Integrative immunoinformatics for Mycobacterial diseases in R platform

Abstract

The sequencing of genomes of the pathogenic Mycobacterial species causing pulmonary and extrapulmonary tuberculosis, leprosy and other atypical mycobacterial infections, offer immense opportunities for discovering new therapeutics and identifying new vaccine candidates. Enhanced RV, which uses additional algorithms to Reverse Vaccinology (RV), has increased potential to reduce likelihood of undesirable features including allergenicity and immune cross reactivity to host. The starting point for MycobacRV database construction includes collection of known vaccine candidates and a set of predicted vaccine candidates identified from the whole genome sequences of 22 mycobacterium species and strains pathogenic to human and one non-pathogenic Mycobacterium tuberculosis H37Ra strain. These predicted vaccine candidates are the adhesins and adhesin-like proteins obtained using SPAAN at P ad [ 0.6 and screening for putative extracellular or surface localization characteristics using PSORTb v.3.0 at very stringent cutoff. Subsequently, these protein sequences were analyzed through 21 publicly available algorithms to obtain Orthologs, Paralogs, BetaWrap Motifs, Transmembrane Domains, Signal Peptides, Conserved Domains, and similarity to human proteins, T cell epitopes, B cell epitopes, Discotopes and potential Allergens predictions. The Enhanced RV information was analysed in R platform through scripts following well structured decision trees to derive a set of nonredundant 233 most probable vaccine candidates. Additionally, the degree of conservation of potential epitopes across all orthologs has been obtained with reference to the M. tuberculosis H37Rv strain, the most commonly used strain in M. tuberculosis studies. Utilities for the vaccine candidate search and analysis of epitope conservation across the orthologs with reference to M. tuberculosis H37Rv strain are available in the mycobacrvR package in R platform accessible from the ''Download'' tab of MycobacRV webserver. MycobacRV an immunoinformatics database of known and predicted mycobacterial vaccine candidates has been developed and is freely available at http://mycobacteriarv.igib.res.in.

A Web-Based Platform for Designing Vaccines against Existing and Emerging Strains of Mycobacterium tuberculosis

“…For tuberculosis vaccine policies, Zwerling et al has developed a tool [ 54 ]. MycobacRv is another database related to TB vaccine [ 55 ]. MycobacRv has limits its focus to adhesion proteins in the genomes of different mycobacterial species.…”

The Impact of Bioinformatics on Vaccine Design and Development

“…Molecules localized on the cell membrane or extracellularly are beter antigens because they are more exposed to host cells, speciically to those related to the immune system; thus, they have a greater probability of generating a protective response [15]. In addition to the software that can predict these characteristics, there are protein databases that generate information about protein subcellular localization, such as LOCATE, LocDB, and eSLDB.…”

Identification of Novel Potential Vaccine Candidates against Tuberculosis Based on Reverse Vaccinology

“…The RV process begins with the proteomic information in a database; then, the selection of vaccine candidates is performed by means of different bioinformatics tools that analyze the properties of each protein and the human immune response generated by them [ 8 – 10 , 15 ]. Good vaccine candidates are considered those that do not present homology with human proteins to avoid the generation of a potential autoimmune response [ 16 ]; these candidates must also lack transmembrane regions, in order to facilitate their expression. In addition, it is necessary to analyze the lack of cross-reaction among other pathogenic antigens [ 14 ].…”

“…Another characteristic a good vaccine candidate should have is to possess good antigenic and adhesin properties, which are important for the pathogenesis of the microorganism and for protection against the disease [ 13 , 17 ]. Extracellular or cell surface localized proteins are good vaccine candidates due to their increased accessibility to the immune system [ 14 , 16 ]. Currently, software useful for simulation of the immune response has been developed that could help in the search for novel vaccine candidates [ 15 ].…”