Zheng, W. and Mutha, N.V.R. and Heydari, H. and Dutta, A. and Siow, C.C. and Jakubovics, N.S. and Wee, W.Y. and Tan, S.Y. and Ang, M.Y. and Wong, G.J. and Choo, S.W. (2016) NeisseriaBase: A specialised Neisseria genomic resource and analysis platform. PeerJ, 2016 (3). p. 1698. ISSN 2167-8359, DOI https://doi.org/10.7717/peerj.1698.
Full text not available from this repository.Abstract
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 horizontal 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 Neisseria species. Methods. The genomic data were retrieved from National Center for Biotechnology Information (NCBI) and annotated using the RAST server which were then stored into the MySQL database. The protein-coding genes were further 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 CSS, utilizing the model-view-controller (MVC) framework. The in-house developed bioinformatics 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 Neisseria 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 Genome Comparison tool (PGC) for comparative genomic 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 http://neisseria.um.edu.my.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Comparative analysis; Genomic resources; Neisseria; NeisseriaBase; Pairwise Genome Comparison tool; Pathogenomics Profiling tool |
| Subjects: | Q Science > Q Science (General) R Medicine > RK Dentistry T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Faculty of Dentistry |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 14 May 2018 08:56 |
| Last Modified: | 14 May 2018 08:56 |
| URI: | http://eprints.um.edu.my/id/eprint/18665 |
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