Development of High-Performance Chemical Isotope Labeling LC鈥揗S for Profiling the Human Fecal Metabolome

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• 作者：Wei Xu ; Deying Chen ; Nan Wang ; Ting Zhang ; Ruokun Zhou ; Tao Huan ; Yingfeng Lu ; Xiaoling Su ; Qing Xie ; Liang Li ; Lanjuan Li
• 刊名：Analytical Chemistry
• 出版年：2015
• 出版时间：January 20, 2015
• 年：2015
• 卷：87
• 期：2
• 页码：829-836
• 全文大小：429K
• ISSN：1520-6882

文摘

Human fecal samples contain endogenous human metabolites, gut microbiota metabolites, and other compounds. Profiling the fecal metabolome can produce metabolic information that may be used not only for disease biomarker discovery, but also for providing an insight about the relationship of the gut microbiome and human health. In this work, we report a chemical isotope labeling liquid chromatography鈥搈ass spectrometry (LC鈥揗S) method for comprehensive and quantitative analysis of the amine- and phenol-containing metabolites in fecal samples. Differential ¹³C₂/¹²C₂-dansyl labeling of the amines and phenols was used to improve LC separation efficiency and MS detection sensitivity. Water, methanol, and acetonitrile were examined as an extraction solvent, and a sequential water鈥揳cetonitrile extraction method was found to be optimal. A step-gradient LC鈥揢V setup and a fast LC鈥揗S method were evaluated for measuring the total concentration of dansyl labeled metabolites that could be used for normalizing the sample amounts of individual samples for quantitative metabolomics. Knowing the total concentration was also useful for optimizing the sample injection amount into LC鈥揗S to maximize the number of metabolites detectable while avoiding sample overloading. For the first time, dansylation isotope labeling LC鈥揗S was performed in a simple time-of-flight mass spectrometer, instead of high-end equipment, demonstrating the feasibility of using a low-cost instrument for chemical isotope labeling metabolomics. The developed method was applied for profiling the amine/phenol submetabolome of fecal samples collected from three families. An average of 1785 peak pairs or putative metabolites were found from a 30 min LC鈥揗S run. From 243 LC鈥揗S runs of all the fecal samples, a total of 6200 peak pairs were detected. Among them, 67 could be positively identified based on the mass and retention time match to a dansyl standard library, while 581 and 3197 peak pairs could be putatively identified based on mass match using MyCompoundID against a Human Metabolome Database and an Evidence-based Metabolome Library, respectively. This represents the most comprehensive profile of the amine/phenol submetabolome ever detected in human fecal samples. The quantitative metabolome profiles of individual samples were shown to be useful to separate different groups of samples, illustrating the possibility of using this method for fecal metabolomics studies.