Use of whole genome sequencing of commensal Escherichia coli in pigs for antimicrobial resistance surveillance, United Kingdom, 2018.
ABSTRACT: BackgroundSurveillance of commensal Escherichia coli, a possible reservoir of antimicrobial resistance (AMR) genes, is important as they pose a risk to human and animal health. Most surveillance activities rely on phenotypic characterisation, but whole genome sequencing (WGS) presents an alternative.AimIn this retrospective study, we tested 515 E. coli isolated from pigs to evaluate the use of WGS to predict resistance phenotype.MethodsMinimum inhibitory concentration (MIC) was determined for nine antimicrobials of clinical and veterinary importance. Deviation from wild-type, fully-susceptible MIC was assessed using European Committee on Antimicrobial Susceptibility Testing (EUCAST) epidemiological cut-off (ECOFF) values. Presence of AMR genes and mutations were determined using APHA SeqFinder. Statistical two-by-two table analysis and Cohen's kappa (k) test were applied to assess genotype and phenotype concordance.ResultsOverall, correlation of WGS with susceptibility to the nine antimicrobials was 98.9% for test specificity, and 97.5% for the positive predictive value of a test. The overall kappa score (k?=?0.914) indicated AMR gene presence was highly predictive of reduced susceptibility and showed excellent correlation with MIC. However, there was variation for each antimicrobial; five showed excellent correlation; four very good and one moderate. Suggested ECOFF adjustments increased concordance between genotypic data and kappa values for four antimicrobials.ConclusionWGS is a powerful tool for accurately predicting AMR that can be used for national surveillance purposes. Additionally, it can detect resistance genes from a wider panel of antimicrobials whose phenotypes are currently not monitored but may be of importance in the future.
Project description:The aim of this study was to evaluate the correlation between antimicrobial resistance (AMR) profiles of 96 clinical isolates of Actinobacillus pleuropneumoniae, an important porcine respiratory pathogen, and the identification of AMR genes in whole genome sequence (wgs) data. Susceptibility of the isolates to nine antimicrobial agents (ampicillin, enrofloxacin, erythromycin, florfenicol, sulfisoxazole, tetracycline, tilmicosin, trimethoprim, and tylosin) was determined by agar dilution susceptibility test. Except for the macrolides tested, elevated MICs were highly correlated to the presence of AMR genes identified in wgs data using ResFinder or BLASTn. Of the isolates tested, 57% were resistant to tetracycline [MIC ? 4 mg/L; 94.8% with either tet(B) or tet(H)]; 48% to sulfisoxazole (MIC ? 256 mg/L or DD = 6; 100% with sul2), 20% to ampicillin (MIC ? 4 mg/L; 100% with blaROB-1), 17% to trimethoprim (MIC ? 32 mg/L; 100% with dfrA14), and 6% to enrofloxacin (MIC ? 0.25 mg/L; 100% with GyrAS83F). Only 33% of the isolates did not have detectable AMR genes, and were sensitive by MICs for the antimicrobial agents tested. Although 23 isolates had MIC ? 32 mg/L for tylosin, all isolates had MIC ? 16 mg/L for both erythromycin and tilmicosin, and no macrolide resistance genes or known point mutations were detected. Other than the GyrAS83F mutation, the AMR genes detected were mapped to potential plasmids. In addition to presence on plasmid(s), the tet(B) gene was also found chromosomally either as part of a 56 kb integrative conjugative element (ICEApl1) in 21, or as part of a Tn7 insertion in 15 isolates. Our results indicate that, with the exception of macrolides, wgs data can be used to accurately predict resistance of A. pleuropneumoniae to the tested antimicrobial agents and provides added value for routine surveillance.
Project description:Antimicrobial resistance in Streptococcus suis, a global zoonotic pathogen of pigs, has been mostly studied only in diseased animals using surveys that have not evaluated changes over time. We compared patterns of resistance between S. suis isolates from clinical cases of disease (CC) and non-clinical case (NCC) pigs in England, collected over two discrete periods, 2009-2011 and 2013-2014. Minimum inhibitory concentrations (MIC) of 17 antimicrobials (nine classes) were determined on 405 S. suis isolates categorised by sampling period and disease association to assess changes in resistance over time and association with disease. First, isolates were characterized as resistant or susceptible using published clinical breakpoints. Second, epidemiological cut-offs (ECOFF) were derived from MIC values, and isolates classified as wild type (WT) below the ECOFF and non-wild type (NWT) above the ECOFF. Finally, isolate subsets were analysed for shifts in MIC distribution. NCC isolates were more resistant than CC isolates to cephalosporins, penams, pleuromutilins, potentiated sulphonamides and tetracyclines in both study periods. Resistance levels among CC isolates increased in 2013-2014 relative to 2009-2011 for antimicrobials including aminoglycosides, cephalosporins, fluoroquinolones, pleuromutilins, potentiated sulphonamides and tetracyclines. The prevalence of isolates categorised as NWT for five or more classes of antimicrobials was greater among NCC than CC isolates for both time periods, and increased with time. This study used standardised methods to identify significant shifts in antimicrobial resistance phenotypes of S. suis isolated from pigs in England, not only over time but also between isolates from known clinical cases or disease-free pigs.
Project description:Antimicrobial susceptibility testing (AST) is increasingly needed to guide the Helicobacter pylori (H. pylori) treatment but remains laborious and unavailable in most African countries. To assess the clinical relevance of bacterial whole genome sequencing (WGS)-based methods for predicting drug susceptibility in African H. pylori, 102 strains isolated from the Democratic Republic of Congo were subjected to the phenotypic AST and next-generation sequencing (NGS). WGS was used to screen for the occurrence of genotypes encoding antimicrobial resistance (AMR). We noted the broad-spectrum AMR of H. pylori (rates from 23.5 to 90.0%). A WGS-based method validated for variant discovery in AMR-related genes (discovery rates of 100%) helped in identifying mutations of key genes statistically related to the phenotypic AMR. These included mutations often reported in Western and Asian populations and, interestingly, several putative AMR-related new genotypes in the pbp1A (e.g., T558S, F366L), gyrA (e.g., A92T, A129T), gyrB (e.g., R579C), and rdxA (e.g., R131_K166del) genes. WGS showed high performance for predicting AST phenotypes, especially for amoxicillin, clarithromycin, and levofloxacin (Youden's index and Cohen's Kappa > 0.80). Therefore, WGS is an accurate alternative to the phenotypic AST that provides substantial decision-making information for public health policy makers and clinicians in Africa, while providing insight into AMR mechanisms for researchers.
Project description:OBJECTIVES:Antimicrobial resistance (AMR) in Neisseria gonorrhoeae, compromising gonorrhoea treatment, is a threat to reproductive health globally. South-East and East Asia have been major sources of emergence and subsequent international spread of AMR gonococcal strains during recent decades. We investigated gonococcal isolates from 2011 and 2015-16 in Vietnam using AMR testing, WGS and detection of AMR determinants. METHODS:Two hundred and twenty-nine gonococcal isolates cultured in 2015-16 (n?=?121) and 2011 (n?=?108) in Vietnam were examined. AMR testing was performed using Etest and WGS with Illumina MiSeq. RESULTS:Resistance among the 2015-16 isolates was as follows: ciprofloxacin, 100%; tetracycline, 79%; benzylpenicillin, 50%; cefixime, 15%; ceftriaxone, 1%; spectinomycin, 0%; and 5% were non-WT to azithromycin. Eighteen (15%) isolates were MDR. The MIC range for gentamicin was 2-8?mg/L. Among the 2015-16 isolates, 27% (n?=?33) contained a mosaic penA allele, while no isolates had a mosaic penA allele in 2011. Phylogenomic analysis revealed introduction after 2011 of two mosaic penA-containing clones (penA-10.001 and penA-34.001), which were related to cefixime-resistant strains spreading in Japan and Europe, and a minor clade (eight isolates) relatively similar to the XDR strain WHO Q. CONCLUSIONS:From 2011 to 2015-16, resistance in gonococci from Vietnam increased to all currently and previously used antimicrobials except ceftriaxone, spectinomycin and tetracycline. Two mosaic penA-containing clones were introduced after 2011, explaining the increased cefixime resistance. Significantly increased AMR surveillance, antimicrobial stewardship and use of WGS for molecular epidemiology and AMR prediction for gonococcal isolates in Vietnam and other Asian countries are crucial.
Project description:Surveillance of antimicrobial resistance (AMR) in non-typhoidal Salmonella enterica (NTS), is essential for monitoring transmission of resistance from the food chain to humans, and for establishing effective treatment protocols. We evaluated the prediction of phenotypic resistance in NTS from genotypic profiles derived from whole genome sequencing (WGS). Genes and chromosomal mutations responsible for phenotypic resistance were sought in WGS data from 3,491 NTS isolates received by Public Health England's Gastrointestinal Bacteria Reference Unit between April 2014 and March 2015. Inferred genotypic AMR profiles were compared with phenotypic susceptibilities determined for fifteen antimicrobials using EUCAST guidelines. Discrepancies between phenotypic and genotypic profiles for one or more antimicrobials were detected for 76 isolates (2.18%) although only 88/52,365 (0.17%) isolate/antimicrobial combinations were discordant. Of the discrepant results, the largest number were associated with streptomycin (67.05%, n = 59). Pan-susceptibility was observed in 2,190 isolates (62.73%). Overall, resistance to tetracyclines was most common (26.27% of isolates, n = 917) followed by sulphonamides (23.72%, n = 828) and ampicillin (21.43%, n = 748). Multidrug resistance (MDR), i.e., resistance to three or more antimicrobial classes, was detected in 848 isolates (24.29%) with resistance to ampicillin, streptomycin, sulphonamides and tetracyclines being the most common MDR profile (n = 231; 27.24%). For isolates with this profile, all but one were S. Typhimurium and 94.81% (n = 219) had the resistance determinants blaTEM-1,strA-strB, sul2 and tet(A). Extended-spectrum ?-lactamase genes were identified in 41 isolates (1.17%) and multiple mutations in chromosomal genes associated with ciprofloxacin resistance in 82 isolates (2.35%). This study showed that WGS is suitable as a rapid means of determining AMR patterns of NTS for public health surveillance.
Project description:Antimicrobial resistance (AMR) in Mycoplasma bovis has been previously associated with topoisomerase and ribosomal gene mutations rather than specific resistance-conferring genes. Using whole genome sequencing (WGS) to identify potential new AMR mechanisms for M. bovis, it was found that a 2019 clinical isolate with high MIC (2019-043682) for fluoroquinolones, macrolides, lincosamides, pleuromutilins and tetracyclines had a new core genome multilocus sequencing (cgMLST) type (ST10-like) and 91% sequence similarity to the published genome of M. bovis PG45. Closely related to PG45, a 1982 isolate (1982-M6152) shared the same cgMLST type (ST17), 97.2% sequence similarity and low MIC results. Known and potential AMR- associated genetic events were identified through multiple sequence alignment of the three genomes. Isolate 2019-043682 had 507 genes with non-synonymous mutations (NSMs) and 67 genes disrupted. Isolate 1982-M6152 had 81 NSMs and 20 disruptions. Using functional roles and known mechanisms of antimicrobials, a 55 gene subset was assessed for AMR potential. Seventeen were previously identified from other bacteria as sites of AMR mutation, 38 shared similar functions to them, and 11 contained gene-disrupting mutations. This study indicated that M. bovis may obtain high AMR characteristics by mutating or disrupting other functional genes, in addition to topoisomerases and ribosomal genes.
Project description:Background:Tracking the spread of antimicrobial-resistant Neisseria gonorrhoeae is a major priority for national surveillance programmes. Objectives:We investigate whether WGS and simultaneous analysis of multiple resistance determinants can be used to predict antimicrobial susceptibilities to the level of MICs in N. gonorrhoeae. Methods:WGS was used to identify previously reported potential resistance determinants in 681 N. gonorrhoeae isolates, from England, the USA and Canada, with phenotypes for cefixime, penicillin, azithromycin, ciprofloxacin and tetracycline determined as part of national surveillance programmes. Multivariate linear regression models were used to identify genetic predictors of MIC. Model performance was assessed using leave-one-out cross-validation. Results:Overall 1785/3380 (53%) MIC values were predicted to the nearest doubling dilution and 3147 (93%) within ±1 doubling dilution and 3314 (98%) within ±2 doubling dilutions. MIC prediction performance was similar across the five antimicrobials tested. Prediction models included the majority of previously reported resistance determinants. Applying EUCAST breakpoints to MIC predictions, the overall very major error (VME; phenotypically resistant, WGS-prediction susceptible) rate was 21/1577 (1.3%, 95% CI 0.8%-2.0%) and the major error (ME; phenotypically susceptible, WGS-prediction resistant) rate was 20/1186 (1.7%, 1.0%-2.6%). VME rates met regulatory thresholds for all antimicrobials except cefixime and ME rates for all antimicrobials except tetracycline. Country of testing was a strongly significant predictor of MIC for all five antimicrobials. Conclusions:We demonstrate a WGS-based MIC prediction approach that allows reliable MIC prediction for five gonorrhoea antimicrobials. Our approach should allow reasonably precise prediction of MICs for a range of bacterial species.
Project description:Whole-genome sequencing (WGS) has transformed our understanding of antimicrobial resistance, helping us to better identify and track the genetic mechanisms underlying phenotypic resistance. Previous studies have demonstrated high correlations between phenotypic resistance and the presence of known resistance determinants. However, there has never been a large-scale assessment of how well resistance genotypes correspond to specific MICs. We performed antimicrobial susceptibility testing and WGS of 1,738 nontyphoidal Salmonella strains to correlate over 20,000 MICs with resistance determinants. Using these data, we established what we term genotypic cutoff values (GCVs) for 13 antimicrobials against Salmonella For the drugs we tested, we define a GCV as the highest MIC of isolates in a population devoid of known acquired resistance mechanisms. This definition of GCV is distinct from epidemiological cutoff values (ECVs or ECOFFs), which currently differentiate wild-type from non-wild-type strains based on MIC distributions alone without regard to genetic information. Due to the large number of isolates involved, we observed distinct MIC distributions for isolates with different resistance gene alleles, including for ciprofloxacin and tetracycline, suggesting the potential to predict MICs based on WGS data alone.
Project description:BACKGROUND:Multidrug-resistant Neisseria gonorrhoeae strains are prevalent, threatening gonorrhoea treatment globally, and understanding of emergence, evolution, and spread of antimicrobial resistance (AMR) in gonococci remains limited. We describe the genomic evolution of gonococci and their AMR, related to the introduction of antimicrobial therapies, examining isolates from 1928 (preantibiotic era) to 2013 in Denmark. This is, to our knowledge, the oldest gonococcal collection globally. METHODS:Lyophilised isolates were revived and examined using Etest (18 antimicrobials) and whole-genome sequencing (WGS). Quality-assured genome sequences were obtained for 191 viable and 40 non-viable isolates and analysed with multiple phylogenomic approaches. RESULTS:Gonococcal AMR, including an accumulation of multiple AMR determinants, started to emerge particularly in the 1950s-1970s. By the twenty-first century, resistance to most antimicrobials was common. Despite that some AMR determinants affect many physiological functions and fitness, AMR determinants were mainly selected by the use/misuse of gonorrhoea therapeutic antimicrobials. Most AMR developed in strains belonging to one multidrug-resistant (MDR) clade with close to three times higher genomic mutation rate. Modern N. gonorrhoeae was inferred to have emerged in the late-1500s and its genome became increasingly conserved over time. CONCLUSIONS:WGS of gonococci from 1928 to 2013 showed that no AMR determinants, except penB, were in detectable frequency before the introduction of gonorrhoea therapeutic antimicrobials. The modern gonococcus is substantially younger than previously hypothesized and has been evolving into a more clonal species, driven by the use/misuse of antimicrobials. The MDR gonococcal clade should be further investigated for early detection of strains with predispositions to develop and maintain MDR and for initiation of public health interventions.
Project description:BACKGROUND:To monitor the prevalence of antimicrobial resistance (AMR), methods for interpretation of susceptibility phenotypes of bacteria are needed. Reference limits to declare resistance are generally based on or dominated by data from human bacterial isolates and may not reflect clinical relevance or wild type (WT) populations in livestock or other hosts. METHODS:We compared the observed prevalence of AMR using standard and bespoke interpretations based on clinical breakpoints or epidemiological cut-offs (ECOFF) using gram positive (Staphylococcus aureus) and gram negative (Escherichia coli) bacteria from sheep as exemplars. Isolates were obtained from a cross-sectional study in three lowland sheep flocks in Scotland, and from a longitudinal study in one flock in Norway. S. aureus (n = 101) was predominantly isolated from milk or mammary glands whilst E. coli (n = 103) was mostly isolated from faecal samples. Disc diffusion testing was used to determine inhibition zone diameters, which were interpreted using either clinical breakpoints or ECOFF, which distinguish the bacterial wild type population from bacteria with acquired or mutational resistance to the compound of interest (non-wild type). Standard ECOFF values were considered as well as sheep-specific values calculated from the data using Normalized Resistance Interpretation (NRI) methodology. RESULTS:The prevalence of AMR as measured based on clinical breakpoints was low, e.g. 4.0% for penicillin resistance in S. aureus. Estimation of AMR prevalence based on standard ECOFFs was hampered by lack of relevant reference values. In addition, standard ECOFFS, which are predominantly based on human data, bisected the normal distribution of inhibition zone diameters for several compounds in our analysis of sheep isolates. This contravenes recommendations for ECOFF setting based on NRI methodology and may lead to high apparent AMR prevalence. Using bespoke ECOFF values based on NRI, S. aureus showed non-wild type for less than 4% of isolates across 13 compounds, and ca. 13% non-wild type for amoxicillin and ampicillin, while E. coli showed non-wild type for less than 3% of isolates across 12 compounds, and ca. 13% non-wild type for tetracyclines and sulfamethoxazole-trimethoprim. CONCLUSION:The apparent prevalence of AMR in bacteria isolated from sheep is highly dependent on interpretation criteria. The sheep industry may want to establish bespoke cut-off values for AMR monitoring to avoid the use of cut-offs developed for other host species. The latter could lead to high apparent prevalence of resistance, including to critically important antimicrobial classes such as 4th generation cephalosporins and carbapenems, suggesting an AMR problem that may not actually exist.