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Population structure, biogeography and transmissibility of Mycobacterium tuberculosis

Author

Listed:
  • Luca Freschi

    (Harvard Medical School)

  • Roger Vargas

    (Harvard Medical School
    Harvard Medical School)

  • Ashaque Husain

    (Ministry of Health and Family Welfare)

  • S. M. Mostofa Kamal

    (National Institute of Diseases of the Chest and Hospital)

  • Alena Skrahina

    (Republican Scientific and Practical Centre for Pulmonology and Tuberculosis)

  • Sabira Tahseen

    (National Tuberculosis Control Programme)

  • Nazir Ismail

    (National Institute for Communicable Diseases
    University of Pretoria)

  • Anna Barbova

    (Ministry of Health)

  • Stefan Niemann

    (Borstel Research Centre)

  • Daniela Maria Cirillo

    (IRCCS San Raffaele Scientific Institute)

  • Anna S. Dean

    (World Health Organization)

  • Matteo Zignol

    (World Health Organization)

  • Maha Reda Farhat

    (Harvard Medical School
    Massachusetts General Hospital)

Abstract

Mycobacterium tuberculosis is a clonal pathogen proposed to have co-evolved with its human host for millennia, yet our understanding of its genomic diversity and biogeography remains incomplete. Here we use a combination of phylogenetics and dimensionality reduction to reevaluate the population structure of M. tuberculosis, providing an in-depth analysis of the ancient Indo-Oceanic Lineage 1 and the modern Central Asian Lineage 3, and expanding our understanding of Lineages 2 and 4. We assess sub-lineages using genomic sequences from 4939 pan-susceptible strains, and find 30 new genetically distinct clades that we validate in a dataset of 4645 independent isolates. We find a consistent geographically restricted or unrestricted pattern for 20 groups, including three groups of Lineage 1. The distribution of terminal branch lengths across the M. tuberculosis phylogeny supports the hypothesis of a higher transmissibility of Lineages 2 and 4, in comparison with Lineages 3 and 1, on a global scale. We define an expanded barcode of 95 single nucleotide substitutions that allows rapid identification of 69 M. tuberculosis sub-lineages and 26 additional internal groups. Our results paint a higher resolution picture of the M. tuberculosis phylogeny and biogeography.

Suggested Citation

  • Luca Freschi & Roger Vargas & Ashaque Husain & S. M. Mostofa Kamal & Alena Skrahina & Sabira Tahseen & Nazir Ismail & Anna Barbova & Stefan Niemann & Daniela Maria Cirillo & Anna S. Dean & Matteo Zign, 2021. "Population structure, biogeography and transmissibility of Mycobacterium tuberculosis," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26248-1
    DOI: 10.1038/s41467-021-26248-1
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    References listed on IDEAS

    as
    1. Maha R. Farhat & Luca Freschi & Roger Calderon & Thomas Ioerger & Matthew Snyder & Conor J. Meehan & Bouke de Jong & Leen Rigouts & Alex Sloutsky & Devinder Kaur & Shamil Sunyaev & Dick van Soolingen , 2019. "GWAS for quantitative resistance phenotypes in Mycobacterium tuberculosis reveals resistance genes and regulatory regions," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    2. Dray, Stéphane & Dufour, Anne-Béatrice, 2007. "The ade4 Package: Implementing the Duality Diagram for Ecologists," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 22(i04).
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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.

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