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NeisseriaBase: a specialised Neisseria genomic resource and analysis platform

Lookup NU author(s): Professor Nicholas JakubovicsORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Background. The gram-negative Neisseria is associated with two of the most potent human epidemic diseases: meningococcal meningitis and gonorrhoea. In both cases, disease is caused by bacteria colonizing human mucosal membrane surfaces. Overall, the genus shows great diversity and genetic variation mainly due to its ability to acquire and incorporate genetic material from a diverse range of sources through orizontal gene transfer. Although a number of databases exist for the Neisseria genomes, they are mostly focused on the pathogenic species. In this present study we present the freely available NeisseriaBase, a database dedicated to the genus Neisseria encompassing the complete and draft genomes of 15 pathogenic and commensal Netsseria species.Methods. The genomic data were retrieved from National Center for Biotechnology Information (NCBI) and annotated using the RAST server whic were then stored into the MySQL database. The protein-coding genes were ftirther analyzed to obtain information such as calculation of GC content (%), predicted hydrophobicity and molecular weight (Da) using in-house Perl scripts. The web application was developed following the secure four-tier web application architecture: (1) client workstation, (2) web server, (3) application server, and (4) database server. The web interface was constructed using PHP, JavaScript, jQuery, AJAX and CBS, utilizing the model view-controller (MVC) framework. The in-house developed bioinforrnatics tools implemented in NeisseraBase were developed using Python, Perl, BioPerl and R languages.Results. Currently, NeisseriaBase houses 603,500 Coding Sequences (CDSs), 16,071 RNAs and 13,119 tRNA genes from 227 Netsserta genomes. The database is equipped with interactive web interfaces. Incorporation of the JBrowse genome browser in the database enables fast and smooth browsing of Neisseria genomes. NeisseriaBase includes the standard BLAST program to facilitate homology searching, and for Virulence Factor Database (VFDB) specific homology searches, the VFDB BLAST is also incorporated into the database. In addition, NeisseriaBase is equipped with in-house designed tools such as the Pairwise Genonle Comparison tool (PGC) for comparative genornic analysis and the Pathogenomics Profiling Tool (PathoProT) for the comparative pathogenomics analysis of Neisseria strains.Discussion. This user-friendly database not only provides access to a host of genomic resources on Neisseria but also enables high-quality comparative genome analysis, which is crucial for the expanding scientific community interested in Neisseria research. This database is freely available at

Publication metadata

Author(s): Zheng WN, Mutha NVR, Heydari H, Dutta A, Siow CC, Jakubovics NS, Wee WY, Tan SY, Ang MY, Wong GJ, Choo SW

Publication type: Article

Publication status: Published

Journal: PeerJ

Year: 2016

Volume: 4

Online publication date: 17/03/2016

Acceptance date: 26/01/2016

Date deposited: 16/05/2016

ISSN (electronic): 2167-8359

Publisher: PeerJ, Ltd.


DOI: 10.7717/peerj.1698


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Funder referenceFunder name
University of Malaya
RG541-13HTMUniversity of Malaya
UM.C/625/1/HIR/MOE/CHAN/08Ministry of Education, Malaysia