混合培养中吲哚最优产量的动态优化

Ranjana Singh, Surbhi Sharma, L. Giri, K. Mitra
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引用次数: 0

摘要

当大肠杆菌K12与枯草芽孢杆菌168在长时间的混合培养中受到胁迫时,产生吲哚。由于吲哚的治疗用途,混合培养过程的数学模型奠定了生长的基础,并提供了最佳的操作条件,可以证明对工业中吲哚的大规模生产非常有用。本实验研究了在最小培养基中对大肠杆菌和枯草芽孢杆菌进行长时间混合培养的效果。以葡萄糖为底物,对混合培养前后细菌的个体生长情况进行实验研究,分析相互作用的影响。采用了一种基于混合优化技术的混合培养最优非结构化模型辨识的计算策略。为了模拟混合培养,采用了长时间传代动力学实验动态优化技术,可用于寻找最佳操作条件。这项工作代表了混合和动态优化技术应用于混合培养的非结构化建模和优化的第一个实例,作为工业规模和药物发现的吲哚优化生产的新框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic optimization for Optimal production of Indole in a mixed culture
Indole is produced when Escherichia Coli K12 is subjected to stress in a long duration mixed culture with Bacillus subtilis 168. Due to the therapeutic uses of Indole, a mathematical model of the mixed culture process underlying the growth and providing the optimal operating condition could prove immensely useful for the large scale production of Indole in industries. In this work, an experimental study has been conducted to study the long duration mixed culture effect on Escherichia Coli and Bacillus Subtilis in minimal media. Experimental investigation of individual growth profile of both the bacteria before and after the mixed culture is also conducted with glucose as substrate to analyze the effect of interaction. A computational strategy for identification of optimal unstructured model for mixed culture using hybrid optimization technique has been adopted. For modelling the mixed culture, dynamics of long duration passage experiment dynamic optimization technique has been implemented, which can be used to find optimal operating conditions. This work represents the first instance, where hybrid and dynamic optimization techniques have been applied for unstructured modeling and optimization of mixed culture, acting as a novel framework for optimal production of Indole at industrial scale and drug discovery.
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