Topological signatures of species interactions in metabolic networks.
The topology of metabolic networks can provide insight not only into the metabolic processes that occur within each species, but also into interactions between different species. Here, we introduce a novel pair-wise, topology-based measure of biosynthetic support, reflecting the extent to which the nutritional requirements of one species could be satisfied by the biosynthetic capacity of another. To evaluate the biosynthetic support for a given pair of species, we use a graph-based algorithm to identify the set of exogenously acquired compounds in the metabolic network of the first species, and calculate the fraction of this set that occurs in the metabolic network of the second species. Reconstructing the metabolic network of 569 bacterial species and several eukaryotes, and calculating the biosynthetic support score for all bacterial-eukaryotic pairs, we show that this measure indeed reflects host-parasite interactions and facilitates a successful prediction of such interactions on a large-scale. Integrating this method with phylogenetic analysis and calculating the biosynthetic support of ancestral species in the Firmicutes division (as well as other bacterial divisions) further reveals a large-scale evolutionary trend of biosynthetic capacity loss in parasites. The inference of ecological features from genomic-based data presented here lays the foundations for an exciting "reverse ecology" framework for studying the complex web of interactions characterizing various ecosystems.
Borenstein
Elhanan
E
Department of Biology, Stanford University, Stanford, CA 94305-5020, USA. ebo@stanford.edu
Feldman
Marcus W
MW
D000465:Algorithms; D000818:Animals; D001419:Bacteria / Q000145:classification / Q000235:genetics / Q000378:metabolism*; D019295:Computational Biology / Q000379:methods; D017753:Ecosystem; D006790:Host-Parasite Interactions; D006801:Humans; D053858:Metabolic Networks and Pathways; D055432:Metabolomics / Q000379:methods; D008954:Models, Biological; D010802:Phylogeny; D025941:Protein Interaction Mapping