Zanthoxylum, dried ginger rhizome, ginseng, and maltose were purchased from Beijingtongrentang Co., Ltd. (Beijing, China). Reference standards, including skimmianine, 6-gingerol, 6-shogaol, ginsenoside Rb₁, ginsenoside Re, and ginsenoside Rg₁, were obtained from Chengdu Push Bio-Technology Co., Ltd. (Sichuan, China). DSS (MW 36,000–50,000) was purchased from MP Biomedicals (Santa Ana, CA, USA), and sulfasalazine (SASP) was purchased from MedChemExpress Co., Ltd. (NJ, USA). Methanol, acetonitrile, and formic acid were sourced from Macklin Biochemical Co., Ltd. (Shanghai, China).

Following extraction from colonic tissues, total protein was quantified and analyzed by Western blotting using standard protocols [36]. The following primary antibodies were used: anti-ZO-1 (1:1000, Cat #ab276131; Abcam, Cambridge, MA, USA), anti-Occludin (1:1000, Cat #ab216327; Abcam), anti-Claudin-2 (1:1000, Cat # A14085; Abclonal, Boston, MA), anti-p-STAT3 (1:1000, Cat #ab32143; Abcam), anti-STAT3 (1:1000, Cat #ab68153; Abcam), and anti-GAPDH (1:5000, Cat #ab8245; Abcam) antibodies.

Immunostaining was performed according to standard protocols [30]. Sections were probed with anti-IL-22 (1:100, Cat #ab227033; Abcam) or anti-proliferating cell nuclear antigen (PCNA; 1:100, Cat #ab92552, Abcam) primary antibodies. Probed with fluorochrome-conjugated secondary antibodies after PBS rinses, sections were 4’6-diamidino-2-phenylindole (DAPI)-counterstained for subsequent imaging.

Genomic DNA was extracted from fecal samples using the cetyltrimethylammonium bromide method, and its integrity was assessed by agarose gel electrophoresis. The V3–V4 regions of the 16S rRNA gene were amplified and sequenced on an Illumina MiSeq platform (Illumina, San Diego, CA, USA). After quality control, adapter trimming, and read merging, operational taxonomic units (OTUs) were clustered at 97% similarity using UPARSE (v7.0.1001) within QIIME2 (v2020.6). Taxonomy was assigned against the SILVA database with Mothur. Microbial diversity was evaluated through α-diversity metrics and β-diversity via principal coordinates analysis (PCoA) based on Bray–Curtis distances in R software (v4.0.3). Differential abundance was identified using linear discriminant analysis effect size (LEfSe) with a linear discriminant analysis (LDA) score threshold > 4.

Genomic DNA was isolated from fecal samples with a Mag-Bind Stool DNA Kit (Omega Biotek, USA), and integrity was verified via agarose gel electrophoresis. The DNA was sheared to ~ 300 bp using a Covaris M220 ultrasonicator (Gene Company Limited, China) for library preparation, which was carried out with the NEXTFLEX Rapid DNA-Seq kit (Bio Scientific, USA). Finally, paired-end sequencing was conducted on an Illumina NovaSeq platform at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China). The analytical pipeline consistent with that used for 16S rRNA gene sequencing. Functional potentials were predicted with PICRUSt2 and annotated against the Kyoto Encyclopedia of Genes and Genomes (KEGG) database to identify differentially abundant pathways between different groups.

The SCFAs and Trp metabolites in fecal samples were quantified using precision-targeted metabolomics as described previously [30]. Targeted metabolomic analysis was conducted on an ultra-performance liquid chromatography-quadrupole-time of flight-mass spectrometry (UPLC-Q-TOF-MS) system (Agilent 1290 Infinity LC coupled to Agilent 6495 Triple Quadrupole MS; Agilent Technologies, USA). Separation was carried out on an ACQUITY UPLC HSS T3 column (2.1 × 100 mm, 1.8 µm; Waters) with a mobile phase of 0.1% formic acid in water (v/v) (A) and 0.1% formic acid in acetonitrile (v/v) (B). The gradient elution program was as follows: 0–2 min: 98% A, 2–10 min: 98%-65% A, 10–12 min: 65%-20% A, 12–14 min: 20%-2% A.

Statistical analyses were conducted with GraphPad Prism 8.0 (GraphPad, USA). Data are expressed as mean ± standard error of the mean (SEM). Group comparisons were made using a two-tailed unpaired t-test (two groups) or two-way analysis of variance (ANOVA) with Dunnett’s post hoc test (multiple groups). For 16S rRNA and metagenomic data, a two-tailed Wilcoxon rank-sum test was applied in R. A P-value < 0.05 was considered statistically significant.

Under optimized conditions, the chemical composition of DKT was comprehensively characterized. Data acquisition in both positive and negative ionization modes ensured broad metabolite detection (Supplementary Fig. S1A and SB). 74 constituents were identified via accurate mass, MS/MS fragmentation, retention characteristics, and comparison with reference standards or online databases [38, 39] (Supplementary File S1). The predominant compounds included saponins, gingerols, flavonoids, peppermint amides, and other substances. Six core compounds, including skimmianine (zanthoxylum), 6-gingerol, 6-shogaol (dried ginger rhizome), ginsenoside Rb₁, ginsenoside Re, and ginsenoside Rg₁ (ginseng), were identified through the comparative analysis of accurate molecular weight, retention time, and MS/MS spectra of reference standards and chromatographic peaks (Supplementary Fig. S1C). The corresponding chemical structures are provided in Supplementary Fig. S2.

To evaluate the therapeutic efficacy of DKT on AC, a mouse model was induced. DSS-treated mice exhibited marked weight loss and higher DAI scores, along with characteristic colitis symptoms, such as diarrhea and hematochezia, thus confirming successful induction of AC (Fig. 1B). DKT administration attenuated DSS-induced weight loss and DAI elevation in a dose-responsive manner, and the therapeutic potency of low-dose DKT was equivalent to that of SASP. As shown in Fig. 1C, mice with AC exhibited marked colon shortening, whereas DKT treatment significantly reduced the colon weight-to-length ratio. DKT also attenuated DSS-induced increase in MPO levels in colon tissues, indicating lower neutrophil infiltration (Fig. 1D). Additionally, DKT treatment significantly reduced TNF-α, IL-17A, IL-6, and IL-1β, and increased the IL-22 (Fig. 1E).

The intestinal mucosal barrier, which is primarily composed of epithelial cells and tight junctions, serves as the first line of defense against pathogenic invasion. The AC group showed significantly higher serum fluorescence intensity compared to the controls in the FITC-dextran permeability assay, confirming the intestinal barrier dysfunction. DKT administration significantly attenuated levels of FITC-dextran in serum compared to those of the AC group, demonstrating its protective effect on intestinal barrier integrity. (Fig. 1F). Consistently, DSS administration significantly downregulated Occludin and ZO-1, which were effectively restored by DKT treatment (Fig. 1G). Altogether, DKT alleviated disease symptoms, mitigated colonic inflammation, and restored intestinal barrier function in DSS-induced AC mice.

Given the crucial role of gut microbiota in intestinal homeostasis and overall health, the impact of DKT on microbial dysbiosis was evaluated via 16S rRNA sequencing. Analysis of microbial α-diversity indicated that DSS administration significantly reduced the gut microbial diversity, which was partially restored after DKT treatment (Fig. 2A). As shown in the Venn diagram in Fig. 2B, the distribution of microbial species followed distinct patterns, demonstrating both unique and shared OTUs among the three experimental groups. Furthermore, PCoA showed clear separation of gut microbiota across experimental groups, with the DKT-H group showing greater similarity to the control group (Fig. 2C). Microbial composition was further characterized at multiple taxonomic levels. The Firmicutes (Bacillota)/Bacteroidetes (F/B) ratio is a key indicator of intestinal homeostasis [40]. Consistent with clinical observations in UC patients, the AC group exhibited a reduced F/B ratio, which was restored to near normal levels following DKT treatment (Fig. 2D).

The predominant bacterial families in the control group were Lactobacillaceae, Bacillaceae, and Saccharimonadaceae. As shown in Fig. 2E, DKT administration effectively restored the DSS-elevated abundance of Erysipelotrichaceae and Streptococcaceae and restored those of Lactobacillaceae and Bacillaceae in the DSS-treated mice. DSS-treated mice exhibited decreased relative abundances of Lactobacillus and Bacillus, but an increase in Streptococcus. However, DKT treatment notably reversed these DSS-induced changes (Fig. 2F). LEfSe revealed discriminative taxa that were significantly enriched in the AC and DKT treatment groups (Fig. 2G). The predominant bacteria in the AC group belonged to the phylum Bacteroidetes (specifically Prevotellaceae UCG-001), while the DKT group was dominated by the phylum Firmicutes (primarily Lactobacillaceae and Lactobacillus). Taken together, DKT regulated the gut microbiota of mice and increased Lactobacillaceae and Lactobacillus.

Since short-term DSS administration cannot simulate the recurrent inflammation and tissue remodeling characteristic of UC, a CUC model was established through multiple cycles of DSS intervention to comprehensively assess the therapeutic potential of DKT. As shown in Fig. 3B, the controls exhibited a steady increase in weight over the experimental period. The CUC group mice exhibited three cycles of rapid weight loss during the disease induction phases, followed by gradual recovery during the remission periods. Nevertheless, the CUC group exhibited persistently lower body weight compared to controls. Although periodic weight fluctuations were observed in the DKT group, the DKT treatment significantly attenuated colitis-related weight loss. Additionally, mice with DSS-induced CUC displayed symptoms, including listlessness, diarrhea, and bloody stools, while the control group mice maintained normal activity without any pathological signs. The colitis symptoms progressively resolved following DSS withdrawal. The DAI scores showed similar trends in the DKT and CUC groups; the DKT treatment significantly lowered DSS-induced increases in DAI scores, ultimately reaching the levels of controls. The CUC group exhibited significant colon shortening relative to controls, which was attenuated by DKT (Fig. 3C and 3D). In addition, CUC also resulted in splenomegaly, as indicated by a marked elevation in the spleen index (spleen-to-body weight ratio). DKT intervention significantly reduced splenomegaly and normalized the spleen indices (Fig. 3C and 3D). In the control group, histopathological analysis revealed intact colonic mucosa without inflammatory infiltrates. In contrast, the CUC group exhibited severe architectural disruption with mucosal thinning, crypt destruction, goblet cell depletion, and extensive inflammatory infiltration. However, DKT treatment ameliorated these changes and significantly lowered the histological scores (Fig. 3E). Furthermore, the CUC group showed increased MPO activity and TNF-α expression and reduced IL-10 and IL-22. DKT administration effectively reversed these alterations (Fig. 3F). These findings indicated that the therapeutic potential of DKT against CUC might be driven by the modulation of inflammatory responses.

Mucins, highly glycosylated proteins secreted by colonic goblet cells, are critical for preserving intestinal barrier integrity and inhibiting bacterial translocation. PAS staining showed lower mucin expression in CUC mice compared to the controls, which was significantly restored to normal levels by DKT treatment (Fig. 4A). Furthermore, compared to the CUC group, DKT downregulated the Claudin-2 mRNA expression and significantly upregulated Occludin and ZO-1 mRNA expressions (Fig. 4B). Consistently, DSS-induced CUC exhibited increased Claudin-2 protein expression and reduced protein levels of Occludin and ZO-1, which were reversed by DKT treatment (Fig. 4C). CUC is characterized by impaired structural integrity of the intestinal mucosa, largely resulting from epithelial barrier damage. DKT facilitated intestinal repair in the CUC model through regulation of tight junction and mucin expression.

Next, it was hypothesized that DKT could modulate the gut microbiota CUC mice similar to that observed in the AC model. Metagenomic sequencing was used to test this hypothesis. α-Diversity analysis demonstrated DKT significantly counteracted the reduction in microbial biodiversity relative to the CUC group (Fig. 5A). The overall structural differences in microbial communities were assessed using PCoA. As shown in Fig. 5B, DKT group was closer to controls as compared to the CUC, indicating that DKT treatment partially restored gut microbiota to a state resembling that of the controls. Firmicutes, Bacteroidetes, and Actinomycetota were the predominant phyla. DSS intervention increased Bacteroidetes and reduced Firmicutes and Actinomycetota. However, DKT treatment partially reversed these changes and restored the F/B ratio (Fig. 5C).

At the family level, DSS administration significantly reduced Lactobacillaceae and increased Bacteroidaceae and Enterobacteriaceae. The DKT treatment reversed these dysbiosis trends (Fig. 5D). At the genus level, the CUC mice exhibited significantly decreased Ligilactobacillus and Lactobacillus and increased Bacteroides, Phocaeicola, and Escherichia (Fig. 5E). DKT treatment effectively restored these genera to near-baseline levels. Further analysis at the species level revealed that Ligilactobacillus murinus, Lactobacillus taiwanensis, and Lactobacillus johnsonii were downregulated in the CUC group, while Bacteroides acidifaciens, Bacteroidales bacterium, and E. coli were markedly upregulated (Fig. 5F). DKT intervention reduced the abundance of harmful species, thus demonstrating its ability to ameliorate dysbiosis of gut microbiota in CUC.

LEfSe identified discriminative taxa, revealing a significant increase in Lactobacillaceae following DKT treatment. Notably, genera such as Lactobacillus and Limosilactobacillus displayed elevated LDA scores following DKT treatment, implicating their involvement in the DKT's protective mechanisms against CUC (Fig. 6A and 6B). KEGG pathway analysis indicated that the Trp metabolism and janus kinase (JAK)-signal transducer and activator of transcription (STAT) signaling pathways might be involved in the therapeutic action of DKT (Fig. 6C). Spearman correlation analysis further established significant relationships between the shifts in the composition of gut microbiota and colitis-related parameters. Notably, the abundance of L. taiwanensis (upregulated by DKT) and E. coli (downregulated by DKT) correlated significantly with the major indicators of colitis (Fig. 6D). Collectively, these findings indicate beneficial effects of DKT against CUC were mediated via modulation of gut microbiota, particularly through the enrichment of L. taiwanensis.

Alterations in the gut microbiota frequently correlate with shifts in microbial metabolite profiles. To determine whether the therapeutic effects of DKT on CUC were mediated by gut bacterial metabolites, targeted metabolomic analysis was conducted on the fecal samples, with particular focus on Trp metabolites and SCFAs. The metabolic profiles of the different groups were analyzed using partial least squares-discriminant analysis (PLS-DA). As shown in Supplementary Fig. S3A, DKT treatment subtly shifted the overall metabolic composition but did not cause any valid alterations in most SCFAs. DKT increased hexanoic acid, isovaleric acid, and propionic acid; nevertheless, neither hexanoic acid nor isovaleric acid was known to alleviate colitis. Moreover, the total SCFA content, acetic acid, butyric acid, isobutyric acid, and pentanoic acid, remained unchanged (Supplementary Fig. S3B). This suggested that SCFAs were not the key mediators of the anti-inflammatory and therapeutic effects of DKT. The Trp metabolites involved in indole, kynurenine (Kyn), and 5-hydroxytryptamine (5-HT) pathways were also quantified. As shown in Fig. 7A, PLS-DA demonstrated clear separation among the groups, suggesting significant differences in Trp metabolite profiles. DKT administration markedly altered the levels of indole-related metabolites, while exerting minimal effects on the Kyn and 5-HT. Specifically, Trp levels were markedly lower in the CUC group. In addition, a notable reduction in indole and its derivatives, including indole-3-acrylic acid (IA), indole-3-propionic acid (IPA), indole-3-acetic acid (IAA), indole-3-carboxylic acid (ICA), and tryptamine were also observed. In contrast, DSS treatment elevated the indole-3-lactic acid (ILA) levels. DKT treatment increased the fecal levels of indole, IA, and ICA by almost two-fold compared to those in the CUC. Furthermore, IPA, IAA, and tryptamine levels increased, while that of ILA decreased following DKT intervention (Fig. 7B and 7C). Spearman correlation analysis also revealed significant associations between gut microbiota and Trp metabolites. L. murinus and L. taiwanensis correlated positively with Trp metabolites, particularly indole and its derivatives, while E. coli exhibited a strong negative correlation with 5-HT (Fig. 6D). Taken as a whole, these results demonstrated that the therapeutic efficacy of DKT were primarily driven by the microbial Trp/indole pathway, with IA and ICA as the potential key bioactive mediators.