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. 2024 Apr 4;72(15):8536–8549. doi: 10.1021/acs.jafc.3c08910

Probiotic Mixture Ameliorates a Diet-Induced MASLD/MASH Murine Model through the Regulation of Hepatic Lipid Metabolism and the Gut Microbiome

Fangfei Zhang †, Emily Kwun Kwan Lo †, Jiarui Chen ‡,§,∥, Ke Wang ⊥,#, Felicianna †, Marsena Jasiel Ismaiah †, Hoi Kit Matthew Leung †, Danyue Zhao ⊥,#,*, Jetty Chung-Yung Lee †, Hani El-Nezami †,∇,*
PMCID: PMC11037262  PMID: 38575146

Abstract

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Metabolic dysfunction-associated steatotic liver disease (MASLD) is a prevalent metabolic disease that has no effective treatment. Our proprietary probiotic mixture, Prohep, has been proven in a previous study to be helpful in reducing hepatocellular carcinoma (HCC) in vivo. However, its prospective benefits on the treatment of other liver diseases such as MASLD, which is one of the major risk factors in the development of HCC, are unclear. To investigate the potential of Prohep in modulating the development and progression of MASLD, we first explored the effect of Prohep supplementation via voluntary intake in a high-fat diet (HFD)-induced MASLD/metabolic dysfunction-associated steatohepatitis (MASH) murine model. Our results indicated that Prohep alleviated HFD-induced liver steatosis and reduced excessive hepatic lipid accumulation and improved the plasma lipid profile when compared with HFD-fed control mice through suppressing hepatic de novo lipogenesis and cholesterol biosynthesis gene expressions. In addition, Prohep was able to modulate the gut microbiome, modify the bile acid (BA) profile, and elevate fecal short-chain fatty acid (SCFA) levels. Next, in a prolonged HFD-feeding MASLD/MASH model, we observed the effectiveness of Prohep in preventing the transition from MASLD to MASH via amelioration in hepatic steatosis, inflammation, and fibrosis. Taken together, Prohep could ameliorate HFD-induced MASLD and control the MASLD-to-MASH progression in mice. Our findings provide distinctive insights into the development of novel microbial therapy for the management of MASLD and MASH.

Keywords: metabolic dysfunction-associated steatotic liver disease, probiotic, gut microbiota, short-chain fatty acid, bile acid

1. Introduction

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a common chronic liver disease, which affects 20–30% of the global population.1 The manifestation of MASLD is a spectrum linked with a wide range of metabolic dysfunctions in parallel with hepatic lipid accumulation, inflammation, apoptosis, and fibrosis and commonly co-occurs with obesity, type 2 diabetes, and cardiovascular diseases.2 The early stage of MASLD usually starts from benign steatosis without hepatocellular injury.3 With too much fat building up in the liver, the continuous metabolic overload could lead to oxidative stress, endoplasmic reticulum (ER) stress, and hepatocyte apoptosis that prompt the progression of MASLD to metabolic dysfunction-associated steatohepatitis (MASH).4 Eventually, pathological MASH develops, which is characterized by hepatic fat accumulation, lobular inflammation, and hepatocellular ballooning.5 The rising prevalence of MASH in the past decade made it the fastest growing cause of liver cancer in the United States, Europe, and Asia.6 To date, there is a lack of approved drug or promising surgical intervention for MASH treatment, while the most recommended approach for MASLD-MASH management is lifestyle modification that aims mainly in controlling metabolic disorder to benefit MASLD treatment.7

It is well-known that the gut–liver axis participates in the progression of numerous liver diseases including MASLD, MASH, cholestatic liver diseases, and hepatocellular carcinoma (HCC).8 The liver and gut crosstalk with each other mainly through two paths, the hepatic portal vein and bile acids (BAs). The hepatic portal vein carries most of the blood supply from the intestine to the liver, while BAs from the liver transport the metabolites to the intestine.9 Because of the close association between the gut and the liver, the health status of the gut and the residing microbiota are associated with liver diseases including MASLD.10 Consequently, gut microbiome modulation could be a therapeutic target in MASLD.

Probiotics are live bacteria that can confer a beneficial effect on human health when administered in adequate amounts.11 Microbial therapies have been shown to benefit the host via several mechanisms including competition for space with pathogenic bacteria, synthesis of nutrients, maintenance of mucosal integrity and intestinal barrier function, action on the intestinal immune system, regulation of gut mobility, and so on.12 Probiotic strains, namely, Lactobacillus rhamnosus and Lactobacillus paracasei, have previously been found to improve liver steatosis via the modulation of lipid metabolism and production of gut microbiota-derived metabolites.13 Gut microbiota-derived metabolites, such as short-chain fatty acids (SCFAs) and secondary BAs, could alleviate energy expenditure, insulin sensitivity, and lipid metabolism.14 Although increasing the individual probiotic strain was identified to be beneficial to the liver health, multistrained probiotic mixtures were reported to have additive and synergistic effects among strains15 and hence provide a wider coverage of actions than an individual strain.16 Prohep, a novel multistrain formulation, has previously been shown to have antitumor, anti-inflammatory, and immune-modulating effects in hepatocellular carcinoma.17 Considering the modulating effect of Prohep on the gut microbiota, we hypothesized that it could attenuate MASLD through the regulation of the gut microbiota due to the microbial metabolites produced. In this study, the alleviated effect of Prohep was first tested in a high-fat diet-induced (HFD) MASLD model. Thereafter, we examined its efficacy and mechanisms of action in preventing the deteriorating progression from MASLD to MASH in HFD-fed mice.

2. Materials and Methods

2.1. Probiotic Mixture Composition

Prohep is a new proprietary probiotic mixture developed by our team17 (IP00475). The formula was slightly modified and composed of Lactobacillus helveticus, Bifidobacterium lactis, Lactobacillus plantarum (L. plantarum), Lactobacillus rhamnosus, Lactobacillus paracasei (L. paracasei), Lactobacillus acidophilus, Bifidobacterium breve, and Streptococcus thermophilus in lyophilized powder, produced under GMP (Fukopharma, Finland).

2.2. Animals and Prohep Administration

Eight-weeks-old male C57BL/6J mice (Center of Comparative Medicine Research, The University of Hong Kong) were maintained under controlled environmental conditions (23 ± 1 °C, 50–60% humidity, and 12 h light/dark cycles) with food and water ad libitum. The body weight and food intake were monitored weekly. All animal experimental procedures were approved by the Committee on the Use of Live Animals in Teaching and Research at the University of Hong Kong (reference number CULATR 5933-21) and received humane care according to the criteria outlined in the “Guide for the Care and Use of Laboratory Animals.” After 1 week of acclimatization, the mice were trained for voluntary oral administration as previously described.18 The mice were then randomly distributed and fed with either an HFD (containing 42% fat, 44% carbohydrates, 14% proteins, and 0.2% cholesterol, TP26304, trophic diet, Nantong, China) or a normal chow diet (containing 10% fat from lard, 70% carbohydrates, and 20% proteins, D12450J, Research Diets, New Brunswick, NJ) plus daily administration of either 0.25 g of MediGel sucralose (ClearH2O, ME, US), which served as a control gel, or 7 × 109 CFU per mice of Prohep in a control gel that added up to 0.25 g.

In the MASLD model, eight-weeks-old male C57BL/6J mice (n = 28, Center of Comparative Medicine Research, The University of Hong Kong) were given an HFD for 16 weeks. The mice were randomly divided into three groups (n = 9–10) (Figure 1): (1) mice fed with NC and given daily supplementation of the control gel; (2) mice fed with HFD and given daily supplementation of the control gel; (3) mice fed with HFD and given daily supplementation of Prohep in a control gel. In the MASLD-MASH model, eight-weeks-old male C57BL/6J mice (n = 20) were given an HFD for 24 weeks. The mice were randomly divided into two groups (n = 10): (1) mice fed with HFD and given daily supplementation of the control gel; (2) mice fed with HFD and given daily supplementation of Prohep in a control gel. At the end of weeks 16 (MASLD model) and 24 (MASLD-MASH model), the mice were sacrificed by an overdose of sodium pentobarbital. Whole blood was collected from the inferior vena cava and coagulated in a CAT serum clot activator (Greiner Bio One, Austria). Then, they were centrifuged at 2000g for 15 min at 4 °C. The supernatant (serum) was taken and stored in −80 °C for subsequent experiments. Liver and epidermal white adipose tissues (eWAT) were dissected and weighted. Parts of the organs were snap-frozen in liquid nitrogen and stored in −80 °C for subsequent experiments.

Figure 1.

Figure 1

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Experimental design of the study. MASLD, metabolic dysfunction-associated steatotic liver disease; MASH, metabolic dysfunction-associated steatohepatitis; NC, normal chow; HFD, high-fat diet.

2.3. Histopathological Analysis

Fresh mouse liver tissues were processed and embedded in paraffin or directly embedded with an optimal cutting temperature compound to make frozen sections (Sakura Finetek USA, lnc., Torrance). The paraffin sections were prepared in 5 μm thickness, subsequently deparaffinized, and rehydrated in xylene and graded ethanol. The sections were stained with a hematoxylin and eosin (H&E) kit according to the manufacturer’s instructions (BASO, Wuhan, China) to evaluate the morphology. Hepatic pathology was evaluated according to the NAFLD activity score (NAS).19 Based on the pathological appearance, steatosis, lobular inflammation, and hepatocyte ballooning were assessed. For steatosis, 0: steatosis area < 5%; 1: steatosis area = 5–33%; 2: steatosis area = 33–66%; 3: steatosis area > 66%. For lobular inflammation, 0: no foci; 1: <2 foci per 200× field; 2: 2–4 foci per 200× field; 3: >4 foci per 200× field. For hepatocyte ballooning, 0: none; 1: few balloon cells; 1: many balloon cells.19 Sirius red staining (Abcam, Cambridge, UK) was also performed according to the manufacturer’s protocol in order to evaluate the degree of liver collagen deposition and fibrosis. The degree of liver fibrosis was quantified by calculating the percentage of the positive red staining area over the total colon area measured. The frozen sections were processed for oil red O (ORO) staining to evaluate the intrahepatic lipids using an oil red O stain kit (BASO, Wuhan, China). All sections were visualized with a biological microscope (Olympus, BX41), and images were captured with a color digital camera (Olympus, DP72). Periodic acid–Schiff (PAS) staining20 was used to evaluate the intrahepatic glycogen.

2.4. Biochemical Measurements in Serum

A volume of 20 μL of serum was diluted 5 times with deionized H2O for biochemical measurements. Serum total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), alanine aminotransferease (ALT), and aspartate aminotransferase (AST) were measured using a cobas c111 analyzer (Roche Diagnostics; Indianapolis, IN, USA) according to the manufacturer’s instructions.

2.5. Hepatic Content Extraction and Measurement

The hepatic TC, triglycerides (TG), and glycogen were extracted and measured using a cholesterol assay kit HDL and LDL/VLDL (ab65390), triglyceride assay kit quantification (ab65336), and a glycogen assay kit (ab65620). The absorbances were measured using a microplate reader at OD 570 nm for the colorimetric assay according to the manufacturer’s instructions (Abcam, UK). For hepatic cytokines, liver tissues were homogenized with a RIPA buffer, and the levels of tumor necrosis factor-α (TNF-α), interleukin-17 (IL-17), interleukin-6 (IL-6), and interleukin-10 (IL-10) were determined via measuring the absorbance at 450 nm according to the manufacturer’s instructions (BioLegend, lnc., San Diego, CA).

2.6. Quantitative Real-Time Polymerase Chain Reaction (RT-qPCR)

RNA was extracted from mouse livers using an RNeasy Plus mini kit (Qiagen, Germany). The integrity of the RNA was confirmed through gel electrophoresis, and the concentrations were checked using Thermo Scientific NanoDrop 2000/2000c spectrophotometers. cDNA was synthesized from 2 μg of RNA, using a HiScript II QRT supermix for qPCR (Vazyme Biotech, Nanjing, China). For RT-qPCR, a reaction mixture containing an AceQ qPCR SYBR Green Master mix (Vazyme Biotech, China), cDNA and primers was prepared. The sequences of primers used in this study are listed in Table S1. Relative gene expression was normalized to β-actin and calculated by the 2–ΔΔCt method.

2.7. Short-Chain Fatty Acid Analysis

Short-chain fatty acids (SCFAs), including acetate, propionate, butyrate, and isobutyrate levels, were quantified in fecal samples as previously described, with modifications.21,22 In brief, around 50 mg of fecal samples was homogenized in a 0.005 M sodium hydroxide buffer containing an internal standard (10 μg/mL acetic acid-d4, Cambridge Isotope Laboratories, USA) and centrifuged at 13,200g for 20 min at 4 °C. The supernatant was mixed with 0.5 mL of 1-propanol/pyridine (3:2, v/v) and 0.1 mL of propyl chloroformate. After incubation at 60 °C for 1 h, 0.5 mL of hexane was added and centrifuged for 5 min at 2000g. A volume of 0.4 mL of the upper layer was transferred to a glass vial for GC–MS analysis (Agilent 6890 N-5973 GC-MS, USA) under the conditions described by Zheng.21 The derivative (1 μL) was injected in the split mode with a ratio of 10:1. The electron energy was −70 eV, and mass spectral data were recorded in a full-scan mode (m/z 30–600). The content of SCFAs was then quantified using calibration curves constructed using the peak area of acetate, propionate, butyrate, and isobutyrate against acetic acid-d4.

2.8. Bile Acid Analysis

Bile acid (BA) was quantified in cecal samples as previously described.23 Cecal samples (100 mg) were homogenized in 5 volumes of ice-cold methanol and spiked with an internal standard (cholic acid-d4, deoxycholic acid-d4, and tauro-cholic acid-d4; Cayman, MI, USA) at a final concentration of 50 ng/mL. The homogenate was vortexed vigorously for 1 min, incubated at room temperature for 15 min, and centrifuged at 17,000g at 4 °C for 10 min. The recovered organic supernatants were then dried by a SpeedVac vacuum concentrator. The residue was reconstituted with 100 μL of 50% methanol, vortexed for 1 min, sonicated for 5 min, and centrifuged at 17,000g for 10 min. The supernatant was collected and analyzed by LC-MS/MS (UHPLC-QTrap-MS/MS, AB Sciex, Foster City, CA, USA). The chromatographic column used was a Waters ACQUITY HSS T3 column, 2.1 × 100 mm, 1.8 μm (Milford, MA, USA) equipped with an HSS T3 VanGuard precolumn (2.1 × 5 mm, 1.8 μm). The column temperature was 40 °C, and the injection volume was 1 μL. UHPLC was set accordingly: the mobile phase was composed of 0.1% (v/v) formic acid for mobile phase A and 0.1% (v/v) formic acid in acetonitrile for mobile phase B. The flow rate was set at 0.3 mL/min. The gradient elution program was as follows: at 30% B; 1 min, 30% B; 6 min, 65% B; 9 min, 98% B; 11 min, 98% B; 11.1 min, 30% B; 14 min, 30% B.

2.9. Total Microbial DNA Extraction and Metagenomic Sequencing

DNA of the fecal samples was extracted using a QIAamp PowerFecal Pro DNA kit (Qiagen, Germany) according to the manufacturer’s instructions and stored at −80 °C. The integrity of the DNA was confirmed through gel electrophoresis, and the purity and concentrations were checked using Thermo Scientific NanoDrop 2000/2000c spectrophotometers (Thermo Scientific, DE, USA). After passing the quality check, the extracted samples (n = 9–10 per group) were sent to Beijing Genomics Institute Hong Kong Co., Limited (BGI, Hong Kong) for sequencing using the DNBseq platform (BGI, Tianjin). The raw pair-end reads generated from metagenomic shotgun sequencing were aligned to the mouse reference genome GRCm39 using BWA-MEM24 for host contamination removal. Adaptor regions, low-quality reads, and PCR duplicates were further filtered with an in-house script as previously described.17 Details about the metagenomic profiling and corresponding statistical analysis are provided in the Supporting Information.

2.10. Statistical Analysis

Aside from the metagenomics analysis as described above, another statistical analysis was performed with GraphPad Prism 8.0 (GraphPad Software, San Diego, CA, USA) unless specified.

Results are expressed as means ± standard deviation (SD). Outliers were identified using Grubbs’ test. Comparisons of differences between two groups were analyzed with Student’s t tests or Mann–Whitney U tests. Comparisons of differences in more than two groups were analyzed with one-way analysis of variance (ANOVA) followed by Tukey’s multiple comparison test or the Kruskal–Wallis test followed by Dunn’s multiple comparison test. P values of <0.05 were considered statistically significant.

3. Results

3.1. Prohep Attenuated High-Fat Diet (HFD)-Induced MASLD Progression

The protective effect of Prohep on HFD-induced MASLD mice was first evaluated by assessing their liver function and lipid profile. Overall, Prohep ameliorated hepatic steatosis, tissue inflammation, and metabolic disorders in a mouse model of HFD-induced MASLD. HFD-fed mice showed a significantly higher body weight than normal chow (NC) groups (Figure 2A). Although no significant differences in body weight, food intake, or eWAT weights were found between the Prohep group and the HFD group (Figure S1A–C), the liver-to-body ratio was significantly decreased in the Prohep group (Figure 2B). In addition, Prohep significantly decreased the serum ALT level (Figure 2C).

Figure 2.

Figure 2

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Prohep exhibits a therapeutic effect on HFD-induced MASLD. (A) Body weight of mice at week 16. (B) Liver-to-body weight ratio. (C) Representative images of H&E and ORO (arrows indicate lipid droplets) staining of liver specimens. (D) Serum ALT and AST levels. (E) Serum TC, LDL-C, and HDL-C levels. (F) Hepatic TC and TG levels. (G) Relative expression of cholesterol biosynthesis, de novo lipogenesis, and β-oxidation genes. (H) Hepatic levels of proinflammatory cytokines IL-17, IL-6, and TNF-α and anti-inflammatory cytokine IL-10. Data are presented as the mean ± SD. One-way ANOVA followed by Tukey’s multiple comparison tests were used among NC, HFD-E, and HFDP-E groups. Student’s t tests were used between HFD-E and HFDP-E groups. *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

Fasting blood glucose, glucose tolerance, and insulin resistance were significantly improved in HFDP-E when compared to the HFD-E group (Figure S1D–F). Moreover, Prohep alleviated blood dyslipidemia resulting from HFD feeding by significantly lowering serum TC, LDL-C, and HDL-C (Figure 2D). Images of H&E (NAS score, Figure S1J) and ORO staining revealed that Prohep reduced HFD-induced hepatic lipid accumulation (Figure 2E). In addition, we also found that intrahepatic TG and TC levels were significantly decreased in the HFDP-E group when compared to the HFD group (Figure 2F).

In agreement with the suppression in hepatic lipid accumulation, we found significant downregulation of the expression of key cholesterol metabolism genes, ACAT2, HMGCR, IDI, MVK, MVD, FDTF1, and LSS, as well as fatty acid metabolism genes FASN (Figure S1H) and ACC in the HFDP-E group. The β-oxidation gene CPT1 was significantly upregulated in the HFDP-E group (Figure 2G). We further investigated the effect of Prohep on hepatic inflammation. Prohep significantly reduced secretion of proinflammatory cytokines, including IL-17, TNF-α, and IL-6, but increased an anti-inflammatory cytokine, IL-10, when compared to the HFD-E group (Figure 2H).

3.2. Prohep Alleviated HFD-Induced Gut Microbiota Dysbiosis in an MASLD Mouse Model

Next, we investigated the impact of Prohep on gut microbiota composition through shotgun sequencing. Alpha diversity (Shannon and Chao-1 indices) (Figure 3A) was significantly increased in the HFDP-E groups, which indicated an increase in species richness. Furthermore, nonmetric multidimensional scaling (NMDS) was performed with the Bray–Curtis distance revealing a significant separation in the gut microbiota structure among NC, HFD-E, and HFDP-E groups (Figure 3B, p < 0.05, PERMANOVA). At the genus level, Bifidobacterium, Dubosiella, Muribaculum, and Streptococcus were amplified in the HFDP-E group (Figure S2). At the species level, we found that some species, e.g., Bifidobacterium animalis, Bifidobacterium breve, Lactobacillus acidophilus, Lactobacillus plantarum, Lactobacillus rhamnosus, and Streptococcus thermophilus, which are components of the Prohep mixture, increased in abundance, which suggests a successful colonization of these bacteria to the gut (Figure 3C). In addition, other species, including Dubosiella newyorkensis, Helicobacter typhonius, Lachnospiraceae bacterium COE1, and Muribaculum intestinale, were enriched in the HFDP-E group (Figure 3C). To identify the connections among gut microbes, we established a coabundance network based on the relative abundance of bacterial species to gain a better grasp of the interactions between species and overall connectedness within communities (Figure 3D). Notably, coabundance analysis revealed that Prohep strains Bifidobacterium animalis, Bifidobacterium breve, Lactobacillus acidophilus, Lactobacillus plantarum, Lactobacillus rhamnosus, and Streptococcus thermophilus and Prohep-promoted strains Helicobacter typhonius and Lachnospiraceae bacterium COE1 were highly associated with each other. They contributed collectively to modulate the gut microbiota composition via inhibiting the growth of Helicobacter ganmani and Acutalibacter muris and promote the increase of species commonly associated with beneficial effects, notably Dubosiella newyorkensis and Muribaculum intestinale. Among these, Bifidobacterium breve and Helicobacter typhonius were identified to be the main contributors of the gut microbiota modulations, which significantly correlated with 12 other species including Acutalibacter muris, Streptococcus thermophilus, Lactobacillus rhamnosus, Bifidobacterium animalis, Lactobacillus acidophilus, Lactobacillus plantarum, Helicobacter ganmani, Turicimonas muris, Lachnospiraceae bacterium 10-1, Alistipes timonensis, Enterorhabdus cecimuris, and Faecalibaculum rodentium.

Figure 3.

Figure 3

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Prohep regulated the composition of the intestinal microbiota. (A) Shannon and Chao-1 diversity indices, (B) NMDS analysis, and (C) gut microbial compositions with significant differentiations in abundance at the species level. (D) Coabundance network among the significant species in MASLD mice. Nodes filled in gray and pink represent species enriched in HFD-E and HFDP-E, respectively. The key species with the highest degree are marked in black circles. The edges colored in red and blue represent the positive and negative correlation, respectively. The color of the edges indicates the correlation coefficient value. Data are presented as the mean ± SD. One-way ANOVA followed by Tukey’s multiple comparison tests were used among NC, HFD-E, and HFDP-E groups. Student’s t tests were used between HFD-E and HFDP-E. *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

3.3. Prohep Altered SCFA and BA Profiles in an MASLD Mouse Model

As the microbial functional analysis revealed a potential enrichment of bacteria involved in the biosynthesis of SCFAs and metabolism of BAs in the HFDP-E group (Figure 4A), SCFA and BA levels were further examined. We first examined SCFA levels in fecal samples where two SCFAs, namely, acetate and isobutyrate, and the total SCFA levels showed a significant increase in the Prohep group compared to the HFD group (Figure 4B). Moreover, the mRNA expression of a hepatic SCFA receptor, G protein-coupled receptor 43 (GPR43), was significantly upregulated in the HFDP-E group compared to HFD-E, which implied that GPR43 is activated in the Prohep group compared to the HFD group (Figure 4C).

Figure 4.

Figure 4

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Prohep treatment modulated microbial functions, elevated SCFA production, and altered BA metabolism in the HFD-E and HFDP-E groups. (A) Significantly enriched KEGG pathways generated from fecal metagenomic data. (B) Fecal SCFA compositions. (C) Hepatic expression of GPR43. (D) Cecal total BA amount. (E) Cecal BA compositions. (F) Cecal levels of significantly altered BA species. (G) Spearman correlations between bacterial relative abundance and metabolic indices from feces, serum, cecal content, and liver. Small circles indicate FDR < 0.25, and big circles indicate p < 0.05 and FDR < 0.25. Data are presented as the mean ± SD. Student’s t tests were used. *p < 0.05.

Next, we further investigated the BA levels in the cecal content. The total cecal BA content was increased in the HFDP-E group (Figure 4D). Prohep treatment remarkably changed the cecal BA pool (Figure 4E,F and Figure S5A) where conjugated BAs, tauro-lithocholate acid (TLCA), tauro-deoxycholic acid (TDCA), tauro-cholic acid (TCA), tauro-ursodeoxycholic acid (TUDCA), tauro-chenodeoxycholic acid (TCDCA), and tauro-β-muricholic acid (T-β-MCA) and unconjugated BAs, including chenodeoxycholic acid (CDCA), lithocholate (LCA), and ω-muricholic acid (ω-MCA), were increased in the HFDP-E group (Figure 4F).

To identify the association of gut microbiome signatures with metabolic indices, we calculated the Spearman correlations between bacterial relative abundances and metabolic index measurements (Figure 4G). Prohep strains, Bifidobacterium animalis, Bifidobacterium breve, Lactobacillus acidophilus, Lactobacillus plantarum, Lactobacillus rhamnosus, and Streptococcus thermophilus and Prohep-promoted strains, Dubosiella newyorkensis and Helicobacter typhonius, were negatively correlated with the liver-to-body weight ratio, hepatic TG and TC levels, and serum LDL levels. In addition, these species were negatively correlated with the levels of hepatic inflammatory cytokines, e.g., IL-6 and IL-17, and positively correlated with the level of anti-inflammatory cytokines, e.g., IL-10. Noteworthily, Lachnospiraceae bacterium COE1, Lactobacillus acidophilus, Dubosiella newyorkensis, and Helicobacter typhonius were negatively correlated with the liver ALT level. In terms of bacterial secondary metabolites, Prohep strains were positively correlated with fecal acetate and butyrate levels and cecal TLCA, TDCA, ω-MCA, and LCA levels.

3.4. Prohep protected against MASLD-to-MASH progression in HFD-fed mice

To explore the impact of Prohep on the pathological progression of MASLD to MASH, the mice were subjected to HFD feeding for 8 weeks before the intervention, i.e., the MASLD model is well-established, while the MASH characteristics are yet to manifest (Figure 1).25 Consistent with our findings in the MASLD study, Prohep significantly decreased the liver-to-body weight ratio (Figure 5A) and alleviated glucose intolerance and insulin resistance (Figure S2D,E). Serum ALT, TC, HCL-C, and LDL-C levels were also reduced (Figure 5B,C). Both histological analyses (Figure 5D) (NAS score, Figure S2K) and hepatic TG and TC measurements (Figure 5E) displayed less lipid accumulation in the HFDP-L group. On top of this, assessed by Sirius red staining, less severe fibrosis (which was not prominent in the MASLD model) was observed in the HFDP-L group (Figure 5D). Furthermore, hepatic glycogen deposition, measured by PAS staining, was significantly increased in the HFDP-L group (Figure S2G). Furthermore, Prohep administration downregulated mRNA expressions of genes (Figure 5F) related to cholesterol biosynthesis (ACAT2, IDI, FDTF1, LSS, and MVK), de novo lipogenesis (FASN (Figure S2H) and ACC), and an insulin receptor (IRS2). Moreover, the HFDP-L group also had a higher hepatic level of anti-inflammatory cytokine IL-10 and a lower level of proinflammatory cytokine IL-6 when compared to the HFD-L group (Figure 5G). These results indicated that the Prohep could effectively prevent the deteriorating progression from MASLD to MASH.

Figure 5.

Figure 5

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Prohep protected against MASLD-to-MASH progression in HFD-fed mice. (A) Body weight. (B) Liver-to-body weight ratio of mice at week 24. (B) Serum ALT and AST levels. (C) Serum TC, LDL-C HDL-C levels. (D) Representative images of H&E, ORO (Arrow indicates lipid droplet) and Sirius Red (Arrow indicates hepatic collagen) staining of the liver. (E) Hepatic TC and TG levels. (F) Hepatic levels of proinflammatory cytokine IL-6 and anti-inflammatory cytokine IL-10. (G) Relative mRNA expression of genes for cholesterol biosynthesis, de novo lipogenesis, and insulin receptor. Data are presented as the mean ± SD. Student’s t tests were used. *p < 0.05.

3.5. Prohep Regulated the Gut Microbiota Composition and Promoted the Production of SCFA and the Deconjugation Process of BA Metabolism in an MASLD-MASH Mouse Model

We further investigated the modulatory effects of Prohep on the gut microbiome in an HFD-induced MASLD-MASH mouse model. The Prohep treatment increased the Chao-1 diversity in the HFDP-L group (Figure 6A). At the genus level, the differential abundances of Akkermansia and Streptococcus were increased in the HFDP-L group (Figure S4). At the species level, Lactobacillus acidophilus, Lactobacillus plantarum, Lactobacillus rhamnosus, Bifidobacterium animalis, Akkermansia muciniphila, Streptococcus thermophilus, Bifidobacterium breve, and Bacteroides cecimuris were enriched in the HFDP-L group, whereas Acetatifactor muris, Asaccharobacter celatus, Adlercreutzia equolifaciens, Faecalibaculum rodentium, Helicobacter ganmani, and Clostridium cocleatum were decreased in the HFDP-L group (Figure 6C). Consistent with the findings from the MASLD model (Figure 4), 6 Prohep strains, namely, Lactobacillus acidophilus, Lactobacillus plantarum, Lactobacillus rhamnosus, Bifidobacterium animalis, Streptococcus thermophilus, and Bifidobacterium breve were enriched. The 6 Prohep strains and Bacteroides cecimuris showed robust positive correlations in Spearman correlation analysis, while these strains negatively correlated with Faecalibaculum rodentium (Figure 6D). Importantly, among them, 5 Prohep strains, namely, Lactobacillus acidophilus, Lactobacillus plantarum, Lactobacillus rhamnosus, Streptococcus thermophilus, and Bifidobacterium breve, were identified to be the main contributors of gut microbiota modulations since they possessed the highest node degree in the networks (Figure 6D). Noteworthily, in both MASLD and MASLD-MASH studies, one Prohep strain Bifidobacterium breve was one of the main contributors. Yet, some differences were observed regarding the microbiota remodeling effects in MASLD and MASLD-MASH studies, which are likely attributable to the differences in the Prohep intervention scheme and duration of HFD intake.

Figure 6.

Figure 6

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Prohep regulated the gut microbiota composition, SCFA production, and BA metabolism. (A) Shannon and Chao-1 diversity. (B) NMDS analysis. (C) Gut microbial compositions with significant differentiations in abundance at the species level. (D) Coabundance network among the significant species in MASLD-MASH mice. Nodes filled in dark blue and purple represent species enriched in HFD-L and HFDP-L, respectively. The key species with the highest degree are marked in black circles. The edges colored in red and blue represent the positive and negative correlation, respectively. The color of the edges indicates the correlation coefficient value. (E) Fecal SCFA contents between HFD-L and HFDP-L. (F) Hepatic expression of GPR43 between HFD-L and HFDP-L. (G) Total BA amount in the cecal content. (H) Cecal secondary-to-primary BA ratio. (I) Cecal conjugated/unconjugated BA ratio. (J) Cecal BA composition. (K) Measurements of significantly altered BA species. Data are presented as the mean ± SD. Student’s t tests were used. *p < 0.05.

Consistent with our findings in the MASLD study (Figure 4), the modulation of the gut microbiota altered the profile of bacterial secondary metabolites, especially SCFAs, in the MASLD-MASH study. The acetate and isobutyrate levels were increased in the HFDP-L group when compared to those in HFD-L (Figure 6E). Bacteroides cecimuris was positively correlated with the increase in acetate, while the Prohep strain Bifidobacterium animalis was positively correlated with the increase in isobutyrate levels (Figure S6). The increased production of SCFAs by gut microbes in the HFDP-L group was accompanied by the significantly upregulated hepatic GPR43 gene expression (Figure 6F). Furthermore, the regulatory effects of gut microbiota on BA metabolism were also confirmed in the MASLD-MASH model. Although the increase of the cecal total BA level was not statistically significant when compared to HFD-L (Figure 6G), the ratio of secondary-to-primary BAs was significantly increased (Figure 6H). Furthermore, the ratio of conjugated to unconjugated BAs was significantly decreased (Figure 6I). Notably, Prohep markedly modulated the BA pool (Figure 6J) and increased the levels of LCA and ω-MCA (Figure 6K), and the aforementioned 6 Prohep strains, Lactobacillus acidophilus, Lactobacillus plantarum, Lactobacillus rhamnosus, Bifidobacterium animalis, Streptococcus thermophilus, and Bifidobacterium breve, were positively correlated with the production of LCA especially.

4. Discussion

The present study was designed to investigate the efficacy of a probiotic cocktail, Prohep, in treating diet-induced fatty liver diseases, particularly MASLD and MASH. Prohep was previously shown to inhibit tumor growth in hepatocellular carcinoma through suppressing the inflammatory cytokine IL-17.17 Here, we found that in addition to its immunomodulatory properties, Prohep also alleviated hepatic steatosis, attenuated hypercholesterolemia, and favorably modulated gut microbiota composition and functions. These findings suggest that Prohep may be an effective microbial therapy for MASLD and MASH.

Given that probiotics are bacteria that do not have direct access to the liver, we believe that the effectiveness of Prohep is achieved through its modulatory actions on the resident gut micro-organisms and the release of beneficial secondary metabolites. Prohep was found to suppress a previously reported microbial signature in MASLD, Bacteroides vulgatus (Figure 3C,D). Bacteroides vulgatus is one of the enriched gut microbes in mild/moderate MASLD and advanced fibrosis patients.26,27 Its abundance was positively correlated with proinflammatory mediators including IL-6, TNF-α, insulin resistance, and obesity in multiple in vivo and in vitro studies.28−30 In the meantime, two beneficial strains, Dubosiella newyorkensis and Muribaculum intestinale, were enriched in the HFDP-E group (Figure 3C,D). Dubosiella newyorkensis was previously identified as a promising probiotic for its ability to produce l-lysine, which contributes to an immunosuppressive microenvironment mediated by the Treg in inflammatory bowel diseases.31,32Muribaculum intestinale is a newly culturable species and has been reported to decrease in abundance upon HFD feeding.33 In both MASLD and MASLD-MASH studies, coabundance analysis revealed that component species of Prohep, Bifidobacterium animalis, Bifidobacterium breve, Lactobacillus acidophilus, Lactobacillus plantarum, Lactobacillus rhamnosus, and Streptococcus thermophilus, contributed largely to the modulation of gut microbiota (Figures 3D and 6D). Of note, two main contributors identified from the coabundance analysis were a component of Prohep, Bifidobacterium breve, and another newly identified bacterium, Helicobacter typhonius. While previous studies have shown an enrichment of Helicobacter typhonius in immunodeficient enteric disease mice34 and intestine-specific conditional Apc mutant mice with an intestinal tumor,35 there has not been a comprehensive evaluation of its involvement in gut microbial dysbiosis generated by an HFD. In the present study, we observed a positive correlation between the abundance of Helicobacter typhonius and the levels of fecal isobutyrate, butyrate, and acetate. Conversely, we found a negative correlation between its abundance and hepatic TG and TC levels as well as inflammatory responses. Further research is required to enhance our understanding of the role of Helicobacter typhonius in various disease conditions.

To determine the potential mechanisms by which the present probiotic combination produced these favorable effects, we conducted a KEGG pathway enrichment analysis of the gut microbiota. Consistent with a previous study,17 our data show that KEGG pathways, “propanoate metabolism” and “pyruvate metabolism”, were enriched in the HFDP-E group (Figure 4A). Both contribute to the overall production of SCFAs. In accordance with the KEGG pathway analyses, Prohep increased the acetate level and the total fecal SCFA content as well as upregulated a hepatic SCFA receptor, GPR43. Indeed, acetic acid was previously reported to reduce hyperglycemia through binding to GPR43, which activates AMP-activated protein kinase (AMPK)-initiated pathways.36,37 Activation of AMPK signaling in the liver could simulate oxidative metabolism, by which our body utilizes fat to generate energy.37 Our results show that Prohep decreased hepatic TG levels and downregulated the hepatic expression of de novo lipogenesis enzymes, FAS and ACC1, while it upregulated the fatty acid oxidation enzyme CPT1 expression (Figure 2F,G). Indeed, hepatic fat accumulation plays a major role in the development of MASLD. Previous studies on Prohep strains, L. plantarum(14) and Lactobacillus paracasei,38 also showed their effects in suppressing hepatic lipid accumulation. Specifically, L. plantarum supplementation was proven to regulate the de novo lipogenesis through the Srebp-1c-ACC/FAS/SCD-1 pathway in the liver.39

Abnormalities in hepatic lipid composition are strongly linked to lipotoxicity that could lead to organelle dysfunction, chronic inflammation, cellular damage, and even cell death.40,41 To assess the effects of Prohep on liver inflammatory responses, we examined various levels of liver cytokines. Our results also demonstrate that Prohep suppressed hepatic inflammatory cytokines, mainly IL-6, IL-17, and TNF-α, while increasing the secretion of anti-inflammatory cytokines, mainly IL-10 (Figures 2H and 5G). Without the control of hepatic inflammation, the prolonged presence of inflammatory activity may exacerbate tissue injury and impair normal wound healing responses, thereby accelerating the progression from MASLD to MASH,42,43 which is characterized by steatosis, inflammation, and hepatocellular injury with varying degrees of fibrosis.44 By suppressing lipid accumulation, SCFAs could control inflammatory response in the liver.45 SCFA acetate was previously reported to decrease serum IL-1β and IL-6 levels in HFD-induced diabetic mice.46 Our results suggest that the effect of Prohep is partly contributed by its ability to increase microbial SCFA production.

Hepatic cholesterol was lowered in the Prohep-treated group in both MASLD and MASLD-MASH studies, through suppressing hepatic cholesterol biosynthesis genes (ACAT2, HMGCR, IDI, MVK, MVD, FDTF1, and LSS) (Figures 2G and 5F) and upregulating BA synthesis genes, including cholesterol 7α-hydroxylase (CYP7A1), sterol 27-hydroxylase (CYP27A1), and sterol 12α-hydroxylase (CYP8B1) (Figures S1I and S2I). BAs are synthesized in the liver chiefly via the classical pathway orchestrated by several BA synthesis genes, e.g., CYP7A1, CYP27A1, and CYP8A1, and can also be synthesized via an alternative pathway mainly involving CYP27A1 and CYP7B1 genes. Increased expression of CYP7A1 and CYP27A1 promotes BA de novo synthesis and release from the liver and thus contributes to the decreased cholesterol levels in the body.47 A previous study on the administration of L. paracasei, also a component species of Prohep, showed reduction in serum cholesterol levels resulting from declined HMGCR and increased CYP7A1 expressions in the liver.38 Furthermore, probiotic mixture VSL#3-treated mice also exhibited increased mRNA levels of CYP7A1 and CYP8B1.48 Of note, KEGG pathways “primary bile acid biosynthesis” and “secondary bile acid synthesis” were significantly enriched in the Prohep-supplemented group (Figure 4A). The primary BAs synthesized are conjugated in the liver, mostly with taurine in murine.49 In the gastrointestinal tract, some BAs will be deconjugated and modified by gut bacteria to generate a variety of secondary BAs. Bacterial bile salt hydrolase (BSH) participates in the hydrolysis process of conjugated BAs in the gut.49 Multiple probiotic strains in our mixture including Bifidobacterium animalis, Streptococcus thermophilus, and Lactobacillus plantarum were previously documented to exhibit BSH activity.50−52 After Prohep treatment, the ratio between conjugated and unconjugated BAs decreased, and the ratio between secondary and primary BAs increased, especially in the MASLD-MASH model, indicating that more BAs were deconjugated and metabolized into secondary BAs (Figure 6H,I). The changes were only observed in the MASLD-MASH model rather than in the MASLD model probably due to the compensation of intrinsic gut microbiota BSH activity, as in MASLD model, where the gut microbiota is less disrupted. Deconjugated bile salts with lower solubility than their conjugated counterparts were absorbed less effectively from the inner intestinal lumen and therefore eliminated fecal matter more readily.53 A previous study using another microbial mixture VSL#3 also showed induced hepatic BA synthesis with enhanced BA deconjugation and fecal BA elimination.48 Higher BSH activity has also been linked to less hepatic steatosis in previous rodent studies.54,55 In both MASLD and MASLD-MASH models, Prohep led to an increase of cecal unconjugated secondary BAs, ω-MCA and LCA (Figures 4F and 6K). Previously, ω-MCA was shown to act as a cholesterol eliminator and decrease the cecal content in a rodent MASLD model.56 LCA, as one of the strongest activators of TGR5, has been repeatedly reported to activate G-protein-coupled bile acid receptor 1 (TGR5)/glucagon-like peptide-1 (GLP-1) signaling to improve insulin sensitivity.57,58 A previous study has shown that the increase of LCA was due to the increase of LCA-producing bacteria, Bacteroides species with high BSH activity, and contributed to hepatic glucose and insulin sensitivity.58

Although Prohep shows potential to be applied as a viable anti-MASLD/MASH therapeutic, this study has several limitations. One notable limitation is the absence of serum SCFA and BA data, which may have offered more thorough insight into the systemic effects of Prohep on SCFA production and BA metabolism. Fecal data provide valuable insights into gut health and microbiota activity, whereas serum data indicate the overall metabolic activity of the body and are essential for assessing the clinical relevance of these findings.59,60 Hence, future studies should integrate both types of data to draw more robust conclusions. Additionally, we acknowledge the importance of clarifying the causal relationship among various contributing factors and treatment outcomes. To better understand the precise impact of Prohep on secondary metabolites, we recommend using germ-free animal models and conducting fecal microbiota transplantation experiments, which reveal the corresponding changes and shed light on the underlying mechanisms. Addressing these limitations will improve our comprehensive understanding of the therapeutic benefits of Prohep.

5. Conclusions

In conclusion, our results demonstrated that Prohep could attenuate liver steatosis, hepatic inflammation, and insulin resistance. Based on our observations, the mechanism by which the Prohep alleviated steatosis and its associated deteriorating conditions may involve the following: (1) gut microbiome modulation that altered gut microbial composition and increased the abundance of beneficial gut microbes, including component species of Prohep, Dubosiella newyorkensis, and Muribaculum intestinale; (2) modulated SCFA metabolism and increased production of acetate and isobutyrate and the total SCFA; (3) modulated BA metabolism and increased production of ω-MCA and LCA; (4) decreased hepatic de novo lipogenesis and cholesterol biosynthesis; (5) decreased liver lipotoxicity and inflammation. Altogether, our findings would be of great value when considering the application of Prohep in MASLD treatment in the future as preventive or early-stage therapeutics.

Acknowledgments

Graphical abstract and Figure 1 were created with BioRender.com.

Glossary

Abbreviation

HFD

high-fat diet

MASLD

metabolic dysfunction-associated steatotic liver disease

MASH

metabolic dysfunction-associated steatohepatitis

HCC

hepatocellular carcinoma

FAS

fatty acid synthase

ACC

acetyl-CoA carboxylase

CPT1

carnitine palmitoyltransferase 1

ACAT2

acetyl coenzyme A acetyltransferase

HMGCR

HMG CoA reductase

IDI

isopentenyl diphosphate isomerase

MVK

mevalonate kinase

MVD

mevalonate diphosphate decarboxylase

FDTF1

farnesyl-diphosphate farnesyltransferase 1

LSS

lanosterol synthase

CYP7A1

cholesterol 7α-hydroxylase

CYP27A1

sterol 27-hydroxylase

CYP8B1

sterol 12α-hydroxylase

SCFA

short-chain fatty acid

GPCR

G protein-coupled receptors

GPR43

G protein-coupled receptor 43

TCA

tauro-cholic acid

TCDCA

tauro-chenodeoxycholic acid

TUDCA

tauro-ursodeoxycholic acid

TDCA

tauro-deoxycholic acid

TLCA

tauro-lithocholate acid

T-β-MCA

tauro-β-muricholic acid

CDCA

chenodeoxycholic acid

ω-MCA

ω-muricholic acid

LCA

lithocholate

FXR

farnesoid X receptor

BSH

bile salt hydrolase

AMPK

AMP-activated protein kinase

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jafc.3c08910.

  • Description of mouse body weights (Figures S1A and S2A); food intakes (Figures S1B and S2B); epididymal white adipose tissue weights (Figures S1C and S2C); analyses of the intraperitoneal glucose tolerance test (IPGTT) and insulin tolerance test (ITT) (Figures S1D–F and S2D,E); analyses of periodic acid–Schiff (PAS) staining results (Figures S1G and S2G); hepatic expression of fatty acid synthase (FAS) protein (Figures S1H and S2H) and CYP7A1, CYP27A1, CYP8B1, and α-SMA genes (Figures S1I, S2F, and S2I); hepatic cytokines IL-17 and TNF-α levels (Figure S2J); MASLD activity score (NAS) (Figures S1J and S2K); Spearman’s rank correlation coefficient between enriched pathways and metabolic indices (Figures S3 and S4); cecum bile acid measurements (Figure S5); supplementary methods and materials; table of primer sequences for RT-qPCR (Table S1) (PDF)

Author Contributions

○ F.Z. and E.K.K.L. contributed equally to this work and share first authorship.

The authors declare no competing financial interest.

Supplementary Material

jf3c08910_si_001.pdf (636.7KB, pdf)

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