The population structure of Mycobacterium tuberculosis is typically clonal therefore genotypic lineages can be unequivocally identified by characteristic markers such as mutations or genomic deletions. In addition, drug resistance is mainly mediated by mutations. These issues make multiplexed detection of selected mutations potentially a very powerful tool to characterise Mycobacterium tuberculosis. We used Multiplex Ligation-dependent Probe Amplification (MLPA) to screen for dispersed mutations, which can be successfully applied to Mycobacterium tuberculosis as was previously shown. Here we selected 47 discriminative and informative markers and designed MLPA probes accordingly to allow analysis with a liquid bead array and robust reader (Luminex MAGPIX technology). To validate the bead-based MLPA, we screened a panel of 88 selected strains, previously characterised by other methods with the developed multiplex assay using automated positive and negative calling. In total 3059 characteristics were screened and 3034 (99.2%) were consistent with previous molecular characterizations, of which 2056 (67.2%) were directly supported by other molecular methods, and 978 (32.0%) were consistent with but not directly supported by previous molecular characterizations. Results directly conflicting or inconsistent with previous methods, were obtained for 25 (0.8%) of the characteristics tested. Here we report the validation of the bead-based MLPA and demonstrate its potential to simultaneously identify a range of drug resistance markers, discriminate the species within the Mycobacterium tuberculosis complex, determine the genetic lineage and detect and identify the clinically most relevant non-tuberculous mycobacterial species. The detection of multiple genetic markers in clinically derived Mycobacterium tuberculosis strains with a multiplex assay could reduce the number of TB-dedicated screening methods needed for full characterization. Additionally, as a proportion of the markers screened are specific to certain Mycobacterium tuberculosis lineages each profile can be checked for internal consistency. Strain characterization can allow selection of appropriate treatment and thereby improve treatment outcome and patient management.
BACKGROUND: Current laboratory methods for monitoring the response to therapy for tuberculosis (TB) rely on mycobacterial culture. Their clinical usefulness is therefore limited by the slow growth rate of Mycobacterium tuberculosis. Rapid methods to reliably quantify the response to anti-TB drugs are desirable.
We developed a QIAplex system for the simultaneous detection of 24 Mycobacterium tuberculosis gene mutations responsible for resistance to isoniazid (INH), rifampin (RIF), streptomycin (STM), and ethambutol (EMB) in 196 M. tuberculosis isolates recovered in the Republic of Georgia. In comparison to phenotypic susceptibility tests, the QIAplex showed sensitivity and specificity of 85.4% and 96.1% for INH, 94.4% and 99.4% for RIF, 69.6% and 99.2% for STM, 50.0% and 98.8% for EBM, and 86.7% and 100.0% for multidrug resistance, respectively. The dominant resistance mutations revealed were a mutation in katG resulting in S315T (katG S315T), rpsL K43R, and rpoB S531L. Mutations katG S315G and S315T and rpoB S531L were detected with higher frequencies in pretreated patients than in naive patients (P < 0.05). Simultaneous detection of 24 common drug resistance-related mutations provides a molecular tool for studying and monitoring M. tuberculosis resistance mechanism and epidemiology.
BackgroundMultiplex ligation-dependent probe amplification (MLPA) is a powerful tool to identify genomic polymorphisms. We have previously developed a single nucleotide polymorphism (SNP) and large sequence polymorphisms (LSP)-based MLPA assay using a read out on a liquid bead array to screen for 47 genetic markers in the Mycobacterium tuberculosis genome. In our assay we obtain information regarding the Mycobacterium tuberculosis lineage and drug resistance simultaneously. Previously we called the presence or absence of a genotypic marker based on a threshold signal level. Here we present a more elaborate data analysis method to standardize and streamline the interpretation of data generated by MLPA. The new data analysis method also identifies intermediate signals in addition to classification of signals as positive and negative. Intermediate calls can be informative with respect to identifying the simultaneous presence of sensitive and resistant alleles or infection with multiple different Mycobacterium tuberculosis strains.ResultsTo validate our analysis method 100 DNA isolates of Mycobacterium tuberculosis extracted from cultured patient material collected at the National TB Reference Laboratory of the National Center for Tuberculosis and Lung Diseases in Tbilisi, Republic of Georgia were tested by MLPA. The data generated were interpreted blindly and then compared to results obtained by reference methods. MLPA profiles containing intermediate calls are flagged for expert review whereas the majority of profiles, not containing intermediate calls, were called automatically. No intermediate signals were identified in 74/100 isolates and in the remaining 26 isolates at least one genetic marker produced an intermediate signal.ConclusionBased on excellent agreement with the reference methods we conclude that the new data analysis method performed well. The streamlined data processing and standardized data interpretation allows the comparison of the Mycobacterium tuberculosis MLPA results between different experiments. All together this will facilitate the implementation of the MLPA assay in different settings.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-572) contains supplementary material, which is available to authorized users.
Background Kazakhstan remains a high-burden TB prevalence country with a concomitent high-burden of multi-drug resistant tuberculosis. For this reason, we performed an in depth genetic diversity and population structure characterization of Mycobacterium tuberculosis complex (MTC) genetic diversity in Kazakhstan with both patient and community benefit. Methods A convenience sample of 700 MTC DNA cultures extracts from 630 tuberculosis patients recruited from 12 out of 14 regions in Kazakhstan, between 2010 and 2015, was independently studied by high-throughput hybridization-based methods, TB-SPRINT (59-Plex, n = 700), TB-SNPID (50-Plex, n = 543). DNA from 391 clinical isolates was successfully typed by two methods. To resolve the population structure of drug-resistant clades in more detail two complementary assays were run on the L2 isolates: an IS 6110 -NTF insertion site typing assay and a SigE SNP polymorphism assay. Results Strains belonged to L2/Beijing and L4/Euro-American sublineages; L2/Beijing prevalence totaled almost 80%. 50% of all samples were resistant to RIF and to INH., Subtyping showed that: (1) all L2/Beijing were “modern” Beijing and (2) most of these belonged to the previously described 94–32 sublineage (Central Asian/Russian), (3) at least two populations of the Central Asian/Russian sublineages are circulating in Kazakhstan, with different evolutionary dynamics. Conclusions For the first time, the global genetic diversity and population structure of M. tuberculosis genotypes circulating in Kazakhstan was obtained and compared to previous local studies. Results suggest a region-specific spread of a very limited number of L2/Beijing clonal complexes in Kazakhstan many strongly associated with an MDR phenotype. Electronic supplementary material The online version of this article (10.1186/s12879-019-4201-2) contains supplementary material, which is available to authorized users.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.