A 9‐pool metabolic structured kinetic model describing days to seconds dynamics of growth and product formation by Penicillium chrysogenum
A 9‐pool metabolic structured kinetic model describing days to seconds dynamics of growth and product formation by Penicillium chrysogenum
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DOI：
10.1002/bit.26294
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发表时间：
2017-08
影响因子：
3.8
通讯作者：
Wenjun Tang;A. Deshmukh;C. Haringa;Guan Wang;W. V. van Gulik;W. V. van Winden;M. Reuss;J. Heijnen-J.-Heij
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文献类型：
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作者：
Wenjun Tang;A. Deshmukh;C. Haringa;Guan Wang;W. V. van Gulik;W. V. van Winden;M. Reuss;J. Heijnen-J.-Heij
集成大规模计算流体动力学（CFD）和细胞反应动力学（CRD）的详细模拟是工业生物过程优化的一个有力方法。然而，包含大量方程的复杂代谢动力学模型给CFD - CRD耦合和计算时间带来了巨大的挑战。这就需要制定一个相对简单但具有代表性的模型结构。这样的动力学模型应该能够在工业生物过程中再现短期（混合时间尺度为数十秒）和长期（饲养批量培养数小时/天）的代谢反应动态。本文以青霉菌为模型系统，建立了其生长和生产的代谢结构动力学模型。通过将最重要的细胞内代谢物集中在5个池和4个细胞内酶池中，通过10个反应连接，我们成功地保持了模型结构相对简单，同时提供了对生物体状态的信息洞察力。该9池模型的性能在分钟时间尺度上通过葡萄糖盛宴-饥荒周期实验进行了验证。将该模型与已报道的该菌株的黑箱模型进行比较，表明在饥-缺条件下采用结构化模型的必要性。该模型提供了对体内动力学的更深入的了解，最重要的是，可以直接集成到计算流体动力学框架中，用于模拟大型和小型发酵罐的完全发酵性能和细胞种群动力学。Biotechnol。Bioeng。2017;114: 1733 - 1743。©2017 Wiley期刊公司
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.