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Abstract
The analysis of metabolic pathways for dysfunction has been used for many years in the scientific and medical community to determine overall health. Metabonomics (metabolomics), the global profiling of metabolites, has experienced a rekindling of interest due, in part, to advances in analytical instrumentation for conducting measurements and informatics available for interpretation of the data acquired in this area of biomedical research. Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) based approaches are two primary analytical methods of choice for conducting metabonomic measurements. To overcome the complexity and wide dynamic range of concentrations of metabolites present in biological samples, a common practice is to couple online an analytical separation, typically high performance liquid chromatography (HPLC), with the mass spectrometer. Hence, of critical importance are not only the MS acquisition parameters, but also optimization of those variables that impact the analytical HPLC separation as well. A systematic investigation of a number of variables related to HPLC, such as mobile phase composition and flow rate, gradient time, column dimensions, and packing material properties has been conducted. The results of this study show that 10 cm long×1 mm inner diameter (i.d.), C18 reversed‐phase columns provide higher resolution than C8 or C4 columns for the analysis of urine samples. The results also show that longer columns and extended mobile phase gradients allowed detection of a greater number of metabolites. As expected, MS analysis of the same urine sample using positive and negative ionization modes resulted in detection of a different ensemble of metabolites. Though prior dilution of rat and mouse urine is a common practice in conducting HPLC‐MS metabonomic analyses, our results suggest that a greater number of species may be observed using undiluted urine. The matrix (composition) of urine collected from different individuals affected the reproducibility of retention times. The variability in metabolite retention times using internal standards, although improved, was not completely corrected.
Acknowledgments
We would like to thank Dr. Xia Xu and Mr. John Roman for supplying the dansylated internal standards used in this study. This project has been funded in whole, or in part, with federal funds from the National Cancer Institute, National Institutes of Health, under contract N01‐CO‐12400. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.