Advertisement

Wachstumskinetik

  • Dirk Weuster-Botz
  • Ralf Takors
Chapter

Zusammenfassung

Mikroorganismen (Bakterien, Hefen, Pilze, Mikroalgen) und Gewebezellen (tierische Zellen, pflanzliche Zellen) werden neben isolierten Enzymen als Biokatalysatoren in vielfältiger Weise in der industriellen Produktion eingesetzt. Die quantitative Kenntnis der Reaktionsgeschwindigkeiten dieser Biokatalysatoren (Substratverbrauch, Wachstum und Produktbildung) in Abhängigkeit der Reaktionsbedingungen ist von zentraler Bedeutung für Auslegung und Betrieb von Bioreaktoren. Die grundlegenden Konzepte zur Wachstumsmodellierung von Mikroorganismen und Zellen werden in diesem Kapitel beschrieben.

Literatur

  1. [1]
    Müller S (2007) Modes of cytometric bacterial DNA pattern: A tool for pursuing growth. Cell Proliferat 40:621–639CrossRefGoogle Scholar
  2. [2]
    Zwietering MH, Jongenburger I, Rombouts FM, van’t Riet K (1990) Modeling of the bacterial growth curve. Appl Environ Microbiol 56:18575–1881Google Scholar
  3. [3]
    Bellgardt K-H (1991) Cell models. In: Rehm H-J, Reed G, Pühler A, Stadler P, Schügerl K (Hrsg) Biotechnology, Vol. 4, Measuring, Modeling and Control, VCH, Weinheim, S 267–298Google Scholar
  4. [4]
    Monod J (1942) Recherches sur la croissance des cultures bacteriennes, 2. Aufl. Hermann, ParisGoogle Scholar
  5. [5]
    Andrews JF (1968) A mathematical model for continuous culture of microorganisms utilizing inhibitory substrates. Biotechnol Bioeng 10:707CrossRefGoogle Scholar
  6. [6]
    Levenspiel O (1980) The Monod equation: a revisit and a generalization to product inhibition situations. Biotechnol Bioeng 22:1671–1687CrossRefGoogle Scholar
  7. [7]
    Ierusalimski ND, Neronova NM (1965) Quality concentration of exchange products as dependent on rate of growth of microorganisms. Doklady Akademii Nauk SSSR 161:1437Google Scholar
  8. [8]
    Edwards VH (1970) The influence of high substrate concentrations on microbial kinetics. Biotechnol Bioeng 12:679CrossRefGoogle Scholar
  9. [9]
    Pirt SJ (1965) The maintenance energy of bacteria in growing cultures. Proc R Soc Ser B 163:224CrossRefGoogle Scholar
  10. [10]
    Tsao GT, Hanson TP (1975) Extended Monod equation for batch cultures with multiple exponential phases. Biotechnol Bioeng 12:1591–1598CrossRefGoogle Scholar
  11. [11]
    Roels JA (1983) Energetics and kinetics in biotechnology. Elsevier, AmsterdamGoogle Scholar
  12. [12]
    Gaden EL (1959) Fermentation process kinetics. J Biochem Microbiol Techn Eng 1:413–429CrossRefGoogle Scholar
  13. [13]
    Takors R, Wiechert W, Weuster-Botz D (1997) Experimental design for the identification of macrokinetic models and model discrimination. Biotech Bioeng 56:564–576CrossRefGoogle Scholar
  14. [14]
    Nielsen J (1993) A simple morphologically structured model describing the growth of filamentous microorganisms. Biotechnol Bioeng 41:715–727CrossRefGoogle Scholar
  15. [15]
    De Ory I, Romero LE, Cantero D (1998) Modelling the kinetics of growth of Acetobacter aceti in discontinuous culture: influence of the temperature of operation. Appl Microbiol Biotechnol 49:189û193CrossRefGoogle Scholar
  16. [16]
    Olsen KN, Budde BB, Siegumfeldt H, Rechinger KB, Jakobsen M, Ingmer H (2002) Noninvasive measurement of bacterial intracellular pH on a single-cell level with green fluorescent protein and fluorescence ratio imaging microscopy. Appl Environ Microbiol 68:4145–4147CrossRefGoogle Scholar
  17. [17]
    Shimamoto T, Inaba K, Thelen P, Ishikawa T, Goldberg EB, Tsuda M, Tsuchiya T (1994) The NhaB Na+/H+ antiporter is essential for intracellular pH regulation under alkaline conditions in Escherichia coli. J Biochem 116:285–290CrossRefGoogle Scholar
  18. [18]
    Nicholls DG, Fergusan SJ (1992) Bioenergetics 2. Academic Press, LondonGoogle Scholar
  19. [19]
    Ackermann T (1992) Physikalische Biochemie. Springer, BerlinCrossRefGoogle Scholar
  20. [20]
    Lehninger AL, Nelson DL, Cox MM (1994) Prinzipien der Biochemie, 2. Aufl. Spektrum Akademischer Verlag, HeidelbergGoogle Scholar
  21. [21]
    Schuhmacher T, Löffler M, Hurler T, Takors R (2014) Phosphate limited fed-batch process: Impact on carbon usage and energy metabolism in Escherichia coliEscherichia coli. J Biotechnol 190:96–104CrossRefGoogle Scholar
  22. [22]
    Pyle AM (1996) Role of metal ions in ribozymes. Met Ions Biol Syst: 479–520Google Scholar
  23. [23]
    Silver S (1998) Genes for all metalls – A bacterial view of the periodic table. The 1996 Thom Award Lecture. J Ind Microbiol Biotechnol 20:1–12CrossRefGoogle Scholar
  24. [24]
    Otterbach H (1974) Äthylendiamin-tetraessigsäure. In: Ullmanns Encyklopädie der technischen Chemie, Bd 8, 4. Aufl. Verlag Chemie, WeinheimGoogle Scholar
  25. [25]
    Silver S, Perry RD (1982) Bacterial inorganic cation and anion transport systems. In: Martonosi AN (Hrsg) Membranes and transport, Bd 2. Plenum Press, New York, S 115–121CrossRefGoogle Scholar
  26. [26]
    Jasper P, Silver S (1977) Magnesium transport in microorganisms. In: Weinberg ED (Hrsg) Microorganisms and minerals, Marcel Dekker, Inc. New York, S. 7–47Google Scholar
  27. [27]
    Marks J (1993) Biological functions of vitamins. In: Ottaway PB (Hrsg) The technology of vitamins in food, Chapman & Hall, LondonGoogle Scholar
  28. [28]
    Zabriskie DW, Armiger WB, Phillips DH, Albano PA (1982): Trader’s guide to fermentation media formulation. Traders protein, P.O. box 8407, Memphis, Tennessee 38108, USAGoogle Scholar
  29. [29]
    Weuster-Botz D (2000) Experimental design for fermentation media development: Statistical design or global random search? J Bioscience Bioeng 90:473–483CrossRefGoogle Scholar
  30. [30]
    Khuri AI, Cornell JA (1987) Response surfaces. Marcel Dekker, New YorkGoogle Scholar
  31. [31]
    Holland JH (1975) Adaption in natural and artificial systems. The University of Michigan Press, Ann ArborGoogle Scholar
  32. [32]
    Link H, Weuster-Botz D (2006) Genetic algorithm for multi-objective experimental optimization. Bioprocess Biosyst Eng 29:385–390CrossRefGoogle Scholar
  33. [33]
    Sprave J (1995) Evolutionäre Algorithmen zur Parameteroptimierung. at 43:110–117Google Scholar

Copyright information

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

Authors and Affiliations

  1. 1.Technische Universität MünchenLehrstuhl für BioverfahrenstechnikGarchingDeutschland
  2. 2.Universität StuttgartInstitut für BioverfahrenstechnikStuttgartDeutschland

Personalised recommendations