- Authors: Perdigão J, Silva C, Diniz J, Pereira C, Machado D, Ramos J, Silva H, Abilleira F, Brum C, Reis AJ, Macedo M, Scaini JL, Silva AB, Esteves L, Macedo R, Maltez F, Clemente S, Coelho E, Viegas S, Rabna P, Rodrigues A, Taveira N, Jordao L, Kritski A, Lapa e Silva JR, Mokrousov I, Couvin D, Rastogi N, Couto I, Pain A, McNerney R, Clark TG, von Groll A, Dalla Costa ER, Rossetti ML, Silva PEA, Viveiros M, Portugal I
- Publication Year: 2019
- Journal: Infection Genetics and Evolution
- Link: https://www.sciencedirect.com/science/article/pii/S1567134818301023?via%3Dihub%20
Tuberculosis (TB) remains a major health problem within the Community of Portuguese Language Speaking Countries (CPLP). Despite the marked variation in TB incidence across its member-states and continued human migratory flux between countries, a considerable gap in the knowledge on the Mycobacterium tuberculosis population structure and strain circulation between the countries still exists. To address this, we have assembled and analysed the largest CPLP M. tuberculosis molecular and drug susceptibility dataset, comprised by a total of 1447 clinical isolates, including 423 multidrug-resistant isolates, from five CPLP countries. The data herein presented reinforces Latin American and Mediterranean (LAM) strains as the hallmark of M. tuberculosis populational structure in the CPLP coupled with country-specific differential prevalence of minor clades. Moreover, using high-resolution typing by 24-loci MIRU-VNTR, six cross-border genetic clusters were detected, thus supporting recent clonal expansion across the Lusophone space. To make this data available to the scientific community and public health authorities we developed CPLP-TB (available at http://cplp-tb.ff.ulisboa.pt), an online database coupled with web-based tools for exploratory data analysis. As a public health tool, it is expected to contribute to improved knowledge on the M. tuberculosis population structure and strain circulation within the CPLP, thus supporting the risk assessment of strain-specific trends.