Optimization of a GC-MS metabolic fingerprint method and its application in characterizing engineered bacterial metabolic shift.
Optimization of a GC-MS metabolic fingerprint method and its application in characterizing engineered bacterial metabolic shift.
复制标题
DOI：
10.1002/jssc.200800727
复制
发表时间：
2009-07
影响因子：
3.1
通讯作者：
Jing Tian;P. Sang;P. Gao;Ruiyan Fu;Dawei Yang;Lei Zhang;Jing Zhou;Si Wu;Xin Lu;Y. Li;Guowang Xu
中科院分区：
文献类型：
--
作者：
Jing Tian;P. Sang;P. Gao;Ruiyan Fu;Dawei Yang;Lei Zhang;Jing Zhou;Si Wu;Xin Lu;Y. Li;Guowang Xu
Metabolomics influences many aspects of life sciences including microbiology. Here, we describe the systematic optimization of metabolic quenching and a sample derivatization method for GC-MS metabolic fingerprint analysis. Methanol, ethanol, acetone, and acetonitrile were selected to evaluate their metabolic quenching ability, and acetonitrile was regarded as the most efficient agent. The optimized derivatization conditions were determined by full factorial design considering temperature, solvent, and time as parameters. The best conditions were attained with N,O-bis(trimethylsiyl) trifluoroacetamide as derivatization agent and pyridine as solvent at 75 degrees C for 45 min. Method validation ascertained the optimized method to be robust. The above method was applied to metabolomic analysis of six different strains and it is proved that the metabolic trait of an engineered strain can be easily deduced by clustering analysis of metabolic fingerprints.
