Planta Med 2014; 80 - P1M8
DOI: 10.1055/s-0034-1394575

Metabolic Profiling of Clematis species to identify compounds with an inhibitor effect on NF-κB transactivation

M Monschein 1, EM Pferschy-Wenzig 1, S Ortmann 1, C Huber 1, E Heiss 2, C Malainer 2, A Georgiev Atanasov 2, V Dirsch 2, J Hartler 3, 4, G Thallinger 3, 4, JH Miao 5 R Bauer 1, et al
  • 1Institute of Pharmaceutical Sciences, Department of Pharmacognosy, University of Graz, Universitaetsplatz 4, 8010 Graz, Austria
  • 2Department of Pharmacognosy, University of Vienna, Althanstrasse 14, 1090 Vienna, Austria
  • 3Bioinformatics Group, Institute for Knowledge Discovery, Graz-University of Technology, Petersgasse 14/V, 8010 Graz, Austria
  • 4Omics Center Graz, Stiftingtalstrasse 24, 8036 Graz, Austria
  • 5Guangxi Botanical Garden of Medicinal Plants, 189 Changgang Road, Nanning, China

Clematis L. (Ranunculaceae) is a genus of about 300 species widespread throughout the world. Many Clematis species are traditionally used for various ailments, among them many diseases related to inflammation. Based on this knowledge and on the results of a large screening of Chinese medicinal plant extracts, the genus Clematis was chosen as a subject for a study in order to explore the feasibility of correlating metabolic profiles and bioactivity of crude extracts to identify their active constituents. Ethanolic extracts from 48 different Clematis samples originating from C. uncinata, C. smilacifolia, C. finetiana, C. gouriana, C. leschenaultiana, C. chingii, C. loureiroana, C. apiifolia var. argentilucida, C. chinensis, C. meyeniana, C. peterae, C. parviloba, C. puberula var. tenuisepala and C. buchananiana were included in this investigation. The extracts were tested for inhibition of NF-κB luciferase reporter transactivation in HEK293 cells [1]. At a concentration of 50 µg/ml, the extracts showed distinct activities, some of them possessing a very good inhibitory effect. In parallel, the metabolic profiles of the extracts were analysed by LC-HRMS in the ESI negative mode (Dionex Ultimate 3000 UHPLC; Q ExactiveTM Hybrid Quadrupole Orbitrap-MS, Thermo Fisher). The LC-MS data were processed in an untargeted approach by MZmine 2 [2]; peaks were verified and quantified by Lipid Data Analyzer [3]. The abundance of the peaks was linked to the pharmacological activity of the extracts using the software SIMCA 13 [4]. Principal component analyses as well as orthogonal partial least squares-discriminant analyses (OPLS-DA) and visualisation of the data by means of S-plot was conducted. This approach led to the identification of eight phenolic compounds which seem to be highly relevant for NF-κB inhibitory activity.

Acknowledgements: We gratefully acknowledge the funding provided by the Austrian Science Fund (FWF) for project SS10705-B13 within the NFN (Drugs from Nature Targeting Inflammation).

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