代谢组学
重复性
质谱法
色谱法
化学
协议(科学)
液相色谱-质谱法
选择性反应监测
生物标志物发现
三级四极质谱仪
计算生物学
串联质谱法
生物
蛋白质组学
生物化学
病理
基因
医学
替代医学
作者
Fujian Zheng,Xinjie Zhao,Zhongda Zeng,Lichao Wang,Wangjie Lv,Qingqing Wang,Guowang Xu
出处
期刊:Nature Protocols
[Springer Nature]
日期:2020-06-24
卷期号:15 (8): 2519-2537
被引量:159
标识
DOI:10.1038/s41596-020-0341-5
摘要
Untargeted methods are typically used in the detection and discovery of small organic compounds in metabolomics research, and ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) is one of the most commonly used platforms for untargeted metabolomics. Although they are non-biased and have high coverage, untargeted approaches suffer from unsatisfying repeatability and a requirement for complex data processing. Targeted metabolomics based on triple-quadrupole mass spectrometry (TQMS) could be a complementary tool because of its high sensitivity, high specificity and excellent quantification ability. However, it is usually applicable to known compounds: compounds whose identities are known and/or are expected to be present in the analyzed samples. Pseudotargeted metabolomics merges the advantages of untargeted and targeted metabolomics and can act as an alternative to the untargeted method. Here, we describe a detailed protocol of pseudotargeted metabolomics using UHPLC-TQMS. An in-depth, untargeted metabolomics experiment involving multiple UHPLC-HRMS runs with MS at different collision energies (both positive and negative) is performed using a mixture obtained using small amounts of the analyzed samples. XCMS, CAMERA and Multiple Reaction Monitoring (MRM)-Ion Pair Finder are used to find and annotate peaks and choose transitions that will be used to analyze the real samples. A set of internal standards is used to correct for variations in retention time. High coverage and high-performance quantitative analysis can be realized. The entire protocol takes ~5 d to complete and enables the simultaneously semiquantitative analysis of 800-1,300 metabolites.
科研通智能强力驱动
Strongly Powered by AbleSci AI