Development of a metabolomic approach based on urine samples and direct infusion mass spectrometry
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...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2014 |
| País: | España |
| Institución: | Universidad de Huelva (UHU) |
| Repositorio: | Arias Montano. Repositorio Institucional de la Universidad de Huelva |
| Idioma: | inglés |
| OAI Identifier: | oai:ariasmontano.uhu.es:10272/14476 |
| Acceso en línea: | http://hdl.handle.net/10272/14476 |
| Access Level: | acceso abierto |
| Palabra clave: | Metabolomics Urine Direct infusion mass spectrometry Ion suppression Normalization APP/PS1 mice |
| Sumario: | 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. |
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