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Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS
Published on: May 20, 2013
Development of a metabolomic approach based on urine samples and direct infusion mass spectrometry
Raúl González-Domínguez1, Rocío Castilla-Quintero1, Tamara García-Barrera1
1Department of Chemistry and CC.MM, Faculty of Experimental Science, Campus de El Carmen, University of Huelva, 21007 Huelva, Spain; International Campus of Excellence on Agrofood (CEIA3), University of Huelva, 21007 Huelva, Spain; Research Center of Health and Environment (CYSMA), Campus de El Carmen, University of Huelva, 21007 Huelva, Spain.
Abstract:
The analysis of urine by direct infusion mass spectrometry suffers from ion suppression due to its high salt content and inter-sample variability caused by the differences in urine volume between persons. Thus, urine metabolomics requires a careful selection of the sample preparation procedure and a normalization strategy to deal with these problems. Several approaches were tested for metabolomic analysis of urine samples by direct infusion electrospray mass spectrometry (DI-ESI-MS), including solid phase extraction, liquid-liquid extraction, and sample dilution. In addition, normalization of results based on conductivity values and statistical treatment was performed to minimize sample variability. Both urine dilution and solid phase extraction with mixed mode sorbent considerably reduced the salt content in urine, providing comprehensive metabolomic fingerprints. Moreover, statistical data normalization enabled the correction of inter-sample physiological variability, improving the quality of results obtained. Therefore, high-throughput DI-ESI-MS fingerprinting of urine samples can be achieved with simple pretreatment procedures allowing the use of this noninvasive sampling in metabolomics. Finally, the optimized approach was tested in a pilot metabolomic investigation of urine samples from transgenic mice models of Alzheimer's disease (APP/PS1) in order to illustrate the potential of the methodology.

