Feature-Based Molecular Networking to Target the Isolation of New Caffeic Acid Esters from Yacon (Smallanthus sonchifolius, Asteraceae)

Abstract

Smallanthus sonchifolius (yacon) is an edible tuberous Andean shrub that has been included in the diet of indigenous people since before recorded history. The nutraceutical and medicinal properties of yacon are widely recognized, especially for the improvement of hyperglycemic disorders. However, the chemical diversity of the main bioactive series of caffeic acid esters has not been explored in detail. In this metabolomics study, we applied the latest tools to facilitate the targeted isolation of new caffeic acid esters. Using liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), we analyzed extracts from different organs (roots, vascular tissues of the stems, stem epidermis, leaves, bracts, and ray flowers) and followed a feature-based molecular networking approach to characterize the structural diversity of caffeic acid esters and recognize new compounds. The analysis identified three potentially new metabolites, one of them confirmed by isolation and full spectroscopic/spectrometric assignment using nuclear magnetic resonance (NMR), high-resolution mass spectrometry (HRMS), and MS/MS. This metabolite (5-O-caffeoyl-2,7-anhydro-d-glycero-β-d-galacto-oct-2-ulopyranosonic acid), along with eight known caffeic acid esters, was isolated from the roots and stems. Furthermore, based on detailed tandem MS analyses, we suggest that the two isomeric monocaffeoyl-2,7-anhydro-2-octulopyranosonic acids found in yacon can be reliably distinguished based on their characteristic MS2 and MS3 spectra. The outcome of the current study confirms the utility of feature-based molecular networking as a tool for targeted isolation of previously undescribed metabolites and reveals the full diversity of potentially bioactive metabolites from S. sonchifolius.