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Conserved moieties are groups of atoms that remain intact in all reactions ofa metabolic network. Identification of conserved moieties gives insight intothe structure and function of metabolic networks and facilitates metabolicmodelling. All moiety conservation relations can be represented as nonnegativeinteger vectors in the left null space of the stoichiometric matrixcorresponding to a biochemical network. Algorithms exist to compute suchvectors based only on reaction stoichiometry but their computational complexityhas limited their application to relatively small metabolic networks. Moreover,the vectors returned by existing algorithms do not, in general, representconservation of a specific moiety with a defined atomic structure. Here, weshow that identification of conserved moieties requires data on reaction atommappings in addition to stoichiometry. We present a novel method to identifyconserved moieties in metabolic networks by graph theoretical analysis of theirunderlying atom transition networks. Our method returns the exact group ofatoms belonging to each conserved moiety as well as the corresponding vector inthe left null space of the stoichiometric matrix. It can be implemented as apipeline of polynomial time algorithms. Our implementation completes in underfive minutes on a metabolic network with more than 4,000 mass balancedreactions. The scalability of the method enables extension of existingapplications for moiety conservation relations to genome-scale metabolicnetworks. We also give examples of new applications made possible byelucidating the atomic structure of conserved moieties.

Identification of conserved moieties in metabolic networks by graph theoretical analysis of atom transition networks