METHODS: Liquid-liquid partition chromatography was used to separate methanolic extract to get hexane, ethyl acetate, butanol and residual aqueous fractions. The total antioxidant activity was determined by 2,2-diphenyl-1-picrylhydrazy (DPPH) radical scavenging and ferric reducing antioxidant power assay (FRAP). The antidiabetic activity of methanol extract and its consequent fractions were examined by α-glucosidase inhibitory bioassay. The chemical profiling was carried out by gas chromatography coupled with quadrupole time-of-flight mass spectrometry (GC Q-TOF MS).
RESULTS: The total yield for methanol extraction was (12.63 ± 0.98) % (w/w) and highest fractionated value found for residual aqueous (52.25 ± 1.01) % (w/w) as compared to the other fractions. Significant DPPH free radical scavenging activity was found for methanolic extract (63.07 ± 0.11) % and (79.98 ± 0.31) % for ethyl acetate fraction among all the fractions evaluated. Methanol extract was the most prominent in case of FRAP (141.89 ± 0.87 μg AAE/g) whereas most effective reducing power observed in ethyl acetate fraction (133.6 ± 0.2987 μg AAE/g). The results also indicated a substantial α-glucosidase inhibitory activity for butanol fraction (72.16 ± 1.0) % and ethyl acetate fraction (70.76 ± 0.49) %. The statistical analysis revealed that total phenolic and total flavonoid content of the samples had the significant (p
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.