Development and Analysis of Bacterial Pangenome and Reverse Vaccinology based Pipeline (PanRV)

Abstract

The high level of antibiotic resistance in microbial species and their continuously evolving genomes are making the existing therapies ineffective. Therefore, vaccines are generally considered better alternative to combat antibiotic resistance and reducing bacterial infection burden. Since the last decade, a revolutionary diversion has been observed from classical vaccinology to reverse vaccinology mainly due to the ever-increasing genomics and proteomics data that has greatly facilitated the vaccine designing and development process. Additionally, reverse vaccinology is considered as a cost-effective and proficient approach to screen the entire pathogen genome/proteome. The genome variations among several strains belong to varied ecological niches, limiting the efficacy of vaccines against a finite range of bacteria. This vast genomic diversity accumulates a large number of variable genes in species gene pool ultimately resulting in the species pangenome expansion. Therefore, considering a single representative strain (genome) is not sufficient to estimate the exact pangenome and is unfavorable to be targeted for broad-spectrum therapeutics. For instance, single antigenic protein ClfA, Efb, FnBPB, Hla, IsdB, SdrD, and Spa are effective against some of Staphylococcus aureus (S. aureus) strains but not all. Therefore, a vaccine must consist of highly conserved, immunogenic, and antigenic protein to be effective against broad range of closely related microbial species. Thousands of bacterial genomes are now available to explore genomic diversity and new therapeutic targets. This ever-expending genomic data require computational biologists to develop a faster, efficient, and cost-effective computational framework to analyze the genomic data, conservation in species in order to expedite the ABSTRACT xv vaccine development process and to design a universal broad-spectrum vaccine against multi-drug resistant pathogens. The integration of different predictive tools in the form of a single package can be useful to deal with more complicated biological problems. This approach saves time and provides ease to biologist to tackle with extensive biological data. It generates predictive results of complex biological mechanisms by combining the outputs obtained from various other tools with high precision and better interpretation. Considering the aforementioned scenario and to bring ease in prediction of effective vaccine candidates in larger set of data (multiple genomes), a Pangenome Reverse Vaccinology pipeline “PanRV” has been developed. PanRV is the first comprehensive automated pipeline that employed pangenome concept into the RV approach so that genomic repertoire of all the available isolates of a species can be exploited to identify vaccine targets. The pipeline is user-friendly as it has an interactive graphical interface and one step installation process through the designed installer. It is a Linux based package developed in JAVA language. Nonetheless, it is a significant step towards the prioritization of broad-spectrum drugs and vaccine candidates. The pipeline is tested on selected bacterial species though equally applicable to all bacterial species. The pipeline integrates a number of standalone bioinformatics tools and databases. The pipeline has multiple functional modules and provides an interactive Graphical User Interface (GUI). The two major modules include 1) Pangenome Estimation Module (PGM) and 2) Reverse Vaccinology Module (RVM). Other modules include 3) Functional Annotation Module (FAM) and 4) Antibiotic Resistance Association Module (ARM). The full PanRV package with all dependencies, automatic installer and the user manual are provided at https://sourceforge.net/projects/panrv2/.