Systems biology approach for enhancing limonene yield by re-engineering Escherichia coli.

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Jasmeet Kaur Khanijou, Yan Ting Hee, Clement P M Scipion, Xixian Chen, Kumar Selvarajoo
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Abstract

Engineered microorganisms have emerged as viable alternatives for limonene production. However, issues such as low enzyme abundance or activities, and regulatory feedback/forward inhibition may reduce yields. To understand the underlying metabolism, we adopted a systems biology approach for an engineered limonene-producing Escherichia coli strain K-12 MG1655. Firstly, we generated time-series metabolomics data and, secondly, developed a dynamic model based on enzyme dynamics to track the native metabolic networks and the engineered mevalonate pathway. After several iterations of model fitting with experimental profiles, which also included 13C-tracer studies, we performed in silico knockouts (KOs) of all enzymes to identify bottleneck(s) for optimal limonene yields. The simulations indicated that ALDH/ADH (aldehyde dehydrogenase/alcohol dehydrogenase) and LDH (lactate dehydrogenase) suppression, and HK (hexokinase) enhancement would increase limonene yields. Experimental confirmation was achieved, where ALDH-ADH and LDH KOs, and HK overexpression improved limonene yield by 8- to 11-fold. Our systems biology approach can guide microbial strain re-engineering for optimal target production.

通过改造大肠杆菌提高柠檬烯产量的系统生物学方法。
工程微生物已成为生产柠檬烯的可行替代品。然而,酶丰度或活性低以及调控反馈/前向抑制等问题可能会降低产量。为了了解潜在的新陈代谢,我们采用了一种系统生物学方法来研究工程大肠杆菌 K-12 MG1655 的柠檬烯生产。首先,我们生成了时间序列代谢组学数据;其次,我们开发了一个基于酶动力学的动态模型,以跟踪原生代谢网络和工程甲羟戊酸途径。在对模型与实验曲线(包括 13C 示踪剂研究)进行多次迭代拟合之后,我们对所有酶进行了硅基因敲除(KO),以确定实现最佳柠檬烯产量的瓶颈。模拟结果表明,抑制 ALDH/ADH(醛脱氢酶/醇脱氢酶)和 LDH(乳酸脱氢酶)以及增强 HK(己糖激酶)可提高柠檬烯产量。实验证实,ALDH-ADH 和 LDH KOs 以及 HK 的过表达可使柠檬烯产量提高 8 到 11 倍。我们的系统生物学方法可以指导微生物菌株的再工程,以获得最佳的目标产量。
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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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