Ginsenoside Rg5 Activates the LKB1/AMPK/mTOR Signaling Pathway and Modifies the Gut Microbiota to Alleviate Nonalcoholic Fatty Liver Disease Induced by a High-Fat Diet

We purchased Rg₅ with a purity > 98% (item number 186763-78-0), made in China, from Changchun Yuanda Biotechnology Co. Ltd., Changchun, China. We obtained 10% and 60% kcal fat calorie high-fat mouse foods (U.S. item number 112252) from Dyets Biotechnology (Wuxi, China) Co., Ltd.; glucose (item number DE0149) was purchased from Beijing BioDee Biotechnology Co., Ltd., Beijing, China; insulin (item number Y0001717) was acquired from Sigma Aldrich (Shanghai, China) Trading Co., Ltd. Assay kits for alanine aminotransferase (GPT/ALT) (item number C009-2-1), aspartate aminotransferase (GOT/AST) (item number C010-2-1), catalase from micrococcus lysodeiktic (CAT) (item number A007-1-1), superoxide dismutase (SOD) (item number A001-1-2), malondialdehyde (MDA) (item number A003-1-2), and glutathione peroxidase (GSH-Px) (item number A005-1-2) were purchased from Nanjing Jiancheng Haihao Biotechnology Co., Ltd., Nanjing, China. We acquired vancomycin (V871983-1 g); neomycin sulfate (N814740-25 g); metronidazole (M813526-25 g); and ampicillin (A830931-5 g), Macklin brand, from Beijing Essun Huitong Technology Co., Ltd., Beijing, China. We obtained metaphosphoric acid of analytical purity from Sinopharm Chemical Reagent Co., Ltd., Shanghai, China. We procured ethyl butyric acid of analytical purity from Sinopharm Chemical Reagent Co., Ltd., (Shanghai, China). Furthermore, we obtained acetic acid (purity of 99.9%, CAS NO. 64-19-7), propionic acid (purity of 99.9%, CAS NO. 79-09-4), butyric acid (purity of 99.9%, CAS NO. 107-92-6), isobutyric acid (purity of 99.8%, CAS NO. 79-31-2), valeric acid (purity of 99.1%, CAS NO. 109-52-4), isovaleric acid (purity of 99.8%, CAS NO. 503-74-2), and hexanoic acid (purity of 99.9%, CAS NO. 142-62-1) from Shanghai Acmec Biochemical Technology Co., Ltd., Shanghai, China, using the BCA protein assay kit (P0009, Beyotime, Shanghai, China).

A total of 70 eight-week-old male C57BL/6J mice (18–22 g) were purchased from Liaoning Changsheng Biotechnology Co., Ltd., Changchun, China, with certificate number SCXK (Liao) 2020-0001. They were kept in an animal care facility maintained at a constant temperature of 40 °C, with a relative humidity of 50–60% and a 12 h light/12 h dark cycle. Animals were provided with free access to food and water. The animal program was approved by the Institutional Animal Care Committee of the Chinese Academy of Agricultural Sciences and complied with the Animal Management Rules of the Ministry of Health of the People’s Republic of China.

Donor mice: NAFLD mice model of 40 male C57BL/6J mice. All mice were acclimatized for 1 week and then randomly divided into four groups, namely the normal diet group (ND, n = 10), the high-fat diet group (HFD, n = 10), the low-dose group of HFD with Rg₅ (50 mg/kg/d, n = 10), and the high-dose group of HFD with Rg₅ (100 mg/kg/d, n = 10).

Recipient mice: FMT mice model of 30 male C57BL/6J mice. All mice were acclimatized for one week and then randomly divided into three groups: the model group (HFD →Model) (n = 10), the NR group (natural recovery) (n = 10), and the Rg₅ group (HFD + Rg₅→Rg₅, n = 10). All mice were fed with 60% kcal chow and given access to autoclaved distilled water containing 4 antibiotics for the first month and normal autoclaved distilled water for the second month.

The ND group was fed with a normal diet, while the HFD group, HFD + Rg₅ (50 mg/kg) group, and HFD + Rg₅ (100 mg/kg) group were fed an HFD for three months; the components of the normal diet and the HFD are listed in the Supplementary File (Tables S1 and S2).

Mice from the HFD and HFD + Rg₅ (50 mg/kg/d) groups were used as donor mice and kept in an optimal environment. Fresh fecal samples were collected daily to perform FMT experiments. Fecal samples from each group of donor mice were collected and diluted 1:5 with sterile PBS. The samples were then ground up and filtered through a 70 mm filter. The resulting supernatant was collected for further use [14]. C57BL/6J male recipient mice were fed with HFD in month 1, and a fresh mixture of antibiotics (ampicillin 1 g/L, vancomycin 0.5 g/L, neomycin 1 g/L, and metronidazole 1 g/L) was added to sterile water for the recipient mice [15]. After completing the antibiotic treatment, normal sterile water was used instead of the previously mixed antibiotic water, starting from the second month. Recipient mice were then tube-fed via the daily administration of microbiota from donor mice. After two months of treatment, the animals were euthanized, and serum and tissues were collected.

Mice were subjected to OGTT and ITT after 12 weeks of treatment. Mice fasted for 6 h before the experiment and were given 50% (w/v) D-glucose (2 g/kg/BW) solution via gavage, and tail vein blood was collected at different time points after fasting. Blood glucose levels were measured using a sinoheart blood glucose meter (China Sinocare Biosensor Co., Ltd., Changsha, China), and then the area under the curve (AUC) was calculated to quantify the cumulative change in glycemic response. In the insulin tolerance test, mice were fasted for 6 h before commencing the experiment. Then mice were intraperitoneally injected with 0.75 U/kg of insulin, blood samples were collected from the tail vein at different time points after insulin injection, blood glucose was measured, and finally the area under the curve (AUC) was calculated [16].

Total cholesterol (TC), triglyceride (TG), low-density lipid cholesterol (LDL-C), aspartate aminotransferase (AST), and almandine aminotransferase (ALT), catalase (CAT), glutathione peroxidase (GSH-Px), malondialdehyde (MDA), and superoxide dismutase (SOD), all indices of serum and liver tissues were assayed using the corresponding commercial kits (manufactured by Jiancheng, Nanjing, China).

Following the standard protocol, the liver and colon tissues of mice were fixed with 4% paraformaldehyde, dehydrated, and embedded in paraffin wax. Then, 4 μm-thick tissue sections were prepared and mounted onto glass slides. The liver and colon tissues were stained with hematoxylin and eosin (H&E) and Oil Red O. Finally, the images were captured using a light microscope and then subjected to analysis. Images were acquired at 200× and 400× magnification under a microscope. All data were quantified using ImageJ software version 1.54b (National Institutes of Health, Bethesda, MD, USA).

Total protein was extracted from liver tissue and colon tissue, and BCA protein content was determined. Protein was denatured at 95 °C for 5 min, separated via polyacrylamide gel electrophoresis, and then transferred to a polyvinylidene fluoride membrane (PVDF). The membrane was blocked with 5% skim milk for 1 h at room temperature and then mixed with ZO-1 (1:500; ab96587; abcam, Cambridge, UK), Occludin (1:1000; ab216327; abcam, Cambridge, UK), Claudin-1 (1:1000; ab307692; abcam, Cambridge, UK) and GAPDH (1:10,000; ab8245; abcam, Cambridge, UK) overnight at 4 °C, as well as with LKB1 (1:1000; ab15095; abcam Cambridge, UK), AMPK (1:1000; ab32047; abcam, Cambridge, UK), p-AMPK (1:1000; Ab133448↗; abcam Cambridge, UK), mTOR (1:10,000; ab32047; abcam Cambridge, UK), p-mTOR (1:10,000; ab109268; abcam Cambridge, UK), and β-actin (1:1000; 4970S; CST, Danvers, ME, USA). After three washes with PBST, the membrane was then incubated with horseradish peroxidase-conjugated anti-rabbit and anti-mouse secondary antibodies (1:10,000 dilution) for 1 h at room temperature, respectively. Protein bands were imaged using ECL kits (Merck Millipore, Darmstadt, Germany), and we finally quantified band intensity using Image J software version 1.54b (National Institutes of Health, Bethesda, MD, USA).

The feces of each group of mice were collected under aseptic conditions, and 0.2 g of fecal samples was sent to Shanghai Personal Biotechnology Co., Ltd. (Shanghai, China), for the detection of intestinal microorganisms using 16S rRNA analysis. For pre-treated samples, the Mag-Bind Soil DNA Kit (Catalog M5635-02) from OMEGA was used for extraction. For the extracted DNA, 0.8% agarose gel electrophoresis was performed to determine its molecular size, and the DNA was quantified using Nanodrop. We selected the 16S rRNA V3-V4 region for designing polymerase chain reaction (PCR) amplification primers. The forward primer was ACTCC-TACGGGAGGCAGCA and the reverse primer was GGACTACHVGGGTWTCTAAT. Illumina NovaSeq platform for paired-end sequencing. PCR products were quantified using the Quant-iT PicoGreen dsDNA Assay Kit on a Microplate reader (BioTek, FLx800), Invitrogen, Carlsbad, CA, USA. The products were then mixed based on the desired amount of data for each sample, and library construction was performed. Microbiome biology information was analyzed using QIIME version 2019. 4 [17]. The Greengenes database was utilized to acquire the classification data associated with every ASV [18]. We utilized R packages (version 3.6.1) and QIIME2 software (version 2022.11) for data processing tasks, such as taxonomic composition analysis. Biomarkers of differential abundance between groups were further investigated using linear discriminant analysis effect size (LEfSe) analysis and random forest analysis. Histograms were used to display the distribution of LDA values, highlighting significantly enriched species and their significance. The metabolic functions of microflora were predicted using PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) on MetaCyc and KEGG databases.

Gas chromatography/mass spectrometry (GC-MS) was used to determine SCFAs in mouse fecal content, including acetic acid, propionic acid, butyric acid, valeric acid, isobutyric acid, and isovaleric acid. SCFAs concentrations in mouse feces are reported in mmol/L. Sample pretreatment and the preparation of reagents were conducted, taking into account similar methods described in the literature [19,20].

All data are shown as mean ± SD. To compare the two groups, a two-tailed Student’s t-test was used. Multiple comparisons were statistically assessed using one-way analysis of variance (ANOVA) and post hoc Tukey tests. In all cases, p < 0.001, p < 0.01, or p < 0.05 were considered to be statistically significant. Statistical graphs were created using the GraphPad Prism software package, version 8 (GraphPad, CA, San Diego, CA, USA).

To create a model of NAFLD, C57/BL6 mice were fed with an HFD for 12 weeks (Figure 1A). Throughout the experiment, all groups experienced an increase in body weight and food intake. As anticipated, following 12 weeks of intragastric administration, the mice on HFD had significantly higher body weights compared with ND (p < 0.05), while mice on HFD + Rg₅ (50 mg/kg) and HFD + Rg₅ (100 mg/kg) had significantly lower body weights after Rg₅ treatment (Figure 1B). In addition, there were no significant differences in the food intake of the mice in each group (Figure 1C). Glucose and insulin levels were quantified in blood samples obtained during the OGTT and ITT in order to evaluate the metabolic status of glycemia in response to the treatment. As depicted in Figure 1D, blood glucose levels showed a significant increase within 30 min following oral glucose administration in all groups, subsequently declining thereafter. Compared to the ND group and the Rg₅ ginsenoside group, the HFD group demonstrated markedly elevated blood glucose levels. The administration of Rg₅ reversed the increase in the AUC of OGTT induced by the HFD (p < 0.001). Furthermore, the concentration of ITT in mice fed with HFD was higher than that in the ND group (p < 0.01), while supplementation with ginsenoside Rg₅ decreased ITT levels (p < 0.001, Figure 1E). The results demonstrate that intervention with ginsenoside Rg₅ significantly ameliorated glucose tolerance and insulin sensitivity in HFD-fed mice. The findings indicated that mice subjected to an HFD displayed more pronounced elevations in organ indices for hepatic, mesenteric fat, and perirenal fat in comparison to the group receiving a ND. However, this increase was significantly reversed via the intervention with Rg₅ (Figure 1D).

According to the H&E staining of liver tissues (Figure 2A), the liver lobules in the ND group appeared structurally organized and normal, with liver tissues of normal size and an orderly arrangement. In contrast, liver tissue from HFD mice exhibited more severe hepatocyte steatosis and inflammatory cell infiltration. However, hepatocellular steatosis improved after treatment with Rg₅. The results of Oil Red O staining revealed a significantly greater red-stained area in the HFD group compared to the ND group, signifying a higher abundance of lipid droplets in the HFD group. This indicates that Rg₅ intake significantly reduced lipid deposition in the liver and minimized HFD-induced liver injury.

The lipid profiles of the four groups were measured at the end of the 12-week experiment. We found that the serum levels of TG, TC, LDL-C, AST, ALT, and MDA were significantly higher and the levels of SOD, CAT, and GSH-Px were substantially lower in the mice in the HFD group compared to the mice in the ND group. Furthermore, treatment with Rg₅ reversed these effects and ameliorated the hepatic impairment and oxidative stress (Figure 2B–J).

Western blot results showed that, compared with the ND group, mice fed with HFD exhibited suppressed protein expression levels of LKB1 and p-AMPK, upregulated protein expression levels of p-mTOR, and Rg₅ protein expression levels that tended to be similar to those of the normal group (Figure 2K,L). Additionally, these proteins are believed to promote lipolysis. The results of these studies indicate that Rg₅ possesses the potential to enhance energy metabolism, facilitate lipid breakdown, and increase autophagic levels by activating LKB1/AMPK/mTOR, hence leading to the improvement of hepatic lipid accumulation in NAFLD.

The results reveal that within the HFD group, there is a decrease in the length of intestinal villi, accompanied by disorganized shedding and coinciding with the arrangement of intestinal epithelial cells. Additionally, the mucosal epithelial cells of the intestinal lining exhibit signs of atrophy, and the intrinsic muscle layer appears thinner. These observations collectively indicate significant impairment of the intestinal barrier. Importantly, it is worth noting that these changes undergo reversal in the Rg₅ group (Figure 3A). To further explore the molecular mechanism of Rg₅ treatment for intestinal injury protection, we performed Western blot experiments. To better observe their impact on intestinal mucosal integrity, we assessed the expression of epithelial tight-junction molecules (including ZO-1, Claudin-1, and Occludin) in the intestinal tissues of receptor mice. Next, we sought to determine whether Rg₅ protected mice on an HFD from intestinal barrier damage. As expected, the expression of these proteins was significantly reduced in the HFD group compared with the ND group (p < 0.001), indicating disruption of the intestinal mucosal barrier. Conversely, the group treated with Rg₅ via gavage exhibited a notable upregulation in the expression of these proteins, indicating the potential restoration of intestinal barrier function via Rg₅ treatment (Figure 3B,C).

SCFAs are among the primary metabolites of the gut microbiota, playing crucial roles in host metabolism [21]. As reported in the literature, SCFAs derived from gut microbiota can serve as potent regulators of hepatic metabolic functions by acting as lipid precursors. Furthermore, they function as ligands for G-protein-coupled receptors (GPCRs), thereby modulating molecular signal transduction. This indicates that SCFAs play a more direct role in the gut–liver axis [22]. This segment of our study delved into the correlation between alterations in SCFAs and modifications of gut microbiota among mice afflicted with NAFLD. Our findings demonstrated notable alterations in the concentrations of six SCFAs within the HFD group when juxtaposed with the ND group. More specifically, a substantial decrease was observed in acetic acid, propionic acid, and butyric acid levels, while a significant elevation was noted in the content of isobutyric acid and the overall SCFAs content (Figure 3D). The administration of Rg₅ exhibited a tendency to elevate the concentrations of these six SCFAs and the total SCFAs content in comparison to the HFD group, although this trend did not reach statistical significance. The findings propose that the administration of Rg₅ could potentially disturb intestinal homeostasis by impacting the composition of the intestinal microbial community and its associated metabolism. However, following Rg₅ treatment, there was a certain recovery effect, but it did not demonstrate significance. Following the analysis of our results, we posited that alterations in the contents of SCFAs correlate with various factors. The existing literature underscores feed as a crucial determinant shaping the composition of gut microorganisms. On the one hand, the diet serves to supply nutrients to the host; on the other hand, the feed acts as a substrate for the fermentation of mice gut microorganisms, thereby governing microbial growth, reproduction, and the concentration of their metabolites, SCFAs, consequently impacting gut health [23]. This is because the HFD used in our study was a commercially produced concentrate feed with a straightforward nutrient composition. Furthermore, the literature indicates that SCFAs can result from probiotic fermentation by specific gut bacteria, including Bacteroides, Prevotella, Blautia, and others, within the intestinal tract and colon. Rg₅ may reduce the abundance of these bacteria and, as a result, decrease the content of acetic or propionic acid. The bacteria responsible for producing butyric acid and propionic acid are distinctly different, and this distinction is also a contributing factor to the lack of significant changes in SCFA levels between the two groups following intervention. This finding aligns with similar observations made in the literature [24]. We hypothesized that liver injury and disruptions in the intestinal environment caused by an HFD are linked to decreases in the concentration of total SCFAs and the bacteria responsible for their production. Previous studies have suggested that the production of butyrate is influenced by the expression and activity of specific enzymes, which can in turn be affected by the type of diet [25]. This is consistent with the pattern we observed in the overall structure of the gut microbiota. The findings indicate that Rg₅ potentially exerts its anti-NAFLD activity via the modulation of gut metabolites, specifically SCFAs.

In the present study, we identify the connections between gut microorganisms and serological markers and emphasize their significance in regulating lipid metabolism. This information is crucial for examining the impact of modifications to gut flora on Rg₅ in the treatment of NAFLD. Redundancy analysis (RDA) is a multivariate statistical method primarily used to explore the relationship between multivariate response data and one or more sets of explanatory variables [26]. The results showed that at the genus level, TC, TG, LDL-C, ALT, AST, and MDA were positively correlated with Allobaulum and Lactobacillus, while being negatively correlated with Oscillospira, Bifidobacterium, and Turicibacter. On the other hand, CAT, SOD, and GSH-Px were positively correlated with Oscillospira, Turicibacter, and Bifidobacterium, but negatively correlated with Allobaulum and Lactobacillus (Figure 3E). The results suggest that the changes in the abundance of these colonies are closely related to the changes in the structure of the intestinal flora in mice before and after Rg₅ treatment.

In order to further analyze the potential therapeutic effects of Rg₅ on non-alcoholic fatty liver, we employed 16S rRNA sequencing to investigate the impact of Rg₅ on the gut microbiota of NAFLD. The analysis of alpha diversity results revealed that, compared to the ND group, the Rg₅ group exhibited increased species diversity and richness, while the HFD group did not show a significant decrease in species diversity and richness (Figure 4A). Principal coordinate analysis (PCoA) reveals a pronounced divergence in the composition of the intestinal microbiota across mice subjected to distinct dietary conditions (Figure 4B). This suggests that the gut microbial profiles of the mice underwent significant changes after supplementation with Rg₅. The Venn diagram visually represents distinctions in the quantity of operational taxonomic units (OTUs), notably highlighting that the Rg₅ group exhibits a significantly greater OTU count in comparison to the HFD group (Figure 4C).

Secondly, in terms of the species composition of the flora, the analysis at the phylum level analysis revealed that Firmicutes, Bacteroides, Actinobacteria, Proteobacteria, and Verrucomicrobia were among the most abundant bacteria in all groups of the top 10 phyla selected for this study (Figure 4D). In comparison to the HFD group, the Rg₅ group exhibited a reduction in the Firmicutes/Bacteroidetes (F/B) ratio post-administration, signifying an amelioration in the gut microbiota environment of mice with NAFLD (Figure 4E). The abundance ratios of Firmicutes and Bacteroidetes exhibited significant elevations, serving as indicative markers for obesity [27]. This improvement helped to alleviate lipid metabolism disorders in the HFD mice to some extent.

In order to examine the differences in species composition between samples to an even greater extent, we conducted species composition analyses using heat maps of abundance data for the top 20 genera based on average abundance. The results of 16S rRNA gene sequencing analyses suggest that an HFD alters the composition of the gut flora. This finding is consistent with previous research. Compared to the ND group, the HFD intervention enriched the relative abundance of Allobaculum, Olsenella, and Mucispirillum, while also reducing the relative abundance of Odoribacter and Bacteroide. Under HFD conditions, supplementation with Rg₅ increased the relative abundance of the genera Akkermansia, Oscillospira, Phascolarctobacterium, Bacteroides, and Dehalobacterium and decreased the relative abundance of the genera Allobaculum and Olsenla (Figure 4F). These findings serve as the basis of the theoretical groundwork for the prospective utilization of Rg₅ as an innovative pharmaceutical, underpinning the formulation of strategies aimed at treating NAFLD by modulating the gut microbiota. In addition, our results showed that supplementation with Rg₅ significantly upregulated the relative abundance of Bacteroides, a phylum of bacteria, and downregulated the relative abundance of Allobaculum and Olsenella. Gavage treatment with Rg₅ significantly reduced the relative abundance of the harmful bacterium Helicobacter and promoted the growth of Akkermansia and Oscillospira (Figure 4F). Overall, the findings imply that the administration of Rg₅ has the potential to ameliorate HFD-induced dysbiosis in intestinal microbiota, enhancing the abundance of certain key microorganisms, such as Allobaculum, Akkermansia, and Coprococcus. Utilizing the outcomes of LEfSe analysis, we successfully pinpointed the key microbial groups that experienced enrichment in the Rg₅ group. The results showed that a total of 82 different bacterial species were screened in these three groups. There were 19, 23, and 40 significantly different genera in three groups, respectively (p < 0.05, LDA > 2) (Supplementary File Figure S1).

Subsequently, we conducted a Spearman association heat map analysis to examine the phenotypic correlation indices with the microorganisms of the intestinal flora (Figure 4H). As anticipated, in the phylum level analysis, the heat map results revealed that the Firmicutes and Bacteroidetes were negatively correlated with lipid related factors (TC, TG, and LDL-C) and liver damage indicators (AST, ALT), while being positively correlated with oxidative stress indicator (CAT, SOD, and GSH-Px) (Supplementary File Figure S2). Additionally, Bacteroidetes is also negatively correlated with acetic acid, propionic acid, butyric acid, and total SCFAs, as well as displaying a positive correlation with liver weight. At the genus level, the results align with those observed at the phylum level. From this perspective, the dysregulation of gut microbiota is directly associated with diminished inflammatory factors and a decrease in SCFA contents. Furthermore, this clarifies why the reduction in harmful bacteria and the increase in beneficial bacteria can efficiently regulate HFD-induced NAFLD in mice.

In order to validate the gut microbiota’s involvement in mediating host metabolic regulation and assess its effectiveness against NAFLD via FMT, we delved deeper into our investigation. The HFD group and the Rg₅ group were administered, preparing fecal bacterial fluids via gavage. The donors for the model group were mice from the NAFLD model group, while the donors for the Rg₅ group were mice from the HFD + Rg₅ group (Figure 5A). According to the H&E staining of liver tissues (Figure 5B), we observed a decrease in vacuoles and inflammatory cell infiltration in hepatocytes, as well as reduced steatosis in the liver tissues of mice in the NR and Rg₅ groups compared to the model group. After clearing the colony in the first month of antibiotic treatment, there was no significant difference in body weight among the three groups of mice, all of which grew steadily (note: during the two-month experimental period, all three groups were fed an HFD with 60% calories) (Figure 5C). The results showed that mice in the Rg₅ group exhibited lower liver, mesenteric, and perirenal fat organ indices compared to the model group (Figure 5D). The lipid profiles of the three groups were measured at the end of the experiment in week 2. The serum levels of TG, TC, and LDL-C were significantly reduced in the Rg₅ group of mice compared to the model group of mice. However, the effect was not significant in the NR group, although there was some degree of improvement (Figure 5E–G).

In addition, the serum levels of AST, ALT, and MDA were significantly reduced, and the levels of SOD, CAT, and GSH-Px showed significant increases in the Rg₅ group of mice that were administered with fecal bacteria orally compared to those in the model group. However, the extent of recovery in the NR group was not very significant compared to the Rg₅ group (Figure 5H–M). Overall, the obtained data indicate that FMT mitigates hepatic inflammation and oxidative stress in recipient mice, exhibiting a comparable effect to the treatment of donor mice with the Rg₅ group.

We conducted 16S rRNA gut flora sequencing on the feces of recipient mice to further investigate the differences in the fecal microbiota between NAFLD mice and FMT mice. Compared to model group treatment, treatment of the Rg₅ group resulted in slight increases in the Chao1 index, Shannon index, and Simpson index, but the increases were not statistically significant. Furthermore, these three indices were significantly lower in the CB group compared to the other groups. This indicates that the antibiotic clearance of the flora during the initial premonitory period of the first month had a significant impact and should not be considered among the confounding factors affecting the experimental results (Figure 6A). According to the PCA score plot, there were notable structural variations in the gut microbiota between the Rg₅ group and the model group (Figure 6B). The Venn diagram visually represents distinctions in the quantity of operational taxonomic units (OTUs) (Figure 6C). In addition, Proteobacteria increased at the portal level, while Firmicutes, Bacteroides, Actinobacteria, and Deferribacteres decreased in the Rg₅ group compared to the model group with the NR sample (Figure 6D). It is also noteworthy that the F/B values were significantly lower following the gavage of Rg₅ fecal bacteria treatment (Figure 6E). At the genus level, among the top 20 genera with significant differences, the relative abundance of certain potentially harmful genera such as Allobaulum and Ralstonia, as well as iterations with reduced harm such as Roseburia, Oscillospira, Adlercreutzia, and Akkermansia, were increased in the model group treated with gavage HFD fecal transplantation, Prarabacteroides, and the Coprococcus beneficial bacterial genera. The Rg₅ group reinstated alterations in the relative abundance of these genera induced by the model group, enriching Odoribacter, Subdoligranulum, Akkermansia, Coprococcus, Parabacteroides, etc., and decreasing the relative abundance of Allobaulum, Ralstonia, and Dore. Furthermore, the NR group enriched the relative abundance of Roseburia, Bacteroides, and decreased the Alistipes, Prevotella, and Odoribacter relative abundance (Figure 6F). This discovery investigated the effects of supplementing with Rg₅ in donor mice subjected to an HFD. We further identified specific colonies and biomarkers through LEfSe analysis to determine the dominant flora in each group (Figure 6G). We found that at the genus level, recipient mice in the model group were enriched in the genera Allobaculum and Olsenella. These genera were also dominant in donor mice in the HFD group. Additionally, Coprococcus was more prevalent in recipient mice in the Rg₅ group than in donor mice. Intriguingly, Akkermansia predominated in donor mice in the Rg₅ group, suggesting that these bacteria could potentially serve as biomarkers for identification purposes. Additionally, the gut microbiota of the recipient mice somewhat resembled that of the donor mice with which they were matched. These findings imply that FMT holds the potential to positively influence the enhancement of the gut microbiota environment, thus presenting it as a beneficial intervention against NAFLD.

The data for this study is included in both the article and. Supplementary Materials