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
RESULTS: For PTG, triacylglycerol oligomers and dimers showed a significant increase (P
AIM OF THE STUDY: As allergy could be mediated by both IgE and IgG, we further evaluated the anti-allergy potential of CNAE in both in vitro model of IgG-induced macrophage activation and in vivo anaphylaxis models to further dissect the mechanism of action underlying the anti-allergic properties of CNAE.
MATERIAL & METHODS: The anti-allergy potential of CNAE was evaluated in in vivo anaphylaxis models of ovalbumin-challenged active systemic anaphylaxis (OVA-ASA) and IgE-challenged passive systemic anaphylaxis (PSA) using Sprague Dawley rats as well as IgG-challenged passive systemic anaphylaxis (IgG-PSA) using C57BL/6 mice. Meanwhile, in vitro model of IgG-induced macrophage activation model was performed using IC-21 macrophages. The release of soluble mediators from both IgE and IgG-mediated pathways were measured using enzyme-linked immunosorbent assay (ELISA). The signaling molecules targeted by CNAE were identified by performing Western blot.
RESULTS: IgG, platelet-activating factor (PAF) and IL-6 was suppressed by CNAE in OVA-ASA, but not IgE. In addition, CNAE significantly suppressed PAF and IL-6 in IgG-PSA but did not suppress histamine, IL-4 and leukotrienes C4 (LTC4) in IgE-PSA. CNAE also inhibited IL-6 and TNF-α by inhibiting the phosphorylation of ERK1/2 in the IgG-induced macrophage activation model.
CONCLUSION: Overall, our findings supported that CNAE exerts its anti-allergic properties by suppressing the IgG pathway and its mediators by inhibiting ERK1/2 phosphorylation, thus providing scientific evidence supporting its traditional use in managing allergy.
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.