title: On flux coupling analysis of metabolic subsystems.
abstract: Genome-scale metabolic networks are useful tools for achieving a system-level understanding of metabolism. However, due to their large size, analysis of such networks may be difficult and algorithms can be very slow. Therefore, some authors have suggested to analyze subsystems instead of the original genome-scale models. Flux coupling analysis (FCA) is a well-known method for detecting functionally related reactions in metabolic networks. In this paper, we study how flux coupling relations may change if we analyze a subsystem instead of the original network. We show mathematically that a pair of fully, partially or directionally coupled reactions may be detected as uncoupled in certain subsystems. Interestingly, this behavior is the opposite of the flux coupling changes that may occur due to missing reactions, or equivalently, deletion of reactions. Computational experiments suggest that the analysis of plastid (but not mitochondrial) subsystems may significantly influence the results of FCA. Therefore, the results of FCA for subsystems, especially plastid subsystems, should be interpreted with care.
authors.affiliation: FB Mathematik und Informatik, Freie Universität Berlin, Arnimallee 6, D-14195 Berlin, Germany. marashi@molgen.mpg.de
authors.forename: Sayed-Amir
authors.initials: SA
authors.lastname: Marashi
authors.forename: Laszlo
authors.initials: L
authors.lastname: David
authors.forename: Alexander
authors.initials: A
authors.lastname: Bockmayr
mesh_terms: D019295:Computational Biology / Q000379:methods; D016678:Genome; D006801:Humans; D053858:Metabolic Networks and Pathways / Q000502:physiology*; D008928:Mitochondria / Q000378:metabolism; D008954:Models, Biological; D015388:Organelles / Q000378:metabolism; D010944:Plants / Q000378:metabolism; D049490:Systems Biology / Q000379:methods