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Dereplication represents a key step for rapidly identifying known secondary metabolites in complex biological matrices. In this context, liquid-chromatography coupled to high resolution mass spectrometry (LC-HRMS) is increasingly used and, via untargeted data-dependent MS/MS experiments, massive amounts of detailed information on the chemical composition of crude extracts can be generated. An efficient exploitation of such data sets requires automated data treatment and access to dedicated fragmentation databases. Various novel bioinformatics approaches such as molecular networking (MN) and in-silico fragmentation tools have emerged recently and provide new perspective for early metabolite identification in natural products (NPs) research.

Countercurrent chromatography techniques are increasingly used in the fractionation and purification steps of natural products due to their excellent versatility and efficiency. However, one of the major bottlenecks in liquid-liquid chromatography is the solvent system selection. In this work, a NMR-based analysis of complex solvent mixtures was developed for biphasic system selection and modification. This allowed us to develop more versatile separation conditions, such as gradients. Additionally, we hyphenated our countercurrent chromatography device with NMR and mass spectrometry.

The phytochemical study of the root extract of the stilbenoid-rich Vitis riparia × Vitis berlandieri grapevine was carried out by centrifugal partition chromatography (CPC). For this reason, we developed a new elution mode we named back-step, which allowed us to obtain cleaner fractions and a more efficient separation process when used in conjunction with a classical elution approach. Three hydroxystilbenes: (E)-resveratrol, (E)-ɛ-viniferin and (E)-vitisin C, with greater than 90% purity were thus obtained through such process, with minimal sample handling and purification steps.