A Protocol to Compare Methods for Untargeted Metabolomics.
A Protocol to Compare Methods for Untargeted Metabolomics.
复制标题
比较非靶向代谢组学方法的方案。
DOI：
10.1007/978-1-4939-8769-6_1
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Patti,GaryJ
中科院分区：
文献类型：
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作者：
Wang,Lingjue;Naser,FuadJ;Spalding,JonathanL;Patti,GaryJ
有数千种已发表的方法用于用液相色谱/质谱法（LC/MS）分析代谢物。虽然已经针对少数选定代谢物对许多方法进行了评价和优化，但很少基于全球代谢物覆盖率进行评估。因此，在进行非靶向代谢组学时，研究人员经常质疑提取技术、色谱分离和质谱仪的哪种组合最适合进行全局分析。方法比较是复杂的，因为在一个典型的非靶向代谢组学实验中，成千上万的LC/MS信号（所谓的特征）不能很容易地用现有的资源来识别。因此，区分由于代谢物覆盖率提高而增加信号数量的方法与由于污染和伪影而增加信号数量的方法具有挑战性。在这里，我们提出了识别协议，以消除后者从非目标代谢组学数据集，而不必确定代谢物的结构。该方案可用于比较或优化与非靶向代谢组学工作流程的任何步骤有关的方法（例如，萃取、色谱法、质谱仪、信息学软件等）。
There are thousands of published methods for profiling metabolites with liquid chromatography/mass spectrometry (LC/MS). While many have been evaluated and optimized for a small number of select metabolites, very few have been assessed on the basis of global metabolite coverage. Thus, when performing untargeted metabolomics, researchers often question which combination of extraction techniques, chromatographic separations, and mass spectrometers is best for global profiling. Method comparisons are complicated because thousands of LC/MS signals (so-called features) in a typical untargeted metabolomic experiment cannot be readily identified with current resources. It is therefore challenging to distinguish methods that increase signal number due to improved metabolite coverage from methods that increase signal number due to contamination and artifacts. Here, we present thecredentialingprotocol to remove the latter from untargeted metabolomic datasets without having to identify metabolite structures. This protocol can be used to compare or optimize methods pertaining to any step of the untargeted metabolomic workflow (e.g., extraction, chromatography, mass spectrometer, informatic software, etc.).