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

Motivation: In principle, an organisms ability to survive in a specific environment, is an observable result of the organisms 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