Literature DB >> 28322433

A 9-pool metabolic structured kinetic model describing days to seconds dynamics of growth and product formation by Penicillium chrysogenum.

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.
© 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  Penicillium chrysogenum; black box model; feast-famine; kinetics; structured model

Mesh:

Substances:

Year:  2017        PMID: 28322433     DOI: 10.1002/bit.26294

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  6 in total

1.  Euler-Lagrangian Simulations: A Proper Tool for Predicting Cellular Performance in Industrial Scale Bioreactors.

Authors:  Christopher Sarkizi Shams Hajian; Julia Zieringer; Ralf Takors
Journal:  Adv Biochem Eng Biotechnol       Date:  2021       Impact factor: 2.635

2.  Bioprocess scale-up/down as integrative enabling technology: from fluid mechanics to systems biology and beyond.

Authors:  Frank Delvigne; Ralf Takors; Rob Mudde; Walter van Gulik; Henk Noorman
Journal:  Microb Biotechnol       Date:  2017-08-14       Impact factor: 5.813

3.  Stochastic parcel tracking in an Euler-Lagrange compartment model for fast simulation of fermentation processes.

Authors:  Cees Haringa; Wenjun Tang; Henk J Noorman
Journal:  Biotechnol Bioeng       Date:  2022-04-11       Impact factor: 4.395

4.  Integrating a dynamic central metabolism model of cancer cells with a hybrid 3D multiscale model for vascular hepatocellular carcinoma growth.

Authors:  Alexey Lapin; Holger Perfahl; Harsh Vardhan Jain; Matthias Reuss
Journal:  Sci Rep       Date:  2022-07-20       Impact factor: 4.996

5.  Comparative performance of different scale-down simulators of substrate gradients in Penicillium chrysogenum cultures: the need of a biological systems response analysis.

Authors:  Guan Wang; Junfei Zhao; Cees Haringa; Wenjun Tang; Jianye Xia; Ju Chu; Yingping Zhuang; Siliang Zhang; Amit T Deshmukh; Walter van Gulik; Joseph J Heijnen; Henk J Noorman
Journal:  Microb Biotechnol       Date:  2018-01-15       Impact factor: 5.813

Review 6.  In Silico Prediction of Large-Scale Microbial Production Performance: Constraints for Getting Proper Data-Driven Models.

Authors:  Julia Zieringer; Ralf Takors
Journal:  Comput Struct Biotechnol J       Date:  2018-07-06       Impact factor: 7.271

  6 in total

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