Chemical and biological evaluations of pegaga (Centella asiatica (L.) Urb., Hydrocotyle bonariensis Comm. ex Lam. and Hydrocotyle sibthorpioides Lam.) extracts and their effects on an obese diabetic rat model using 1H NMR metabolomics

Pegaga is one of the important medicinal herbs in Malay culture. The herb comprises of several known varieties which raises the inevitable possibility of large variations with respect to their metabolites and bioactivities. Therefore, to ensure safety and efficacy of products derived from the herb, proper quality control and standardization (e.g. authentication via the use of marker compounds and consistent bioactivities) are necessary. Thus, the metabolites of three species of Pegaga, viz Centella asiatica, Hydrocotyle bonariensis and H. sibthorpioides, were analyzed using 1H NMR-based metabolomics approach. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) resolved the three species into separate clusters, wherein, saponins such as asiaticoside and madecassoside, along with chlorogenic acids were the metabolites contributing most to the separation. Identification of these components was supported by LCMS/MS data and by comparison with literature data. In addition, the metabolite contents of Pegaga grown under different light conditions were also investigated. The extracts of C. asiatica grown under full exposure to sunlight exhibited stronger radical scavenging activity and contained higher amounts of triterpenes (asiaticoside and madecassoside), flavonoids, and chlorogenic acids as compared to plants grown under 50% shade. The three Pegaga species were further investigated for their DPPH free radical scavenging activity. The combined bioactivity and 1H-NMR data of the plant samples were subjected to multivariate data analysis to find possible correlations. The use of PLS, a linear method in modelling, was compared to that of artificial neural network (ANN), a non-linear method. The result showed that both were good models for the prediction of IC50 values of the extracts. However, on the overall, the PLS model is comparatively more appropriate for the prediction of free radical scavenging activity of Pegaga varieties. Better prediction was achieved for extracts at higher concentration in both models. The loading scatter plot for the PLS analysis revealed that caffeoylquinic acid derivatives, kaempferol and quercetin were responsible for the bioactivity. Further statistical analysis using ANOVA showed that C. asiatica variety 3 (extract E) gave the most potent radical scavenging activity among the extracts. This metabolomic technique could be beneficial for the standardization of C. asiatica extract that possess radical scavenging activity. As an extension to our research interests, this study also reported the application of 1H-NMR-based metabolomics in the detection of physiological changes in the urine and serum samples of obese-diabetic (obdb) Sprague-dawley rats treated with standardized C.asiatica and H. bonariensis extracts. This model mimics the symptoms in Type 2 diabetes. After one month of treatment with 300 mg/kg body weight of C. asiatica and H. bonariensis extracts, results showed that the glucose level was decreased by 19.3% after the obdb rats were treated with C. asiatica (300 mg/kg), while treatment with H. bonariensis extracts did not show a similar decrease in glucose levels. Detailed analysis of the altered metabolites using mean peak height of 1H-NMR signals revealed that the administration of C. asiatica extract to the obdb animal model improved glucose metabolism, creatine metabolism, lipid metabolism, tricarboxylic acid cycle, amino acid metabolism, trimethylamine metabolism, and purine metabolism. 1H NMR-based metabolomics has been successfully applied in the chemical and biological evaluations of Pegaga extracts. The results of this metabolomics study will be useful in establishing standards for phytomedicinal preparations.

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