Bioprocess and Biosystems Engineering

, Volume 35, Issue 6, pp 1023–1033 | Cite as

Genome-based kinetic modeling of cytosolic glucose metabolism in industrially relevant cell lines: Saccharomyces cerevisiae and Chinese hamster ovary cells

  • Ning Chen
  • Georgios C. Koumpouras
  • Karen M. Polizzi
  • Cleo KontoravdiEmail author
Original Paper


Model-based analysis of cellular metabolism can facilitate our understanding of intracellular kinetics and aid the improvement of cell growth and biological product manufacturing. In this paper, a model-based kinetic study of cytosolic glucose metabolism for two industrially relevant cell lines, Saccharomyces cerevisiae and Chinese hamster ovary (CHO) cells, based on enzyme genetic presence and expression information is described. We have reconstructed the cytosolic glucose metabolism map for S. cerevisiae and CHO cells, containing 18 metabolites and 18 enzymes using information from the Kyoto Encyclopedia of Genes and Genomes (KEGG). Based on this map, we have developed a kinetic mathematical model for the pathways involved, considering regulation and/or inhibition by products or co-substrates. The values of the maximum rates of reactions (V max) were estimated based on kinetic parameter information and metabolic flux analysis results available in literature, and the resulting simulation results for steady-state metabolite concentrations are in good agreement with published experimental data. Finally, the model was used to analyse how the production of DHAP, an important intermediate in fine chemicals synthesis, could be increased using gene knockout.


Kinetic modelling Saccharomyces cerevisiae Chinese hamster ovary cells Genome-scale metabolic reconstruction Glucose metabolism 



Financial support from the Centre for Process Systems Engineering Industrial Consortium is gratefully acknowledged. Finally, CK would like to thank the Research Councils UK and Lonza Biologics plc for her fellowship.


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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Ning Chen
    • 1
  • Georgios C. Koumpouras
    • 2
    • 3
  • Karen M. Polizzi
    • 4
    • 5
  • Cleo Kontoravdi
    • 1
    Email author
  1. 1.Centre for Process Systems Engineering, Department of Chemical EngineeringImperial College LondonLondonUK
  2. 2.Process Systems EnterpriseLondonUK
  3. 3.Energy & Chemicals ConsultingLondonUK
  4. 4.Centre for Synthetic Biology and InnovationImperial College LondonLondonUK
  5. 5.Division of Molecular Biosciences, Department of Life SciencesImperial College LondonLondonUK

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