Correlated Evolution of Metabolic Functions over the Tree of Life

We are interested in the structure and evolution of metabolism inorder to better understand its complexity. We study metabolicfunctions in 1459 species within which several hundreds of thousandsof families of homologous genes have been identified [1]. Given aprotein sequence, PRIAM search [2] delivers probabilities of thepresence of several thousand enzymes (ECs). This allows us to inferreaction sets and to construct a metabolic network for an organism,given its set of sequences.We then propagate these ECs to the ancestral nodes of the species treeusing maximimum likelihood methods. These evolutionary scenarios aresystematically compared using pairwise mutual information. Weidentify co-evolving enzyme sets from the graph of these relationshipsusing community detection algorithms [3,4]. This sheds light on thestructure of the metabolic networks in terms of co-evolving metabolicmodules. These modules are also interpreted from a functionalperspective using stoichiometric models of metabolic networks.[1] Penel et al., BMC Bioinformatics, 10(6):S3, 2009[2] Claudel-Renard et al., Nucleic Acids Research, 31(22):6633--6639, 2003[3] Ahn et al., Nature, 446:761--764, 2010[4] Blondel et al., Journal of Statistical Mechanics, 2008(10):P10008, 2008