Application of Kinetically Optimised Online HILIC × RP-LC Methods Hyphenated to High Resolution MS for the Analysis of Natural Phenolics

Abstract

Phenolics are a large group of secondary plant metabolites that are of interest because of their proposed health benefits. The analysis of plant phenolics is challenging due to their extreme structural diversity. Comprehensive two-dimensional liquid chromatography (LC × LC) coupled to high-resolution mass spectrometry (HR-MS) offers a powerful analytical tool for the analysis of such complex mixtures. Especially, the combination of hydrophilic interaction chromatography (HILIC) and reversed-phase liquid chromatography (RP-LC) is attractive for phenolic analysis due to the orthogonal group-type separations attainable. However, online hyphenation of HILIC and RP-LC is complicated by the relative elution strengths of the mobile phases used in both dimensions. Coupled to the inherent complexity of method development in LC × LC, this hampers the more widespread application of HILIC × RP-LC. In this study, a generic HILIC × RP-LC‒DAD-MS methodology for phenolic analysis utilising dilution of the first dimension flow and large volume injection in the second dimension is derived by kinetic optimisation of experimental parameters to provide maximum performance. The scope of the experimental configuration is demonstrated by its application to the analysis of rooibos tea, wine and grape samples containing a range of different flavonoid and non-flavonoid phenolic classes. Using this approach, excellent chromatographic performance was obtained, and a total of 149 phenolic compounds were tentatively identified in the investigated samples based on retention data in two dimensions, UV–Vis spectral as well as high- and low collision energy HR-MS data (72 in grape seeds, 32 in rooibos tea and 45 in wine and grapes) with minimal method development time. The results confirm the applicability of the proposed methodology for the detailed screening of phenolic constituents in natural products.