Procedure for tissue sample preparation and metabolite extraction for high-throughput targeted metabolomics View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2012-02

AUTHORS

Werner Römisch-Margl, Cornelia Prehn, Ralf Bogumil, Cornelia Röhring, Karsten Suhre, Jerzy Adamski

ABSTRACT

Reproducible quantification of metabolites in tissue samples is of high importance for characterization of animal models and identification of metabolic changes that occur in different tissue types in specific diseases. However, the extraction of metabolites from tissue is often the most labor-intensive and error-prone step in metabolomics studies. Here, we report the development of a standardized high-throughput method for rapid and reproducible extraction of metabolites from multiple tissue samples from different organs of several species. The method involves a bead-based homogenizer in combination with a simple extraction protocol and is compatible with state-of-the-art metabolomics kit technology for quantitative and targeted flow injection tandem mass spectrometry. We analyzed different extraction solvents for both reproducibility as well as suppression effects for a range of different animal tissue types including liver, kidney, muscle, brain, and fat tissue from mouse and bovine. In this study, we show that for most metabolites a simple methanolic extraction is best suited for reliable results. An additional extraction step with phosphate buffer can be used to improve the extraction yields for a few more polar metabolites. We provide a verified tissue extraction setup to be used with different indications. Our results demonstrate that this high-throughput procedure provides a basis for metabolomic assays with a wide spectrum of metabolites. The developed method can be used for tissue extraction setup for different indications like studies of metabolic syndrome, obesity, diabetes or cardiovascular disorders and nutrient transformation in livestock. More... »

PAGES

133-142

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11306-011-0293-4

DOI

http://dx.doi.org/10.1007/s11306-011-0293-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1004591576


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