Modeling Biological Networks

IV.1 Coordinators
IV.2 Participants
IV.3 Introduction
IV.4 Background and Significance
IV.5 Research Plan

IV.6 Specific Subprojects
IV.7 Connection to Specific Projects 2 (cytoskeleton) and 3 (organogenesis)
IV.8 Timeline

IV.5.ii.b Metabolic Networks:

To address the large-scale structural organization of metabolic networks, we have examined the topology of the core metabolic networks of forty-three different organisms using data from the WIT (now ERGO) database (Overbeek et al., 2000). In the metabolic network, nodes are substrates which connect to each other through metabolic reactions. Figure IV.2 a, shows that in E. coli, the probability that a given substrate participates in k reactions follows a power-law distribution, i.e., the E. coli metabolic network is scale-free. Furthermore, we find that metabolic networks in all organisms in all three domains of life are scale-free, indicating the universality of this structural organization. We obtained essentially identical results for the topology of the information transfer pathways of the forty-three different organisms based on the "Information transfer" data in the WIT/ERGO database.

Many complex networks have small-world character (Strogatz, 2001; Watts and Strogatz, 1998), i.e., any two nodes in the system connect by relatively short paths along existing links. In metabolic networks, these paths correspond to the biochemical pathways connecting two substrates. The network diameter, defined as the shortest biochemical pathway averaged over all pairs of substrates, characterizes the degree of interconnectivity. In all non-biological networks we have examined, the average connectivity of a node is fixed, implying that the diameter of the network increases logarithmically with the addition of new nodes (Barabasi and Albert, 1999; Watts and Strogatz, 1998; Barthelemy and Amaral, 1999). In contrast, the diameter of the metabolic network is the same for all forty-three organisms, irrespective of the number of substrates in the species. This surprising independence of metabolic diameter requires individual substrates in more complex organisms to connect via more links. Increasing connectivity may increase the ability of more complex organisms to respond to external changes or internal errors. For example, time constants involved in changing enzyme concentrations largely govern the transition time between metabolic steady-states (Cascante et al., 1995). Quick transitions require that a few enzymes control many biochemical reactions.