The Small World Inside Large Metabolic Networks

We analyze the structure of a large metabolic network, that of the energy and biosynthesis metabolism of “Escherichia coli.” This network is a paradigmatic case for the large genetic and metabolic networks that functional genomics efforts are beginning to elucidate. To analyze the structure of networks involving hundreds or thousands of components by simple visual inspection is impossible, and a quantitative framework is needed to analyze them. We propose a graph theoretical description of the “E. coli” metabolic network, a description that we hope will prove useful for other genetic networks. We find that this network is a small-world graph, a type of graph observed in a variety of seemingly unrelated areas, such as friendship networks in sociology, the structure of electrical power grids, and the nervous system of “C. elegans.” Moreover, its connectivity follows a power law, another unusual but by no means rare statistical distribution. This architecture may serve to minimize transition times between metabolic states, and also reflect the evolutionary history of metabolism.