Abstract

Metabolomics deals with analysis of highly complex biological samples resulting in insufficient separation of relevant metabolites from matrix substances with one-dimensional liquid chromatography. Comprehensive twodimensional liquid chromatography (2D-LC) is a promising technique for the analysis of complex samples because of its increased peak capacity. Comprehensive 2D-LC-MS/MS has been applied for a targeted metabolomics approach regarding metabolites from RNA catabolism. Combination of a Zorbax Eclipse Plus C18 column with a Zorbax Bonus-RP column resulted in increased peak capacity, minimisation of matrix effects and excellent reproducibility.

Highlights

  • The emerging field of metabolomics often deals with the analysis of highly complex matrices

  • Metabolomics deals with analysis of highly complex biological samples resulting in insufficient separation of relevant metabolites from matrix substances with one-dimensional liquid chromatography

  • Comprehensive 2D-LC-MS/MS has been applied for a targeted metabolomics approach regarding metabolites from RNA catabolism

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Summary

Introduction

The emerging field of metabolomics often deals with the analysis of highly complex matrices. The main task in 2D-LC method development is to maximize peak capacity of two different separation techniques such as reversed phase and normal phase LC, while maintaining the possibility to couple these two dimensions. The multiplicity of 2D separations can be explained by the following equation: In this equation n1c is the peak capacity of the 2D separation. If the separation mechanisms of the first and second chromatographic dimension show no correlation, the separation is highly orthogonal. There are different concepts to theoretically assess the orthogonality of a two dimensional separation [3,4,5], which can be applied for evaluation of different separation mechanisms during method development. Gilar et al [4] developed the following equation for calculation of orthogonality based on plotting a 2D separation space and spotting data points into rectangular bins:. In consideration of the wide concentration range of metabolites in biological samples, choosing the optimal sampling time can be challenging

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