An environmental perspective on large-scale genome clustering based on metabolic capabilities.
BACKGROUND
In principle, an organism's ability to survive in a speci.c 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.


BACKGROUND
Supplementary data are available at Bioinformatics online.
Kastenmüller
Gabi
G
Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. g.kastenmueller@helmholtz-muenchen.de
Gasteiger
Johann
J
Mewes
Hans-Werner
HW
D005075:Biological Evolution; D002874:Chromosome Mapping / Q000379:methods*; D016000:Cluster Analysis; D003198:Computer Simulation; D004777:Environment; D005786:Gene Expression Regulation / Q000235:genetics*; D014644:Genetic Variation / Q000235:genetics; D008957:Models, Genetic; D020543:Proteome / Q000235:genetics* / Q000378:metabolism*; D012641:Selection, Genetic
D020543:Proteome