title: Enzyme sequence similarity improves the reaction alignment method for cross-species pathway comparison.
abstract: Pathway-based information has become an important source of information for both establishing evolutionary relationships and understanding the mode of action of a chemical or pharmaceutical among species. Cross-species comparison of pathways can address two broad questions: comparison in order to inform evolutionary relationships and to extrapolate species differences used in a number of different applications including drug and toxicity testing. Cross-species comparison of metabolic pathways is complex as there are multiple features of a pathway that can be modeled and compared. Among the various methods that have been proposed, reaction alignment has emerged as the most successful at predicting phylogenetic relationships based on NCBI taxonomy. We propose an improvement of the reaction alignment method by accounting for sequence similarity in addition to reaction alignment method. Using nine species, including human and some model organisms and test species, we evaluate the standard and improved comparison methods by analyzing glycolysis and citrate cycle pathways conservation. In addition, we demonstrate how organism comparison can be conducted by accounting for the cumulative information retrieved from nine pathways in central metabolism as well as a more complete study involving 36 pathways common in all nine species. Our results indicate that reaction alignment with enzyme sequence similarity results in a more accurate representation of pathway specific cross-species similarities and differences based on NCBI taxonomy.
authors.affiliation: Chemical and Biochemical Engineering Department, Rutgers University, Piscataway, NJ 08854, USA.
authors.forename: Meric A
authors.initials: MA
authors.lastname: Ovacik
authors.forename: Ioannis P
authors.initials: IP
authors.lastname: Androulakis
mesh_terms: D000465:Algorithms; D000818:Animals; D030541:Databases, Genetic; D006801:Humans; D053858:Metabolic Networks and Pathways / Q000502:physiology*; D010802:Phylogeny; D013045:Species Specificity