Characterization of Constituents with Potential Anti-Inflammatory Activity in Chinese Lonicera Species by UHPLC-HRMS Based Metabolite Profiling

通过基于 UHPLC-HRMS 的代谢物分析对中国忍冬属植物中具有潜在抗炎活性的成分进行表征

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作者:Eva-Maria Pferschy-Wenzig, Sabine Ortmann, Atanas G Atanasov, Klara Hellauer, Jürgen Hartler, Olaf Kunert, Markus Gold-Binder, Angela Ladurner, Elke H Heiß, Simone Latkolik, Yi-Min Zhao, Pia Raab, Marlene Monschein, Nina Trummer, Bola Samuel, Sara Crockett, Jian-Hua Miao, Gerhard G Thallinger, Valer

Abstract

This study centered on detecting potentially anti-inflammatory active constituents in ethanolic extracts of Chinese Lonicera species by taking an UHPLC-HRMS-based metabolite profiling approach. Extracts from eight different Lonicera species were subjected to both UHPLC-HRMS analysis and to pharmacological testing in three different cellular inflammation-related assays. Compounds exhibiting high correlations in orthogonal projections to latent structures discriminant analysis (OPLS-DA) of pharmacological and MS data served as potentially activity-related candidates. Of these candidates, 65 were tentatively or unambiguously annotated. 7-Hydroxy-5,3',4',5'-tetramethoxyflavone and three bioflavonoids, as well as three C32- and one C34-acetylated polyhydroxy fatty acid, were isolated from Lonicera hypoglauca leaves for the first time, and their structures were fully or partially elucidated. Of the potentially active candidate compounds, 15 were subsequently subjected to pharmacological testing. Their activities could be experimentally verified in part, emphasizing the relevance of Lonicera species as a source of anti-inflammatory active constituents. However, some compounds also impaired the cell viability. Overall, the approach was found useful to narrow down the number of potentially bioactive constituents in the complex extracts investigated. In the future, the application of more refined concepts, such as extract prefractionation combined with bio-chemometrics, may help to further enhance the reliability of candidate selection.

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