Solid-Phase Extraction and Nanoflow Liquid Chromatography-Nanoelectrospray Ionization Mass Spectrometry for Improved Global Urine Metabolomics
Year: 2014
Type: article
Abstract: Global urine metabolomics is a rapidly expanding field with the potential to discover biomarkers of disease and exposure. To date, most methods focus on rapid sample preparation, using neat or diluted urine, together with high-throughput analyses, and are poorly suited for detection of low abundance metabolites present in urine samples. In this study, novel methods have been developed to analyze urine by splitless nanoflowUHPLC-nanoESI-TOFMS (nUHPLC-nESI-TOFMS) after preconcentration by solid-phase extraction (SPE), thus enabling significant improvements in analytical sensitivity and coverage of the urinary metabolome. In initial work, urine samples were extracted by both anion and cation exchange mixed-mode polymeric SPE cartridges and qualitatively compared with those using conventional sample preparations using UHPLC-ESI-TOFMS analyses. Compared with neat or diluted urine samples, SPE concentration of urine resulted in detection of additional metabolites including bile acids, lipids, pharmaceuticals, and markers of lifestyle, with little loss of other components of the metabolome. Analyses of SPE preparations by nUHPLC-nESI-TOFMS revealed excellent retention time repeatability with <1% coefficient of variation (CV) for 96% of analyzed peaks. The repeatability of the MS response was <30% CV for >79% of MS features in both negative and positive nESI modes. Compared with UHPLC-ESI-TOFMS, analysis by the nanoplatform enabled detection of signaling molecules important in disease processes including sex steroids, glucocorticoids, eicosanoids, and neurotransmitter metabolites. The significant improvement in sensitivity arising from use of splitless nUHPLC-nESI-TOFMS analyses of SPE-concentrated samples represents a step change in coverage of the urinary metabolome, thereby increasing the potential for biomarker discovery.
Source: Analytical Chemistry
DOI: 10.1021/ac503769q
Institution: University of Sussex
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Award: G6393195472
OpenAlex ID: W2017945415
