eLife (Jul 2022)

Population-based sequencing of Mycobacterium tuberculosis reveals how current population dynamics are shaped by past epidemics

  • Irving Cancino-Muñoz,
  • Mariana G López,
  • Manuela Torres-Puente,
  • Luis M Villamayor,
  • Rafael Borrás,
  • María Borrás-Máñez,
  • Montserrat Bosque,
  • Juan J Camarena,
  • Caroline Colijn,
  • Ester Colomer-Roig,
  • Javier Colomina,
  • Isabel Escribano,
  • Oscar Esparcia-Rodríguez,
  • Francisco García-García,
  • Ana Gil-Brusola,
  • Concepción Gimeno,
  • Adelina Gimeno-Gascón,
  • Bárbara Gomila-Sard,
  • Damiana Gónzales-Granda,
  • Nieves Gonzalo-Jiménez,
  • María Remedios Guna-Serrano,
  • José Luis López-Hontangas,
  • Coral Martín-González,
  • Rosario Moreno-Muñoz,
  • David Navarro,
  • María Navarro,
  • Nieves Orta,
  • Elvira Pérez,
  • Josep Prat,
  • Juan Carlos Rodríguez,
  • Ma Montserrat Ruiz-García,
  • Hermelinda Vanaclocha,
  • Valencia Region Tuberculosis Working Group,
  • Iñaki Comas

DOI
https://doi.org/10.7554/eLife.76605
Journal volume & issue
Vol. 11

Abstract

Read online

Transmission is a driver of tuberculosis (TB) epidemics in high-burden regions, with assumed negligible impact in low-burden areas. However, we still lack a full characterization of transmission dynamics in settings with similar and different burdens. Genomic epidemiology can greatly help to quantify transmission, but the lack of whole genome sequencing population-based studies has hampered its application. Here, we generate a population-based dataset from Valencia region and compare it with available datasets from different TB-burden settings to reveal transmission dynamics heterogeneity and its public health implications. We sequenced the whole genome of 785 Mycobacterium tuberculosis strains and linked genomes to patient epidemiological data. We use a pairwise distance clustering approach and phylodynamic methods to characterize transmission events over the last 150 years, in different TB-burden regions. Our results underscore significant differences in transmission between low-burden TB settings, i.e., clustering in Valencia region is higher (47.4%) than in Oxfordshire (27%), and similar to a high-burden area as Malawi (49.8%). By modeling times of the transmission links, we observed that settings with high transmission rate are associated with decades of uninterrupted transmission, irrespective of burden. Together, our results reveal that burden and transmission are not necessarily linked due to the role of past epidemics in the ongoing TB incidence, and highlight the need for in-depth characterization of transmission dynamics and specifically tailored TB control strategies.

Keywords