Runchangningshen paste activates NLRP6 inflammasome-mediated autophagy to stimulate colonic mucin-2 secretion and modulates mucosal microbiota in functional constipation

Abstract

BACKGROUND

Runchangningshen paste (RCNSP) is a paste made of four medicinal and edible homologous Chinese medicine mixed with honey. It is known for its ability to nourish yin and blood as well as to loosen the bowel to relieve constipation. The pathophysiology of functional constipation (FC) is associated with a reduction in mucin-2 (MUC2) secretion and microbial dysbiosis.

AIM

To investigate the underlying mechanism of RCNSP against FC through MUC2 and the gut mucosal microbiota.

METHODS

Ultra-performance liquid chromatography tandem mass spectrometry characterized RCNSP composition to elucidate the material basis of action. FC model was induced via loperamide gavage (16 mg/kg) twice daily for 7 days. Applying defecation function and gastrointestinal motility to assess constipation severity. Hematoxylin and eosin and Alcian blue-periodic acid-schiff staining analyzed colonic mucosal morphology. Transmission electron microscope was used to observe the ultrastructure of goblet cells (GCs). Immunofluorescence colocalization, quantitative PCR, and western blot assessed the impact of RCNSP on gene and protein expression within the NLRP6/autophagy pathway. 16S rDNA was employed to sequence the gut mucosal microbiota.

RESULTS

RCNSP contained 12 components with potential laxative effects. It enhanced defecation function, accelerated gastrointestinal motility, and maintained colonic mucosal integrity. RCNSP treatment significantly increased GC abundance and MUC2 production while preserving GC ultrastructure. At the molecular level, RCNSP enhanced the colocalized expression of key regulatory proteins and modulated mRNA and protein expressions in the NLRP6/autophagy pathway. Through 16S rDNA sequencing analysis, RCNSP significantly altered the mucosal microbiota composition. Specifically, it increased beneficial bacterial strains while reducing harmful ones. Simultaneously, RCNSP reduced butyrate-producing bacteria like Proteobacteria, Enterobacteriaceae, Blautia, and Eubacterium and decreased hydrogen sulfide-producing species, such as Prevotellaceae. It also reduced bile acid-inhibiting species, such as g_Eubacter_coprostanoligenes_group and Erysipelotrichaceae while increasing bile acid-producing species, such as Colidextribacter.

CONCLUSION

Our findings suggested that RCNSP ameliorated constipation through a dual mechanism: It stimulated colonic MUC2 secretion by activating NLRP6 inflammasome-mediated autophagy and modulated the composition of the mucosal microbiota.

Key Words: Traditional Chinese medicine; Functional constipation; NLRP6; Autophagy; Mucosal microbiota; Mucin; Goblet cells

Core Tip: Runchangningshen paste (RCNSP) is used to treat functional constipation. Based on the ultra-performance liquid chromatography tandem mass spectrometry, animal experiments, and the gut microbiota sequencing, we found that RCNSP could activate the inflammasome-mediated autophagy pathway to promote mucin-2 secretion and modulate the mucosal microbiota. In addition, mucosal microbiota might also promote mucin-2 secretion by activating the NLRP6-mediated autophagy pathway. These findings offer valuable information on the therapeutic efficacy of RCNSP and enhance the theoretical basis of traditional Chinese medicine regarding the nourishment of yin and blood for treating functional constipation.

INTRODUCTION

Patients with functional constipation (FC) typically experience symptoms of rare bowel movements (less than three per week), which is a sensation of incomplete evacuation or blockage, straining while defecating, and extended colonic and rectal transit times[1]. The worldwide morbidity of FC ranged from 10.1% to 15.3% between 1990 and 2020, based on the Rome I-IV criteria[1]. Constipation also increases the risk of various complications and illnesses, including hemorrhoids, anal fissures, stool impaction, irritable bowel syndrome, neurological diseases, atherosclerosis, and even colorectal cancer[2]. Consequently, constipation is now widely recognized as a significant public health issue due to its considerable impact on living standards. FC may result from lifestyle, psychological, behavioral, and pharmacological factors[3]. The pathophysiology of constipation is intricate, involving dysfunction of the intestinal nervous system, decreased gastrointestinal motility, and an abnormal distribution of interstitial Cajal cells[4,5]. Regarding the aforementioned pathological mechanisms, commonly used medications such as laxatives, serotonin agonists, peripheral μ-opioid receptor antagonists, and secretagogues have been employed in the management and treatment of constipation. However, many of these treatments are ineffective and come with the adverse reactions, such as diarrhea, headaches, dizziness, and insomnia[6]. Therefore, it remains imperative to identify more effective and low-toxicity pharmacological agents for the management of FC.

Constipation is increasingly linked to decreased mucus secretion[7,8]. The reduction in goblet cells (GCs) and mucin density leading to intestinal mucus barrier defects represent significant contributing factors to constipation in elderly populations[9]. The colonic mucus layer, mainly composed of mucin from GCs, is crucial for lubricating colonic contents and enhancing fecal elimination. The primary mucin, mucin-2 (MUC2), contains O-glycans that bind water to form a gel-like mucin structure, aiding in defecation. It also has a three-dimensional surface for interacting with cells or microorganisms. The mucus layer comprises a loose outer layer that supports commensal microbes and a dense inner layer attached to the epithelium to block microbe penetration. The symbiotic colonic microbes inhabit the outer and inner mucus layers, breaking down mucin O-glycans for energy using glycan-degrading enzymes. MUC2 serves as a nutrient that promotes the formation of unique microbial colonies in the gut. These colonies keep the balance of microbes in the gut by competing with each other or working together. Several studies indicate that the gut microbial dysbiosis plays an essential role in FC pathogenesis[6-8]. Among these, mucosal microbiota, not luminal microbiota, have emerged as a predictor of constipation[10]. The mechanism by which the microbiota affects constipation may be related to the secretion of MUC2 induced by the activation of the NLRP6/autophagy pathway. The NLRP6/autophagy pathway is characterized by autophagy triggered by the activation of the NOD-like inflammasome 6. It is a key mechanism that promotes MUC2 secretion in GCs. Deficiency in NLRP6 leads to autophagic damage in GCs, while partial autophagic signaling absence is linked to an impaired mucus layer, GC proliferation, and secretion defects[11,12]. Simultaneously, the composition of microbiota and their metabolites can modulate the activation of NLRP6, thereby influencing the occurrence of autophagy[13,14]. Therefore, the NLRP6/autophagy pathway is involved in microbial recognition and the secretion of MUC2. Targeting the NLRP6/autophagy pathway to modulate the relationship between MUC2 and the microbiota presents a promising therapeutic strategy for FC management.

Traditional Chinese medicine (TCM) is widely recognized as a promising potential source of compounds for the development of more effective and less toxic pharmaceuticals. A comprehensive review and meta-analysis have indicated that herbal medicine notably enhances the bristol stool scale score, boosts bowel movement frequency, and improves overall symptom evaluation in patients with FC[15]. TCM defines FC as “constipation” and attributes its cause to yin and blood deficiency. Runchangningshen paste (RCNSP) is composed of 1000 g of Mulberry Morus alba L. [Moraceae], 600 g of Polygonatum odoratum (Mill.) Druce [Asparagaceae], 400 g of Cannabis sativa L. [Cannabaceae], and 100 g of Cistanche deserticola Ma. [Orobanchaceae] per kilogram [(We have already examined the plant’s name with MPNS (http: //mpns.kew.org)]. These ingredients are mixed with honey to create a paste-like medication. Approved by the China Food and Drug Administration (National Drug Approval No: Z10980065), it nourishes yin and blood while acting as a laxative to relieve constipation. While RCNSP is effective in treating constipation[16], its fundamental mechanism remains unclear. Lactulose (LAC) is formed by the combination of fructose and galactose through a β-glycosidic bond, which is not hydrolyzed by the digestive enzymes of mammals; therefore, the ingested LAC is not absorbed by the human body[17]. Mucus primarily consists of glucose, galactose, and fructose[18]. The fructose and galactose present in LAC can be converted into mucus to lubricate the intestines to treat constipation[19]. Therefore, LAC served as a positive control drug to assess the impact of RCNSP on mucin secretion in constipated rats. The objective of this research was to determine if RCNSP could alleviate constipation by stimulating intestinal mucin secretion and regulating the gut mucosal microbiota in constipated rats induced by loperamide (LOP).

MATERIALS AND METHODS

Chemicals and reagents

Hematoxylin and eosin (H&E) staining kit (G1076) was purchased from Servicebio Technology Co., Ltd (Wuhai, China). Alcian blue-periodic acid-schiff (AB-PAS) staining kit (S0127-6) was acquired from Biosynthesis Biotechnology Co., Ltd (Beijing, China). TRIzol reagent (T9424) was acquired from Thermo Fisher Scientific (Waltham, MA, United States). Reverse transcription reagent (R223-01) was purchased from Vazyme Biotech Co., Ltd (Nanjing, China). RIPA (P0013E), a BCA kit (P0010S), and BeyoECL Star Kit (P0018AS) were purchased from Beyotime Biotechnology (Shanghai, China). SDS-PAGE (12.5%) (PG113) was acquired from Epizyme Biomedical Technology Co., Ltd (Shanghai, China). PVDF membrane (IPVH00010) was acquired from Merck Millipore (Ireland). NLRP6 antibody (AF6421), mouse IgG antibody (A0216), and rabbit IgG antibody (A0208) were purchased from Beyotime Biotechnology (Shanghai, China). LC3 antibody (81004-1-RR), MUC2 antibody (27675-1-AP), Caspase1 antibody (81482-1-RR), ASC antibody (67494-1-Ig), interleukin (IL) 1β antibody (26048-1-AP), IL18 antibody (60070-1-Ig), and Beclin1 antibody (66665-1-Ig) were purchased from Proteintech Group, Inc (Wuhan, China). P62 antibody (#5114) was acquired from Cell Signaling Technology (Danvers, MA, United States).

Drug preparation

The RCNSP was supplied by Guangdong Shaxi Pharmaceutical Co., Ltd. (2304004/2304005, Guangdong, China). The LOP hydrochloride capsules (2 mg/tablet) were obtained from Xian Janssen Pharmaceutical Co., Ltd. (NBJ5634, Xian, China). The LAC oral solution (15 mL/pouch) was acquired from Shanghai Abbott Laboratories Co., Ltd. (370124, Shanghai, China). Saline (0.9%) was obtained from Beijing Genecome. Co., Ltd (Beijing, China).

Qualitative analysis of the RCNSP

The ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) method was performed for qualitative analysis of the RCNSP extract. The following treatments were required for the samples prior to testing. First, 800 μL of methanol was incorporated into 100 μL of the RCNSP. The sample was vortexed for 30 s and sonicated for 20 min. After centrifugation for 10 min (13000 rpm, 4 °C), we aspirated 150 μL of the supernatant from the syringe, filtered it through a 0.22 μm organic phase needle filter, transferred it to an LC sampling vial, and stored it at -80°C until LC-MS analysis. For this experiment, the LC-MS system used was an ABExionLC UHPLC connected to a tandem QE high-resolution mass spectrometer (Thermo Fisher, Fair Lawn, NJ, United States). The UPLC analysis was conducted using a Waters ACQUITY UPLC system utilizing an HSS T3 (2.1 mm × 100 mm, 1.8 m) at 40 °C. The separation was achieved using gradient elution with acetonitrile as solvent A and a solution of formic acid/water (0.1%) as solvent B. The procedure was performed in the following manner: 98%-50% A, 0-13 minutes; and 5%-95% B, 25-35 minutes. Injection volume was 7 μL; flow rate was 0.3 mL/min for tandem MS system. The MS analyses were conducted using electrospray ionization in positive and negative modes. Ion source temperature was 300 °C, auxiliary gas flow at 15 units, sheath gas at 35 units, and capillary temperature at 350 °C in both modes. The variation was in the positive mode with a backflow gas velocity of 0 arb, spray voltage of 3.8 kV, and S-Lens RF level at 30%. In contrast, the negative mode had a backflow gas velocity of 1 arb, an S-Lens RF level of 60%, and a spray voltage of 3.2 kV. Additionally, fourier transform was used as the quality detector, and the data-dependent acquisition mode was selected for the analysis. The resolution of MS1 was 60000 and that of MS2 was 15000, and the MS ranged from 50 to 1500 m/z.

Data analysis was conducted using Compound Discoverer 3.3 software (Thermo Fisher Scientific, United States). The MS data were matched with the data in the mzCloud database, and the chemical components and molecular formulas in the samples were determined based on the scoring information of the chromatographic peaks.

Animals and induction of constipation

According to the resource equation[20], the maximum sample size for each group was five rats. Based on literature[21-23] and preliminary experiments, each group was set to consist of six rats, resulting in a total sample size of 36. Sprague Dawley rats (180-200 g), licensed by Shanghai SLAC Animal Biotechnology Co., Ltd. under license number SCXK (Shanghai) 2017-0005, were housed in a SPF facility at Shanghai University of TCM (Shanghai, China). The rats were subjected to the following controlled conditions: 12 h light/dark cycles, a steady humidity of 50% ± 2%, and a temperature of 22 °C ± 2 °C. Approval for the animal experiments was granted by the Shanghai University of TCM Animal Experimental Ethics Committee (PZSHUTCM2306150012). Common dietary pellets and sterilized water were provided randomly. Following a week of acclimatization, 36 Sprague Dawley rats were grouped using the randomized block design. Initially, the rats were stratified based on body weight, and then random numbers were generated using SPSS software to further randomly assign them into six groups (n = 6): The normal control group (NC), the FC model group (FC), the low dose of RCNSP group (LRCNSP), the moderate dose of RCNSP group (MRCNSP), the high dose of RCNSP group (HRCNSP), and the LAC group (LAC). The FC rat model was replicated using the methodology described[24], with minor modifications. All groups except NC received the LOP hydrochloride solution orally (16 mg/kg) twice daily during the initial week and once daily in the subsequent week to trigger constipation[24]. Additionally, NC group rats received 0.9% saline (10 mL/kg) via gavage. This study followed the principles of animal protection, animal welfare, and ethics. When the experiment was over, all animals were euthanized by barbiturate overdose (intravenous injection, 2% concentration) for tissue collection.

Administration plan

The RCNSP and the LAC oral solution were dissolved in 0.9% saline. Equivalent doses for humans and rats were determined utilizing the body surface area method[25]. The conversion equation for the rat dose is 6.2 * Ng/kg, where Ng/kg is the daily clinical dose for adults based on an adult weighing 60 kg and a rat weighing 150 g[25]. According to the literature[26], the moderate dose in rats was considered the adult equivalent dose, with the lower dosage being half of the moderate dosage and the higher dosage being twice the moderate dosage. The recommended dosage for patients of the RCNSP is 30 g/day, which translates to 3.13 g/kg/day for rats. We chose 3.13 g/kg/day as the moderate dose, with 1.57 g/kg/day and 6.26 g/kg/day as the low and high doses, respectively. The LAC dosage was adjusted to 2.09 g/kg/day using a clinical equivalent dose calculation. The volume of the gavage was 1 mL/100 g body weight (BW). From the second week onwards, rats were orally administered saline, RCNSP, or LAC daily for a week. Throughout the study, we recorded the daily BW and food intake of the rats. The specific administration plan was as follows.

(1) NC group: Rats were gavaged with 0.9% saline (10 mL/kg, bid, i.g.) for 14 days; (2) FC group: In the first week, rats were gavaged with LOP hydrochloride solution (16 mg/kg, bid, i.g.) for 7 days; in the second week, rats were gavaged with LOP hydrochloride solution (16 mg/kg, qd, i.g.) and 0.9% saline (10 mL/kg, qd, i.g.) for 7 days; (3) LRCNSP group: In the first week, rats were gavaged with LOP hydrochloride solution (16 mg/kg, bid, i.g.) for 7 days; in the second week, rats were gavaged with LOP hydrochloride solution (16 mg/kg, qd, i.g.) and RCNSP solution (1.57 g/kg, qd, i.g.) for 7 days; (4) MRCNSP group: In the first week, rats were gavaged with LOP hydrochloride solution (16 mg/kg, bid, i.g.) for 7 days; in the second week, rats were gavaged with LOP hydrochloride solution (16 mg/kg, qd, i.g.) and RCNSP solution (3.13 g/kg, qd, i.g.) for 7 days; (5) HRCNSP group: In the first week, rats were gavaged with LOP hydrochloride solution (16 mg/kg, bid, i.g.) for 7 days; in the second week, rats were gavaged with LOP hydrochloride solution (16 mg/kg, qd, i.g.) and RCNSP solution (6.26 g/kg, qd, i.g.) for 7 days; and (6) LAC group: In the first week, rats were gavaged with LOP hydrochloride solution (16 mg/kg, bid, i.g.) for 7 day; in the second week, rats were gavaged with LOP hydrochloride solution (16 mg/kg, qd, i.g.) and LAC solution (2.09 g/kg, qd, i.g.) for 7 days.

Evaluation of the laxative impact of RCNSP in constipated rats

Evaluation of the defecation function: Fecal pellets were collected on day 8 post-modeling and 1 day before euthanasia to assess fecal factors such as the fecal number, weight, and water content. Fresh fecal samples were dehydrated in a thermostatic heating incubator (DHP-9082, Yiheng Scientific Instrument Co, Shanghai, China) at 60 °C until weight stabilized. The moisture content of the feces was determined utilizing the equation: Water content of feces (%) = (difference between wet and dry weights/wet weight) × 100%[24].

Evaluation of gastrointestinal motility: Semi-solid paste containing carbon powder was formulated based on a previous study performed by our group[27]. Rats were fasted for 12 h before being orally administered the paste at 1.5 mL/100 g of BW. The weight of the solid paste was recorded. After 30 min of anesthesia with 2% sodium pentobarbital, the abdominal cavity was dissected. The pylorus and cardia were ligated using surgical threads, and the stomach was removed. The weights of the full and evacuated stomachs were measured. In addition, we excised the pylorus-rectum and examined the entire length of the bowel of each rat, measuring the maximum distance covered by the semi-solid paste without causing tension on the bowel. The gastric and intestinal propulsion rates were determined using the following equations[27]: The gastric emptying rate (%) = [1 – (entire stomach mass – empty stomach mass)/semi-solid paste mass] × 100%; and the intestinal propulsion rate (%) = the furthest distance traveled by carbon/total length of the intestinal tract × 100%.

Histomorphometric analysis

After anesthesia, 3 mm × 3 mm of the proximal colon tissue was gathered, preserved in 4% paraformaldehyde, and made into 5 µm tissue sections embedded in paraffin blocks. The sections were then stained using an H&E staining kit to visualize the morphological changes in the mucosal layers and an AB-PAS staining kit to identify the colonic mucin secretion. The stained sections were dehydrated, permeabilized, and finally sealed with a neutral resin. Histomorphometric changes in the colonic tissue were observed using a light microscope (Cx31rtsf, Olympus, China).

Transmission electron microscope

After anesthetization, the proximal colon tissue (1 mm × 3 mm in size) was rapidly fixed in a 2.5% glutaraldehyde fixation. After rinsing, fixation, rinsing, dehydration, and osmotic embedding, 0.5 mm × 0.3 mm ultrathin sections were made. The sections were exposed to lead citrate and analyzed using transmission electron microscope (TEM) (FEI Tecnai G2 spirit, Czekh). In particular, attention was paid to the ultrastructure of the GCs that consisted of the number of vesicles at the bottom of the GCs (without mucin secretion), the structure of the mitochondria, and the presence or absence of autophagosomes.

Immunofluorescence co-staining

Paraffin sections of colon tissue were dehydrated, antigenically repaired, and exposed to specific antibodies [NLRP6 (1:20000), LC3 (1:6000), and MUC2 (1:15000)] at 4 °C overnight. Fluorescent-conjugated secondary antibodies were applied followed by DAPI staining. A confocal laser scanning microscope was used to detect the immunofluorescence staining images of the MUC2, NLRP6, and LC3 proteins.

Quantitative PCR

Total RNA was isolated from rat colon samples utilizing TRIzol reagent and quantified with an enzyme labeler (SynergyLX, BioTek, United States). Subsequently, cDNA was synthesized from RNA via reverse transcription and assayed with a kit and a LightCycler 480 II instrument (Lightcycler 480 II, Roche Diagnostics GmbH, Switzerland). The gene expression was then standardized relative to the actin levels and reported as a comparative value. Primers from Shengong Biotech (Shanghai, China) were used (Table 1).

Table 1 The primer information.

Gene	Sequence (5‘-3’)
β-actin	Forward: GGCTGTGTTGTCCCTGTATGC
	Reverse: TCACGCACGATTTCCCTCTC
NLRP6	Forward: AAGGGATGAAGCAGTGTCT
	Reverse: GGAGGTATTGGCGGTTAT
Caspase1	Forward: CTGGGAAGAGGTAGAAAC
	Reverse: TTTTGAAGATGATGGCA
ASC	Forward: GGACCCCATAGACCTCACTG
	Reverse: CCATACAGAGCATCCAGCAA
IL18	Forward: CACTTTGGCAGACTTCA
	Reverse: GTCCTCTTACTTCACTATCTT
IL1β	Forward: GACAGTGAGGAGAATGACCT
	Reverse: GGTGCTTGGGTCCTCAT
Muc2	Forward: TCGTAGTAGTGCTTGGGAGGC
	Reverse: TGCTGCTGATGAGTGGTTGG

IL: Interleukin; Muc2: Mucin-2.

Western blot

Proteins were isolated from the colon tissues utilizing a RIPA buffer quantified with a BCA kit. Standardized samples underwent 12.5% SDS-PAGE electrophoresis, followed by protein transfer to a PVDF membrane. The membranes were blocked with skim milk, rinsed with PBST, and subsequently exposed to the following different antibodies: Anti-Caspase1 (1:2000); anti-ASC (1:2000); anti-IL1β (1:1000); anti-IL18 (1:2000); anti-NLRP6 (1:500); anti-Beclin1 (1:1000); anti-P62 (1:1000); anti-LC3 (1:1000); anti-MUC2 (1:1000); and anti-β-actin (1:20000) at 4 °C overnight. After rinsing and incubating with secondary antibodies [anti-rabbit IgG (1:1000) and anti-mouse IgG (1:1000)], protein bands were visualized using BeyoECL Star kit under a chemiluminescence image analysis system (5200Multi, Tanon, Shanghai, China). The protein density was quantified using Image J.

Analysis of the gut mucosa microbiota

Fresh mucosa samples from the ascending colons (1-2 g) of rats were obtained and stored in sterile tubes. Samples were rapidly cryopreserved in liquid nitrogen for subsequent analysis. Following the manufacturer’s protocol, genomic DNA was extracted from 0.5 g frozen mucosa samples using an E.Z.N.A.^® soil DNA Kit. The DNA concentration and purity were determined using 1.0% agarose gel electrophoresis and a NanoDrop^® ND-2000 spectrophotometer (Thermo Scientific Inc., United States) to ensure that the quality of the samples met the requirements for subsequent analysis. The hypervariable region V3-V4 of the bacterial 16S rRNA gene was amplified with primer pairs 338F (5’-ACTCCTACGGGAGGCAGCAG-3’) and 806R (5’-GGACTACHVGGGTWTCTAAT-3’) using a T100 Thermal Cycler (BIO-RAD, United States). PCR quantification and purification were then conducted. Finally, an Illumina NextSeq 2000 PE300 platform (Illumina, San Diego, CA, United States) was selected for high-throughput sequencing and species annotation according to the standard protocols by Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China).

Data and statistical analyses

We analyzed data using SPSS 26.0 and GraphPad Prism 10.0, demonstrating a normal distribution. Results were presented as mean ± SD. Levene’s test was employed to assess the homogeneity of variances in the data, and the results showed that the variances were homogeneous. To compare multiple groups, a one-way analysis of variance was employed, while the Fisher’s least significant difference method was utilized for pairwise comparisons. Statistical significance was established at a P value of less than 0.05.

Differences in the mucosal microbiota diversity were analyzed using the α-diversity and β-diversity based on operational taxonomic unit (OTU) clustering. The α-diversity assesses species composition within habitats using the Shannon, Chao, Simpson, and Ace indexes. The β-diversity, which measures diversity between habitats, is measured using a principal component analysis, a non-metric multidimensional scaling analysis, principal coordinate analysis, and a partial least squares discriminant analysis. The Bray-Curtis metric distances and the Kulczynski algorithm were used in the diversity analysis, while the ANOSIM method was used to determine significant diversity changes. Taxonomic analyses of the mucosal microbiota at family, genus, and phylum levels were conducted utilizing the Kruskal-Wallis H test and the Wilcoxon rank-sum test.

RESULTS

Qualitative assessment of the chemical constituents of the RCNSP extract

The UPLC-MS/MS analysis identified the chemical constituents of the RCNSP extract. The total ion chromatograms of the RCNSP in both positive and negative ion modes are shown in Figure 1. The extracts were preliminarily identified based on the retention times, the mass charge ratio, the molecular weight, and the peak intensity. We identified 33 compounds using the mzCloud best match value > 90 and the mzVault best match value > 70. We found that emodin-3-methylether/physcion, hyperoside, rutin, scopoletin, betaine, genkwanin, trigonelline HCl, adenosine, caffeic acid, α-linolenic acid, chlorogenic acid, and 6-hydroxyindole are the most strongly correlated medications with constipation-relieving responses (Supplementary Table 1).

Figure 1 Ultra-performance liquid chromatography tandem mass spectrometry extracted ion chromatograms of Runchangningshen paste. A: Positive ion modes; B: Negative ion modes.

RCNSP promoted the defecation function in FC rats

In this research, we employed the LOP gavage technique to develop the FC model. We specifically monitored alterations in various defecation function indexes during the modelling process and evaluated FC from three aspects: Health status; fecal parameters; and gastrointestinal motility. In terms of health status, the FC group had significantly lower BW and food intake compared to the NC group (P < 0.0001, Figure 2A and B). Fecal parameters are crucial indicators for assessing the severity of FC, and they include the fecal number, fecal weight, and the water content of feces. As expected, after the administration of LOP orally twice daily for a period of 7 days, fecal parameters were markedly reduced in the FC group compared to the NC group (P < 0.0001, Figure 2C-E), suggesting effective constipation induction. To maintain the modeling conditions, LOP was administered once daily for 7 days, resulting in significantly lower fecal parameters in the FC group compared to the NC group at 16 days (P < 0.0001, Figure 2C-E). Gastrointestinal motility was measured by the gastric and intestinal propulsion rates. FC delayed the gastric emptying and intestinal transit rates in comparison to the NC group (P < 0.0001, Figure 2F and G). Different doses of RCNSP served as the treatment group, and clinically equivalent doses of LAC served as the positive control group. One week after treatment, RCNSP and LAC reversed these changes. Notably, compared to the FC group, the RCNSP group dose-dependently increased BW and food intake and promoted the rate of gastric emptying and intestinal propulsion, fecal number, fecal weight, and fecal water content (P < 0.05, Figure 2).

Figure 2 Runchangningshen paste relieved the inhibitory effect of functional constipation on the defecation function. A: Measurement of body weight (n = 6); B: Measurement of food intake (n = 6); C-E: Measurement of the 24-h fecal index (n = 6) (C: Fecal number; D: Fecal weight; E: Water content of feces); F and G: Measurement of gastrointestinal motility. Rats were intragastrically administered the black solid paste and sacrificed 30 min later. The stomach was removed, and the weights of the entire stomach and empty stomach were measured. The intestine was removed, and the rate of the black solid paste propulsion was calculated (n = 6) (F: Gastric emptying rate; G: Intestinal propulsion rate test). All data were shown as the mean ± SD. P values were calculated using one-way analysis of variance followed by Fisher’s least significant difference test. ^aP < 0.0001 vs normal control (NC) group; ^bP < 0.05 vs functional constipation model (FC) group; ^cP < 0.01 vs FC group; ^dP < 0.001 vs FC group; ^eP < 0.0001 vs FC group. HRCNSP: High dose of runchangningshen paste group; LAC: Lactulose group; LRCNSP: Low dose of runchangningshen paste group; MRCNSP: Medium dose of runchangningshen paste group.

RCNSP protected the colon mucosal layer and promoted the mucin secretion in FC rats

Constipation is associated with damage to the integrity of the intestinal barrier. We employed H&E staining to analyze the morphological changes in colonic tissue, with a particular focus on the integrity of the colonic mucosa. The results showed that colonic mucosal damage was more severe in the FC group and was characterized by detached mucosal epithelial cells, a reduced number of GCs, disrupted structure of the colonic crypts, increased fibrous tissue hyperplasia, disrupted glands, and disruption of the regular arrangement of the colonic crypts in the FC group (Figure 3A). Fortunately, the damaged intestinal mucosal barrier was restored after RCNSP and LAC treatment. Specifically, RCNSP groups increased the number of colonic glands and GCs while decreasing intestinal epithelial damage compared to the FC group (Figure 3A). These results demonstrated that the RCNSP had a protective impact on the colonic mucosal layer. Next, mucin secretion from GCs in the colonic tissues was observed using AB-PAS staining (Figure 3B). Significantly higher numbers of GCs and increased mucin secretion were observed in the RCNSP groups compared to the FC group, especially in the HRCNSP group, which closely resembled the NC group (Figure 3B).

Figure 3 Runchangningshen paste alleviated the impairment effect of functional constipation on the colonic mucosal layer and the mucin production. A: Representative image of hematoxylin and eosin staining (× 200 magnification). The yellow arrows indicate the mucosal epithelial cells, the red circles indicate the goblet cells, the green zones indicate the colonic crypts, the orange boxes indicate the fibrous tissue, and the blue circles indicate the glands; B: Representative image of Alcian blue-periodic acid-schiff staining (× 200 magnification). Purple-pink indicates mucin. FC: Functional constipation model group; HRCNSP: High dose of runchangningshen paste group; LAC: Lactulose group; LRCNSP: Low dose of runchangningshen paste group; MRCNSP: Medium dose of runchangningshen paste group; NC: Normal control group.

RCNSP promoted the mucin secretion through autophagy of GCs in FC rats

The reduction of mucin in constipation is often characterized by the downregulation of GC secretory function. To evaluate the mechanisms by which constipation affected mucin secretion and RCNSP promoted mucin secretion, we observed the ultrastructure of GCs from different groups of rats using TEM (Figure 4). As expected, the results revealed that FC led to a significant impairment of the exocytosis action of mucin granules. Notably, this was indicated by the GCs having reduced the autophagosomes, increased the degenerating mitochondria (referred to as unhealthy due to the absence of intact cristae and the presence of dense inclusion bodies of proteins), increased the intracellular mucin granule accumulation, and an apparent inability of these granules to merge with the apical surface of the intestinal epithelium. Fortunately, RCNSP dose-dependently improved these conditions by increasing autophagosomes, reducing degenerated mitochondria, and inducing the secretion of mucins near the intestinal lumen. The results suggested that defects in autophagy within the GCs might affect mucin secretion, aligning with the findings of Yeom et al[28]. In addition, it was also shown that RCNSP increased mucin secretion by regulating the autophagy.

Figure 4 Runchangningshen paste improved the inhibition effect of functional constipation on autophagy and mucin exocytosis in goblet cells. The representative picture of the ultrastructure of the goblet cells by the transmission electron microscope (× 3400 magnification). The blue area and dots indicate the mucins, the red arrows indicate the autophagosome, and the yellow arrows indicate the damaged mitochondria. FC: Functional constipation model group; HRCNSP: High dose of runchangningshen paste group; LAC: Lactulose group; LRCNSP: Low dose of runchangningshen paste group; MRCNSP: Medium dose of runchangningshen paste group; NC: Normal control group.

RCNSP activated the NLRP6/autophagy pathway to promote colonic MUC2 secretion in FC rats

To study the NLRP6/autophagy pathway effect on MUC2 secretion, we analyzed the core protein expression using immunofluorescence. The level of activation of the NLRP6/autophagy pathway was assessed by observing the colocalization of NLRP6, LC3, and MUC2. The colocalization was significantly decreased in FC rats (P < 0.0001), while RCNSP and LAC reversed this process (P < 0.01, Figure 5A and B). These findings suggested that RCNSP might activate the NLRP6/autophagy pathway to enhance MUC2 secretion in FC rats. To further validate this hypothesis, we utilized quantitative PCR and western blot to evaluate the expression of relevant genes and proteins in the NLRP6/autophagy pathway in colonic samples from FC rats. Genes linked to NLRP6 activation, including NLRP6, ASC, Caspase1, IL1β, and IL18, exhibited decreased expression in the FC group compared with the NC group (P < 0.0001, Figure 5C-G). Remarkably, the RCNSP treatment reversed this trend, leading to a dose-dependent increase in these gene expressions (P < 0.01, Figure 5C-G). Meanwhile, MUC2 gene expression was correlated with changes in NLRP6-related genes across all groups, as evidenced by elevated MUC2 gene expression in the RCNSP groups compared to the FC group (P < 0.001, Figure 5H). Furthermore, in the FC group, the protein levels of the NLRP6/autophagy pathway marker NLRP6, ASC, Caspase1, IL1β, IL18, LC3II, Beclin1, and MUC2 were decreased and those of P62 were increased compared to the NC group (P < 0.0001, Figure 5I-S). In contrast, RCNSP treatment restored these protein levels to be similar to those in the NC group (Figure 5I-S).

Figure 5 Runchangningshen paste attenuated the inhibition effect of functional constipation on the NLRP6/autophagy/mucin-2 pathway in colon tissue. A: The colon tissues were stained with the NLRP6 markers (green), LC3 markers (pink) and mucin-2 (MUC2) markers (red); B: NLRP6/LC3/MUC2 colocalization expression intensity by the Tissue Gnostics calculation (n = 3); C-H: The mRNA levels of NLRP6, Asc, Caspase1, interleukin (IL) 1β, IL18, and MUC2 were measured using reverse transcription quantitative PCR; I: The protein expression levels of NLRP6, Asc, Caspase1, IL1β, IL18 were analyzed by western blot; J-N: Density calculations for NLRP6, Asc, Caspase1, IL1β, IL18 (n = 6); O: The protein expression levels of LC3II, Beclin1, P62, and MUC2 were analyzed by western blot; P-S: Density calculations for LC3II, Beclin1, P62, and MUC2 (n = 6). All data were shown as the mean ± SD. P values were calculated using one-way analysis of variance followed by Fisher’s least significant difference test. ^aP < 0.0001 vs normal control (NC) group; ^bP < 0.05 vs functional constipation model (FC) group; ^cP < 0.01 vs FC group; ^dP < 0.001 vs FC group; ^eP < 0.0001 vs FC group. HRCNSP: High dose of runchangningshen paste group; LAC: Lactulose group; LRCNSP: Low dose of runchangningshen paste group; MRCNSP: Medium dose of runchangningshen paste group.

RCNSP regulated the gut mucosal microbiota in FC rats

RCNSP changed the gut mucosal microbiota diversity in FC rats: To evaluate the impacts of the RCNSP treatment on the gut mucosal microbiota, we conducted high-throughput gene sequencing of 16S rDNA. The pan/core curves showed the common/core species counts across all samples. A plateau in the curves suggested that the sample sizes sequenced were adequate for further analyses (Figure 6A and B). The rank-abundance curves helped us to understand the species diversity and evenness. Figure 6C showed that the FC group had narrower and steeper curves, suggesting reduced microbial abundance and homogeneity compared to the NC and post-treatment groups. To further determine the richness and variety of the gut microbiota, we evaluated the α-diversity and β-diversity in six sets of the mucosal samples. Coincidentally, several OTU-based indexes, such as Simpson, Shannon, Chao, and Ace, exhibited no notable differences among the six groups (P > 0.05), indicating similar microbiota abundance and homogeneity in the α-diversity analysis (Figure 6D-G). The β-diversity of the mucosal microbiota was demonstrated using the principal coordinate analysis, principal component analysis, non-metric multidimensional scaling analysis, and partial least squares discriminant analysis (Figure 6H-K). At the OTU level, the microbiota structure of the FC group differed significantly from that of the NC group and each medication group (P < 0.01), whereas the HRCNSP microbiota structure exhibited higher similarity to that of the NC group. The β-diversity differences in the mucosal microbiota between the FC, NC, and medication groups were notably larger than those within each group according to the ANOSIM and the Kruskal-Wallis H test results (P < 0.001) (Figure 6L and M). The FC and NC groups had distinct mucosal microbiota compositions, and RCNSP treatment promoted the normalization of the mucosal microbiota structure.

Figure 6 Runchangningshen paste changed the gut mucosal microbiota diversity in functional constipation rats. A: Pan curve; B: Core curve; C: Rank-Abundance curves; D-G: Alpha diversity analysis. The y-axis represents the operational taxonomic unit (OTU) level corresponding to each group based on the different indexes (n = 6) (D: Simpson index analysis; E: Shannon index analysis; F: Chao index analysis; G: Ace index analysis); H-M: Beta diversity analysis. The x-axis and y-axis represent two selected principal component (PC1 and PC2) axes, while the percentages indicate the explanatory values of the principal components regarding the differences in sample composition. Stress is used to assess the quality of the Non-metric multidimensional scaling analysis (NMDS) analysis results. Different colors or shapes represent different samples or groups. The closer the sample points or shapes are, the more similar the species composition of the two or two groups of samples becomes (n = 6) [H: Principal coordinates analysis (PCoA); I: Principal component analysis (PCA); J: NMDS analysis; K: Partial least squares discriminant analysis (PLS-DA); L: ANOSIM analysis; M: Kruskal-Wallis; H test analysis). All data were shown as the mean ± SD. P values were calculated using the ANOSIM test. ANOVA: Analysis of variance; FC: Functional constipation model group; HRCNSP: High dose of runchangningshen paste group; LAC: Lactulose group; LRCNSP: Low dose of runchangningshen paste group; MRCNSP: Medium dose of runchangningshen paste group; NC: Normal control group.

RCNSP changed the composition of the gut mucosal microbiota at the multispecies level in FC rats: To investigate the role of RCNSP in the microbial communities, a Venn map (Figure 7A), community heatmap, and cluster histograms were used to display the alterations in the gut mucosal microbiota at the phylum, family, and genus levels. Figure 7A showed that 647 OTUs were common to all six groups, with 1042 OTUs in the NC group, 876 OTUs in the FC group, 974 OTUs in the LRCNSP group, 980 OTUs in the MRCNSP group, 1014 OTUs in the HRCNSP group, and 991 OTUs in the LAC group. This indicated that FC reduced the mucosal microbial diversity, while the RCNSP treatment enhanced it, with HRCNSP being the most effective.

Figure 7 Runchangningshen paste changed the composition of gut mucosal microbiota at the multispecies level in functional constipation rats. A: Operational taxonomic unit analysis: Venn diagrams; B: Community heatmap analysis at the phylum level between normal control group (NC), functional constipation model group (FC), runchangningshen paste group (RCNSP), and lactulose group (LAC) group; C: Diagram of intergroup comparisons of NC, FC, and high RCNSP (HRCNSP) at the phylum level (n = 6); D: Diagram of intergroup comparison of NC and FC at the phylum level (n = 6); E: Diagram of intergroup comparison of FC and HRCNSP at the phylum level (n = 6); F: Community heatmap analysis at the family level between NC, FC, RCNSP, and LAC; G: Diagram of intergroup comparisons of NC, FC, and HRCNSP at the family level (n = 6); H: Diagram of intergroup comparison of NC and FC at the family level (n = 6); I: Diagram of intergroup comparison of FC and HRCNSP at the family level (n = 6); J: Community heatmap analysis at the genus level between NC, FC, RCNSP, and LAC; K: Diagram of intergroup comparisons of NC, FC, and HRCNSP at the genus level (n = 6); L: Diagram of intergroup comparison of NC and FC at the genus level (n = 6); M: Diagram of intergroup comparison of FC and HRCNSP at the genus level (n = 6). In graphs B, F, and J, the x-axis represents the group names, while the y-axis denotes the species names. The color gradient of the blocks illustrates the variations in abundance of different species within the groups, with the values represented by the color gradient displayed on the right side of the figure. In graphs C-E, G-I, and K-M, the x-axis shows the mean proportion or proportion difference of species in the sample, and the y-axis lists the species names or P values. The different colors of the bars denote distinct groups. The width of the bars reflects the magnitude of the species’ proportions. Data were expressed as mean ± SD. P values were calculated using Kruskal-Wallis H test or Wilcoxon rank-sum test. LRCNSP: Low dose of runchangningshen paste group; MRCNSP: Medium dose of runchangningshen paste group.

In the six sample groups, 22 bacterial species with significant variances were identified at the phylum level, primarily including Firmicutes, Bacteroidetes, Desulfobacterota, Campylobacteria, and Proteobacteria (Figure 7B). From this study, HRCNSP (6.26 g/kg/d) showed the strongest therapeutic effect on FC compared to the other treatment groups. Therefore, only the HRCNSP group was selected for a species composition comparison analysis. The Kruskal-Wallis rank sum test revealed notable variances in six bacteria at the phylum level among the NC, FC, and HRCNSP groups. Specifically, the Firmicutes, Bacteroidota, Proteobacteria, Campylobacteria, Deferribacterota, and Cyanobacteria exhibited statistically significant variances (P < 0.05, Figure 7C). In comparison with the NC group, the FC group decreased the Firmicutes (P < 0.01) and increased the Bacteroidota (P < 0.01), Campylobacteria (P < 0.05), Proteobacteria (P < 0.01), Cyanobacteria (P < 0.01), and Deferribacterota (P < 0.05) (Figure 7D). RCNSP treatment helped restore the FC mucosal microbiota composition. In contrast with the FC group, the HRCNSP group exhibited a reduction in the Proteobacteria (P < 0.05), Campylobacteria (P < 0.05), Cyanobacteria (P < 0.05), and unclassified_k__norank_d__Bacteria (P < 0.05), along with an increase in Spirochaetota (P < 0.05) (Figure 7E). Combining these two findings, changes in the phylum levels, particularly of the Campylobacteria, Proteobacteria, and Cyanobacteria, indicated the pathology of FC and could be potential targets for RCNSP effectiveness.

In six sample groups, 50 different bacterial species were detected at the family level, primarily including the Lactobacillus, Lachnospiraceae, Erysipelotrichaceae, Eubacterium_coprostanoligenes_group, Spirochaetaceae, Prevotellaceae, Ruminococcaceae, Helicobacteraceae, and Staphylococcaceae (Figure 7F). In the following, we chose the HRCNSP group with the best efficacy as the treatment group to compare the species composition at the family level. Fifteen bacteria were remarkably different in the NC, FC, and HRCNSP groups. These included Erysipelotrichaceae, Lactobacillaceae, Eubacterium_coprostanoligenes_group, Enterobacteriaceae, Helicobacteraceae, Xanthobacteraceae, Beijerinckiaceae, Comamonadaceae, and Carnobacteriaceae (P < 0.05, Figure 7G). In contrast with the NC group, the FC group reduced Erysipelotrichaceae (P < 0.05), Lactobacillaceae (P < 0.05), and Butyricicoccacea (P < 0.05), while increasing Muribaculaceae (P < 0.05), Eubacterium_coprostanoligenes_group (P < 0.05), Prevotellaceae (P < 0.01), Enterobacteriaceae (P < 0.01), Helicobacteraceae (P < 0.05), Deferribacteraceae (P < 0.05), UCG-010 (P < 0.05), Sphingomonadaceae (P < 0.01), Beijerinckiaceae (P < 0.01), Xanthobacteraceae (P < 0.05), Tannerellaceae (P < 0.05), and Carnobacteriaceae (P < 0.05) (Figure 7H). The RCNSP treatment improved the distribution of the FC mucosal microbiota at the family level. In comparison with the FC group, the HRCNSP group significantly increased certain bacteria such as the Lactobacillaceae (P < 0.01), Erysipelotrichaceae (P < 0.05), Spirochaetaceae (P < 0.05), Clostridiaceae (P < 0.05), Sutterellaceae (P < 0.05), Peptococcaceae (P < 0.05), and Bifidobacteriacea (P < 0.01) while decreasing the levels of the Eubacterium_coprostanoligenes_group (P < 0.05), Enterobacteriaceae (P < 0.01), Helicobacteraceae (P < 0.05), Xanthobacteraceae (P < 0.05), Beijerinckiaceae (P < 0.05), Carnobacteriaceae (P < 0.05), unclassified_k__norank_d__Bacteria (P < 0.05), and Rhizobiacea (P < 0.05), as shown in Figure 7I. Combined with these two findings, changes in the abundance of specific bacterial families, such as the Erysipelotrichaceae, Lactobacillaceae, Eubacterium_coprostanoligenes_group, Enterobacteriaceae, Helicobacteraceae, Beijerinckiaceae, Xanthobacteraceae, and Carnobacteriaceae, indicated the pathology of FC and served as potential targets for RCNSP effectiveness.

In total, 50 different bacterial species were detected in the six groups at the genus level, including Lactobacillus, Lachnospiraceae, Desulfovibrio, norank_f__Eubacterium_coprostanoligenes_group, norank_f__Desulfovibrionaceae, Treponema, norank_f__Oscillospiraceae, Helicobacter, Romboutsia, and Corynebacterium (Figure 7J). As before, the HRCNSP group with the highest efficacy was chosen as the treatment group to compare the species composition at the genus level. Notable variances were identified among the NC, FC, and HRCNSP groups across 15 bacterial species, such as norank_f__Muribaculaceae, Allobaculum, norank_f__Eubacterium_coprostanoligenes_group, Lactobacillus, norank_f__Desulfovibrionaceae, Alloprevotella, unclassified_f__Enterobacteriaceae, Helicobacter, unclassified_f__Lachnospiraceae, Colidextribacter, Blautia, Dubosiella, Faecalibaculum, Staphylococcus, and Mucispirillum (P < 0.05, Figure 7K). In contrast with the NC group, the FC group remarkably increased the abundance of norank_f__Muribaculaceae (P < 0.05), norank_f__Eubacterium_coprostanoligenes_group (P < 0.05), norank_f__Desulfovibrionaceae (P < 0.05), unclassified_f__Enterobacteriaceae (P < 0.01), Helicobacter (P < 0.05), Alloprevotella (P < 0.05), Blautia (P < 0.05), Mucispirillum (P < 0.05), norank_f__UCG-010 (P < 0.05), and Staphylococcus (P < 0.05) while decreasing the abundance of Allobaculum (P < 0.05), Lactobacillus (P < 0.05), Colidextribacter (P < 0.01), Dubosiella (P < 0.01), and Faecalibaculum (P < 0.05) (Figure 7L). The RCNSP treatment reversed the distribution of FC mucosal microbiota at the genus level. In comparison with the FC group, the HRCNSP group showed a significant decrease in the levels of several bacteria such as norank_f__Eubacterium_coprostanoligenes_group (P < 0.05), norank_f__Desulfovibrionaceae (P < 0.01), unclassified_f__Enterobacteriaceae (P < 0.01), Helicobacter (P < 0.05), Blautia (P < 0.05), and unclassified_f__Xanthobacteraceae (P < 0.05) (Figure 7M). Conversely, there was an increase in the proportion of Lactobacillus (P < 0.01), Treponema (P < 0.05), Desulfovibrio (P < 0.05), unclassified_f__Lachnospiraceae (P < 0.05), Clostridium_sensu_stricto_1 (P < 0.05), Faecalibaculum (P < 0.01), Parasutterella (P < 0.05), Dubosiella (P < 0.01), and Colidextribacter (P < 0.05), as shown in Figure 7M. According to the results, changes in the abundance of certain bacteria such as Lactobacillus, Colidextribacter, Dubosiella, Faecalibaculum, norank_f__Eubacterium_coprostanoligenes_group, Desulfovibrio, unclassified_f__Enterobacteriaceae, Helicobacter, and Blautia at the genus level indicated the pathology of FC and were potential targets for RCNSP efficacy. Therefore, the results showed that the RCNSP restored the disrupted mucosal microbiota caused by FC at the phylum, family, and genus levels.

RCNSP modulated the mucosal microbiota composition to promote defecation in FC rats

To further elucidate the mechanism of RCNSP in mitigating FC, Spearman’s correlation analysis was conducted among the mucosal microbiota and the indicators of defecation function (fecal number, fecal weight, water content of faces, gastric emptying rates, and intestinal propulsion rate) in the NC group, FC group, and HRCNSP group. At the phylum level, Firmicutes were positively correlated with the defecation function, whereas Proteobacteria, Bacteroidota, Cyanobacteria, Patescibacteria, Campylobacteria, and Deferribacterota were negatively correlated with the defecation function (P < 0.05) (Figure 8A). At the family level, Bifidobacteriaceae, Erysipelotrichaceae, and Atopobiaceae were positively correlated with the defecation function (P < 0.05); whereas Comamonadaceae, Sphingomonadaceae, Xanthobacteraceae, Prevotellaceae, Enterobacteriaceae, Beijerinckiaceae, Marinifilaceae, Muribaculaceae, Eubacterium_coprostanoligenes_group, Deferribacteraceae, Carnobacteriaceae, UCG-010, Erysipelatoclostridiaceae, Pseudomonadaceae, Helicobacteraceae, and Tannerellaceae were negatively associated with the defecation function (P < 0.05) (Figure 8B). At the genus level, Eubacterium_xylanophilum_group, Colidextribacter, Faecalibaculum, Allobaculum, and Dubosiella were positively correlated with the defecation function (P < 0.05), whereas unclassified_f__Enterobacteriaceae, Helicobacter, Mucispirillum, norank_f__Eubacterium_coprostanoligenes_group, Alloprevotella, norank_f__Muribaculaceae, norank_f__UCG-010, norank_f__Desulfovibrionaceae, and Blautia were negatively correlated with the defecation function (P < 0.05) (Figure 8C). Results indicated that the defecation dysfunction in FC rats was associated with the mucosal microbiota dysbiosis and that RCNSP could adjust the mucosal microbiota structure to promote defecation.

Figure 8 Runchangningshen paste modulated the mucosal microbiota composition to promote the defecation in functional constipation rats. A: Heatmap of the correlation between the differential microbiota at the phylum level and the indicators of the defecation function (n = 6); B: Heatmap of the correlation between the differential microbiota at the family level and the indicators of the defecation function (n = 6); C: Heatmap of the correlation between the differential microbiota at the genus level and the indicators of the defecation function (n = 6). Average was used for both clinical factors and species hierarchical clustering methods. We calculated the correlation between variables using the Spearman’scorrelation coefficient. The x-axis and y-axis represent clinical factors and species, respectively. The correlation coefficients (r values) and P values were obtained through calculations. The r values are displayed in the figure using different colors. ^aP < 0.05; ^bP < 0.01; ^cP < 0.001.

RCNSP changed the mucosal microbiota function to promote MUC2 secretion in FC rats

Changes in the symbiotic relationship of mucosal microbiota also indicate functional changes. To understand the role of RCNSP in the mucosal microbiota function in FC rats, we conducted PICRUSt2 functional prediction analyses on the FC, NC, and HRCNSP groups using 16S rDNA high-throughput sequencing data. This analysis utilized the Cluster of Orthologous Groups of proteins and Kyoto Encyclopedia of Genes and Genomes databases (Figure 9). First, the functional genes of the three groups of the mucosal microbiota focused on metabolism (Figure 9A), and this primarily included metabolic pathways and the biosynthesis of secondary metabolites as well as the microbial metabolism in diverse environments (Figure 9B). Subsequently, according to Figure 9C and D, the specific differential metabolic pathways included energy metabolism, carbohydrate metabolism, amino acid metabolism, lipid metabolism, nucleotide metabolism, the metabolism of terpenoids and polyketides, and glycan biosynthesis and metabolism. It was also shown that FC affected the metabolism of carbohydrate, amino acid, lipid, nucleotide, glycan, terpenoids and polyketides, and energy. In addition, other pathways for the enrichment of different microbiota included the excretory system, intracellular trafficking, secretion, and vesicular transport, membrane transport, folding sorting and degradation, defense mechanisms, cell motility, immune system, and signal transduction. In summary, RCNSP might play therapeutic roles in FC by modulating the above-mentioned pathways. Among these, the exocytosis process of ‘membrane transport’ is related to mucin secretion from the GCs: ‘Glycan biosynthesis and metabolism’ and ‘folding sorting and degradation’ are related to MUC2 synthesis; ‘intracellular trafficking, secretion’ and ‘vesicular transport’ are associated with MUC2 secretion in the GCs; and ‘immune system’ and ‘defense mechanisms’ are associated with the NLRP6 inflammasome activation. Thus, the therapeutic impact of RCNSP on FC might be associated with the modulation of MUC2 secretion.

Figure 9 Runchangningshen paste changed the mucosal microbiota function to promote mucin-2 secretion in functional constipation rats. A: Heatmap of Kyoto Encyclopedia of Genes and Genomes database (KEGG) functional enrichment of differential microbiota between normal control group (NC), functional constipation model group (FC) and high dose of runchangningshen paste (HRCNSP) groups at the pathway level 1 (n = 6); B: Heatmap of KEGG functional enrichment of differential microbiota between NC, FC and HRCNSP groups at the pathway level 2 (n = 6); C: Heatmap of KEGG functional enrichment of differential microbiota between NC, FC and HRCNSP groups at the pathway level 3 (n = 6); D: Orthologous groups of proteins database functional classification diagram of differential microflora among NC, FC, and HRCNSP groups (n = 6). In Figures A-C, the x-axis represents the group names, while the y-axis indicates the functional names at pathway levels 1/2/3. The color gradient of the blocks illustrates the variations in functional abundance across the groups, with the legend indicating the values represented by the color gradient. In Figure D, different colors represent different functional classifications, the x-axis represents the relative abundance of functional classifications, and the y-axis represents groups. COG: Cluster of Orthologous Groups.

RCNSP adjusted the relationship between the mucosal microbiota and NLRP6/autophagy pathway to promote MUC2 secretion in FC rats

Spearman’s correlation assessed the link between mucosal microbiota and the NLRP6/autophagy pathway in the NC, FC, and HRCNSP groups. First, at the phylum level, Firmicutes were positively correlated with the NLRP6/autophagy pathway (P < 0.05), whereas Proteobacteria, Bacteroidota, Cyanobacteria, Patescibacteria, and Deferribacterota were negatively correlated with the NLRP6/autophagy pathway (P < 0.05) (Figure 10A). Second, at the family level, Bifidobacteriaceae and Atopobiaceae were positively correlated with the NLRP6/autophagy pathway (P < 0.05), whereas Sphingomonadaceae, Xanthobacteraceae, Prevotellaceae, Enterobacteriaceae, Beijerinckiaceae, Eubacterium_coprostanoligenes_group, Deferribacteraceae, and Carnobacteriaceae were negatively associated with the NLRP6/autophagy pathway (P < 0.05) (Figure 10B). Third, at the genus level, the Eubacterium_xylanophilum_group, Faecalibacterium, Allobaculum, and Dubosiella were positively correlated with the NLRP6/autophagy pathway (P < 0.05); whereas the unclassified_f__Enterobacteriaceae, Mucispirillum, norank_f__Eubacterium_coprostanoligenes_group, norank_f__Desulfovibrionaceae, and Blautia were negatively correlated with the NLRP6/autophagy pathway (P < 0.05) (Figure 10C).

Figure 10  Runchangningshen paste adjusted the relationship between the mucosal microbiota and NLRP6/autophagy pathway to promote mucin-2 secretion in functional constipation rats. A: Heatmap of the correlation between the differential microbiota at the phylum level and NLRP6/autophagy pathway (n = 6); B: Heatmap of the correlation between the differential microbiota at the family level and NLRP6/autophagy pathway (n = 6); C: Heatmap of the correlation between the differential microbiota at the genus level and NLRP6/autophagy pathway (n = 6). The average was used for both clinical factors and species hierarchical clustering methods. We calculated the correlation between variables using the spearman's correlation coefficient. The x-axis and y-axis represent clinical factors and species, respectively. The correlation coefficients (r values) and P values were obtained through calculations. The r values are displayed in the figure using different colors. ^aP < 0.05; ^bP < 0.01; ^cP < 0.001.

DISCUSSION

An increasing number of researchers believe that constipation is related to decreased mucin secretion and the gut microbiota dysbiosis[6]. TCM has obvious advantages in the treatment of this disease. RCNSP has the function of nourishing yin and blood and loosening the bowel to relieve constipation. It has demonstrated notable clinical effectiveness in constipation[16]. However, the exact mechanism behind its actions remained unclear. Our study used a comprehensive approach, including UPLC-MS/MS, animal experiments, and gut microbiota sequencing, to investigate how RCNSP affected MUC2 secretion and the gut microbiota in FC rats. The results showed that RCNSP treated constipation by modulating the mucosal microbiota and activating the NLRP6/autophagy pathway to promote mucin secretion. These findings offered valuable information on the therapeutic efficacy of RCNSP in FC and enhanced the theoretical basis of TCM regarding the nourishment of yin and blood for treating FC.

Based on the UPLC-MS/MS analysis, the primary elements of RCNSP that might have the laxative effect were emodin-3-methylether/physcion, hyperoside, rutin, scopoletin, betaine, genkwanin, trigonelline HCl, adenosine, caffeic acid, α-linolenic acid, chlorogenic acid, and 6-hydroxyindole. Among these, adenosine regulates intestinal function by controlling secretion, motility, and sensation in the gut while participating in ATP synthesis[29]. Chlorogenic acid improves the intestinal barrier and regulates the brain-gut axis[30], which may have a therapeutic effect on constipation. Emodin-3-methylether/physcion and hypericin, classified as anthraquinone compounds, demonstrate laxative properties through enhanced intestinal motility, stimulation of fluid, and electrolyte secretion[31,32].Rutin belongs to the flavonoid class of compounds, and the purified flavonoid components can significantly improve the main symptoms of hemorrhoids[33]. Allium mongolicum Regel, which contains flavonoids, upregulates the expression of AQP3 to increase the luminal water content and activates the Gα/PI3K signaling pathway to promote the influx of calcium from the extracellular space into the cells, thereby enhancing colonic muscle contractions to treat constipation[34]. Scopolamine administration aids in restoring gastrointestinal epithelial and smooth muscle tissue disruption caused by a high-glucose diet, ameliorating abnormal food accumulation while rehabilitating intestinal structure and transport function[35]. Cistanche total alditol extract, which contains betaine, significantly modulates neurotransmitters, upregulates c-kit expression, enhances intestinal transit, and reduces intestinal inflammation in FC rats[36]. Flavone genkwanin, a non-glycosylated compound, demonstrates diverse bioactivities including anti-inflammatory, antioxidant, anticancer, antimicrobial, and neuroprotective properties that may contribute to alleviating constipation[37]. Trigonelline enhances mitochondrial respiration and biogenesis, mitigates age-related muscle atrophy via an NAD+-dependent mechanism, and may have the potential to influence colonic muscle strength to produce a laxative effect[38]. SGE-107, which primarily contains caffeic acid, exhibits antioxidant and anti-inflammatory properties, significantly improving symptoms of constipation[39]. Flaxseeds, which are rich in α-linolenic acid, have the potential to decrease intestinal permeability and endotoxemia[40], leading to a notable increase in bowel movement frequency and an improvement in stool consistency[41]. Bombax ceiba Linnaeus, which contains chlorogenic acid and rutin, can restore the function of colonic GCs, protect the colonic mucosa, downregulate the expression of AQP3 protein, and increase the expression of c-kit protein to treat constipation[42]. Additionally, rosmarinic acid, which contains 6-hydroxyindole, can influence the gut microbiota metabolites, leading to the activation of the NLRP6 inflammasome and enhancement of colonic mucus secretion[43].

In this research, we initially examined the impact of RCNSP on LOP-induced defecation indicators and mucin secretion. LOP gavage resulted in reduced fecal number, weight, and water content within 24 h. Meanwhile, the rate of gastric emptying and intestinal propulsion declined, consistent with the FC phenotype reported in the existing literature[44]. Additionally, anorexia emerged as an important symptom of constipation[45], with reduced food intake potentially contributing to weight loss. In this study, FC rats showed decreased appetites and weight loss, aligning with findings in the literature[45]. Constipation is associated with reduced mucus secretion that leads to insufficient intestinal lubrication and prolonged retention time of feces. Those result in reduced moisture in the fecal matter and delayed gastrointestinal transit. MUC2 is the main component of mucus, and it is secreted by the GCs derived from stem cell renewal at the base of the colonic mucosa crypts. Consistent with previous studies[8], H&E and AB-PAS tissue staining revealed damage to the mucosal layer and reduced mucin secretion in FC rats. Fortunately, RCNSP promoted gastrointestinal transit, increased mucin secretion, and repaired intestinal epithelial damage in FC rats. Overall, RCNSP alleviated LOP-induced changes in gastrointestinal motility and mucin content. Further studies showed that RCNSP increased autophagy in GCs and protected mitochondria, activated the expression of genes and proteins in the NLRP6/autophagy/MUC2 pathway, and adjusted the intestinal mucosal microbiota structure. Thus, RCNSP might activate the NLRP6/autophagy pathway to promote MUC2 secretion and modulate mucosal microbiota.Autophagy produces double-membrane autophagic vesicles that merge with lysosomes for degradation, enclosing the components. This process is associated with immunity and inflammation. Mitochondrial autophagy degrades the damaged mitochondria to maintain cellular function. Defective cellular autophagy leads to an increase in the damaged mitochondria. Elevated autophagy levels in GCs have been linked to mucin production[46]. Knockdown of an autophagy-related gene in the colon epithelium reduces mucin production and release[47]. Examination of the ultrastructure of GCs using TEM in the FC group showed fewer autophagosomes, degenerated mitochondria, and an accumulation of intracellular mucin granules, similar to previous research findings[14]. In contrast, the RCNSP treatment increased the autophagic vesicles, decreased degenerating mitochondria, and enhanced mucin secretion into the intestinal lumen. Complex exocytosis involves interconnected cellular processes like endocytosis, autophagy, inflammasome assembly, and endoplasmic reticulum stress[48]. These processes regulate the storage and release of mucin particles, serving as the main mechanisms for mucin secretion[48]. NLRP6, highly expressed in the colon, can enhance MUC2 secretion from GCs through the NLRP6/autophagy pathway[14]. NLRP6 assembly involves specific steps. First, tumor necrosis factor alpha, viral stimuli, and microbiome signals induce NLRP6 transcription. Second, PPARγ binds to the NLRP6 promoter to start transcription. Finally, microbial elements and damage-associated patterns activate NLRP6, forming an inflammasome that activates IL18 and IL1β via ASC and Caspase-1 interactions. In terms of autophagic activation, Beclin1 regulates VPS34 complex activation, initiating autophagy. LC3-I binds with phosphatidylethanolamine to form LC3-II, essential for autophagosome formation. P62 facilitates the degradation of ubiquitinated substrates by interacting with ubiquitin and LC3-II or transporting damaged proteins to the proteasome. Therefore, the decrease in P62 levels indicates a smooth flow of autophagy. The NLRP6/autophagy pathway maintains the intestinal epithelial cell homeostasis and is linked to functional dyspepsia[49] and ulcerative colitis[49]. In this study, we found that FC pathology resulted from the downregulation of this pathway, while RCNSP activated this pathway to treat FC. The herbal formula of the Qing-Chang-Hua-Shi granule also has the potential to enhance colonic MUC2 secretion by influencing the NLRP6 pathway, similar to the findings of our research[50].

Microbiota dysbiosis results from disruptions in the composition and function of the microbiota due to environmental and host-related factors, surpassing their ability to resist and recover. This condition has been linked to the development of FC[6-8]. Colonic mucosal microbiota maximize the expression of information about the microbiota in the colon and are thought to be more closely related to FC[10]. Therefore, we explored the relationship between the mucosal microbiota and FC. Sequencing analysis of the mucosal microbiota in the ascending colon revealed that the FC group exhibited reduced microbiota diversity, but the RCNSP treatment helped normalize the mucosal microbiota structure of the FC group and increase the microbiota diversity. By conducting Spearman’s correlation analysis between differential microbiota at the family, genus, and phylum levels for the FC, NC, and HRCNSP groups and the defecation indicators, we could elucidate the mucosal microbiota related to the pathological features of FC and the target of the RCNSP effect. Among them, beneficial bacteria that positively correlate with defecation indicators promote defecation, while harmful bacteria that negatively correlate with these indicators inhibit it. The probiotics mentioned in this research included Faecalibacterium, Erysipelotrichaceae, Bifidobacteriaceae, and Dubosiella, among others. Studies have shown that the use of Bifidobacterium-containing probiotics can increase serotonin levels and mucin-related genes and increase the abundance of Erysipelotrichaceae for the treatment of LOP-induced constipation[51]. Faecalibacterium enhances the gut barrier to stabilize the gut microflora structure[52]. Psyllium husk can treat constipation by increasing Faecalibacterium to increase fecal water content[53].The comparison of 16S rRNA sequencing results of fecal microbiota between patients experiencing constipation and healthy individuals revealed that Faecalibacterium and Blautia were protective bacterial species that helped prevent constipation[54]. The abundance of Dubosiella is associated with the expression of AQP8 and vasoactive intestinal peptide receptor 1[55]. Additionally, Bifidobacterium FXJCJ32M2 can increase Dubosiella to treat constipation[55]. Strains of bacteria such as Cyanobacteria and Campilobacterota were the harmful bacteria identified in this study, which could disrupt the balance of gut microbes by competing for nutrients or releasing antimicrobial substances to inhibit the growth of beneficial bacteria. Cyanobacteria produces lipopolysaccharide, a type of endotoxin that may reduce nitrergic neurons and inhibit colonic transit, potentially leading to constipation[56]. Campylobacter belongs to the Campilobacterota, and increased Campylobacter in mucosal microbiota has been linked to various diseases, including nodular lymphoid hyperplasia in the small intestine[57] and oral squamous cell carcinoma that could potentially lead to colorectal cancer[58]. Degradation of drugs by the gut microbiota can produce metabolites such as short-chain fatty acids (SCFAs), organic acids, and gases to affect the gut function[59]. SCFAs are the primary end products that can affect defecation through various mechanisms. For instance, they can enhance the production of serotonin, regulate the enteric neurons to affect the gut motility[60], and modulate the production of mucins and the expression of antimicrobial peptides, thereby regulating intestinal immune responses and epithelial barrier function[61]. Last but not least, they can also regulate the contractility of colonic smooth muscle[62], impacting the absorption of water and electrolytes[60]. Butyrate, recognized as a postbiotic, refers to an SCFA generated by the gut microbiota via anaerobic bacterial fermentation. It acts as the primary energy supplier for intestinal epithelial cells. In the colon, butyrate suppresses mucin secretion[63], reduces stool volume by increasing water and electrolyte absorption[64,65], and inhibits smooth muscle contraction[66], potentially raising the risk of constipation. The literature indicated that an increase in butyric acid-producing flora such as Proteobacteria, Enterobacteriaceae, Blautia, and Eubacterium was associated with FC[67-69]. Proteobacteria is the second largest phylum of hydrogenogenic CO oxidizers, consisting of members categorized into various classes (α-, β-, γ-, and ε-proteobacteria). In this study, Beijerinckiaceae, Xanthobacteraceae, and Helicobacteraceae belong to Proteobacteria. The Helicobacteraceae family primarily includes Helicobacter, notably Helicobacter pylori (HP), a significant human pathogen linked to gastrointestinal diseases. Chronic HP infection shifts the gut microbiota by altering stomach acidity, enabling more microorganisms to bypass gastric acid and colonize the lower intestine. FC is common in children with HP infection[70], and treating the infection can alleviate constipation symptoms[71]. Enterobacteriaceae synthesize Curli, an amyloid protein that has the potential to facilitate the aggregation of α-synuclein in both the intestinal and cerebral regions, results in disrupted colonic motility[72,73]. Treatment of mice with intestinal-restricted amyloid inhibitors has been shown to mitigate motor dysfunction and symptoms resembling constipation[73]. Bile acids are associated with colonic transport and the secretion of gut hormones[74,75], which is why there is a reduction in fecal bile acid content in patients with constipation[76]. The g_Eubacter_coprostanoligenes_group has the potential to modulate bile acid synthesis and metabolism by augmenting the enzymatic function of 7α-dehydroxylase[75], ultimately leading to decreased absorption, peristalsis, and defecation[75].Erysipelotrichaceae has the potential to impair intestinal barrier integrity and diminish nutrient absorption by generating endotoxins and influencing bile acid metabolism[77]. In contrast, Colidextribacter stimulates bile acid production[78] and improves the intestinal barrier[79] to treat constipation. Hydrogen sulfide is a gaseous transmitter that modulates colonic motility by inhibiting L-type calcium channels and BKCa channels in rat colonic smooth muscle cells[80] and is involved in gastrointestinal tract inflammation and mucosal repair[81]. Prevotellaceae can secrete hydrogen sulfide, and an increase in Prevotella_2 and Prevotella_9 has been observed in children with constipation-type autism spectrum disorders[82]. However, it has also been shown that Prevotellaceae produce SCFAs to promote gastrointestinal peristalsis[83] and increase fecal water content[84].

The intestinal barrier is formed by the mucus produced by the epithelium, intestinal epithelial cells, and tight junctions. This barrier prevents toxins, antigens, and the gut microflora from entering the intestinal mucosa, thus maintaining a stable internal environment. Reduced mucus levels can weaken the barrier and change the microbiota composition. Research suggested that reduced mucus thickness from constipation allowed the gut microbiota to penetrate the epithelium, leading to an abnormal microbiota composition[85]. In contrast, the colonization of specific microbiota could affect mucin production[86]. This study suggested that the changes in the mucosal microbiota structure during constipation might influence the mucus layer thickness. Functional enrichment analyses of the different microbiota among the NC, FC, and HRCNSP groups indicated that the effectiveness of RCNSP on FC might be linked to the regulation of MUC2 secretion. Subsequently, we analyzed the relationship between different microbes and the core proteins in the NLRP6/autophagy pathway. We identified microbiome species associated with the NLRP6/autophagy pathway at different taxonomic levels. This pathway initiates with the activation of NLRP6 inflammasome, and existing studies have also shown that some of the microbiota identified in this study promote inflammasome activation. For example, Firmicutes are Gram-positive bacteria containing the surface-associated adhesion compound lipoteichoic acid that trigger the NLRP6 inflammasome activation[87]. Bifidobacterium bifidum has a double regulatory effect on NLRP6 expression, whereas Bacteroides fragilis inhibits NLRP6 protein expression[88]. In addition, substances produced by microorganisms, such as organic acids and taurine, can activate the NLRP6 inflammasome, while histamine and spermine can inhibit it[89]. Therefore, we thought that the microbiota might regulate mucus secretion by activating the NLRP6/autophagy pathway. Similarly, the colonization of Akkermansia muciniphila enhances the NLRP6/autophagy pathway to promote the secretion of antimicrobial peptides[90]. The glycosylation profile of mucins can influence the composition of mucus-associated microbiota, and mucin O-glycans promote the homeostasis between host and microbiota[91]. In this study, the pathological mechanism of FC might involve reduced mucin secretion, leading to the disruption of the mucosal microbiota structure. The deficiency in dietary fiber is a significant factor contributing to constipation. Research has confirmed that the lack of dietary fiber can lead to a reduction in mucus thickness and dysbiosis of the gut microbiota[92]. Conversely, supplementation with dietary polysaccharides can increase MUC2 content and modulate the structure of the gut microbiota[93]. Mucosal microbiota dysbiosis might affect the activation of the NLRP6/autophagy pathway and exacerbate the reduction in mucus secretion[94-96]. Consequently, it might lead to reduced water content in feces, causing difficulty in passing solid stools. RCNSP could activate the NLRP6/autophagy pathway to promote MUC2 secretion by modulating the structure of the mucosal microbiota to treat constipation. Similar to the present study, existing literature also confirms that TCM can affect the gut microbiota and promote NLRP6 activation to promote the mucosal health in gastrointestinal disorders. For instance, mild moxibustion for post-infectious irritable bowel syndrome[97] and mulberry for colitis[98].

In this study, UPLC-MS/MS analysis revealed that the active components in RCNSP, such as emodin-3-methylether/physcion, hyperoside, rutin, scopoletin, betaine, genkwanin, trigonelline HCl, adenosine, caffeic acid, α-linolenic acid, chlorogenic acid, and 6-hydroxyindole, might ameliorate constipation by protecting the function of colonic GCs, modulating the expression of AQP3, activating the Gα/PI3K signaling pathway, regulating the brain-gut axis, and adjusting the gut microbiota, thereby controlling intestinal secretion, motility, and sensory functions. Animal experiments indicated that RCNSP might alleviate constipation by promoting MUC2 secretion through the activation of the NLRP6/autophagy pathway. Mucosal microbiota sequencing revealed that RCNSP potentially treated constipation by increasing beneficial microorganism strains, reducing harmful microorganism strains that produce butyrate and hydrogen sulfide, and decreasing microorganism strains that inhibit bile acids. Correlation analysis between key proteins of the NLRP6/autophagy pathway and differential microbiota indicated that the microbiota regulated by RCNSP might activate the NLRP6/autophagy pathway through its lipoteichoic acid or metabolic products, thereby promoting MUC2 secretion. In summary, the components in RCNSP might regulate the mucosal microbiota structure through multitarget and multipathway effects to activate the NLRP6/autophagy pathway, thereby promoting MUC2 secretion to treat constipation.

Mucosal microbiota and mucin are critical components of the intestinal barrier. This study revealed that RCNSP might modulate the mucosal microbiota to enhance mucin secretion, thereby providing protection to the intestinal barrier. In clinical practice, when treating diseases associated with barrier defects, such as irritable bowel syndrome[99], inflammatory bowel disease[100], obesity, and type II diabetes[100], the use of RCNSP may be considered, particularly in the presence of constipation. Clinical research has found that RCNSP not only has a laxative effect but can also treat insomnia[16]. Therefore, we discuss its laxative mechanism solely from the perspectives of mucins and the mucosal microbiota, without exploring it from the gut-brain axis perspective, which is somewhat lacking. Furthermore, for this study, the specific mechanism by which RCNSP-dependent microbiota activates the NLRP6/autophagy pathway to promote MUC2 secretion requires further validation. The directions of our subsequent research are as follows. Through microbiota depletion and microbial transplantation, we will identify the core bacterial species involved in the activation of the NLRP6/autophagy pathway that promote MUC2 secretion. Next, we will isolate the selected core microbial communities and purify or synthesize new functional metabolites to evaluate or validate their safety and efficacy. Based on the results obtained, these will be applied in the clinical treatment of patients with constipation to verify their therapeutic effects.

CONCLUSION

This study suggested that RCNSP might promote mucin secretion to increase fecal water content and accelerate gastrointestinal transit to treat FC. The mechanism involved the modulation of mucosal microbiota structure and the activation of the NLRP6/autophagy pathway to enhance colonic MUC2 secretion. In addition, mucosal microbiota might promote MUC2 secretion by activating the NLRP6-mediated autophagy pathway. This point deserves further exploration.

ACKNOWLEDGEMENTS

We thank all the members of the research team.