The stability and robustness of metabolic states: Identifying stabilizing sites in metabolic networks

Molecular Systems Biology

Volumn 3, Issue , 2007, Pages

  Grimbs, Sergio ^a   Selbig, Joachim ^a,b   Bulik, Sascha ^c   Holzhütter, Hermann Georg ^c   Steuer, Ralf ^d  

^a MAX PLANCK INSTITUTE OF MOLECULAR PLANT PHYSIOLOGY   (Germany)

^b UNIVERSITY OF POTSDAM   (Germany)

^c CHARITÉ UNIVERSITÄTSMEDIZIN BERLIN   (Germany)

^d HUMBOLDT UNIVERSITY   (Germany)

Author keywords

Dynamic behavior; Kinetic modeling; Metabolic network; Robustness; Stability

Indexed keywords

ARTICLE; CONTROLLED STUDY; ENZYME KINETICS; ENZYME REGULATION; ENZYME STABILITY; ERYTHROCYTE METABOLISM; HUMAN; HUMAN CELL; METABOLISM; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; ALLOSTERISM; BIOLOGICAL MODEL; ENERGY METABOLISM; ERYTHROCYTE; OXIDATION REDUCTION REACTION;

ALLOSTERIC REGULATION; ENERGY METABOLISM; ERYTHROCYTES; HUMANS; METABOLIC NETWORKS AND PATHWAYS; MODELS, BIOLOGICAL; OXIDATION-REDUCTION;

EID: 36248952170     PISSN: 17444292     EISSN: 17444292     Source Type: Journal    
DOI: 10.1038/msb4100186     Document Type: Article

References (38)

1. Ataullakhanov FI, Vitvitsky VM, Zhabotinsky AM, Pichugin AV, Platonova OV, Kholodenko BN, Ehrlich LI (1981) The regulation of glycolysis in human erythrocytes the dependence of the glycolytic flux on the ATP concentration. Eur J Biochem 115: 359-365
2. Bailey JE (1991) Toward a science of metabolic engineering. Science 252: 1668-1675
3. Becker J, Klopprogge C, Zelder O, Heinzle E, Wittmann C (2005) Amplified expression of fructose 1,6-bisphosphatase in Corynebacterium glutamicum increases in vivo flux through the pentose phosphate pathway and lysine production on different carbon sources. Appl Environ Microbiol 71: 8587-8596
4. Dariyerli N, Toplan S, Akyolcu MC, Hatemi H, Yigit G (2004) Erythrocyte osmotic fragility and oxidative stress in experimental hypothyroidism. Endocrine 25: 1-5
5. de Atauri P, Ramírez MJ, Kuchel PW, Carreras J, Cascante M (2006) Metabolic homeostasis in the human erythrocyte: in silico analysis. Biosystems 83: 118-124
6. Deutscher D, Meilijson I, Kupiec M, Ruppin E (2006) Multiple knockouts analysis of genetic robustness in the yeast metabolic network. Nat Genet 38: 993-998
7. Edwards JS, Palsson BO (2000) Robustness analysis of the Escherichia coli metabolic network. Biotechnol Prog 16: 927-939
8. Fernie AR, Trethewey RN, Krotzky AJ, Willmitzer L (2004) Metabolite profiling: from diagnostics to systems biology. Nat Rev Mol Cell Biol 5: 763-769
9. Goodacre R, Vaidyanathan S, Dunn WB, Harrigan GG, Kell DB (2004) Metabolomics by numbers: acquiring and understanding global metabolite data. Trends Biotechnol 22: 245-252
10. Heinrich R, Schuster S (1996) The Regulation of Cellular System. New York: Chapman & Hall
11. Henry CS, Jankowski MD, Broadbelt LJ, Hatzimanikatis V (2006) Genome-scale thermodynamic analysis of Escherichia coli metabolism. Biophys J 90: 1453-1461
12. Holzhütter HG (2004) The principle of flux minimization and its application to estimate stationary fluxes in metabolic networks. Eur J Biochem 271: 2905-2922
13. Holzhütter HG, Jacobasch G, Bisdorff A (1985) Mathematical modelling of metabolic pathways affected by an enzyme deficiency a mathematical model of glycolysis in normal and pyruvate-kinase-deficient red blood cells. Eur J Biochem 149: 101-111
14. Hoppe A, Hoffmann S, Holzhütter HG (2007) Including metabolite concentrations into flux balance analysis: thermodynamic realizability as a constraint on flux distributions in metabolic networks. BMC Syst Biol 1: 23
15. Jacobasch G, Rapoport SM (1996) Hemolytic anemias due to erythrocyte enzyme deficiencies. Mol Aspects Med 17: 143-170
16. Joshi A, Palsson BO (1989) Metabolic dynamics in the human red cell. Part i-a comprehensive kinetic model. J Theor Biol 141: 515-528
17. Kodicek M (1986) Enhanced glucose consumption in erythrocytes under mechanical stress. Cell Biochem Funct 4: 153-155
18. Kumar P, Shoukri M (2007) Copula based prediction models: an application to an aortic regurgitation study. BMC Med Res Methodol 7: 21
19. Kümmel A, Panke S, Heinemann M (2006) Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data. Mol Syst Biol 2; 2006.0034
20. McIntyre LM, Thorburn DR, Bubb WA, Kuchel PW (1989) Comparison of computer simulations of the f-type and l-type non-oxidative hexose monophosphate shunts with 31p-nmr experimental data from human erythrocytes. Eur J Biochem 180: 399-420
21. Morohashi M, Winn A, Borisuk M, Bolouri H, Doyle J, Kitano H (2002) Robustness as a measure of plausibility in models of biochemical networks. J Theor Biol 216: 19-30
22. Mulquiney PJ, Kuchel PW (1999) Model of 2,3-bisphosphoglycerate metabolism in the human erythrocyte based on detailed enzyme kinetic equations: computer simulation and metabolic control analysis. Biochem J 342 (Part 3): 597-604
23. Nakayama Y, Kinoshita A, Tomita M (2005) Dynamic simulation of red blood cell metabolism and its application to the analysis of a pathological condition. Theor Biol Med Model 2: 18
24. Ni TC, Savageau MA (1996a) Application of biochemical systems theory to metabolism in human red blood cells. Signal propagation and accuracy of representation. J Biol Chem 271: 7927-7941
25. Ni TC, Savageau MA (1996b) Model assessment and refinement using strategies from biochemical systems theory: application to metabolism in human red blood cells. J Theor Biol 179: 329-368
26. Rapoport TA, Heinrich R, Rapoport SM (1976) The regulatory principles of glycolysis in erythrocytes in vivo and in vitro. A minimal comprehensive model describing steady states, quasi-steady states and time-dependent processes. Biochem J 154: 449-469
27. Sauer U (2004) High-throughput phenomics: experimental methods for mapping fluxomes. Curr Opin Biotechnol 15: 58-63
28. Schuster R, Holzhütter HG (1995) Use of mathematical models for predicting the metabolic effect of large-scale enzyme activity alterations. Application to enzyme deficiencies of red blood cells. Eur J Biochem 229: 403-418
29. Schuster S, Dandekar T, Fell DA (1999) Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering. Trends Biotechnol 17: 53-60
30. Shannon CE (1948) A mathematical theory of communication. Bell System Technical J 27: 379-423, 623-656
31. Stelling J, Klamt S, Bettenbrock K, Schuster S, Gilles ED (2002) Metabolic network structure determines key aspects of functionality and regulation. Nature 420: 190-193
32. Steuer R, Gross T, Selbig J, Blasius B (2006) Structural kinetic modeling of metabolic networks. Proc Natl Acad Sci USA 103: 11868-11873
33. Steuer R, Kurths J, Daub CO, Weise J, Selbig J (2002) The mutual information: detecting and evaluating dependencies between variables. Bioinformatics 18: S231-S240
34. Steuer R, Kurths J, Fiehn O, Weckwerth W (2003) Observing and interpreting correlations in metabolomic networks. Bioinformatics 19: 1019-1026
35. Tekir SD, Cakir T, Ülgen KÖ (2006) Analysis of enzymopathies in the human red blood cells by constraint-based stoichiometric modeling approaches. Comput Biol Chem 30: 327-338
36. Varma A, Palsson BO (1994) Metabolic flux balancing: basic concepts, scientific and practical use. Nat Biotechnol 12: 994-998
37. von Dassow G, Meir E, Munro EM, Odell GM (2000) The segment polarity network is a robust developmental module. Nature 406: 188-192
38. Wang L, Birol I, Hatzimanikatis V (2004) Metabolic control analysis under uncertainty: framework development and case studies. Biophys J 87: 3750-3763