Planta Med 2014; 80 - P1M12
DOI: 10.1055/s-0034-1394579

LC-MS Metabolic profiling for identification of active compounds in Lonicera species

S Ortmann 1, M Monschein 1, J Hartler 2, 3, YM Zhao 4, JH Miao 4, GG Thallinger 2, 3, R Bauer 1
  • 1Institute of Pharmaceutical Sciences, University of Graz, Universitaetsplatz 4/I, 8010 Graz, Austria
  • 2Bioinformatics Group, Institute for Knowledge Discovery, Graz-University of Technology, Petersgasse 14/V, 8010 Graz, Austria
  • 3Omics Center Graz, Stiftingtalstrasse 24, 8036 Graz, Austria
  • 4Guangxi Botanical Garden of Medicinal Plants, 189 Changgang Road, Nanning, China

Lonicera japonica Thunb. (Caprifoliaceae) is widely used in traditional Chinese medicine for its antibacterial and anti-inflammatory properties. Based on this knowledge, and following the results of a screening of a large number of Chinese medicinal plants, the genus Lonicera was chosen for a proof-of-principle study in which the active principles should be identified by correlating the LC-MS profiles of the constituents to the biological activity. Ethanolic extracts of 36 Lonicera samples were investigated. The extracts were tested for inhibition of NO production in LPS-/IFN-γ-stimulated RAW 264.7 mouse macrophages [1]. At a concentration of 50 µg/ml some extracts showed a very good inhibitory effect (up to 88% inhibition referred to control) on the NO production. In parallel the extracts were analysed by LC-MS (Dionex Ultimate 3000 UHPLC focused; Q ExactiveTM Hybrid Quadrupole Orbitrap-MS, Thermo Fisher). The LC-MS metabolic profiles were processed in an untargeted manner by MZmine 2 [2]. Peaks were subsequently verified and quantified by Lipid Data Analyzer [3]. The abundance of the peaks was linked to the pharmacological data using SIMCA 13 [4]. Principal component analysis as well as orthogonal partial least squares-discriminant analysis and visualisation of the data by means of the so-called S-plot were conducted. This approach led to the identification of ca. fifteen compounds which seem to be most relevant for the inhibitory effects of the extracts on the NO-production.

Keywords: metabolomics, inflammation, iNOS, Lonicera

References:

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[2] Pluskal T. et al. BMC Bioinformatics 2010; 11:395.

[3] Hartler J. et al. Bioinformatics 2011; 27:572 – 577.

[4] Whelehan O.P. et al. Chemometrics and Intelligent Laboratory Systems 2006; 84: 82 – 87.