Metabolic network structure determines key aspects of functionality and regulation

The relationship between structure, function and regulation in complex cellular networks is a still largely open question. Systems biology aims to explain this relationship by combining experimental and theoretical approaches. Current theories have various strengths and shortcomings in providing an integrated, predictive description of cellular networks. Specifically, dynamic mathematical modelling of large-scale networks meets difficulties because the necessary mechanistic detail and kinetic parameters are rarely available. In contrast, structure-oriented analyses only require network topology, which is well known in many cases. Previous approaches of this type focus on network robustness or metabolic phenotype, but do not give predictions on cellular regulation. Here, we devise a theoretical method for simultaneously predicting key aspects of network functionality, robustness and gene regulation from network structure alone. This is achieved by determining and analysing the non-decomposable pathways able to operate coherently at steady state (elementary flux modes). We use the example of Escherichia coli central metabolism to illustrate the method.

[1]  William S. Cleveland,et al.  Visualizing Data , 1993 .

[2]  R. Heinrich,et al.  The Regulation of Cellular Systems , 1996, Springer US.

[3]  S. Leibler,et al.  Robustness in simple biochemical networks , 1997, Nature.

[4]  D. Eisenberg,et al.  A combined algorithm for genome-wide prediction of protein function , 1999, Nature.

[5]  D. Fell,et al.  Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering. , 1999, Trends in biotechnology.

[6]  B. Snel,et al.  Pathway alignment: application to the comparative analysis of glycolytic enzymes. , 1999, The Biochemical journal.

[7]  B. Palsson,et al.  The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[8]  D. Fell,et al.  A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks , 2000, Nature Biotechnology.

[9]  G. Odell,et al.  The segment polarity network is a robust developmental module , 2000, Nature.

[10]  Neal S. Holter,et al.  Fundamental patterns underlying gene expression profiles: simplicity from complexity. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[11]  R. Albert,et al.  The large-scale organization of metabolic networks , 2000, Nature.

[12]  B. Palsson,et al.  Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective. , 2000, Journal of theoretical biology.

[13]  U. Sauer,et al.  Metabolic flux response to phosphoglucose isomerase knock-out in Escherichia coli and impact of overexpression of the soluble transhydrogenase UdhA. , 2001, FEMS Microbiology Letters.

[14]  A. Cornish-Bowden,et al.  Complex networks of interactions connect genes to phenotypes. , 2001, Trends in biochemical sciences.

[15]  B. Palsson,et al.  In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data , 2001, Nature Biotechnology.

[16]  C. Peterson,et al.  Topological properties of citation and metabolic networks. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  G. Church,et al.  Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae , 2001, Nature Genetics.

[18]  Hiroaki Kitano,et al.  Foundations of systems biology , 2001 .

[19]  S. Strogatz Exploring complex networks , 2001, Nature.

[20]  H. Westerhoff,et al.  Transcriptome meets metabolome: hierarchical and metabolic regulation of the glycolytic pathway , 2001, FEBS letters.

[21]  S. Bonhoeffer,et al.  Cooperation and Competition in the Evolution of ATP-Producing Pathways , 2001, Science.

[22]  M. Lidstrom,et al.  Stoichiometric model for evaluating the metabolic capabilities of the facultative methylotroph Methylobacterium extorquens AM1, with application to reconstruction of C(3) and C(4) metabolism. , 2002, Biotechnology and bioengineering.

[23]  H. Kitano Systems Biology: A Brief Overview , 2002, Science.

[24]  B. Palsson,et al.  Transcriptional regulation in constraints-based metabolic models of Escherichia coli Covert , 2002 .

[25]  Katy C. Kao,et al.  Global Expression Profiling of Acetate-grown Escherichia coli * , 2002, The Journal of Biological Chemistry.

[26]  K. Yau,et al.  The heteromeric cyclic nucleotide-gated channel adopts a 3A:1B stoichiometry , 2002, Nature.

[27]  Steffen Klamt,et al.  FluxAnalyzer: exploring structure, pathways, and flux distributions in metabolic networks on interactive flux maps , 2003, Bioinform..