Nontargeted Modification-Specific Metabolomics Study Based on Liquid Chromatography–High-Resolution Mass Spectrometry

• Published in: Analytical chemistry (Washington) Vol. 86; no. 18; pp. 9146 - 9153
• Main Authors: Dai, Weidong, Yin, Peiyuan, Zeng, Zhongda, Kong, Hongwei, Tong, Hongwei, Xu, Zhiliang, Lu, Xin, Lehmann, Rainer, Xu, Guowang
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 16.09.2014
• Subjects: Adult; Area Under Curve; Biochemistry; Biology; Chromatography; Chromatography, High Pressure Liquid; Databases, Factual; Female; Fragments; Genes; Glucuronic Acid - chemistry; Glucuronic Acid - urine; Humans; Liquids; Liver Cirrhosis - metabolism; Liver Cirrhosis - pathology; Liver Function Tests; Male; Mass Spectrometry; Metabolites; Metabolome; Metabolomics; Middle Aged; Principal Component Analysis; Profiling; Proteins; Ribose - chemistry; Ribose - urine; ROC Curve; Strategy; Sulfuric Acids - chemistry; Sulfuric Acids - urine; Systematic biology; Urine; Xenobiotics - metabolism
• ISSN: 0003-2700; 1520-6882
• DOI: 10.1021/ac502045j

Modifications of genes and proteins have been extensively studied in systems biology using comprehensive analytical strategies. Although metabolites are frequently modified, these modifications have not been studied using -omics approaches. Here a general strategy for the nontargeted profiling of modified metabolites, which we call “nontargeted modification-specific metabolomics”, is reported. A key aspect of this strategy was the combination of in-source collision-induced dissociation liquid chromatography–mass spectrometry (LC-MS) and global nontargeted LC-MS-based metabolomics. Characteristic neutral loss fragments that are specific for acetylation, sulfation, glucuronidation, glucosidation, or ribose conjugation were reproducibly detected using human urine as a model specimen for method development. The practical application of this method was demonstrated by profiling urine samples from liver cirrhosis patients. Approximately 900 features were identified as modified endogenous metabolites and xenobiotics. Moreover, this strategy supports the identification of compounds not included in traditional metabolomics databases (HMDB, Metlin, and KEGG), which are currently referred to as “unknowns” in metabolomics projects. Nontargeted modification-specific metabolomics opens a new perspective in systems biology.