A graph analysis method to detect metabolic sub-networks based on phylogenetic profile

To elucidate fundamental constituting principle of functional modules or building blocks of metabolic networks, computational methods to analyze the network structure of metabolism are getting much attention. We propose a graph search method to extract highly conserved sub-networks of metabolic networks based on phylogenetic profile. We formulated reaction-conservation score for the measure of the phylogenetic conservation of reactions. We also formulated compound-conservation score to eliminate biologically-meaningless compounds and reduce the size of the networks. By applying our approach to the metabolic networks of 19 representative organisms selected from bacteria, archaea, and eukaryotes in the KEGG database, we detected some highly conserved sub-networks among the organisms. Comparing them to the metabolic maps in KEGG, we found they were mainly included in energy metabolism, sugar metabolism, and amino acid metabolism.