| Literature DB >> 28322433 |
Wenjun Tang1, Amit T Deshmukh2, Cees Haringa3, Guan Wang1, Walter van Gulik3, Wouter van Winden2, Matthias Reuss4, Joseph J Heijnen3, Jianye Xia1, Ju Chu1, Henk J Noorman2.
Abstract
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.Entities:
Keywords: Penicillium chrysogenum; black box model; feast-famine; kinetics; structured model
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Year: 2017 PMID: 28322433 DOI: 10.1002/bit.26294
Source DB: PubMed Journal: Biotechnol Bioeng ISSN: 0006-3592 Impact factor: 4.530