Nontargeted metabolomic analysis and multiple criteria decision-making method induced robust quality markers screening for the authentication of herbal medicines from different origins by taking Ophiopogon japonicus (L. f.) Ker-Gawl. as a case study

Metabolomics analysis of Ligustri Lucidi Fructus at different harvest times during the whole growing period based on ultra-high-performance liquid chromatography with mass spectrometry

After medicinal market research, it was found that the harvest time of Ligustri Lucidi Fructus (LLF) was chaotic in practice. In order to determine the optimal harvest period of LLF to ensure its pharmacological activity, metabolomics analysis of LLF at different harvest times based on ultra-high-performance liquid chromatography-triple quadrupole-(linear ion trap)-tandem mass spectrometry was established. In this study, 166 differential metabolites (DMs) in 448 metabolites at different harvest times were screened out based on variable importance in projection value, and among them, 94 DMs with regular trends of change in relative content (59 increased and 35 decreased with the growth period) were chosen to further research. The result of the multivariate statistical analysis showed that November was the optimal harvest period of LLF. Additionally, 10-hydroxyligustroside, oleoside 11-methyl ester, and salidroside were screened out to be used as the evaluation indicators of immature LLF, while specnuezhenide, nuezhenoside G13, and neonuezhenide were the evaluation indicators of mature LLF. This study provides fundamental insight for metabolite identification and proposes the best harvest period of LLF to avoid confusion in the medicinal market.

Characterization and Discrimination of Ophiopogonis Radix with Different Levels of Sulfur Fumigation Based on UPLC-QTOF-MS Combined Molecular Networking with Multivariate Statistical Analysis

Ophiopogonis Radix, also known as "Maidong" (MD) in China, is frequently sulfur-fumigated (SF) in the pretreatment process of MD to improve the appearance and facilitate preservation. However, the process leads to changes in chemical composition, so it is essential to develop an approach to identify the chemical characteristics between nonfumigated and sulfur-fumigated products. This paper provided a practical method based on UPLC-QTOF-MS combined Global Natural Products Social Molecular Networking (GNPS) with multivariate statistical analysis for the characterization and discrimination of MD with different levels of sulfur fumigation, high concentration sulfur fumigation (HS), low concentration sulfur fumigation (LS) and without sulfur fumigation (WS). First, a number of 98 compounds were identified in those MD samples. Additionally, the results of Principal component analysis (PCA) and Orthogonal partial least-squares-discriminant analysis (OPLS-DA) demonstrated that there were significant chemical differences in the chemical composition of MD with different degrees of SF. Finally, fourteen and sixteen chemical markers were identified upon the comparison between HS and WS, LS and WS, respectively. Overall, these results can be able to discriminate MD with different levels of SF as well as establish a solid foundation for further quality control and pharmacological research.

Discovery of Quality Markers of Nucleobases, Nucleosides, Nucleotides and Amino Acids for Chrysanthemi Flos From Different Geographical Origins Using UPLC-MS/MS Combined With Multivariate Statistical Analysis

Nucleobases, nucleosides, nucleotides and amino acids, as crucial nutrient compositions, play essential roles in determining the flavor, function and quality of Chrysanthemi Flos. The quality of Chrysanthemi Flos from different geographical origins is uneven, but there have been no reports about the screening of their quality markers based on nutritional ingredients. Here, we developed a comprehensive strategy integrating ultra performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry (UPLC-MS/MS) and multivariate statistical analysis to explore quality markers of Chrysanthemi Flos from different geographical origins and conduct quality evaluation and discrimination of them. Firstly, a fast, sensitive, and reliable UPLC-MS/MS method was established for simultaneous quantification 28 nucleobases, nucleosides, nucleotides and amino acids of Chrysanthemi Flos from nine different regions in China. The results demonstrated that Chrysanthemi Flos from nine different cultivation regions were rich in the above 28 nutritional contents and their contents were obvious different; however, correlation analysis showed that altitude was not the main factor for these differences, which required further investigation. Subsequently, eight crucial quality markers for nine different geographical origins of Chrysanthemi Flos, namely, 2'-deoxyadenosine, guanosine, adenosine 3',5'-cyclic phosphate (cAMP), guanosine 3',5'-cyclic monophosphate (cGMP), arginine, proline, glutamate and tryptophan, were screened for the first time using partial least squares discriminant analysis (PLS-DA) and the plot of variable importance for projection (VIP). Moreover, a hierarchical clustering analysis heat map was employed to intuitively clarify the distribution of eight quality markers in the nine different regions of Chrysanthemi Flos. Finally, based on the contents of selected eight quality markers, support vector machines (SVM) model was established to predict the geographical origins of Chrysanthemi Flos, which yielded excellent prediction performance with an average prediction accuracy of 100%. Taken together, the proposed strategy was suitable to discover the quality markers of Chrysanthemi Flos and could be used to discriminate its geographical origin.

Discovery and validation of quality markers of Fructus Aurantii against acetylcholinesterase using metabolomics and bioactivity assays

Fructus Aurantii is a traditional medicated diet in East Asia. To determine the underlying chemical markers responsible for the quality and efficacy of Fructus Aurantii, a sensitive metabolomic method was applied to distinguish Fructus Aurantii in Jiangxi Province from other two geographical locations (Hunan Province and Chongqing City) in China. In the present study, multivariate analyses were adopted to compare chemical compositions in 21 batches of Fructus Aurantii samples. Among three geographical origins, 23 differential compounds were structurally identified. Serum pharmacochemistry exhibited that 22 components could be detected in rat serum. Six differential and absorbed components were selected as six potential markers. Statistical analysis revealed that the content of six markers varied widely in three origins of Fructus Aurantii. Six differential and absorbed components were evaluated further by biological activity. Neohesperidin, naringin, and meranzin showed inhibitory effect on acetylcholinesterase that regulates gastrointestinal motility in vitro and in silico, suggesting that these three components may be determined as the active biomarkers of Fructus Aurantii. These findings demonstrate the potential of biomarkers for identification and quality control of Fructus Aurantii.