Evaluation of extraction protocols for simultaneous polar and non-polar yeast metabolite analysis using multivariate projection methods.

Aalim Weljie,Nicolas Tambellini,Raymond Turner,Vanina Zaremberg

doi:10.3390/metabo3030592

Aalim Weljie, Nicolas Tambellini + Show 2 more

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https://doi.org/10.3390/metabo3030592

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Journal: Metabolites	Publication Date: Jul 23, 2013
Citations: 56	License type: CC BY 4.0

Affiliation: University of Calgary, University of Pennsylvania

Abstract

Metabolomic and lipidomic approaches aim to measure metabolites or lipids in the cell. Metabolite extraction is a key step in obtaining useful and reliable data for successful metabolite studies. Significant efforts have been made to identify the optimal extraction protocol for various platforms and biological systems, for both polar and non-polar metabolites. Here we report an approach utilizing chemoinformatics for systematic comparison of protocols to extract both from a single sample of the model yeast organism Saccharomyces cerevisiae. Three chloroform/methanol/water partitioning based extraction protocols found in literature were evaluated for their effectiveness at reproducibly extracting both polar and non-polar metabolites. Fatty acid methyl esters and methoxyamine/trimethylsilyl derivatized aqueous compounds were analyzed by gas chromatography mass spectrometry to evaluate non-polar or polar metabolite analysis. The comparative breadth and amount of recovered metabolites was evaluated using multivariate projection methods. This approach identified an optimal protocol consisting of 64 identified polar metabolites from 105 ion hits and 12 fatty acids recovered, and will potentially attenuate the error and variation associated with combining metabolite profiles from different samples for untargeted analysis with both polar and non-polar analytes. It also confirmed the value of using multivariate projection methods to compare established extraction protocols.

Highlights

The field of metabolomics is rapidly seeing more widespread use for the determination of system level metabolic changes caused by influences such as diet, environmental stress and disease [1,2,3,4,5].to accurately determine the changes in a metabolite profile caused by these influences, care must be taken in order to optimize the different factors that affect data quality and reproducibility
Studies looking at optimal polar metabolite extraction protocols for biological compounds including sugars, amino acids and water soluble metabolic precursors or intermediates have been carried out for single platforms including nuclear magnetic resonance (NMR) [6,7], gas chromatography mass spectrometry (GC-MS) [8,9,10,11], and liquid chromatography mass spectrometry (LC-MS) [12,13,14]
Cheminformatics is a field that is growing rapidly and will be of great use for metabolomic studies, especially as compound databases continue to expand. This will allow for untargeted analysis of many different sample types to be carried out

Summary

Introduction

The field of metabolomics is rapidly seeing more widespread use for the determination of system level metabolic changes caused by influences such as diet, environmental stress and disease [1,2,3,4,5]. To accurately determine the changes in a metabolite profile caused by these influences, care must be taken in order to optimize the different factors that affect data quality and reproducibility. Studies looking at optimal polar metabolite extraction protocols for biological compounds including sugars, amino acids and water soluble metabolic precursors or intermediates have been carried out for single platforms including nuclear magnetic resonance (NMR) [6,7], gas chromatography mass spectrometry (GC-MS) [8,9,10,11], and liquid chromatography mass spectrometry (LC-MS) [12,13,14].

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