The molecular clock of Mycobacterium tuberculosis

PLoS Pathog. 2019 Sep 12;15(9):e1008067. doi: 10.1371/journal.ppat.1008067. eCollection 2019 Sep.

Abstract

The molecular clock and its phylogenetic applications to genomic data have changed how we study and understand one of the major human pathogens, Mycobacterium tuberculosis (MTB), the etiologic agent of tuberculosis. Genome sequences of MTB strains sampled at different times are increasingly used to infer when a particular outbreak begun, when a drug-resistant clone appeared and expanded, or when a strain was introduced into a specific region. Despite the growing importance of the molecular clock in tuberculosis research, there is a lack of consensus as to whether MTB displays a clocklike behavior and about its rate of evolution. Here we performed a systematic study of the molecular clock of MTB on a large genomic data set (6,285 strains), covering different epidemiological settings and most of the known global diversity. We found that sampling times below 15-20 years were often insufficient to calibrate the clock of MTB. For data sets where such calibration was possible, we obtained a clock rate between 1x10-8 and 5x10-7 nucleotide changes per-site-per-year (0.04-2.2 SNPs per-genome-per-year), with substantial differences between clades. These estimates were not strongly dependent on the time of the calibration points as they changed only marginally when we used epidemiological isolates (sampled in the last 40 years) or three ancient DNA samples (about 1,000 years old) to calibrate the tree. Additionally, the uncertainty and the discrepancies in the results of different methods were sometimes large, highlighting the importance of using different methods, and of considering carefully their assumptions and limitations.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bayes Theorem
  • Biological Clocks / genetics*
  • Biological Clocks / physiology
  • DNA, Bacterial / genetics
  • Evolution, Molecular
  • Genome, Bacterial
  • Humans
  • Models, Biological
  • Molecular Epidemiology
  • Mycobacterium bovis / genetics
  • Mycobacterium bovis / physiology
  • Mycobacterium tuberculosis / genetics*
  • Mycobacterium tuberculosis / pathogenicity
  • Mycobacterium tuberculosis / physiology
  • Phylogeny
  • Polymorphism, Single Nucleotide
  • Time Factors
  • Tuberculosis / epidemiology
  • Tuberculosis / microbiology

Substances

  • DNA, Bacterial

Grants and funding

SG, DB and FM were supported by the Swiss National Science Foundation (grants 310030_166687, IZRJZ3_164171, IZLSZ3_170834 and CRSII5_177163), the European Research Council (309540-EVODRTB) and SystemsX.ch. SD was supported by a McKenzie fellowship from the University of Melbourne. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.