Assessing specialized metabolite diversity of Alnus species by a digitized LC-MS/MS data analysis workflow

Abstract

Alnus spp. (Betulaceae) have been used for treatments of hemorrhage, burn injuries, antipyretic fever, diarrhea, and alcoholism in traditional medicines. In this study, a digitized LC-MS/MS data analysis workflow was applied to provide an overview on chemical diversity of 15 Alnus extracts prepared from bark, twigs, leaves, and fruits of A. japonica, A. firma, A. hirsuta, and A. hirsuta var. sibirica. Most of the MS/MS spectra could be putatively annotated based on library matching, in silico fragmentation, and substructural topic modeling. The putative annotation allowed us to discriminate the extracts into three chemotypes based on dominant chemical scaffolds: diarylheptanoids, flavonoids or tannins. This high-throughput chemical annotation was correlated with a-glucosidase inhibition data of extracts, and it allowed us to identify gallic acid as the major active compound of A. firma.