Want Elizabeth J, O'Maille Grace, Smith Colin A, Brandon Theodore R, Uritboonthai Wilasinee, Qin Chuan, Trauger Sunia A, Siuzdak Gary
Department of Molecular Biology, The Scripps Research Institute, La Jolla, California 92037, USA.
Anal Chem. 2006 Feb 1;78(3):743-52. doi: 10.1021/ac051312t.
The aim of metabolite profiling is to monitor all metabolites within a biological sample for applications in basic biochemical research as well as pharmacokinetic studies and biomarker discovery. Here, novel data analysis software, XCMS, was used to monitor all metabolite features detected from an array of serum extraction methods, with application to metabolite profiling using electrospray liquid chromatography/mass spectrometry (ESI-LC/MS). The XCMS software enabled the comparison of methods with regard to reproducibility, the number and type of metabolite features detected, and the similarity of these features between different extraction methods. Extraction efficiency with regard to metabolite feature hydrophobicity was examined through the generation of unique feature density distribution plots, displaying feature distribution along chromatographic time. Hierarchical clustering was performed to highlight similarities in the metabolite features observed between the extraction methods. Protein extraction efficiency was determined using the Bradford assay, and the residual proteins were identified using nano-LC/MS/MS. Additionally, the identification of four of the most intensely ionized serum metabolites using FTMS and tandem mass spectrometry was reported. The extraction methods, ranging from organic solvents and acids to heat denaturation, varied widely in both protein removal efficiency and the number of mass spectral features detected. Methanol protein precipitation followed by centrifugation was found to be the most effective, straightforward, and reproducible approach, resulting in serum extracts containing over 2000 detected metabolite features and less than 2% residual protein. Interestingly, the combination of all approaches produced over 10,000 unique metabolite features, a number that is indicative of the complexity of the human metabolome and the potential of metabolomics in biomarker discovery.
代谢物谱分析的目的是监测生物样品中的所有代谢物，以应用于基础生化研究、药代动力学研究和生物标志物发现。在此，使用了新型数据分析软件XCMS来监测从一系列血清提取方法中检测到的所有代谢物特征，并将其应用于电喷雾液相色谱/质谱（ESI-LC/MS）的代谢物谱分析。XCMS软件能够在重现性、检测到的代谢物特征的数量和类型以及不同提取方法之间这些特征的相似性方面对方法进行比较。通过生成独特的特征密度分布图来检查代谢物特征疏水性方面的提取效率，该图显示了沿色谱时间的特征分布。进行层次聚类以突出提取方法之间观察到的代谢物特征的相似性。使用Bradford法测定蛋白质提取效率，并使用纳升液相色谱/串联质谱法鉴定残留蛋白质。此外，还报告了使用傅里叶变换质谱（FTMS）和串联质谱法对四种电离程度最高的血清代谢物的鉴定。从有机溶剂、酸到热变性的提取方法在蛋白质去除效率和检测到的质谱特征数量方面差异很大。发现甲醇蛋白质沉淀后离心是最有效、最直接且可重现的方法，得到的血清提取物含有超过2000个检测到的代谢物特征且残留蛋白质少于2%。有趣的是，所有方法的组合产生了超过10000个独特的代谢物特征，这一数字表明了人类代谢组的复杂性以及代谢组学在生物标志物发现中的潜力。
