Whole genome sequencing of ESBL-producing Escherichia coli isolated from patients, farm waste and canals in Thailand

Runcharoen, Chakkaphan; Raven, Kathy E.; Reuter, Sandra; Kallonen, Teemu; Paksanont, Suporn; Thammachote, Jeeranan; Anun, Suthatip; Blane, Beth; Parkhill, Julian; Peacock, Sharon J.; Chantratita, Narisara

doi:10.1186/s13073-017-0471-8

Cited by 88 publications

(59 citation statements)

References 63 publications

(56 reference statements)

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“…We used 1681 strains from four large-scale clinical and environmental E. coli collections, with available data on the year of isolation, drug susceptibility phenotypes, and whole genome sequence [15, 16]. Furthermore, we collected 255 strains from a range of ecological niches: hospital sewage and water treatment plant from Sweden (Carl-Fredrik Flach); human clinical isolates isolated in Pakistan, Syria, Sweden and USA (Culture Collection University of Gothenburg); a collection of strains producing extended-spectrum β-lactamases isolated in Sweden (Christina Åhrén) and environmental samples from Belgium (Jan Michiels).…”

Section: Methodsmentioning

confidence: 99%

Precise prediction of antibiotic resistance in Escherichia coli from full genome sequences

Moradigaravand

Palm

Farewell

et al. 2018

Preprint

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The emergence of microbial antibiotic resistance is a global health threat. In clinical settings, the key to controlling spread of resistant strains is accurate and rapid detection. As traditional culture-based methods are time consuming, genetic approaches have recently been developed for this task. The diagnosis is typically made by measuring a few known determinants previously identified from whole genome sequencing, and thus is restricted to existing information on biological mechanisms. To overcome this limitation, we employed machine learning models to predict resistance to 11 compounds across four classes of antibiotics from existing and novel whole genome sequences of 1936 E. coli strains. We considered a range of methods, and examined population structure, isolation year, gene content, and polymorphism information as predictors. Gradient boosted decision trees consistently outperformed alternative models with an average F1 score of 0.88 on held-out data (range 0.66-0.96). While the best models most frequently employed all inputs, an average F1 score of 0.73 could be obtained using population structure information alone. Single nucleotide variation data were less useful, and failed to improve prediction for ten out of 11 antibiotics. These results demonstrate that antibiotic resistance in E. coli can be accurately predicted from whole genome sequences without a priori knowledge of mechanisms, and that both genomic and epidemiological data are informative. This paves way to integrating machine learning approaches into diagnostic tools in the clinic.SummaryOne of the major health threats of 21st century is emergence of antibiotic resistance. To manage its economic impact, efforts are made to develop novel diagnostic tools that rapidly detect resistant strains in clinical settings. In our study, we employed a range machine learning tools to predict antibiotic resistance from whole genome sequencing data for E. coli. We used the presence or absence of genes, population structure and isolation year of isolates as predictors, and could attain average precision of 0.93 and recall of 0.83, without prior knowledge about the causal mechanisms. These results demonstrate the potential application of machine learning methods as a diagnostic tool in healthcare settings.

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Section: Methodsmentioning

confidence: 99%

Precise prediction of antibiotic resistance in Escherichia coli from full genome sequences

Moradigaravand

Palm

Farewell

et al. 2018

Preprint

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“…ST131 is a dominant international clinical clone. ST405 has been associated internationally with the carriage of ESBLs and ST410 has been reported worldwide in extra intestinal pathogens associated with resistance to fluoroquinolones, third-generation cephalosporins and carbapenems [50,51]. The distribution of the different sequence types and the plasmid replicon types of the ESBL isolates especially the predominant ones across the three hospitals suggests a probable clonal spread of the ESBL strains both intra and inter-hospital.…”

Section: Plos Onementioning

confidence: 99%

Whole genome sequencing of extended-spectrum β-lactamase genes in Enterobacteriaceae isolates from Nigeria

et al. 2020

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Extended Spectrum β-lactamase (ESBL)-producing Enterobacteriaceae are of major concern as they are implicated in multidrug resistant nosocomial infections. They are listed on a recently published global priority list of antibiotic-resistant bacteria by the World Health Organization which raises concern in both healthcare and community settings. This study aimed at determining the frequency of ESBL genes in multidrug resistant human clinical Enterobacteriaceae isolates from Edo state Nigeria and to characterize the resistance mechanisms using whole genome sequencing. A total of 217 consecutive clinical isolates of Enterobacteriaceae, selection based on inclusion criteria, were collected from March-May 2015 from three medical microbiology laboratories of hospitals in Edo state Nigeria. All isolates were analyzed using matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry. Antibiotic susceptibility testing was performed by Kirby-Bauer method and minimum inhibitory concentration (MIC) determination by E-test method. Double disc synergy test was used to screen for the production of ESBL. Whole genome sequencing (WGS) was performed for isolate characterization and identification of resistance determinants. Out of 217 consecutive clinical Enterobacteriaceae isolates, 148 (68.2%) were multi-drug resistant. Of these multi-drug resistant isolates, 60 (40.5%) were positive for the ESBL phenotypic test and carried ESBL genes. CTX-M-15 was the predominant ESBL found, among 93.3% (n = 56/60). Thirty-two plasmid incompatibility groups and 28 known and two new sequence types were identified among the ESBL isolates. The high occurrence of CTX-M-15 with associated resistant determinants in multidrug resistant Enterobacteriaceae harboring different plasmid incompatibility groups and sequence types calls for the need of continuous monitoring of this resistance threat to reduce its public health impact. To our knowledge, this study presents the first genomic characterization of ESBL production mediated by bla CTX-M-15 in human clinical isolates of Enterobacter hormaechei, Citrobacter werkmanii and Atlantibacter hermannii from Nigeria.

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“…Over the past two decades, there has been a significant number of infections caused by bacteria expressing extendedspectrum-β-lactamase (ESBL) and carbapenemases (Logan and Weinstein, 2017). In particular, ESBL isolates have been found in humans (Pitout and Laupland, 2008), animals, the environment (water and soil) (Runcharoen et al, 2017), meat and even vegetables (Yang et al, 2019). ESBL are becoming more common because this phenotype is being selected for by the use and exposure to β-lactams, especially the cephalosporins.…”

Section: Introductionmentioning

confidence: 99%

Increasing Prevalence of ESBL-Producing Multidrug Resistance Escherichia coli From Diseased Pets in Beijing, China From 2012 to 2017

et al. 2019

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We investigated antimicrobial resistance trends and characteristics of ESBL-producing Escherichia coli isolates from pets and whether this correlates with antibiotic usage in the clinic. Clinical samples containing E. coli from diseased cats and dogs were screened for antibiotic sensitivity and associated genotypic features. We identified 127 E. coli isolates from 1886 samples from dogs (n = 1565) and cats (n = 321) with the majority from urinary tract infections (n = 108, 85%). High rates of resistance were observed for β-lactams and fluoroquinolones and resistance to > 3 antibiotic classes (MDR) increased from 67% in 2012 to 75% in 2017 (P < 0.0001). This was especially true for strains resistant to 6-9 antibiotics that increased from 26.67 to 60.71%. Increased rates in β-lactam use for clinical treatment accompanied these increasing resistance rates. Accordingly, the most frequently encountered subtypes were bla CTX-M (n = 44, 34.65%), bla CTX-M-65 (n = 19) and bla CTX-M-15 (n = 18) and qnrB (n = 119, 93.70%). The bla CTX-M-isolates possessed 36 unique pulsed field electrophoretic types (PFGEs) and 28 different sequence types (STs) in ST405 (7, 15.9%), ST131 (3, 6.8%), ST73, ST101, ST372, and ST827 (2, 4.5% each) were the most prevalent. This data demonstrated a high level of diversity for the bla CTX-M-positive E. coli isolates. Additionally, bla NDM-5 was detected in three isolates (n = 3, 2.36%), comprised of two ST101 and one ST405 isolates, and mcr-1 was also observed in three colistin-resistant E. coli with three different STs (ST6316, ST405, and ST46). Our study demonstrates an increasing trend in MDR and ESBL-producing E. coli and this correlated with β-lactam antibiotic usage for treatment of these animals. This data indicates that there is significant risk for the spread of resistant bacteria from pets to humans and antibiotic use for pets should be more strictly regulated.

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Whole genome sequencing of ESBL-producing Escherichia coli isolated from patients, farm waste and canals in Thailand

Cited by 88 publications

References 63 publications

Precise prediction of antibiotic resistance in Escherichia coli from full genome sequences

Precise prediction of antibiotic resistance in Escherichia coli from full genome sequences

Whole genome sequencing of extended-spectrum β-lactamase genes in Enterobacteriaceae isolates from Nigeria

Increasing Prevalence of ESBL-Producing Multidrug Resistance Escherichia coli From Diseased Pets in Beijing, China From 2012 to 2017

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