Systembiologie in der Bioverfahrenstechnik

  • Ralf TakorsEmail author


Die Systembiologie ist eine Wissenschaft, die sich nach wie vor rasant entwickelt. Sie verfolgt den Ansatz, ein biologisches System holistisch, d. h. ganzheitlich zu betrachten und quantitativ zu beschreiben. Dabei steht die Interaktion der einzelnen Module (Moleküle, Zellen, Regulationsmechanismen oder Populationen) im Vordergrund der Untersuchungen. Folgerichtig setzen sich systembiologische Studien aus unterschiedlichsten Facetten der Forschungsthemen zusammen und adressieren vielfältige Themenfelder der Biologie und Medizin. Das nachfolgende Kapitel stellt nur einen kleinen Teilaspekt in den Vordergrund: nämlich die systembiologischen Aspekte in der Bioverfahrens- bzw. Bioprozesstechnik. Weitere Themenfelder werden in den Übersichten vorgestellt.


  1. [1]
    Aiba S, Matsuoka M (1979) Identification of metabolic model: Citrate production from glucose by Candida lipolytica. Biotechnol Bioeng 21:1373‒1386Google Scholar
  2. [2]
    Antoniewicz MR, Kelleher JK, Stephanopoulos G (2007) Elementary metabolite units (EMU): A novel framework for modeling isotopic distributions. Metab Eng 9:68‒86PubMedGoogle Scholar
  3. [3]
    Antoniewicz MR, Kraynie DF, Laffend LA, Gonzalez-Lergier J, Kelleher JK, Stephanopoulos G (2007) Metabolic flux analysis in a nonstationary system: Fed-batch fermentation of a high yielding strain of E. coli producing 1,3-propanediol. Metab Eng 9:277‒292PubMedPubMedCentralGoogle Scholar
  4. [4]
    Avery SV (2006) Microbial cell individuality and the underlying sources of heterogeneity. Nature Rev 4:577–587Google Scholar
  5. [5]
    Bailey JE (1991) Towards a science of metabolic engineering. Science 252:1668‒1674PubMedGoogle Scholar
  6. [6]
    Bailey JE (1999) Lessons from metabolic engineering for functional genomics and drug discovery. Nat Biotechnol 17:616–618PubMedGoogle Scholar
  7. [7]
    Beckwith JR (1967) Regulation of the lac operon. Recent studies on the regulation of lactose metabolism in Escherichia coli support the operon model. Science 156:597‒604PubMedGoogle Scholar
  8. [8]
    Blank LM, 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:R49PubMedPubMedCentralGoogle Scholar
  9. [9]
    Blum JJ, Stein RB. (1982) On the analysis of metabolic networks. In: Goldberger RF (Hrsg) Biological regulation and development, Plenum Press, New York, S 99‒124Google Scholar
  10. [10]
    Bonarius HPJ, Schmidt G, Tramper J (1997) Flux analysis of underdetermined metabolic systems: The quest of missing constraints. Trends Biotechnol 15:308‒314Google Scholar
  11. [11]
    Bordel S, Nielsen J (2010) Identification of flux control in metabolic networks using non-equilibrium thermodynamics. MetabEng 12:369–377Google Scholar
  12. [12]
    Buchholz J, Graf M, Freund A, Busche J, Kalinowski J, Blombach B, Takors R (2014) CO2/HCO3 perturbations of simulated large scale gradients in a scale-down device cause fast transcriptional responses in Corynebacterium glutamicum. Appl Microbiol Biotechnol 98(29):8563–8572PubMedGoogle Scholar
  13. [13]
    Burgard AP, Phakya P, Maranas CD (2003) OptKnock, a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnol Bioeng 84:647‒657PubMedGoogle Scholar
  14. [14]
    Burns JA, Cornish-Bowden A, Groen AK, Heinrich R, Kacser H, Porteous JW, Rapoport SM, Rapoport TA, Stucki JW, Tager JM, Wanders RJA, Westerhoff HV (1985) Control analysis of metabolic systems. Trends Biochem Sci 10:16Google Scholar
  15. [15]
    Bylund F, Collet E, Enfors SO, Larsson G (1998) Substrate gradient formation in the large-scale bioreactor lowers cell yield and increases by-product formation, Bioproc Eng 18:171–180Google Scholar
  16. [16]
    Cameron DC, Tong T-T (1993) Cellular and metabolic engineering. Appl Biochem Biotechnol 38:105‒140PubMedGoogle Scholar
  17. [17]
    Caspeta L, Nielsen J (2013) Towards systems metabolic engineering of Aspergillus and Pichia species for the production of chemicals and biofuels. Biotechnol J 8:534–544.PubMedGoogle Scholar
  18. [18]
    Chance B, Garfinkel D, Higgins J, Hess B (1960) Metabolic control mechanisms. J Biol Chem 235:2426‒2439PubMedGoogle Scholar
  19. [19]
    Christensen B, Nielsen J (1999) Metabolic network analysis – a powerful tool in metabolic engineering. Adv Biochem Eng Biotechnol 66:209‒231Google Scholar
  20. [20]
    Christensen B, Nielsen J (1999) Isotopomer analysis using CG-MS. Metab Eng 1:282‒290PubMedGoogle Scholar
  21. [21]
    de Graaf AA (2000) Metabolic analysis of Zymomonas mobilis. In: Schügerl K, Belgardt KH (Hrsg) Bioreaction Engineering, Modelling and Control, Springer Verlag, New YorkGoogle Scholar
  22. [22]
    Delvigne F, Brognaux A, Gorret N, Neubauer P, Delafosse A, Collignon ML, Toye D, Crine M, Boxus M, Thonart P (2011) Characterization of the response of GFP microbial biosensors sensitive to substrate limitation in scale-down bioreactors. Biochem Eng J 55:131–139Google Scholar
  23. [23]
    Feist AM, Henry CS, Reed JL, Krummenacker M, Joyce AR, Karp P-D, Broadbelt LJ, Hatzimanikatis V, Palsson BO (2007) A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Mol Syst Biol 3:121PubMedPubMedCentralGoogle Scholar
  24. [24]
    Fell DA (1997) Metabolic control analysis: A survey of its theoretical and experimental development. Biochem J 286:313‒330Google Scholar
  25. [25]
    Ferenci T (2001) Hungry bacteria ‒ definition and properties of a nutritional state. Environ Microbiol 3(10):605‒611PubMedGoogle Scholar
  26. [26]
    Griffith JS (1968) Mathematics of cellular control processes. I. Negative feedback to one gene. J Theor Biol 20:202‒208PubMedGoogle Scholar
  27. [27]
    Griffith JS (1968) Mathematics of cellular control processes. II. Positive feedback to one gene. J Theor Biol 20:209‒216PubMedGoogle Scholar
  28. [28]
    Hatzimanikatis V, Bailey JE (1997) Effects of spatiotemporal variations on metabolic control: Approximate analysis using (log) linear kinetic models. Biotechnol Bioeng 1:75–87Google Scholar
  29. [29]
    Hatzimanikatis V, Emmerling M, Sauer U, Bailey JE (1998) Application of mathematical tools for metabolic design of microbial ethanol production. Biotechnol Bioeng 58:154–161PubMedGoogle Scholar
  30. [30]
    Hatzimanikatis V, Floudas CA, Bailey JE (1996) Analysis and design of metabolic reaction networks via mixed-integer linear optimization. AICHE J 42:1277–1292Google Scholar
  31. [31]
    Heinrich R, Rapoport TA (1974) A linear steady-state treatment of enzymatic chains. General properties, control and effector strength. Eur J Biochem 42:89‒95PubMedGoogle Scholar
  32. [32]
    Henry CS, Broadbelt LJ, Hatzimanikatis V (2007) Thermodynamics-based metabolic flux analysis. Biophys J 92(5):1792‒1805PubMedGoogle Scholar
  33. [33]
    Henson MA (2003) Dynamic modeling of microbial populations. Curr Opin Biotechnol 14:460–467PubMedGoogle Scholar
  34. [34]
    Hess B, Boiteux A (1968) Mechanism of glycolytic oscillation in yeast. I. Aerobic and anaerobic growth conditions for obtaining glycolytic oscillation. Hoppe-Seylers Z physiol Chem 349(11):1567‒1574PubMedGoogle Scholar
  35. [35]
    Hewitt C, Nebe-von Caron G, Axelsson B, McFarlane CM, Nienow AW (2003) Studies related to the scale-up of high-cell-density E.coli fed-batch fermentations using multiparameter flow cytometry: Effect of a changing microenvironment with respect to glucose and dissolved oxygen concentration. Biotechnol Bioeng 70(4):381–390Google Scholar
  36. [36]
    Ibarra RU, Edwards JS, Palsson BO (2002) Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth. Nature 420: 186‒189PubMedGoogle Scholar
  37. [37]
    Jandt U, Platas Barradas O, Pörtner R, Zeng AP (2014) Mammalian cell culture synchronization under physiological conditions and population dynamic simulation. Appl Microbiol Biotechnol 98:4311–4319PubMedGoogle Scholar
  38. [38]
    Junker BH (2004) Scale-up Methodologies for Escherichia coli and Yeast Fermentation Process. J BiosciBioeng 97(6):347–364Google Scholar
  39. [39]
    Kacser H, Burns, JA (1973) The control of flux. Symp Soc Exp Biol 27:37‒63Google Scholar
  40. [40]
    Käß F, Hariskos I, Michel A, Brandt H-J, Spann R, Junne S, Wiechert W, Neubauer P, Oldiges M (2013) Assessment of robustness against dissolved oxygen/substrate oscillations for C. glutamicum DM1933 in two-compartment bioreactor. Bioprocess Biosystems Eng 37(6):1–12. PubMedGoogle Scholar
  41. [41]
    Käß F, Junne S, Neubauer P, Wiechert W, Oldiges M (2014) Process inhomogeneity leads to rapid side product turnover in cultivation of Corynebacterium glutamicum. Microb Cell Fact 13:6. CrossRefPubMedPubMedCentralGoogle Scholar
  42. [42]
    Klipp E, Herwig R, Kowald A, Wierling C, Lehrach H (2005) Systems Biology in Practice. Wiley-VCH, WeinheimGoogle Scholar
  43. [43]
    Kümme A, Panke S, Heinemann M (2006) Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data. Mol Syst Biol 2: 1‒10.
  44. [44]
    Lapin A, Müller D, Reuss M (2004) Dynamic behavior of microbial populations in stirred bioreactors simulated with euler-lagrange methods: Travelling along the Lifeline of Single Cells. Ind Eng Chem Res 43:4647–4657Google Scholar
  45. [45]
    Lapin A, Schmid J, Reuss M (2006) Modeling the dynamics of E. coli populations in the three-dimensional turbulent field of a stirred-tank bioreactor – A structured – segregated approach. Chem Eng Sci 61:4783–4797Google Scholar
  46. [46]
    Lara AR, Galindo E, Ramirez OT, Palomares LA (2006) Living with heterogeneities in bioreactors. Mol Biotechnol 34:355‒381PubMedGoogle Scholar
  47. [47]
    Lee SY (2009) Systems Biology and Biotechnology of Escherichia coli. Springer Science+Business Media B.V., BerlinGoogle Scholar
  48. [48]
    Lee SY, Mattanovich D, Villaverde A (2013) Systems metabolic engineering, industrial biotechnology and microbial cell factories. Microb Cell Fact 11:156.Google Scholar
  49. [49]
    Leighty RW Antoniewicz MR (2011) Dynamic metabolic flux analysis (DMFA): a framework for determining fluxes at metabolic non-steady-state. Metab Eng 13(6):745–55PubMedGoogle Scholar
  50. [50]
    Lencastre Fernandes R, Nierychlo M, Pedersen AE, Puentes Tellez PE, Dutta A, Calquist M, Bolic A, Schäpper D, Brunetti AC, Helmark S, Heins A-L, Jensen AD, Nopens I, Rottwit K, Szita N, van Alsas JD, Nielsen PH, Martinussen J, Sorensen SJ, Lantz AE, Gernaey KV (2011) Experimental methods and modeling techniques for description of cell population heterogeneity. Biotechnol Adv 29:575–599PubMedGoogle Scholar
  51. [51]
    Liebermeister W, Klipp E (2006) Bringing metabolic networks to life: convenience rate law and thermodynamic constraints. Theor Biol Med Model 3:41PubMedPubMedCentralGoogle Scholar
  52. [52]
    Lieder S, Nikel PI, de Lorenzo V, Takors R (2015) Genome reduction boosts heterologous gene expression in Pseudomonas putida. Microb Cell Fac 14:23.Google Scholar
  53. [53]
    Löffler M, Simen JD, Jäger G, Schäferhoff K, Freund A, Takors R (2016) Engineering E. coli for Large-Scale Production – Strategies Considering ATP Expenses and Transcriptional Responses. Metab Eng. PubMedGoogle Scholar
  54. [54]
    Magnus JB, 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):1071‒1083PubMedGoogle Scholar
  55. [55]
    Makinoshima H, Nishimura A, Ishihama A (2002) Fractionation of Escherichia coli cell populations at different stages during growth transition to stationary phase. Mol Micro 43:269–279Google Scholar
  56. [56]
    Malloy CR, Sherry AD, Jeffrey FMH (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
  57. [57]
    Marx A, de Graaf AA, 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 49:111‒129PubMedGoogle Scholar
  58. [58]
    Müller S, Harms H, Bley T (2010) Origin and analysis of microbial population heterogeneity in bioprocesses. Curr Opin Biotechnol 21(1):100–113PubMedGoogle Scholar
  59. [59]
    Mustafi N, Gruenberger A, Mahr R, Helfrich S, Nöh K, Blombach B, Kohlheyer D, Frunzke J (2014) Application of a genetically encoded biosensor for live cell imaging of L-valine production in pyruvate dehydrogenase complex-deficient Corynebacterium glutamicum strains. PlosOne 9(1):e85731PubMedPubMedCentralGoogle Scholar
  60. [60]
    Neubauer P, Junne S (2010) Scale-down simulators for metabolic analysis of large-scale bioprocesses. Cur Opin Biotechnol 21:114–121Google Scholar
  61. [61]
    Neubauer P, Cruz N, Glauche F, Junne S, Knepper A, Raven M (2013) Consistent development of bioprocesses from microliter cultures to the industrial scale. Eng Life Sci 13:224–238Google Scholar
  62. [62]
    Nielsen J (1997) Metabolic control analysis of biochemical pathways based on a thermokinetic description of reaction rates. Biochem J 321:133‒138PubMedPubMedCentralGoogle Scholar
  63. [63]
    Nielsen J, Villadsen J, Liden G (2003) Bioreaction Engineering Principles. Kluwer Academic/Plenum Publishers, New YorkGoogle Scholar
  64. [64]
    Nöh K, Grönke 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):249‒267PubMedGoogle Scholar
  65. [65]
    Onsager L (1931) Reciprocal relations in irreversible processes I. Physical Rev 37:405‒426Google Scholar
  66. [66]
    Palsson BO (2006) Systems Biology – Properties of reconstructed networks. University Press, CambridgeGoogle Scholar
  67. [67]
    Patil KR, Rocha I, Förster J, Nielsen J (2005) Evolutionary programming as a platform for in silico metabolic engineering. BMC Bioinformatics 6:308PubMedPubMedCentralGoogle Scholar
  68. [68]
    Petersen S, de Graaf AA, Eggeling L, Möllmay M, Wiechert W, Sahm H (2000) In vivo quantification of parallel and bidirectional fluxes in the anaplerosis of Corynebacterium glutamicum. J Biol Chem 275: 35932‒35941PubMedGoogle Scholar
  69. [69]
    Pharkya P, Burgard AP, Maranas CD (2004) OptStrain: A computational framework for redesign of microbial production systems. Genome Res 14:2367–2376PubMedPubMedCentralGoogle Scholar
  70. [70]
    Pharkya P, Maranas CD (2006) An optimization framework for identifying reaction activation/inhibition or elimination candidates for overproduction in microbial systems. Metab Eng 8:1–13PubMedGoogle Scholar
  71. [71]
    Reder C (1988) Metabolic control theory: a structural approach. J Theor Biol 135:175‒201PubMedGoogle Scholar
  72. [72]
    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.
  73. [73]
    Rottenberg H (1973) The thermodynamic description of enzyme-catalyzed reactions. Biophys J 13: 503‒511PubMedPubMedCentralGoogle Scholar
  74. [74]
    Savageau MA (1976) Biochemical Systems Analysis: A Study of Function and Design in Molecular Biology. Addison-Wesley, Reading, MAGoogle Scholar
  75. [75]
    Sauer U (2006) Metabolic networks in motion: 13C-based flux analysis. Mol Syst Biol 2:62PubMedPubMedCentralGoogle Scholar
  76. [76]
    Schaub J, Clemens C, Kaufmann H, Schulz TW (2011) Advancing Biopharmaceutical Bioprocess Development By System-Level Data Analysis and Integration of Omics Data.Adv. Biochem Engin/Biotechnol. Google Scholar
  77. [77]
    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 99:1170‒1185PubMedGoogle Scholar
  78. [78]
    Schmalzriedt S, Jenne M, Mauch K, Reuss M (2003) Integration of Physiology and Fluid Dynamics. Adv Biochem Eng 80:19–68Google Scholar
  79. [79]
    Schmidt K, Carlsen M, Nielsen J, Villadsen J (1997) Modeling isotopomer distribution in biochemical networks using isotopomer maping matrices. Biotechnol Bioeng 55:831‒840PubMedGoogle Scholar
  80. [80]
    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 71:175‒189PubMedGoogle Scholar
  81. [81]
    Schuhmacher T, Löffler M, Hurler T, Takors R (2014) Phosphate limited fed-batch processes: Impact on carbon usage and energy metabolism in Escherichia coli. J Biotechnol 190:96–104. CrossRefPubMedGoogle Scholar
  82. [82]
    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 18:326‒332Google Scholar
  83. [83]
    Schweder T, Krüger E, Xu B, Jürgen B, Blomsten G, Enfor S-O, Hecker M (1999) Monitoring of genes that respond to process-related stress in large-scale bioprocesses. Biotechnol Bioeng 65:151‒159PubMedGoogle Scholar
  84. [84]
    Segre D, Vitkup D, Church GM (2002) Analysis of optimality in natural perturbed metabolic networks. Proc Natl Acad Sci USA 99:15112‒15117PubMedGoogle Scholar
  85. [85]
    Shimizu K (2009) Towards systematic metabolic engineering based on the analysis of metabolic regulation by integration of different levels of information. Biochem Eng J 46:235‒251Google Scholar
  86. [86]
    Shlomi T, Berkman O, Ruppin E (2005) Regulatory on/off minimization of metabolic flux changes after genetic perturbations. PNAS 102(21):7695–7700PubMedGoogle Scholar
  87. [87]
    Sonntag K, Eggeling L, de Graaf AA, 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 213:1325‒1331PubMedGoogle Scholar
  88. [88]
    Stephanopoulos GN, Aristidou AA, Nielsen J (1998) Metabolic Engineering. Academic Press, San DiegoGoogle Scholar
  89. [89]
    Szyperski T (1995) Biosynthetically directed fractional 13 C labelling of proteinogenic amino acids – an efficient analytical tool to investigate intermediary metabolism. Eur J Biochem 232:433‒448PubMedGoogle Scholar
  90. [90]
    Szyperski T (1998) 13C-NMR, MS and metabolic flux balancing in biotechnological research. Q Rev Biophys 31:41‒106PubMedGoogle Scholar
  91. [91]
    Takors R (2012) Scale-up of microbial processes: Impacts, tools and open questions. J Biotechnol 160:3–9PubMedGoogle Scholar
  92. [92]
    Tang YJ, Martin HG, Myers S, Rodriguez S, Baidoo EE, Keasling JD (2009) Advances in analysis of microbial metabolic fluxes cia 13c isotopic labeling. Mass Spectrom Rev 28:362‒375PubMedGoogle Scholar
  93. [93]
    Umbarger HE, Brown B (1957) Threonine deamination in Escherichia coli. II. Evidence for two L-threonine deaminases. J Bacteriol 73:105‒112PubMedPubMedCentralGoogle Scholar
  94. [94]
    Vallino JJ, Stephanopoulos G (1993) Metabolic flux distribution in Corynbacterium glutamicum during growth and lysine overproduction. Biotechnol Bioeng 41:633‒646PubMedGoogle Scholar
  95. [95]
    Van Berlo RJ, de Ridder D, Daran JM, Daran-Lapujade PA, Teusink B, Reinders MJ (2011) Predicting metabolic fluxes using gene expression differences as constraints. IEEE/ACM Transactions on Computational Biology and Bioinformatics 8(1):206–216PubMedGoogle Scholar
  96. [96]
    van der Meer R, Westerhoff HV, van Dam K (1980) Linear relation between rate and thermodynamic force in enzyme-catalyzed reactions. Biochim Biophys Acta 591:488‒493PubMedGoogle Scholar
  97. [97]
    Varma A, Boesch BW, Palsson BO (1993) Stoichiometric interpretation of Escherichia coli glucose catabolism under various oxygenation rates. Appl Environ Microbiol 59:2465‒2473PubMedPubMedCentralGoogle Scholar
  98. [98]
    Varma A. Palsson BO (1994) Metabolic flux balancing: basic concepts, scientific and practical use. Bio/Technology 12:994‒998Google Scholar
  99. [99]
    Vaseghi S, Baumeister A, Rizzi M, Reuss M (1999) In vivo dynamics of the pentose phosphate pathway in Saccharomyces cerevisiae. Metab Eng 1:128‒140PubMedGoogle Scholar
  100. [100]
    Visser D, Heijnen JJ (2002) The mathematics of metabolic control analysis revisited. Metab Eng 4:114‒123PubMedGoogle Scholar
  101. [101]
    Visser D, Heijnen JJ (2003) Dynamic simulation and metabolic re-design of a branched pathway using linlog kinetics. Metab Eng 5:164‒176PubMedGoogle Scholar
  102. [102]
    Vrabel P, van der Lans RGJM, van der Schot FN, Luyben KChAM, Xu B, Enfor S-O (2001) CMA: integration o fluid dynamics and microbial kinetics in modeling of large-scale fermentations, Chem Eng J 84:463–474Google Scholar
  103. [103]
    Westerhoff HV, Palsson BO (2004) The evolution of molecular biology into systems biology. Nature Biotechnol 22(10):1249‒1252Google Scholar
  104. [104]
    Westerhoff HV, van Dam K (1987) Thermodynamics and control of biological free-energy transduction. Elsevier, AmsterdamGoogle Scholar
  105. [105]
    Wiechert W (2001) 13C Metabolic Flux Analysis. Metab Eng 3:195–206PubMedGoogle Scholar
  106. [106]
    Wiechert W. (2002) Modeling and simulation: tools for metabolic engineering. J Biotechnol 94:37‒63PubMedGoogle Scholar
  107. [107]
    Wiechert W, Möllney M, Isermann N, Wurzel M, de Graaf AA (1999) Bidirectional reaction steps in metabolic networks part III: Explicit solution and analysis of isotopomer labelling systems. Biotechnol Bioeng 66:69‒85PubMedGoogle Scholar
  108. [108]
    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 268:2441‒2455PubMedGoogle Scholar
  109. [109]
    Woolston BM, Edgar S, Stephanolpoulos G (2013) Metabolic Engineering: Past and Future. Ann Rev Chem Biomol Eng 4:259–288Google Scholar
  110. [110]
    Wright BE, Kelly PJ (1981) Kinetic models of metabolism in intact cells, tissues and organisms. Curr Top Cell Regul 19:103‒158PubMedGoogle Scholar
  111. [111]
    Wu L, Wang W, van Winden WA, van Gulik WM, Heijnen JJ (2004) A new framework for the estimation of control parameters in metabolic pathways using lin-log kinetics. Eur J Biochem 271:3348‒3359PubMedGoogle Scholar
  112. [112]
    Zupke G, Stephanopoulos G (1994) Modeling of isotope distributions and intracellular fluxes in metabolic networks using atom mapping matrices. Biotechnol Prog 10:489–498Google Scholar

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© Springer-Verlag GmbH Deutschland, ein Teil von Springer Nature 2018

Authors and Affiliations

  1. 1.Universität StuttgartInstitut für BioverfahrenstechnikStuttgartDeutschland

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