Abstract
Metabolomics is a powerful and widely used approach that aims to screen endogenous small molecules (metabolites) of different families present in biological samples. The large variety of compounds to be determined and their wide diversity of physical and chemical properties have promoted the development of different types of hydrophilic interaction liquid chromatography (HILIC) stationary phases. However, the selection of the most suitable HILIC stationary phase is not straightforward. In this work, four different HILIC stationary phases have been compared to evaluate their potential application for the analysis of a complex mixture of metabolites, a situation similar to that found in non-targeted metabolomics studies. The obtained chromatographic data were analyzed by different chemometric methods to explore the behavior of the considered stationary phases. ANOVA-simultaneous component analysis (ASCA), principal component analysis (PCA) and partial least squares regression (PLS) were used to explore the experimental factors affecting the stationary phase performance, the main similarities and differences among chromatographic conditions used (stationary phase and pH) and the molecular descriptors most useful to understand the behavior of each stationary phase.
Highlights
Over the past decade, metabolomics has received considerable attention from the scientific community
Due to its high-resolution power, sensitivity and accuracy of m/z detection, liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) has become the analytical platform most used in metabolomics studies
Reversed phased liquid chromatography (RPLC) is not recommended for the analysis of some of the most usual metabolite families characterized as being polar and hydrophilic compounds [2,6,7,8,9]
Summary
Metabolomics has received considerable attention from the scientific community. Like ANOVA-simultaneous component analysis (ASCA) [19], can help evaluating the statistical significance of the experimental factors involved in a non-targeted metabolomics study, such as when different HILIC stationary phases and mobile phase conditions are assessed. On the other hand, building models linking the physicochemical properties of compounds (molecular descriptors, MDs) and their chromatographic behavior (retention factors) could help to get a different insight into the HILIC stationary phase performance [11,20,21,22,23,24,25,26,27,28,29]. Partial least squares regression (PLS) models based on MDs computed from molecular structures of different metabolite families were calculated for evaluating the chromatographic behavior of the four HILIC stationary phases considering the retention factor of the analyzed metabolites
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