Investigating extradomiciliary transmission of tuberculosis: An exploratory approach using social network patterns of TB cases and controls and the genotyping of Mycobacterium tuberculosis.

Extradomiciliary contacts have been overlooked in the study of TB transmission due to difficulties in identifying actual contacts in large populations. Complex network analysis provides a framework to model the structure of contacts, specially extradomiciliary ones. We conducted a study of incident sputum-positive TB cases and healthy controls occurring in a moderate TB burden city. Cases and controls were interviewed to obtain data regarding the usual locations of residence, work, study, and leisure. Mycobacterium tuberculosis isolated from sputum was genotyped. The collected data were used to build networks based on a framework of putative social interactions indicating possible TB transmission. A user-friendly open source environment (GraphTube) was setup to extract information from the collected data. Networks based on the likelihood of patient-patient, patient-healthy, and healthy-healthy contacts were setup, depending on a constraint of geographical distance of places attended by the volunteers. Using a threshold for the geographical distance of 300 m, the differences between TB cases and controls are revealed. Several clusters formed by social network nodes with high genotypic similarity were characterized. The developed framework provided consistent results and can be used to support the targeted search of potentially infected individuals and to help to understand the TB transmission.

SNP typing reveals similarity in Mycobacterium tuberculosis genetic diversity between Portugal and Northeast Brazil.

Human tuberculosis is an infectious disease caused by bacteria from the Mycobacterium tuberculosis complex (MTBC). Although spoligotyping and MIRU-VNTR are standard methodologies in MTBC genetic epidemiology, recent studies suggest that Single Nucleotide Polymorphisms (SNP) are advantageous in phylogenetics and strain group/lineages identification. In this work we use a set of 79 SNPs to characterize 1987 MTBC isolates from Portugal and 141 from Northeast Brazil. All Brazilian samples were further characterized using spolygotyping. Phylogenetic analysis against a reference set revealed that about 95% of the isolates in both populations are singly attributed to bacterial lineage 4. Within this lineage, the most frequent strain groups in both Portugal and Brazil are LAM, followed by Haarlem and X. Contrary to these groups, strain group T showed a very different prevalence between Portugal (10%) and Brazil (1.5%). Spoligotype identification shows about 10% of mis-matches compared to the use of SNPs and a little more than 1% of strains unidentifiability. The mis-matches are observed in the most represented groups of our sample set (i.e., LAM and Haarlem) in almost the same proportion. Besides being more accurate in identifying strain groups/lineages, SNP-typing can also provide phylogenetic relationships between strain groups/lineages and, thus, indicate cases showing phylogenetic incongruence. Overall, the use of SNP-typing revealed striking similarities between MTBC populations from Portugal and Brazil.