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Ai-Ping LI, Zhen-Yu LI, Ting-Li QU, Xue-Mei QIN, Guan-Hua DU. Nuclear magnetic resonance based metabolomic differentiation of different Astragali Radix[J]. Chinese Journal of Natural Medicines, 2017, 15(5): 363-374. DOI: 10.3724/SP.J.1009.2017.00363
Citation: Ai-Ping LI, Zhen-Yu LI, Ting-Li QU, Xue-Mei QIN, Guan-Hua DU. Nuclear magnetic resonance based metabolomic differentiation of different Astragali Radix[J]. Chinese Journal of Natural Medicines, 2017, 15(5): 363-374. DOI: 10.3724/SP.J.1009.2017.00363

Nuclear magnetic resonance based metabolomic differentiation of different Astragali Radix

  • Abstract: Astragali Radix (AR) is one of the most popular herbal medicines in traditional Chinese medicine (TCM). Wild AR is believed to be of high quality, and substitution with cultivated AR is frequently encountered in the market. In the present study, two types of ARs (wild and cultivated) from Astragalus membranaceus (Fisch.) Bge. and A. membranaceus var. mongholicus (Bge.) Hsiao, growing in different regions of China, were analyzed by NMR profiling coupled with multivariate analysis. Results showed that both could be differentiated successfully and cultivation patterns or growing years might have greater impact on the metabolite compositions than the variety; the metabolites responsible for the separation were identified. In addition, three extraction methods were compared and the method (M1) was used for further analysis. In M1, the extraction solvent composed of water, methanol, and chloroform in the ratio of 1:1:2 was used to obtain the aqueous methanol (upper layer) and chloroform (lower layer) fractions, respectively, showing the best separation. The differential metabolites among different methods were also revealed. Moreover, the sucrose/glucose ratio could be used as a simple index to differentiate wild and cultivated AR. Meanwhile, the changes of correlation pattern among the differential metabolites of the two varieties were found. The work demonstrated that NMR-based non-targeted profiling approach, combined with multivariate statistical analysis, can be used as a powerful tool for differentiating AR of different cultivation types or growing years.

     

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