Kinetic models in industrial biotechnology – Improving cell factory performance

J. Almquist, M. Cvijovic, V. Hatzimanikatis, J. Nielsen, M. Jirstrand. Metabolic Engineering, July, 2014, 24, 38-60.

An increasing number of industrial bioprocesses capitalize on living cells by using them as cell factories that convert sugars into chemicals. These processes range from the production of bulk chemicals in yeasts and bacteria to the synthesis of therapeutic proteins in mammalian cell lines. One of the tools in the continuous search for improved performance of such production systems is the development and application of mathematical models. To be of value for industrial biotechnology, mathematical models should be able to assist in the rational design of cell factory properties or in the production processes in which they are utilized. Kinetic models are particularly suitable towards this end because they are capable of representing the complex biochemistry of cells in a more complete way compared to most other types of models. They can, at least in principle, be used to in detail understand, predict, and evaluate the effects of adding, removing, or modifying molecular components of a cell factory and for supporting the design of the bioreactor or fermentation process. However, several challenges still remain before kinetic modeling will reach the degree of maturity required for routine application in industry. Here we review the current status of kinetic cell factory modeling. Emphasis is on modeling methodology concepts, including model network structure, kinetic rate expressions, parameter estimation, optimization methods, identifiability analysis, model reduction, and model validation, but several applications of kinetic models for the improvement of cell factories are also discussed.

Authors and Affiliations

  • Joachim Almquist, Fraunhofer-Chalmers Centre, Sweden
  • Marija Cvijovic, Chalmers University of Technology and University of Gothenburg, Sweden
  • Vassilis Hatzimanikatis, Ecole Polytechnique Federale de Lausanne, Switzerland
  • Jens Nielsen, Chalmers University of Technology, Sweden
  • Mats Jirstrand, Fraunhofer-Chalmers Centre, Sweden

Photo credits: Nic McPhee