Wikler, M.A. Performance Standards for Antimicrobial Susceptibility Testing; Sixteenth Informational Supplement, M 100-S 16; Clinical and Laboratory Standards Institute: Malvern, PA, USA, 2006. [Google Scholar]
Pathogens 11 00385 g001 550
Figure 1. UPGMA cluster of RAPD band patterns for 75 E. coli isolates. The analysis was performed using RAPD primer 5 of the Ready-To-Go-RAPD Analysis kit. Five clusters were generated at 76% of RAPD profile similarity value using Bionumerics software.
Figure 1. UPGMA cluster of RAPD band patterns for 75 E. coli isolates. The analysis was performed using RAPD primer 5 of the Ready-To-Go-RAPD Analysis kit. Five clusters were generated at 76% of RAPD profile similarity value using Bionumerics software.
Pathogens 11 00385 g001
Pathogens 11 00385 g002 550
Figure 2. Cluster analysis of MSP dendrogram generated by MALDI-TOF MS for E. coli isolates. The dendrogram was generated using MALDI Biotyper 3.0, and the distance level in the dendrogram was set at a maximal value of 1000. The scale below the dendrogram signifies the relative distances. The five clusters were made at the distance level of 500.
Figure 2. Cluster analysis of MSP dendrogram generated by MALDI-TOF MS for E. coli isolates. The dendrogram was generated using MALDI Biotyper 3.0, and the distance level in the dendrogram was set at a maximal value of 1000. The scale below the dendrogram signifies the relative distances. The five clusters were made at the distance level of 500.
Pathogens 11 00385 g002
Table
Table 1. O-serotyping and virulence gene distribution of E. coli isolates.
Table 1. O-serotyping and virulence gene distribution of E. coli isolates.
Pathotypes (%)Virulence GenesTotal No. of IsolatesO Serotype (Total No. of Isolates)
ETEC (6.6)st5O25(3), O159(1), UN(1)
ETEC and EAEC (2.7)st, aggR2O159(1), UN(1)
ETEC and EPEC (6.6)st, eaeA, bfpA1O8(1)
st, eaeA2UN(2)
st, bfpA2UN(2)
EPEC (47.0)eaeA27O8(2), O18(2), O20(2), O55(1), O119(3), O125(1), O153(1), O166(2), O127a(2), O28ac(1), UN(10)
eaeA, bfpA2UN(2)
bfpA6O6(1), O153(1), UN(4)
EPEC and EAEC (4.0)eaeA, aggR3O159(1), O169(1), UN(1)
EAEC (33.3)aggR25O1(1), O8(1), O20(2), O25(1), O78(1), O166(4), O28ac(2), UN(13)
UN: unknown.
Table
Table 2. Antimicrobial resistance rate of E. coli isolates.
Table 2. Antimicrobial resistance rate of E. coli isolates.
Antimicrobial (Abbreviations)No. of Resistant Isolates (%)No. of Intermediate Isolates (%)No. of Susceptible Isolates (%)
Penicillins
Ampicillin (AM)30 (40.0)045 (60)
Ticarcillin (TIC)29 (38.7)1 (1.3)45 (60)
ß-Lactam/ß-Lactamase inhibitor combinations
Ampicillin/Sulbactam (SAM)12 (16.0)8 (10.7)55 (73.3)
Cephems
Cefazolin (CZ)6 (8.0)069 (92)
Cefepime (FEB)1 (1.3)3 (4.0)71 (94.6)
Cefotaxime (CTX)4 (5.3)2 (2.7)69 (92)
Cefotetan (CTT)1 (1.3)074 (98.6)
Cephalothin (CF)11 (14.7)19 (25.3)45 (60)
Phenicols
Chloramphenicol (C)4 (5.3)071 (94.6)
Fluoroquinolones
Ciprofloxacin (CIP)10 (13.3)4 (5.3)61 (81.3)
Aminoglycosides
Amikacin (AN)5 (6.6)1 (1.3)69 (92)
Gentamicin (GM)14 (18.7)3 (4.0)58 (77.3)
Carbapenems
Imipenem (IPM)1 (1.3)074 (98.6)
Quinolones
Nalidixic acid (NA)33 (44.0)1 (1.3)41 (54.6)
Tetracyclines
Tetracycline (TE)31 (41.3)044 (58.6)
Folate pathway inhibitors
Trimethoprim/sulfamethoxazole (SXT)26 (34.7)2 (2.7)47 (62.6)
Table
Table 3. Antimicrobial resistance patterns of 75 E. coli isolates.
Table 3. Antimicrobial resistance patterns of 75 E. coli isolates.
No. of AntimicrobialsResistance PatternsNo. of Isolates
0-23
1SXT1
CZ1
TE1
NA8
TIC2
AM1
2TE, NA1
TE, TIC1
AN, TE1
AN, NA1
3AM, CF, SAM1
TE, NA, TIC2
CF, NA, TIC1
C, TE, NA1
4AM, SXT, NA, TIC1
AM, SXT, TE, SAM1
AM, NA, SAM, TIC1
AM, SXT, TE, TIC3
AM, SXT, TE, NA1
5AM, SXT, TE, NA, TIC2
AM, CF, C, TE, TIC1
GM, SXT, C, NA, TIC1
AM, CF, CIP, IPM, TE1
AM, GM, CTT, SAM, TIC1
6AM, CF, SXT, C, TE, TIC1
AM, CIP, SXT, TE, NA, SAM1
AM, GM, SXT, TE, NA, TIC3
AM, CZ, CF, SXT, TE, NA1
AM, CF, SXT, TE, NA, TIC1
7AM, GM, CIP, SXT, TE, NA, TIC3
8AM, GM, CIP, SXT, TE, NA, SAM, TIC2
AM, GM, AN, CTX, CIP, SXT, TE, SAM1
AM, CZ, CF, AN, SXT, NA, SAM, TIC1
10AM, CZ, CF, GM, AN, FEP, CTX, SXT, SAM, TIC1
11AM, CZ, CF, GM, CTX, CIP, SXT, TE, NA, SAM, TIC2
Total35 patterns75 strains
SXT (Trimethoprim/Sulfamethoxazole), CZ (Cefazolin), TE (Tetracycline), NA (Nalidixic acid), TIC (Ticarcillin), AM (Ampicillin), AN (Amikacin), CF (Cephalothin), SAM (Ampicillin/Sulbactam), C (Chloramphenicol), CIP (Ciprofloxacin), IPM (Imipenem), GM (Gentamicin), CTT (Cefotetan), CTX (Cefotaxime), FEB (Cefepime).
Table
Table 4. Correlation analysis between clustal analysis by MALDI-TOF MS and phylogroup analysis by RAPD.
Table 4. Correlation analysis between clustal analysis by MALDI-TOF MS and phylogroup analysis by RAPD.
No. (%) of StrainsMALDI-TOF MS
RAPDABCDTotal N (%)
I3 (4.0)--6 (8.0)9 (12.0)
II-1 (1.3)2 (2.7)41 (54.6) *44 (58.7) *
III6 (8.0)1 (1.3)3 (4.0)1 (1.3)11 (14.7)
IV-4 (5.3)-2 (2.7)6 (8.0)
V2 (2.7)1 (1.3)--3 (4.0)
None1 (1.3)--1 (1.3)2 (2.7)
Total N (%)12 (16.0)7 (9.3)5 (6.7)51 (68.0) *75 (100)
* Statistical significance was assessed by Chi-squared test (p < 0.05).
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Park, S.B.; Park, Y.K.; Ha, M.W.; Thompson, K.D.; Jung, T.S. Antimicrobial Resistance, Pathogenic, and Molecular Characterization of Escherichia coli from Diarrheal Patients in South Korea. Pathogens 2022, 11, 385. https://doi.org/10.3390/pathogens11040385

AMA Style

Park SB, Park YK, Ha MW, Thompson KD, Jung TS. Antimicrobial Resistance, Pathogenic, and Molecular Characterization of Escherichia coli from Diarrheal Patients in South Korea. Pathogens. 2022; 11(4):385. https://doi.org/10.3390/pathogens11040385

Chicago/Turabian Style

Park, Seong Bin, Yon Kyoung Park, Min Woo Ha, Kim D. Thompson, and Tae Sung Jung. 2022. "Antimicrobial Resistance, Pathogenic, and Molecular Characterization of Escherichia coli from Diarrheal Patients in South Korea" Pathogens 11, no. 4: 385. https://doi.org/10.3390/pathogens11040385

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop