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Phytochemistry 2013-Dec

Phytochemical, phylogenetic, and anti-inflammatory evaluation of 43 Urtica accessions (stinging nettle) based on UPLC-Q-TOF-MS metabolomic profiles.

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Mohamed A Farag
Maximilian Weigend
Federico Luebert
Grischa Brokamp
Ludger A Wessjohann

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Útdráttur

Several species of the genus Urtica (especially Urtica dioica, Urticaceae), are used medicinally to treat a variety of ailments. To better understand the chemical diversity of the genus and to compare different accessions and different taxa of Urtica, 63 leaf samples representing a broad geographical, taxonomical and morphological diversity were evaluated under controlled conditions. A molecular phylogeny for all taxa investigated was prepared to compare phytochemical similarity with phylogenetic relatedness. Metabolites were analyzed via UPLC-PDA-MS and multivariate data analyses. In total, 43 metabolites were identified, with phenolic compounds and hydroxy fatty acids as the dominant substance groups. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) provides a first structured chemotaxonomy of the genus. The molecular data present a highly resolved phylogeny with well-supported clades and subclades. U. dioica is retrieved as both para- and polyphyletic. European members of the U. dioica group and the North American subspecies share a rather similar metabolite profile and were largely retrieved as one, nearly exclusive cluster by metabolite data. This latter cluster also includes - remotely related - Urtica urens, which is pharmaceutically used in the same way as U. dioica. However, most highly supported phylogenetic clades were not retrieved in the metabolite cluster analyses. Overall, metabolite profiles indicate considerable phytochemical diversity in the genus, which largely falls into a group characterized by high contents of hydroxy fatty acids (e.g., most Andean-American taxa) and another group characterized by high contents of phenolic acids (especially the U. dioica-clade). Anti-inflammatory in vitro COX1 enzyme inhibition assays suggest that bioactivity may be predicted by gross metabolic profiling in Urtica.

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