UPLC/MS-based untargeted metabolomics reveals the changes of metabolites profile of Salvia miltiorrhiza bunge during Sweating processing

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作者
Mengyang Cao
Yingying Liu
Weimin Jiang
Xiaoxi Meng
Wei Zhang
Weidong Chen
Daiyin Peng
Shihai Xing
机构
[1] Anhui University of Chinese Medicine,College of Pharmacy
[2] Anhui Academy of Chinese Medicine,Institute of Traditional Chinese Medicine Resources Protection and Development
[3] Anhui University of Chinese Medicine,College of Humanities and International Education Exchange
[4] Hengyang Normal University,College of Life Sciences and Environment
[5] University of Minnesota,Department of Horticultural Science
[6] Synergetic Innovation Center of Anhui Authentic Chinese Medicine Quality Improvement,undefined
[7] Anhui Province Key Laboratory of Research and Development of Chinese Medicine,undefined
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摘要
Salvia miltiorrhiza has numerous compounds with extensive clinical application. “Sweating”, a processing method of Traditional Chinese Medicine (TCM), results in great changes in pharmacology and pharmacodynamics. Previously, chromatogram of 10 characteristic metabolites in S. miltiorrhiza showed a significant difference after “Sweating”. Due to the complexity of TCM, changes in metabolites should be investigated metabolome-wide after “Sweating”. An untargeted UPLC/MS-based metabolomics was performed to discover metabolites profile variation of S. miltiorrhiza after “Sweating”. Multivariate analysis was conducted to screen differential metabolites. Analysis indicated distinct differences between sweated and non-sweated samples. 10,108 substance peaks had been detected altogether, and 4759 metabolites had been identified from negative and positive ion model. 287 differential metabolites were screened including 112 up-regulated and 175 down-regulated and they belong to lipids and lipid-like molecules, and phenylpropanoid and polyketides. KEGG analysis showed the pathway of linoleic acid metabolism, and glyoxylate and dicarboxylate metabolism were mainly enriched. 31 and 49 identified metabolites were exclusively detected in SSM and NSSM, respectively, which mainly belong to carboxylic acids and derivatives, polyketides and fatty acyls. By mapping tanshinones and salvianolic acids to 4759 identified metabolites library, 23 characteristic metabolites had been identified, among which 11 metabolites changed most. We conclude that “Sweating’’ has significant effect on metabolites content and composition of S. miltiorrhiza.
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