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Integration of microbial kinetics and fluid dynamics toward model-driven scale-up of industrial bioprocesses

机译:集成微生物动力学和流体动力学,以模型驱动的规模扩大工业生物过程

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摘要

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.
机译:尚未解决的问题阻碍了生物工艺的规模扩大,这主要与不良的混合和传质限制有关。由于发酵罐的混合时间通常长于相关的细胞反应时间,因此可能在时间和空间上引起底物,二氧化碳和氧气的浓度梯度,特别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中。结果,与充分混合的小型生物反应器相比,工业实践中的异质性通常会降低产量,效价或生产率或其组合,并增加副产物的形成,这被总结为放大效应。查明微生物对各种外部扰动的反应机制,对于查明代谢瓶颈和代谢工程的目标非常重要。在这篇综述中,提出了脉冲响应实验作为一种获取动力学信息的理想方法,并结合了按比例缩小的方法来深入了解动态响应机制。作为一种新兴工具,计算流体动力学能够对发酵罐中的流体流动和浓度场进行全面描绘,并发现其可用于优化发酵罐设计和工艺策略。将来,预期的定向应变改善和发酵罐的重新设计将在很大程度上取决于模型,在模型中,微生物动力学和流体动力学都得到了完全整合。

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