Molecular Analysis of Escherichia coli and Correlations Between Phylogroups and Sequence Types from Different Sources
by
, , , , and
João Gabriel Material Soncini
1
,
Vanessa Lumi Koga
1,
Bruna Fuga
2,
Zuleica Naomi Tano
1,
Gerson Nakazato
3,
Renata Katsuko Takayama Kobayashi
3,
Nilton Lincopan
4 and
Eliana Carolina Vespero
1,* 1
Department of Pathology, Clinical and Toxicological Analysis, Health Sciences Center, State University of Londrina, Londrina 86057-970, Paraná, Brazil
2
Department of Cell Biology, Institute of Biological Sciences, University of Brasília, Brasília 70910-900, Goiás, Brazil
3
Department of Microbiology, Biological Science Center, State University of Londrina, Londrina 86057-970, Paraná, Brazil
4
Department of Microbiology, Biomedical Sciences Institute, University of São Paulo, São Paulo 05508-220, São Paulo, Brazil
*
Author to whom correspondence should be addressed.
Microorganisms 2024, 12(12), 2645; https://doi.org/10.3390/microorganisms12122645
Submission received: 27 November 2024
/
Revised: 9 December 2024
/
Accepted: 17 December 2024
/
Published: 20 December 2024
(This article belongs to the Special Issue Antimicrobial Resistance in Enterobacteriaceae and Enterococci)
Abstract
:Escherichia coli is a significant pathogen responsible for infections in both humans and livestock, possessing various virulence mechanisms and antimicrobial resistance that make it even more concerning. In this study, several internationally recognized clones of E. coli were identified, such as ST131, ST38, ST648, and ST354, from chicken meat, pork, and human infection samples. Notably, ST131, belonging to phylogroup B2, was the dominant sequence type (ST) in human samples, while ST38, belonging to phylogroup D, was the most prevalent in meat samples. Several antibiotic resistance genes were identified: the gyrA gene mutation was the most prevalent, and CTX-M-55 was the most common extended-spectrum beta-lactamases (ESBLs), with significant differences noted for CTX-M-2 and CTX-M-15. Virulence-associated genes (VAGs) such as gad and iss were frequently found, especially in human isolates. These findings highlight the complex epidemiology of antibiotic-resistant E. coli in community settings and the potential risks associated with commercial meat.
1. Introduction
Escherichia coli is one of the main bacterial pathogens associated with urinary tract infections (UTIs), accounting for a significant proportion of community-acquired infections [1]. Infections caused by E. coli strains producing extended-spectrum beta-lactamases (ESBLs) have become a major clinical challenge due to antibiotic resistance, resulting in limited treatment options and higher morbidity rates [2]. The spread of resistant strains, often associated with the inappropriate use of antimicrobials, raises concerns about public health and the effectiveness of antimicrobial therapies, especially in the context of increasing resistance in community settings [3].
In addition to infections in humans, E. coli is also frequently isolated from meats, especially chicken and pork, which are widely consumed in the human diet [4]. The use of antimicrobials in agriculture, aimed at promoting animal growth and preventing diseases, is associated with the development of bacterial resistance. The indiscriminate use of these medications in animal husbandry can lead to the selection of resistant strains, which, once introduced into the food chain, pose a significant risk to public health [3,5].
Antimicrobial resistance genes and virulence-associated genes (VAGs) can be easily transferred between different E. coli isolates. The CTX-M type is one of the largest groups of ESBLs and can be found on highly transferable plasmids [6]. Among E. coli uropathogenic (UPEC) isolates, CTX-M-15 is the most common; however, numerous CTX-M-producing E. coli strains have been identified as specific clones frequently associated with UTI cases in certain regions, and these clones are widely disseminated globally. Research indicates that CTX-M genotypes in food isolates may occasionally align with dominant human clones prevalent in the same area [7,8].
Additionally, VAGs play a crucial role in the pathogenicity of E. coli, enabling the bacterium to colonize, evade the host immune system, and cause disease. These genes encode factors such as adhesins, toxins, iron acquisition systems, and immune evasion mechanisms, which contribute to the ability of pathogenic E. coli strains to establish infections in diverse host environments. The distribution and prevalence of VAGs vary widely among different E. coli phylogroups and sequence types, reflecting their adaptation to specific niches [6,8,9].
E. coli ST131 is an example of a globally disseminated pandemic clone associated with CTX-M production, as well as other resistance mechanisms. Belonging to phylogroup B2, E. coli ST131 is also known for carrying numerous VAGs, making it highly pathogenic. Although it is strongly associated with urinary tract infections (UTIs), studies increasingly report its presence in veterinary, food, and environmental sources [6,9,10].
Other clones such as ST648, belonging to phylogroup F, have shown a significant increase in reports across human, veterinary, and environmental contexts in several countries, including Brazil, the United Kingdom, and India [11]. The dissemination of ST648 suggests a complex interconnection between human and animal reservoirs, making control of its spread challenging [12,13].
Given the significant impact of E. coli infections in Brazil on both human health and livestock, as well as the critical need to understand the spread of resistance and virulence genes, we conducted this epidemiological study from a One Health perspective. Our aim was to assess the transmission patterns of E. coli isolated from meat products and human patients in southern Brazil.
2. Materials and Methods
2.1. Study Population
This study includes 135 E. coli strains obtained from human urine samples (n = 59), chicken meat samples (n = 52), and pork samples (n = 24). These strains were previously selected and had their complete genome selected, as in a previously published study [4].
2.2. Bacterial Identification and Antimicrobial Susceptibility Test
The VITEK® 2 AST 239 card and the VITEK® 2 GN ID card (BioMérieux, Durham, NC, USA) were used for identification and antimicrobial susceptibility tests. Antimicrobial susceptibility was tested with 14 types of antibiotics: ampicillin, amoxicillin/clavulanate, ceftriaxone, cefepime, ertapenem, meropenem, nalidixic acid, ciprofloxacin, norfloxacin, gentamicin, amikacin, nitrofurantoin, trimethoprim/sulfamethoxazole, and piperacillin/tazobactam. In some cases, chromogenic agar medium (ChromID ESBL, BioMérieux, Marcy L’Etoile, France) was used to confirm for ESBL production.
The interpretation of the results was based on the CLSI 2020 (Clinical and Laboratory Standards Institute) criteria, and the E. coli ATCCⓇ 25922 strain was used as a quality control [14].
2.3. ERIC-PCR
2.4. DNA Isolation and Whole-Genome Sequencing
For DNA extraction, the strains were cultured on Mueller–Hinton Agar and allowed to grow overnight at 37 °C. Subsequently, a single colony was inoculated into 2 mL of Luria–Bertani broth and incubated for 12 h at 37 °C. The resulting suspension was used for DNA extraction and purification using the DNA extraction kit from Invitrogen (Carlsbad, CA, USA). The extracted DNA was quantified using the Qubit dsDNA BR assay kit from Invitrogen (Carlsbad, CA, USA). Once quantified, the DNA was utilized to construct a paired-end library (150 bp) and subjected to sequencing on a NextSeq platform from Illumina (San Diego, CA, USA). All steps followed the instructions provided by the respective manufacturers.
2.5. Bioinformatic Analysis
Genome quality filtering and assemblies were performed using CLC Genomics Workbench version 7.0 (Aarhus, Denmark). Multilocus sequence type (MLST), resistome, and virulome were identified using MLST v2.0, ResFinder v3.1, VirulenceFinder v2.0, PlasmidFinder v2.1, FimTyper v1.0, and SerotypeFinder v.2.0, respectively [17,18,19,20,21,22].
2.6. Statistical Analysis
Categorical data were represented as frequencies and percentages. Fisher’s exact test or a chi-square test was applied as appropriate, considering an alpha significance level of 0.05. Data analysis was performed using Statistical Package for Social Sciences (SPSS—IBM Corp., New York, NY, USA), version 20, for Windows.
3. Results
All data for each sample are compiled in Supplementary Materials (Complete Data Table), and a heatmap (Figure 1) was created with samples that shared the same ST in at least two of the studied sources.
3.1. Antibiotic Resistance Genes
Different resistance genes were found in the studied samples. The mutation in the gyrA gene was the most predominant resistance among the samples, being present in 88.5% (n = 46) of the chicken meat, 54.2% (n = 13) of the pork, and 79.7% (n = 47) of the human isolates. Two pork samples tested positive for the mcr-1 gene (n = 8.3%). The most prevalent ESBL gene was blaCTX-M-55, positive in 42.3% (n = 22) of the chicken meat, 41.7% (n = 10) the pork, and 10.2% (n = 6) of the human samples.
Among the ESBLs genes that showed significant differences (Table 1) were blaCTX-M-2 (p = 0.002), blaCTX-M-15 (p = 0.001), and blaCTX-55 (p < 0.001).
3.2. Virulence-Associated Genes
The VAGs gad and iss were the most frequently found among the samples, being present in 63.5% (n = 33) and 78.8% (n = 41) of the chicken meat, 70.7% (n = 17) and 70.8% (n = 17) of the pork, and 96.6% (n = 57) and 72.9% (n = 43) of the human isolates, respectively.
Several prominent VAGs exhibited statistically significant differences across samples (Table 2). The exotoxin hlyF (p < 0.001) was detected exclusively in the chicken meat samples (40.4%) and pork samples (25.0%). The nutritional/metabolic factor iutA (p < 0.001), which was present in 38.5% of the chicken meat samples and 8.3% of the pork samples, chuA (p < 0.001), found in 26.9% of the chicken meat samples and 16.7% of the pork samples, and fyuA (p = 0.003), detected in 13.5% of the chicken meat samples and 16.7% of the pork samples, also demonstrated significant differences. Additionally, the genes classified as other factors, gad (p < 0.001), the most prevalent, and papC (p = 0.002), found in 15.4% of the chicken meat samples and 12.5% of the pork samples, highlighted their relevance.
Various fimH types were detected and are listed in Supplementary Materials (Table S1). The most prevalent were fimH27, present in six chicken meat samples (11.5%), one pork sample (4.2%), and twelve human samples (20.3%), and fimH30, found in one chicken meat sample (1.9%) and thirteen human samples (22.0%). Only fimH30 showed a significant difference between the different sources (p < 0.0001).
3.3. Serotypes
Various serotypes were identified among the isolates, with the two most frequent ones also showing statistically significant differences, these being O25:H4 (p = 0.010), present in two (3.8%) chicken meat and nine (15.3%) human samples, and O1:H6 (p = 0.042), found in one (4.3%) pork and six (10.2%) human samples. All the O25:H4 strains belong to the ST131 clone, while the serotype O1:H6 is associated with ST648. All the results can be seen in Supplementary Materials (Table S2).
3.4. Sequence Types
A total of 55 different STs were identified, with the most prevalent being ST131 (n = 14), ST38 (n = 10), ST648 (n = 9), and ST354 (n = 7). The ST131 clone was predominantly found in human samples (n = 12) and in only two chicken meat samples. ST38 and ST648 were detected in all three different origins, with four and one from chicken meat, one and one from pork, and five and seven from humans, respectively. Lastly, ST354 was found in four chicken meat and three human samples.
3.5. Phylogroups
All phylogroups were identified in the studied samples, with B1 (n = 30) being the most prevalent, followed by A (n = 23), F (n = 23), B2 (n = 19), D (n = 19), E (n = 8), C (n = 6), and G (n = 6). Each phylogroup was detected in at least two different origins. Specifically, B1 (n = 14) and A (n = 12) were the most prevalent in human samples, while B2 (n = 17) was the most commonly found in chicken meat, and B1 (n = 7) was the most frequently diagnosed in pork samples. All isolates with the same ST belong to the same phylogroup.
4. Discussion
This study is a surveillance work that analyzed 135 E. coli isolates present in meats marketed for human consumption (chicken meat (n = 52) and pork (n = 24)) and in urine samples from community-acquired UTI patients (n = 59). The presence of internationally recognized clones among isolates from these different sources raises important questions about the spread of resistant and pathogenic E. coli lineages. The predominance of the ST131 clone, belonging to phylogroup B2, in human samples is well documented in the scientific literature, consistent with its strong association with clinical infections in both community and hospital settings [23,24]. In contrast, the ST38 (belonging to phylogroup D), ST648, and ST354 clones (belonging to phylogroup F) have been reported in both human infections and meat products and are considered emerging in the dissemination of antimicrobial resistance, particularly to quinolones and cephalosporins. Similar data can be found in the literature, with reports that ST38, phylogroup D, was found in 22% of the chicken samples and 14% of the UTI case samples, while ST648, phylogroup F, was identified in 10% of the pork samples and 8% of the human samples [4,25].
The dissemination of E. coli clones is closely associated with the spread of resistance genes. The CTX-M type represents one of the largest groups of ESBLs, and recent studies investigating the epidemiology of these enzymes in Brazil have highlighted CTX-M-2, CTX-M-8, CTX-M-9, and CTX-M-15 as predominant variants in this country [12]. Amongst all the samples in this study, nine types of blaCTX-M genes were found; however, statistical differences were only found for the blaCTX-M-2 (p = 0.002), blaCTX-M-15 (p = 0.001), and blaCTX-M-55 (p < 0.001) genes. The blaCTX-M-2 and blaCTX-M-55 genes were detected in higher quantities in the chicken meat samples (n = 18 and n = 22, respectively), while the blaCTX-M-15 gene was more prevalent in the human urine samples (n = 14). These results are highly consistent with a study showing the proportion of isolates carrying the blaCTX-M-2 and blaCTX-M-55 genes as 78% and 45% in chicken samples and 15% and 5% in human samples, respectively, while the blaCTX-M-15 gene was more frequent in humans (45%) than in chickens (8%), suggesting that the transfer of these genes occurs more frequently within E. coli strains associated with either humans or chickens, and it may be less common among E. coli strains from different animal species. Increased interaction among members of the same animal species may contribute to the transfer of bacteria and bacterial genes among these populations [26].
The ESBL variants CTX-M-2 and CTX-M-55 are frequently found in E. coli isolated from chicken meat and pork, and their detection has been reported in countries such as the United States, the United Kingdom, France, and China. The beta-lactamase CTX-M-15 is endemic in various countries and is frequently associated with the epidemic clone E. coli ST131 (B2) which has worldwide distribution, primarily associated with human infections, as demonstrated by the data from the present study [27,28]. Although studies have been conducted on the chromosomal location of blaCTX-M genes, plasmids are still considered the main vehicles for their rapid dissemination. Currently, it is reported that the blaCTX-M genes are mainly located on plasmids IncFII, IncI1, IncI2, and IncHI2 and often appear together with other antimicrobial resistance genes, as observed in our findings [29].
The frequency of coexistence of various resistance genes to different classes of antimicrobials highlights the complexity and adaptability of E. coli in response to the selective pressure exerted by antimicrobials. Furthermore, the coexistence of these genes in diverse sources, including humans, animals, and even the environment, suggests a broad and interconnected dissemination of antimicrobial resistance, known as One Health [26,30].
Although not statistically significant, the mcr-1 gene was found only in the pork samples, which is consistent with published studies, where they reported a higher prevalence of the mcr-1 gene in swine compared to other sources. Interestingly, it is known that fourteen distinct plasmid incompatibility groups are capable of carrying the mcr-1 gene, with over 90% of globally identified plasmids belonging to the IncX4, IncI2, and IncHI2 groups. In our study, the presence of the IncX4 group was observed in all two E. coli isolates carrying the mcr-1 gene, consistent with other studies indicating that the IncX4 plasmid exhibits high transmissibility [31,32]. Additionally, the isolates belong to phylogroup B1, which is frequently reported in the literature as harboring the mcr-1 gene [33,34].
Multiple VAGs were detected in our isolates and perform various mechanisms that assist in E. coli pathogenicity, enhancing its virulence and enabling the isolate to cause infections and damage to the host tissues. Among the VAGs that showed statistical differences between the groups, the ones that were prevalent in human urine samples were sat (p < 0.001), cnf1 (p = 0.014), senB (p < 0.001), and nfaE (p = 0.006). Epidemiological data indicate a higher prevalence of these genes in UPEC when compared to other strains of E. coli [9]. Furthermore, in an interesting study using mouse models, it was demonstrated that cnf1-positive strains show increased colonization of the bladder, higher recovery rates in urine, and enhanced resistance to human neutrophil-mediated killing compared to cnf1-negative strains [35]. In this way, our results are consistent with those previously reported in the literature.
Most of the VAGs that showed significant differences were found in meat samples, like iutA, kpsMII, and papC. These genes were prevalent in the chicken meat isolates, consistent with results from other studies suggesting that APEC is the major carrier of resistance and virulence genes in chickens, responsible for losses in all types of poultry production systems. APEC is prevalent (9.52% to 36.73%) in all age groups of chickens, with broilers aged 4 to 6 weeks being the most susceptible to infection [36,37].
Recent research indicates that APEC is a potential zoonotic pathogen transmitted through food, as well as a source or reservoir of extra-intestinal infections in humans. Specifically, APEC shares genetic similarities with human ExPEC (UPEC), possessing virulence genes characteristic of UPEC, allowing it to cause UTIs [4,36,38]. This finding is further supported by our dates, as several VAGs are present in both our meat-derived isolates and in urine samples from patients with UTIs, with astA (p < 0.001), cma (p = 0.004), capU (p = 0.043), and gad (p < 0.001) showing statistically significant differences. Moreover, the identification of APEC-specific ColV (colicin V) plasmids in human UPEC isolates suggests a potential zoonotic transmission of APEC from avian sources to humans. Consequently, APEC represents a significant pathogen for both the poultry industry and public health [37,38].
Despite VAGs not being prevalent in pork compared to chicken meat isolates and human urine, it is known that these genes are also responsible for significant economic losses in the swine industry due to high morbidity, mortality, growth retardation, and increased therapy costs. Furthermore, they pose risks to human and poultry health due to horizontal gene transfer among E. coli from different sources [39,40].
With mechanisms of cell epithelial adhesion mediated by proteins, fimH becomes a crucial virulence factor for E. coli strains. Thus, the fimH gene is highly conserved and extremely common in E. coli isolates from different sources [41]. In our results, fimH30 (p < 0.001) was the only one that showed statistically significant differences, being prevalent in human urine isolates. The fimH30 variant is commonly associated with the pandemic E. coli ST131 lineage, a clone closely related to UTIs. In a study, fimH alleles of globally dominant UPEC ST131-B2 were evaluated, and it was observed that the fimH30 variant has a greater ability to penetrate uroepithelial cells when compared to others, which explains the predominance of fimH30 in E. coli derived from human urine [41,42].
Apart from adhesins, E. coli strains possess flagella, which contribute to bacterial mobility and serve as a significant antigenic component. The identification of serogroups is facilitated through the application of anti-O sera. Moreover, the antigenic diversity of flagella (H), combined with variability in O antigens, delineates the serotypes within the E. coli group. Among the prevalent serotypes linked to infections caused by UPEC strains are O1:H6 and O25:H4 [43,44]. These two serotypes showed statistically significant results in our study and were more prevalent in human urine isolates. An analysis of serotypes in 80 UPEC isolates in a study demonstrated that 51% belonged to classic serotypes such as O6:H1, O7:H4, O1:H6, O4:H5, O25:H4, O51:HNT, O34:HNM, and O8:H7, affirming our data [45].
One limitation of this study is that, although it used samples of meat sold for human consumption, E. coli isolates may have been introduced during processing, either by human handlers or by the instruments used to prepare the meat. Previous studies have shown that both equipment and workers’ hands can be significant sources of contamination [46,47]. Therefore, it is essential that further studies be conducted to provide a more comprehensive understanding of the epidemiology of E. coli.
In conclusion, E. coli is a complex microorganism characterized by various clones and serotypes, capable of acquiring diverse mobile genetic elements, which makes it a dangerous pathogen. The correlation between the presence of important clones in food products and their detection in clinical cases underscores the risk of transmission and highlights the urgent need for control strategies to mitigate the spread of resistant pathogens between humans and animals.
Supplementary Materials
Additional Supplementary Materials can also be accessed through Figshare, including additional files related to this study, such as tables and FASTA files: https://doi.org/10.6084/m9.figshare.27853665.v4 (accessed on 9 December 2024).
Author Contributions
E.C.V., Z.N.T. and R.K.T.K. conceived and designed the experiments. J.G.M.S., V.L.K. and B.F. performed the experiments. J.G.M.S., V.L.K. and E.C.V. analyzed the data. E.C.V., Z.N.T., G.N., R.K.T.K. and N.L. contributed reagents and materials. E.C.V. and Z.N.T. reviewed this study. V.L.K. performed confirmation experiments. All authors have read and agreed to the published version of the manuscript.
Funding
This research received full funding from the Bill & Melinda Gates Foundation (grant number OPP1193112). This grant is part of the Grand Challenges Explorations Brazil initiative, which focuses on innovative methods for assessing the global impact of antimicrobial resistance (OPP1193112).
Institutional Review Board Statement
This study was approved by the Ethics and Research Committee of the State University of Londrina CAAE 56869816.0.000.5231, on 18 October 2018.
Informed Consent Statement
An informed consent form was signed by the participants, and all experiments were performed in accordance with ethical regulations.
Data Availability Statement
The data presented in this study are openly available in FigShare at https://doi.org/10.6084/m9.figshare.27853665.v4.
Acknowledgments
The authors thank the Bill & Melinda Gates Foundation for funding this project through the Grand Challenges Explorations Brazil initiative (OPP1193112). We also acknowledge the Araucaria Foundation, the Research Support Facilities Center at the University of São Paulo (CEFAP-USP), the Institute of Biomedical Sciences at the University of São Paulo (ICB-USP), and the Clinical and Laboratory Pathophysiology program at the State University of Londrina.
Conflicts of Interest
The authors declare no conflicts of interest.
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Figure 1.
Heatmap. A visual scheme displaying the sample codes, sources, STs, phylogroups, ESBLs, quinolone resistance genes (QRGs), quinolone resistance-determining regions (QRDRs), VAGs, and serotypes. Color legend: In the source column, the yellow and green icons represent isolates derived from chicken and pork meat, respectively, while the blue icon represents those of human origin. The presence of ESBLs, QRGs, and QRDRs is represented by the colors brown, golden yellow and yellow, respectively. In the VAGs section, each color represents the classification of the gene: purple—effector delivery system; dark blue—adhesins; teal—exotoxin; blue—nutritional/metabolic factor; blue-green—capsule; light blue—other. The symbols ** represent E. coli scheme sequence type II (Institut Pasteur).
Figure 1.
Heatmap. A visual scheme displaying the sample codes, sources, STs, phylogroups, ESBLs, quinolone resistance genes (QRGs), quinolone resistance-determining regions (QRDRs), VAGs, and serotypes. Color legend: In the source column, the yellow and green icons represent isolates derived from chicken and pork meat, respectively, while the blue icon represents those of human origin. The presence of ESBLs, QRGs, and QRDRs is represented by the colors brown, golden yellow and yellow, respectively. In the VAGs section, each color represents the classification of the gene: purple—effector delivery system; dark blue—adhesins; teal—exotoxin; blue—nutritional/metabolic factor; blue-green—capsule; light blue—other. The symbols ** represent E. coli scheme sequence type II (Institut Pasteur).
Table 1.
Prevalence and statistical analysis of antimicrobial resistance genes.
| Antibiotic Resistance | Resistance Genes | Sources | p-Value | ||
|---|---|---|---|---|---|
| Meats | Human | ||||
| Chicken Meat n = 52 (%) | Pork n = 24 (%) | Urine n = 59 (%) | |||
| ESBL | blaCTX-M-1 | 1 (1.9) | 0 (0.0) | 0 (0.0) | 1.000 |
| blaCTX-M-2 | 18 (34.6) | 3 (12.5) | 4 (6.8) | 0.002 * | |
| blaCTX-M-3 | 0 (0.0) | 0 (0.0) | 1 (1.7) | 0.437 | |
| blaCTX-M-8 | 6 (11.5) | 3 (12.5) | 9 (15.3) | 0.615 | |
| blaCTX-M-14 | 1 (1.9) | 0 (0.0) | 6 (10.2) | 0.043 | |
| blaCTX-M-15 | 0 (0.0) | 3 (12.5) | 14 (23.7) | 0.001 * | |
| blaCTX-M-24 | 0 (0.0) | 0 (0.0) | 2 (3.4) | 0.189 | |
| blaCTX-M-27 | 0 (0.0) | 0 (0.0) | 3 (5.1) | 0.081 | |
| blaCTX-M-55 | 22 (42.3) | 10 (41.7) | 6 (10.2) | <0.001 * | |
| β-lactam | blaCMY-2 | 8 (15.4) | 2 (8.3) | 3 (5.1) | 0.147 |
| blaSHV-12 | 2 (3.8) | 0 (0.0) | 0 (0.0) | 0.504 | |
| blaOXA-1 | 0 (0.0) | 1 (4.2) | 6 (10.2) | 0.043 * | |
| blaTEM-1A | 1 (1.9) | 3 (12.5) | 0 (0.0) | 0.131 | |
| blaTEM-1B | 22 (42.3) | 14 (58.3) | 28 (47.6) | 1.000 | |
| blaTEM-141 | 9 (17.3) | 6 (25.0) | 0 (0.0) | <0.001 * | |
| blaTEM-206 | 9 (17.3) | 6 (25.0) | 0 (0.0) | <0.001 * | |
| blaTEM-209 | 0 (0.0) | 1 (4.2) | 0 (0.0) | 1.000 | |
| blaTEM-214 | 9 (17.3) | 6 (25.0) | 0 (0.0) | 0.005 * | |
| Sulphonamide | sul1 | 25 (48.1) | 7 (29.2) | 36 (61.0) | 0.037 * |
| sul2 | 26 (50.0) | 10 (41.7) | 30 (50.8) | 0.730 | |
| sul3 | 6 (11.5) | 1 (4.2) | 1 (1.7) | 0.137 | |
| Tetracycline | tet(A) | 9 (17.3) | 7 (29.2) | 27 (45.8) | 0.003 * |
| tet(B) | 10 (19.2) | 10 (41.7) | 17 (28.8) | 0.846 | |
| tet(G) | 0 (0.0) | 0 (0.0) | 1 (1.7) | 0.437 | |
| tet(M) | 0 (0.0) | 0 (0.0) | 1 (1.7) | 0.437 | |
| Fosfomycin | fosA | 15 (28.8) | 8 (33.3) | 3 (5.1) | <0.001 * |
| Phenicols | catA1 | 1 (1.9) | 1 (4.2) | 4 (6.8) | 0.404 |
| catB3 | 0 (0.0) | 0 (0.0) | 7 (11.9) | 0.021 * | |
| cmlA1 | 4 (7.7) | 1 (4.2) | 2 (3.4) | 0.465 | |
| floR | 3 (5.8) | 4 (16.7) | 2 (3.4) | 0.298 | |
| mdf(A) | 4 (7.7) | 1 (4.2) | 2 (3.4) | 0.468 | |
| mph(A) | 1 (1.9) | 3 (12.5) | 26 (44.1) | <0.001 * | |
| mph(B) | 0 (0.0) | 1 (4.2) | 0 (0.0) | 1.000 | |
| Trimethoprim | dfrA1 | 4 (7.7) | 3 (12.5) | 10 (16.9) | 0.314 |
| dfrA5 | 0 (0.0) | 0 (0.0) | 1 (1.7) | 0.437 | |
| dfrA7 | 2 (3.8) | 0 (0.0) | 0 (0.0) | 0.504 | |
| dfrA8 | 0 (0.0) | 1 (4.2) | 3 (5.1) | 0.318 | |
| dfrA12 | 3 (5.8) | 0 (0.0) | 5 (8.5) | 0.296 | |
| dfrA14 | 3 (5.8) | 1 (4.2) | 2 (3.4) | 0.696 | |
| dfrA17 | 6 (11.5) | 3 (12.5) | 27 (45.8) | <0.001 * | |
| dfrA25 | 0 (0.0) | 0 (0.0) | 1 (1.7) | 0.437 | |
| erm(42) | 0 (0.0) | 0 (0.0) | 1 (1.7) | 0.437 | |
| erm(B) | 0 (0.0) | 0 (0.0) | 4 (6.8) | 0.034 * | |
| Quinolones | QnrB19 | 6 (11.5) | 3 (12.5) | 4 (6.8) | 0.246 |
| QnrS1 | 1 (1.9) | 0 (0.0) | 4 (6.8) | 0.167 | |
| rmtB | 0 (0.0) | 0 (0.0) | 1 (1.7) | 0.437 | |
| Aminoglycosides | aac(3)-Iv | 0 (0.0) | 1 (4.2) | 0 (0.0) | 1.000 |
| aac(3)-VIa | 19 (36.5) | 2 (8.3) | 4 (6.8) | 0.002 * | |
| aac(3)-IIa | 0 (0.0) | 0 (0.0) | 3 (5.1) | 0.081 | |
| aac(3)-IId | 3 (5.8) | 1 (4.2) | 8 (13.6) | 0.128 | |
| aac(6′)Ib-cr | 0 (0.0) | 1 (4.2) | 8 (13.6) | 0.010 * | |
| aph(6)-Id | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0.131 | |
| aph(3′)-Ia | 4 (7.7) | 3 (12.5) | 1 (1.7) | 0.137 | |
| aph(3″)-Ib | 4 (7.7) | 6 (25.0) | 0 (0.0) | 0.003 * | |
| aph(3′)-Ic | 1 (1.9) | 1 (4.2) | 2 (3.4) | 1.000 | |
| aph(4)-Ia | 1 (1.9) | 1 (4.2) | 1 (1.7) | 1.000 | |
| ant(2″)-Ia | 2 (3.8) | 0 (0.0) | 0 (0.0) | 0.504 | |
| aph(6)-Id | 4 (7.7) | 6 (25.0) | 0 (0.0) | 0.035 * | |
| aacA4 | 0 (0.0) | 0 (0.0) | 2 (3.4) | 0.189 | |
| aadA1 | 32 (61.5) | 9 (37.5) | 15 (25.4) | 0.001 * | |
| aadA2 | 5 (9.6) | 1 (4.2) | 6 (10.2) | 0.763 | |
| aadA2b | 1 (1.9) | 0 (0.0) | 0 (0.0) | 1.000 | |
| aadA5 | 5 (9.6) | 3 (12.5) | 25 (42.4) | <0.001 * | |
| aadA12 | 0 (0.0) | 1 (4.2) | 0 (0.0) | 1.000 | |
| aadA24 | 0 (0.0) | 1 (4.2) | 0 (0.0) | 1.000 | |
| aadB | 4 (7.7) | 0 (0.0) | 3 (5.1) | 1.000 | |
| strA | 12 (23.1) | 9 (37.5) | 25 (42.4) | 0.099 | |
| strB | 12 (23.1) | 9 (37.5) | 25 (42.4) | 0.099 | |
| Fluroquinoles | parC:p.S56T | 1 (1.9) | 1 (4.2) | 1 (1.7) | 1.000 |
| parC:p.S57T | 2 (3.8) | 1 (4.2) | 0 (0.0) | 0.256 | |
| parC:p.S80I | 37 (71.2) | 16 (66.7) | 43 (72.9) | 0.707 | |
| parC_S80R | 0 (0.0) | 0 (0.0) | 2 (3.4) | 0.189 | |
| parC_E84A | 0 (0.0) | 0 (0.0) | 1 (1.7) | 0.437 | |
| parC:p.E84K | 2 (3.8) | 2 (8.3) | 0 (0.0) | 0.131 | |
| parC:p.E84G | 4 (7.7) | 0 (0.0) | 4 (6.8) | 0.729 | |
| parC_E84V | 0 (0.0) | 0 (0.0) | 12 (20.3) | <0.001 * | |
| parE_L416F | 0 (0.0) | 0 (0.0) | 4 (6.8) | 0.034 * | |
| parE:p.S458A | 4 (7.7) | 7 (29.2) | 14 (23.7) | 0.187 | |
| parE:p.I355T | 6 (11.5) | 1 (4.2) | 3 (5.1) | 0.512 | |
| parE_I529L | 0 (0.0) | 0 (0.0) | 12 (20.3) | <0.001 * | |
| gyrA:p.S83L | 46 (88.5) | 13 (54.2) | 47 (79.7) | 0.348 | |
| gyrA:p.D87Y | 1 (1.9) | 8 (33.3) | 3 (5.1) | 1.000 | |
| gyrA:pD87N | 33 (63.5) | 13 (54.2) | 41 (69.5) | 0.365 | |
| Colistin | mcr-1 | 0 (0.0) | 3 (12.5) | 0 (0.0) | 0.256 |
| Peroxide | sitABCD | 19 (36.5) | 7 (29.2) | 0 (0.0) | <0.001 * |
| Quaternary | qacE | 14 (26.2) | 4 (16.7) | 0 (0.0) | <0.001 * |
| Aldehyde | formA | 3 (5.8) | 3 (12.5) | 0 (0.0) | 0.035 * |
| Lincosamide | Inu(A) | 1 (1.9) | 2 (8.3) | 0 (0.0) | 1.000 |
| cmIA1 | 4 (7.7) | 0 (0.0) | 0 (0.0) | 0.256 | |
* Indicates significant difference.
Table 2.
Prevalence and statistical analysis of virulence-associated genes.
| Genes | Virulence-Associated Genes | Sources | p-Value | |||
|---|---|---|---|---|---|---|
| Meats | Human | |||||
| Chicken Meat, n = 52 (%) | Pork, n = 24 (%) | Urine, n = 59 (%) | ||||
| Adhesins | afaD | Adhesin Afa | 1 (1.9) | 0 (0.0) | 0 (0.0) | 0.563 |
| air | Enteroaggregative immunoglobulin repeat protein | 10 (19.2) | 5 (20.8) | 18 (30.5) | 0.149 | |
| iha | Adherence protein | 18 (34.6) | 3 (12.5) | 17 (28.8) | 0.88 | |
| Effector delivery system | aaiC | Chromosomal gene | 0 (0.0) | 1 (4.2) | 0 (0.0) | 0.563 |
| pic | Serin protease autotransporter | 2 (3.8) | 0 (0.0) | 3 (5.1) | 0.653 | |
| sat | Secreted autotransporter toxin | 0 (0.0) | 0 (0.0) | 15 (25.4) | <0.001 * | |
| tsh | Temperature-sensitive hemagglutinin | 13 (25.0) | 2 (8.3) | 5 (8.5) | 0.068 | |
| vat | Vacuolating autotransporter toxin | 2 (3.8) | 0 (0.0) | 6 (10.2) | 0.066 | |
| Exotoxin | astA | EAST-1 heat-stable toxin | 23 (44.2) | 10 (41.7) | 6 (10.2) | <0.001 * |
| cba | Colicin B | 8 (15.4) | 0 (0.0) | 0 (0.0) | 0.01 * | |
| cea | Colicin E1 | 6 (11.5) | 4 (16.7) | 0 (0.0) | 0.003 * | |
| celb | Endonuclease colicin E2 | 3 (5.8) | 1 (4.2) | 0 (0.0) | 0.131 | |
| cia | Colicin Ia | 9 (17.3) | 6 (25.0) | 0 (0.0) | <0.001 * | |
| cib | Colicin Ib | 2 (3.8) | 0 (0.0) | 0 (0.0) | 0.504 | |
| cma | Colicin M activity | 20 (38.5) | 2 (8.3) | 5 (8.5) | 0.004 * | |
| cnf1 | Cytotoxic necrotizing factor 1 | 0 (0.0) | 0 (0.0) | 5 (8.5) | 0.014 * | |
| hlyE | Hemolysin E | 1 (1.9) | 1 (4.2) | 0 (0.0) | 0.504 | |
| hlyF | Hemolysin F | 21 (40.4) | 6 (25.0) | 0 (0.0) | <0.001 * | |
| ompT | Outer membrane protease | 26 (50.0) | 13 (54.2) | 0 (0.0) | <0.001 * | |
| senB | Enterotoxin SenB/TieB | 0 (0.0) | 0 (0.0) | 10 (16.9) | <0.001 * | |
| Nutritional/ metabolic factor | chuA | Outer membrane hemin receptor | 14 (26.9) | 4 (16.7) | 0 (0.0) | <0.001 * |
| fyuA | Yersiniabactin siderophore receptor | 7 (13.5) | 3 (12.5) | 0 (0.0) | 0.003 * | |
| ireA | Iron-responsive element | 8 (15.4) | 4 (16.7) | 4 (6.8) | 0.178 | |
| iroN | Salmochelin siderophore receptor | 27 (51.9) | 5 (20.8) | 16 (27.1) | 0.071 | |
| irp2 | Yersiniabactin | 7 (13.5) | 3 (12.5) | 0 (0.0) | 0.003 * | |
| iucC | Aerobactin synthetase | 21 (40.4) | 3 (12.5) | 0 (0.0) | <0.001 * | |
| iutA | Aerobactin siderophore receptor | 20 (38.5) | 2 (8.3) | 0 (0.0) | <0.001 * | |
| sitA | Iron/manganese transport | 23 (44.2) | 8 (33.3) | 0 (0.0) | <0.001 * | |
| Capsule | kpsE | Capsule polysaccharide export inner membrane protein | 12 (23.1) | 3 (12.5) | 0 (0.0) | <0.001 * |
| kpsMII | Group capsular II | 7 (13.5) | 2 (8.3) | 0 (0.0) | 0.005 * | |
| kpsMII_K1 | Group capsular II | 3 (5.8) | 0 (0.0) | 0 (0.0) | 0.256 | |
| kpsMII_k5 | Group capsular II | 2 (3.8) | 1 (4.2) | 0 (0.0) | 0.256 | |
| neuC | Polysialic acid capsule biosynthesis protein | 3 (5.8) | 0 (0.0) | 0 (0.0) | 0.256 | |
| Invasion | ibeA | Invasion of brain endothelium | 1 (1.9) | 0 (0.0) | 0 (0.0) | 0.376 |
| Other | aap | Anti-aggregation protein | 0 (0.0) | 0 (0.0) | 1 (1.7) | 0.437 |
| capU | Hexosyltransferase homolog | 0 (0.0) | 1 (4.2) | 6 (10.2) | 0.043 * | |
| ccl | Cloacin | 0 (0.0) | 0 (0.0) | 1 (1.7) | 0.437 | |
| cvaC | Microcin C | 12 (23.1) | 3 (12.5) | 0 (0.0) | <0.001 * | |
| eatA | Enterotoxigenic E. coli (ETEC) autotransporter A | 0 (0.0) | 0 (0.0) | 1 (1.7) | 0.437 | |
| eilA | Salmonella HilA homolog | 18 (34.6) | 9 (37.5) | 20 (33.9) | 0.858 | |
| estC | Putative type I secretion outer membrane protein | 17 (32.7) | 4 (16.7) | 0 (0.0) | <0.001 * | |
| gad | Glutamate decarboxylase | 33 (63.5) | 17 (70.7) | 57 (96.6) | <0.001 * | |
| hra | Heat-resistant agglutinin | 8 (15.4) | 6 (25.0) | 0 (0.0) | <0.001 * | |
| IpfA | Long polar fimbriae | 23 (44.2) | 15 (62.5) | 27 (45.8) | 0.625 | |
| iss | Increased serum survival | 41 (78.8) | 17 (70.8) | 43 (72.9) | 0.648 | |
| katP | Plasmid-encoded catalase peroxidase | 0 (0.0) | 1 (4.2) | 0 (0.0) | 0.563 | |
| mchB | ABC transporter protein MchB | 0 (0.0) | 0 (0.0) | 2 (3.4) | 0.189 | |
| mchC | ABC transporter protein MchC | 0 (0.0) | 0 (0.0) | 3 (5.1) | 0.081 | |
| mchF | ABC transporter protein MchF | 16 (30.8) | 4 (16.7) | 13 (22.0) | 0.566 | |
| mcmA | Microcin M part of colicin H | 0 (0.0) | 1 (4.2) | 2 (3.4) | 0.581 | |
| nfaE | Nonfimbrial adhesin | 0 (0.0) | 0 (0.0) | 6 (10.2) | 0.006 * | |
| papA_F19 | P fimbriae A | 1 (1.9) | 0 (0.0) | 0 (0.0) | 0.563 | |
| papA_F20 | P fimbriae A | 1 (1.9) | 1 (4.2) | 0 (0.0) | 0.504 | |
| papC | P fimbriae C | 8 (15.4) | 3 (12.5) | 0 (0.0) | 0.002 * | |
| terC | Tellurium ion resistance protein | 28 (53.8) | 15 (62.5) | 0 (0.0) | <0.001 * | |
| traT | Outer membrane lipoprotein | 24 (46.2) | 12 (50.0) | 0 (0.0) | <0.001 * | |
| yfcV | Fimbrial protein | 4 (7.7) | 2 (8.3) | 0 (0.0) | 0.035 * | |
* Indicates significant difference.
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Soncini, J.G.M.; Koga, V.L.; Fuga, B.; Tano, Z.N.; Nakazato, G.; Kobayashi, R.K.T.; Lincopan, N.; Vespero, E.C. Molecular Analysis of Escherichia coli and Correlations Between Phylogroups and Sequence Types from Different Sources. Microorganisms 2024, 12, 2645. https://doi.org/10.3390/microorganisms12122645
AMA Style
Soncini JGM, Koga VL, Fuga B, Tano ZN, Nakazato G, Kobayashi RKT, Lincopan N, Vespero EC. Molecular Analysis of Escherichia coli and Correlations Between Phylogroups and Sequence Types from Different Sources. Microorganisms. 2024; 12(12):2645. https://doi.org/10.3390/microorganisms12122645
Chicago/Turabian StyleSoncini, João Gabriel Material, Vanessa Lumi Koga, Bruna Fuga, Zuleica Naomi Tano, Gerson Nakazato, Renata Katsuko Takayama Kobayashi, Nilton Lincopan, and Eliana Carolina Vespero. 2024. "Molecular Analysis of Escherichia coli and Correlations Between Phylogroups and Sequence Types from Different Sources" Microorganisms 12, no. 12: 2645. https://doi.org/10.3390/microorganisms12122645
APA StyleSoncini, J. G. M., Koga, V. L., Fuga, B., Tano, Z. N., Nakazato, G., Kobayashi, R. K. T., Lincopan, N., & Vespero, E. C. (2024). Molecular Analysis of Escherichia coli and Correlations Between Phylogroups and Sequence Types from Different Sources. Microorganisms, 12(12), 2645. https://doi.org/10.3390/microorganisms12122645
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