Experimental and computational optimization of an Escherichia coli co-culture for the efficient production of flavonoids
Experimental and computational optimization of an Escherichia coli co-culture for the efficient production of flavonoids
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DOI：
10.1016/j.ymben.2016.01.006
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发表时间：
2016-05-01
影响因子：
8.4
通讯作者：
Koffas, Mattheos A. G.
中科院分区：
文献类型：
--
作者：
Jones, J. Andrew;Vernacchio, Victoria R.;Koffas, Mattheos A. G.
代谢工程和合成生物学使微生物生产平台能够用于许多高价值天然产品的可再生生产。然而，滴度和产量往往太低，无法产生商业上可行的工艺。微生物共培养有能力分配代谢负担，并允许模块化的特定优化的方式，是不可能通过传统的单一培养发酵方法。在这里，我们提出了一种大肠杆菌共培养，用于体内黄酮类化合物的高效生产，结果黄酮类化合物-3-醇的滴度比以前发表的单一培养产品提高了970倍。为了实现滴度的提高，对菌株相容性、碳源、温度、诱导点、接种比等因素进行了初步优化。在初始优化数据的基础上，建立了经验比例高斯模型来预测系统的最优点。模型预测的实验验证导致滴度提高65%，达到40.7 +/- 0.1 mg/L黄烷-3-醇，比之前的最佳值。总的来说，本研究首次应用了共培养生产黄酮类化合物，是迄今为止最深入的共培养优化，也是第一次应用经验系统建模来提高共培养系统的滴度。(C) 2016国际代谢工程学会。Elsevier Inc.出版。版权所有。
Metabolic engineering and synthetic biology have enabled the use of microbial production platforms for the renewable production of many high-value natural products. Titers and yields, however, are often too low to result in commercially viable processes. Microbial co-cultures have the ability to distribute metabolic burden and allow for modular specific optimization in a way that is not possible through traditional monoculture fermentation methods. Here, we present an Escherichia coli co-culture for the efficient production of flavonoids in vivo, resulting in a 970-fold improvement in titer of flavan-3-ols over previously published monoculture production. To accomplish this improvement in titer, factors such as strain compatibility, carbon source, temperature, induction point, and inoculation ratio were initially optimized. The development of an empirical scaled-Gaussian model based on the initial optimization data was then implemented to predict the optimum point for the system. Experimental verification of the model predictions resulted in a 65% improvement in titer, to 40.7 +/- 0.1 mg/L flavan-3-ols, over the previous optimum. Overall, this study demonstrates the first application of the co-culture production of flavonoids, the most in-depth co-culture optimization to date, and the first application of empirical systems modeling for improvement of titers from a co-culture system. (C) 2016 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.