Therapeutic Potential of Danyankang Capsule in High-Fat Diet-Induced Cholelithiasis and Its Impact on Liver FXR Signaling and Gut Microbiota

Abstract

Cholelithiasis, commonly known as gallstones, represents a prevalent hepatobiliary disorder. This study aimed to elucidate the therapeutic role and mechanism of Danyankang capsulein treating cholelithiasis induced by a high-fat diet in C57BL/6 mice. The therapeutical potential of Danyankang was assessed through biochemical analyses, histopathological examinations, protein detection, and 16S rDNA sequencing. A high-fat diet resulted in cholelithiasis manifestation in mice, with discernable abnormal serum biochemical indices and disrupted biliary cholesterol homeostasis. Danyankang treatment notably ameliorated liver inflammation symptoms and rectified serum and liver biochemical abnormalities. Concurrently, it addressed biliary imbalances. Elevated expressions of toll-like receptor 4 (TLR4), nuclear factor-kappaB (NF-κB)/pNF-κB, HMGCR, CYP7A1, and CYP8B1 observed at the inception of cholelithiasis, were notably reduced upon Danyankang administration. Furthermore, 16S rDNA analysis revealed a decline in species number and diversity of the intestinal flora in cholelithiasis-treated mice, while the decline was reversed with Danyankang treatment. Danyankang capsules reduced the abundance of Verrucomicrobiota and increased the abundance of Actinobacteriota and Proteobacteria. In conclusion, the present study demonstrates that Danyankang exerts potent therapeutic efficacy against high-fat diet-induced cholelithiasis. This beneficial outcome is potentially linked to the inhibition of the TLR4/pNF-κB and SHP/CYP7A1/CYP8B1 signaling pathways, as well as the enhancement of intestinal flora species abundance.

INTRODUCTION

Cholelithiasis is a prevalent hepatobiliary condition wherein calculi, often referred to as gallstones, manifest within the biliary system, including the gallbladder and bile ducts. These stones are precipitated aggregations of cholesterol, bilirubin, calcium salts, and mucosal components, instigated by various pathophysiological factors.^1,2) With shifts in dietary habits and an aging demographic, its incidence exhibits an upward trajectory, with a prevalence ranging between 6.3 to 12.1% among adults in China.^3,4) Current cholelithiasis management primarily hinges on surgical interventions. However, these procedures are not devoid of potential post-operative complications, including bile duct injuries, intra-abdominal hemorrhage, and biliary fistulas. Moreover, there is a looming risk of recurrence post-surgery.^5,6)

Farnesoid X receptor (FXR) stands as an important nuclear receptor in humans, orchestrating bile acid homeostasis, inflammation mitigation, and enterohepatic circulation.⁷⁾ Its intricate involvement extends to bile acid metabolism, cholesterol reversal functions, and hepatocyte protection.^8,9) A decrement in bile acid synthesis, majorly instigated by the SHP/RXRs/c-Jun N-terminal kinase (JNK)-c-Jun signaling cascade, and the therapeutic implications of FXR agonists, especially in quelling intestinal inflammation, have been documented.¹⁰⁾ Recent insights have underscored the intricate association between gut microbiota alterations and cholesterol stone formation. The gut flora, which shares a symbiotic relationship with the host, plays a quintessential role in maneuvering the intestinal-hepatic bile acid cycle. A perturbation in this microbial equilibrium can cascade into various disorders, including colon inflammation, carcinoma, cholelithiasis, and obesity.^6,11) Empirical evidence suggests that certain phyla, such as Firmicutes, are notably diminished in lithogenic diet-fed mice, echoing the profound influence of diet on gut microbiota.^12,13) Furthermore, clinical scrutiny revealed an augmented prevalence of the Proteobacteria phylum in cholelithiasis patients, underscoring the potential link between specific gut microbiota shifts and perturbations in cholesterol and bile acid metabolism.¹⁴⁾

The Danyankang capsule, a concoction comprises various herbs with ethnopharmacological prominence, has been approved by National Medical Products Administration in 2002.¹⁵⁾ It is composed of a blend of several medicinal herbs, including Glechoma longituba, Rumex obtusifolius, Saxifraga stolonifera, Sabia parviflora, Pteris multifida, Scutellaria baicalensis, Phellodendron chinen, and Andrographis paniculata. These herbs were carefully selected for their ethnopharmacological significance and their historical use in traditional Chinese medicine to treat various ailments related to liver and gallbladder function, such as heat and dampness, gallstones, and associated pain. The formulation of the Danyankang capsule is the result of extensive research and development efforts aimed at harnessing the synergistic effects of its constituent herbs. This synergy is a cornerstone of traditional Chinese medicine, wherein the combination of herbs is believed to enhance therapeutic efficacy and minimize potential side effects. Besides, certain ingredients, such as Glechoma longituba (Nakai) Kupr, have showcased efficacy against cholesterol stones in specific animal models¹⁶⁾; Furthermore, several active compounds within these herbs, like rosmarinic acid, emodin, and baicalin, have demonstrated potential benefits in stone prevention, gallbladder contractibility, and alleviation of cholelithiasis-induced hepatic injury.^17,18)

This research aims to investigate the therapeutic mechanisms of the Danyankang capsule in addressing cholelithiasis. Employing a high-fat diet-induced mouse model, we examine alterations in blood biochemistry, protein expression, and gut flora dynamics associated with cholelithiasis.

MATERIALS AND METHODS

Animals

Male SPF C57BL/6 mice, aged 6–8 weeks and weighing 18–20 g, were procured from Hunan SJA Laboratory Animal Co., Ltd. (Certificate: SCXK (Hunan) 2019-0004). They were housed under a temperature of (22 ± 2) °C with relative humidity at 60 ± 5%. Throughout the experiment, the mice had unrestricted access to water and food. The whole animal procedure was performed in strict accordance with the guidelines for the care and use of laboratory animals (The National Academies Press, 8th Ed., 2011) and the U.S. guidelines (NIH publication #85-23, revised in 1985). The experimental protocol received approval from the Animal Ethics Committee of the Jiangxi University of Chinese Medicine (JZLLSC20230462, approved on 03/24/2023).

The Extraction and Preparation of Danyankang Capsule

The commercial Danyankang capsules (Batch No. A20220804, each capsule contains 60 µg emodin, Table 1) were purchased from Guizhou Bailing Group Pharmaceutical Co., Ltd. (Guizhou, China). In detail, the Danyankang capsule is formulated with the following eight herbs: Glechoma longituba (Nakai) Kupr, Rumex nepalense Spreng, Saxifraga stolonifera Meerb, Pteris multifida Poir, Sabia parviflora Wall. ex Roxb, Scutellaria baicalensis Georgi, Phellodendron chinense Schneid, and Andrographis paniculata (Burm.f.) Nees in a ratio of 1 : 1 : 1 : 1 : 1 : 1 : 1 : 1. Among these, earth rhubarb and Scutellaria baicalensis Georgi were firstly crushed into a fine powder. The remaining six herbs were decocted in water twice, with each decoction lasting 2 h. This decoction was then filtered, and the resulting filtrate was concentrated to achieve a relative density of 1.20–1.25 at 80 °C. This concentrated mixture was combined with the previously made fine powder (earth rhubarb and Scutellaria baicalensis Georgi). After granulation and drying, the mixture was encapsulated to produce capsules.

Table 1. The Composition of Danyankang Capsule (DYK)

Scientific name	Chinese name	Weight (g)	Ratio (%)
Glechoma longituba (Nakai) Kupr	Lianqiancao	100	12.5
Rumex nepalense Spreng., Rumex crispus L., Rumex dentatus L.	Tudahuang	100	12.5
Saxifraga stolonifera Meerb	Huercao	100	12.5
Pteris multifida Poir	Fengweicao	100	12.5
Sabia parviflora Wall. ex Roxb	Xiaohuaqingfengteng	100	12.5
Scutellaria baicalensis Georgi	Huangqin	100	12.5
Phellodendron chinense Schneid	Huangbo	100	12.5
Andrographis paniculata (Burm.f.) Nees	Chuanxinlian	100	12.5

Component Analysis of Extracts of Danyankang Capsule

A precise quantity of 5g from the Danyankang capsule content was transferred into a 50 mL conical flask. Subsequently, 25 mL of methanol was added. The mixture underwent ultrasonic extraction for 1 h. Post sonication, the sample was allowed to equilibrate to room temperature. Any solvent loss during the process was compensated by the addition of methanol to regain the initial weight. Chromatographic assessment was conducted on an HPLC system, specifically the Wayeal3210. The analytical column used for separation was the InertSustain C18 column (250 × 4.6 mm, 5 µm), with a maintained column temperature of 30 °C. The elution profile employed a mobile phase consisting of Solution A (0.1% phosphoric acid in water, v/v) and Solution B (acetonitrile). The gradient elution parameters were as follows: 10–20% B (0–18 min), 20–22% B (18–30 min), 22–60% B (30–35 min), 60–80% B (35–60 min), and 80–100% B (60–70 min). The pump operated at a consistent flow rate of 1.0 mL/min. The injection volume was set at 10 µL, and the UV detection wavelengths were adjusted to 270 nm (0–30 min), 330 nm (30–40 min), and 330 nm (40–70 min). Individual samples of Emodin (1.03 mg), Chrysophanol (1.05 mg), Rosemarinic acid (2.46 mg), and Bergenin (1.58 mg) were weighed and diluted to volume in 10 mL volumetric flasks using methanol. Emodin 3-methyl ether (0.71 mg) was similarly weighed and diluted to a 5 mL volumetric flask using methanol. Prior to HPLC analysis, each solution was filtered through a 0.22 µm microporous membrane, and the filtrate was collected. Emodin (No. M29IB216001), Chrysophanol (No. A12HB191461), Rosemarinic acid (No. Y06A9K67402), and Bergenin (No.H14J10Z79791) were sourced from Shanghai Yuanye Bio-Technology Co., Ltd. (Shanghai, China). Emodin 3-methyl ether (No. C16H1205) was procured from Nanjing Spring & Autumn Biological Engineering Co., Ltd. (Nanjing, China).

Reagents

Ursodeoxycholic acid capsule was purchased from A&Z Pharmaceutical Inc. (Guangzhou, China). Total cholesterol (TC), total bile acids (TBA), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) kits were purchased from Nanjing JianCheng Bioengineering Institute (Nanjing, China). Interleukin-1β (IL-1β) enzyme-linked immunosorbent assay (ELISA) kits were purchased from Neo Bioscience Technology Co.,Ltd. (Shenzhen, China). Anti-β-actin antibody, was purchased from Proteintech (Wuhan, China). The anti-FXR antibody was purchased from Cell Signaling Technology (Beverly, MA, U.S.A.). The anti-toll-like receptor 4 (TLR4) antibody, anti-p nuclear factor-kappaB (NF-κB) antibody, anti-CYP8B1 antibody, anti-SHP antibody and anti-NF-κB antibody were purchased from Abcam (Cambridge, U.K.). The anti-CYP7A1 antibody and anti-HMGCR antibody were purchased from Thermo Fisher Scientific (MA, U.S.A.).

Animal Modeling and Drug Administration

After a week-long acclimatization period, 72 mice were equally divided into six groups (12 mice per group): a normal group, a model group (fed a lithogenic diet), a group treated with Ursodeoxycholic Acid (130 mg/kg), and three Danyankang groups with doses of 0.65, 1.3, and 2.6 g/kg, respectively.¹⁹⁾ During the study, the normal group was sustained on standard mouse chow. In contrast, all other groups received a lithogenic diet, enriched with 1.25% cholesterol and 0.5% cholic acid. After a 4-week feeding period, mice were examined for gallbladder clarity and potential granular or sedimentary deposits. A gallbladder with reduced translucency and the presence of granular deposits indicated successful modeling. From weeks 5 to 8, the normal and model groups were administered distilled water daily through oral gavage. The first Danyankang group (DYK-L) received a daily dose of 0.65g/kg Danyankang, the second (DYK-M) 1.3 g/kg, and the third (DYK-H) 2.6 g/kg. Meanwhile, the UDCA group was given a daily dose of 130 mg/kg UDCA. Following the final treatment, mice underwent a 12-hour fasting period before being anesthetized using 150 mg/kg of pentobarbital sodium, administered intraperitoneally. Subsequent to anesthesia, 100 µL of serum was extracted from each mouse, and tissue samples from the liver, gallbladder, and intestine were collected. These samples were preserved at −80 °C for later analysis.

Hematoxylin–Eosin (H&E) Staining

Liver tissues, which were preserved in 4% paraformaldehyde, were carefully trimmed using a blade inside an embedding box. Following the trimming, the tissues were rinsed overnight with continuous running water. They were then dehydrated in a progressive sequence of ethanol concentrations: 50, 75, 85, 95%, followed by anhydrous ethanol and xylene. After the dehydration process, the tissues were immersed in paraffin wax, embedded, sectioned, and stained using the H&E method. Pathological morphological changes in the tissues were subsequently examined under a microscope. The criteria for scoring these changes are detailed in Table 2.

Table 2. Histopathological Scoring Criteria of Liver Tissue of Cholelithiasis

Liver tissue	Score
The cell structure was normal, neatly arranged and tightly packed state, there was no inflammatory cell infiltration	0
Small amount of fat vacuoles	1
Small amount of inflammatory cell infiltration	2
Small amount of inflammatory cell infiltration with fat vacuoles of varying sizes	3
Increased aggregation of large numbers of inflammatory cells, small numbers of fat vacuoles	4

Measurement of Serum, Liver Tissue and Bile Biochemical

The concentrations of TC, TBA, LDL-C, IL-1β, and HDL-C in the serum, as well as the TC in the bile, were determined using commercial kits.

Western Blot

Liver tissues were transferred to a 2.5 mL centrifuge tube and lysed in a 2% sodium dodecyl sulfate (SDS) solution containing protease and phosphatase inhibitors. After homogenizing with a tissue homogenizer, the mixture was left at room temperature for 20 min to ensure complete lysis. The supernatant’s protein concentration was determined using a BCA kit. For protein denaturation, 5× Loading Buffer was added, and the samples were then heated to 100 °C for 10 min. Based on their concentration, samples underwent standard electrophoresis. Post-electrophoresis, the gel was transferred onto a polyvinylidene difluoride (PVDF) membrane at 250 mA for 90 min. This membrane was then blocked in 5% non-fat milk at room temperature for 2 h. After washing thrice with TBST for 10 min each, the membrane was incubated with the primary antibody overnight at 4 °C. The following day, it was incubated with the secondary antibody for 1 h on a shaking table. Bands were visualized using ECL luminescent liquid, and their grayscale values were analyzed using Image Lab software.

DNA Extraction and Intestinal Flora 16S rDNA Sequencing

Intestinal contents from mice were collected in cold storage tubes, immediately snap-frozen in liquid nitrogen, and stored at −80 °C. Majorbio Biomedical Technology Co., Ltd. handled the analysis of the intestinal flora. Following genomic DNA extraction, the quality of the extracted DNA was verified using 1% agarose gel electrophoresis. Bacterial DNA targeting the V3–V4 regions was amplified with specific primers. These amplified PCR products were purified and sequenced on the Illumina MiSeq platform. Post-sequencing, PE reads were merged based on overlapping regions. These sequences underwent quality control, filtering, and sample differentiation. Operational taxonomic unit (OTU) clustering and species taxonomy analyses were conducted. Multiple diversity indices were calculated based on OTUs, which also allowed the evaluation of sequencing depth. Comprehensive analysis was facilitated by the Microbiome Visualization Platform (https://report.majorbio.com/).

Statistical Analysis

The Kruskal–Wallis sum-rank test was employed to evaluate significant differences in α diversity between groups, while β diversity was illustrated using principal coordinates analysis (PCoA) based on the Bray–Curtis distance matrix. LEfSe differences between groups were analyzed using the Kruskal–Wallis sum-rank test. Results were presented as mean values (x̅ ± s). Protein band gray values were obtained using Image Lab software and analyzed with GraphPad Prism 9. One-way ANOVA was utilized for inter-group difference assessment. A p-value of less than 0.05 was deemed statistically significant.

RESULTS

Identification of Compounds in Danyangkang

As shown in Fig. 1, five compounds were identified based on their retention times:

Fig. 1. (A) HPLC Fingerprint of Danyankang; (B) the HPLC Chromatogram of Standard Substance

1. Bergeninand, 2. rosemarinic acid, 3. emodin, 4. chrysophanol, 5. emodin 3-methyl ether.

• 1. Bergeninand (8.817 min), 2. Rosemarinic acid (34.354 min), 3. Emodin (44.519 min), 4. Chrysophanol (50.159 min), 5. Emodin 3-methyl ether (52.159 min)

Effect of Danyankang Capsule on Cholelithiasis in the Liver of Mice

As shown in Fig. 2, the liver tissue structure of mice in the normal group exhibited no unusual changes. In contrast, the liver tissues of mice in the model group demonstrated inflammatory cell infiltration, abundant fat vacuoles, and pronounced fatty degeneration. When compared to the model group, the liver tissue of mice in the UDCA group displayed minimal steatosis, with cells arranged in a neat and compact manner. Mice treated with various dosages of the Danyankang capsule showed a notable decrease in fat vacuoles and a reduced extent of steatosis.

Fig. 2. Histopathological Assessment Showing the Effect of DYK on Liver Tissue in Mice with Cholelithiasis

(A) Representative images. (B) Histopathological quantitative score. Red arrows indicate fat vacuoles, black arrows indicate inflammatory cell infiltration.

Effect of Danyankang Capsule on Serum TC, TBA, LDL-C, HDL-C and IL-1β of Mice with Cholelithiasis

As presented in Figs. 3A–E, there were significant changes in serum levels when comparing the normal group to the model group. Specifically, levels of TC, TBA, LDL-C, and IL-1β in the model group exhibited a significant increase (p < 0.01), whereas HDL-C levels significantly declined (p < 0.01). In comparison to the model group, the UDCA and Danyankang groups showed a notable reduction in the levels of TC, TBA, LDL-C, and IL-1β. Furthermore, the UDCA, Danyankang medium-dose, and Danyankang high-dose groups saw a significant increase in HDL-C (p < 0.05, p < 0.01).

Fig. 3. Danyankang Attenuated High-Fat Diet-Induced Metabolic Disorders

(A) Serum levels of total cholesterol (TC), (B) serum levels of total bile acids (TBA), (C) serum levels of low-density lipoprotein cholesterol (LDL-C), (D) serum levels of high-density lipoprotein cholesterol (HDL-C), (E) serum levels of interleukin-1β (IL-1β), (F) bile levels of cholesterol (TC), (G) liver index. Data are the mean x̅ ± s, n = 6); Compared with control group, ^##p < 0.01; Compared with the model group, * p < 0.05, ** p < 0.01.

Effect of Danyankang Capsule on Liver Index and TC in Bile of Mice with Cholelithiasis

As illustrated in Figs. 3F and G, the liver indices and bile TC levels in the model group were significantly higher compared to the normal group (p < 0.05, p < 0.01). When contrasted with the model group, the UDCA group displayed significantly decreased liver indices and bile TC levels (p < 0.05, p < 0.01). The Danyankang medium-dose group showed a notable reduction in bile TC (p < 0.01), while both the Danyankang low-dose and medium-dose groups experienced a significant decrease in liver indices (p < 0.05).

Effect of Danyankang Capsule on the Activity of TLR4/NF-κB, FXR, SHP, HMGCR, CYP7A1 and CYP8B1 Signaling Pathway Proteins in the Hepatic Tissue

As shown in Fig. 4, compared to the control group, the model group exhibited significantly elevated levels of TLR4, pNF-κB, and HMGCR proteins (p < 0.01). In contrast, levels of CYP7A1, CYP8B1, and FXR were significantly decreased (p < 0.05), with SHP also showing a decreasing trend.

Fig. 4. Expression of Key Components in the Cholesterol Metabolism Pathway in Liver and Small Intestine Tissues of Mice

Expression levels of pivotal components, including TLR4, p-NF-κB, CYP8B1, CYP7A1, HMGCR, FXR, and SHP, were assessed in the liver and small intestine tissues of mice across six groups. (A) Expression of TLR4 in liver in each group, (B) expression of HMGCR in liver in each group, (C) expression of CYP8B1 in liver in each group, (D) expression of CYP7A1 in liver in each group, (E) expression of p-NF-κB in liver in each group, (F) expression of FXR in liver in each group, (G) expression of SHP in liver in each group. Note: compared with control group, ^#p < 0.05, ^## p < 0.01; Compared with the model group, * p < 0.05, ** p < 0.01.

When set against the model group: the UDCA group had significantly reduced levels of TLR4, pNF-κB, and HMGCR proteins (p < 0.05) while levels of CYP7A1 and CYP8B1 were notably increased (p < 0.01). The Danyankang high-dose group showed significantly decreased levels of TLR4, pNF-κB, and HMGCR proteins (p < 0.01). Meanwhile, there was a significant upswing in the levels of CYP7A1, CYP8B1, SHP, and FXR (p < 0.01). The Danyankang medium-dose group also exhibited a significant decline in TLR4, pNF-κB, and HMGCR proteins (p < 0.01), along with an increase in the levels of CYP7A1, CYP8B1, SHP, and FXR (p < 0.01). In the Danyankang low-dose group, levels of TLR4 and HMGCR were significantly lowered (p < 0.01). Additionally, there was an observed uptick in the levels of CYP7A1, CYP8B1, and FXR (p < 0.01).

Effects of Danyankang Capsule on Intestinal Flora

Figures 5A–D, the α-diversity of the gut flora of the cholelithiasis model mice, was significantly reduced (p < 0.05, p < 0.01) at both the phylum level and the genus level (p < 0.05, p < 0.01). A significant drop in both the sobs and Shannon index for the model group suggests a substantial reduction in the number and diversity of gut microbial species. As shown in Figs. 5E–H, the β-diversity analysis highlighted discernible differences in the distribution and composition of intestinal flora between the model and normal groups at the phylum and genus level. Both PCoA and NMDS, utilizing Bray–Curtis distance analysis, showcased the distinct separation between the two groups. The samples from the normal and model groups were markedly segregated in NMDS and PCoA plots, suggesting considerable differences in species composition. At the phylum level, The PCoA (R = 0.2574, p = 0.001) and NMDS (STRESS: 0.097, R = 0.2574, p = 0.001), and at the genus level, The PCoA (R = 0.4411, p = 0.001) and NMDS (STRESS: 0.171, R = 0.4411, p = 0.001) analyses revealed significant differences in colonies between the model and other groups. Notably, the Cholestyramine capsule dose groups deviated from the model group, aligning more closely with the normal group.

Fig. 5. Microbial Community Characteristics Generated by 16S rDNA Sequencing

The alpha-diversity indices in the gallstone. (A) The alpha-diversity indices in the gallstone observed Sobs index at the phylum level. (B) The alpha-diversity indices in the gallstone observed Shannon index at the phylum level. (C) The alpha-diversity indices in the gallstone observed Sobs index at the genus level. (D) The alpha-diversity indices in the gallstone observed Shannon index at the genus level. (E) The beta-diversity indices in the gallstone observed PCoA data at the phylum level. (F) The beta-diversity indices in the gallstone observed NMDS data at the phylum level. (G) The beta-diversity indices in the gallstone observed PCoA data at the genus level. (H) The beta-diversity indices in the gallstone observed NMDS data at the genus level. Dots of different colors or shapes represent different groupings of samples, and the closer the dots of two samples are, the more similar the species composition of the two samples. It is usually assumed that stress <0.2 can be represented by the two-dimensional point map of NMDS, whose graphs have some interpretive significance; when stress <0.1, it can be regarded as a good ordering; Note: * p < 0.05, ** p < 0.01,*** p < 0.001.

Figure 6A illustrates alterations at the phylum level compared in response to Danyangkang treatment. Cholelithiasis resulted in a significant decrease in the relative abundance of Firmicutes, Desulfobacterota, Bacteroidota, Actinobacteriota and Patescibacteria, coupled with an increase in Verrucomicrobiota and Proteobacteria. Subsequent administration of Danyankang demonstrated marked restorative effects, leading to a substantial increase in Firmicutes and Actinobacteriota abundance, while reducing the abundance of Verrucomicrobiota and Bacteroidota. Figure 6C illustrates alterations at the genus level compared in response to Danyangkang treatment. Further examination at the genus level revealed that the model group exhibited a noteworthy increase in the relative abundance of Akkermansia, establishing it as the dominant genus. Additionally, norank_f__Lachnospiraceae, Lachnoclostridium, Ruminococcus_torques_group, and norank__f__Desulfovibrionaceae saw an increase in their respective abundances, while unclassified__f__Lachnospiraceae and Desulfovibrio decreased in abundance. Following Danyankang administration, these trends were reversed, with a significant decrease in Akkermansia, norank_f__Desulfovibrionaceae, and Ruminococcus_torques_group, and an increase in Desulfovibrio, Lachnospiraceae, unclassified__f__Lachnospiraceae, Allobaculum, and Enterorhabdus relative abundance. These findings indicate the substantial impact of Danyankang on the gut microbiota composition at both the phylum and genus levels.

Fig. 6. Gut Microbiota Abundance at Phylum and Genus Levels

(A) Microbiota composition at the phylum Level. (B) Phylum-level species difference test bar chart. (C) Microbiota composition at the genus Level. (D) Genus-level species difference test bar chart. The horizontal/vertical coordinates display sample names, while the vertical/transverse coordinates indicate the proportion of species within each sample. Different colored bars represent distinct species, and the bar length corresponds to the proportion of that species. The Y-axis specifies species names at the given taxonomic level, and the X-axis shows the mean relative abundance across different subgroups of species, with different colored bars denoting unique subgroups. Significance levels are indicated as follows: * p < 0.05, ** p < 0.01, *** p < 0.001.

Figures 7A, B, LEfSe plots identified distinct marker taxa for each group: normal group: p__Bacteroidota, f__Eggerthellaceae, f__Muribaculaceae, g__E-nterorhabdus; Model group: p__Verrucomicrobiota, f__Ruminococcaceae, g__Akkermansia; UDCA group: p__Firmicutes; Danyankang low-dose group: g__Dubosiella, g__Allobaculum, c__Bacilli, f__Eubacterium_coprostanoligenes_group; Danyankang medium-dose group: p__Firmicutes, o__Firmicutes; Danyankang high-dose group: c__Clostridia, f__Oscillospiraceae, o__Lachnospirales.

Fig. 7. Microbial Community Analysis and Taxonomic Distribution

(A) LEfSE Analysis: Variously colored nodes highlight microbial taxa significantly enriched in their respective groups, contributing to notable intergroup variations. Yellowish nodes indicate microbial taxa displaying no significant differences across subgroups or having minimal impact on intergroup disparities. (B) LDA Discriminant Table: The LDA discriminant bar chart enumerates microbial taxa with substantial effects across multiple groups. LDA scores obtained via linear regression analysis are presented, with larger LDA scores indicating heightened influence of species abundance on differential effects. (C) Circos Sample-Species Relationship and Intergroup Differences: In the Circos diagram, the left half-circle depicts species composition within the sample. The outer band color denotes subgroup origin, the inner band color signifies the species, and length reflects species’ relative abundance in the respective sample. The right half-circle illustrates species distribution at the taxonomic level across different samples, with the outer band representing species, the inner band color indicating subgroups, and length representing the proportion of species distribution within a given sample.

Figure 7C, both the Circos plot and the species difference bar chart underscored Firmicutes was the most dominant bacterial family in each group. Compared to the normal group, Verrucomicrobiota in the model group increased dramatically from 3.7 to 44% (p < 0.01), Proteobacteria increased from 11 to 31%, while the Bacteroidota group decreased sharply from 57 to 5.7% (p < 0.01). Firmicutes in Danyankang percentage increased from a maximum of 12 to 20% and Verrucomicrobiota decreased from 44 to 5%.

Correlation between Intestinal Flora and Blood Biochemical Indices

Figure 8A, at the phylum level, TC was positively correlated with the relative abundance of Verrucomicrobiota, and negatively correlated with the relative abundance of Bacteroidota, Patescibacteria and Spirochaetota; TBA was negatively correlated with the relative abundance of Firmicutes, and positively correlated with the relative abundance of Verrucomicrobiota; LDL-C content was negatively correlated with the relative abundance of Bacteroidota, Cyanobacteria, Patescibacteria and Verrucomicrobiota, and negatively correlated with Desulfobacterota abundance; HDL-C content was positively correlated with the relative abundance of Bacteroidota and Patescibacteria, and negatively correlated with the relative abundance of Proteobacteria; LDL-C content levels were positively correlated with the relative abundance of Verrucomicrobiota, and positively correlated with the relative abundance of Bacteroidota and Spirochaetota. Figure 8B, at the genus level, Akkermansia, Clostridium_innocuum_group, UBA1819 flora positively correlated with TC, TBA, LDL-C and negatively correlated with HDL-C. Dubosiella, Lachnospiraceae_UCG-006, Turicibacter, Lachnospiraceae_UCG-006, Eubacterium_xylanophilum_group, Christensenellaceae_R-7_group, norank_f__UCG-010 positively correlated with HDL-C and negatively correlated with TC, TBA, LDL-C.

Fig. 8. Correlation Analysis between Intestinal Flora and Blood Biochemical Indices

(A) Correlations at the phylum level. (B) Correlations at the genus level. The X-axis represents environmental factors, while the Y-axis represents species. Correlation values (R) and associated significance levels (p-values) were determined through statistical calculations. Significance is denoted as * p < 0.05, ** p < 0.01 and *** p < 0.001.

DISCUSSION

Cholelithiasis is a multifaceted disease arising from a combination of environmental, genetic, and other factors.²⁰⁾ Although the disease manifests with diverse composition and calcification patterns, the oversaturation of bile stands out as a primary instigator for gallbladder stone formation, as emphasized by recent research.²¹⁾

It was found that^22,23) TC, TBA, LDL-C levels were significantly increased and HDL-C levels were significantly downregulated in the stone group. In this study, we observed significant increases in TC, TBA, and LDL-C levels in serum, as well as TC content in gallbladder bile, HDL-C levels in serum were significantly reduced in all cases, following 8 weeks of high-fat chow feeding in mice. This increase in cholesterol saturation likely played a role in gallbladder stone formation.

FXR, a ligand-activated transcription factor, primarily exists in two isoforms: FXRα and FXRβ. These isoforms are crucial in regulating bile acids, lipids, glucose metabolism, hepatic regeneration, and more.⁷⁾ Cholesterol, serving as the primary ingredient for bile acid synthesis, undergoes regulation chiefly by enzymes like CYP7A1, CYP8B1, and CYP27A1. These enzymes facilitate the conversion of cholesterol to primary bile acids in hepatocytes through intricate enzymatic reactions.^24,25) This transformation operates via two main routes: the classical and the alternative pathways. In the classical sequence, CYP7A1 plays a role by catalyzing the formation of 7α-hydroxycholesterol. In contrast, the alternative pathway predominantly involves the actions of CYP27A1.^26,27) Bile acid homeostasis is maintained through a feedback mechanism controlled by the nuclear receptors FXR and SHP.^28,29) Bile acids can exert their biological effects by either activating or inhibiting FXR. The activation of FXR leads to the expression of SHP, a crucial regulator of cholesterol metabolism and bile acid production, which, in turn, acts in opposition to the rate-limiting enzyme for bile acid production, CYP7A1.^30,31) Moreover, FXR can mitigate liver diseases in mice by binding to hepatic FGFR4, resulting in the inhibition of CYP7A1 and CYP8B1 expression in liver tissue.³²⁾ HMGCR, another critical enzyme, serves as the rate-limiting factor in catalyzing the conversion of 3-hydroxy-3-methylglutaryl CoA to mevalonate during cholesterol synthesis. Both HMGCR and CYP7A1 play crucial roles in regulating cholesterol synthesis and metabolism.^33–35) The metabolic process of TC is disrupted when CYP7A1 activity decreases, preventing TC from being converted into bile acids and resulting in its accumulation in the body. This accumulation can lead to elevated TC levels, contributing to the formation of gallbladder stones. Notably, in this study, the expression of CYP7A1 and CYP8B1 was reduced in the model group of mice, although there was no significant alteration in FXR expression. It has been found that an increase in the proportion of intestinal Firmicutes can activate bile acid synthesis in the liver by up-regulating CYP7A1 and CYP8B1, and a decrease in the number of Bacteroidota leads to down-regulation of FXR expression.³⁶⁾ Based on the experimental results, it was hypothesized that the decrease in Bacteroidota directly affected the decrease in FXR expression. It is plausible that the down-regulation of CYP7A1 and CYP8B1 may be linked to the modulation of PPAR-α or LXR.³⁷⁾

NF-κB is a nuclear transcription factor responsible for regulating the expression of immunoglobulin K chain in B cells, while TLR4 is a prominent member of the Toll-like receptor family, primarily recognizing microorganisms and initiating inflammatory responses.^38,39) Activation of the TLR4/NF-κB signaling pathway, a critical pathway linked to inflammatory responses, triggers the production of various inflammatory factors such as IL-1β, tumor necrosis factor α (TNF-α), and IL-6.⁴⁰⁾ Notably, our study found that the low, medium, and high doses of Danyankang effectively reduced hepatic TLR4 and IL-6 levels, concurrently inhibiting the expression of NF-κB nuclear proteins. This suggests that the Danyankang capsule possesses the capability to intervene in and mitigate hepatic inflammation.

The gut microbiota appears to play a crucial role in cholelithiasis formation by modulating bile acid metabolism, thereby influencing stone formation. Metabolites, including short-chain fatty acids and amino acids, generated by the intestinal flora exert regulatory effects on remote organs such as the liver.⁴¹⁾ For instance, primary bile acids supplementation increased intestinal flora diversity, whereas secondary bile acids led to increased proportions of the Thick-walled Bacteria and Bacteriodesmus phyla. Previous studies have demonstrated that the addition of bile salts or bile acid analogs to food can impact the composition of the intestinal microbiota, the predominant producers of short-chain fatty acids in the intestinal environment are Bacteroidota and Firmicutes.^42–44)

Recent studies have reported that the gallstone group is characterized by a decreased abundance of Firmicutes and Spirochaetia, alongside an increase in Bacteroidota, Deferribacteres, and Proteobacteria.^45,46) In our study, we found that a high-fat diet compromises the diversity of the gut microbiota in mice. Notably, Danyankang administration led to an augmented abundance of Bacteroidota. Bacteroidota, a phylum of bacteria abundant in the human gut, plays a crucial role in the inflammation and the metabolism of bile acids, dietary fats, and other compounds.⁴⁷⁾ The decrease in Bacteroidota observed in mice fed a high-fat diet suggests a disruption in these metabolic processes, potentially contributing to the development of cholelithiasis through altered bile acid composition and impaired gallbladder function.⁴⁸⁾ Conversely, the ability of Danyankang capsule to increase the relative abundance of Bacteroidota in these mice indicates a restoration of a beneficial gut microbial balance. The increased Bacteroidota may contribute to the production of short-chain fatty acids (SCFAs) and other metabolites that have anti-inflammatory properties, potentially inhibiting the activation of the TLR4/NF-κB pathway.⁴⁹⁾ This inhibition could, therefore, reduce the inflammatory processes involved in cholelithiasis development. Besides, the secondary bile acids produced by Bacteroidota might serve as ligands for nuclear receptors such as FXR, which in turn induces the expression of SHP.⁵⁰⁾ SHP negatively regulates the expression of CYP7A1 and CYP8B1, thus modulating bile acid synthesis in a manner that prevents cholelithiasis. On the other hand, our study demonstrated that treatment with the Danyankang capsule significantly reduced the abundance of Akkermansia, activated the SHP/CYP7A1/CYP8B1 pathway, and inhibited the TLR4/NF-κB pathway. This suggests a mechanistic interplay where the modulation of Danyankang on the Akkermansia levels directly influences these signaling pathways. The decrease in Akkermansia following Danyankang treatment might play a pivotal role in restoring a balanced gut microbiome, which is crucial for metabolic health and inflammatory regulation. Akkermansia is known for its mucin-degrading capabilities, which, when overrepresented, can disrupt gut barrier integrity and contribute to systemic inflammation, potentially triggering the activation of the TLR4/NF-κB pathway.^51,52) By reducing Akkermansia, Danyankang may help maintain the gut barrier’s integrity, thereby reducing the inflammatory stimuli that activate the TLR4/NF-κB pathway. Simultaneously, the restoration of a balanced gut microbiota by Danyankang, characterized by reduced Akkermansia levels, may facilitate the normalization of bile acid metabolism. This normalization is critical for the activation of the SHP/CYP7A1/CYP8B1 signaling pathway. Similarly, Wu et al.⁵³⁾ highlighted that Bacteroidota could synthesize polysaccharide A, which has the potential to inhibit pro-inflammatory cytokines. This aligns with findings by Lu et al.,⁵⁴⁾ suggesting that TLR4 −/− mice, which may have an altered Bacteroides abundance, showcase compromised immune responses. Besides, SCFAs, like propionic acid, have been demonstrated to attenuated hepatic cholesterol synthesis and stimulate IL-10 release via activating GPR41 and GPR43, thus rendering anti-inflammatory benefits.^55–57) A study on acute lung injury also revealed a substantial inverse correlation between Firmicutes abundance and the inflammatory markers IL-1β and IL-6.⁵⁸⁾ Our data further confirms this trend, showing reduced species diversity and count of TLR4 and IL-1β in the gut flora of mice treated with Danyankang. Cumulatively, these findings advocate for the pivotal role of gut microbiota dysbiosis in modulating inflammatory responses, potentially contributing to gallstone formation in mice.

CONCLUSION

In conclusion, Danyankang capsule has demonstrated the potential to modulate gut flora structure and ameliorate high-fat diet-induced cholelithiasis in mice. The underlying mechanisms of its action appear to involve the TLR4/NF-κB and HMGCR/CYP8B1 signaling pathways, in addition to its capacity to influence the gut flora composition (Fig. 8).

Acknowledgments

The project was supported by Grants from the National Natural Science Foundation of China (No. 82060757), Guizhou Provincial Key Technology R&D Program [2023] general 101, Traditional Chinese Medicine Research Project of Jiangxi Provincial Health and Family Planning Commission (No. 2018A390), and Jiangxi University of Chinese Medicine Science and Technology Innovation Team Development Program (CXTD22002).

Author Contributions

J-XZ conceived of the project. LZ, C-LZ and KJ performed the experiments. W-WX and H-YC analyzed data. JX-Z and LZ wrote the manuscript. All authors read and approved the submission.

Conflict of Interest

The authors declare no conflict of interest.

Data Availability

The original contributions are presented in the study and further inquiries about the original data can be directed to the corresponding author.

REFERENCES

• 1) Li J, Chen J, Liang J. Consensus opinion on the combined diagnosis and treatment of cholelithiasis with traditional and western medicine. Chin. J. Integr. Tradit. West. Med. Dig, 26, 132–138 (2018).
• 2) Wang Y, Zhang W, Wang X. A review of the risk factors for cholelithiasis in China. Chin. J. Mult. Organ. Dis. Elderly, 17, 636–640 (2019).
• 3) Ding P, Wang Z. Research progress in the treatment of gallstones by traditional medicine. Zhongchengyao, 41, 1125–1128 (2019).
• 4) Liu H, Ni X, Sheng S. Treatment status and meditation of benign gallbladder diseases. Zhonghua Xiaohua Waike Zazhi, 20, 813–819 (2020).
• 5) Hand TW, Vujkovic-Cvijin I, Ridaura VK, Belkaid Y. Linking the microbiota, chronic disease, and the immune system. Trends Endocrinol. Metab., 27, 831–843 (2016).
• 6) Schroeder BO, Bäckhed F. Signals from the gut microbiota to distant organs in physiology and disease. Nat. Med., 22, 1079–1089 (2016).
• 7) Qin Y, Tan J, Han X, Wang N, Zhai X, Lu Y. Effects of Yinzhihuang on alleviating cyclosporine A-induced cholestatic liver injury via farnesoid X receptor-mediated regulation of transporters and enzymes in vitro and in vivo. Biol. Pharm. Bull., 46, 1810–1819 (2023).
• 8) Li S, Zhang Z, Guan Y. On the bile acid receptor FXR. Sheng Li Ke Xue Jin Zhan, 34, 314–318 (2003).
• 9) Cai X, Qin W, Liu Y, Wang Y, Luo L, Yang F. Mechanism of Cinnamomi Ramulus improving rat model of intrahepatic cholestasis induced by ANIT by regulating FXR pathway. Zhongguo Zhongyao Zazhi, 44, 2594–2599 (2019).
• 10) Fang B-J, Shen J-Y, Zhang H, Zhou S, Lyu C-Z, Xie Y-Q. Effect of emodin on mobility signal transduction system of gallbladder smooth muscle in Guinea pig with cholelithiasis. Asian Pac. J. Trop. Med., 9, 1013–1018 (2016).
• 11) Orth M, Bellosta S. Cholesterol: its regulation and role in central nervous system disorders. Cholesterol, 2012, 292598 (2012).
• 12) Wang Q, Hao C, Yao W, Zhu D, Lu H, Li L, Ma B, Sun B, Xue D, Zhang W. Intestinal flora imbalance affects bile acid metabolism and is associated with gallstone formation. BMC Gastroenterol., 20, 59 (2020).
• 13) Cui JJ, Huang ZY, Xie YH, Wu JB, Xu GH, Li CF, Zhang MM, Yi LT. Gut microbiota mediated inflammation, neuroendocrine and neurotrophic functions involved in the antidepressant-like effects of diosgenin in chronic restraint stress. J. Affect. Disord., 321, 242–252 (2023).
• 14) Ma J. Distribution of gut microbiota in asymptomatic patients with gallstones and its clinical significance. Chin. J. Integr. Tradit. West. Med. Dig, 28, 43–46 (2020).
• 15) Chinese patent medicine local standards rising national standards part of internal medicine hepatobiliary sub-volume. Compilation of National Standard for Traditional Chinese Medicines, pp. 30–33 (2002).
• 16) Ge S, Peng D, Liu J, Ye L. An experimental study on the treatment of cholesterol stones by Glechoma longituba. Zhong Yao Cai, 07, 842–845 (2007).
• 17) Huang Y, Huang R, Zheng X. Effect of rosmarinic acid on renal calcium oxalate stone formation in rats. Zhongguo Yiyuan Yaoxue Zazhi, 31, 1196–1199 (2011).
• 18) Cheng G, Wu S. Role of baicalin and liver x receptor alpha in the formation of cholesterol gallstones in mice. Gastroenterol. Res. Pract., 2020, 1343969 (2020).
• 19) Huang J, Huang X, Chen Z, Zheng Q, Sun R. Dose conversion among different animals and healthy volunteers in pharmacological study. Chin. J. Clin. Pharmacol. Ther, 09, 1069–1072 (2004).
• 20) Hou X, Zhao Z, Wu J, Zhang H, Huo Z, Li X, Li R, Zhao D, Liu L. Analysis of the clinical and on biliary microflora features in patients with cholelithiasis and Oddi sphincter dysfunction. Chin. J. Gen. Surg, 32, 211–220 (2023).
• 21) Zhang Y, Li J, Wang Y. Role of bile acid metabolism and related receptors in the development and progression of nonalcoholic fatty liver disease. J. Clin. Hepatol., 36, 1374–1377 (2020).
• 22) Fan N, Meng K, Zhang Y, Hu Y, Li D, Gao Q, Wang J, Li Y, Wu S, Cui Y. The effect of ursodeoxycholic acid on the relative expression of the lipid metabolism genes in mouse cholesterol gallstone models. Lipids Health Dis., 19, 158 (2020).
• 23) Wen L, Cheng H, Zhong G, Li X, Jiang K, Xiang X, Zhu J. Protective effect of total extract and total alkaloids from incarvillea arguta royle on cholesterol gallstone and its choleretic effects. Zhongyao Xinyao Yu Linchuang Yaoli, 30, 822–828 (2019).
• 24) Cheng S, He J. Role of nuclear receptors in the formation of cholesterol gallstones. Prog. Physiol. Sci., 47, 97–102 (2016).
• 25) Zeng Z, Liu R, Tang L, Li W. Interaction between gut microbiota and bile acid metabolism. Zhongguo Weishengtaixue Zazhi, 33, 849–856 (2021).
• 26) Kong B, Wang L, Chiang JY, Zhang Y, Klaassen CD, Guo GL. Mechanism of tissue-specific farnesoid X receptor in suppressing the expression of genes in bile-acid synthesis in mice. Hepatology, 56, 1034–1043 (2012).
• 27) Sánchez B. Bile acid-microbiota crosstalk in gastrointestinal inflammation and carcinogenesis: a role for bifidobacteria and lactobacilli? Nat. Rev. Gastroenterol. Hepatol., 15, 205 (2018).
• 28) Fiorucci S, Baldoni M, Ricci P, Zampella A, Distrutti E, Biagioli M. Bile acid-activated receptors and the regulation of macrophages function in metabolic disorders. Curr. Opin. Pharmacol., 53, 45–54 (2020).
• 29) Anakk S, Watanabe M, Ochsner SA, McKenna NJ, Finegold MJ, Moore DD. Combined deletion of Fxr and Shp in mice induces Cyp17a1 and results in juvenile onset cholestasis. J. Clin. Invest., 121, 86–95 (2011).
• 30) Xi Y, Li H. Role of farnesoid X receptor in hepatic steatosis in nonalcoholic fatty liver disease. Biomed. Pharmacother., 121, 109609 (2020).
• 31) Hartmann P, Hartmann K, Horvath A, Chen P, et al. Modulation of the intestinal bile acid/farnesoid X receptor/fibroblast growth factor 15 axis improves alcoholic liver disease in mice. Hepatology, 67, 2150–2166 (2018).
• 32) Leduc V, Bourque L, Poirier J, Dufour R. Role of rs3846662 and HMGCR alternative splicing in statin efficacy and baseline lipid levels in familial hypercholesterolemia. Pharmacogenet. Genomics, 26, 1–11 (2016).
• 33) Liu J, Li Y, Sun C, Liu S, Yan Y, Pan H, Fan M, Xue L, Nie C, Zhang H, Qian H, Ying H, Wang L. Geniposide reduces cholesterol accumulation and increases its excretion by regulating the FXR-mediated liver-gut crosstalk of bile acids. Pharmacol. Res., 152, 104631 (2020).
• 34) Li L, Li J, He X, Liu L, Zhang H, Zhong Y, Song B. TLR4/MyD88/AMPK pathway involves in regulating adipose tissue inflammation and apoptosis in high-fat diet-induced obese mice. Chin. J. Immunol., 38, 1824–1828 (2022).
• 35) Liang C, Wang K, Cao W, Gao L, He W, Zeng Z, Song J. Sinapic acid ameliorated lipid metabolism and oxidative stress in high fat diet fed Syrian hamsters. Xiandai Shipin Keji, 37, 8–16 (2021).
• 36) Degirolamo C, Rainaldi S, Bovenga F, Murzilli S, Moschetta A. Microbiota modification with probiotics induces hepatic bile acid synthesis via downregulation of the Fxr-Fgf15 axis in mice. Cell Rep., 7, 12–18 (2014).
• 37) Fan N, Meng K, Zhang Y, Hu Y, Li D, Gao Q, Wang J, Li Y, Wu S, Cui Y. The effect of ursodeoxycholic acid on the relative expression of the lipid metabolism genes in mouse cholesterol gallstone models. Lipids Health Dis., 19, 158 (2020).
• 38) Cui K, Wang X, Han C, Liu S, Hu Y. Mechanism of human cytomegalovirus-induced epithelial-mesenchymal transition in glioma cells via the upregulation of RIP2 expression. Biol. Pharm. Bull., 46, 1506–1511 (2023).
• 39) Zhang MM, Guo MX, Zhang QP, Chen XQ, Li NZ, Liu Q, Cheng J, Wang SL, Xu GH, Li CF, Zhu JX, Yi LT. IL-1R/C3aR signaling regulates synaptic pruning in the prefrontal cortex of depression. Cell Biosci., 12, 90 (2022).
• 40) Xiong F, Wu SG, Zhang J, Jakovlić I, Li WX, Zou H, Li M, Wang GT. Dietary bile salt types influence the composition of biliary bile acids and gut microbiota in grass carp. Front. Microbiol., 9, 2209 (2018).
• 41) Yang G, Ma J, Li X, Ge L, Zhang J. Research advance on regulation of skeletal muscle physiology function by short chain fatty acids. China Anim. Husb. Vet. Med, 50, 2286–2295 (2023).
• 42) Zhang G, Liu W, Song X, Liu X, Shu W, Qin Q, Wang H. Effects of Shaoyao Gancao decoction on intestinal flora in rats with acute lung injury. China Pharm., 34, 2063–2068 (2023).
• 43) Wu Y, Yang K, Huang X, Zhou C, Xu C, Huang Z, Yu W, Xun P, Huang J, Mai X, Lin H. Effects of dietary Clostridium butyricum supplementation on growth performance and intestinal flora of juvenile Trachinotus ovatus. Nanfang Shuichan Kexue, 35, 5904–5918 (2023).
• 44) Zhang JC, Fan JK, Luo H, Liang ZW, Guan YH, Lei X, Bo NG, Zhao M. Alleviation of alcoholic fatty liver by Dendrobium officinale flower extracts due to regulation of gut microbiota and short-chain fatty acids in mice exposed to chronic alcohol. Foods, 12, 1428 (2023).
• 45) Wang Q, Xue D. Intestinal flora participates in cholesterol gallstone formation by affecting bile acid metabolism. J. Hepatopancreatobiliary Surg., 32, 6–8 (2020).
• 46) Chen Y, Wang Q, Gao W, Ma B, Xue D, Hao C. Changes and correlations of the intestinal flora and liver metabolite profiles in mice with gallstones. Front. Physiol., 12, 716654 (2021).
• 47) Gibiino G, Lopetuso LR, Scaldaferri F, Rizzatti G, Binda C, Gasbarrini A. Exploring bacteroidetes: metabolic key points and immunological tricks of our gut commensals. Dig. Liver Dis., 50, 635–639 (2018).
• 48) Collins SL, Stine JG, Bisanz JE, Okafor CD, Patterson AD. Bile acids and the gut microbiota: metabolic interactions and impacts on disease. Nat. Rev. Microbiol., 21, 236–247 (2023).
• 49) Fusco W, Lorenzo MB, Cintoni M, Porcari S, Rinninella E, Kaitsas F, Lener E, Mele MC, Gasbarrini A, Collado MC, Cammarota G, Ianiro G. Short-chain fatty-acid-producing bacteria: key components of the human gut microbiota. Nutrients, 15, 2211 (2023).
• 50) Masse KE, Lu VB. Short-chain fatty acids, secondary bile acids and indoles: gut microbial metabolites with effects on enteroendocrine cell function and their potential as therapies for metabolic disease. Front. Endocrinol. (Lausanne), 14, 1169624 (2023).
• 51) Si J, Kang H, You HJ, Ko G. Revisiting the role of Akkermansia muciniphila as a therapeutic bacterium. Gut Microbes, 14, 2078619 (2022).
• 52) Aggarwal V, Sunder S, Verma SR. Disease-associated dysbiosis and potential therapeutic role of Akkermansia muciniphila, a mucus degrading bacteria of gut microbiome. Folia Microbiol. (Praha), 67, 811–824 (2022).
• 53) Wu T, Zhang Z, Liu B, Hou D, Liang Y, Zhang J, Shi P. Gut microbiota dysbiosis and bacterial community assembly associated with cholesterol gallstones in large-scale study. BMC Genomics, 14, 669 (2013).
• 54) Lu Q, Jiang Z, Wang Q, Hu H, Zhao G. The effect of Tauroursodeoxycholic acid (TUDCA) and gut microbiota on murine gallbladder stone formation. Ann. Hepatol., 23, 100289 (2021).
• 55) Pirozzi C, Francisco V, Guida FD, Gómez R, Lago F, Pino J, Meli R, Gualillo O. Butyrate modulates inflammation in chondrocytes via GPR43 receptor. Cell. Physiol. Biochem., 51, 228–243 (2018).
• 56) Mariño E, Richards JL, McLeod KH, et al. Gut microbial metabolites limit the frequency of autoimmune T cells and protect against type 1 diabetes. Nat. Immunol., 18, 552–562 (2017).
• 57) Barber TM, Kabisch S, Pfeiffer AFH, Weickert MO. The health benefits of dietary fibre. Nutrients, 12, 3209–3209 (2020).
• 58) Wang L, Guo M, Gao Q, Yang J, Yang L, Pang X, Jiang X. The effects of probiotics on total cholesterol: a meta-analysis of randomized controlled trials. Medicine (Baltimore), 97, e9679 (2018).