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代谢分析

Metabolic analysis.

作者信息

Tolstikov Vladimir V

机构信息

University of California Davis Genome Center, Davis, CA, USA.

出版信息

Methods Mol Biol. 2009;544:343-53. doi: 10.1007/978-1-59745-483-4_22.

Abstract

Analysis of the metabolome with coverage of all of the possibly detectable components in the sample, rather than analysis of each individual metabolite at a given time, can be accomplished by metabolic analysis. Targeted and/or nontargeted approaches are applied as needed for particular experiments. Monitoring hundreds or more metabolites at a given time requires high-throughput and high-end techniques that enable screening for relative changes in, rather than absolute concentrations of, compounds within a wide dynamic range. Most of the analytical techniques useful for these purposes use GC or HPLC/UPLC separation modules coupled to a fast and accurate mass spectrometer. GC separations require chemical modification (derivatization) before analysis, and work efficiently for the small molecules. HPLC separations are better suited for the analysis of labile and nonvolatile polar and nonpolar compounds in their native form. Direct infusion and NMR-based techniques are mostly used for fingerprinting and snap phenotyping, where applicable. Discovery and validation of metabolic biomarkers are exciting and promising opportunities offered by metabolic analysis applied to biological and biomedical experiments. We have demonstrated that GC-TOF-MS, HPLC/UPLC-RP-MS and HILIC-LC-MS techniques used for metabolic analysis offer sufficient metabolome mapping providing researchers with confident data for subsequent multivariate analysis and data mining.

摘要

代谢组分析可涵盖样品中所有可能检测到的成分,而非在给定时间对每种单独的代谢物进行分析,这可通过代谢分析来实现。针对特定实验,根据需要采用靶向和/或非靶向方法。在给定时间监测数百种或更多代谢物需要高通量和高端技术,以便在宽动态范围内筛选化合物的相对变化而非绝对浓度。大多数适用于这些目的的分析技术使用与快速准确的质谱仪联用的气相色谱(GC)或高效液相色谱/超高效液相色谱(HPLC/UPLC)分离模块。GC分离在分析前需要进行化学修饰(衍生化),对小分子分析效果良好。HPLC分离更适合分析天然形式的不稳定和非挥发性极性及非极性化合物。直接进样和基于核磁共振(NMR)的技术主要用于指纹图谱分析和快速表型分析(如适用)。代谢生物标志物的发现和验证是代谢分析应用于生物学和生物医学实验所提供的令人兴奋且充满前景的机会。我们已经证明,用于代谢分析的GC-TOF-MS、HPLC/UPLC-RP-MS和HILIC-LC-MS技术可提供足够的代谢组图谱,为研究人员提供可靠数据用于后续的多变量分析和数据挖掘。

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