Dataset Information

Using Genetic Distance from Archived Samples for the Prediction of Antibiotic Resistance in Escherichia coli.

ABSTRACT: The rising rates of antibiotic resistance increasingly compromise empirical treatment. Knowing the antibiotic susceptibility of a pathogen's close genetic relative(s) may improve empirical antibiotic selection. Using genomic and phenotypic data for Escherichia coli isolates from three separate clinically derived databases, we evaluated multiple genomic methods and statistical models for predicting antibiotic susceptibility, focusing on potentially rapidly available information, such as lineage or genetic distance from archived isolates. We applied these methods to derive and validate the prediction of antibiotic susceptibility to common antibiotics. We evaluated 968 separate episodes of suspected and confirmed infection with Escherichia coli from three geographically and temporally separated databases in Ontario, Canada, from 2010 to 2018. Across all approaches, model performance (area under the curve [AUC]) ranges for predicting antibiotic susceptibility were the greatest for ciprofloxacin (AUC, 0.76 to 0.97) and the lowest for trimethoprim-sulfamethoxazole (AUC, 0.51 to 0.80). When a model predicted that an isolate was susceptible, the resulting (posttest) probabilities of susceptibility were sufficient to warrant empirical therapy for most antibiotics (mean, 92%). An approach combining multiple models could permit the use of narrower-spectrum oral agents in 2 out of every 3 patients while maintaining high treatment adequacy (?90%). Methods based on genetic relatedness to archived samples of E. coli could be used to predict antibiotic resistance and improve antibiotic selection.

SUBMITTER: MacFadden DR

PROVIDER: S-EPMC7179619 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Using Genetic Distance from Archived Samples for the Prediction of Antibiotic Resistance in <i>Escherichia coli</i>.

MacFadden Derek R DR Coburn Bryan B Břinda Karel K Corbeil Antoine A Daneman Nick N Fisman David D Lee Robyn S RS Lipsitch Marc M McGeer Allison A Melano Roberto G RG Mubareka Samira S Hanage William P WP

Antimicrobial agents and chemotherapy 20200421 5

The rising rates of antibiotic resistance increasingly compromise empirical treatment. Knowing the antibiotic susceptibility of a pathogen's close genetic relative(s) may improve empirical antibiotic selection. Using genomic and phenotypic data for <i>Escherichia coli</i> isolates from three separate clinically derived databases, we evaluated multiple genomic methods and statistical models for predicting antibiotic susceptibility, focusing on potentially rapidly available information, such as li ...[more]

PMID: 32152083

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Project description:A 7.8-kbp fragment of chromosomal DNA from a region controlling multiple antibiotic resistance (Mar) in Escherichia coli has been sequenced. Within the fragment is a potential divergent promoter region including marO, which contains two pairs of direct repeats, suggesting possible operator-regulatory sites. To the left of marO (region I) are one or two transcriptional units with three putative open reading frames (ORFs) encoding 64, 157, and 70 amino acids. To the right (region II) is a transcriptional unit containing three putative ORFs (ORF125/144, ORF129, and ORF72). Of six independent Mar mutants, four had mutations within the ORF encoding the first putative protein (ORF125/144) downstream of marO, including three different single-point mutations and an IS2 insertion. One of the other mutations occurred in marO (20-bp duplication), and the other occurred in a site in marO or ORF144 (a 1-bp change). All six mutations led to increased transcription of the region II transcript. High-copy-number plasmids containing marO and the adjacent ORF125/144 region from a wild-type source but not from a Mar mutant reduced the antibiotic resistance of a Mar mutant to levels comparable to those of wild-type cells. High-copy-number plasmids containing wild-type marO alone caused an increase in resistance to tetracycline, chloramphenicol, and norfloxacin in a wild-type strain. The nature of the Mar mutations and the results of the complementation studies suggest that ORF125/144 encodes a repressor (designated MarR) which acts at marO. The second ORF (ORF129), designated marA, would encode a protein, MarA, whose sequence shows strong similarity to those of a family of positive transcriptional regulators. A Tn5 insertion in marA inactivated the multiresistance phenotype of Mar mutants. The function of ORF72, designated marB, encoding the third putative protein in the operon, and that of other ORFs detected within the 7.8-kb fragment have not yet been determined.

Project description:To investigate the distribution of urine isolates and antibiotic resistance patterns in the predominant uropathogen Escherichia coli in migrant and non-migrant individuals. We linked a cohort consisting of all migrants obtaining residence as refugees or family-reunited migrants in Denmark between January 1993 and December 2015 to hospital urine samples examined from January 2000 to December 2015 at the Department of Microbiology, University Hospital Hvidovre, Denmark. Samples from non-migrant individuals, Danish-born from Danish parents, were included as comparison. Analysis was carried out using multivariate logistic regression. There were 14 561 first-time urine samples included, with E. coli being the most prevalent bacterial pathogen. Of the identified isolates, 4686/11 737 were E. coli among non-migrants and 1032/2824 among migrants.Sulfamethoxazol-Trimethoprim (SXT) resistance was found in 34.3% (350/1020) of E. coli isolates among migrants and 23.2% (1070/4619) among non-migrant patients [odds ratio (OR) 1.73, 95% confidence interval (CI): 1.47-2.03]. Ciprofloxacin resistance was found in 5.8% (36/618) of isolates among migrants and 2.2% (67/3092) among non-migrants (OR 2.20, 95% CI: 1.37-3.53). Gentamicin (GEN) resistance was seen in 10.8% (61/565) and 4.7% (110/2328) of isolates (OR 2.33, 95% CI:1.63-3.34), Cefuroxime resistance in 8.5% (87/1019) and 3.4% (158/4618) (OR 2.40, 95% CI:1.77-3.24), Ampicillin (AMP) resistance in 51.4% and 40.8% (OR 1.65, 95% CI: 1.42-1.92) and Piperacillin-Tazobactam resistance in 6.9% (30/432) and 4.2% (65/1532) for migrant and non-migrant patients, respectively. When stratifying according to migrant status, family-reunited had higher odds of resistance than refugees for SXT, GEN and AMP. Prevalence of antibiotic resistance was significantly higher in E. coli isolates among migrants, both refugees and family-reunited, than non-migrant patients. Differences could not be explained by comorbidity or income. The results emphasize the importance of urine sample testing in both local-born and migrants before antibiotic start-up and point to the benefit of considering migration to secure individual treatment and equal health outcomes.

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Project description:Background and aimRaw milk is considered an essential source of nutrition during all stages of human life because it offers a valuable supply of protein and minerals. Importantly, milk is considered a good media for the growth and contamination of many pathogenic bacteria, especially food-borne pathogens such as Escherichia coli. Thus, the objective of this study was to characterize E. coli and detect its virulence factors and antibiotic resistance from raw milk samples.Materials and methodsRaw milk samples (n=100) were collected from different localities in Qena, Egypt, and investigated for the presence of E. coli using different biochemical tests, IMViC tests, serotyping to detect somatic antigen type, and molecularly by polymerase chain reaction (PCR) tests. The presence of different virulence and antimicrobial genes (hly, eae, stx1, stx2, blaTEM, tetA(A), and tetB genes) in E. coli isolates was evaluated using PCR.ResultsThe results demonstrated that 10 out of 100 milk samples were contaminated with E. coli. Depending on serology, the isolates were classified as O114 (one isolate), O27 (two isolates), O111 (one isolate), O125 (two isolates), and untypeable (five isolates) E. coli. The sequencing of partially amplified 16S rRNA of the untypeable isolates resulted in one isolate, which was initially misidentified as untypeable E. coli but later proved as Enterobacter hormaechei. Moreover, antibacterial susceptibility analysis revealed that nearly all isolates were resistant to more than 3 families of antibiotics, particularly to b-lactams, clindamycin, and rifampin. PCR results demonstrated that all E. coli isolates showed an accurate amplicon for the blaTEM and tetA(A) genes, four isolates harbored eae gene, other four harbored tetB gene, and only one isolate exhibited a positive stx2 gene.ConclusionOur study explored vital methods for identifying E. coli as a harmful pathogen of raw milk using 16S rRNA sequencing, phylogenetic analysis, and detection of virulence factors and antibiotic-resistant genes.

Project description:BackgroundThe prevalence of antimicrobial resistance (AMR) among Gram-negative bacteria is alarmingly high. Reintroduction of colistin as last resort treatment in the infections caused by drug-resistant Gram-negative bacteria has led to the emergence and spread of colistin resistance. This study was designed to determine the prevalence of drug-resistance among beta-lactamase-producing strains of Escherichia coli and Klebsiella pneumoniae, isolated from the clinical specimens received at a tertiary care centre of Kathmandu, Nepal during the period of March to August, 2019.MethodsA total of 3216 different clinical samples were processed in the Microbiology laboratory of Kathmandu Model Hospital. Gram-negative isolates (E. coli and K. pneumoniae) were processed for antimicrobial susceptibility test (AST) by using modified Kirby-Bauer disc diffusion method. Drug-resistant isolates were further screened for extended-spectrum beta-lactamase (ESBL), metallo-beta-lactamase (MBL), carbapenemase and K. pneumoniae carbapenemase (KPC) production tests. All the suspected enzyme producers were processed for phenotypic confirmatory tests. Colistin resistance was determined by minimum inhibitory concentration (MIC) using agar dilution method. Colistin resistant strains were further screened for plasmid-mediated mcr-1 gene using conventional polymerase chain reaction (PCR).ResultsAmong the total samples processed, 16.4% (529/3216) samples had bacterial growth. A total of 583 bacterial isolates were recovered from 529 clinical samples. Among the total isolates, 78.0% (455/583) isolates were Gram-negative bacteria. The most predominant isolate among Gram-negatives was E. coli (66.4%; 302/455) and K. pneumoniae isolates were 9% (41/455). In AST, colistin, polymyxin B and tigecycline were the most effective antibiotics. The overall prevalence of multidrug-resistance (MDR) among both of the isolates was 58.0% (199/343). In the ESBL testing, 41.1% (n = 141) isolates were confirmed as ESBL-producers. The prevalence of ESBL-producing E. coli was 43% (130/302) whereas that of K. pneumoniae was 26.8% (11/41). Similarly, 12.5% (43/343) of the total isolates, 10.9% (33/302) of E. coli and 24.3% of (10/41) K. pneumoniae were resistant to carbapenem. Among 43 carbapenem resistant isolates, 30.2% (13/43) and 60.5% (26/43) were KPC and MBL-producers respectively. KPC-producers isolates of E. coli and K. pneumoniae were 33.3% (11/33) and 20% (2/10) respectively. Similarly, 63.6% (21/33) of the E. coli and 50% (5/10) of the K. pneumoniae were MBL-producers. In MIC assay, 2.2% (4/179) of E. coli and 10% (2/20) of K. pneumoniae isolates were confirmed as colistin resistant (MIC ≥ 4 µg/ml). Overall, the prevalence of colistin resistance was 3.1% (6/199) and acquisition of mcr-1 was 16.6% (3/18) among the E. coli isolates.ConclusionHigh prevalence of drug-resistance in our study is indicative of a deteriorating situation of AMR. Moreover, significant prevalence of resistant enzymes in our study reinforces their roles in the emergence of drug resistance. Resistance to last resort drug (colistin) and the isolation of mcr-1 indicate further urgency in infection management. Therefore, extensive surveillance, formulation and implementation of effective policies, augmentation of diagnostic facilities and incorporation of antibiotic stewardship programs can be some remedies to cope with this global crisis.

Dataset Information

Using Genetic Distance from Archived Samples for the Prediction of Antibiotic Resistance in Escherichia coli.

Publications

Using Genetic Distance from Archived Samples for the Prediction of Antibiotic Resistance in <i>Escherichia coli</i>.

Similar Datasets

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