CoryneRegNet is an ontology-based data warehouse for the reconstruction and visualization of transcriptional regulatory interactions in prokaryotes. To extend the biological content of CoryneRegNet, we added comprehensive data on transcriptional regulations in the model organism Escherichia coli K-12, originally deposited in the international reference database RegulonDB. The enhanced web interface of CoryneRegNet offers several types of search options. The results of a search are displayed in a table-based style and include a visualization of the genetic organization of the respective gene region. Information on DNA binding sites of transcriptional regulators is depicted by sequence logos. The results can also be displayed by several layouters implemented in the graphical user interface GraphVis, allowing, for instance, the visualization of genome-wide network reconstructions and the homology-based inter-species comparison of reconstructed gene regulatory networks.
1. Baumbach J, Wittkop T, Rademacher K, Rahmann S, Brinkrolf K, Tauch A. (2007) CoryneRegNet 3.0 - An interactive systems biology platform for the analysis of gene regulatory networks in corynebacteria and Escherichia coli. J Biotechnol. 2007 (in press, http://dx.doi.org/10.1016/j.jbiotec.2006.12.012).
2. Baumbach J, Brinkrolf K, Wittkop T, Tauch A, Rahmann S (2006) CoryneRegNet 2: An Integrative Bioinformatics Approach for Reconstruction and Comparison of Transcriptional Regulatory Networks in Prokaryotes. Journal of Integrative Bioinformatics, 3(2):24, 2006.
3. Baumbach J, Brinkrolf K, Czaja LF, Rahmann S, Tauch A (2006) CoryneRegNet: An ontology-based data warehouse of corynebacterial transcription factors and regulatory networks. BMC Genomics. 2006 Feb 14;7(1):24. (http://www.biomedcentral.com/1471-2164/7/24).
Translation Initiation Site Annotation in prokaryotic genomes
G-quadruplex motifs in the promoters of human, chimpanzee, rat, mouse and bacterial genes
small regulatory RNA in microbial genomes
Bacteriocin natural antimicrobial peptides
Peroxidases from plants, bacteria and fungi
A database for multilocus sequence typing analysis of the Bacillus cereus group of bacteria
Conserved syntenies for various animal, plant and bacterial genomes
The treatment of infections is increasingly compromised by the ability of bacteria to develop resistance to antibiotics through mutations or through the acquisition of resistance genes. Antibiotic resistance genes also have the potential to be used for bio-terror purposes through genetically modified organisms. In order to facilitate the identification and characterization of these genes, we have created a manually curated database - the Antibiotic Resistance Genes Database (ARDB) - unifying most of the publicly available information on antibiotic resistance. Each gene and resistance type is annotated with rich information, including resistance profile, mechanism of action, ontology, COG, and CDD annotations, as well as external links to sequence and protein databases. Our database also supports sequence similarity searches and implements an initial version of a tool for characterizing common mutations that confer antibiotic resistance. The information we provide can be used as compendium of antibiotic resistance factors as well as to identify the resistance genes of newly sequenced genes, genomes, or metagenomes. Currently, ARDB contains resistance information for 13,293 genes, 377 resistance types, 257 antibiotics, 632 genomes, 933 species and 124 genera.
Recent develoments :
Several analyses provided by our database now also produce output in tab-delimited spreadsheet format (with .xls extension for easy access from OpenOffice or MS Office). Such output is now available for comparisons of resistance profiles between two or more organisms in our database, as well as for genome annotation. Several of the algorithms underlying our database have been improved resulting in faster access and eliminating browser time-outs for the more intensive queries.
Alignable Tight Genomic Clusters of Closely Related Prokaryotic Genomes
Predicted operons in bacterial and archaeal genomes
Predicted highly expressed genes in prokaryotic genomes
Predicted operons in bacterial and archaeal genomes
Database for comparative genome analysis of 15 strains of the genus Streptococcus
The VNTRDB provides comprehensive information about bacterial VNTR loci in genome sequences. This database was constructed by the method, VNTR Analyzer, developed by Chang et al., (1) and the accuracy of the database content was tested by comparing it with published TR loci. Although a similar site, GPMS, has been reported by Denoeud and Vergnaud (2), what the database provides are mainly VNTRs discovered when comparing two highly-conserved strains of a single bacterial species. But in the VNTRDB, three extra functions can be obtained: 1) A visualization tool is provided to allow users to examine or realign the alignments, it may solve those problems caused by the uncertainties of locus length or copy number; 2) To enable the discovery of more putative polymorphic tandem repeats, the comparisons were made between bacterial genomes that are not necessarily from the same species or with high levels of sequence identity; 3) The identification of unique tandem repeats. Theoretically, any unique sequence can serve as DNA marker for the identification of bacteria, so a VNTR locus that is unique could be one such marker. In order to confirm the utility of these loci for identification they would need to be tested experimentally. Although VNTRDB and GPMS were constructed by different strategies and have somewhat different database contents, the two databases are likely to serve the users in a complementary fashion.
This work was partially supported by grants NSC93-3112-B-002-022 and NSC92-2313-B-130-001 from the National Science Council, and grant COA95-13.3.2-BAPHIQ-B1 from Bureau of Animal and Plant Health Inspection and Quarantine.
1. Chang, C.H., Chuang, H. Y., Chiang, Y. H., Chiou, C. S., Lu, H. I., and Kao, C. Y. (2004) Automatically predicting possible loci of variable number of tandem repeats. BIBE’04,
2. Denoeud, F. and Vergnaud, G. (2004) Identification of polymorphic tandem repeats by direct comparison of genome sequence from different bacterial strains: a Web-based resource. BMC Bioinformatics, 5, 4.