Targeting the Gut-Kidney Axis in Diarrhea with Kidney-Yang Deficiency Syndrome: The Role of Sishen Pills in Regulating TMAO-Mediated Inflammatory Response

Introduction

TMAO is a metabolic byproduct produced by the gut microbiota. Trimethylamine (TMA) is produced when dietary choline, carnitine, and betaine are metabolized by the gut microbiota [1]. Following intestinal absorption, TMA is transported to the liver via the portal vein, where it is metabolized by the hepatic flavin monooxygenase enzyme (primarily FMO3) to become TMAO [2,3]. The levels of TMAO are influenced by the abundance of 13 different bacterial genera, including Prevotella, Mitsuokella, Fusobacterium, Desulfovibrio, Lachnospiraceae, and Methanobrevibacter smithii [4]. Although only a tiny fraction of gut microorganisms (less than 1%) possess the genes necessary for TMA production, they can still produce substantial amounts of TMA [5,6], indicating that the composition of individual microbial communities significantly affects TMA production. Recent investigations have shown that TMAO is a pivotal regulator of various physiological and pathological processes. Studies have demonstrated a positive correlation between TMAO concentration and metabolic disorders, cardiovascular diseases, and inflammation [7]. Additionally, TMAO plays a significant role in diseases associated with endothelial dysfunction by modulating inflammatory responses, regulating vascular endothelial growth factor, inhibiting nitric oxide synthesis, and interfering with cell signal transduction [8]. Moreover, TMAO influences the development and progression of metabolic disorders through multiple pathways, including modulation of lipid metabolism, modulation of glucose metabolism, regulation of inflammatory responses, and modulation of the gut microbiota [9]. Although there have been advancements in our understanding of TMAO, debates and open questions remain. To provide more precise preventive and treatment advice, additional studies are required to elucidate the underlying mechanisms of action.

The primary feature of TMAO in the “gut-kidney axis” is the bidirectional pathogenic relationship between kidney disorders and the gut microbiota [10]. In recent years, the “gut-kidney axis” in chronic kidney disease (CKD) has gradually garnered widespread attention, referring to the accumulation of uremic toxins produced by gut microbiota metabolism, which induces the onset and progression of CKD [11]. Renal failure and kidney fibrosis are significantly influenced by TMAO, a water-soluble, low-molecular-weight uremic toxin generated from the gut [12–14]. TMAO is an important chemical involved in dysbiosis of the gut microbiota and disturbance of the structure and function of the intestinal barrier in inflammatory bowel disease (IBD) [15,16]. Renal inflammation and fibrosis are the result of metabolites generated by dysbiosis of the gut microbiota and associated inflammatory cytokines that circulate into the kidneys via the circulation [17–19].

Diarrhea, a prevalent global health issue, is associated with alterations in the gut microbiota and intestinal secretion mechanisms. The gut microbiota can resist diarrheal pathogen colonization. However, intestinal dysfunction or dysbiosis of the gut microbiota can contribute to diarrhea [20,21]. The normal transmission of the gut-kidney axis is regulated by multiple molecules, whereas the presence of diarrhea with kidney-yang deficiency syndrome affects how energy metabolism, inflammatory responses, and factors related to oxidative stress are transmitted through the “gut-kidney axis” either directly or indirectly [22,23]. Moreover, an imbalance in the “gut-kidney axis” may induce the occurrence and development of diarrhea. Diarrhea and IBD are common after kidney transplants [24–26], and CKD patients are at considerably greater risk of developing diarrhea linked to Clostridium difficile and recurring diarrhea [27]. As a result, by transferring related inflammatory components, TMAO may contribute to the development of diarrhea via the “gut-kidney axis”.

Prolonged diarrhea can lead to deficiency, spleen weakening, and kidney-yang insufficiency, which in turn results in diarrhea with kidney-yang deficiency syndrome. Watery stools, a painful and chilly abdomen, cold limbs, and tenderness and weakness in the lower back and knees are typical clinical signs. Dysbiosis of the gut microbiota and specific pathological damage to the kidneys are characteristics of the “gut-kidney axis” in diarrhea with kidney-yang deficiency disease [23]. SSPs are well-known traditional Chinese medicine remedies that are frequently used to alleviate kidney-yang deficiency syndrome-related diarrhea. It achieves therapeutic effects through the combined actions of multiple herbal components [28]. By controlling the immune system and gut microbiome, SSPs considerably decreased inflammation in diarrhea with kidney-yang deficiency syndrome [29,30].

This study used a combination of network pharmacology and animal experiments to examine the role of TMAO in the context of diarrhea with kidney-yang deficiency syndrome and to determine whether the effectiveness of SSP is correlated with the modulation of TMAO levels. Using adenine and Folium sennae decoction, a mouse model of diarrhea with kidney-yang deficiency syndrome was generated. We investigated whether SSP affects the gut microbiota, inhibits the spread of inflammatory factors along the “kidney-gut axis,” and decreases intestinal barrier damage and renal fibrosis linked to elevated TMAO levels in diarrhea with kidney-yang deficiency syndrome. These ideas were approached from the perspectives of the TMAO-mediated “kidney-gut axis,” anti-inflammatory effects, and microbiota regulation.

Material and Methods

Network Pharmacology Analysis

ACQUISITION OF INGREDIENTS AND TARGET COLLECTION OF SSPS:

The chemical components of Myristica fragrans, Schisandra chinensis, Evodia rutaecarp, Zingiber officinale, and Ziziphus jujuba were screened using the criteria of oral bioavailability (OB ≥30%) and drug likeness (DL ≥0.18) in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (https://old.tcmsp-e.com/tcmsp.php). The chemical components of Psoralea corylifolia L. were identified using the bioinformatics analysis tool in traditional Chinese medicine Molecular Mechanics (BATMAN-TCM; http://bionet.ncpsb.org.cn/batman-tcm/index.php), with a cutoff score of ≥30 and p<0.05. Gene numbers for proteins were retrieved from the UniProt database (https://www.uniprot.org/) under the species selection “Homo sapiens” after duplicate data were removed.

PREDICTION OF POTENTIAL TARGETS FOR DIARRHEA:

Relevant targets were identified by using the term “diarrhea” in the GeneCards (https://www.genecards.org/), OMIM (https://www.omim.org/), and DisGeNET (https://www.disgenet. org) databases. Owing to the substantial quantity of targets associated with diarrhea that were found through screening in both GeneCards and DisGeNET, we established the screening criteria of a GeneCards database score ≥(1.199) and a DisGeNET database score ≥twice the median (0.02) to find targets that are more closely associated with diarrhea and to improve visualization of the data. Potential targets for diarrhea were identified by merging information from the 3 databases and eliminating duplicates.

CONSTRUCTION OF A PROTEIN–PROTEIN INTERACTION (PPI) NETWORK FOR SSP-DIARRHEA:

Venn diagrams were used to compare the common targets of diarrhea and the active components of the SSPs. The STRING 11.0 database (https://version-11-0.string-db.org/) was then used to import these targets, with “Homo sapiens” as the species. The confidence score of the STRING 11.0 database indicates how consistently genes or proteins interact. These interactions can be regarded as possible biological linkages deserving of additional experimental confirmation when the confidence level is greater than 0.4. As a result, a confidence score greater than 0.4 was established as the screening criterion. Cytoscape 3.9.1 software was used to visualize the results.

GENE ONTOLOGY (GO) AND KYOTO ENCYCLOPEDIA OF GENES AND GENOMES (KEGG) ENRICHMENT ANALYSES:

The DAVID database (https://david.ncifcrf.gov/) was used to import the shared targets. The “official gene symbol” was selected for identification, and “Homo sapiens” was selected as the species. The shared targets were copied and copied into “Step 1: Enter Gene List” to download the KEGG enrichment and GO analysis findings. P<0.001 was the designated significance threshold for enrichment analysis. Based on the P values, the top 10 KEGG and GO enrichment pathways (biological processes, cellular components and molecular activities) were then acquired. To visualize the enriched pathways, the Microbiome Cloud Platform (https://www.bioinformatics.com.cn/) was used to visualize the KEGG and GO enrichment pathways.

ANIMALS: This study used only male mice to avoid sex-related effects on the gut microbiota [31]. We obtained 24 four-week-old Kunming mice weighing 18–22 g from Hanan Slac Jingda Laboratory Animal Co. (No. 430727231101380948). The mice were kept in a controlled environment at Hunan University’s Animal Experiment Center (SYXK(Xiang)2019-0009). The facility was maintained under optimal conditions, with a temperature of 23–25°C, humidity of 47–53%, and a regular 12-h light-dark cycle.

DRUGS: The adenine suspension was prepared in sterile water at 50 mg/kg [32].

Folium sennae (2008232) decoction was made by soaking it in boiling water, filtering the solution, and then concentrating it to 1 g/m using a rotary evaporator [33].

The SSP decoction consisted of Psoralea corylifolia L. (2023021602), Myristica fragrans (23020923), Schisandra chinensis (220401), Evodia rutaecarpa (2210033), Zingiber officinale, and Ziziphus jujuba (2304165) (at a ratio of 4: 2: 2: 1: 2: 2), for a total of 39 g. These herbal ingredients were obtained from the Pharmacy of the First Affiliated Hospital of Hunan University of Chinese Medicine and stored in the laboratory. To prepare the herbal solution, the herbs were weighed following the formula’s proportions, soaked in 300 mL of water for 30 min, boiled, simmered for 30 min, and then filtered. Using the same procedure, the leftover herbal residue was cooked in 200 mL of water. The 2 liquid batches were mixed and concentrated under low heat to a final volume of 58 mL, yielding a concentration of 0.29 g/mL.

REAGENTS AND KITS:

FDA stock solution was prepared by mixing FDA and acetone at a ratio of 2: 1. To prepare the FDA reaction mixture, the FDA stock solution was added to PBS until it reached a final concentration of 10 μg/mL. The Occludin rabbit pAb antibody (Servicebio, GB111401) was diluted at 1: 500. The ZO-1 rabbit pAb antibody (Servicebio, GB111402) was diluted at 1: 500. The HRP-conjugated goat anti-rabbit secondary antibody (Servicebio, GB23303) was diluted at 1: 200. TMAO, NLRP3, IL-1β, and TGF-β1 ELISA kits (SU-B20977, CK-E21160, CK-E20533, and CK-E20217) were used in the experiment. These kits were purchased from Quanzhou Conodi Biotechnology Co., Ltd. (Hubei, China).

GROUPING AND MODELING OF THE ANIMALS: After 3 days of adaptive feeding, 24 mice were randomly divided into 8 mice for the normal control group (CC) and 16 mice for the model control group (MC) using a random number table. Adenine and Folium sennae decoction were used in conjunction to cause diarrhea in a mouse model of kidney-yang deficiency disease, as demonstrated in our research group’s previous paper [33]. The MC group received oral gavages of the adenine suspension (50 mg/(kg·d), 0.4 mL/mouse, once a day) for 14 days in succession, and the Folium sennae decoction (10 g/(kg·d), 0.4 mL/mouse, once a day) for 7 days in succession, beginning on the eighth day. Throughout this time, the sterile water volume and frequency were the same for the normal control group. Following successful establishment of the model, 8 mice from the MC group were placed in the NR group and 8 mice were placed in the SSP intervention (SSP) group, using a random number table. From the 15th day, the SSP group were orally gavaged with SSP decoction (5 g/(kg·d), 0.35 mL/mouse, twice a day) for 7 consecutive days, while those in the CC group and NR group were orally gavaged with sterile water at the same frequency and volume.

MODEL EVALUATION CRITERIA: The “Consensus opinion on TCM diagnosis and treatment of diarrhea” indicates that the main clinical manifestations of diarrhea with kidney-yang deficiency syndrome are loose stools or partially digested grains. The secondary clinical features include painful and cold sensations in the umbilical region, a preference for warmth, cold limbs, and soreness and weakness in the lower back and knees. The diagnostic standard is predicated on the co-occurrence of primary and secondary symptoms [34]. Based on these findings, we created model evaluation indicators for diarrhea with kidney-yang deficiency syndrome. The general behavioral observations (activity levels and a tendency toward lethargy) of the mice were associated with the clinical indications of exhaustion, sluggishness, and delayed responsiveness. The clinical indications of “diarrhea” were evaluated by evaluating the fecal water content. Huddling and stooped posture were linked to the clinical presentation of “chills and cold extremities” in addition to rectal temperature readings. The clinical signs of “loss of appetite, emaciation” were associated with food intake, water consumption, and body weight change. Pathological sections from small intestine and renal tissues together offered a reliable foundation for model assessment [22].

DETERMINATION OF ANAL TEMPERATURE, BODY WEIGHT CHANGE RATE, FOOD AND WATER INTAKE, AND FECAL CONTENT:

Anal temperature and body weight were measured on the 1^st, 4^th, 7^th, 11^th, 14^th, 18^th, and 21^st days of the study. The fecal water content was measured from the 7^th to the 21^st day. We also recorded daily food and water intake. The calculation formulas are as follows:

DETERMINATION OF MICROBIAL ACTIVITY: We used spectrophotometry-based colorimetry to assess microbial activity in the contents of the small intestine. The concentration of a material in solution is directly proportional to the intensity of light absorbed, as per the Beer-Lambert Law. The FDA antimicrobial assay is dependent on active bacteria cleaving fluorescein diacetate in a metabolism-dependent manner [35]. The concentration of reaction products in the crude enzyme solution is assessed by measuring its absorbance at particular wavelengths, which in part reflects the metabolic capacity of the bacteria therein [36]. Under aseptic conditions, the small intestinal contents were removed and placed in 50-mL EP tubes. The samples were placed on a shaker and agitated for 90 min after being diluted to a ratio of 3 g to 50 mL of sterile water. After centrifugation at 3000 rpm for 10 min, the supernatant (crude enzyme solution) was collected. The absorbance of the crude enzyme solution was measured at 490 nm using a visible spectrophotometer [37].

KIDNEY HISTOPATHOLOGICAL OBSERVATION:

Masson’s trichrome staining was used to assess the extent of renal fibrosis. The kidney tissues were fixed in 4% formalin solution and stored at room temperature. Paraffin sections were dewaxed in water, stained with hematoxylin for nuclear staining, differentiated in acid ethanol differentiation solution, returned to blue with Masson’s blue solution, stained with Light Green Ponceau S for cytoplasmic staining, and stained with aniline blue for collagen staining. The sections were mounted for microscopic inspection after being dehydrated and cleaned. The staining was completed by Wuhan Cy-vale Biotech Co., Ltd. (China). A semiquantitative examination of the percentage of collagen fibers in kidney tissue was conducted using ImageJ software.

ZO-1 AND OCCLUDIN EXPRESSION IN SMALL INTESTINE TISSUES:

ZO-1 and Occludin protein expression in small intestine tissues was detected by immunohistochemical staining. One- to two-centimeter-long small intestinal tissues from each group were maintained at room temperature in a 4% paraformaldehyde solution. The specific steps were as follows: paraffin sectioning, dewaxing and hydration, antigen retrieval, cell permeabilization, inactivation of endogenous peroxidase and biotin, serum blocking, addition of primary and secondary antibodies, section rinsing, DAB staining, counterstaining, and mounting for microscopic examination. The Wuhan Cy-vale Biotech Co., Ltd. (China) was commissioned to complete the staining. The average optical density (AOD) of the small intestine sections was measured using ImageJ software as a measure of the intensity of positive expression.

DETERMINATION OF TMAO, NLRP3, IL-1β, AND TGF-β1 CONCENTRATIONS:

Kidney and small intestine tissues were homogenized using ultrasonic homogenization. To obtain the supernatant, the tissue homogenates and blood were centrifuged for 10 min at 3000 rpm. Standard, sample, and blank wells were set up in accordance with the ELISA kit’s instructions. After the samples were added, the enzymes were added. After that, the substrate was applied, and the plate was cleaned and incubated in the dark. The optical density (OD) of each well was measured at a wavelength of 450 nm using an enzyme marker within 15 min.

BIOINFORMATICS AND STATISTICAL ANALYSIS:

The dada2 method in QIIME2 2020.6 software was used to denoise the sequences and obtain ASVs. We used the picante package version 1.8.2 in conjunction with R version 3.1.1 to investigate alpha diversity (including the ACE, Chao1, Simpson, Shannon and PD_whole_tree indices). Using QIIME 1.8.0 software (principal_coordinates.py) for PCoA analysis and QIIME 1.9.1 software (nmds.py) for NMDS analysis, beta diversity was assessed. To categorize the taxonomic aspects of the sequencing data, a naive Bayes classifier was used with the Silva 138 reference database. This produced information on species classification and reflected the relative abundance distribution of each species. To identify groups with varying colonic mucosal abundances and possible biomarkers, variations across several samples were evaluated. The true-positive rate (TPR), false-positive rate (FPR), and area under the curve (AUC) of receiver operating characteristic (ROC) analysis were computed for each group at different thresholds using the R script with the pROC package after the samples were sorted using random forest. Furthermore, PICRUSt2 2.3.0 software was used to analyze species composition data from 16S sequencing data to deduce the functional gene composition of the samples and obtain KEGG pathway information for functional annotation.

Statistical analysis was performed using SPSS 25.00 software. The data from each group are presented as the mean±standard deviation. Independent sample t tests were used for between-group comparisons when the data met the assumptions of normality and homogeneity of variance. One-way analysis of variance (ANOVA) was used for multiple-group comparisons. If the data did not meet the assumptions of normality and homogeneity of variance, the Mann-Whitney U test was used for between-group comparisons, and the Kruskal-Wallis H test was used for multiple-group comparisons. The linear correlation and statistical significance between the 2 variables were evaluated using the Pearson correlation coefficient. The significance level was set at α=0.05.

Results

Network Pharmacology Analysis

EFFECTIVE INGREDIENTS AND CORRESPONDING TARGETS OF SSP:

Overall, 67 active components of SSP were found after being retrieved, integrated, and deduplicated from the TCMSP and BATMAN-TCM databases. Following the UniProt database’s standardization of drug molecule targets, 270 possible drug targets were identified.

SCREENING AND NETWORK ANALYSIS OF COMMON TARGETS FOR “SSP-DIARRHEA”: As shown in Figure 1A, a total of 108 possible therapeutic targets for diarrhea by SSPs were identified by overlapping the protein targets of the chemicals active in the drug with targets linked to disorders related to diarrhea. A protein–protein interaction (PPI) network was created by importing these intersecting targets into the STRING 11.0 database. The CentiScaPe 2.2 plugin in Cytoscape 3.9.1 was used to identify central hubs and core targets in the protein–protein interaction (PPI) network, with degree, closeness, and betweenness centrality serving as the main criteria. Figure 1B shows that 52 nodes and 998 edges were generated by applying thresholds of degree ≥32.38, betweenness ≥80.64, and closeness ≥0.0055. This shows that there are 998 known interaction linkages among the 52 different key protein targets linked to both diarrhea and the SSP. The top 6 core targets – caspase 3 (CASP3), albumin (ALB), insulin (INS), IL-1β, tumor necrosis factor (TNF), and Akt serine/threonine kinase 1 (AKT1) – were selected based on a degree >70, as indicated in Figure 1C.

SCREENING AND NETWORK ANALYSIS OF COMMON TARGETS FOR “SSP-DIARRHEA”: According to the GO enrichment analysis, a total of 595 biological processes, 62 cellular components, and 104 molecular functions were identified. The biological processes mainly included positive regulation of gene expression, response to xenobiotic stimulus, response to lipopolysaccharide, positive regulation of apoptotic process, and negative regulation of apoptotic process. The cellular components primarily consisted of extracellular space, membrane rafts, cell surfaces, macromolecular complexes, and extracellular regions. The molecular functions included enzyme binding, identical protein binding, protein binding, heme binding, and ubiquitin protein ligase binding (Figure 2A). Through KEGG pathway enrichment analysis, 156 signaling pathways were identified, with the top 5 pathways being pathways involved in cancer, fluid shear stress and atherosclerosis, lipid and atherosclerosis, and the AGE-RAGE signaling pathway involved in diabetic complications and leishmaniasis (Figure 2B).

GENERAL BEHAVIORAL OBSERVATIONS AND SYMPTOMS: As Figure 3A illustrates, the mice in the CC and SSP groups behaved well, had silky coats, and were in good mental health. However, since they were cold, the mice in the NR group displayed indications of fatigue, including leg weakening and thinning fur.

As shown in Figure 3B, the mice in the SSP group showed a progressive convergence of food intake, water consumption, rectal temperature and weight change rate toward those of the CC group during the SSP treatment period, while differences continued to exist between the NR group and the CC group. On the 11th day after modeling, the rectal temperature of the CC group (36.67±0.33°C) was considerably greater than that of the NR group (35.79±0.19°C, P=0.000) and SSP group (36.19±0.35°C, P=0.017). However, the rectal temperature in the SSP group (37.01±0.34°C) was substantially higher than that in the NR group (36.13±0.54°C) 1 week after the SSP intervention (P=0.010). Additionally, the weight change rates of the NR and SSP groups were significantly lower than those of the CC group on the 11th day of modeling (CC: NR: SSP (%)=37.14±4.85: 16.14±4.53: 19.71±4.92, P CC vs NR=0.000, P CC vs SSP=0.000), and the 14th day of modeling (CC: NR: SSP (%)=45.29±6.82: 29.14±7.03: 32.43±6.53, P CC vs NR=0.000, P CC vs SSP=0.006). These results suggest that SSP decoction has a somewhat restorative impact on the signs and symptoms of diarrhea with kidney-yang deficiency syndrome caused by the modeling procedure.

STOOL CHARACTERISTICS: After the administration of Folium sennae decoction, the mice in the NR and SSP groups experienced an increase in diarrhea symptoms and fecal water content. During the treatment period, we noticed that the bedding was damp and the mice had feces in their perianal areas in the NR group. Nonetheless, clean perianal regions and dry bedding were observed in the mice in the SSP group (Figure 4A). Additionally, there was a gradual decrease in the fecal water content in both the SSP group and the NR group. However, the fecal water content in the NR group was consistently greater than that in the SSP group (Figure 4B). Suggesting that the SSP decoction effectively cured diarrhea with kidney-yang deficiency.

ORGAN INDICES: Compared with those in the CC and SSP groups, the spleen and thymus indices in the NR group tended to increase (Figure 5A, 5B). The spleen indicators showed a substantial difference (P CC vs NR=0.006, P NR vs SSP=0.005), suggesting that the SSP decoction had some therapeutic effect on the immunological response that the model had triggered.

MICROBIAL ACTIVITY: As shown in Figure 5C, microbial activity was significantly lower in the NR group than in the CC group (P=0.000). However, after treatment, the microbial activity in the SSP group significantly increased compared to that in the NR group (P=0.000). These results indicate that the SSP decoction can partially restore microbial metabolic capacity.

CHANGES IN TMAO, NLRP3, AND IL-1β LEVELS: As shown in Figure 6A, the SSP group had significantly lower levels of TMAO (P TMAO in serum=0.011, P TMAO in small bowel=0.012 and P TMAO in kidney=0.014), NLRP3 (P=0.001), and IL-1β (P=0.000) than did the NR group. Significant positive correlations between TMAO concentrations and NLRP3 and IL-1β levels were found by correlation analysis (Figure 6B). These results imply that by controlling the excessive inflammatory response caused by elevated TMAO levels, SSP decoction can reduce the symptoms of diarrhea with kidney-yang deficiency syndrome.

IMPROVING RENAL FIBROSIS AND RESTORING INTESTINAL BARRIER FUNCTION: Masson staining revealed abundant blue collagen fiber deposition and damage to the glomerular basement membrane in the NR group. However, the SSP group experienced a decrease in collagen deposition and a restoration of the glomerular basement membrane (Figure 7A). The levels of TGF-β1 in the NR group were significantly greater than those in the CC group (P=0.000). In contrast, the SSP group exhibited significantly lower TGF-β1 levels than did the NR group (P=0.000) (Figure 6A). Correlation analysis demonstrated a positive correlation between TMAO concentration and TGF-β1 level (Figure 6B). These results point to a therapeutic role for SSP decoction in treating renal fibrosis caused by high levels of TMAO.

A brownish-yellow pattern of Occludin and ZO-1 protein expression was observed in the small intestinal tissue (Figure 7B, 7C). The brown staining of Occludin (P=0.046) and ZO-1 (P=0.027) in the NR group was substantially weaker than that in the CC group. After SSP decoction intervention, the expression of both proteins in the SSP group tended to increase, with ZO-1 exhibiting a significant increase (P=0.020). These results indicate that SSP decoction can restore damaged intestinal barrier function.

QUALITY ASSESSMENT OF SEQUENCING DATA: We obtained 1 655 167 raw sequences after sequencing. After quality control, we obtained 1 509 194 high-quality sequences, and 1 377 896 valid sequences were ultimately obtained (Figure 8A). The sequencing data quality was assessed using the Shannon index, dilution curve, and coverage index. The results showed that the coverage index exceeded 99% for all the samples (Figure 8B; min=99.91%, max=99.99%, median=99.95%), indicating that the sequencing accurately reflected the sample information. Figure 8C, 8D shows that the sequencing data adequately captured the majority of the microbial species, as the dilution and Shannon index curves gradually reached a plateau with increasing sampling time. Therefore, the sequencing data satisfied the study’s requirements and were trustworthy.

ANALYSIS OF α-DIVERSITY AND β-DIVERSITY CHANGES: Figure 9A shows that the Ace (P=0.003), Chao1 (P=0.002), Shannon (P=0.010), and PD_whole_tree indices (P=0.026) in the NR group were much greater than those in the CC group. After treatment, the PD_whole_tree index in the SSP group was marginally lower than that in the NR group (P=0.0397). These findings suggested that in cases of diarrhea with kidney-yang deficiency syndrome, the species richness and diversity of the intestinal microbiota may be somewhat reduced by SSP decoction.

Furthermore, based on the PCoA and NMDS analyses (Figure 9B), the structural distribution characteristics of the small intestinal mucosal microbiota in the 3 groups significantly differed. These findings indicate the rationality of grouping and the modulatory effect of SSP decoction on the composition of the intestinal mucosal microbiota with kidney-yang deficiency diarrhea.

ANALYSIS OF INTESTINAL MUCOSAL MICROBIOTA ASV AND TAXONOMIC COMPOSITION: As shown in Figure 10A, the CC group had 6117 ASVs, 4514 of which were unique to this group. The NR group had 14710 ASVs, with 12215 ASVs unique to this group. The SSP group had 12605 ASVs, with 10154 ASVs unique to this group. There were 905 ASVs shared among the 3 groups. The compositions of the ASVs in the SSP group resembled those in the CC group more than those in the NR group.

As illustrated in Figure 10B, by comparing the changes in taxonomic composition at the phylum, class, order, family, and genus levels among the 3 groups after intervention with SSP decoction, we found that the NR group had higher taxonomic levels than did the CC group. In contrast, the taxonomic levels of the SSP group were lower than those of the NR group. These findings indicate that the taxonomic composition and microbial community of the intestinal mucosal microbiota are restored by SSP decoction.

DOMINANT INTESTINAL MUCOSAL MICROBIOTA ANALYSIS: Based on the gut microbiota results, we chose the top 10 bacterial phyla and species according to their frequency and abundance. These bacteria could be important components of the intestinal environment and have a large impact on the functionality and health of the host. By comparing the relative abundance of the top 10 bacteria at the phylum level, we found that the phyla Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria, and Verrucomicrobia were dominant in all 3 groups (Figure 11A). Compared to that in the CC group, the relative abundance of Proteobacteria in both the NR and SSP groups significantly increased (P=0.005), while the relative abundance of unclassified_Archaea substantially decreased in both the NR (P=0.006) and SSP groups (P=0.005) (Figure 11B). The relative abundance of Firmicutes decreased by 1.21% in the SSP group compared to that in the NR group, but this difference was not statistically significant.

By comparing the relative abundance of the top 10 bacteria at the genus level, we found that Akkermansia, unclassified bacteria, unclassified Muribaculaceae, and Lactiplantibacillus were dominant in all 3 groups. Compared to those in the CC group, the relative abundances of Akkermansia, unclassified Muribaculaceae, and Lactiplantibacillus in the NR and SSP groups increased. In contrast, the relative abundance of unclassified bacteria tended to decrease (Figure 11C). These findings indicate that intervention with SSP decoction alters the composition of the dominant intestinal mucosal microbiota at both the phylum and genus levels.

ANALYSIS OF THE CHARACTERISTIC INTESTINAL MUCOSAL MICROBIOTA: As shown in Figure 12A, 12B, we used random forest analysis to screen the top 10 characteristic bacterial phyla and genera in the intestinal mucosal microbiota. We performed ROC curve analysis on the selected genus-level characteristic bacteria (Figure 12C, 12D). The results revealed that Clostridium tyrobutyricum, Sphingobacteriia bacterium WF20.1, Sphingobacteriia bacterium WF20, Inostemma sp. AD 2014, and Succinatimonas hippei (AUC >0.8) were characteristic bacteria in both the CC and NR groups, while Clostridium tyrobutyricum, uncultured Solirubrobacter sp., and Succinatimonas hippei (AUC >0.8) were characteristic bacteria in the SSP and NR groups. These findings suggest that Clostridium tyrobutyricum and Succinatimonas hippei have diagnostic significance for assessing the risk of diarrhea with kidney-yang deficiency syndrome and evaluating the therapeutic efficacy of SSP decoction.

ANALYSIS OF INTESTINAL MUCOSAL MICROBIOTA FUNCTION: The functional analysis of the intestinal mucosal microbiota can generally be divided into 6 major categories, including 46 secondary subfunctional categories. With a total of 111 categories, metabolic functions had the highest abundance of any subfunctional category (there were 182 tertiary categories with a median value greater than 660 119). We selected the top 20 KEGG pathways for comparison. Seventy-five percent of all genes were involved in metabolic processes, which included global and overview processes, carbohydrate metabolism, energy metabolism, nucleotide metabolism, and amino acid metabolism (Figure 13A). Subsequent examination demonstrated that the metabolic activities in the SSP group tended to decline in comparison to those in the NR group, eventually approaching those in the CC group (Figure 13B). Next, we performed a Stamp analysis, and the results revealed significant differences in multiple functional pathways between the CC and NR groups. Figure 13C displays the 5 pathways associated with the most significant differences, including bacterial invasion of epithelial cells (P=0.002), ubiquinone and other terpenoid-quinone biosynthesis (P=0.002), glycosphingolipid biosynthesis-globin and isoglobo series (P=0.002), glycosphingolipid biosynthesis-lacto and neolacto series (P=0.002), and protein processing in the endoplasmic reticulum (P=0.001). There was a substantial increase in 2 functional pathways in the SSP group compared with those in the NR group: the lysosomal pathway (P=0.035) and the hematopoietic cell lineage pathway (P=0.038) (Figure 13D). These results indicate that in diarrhea with kidney-yang deficiency syndrome, SSP decoction has a particular regulatory influence on intestinal mucosal microbiota function.

CORRELATION ANALYSIS OF THE CHARACTERISTICS OF BACTERIAL GENERA IN THE INTESTINAL MUCOSA WITH TMAO CONCENTRATIONS, INFLAMMATORY MARKERS, AND RENAL FIBROSIS MARKERS: RDA combined with correlation analysis indicated that Succinatimonas hippei (P TMAO in serum=0.001, P TMAO in kidneys=0.009, P TMAO in small bowel=0.014, P NLRP3=0.000, P IL-1β=0.000, P TGF-β1=0.000) and Clostridium tyrobutyricum (P TMAO in serum=0.000, P TMAO in kidneys=0.031, P TMAO in small bowel=0.034, P NLRP3=0.006, P IL-1β=0.001, P TGF-β1=0.000) were strongly positively related to TMAO, NLRP3, IL-1β, and TGF-β1 (Figure 14A–14C). Dysregulation of the characteristic bacterial genera Succinatimonas hippei and Clostridium tyrobutyricum in the intestinal mucosa may be associated with elevated TMAO levels, which can lead to inflammatory reactions and damage to the kidneys and intestines. However, by controlling the imbalance of these bacterial species and lowering the increased amounts of TMAO, the decoction of SSP may help relieve the symptoms of diarrhea with kidney-yang deficiency syndrome.

Discussion

After the SSP decoction intervention, mice in the SSP group had an average increase in rectal temperature of 0.93°C and a 10.15% decrease in fecal water content compared to those in the NR group. These findings show a notable improvement in diarrhea and yang deficiency symptoms. Concurrently, there was some alleviation in their aversion to cold, preference for aggregation, and hunched posture. The gradual normalization of diet, water intake, rectal temperature, and body weight was observed. These results indicate that SSP decoction can partially improve the general behavior of mice exhibiting diarrhea with kidney-yang deficiency syndrome.

The intestine serves as an innate barrier to maintain intestinal homeostasis and prevent pathogenic bacteria and toxins [39]. The gut microbiota mainly consists of the mucosal microbiota and the luminal microbiota, which adhere to the intestinal mucosal layer, forming a multilayered intestinal microbial barrier [40,41]. Digestion is linked to modifications in the intestinal mucosal microbiome. Changes in the community structure of lactase-producing bacteria in the intestinal mucosa might decrease the amount of important lactase-producing bacteria and increase the likelihood of diarrhea [42]. In mice with antibiotic-associated diarrhea, the richness and diversity of the gut microbiota decrease, while the quantity of pathogenic bacteria increases noticeably under specific circumstances [43]. In IBD patients, mucosal microbiota dysbiosis usually occurs in both inflammatory and noninflammatory areas [44]. Research has demonstrated that SSP can enhance the variety and organization of the intestinal mucosal microbiota in mice [45], increase the relative quantity of lactobacilli, ameliorate colitis, decrease the levels of IL-1β, IL-4, IL-9, and IL-17A, and mitigate inflammatory reactions [46].

The bacterial genes responsible for conversion of choline, carnitine, and gamma-butyrobetaine into TMA have been identified as two-component Rieske-type oxygenase/reductase (CntA/B), choline-TMA lyase (CutC), and its activator CutD [5]. Certain strains belonging to the phyla Proteobacteria and Firmicutes have relatively complete methylase systems. In Proteobacteria, Firmicutes, and Actinobacteria, Jameson et al identified the choline degradation gene CutC/D and the carnitine degradation gene cntA/B [47], showing that the alpha and beta diversity of the murine mucosal microbiota changed after administration of the SSP decoction, showing a decreasing trend. Proteobacteria and Firmicutes exhibited more marked growth tendencies at the phylum level in the NR group than in the CC group. Following SSP decoction intervention, there was a 1.21% reduction in the relative abundance of Firmicutes in the SSP group compared to that in the NR group. In instances of diarrhea with kidney-yang deficiency syndrome, the increase in Firmicutes and Proteobacteria amplifies TMA levels. As excess TMA enters the liver through the portal vein, it is oxidized by FMO3, yielding higher concentrations of TMAO. However, the SSP decoction adjusted the Firmicutes concentration, thereby reducing the TMA/TMAO content. Random forest analysis combined with ROC curve analysis revealed that Succinatimonas hippei and Clostridium tyrobutyricum were characteristic microbial taxa in both the CC group and the NR group, as well as in the NR group and the SSP group. These findings could aid in diagnosing the risk of diarrhea with kidney-yang deficiency syndrome and determining the therapeutic efficacy of SSP decoction. Furthermore, Succinatimonas hippei and Clostridium tyrobutyricum were significantly correlated with TMAO, NLRP3, IL-1β, and TGF-β1. These findings show that the reduction in TMAO concentration following SSP decoction intervention may be associated with reductions in Firmicutes, Succinatimonas hippei, and Clostridium tyrobutyricum. By controlling Succinatimonas hippei and Clostridium tyrobutyricum, SSP decoction can mitigate intestinal barrier damage and renal fibrosis caused by high TMAO levels, thereby reducing diarrhea with kidney-yang deficiency syndrome.

By regulating the endoplasmic reticulum (ER) stress response, the protein kinase RNA-like endoplasmic reticulum kinase (PERK) plays a crucial role in controlling cellular metabolism. The transcription factor Forkhead box protein O1 (FoxO1) controls functions such as fat and glucose metabolism. These factors are essential for the regulation of metabolism since their abnormal activation or loss may lead to the development of metabolic diseases such as diabetes and obesity [48,49]. According to one study, at physiological concentrations, TMAO binds to PERK and suppresses TMAO-synthesizing enzymes in the gut microbiota. This, in turn, induces the transcription factor FoxO1 in a PERK-dependent manner, which results in metabolic problems [50]. The experimental results showed a significant decrease in the metabolic capacity of the fecal microbiota in the model mice, which was significantly improved after intervention with the SSP decoction. We believe that the decoction of SSP might, in part, encourage the expansion of particular microbial populations or the expression of their functional genes.

The SSP formulation has been proven to be effective at reducing inflammation and promoting recovery in the intestines and kidneys, which are often damaged by inflammatory cell infiltration [51–53]. Studies have demonstrated that serum levels of NLRP3 are significantly higher in patients with ulcerative colitis and are strongly connected with the course of the disease [54]. After patients are treated with traditional Chinese herbal decoction, the serum levels of NLRP3 decrease significantly [55]. The psoralen found in Psoralea corylifolia L. can decrease the expression of inflammatory markers, such as the NLRP3 inflammasome, IL-1β, and cleaved caspase-1, facilitating recovery from renal tubular injury, interstitial fibrosis, and intestinal barrier damage. It also reduces the expression levels of TGF-β1, α-SMA, and pSmad2/3, while regulating the proliferation of epithelial cells in the mucous layer. Additionally, it increases the levels of tight junction proteins such as claudin-1 and ZO-1 [56,57]. Methoxyeugenol in Myristica fragrans inhibits the NF-κB signaling pathway and the expression of proinflammatory cytokines, contributing to anti-inflammatory and antiproliferative effects [58]. Schisandrin B in Schisandra chinensis reduces the protein expression of the NLRP3 inflammasome and cCASP-1, consequently leading to a decrease in IL-1β levels [59]. Evodiamine (EVO) and rutaecarpine (RUT) are active alkaloids found in Evodia rutaecarpa. EVO regulates the expression of ZO-1 and Occludin during colitis, thereby preserving the integrity of tight junction structures. It also significantly inhibits the NLRP3 inflammasome and IL-1β, effectively preventing DSS-induced colitis [60]. According to the results of the pharmacoinformatics analysis, the primary inflammatory targets of SSP for the treatment of diarrhea are TNF-α and IL-1β. KEGG enrichment analysis revealed that the AGE-RAGE signaling pathway in diabetic complications is the primary pathway targeted by SSP for treating diarrhea. Research has demonstrated that activation of the AGE-RAGE signaling pathway results in the production of many inflammatory mediators, including IL-6, IL-1β, TNF-α, and the NLRP3 inflammasome [61,62]. Furthermore, oxidative stress is increased by activating the AGE-RAGE signaling pathway, which leads to an imbalance in intracellular redox homeostasis and exacerbates the inflammatory response [63]. However, further investigation and validation of the relationship between RDS and diarrhea are still needed. The experimental findings demonstrated that, compared with the NR group, the SSP group exhibited 15.71% lower serum TMAO levels, 11.39% lower renal tissue TMAO levels, 15.66% lower intestinal tissue TMAO levels, and 19.70%, 21.62%, and 23.77% lower serum NLRP3, IL-1β, and TGF-β1 levels, respectively. Additionally, we detected significant positive correlations between TMAO concentration and NLRP3, IL-1β, and TGF-β1 levels. Through Masson staining of kidney sections and immunohistochemical staining of small intestine sections, we observed a substantial reduction in the deposition of blue collagen fibers in the renal interstitium after SSP decoction treatment. Moreover, there was an increase in the protein expression of Occludin and ZO-1 in the small intestinal villi. These findings imply that SSP decoction can effectively prevent damage to the “gut-kidney axis” caused by inflammatory reactions caused by high TMAO levels, thereby ameliorating renal fibrosis and intestinal barrier damage.

Conclusions

SSP decoction can reduce the level of TMAO by modulating Firmicutes, Succinatimonas hippei, and Clostridium tyrobutyricum. This, in turn, prevents the “gut-kidney axis” from transmitting inflammatory cytokines such as NLRP3 and IL-1β, consequently improving intestinal barrier damage and renal fibrosis (Figure 15).