Department of Medicine, Diabetes Center, Stable Isotope and Metabolomics Core Facility, Albert Einstein College of Medicine, Bronx, New York 10461, United States.
J Proteome Res. 2011 Apr 1;10(4):2104-12. doi: 10.1021/pr1011119. Epub 2011 Mar 7.
In this study, a tandem LC-MS (Waters Xevo TQ) MRM-based MS method was developed for rapid, broad profiling of hydrophilic metabolites from biological samples, in either positive or negative ion modes without the need for an ion pairing reagent, using a reversed-phase pentafluorophenylpropyl (PFPP) column. The developed method was successfully applied to analyze various biological samples from C57BL/6 mice, including urine, duodenum, liver, plasma, kidney, heart, and skeletal muscle. As result, a total 112 of hydrophilic metabolites were detected within 8 min of running time to obtain a metabolite profile of the biological samples. The analysis of this number of hydrophilic metabolites is significantly faster than previous studies. Classification separation for metabolites from different tissues was globally analyzed by PCA, PLS-DA and HCA biostatistical methods. Overall, most of the hydrophilic metabolites were found to have a "fingerprint" characteristic of tissue dependency. In general, a higher level of most metabolites was found in urine, duodenum, and kidney. Altogether, these results suggest that this method has potential application for targeted metabolomic analyzes of hydrophilic metabolites in a wide ranges of biological samples.
本研究建立了一种串联 LC-MS（Waters Xevo TQ）MRM 基于 MS 的方法，用于快速、广泛地分析生物样品中的亲水性代谢物，无需离子对试剂，可在正离子或负离子模式下进行，采用反相五氟苯基丙基（PFPP）柱。所建立的方法成功地应用于分析来自 C57BL/6 小鼠的各种生物样品，包括尿液、十二指肠、肝脏、血浆、肾脏、心脏和骨骼肌。结果，在 8 分钟的运行时间内检测到 112 种亲水性代谢物，以获得生物样品的代谢物图谱。与以前的研究相比，分析如此数量的亲水性代谢物的速度明显加快。通过 PCA、PLS-DA 和 HCA 生物统计方法对来自不同组织的代谢物进行全局分类分离。总体而言，大多数亲水性代谢物都具有组织依赖性的“指纹”特征。一般来说，尿液、十二指肠和肾脏中大多数代谢物的水平较高。总之，这些结果表明，该方法具有广泛应用于生物样品中亲水性代谢物靶向代谢组学分析的潜力。
