Network theory has become a well-established tool in the study of metabolic networks; our aim is to take this to the next level by looking at the effects of evolution on metabolic network topology,
A number of recent studies have combined the wealth of data available from genome sequencing projects with the mathematical tools of network theory to investigate the structure and evolution of metabolic networks – the complex set of chemical reactions used by cells to convert external nutrients into cellular components for growth and reproduction. Modern metabolic networks are complex and highly regulated; understanding how they came to be this way is essential to placing life in a planetary and solar system context. One important conclusion is that metabolic networks, like many other biological networks, exhibit a scale-free structure with a power-law degree distribution P(k) ~ k-γ. Scale-free structures have been shown to form by network growth with preferential attachment where new nodes are more likely to attach to well-connected older nodes; this observation gives important clues about how metabolic networks may have evolved.
Other insights have been gained by comparing the metabolic networks of organisms with different levels of complexity – unicellular vs. multicellular, prokaryotic vs. eukaryotic, stationary vs. motile, etc. The metabolic networks of more complex organisms have a tendency to be larger and more centrally organized, with a larger number of highly-connected nodes. When the metabolic networks of ancestral organisms were constructed by inference based on modern species, it was found that network modularity tends to decrease along evolutionary lineages
These results are consistent with Carl Woese's “genetic annealing” hypothesis, which discards the notion of a single universal common ancestor in favor of an ancestral community of simple protobionts. These would have been simple entities with sloppy DNA replication and protein translation machinery, sharing genes promiscuously through horizontal gene transfer (HGT). High mutation rates and rampant HGT characterize high “evolutionary temperature,” which would gradually lower as the cellular machinery grows more complex and refractory to HGT. This hypothesis predicts the formation of highly-modular cellular systems dominated by genes that travel together in functional units (similar to operons).
We are beginning a research effort in which we will use the topological tools of network theory, combined with temporal evolution methods such as kinetic monte carlo (KMC) techniques, to study the evolution of metabolic networks, both in light of the topological changes associated with evolutionary change and the specific predictions of the genetic annealing hypothesis.
