In Silico identification of M. TB proteins with diagnostic potential

Abstract

TB, caused by Mycobacterium tuberculosis (MTB), is one of the major global infectious diseases. For the pandemic control, early diagnosis with sensitive and specific methods is fundamental. With the advent of bioinformatics' tools, the identification of several proteins involved in the pathogenesis of TB (TB) has been possible. In the present work, the MTB genome was explored to look for molecules with possible antigenic properties for their evaluation as part of new generation diagnostic kits based on the release of cytokines. Seven proteins from the MTB proteome and some of their combinations suited the computational test and the results suggested their potential use for the diagnosis of infection in the following population groups: Cuba, Mexico, Malaysia and sub-Saharan Africa. Our predictions were performed using public bioinformatics tools plus three computer programs, developed by our group, to facilitate information retrieval and processing.

Figure 1

Population coverage (HLA Class I & Class II) of seven selected proteins (listed on Table 1) and three of its combinations (CB1: Rv1509+Rv1508c; CB2: Rv2645+Rv1509; CB3: Rv2658c+Rv1508c), for the tested populations.