Model-Based Design of Superior Cell Factory: An Illustrative Example of Penicillium chrysogenum

  • I. Emrah Nikerel
  • Peter J. T. Verheijen
  • Walter M. van Gulik
  • Joseph J. Heijnen


A dynamic model for metabolic reaction network of Penicillium chrysogenum, coupling the central metabolism to growth, product formation and storage pathways is presented. In constructing the model, we started from an existing stoichiometric model, and systematically reduced this initial model to a one compartment model and further eliminated unidentifiabilities due to time scales. Kinetic analysis focuses on a time scale of seconds, thereby neglecting biosynthesis of new enzymes. We used linlog kinetics in representing the kinetic rate equations of each individual reaction. The final parameterization is performed for the final reduced model using previously published short term glucose perturbation data. The constructed model is a self-contained model in the sense that it can also predict the cofactor dynamics. Using the model, we calculated the Metabolic Control Analysis (MCA) parameters and found that the interplay among the growth, product formation and production of storage materials is strongly governed by the energy budget in the cell, which is in agreement with the previous findings. The model predictions and experimental observations agree reasonably well for most of the metabolites.


Model-based design Penicillium chrysogenum Dynamic model Metabolic network Cell factory Linlog kinetics Parameterization Metabolic Control Analysis (MCA) Model prediction Time-scale analysis Elasticities Kinetic model P/O ratio Post-genomic Genome-scale Stimulus response experiments Metabolic flux Stoichiometry Network reconstruction Compartments Pseudo equilibrium Pseudo steady-state 


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Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • I. Emrah Nikerel
    • 1
    • 2
  • Peter J. T. Verheijen
    • 2
  • Walter M. van Gulik
    • 2
  • Joseph J. Heijnen
    • 2
  1. 1.Delft Bioinformatics LabDelft University of TechnologyDelftThe Netherlands
  2. 2.Department of Biotechnology, Kluyver Centre for Genomics of Industrial FermentationDelft University of TechnologyDelftThe Netherlands

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