Dataset Information

Systematic Review of Whole-Genome Sequencing Data To Predict Phenotypic Drug Resistance and Susceptibility in Swedish Mycobacterium tuberculosis Isolates, 2016 to 2018.

ABSTRACT: In this retrospective study, whole-genome sequencing (WGS) data generated on an Ion Torrent platform was used to predict phenotypic drug resistance profiles for first- and second-line drugs among Swedish clinical Mycobacterium tuberculosis isolates from 2016 to 2018. The accuracy was ?99% for all first-line drugs and 100% for four second-line drugs. Our analysis supports the introduction of WGS into routine diagnostics, which might, at least in Sweden, replace phenotypic drug susceptibility testing in the future.

SUBMITTER: Enkirch T

PROVIDER: S-EPMC7179598 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Systematic Review of Whole-Genome Sequencing Data To Predict Phenotypic Drug Resistance and Susceptibility in Swedish Mycobacterium tuberculosis Isolates, 2016 to 2018.

Enkirch Theresa T Werngren Jim J Groenheit Ramona R Alm Erik E Advani Reza R Lind Karlberg Maria M Mansjö Mikael M

Antimicrobial agents and chemotherapy 20200421 5

In this retrospective study, whole-genome sequencing (WGS) data generated on an Ion Torrent platform was used to predict phenotypic drug resistance profiles for first- and second-line drugs among Swedish clinical <i>Mycobacterium tuberculosis</i> isolates from 2016 to 2018. The accuracy was ∼99% for all first-line drugs and 100% for four second-line drugs. Our analysis supports the introduction of WGS into routine diagnostics, which might, at least in Sweden, replace phenotypic drug susceptibili ...[more]

PMID: 32122893

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Project description:BackgroundPatients with multidrug-resistant (MDR) tuberculosis may have phenotypic heterogeneity in results of drug-susceptibility tests (DSTs). However, the impact of this on clinical outcomes among patients treated for MDR tuberculosis is unknown.MethodsPhenotypic DST heterogeneity was defined as presence of at least 1 Mycobacterium tuberculosis isolate susceptible to rifampicin and isoniazid recovered <3 months after MDR tuberculosis treatment initiation from a patient with previous documented tuberculosis due to M. tuberculosis resistant to at least rifampicin and isoniazid. The primary outcome was defined as good (ie, cure or treatment completion) or poor (ie, treatment failure, treatment default, or death). A secondary outcome was time to culture conversion. Cox proportional hazard models were used to determine the association between phenotypic DST heterogeneity and outcomes.ResultsPhenotypic DST heterogeneity was identified in 33 of 475 patients (7%) with MDR tuberculosis. Poor outcome occurred in 126 patients (28%). Overall, patients with MDR tuberculosis who had phenotypic DST heterogeneity were at greater risk of poor outcome than those with MDR tuberculosis but no phenotypic DST heterogeneity (adjusted hazard ratio [aHR], 2.1; 95% confidence interval [CI], 1.2-3.6). Among HIV-infected patients with MDR tuberculosis, the adjusted hazard for a poor outcome for those with phenotypic DST heterogeneity was 2.4 (95% CI, 1.3-4.2) times that for those without phenotypic DST heterogeneity, whereas among HIV-negative patients with MDR tuberculosis, the adjusted hazard for those with phenotypic DST heterogeneity was 1.5 (95% CI, .5-4.3) times that for those without phenotypic DST heterogeneity. HIV-infected patients with MDR tuberculosis with phenotypic DST heterogeneity also had a longer time to culture conversion than with HIV-infected patients with MDR tuberculosis without phenotypic DST heterogeneity (aHR, 2.9; 95% CI, 1.4-6.0).ConclusionsPhenotypic DST heterogeneity among persons with HIV infection who are being treated for MDR tuberculosis is associated with poor outcomes and longer times to culture conversion.

Project description:BackgroundWhole-genome sequencing (WGS) of Mycobacterium tuberculosis complex has become an important tool in diagnosis and management of drug-resistant tuberculosis. However, data correlating resistance genotype with quantitative phenotypic antimicrobial susceptibility testing (AST) are scarce.MethodsIn a prospective multicentre observational study, 900 clinical M tuberculosis complex isolates were collected from adults with drug-resistant tuberculosis in five high-endemic tuberculosis settings around the world (Georgia, Moldova, Peru, South Africa, and Viet Nam) between Dec 5, 2014, and Dec 12, 2017. Minimum inhibitory concentrations (MICs) and resulting binary phenotypic AST results for up to nine antituberculosis drugs were determined and correlated with resistance-conferring mutations identified by WGS.FindingsConsidering WHO-endorsed critical concentrations as reference, WGS had high accuracy for prediction of resistance to isoniazid (sensitivity 98·8% [95% CI 98·5-99·0]; specificity 96·6% [95% CI 95·2-97·9]), levofloxacin (sensitivity 94·8% [93·3-97·6]; specificity 97·1% [96·7-97·6]), kanamycin (sensitivity 96·1% [95·4-96·8]; specificity 95·0% [94·4-95·7]), amikacin (sensitivity 97·2% [96·4-98·1]; specificity 98·6% [98·3-98·9]), and capreomycin (sensitivity 93·1% [90·0-96·3]; specificity 98·3% [98·0-98·7]). For rifampicin, pyrazinamide, and ethambutol, the specificity of resistance prediction was suboptimal (64·0% [61·0-67·1], 83·8% [81·0-86·5], and 40·1% [37·4-42·9], respectively). Specificity for rifampicin increased to 83·9% when borderline mutations with MICs overlapping with the critical concentration were excluded. Consequently, we highlighted mutations in M tuberculosis complex isolates that are often falsely identified as susceptible by phenotypic AST, and we identified potential novel resistance-conferring mutations.InterpretationThe combined analysis of mutations and quantitative phenotypes shows the potential of WGS to produce a refined interpretation of resistance, which is needed for individualised therapy, and eventually could allow differential drug dosing. However, variability of MIC data for some M tuberculosis complex isolates carrying identical mutations also reveals limitations of our understanding of the genotype and phenotype relationships (eg, including epistasis and strain genetic background).FundingBill & Melinda Gates Foundation, German Centre for Infection Research, German Research Foundation, Excellence Cluster Precision Medicine of Inflammation (EXC 2167), and Leibniz ScienceCampus EvoLUNG.

Project description:Mycobacterium avium complex (MAC) infections are a significant clinical challenge. Determining drug-susceptibility profiles and the genetic basis of drug resistance is crucial for guiding effective treatment strategies. This study aimed to determine the drug-susceptibility profiles of MAC clinical isolates and to investigate the genetic basis conferring drug resistance using whole-genome sequencing (WGS) analysis. Drug-susceptibility profiles based on minimum inhibitory concentration (MIC) assays were determined for 38 MAC clinical isolates (12 Mycobacterium avium and 26 Mycobacterium intracellulare). Mutations associated with drug resistance were identified through genome analysis of these isolates, and their phylogenetic relationships were also examined. Drug resistance, based on MIC values, was most commonly observed for moxifloxacin (81.6%), followed by linezolid (78.9%), clarithromycin (44.7%) and amikacin (36.8%). We identified specific mutations associated with resistance to amikacin. These include the rrs mutation at C464T in amikacin intermediate-resistance M. avium, and two mutations at T250A and G1453T in amikacin non-susceptible M. intracellulare. Mutations in rrl at A2058G, A2059C and A2059G were potentially linked to clarithromycin resistance. MAC clinical isolates not susceptible to linezolid exhibited mutations in rplC at G237C and C459T, as well as two rplD mutations at G443A and A489G. GyrB substitution Thr521Ala (T521A) was identified in moxifloxacin non-susceptible isolates, which may contribute to this resistance. A phylogeny of our MAC isolates revealed high levels of genetic diversity. Our findings suggest that the standard treatment regimen for MAC infections using moxifloxacin, linezolid, clarithromycin and amikacin may be driving development of resistance, potentially due to specific mutations. The combination of phenotypic and genotypic susceptibility testing can be valuable in guiding the clinical use of drugs for the treatment of MAC infections.

Project description:Standard antimicrobial susceptibility testing (AST) approaches lead to delays in the selection of optimal antimicrobial therapy. Here, we sought to determine the accuracy of antimicrobial resistance (AMR) determinants identified by Nanopore whole-genome sequencing in predicting AST results. Using a cohort of 40 clinical isolates (21 carbapenemase-producing carbapenem-resistant Klebsiella pneumoniae, 10 non-carbapenemase-producing carbapenem-resistant K. pneumoniae, and 9 carbapenem-susceptible K. pneumoniae isolates), three separate sequencing and analysis pipelines were performed, as follows: (i) a real-time Nanopore analysis approach identifying acquired AMR genes, (ii) an assembly-based Nanopore approach identifying acquired AMR genes and chromosomal mutations, and (iii) an approach using short-read correction of Nanopore assemblies. The short-read correction of Nanopore assemblies served as the reference standard to determine the accuracy of Nanopore sequencing results. With the real-time analysis approach, full annotation of acquired AMR genes occurred within 8 h from subcultured isolates. Assemblies sufficient for full resistance gene and single-nucleotide polymorphism annotation were available within 14 h from subcultured isolates. The overall agreement of genotypic results and anticipated AST results for the 40 K. pneumoniae isolates was 77% (range, 30% to 100%) and 92% (range, 80% to 100%) for the real-time approach and the assembly approach, respectively. Evaluating the patients contributing the 40 isolates, the real-time approach and assembly approach could shorten the median time to effective antibiotic therapy by 20 h and 26 h, respectively, compared to standard AST. Nanopore sequencing offers a rapid approach to both accurately identify resistance mechanisms and to predict AST results for K. pneumoniae isolates. Bioinformatics improvements enabling real-time alignment, coupled with rapid extraction and library preparation, will further enhance the accuracy and workflow of the Nanopore real-time approach.

Dataset Information

Systematic Review of Whole-Genome Sequencing Data To Predict Phenotypic Drug Resistance and Susceptibility in Swedish Mycobacterium tuberculosis Isolates, 2016 to 2018.

Publications

Systematic Review of Whole-Genome Sequencing Data To Predict Phenotypic Drug Resistance and Susceptibility in Swedish Mycobacterium tuberculosis Isolates, 2016 to 2018.

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