Green Radish Polysaccharide Prevents Alcoholic Liver Injury by Interfering with Intestinal Bacteria and Short-Chain Fatty Acids in Mice

Abstract

This study aimed to ascertain the potential benefits of green radish polysaccharide (GRP) in treating alcoholic liver disease (ALD) in mice and explore its mechanism of action. Using biochemical analysis, high-throughput sequencing of gut microbiota, and gas chromatography-mass spectrometry to measure short-chain fatty acids (SCFAs) in feces, we found that GRP intervention significantly improved lipid metabolism and hepatic function in mice subjected to excessive alcohol intake. The GRP intervention reduced malondialdehyde levels by 66% and increased total superoxide dismutase levels by 22%, thereby mitigating alcohol-induced oxidative stress. Furthermore, GRP intervention in mice with alcohol consumption resulted in a reduction in tumor necrosis factor, interleukin 6, and lipopolysaccharide levels by 12%, 9%, and 25%, respectively, effectively attenuating alcoholic liver inflammation. 16S rRNA amplicon sequencing demonstrated that excessive alcohol consumption markedly altered the gut microbiota composition in mice. The GRP treatment resulted in a significant reduction in the number of beneficial bacteria (Lactobacillus and Lachnospiraceae_NK4A136_group) and an increase in the proportion of harmful bacteria (Muribaculaceae and Verrucomicrobiota). The metabolomic analyses of the SCFAs demonstrated an increase in the contents of SCFAs, acetic acid, propionic acid, and butyric acid, following GRP supplementation. Furthermore, the metabolic levels of cholinergic synapses and glycolysis/gluconeogenesis were found to be modulated. In conclusion, these findings suggest that GRP may attenuate alcohol-induced oxidative damage in the liver by modulating the gut microbiota and hepatic metabolic pathways. This may position GRP as a potential functional component for ALD prevention.

Keywords: alcoholic liver disease; green radish; gut microbiota; polysaccharide; short-chain fatty acid metabolism.

Figure 1

GRP did not affect body weight in alcohol-induced mice but decreased alcohol-induced organ index: (A) representative weights; (B) organ index. The results are expressed as the mean ± SD (n = 6–8). * p < 0.05 and ** p < 0.01.

Figure 2

Effects of GRP on serum biochemical indices and histopathology. (A–C) Representative images of hematoxylin and eosin (H&E) staining of liver tissues. The images are shown at a 20× zoom level; the ratio was 100 μm. (D–G) The levels of TC, TG, ALT, and AST in serum were measured, and the results are expressed as the mean ± SD (n = 6–8). ** p < 0.01.

Figure 3

The levels of T-SOD, GSH-Px, MDA, CAT, TNF-α, LPS, and IL-6 in the liver tissues of each group were measured (A–G), and the results are expressed as the mean ± SD (n = 6–8). * p < 0.05 and ** p < 0.01.

Figure 4

GRP altered gut microbial composition and diversity in alcohol-induced mice: (A) Shannon index; (B) Chao1 index; (C) Venn diagram; (D) PCA diagram.

Figure 5

GRP altered the composition of the gut microbiota in alcohol-administered mice: (A) average relative abundance of each group at the gate level; (B) average relative abundance (n = 6) for each genus level.

Figure 6

Fecal metabolomics LC-MS analysis. (A) The OPLS-DA rating scale shows the differences in metabolites among the groups. The horizontal coordinate indicates the inter-group change, and the vertical coordinate indicates the intra-group change. (B–H) The acetic acid, propionic acid, butyric acid, valeric acid, caproic acid, isovaleric acid, and isobutyric acid levels are expressed as the mean ± SD (n = 6). * p < 0.05 and ** p < 0.01.

Figure 7

GRP improves the predictive pathways associated with ALD’s effect. Green dots represent metabolic pathways, and other dots represent metabolite molecules. The size of the metabolic pathway point indicates the number of metabolite molecules connected to it, where the higher the number, the larger the point, and the size of the metabolite molecular point indicates the log₂(FC) value through the gradient change. The colors in the figure represent correlations, with green representing negative correlations and red representing positive correlations. The red boxes are the two main metabolic pathways described below.