OBJECTIVE: To compare the metabolite profile of Chrysanthemum morifolium flower fraction with that of its detannified fraction in relation to XO inhibitory activity using a rapid and effective metabolomics approach.
METHODS: Proton nuclear magnetic resonance (1 H-NMR)-based metabolomics approach coupled with multivariate data analysis was utilised to characterise the XO inhibitors related to the antioxidant properties, total phenolic, and total flavonoid contents of the C. morifolium dried flowers.
RESULTS: The highest XO inhibitory activity, 1,1-diphenyl-2-picryl hydrazyl (DPPH) radical scavenging activity, total phenolic and flavonoid content with strong positive correlation between them were observed in the ethyl acetate (EtOAc) fraction. Detannified EtOAc showed higher XO inhibitory activity than non-detannified EtOAc fraction. A total of 17 metabolites were tentatively identified, of which three namely kaempferol, 4-hydroxybenzoic acid and apigenin, could be suggested to be responsible for the strong XO inhibitory activity. Additive interaction between 4-hydroxybenzoic acid and apigenin (or kaempferol) in XO inhibition was demonstrated in the interaction assay conducted.
CONCLUSION: Chrysanthemum morifolium dried flower-part could be further explored as a natural XO inhibitor for its anti-hyperuricemic potential. Metabolomics approach served as an effective classification of plant metabolites responsible for XO inhibitory activity, and demonstrated that multiple active compounds can work additively in giving combined inhibitory effects.
Methods: Proton nuclear magnetic resonance spectroscopy (1H NMR)-based metabolomics approach was used to investigate fecal and serum metabolome of rat model of IBS-D with and without HPM treatment.
Results: The current results showed that IBS-induced metabolic alterations in fecal and serum sample include higher level of threonine and UDP-glucose together with lower levels of aspartate, ornithine, leucine, isoleucine, proline, 2-hydroxy butyrate, valine, lactate, ethanol, arginine, 2-oxoisovalerate and bile acids. These altered metabolites potentially involve in impaired gut secretory immune system and intestinal inflammation, malabsorption of nutrients, and disordered metabolism of bile acids. Notably, the HPM treatment was found able to normalize the Bristol stool forms scale scores, fecal water content, plasma endotoxin level, and a number of IBS-induced metabolic changes.
Conclusions: These findings may provide useful insight into the molecular basis of IBS and mechanism of the HPM intervention.
METHODS: The N. oleracea fractions were obtained using solid phase extraction (SPE). A metabolomics approach that coupled the use of proton nuclear magnetic resonance (1H NMR) with multivariate data analysis (MVDA) was applied to distinguish the metabolite variations among the N. oleracea fractions, as well as to assess the correlation between metabolite variation and the studied bioactivities (DPPH free radical scavenging and α-glucosidase inhibitory activities). The bioactive fractions were then subjected to ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) analysis to profile and identify the potential bioactive constituents.
RESULTS: The principal component analysis (PCA) discriminated EF and MF from the other fractions with the higher distributions of phenolics. Partial least squares (PLS) analysis revealed a strong correlation between the phenolics and the studied bioactivities in the EF and the MF. The UHPLC-MS/MS profiling of EF and MF had tentatively identified the phenolics present. Together with some non-phenolic metabolites, a total of 37 metabolites were tentatively assigned.
CONCLUSIONS: The findings of this work supported that N. oleracea is a rich source of phenolics that can be potential antioxidants and α-glucosidase inhibitors for the management of diabetes. To our knowledge, this study is the first report on the metabolite-bioactivity correlation and UHPLC-MS/MS analysis of N. oleracea fractions.
RESULTS: Comparison of the PLS and RF showed that RF exhibited poorer generalization and hence poorer predictive performance. Both the regression coefficient of PLS and the variable importance of RF revealed that quercetin and kaempferol derivatives, caffeic acid and vitexin-2-O-rhamnoside were significant towards the tested bioactivities. Furthermore, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) results showed that sonication and absolute ethanol are the preferable extraction method and ethanol ratio, respectively, to produce N. oleracea extracts with high phenolic levels and therefore high DPPH scavenging and α-glucosidase inhibitory activities.
CONCLUSION: Both PLS and RF are useful regression models in metabolomics studies. This work provides insight into the performance of different multivariate data analysis tools and the effects of different extraction conditions on the extraction of desired phenolics from plants. © 2017 Society of Chemical Industry.