4.7 Article

Metabolomics Study of Different Germplasm Resources for Three Polygonatum Species Using UPLC-Q-TOF-MS/MS

期刊

FRONTIERS IN PLANT SCIENCE
卷 13, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fpls.2022.826902

关键词

Polygonatum; species discrimination; metabolomics; UPLC-Q-TOF-MS; MS; iconic metabolites

资金

  1. National Natural Science Foundation of China [31670299]
  2. National Key Technologies RAMP
  3. D Program for Modernization of Traditional Chinese Medicine [2019YFC1712600, 2017YFC1701300, 2017YFC1700706]
  4. Fundamental Research Funds for the Central Universities [GK202103065, GK201806006]
  5. Shaanxi Provincial Key RD Program [2021SF-383, 2021SF-389, 2020LSFP2-21, 2018FP2-26]
  6. Xi'an Science and Technology Project [20NYYF0057]
  7. Research Project on Postgraduate Education and Teaching Reform of Shaanxi Normal University [GERP-20-41]

向作者/读者索取更多资源

This study employed UPLC-Q-TOF-MS/MS based metabolomics for the first time to discriminate between three Polygonatum species, and identified key compounds suitable for their identification. The results showed that adenosine, sucrose, and pyroglutamic acid can be used to distinguish different Polygonatum species.
Rhizomes of the Polygonatum species are well-known in traditional Chinese medicine. The 2020 edition of Chinese Pharmacopoeia includes three different species that possess different pharmacological effects. Due to the lack of standardized discriminant compounds there has often been inadvertently incorrect prescriptions given for these medicines, resulting in serious consequences. Therefore, it is critical to accurately distinguish these herbal Polygonatum species. For this study, UPLC-Q-TOF-MS/MS based metabolomics was employed for the first time to discriminate between three Polygonatum species. Partial least squares discriminant analysis (PLS-DA) models were utilized to select the potential candidate discriminant compounds, after which MS/MS fragmentation patterns were used to identify them. Meanwhile, metabolic correlations were identified using the R language package corrplot, and the distribution of various metabolites was analyzed by box plot and the Z-score graph. As a result, we found that adenosine, sucrose, and pyroglutamic acid were suitable for the identification of different Polygonatum species. In conclusion, this study articulates how various herbal Polygonatum species might be more accurately and efficiently distinguished.

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