Lupinus albus or white lupine has recently received increase attention for its medicinal values. Several studies have described the hypoglycemic effect of the white lupine, which is known as a food plant with potential value for treatment of diabetes. This study provides useful information for the identification and quantification of compounds in L. albus fractions by proton nuclear magnetic resonance (1H NMR) spectroscopy. In total, 35 metabolites were identified from L. albus fractions.Principal component analysis (PCA) was used as a multivariate projection method for visualizing the different composition of four different fractions. The bioactivities of fractions with different polarity obtained from the extract of L. albus seeds are reported. Among the fractions studied, the chloroform fraction (CF) exhibits a high free radical scavenging (DPPH) and α-glucosidase inhibitory activities with IC50 values of 24.08 and 20.08 μg/mL, respectively. A partial least-squares analyses (PLS) model had been successfully performed to correlate the potential active metabolites with the corresponding biological activities. Metabolites containing proline, caprate, asparagine, lupinoisolone C, hydroxyiso lupalbigenin and some unknown compounds show high correlation with the bioactivities studied. Moreover, the structural identification in the active fraction was supported by ultrahigh-performance-liquid chromatography-electrospray ionization tandem mass spectrometry (UHPLC-ESI-MS/MS) analysis. A total of 21 metabolites were tentatively identified from MS/MS data by comparison with previously reported data. Most of these compounds are isoflavonoids without known biological activity. This information may be useful for developing functional food from L. albus with potential application in the management of diabetes.
Claims of effective therapy against diabetes using plants including Peganum harmala L., Zygophyllum album, Anacyclus valentinus L., Ammodaucus leucotrichus, Lupinus albus, and Marrubium vulgare in Algerian empirical medicine prompted our interest in evaluating their antidiabetic activity by screening their free radical scavenging (DPPH), α-glucosidase, and nitric oxide (NO) inhibitory activities as well as the total phenolic content (TPC). Extracts of the selected plants were prepared using different ratios of ethanol (0, 50, 80, and 100%). In this study, 100%, and 80% ethanol extracts of L. albus were found to be the most potent, in inhibiting α-glucosidase activity with IC50 values of 6.45 and 8.66 μg/mL, respectively. The 100% ethanol extract of A. leucotrichus exhibited the highest free radical scavenging activity with an IC50 value of 26.26 μg/mL. Moreover, the highest TPC of 612.84 μg GAE/mg extract was observed in M. vulgare, extracted with 80% ethanol. Metabolite profiling of the active extract was conducted using 1H-NMR metabolomics. Partial least square analysis (PLS) was used to assess the relationship between the α-glucosidase inhibitory activity of L. albus and the metabolites identified in the extract. Based on the PLS model, isoflavonoids (lupinoisoflavone G, lupisoflavone, lupinoisolone C), amino acids (asparagine and thiamine), and several fatty acids (stearic acid and oleic acid) were identified as metabolites that contributed to the inhibition of α-glucosidase activity. The results of this study have clearly strengthened the traditional claim of the antihyperglycemic effects of L. albus.
Tea is one of the world's most popular beverages, with several health benefits. Polyphenols are the predominant constituents to account for its health benefits. Despite the well-known benefits of tea on health, the uniqueness of its aroma, taste, and features is an added value that contribute to the increased popularity of this beverage worldwide, and they are associated with the alterations in the metabolites during tea processing and cultivation. The manufacturing of tea consists of several stages with various processes as withering, fixing, rolling, fermentation and drying. The classification into tea types is according to such processing. The high-quality production of the various tea classes also depends on agricultural conditions, such as shading, plucking, climate, and soil composition. Metabolomics is well recognized as an effective tool for evaluating the quality of tea products. Applications in controlling the quality of tea products and adulterant detection are discussed in this review.