Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12530/29919
Title: Optimizing and accelerating the assignation of lineages in Mycobacterium tuberculosis using novel alternative single-tube assays.
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Issue Date: 2017
Citation: PLoS ONE.2017;(12)11:e0186956
Abstract: The assignation of lineages in Mycobacterium tuberculosis (MTB) provides valuable information for evolutionary and phylogeographic studies and makes for more accurate knowledge of the distribution of this pathogen worldwide. Differences in virulence have also been found for certain lineages. MTB isolates were initially assigned to lineages based on data obtained from genotyping techniques, such as spoligotyping or MIRU-VNTR analysis, some of which are more suitable for molecular epidemiology studies. However, since these methods are subject to a certain degree of homoplasy, other criteria have been chosen to assign lineages. These are based on targeting robust and specific SNPs for each lineage. Here, we propose two newly designed multiplex targeting methods-both of which are single-tube tests-to optimize the assignation of the six main lineages in MTB. The first method is based on ASO-PCR and offers an inexpensive and easy-to-implement assay for laboratories with limited resources. The other, which is based on SNaPshot, enables more refined standardized assignation of lineages for laboratories with better resources. Both methods performed well when assigning lineages from cultured isolates from a control panel, a test panel, and a problem panel from an unrelated population, Mexico, which included isolates in which standard genotyping was not able to classify lineages. Both tests were also able to assign lineages from stored isolates, without the need for subculture or purification of DNA, and even directly from clinical specimens with a medium-high bacilli burden. Our assays could broaden the contexts where information on lineages can be acquired, thus enabling us to quickly update data from retrospective collections and to merge data with those obtained at the time of diagnosis of a new TB case.
PMID: 29091913
URI: https://hdl.handle.net/20.500.12530/29919
Rights: openAccess
Appears in Collections:Fundaciones e Institutos de Investigación > IIS H. General U. Gregorio Marañón > Artículos

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