The molecular clock of Mycobacterium tuberculosis
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 causal 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 MTB molecular clock on a large genomic data set (6,285 strains), covering most of the global MTB diversity and representing different epidemiological settings. We found wide variation in the degree of clocklike structure among data sets, indicating that sampling times are sometimes insufficient to calibrate the clock of MTB. For data sets with temporal structure, we found that MTB genomes accumulate between 1x10-8 and 5x10-7 nucleotide changes per-site-per-year, which corresponds to 0.04 - 2.2 SNPs per-genome-per-year. Contrary to what expected, these estimates were not dependent on the time of the calibration points as they did not change significantly when we used epidemiological isolates (sampled in the last 40 years) or 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 often large, highlighting the importance of using different methods, and of considering carefully their assumptions and limitations. Significance StatementOne of the major recent advancement in evolutionary biology is the development of statistical methods to infer the past evolutionary history of species and populations with genomic data. In the last five years, many researchers have used the molecular clock to study the evolution of Mycobacterium tuberculosis, a bacterial pathogen that causes tuberculosis and is responsible for millions of human deaths every year. The application of the molecular clock to tuberculosis is extremely useful to understand the evolution of drug resistance, the spread of different strains and the origin of the disease. Since some of these studies found contrasting results, we performed a systematic analysis of the molecular clock of MTB. This study will provide an important guideline for future analyses of tuberculosis and other organisms.
02 /Specification & Classification
Click any tag to browse matching papers- Organism
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Within-host Mycobacterium tuberculosis evolution: a population genetics perspective
Ana Y. Morales‐Arce, Rebecca B. Harris, … Jeffrey D. Jensen·EvolutionPeer-reviewed·Mar 31, 2020
- A seventeenth-century Mycobacterium tuberculosis genome supports a Neolithic emergence of the Mycobacterium tuberculosis complex
Susanna J. Sabin, Alexander Herbig, … Kirsten I. Bos·Genome biologyPeer-reviewed·Aug 10, 2020
- Insertion and deletion evolution reflects antibiotics selection pressure in a Mycobacterium tuberculosis outbreak.
M. Godfroid, T. Dagan, … A. Kupczok·PLOS PathogensPeer-reviewed·Sep 30, 2020
- Understanding the epidemiology and pathogenesis of Mycobacterium tuberculosis with non-redundant pangenome and population genetics
Yang Zhou, Richard M. Anthony, … Dick van Soolingen·PLoS ONEPeer-reviewed·May 19, 2025
- Gene Evolutionary Trajectories in M. tuberculosis Reveal Temporal Signs of Selection
A. Chiner-Oms, M. G. Lopez, I. Comas·bioRxiv·Jul 15, 2021
- Unravelling the population structure and transmission patterns of Mycobacterium tuberculosis in Mozambique, a high TB/HIV burden country
Belén Saavedra, Mariana G. López, … Iñaki Comas·Microbial GenomicsPeer-reviewed·Jul 5, 2022