Chemical Constituents, Antioxidant, and α-Glucosidase Inhibitory Activities of Different Fermented Gynostemma Pentaphyllum Leaves and Untargeted Metabolomic Measurement of the Metabolite Variation

Abstract

To assess the effects of microbial fermentation on Gynostemma pentaphyllum leaves (GPL), four probiotics were used to ferment GPL (FGPL) for 7 days. At different stages of fermentation, changes in the active components and biological activities of FGPL were determined. The findings suggest that short-term fermentation with probiotics can enhance both the content and bioactivity of active components in GPL. However, prolonged fermentation may lead to a decline in these aspects. Among them, the best effect was observed with SWFU D16 fermentation for 2 days. This significantly improved the total phenolic and total flavonoid content, antioxidant capacity, and inhibitory ability against α-glucosidase activity with an increase of 28%, 114.82%, 7.42%, and 31.8%, respectively. The high-performance liquid chromatography (HPLC) analysis results also supported this trend. Untargeted metabolomics analysis revealed metabolite changes between GPL and FGPL and the key metabolites associated with these functional activities. These key metabolites are mainly organic acids, flavonoids, carbohydrates, terpenoids, and other substances. KEGG analysis demonstrated that microbial metabolism in diverse environments and carbon metabolism were the most significantly enriched pathways. Among them, 3-(3-hydroxyphenyl) propanoic acid, d-glucose, gallic acid, gluconic acid, l-lactic acid, and l-malic acid were mostly involved in the microbial metabolism of diverse environmental pathways. In contrast, D-glucose, gluconic acid, and l-malic acid were mainly related to the carbon metabolism pathway. This study revealed the positive effect of probiotic fermentation on GPL and its potential metabolism mechanism, which could provide supporting data for further research.

Keywords: Gynostemma pentaphyllum leaves; antioxidant capacity; metabolomics; probiotic fermentation; α-glucosidase inhibitory activity.

Figure 1

Changes in the pH value, total phenolic content (TPC), total flavonoid content (TFC), DPPH· scavenging capacities, ABTS·⁺ scavenging capacities, ferric reducing antioxidant power (FRAP), and α-glucosidase inhibitory capacity of GPL at different fermentation stages with different probiotics. (a1–a4) Changes in the pH value; (b1–b4) Changes in the TPC; (c1–c4) Changes in the TFC; (d1–d4) Changes in DPPH· scavenging capacity; (e1–e4) Changes in ABTS·⁺ scavenging capacity; (f1–f4) Changes in FRAP; (g1–g4) Changes in the α-glucosidase inhibitory capacity of GPL during probiotic fermentation; the labels (a1–g4) represent the identification numbers of each indicator chart, and the following numbers 1, 2, 3, and 4 correspond to the following strains: (1) ATCC 8014 (L. plantarum), (2) ATCC 334 (L. casei), (3) SWFU D16 (L. plantarum), and (4) ATCC 53013 (L. rhamnosus). The symbols “a, b, c, d, ab, cd, et al.” at the top of the bar graph represent the significance analysis of each index during the fermentation process.

Figure 2

Associations among different indicators. (A) Correlation heatmap. (B) Correlation network. (C) Principal component analysis, the numbers 1, 2, and 3 represent the three replicates of the sample. TPC = total phenolic content; TFC = total flavonoid content; DPPH = DPPH·scavenging capacity; ABTS = ABTS·⁺ scavenging capacity; FRAP = ferric reducing antioxidant power; α-Glucosidase = α-glucosidase inhibition capacity.

Figure 3

HPLC chromatogram of the FGPL. 1—gallic acid, 2—catechin, 3—chlorogenic acid, 4—epicatechin, 5—dihydromyricetin and 6—epicatechin gallate. (A) Liquid chromatogram of FGPL fermentation broth of different strains at 280 nm. (B) Liquid chromatography of FGPL SWFU D16 fermentation broth at 280 nm at different fermentation stages. (C) Liquid chromatogram of FGPL ATCC 334 fermentation broth at 280 nm at different fermentation stages.

Figure 4

BPC of GPL and FGPL in the positive (A,C) and negative (B,D) ion modes. Mean ± standard deviation (n = 3). The schematic diagram of the different classifications of the metabolites of FGPL (E,F). PCA, volcano plots, and a heat map showed the metabolite changes in GPL and FGPL. (G) Score plot in positive ion mode. (H) Score plot in negative ion mode. (I) Volcano plot in positive ion mode. (J) Volcano plot in negative ion mode. The blue dots represent significantly downregulated and differentially expressed metabolites. The red dots represent significantly upregulated and differentially expressed metabolites. Significant metabolite differences between groups were determined by p < 0.05 and an absolute fold change ≥ 1. (K) Heat map in positive ion mode. (L) Heat map in negative ion mode. Each sample is represented by one column, and each metabolite is visualized in one row. Red indicates high abundance; blue indicates relatively low metabolite abundance.

Figure 5

Spearman’s analysis and associated network diagram show the correlation between metabolites and five functional activities. (A,B) Spearman’s analysis of FGPL in the positive and negative ion modes. (C,D) Associated networks of FGPL in positive and negative ion modes (a–h). Asterisks represent p < 0.05 *, p ≤ 0.01 **, respectively. The gray line represents a negative correlation, and the yellow line represents a positive correlation. (E) KEGG pathway network diagram. The orange elliptical nodes represent pathways, and the green elliptical nodes represent metabolites.