Dataset Information

PyroTyping, a novel pyrosequencing-based assay for Mycobacterium tuberculosis genotyping.

ABSTRACT: We developed a novel method, PyroTyping, for discrimination of Mycobacterium tuberculosis isolates combining pyrosequencing and IS6110 polymorphism. A total of 100 isolates were analysed with IS6110-restriction fragment length polymorphism (RFLP), spoligotyping, mycobacterial interspersed repetitive units - variable number tandem repeats (MIRU-VNTR), and PyroTyping. PyroTyping results regarding clustering or discrimination of the isolates were highly concordant with the other typing methods performed. PyroTyping is more rapid than RFLP and presents the same discriminatory power, thus, it may be useful for taking timely decisions for tuberculosis control.

SUBMITTER: Molina-Moya B

PROVIDER: S-EPMC5533701 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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PyroTyping, a novel pyrosequencing-based assay for Mycobacterium tuberculosis genotyping.

Molina-Moya B B Lacoma A A García-Sierra N N Blanco S S Haba L L Samper S S Ruiz-Manzano J J Prat C C Arnold C C Domínguez J J

Scientific reports 20170728 1

We developed a novel method, PyroTyping, for discrimination of Mycobacterium tuberculosis isolates combining pyrosequencing and IS6110 polymorphism. A total of 100 isolates were analysed with IS6110-restriction fragment length polymorphism (RFLP), spoligotyping, mycobacterial interspersed repetitive units - variable number tandem repeats (MIRU-VNTR), and PyroTyping. PyroTyping results regarding clustering or discrimination of the isolates were highly concordant with the other typing methods perf ...[more]

PMID: 28754991

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Project description:BACKGROUND: Multiplex 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. RESULTS: To 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. CONCLUSION: Based 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.

Project description:BackgroundGenotyping methods developed to survey the transmission dynamics of Mycobacterium tuberculosis currently rely on the interpretation of restriction and amplification profiles. Multispacer sequence typing (MST) genotyping is based on the sequencing of several intergenic regions selected after complete genome sequence analysis. It has been applied to various pathogens, but not to M. tuberculosis.Methods and findingsIn M. tuberculosis, the MST approach yielded eight variable intergenic spacers which included four previously described variable number tandem repeat loci, one single nucleotide polymorphism locus and three newly evaluated spacers. Spacer sequence stability was evaluated by serial subculture. The eight spacers were sequenced in a collection of 101 M. tuberculosis strains from five phylogeographical lineages, and yielded 29 genetic events including 13 tandem repeat number variations (44.82%), 11 single nucleotide mutations (37.93%) and 5 deletions (17.24%). These 29 genetic events yielded 32 spacer alleles or spacer-types (ST) with an index of discrimination of 0.95. The distribution of M. tuberculosis isolates into ST profiles correlated with their assignment into phylogeographical lineages. Blind comparison of a further 93 M. tuberculosis strains by MST and restriction fragment length polymorphism-IS6110 fingerprinting and mycobacterial interspersed repetitive units typing, yielded an index of discrimination of 0.961 and 0.992, respectively. MST yielded 41 different profiles delineating 16 related groups and proved to be more discriminatory than IS6110-based typing for isolates containing < 8 IS6110 copies (P<0.0003). MST was successfully applied to 7/10 clinical specimens exhibiting a Cts < or = 42 cycles in internal transcribed spacer-real time PCR.ConclusionsThese results support MST as an alternative, sequencing-based method for genotyping low IS6110 copy-number M. tuberculosis strains. The M. tuberculosis MST database is freely available (http://ifr48.timone.univ-mrs.fr/MST_MTuberculosis/mst).

Dataset Information

PyroTyping, a novel pyrosequencing-based assay for Mycobacterium tuberculosis genotyping.

Publications

PyroTyping, a novel pyrosequencing-based assay for Mycobacterium tuberculosis genotyping.

Similar Datasets

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