OBJECTIVE: This study investigated the metabolite variations in A. elliptica leaves and the correlation with antioxidant activities.
METHODOLOGY: Total phenolic content (TPC), 2,2-diphenyl-1-picrylhydrazyl (DPPH) and nitric oxide (NO) radicals scavenging assays were performed on A. elliptica leaves extracted with four different ethanol ratios (0%, 50%, 70% and absolute ethanol). The correlation of metabolites with antioxidant activities was evaluated using a nuclear magnetic resonance (NMR)-based metabolomics approach.
RESULTS: The results showed that the 50% and 70% ethanolic extracts retained the highest TPC, and the 70% ethanolic extract was the most active, exhibiting half maximal inhibitory concentration (IC50 ) values of 10.18 ± 0.83 and 43.05 ± 1.69 μg/mL, respectively, in both radical scavenging assays. A total of 46 metabolites were tentatively identified, including flavonoids, benzoquinones, triterpenes and phenolic derivatives. The 50% and 70% ethanolic extracts showed similarities in metabolites content and were well discriminated from water and absolute ethanol extracts in a principal component analysis (PCA) model. Moreover, 31 metabolites were found to contribute significantly to the differentiation and antioxidant activity.
CONCLUSION: This study provides information on bioactive compounds in A. elliptica leaves, which is promising as a functional ingredient for food production or for the development of phytomedicinal products.
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.
OBJECTIVE: Evaluate the relationship between the chemical composition of C. nutans and its anti-inflammatory properties using nuclear magnetic resonance (NMR) metabolomics approach.
METHODOLOGY: The anti-inflammatory effect of C. nutans air-dried leaves extracted using five different binary extraction solvent ratio and two extraction methods was determined based on their nitric oxide (NO) inhibition effect in lipopolysaccharide-interferon-gamma (LPS-IFN-γ) activated RAW 264.7 macrophages. The relationship between extract bioactivity and metabolite profiles and quantifications were established using 1 H-NMR metabolomics and liquid chromatography-tandem mass spectrometry (LC-MS/MS). The possible metabolite biosynthesis pathway was constructed to further strengthen the findings.
RESULTS: Water and sonication prepared air-dried leaves possessed the highest NO inhibition activity (IC50 = 190.43 ± 12.26 μg/mL, P