A 9-pool metabolic structured kinetic model describing days to seconds dynamics of growth and product formation by Penicillium chrysogenum.
A powerful approach for the optimization of industrial bioprocesses is to perform detailed simulations integrating large-scale computational fluid dynamics (CFD) and cellular reaction dynamics (CRD). However, complex metabolic kinetic models containing a large number of equations pose formidable challenges in CFD-CRD coupling and computation time afterward. This necessitates to formulate a relatively simple but yet representative model structure. Such a kinetic model should be able to reproduce metabolic responses for short-term (mixing time scale of tens of seconds) and long-term (fed-batch cultivation of hours/days) dynamics in industrial bioprocesses. In this paper, we used Penicillium chrysogenum as a model system and developed a metabolically structured kinetic model for growth and production. By lumping the most important intracellular metabolites in 5 pools and 4 intracellular enzyme pools, linked by 10 reactions, we succeeded in maintaining the model structure relatively simple, while providing informative insight into the state of the organism. The performance of this 9-pool model was validated with a periodic glucose feast-famine cycle experiment at the minute time scale. Comparison of this model and a reported black box model for this strain shows the necessity of employing a structured model under feast-famine conditions. This proposed model provides deeper insight into the in vivo kinetics and, most importantly, can be straightforwardly integrated into a computational fluid dynamic framework for simulating complete fermentation performance and cell population dynamics in large scale and small scale fermentors. Biotechnol. Bioeng. 2017;114: 1733-1743. © 2017 Wiley Periodicals, Inc.
State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, P.O. Box 329#, No.130, Meilong Road, Shanghai, P.R. China.
Wenjun
W
Tang
DSM Biotechnology Center, Delft, The Netherlands.
Amit T
AT
Deshmukh
Cell Systems Engineering, Department of Biotechnology, Delft University of Technology, Delft, The Netherlands.
Cees
C
Haringa
State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, P.O. Box 329#, No.130, Meilong Road, Shanghai, P.R. China.
Guan
0000-0003-2341-3054
G
Wang
Cell Systems Engineering, Department of Biotechnology, Delft University of Technology, Delft, The Netherlands.
Walter
W
van Gulik
DSM Biotechnology Center, Delft, The Netherlands.
Wouter
W
van Winden
Institute of Biochemical Engineering, University of Stuttgart, Stuttgart, Germany.
Matthias
M
Reuss
Cell Systems Engineering, Department of Biotechnology, Delft University of Technology, Delft, The Netherlands.
Joseph J
JJ
Heijnen
State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, P.O. Box 329#, No.130, Meilong Road, Shanghai, P.R. China.
Jianye
J
Xia
State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, P.O. Box 329#, No.130, Meilong Road, Shanghai, P.R. China.
Ju
0000-0002-6406-1748
J
Chu
DSM Biotechnology Center, Delft, The Netherlands.
Henk J
HJ
Noorman
D049109:Cell Proliferation / Q000502:physiology*; D003198:Computer Simulation; D005656:Fungal Proteins / Q000378:metabolism; D015971:Gene Expression Regulation, Enzymologic / Q000502:physiology; D015966:Gene Expression Regulation, Fungal / Q000502:physiology; D005947:Glucose / Q000378:metabolism*; D007700:Kinetics; D008657:Metabolic Clearance Rate / Q000502:physiology; D064688:Metabolic Flux Analysis / Q000379:methods*; D053858:Metabolic Networks and Pathways / Q000502:physiology*; D008954:Models, Biological; D009097:Multienzyme Complexes / Q000378:metabolism; D010408:Penicillium chrysogenum / Q000166:cytology / Q000502:physiology*; D013997:Time Factors
D005656:Fungal Proteins; D009097:Multienzyme Complexes; D005947:Glucose
Penicillium chrysogenum; black box model; feast-famine; kinetics; structured model