All animal experiments reported in this manuscript were approved by the Ethics Committee for Scientific Research of Fenyang College of Shanxi Medical University (Approval No. 2023021). C57BL/6J male mice were purchased from Shanxi Medical University Laboratory Animal Central (Taiyuan, China), with permission code SCXK2019-0004. All animals were housed in individually ventilated cages during the experiment under the following conditions: ambient temperature of 20–26°C, relative humidity between 40–60%, minimum static pressure difference of 10 Pa, noise level ≤60 dB (A), and a 12-h light/dark cycle. Water and feed were provided ad libitum. The breeding cages for C57 mice measured 380 × 160 × 180 mm. At the end of the experiment, all mice were anesthetized with sodium pentobarbital and then euthanized by cervical dislocation.

Both the normal and HFDs used in the experiment were prepared manually in the laboratory. The main components and their proportions in the normal diet and the HFD are detailed in Table 1 (Anhê et al., 2019). The normal diet primarily consisted of whey protein, cornstarch, sucrose, and other components, while the high-fat diet significantly increased the fat content, particularly through the addition of lard and soybean oil.

Thirty-six 8-week-old male C57BL/6J mice (21.3 ± 1.5 g) were randomly divided into four groups of nine mice each using a computer-based random number generator: normal diet (ND), high-fat diet (HFD), HFD + Orlistat (ORL), and antibiotic complex + ORL (Abx + ORL). The ND group was fed a normal diet, while the other three groups were fed a HFD. Mice in the ORL group received Orlistat (Zein Biotechnology, Chongqing, China) at 50 mg/kg/day. The drug was dissolved in normal saline and administered intragastrically at 200 μL per dose, once daily. Mice in the ORL + Abx group were treated similarly to the ORL group, with the addition of antibiotics (1 g/L metronidazole, 1 g/L ampicillin, 0.5 g/L neomycin, and 0.5 g/L vancomycin) in their drinking water (Secombe et al., 2021; Kennedy et al., 2018). All antibiotics were purchased from Sigma-Aldrich (Shanghai) Trading Co., Ltd., and drinking water was prepared daily. Each group was weighed and fed every Sunday morning at 9 am. After 10 weeks of Orlistat administration, blood samples were collected via orbital bleeding. Animals were then euthanized, and visceral adipose tissue (including epididymal and mesenteric fat) and subcutaneous adipose tissues were collected and weighed. Mice livers, jejunum, and caecum were also collected. The liver was fixed with 4% paraformaldehyde for 12 h for hematoxylin and eosin (H&E) staining, with the remaining liver tissue preserved at −80°C. Jejunum and caecum samples were rinsed with phosphate buffer solution (PBS, pH 7.3), then flash-frozen in liquid nitrogen and stored at −80°C for quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR) analysis.

Male mice aged 8 weeks were divided into four groups (n = 9 per group) using a computer-based random number generator: ND, HFD, high-fat diet mice fecal microbiota transplantation (FMT-HFD), and Orlistat-treated mice FMT (FMT-ORL). Prior to fecal microbiota transplantation, the FMT-HFD and FMT-ORL groups received antibiotics in their drinking water (ampicillin 0.5 g/L, neomycin 0.25 g/L, and metronidazole 0.5 g/L) (Secombe et al., 2021). Additionally, these groups were treated with 200 μL of an antibiotic cocktail (ampicillin 1 g/L, neomycin 0.5 g/L, vancomycin 0.5 g/L, and metronidazole 1 g/L) via oral gavage for 7 days to clear their gut microbiota. Following antibiotic treatment, three fecal samples were randomly collected from each cage of the FMT-HFD and FMT-ORL groups. Fecal samples were collected under a laminar flow hood to maintain a sterile environment. All equipment, including collection tubes and pipettes, was sterilized by autoclaving at 121°C for 20 min prior to use. The fecal suspension was prepared in a biosafety cabinet using sterile phosphate buffered saline (PBS, pH 7.3). The suspension was centrifuged at 3,000 rpm for 2 min, and the supernatant was collected under sterile conditions. Fresh transplant material was prepared immediately before each transplantation to avoid any potential microbial contamination. The fecal samples were thoroughly mixed and ground. Fecal bacterial solutions were then extracted by centrifugation at 3,000 rpm for 2 min. The bacterial content in the feces was estimated using the dilution plating method to assess the effectiveness of the antibiotic treatment. The samples were diluted 100-fold in sterile phosphate-buffered saline (PBS) and plated on LB solid medium (V900857, Sigma-Aldrich). The plates were incubated at 37°C for 24–48 h, and bacterial colonies were counted. The ND group, which did not receive antibiotic treatment, served as the control. The results confirmed a significant reduction in bacterial growth in the FMT-HFD and FMT-ORL groups compared to the ND group, indicating successful depletion of gut microbiota.

Eight-week-old male donor mice (n = 4 per diet group) were fed either a HFD or HFD supplemented with Orlistat for 15 weeks. After 4 weeks of feeding, stools were collected daily for the subsequent 2 weeks under sterile conditions in a laminar flow hood. Stools from donor mice of each diet group were pooled, and 200 mg was resuspended in 1 mL of PBS buffer solution. The mixture was centrifuged at 3,000 rpm for 2 min. The supernatant was collected and used as transplant material; this process took place in a biosafety cabinet. Fresh transplant material was prepared on the day of transplantation within 30 min before oral gavage to prevent changes in bacterial composition. The FMT-HFD and FMT-ORL groups were inoculated with fresh transplant material (200 μL per mouse) via oral gavage three times a week for 2 weeks (Borody et al., 2013). The mice were then euthanized for subsequent analysis.

Serum samples were obtained by centrifuging blood at 3000 rpm for 10 min at 4°C. An Epoch microplate spectrophotometer was used to measure serum biochemical parameters. The biochemical assay kits used in this study were purchased from the Nanjing Jiancheng Bioengineering Institute (Nanjing, China). These include the Total Cholesterol Assay Kit (A111-1-1, single reagent GPO-PAP method), Triglyceride Assay Kit (A110-1-1, single reagent GPO-PAP method), High-Density Lipoprotein Cholesterol Assay Kit (A112-1-1, dual reagent direct method), Low-Density Lipoprotein Cholesterol Assay Kit (A113-1-1, dual reagent direct method), and Glucose Assay Kit (A154-1-1, glucose oxidase method). All kits were used strictly in accordance with the manufacturer’s instructions to ensure the accuracy and reliability of the results.

Total RNA from liver and small intestine was isolated from liquid nitrogen-frozen and ground tissues using RNAiso Plus (Takara 9109, China). Equal amounts of total RNA were used to synthesize cDNA with the PrimeScript^™ RT reagent Kit with gDNA Eraser (Takara RR047A, China). Quantitative real-time reverse-transcription PCR (qRT-PCR) was performed in triplicate using TB Green, 96-well plates, and the CFX96 Real-Time PCR Detection System (Bio-Rad). Each well contained a total of 25 μL, consisting of 2 μL of cDNA, 2 μL of target primers, 8.5 μL of water, and 12.5 μL of TB Green Premix Ex Taq II. GAPDH was chosen as the housekeeping gene to normalize target gene levels. Hot-start PCR was performed for 40 cycles, with each cycle consisting of denaturation for 5 s at 95°C, followed by annealing and elongation for 30 s at 60°C. Relative quantification was done using the 2 − ΔΔCT method (Ke et al., 2020), where ΔΔCT = (CT Target − CT GAPDH) treatment − (CT Target − CT GAPDH) control. Relative expression was normalized and expressed as a ratio to the expression in the control group. The primers used are shown in Table 2.

Liver tissue samples preserved in 4% paraformaldehyde were dehydrated, cleared, and embedded in paraffin wax using a tissue processor. After solidification, the blocks were sectioned using a microtome to a thickness of 4–6 μm. The sections were mounted on glass slides and baked at 65°C for approximately 2 h. H&E staining was performed according to standard protocols (Cardiff et al., 2014).

After sacrificing each group of mice, cecal contents were collected, flash-frozen in liquid nitrogen, stored on dry ice, and transported to Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China) for analysis. Total DNA was extracted from the cecal content samples using the E.Z.N.A.^® soil DNA Kit (Omega Bio-tek, Norcross, GA, United States) according to the manufacturer’s instructions. DNA quality and concentration were assessed using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Wilmington, DE, United States). Bacterial 16S rRNA gene fragments (V3–V4 region) were amplified from the extracted DNA using primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). PCR conditions were as follows: 27 cycles of 95°C for 30 s, 55°C for 30 s, and 72°C for 45 s. Each PCR reaction (20 μL) contained 4 μL 5× TransStart FastPfu buffer, 2 μL 2.5 mM deoxynucleoside triphosphates (dNTPs), 0.8 μL of each primer (5 μM), 0.4 μL TransStart FastPfu DNA Polymerase, 10 ng of extracted DNA, and ddH₂O to make up the final volume. Amplicon size was verified by agarose gel electrophoresis. Paired-end sequencing was performed on the Illumina MiSeq platform using PE300 chemistry at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China). Raw reads were deposited in the NCBI Sequence Read Archive database (Bioproject ID: PRJNA1130423).

After demultiplexing, the resulting sequences were merged using FLASH (v1.2.11) (Magoč and Salzberg, 2011) and quality-filtered with fastp (v0.19.6) (Chen et al., 2018). The high-quality sequences were then denoised using the DADA2 (Callahan et al., 2016) plugin in the Qiime2 (v2020.2) (Bolyen et al., 2019) pipeline using the recommended parameters, which allowed for single-nucleotide resolution based on error profiles within the samples. DADA2 denoised sequences are typically referred to as amplicon sequence variants (ASVs). Taxonomic assignment of ASVs was performed using the Naive Bayes consensus taxonomy classifier implemented in Qiime2 and the SILVA 16S rRNA database (v138). Analysis of the 16S rRNA microbiome sequencing data was performed using the free online platform of Majorbio Cloud Platform.¹

Data are expressed as mean ± standard error of the mean (SEM). Differences between groups were assessed using unpaired two-tailed Student’s t-tests (GraphPad Prism 8 software). All statistical analyses were performed using one-way analysis of variance with homogeneity of variances tested via Levene’s test. A p-value of <0.05 was considered statistically significant.

We sought to determine the effect of Orlistat on HFD-fed mice by measuring body weight, food intake, subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT) weights (Figures 1A,B,D–G). As expected, the HFD significantly increased body weight (p < 0.001), relative weight of SAT (p < 0.001), and the VAT to body weight ratio in mice (p < 0.001). Orlistat treatment significantly inhibited weight gain induced by the HFD (p < 0.05). Additionally, Orlistat treatment significantly decreased SAT weight (p < 0.01) and VAT weight (p < 0.05) in mice. Mice from the ORL group showed greater weight reduction compared to the ORL + antibiotics group, but this difference was not statistically significant (p > 0.05). Interestingly, food intake decreased significantly in the ORL + antibiotics group. We further calculated the feed conversion ratio (food intake/weight gain) to assess the relationship between weight gain and food intake (Figure 1C). Here, we found that a higher feed conversion ratio suggests that more food is consumed in order to gain the same amount of weight, which is indicative of a reduced risk of obesity. Compared to the ORL group, the feed conversion ratio in the ORL + Abx group decreased significantly (p < 0.001), but there was no significant difference in body weight between the two groups (p > 0.05). This suggests that antibiotic treatment suppresses appetite and inhibits fat consumption in mice. Taken together, Orlistat treatment reduced weight gain and fat tissue accumulation induced by the HFD in mice. While antibiotics decreased the feed conversion ratio in the ORL + Abx group, there were no significant differences in body weight and fat tissue weight between the ORL group and the Abx + ORL group.

We further analyzed serum concentrations of lipid metabolites (Figures 2A–E) and found that the HF diet increased serum levels of GLU, T-CHO, TG, LDL, and HDL (p < 0.05). Orlistat administration significantly reduced serum levels of GLU (p < 0.001), T-CHO (p < 0.05), and TG (p < 0.05) compared to the HFD group, but had little effect on the serum level of HDL while improving the serum level of LDL (p < 0.05). Mice from the ORL + antibiotics group showed lower LDL and HDL levels compared to the ORL group, but this difference was not statistically significant (p > 0.05). Interestingly, TG levels increased significantly in the ORL + antibiotics group. There were no significant differences in GLU and T-CHO serum levels between these groups. In addition, we extracted and weighed the livers of mice in each group and found that there were no statistically significant differences in liver weight among the groups (Figure 2F).

We found the prevalence of steatohepatitis to be 100% in the HFD group. H&E staining revealed normal hepatic ultrastructure in the ND group. Hepatocytes in the ND group showed abundant cytoplasm with centrally located nuclei (Jia et al., 2019). In contrast, hepatocytes in the HFD group exhibited numerous vacuoles (lipid droplets) in their cytoplasm, and they were disordered, deformed, and compressed. In the ORL group, there was minimal liver injury, with most hepatocytes displaying normal ultrastructure, intact cell membranes, and few lipid droplets. Although the degree of liver damage in the ORL + Abx group was less severe than in the HFD group, it was more pronounced compared to the ORL group. The ultrastructure of these hepatocytes was disordered, and lipid droplets were more abundant (Figure 2G). These findings suggest that antibiotic treatment attenuated the inhibitory effect of Orlistat on fatty liver degeneration in HFD mice.

Herein, we sought to measure expression levels of the proinflammatory cytokines, IL-1β, IL-6, and TNF-α, which are known to cause inflammation in intestinal tissue. Notably, we found that the expression of IL-1β in the ND group was significantly higher than in the other groups (p < 0.001) (Figure 3A). Further, IL-6 and TNF-α expression was consistent with previous findings in the literature (Li et al., 2008). Compared to the ND, the HFD promoted expression of these proinflammatory cytokines (p < 0.05). As shown in Figures 3A–C, the expression of IL-1β (Figure 3A), IL-6 (Figure 3B), and TNF-α (Figure 3C) in the HFD group was slightly higher than in the ORL group, but these differences were not statistically significant (p > 0.05). Additionally, proinflammatory cytokine expression in the ORL group was generally consistent with the FMT-ORL group. Together, these data show that a HFD increases proinflammatory cytokine expression. Moreover, while Orlistat inhibited fat absorption in mice, it did not reduce proinflammatory cytokine expression, and antibiotic treatment failed to reverse this trend.

We also measured glucagon gene (Gcg), glucose-dependent insulinotropic polypeptide (GIP), and cholecystokinin (CCK) mRNA expression in the colon of all study animals. As shown in Figures 3D–F, Gcg (Figure 3D), GIP (Figure 3E), and CCK (Figure 3F) expression in the HFD group was slightly lower compared to mice in the ND group, but these differences were not statistically significant (p > 0.05). Interestingly, when compared to the HFD group, Gcg and GIP mRNA expression was significantly reduced in the ORL group (p < 0.05), while CCK expression remained unchanged (p > 0.05). Furthermore, when comparing the Abx + ORL group to the ORL group, Gcg and GIP expression was significantly upregulated (p < 0.005), whereas CCK expression remained similar (p > 0.05). These data may explain the reduced food intake observed in the Abx + ORL group.

The gut microbiota is closely associated with obesity and lipid metabolism. Therefore, we sought to further examine the composition of fecal microbiota samples by performing 16S rRNA gene sequencing of the intestinal microbiota. Shannon and Simpson indices were assessed to evaluate the α diversity of the microbiomes. Compared to the ND and HFD groups, mice in the ORL group exhibited lower microbiota diversity, as indicated by decreased Shannon indices (p < 0.05) (Figure 4A). Although the Simpson index increased, this change was not statistically significant (p > 0.05) (Figure 4B). Beta diversity analysis, which reflects differences between samples, was also performed. Bray–Curtis distance-based principal coordinate analysis (PCoA) revealed distinct clustering of intestinal microbial communities for each experimental group. Both the HFD and Orlistat interventions induced significant changes in the microbiota community structure. As shown in Figure 4C, PC1 represents the first principal coordinate, accounting for 27.62% of the total variance, while PC2 represents the second principal coordinate, accounting for 18.19% of the total variance. The distinct separation of the ND and HFD groups, along with the significant distance between the ORL and HFD groups in the PCoA plot, suggests that Orlistat consumption induced similar changes in microbial composition (Figure 4C).

Through a comparative analysis of the sequences from the fecal samples, we studied the microbial community structure in Orlistat-treated mice and compared it with the ND and HFD groups. As shown in Figures 4D,F, the gut microbiota at the phylum level primarily consists of Bacteroidetes, Firmicutes, Verrucomicrobiota, and Actinobacteria. We employed the Kruskal–Wallis H test to evaluate the significance of species abundance differences among multiple sample groups. As illustrated in Figure 4E, the abundance of Verrucomicrobiota in the ORL group was higher compared to the ND and HFD groups (p < 0.01), while Proteobacteria levels were lower (p < 0.05). Additionally, Campylobacterota levels in the HFD group were higher than those in the ND group (p < 0.05), but this trend was reversed with Orlistat supplementation. Relevant studies indicate that Firmicutes and Bacteroidetes are closely related to glucose and lipid metabolism, as well as bile acid metabolism (Qu et al., 2020). The Firmicutes to Bacteroidetes ratio (F/B) has become an important indicator for determining obesity (Volokh et al., 2019). A higher F/B ratio suggests greater energy absorption by the intestinal tract, while a lower ratio indicates slower energy absorption, which may help reduce lipid levels (Barczynska et al., 2015). We found that the F/B ratio in the ORL group was slightly higher than in the HFD group; however, this difference was not statistically significant (p > 0.05).

The composition of bacterial genera identified in this work is shown in Figures 4G–I, with specific emphasis on genera with a total abundance ratio greater than 0.01. As illustrated in these figures, the abundance of Alloprevotella and Bifidobacterium in the HFD group was higher than in the ND group, while Akkermansia, Allobaculum, and Clostridium_sensu_stricto_1 were lower compared to the ND group. These trends were reversed with Orlistat supplementation, particularly with Akkermansia being enriched in the ORL group. Many studies have found that reduced Akkermansia abundance is associated with various diseases in mouse models and humans. Further, Akkermansia has been shown to improve obesity, type 1 and type 2 diabetes mellitus, hepatic steatosis, intestinal inflammation, and different cancers (including colon cancer and response to immune checkpoint therapies) in mice (Cani et al., 2022). The relative abundance of Akkermansia in the ND, HFD, and ORL groups was 1.5, 0.02, and 10.62%, respectively. Overall, these findings indicate considerable changes in the composition of dominant bacteria at the phylum and genus levels in the mouse gut microbiota following Orlistat treatment.

To analyze changes in gut microbiota composition among the different study groups, we used linear discriminant effect size (LEfSe) analysis to identify characteristic taxa in each group (Figures 4J,K). The results indicated that there were eight characteristic taxa in the HFD and ORL groups when the LDA score was >3. In the HFD group, there was a notable increase in Alloprevotella, Ileibacterium, Bifidobacterium, and norank_f_Oscillospiraceae. Conversely, the ORL group was enriched in Akkermansia and Clostridium_sensu_stricto_1.

We then investigated whether microbiota transplantation from Orlistat-treated mice could alleviate or exacerbate lipid accumulation in HFD mice. HFD mice received either a regular diet or Orlistat by oral gavage for 4 weeks (n = 4 for each group). Fecal samples were then collected and transplanted into antibiotic-treated mice (n = 9). After 1 week of combined antibiotic treatment, fecal samples were collected from mice in each group, diluted 100-fold, and plated on LB solid medium. The ND group, which did not receive antibiotic treatment, served as the control. The results show a significant reduction in bacterial growth in the FMT-HFD and FMT-ORL groups compared to the ND group, confirming that the antibiotic treatment successfully depleted the majority of gut microbes (Supplementary Figure S1). The microbiota-transplanted mice were subsequently fed a HFD for an additional 2 weeks.

As shown in Figure 5A, microbiota transplantation from Orlistat-treated mice inhibited weight gain, which was significantly lower compared to the HFD group (p < 0.05) and also lower than the ND group, although this difference was not statistically significant (p > 0.05). Interestingly, weight gain in mice in the FMT-HFD group was significantly lower compared to animals in the HFD group (p < 0.05) and similar to those in the ND group, but still higher than mice in the FMT-ORL group (p > 0.05). There were no statistically significant differences in food intake (Figure 5B). Mice were subsequently sacrificed after 2 weeks of microbiota transplantation. The mass of SAT and VAT in each group is shown in Figures 5C–F. We found that the HFD significantly increased the accumulation of subcutaneous fat (p < 0.005) and visceral fat (p < 0.05) compared to the ND group. Notably, microbiota transplantation in FMT-ORL treated mice significantly reduced the accumulation of subcutaneous fat (p < 0.05) and visceral fat (p < 0.01) in high-fat fed mice compared to those in the HFD group. Compared to the FMT-ORL group, the weighed mass of subcutaneous fat and visceral fat in the FMT-HFD group was slightly higher, but these differences were not significant (p > 0.05). Furthermore, serum levels of GLU (p < 0.01), HDL (p < 0.05), and TG (p < 0.05) were elevated compared to those in the FMT-ORL group. In addition, there were no significant changes in liver weight (p > 0.05) (Figures 5G–L). These results suggest that microbiota transplantation from Orlistat-treated mice reduces fat accumulation and metabolic disturbances in HFD-fed mice.

To investigate the potential of microbiota transplantation to reduce the expression of intestinal inflammatory factors, we examined the expression levels of IL-1β, IL-6, and TNF-α (Figures 6A–C). We found that, compared to normal mice, mRNA expression of the inflammatory factors IL-1β and IL-6 was significantly increased in HFD-induced obese mice (p < 0.05). Compared to the HFD group, IL-1β and IL-6 mRNA expression was significantly reduced in the FMT-ORL group (p < 0.05), whereas TNF-α expression remained unchanged (p > 0.05). Moreover, expression levels of inflammatory factors in the FMT-ORL group were similar to those in the ND group. Interestingly, there were no statistically significant differences in the expression of IL-1β, IL-6, and TNF-α between the FMT-HFD group and the HFD-ORL group (p > 0.05).

To investigate whether microbiota transplantation from Orlistat-treated mice can alter the expression of appetite hormones in germ-free recipient mice, we examined the expression levels of the appetite hormones, GIP, Gcg, and CCK, in the FMT recipients (Figures 6D–F). Interestingly, there were no statistically significant differences in the expression of these appetite hormones in the recipient group transplanted with fecal microbiota from Orlistat-treated mice compared to the ND, HFD, and FMT-HFD groups (p > 0.05). Additionally, there were no statistically significant differences among the other groups.

To investigate the effects of intestinal microbiota transplantation on the structure and function of gut microbiota in antibiotic-treated germ-free mice, we conducted 16S rRNA sequencing on the gut microbiota of the FMT recipient mice.

A comparison of α diversity between the FMT-HFD group and the FMT-ORL group is depicted in Figures 7A,B. The Simpson index for the FMT-HFD group was higher than that for the FMT-ORL group; however, there was no statistically significant difference in the Shannon and Simpson indices between the two groups (p > 0.05). Unweighted UniFrac-based PCoA revealed distinct clustering of intestinal microbial communities for both experimental groups (Figure 7C). A significant distance was observed between the FMT-HFD group and the FMT-ORL group, indicating that the microbiota community structure of recipient mice that received fecal bacteria from either the HFD or ORL group underwent notable changes.

Using a comparative analysis of the sequences from the fecal samples, we studied and compared the microbial community structure of the FMT-HFD and FMT-ORL groups. We found that at the phylum level the gut microbiota is primarily composed of Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria (Figures 7D,F). We used the Wilcoxon rank-sum test to assess species abundance differences among multiple sample groups. As illustrated in Figure 7H, the abundance of Verrucomicrobiota in the FMT-ORL group was significantly higher (p < 0.05) than in the FMT-HFD group. This finding aligns with previous observations regarding changes in the microbiota composition of mice in the ORL group. The genus-level composition of bacterial types is shown in Figures 7E,G, which highlight those with a total abundance ratio greater than 0.01. As depicted in Figure 7E, the abundance of Clostridium_sensu_stricto_1 and Romboutsia in the FMT-HFD group was higher than observed in the FMT-ORL group, while norank_f__Muribaculaceae, Lactobacillus, Ileibacterium, and Coriobacteriaceae_UCG-002 were less abundant in the FMT-HFD group compared to the FMT-ORL group. Figure 7G shows that Wilcoxon rank-sum test analysis indicated that Ileibacterium, Coriobacteriaceae_UCG-002, Alloprevotella, and Akkermansia were more abundant in the FMT-ORL group than in the FMT-HFD group (p < 0.05), while Romboutsia was less abundant in the FMT-ORL group (p < 0.05). The differences at the genus level between the FMT-ORL and FMT-HFD groups remain largely consistent with those observed earlier. Notably, similar to previous experimental conditions or dietary groups, the abundance of Akkermansia and Allobaculum, particularly Akkermansia, were significantly upregulated in the FMT-ORL group.

To analyze changes in the composition of gut microbiota between the two groups of mice, we used LEfSe analysis to identify characteristic taxa in each group (Figures 7I,J). The results showed that when the LDA score was >3, there were 13 characteristic groups in the FMT-HFD group and 12 characteristic groups in the FMT-ORL group. The FMT-ORL group was particularly rich in the phylum Verrucomicrobiota, order Verrucomicrobiales, and genus Akkermansia. These findings indicate that mice transplanted with fecal microbiota from the HFD and ORL groups exhibited similar gut microbiota communities when compared to HFD-fed mice and Orlistat-treated mice.

To further analyze the correlation between key microorganisms regulated by Orlistat and lipid metabolism indicators, we performed Spearman correlation analysis and generated a correlation heatmap (Figure 7K). The results revealed a significant negative correlation (p < 0.05) between the abundance of Akkermansia and the degree of hepatocyte steatosis as well as serum lipid indicators (e.g., TG, TC, LDL). Additionally, the abundance of Akkermansia showed a positive correlation with that of Allobaculum and Clostridium_sensu_stricto_1, suggesting that these microorganisms may play synergistic roles in the improvement of lipid metabolism by Orlistat.