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A robust SNP barcode for typing Mycobacterium tuberculosis complex strains

Author

Listed:
  • Francesc Coll

    (Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine)

  • Ruth McNerney

    (Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine)

  • José Afonso Guerra-Assunção

    (Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine)

  • Judith R. Glynn

    (Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine)

  • João Perdigão

    (Centro de Patogénese Molecular, Faculdade de Farmácia da Universidade de Lisboa)

  • Miguel Viveiros

    (Grupo de Micobactérias, Unidade de Microbiologia Médica, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa)

  • Isabel Portugal

    (Centro de Patogénese Molecular, Faculdade de Farmácia da Universidade de Lisboa)

  • Arnab Pain

    (King Abdullah University of Science and Technology)

  • Nigel Martin

    (School of Computer Science and Information Systems, Birkbeck College)

  • Taane G. Clark

    (Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine
    Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine)

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.

Suggested Citation

  • Francesc Coll & Ruth McNerney & José Afonso Guerra-Assunção & Judith R. Glynn & João Perdigão & Miguel Viveiros & Isabel Portugal & Arnab Pain & Nigel Martin & Taane G. Clark, 2014. "A robust SNP barcode for typing Mycobacterium tuberculosis complex strains," Nature Communications, Nature, vol. 5(1), pages 1-5, December.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms5812
    DOI: 10.1038/ncomms5812
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    Cited by:

    1. Anna G. Green & Chang Ho Yoon & Michael L. Chen & Yasha Ektefaie & Mack Fina & Luca Freschi & Matthias I. Gröschel & Isaac Kohane & Andrew Beam & Maha Farhat, 2022. "A convolutional neural network highlights mutations relevant to antimicrobial resistance in Mycobacterium tuberculosis," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    2. Arianne Lovey & Sheetal Verma & Vaishnavi Kaipilyawar & Rodrigo Ribeiro-Rodrigues & Seema Husain & Moises Palaci & Reynaldo Dietze & Shuyi Ma & Robert D. Morrison & David. R. Sherman & Jerrold J. Elln, 2022. "Early alveolar macrophage response and IL-1R-dependent T cell priming determine transmissibility of Mycobacterium tuberculosis strains," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    3. Jody Phelan & Paula Josefina Gomez-Gonzalez & Nuria Andreu & Yosuke Omae & Licht Toyo-Oka & Hideki Yanai & Reiko Miyahara & Supalert Nedsuwan & Paola Florez Sessions & Susana Campino & Neneh Sallah & , 2023. "Genome-wide host-pathogen analyses reveal genetic interaction points in tuberculosis disease," Nature Communications, Nature, vol. 14(1), pages 1-7, December.

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