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PAIDB - Pathogenicity Island Database


NAR Molecular Biology Database Collection entry number 944
Yoon S.H.1, Hur C.-G.2, Oh T.K.3, and Kim J.F.1
1Systems Microbiology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 52 Oun-dong, Yuseong, Daejeon 305-806, Republic of Korea
2Plant Genome Research Center, KRIBB, Republic of Korea
SUP>321C Frontier Microbial Genomics and Applications Center, KRIBB, Republic of Korea

Database Description

The pathogenicity island database (PAIDB; http://www.gem.re.kr/paidb) is a comprehensive relational database of all the reported pathogenicity islands (PAIs) and potential PAI regions which were predicted by a method that combines feature-based analysis and similarity-based analysis. PAIs are genetic elements whose products are essential to the process of disease development. They have been horizontally (laterally) transferred from other microbes and are important in evolution of pathogenesis. Using the PAI Finder search engine application, a multi-sequence query can be analyzed on site for the presence of potential PAIs. As of April 2006, PAIDB contains 112 types of PAIs and 889 GenBank accessions containing either partial or all PAI loci previously reported in the literature, which are present in 497 strains of pathogenic bacteria. The database also offers 310 candidate PAIs predicted from the 118 sequenced prokaryotic genomes. With the increasing number of prokaryotic genomes without functional inference and sequenced genetic regions of suspected involvement in diseases, this internet-based, user-friendly resource has the potential to be of significant use in pathogenomics. PAIDB is part of Genome Encyclopedia of Microbes (GEM; www.gem.re.kr) that is a web portal for microbial genome information.

Acknowledgements

Special thanks go to Young-Kyu Park who was pivotal in constructing web interface and Soohyun Lee who collected PAI-related literature. We are also indebted to Doil Choi, Haeyoung Jeong, Seung-Hwan Park, Choong-Min Ryu, and GEM members for critically reading the manuscript and supporting the work. GEM was funded by the 21C Frontier Microbial Genomics and Applications Center Program, Ministry of Science and Technology, Republic of Korea.

References

1. Yoon S.H., Hur C.-G., Kang H.Y., Kim Y.H., Oh T.K., and Kim J.F. (2005) A computational approach for identifying pathogenicity islands in prokaryotic genomes. BMC Bioinformatics 6: 184.
2. Yoon S.H., Park Y.-K., Lee S., Choi D., Oh T.K., Hur C.-G., and Kim J.F. (2007) Towards pathogenomics: a web-based resource for pathogenicity islands. Nucleic Acids Research 35: in press


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