ABSTRACT
ETHNOPHARMACOLOGICAL RELEVANCE: Flos Chrysanthemi Indici (FCI), the flower of Chrysanthemum Indicum L., is a popular traditional Chinese medicine (TCM) for treatment of inflammatory diseases in China. FCI is also a functional food, and is widely used as herbal tea for clearing heat and detoxicating. AIM OF THE STUDY: To explore quality control markers of FCI based on the optimal harvest period. MATERIALS AND METHODS: First, UPLC-Q-TOF/MS based untargeted metabolomics was applied to explore the chemical profiles of FCIs collected at bud stages (BS), initial stages (IS), full bloom stages (FS) and eventual stages (ES) from eight cultivated regions in China. Subsequently, lipopolysaccharide (LPS)-induced RAW264.7 cell inflammatory model and carrageenan-induced rat paw edema model were used to confirm the anti-inflammatory effect of FCIs collected at IS/FS. Then, UPLC-PDA targeted metabolomics was used to quantitatively analyze 9 constituents with anti-inflammatory activity (7 flavonoids and 2 phenolic acids) changed significantly (VIP > 4) during flowering stages. Finally, ROC curves combined with PCA analysis based on the variation of 9 active constituents in FCIs from different flowering stages were applied to screen the quality markers of FCI. RESULTS: FCIs at IS/FS had almost same chemical characteristics, but quite different from those at BS and ES. A total of 32 constituents in FCIs including flavonoids and phenolic acids were changed during flowering development. Most of the varied constituents had the highest or higher contents at IS/FS compared with those at ES, indicating that the optimal harvest period of FCI should be at IS/FS. FCI extract could effectively suppress nitric oxide (NO) production in LPS-induced RAW264.7 cells and regulate the abnormal levels of cytokines and PGE2 in carrageenan-induced paw edema model rat. The results of quantitatively analysis revealed that the variation trends of phenolic acids and flavonoids in FCIs were different during flowering development, but most of them had higher contents at IS/FS than those at ES in all FCIs collected from eight cultivated regions, except TC, Anhui. Finally, linarin, luteolin, apigenin and 3,5-dicaffeoylquinic acid were selected as the Q-markers based on the contribution of their AUC values in ROC and clustering of PCA analysis. CONCLUSIONS: Our study demonstrates the optimal harvest period of FCI and specifies the multi-constituents Q-markers of FCI based on the influence of growth progression on the active constituents using untargeted/targeted metabolomics. The findings not only greatly increase the utilization rate of FCI resources and improve quality control of FCI products, but also offer new strategy to identify the Q-markers of FCI.
