4.8 Article

Cross-Platform Comparison of Methods for Quantitative Metabolomics of Primary Metabolism

Journal

ANALYTICAL CHEMISTRY
Volume 81, Issue 6, Pages 2135-2143

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/ac8022857

Keywords

-

Funding

  1. European Union
  2. UBS Wealth

Ask authors/readers for more resources

Quantitative metabolomics is under intense development, and no commonly accepted standard analytical technique has emerged, yet. The employed analytical methods were mostly chosen based on educated guesses. So far, there has been no systematic cross-platform comparison of different separation and detection methods for quantitative metabolomics. Generally, the chromatographic separation of metabolites followed by their selective detection in a mass spectrometer (MS) is the most promising approach in terms of sensitivity and separation power. Using a defined mixture of 91 metabolites (coveting glycolysis, pentose phosphate pathway, the tricarboxylic acid (TCA) cycle, redox metabolism, amino acids, and nucleotides), we compared six separation methods designed for the analysis of these mostly very polar primary metabolites, two methods each for gas chromatography (GC), liquid chromatography (LC), and capillary electrophoresis (CE). For analyses on a single platform, LC provides the best combination of both versatility and robustness. If a second platform can be used, it is best complemented by GC. Only liquid-phase separation systems can handle large polar metabolites, such as those containing multiple phosphate groups. As assessed by supplementing the defined mixture with C-13-labeled yeast extracts, matrix effects are a common phenomenon on all platforms. Therefore, suitable internal standards, such as C-13-labeled biomass extracts, are mandatory for quantitative metabolomics with any methods.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available