非模式细菌的综合多维建模确定了阿卡波糖生物合成优化的工程靶点。

IF 4.5 Q1 BIOCHEMICAL RESEARCH METHODS
Feifei Cai, Shijie Zhang, Yang Dai, Ziqi Zhao, Xinnan Fu, Qianjin Kang, Yongyong Shi, Zhuo Wang, Linquan Bai
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引用次数: 0

摘要

高价值化合物如阿卡波糖(一种糖尿病药物)的代谢工程需要对代谢调节有系统的了解。在这里,我们应用了多维系统生物学方法对非模式产糖细菌Actinoplanes sp. SE50/110进行研究。我们重建了一个改进的基因组尺度代谢模型(iASE1267),其代谢覆盖范围扩大,MEMOTE评分为80%,能够更准确地预测表型。利用双目标OptRAM菌株设计策略,我们确定了两组静态工程靶点,包括AcbR过表达和腺苷琥珀酸裂解酶抑制,以及dtdp -葡萄糖4,6-脱水酶过表达和4-(胞苷5'-二磷酸)-2-甲基-d -赤藓糖醇激酶抑制。时间过程代谢模型进一步揭示了动态代谢阀——aspo1、PC和pyk控制通量再分布。整合这些靶点,我们重建了一个核心转录代谢网络,并鉴定了两个多效性负转录因子(TFs)。这些tf和代谢基因的实验验证使阿卡波糖滴度提高了18%-23%。这项工作建立了一个将静态/动态代谢建模与转录网络相结合的框架,用于工程非模式微生物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrated multi-dimensional modeling of non-model bacteria identifies engineering targets for acarbose biosynthesis optimization.

Metabolic engineering for high-value compounds such as acarbose, a diabetes drug, requires systematic understanding of metabolic regulation. Here, we applied a multi-dimensional systems biology approach in Actinoplanes sp. SE50/110, a non-model acarbose-producing bacterium. We reconstructed an improved genome-scale metabolic model (iASE1267) with expanded metabolic coverage and a MEMOTE score of 80%, enabling more accurate phenotype predictions. Using a dual-objective OptRAM strain design strategy, we identified two sets of static engineering targets, including AcbR overexpression with adenylosuccinate lyase repression, and overexpression of dTDP-glucose 4,6-dehydratase with repression of 4-(cytidine 5'-diphospho)-2-methyl-D-erythritol kinase. Time-course metabolic modeling further revealed dynamic metabolic valves-ASPO1, PC, and PYK-governing flux redistribution. Integrating these targets, we reconstructed a core transcription-metabolism network and identified two pleiotropic negative transcription factors (TFs). Experimental validation of these TFs and metabolic genes increased acarbose titers by 18%-23%. This work establishes a framework integrating static/dynamic metabolic modeling with transcriptional networks for engineering non-model microbes.

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来源期刊
Cell Reports Methods
Cell Reports Methods Chemistry (General), Biochemistry, Genetics and Molecular Biology (General), Immunology and Microbiology (General)
CiteScore
3.80
自引率
0.00%
发文量
0
审稿时长
111 days
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