title: Generally applicable fed-batch culture concept based on the detection of metabolic state by on-line balancing.
abstract: In many microorganisms, flux limitations in oxidative metabolism lead to the formation of overflow metabolites even under fully aerobic conditions. This can be avoided if the specific growth rate is controlled at a low enough value. This is usually accomplished by controlling the substrate feeding profile in a fed-batch process. The present work proposes a control concept which is based on the on-line detection of metabolic state by on-line calculation of mass and elemental balances. The advantages of this method are: 1) the check of measurement consistency based on all of the available measurements, 2) the minimum requirement of a priori knowledge of metabolism, and 3) the exclusive use of simple and established on-line techniques which do not require direct measurement of the metabolite in question. The control concept has been linked to a simple adaptive controller and applied to fed-batch cultures of S. cerevisiae and E. coli, organisms which express different overflow metabolites, ethanol and acetic acid, respectively. Oxidative and oxidoreductive states of S. cerevisiae and E. coli cultures were detected with high precision. As demonstrated by the formation of acetic acid in E. coli cultures, metabolic states could be correctly distinguished for systems for which traditional methods, such as respiratory quotient (RQ), are insensitive. Hence, it could be shown that the control concept allowed avoidance of overflow metabolite formation and operation at maximum oxidative biomass productivity and oxidative conversion of substrate into biomass. Based on mass and elemental balances, the proposed method additionally provides a richness of additional information, such as yield coefficients and estimation of concentrations and specific conversion rates. These data certainly help the operator to additionally evaluate the state of the process on-line.
authors.affiliation: Laboratory of Chemical and Biological Engineering, Swiss Federal Institute of Technology Lausanne (EPFL), CH-1015 Lausanne, Switzerland.
authors.forename: Anna Marya
authors.initials: AM
authors.lastname: Jobé
authors.forename: Christoph
authors.initials: C
authors.lastname: Herwig
authors.forename: Martin
authors.initials: M
authors.lastname: Surzyn
authors.forename: Bernhard
authors.initials: B
authors.lastname: Walker
authors.forename: Ian
authors.initials: I
authors.lastname: Marison
authors.forename: Urs
authors.initials: U
authors.lastname: von Stockar
mesh_terms: D000222:Adaptation, Physiological / Q000502:physiology; D000465:Algorithms; D019149:Bioreactors / Q000382:microbiology*; D018929:Cell Culture Techniques / Q000379:methods*; D003198:Computer Simulation; D004734:Energy Metabolism / Q000502:physiology*; D004926:Escherichia coli / Q000254:growth & development / Q000378:metabolism*; D005246:Feedback; D005947:Glucose / Q000378:metabolism; D007218:Industrial Microbiology / Q000379:methods; D008954:Models, Biological; D009862:Online Systems; D010084:Oxidation-Reduction; D010100:Oxygen / Q000378:metabolism; D012441:Saccharomyces cerevisiae / Q000254:growth & development / Q000378:metabolism*
chemical_list: D005947:Glucose; D010100:Oxygen