[Identification of chemical components in Qinggu San reference sample of classial prescription based on UHPLC-Q/Orbitrap HRMS combined with molecular network technology].

The method of ultra-high performance liquid chromatography-quadrupole-electrostatic field orbitrap high-resolution mass spectrometry(UHPLC-Q/Orbitrap HRMS)combined with molecular network was developed in this study for rapidly analyzing the chemical components of the Qinggu San reference sample of classical prescription. Firstly, an ACQUITY UPLC BEH Shield RP_(18) column(2.1 mm×100 mm, 1.7 µm)was used, and acetonitrile and 0.1% formic acid were taken as the mobile phases for gradient elution. The flow rate was 0.4 mL·min~(-1), and the column temperature was 30 ℃. Under these conditions, the mass spectrum data were collected in both positive and negative ion modes of the heated electrospray ionization source. Subsequently, the mass spectrum data of the Qinggu San reference sample were uploaded to the Global Natural Products Social Molecular Network(GNPS)platform for calculation and analysis, and a visual molecular network was built with Cytoscape 3.8.2 software. On this basis, the chemical components of the Qinggu San reference sample were identified by fragmentation regularity of standard compounds, retention time, accurate relative molecular weight of HR-MS, characteristic fragment ions information, literature, and databases. Finally, a total of 105 chemical components were identified and speculated in the Qinggu San reference sample, including 19 iridoid glycosides, 23 flavonoids, 15 phenylpropanoids, 11 triterpene saponins, and 37 other components. Meanwhile, two of these components are potential new compounds. The method used in this study not only achieved rapid and accurate identification of chemical components in the Qinggu San reference sample and provided a scie-ntific basis for the study of pharmacological substances and quality control of Qinggu San compound preparations but also provided a refe-rence for the rapid identification of chemical components in traditional Chinese medicine compound preparations.

[Monoterpenoids from Paeoniae Radix Rubra based on UPLC-Q-TOF-MS].

The ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry(UPLC-Q-TOF-MS) was used to conduct the qualitative analysis of the monoterpene chemical components from Paeoniae Radix Rubra. Gradient elution was performed on C_(18) HD(2.1 mm×100 mm, 2.5 µm) column with a mobile phase of 0.1% formic acid(A) and acetonitrile(B). The flow rate was 0.4 mL·min~(-1) and the column temperature was 30 ℃. MS analysis was conducted in both positive and negative ionization modes using electrospray ionization(ESI) source. Qualitative Analysis 10.0 was used for data processing. The identification of chemical components was realized by the combination of standard compounds, fragmentation patterns, and mass spectra data reported in the literature. Forty-one monoterpenoids in Paeoniae Radix Rubra extract were identified. Among them, 8 compounds were reported in Paeoniae Radix Rubra for the first time and 1 was presumed to be the new compound 5″-O-methyl-galloylpaeoniflorin or its positional isomer. The method in this study realizes the rapid identification of monoterpenoids from Paeoniae Radix Rubra and provides a material and scientific basis for quality control and further study on the pharmaceutical effect of Paeoniae Radix Rubra.

[Investigation of modulating effect of Qingfei Paidu Decoction on host metabolism and gut microbiome in rats].

This study is to explore the effect of Qingfei Paidu Decoction(QPD) on the host metabolism and gut microbiome of rats with metabolomics and 16 S rDNA sequencing. Based on 16 S rDNA sequencing of gut microbiome and metabolomics(GC-MS and LC-MS/MS), we systematically studied the serum metabolites profile and gut microbiota composition of rats treated with QPD for continued 5 days by oral gavage. A total of 23 and 43 differential metabolites were identified based on QPD with GC-MS and LC-MS/MS, respectively. The involved metabolic pathways of these differential metabolites included glycerophospholipid metabolism, linoleic acid metabolism, TCA cycle and pyruvate metabolism. Meanwhile, we found that QPD significantly regulated the composition of gut microbiota in rats, such as enriched Romboutsia, Turicibacter, and Clostridium_sensu_stricto_1, and decreased norank_f_Lachnospiraceae. Our current study indicated that short-term intervention of QPD could significantly regulate the host metabolism and gut microbiota composition of rats dose-dependently, suggesting that the clinical efficacy of QPD may be related with the regulation on host metabolism and gut microbiome.