Transcontinental spread and evolution of Mycobacterium tuberculosis W148 European/Russian clade toward extensively drug resistant tuberculosis.

Transmission-driven multi-/extensively drug resistant (M/XDR) tuberculosis (TB) is the largest single contributor to human mortality due to antimicrobial resistance. A few major clades of the Mycobacterium tuberculosis complex belonging to lineage 2, responsible for high prevalence of MDR-TB in Eurasia, show outstanding transnational distributions. Here, we determined factors underlying the emergence and epidemic spread of the W148 clade by genome sequencing and Bayesian demogenetic analyses of 720 isolates from 23 countries. We dated a common ancestor around 1963 and identified two successive epidemic expansions in the late 1980s and late 1990s, coinciding with major socio-economic changes in the post-Soviet Era. These population expansions favored accumulation of resistance mutations to up to 11 anti-TB drugs, with MDR evolving toward additional resistances to fluoroquinolones and second-line injectable drugs within 20 years on average. Timescaled haplotypic density analysis revealed that widespread acquisition of compensatory mutations was associated with transmission success of XDR strains. Virtually all W148 strains harbored a hypervirulence-associated ppe38 gene locus, and incipient recurrent emergence of prpR mutation-mediated drug tolerance was detected. The outstanding genetic arsenal of this geographically widespread M/XDR strain clade represents a "perfect storm" that jeopardizes the successful introduction of new anti-M/XDR-TB antibiotic regimens.

Ancient and recent differences in the intrinsic susceptibility of Mycobacterium tuberculosis complex to pretomanid.

OBJECTIVES: To develop a robust phenotypic antimicrobial susceptibility testing (AST) method with a correctly set breakpoint for pretomanid (Pa), the most recently approved anti-tuberculosis drug. METHODS: The Becton Dickinson Mycobacterial Growth Indicator Tube™ (MGIT) system was used at six laboratories to determine the MICs of a phylogenetically diverse collection of 356 Mycobacterium tuberculosis complex (MTBC) strains to establish the epidemiological cut-off value for pretomanid. MICs were correlated with WGS data to study the genetic basis of differences in the susceptibility to pretomanid. RESULTS: We observed ancient differences in the susceptibility to pretomanid among various members of MTBC. Most notably, lineage 1 of M. tuberculosis, which is estimated to account for 28% of tuberculosis cases globally, was less susceptible than lineages 2, 3, 4 and 7 of M. tuberculosis, resulting in a 99th percentile of 2 mg/L for lineage 1 compared with 0.5 mg/L for the remaining M. tuberculosis lineages. Moreover, we observed that higher MICs (≥8 mg/L), which probably confer resistance, had recently evolved independently in six different M. tuberculosis strains. Unlike the aforementioned ancient differences in susceptibility, these recent differences were likely caused by mutations in the known pretomanid resistance genes. CONCLUSIONS: In light of these findings, the provisional critical concentration of 1 mg/L for MGIT set by EMA must be re-evaluated. More broadly, these findings underline the importance of considering the global diversity of MTBC during clinical development of drugs and when defining breakpoints for AST.

Deep amplicon sequencing for culture-free prediction of susceptibility or resistance to 13 anti-tuberculous drugs.

Conventional molecular tests for detecting Mycobacterium tuberculosis complex (MTBC) drug resistance on clinical samples cover a limited set of mutations. Whole-genome sequencing (WGS) typically requires culture.Here, we evaluated the Deeplex Myc-TB targeted deep-sequencing assay for prediction of resistance to 13 anti-tuberculous drugs/drug classes, directly applicable on sputum.With MTBC DNA tests, the limit of detection was 100-1000 genome copies for fixed resistance mutations. Deeplex Myc-TB captured in silico 97.1-99.3% of resistance phenotypes correctly predicted by WGS from 3651 MTBC genomes. On 429 isolates, the assay predicted 92.2% of 2369 first- and second-line phenotypes, with a sensitivity of 95.3% and a specificity of 97.4%. 56 out of 69 (81.2%) residual discrepancies with phenotypic results involved pyrazinamide, ethambutol and ethionamide, and low-level rifampicin or isoniazid resistance mutations, all notoriously prone to phenotypic testing variability. Only two out of 91 (2.2%) resistance phenotypes undetected by Deeplex Myc-TB had known resistance-associated mutations by WGS analysis outside Deeplex Myc-TB targets. Phenotype predictions from Deeplex Myc-TB analysis directly on 109 sputa from a Djibouti survey matched those of MTBSeq/PhyResSE/Mykrobe, fed with WGS data from subsequent cultures, with a sensitivity of 93.5/98.5/93.1% and a specificity of 98.5/97.2/95.3%, respectively. Most residual discordances involved gene deletions/indels and 3-12% heteroresistant calls undetected by WGS analysis or natural pyrazinamide resistance of globally rare "Mycobacterium canettii" strains then unreported by Deeplex Myc-TB. On 1494 arduous sputa from a Democratic Republic of the Congo survey, 14 902 out of 19 422 (76.7%) possible susceptible or resistance phenotypes could be predicted culture-free.Deeplex Myc-TB may enable fast, tailored tuberculosis treatment.

Detection of low-frequency resistance-mediating SNPs in next-generation sequencing data of Mycobacterium tuberculosis complex strains with binoSNP.

Accurate drug resistance detection is key for guiding effective tuberculosis treatment. While genotypic resistance can be rapidly detected by molecular methods, their application is challenged by mixed mycobacterial populations comprising both susceptible and resistant cells (heteroresistance). For this, next-generation sequencing (NGS) based approaches promise the determination of variants even at low frequencies. However, accurate methods for a valid detection of low-frequency variants in NGS data are currently lacking. To tackle this problem, we developed the variant detection tool binoSNP which allows the determination of low-frequency single nucleotide polymorphisms (SNPs) in NGS datasets from Mycobacterium tuberculosis complex (MTBC) strains. By taking a reference-mapped file as input, binoSNP evaluates each genomic position of interest using a binomial test procedure. binoSNP was validated using in-silico, in-vitro, and serial patient isolates datasets comprising varying genomic coverage depths (100-500×) and SNP allele frequencies (1-30%). Overall, the detection limit for low-frequency SNPs depends on the combination of coverage depth and allele frequency of the resistance-associated mutation. binoSNP allows for valid detection of resistance associated SNPs at a 1% frequency with a coverage ≥400×. In conclusion, binoSNP provides a valid approach to detect low-frequency resistance-mediating SNPs in NGS data from clinical MTBC strains. It can be implemented in automated, end-user friendly analysis tools for NGS data and is a step forward towards individualized TB therapy.

Revised Interpretation of the Hain Lifescience GenoType MTBC To Differentiate Mycobacterium canettii and Members of the Mycobacterium tuberculosis Complex.

Using 894 phylogenetically diverse genomes of the Mycobacterium tuberculosis complex (MTBC), we simulated in silico the ability of the Hain Lifescience GenoType MTBC assay to differentiate the causative agents of tuberculosis. Here, we propose a revised interpretation of this assay to reflect its strengths (e.g., it can distinguish some strains of Mycobacterium canettii and variants of Mycobacterium bovis that are not intrinsically resistant to pyrazinamide) and limitations (e.g., Mycobacterium orygis cannot be differentiated from Mycobacterium africanum).

Rapid microarray-based assay for detection of pyrazinamide resistant Mycobacterium tuberculosis.

Pyrazinamide (PZA) is a key antibiotic for the treatment of drug susceptible tuberculosis. PZA-resistance is mainly mediated by mutations in the pncA gene; however the current gold standard is a phenotypic drug susceptibility test requiring a well-adjusted pH-value for reliable results. Our melting curve assay detects a non-wild type genotype in selected pncA regions in at least 3750 gene copies/mL within 2.5 hours. The prototype assay was further evaluated by analyzing 271 Mycobacterium tuberculosis complex isolates from Swaziland originating from a previously published drug resistance survey and including 118 isolates with pncA mutations. Sensitivity was 83% (95% CI 75-89%) and specificity was 100% (95% CI 98-100%). Under consideration of further improvements with regard to the target range our melting curve assay has the potential as a rapid rule-in test for PZA susceptibility (wild type pncA), however false resistant results (mutant pncA, but PZA susceptible) cannot be ruled out completely.

Compensatory evolution drives multidrug-resistant tuberculosis in Central Asia.

Bacterial factors favoring the unprecedented multidrug-resistant tuberculosis (MDR-TB) epidemic in the former Soviet Union remain unclear. We utilized whole genome sequencing and Bayesian statistics to analyze the evolutionary history, temporal emergence of resistance and transmission networks of MDR Mycobacterium tuberculosis complex isolates from Karakalpakstan, Uzbekistan (2001-2006). One clade (termed Central Asian outbreak, CAO) dating back to 1974 (95% HPD 1969-1982) subsequently acquired resistance mediating mutations to eight anti-TB drugs. Introduction of standardized WHO-endorsed directly observed treatment, short-course in Karakalpakstan in 1998 likely selected for CAO-strains, comprising 75% of sampled MDR-TB isolates in 2005/2006. CAO-isolates were also identified in a published cohort from Russia (2008-2010). Similarly, the presence of mutations supposed to compensate bacterial fitness deficits was associated with transmission success and higher drug resistance rates. The genetic make-up of these MDR-strains threatens the success of both empirical and standardized MDR-TB therapies, including the newly WHO-endorsed short MDR-TB regimen in Uzbekistan.

Rapid Microarray-Based Detection of Rifampin, Isoniazid, and Fluoroquinolone Resistance in Mycobacterium tuberculosis by Use of a Single Cartridge.

The rapid and robust identification of mutations in Mycobacterium tuberculosis complex (MTBC) strains mediating multidrug-resistant (MDR) and extensively drug-resistant (XDR) phenotypes is crucial to combating the MDR tuberculosis (TB) epidemic. Currently available molecular anti-TB drug susceptibility tests either are restricted to a single target or drug (i.e., the Xpert MTB/RIF test) or present a risk of cross-contamination due to the design limitations of the open platform (i.e., line probe assays). With a good understanding of the technical and commercial boundaries, we designed a test cartridge based on an oligonucleotide array into which dried reagents are introduced and which has the ability to identify MTBC strains resistant to isoniazid, rifampin, and the fluoroquinolones. The melting curve assay interrogates 43 different mutations in the rifampin resistance-determining region (RRDR) of rpoB, rpoB codon 572, katG codon 315, the inhA promoter region, and the quinolone resistance-determining region (QRDR) of gyrA in a closed cartridge system within 90 min. Assay performance was evaluated with 265 clinical MTBC isolates, including MDR/XDR, non-MDR, and fully susceptible isolates, from a drug resistance survey performed in Swaziland in 2009 and 2010. In 99.5% of the cases, the results were consistent with data previously acquired utilizing Sanger sequencing. The assay, which uses a closed cartridge system in combination with a battery-powered Alere q analyzer and which has the potential to extend the current gene target panel, could serve as a rapid and robust point-of-care test in settings lacking a comprehensive molecular laboratory infrastructure to differentiate TB patients infected with MDR and non-MDR strains and to assist clinicians with their early treatment decisions.

An application of competitive reporter monitored amplification (CMA) for rapid detection of single nucleotide polymorphisms (SNPs).

Single nucleotide polymorphisms (SNPs) are essential parameters in molecular diagnostics and can be used for the early detection and clinical prognosis in various diseases. Available methods for SNP detection are still labor-intensive and require a complex laboratory infrastructure, which are not suitable for the usage in resource-limited settings. Thus, there is an urgent need for a simple, reliable and rapid approach. In this paper we modified the previously developed competitive reporter monitored amplification (CMA) technique for the detection of resistance mediating SNPs in Mycobacterium tuberculosis complex (MTBC) strains. As a proof-of-principle for the application of the CMA-based SNP assay in routine molecular tuberculosis diagnostic, we show that the assay recognizes resistance mediating SNPs for rifampicin, isoniazid and ethambutol from either isolated DNA or heat inactivated M. tuberculosis cell cultures. The CMA-based SNP assay can identify the most prevalent resistance mediating mutations in the genes rpoB, katG, embB, and the promotor region of inhA within one hour.

Mycobacterium tuberculosis resistance prediction and lineage classification from genome sequencing: comparison of automated analysis tools.

Whole-genome sequencing (WGS) has the potential to accelerate drug-susceptibility testing (DST) to design appropriate regimens for drug-resistant tuberculosis (TB). Several recently developed automated software tools promise to standardize the analysis and interpretation of WGS data. We assessed five tools (CASTB, KvarQ, Mykrobe Predictor TB, PhyResSE, and TBProfiler) with regards to DST and phylogenetic lineage classification, which we compared with phenotypic DST, Sanger sequencing, and traditional typing results for a collection of 91 strains. The lineage classifications by the tools generally only differed in the resolution of the results. However, some strains could not be classified at all and one strain was misclassified. The sensitivities and specificities for isoniazid and rifampicin resistance of the tools were high, whereas the results for ethambutol, pyrazinamide, and streptomycin resistance were more variable. False-susceptible DST results were mainly due to missing mutations in the resistance catalogues that the respective tools employed for data interpretation. Notably, we also found cases of false-resistance because of the misclassification of polymorphisms as resistance mutations. In conclusion, the performance of current WGS analysis tools for DST is highly variable. Sustainable business models and a shared, high-quality catalogue of resistance mutations are needed to ensure the clinical utility of these tools.

Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis.

The rise of antibiotic-resistant bacteria has led to an urgent need for rapid detection of drug resistance in clinical samples, and improvements in global surveillance. Here we show how de Bruijn graph representation of bacterial diversity can be used to identify species and resistance profiles of clinical isolates. We implement this method for Staphylococcus aureus and Mycobacterium tuberculosis in a software package ('Mykrobe predictor') that takes raw sequence data as input, and generates a clinician-friendly report within 3 minutes on a laptop. For S. aureus, the error rates of our method are comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.1%/99.6% across 12 antibiotics (using an independent validation set, n=470). For M. tuberculosis, our method predicts resistance with sensitivity/specificity of 82.6%/98.5% (independent validation set, n=1,609); sensitivity is lower here, probably because of limited understanding of the underlying genetic mechanisms. We give evidence that minor alleles improve detection of extremely drug-resistant strains, and demonstrate feasibility of the use of emerging single-molecule nanopore sequencing techniques for these purposes.

Lab-on-Chip-Based Platform for Fast Molecular Diagnosis of Multidrug-Resistant Tuberculosis.

We evaluated the performance of the molecular lab-on-chip-based VerePLEX Biosystem for detection of multidrug-resistant tuberculosis (MDR-TB), obtaining a diagnostic accuracy of more than 97.8% compared to sequencing and MTBDRplus assay for Mycobacterium tuberculosis complex and rifampin and isoniazid resistance detection on clinical isolates and smear-positive specimens. The speed, user-friendly interface, and versatility make it suitable for routine laboratory use.

Whole-genome sequencing for prediction of Mycobacterium tuberculosis drug susceptibility and resistance: a retrospective cohort study.

BACKGROUND: Diagnosing drug-resistance remains an obstacle to the elimination of tuberculosis. Phenotypic drug-susceptibility testing is slow and expensive, and commercial genotypic assays screen only common resistance-determining mutations. We used whole-genome sequencing to characterise common and rare mutations predicting drug resistance, or consistency with susceptibility, for all first-line and second-line drugs for tuberculosis. METHODS: Between Sept 1, 2010, and Dec 1, 2013, we sequenced a training set of 2099 Mycobacterium tuberculosis genomes. For 23 candidate genes identified from the drug-resistance scientific literature, we algorithmically characterised genetic mutations as not conferring resistance (benign), resistance determinants, or uncharacterised. We then assessed the ability of these characterisations to predict phenotypic drug-susceptibility testing for an independent validation set of 1552 genomes. We sought mutations under similar selection pressure to those characterised as resistance determinants outside candidate genes to account for residual phenotypic resistance. FINDINGS: We characterised 120 training-set mutations as resistance determining, and 772 as benign. With these mutations, we could predict 89·2% of the validation-set phenotypes with a mean 92·3% sensitivity (95% CI 90·7-93·7) and 98·4% specificity (98·1-98·7). 10·8% of validation-set phenotypes could not be predicted because uncharacterised mutations were present. With an in-silico comparison, characterised resistance determinants had higher sensitivity than the mutations from three line-probe assays (85·1% vs 81·6%). No additional resistance determinants were identified among mutations under selection pressure in non-candidate genes. INTERPRETATION: A broad catalogue of genetic mutations enable data from whole-genome sequencing to be used clinically to predict drug resistance, drug susceptibility, or to identify drug phenotypes that cannot yet be genetically predicted. This approach could be integrated into routine diagnostic workflows, phasing out phenotypic drug-susceptibility testing while reporting drug resistance early. FUNDING: Wellcome Trust, National Institute of Health Research, Medical Research Council, and the European Union.

PhyResSE: a Web Tool Delineating Mycobacterium tuberculosis Antibiotic Resistance and Lineage from Whole-Genome Sequencing Data.

Antibiotic-resistant tuberculosis poses a global threat, causing the deaths of hundreds of thousands of people annually. While whole-genome sequencing (WGS), with its unprecedented level of detail, promises to play an increasingly important role in diagnosis, data analysis is a daunting challenge. Here, we present a simple-to-use web service (free for academic use at http://phyresse.org). Delineating both lineage and resistance, it provides state-of-the-art methodology to life scientists and physicians untrained in bioinformatics. It combines elaborate data processing and quality control, as befits human diagnostics, with a treasure trove of validated resistance data collected from well-characterized samples in-house and worldwide.

Mycobacterium tuberculosis pyrazinamide resistance determinants: a multicenter study.

Pyrazinamide (PZA) is a prodrug that is converted to pyrazinoic acid by the enzyme pyrazinamidase, encoded by the pncA gene in Mycobacterium tuberculosis. Molecular identification of mutations in pncA offers the potential for rapid detection of pyrazinamide resistance (PZA(r)). However, the genetic variants are highly variable and scattered over the full length of pncA, complicating the development of a molecular test. We performed a large multicenter study assessing pncA sequence variations in 1,950 clinical isolates, including 1,142 multidrug-resistant (MDR) strains and 483 fully susceptible strains. The results of pncA sequencing were correlated with phenotype, enzymatic activity, and structural and phylogenetic data. We identified 280 genetic variants which were divided into four classes: (i) very high confidence resistance mutations that were found only in PZA(r) strains (85%), (ii) high-confidence resistance mutations found in more than 70% of PZA(r) strains, (iii) mutations with an unclear role found in less than 70% of PZA(r) strains, and (iv) mutations not associated with phenotypic resistance (10%). Any future molecular diagnostic assay should be able to target and identify at least the very high and high-confidence genetic variant markers of PZA(r); the diagnostic accuracy of such an assay would be in the range of 89.5 to 98.8%. Importance: Conventional phenotypic testing for pyrazinamide resistance in Mycobacterium tuberculosis is technically challenging and often unreliable. The development of a molecular assay for detecting pyrazinamide resistance would be a breakthrough, directly overcoming both the limitations of conventional testing and its related biosafety issues. Although the main mechanism of pyrazinamide resistance involves mutations inactivating the pncA enzyme, the highly diverse genetic variants scattered over the full length of the pncA gene and the lack of a reliable phenotypic gold standard hamper the development of molecular diagnostic assays. By analyzing a large number of strains collected worldwide, we have classified the different genetic variants based on their predictive value for resistance which should lead to more rapid diagnostic tests. This would assist clinicians in improving treatment regimens for patients.