title: Highly optimised global organisation of metabolic networks.
abstract: High-level, mathematically precise descriptions of the global organisation of complex metabolic networks are necessary for understanding the global structure of metabolic networks, the interpretation and integration of large amounts of biologic data (sequences, various -omics) and ultimately for rational design of therapies for disease processes. Metabolic networks are highly organised to execute their function efficiently while tolerating wide variation in their environment. These networks are constrained by physical requirements (e.g. conservation of energy, redox and small moieties) but are also remarkably robust and evolvable. The authors use well-known features of the stoichiometry of bacterial metabolic networks to demonstrate how network architecture facilitates such capabilities, and to develop a minimal abstract metabolism which incorporates the known features of the stoichiometry and respects the constraints on enzymes and reactions. This model shows that the essential functionality and constraints drive the tradeoffs between robustness and fragility, as well as the large-scale structure and organisation of the whole network, particularly high variability. The authors emphasise how domain-specific constraints and tradeoffs imposed by the environment are important factors in shaping stoichiometry. Importantly, the consequence of these highly organised tradeoffs and tolerances is an architecture that has a highly structured modularity that is self-dissimilar and scale-rich.
authors.affiliation: RIKEN, Bio-Mimetic Control Research Center, Nagoya, Japan. reiko@bmc.riken.jp
authors.forename: R
authors.initials: R
authors.lastname: Tanaka
authors.forename: M
authors.initials: M
authors.lastname: Csete
authors.forename: J
authors.initials: J
authors.lastname: Doyle
mesh_terms: D000818:Animals; D002468:Cell Physiological Phenomena; D006801:Humans; D008660:Metabolism / Q000502:physiology*; D008954:Models, Biological; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*; D049490:Systems Biology / Q000379:methods*
chemical_list: D020543:Proteome