A metabolomics-based method for studying the effect of yfcC gene in Escherichia coli on metabolism

被引:21
作者
Wang, Xiyue [1 ]
Xie, Yuping [2 ]
Gao, Peng [1 ]
Zhang, Sufang [3 ]
Tan, Haidong [3 ]
Yang, Fengxu [2 ]
Lian, Rongwei [2 ]
Tian, Jing [2 ]
Xu, Guowang [1 ]
机构
[1] Chinese Acad Sci, Dalian Inst Chem Phys, CAS Key Lab Separat Sci Analyt Chem, Dalian 116023, Peoples R China
[2] Dalian Polytech Univ, Sch Bioengn, Dalian 116034, Peoples R China
[3] Chinese Acad Sci, Dalian Inst Chem Phys, Div Biotechnol, Dalian 116023, Peoples R China
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
Metabolomics; Gas chromatography-mass spectrometry; Escherichia coli; yfcC; Metabolic profiling; FUNCTIONAL GENOMICS; MASS-SPECTROMETRY; OPTIMIZATION; IMPACT; RECONSTRUCTION; ANNOTATION; EXTRACTION; PATHWAYS; SEQUENCE; GROWTH;
D O I
10.1016/j.ab.2014.01.018
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Metabolomics is a potent tool to assist in identifying the function of unknown genes through analysis of metabolite changes in the context of varied genetic backgrounds. However, the availability of a universal unbiased profiling analysis is still a big challenge. In this study, we report an optimized metabolic profiling method based on gas chromatography-mass spectrometry for Escherichia coli. It was found that physiological saline at -80 degrees C could ensure satisfied metabolic quenching with less metabolite leakage. A solution of methanol/water (21:79, v/v) was proved to be efficient for intracellular metabolite extraction. This method was applied to investigate the metabolome difference among wild-type E. coli, its yfcC deletion, and overexpression mutants. Statistical and bioinformatic analysis of the metabolic profiling data indicated that the expression of yfcC potentially affected the metabolism of glyoxylate shunt. This finding was further validated by real-time quantitative polymerase chain reactions showing that expression of aceA and aceB, the key genes in glyoxylate shunt, was upregulated by yfcC. This study exemplifies the robustness of the proposed metabolic profiling analysis strategy and its potential roles in investigating unknown gene functions in view of metabolome difference. (C) 2014 Elsevier Inc. All rights reserved.
引用
收藏
页码:48 / 55
页数:8
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