TY - JOUR TI - Population-based sequencing of Mycobacterium tuberculosis reveals how current population dynamics are shaped by past epidemics AU - Cancino-Muñoz, Irving AU - López, Mariana G AU - Torres-Puente, Manuela AU - Villamayor, Luis M AU - Borrás, Rafael AU - Borrás-Máñez, María AU - Bosque, Montserrat AU - Camarena, Juan J AU - Colijn, Caroline AU - Colomer-Roig, Ester AU - Colomina, Javier AU - Escribano, Isabel AU - Esparcia-Rodríguez, Oscar AU - García-García, Francisco AU - Gil-Brusola, Ana AU - Gimeno, Concepción AU - Gimeno-Gascón, Adelina AU - Gomila-Sard, Bárbara AU - Gónzales-Granda, Damiana AU - Gonzalo-Jiménez, Nieves AU - Guna-Serrano, María Remedios AU - López-Hontangas, José Luis AU - Martín-González, Coral AU - Moreno-Muñoz, Rosario AU - Navarro, David AU - Navarro, María AU - Orta, Nieves AU - Pérez, Elvira AU - Prat, Josep AU - Rodríguez, Juan Carlos AU - Ruiz-García, Ma Montserrat AU - Vanaclocha, Hermelinda AU - Valencia Region Tuberculosis Working Group AU - Comas, Iñaki A2 - Lewnard, Joseph A2 - Franco, Eduardo A2 - Meehan, Conor J A2 - Walker, Timothy M VL - 11 PY - 2022 DA - 2022/07/26 SP - e76605 C1 - eLife 2022;11:e76605 DO - 10.7554/eLife.76605 UR - https://doi.org/10.7554/eLife.76605 AB - 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. KW - Mycobacterium tuberculosis KW - tuberculosis KW - transmission KW - genomic epidemiology KW - whole-genome sequencing JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -