Thirty male C57BL/6Cnc mice, aged 8 weeks and weighing between 18 and 22 grams, were procured from Cyagen, Suzhou, China. These mice were housed under specific pathogen-free conditions, maintained on a 12-hour light/dark cycle, at a temperature of 21 °C ± 2 °C, and a relative humidity of 45% ± 10%. The mice were fed freely during the entire study, and there was no difference in food consumption between the different groups. All animal experiments were conducted in accordance with the guidelines of the Institutional Animal Care and Use Committee of Shanxi Datong University(NO.202410261). After 1 week of acclimatization, the mice were randomly separated into 3 groups, with 10 mice/group.

All interventions are depicted in Figure 1. During the experimental period, all three groups of mice were administered a 0.9% saline solution via gavage and had ad libitum access to drinking water. The control group received standard sterile water. In contrast, both the model (AS-IV) and intervention groups were initially exposed to a 2% DSS solution for one week, followed by two weeks of normal sterile water; this cycle was repeated three times. Subsequently, the mice were maintained on normal sterile water for an additional week. In the intervention group, AS-IV (Shanghai Aladdin Biochemical Technology Co., Ltd.) was administered orally at the onset of the modeling phase at a dosage of 15 mg/kg, equivalent to 1% of the mice’s body weight. Throughout all experiments, the mice were allowed unrestricted access to food, and no significant differences in food intake were observed among the groups. Throughout the experimental period, the mice were monitored bi-daily for signs of morbidity, and their body weights were systematically recorded. Each mouse was assessed for pathological characteristics, including stool consistency, presence of blood in the stool, and body weight loss. These individual assessments were aggregated to calculate the Disease Activity Index (DAI), following the methodology outlined in prior research (Ma et al., 2023). Diarrhea degree was scored 0 for well-formed pellets, 0.3 for soft pellets, 0.6 for pasty stools, 0.9 for liquid stools. Bleeding degree was scored as 0, when there was no blood; 2, for slight bleeding; 4, for gross bleeding (Wei et al., 2016). Subsequently, all mice were euthanized via an intraperitoneal injection of 0.01–0.02 ml/g of pentobarbital sodium.

All mice were euthanized under general anesthesia. A comprehensive autopsy was conducted to examine the external surface, thoracic cavity, abdominal cavity, and their respective contents. Cecal contents were collected and stored at -80 °C for subsequent 16S rRNA sequencing analysis and non-targeted metabolomics testing. Colon tissue was harvested for RNA isolation and immediately frozen, while the distal colon was preserved for histological examination by fixation in 4% paraformaldehyde. Histopathological analysis of the distal colon was carried out using hematoxylin and eosin (H&E) staining to evaluate the severity of tissue damage induced by colitis.

Cecal contents were collected from each mouse (n=6 per group) for microbiota analysis. Bacterial genomic DNA was extracted from frozen cecal content samples using the QIAamp DNA Stool Mini Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. The V3-V4 hypervariable region of the bacterial 16S rRNA gene was amplified by polymerase chain reaction (PCR) using barcoded universal primers 341F (5′-CCTACGGGNGGCWGCAG-3′) and 806R (5′-GGACTACHVGGGTATCTAAT-3′). The purified, quantified, and normalized amplicons were subjected to paired-end sequencing on an Illumina MiSeq PE250 platform (Illumina, San Diego, CA, USA). Sequencing services were provided by Realbio Technology Co., Ltd. (Shanghai, China). The raw paired-end sequencing data were processed using the QIIME2 pipeline (version 2020.11). Briefly, the DADA2 plugin was employed for quality filtering, denoising, merging of paired-end reads, and chimera removal, yielding high-resolution amplicon sequence variants (ASVs). Representative ASV sequences were taxonomically classified against the SILVA database (release 138). Alpha diversity indices (Chao1, Shannon, Simpson) and Beta diversity [based on Bray-Curtis distance, visualized via Principal Coordinates Analysis (PCoA)] were calculated within QIIME2, with statistical comparisons performed between groups (e.g., PERMANOVA). Finally, the Linear Discriminant Analysis Effect Size (LEfSe) method (with an LDA score threshold > 2.0 and p < 0.05) was applied to identify microbial taxa exhibiting significant differential abundance across groups.

Cecal contents (25 mg ± 1 mg) were collected and combined with beads and 500 μL of an extraction solution composed of methanol, acetonitrile, and water in a 2:2:1 (v/v) ratio. This extraction solution contained deuterated internal standards. The mixture was subjected to vortexing for 30 seconds. Subsequently, the sample was transferred to a clean Eppendorf tube for centrifugation at 15,000 × g for 20 minutes at 4 °C. The resulting supernatant was then utilized for liquid chromatography-mass spectrometry (LC-MS) analysis. LC-MS/MS analyses were conducted using an ultra-high-performance liquid chromatography (UHPLC) system (Vanquish, Thermo Fisher Scientific) equipped with a Waters ACQUITY UPLC BEH Amide column (2.1 mm × 50 mm, 1.7 μm) and coupled to an Orbitrap Exploris 120 mass spectrometer (Orbitrap MS, Thermo). The mobile phase consisted of 25 mmol/L ammonium acetate and 25 mmol/L ammonia hydroxide in water (pH = 9.75) as solvent A, and acetonitrile as solvent B. The auto-sampler was maintained at a temperature of 4 °C, with an injection volume of 2 μL. The Orbitrap Exploris 120 mass spectrometer was employed for its capability to acquire MS/MS spectra in information-dependent acquisition (IDA) mode, controlled by the Xcalibur software (Thermo). In this mode, the acquisition software continuously evaluates the full-scan MS spectrum. The conditions for the electrospray ionization (ESI) source were configured as follows: a sheath gas flow rate of 50 arbitrary units (Arb), an auxiliary gas flow rate of 15 Arb, and a capillary temperature of 320 °C. The full MS resolution was set at 60,000, while the MS/MS resolution was maintained at 15,000. The collision energy was specified as stepped normalized collision energy (SNCE) at 20/30/40. The spray voltage was adjusted to 3.8 kV for positive ion mode and -3.4 kV for negative ion mode. The raw data were converted to the mzXML format using ProteoWizard. Subsequent data processing, including peak detection, extraction, alignment, and integration, was conducted using an in-house program developed in R, based on the XCMS package. Metabolite identification was facilitated by the R package and BiotreeDB (version 3.0).

The colon was fixed in 4% PFA. Paraffin-embedded sections were cut at a thickness of 4 mm and stained with H&E solution. For immunohistochemistry (IHC), paraffin sections were incubated with antibodies specific for Ki-67 antibody (Abcam, cat# ab15580, 1:200 dilution). The specific steps were performed according to previous study.

Statistical analysis was performed using GraphPad Prism 10.0 software (GraphPad Software Inc., La Jolla, CA, USA). One-way analysis of variance with Tukey’s multiple comparison correction was used to detect differences among more than two groups. The results are reported as mean ± SD. A P-value < 0.05 was considered significant. Spearman’s correlation analysis was conducted between the bacteria and the UC-related parameters using R Programming Language (V4.0.2, AT&T Bell Laboratories, Auckland, New Zealand).

Initially, regarding alterations in body weight and colon length, the mice in the DSS group exhibited a significant reduction in weight throughout the 10-week experiment. Conversely, in the AS-IV treatment group, this trend of weight loss was notably reversed. Specifically, when compared to the Control group, the DSS group demonstrated a substantial decrease in weight gain, whereas the AS-IV group showed a gradual recovery in weight gain from week 5 to week 10 (Figure 2a). Furthermore, improvements were observed in both the bleeding index and diarrhea score. The bleeding index indicated a significant increase in the DSS group by the 10th week, while the AS-IV group experienced a marked alleviation of bloody stool symptoms, as evidenced by a significant decrease in the bleeding index (Figure 2b). Mice in the DSS group began experiencing diarrhea from the fifth week, with feces becoming thinner and more difficult to form. However, in the AS-IV treated mice, the diarrhea index significantly decreased, and fecal consistency gradually returned to normal levels (Figure 2c). These findings suggest that AS-IV exerts a potent inhibitory effect on DSS-induced intestinal bleeding. The DAI index also shows the same trend (Figure 2d). Simultaneously, the colon length in the DSS group was markedly reduced, whereas the colon length in the AS-IV group was significantly restored. This suggests that AS-IV has the potential to effectively mitigate pathological alterations, including colon shortening and weight loss, induced by DSS ((Figures 2e, f). Histological examination using Hematoxylin and Eosin (H&E) staining revealed that mice treated with dextran sulfate sodium (DSS) exhibited a loss of crypt structures, infiltration of mononuclear cells, and pronounced mucosal damage. In contrast, the group treated with AS-IV displayed reduced inflammatory cell infiltration, relatively preserved colonic architecture, and diminished mucosal damage ((Figure 2g). These results indicate that the administration of AS-IV significantly alleviated the pathogenic symptoms associated with DSS-induced ulcerative colitis (UC).

The results presented above suggest that a reduction in gut microbiota diversity may contribute to the development of chronic inflammation, thereby necessitating strategies to regulate microbiota diversity and metabolism. In recent years, traditional Chinese medicine has gained attention due to its low side effect profile. Consequently, we employed AS-IV at a dosage of 15 mg/kg as an intervention strategy. Analysis of the gut microbiota revealed that AS-IV significantly mitigated the decline in alpha diversity, as evidenced by the alpha diversity indices Observed, Chao1, Simpson, Shannon, and ACE (Figure 3A). Furthermore, Principal Coordinates Analysis (PCoA) demonstrated significant separation among the three groups, indicating notable differences in microbial community composition (Figure 3b). The taxonomic landscapes of these groups exhibited similar communities at both the phylum and genus levels, with relatively high abundances of the Lachnospiraceae-NK4A136 group, Allobaculum, and the Clostridium_sensu_stricto_1. Moreover, it is apparent that AS-IV intervention has the potential to alleviate the reduction of the Lachnospiraceae-NK4A136 group associated with chronic inflammation, as well as the proliferation of Clostridium_sensu_stricto_1(Figures 3c, d). The phylum-level analysis of differential bacterial populations indicated that AS-IV significantly mitigates the reduction in Bacteroidota and the increase in Actinobacteria induced by DSS (Figure 3e). At the genus level, the analysis demonstrated that AS-IV significantly upregulated 11 bacterial genera associated with chronic inflammation, including Turicibacter, Clostridium sensu stricto 1, and Romboutsia, while significantly downregulating 18 bacterial genera, such as Peptococcus, Roseburia, and Alistipes (Figure 3f). Thereby, AS-IV treatment ameliorated disease progression and was characterized by the restoration of gut microbiota and metabolic product diversity.

Subsequently, we performed untargeted metabolomics analysis on animal models administered with AS-IV. The findings revealed that, in comparison to the Control group, the DSS group exhibited a total of 955 differential metabolites (with a VIP score greater than 1 and a FDR less than 0.05), of which 80 were upregulated and 875 were downregulated. In contrast, the AS-IV intervention group, when compared to the DSS group, demonstrated a total of 610 differential metabolites, with 494 upregulated and 116 downregulated (Figure 4a). Principal Coordinates Analysis (PCoA) indicated distinct clustering of metabolites among the Control, DSS, and AS-IV groups, signifying substantial separation among these groups (Figure 4b). Furthermore, a cross-analysis of metabolites modulated by AS-IV treatment in conjunction with CRC and CK treatment with CRC revealed that 349 metabolites were upregulated, whereas only 53 were downregulated (Figures 4c, d; Supplementary Table S1). Enrichment analysis of these differential metabolites reveals associations with several metabolic pathways, including arachidonic acid metabolism, ubiquinone and other terpenoid-quinone biosynthesis, phenylalanine, tyrosine, and tryptophan biosynthesis, linoleic acid metabolism, arginine and proline metabolism, tryptophan metabolism, phenylalanine metabolism, primary bile acid biosynthesis, alpha-linolenic acid metabolism, purine metabolism, steroid hormone biosynthesis, sphingolipid metabolism, cysteine and methionine metabolism, glycerophospholipid metabolism, steroid biosynthesis, tyrosine metabolism, and fatty acid biosynthesis, among others (Figure 4e). AS-IV treatment was associated with restoration of the gut microbiota and attenuation of inflammation, suggesting a potential role of microbiota modulation in its therapeutic effects.

Initially, we employed the PICRUSt2 analysis tool to predict and examine species functions based on amplicon sequencing data. The findings indicated that AS-IV could significantly mitigate pathways with elevated abundance in the DSS group, such as the synthesis and degradation of ketone bodies, primary bile acid biosynthesis, D-arginine and D-ornithine metabolism, atrazine degradation, carotenoid biosynthesis, caprolactam degradation, proteasome, toxoplasmosis, and Staphylococcus aureus infection. Upon comparing the differential metabolite enrichment pathways regulated by AS-IV, it was observed that only the primary bile acid biosynthesis pathway overlapped. This suggests that AS-IV may alleviate chronic inflammation by modulating the gut microbiota, thereby influencing the biosynthesis of primary bile acids (Figure 5a). Subsequently, a correlation analysis was performed on the differential microbiota and metabolism. The analysis revealed that in the DSS group, bacterial genera such as Prevotellaceae-UCG-001, Clostridium sensu stricto 1, and Romboutsia, which exhibited a significant increase but subsequently decreased following AS-IV intervention, demonstrated a significant negative correlation with metabolites that increased (and significantly decreased post-AS-IV intervention). Conversely, these genera showed a significant positive correlation with metabolites that decreased significantly (and increased after AS-IV intervention). In contrast, bacterial genera such as Alistipes, Odoribacter, and Lachnoclostridium, which significantly decreased in the DSS group and increased following AS-IV intervention, exhibited the opposite correlation trend (Figure 5a).