A comprehensive in silico analysis of putative outer membrane and secretory hydrolases from the pathogenic Leptospira: Possible implications in pathogenesis.

Outer surface/membrane and virulent secretory proteins are primarily crucial for pathogenesis. Secreted and outer membrane hydrolases of many pathogens play an important role in attenuating the host immune system. Leptospira expresses many such proteins, and few have been characterized to display various roles, including host immune evasion. However, identification, classification, characterization, and elucidation of the possible role of Leptospira's outer membrane and secretory hydrolases have yet to be explored. In the present study, we used bioinformatics tools to predict exported proteins from the pathogenic Leptospira proteome. Moreover, we focused on secretory and outer membrane putative hydrolases from the exported proteins to generate a deeper understanding. Our analysis yielded four putative outer/secretory hydrolases, LIC_10995, LIC_11183, LIC_11463, and LIC_12988, containing α/ß hydrolase fold and displayed similarity with lipase motif. Moreover, their conservation analysis of the predicted hydrolases across the spectrum of different Leptospira species showed high clustering with the pathogenic species. Outer membrane and secretory proteins with lipolytic activity may have a role in pathogenesis. This is the first bioinformatics analysis of secretory and outer membrane α/ß hydrolases from leptospiral species. However, experimental studies are indeed required to unravel this possibility.

Multiepitope-based vaccine design by exploring antigenic potential among leptospiral lipoproteins using comprehensive immunoinformatics and structure-based approaches.

Leptospirosis is a tropical and globally neglected zoonotic disease caused by pathogenic spirochetes, Leptospira. Although the disease has been studied for decades, a potent or effective vaccine is not available so far. Efforts are being made to design an efficient vaccine candidate using different approaches. Immunoinformatics approaches have been proven to be promising in terms of time and cost. Here, we used immunoinformatics and structure-based approaches to evaluate antigenic B- and T-cell epitopes present on the leptospiral lipoproteins (LipL). The promiscuous overlapping epitopes (B-cell, T-cell, interferon (IFN)-γ positive, and non-allergens), which can induce humoral, cell-mediated, and innate immunity, were selected to generate a multiepitope chimeric vaccine. To enhance the vaccine immunogenicity, a Toll-like receptor (TLR) agonist was fused to the vaccine with a suitable linker. The chimeric vaccine structure was predicted for molecular docking studies with immune receptors. Moreover, the stability of the vaccine-immune receptor complexes was analyzed by normal mode analysis (NMA). The potency of the vaccine construct was predicted by the immune simulation tool. The study provides additional information toward constructing peptide-based chimeric vaccines  against Leptospira.

Immunoinformatics analysis of antigenic epitopes and designing of a multi-epitope peptide vaccine from putative nitro-reductases of Mycobacterium tuberculosis DosR.

Mycobacterium tuberculosis (Mtb) resides in alveolar macrophages as a non-dividing and dormant state causing latent tuberculosis. Currently, no vaccine is available against the latent tuberculosis. Latent Mtb expresses ~48 genes under the control of DosR regulon. Among these, putative nitroreductases have significantly high expression levels, help Mtb to cope up with nitrogen stresses and possess antigenic properties. In the current study, immunoinformatics methodologies are applied to predict promiscuous antigenic T-cell epitopes from putative nitro-reductases of the DosR regulon. The promiscuous antigenic T-cell epitopes prediction was performed on the basis of their potential to induce an immune response and forming a stable interaction with the HLA alleles. The highest antigenic promiscuous epitopes were assembled for designing an in-silico vaccine construct. A TLR-2 agonist Phenol-soluble modulin alpha 4 was exploited as an adjuvant. Molecular docking and Molecular Dynamics Simulations were used to predict the stability of vaccine construct with the immune receptor. The predicted promiscuous epitopes may be helpful in the construction of a subunit vaccine against latent tuberculosis, which can also be administered along with the BCG to increase its efficacy. Experimental validation is a prerequisite for the in-silico designed vaccine construct against TB infection.