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Nucleic Acids Research Advance Access published online on November 5, 2009
Nucleic Acids Research, doi:10.1093/nar/gkp935
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© The Author(s) 2009. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Database Issue

PeroxisomeDB 2.0: an integrative view of the global peroxisomal metabolome

Agatha Schlüter1,2, Alejandro Real-Chicharro3, Toni Gabaldón4, Francisca Sánchez-Jiménez2,3 and Aurora Pujol1,2,5,*

1Neurometabolic Disease Lab, Institut de Neuropatologia de Bellvitge (IDIBELL), Gran Via n 199, 08907 L’Hospitalet de Llobregat, Barcelona, 2CIBERER, Centro de Investigación Biomédica en Red de Enfermedades Raras, 3Biología Molecular y Bioquímica, Universidad de Málaga, Málaga, 4Bioinformatics Department, Centre de Regulació Genòmica (CRG), Barcelona and 5Institució Catalana de Recerca i Estudis Avançats (ICREA), Spain

*To whom correspondence should be addressed. Tel: +34 93 2607343; Fax: +34 93 2607414; Email: apujol{at}idibell.cat

Received August 19, 2009. Revised October 7, 2009. Accepted October 9, 2009.

Peroxisomes are essential organelles that play a key role in redox signalling and lipid homeostasis. They contain a highly diverse enzymatic network among different species, mirroring the varied metabolic needs of the organisms. The previous PeroxisomeDB version organized the peroxisomal proteome of humans and Saccharomyces cerevisiae based on genetic and functional information into metabolic categories with a special focus on peroxisomal disease. The new release (http://www.peroxisomeDB.org) adds peroxisomal proteins from 35 newly sequenced eukaryotic genomes including fungi, yeasts, plants and lower eukaryotes. We searched these genomes for a core ensemble of 139 peroxisomal protein families and identified 2706 putative peroxisomal protein homologs. Approximately 37% of the identified homologs contained putative peroxisome targeting signals (PTS). To help develop understanding of the evolutionary relationships among peroxisomal proteins, the new database includes phylogenetic trees for 2386 of the peroxisomal proteins. Additional new features are provided, such as a tool to capture kinetic information from Brenda, CheBI and Sabio-RK databases and more than 1400 selected bibliographic references. PeroxisomeDB 2.0 is a freely available, highly interactive functional genomics platform that offers an extensive view on the peroxisomal metabolome across lineages, thus facilitating comparative genomics and systems analysis of the organelle.


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