Anal. Chem. 2011, 83, 382–390
HILIC-UPLC-MS for Exploratory Urinary Metabolic Profiling in Toxicological Studies Konstantina Spagou,†,| Ian D. Wilson,‡ Perrine Masson,† Georgios Theodoridis,§ Nikolaos Raikos,| Muireann Coen,† Elaine Holmes,† John C. Lindon,† Robert S. Plumb,⊥ Jeremy K. Nicholson,† and Elizabeth J. Want*,† Biomolecular Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, U.K., Department of Clinical Pharmacology, Drug Metabolism and Pharmacokinetics, AstraZeneca, Mereside, Alderley Park, Macclesfield, Cheshire SK10 4TG, U.K., Department of Chemistry and Laboratory of Forensic Medicine and Toxicology, Faculty of Medicine, Aristotle University of Thessaloniki, Thessaloniki 54124 Greece, and Waters Corporation, 34 Maple Street, Milford, Massachusetts 01757, United States Hydrophilic interaction ultra performance liquid chromatography (HILIC-UPLC) permits the analysis of highly polar metabolites, providing complementary information to reversed-phase (RP) chromatography. HILIC-UPLCTOF-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. Withinrun 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 (200) over an extended analysis time (60 h). We injected 10 QCconditioning samples prior to the analysis of both the ESI+ and ESI- mode batches. To investigate the reproducibility of peak retention times and detector response (peak intensities), QC samples were injected after every ten study samples throughout the experiment. Principal Components Analysis (PCA) of QC Samples. Prior to any in-depth examination of the data for discriminatory markers between treatment groups, data quality was examined in terms of reproducibility. Clustering of QC samples was assessed using PCA to reveal if platform stability had been achieved. A PCA scores plot (PC1 vs PC2) of all study urine and QC samples analyzed in ESI+ mode within the analytical run is shown in Figure 1A. The QC samples are tightly clustered, indicating good reproducibility of the data. From this initial analysis, we are able to assume that differences between study urine samples primarily reflect biological variation rather than analytical variation. An additional insight into trends and drifts within the whole analytical run is shown in Figure 1C, which depicts the first component t[1] versus the samples, with the 2 and 3 standard deviation (SD) limits of peak height intensities. QC and study samples are plotted in run order, and show little variation throughout the whole analytical run. PCA was also performed on the 30 QC samples separately (10 conditioning QCs and 20 QCs within the run) and the time series dependency of the first component examined, showing a better view of QC sample behavior within the run (Figure S2, Supporting Information) and providing confidence for the quality of the data obtained, especially for a run of 60 h (>200 injections). ESI- mode data were processed similarly, and the PCA scores plot again showed the analytical variation within the run to be less important than the biological variation of the urine samples, Figure 1B, D. Univariate Assessment of Chromatographic and Spectrometric Reproducibility. The behavior of selected urinary metabolites was assessed using a univariate approach. Metabolites were identified by comparison with authentic standards and confirmed through MS/MS analysis (Table 1). Retention time repeatability of these metabolites was examined for the whole QC data set. These metabolites covered the retention time (RT) range of 0.6-7 min and the coefficient of variation (CV) values for RT were
