Anti-inflammatory/anti-oxidant properties and the UPLC-QTOF/MS-based metabolomics discrimination of three yellow camellia species. (October 2022)

• Record Type: Journal Article
• Authors: Zhao, Mingming; Linghu, Ke-Gang; Xiao, Linxuan; Hua, Tianyi; Zhao, Guanding; Chen, Qiling; Xiong, Shihang; Shen, Liyu; Yu, Jinyu; Hou, Xiaotao; Hao, Erwei; Du, Zhengcai; Deng, Jiagang; Bai, Gang; Chen, Xiaojia; Li, Ling; Li, Peng; Yu, Hua
• Is Part Of: Food research international. Volume 160(2022)
• Publication Date: 2022-10
• Subjects: Yellow camellias -- Discrimination -- Metabolomics -- Fingerprint -- Anti-inflammation -- Anti-oxidant; Food -- Analysis -- Periodicals; Food industry and trade -- Periodicals; Food industry and trade -- Canada -- Periodicals; Food Technology -- Periodicals; Food -- Periodicals; Food-Processing Industry -- Periodicals; Aliments -- Industrie et commerce -- Périodiques; Aliments -- Industrie et commerce -- Canada -- Périodiques; Aliments -- Recherche -- Périodiques; Food industry and trade; Canada; Periodicals; Electronic journals; 664.005
• DOI: 10.1016/j.foodres.2022.111628
• Languages: English
• ISSNs: 0963-9969

Abstract

Graphical abstract: Highlights: A sequential-optimization based new statistical model is developed for chemical pattern recognition of three yellow camellia species. The yellow camellia species could be well discriminated from each other. CC and CE present certain similarity on anti-inflammation and anti-oxidation, which is significantly different from CI. Abstract: The species of Camellia nitidissima Chi (CC) and C. euphlebia Merr. ex Sealy (CE) are two most important plant sources for commercialized herbal tea (Jinhuacha) worldwide. However, some other species of camellia genus are also sold as alternatives in market due to the great commercial value. In this study, the similarity and difference of CC and CE as well as C. insularis (CI) are comprehensively compared both in chemistry and pharmacology. Based on the ultraperformance liquid chromatography coupled with a hybrid quadrupole orthogonal time-of-flight mass spectrometer (UPLC-QTOF-MS) analysis, a sequential-optimization based new statistical model has been developed by combining the untargeted metabolomics and fingerprint analyses, and successfully applied for chemical pattern recognition and discrimination of three yellow camellias species. The results indicated that CC, CE and CI could be well discriminated with the optimized chemical combination including quercetin-3-O-rhamnoside ( C 2), okicamelliaside (C4), Kaempferol 7-O-rhamnoside (C6), Corymboside (C9), asiatic acid-glc-rha-xyl (C11) and 3′-methy-4′-glucoside-ellagic acid (C14). Moreover, the 30 % ethanolic extracts of yellow camellias species presented the optimal activities on anti-inflammation/anti-oxidation in LPS-stimulated Raw264.7 macrophages dose-dependently. The averaged 50 % inhibitory concentrations (IC50) on NO production were 754.68 ± 50.96, 1182.39 ± 22.10, 1527.83 ± 106.24 μg(herb)/mL, and ROS production were 311.70 ± 26.57, 332.64 ± 25.46, 917.60 ± 41.36 μg(herb)/mL for CC, CE and CI, respectively. The results indicated a certain similarity of CC and CE, as well as their significant difference from CI.