Integration of microbial kinetics and fluid dynamics toward model‐driven scale‐up of industrial bioprocesses
Integration of microbial kinetics and fluid dynamics toward model‐driven scale‐up of industrial bioprocesses
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DOI：
10.1002/elsc.201400172
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发表时间：
2015-01
影响因子：
2.7
通讯作者：
Guan Wang;Wenjun Tang;Jianye Xia;J. Chu;H. Noorman;W. M. Gulik
中科院分区：
文献类型：
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作者：
Guan Wang;Wenjun Tang;Jianye Xia;J. Chu;H. Noorman;W. M. Gulik
生物工艺的规模扩大受到开放性问题的阻碍，主要与混合不良和传质限制有关。由于发酵罐的混合时间通常长于相关细胞反应时间，因此可能会诱导底物、二氧化碳和氧气在时间和空间上的浓度梯度，尤其是在大规模高细胞密度补料分批工艺中。因此，发酵罐中的细胞反复暴露于动态环境或扰动。因此，与充分混合的小规模生物反应器相比，工业实践中的异质性通常会降低产量、滴度或生产率或其组合，并增加副产物的形成，这被总结为放大效应。确定微生物对各种外部扰动的响应机制对于确定代谢瓶颈和代谢工程的目标非常重要。在这篇综述中，脉冲响应实验被提出作为一种理想的方式来获得动力学信息结合规模缩小的方法，深入了解动态响应机制。作为一种新兴的工具，计算流体动力学能够绘制发酵罐中流体流动和浓度场的整体图像，并在发酵罐设计和工艺策略的优化中找到它的用途。在未来，定向菌株的改进和发酵罐的重新设计，预计将在很大程度上依赖于模型，其中微生物动力学和流体动力学是彻底整合。
Scale‐up of bioprocesses is hampered by open questions, mostly related to poor mixing and mass transfer limitations. Concentration gradients of substrate, carbon dioxide, and oxygen in time and space, especially in large‐scale high‐cell density fed‐batch processes, are likely induced as the mixing time of the fermentor is usually longer than the relevant cellular reaction time. Cells in the fermentor are therefore repeatedly exposed to dynamic environments or perturbations. As a consequence, the heterogeneity in industrial practices often decreases either yield, titer, or productivity, or combinations thereof and increases by‐product formation as compared to well‐mixed small‐scale bioreactors, which is summarized as scale‐up effects. Identification of response mechanisms of the microorganism to various external perturbations is of great importance for pinpointing metabolic bottlenecks and targets for metabolic engineering. In this review, pulse response experimentation is proposed as an ideal way of obtaining kinetic information in combination with scale‐down approaches for in‐depth understanding of dynamic response mechanisms. As an emerging tool, computational fluid dynamics is able to draw a holistic picture of the fluid flow and concentration fields in the fermentor and finds its use in the optimization of fermentor design and process strategy. In the future, directed strain improvement and fermentor redesign are expected to largely depend on models, in which both microbial kinetics and fluid dynamics are thoroughly integrated.