Tuberculosis (TB) kills more individuals in the world than any other disease, and a threat made direr by the coverage of drug-resistant strains of Mycobacterium tuberculosis (Mtb). Bacillus Calmette–Guérin (BCG) is the single TB vaccine licensed for use in human beings and effectively protects infants and children against severe military and meningeal TB. We applied advanced computational techniques to develop a universal TB vaccine. In the current study, we select the very conserved, experimentally confirmed Mtb antigens, including Rv2608, Rv2684, Rv3804c (Ag85A), and Rv0125 (Mtb32A) to design a novel multi-epitope subunit vaccine. By using the Immune Epitopes Database (IEDB), we predicted different B-cell and T-cell epitopes. An adjuvant (Griselimycin) was also added to vaccine construct to improve its immunogenicity. Bioinformatics tools were used to predict, refined, and validate the 3D structure and then docked with toll-like-receptor (TLR-3) using different servers. The constructed vaccine was used for further processing based on allergenicity, antigenicity, solubility, different physiochemical properties, and molecular docking scores. The in silico immune simulation results showed significant response for immune cells. For successful expression of the vaccine in E. coli, in-silico cloning and codon optimization were performed. This research also sets out a good signal for the design of a peptide-based tuberculosis vaccine. In conclusion, our findings show that the known multi-epitope vaccine may activate humoral and cellular immune responses and maybe a possible tuberculosis vaccine candidate. Therefore, more experimental validations should be exposed to it.
An aerobic microorganism with an ability to utilize phenol as sole carbon and energy source was isolated from phenol-contaminated wastewater samples. The isolate was identified as Bacillus amyloliquefaciens strain WJDB-1 based on morphological, physiological, and biochemical characteristics, and 16S rDNA sequence analysis. Strain WJDB-1 immobilized in alginate-chitosan-alginate (ACA) microcapsules could degrade 200 mg/l phenol completely within 36 h. The concentration of phenol was determined using differential pulse voltammetry (DPV) at glassy carbon electrode (GCE) with a linear relationship between peak current and phenol concentration ranging from 2.0 to 20.0 mg/l. Cells immobilized in ACA microcapsules were found to be superior to the free suspended ones in terms of improving the tolerance to the environmental loadings. The optimal conditions to prepare microcapsules for achieving higher phenol degradation rate were investigated by changing the concentrations of sodium alginate, calcium chloride, and chitosan. Furthermore, the efficiency of phenol degradation was optimized by adjusting various processing parameters, such as the number of microcapsules, pH value, temperature, and the initial concentration of phenol. This microorganism has the potential for the efficient treatment of organic pollutants in wastewater.
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