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PanRV: Pangenome-reverse vaccinology approach for identifications of potential vaccine candidates in microbial pangenome.

Authors :
Naz, Kanwal
Naz, Anam
Ashraf, Shifa Tariq
Rizwan, Muhammad
Ahmad, Jamil
Baumbach, Jan
Ali, Amjad
Source :
BMC Bioinformatics. 3/12/2019, Vol. 20 Issue 1, p1-10. 10p. 1 Diagram, 3 Charts, 1 Graph.
Publication Year :
2019

Abstract

Background: A revolutionary diversion from classical vaccinology to reverse vaccinology approach has been observed in the last decade. The ever-increasing genomic and proteomic data has greatly facilitated the vaccine designing and development process. Reverse vaccinology is considered as a cost-effective and proficient approach to screen the entire pathogen genome. To look for broad-spectrum immunogenic targets and analysis of closelyrelated bacterial species, the assimilation of pangenome concept into reverse vaccinology approach is essential. The categories of species pangenome such as core, accessory, and unique genes sets can be analyzed for the identification of vaccine candidates through reverse vaccinology. Results: We have designed an integrative computational pipeline term as “PanRV” that employs both the pangenome and reverse vaccinology approaches. PanRV comprises of four functional modules including i) Pangenome Estimation Module (PGM) ii) Reverse Vaccinology Module (RVM) iii) Functional Annotation Module (FAM) and iv) Antibiotic Resistance Association Module (ARM). The pipeline is tested by using genomic data from 301 genomes of Staphylococcus aureus and the results are verified by experimentally known antigenic data. Conclusion: The proposed pipeline has proved to be the first comprehensive automated pipeline that can precisely identify putative vaccine candidates exploiting the microbial pangenome. PanRV is a Linux based package developed in JAVA language. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14712105
Volume :
20
Issue :
1
Database :
Academic Search Index
Journal :
BMC Bioinformatics
Publication Type :
Academic Journal
Accession number :
135820604
Full Text :
https://doi.org/10.1186/s12859-019-2713-9