Applications of stable isotope‐based metabolomics and fluxomics toward synthetic biology of cyanobacteria

代谢组学 蓝藻 代谢通量分析 合成生物学 代谢工程 系统生物学 代谢网络 生化工程 生物 光合作用 代谢途径 计算生物学 新陈代谢 生物化学 生物信息学 细菌 工程类 遗传学
作者
Piyoosh Kumar Babele,Jamey D. Young
出处
期刊:Wiley Interdisciplinary Reviews: Systems Biology and Medicine [Wiley]
卷期号:12 (3) 被引量:27
标识
DOI:10.1002/wsbm.1472
摘要

Abstract Unique features of cyanobacteria (e.g., photosynthesis and nitrogen fixation) make them potential candidates for production of biofuels and other value‐added biochemicals. As prokaryotes, they can be readily engineered using synthetic and systems biology tools. Metabolic engineering of cyanobacteria for the synthesis of desired compounds requires in‐depth knowledge of central carbon and nitrogen metabolism, pathway fluxes, and their regulation. Metabolomics and fluxomics offer the comprehensive analysis of metabolism by directly characterizing the biochemical activities of cells. This information is acquired by measuring the abundance of key metabolites and their rates of interconversion, which can be achieved by labeling cells with stable isotopes, quantifying metabolite pool sizes and isotope incorporation by gas chromatography/liquid chromatography‐mass spectrometry GC/LC‐MS or nuclear magnetic resonance (NMR), and mathematical modeling to estimate in vivo metabolic fluxes. Herein, we review progress that has been made to adapt metabolomics and fluxomics tools to examine model cyanobacterial species. We summarize the application of metabolic flux analysis (MFA) strategies to identify metabolic bottlenecks that can be targeted to boost cell growth, improve stress tolerance, or enhance biochemical production in cyanobacteria. Despite the advances in metabolomics, fluxomics, and other synthetic and systems biology tools during the past years, further efforts are required to increase our understanding of cyanobacterial metabolism in order to create efficient photosynthetic hosts for the production of value‐added compounds. This article is categorized under: Laboratory Methods and Technologies > Metabolomics Biological Mechanisms > Metabolism Analytical and Computational Methods > Analytical Methods
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