The most important targets for vaccine development are the proteins that are highly expressed by the microorganisms during infection in-vivo. A number of Mycobacterium tuberculosis (Mtb) proteins are also reported to be expressed in-vivo at different phases of infection. In the present study, we analyzed multiple published databases of gene expression profiles of Mtb in-vivo at different phases of infection in animals and humans and selected 38 proteins that are highly expressed in the active, latent and reactivation phases. We predicted T- and B-cell epitopes from the selected proteins using HLAPred for T-cell epitope prediction and BCEPred combined with ABCPred for B-cell epitope prediction. For each selected proteins, regions containing both T- and B-cell epitopes were identified which might be considered as important candidates for vaccine design against tuberculosis.
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.
Despite recent advances in diagnosis, tuberculosis (TB) remains one of the ten leading causes of death worldwide. Here, we engineered Mycobacterium tuberculosis (Mtb) proteins (ESAT6, CFP10, and MTB7.7) to self-assemble into core-shell nanobeads for enhanced TB diagnosis. Respective purified Mtb antigen-coated polyester beads were characterized and their functionality in TB diagnosis was tested in whole blood cytokine release assays. Sensitivity and specificity were studied in 11 pulmonary TB patients (PTB) and 26 healthy individuals composed of 14 Tuberculin Skin Test negative (TSTn) and 12 TST positive (TSTp). The production of 6 cytokines was determined (IFNγ, IP10, IL2, TNFα, CCL3, and CCL11). To differentiate PTB from healthy individuals (TSTp + TSTn), the best individual cytokines were IL2 and CCL11 (>80% sensitivity and specificity) and the best combination was IP10 + IL2 (>90% sensitivity and specificity). We describe an innovative approach using full-length antigens attached to biopolyester nanobeads enabling sensitive and specific detection of human TB.