Properties Of Metabolic Networks Research Articles

Structural comparison of metabolic networks in selected single cell organisms

BackgroundThere has been tremendous interest in the study of biological network structure. An array of measurements has been conceived to assess the topological properties of these networks. In this study, we compared the metabolic network structures of eleven single cell organisms representing the three domains of life using these measurements, hoping to find out whether the intrinsic network design principle(s), reflected by these measurements, are different among species in the three domains of life.ResultsThree groups of topological properties were used in this study: network indices, degree distribution measures and motif profile measure. All of which are higher-level topological properties except for the marginal degree distribution. Metabolic networks in Archaeal species are found to be different from those in S. cerevisiae and the six Bacterial species in almost all measured higher-level topological properties. Our findings also indicate that the metabolic network in Archaeal species is similar to the exponential random network.ConclusionIf these metabolic network properties of the organisms studied can be extended to other species in their respective domains (which is likely), then the design principle(s) of Archaea are fundamentally different from those of Bacteria and Eukaryote. Furthermore, the functional mechanisms of Archaeal metabolic networks revealed in this study differentiate significantly from those of Bacterial and Eukaryotic organisms, which warrant further investigation.

Reconstruction of metabolic networks from genome data and analysis of their global structure for various organisms

Information from fully sequenced genomes makes it possible to reconstruct strain-specific global metabolic network for structural and functional studies. These networks are often very large and complex. To properly understand and analyze the global properties of metabolic networks, methods for rationally representing and quantitatively analyzing their structure are needed. In this work, the metabolic networks of 80 fully sequenced organisms are in silico reconstructed from genome data and an extensively revised bioreaction database. The networks are represented as directed graphs and analyzed by using the 'breadth first searching algorithm to identify the shortest pathway (path length) between any pair of the metabolites. The average path length of the networks are then calculated and compared for all the organisms. Different from previous studies the connections through current metabolites and cofactors are deleted to make the path length analysis physiologically more meaningful. The distribution of the connection degree of these networks is shown to follow the power law, indicating that the overall structure of all the metabolic networks has the characteristics of a small world network. However, clear differences exist in the network structure of the three domains of organisms. Eukaryotes and archaea have a longer average path length than bacteria. The reaction database in excel format and the programs in VBA (Visual Basic for Applications) are available upon request. Bioinformatics Online.

Identification of regulatory properties of metabolic networks by graph theoretical modeling

An earlier graph theoretical model of metabolic and gene-expression networks has been modified and extended to include the effect of electrical potentials on binding constants, representation of uncatalyzed processes, and treatment of parallel reactions catalyzed by a single enzyme. Formal operations on the graph, which are facilitated by a set of standardized guidelines, identify the feedback signals in the network and rank them according to their influence. The technique was applied to a model of glycolysis in ascites tumor cells in the absence and presence of 12.5 mM exogenous glucose. Feedback regulation was widely distributed and mostly due to binding of adenine nucleotide cofactors to the enzymes of the network. The major changes in feedback regulation on adding glucose is the relief of inhibition of hexokinase and phosphofructokinase and the activation of pyruvate kinase. We conclude that regulation of tumor cell glycolysis is not restricted to hexokinase or to (Na+,K+)-ATPase as was previously suggested by others.

Effect of regulatory mechanism on hyperbolic reaction network properties

The notion that the regulated and flux-controlling enzyme in a metabolic network need not correspond suggests that the purpose of regulation may not be flux homeostasis under all physiological circumstances. Additionally, the fact that diversity in the function of intact metabolic networks exists suggests that in addition to time constant separation, other kinetic structure/regulatory mechanism patterns exist. In order to compliment and expand prior work on identifying kinetic structure-property relationships in networks, the present work explores in a general way how the control, dynamic, and energetic properties of metabolic networks depend on operating point, kinetic structure, and regulatory mechanism. The basic feature of trade-offs between properties is illustrated and used as a basis for indicating how particular subsets of structure, regulatory mechanism, and operating point emphasize certain properties that can be associated with a physiological function. Examples of scavenging trace metabolites and amphibolite coordination are proposed. Microstructure logic in terms of turnover number distributions as well as a potential mixed polynomial network analysis approach are also discussed.

Consideration of the gain, enzymatic capacity utilization, and response time properties of metabolic networks as a function of operating point and structure

Computer simulation is used to examine the gain, utilization of enzymatic capacity and response time properties of a simple metabolic network consisting of a sequence of irreversible enzyme reactions controlled by non-allosteric feedback inhibition. The latter properties are chosen because interpretation of a metabolic network's structure can be aided by envisioning the network to maximize a single objective such as flux control. However, by examining the properties as a function of the network's operating point (extent of saturation of the first enzymatic reaction) and structural characteristics, it is found that apparent trade-offs occur between definable objectives. It is suggested that greater consideration of the trade-offs that may occur could help generate metabolic network heuristics and facilitate the interpretation of metabolic networks in terms of the functional role they play in the intact organism.