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.
The purpose of this study was to investigate the composition of throat microbiota in pulmonary tuberculosis patients (PTB) in comparison to healthy tuberculin skin test positive (TSTp) and negative (TSTn) individuals. Throat swabs samples were collected, and the microbiota was characterized. Richer operational taxonomic units (OTUs) were present in PTB group, compared to TSTp and TSTn. Regarding alpha diversity analysis there was a higher community diversity in TSTn compared to TSTp. Beta diversity analysis showed different species composition in TSTp compared to TSTn and PTB. There was higher presence of Firmicutes in PTB and TSTn compared to TSTp group at phylum level. At the genus level, Leuconostoc and Enterococcus were higher in TSTn compared to TSTp and Pediococcus, Chryseobacterium, Bifidobacterium, Butyrivibrio, and Bulleidia were higher in PTB compared to TSTn. Streptococcus was higher in TSTn compared to PTB and Lactobacillus in PTB compared to TSTp. At species level, Streptococcus sobrinus and Bulleidia moorei were higher in PTB compared to TSTn individuals, while Lactobacillus salivarius was higher in PTB compared to TSTp. The differences in the microbiome composition could influence the resistance/susceptibility to Mtb infection.