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中国精品科技期刊2020
兰天,段国珍,祁有朝,等. 红果枸杞和黄果枸杞广泛靶向代谢组学分析[J]. 华体会体育,2024,45(24):9−20. doi: 10.13386/j.issn1002-0306.2024020267.
引用本文: 兰天,段国珍,祁有朝,等. 红果枸杞和黄果枸杞广泛靶向代谢组学分析[J]. 华体会体育,2024,45(24):9−20. doi: 10.13386/j.issn1002-0306.2024020267.
LAN Tian, DUAN Guozhen, QI Youchao, et al. Extensively Targeted Metabolomics Analysis of Red and Yellow Wolfberries[J]. Science and Technology of Food Industry, 2024, 45(24): 9−20. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2024020267.
Citation: LAN Tian, DUAN Guozhen, QI Youchao, et al. Extensively Targeted Metabolomics Analysis of Red and Yellow Wolfberries[J]. Science and Technology of Food Industry, 2024, 45(24): 9−20. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2024020267.

红果枸杞和黄果枸杞广泛靶向代谢组学分析

Extensively Targeted Metabolomics Analysis of Red and Yellow Wolfberries

  • 摘要: 为了深入分析红果枸杞和黄果枸杞之间的差异代谢物及代谢途径,本研究采用超高效液相色谱-串联高分辨质谱联用广泛靶向代谢组学,分析两种枸杞的差异代谢物及主要代谢途径。通过主成分分析、正交偏最小二乘判别分析、聚类分析等多元统计学方法,在差异倍数≥2或≤0.5、变量重要投影值≥1、P<0.05的条件下,正离子模式下检测出红果枸杞和黄果枸杞中差异代谢物共202种(上调148、下调54),负离子模式下检测出240种差异代谢物(上调183、下调57)。进一步通过KEGG富集,发现差异代谢物主要集中在次生代谢物、色氨酸、硫代葡萄糖苷、缬氨酸、异亮氨酸、亮氨酸以及黄酮类生物合成等途径。结果显示,黄果枸杞与红果枸杞相比,差异代谢物主要是黄酮、生物碱、酚酸类、氨基酸及其衍生物,且以上调为主,这可能与色氨酸代谢、缬氨酸、亮氨酸、异亮氨酸和黄酮类生物合成途径相关,这些代谢物与黄果枸杞的生长发育、抗病性及营养价值方面都具有相关性。本研究通过红果枸杞和黄果枸杞广泛靶向代谢组学分析,旨在为两种枸杞的营养价值提供参考,为后续枸杞相关产品加工提供理论基础。

     

    Abstract: In the pursuit of a comprehensive understanding of differential metabolites and metabolic pathways between red wolfberry (Lycium barbarum L.) and yellow wolfberry (Lycium barbarum L. var. auranticarpum K.F.Ching), an analytical approach integrating ultra-performance liquid chromatography with tandem high-resolution mass spectrometry was employed, alongside a broadly targeted metabolomics strategy. Through multivariate statistical methods such as principal component analysis, orthogonal partial least squares discriminant analysis, and cluster analysis, under the conditions of fold change ≥2 or ≤0.5, variable importance projection value ≥1, and P<0.05, 202 differential metabolites (148 up-regulated and 54 down-regulated) were detected in red and yellow wolfberries under positive ion mode. A total of 240 differential metabolites (183 up-regulated and 57 down-regulated) were detected in the negative ion mode. Subsequent KEGG pathway enrichment analysis revealed that these differential metabolites were predominantly associated with secondary metabolite, tryptophan, glucosinolate, valine, isoleucine, leucine, and flavonoid biosynthesis pathways. The data suggested that the differential metabolites in Lycium barbarum L. and Lycium barbarum L. var. auranticarpum K.F.Ching were predominantly flavonoids, alkaloids, phenolic acids, amino acids, and their derivatives, with a general trend of up-regulation. These metabolites might be linked to the growth, development, disease resistance, and nutritional value of Lycium barbarum L. var. auranticarpum K.F.Ching, potentially through their involvement in tryptophan metabolism and biosynthesis pathways for valine, leucine, isoleucine, and flavonoids. The objective of this study was to contribute to the existing knowledge base on the nutritional value of these two wolfberry species and to offer a theoretical foundation for the refinement of wolfberry-related products through extensive metabolomics profiling.

     

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