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      A robust SNP barcode for typing Mycobacterium tuberculosis complex strains

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          Abstract

          Strain-specific genomic diversity in the Mycobacterium tuberculosis complex (MTBC) is an important factor in pathogenesis that may affect virulence, transmissibility, host response and emergence of drug resistance. Several systems have been proposed to classify MTBC strains into distinct lineages and families. Here, we investigate single-nucleotide polymorphisms (SNPs) as robust (stable) markers of genetic variation for phylogenetic analysis. We identify ~92k SNP across a global collection of 1,601 genomes. The SNP-based phylogeny is consistent with the gold-standard regions of difference (RD) classification system. Of the ~7k strain-specific SNPs identified, 62 markers are proposed to discriminate known circulating strains. This SNP-based barcode is the first to cover all main lineages, and classifies a greater number of sublineages than current alternatives. It may be used to classify clinical isolates to evaluate tools to control the disease, including therapeutics and vaccines whose effectiveness may vary by strain type.

          Abstract

          Genetic variation in Mycobacterium tuberculosis complex (MTBC) bacteria is responsible for differences in factors such as virulence and transmissibility. Here, the authors analyse the genomes of 1,601 MTBC isolates from diverse geographic locations and identify 62 SNPs that may be used to resolve lineages and sublineages of these strains.

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          Genotyping of Genetically Monomorphic Bacteria: DNA Sequencing in Mycobacterium tuberculosis Highlights the Limitations of Current Methodologies

          Because genetically monomorphic bacterial pathogens harbour little DNA sequence diversity, most current genotyping techniques used to study the epidemiology of these organisms are based on mobile or repetitive genetic elements. Molecular markers commonly used in these bacteria include Clustered Regulatory Short Palindromic Repeats (CRISPR) and Variable Number Tandem Repeats (VNTR). These methods are also increasingly being applied to phylogenetic and population genetic studies. Using the Mycobacterium tuberculosis complex (MTBC) as a model, we evaluated the phylogenetic accuracy of CRISPR- and VNTR-based genotyping, which in MTBC are known as spoligotyping and Mycobacterial Interspersed Repetitive Units (MIRU)-VNTR-typing, respectively. We used as a gold standard the complete DNA sequences of 89 coding genes from a global strain collection. Our results showed that phylogenetic trees derived from these multilocus sequence data were highly congruent and statistically robust, irrespective of the phylogenetic methods used. By contrast, corresponding phylogenies inferred from spoligotyping or 15-loci-MIRU-VNTR were incongruent with respect to the sequence-based trees. Although 24-loci-MIRU-VNTR performed better, it was still unable to detect all strain lineages. The DNA sequence data showed virtually no homoplasy, but the opposite was true for spoligotyping and MIRU-VNTR, which was consistent with high rates of convergent evolution and the low statistical support obtained for phylogenetic groupings defined by these markers. Our results also revealed that the discriminatory power of the standard 24 MIRU-VNTR loci varied by strain lineage. Taken together, our findings suggest strain lineages in MTBC should be defined based on phylogenetically robust markers such as single nucleotide polymorphisms or large sequence polymorphisms, and that for epidemiological purposes, MIRU-VNTR loci should be used in a lineage-dependent manner. Our findings have implications for strain typing in other genetically monomorphic bacteria.
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            Global phylogeny of Mycobacterium tuberculosis based on single nucleotide polymorphism (SNP) analysis: insights into tuberculosis evolution, phylogenetic accuracy of other DNA fingerprinting systems, and recommendations for a minimal standard SNP set.

            We analyzed a global collection of Mycobacterium tuberculosis strains using 212 single nucleotide polymorphism (SNP) markers. SNP nucleotide diversity was high (average across all SNPs, 0.19), and 96% of the SNP locus pairs were in complete linkage disequilibrium. Cluster analyses identified six deeply branching, phylogenetically distinct SNP cluster groups (SCGs) and five subgroups. The SCGs were strongly associated with the geographical origin of the M. tuberculosis samples and the birthplace of the human hosts. The most ancestral cluster (SCG-1) predominated in patients from the Indian subcontinent, while SCG-1 and another ancestral cluster (SCG-2) predominated in patients from East Asia, suggesting that M. tuberculosis first arose in the Indian subcontinent and spread worldwide through East Asia. Restricted SCG diversity and the prevalence of less ancestral SCGs in indigenous populations in Uganda and Mexico suggested a more recent introduction of M. tuberculosis into these regions. The East African Indian and Beijing spoligotypes were concordant with SCG-1 and SCG-2, respectively; X and Central Asian spoligotypes were also associated with one SCG or subgroup combination. Other clades had less consistent associations with SCGs. Mycobacterial interspersed repetitive unit (MIRU) analysis provided less robust phylogenetic information, and only 6 of the 12 MIRU microsatellite loci were highly differentiated between SCGs as measured by GST. Finally, an algorithm was devised to identify two minimal sets of either 45 or 6 SNPs that could be used in future investigations to enable global collaborations for studies on evolution, strain differentiation, and biological differences of M. tuberculosis.
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              Molecular epidemiology of tuberculosis.

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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Pub. Group
                2041-1723
                01 September 2014
                : 5
                : 4812
                Affiliations
                [1 ]Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine , London WC1E 7HT, UK
                [2 ]Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine , London WC1E 7HT, UK
                [3 ]Centro de Patogénese Molecular, Faculdade de Farmácia da Universidade de Lisboa , 1649-003 Lisboa, Portugal
                [4 ]Grupo de Micobactérias, Unidade de Microbiologia Médica, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa , 1349-008 Lisboa, Portugal
                [5 ]Biological and Environmental Sciences and Engineering (BESE) Division, King Abdullah University of Science and Technology , Thuwal 23955-6900, Kingdom of Saudi Arabia
                [6 ]School of Computer Science and Information Systems, Birkbeck College , London WC1E 7HX, UK
                Author notes
                Article
                ncomms5812
                10.1038/ncomms5812
                4166679
                25176035
                ae339f95-f8f8-4cef-ae2a-be3006abd2c5
                Copyright © 2014, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 11 April 2014
                : 25 July 2014
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