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Bioinformatics 2008 24(16):i56-i62; doi:10.1093/bioinformatics/btn302
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

An environmental perspective on large-scale genome clustering based on metabolic capabilities

Gabi Kastenmüller 1,*, Johann Gasteiger 2,3 and Hans-Werner Mewes 1,4

1Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München—German Research Center for Environmental Health, Ingolstädter Landstraße 1, D-85764 Neuherberg, 2Computer-Chemie-Centrum, University of Erlangen-Nürnberg, Nägelsbachstraße 25, D-91052 Erlangen, 3Molecular Networks GmbH, Henkestraße 91, D-91052 Erlangen and 4Chair for Genome-Oriented Bioinformatics, Technische Universität München, Life and Food Science Center Weihenstephan, Am Forum 1, D-85354 Freising-Weihenstephan, Germany

*To whom correspondence should be addressed.


  Abstract

Motivation: In principle, an organism's ability to survive in a specific environment, is an observable result of the organism's regulatory and metabolic capabilities. Nonetheless, current knowledge about the global relation of the metabolisms and the niches of organisms is still limited.

Results: In order to further investigate this relation, we grouped species showing similar metabolic capabilities and systematically mapped their habitats onto these groups. For this purpose, we predicted the metabolic capabilities for 214 sequenced genomes. Based on these predictions, we grouped the genomes by hierarchical clustering. Finally, we mapped different environmental conditions and diseases related to the genomes onto the resulting clusters. This mapping uncovered several conditions and diseases that were unexpectedly enriched in clusters of metabolically similar species. As an example, Encephalitozoon cuniculi—a microsporidian causing a multisystemic disease accompanied by CNS problems in rabbits— occurred in the same metabolism-based cluster as bacteria causing similar symptoms in humans.

Supplementary information: Supplementary data are available at Bioinformatics online.

Contact: g.kastenmueller{at}helmholtz-muenchen.de


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