A rapid and integrated pyramid screening method to classify and identify complex endogenous substances with UPLC/Q-TOF MS-based metabolomics. Issue 1 (2nd December 2014)

• Record Type: Journal Article
• Authors: Li, Yubo; Zhang, Zhenzhu; Hou, Zhiguo; Wang, Lei; Wu, Xin; Ju, Liang; Zhang, Xiuxiu; Zhang, Yanjun
• Is Part Of: RSC advances. Volume 5:Issue 1(2015)
• Page Start: 202
• Page End: 209
• Publication Date: 2014-12-02
• Subjects: Chemistry -- Periodicals; 540.5
• DOI: 10.1039/c4ra10719e
• Languages: English
• ISSNs: 2046-2069

Abstract

Abstract : Metabolomics plays a role in disease diagnosis, safe and efficacy of drug evaluation, and microbial research. Abstract : Metabolomics plays a role in disease diagnosis, safety and efficacy of drug evaluation, and microbial research. Liquid chromatography-mass spectrometry (MS) is the main analysis tool in metabolomics studies. Given the existence of many different categories of endogenous metabolites is isomers of one another, some problems on classification and identification have emerged. These problems result in high false-positive results, as well as a complex and time-consuming substance identification process. Accordingly, this study reviewed literature and retrieved databases to identify endogenous substances in the same category accompanied by a certain mass range (MR) and mass defect range (MDR), as well as an identical or similar fragmentation pattern in the mass spectrum [ i.e., characteristic and neutral loss (NL) fragments]. We conducted different MS/MS collision energies to analyze different categories of endogenous substances to discover and summarize their fragmentation patterns. We then used the MR and MDR of the parent ion, diagnostic fragments (together with their MDR), and NL as screening tools to establish a pyramid screening method (PSM) for the rapid classification and identification of metabolites. Finally, we compared the PSM with the conventional identification method through known compounds in the literature. PSM was found to solve the key problem in metabolomics to some extent, namely, the classification and identification of substances. This method also facilitated the further development of metabolomics and provides a new perspective on the screening and identification of target components in other complex samples.