Systembiologie in der Bioverfahrenstechnik

  • Ralf Takors


Die Systembiologie ist eine Wissenschaft, die sich äußerst rasant entwickelt (Shimizu 2009). Sie ist derart umfangreich und vielseitig, dass nachfolgend nur ein Teilaspekt vorgestellt werden kann. Im Vordergrund stehen dabei systembiologische Themen, die zur Lösung bioverfahrenstechnischer Probleme beitragen können. Namentlich sind dies Metabolic-Engineering-Ansätze zur Stoffwechselmodellierung und Grundzüge der Signaltransduktion. Einen Überblick über weitere wichtige systembiologische Aspekte, wie beispielsweise transkriptionelle Regulationsnetzwerke inklusive Mechanismen der Genexpression, systembiologische Datenerhebung, Modellierungswerkzeuge und Modellbanken etc., bieten z. B. Klipp et al. (2005), Lee (2009) und Palsson (2006).


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  1. Aiba, S., Matsuoka, M. (1979): Identification of metabolic model: Citrate production from glucose by Candida lipolytica. Biotechnol. Bioeng. 21: 1373–1386CrossRefGoogle Scholar
  2. Antoniewicz, M. R., Kelleher, J. K., Stephanopoulos, G. (2007a): Elementary metabolite units (EMU): A novel framework for modeling isotopic distributions. Metab. Eng. 9: 68–86PubMedCrossRefGoogle Scholar
  3. Antoniewicz, M. R., Kraynie, D. F., Laffend, L. A., Gonzalez-Lergier, J., Kelleher, J. K., Stephanopoulos, G. (2007b): Metabolic flux analysis in a nonstationary system: Fed-batch fermentation of a high yielding strain of E. coli producing 1,3-propanediol. Metab. Eng. 9: 277–292PubMedCrossRefGoogle Scholar
  4. Bailey, J. E. (1991): Towards a science of metabolic engineering. Science 252: 1668–1674PubMedCrossRefGoogle Scholar
  5. Beckwith, J. R. (1967): Regulation of the lac operon. Recent studies on the regulation of lactose metabolism in Escherichia coli support the operon model. Science 156: 597–604PubMedCrossRefGoogle Scholar
  6. Blank, L. M., Kuepfer, L., Sauer, U. (2005): Large-scale 13C-flux analysis reveals mechanistic principles of metabolic network robustness to null mutations in yeast. Genome Biol. 6: R49PubMedCrossRefGoogle Scholar
  7. Blum, J. J., Stein, R. B. (1982): On the analysis of metabolic networks. In: Goldberger, R. F. (Hrsg.) Biological Regulation and Development. Plenum Press, New York, 99–124CrossRefGoogle Scholar
  8. Bonarius, H. P. J., Schmidt, G., Tramper, J. (1997): Flux analysis of underdetermined metabolic systems: The quest of missing constraints. Trends Biotechnol. 15: 308–314CrossRefGoogle Scholar
  9. Brown, G. C., Hoek, J., Kholodenko, B. N. (1997): Why do protein kinase cascades have more than one level. Trends Biochem. Sci. 22: 288PubMedCrossRefGoogle Scholar
  10. Burgard, A. P., Phakya, P., Maranas, C. D. (2003): OptKnock, a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnol. Bioeng. 84: 647–657PubMedCrossRefGoogle Scholar
  11. Burns, J. A., Cornish-Bowden, A., Groen, A. K., Heinrich, R., Kacser, H., Porteous, J. W., Rapoport, S. M., Rapoport, T. A., Stucki, J. W., Tager, J. M., Wanders, R. J. A., Westerhoff, H. V. (1985): Control analysis of metabolic systems. Trends Biochem. Sci. 10: 16CrossRefGoogle Scholar
  12. Cameron, D. C., Tong, T.-T. (1993): Cellular and metabolic engineering. Appl. Biochem. Biotechnol. 38: 105–140PubMedCrossRefGoogle Scholar
  13. Chance, B., Garfinkel, D., Higgins, J., Hess, B. (1960): Metabolic control mechanisms. J. Biol. Chem. 235: 2426–2439PubMedGoogle Scholar
  14. Christensen, B., Nielsen, J. (1999a): Metabolic network analysis — a powerful tool in metabolic engineering. Adv. Biochem. Eng. Biotechnol. 66: 209–231Google Scholar
  15. Christensen, B., Nielsen, J. (1999b): Isotopomer analysis using CG-MS. Metab. Eng. 1: 282–290PubMedCrossRefGoogle Scholar
  16. de Graaf, A. A. (2000): Metabolic analysis of Zymomonas mobilis. In: Schügerl, K., Belgardt, K. H. (Hrsg.) Bioreaction Engineering, Modelling and Control. Springer Verlag, New YorkGoogle Scholar
  17. Feist, A. M., Henry, C. S., Reed, J. L., Krummenacker, M., Joyce, A. R., Karp, P.-D., Broadbelt, L. J., Hatzimanikatis, V., Palsson, B. O. (2007): A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Mol. Syst. Biol. 3: 121PubMedCrossRefGoogle Scholar
  18. Fell, D. A. (1997): Metabolic control analysis: a survey of its theoretical and experimental development. Biochem. J. 286: 313–330Google Scholar
  19. Ferenci, T. (2001): Hungry bacteria — definition and properties of a nutritional state. Environ. Microbiol. 3(10): 605–611PubMedCrossRefGoogle Scholar
  20. Goldbeter, A., Koshland, D. E. (1984): Ultrasensitivity in biochemical systems controlled by covalent modification. Interplay between zero-order and multi step effects. J. Biol. Eng. 259: 14441–14447Google Scholar
  21. Griffith, J. S. (1968a): Mathematics of cellular control processes. I. Negative feedback to one gene. J. Theor. Biol. 20: 202–208PubMedCrossRefGoogle Scholar
  22. Griffith, J. S. (1968b): Mathematics of cellular control processes. II. Positive feedback to one gene. J. Theor. Biol. 20: 209–216PubMedCrossRefGoogle Scholar
  23. Hatzimanikatis, V., Bailey, J. E. (1997): Effects of spatiotemporal variations on metabolic control: approximate analysis using (log) linear kinetic models. Biotechnol. Bioeng. 1: 75–87Google Scholar
  24. Hatzimanikatis, V., Emmerling, M., Sauer, U., Bailey, J. E. (1998): Application of mathematical tools for metabolic design of microbial ethanol production. Biotechnol. Bioeng. 58: 154–161PubMedCrossRefGoogle Scholar
  25. Hatzimanikatis, V., Floudas, C. A., Bailey, J. E. (1996): Analysis and design of metabolic reaction networks via mixedinteger linear optimization. AICHE J. 42: 1277–1292CrossRefGoogle Scholar
  26. Heinrich, R., Neel, G. B., Rapoport, T. A. (2002): Mathematical models of protein kinase signal transduction. Mol. Cell 9: 957–970PubMedCrossRefGoogle Scholar
  27. Heinrich, R., Rapoport, T. A. (1974): A linear steady-state treatment of enzymatic chains. General properties, control and effector strength. Eur. J. Biochem. 42: 89–95PubMedCrossRefGoogle Scholar
  28. Heinrich, R., Westerhoff, H. V. (2005): Principles behind the multi various control of signaltransduction ERK Phophorylation and kinase/phosphatise control. FEBS J. 272: 244–258PubMedGoogle Scholar
  29. Henry, C. S., Broadbelt, L. J., Hatzimanikatis, V. (2007): Thermodynamics-based metabolic flux analysis. Biophys. J. 92(5): 1792–1805PubMedCrossRefGoogle Scholar
  30. Hess, B., Boiteux, A. (1968): Mechanism of glycolytic oscillation in yeast. I. Aerobic and anaerobic growth conditions for obtaining glycolytic oscillation. Hoppe-Seylers Zeitschrift für physiologische Chemie 349(11): 1567–1574CrossRefGoogle Scholar
  31. Hornberg, J. J., Bruggemann, F. J., Binder, B., Geest, C. R., de Vaate, A. J., Lankelmar, J., Heinrich, R., Westerhoff, H. V. (2005) Principles behind the multifarious control of signal transduction. ERK phosphorylation and kinase/phosphatase control. FEBS J. 272: 244–258PubMedCrossRefGoogle Scholar
  32. Hunter, T. (2000): Signalling-2000 and beyond. Cell 100: 113–127PubMedCrossRefGoogle Scholar
  33. Ibarra, R. U., Edwards, J. S., Palsson, B. O. (2002): Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth. Nature 420: 186–189PubMedCrossRefGoogle Scholar
  34. Jordan, J. D., Landau, E. N., Iyingar, R. (2000): Signalling networks: the origins of cellular multitasking. Cell 103: 193–200PubMedCrossRefGoogle Scholar
  35. Kacser, H., Burns, J. A. (1973): The control of flux. Symp. Soc. Exp. Biol. 27: 37–63Google Scholar
  36. Kholodenko, B. N. (2000): Negative feedback and ultra sensitivity can bring about oszillations in the mitogen-activated protein kinase cascades. Eur. J. Biochem. 267: 1583–1588PubMedCrossRefGoogle Scholar
  37. Kholodenko, B. N. (2006): Cell-signalling dynamics in time and space. Nature Rev. Mol. Cell Biol. 7: 165–176CrossRefGoogle Scholar
  38. Knolodenko, B. N., Hoeck, J., Westerhoff, H. W., Brown, G. C. (1997): Quantification of information transfer via cellular signal transduction pathways. FEBS Lett. 414: 430–434CrossRefGoogle Scholar
  39. Klipp, E., Herwig, R., Kowald, A., Wierling, C., Lehrach, H. (2005): Systems Biology in Practice. Wiley-VCH Verlag, WeinheimCrossRefGoogle Scholar
  40. Kummel, A., Panke, S., Heinemann, M. (2006): Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data. Mol. Syst. Biol. 1–10 (doi: 10.1038/msb4100074)Google Scholar
  41. Lara, A. R., Galindo, E., Ramirez, O. T., Palomares, L. A. (2006): Living with heterogeneities in bioreactors. Mol. Biotechnol. 34: 355–381PubMedCrossRefGoogle Scholar
  42. Lee, S. Y. (2009): Systems Biology and Biotechnology of Escherichia coli. Springer Science+Business Media B.V.Google Scholar
  43. Liebermeister, W., Klipp, E. (2006): Bringing metabolic networks to life: convenience rate law and thermodynamic constraints. Theor. Biol. Med. Model 3: 41PubMedCrossRefGoogle Scholar
  44. Magnus, J. B., Hollwedel, D., Oldiges, M., Takors, R. (2006): Monitoring and modelling of the reaction dynamics in the valine/leucine synthesis pathway in Corynebacterium glutamicum. Biotechnol. Prog. 22(4): 1071–1083PubMedCrossRefGoogle Scholar
  45. Malloy, C. R., Sherry, A. D., Jeffrey, F. M. H. (1988): Evaluation of carbon flux and substrate selection through alternate pathways involving the citric asset cycle of the heart by 13C MMR spectroscopy. J. Biol. Chem. 263: 6964–6971PubMedGoogle Scholar
  46. Marx, A., de Graaf, A. A., Wiechert, W., Eggeling, L., Sahm, H. (1996): Determination of the fluxes in central metabolism of Corynebacterium by NMR spectroscopy combined with metabolite balancing. Biotechnol. Bioeng. 49: 111–129PubMedCrossRefGoogle Scholar
  47. Nielsen, J. (1997): Metabolic control analysis of biochemical pathways based on a thermokinetic description of reaction rates. Biochem. J. 321: 133–138PubMedGoogle Scholar
  48. Nielsen, J., Villadsen, J., Liden, G. (2003): Bioreaction Engineering Principles. Kluwer Academic/Plenum Publishers, New YorkCrossRefGoogle Scholar
  49. Noh, K., Gronke, K., Luo, B., Takors, R., Oldiges, M., Wiechert, W. (2007): Metabolic flux analysis at ultra short time scale: isotopically non-stationary 13C labeling experiments. J. Biotechnol. 129(2): 249–267PubMedCrossRefGoogle Scholar
  50. Onsager, L. (1931): Reciprocal relations in irreversible processes. I, Physical Rev. 37: 405–426CrossRefGoogle Scholar
  51. Palsson, B. O. (2006): Systems Biology — Properties of reconstructed networks. Cambridge University PressGoogle Scholar
  52. Petersen S., de Graaf, A. A., Eggeling, L., Mollmay, M., Wiechert, W., Sahm, H. (2000): In vivo quantification of parallel and bidirectional fluxes in the anaplerosis of Corynebacterium glutamicum. J. Biol. Chem. 275: 35932–35941PubMedCrossRefGoogle Scholar
  53. Postma, P. W., Broekhuizen, C. P., Geerse, R. H. (1989): The role of the PEP:carbohydrate phosphotransferase system in the regulation of bacterial metabolism. FEMS Microbiol. Rev. 5: 69–80PubMedCrossRefGoogle Scholar
  54. Postma, P. W., Lengerer, J. W., Jacobsen, G. R. (1993): Phosp hoenolpyruvate:carbohydrate phosphotransferase systems of bacteria. Microbiol. Rev. 57: 543–594PubMedGoogle Scholar
  55. Reder, C. (1988): Metabolic control theory: a structural approach. J. Theor. Biol. 135: 175–201PubMedCrossRefGoogle Scholar
  56. Reuss, M. (2007): Marrying diverse partners — a mixed complementary approach for integrating bottom-up and top-down methods in Systems Biology. In: Systems Biology: a Grand Challenge for Europe. European Science Foundation. www.esf.orgGoogle Scholar
  57. Rohwer, J. M., Meadow, N. D., Roseman, S., Westerhoff, H. V., Postma, P. W. (2000): Understanding glucose transport by the bacterial phosphoenolpyruvate:glucose phosphotransferase system on the basis of kinetic measurements in vitro. J. Biol. Chem. 275: 34909–34921PubMedCrossRefGoogle Scholar
  58. Rottenberg, H. (1973): The thermodynamic description of enzyme-catalyzed reactions. Biophys. J. 13: 503–511PubMedCrossRefGoogle Scholar
  59. Ryan, K. R., Shapiro, L. (2003): Temporal and spatial regulation in prokaryotic cell cycle progression and development. Ann. Rev. Biochem. 72: 367–394PubMedCrossRefGoogle Scholar
  60. Savageau, M. A. (1976): Biochemical Systems Analysis: A Study of Function and Design in Molecular Biology. Addison-Wesley, Reading, MAGoogle Scholar
  61. Sauer, U. (2006): Metabolic networks in motion: 13C-based flux analysis. Mol. Syst. Biol. 2: 62PubMedCrossRefGoogle Scholar
  62. Sauro, A. M., Kholodenko, B. N. (2004): Quantitative analysis of signalling networks. Progr. Biophys. Mol. Biol. 86: 5–43CrossRefGoogle Scholar
  63. Schaub, J., Mauch, K., Reuss, M. (2008): Metabolic flux analysis in Escherichia coli by integrating isotopic dynamic and isotopic stationary C-13 labeling data. Biotechnol. Bioeng. 99: 1170–1185PubMedCrossRefGoogle Scholar
  64. Schmidt, K., Carlsen, M., Nielsen, J., Villadsen, J. (1997): Modeling isotopomer distribution in biochemical networks using isotopomer maping matrices. Biotechnol. Bioeng. 55: 831–840PubMedCrossRefGoogle Scholar
  65. Schmidt, K., Nielsen, J., Villadsen, J. (1999): Quantitative analysis of metabolic fluxes in E.coli using 2-dimensional NMR spectroscopy and complete isotopomer models: J. Biotechnol. 71: 175–189PubMedCrossRefGoogle Scholar
  66. Schuster, S., Fell, D., Dandekar, T. (1999): A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks. Nature Biotechnol. 18: 326–332CrossRefGoogle Scholar
  67. Schweder, T., Kruger, E., Xu, B., Jurgen, B., Blomsten, G., Enfors, S.-O., Hecker, M. (1999): Monitoring of genes that respond to process-related stress in large-scale bioprocesses. Biotechnol. Bioeng. 65: 151–159PubMedCrossRefGoogle Scholar
  68. Segre, D., Vitkup, D., Church, G. M. (2002): Analysis of optimality in natural perturbed metabolic networks. Proc. Natl. Acad. Sci. USA 99: 15112–15117PubMedCrossRefGoogle Scholar
  69. Shimizu, K. (2009): Towards systematic metabolic engineering based on the analysis of metabolic regulation by integration of different levels of information. Biochem. Eng. J. 46: 235–251CrossRefGoogle Scholar
  70. Sonntag, K., Eggeling, L., de Graaf, A. A., Sahm, H. (1993): Flux partitioning in the split pathway of lysine synthesis in Corynebacterium glutamicum — quantification by 13H-and 1H-NMR spectroscopy. Eur. J. Biochem. 213: 1325–1331PubMedCrossRefGoogle Scholar
  71. Stephanopoulos, G. N., Aristidou, A. A., Nielsen, J. (1998): Metabolic Engineering. Academic Press, San DiegoGoogle Scholar
  72. Szyperski, T. (1995): Biosynthetically directed fractional 13 C labelling of proteinogenic amino acids — an efficient analytical tool to investigate intermediary metabolism. Eur. J. Biochem. 232: 433–448PubMedCrossRefGoogle Scholar
  73. Szyperski, T. (1998): 13C-NMR, MS and metabolic flux balancing in biotechnological research. Q. Rev. Biophys. 31: 41–106PubMedCrossRefGoogle Scholar
  74. Tang, Y. J., Martin, H. G., Myers, S., Rodriguez, S., Baidoo, E. E., Keasling, J. D. (2009): Advances in analysis of microbial metabolic fluxes cia 13c isotopic labeling. Mass Spectrom. Rev. 28: 362–375PubMedCrossRefGoogle Scholar
  75. Tyson et al. 2003: Sniffers, buzzers, toggles and blinkers: dynamics of regulatory signaling pathways in the cell. Current Opinion in Cell Biology 15:221–231PubMedCrossRefGoogle Scholar
  76. Umbarger, H. E., Brown, B. (1957): Threonine deamination in Escherichia coli. II. Evidence for two L-threonine deaminases. J. Bacteriol. 73: 105–112PubMedGoogle Scholar
  77. Vallino, J. J., Stephanopoulos, G. (1993): Metabolic flux distribution in Corynbacterium glutamicum during growth and lysine overproduction. Biotechnol. Bioeng. 41: 633–646PubMedCrossRefGoogle Scholar
  78. van der Meer, R., Westerhoff, H. V., van Dam, K. (1980): Linear relation between rate and thermodynamic force in enzymecatalyzed reactions. Biochim. Biophys. Acta 591: 488–493PubMedCrossRefGoogle Scholar
  79. Varma, A., Boesch, B. W., Palsson, B. O. (1993): Stoichiometric interpretation of Escherichia coli glucose catabolism under various oxygenation rates. Appl. Environ. Microbiol. 59: 2465–2473PubMedGoogle Scholar
  80. Varma, A. Palsson, B. O. (1994): Metabolic flux balancing: basic concepts, scientific and practical use. Bio/Technology 12: 994–998CrossRefGoogle Scholar
  81. Vaseghi, S., Baumeister, A., Rizzi, M., Reuss, M. (1999): In vivo dynamics of the pentose phosphate pathway in Saccharomyces cerevisiae. Metab. Eng. 1: 128–140PubMedCrossRefGoogle Scholar
  82. Visser, D., Heijnen, J. J. (2002): The mathematics of metabolic control analysis revisited. Metab. Eng. 4: 114–123PubMedCrossRefGoogle Scholar
  83. Visser, D., Heijnen, J. J. (2003): Dynamic simulation and metabolic re-design of a branched pathway using linlog kinetics. Metab. Eng. 5: 164–176PubMedCrossRefGoogle Scholar
  84. West, A. H., Stock, A. M. (2001): Histidine kinases and response regulator proteins in two-compartment signaling systems. Trends Biochem. Sci. 26: 369–376PubMedCrossRefGoogle Scholar
  85. Westerhoff, H. V. (2008): Signalling control strength. J. Theor. Biol. 252: 555–567PubMedCrossRefGoogle Scholar
  86. Westerhoff, H. V., Palsson, B. O. (2004): The evolution of molecular biology into systems biology. Nature Biotechnol. 22(10): 1249–1252CrossRefGoogle Scholar
  87. Westerhoff, H. V., van Dam, K. (1987): Thermodynamics and control of biological free-energy transduction. Elsevier, AmsterdamGoogle Scholar
  88. Wiechert, W. (2001): 13C Metabolic Flux Analysis. Metab. Eng. 3: 195–206PubMedCrossRefGoogle Scholar
  89. Wiechert, W. (2002): Modeling and simulation: tools for metabolic engineering. J. Biotechnol. 94: 37–63PubMedCrossRefGoogle Scholar
  90. Wiechert, W., Mollney, M., Isermann, N., Wurzel, M., de Graaf, A. A. (1999): Bidirectional reaction steps in metabolic networks part III: Explicit solution and analysis of isotopomer labelling systems. Biotechnol. Bioeng. 66: 69–85PubMedCrossRefGoogle Scholar
  91. Wittmann, C., Heinzle, E. (2001): Application of MALDI-TOF MS to lysine-producing Corynebacterium clutamicum — a novel approach for metabolic flux analysis. Eur. J. Biochem. 268: 2441–2455PubMedCrossRefGoogle Scholar
  92. Wolf, D. M., Arkin, A. P. (2003): Motives, modules and games in bacteria. Curr. Opin. Microbiol. 6: 125–134PubMedCrossRefGoogle Scholar
  93. Wright, B. E., Kelly, P. J. (1981): Kinetic models of metabolism in intact cells, tissues and organisms. Curr. Top. Cell. Regul. 19: 103–158PubMedGoogle Scholar
  94. Wu, L., Wang, W., van Winden, W. A., van Gulik, W. M., Heijnen, J. J. (2004): A new framework for the estimation of control parameters in metabolic pathways using lin-log kinetics. Eur. J. Biochem. 271: 3348–3359PubMedCrossRefGoogle Scholar
  95. Zhang, L., Karin, M. (2001): Mammalian MAP kinase signaling cascades. Nature 410: 37–40CrossRefGoogle Scholar

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© Spektrum Akademischer Verlag Heidelberg 2011

Authors and Affiliations

  • Ralf Takors
    • 1
  1. 1.Institut für BioverfahrenstechnikTechnische Universität StuttgartStuttgart

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