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中国精品科技期刊2020
严淘,杨敏敏,施琳,等. 菊花不同提取物代谢组学分析及其抗氧化活性功效物质成分筛选[J]. 食品工业科技,2021,42(16):8−19. doi: 10.13386/j.issn1002-0306.2021010248.
引用本文: 严淘,杨敏敏,施琳,等. 菊花不同提取物代谢组学分析及其抗氧化活性功效物质成分筛选[J]. 食品工业科技,2021,42(16):8−19. doi: 10.13386/j.issn1002-0306.2021010248.
YAN Tao, YANG Minmin, SHI Lin, et al. Metabonomics Analysis of Different Extracts from Chrysanthemum morifolium and Screening of Its Antioxidant Active Components[J]. Science and Technology of Food Industry, 2021, 42(16): 8−19. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021010248.
Citation: YAN Tao, YANG Minmin, SHI Lin, et al. Metabonomics Analysis of Different Extracts from Chrysanthemum morifolium and Screening of Its Antioxidant Active Components[J]. Science and Technology of Food Industry, 2021, 42(16): 8−19. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2021010248.

菊花不同提取物代谢组学分析及其抗氧化活性功效物质成分筛选

Metabonomics Analysis of Different Extracts from Chrysanthemum morifolium and Screening of Its Antioxidant Active Components

  • 摘要: 为探究采用不同提取方式制备的富硒杭白菊提取物组分差异以及筛选菊花抗氧化活性功效物质,采用高通量液相质谱代谢组学技术对四种杭白菊提取物样本(水煎法BWE、热回流水提法RWE、超声波辅助水提法UWE、超声波辅助醇提法UEE)代谢物组定性解析,共检出776种代谢物,主要包括醇类、氨基酸类、糖类、黄酮苷类等;分光光度法精确定量分析不同提取物的总酚、总黄酮含量,结合对ABTS+和DPPH自由基清除率评价不同提取物抗氧化活性,并以差异代谢物相对含量为统计信息源,基于监督式机器学习算法明晰不同提取方式样本中最优表征抗氧化活性的代谢物。结果表明,不同提取方式菊花代谢物差异显著。其中,33个代谢物显著区分BWE、RWE和UWE组,35个代谢物显著区分UWE和UEE组(多重假设检验校正P<0.05)。BWE、RWE、UWE、UEE组总酚含量分别为13.858%、10.708%、16.644%、20.160%,总黄酮含量分别为26.401%、15.984%、27.299%、40.769%,ABTS+自由基清除率EC50值分别为0.048、0.036、0.055、0.056,DPPH自由基清除率EC50值分别为0.048、0.053、0.059、0.047。总酚、总黄酮含量与DPPH自由基清除率EC50无相关关系,不能最优反映菊花的抗氧化活性。运用随机森林模型筛选出黄豆黄素、丝氨酸、1, 3-二咖啡酰奎宁酸,和麦角硫因、芹菜素、磷脂酰胆碱分别作为最优表征菊花水提物抗氧化活性的功能代谢物质组成。本研究采用代谢组学和机器学习算法,从上百种物质中筛选出最优表征杭白菊水提物抗氧化活性的代谢物,为富硒杭白菊靶向功能性物质提取工艺优化提供新的思路和理论基础。

     

    Abstract: To explore differences in chemical components of Chrysanthemum morifolium extracted by four different methods, i.e. boiling water extract (BWE), reflux water extract (RWE), ultrasonic assisted water extract (UWE) and ultrasonic assisted ethanol extract (UEE) and to identify key compounds reflective of antioxidant activity of Chrysanthemum morifolium extracts, the high-throughput liquid chromatography-mass spectrometry metabolomics was applied. A total of 776 compounds were detected including alcohols and polyols, amino acids, carbohydrates, flavonoid glycosides, etc., contents of total phenols and flavonoids of Chrysanthemum extracts were determined by spectrophotometry. The antioxidant activity of different extracts was evaluated by ABTS+ and DPPH free radical scavenging rate. The key antioxidant compounds were identified using supervised machine learning. Results showed that chemical components of Chrysanthemum morifolium significantly differed between four extracts: Relative contents of 33 and 35 metabolites greatly discriminated BWE, RWE and UWE, or UWE and UEE, respectively (P<0.05 after Bonferroni correction). The contents of total phenols of BWE, RWE, UWE and UEE were 13.858%, 10.708%, 16.644%, 20.160%, respectively; the contents of total flavonoids were 26.401%, 15.984%, 27.299%, 40.769%, respectively. The EC50 of ABTS free radical scavenging rate was respectively 0.048, 0.036, 0.055, 0.056; the EC50 of DPPH free radical scavenging rate was respectively 0.048, 0.053, 0.059, 0.047. No correlation was found between contents of total phenols or total flavonoids with the antioxidant activity indicated by EC50 of ABTS and DPPH free radical scavenging rate. Of note, glycitein, serine, 1, 3-dicaffeoylquinic acid as well as ergothioneine, apigenin, phosphatidylcholines were identified, which could optimally characterize the antioxidant activity of the water extracts of Chrysanthemum morifolium, respectively. Using metabolomics and machine learning, key compounds characterizing antioxidant activity of the Chrysanthemum morifolium water extracts were identified, providing novel insights and theoretical basis for optimizing extraction processes targeting functional components of Chrysanthemum morifolium.

     

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