Padronização da técnica molecular RFLP-IS6110 para estudos epidemiológicos da tuberculose em Mato Grosso do Sul

Abstract

Tuberculosis (TB) is a disease of major importance to global health that causes millions of deaths annually. In 2015, the incidence rate per 100 thousand inhabitants was 28.4 in Mato Grosso do Sul and 39.4 in Dourados. Through molecular tools for epidemiological studies, it is possible to characterize and identify strains of Mycobacterium tuberculosis, assisting in the development of disease control measures. The RFLP-IS6110 technique, when compared with other molecular tools, it is considered gold standard because of its high discriminatory power for these studies. In this context, the aim of this study was to standardize the IS6110 RFLP technique for epidemiologic studies of tuberculosis to identify genotypic characteristics of M. tuberculosis populations in Mato Grosso do Sul. The M. tuberculosis strains were isolated from the Central Laboratory and Research Laboratory in Health Sciences’ bacterial collections and the original protocol for genotyping strains was adapted for its use here in the state. The protocol consisted of digestion step with the restriction enzyme PvuII, followed by electrophoresis, Southern blot, hybridization and colorimetric revelation. Genotypic profiles obtained in the membrane were analysed using the RIVM-BioNumerics database; Applied Maths, Sint-Martens-Latem, Belgium. Different patterns of bands were present in the membranes of IS6110 stating cleavage fragments. However, some bands were difficult to be identified, so adjustments such as applying a lower sample aliquot in the gel and longer revelation time were adopted for a better quality of the membranes. Thus, it was possible to group strains that had the same molecular profiles, forming clusters when two or more isolates showed the same genotypic profile. It was possible to observe the importance of standardization and application of RFLP-IS6110 technique for epidemiologic studies of tuberculosis in Mato Grosso do Sul since it is possible to use it as a tool for a better understanding of the disease dynamics in the state.