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Advances and Applications of Bioengineering

Research Article       Open Access      Peer-Reviewed

Activation of the Nrf2 Signaling Pathway by a Ginseng-Salvia-Notoginseng Composite Alleviates Ulcerative Colitis via Restoring Gut Microbiota and Intestinal Barrier

Xinao Lyu1, Liurong Zhang1, Jia Si1, Shasha Dai1, Huaiyu Su1, Shuhuan Lyu1, Lin Chen1, Jianwei Sun1, Xiangqun Jin1* and Haiyan Li2*

1Department of Pharmacy, Jilin University, Changchun 130021, China
2Department of Pharmacy, Changchun University of Chinese Medicine, Changchun 130021, China

Author and article information

*Corresponding authors: Xiangqun Jin, Department of Pharmacy, Jilin University, Changchun 130021, China, E-mail: [email protected]

Haiyan Li, Department of Pharmacy, Changchun University of Chinese Medicine, Changchun 130021, China, E-mail: [email protected]
doi : 10.17352/aabe.000003
Received: 16 February, 2026 | Accepted: 19 February, 2026 | Published: 20 February, 2026
Keywords: Ulcerative colitis; Nrf2 signaling pathway; Intestinal barrier function; Microbiota dysbiosis; Tight junction proteins; Multi-target therapy

Cite this as

Lyu X, Zhang L, Si J, Dai S, Su H, Lyu S, et al. Activation of the Nrf2 Signaling Pathway by a Ginseng-Salvia-Notoginseng Composite Alleviates Ulcerative Colitis via Restoring Gut Microbiota and Intestinal Barrier. Adv Appl of Bioengine. 2026; 2(1): 004-017. Available from: 10.17352/aabe.000003

Copyright License

© 2026 Lyu X, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Current treatments for ulcerative colitis (UC) often fail to adequately address its multifactorial pathogenesis, involving oxidative stress, barrier dysfunction, and gut microbiota dysbiosis. This study evaluated the therapeutic potential and multi-targeting mechanism of a ginseng, salvia root, and notoginseng oral solution (GSNS) in a DSS-induced mouse colitis model. Based on HPLC-MS/MS technology, 24 major bioactive components were identified. Following the induction of UC with 3.5% dextran sulfate sodium (DSS) in C57BL/6J mice, the animals were treated with GSNS (40, 80, or 160 mg/kg/day) or 5-Amino Salicylic Acid (5-ASA). The therapeutic efficacy was assessed via disease activity, histopathological staining, cytokines, and oxidative stress analysis, and barrier integrity test. Combined data from Western blot, qPCR, immunohistochemistry, electron microscopy, and 16S rRNA sequencing indicate that the therapeutic effect of GSNS against colitis is attributable to its dual role in dampening pro-inflammatory cytokines (TNF-α, IL-6, IL-1β) and potentiating antioxidant defenses via the Nrf2/HO-1 signaling pathway. It also upregulated Occludin expression, repaired tight junctions, and beneficially reshaped the gut microbiota by increasing Prevotellaceae and suppressing Escherichia-Shigella. These findings demonstrated that GSNS exerts a multi-target effect against colitis by synergistically enhancing antioxidant defense, repairing the intestinal barrier, and modulating microbial ecology, supporting its potential as a promising natural compound-based candidate for UC treatment.

Indexing and Abstracting

Introduction

Ulcerative colitis (UC) is a chronic, relapsing inflammatory bowel disease. The core pathology of UC involves disruption to the epithelial barrier, leading to diffuse mucosal injury [1]. Its pathogenesis involves a vicious cycle comprising multiple components, such as oxidative stress, uncontrolled inflammatory responses, and intestinal dysbiosis.

[2-4]. Current therapeutic strategies primarily target specific inflammatory pathways but often fail to address underlying issues such as persistent barrier dysfunction, impaired endogenous antioxidant defences, and gut microbiota dysbiosis [5-7]. This can lead to incomplete remission, high relapse rates, and a suboptimal treatment response in some patients. Consequently, the development of multi-target therapeutic strategies that can intervene in multiple key pathological links of UC simultaneously has become urgent.

Natural products, with their multi-component nature, offer a promising avenue for intervening in this complex pathological network [8]. A classic formulation in traditional Chinese medicine, composed of ginseng (Panax ginseng), salvia root (Salvia miltiorrhiza), and notoginseng (Panax notoginseng), is renowned for its remarkable efficacy and holds an important position in both theoretical and clinical practice. Key bioactive compounds derived from these herbs, including ginsenosides, salvianolic acids, and notoginsenosides, have demonstrated anti-inflammatory, antioxidant, gut microbiota-modulating, and intestinal barrier-repairing properties [9-11].

While the individual pharmacology of ginseng, salvia root, and notoginseng has been investigated, their combined effects in UC remain unclear [12-15]. Current research has largely focused on single herbs or isolated compounds, lacking a systematic assessment of the overall therapeutic efficacy of the ginseng, salvia root, and notoginseng extract in UC [16-18]. Consequently, the material basis and integrated mechanisms underlying its potential multicomponent synergistic effects are still insufficiently clarified. Moreover, most existing mechanistic investigations are limited to single pathways (e.g., anti-inflammation) and fail to incorporate the interplay between key processes such as Nrf2-mediated antioxidant signaling, intestinal barrier repair, and gut microbiota modulation into a unified framework. A holistic, network-based understanding of the formula’s therapeutic actions is thus impeded by the current fragmented approach. At the microbiome level, current evidence is predominantly characterized by compositional descriptions, with a lack of functional validation linking specific microbial shifts, key taxa, or their dynamic interactions to therapeutic outcomes [19]. Therefore, the scientific rationale for using this traditional Chinese medicine (TCM) compound in UC remains incomplete, hindering both systematic formula optimization and the development of precise, mechanism-informed clinical applications.

This study developed the ginseng, salvia root, and notoginseng oral solution (GSNS) and evaluated its therapeutic potential against UC in a DSS-induced mouse model. The chemical profile of GSNS was characterized by LC-MS/MS. Therapeutic efficacy was assessed by monitoring body weight, calculating disease activity indices, measuring colon length, and performing histopathological assessment. To investigate the underlying mechanisms, the expression and localization of inflammatory cytokines, oxidative stress markers, key proteins/genes in the Nrf2 signaling pathway, and tight junction proteins were quantified using enzyme-linked immunosorbent assay (ELISA), Western blot, qPCR, immunohistochemistry (IHC), and immunofluorescence. In parallel, 16S rRNA gene sequencing was performed, combined with diversity analysis, linear discriminant analysis effect size (LEfSe), differential species screening, and correlation network analysis, to systematically elucidate the regulatory effects of GSNS on gut microbiota structure and microbial interaction networks. Collectively, these results demonstrate that GSNS alleviates UC through multi-target mechanisms involving the reduction of oxidative stress, repair of the intestinal barrier, and regulation of gut microbiota ecology.

Materials and methods

Primary chemical reagents

Dextran sulfate sodium (DSS; molecular weight: 40,000 Da, catalogue No. BD123894) was purchased from Bide Pharmatech Co., Ltd. (Beijing, China). Occludin antibody (1:500, BSM-61062R) was purchased from Bioss (Beijing, China). Antibodies against Nrf2/NFE2L2 (66504-1-Ig), HO-1/HMOX1 (66743-1-Ig), GAPDH (66004-1-Ig), and Lamin B1 (66095-1-Ig) were obtained from ProteinTech (Wuhan, China). ELISA kits for interleukin-6 (IL-6), interleukin-10 (IL-10), interleukin-1β (IL-1β), myeloperoxidase (MPO), tumour necrosis factor-α (TNF-α), malondialdehyde (MDA), glutathione (GSH), and superoxide dismutase (SOD) were purchased from FeiYa Biotechnology Co., Ltd. (Nanjing, China) and Multi Sciences (Hangzhou, China), respectively. TRIzol reagent was obtained from Invitrogen (Carlsbad, CA, USA). RIPA lysis buffer (containing PMSF; catalogue No. P0013B), phenylmethylsulfonyl fluoride (PMSF; catalogue No. ST505), and a bicinchoninic acid (BCA) protein assay kit (catalogue No. P0012) were purchased from Beyotime Biotechnology (Shanghai, China). A polyvinylidene fluoride (PVDF) membrane (catalogue No. IPVH00010) was obtained from Millipore (Burlington, MA, USA). The 16S rRNA gene (V4 region) Amplification and Library Preparation Kit (catalogue No. 12933ES96) was purchased from Yeasen Biotechnology Co., Ltd. (Shanghai, China). The following reagents and kits were purchased from Servicebio Biotechnology Co., Ltd. (Wuhan, China): Magnetic Bead-Based Bacterial Genomic DNA Extraction Kit, Universal Tissue Fixative, Optimal Cutting Temperature (OCT) Embedding Medium, Hematoxylin and Eosin (H&E) Staining Kit, RNA Extraction Reagent, SweScript All-in-One RT SuperMix, and 2×Universal Blue SYBR Green qPCR Master Mix. Sequencing was performed on the DNBSEQ-G99 platform by Shenzhen BGI Intelligent Manufacturing Technology Co., Ltd. (Shenzhen, China).

Preparation of ginseng, salvia root, and notoginseng oral liquid

The compound extract GSNS was prepared using a standardized reflux extraction protocol. Briefly, authenticated crude drugs of ginseng, salvia root, and notoginseng were mixed in a 1:1:1 weight ratio. The mixture underwent two rounds of reflux extraction with 50% ethanol solution (10: 1, v/w), each for 3 hours. The combined extracts were filtered, and the filtrate was concentrated under reduced pressure at 40 - 50°C using a rotary evaporator. The resulting concentrated liquid was then lyophilized to a constant weight, yielding the dry extract powder. The extraction yield was calculated accordingly. For in vivo administration, a precise weight of the lyophilized powder was reconstituted in sterile distilled water to the desired concentration. The solution was sterilized by filtration through a 0.22 µm membrane and aliquoted for storage at -20°C.

Chemical profiling of GSNS using UPLC-MS/MS

UPLC-MS/MS analysis was performed on a DioneUltiMate 3000 system coupled to a Thermo Q-Exactive Plus mass spectrometer to determine the chemical constituents of GSNS, according to a published method [20]. Chromatographic separation utilized an ACQUITY UPLC HSS T3 column (1502.1 mm, 1.8 µm). The mobile phase consisted of (A) deionised water containing 0.1% formic acid and (B) acetonitrile containing 0.1% formic acid. These were delivered in gradient elution mode as follows: 0 - 5 min: 5% B; 5 - 95 min: 5% to 95% B (linear gradient); 95 - 100 min: 95% B. Thereafter, the system was returned to the initial conditions (95% A, 5% B) within 0.1 min, after which it was equilibrated for 10 min. A constant flow rate of 0.3 mL/min was maintained throughout the run. Data acquisition and processing were carried out using Xcalibur and TraceFinder 5.1 software (Thermo Fisher Scientific, Waltham, MA, USA).

Animals and handling

Male C57BL/6J mice weighing 20 ± 2 g were obtained from Speifu (Beijing) Biotechnology Co., Ltd. (Changchun, China; licence no. SYXK (Ji) 2021-0003). After a three-day acclimatisation period under controlled conditions (25 ± 2℃, 60 ± 5% relative humidity, 12 h light/dark cycle), the mice were randomly divided into six groups (n = 6). The control group received normal drinking water. The model group received 3.5% (w/v) DSS in drinking water for 7 days. The positive control group received 3.5% DSS water plus 5-ASA (100 mg/kg/day) by oral gavage. Three treatment groups (GSNSL, GSNSM, GSNSH) received 3.5% DSS water plus GSNS at doses of 40, 80, and 160 mg/kg/day, respectively, via oral gavage. Drug administration (5-ASA and GSNS) was performed daily from day 4 to day 10. On day 11, all mice were euthanised. Peripheral blood was collected via orbital bleeding, and colon tissues as well as intestinal contents were immediately harvested for subsequent analysis (see experimental timeline in Figure 2). Animal experiments used six mice per group (n = 6) based on pilot study effect sizes for sufficient statistical power. For molecular analyses (Western blot, qPCR), three randomly selected samples per group (n = 3) served as biological replicates, sufficient to validate in vivo mechanisms. This design follows the Reduction principle of the 3R framework (Replacement, Reduction, Refinement), minimizing animal use while maintaining data reliability [21]. All assays included three technical replicates. All procedures were approved by the Animal Care and Use Committee of the School of Pharmacy, Jilin University (Approval No. 20250121) and conducted in accordance with relevant guidelines.

Mouse body weight, disease activity index, and colon length

Body weights were recorded for all mouse groups each day before treatment; fecal samples were simultaneously evaluated for consistency and signs of bleeding. The disease activity index (DAI) score provides a comprehensive reflection of disease severity in the UC model mice. The calculation formula is: DAI = (Body Weight Loss Score + Fecal Consistency Score + Blood in Feces Score) / 3 [22]. Photograph the colon and measure its length to assess the degree of inflammatory response.

Analysis of serum and colon cytokines and oxidative stress markers

Blood samples were processed by centrifugation at 4,000 rpm for 20 minutes at 4℃ to obtain the serum. Colon samples were homogenised in PBS and centrifuged at 13,000 rpm for 10 minutes to collect the supernatant. Commercial ELISA kits were used to quantify the levels of cytokines (TNF-α, IL-6, IL-10, and IL-1β) in both the serum and the colonic supernatant, and the levels of oxidative stress markers (MPO, MDA, SOD, and GSH) in the colonic supernatant, according to the manufacturers’ instructions.

Hematoxylin-eosin staining and immunohistochemical analysis of mouse colon tissue

Histopathological assessment was conducted based on H&E staining. After routine processing (fixation in 4% paraformaldehyde, paraffin embedding, and sectioning), tissue sections were scored for pathological changes using an established criterion [23]. To detect Nrf2 using IHC, the paraffin sections were subjected to antigen retrieval. Subsequently, endogenous peroxidase was quenched with 3% CH3OH-H2O2, and non-specific sites were blocked with 3% bovine serum albumin (BSA). The sections were then incubated with an anti-Nrf2 primary antibody overnight at 4℃ in a humidified chamber, followed by incubation with a horseradish peroxidase (HRP)-conjugated secondary antibody. Signal visualisation was achieved using 3,3’-diaminobenzidine (DAB) as the chromogen, and the development time was monitored under a microscope. Finally, the sections were counterstained with haematoxylin, dehydrated, cleared, and mounted. Protein expression of Nrf2 was quantified using the H-Score method.

The semi-quantitative scoring system evaluates both staining intensity and the proportion of positive cells. The staining intensity was graded on a scale of 0 to 3 (0, negative; 1, weak/pale yellow; 2, moderate/brownish yellow; 3, strong/dark brown). The H-Score was calculated using the formula: H-Score = ∑ (pii), where ‘i ‘ is the intensity score (0 - 3) and ‘pi’ is the percentage of cells stained at that intensity [24].

Immunofluorescence staining of tight junction proteins

For the localization of tight junction proteins, processed colon sections (from Section 2.7) were subjected to standard immunofluorescence staining. The sections were incubated overnight at 4°C with primary antibodies against ZO-1 and Occludin. After PBS washes, they were incubated with fluorochrome-conjugated secondary antibodies for 1 h at 37°C and then counterstained with DAPI. High-resolution images were acquired using a Leica TCS STELLARIS 5 confocal microscope to assess protein Distribution.

Ultrastructural analysis of mouse colon via transmission electron microscopy

Following initial fixation in 4% glutaraldehyde, the colon tissues were prepared for transmission electron microscopy (TEM). This involved sectioning, dehydration, embedding, polymerisation, and ultrathin sectioning (4 µm). The sections were then post-stained with uranyl acetate and lead citrate, after which they were observed under a Hitachi HT7700 TEM (Japan).

RNA extraction and real-time fluorescent quantitative PCR analysis

ColonTotal RNA was extracted from colon tissue using TRIzol reagent and precipitated with isopropanol. Total RNA was first quantified for concentration and purity on a NanoDrop 2000 Spectrophotometer (Thermo Fisher Scientific, USA). Subsequently, 1 µg of RNA was reverse-transcribed into cDNA using the SweScript All-in-One SuperMix for qPCR Kit (Servicebio, China) following the kit protocol. Quantitative PCR was then carried out on a StepOnePlusTM System (Applied Biosystems, USA) with Universal Blue SYBR Green qPCR Master Mix (Servicebio, China). After an initial 30 s step at 95℃, samples underwent 40 cycles of denaturation (95℃, 15 s) and annealing/extension (60℃, 30 s). Specificity was assessed by melting curve analysis. Gene expression was quantified relative to the geometric mean of Ywhaz and Hprt1 using the 2-∆∆Ct method. For miRNA analysis, miR-146a-5p was normalized against U6 as the reference gene. Primer sequences are listed in Table 1.

Table 1: Primer Sequences Used for Gene Expression Analysis by RT-qPCR.
Gene   Primer Sequences (5′to 3′) Fragment Size (bp) Gene Accession Number
KEAP1 Forward Reverse GAGATATGAGCCAGAGCGGGA AACTGGTCCTGCCCATCGTAG 270 NM_001110305.1
GCLC Forward Reverse CTGTAGATGATAGAACACGGGAGG GAGATGAGCAACGTGCTGTGC 215 NM_010295.2
Srxn1 Forward Reverse GTACCAATCGCCGTGCTCAT GAGCTTGGCAGGAATGGTCT 222 NM_029688.6
Ywhaz Forward Reverse TTGTAGGAGCCCGTAGGTCATC CAGCAACCTCGGCCAAGTAA 249 NM_001253805.1
Hprt1 Forward Reverse TCATGGACTGATTATGGACAGGACT GCTTTAATGTAATCCAGCAGGTCAG 138 NM_013556.2
miR-146a-5p Forward CTCAACTGGTGTCGTGGAGTCGGCAATTCAG TTGAG AACCCATG 66 MIMAT0000158
U6 Reverse Forward Reverse ACACTCCAGCTGGGTGAGAACTGAATTCCA CTCGCTTCGGCAGCACA AACGCTTCACGAATTTGCGT 94 NR_004394.2

Protein expression analysis of relevant signaling pathways (Western Blot)

Total protein was extracted from colon tissues with RIPA lysis buffer supplemented with PMSF, and concentrations were quantified using a BCA assay kit. Equal protein aliquots were then separated by SDS-PAGE and electrophoretically transferred onto PVDF membranes. Following blocking, the membranes were probed overnight at 4℃ with primary antibodies against Occludin, Nrf2, HO-1, Lamin B1, and GAPDH. GAPDH and Lamin B1 served as loading controls for cytoplasmic and nuclear proteins, respectively. After washing, the blots were incubated with horseradish peroxidase (HRP)- conjugated secondary antibodies for 1 h at room temperature. Band detection was performed with a JUNYI chemiluminescent imager. Quantitative analysis was carried out by measuring the optical density of each band using Image J software (NIH, Version 1.8).

Microbial community analysis based on the 16S rRNA Gene

The resulting amplicons were purified, pooled in equimolar amounts, and prepared for sequencing library construction. Sequencing was performed on the DNBSEQ-G99 platform (2 00 bp paired-end), yielding approximately 50,000 raw reads per sample. Data processing was conducted within the QIIME2 (v202.5) workflow. Processing of the raw 16S rRNA sequencing data involved demultiplexing, quality filtering, merging, and denoising using DADA2, followed by clustering into amplicon sequence variants (ASVs). Taxonomic annotations for the ASVs were derived from the SILVA 138 database.

Subsequent analyses included α-diversity metrics (Chao1, Simpson, Shannon, richness, Pielou, and observed ASVs), a β-diversity analysis via PCoA based on Bray-Curtis and Jaccard distances, an examination of ASV sharing using Venn diagrams, and a profiling of community composition at phylum, genus, and species levels, supplemented by a phylogenetic tree. LEfSe was applied to identify key differential microbial features (LDA score > 3.5), listing the top 30 most significant taxa. Finally, a species abundance-based correlation network was constructed. This integrated analysis provided a systematic characterisation of DSS-induced colitis and the impact of GSNS intervention on the structure of the murine gut microbiota.

Statistical Analysis

Statistical analysis was performed using GraphPad Prism 10.0 (GraphPad Software, USA) and SPSS Statistics 22.0 (lBM, Armonk, NY, USA). All data are presented as mean ± standard error of the mean (SEM) from at least three independent experiments. For comparisons among multiple groups, one-way analysis of variance (ANOVA) followed by Tukey’s post-hoc test was conducted using SPSS. Statistical significance was set at p<0.05, and significance levels are indicated as follows: *p < 0.05, **p < 0.01, ***p < 0.001.

Results

LC-MS/MS-Based Identification of Bioactive Constituents in GSNS

The chemical profile of GSNS was established by LC-MS/MS analysis. A total of 25 major bioactive components were identified by comparing retention times and mass spectra with authenticated reference standards (see the total ion chromatogram in Figure 1). These components included various ginsenosides (e.g. 20(R)-ginsenoside Rg2, ginsenoside Rb1 and Rg1) [25-27], notoginsenosides (e.g. notoginsenosides R1) and Salvianolic acids (e.g., salvianolic acid B) [28,29]. Identification criteria were set at a mass error tolerance of <3 ppm and an identification score of >80 [30]. Detailed data for each compound are summarised in Table 2, thereby elucidating the material basis underlying the pharmacological efficacy of GSNS (Figure 1).

Table 2: Chemical compositions of GSNS
NO Name Formula Mass(Da) Measured m/z Error (ppm) Rt (min) Score Polarity Mode
1 20(S)-Ginsenoside Ck C36H62O8 644.42394 645.43122 2.5 73.558 80.1 Positive
2 Apigenin-7-O-β-D-glucoside C21H20O10 432.10527 433.11255 0.8 38.479 85.2 Positive
3 Cimifugin C15H10O4 306.11 307.11728 0.65 58.765 83.4 Positive
4 Cryptotanshinone C16H18O6 296.14109 297.14837 1.1 34.799 90.7 Positive
5 Ginsenoside Rk1 C19H20O3 766.48583 767.49311 0.52 70.74 88.8 Positive
6 Pseudoginsenoside F11 C42H70O12 800.49144 801.49872 1.17 71.467 81.2 Positive
7 Tanshinone IIA C42H72O14 294.12515 295.13243 0.96 58.234 90.9 Positive
8 20(R)-Ginsenoside Rg2 C42H72O13 784.49824 785.50552 1.2 61.71 84 Negative
9 20(R)-Notoginsenoside R2 C41H70O13 770.48215 771.48943 0.65 60.069 81.1 Negative
10 Chikusetsu saponin IVa C42H66O14 1588.89248 1589.89976 1 72.926 87.4 Negative
11 Cynaroside C21H20O11 448.09996 449.10724 1.3 39.605 80.6 Negative
12 Ginsenoside F1 C36H62O9 684.44514 685.45242 2.9 65.117 85.1 Negative
13 Ginsenoside F2 C42H72O13 830.50392 831.5112 2.8 75.861 87 Negative
14 Ginsenoside Rb1 C54H92O23 2217.20669 2218.21397 1.1 68.951 80.6 Negative
15 Ginsenoside Rb2 C36H90O22 2157.18472 2158.192 2.5 69.6 80 Negative
16 Ginsenoside Rc C53H90O22 1124.59903 1125.60631 2.4 71.066 81.9 Negative
17 Ginsenoside Rd C48H82O18 1893.10098 1894.10826 1.6 73.504 82.4 Negative
18 Ginsenoside Re C48H82O18 992.5561 993.56339 1.4 50.336 89.2 Negative
19 Ginsenoside Rf C42H72O14 800.49283 801.50011 0.78 59.247 83.2 Negative
20 Ginsenoside Rg1 C42H72O14 846.49891 847.50619 1.5 63.744 81.3 Negative
21 Ginsenoside Rg2 C42H72O13 830.50435 831.51163 1.56 57.455 80.9 Negative
22 Ginsenoside Rg3 C42H72O13 784.4987 785.50598 1.78 75.298 86.7 Negative
23 Ginsenoside Ro C48H76O19 1912.99893 1914.00621 1.02 69.874 80.4 Negative
24 Notoginsenoside Fe C47H80O17 962.54677 963.55405 2.52 78.006 81 Negative
25 Notoginsenoside R1 C47H80O18 1865.07046 1866.07774 1.6 49.023 80.6 Negative
Figure 1: Total ion chromatography (TIC) of the GSNS extract. (A) Profile obtained in positive ion mode. (B) Profile obtained in negative ion mode.

Impact of GSNS on DAI and Associated Metrics

The experimental design and treatment timeline are summarized in Figure 2A. As shown in Figure 2B, gross examination of colon tissues revealed marked shortening and atrophy in the model group compared to the control. Quantitative measurement confirmed this observation, indicating that colon length in the model group was significantly reduced (p < 0.001, Figure 2C). Regarding dynamic disease progression, control mice exhibited steady weight gain throughout the experiment, while model group mice showed progressive weight loss from day 4 onward (Figure 2D). Concordantly, the DAI remained low in controls but rose sharply in the model group (Figure 2E). Intervention with GSNS dose-dependently alleviated DSS-induced weight loss (P < 0.05, Figure 2D) and significantly reduced DAI scores in the high-dose group (P < 0.05, Figure 2E), with efficacy comparable to 5-ASA (P > 0.05). Furthermore, GSNSM and GSNSH treatments significantly reversed colon shortening (P < 0.001, Figure 2C), demonstrating a dose-dependent protective effect on colonic structure.

Figure 2: Therapeutic effects of GSNS on DSS-induced UC in mice. (A) Schematic diagram of the experimental design and treatment timeline. (B) Representative macroscopic photographs of colon tissues from each group. (C) Measurement results of colon length. (D) Body weight change curves during the treatment period. (E) DAI scores. Data are expressed as the mean ± SEM (n = 6). Statistical significance: *p < 0.05, ***p < 0.001 compared with the Model group.

Modulation of inflammatory and oxidative stress biomarkers by GSNS in Serum and Colon

We confirmed the successful induction of the UC model based on a significant rise in pivotal pro-inflammatory cytokines [31]. As illustrated in Figures 3A - D, DSS induction resulted in a substantial increase (p < 0.001) in TNF-α, IL-6, and IL-1β levels in both serum and colon tissue. It also altered IL-10 expression, an anti-inflammatory cytokine. Administration of GSNS and 5-ASA significantly reversed these aberrant cytokine profiles (p < 0.05, p < 0.01, or p < 0.001). The suppressive effect of GSNS on pro-inflammatory cytokines was dose-dependent, with the high-dose group exhibiting efficacy comparable to the 5-ASA group. Furthermore, data on colonic oxidative stress markers (Figures 3E - H) showed that GSNS reduced MPO activity and MDA content in a dose-dependent manner, while enhancing SOD activity and GSH levels. This antioxidant effect was most pronounced at the GSNSH, equivalent to that achieved with 5-ASA treatment.

Figure 3: Modulation of Inflammatory and Oxidative Stress Profiles by GSNS in Mice with UC.(A - D) Panels show GSNS effects on TNF-α, IL-6, IL-10, and IL-1β levels in both colon tissue and serum (n = 6). (E - H) Panels show GSNS effects on serum markers of oxidative stress: MPO, SOD, MDA, and GSH (n = 6). Statistical significance relative to the Model group is indicated: *p < 0.05, **p < 0.01, ***p < 0.001.

Histopathology of colon tissue and immunohistochemical analysis of Nrf2 Protein Expression

Colon tissue H&E staining results and pathological scores are shown in Figure 4A and C. The control group displayed preserved colonic architecture, characterized by an intact mucosal layer and regularly arranged glands. Inflammatory cells were only sporadically present in the lamina propria. In contrast, the model group displayed typical pathological features of severe UC: extensive mucosal epithelial defects, substantial depletion of goblet cells, destruction and loss of crypt architecture, severe submucosal oedema, and transmural infiltration by a large number of inflammatory cells (P < 0.001 vs. control group) [32]. GSNS treatment improved these pathological injuries in a dose-dependent manner. Compared with the model group, the GSNSM and GSNSH groups showed significantly reduced inflammatory infiltration and improved mucosal architecture (p < 0.001). Notably, the overall histopathological score in the GSNSH group was not significantly different from that in the 5-ASA group (p > 0.05), indicating a similar degree of improvement.

Figure 4: Histopathological evaluation and Nrf2 expression in colonic tissues of DSS-induced colitis mice treated with GSNS. (A) Representative H&E-stained sections of colon tissues (scale bar, 200 µm). (B) Representative immunohistochemical staining images showing Nrf2 expression in colon tissues (scale bar, 100 µm). (C) Histopathological injury scores. (D) Immunohistochemical scores for Nrf2 expression. (E) Quantitative analysis of the Nrf2-positive area ratio. (F) Quantitative analysis of the Nrf2-positive area density. *p < 0.05, **p < 0.01, ***p < 0.001 compared with the model group. The results are expressed as mean ± SEM.

The IHC results presented in Figure 4B and D - F demonstrate that, compared with the control group, the DSS model group showed significantly reduced positive area ratio, areal density, and nuclear positive expression intensity (H-Score) of the Nrf2 protein in colon tissue (p < 0.001 for each). The decrease in the nuclear H-Score, in particular, indicated impaired nuclear translocation of Nrf2. Following GSNS intervention, the positive area ratio, areal density, and nuclear H-Score of Nrf2 increased in a dose-dependent manner in the GSNSM and GSNSH groups. The extent of recovery in the GSNSH group was equivalent to that in the 5-ASA group, with no statistically significant difference [33-35]. These results confirm, at the tissue level, that GSNS can effectively promote the expression and nuclear translocation of Nrf2 in colon tissue, thereby activating the Nrf2 signalling pathway.

Immunofluorescence analysis of desmoglein in the colon

Figure 5A presents representative immunofluorescence images depicting the localization of ZO-1 and Occludin [36]. In the control group, both proteins exhibited continuous, distinct, linear distribution along the colonic epithelial cell membrane. In the DSS model group, this linear fluorescence signal was significantly attenuated and interrupted, indicating severe disruption of tight junction structures. GSNS treatment restored the continuous membrane localization of ZO-1 and Occludin in a dose-dependent manner, with gradual improvement in fluorescence signal intensity and continuity. In the GSNSH group, the distribution patterns of both proteins recovered to a state similar to that of the 5-ASA group, visually confirming GSNS’s effective repair of the intestinal physical barrier.

Figure 5: Effects of GSNS on colonic epithelial barrier integrity. (A) Localization of the tight junction proteins ZO-1 (green) and Occludin (red) in colon tissues across the six experimental groups is shown in representative immunofluorescence images. Nuclei are counterstained with DAPI (blue). (B) Representative TEM images depicting the ultrastructure of colonic epithelial tight junctions.

Transmission electron microscopy analysis of the ultrastructure of the colon epithelium

Representative transmission electron micrographs of colonic tissue are shown in Figure 5B. Examination by TEM revealed that control intestinal epithelial cells were characterized by dense, orderly microvilli, intact tight and gap junctions, and normal organelle structure. The DSS model group demonstrated severe ultrastructural damage: sparse or shed microvilli, widened intercellular spaces, blurred or absent tight junctions, and swollen, vacuolated mitochondria [37]. Following GSNS treatment, epithelial ultrastructure exhibited dose-dependent repair. In the GSNSH group, intestinal epithelial microvillus density, cell junction integrity, and organelle status all approached normal levels, comparable to the 5-ASA group.

GSNS enhances antioxidant and barrier functions at the genetic and protein levels

Western blot analysis results for protein expression are presented in Figure 6A, and corroborate the corresponding gene-level changes. A marked reduction was observed in the expression of Occludin, Nrf2, and its downstream effector HO-1 in the model group [38]. Following GSNS treatment, the protein expression levels of all three targets were significantly increased. Furthermore, the band intensity analysis histograms in Figure 6B - D revealed significant differences between the DSS model group and both the control group and the GSNSH group (p < 0.001). The RT-qPCR results shown in Figure 6E - H indicated that DSS-induced colitis significantly upregulated Keap1 mRNA and miR-146a-5p expression in colon tissue (p < 0.001), while suppressing the expression of the antioxidant gene GCLC and the transcription factor SXRN1. GSNS intervention reversed these abnormal expressions in a dose-dependent manner. In summary, this study demonstrates, at both transcriptional and translational levels, that GSNS alleviates colitis by inhibiting Keap1, promoting Nrf2 nuclear translocation, and subsequently upregulating downstream antioxidant protein HO-1 and barrier protein Occludin.

Figure 6: GSNS alleviated colitis and modulated the expression of associated proteins and genes in DSS-induced UC mice. (A) Representative protein bands of nuclear Nrf2, HO-1, and Occludin (n = 3). (B - D) Histograms depicting the band intensity analysis of nuclear Nrf2, HO-1, and Occludin. (E - G) Expression levels of mRNA genes SRXN1, Keap1, and GCLC in each group. (H) Expression level of the miRNA gene miR-146a-5p in each group. *p < 0.05, **p < 0.01, *** p < 0.001 versus the Model group. Significant differences (p < 0.001) were observed in the GSNSH treatment group compared to the Model group. Data are expressed as mean ± SEM (n = 3).

Furthermore, its regulation of relevant miRNAs, such as miR-146a-5p, highlights its multi-level, synergistic mechanism of action.

Analysis of gut microbiota changes following GSNS Treatment

The effect of GSNS on the gut microbiota in DSS-colitis mice was examined by 16S rRNA gene sequencing of cecal contents; a Venn diagram was generated to visualize OTU overlap, showing common and group-specific microbial features. The Venn diagram analysis revealed the compositional characteristics of OTU distribution across groups (Figure 7A). The proportions of unique OTUs in the control, model, and GSNSH groups were 20.3%, 11.8%, and 7.19%, respectively, indicating that each group harbored a certain proportion of unique microbial taxa. Intergroup comparisons revealed the lowest OTU overlap between the control and model groups (2.61%), indicating that DSS modelling significantly altered the fundamental composition of the gut microbiota. The GSNSH group showed 7.84% OTU overlap with the control group and 10.5% with the model group, suggesting that the microbiota structure after GSNS intervention retained features characteristic of both normal and diseased states. Furthermore, the OTUs shared among the three groups accounted for the highest proportion (39.9%), indicating a core microbiota that remains relatively stable under experimental conditions. These findings demonstrate that DSS intervention significantly alters microbial composition, while GSNS treatment partially restores structural features resembling those of normal microbiota. Assessment of microbial community structure differences between groups via beta diversity analysis revealed significant segregation in Bray-Curtis and Jaccard distance principal coordinate analysis (Figure 7B - C) [39,40]. Samples from the GSNS intervention group exhibited distribution patterns closer to the normal control group. Further assessment of intra-group microbial diversity was performed via alpha diversity analysis using multiple indices (Chao1, Shannon, Simpson, richness, and Pielou’s evenness; Figure 7D - H). The results consistently showed that DSS modeling significantly reduced both microbial richness and evenness in the gut. In contrast, GSNS treatment restored these diversity metrics in a dose-dependent manner, with the most pronounced recovery observed in the GSNSH group. At the phylum level, DSS induction led to a decreased relative abundance of Firmicutes and an increase in Bacteroidetes, a trend that was reversed upon GSNS treatment. This community structure analysis across phylum, family, and genus levels is presented in bar charts (Figure 7I - K), where each bar represents one sample, colors denote different taxa, and the vertical axis shows relative abundance.

Figure 7: Analysis of intestinal contents via 16S rRNA gene sequencing reveals the modulatory effect of GSNS on DSS-induced microbiota dysbiosis. (A) Venn diagram of group-specific and shared ASVs; (B, C) PCoA based on Bray-Curtis and Jaccard distances. Alpha diversity indices: (D) Chao1, (E) Simpson, (F) Shannon, (G) Richness, and (H) Pielou’s evenness. Microbial community composition at the (I) phylum, (J) family, and (K) genus levels. (L) Histogram of LDA scores representing significantly discriminant taxa across groups. (M) Cladogram generated by LEfSe analysis illustrating the phylogenetic distribution of discriminant taxa. (N) Spearman correlation-based network analysis of microbial interactions. The results are expressed as mean ± SEM (n = 6).

LEfSe was employed to identify species with significant intergroup differences (LDA score > 3.5) [41], with the results visualized in Figure 7L, M. Across the four groups at the phylum and genus levels, a total of 30 discriminant taxonomic groups were identified: 18 in the control group, 7 in the model group, and 5 in the GSNSH group. Key taxonomic units with significantly different abundances in the control group gut microbiota included: Muribaculaceae, Oscillospirales, Oscillospiraceae, Ruminococcaceae, Ruminococcus, Oscillibacter, Muribaculum, Colidextribacter, the [Eubacterium] coprostanoligenes group (at both family and genus levels), and the genus Roseburia. Key taxonomic units significantly enriched in the gut microbiota of the model group included: the phylum Proteobacteria, Gammaproteobacteria, Bacteroidaceae, Bacteroides, Enterobacterales, Enterobacteriaceae, and Escherichia-Shigella. Key taxonomic units significantly enriched in the GSNSH group gut microbiota were: Prevotellaceae, Prevotellaceae_UCG-001, and Alphaproteobacteria. The enrichment of these groups may reflect the specific regulatory effects of GSNS intervention on microbial community structure and is associated with improvements in intestinal function.

Furthermore, Spearman correlation network analysis revealed alterations in microbial interactions. Results showed that in the model group, gut microbiota exhibited a disordered interaction pattern centered on inflammation-associated groups such as Proteobacteria. Following GSNS intervention, microbial network structure underwent significant remodeling: not only was positive synergy enhanced among beneficial groups like Lactobacillus and Dubosella, but their associations with opportunistic pathogens such as Enterobacteriaceae were also weakened. Concurrently, the interaction patterns of groups labeled ”positively correlated” in Figure 7 - N, such as the phylum Cyanobacteria, became more stable. This further enhanced overall network complexity and structural stability. These findings indicate that GSNS not only restores gut microbiota balance at the diversity and community structure levels but also enhances ecological network stability by reconfiguring beneficial microbial collaborations. This systemic approach supports the improvement of the pathological state of colitis.

Discussion

A DSS-induced mouse model of UC was employed to evaluate the therapeutic potential and mechanistic basis of the GSNS. Integrated pharmacodynamic, molecular, and microbiome analyses demonstrate that GSNS significantly alleviates disease severity. Its beneficial actions appear to be mediated through a multi-targeted mechanism involving suppression of systemic and local inflammation, activation of the Nrf2/HO-1 pathway to mitigate oxidative stress, enhancement of intestinal barrier integrity, and restoration of gut microbiota homeostasis. These findings collectively support that GSNS exerts its protective effect via a coordinated modulation of the inflammation, oxidative stress, barrier, and microbiota axis.

In terms of anti-inflammatory and antioxidant effects, the pharmacodynamic findings of this study corroborate the mechanisms of action reported in the literature for the active components of individual herbs [16-18]. As shown in Figures 2 - 4, GSNS intervention dose dependently improved DSS-induced weight loss, colon length, and alleviated histopathological damage, while significantly reducing levels of pro-inflammatory factors (TNF-α, IL-6, and IL-1β). These effects align with established reports that ginsenosides, danenol, and notoginsenosides suppress inflammation by modulating the NF-κB pathway [42-44]. Crucially, immunohistochemical and molecular biological analyses further revealed GSNS’s direct antioxidant mechanism: it significantly promoted Nrf2 protein expression and nuclear translocation in colonic tissue (Figure 4) while upregulating the downstream antioxidant protein HO-1. This in situ evidence confirms that GSNS effectively retains and integrates the core activity of its constituent herbs, bolstering cellular antioxidant defenses via activation of the Nrf2/HO-1 signaling axis [45,46].

This research demonstrates that GSNS, particularly at a GSNSH, achieved comparable improvement levels to the 5-ASA group in key parameters, including DAI, colon length restoration, and histopathological score. The comprehensive restorative effect observed in the whole animal model suggests potential synergistic interactions among the multiple components within this compound formulation [47-49]. The enhanced overall efficacy is likely due to the distinct active constituents of ginseng, salvia, and notoginseng acting on interrelated pathological pathways, such as inflammation, oxidative stress, and barrier repair, which ultimately converge to form a more robust, multi-target therapeutic network [50-52]. This amplifies the contributions of individual herbs and exemplifies the holistic regulatory characteristics of traditional Chinese medicine formulas.

At the molecular level, this study further revealed the regulatory effect of GSNS on the Nrf2 signaling pathway. Enhanced nuclear translocation of Nrf2 was observed following GSNS treatment, along with upregulated expression of its downstream effector HO-1 and the tight junction protein Occludin in colon tissues, as determined by Western blot. These changes were consistent with transcriptional alterations: RT-qPCR results confirmed that GSNS downregulated Keap1 mRNA expression while upregulating antioxidant genes GCLC and Srxn1 [53-55]. Furthermore, GSNS restored the abnormally elevated level of miR-146a-5p, a miRNA involved in inflammatory feedback regulation, in DSS-induced mice to near-normal levels [56]. These data suggest that GSNS sustains activation of the Nrf2/HO-1 antioxidant axis by inhibiting Keap1 and may further facilitate inflammation resolution by regulating miR-146a-5p. Notably, the activation of antioxidant signaling and the enhancement of epithelial barrier function exhibited synchronous and dose-dependent responses, indicating that GSNS coordinates key pathways such as Nrf2 to synergistically restore intracellular redox balance and physical barrier integrity.

To elucidate the regulatory effects of GSNS on gut microbiota, 16S rRNA gene sequencing was performed in DSS-induced UC mice [57,58]. Venn analysis indicated a marked alteration in microbial composition following DSS induction, with only 2.61% of OTUs shared between the control and model groups. After GSNS intervention, the overlap with the control group increased to 7.84%, suggesting a partial restoration of microbial structure. Alpha diversity indices, including Chao1 and Shannon, demonstrated that GSNS dose-dependently recovered the DSS-induced reduction in microbial richness and evenness. Beta diversity analysis further supported that GSNS treatment shifted the microbial community closer to that of the control group, as measured by Bray-Curtis and Jaccard distances. At the phylum level, GSNS significantly mitigated the DSS-induced dysbiosis, particularly by restoring the Firmicutes/Bacteroidetes ratio. LEfSe analysis revealed that GSNS downregulated pro-inflammatory taxa enriched in the model group, such as Proteobacteria, Enterobacteriaceae, and Escherichia-Shigella, while promoting beneficial genera including Prevotellaceae. Importantly, Spearman correlation network analysis showed that GSNS remodeled microbial interactions: the Proteobacteria-centered network observed in the model group was replaced, positive correlations among beneficial bacteria, such as Lactobacillus, were strengthened, and overall network complexity and stability were enhanced. In summary, GSNS not only rectifies compositional imbalances in the gut microbiota but also fosters a healthier ecological network, highlighting its role in restoring intestinal microenvironment homeostasis and showing its therapeutic potential in UC.

The findings of this study demonstrate that GSNS alleviates colitis by synergistically activating the Nrf2/HO-1 antioxidant pathway, repairing epithelial tight junctions, and reshaping the gut microbiota. This provides an integrated therapeutic model with a clear multi-target mechanism for complex diseases such as UC, which are characterized by a vicious cycle of oxidative stress, barrier disruption, and dysbiosis. [59-61]. The mode of action of GSNS suggests that its components may act synergistically or through additive effects at the host-microbiota interface to restore intestinal homeostasis more effectively.

However, as a preclinical study, translation to human applications requires further validation [62]. The optimal dosage, long-term safety, and pharmacokinetic profile of GSNS in humans remain to be determined. Moreover, while synchronous improvements across pathways were observed, their temporal and causal relationships are not fully resolved. Future studies are needed to distinguish whether microbiota alterations are primary or secondary to the therapeutic effects of GSNS. Approaches such as using germ-free animals, performing fecal transplants, or isolating specific constituents could help clarify these mechanistic nuances. In addition, the specific chemical constituents responsible for the antioxidant, anti-inflammatory, and microbiota-modulating effects of GSNS need to be identified through compound isolation and reconstitution experiments [63]. Current analyses based on 16S rRNA sequencing primarily provide information on microbial community structure. A multi-omics approach encompassing metagenomics, metabolomics, and transcriptomics is warranted to delineate the specific interactions among microbial genes, metabolites, and host pathways, and to fully decipher the comprehensive regulatory network orchestrated by GSNS [64].

In summary, this work systematically delineates the multi-target, multi-dimensional action framework of GSNS in UC, offering empirical support for the “multi-component-multi-target-multi-pathway” paradigm of herbal formulations in treating complex diseases. It lays a foundation for developing innovative strategies aimed at holistically restoring intestinal homeostasis. Future efforts should focus on identifying active components, elucidating mechanistic causality, and advancing clinical translation to provide UC patients with a potential therapy possessing systemic regulatory benefits.

Conclusions

In conclusion, this study demonstrates that the GSNS alleviates UC through a multi-target mechanism. GSNS exerts its effects by activating the Nrf2 signaling pathway to combat oxidative stress and inflammation, restoring intestinal barrier integrity via Occludin upregulation and preservation of tight junction ultrastructure (as confirmed by TEM), and modulating gut microbiota homeostasis. Collectively, the therapeutic outcome arises from the synergistic regulation of interconnected antioxidant, anti-inflammatory, barrier-repair, and microbial-modulating pathways. These findings provide modern pharmacological validation for the application of this traditional Chinese medicine formulation in UC management, highlighting activation of the Nrf2 signaling pathway as a central mechanism underlying its multi-target efficacy.

Author contributions

Software, X.L. (Xinao Lyu), L.Z., S.D., and S.L.; Formal analysis, X.L. (Xinao Lyu), H.S., and L.C.; Investigation, X.L. (Xinao Lyu), S.D., and J.S.; Data curation, X.L. (Xinao Lyu) and L.Z. (Liurong Zhang); Writing—original draft, X.L. (Xinao Lyu) and L.Z.; Writing—review & editing, H.L.; Funding acquisition, X.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by grants from the Jilin Provincial Department of Education Scientific Research Project. Development Plan Project: JJKH20250214CY.

Institutional review board statement

This study was approved by the Institutional Animal Care and Use Committee of Jilin University School of Pharmaceutical Science (No. 20250121 and Approval Date: 22 August 2025).

Data availability statement

The original contributions presented in this study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding authors.

Disclaimer/Publisher’s Note

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