HILIC-UPLC-MS for Exploratory Urinary Metabolic Profiling in Toxicological Studies

详细信息    查看全文

• 作者：Konstantina Spagou ; Ian D. Wilson ; Perrine Masson ; Georgios Theodoridis ; Nikolaos Raikos ; Muireann Coen ; Elaine Holmes ; John C. Lindon ; Robert S. Plumb ; Jeremy K. Nicholson ; Elizabeth J. Want
• 刊名：Analytical Chemistry
• 出版年：2011
• 出版时间：January 1, 2011
• 年：2011
• 卷：83
• 期：1
• 页码：382-390
• 全文大小：464K
• 年卷期：v.83,no.1(January 1, 2011)
• ISSN：1520-6882

文摘

Hydrophilic interaction ultra performance liquid chromatography (HILIC-UPLC) permits the analysis of highly polar metabolites, providing complementary information to reversed-phase (RP) chromatography. HILIC-UPLC-TOF-MS was investigated for the global metabolic profiling of rat urine samples generated in an experimental hepatotoxicity study of galactosamine (galN) and the concomitant investigation of the protective effect of glycine. Within-run repeatability and stability over a large sample batch (>200 samples, 60 h run-time) was assessed through the repeat analysis of a quality control sample. Following system equilibration, excellent repeatability was observed in terms of retention time (CV < 1.7%), signal intensity (CV < 14%), and mass variability (<0.005 amu), providing a good measure of reproducibility. Classification of urinary metabolic profiles according to treatment was observed, with significant changes in specific metabolites after galN exposure, including increased urocanic acid, N-acetylglucosamine, and decreased 2-oxoglutarate. A novel finding from this HILIC-UPLC-MS approach was elevated urinary tyramine in galN-treated rats, reflecting disturbed amino acid metabolism. These results show HILIC-UPLC-MS to be a promising method for global metabolic profiling, demonstrating high within-run repeatability, even over an extended run time. Retention of polar endogenous analytes and xenobiotic metabolites was improved compared with RP studies, including galN, N-acetylglucosamine, oxoglutarate, and urocanic acid, enhancing metabolome coverage and potentially improving biomarker discovery.