MSC-exosomes pretreated by Danshensu extracts pretreating to target the hsa-miR-27a-5p and STAT3-SHANK2 to enhanced antifibrotic therapy

Abstract

Background

Peritoneal fibrosis (PF) is a serious complication commonly associated with prolonged peritoneal dialysis. Mesenchymal stem cells (MSCs) and their exosomes (Exo) have shown significant therapeutic promise in treating fibrotic conditions. Danshensu (DSS), a bioactive compound from the traditional Chinese herb Danshen reverses fibrosis. This study aims to investigate a novel strategy to enhance the therapeutic efficacy against PF by DSS preconditioning MSCs-derived exosomes (DSS-Exo).

Methods

The in vitro studies included the effects of DSS duration on MSCs, and the characterization of DSS-Exo and Exo, followed by the assessment of RNA and protein expression levels of peritoneal fibrosis markers and inflammatory cytokines levels after treating human peritoneal mesothelial (HMrSV5) cells. In vivo experiments were conducted on a PF mouse model to observe cell morphology, collagen deposition, fibrosis localization, and to evaluate peritoneal functions such as filtration rate, urea nitrogen clearance, peritoneal thickness, and protein leakage. Mechanistic insights were gained through the analysis of the STAT3/HIF-1α/VEGF signaling pathway, tissue dual-fluorescence localization,chromatin immunoprecipitation sequencing (ChIP-seq), and dual-luciferase reporter (DLR) assays. Additionally, the differential expression of miRNAs between DSS-Exo and Exo was explored and validation of key miRNA.

Results

DSS-Exo significantly upregulated E-cadherin, downregulated VEGFA, α-SMA, CTGF and Fibronectin expression in HMrSV5 cells compared to untreated Exo. In vivo studies revealed that DSS-Exo enhanced the ability of Exo to improve peritoneal function,such as the peritoneal filtration rate and urea nitrogen, glucose clearance, while reducing peritoneal thickness and protein leakage, and cell morphology, reduce collagen deposition, and decrease the degree of fibrosis. Mechanistically, these exosomes inhibited the STAT3/HIF-1α/VEGF signaling pathway within peritoneal mesothelial tissues. Furthermore, ChIP-seq and DLR demonstrated that DSS-Exo affected STAT3 directly binds to SHANK2 promoter regions, forming hydrogen bonds between 5 key amino acids such as GLN-344, HIS-332 and 6 key bases such as DG-258, DG-261. miRNA profiling identified DSS-Exo increased hsa-miR-27a-5p_R-1 to regulated STAT3-SHANK2 and modulating the EMT.

Conclusion

This study highlighted the innovative use of Danshensu in enhancing MSC-derived exosome therapy for PF. The identification of the hsa-miR-27a-5p_R-1-STAT3-SHANK2 axis may reveal new molecular mechanisms underlying fibrosis, further research is needed to fully elucidate its impact on PF. The integration of Danshensu from traditional Chinese medicine into modern MSC exosome therapy represents a promising frontier in the development of novel treatments for fibrotic diseases.

Introduction

Currently, there are over 3 million end-stage renal disease patients worldwide, and nearly 10% of them require peritoneal dialysis (PD) treatment. PD is a more convenient and cost-effective method compared to hemodialysis. The application of PD helps alleviate the socioeconomic burden and family expenses [1]. However, the peritoneal dialysis fluid, which contains a high concentration of glucose, can lead to structural and functional changes in peritoneal mesothelial cells, resulting in peritonitis and neovascularization, ultimately leading to PF [2]. Extensive research evidence has confirmed that EMT played a crucial role in the process of peritoneal fibrosis, characterized by the loss of peritoneal mesothelial cells, abnormal growth of α-SMA-positive myofibroblasts, thickening of the submesothelial stroma, and neovascularization [3]. PF is the main reason for discontinuing PD treatment [4]. At present, there are no definite preventive and therapeutic measures.

Research has shown that MSCs have unquestionable efficacy in treating fibrotic diseases such as liver fibrosis, pulmonary fibrosis, and renal fibrosis. MSCs are multipotent adult stem cells derived from bone marrow, adipose tissue, and umbilical cord, and they have immense clinical potential due to their extensive immunoregulatory, anti-fibrotic, and anti-inflammatory effects [5,6,7]. Two recent studies have found that intraperitoneal injection of human MSCs can improve glucose chlorhexidine-induced PF in rats, and serum-free culture conditions could enhance the anti-peritoneal fibrosis capability of MSCs, providing new evidence for the prevention and reversal of PF by MSCs [8, 9]. Another study also suggested that human MSCs-derived exosomes may be more effective in reducing liver fibrosis than MSCs, with lower potential for host reactions [10, 11] . The mechanism of action of MSCs is associated with paracrine secretion rather than transdifferentiation [12,13,14,15].

Exosomes are membrane-bound vesicles with a diameter of approximately 30–150 nm that are generated from multivesicular bodies within cells. They can be generated by most of human cell types and are distributed across tissues, intercellular spaces, and body fluids. Typically, there are approximately 1 × 10^12 exosomes in 1 ml of blood. Exosomes carry proteins, miRNA, lncRNA, circRNA, mRNA, and their degradation fragments, which play important regulatory roles in intracellular signaling pathways and cellular activities. They have shown promising potential as a novel therapeutic approach for various diseases, including tumor metastasis, disease development and immune disorders.

Salvia miltiorrhiza, a traditional Chinese medicine with blood-activating and stasis-resolving properties, is derived from the dried root and rhizome of Salvia miltiorrhiza Bge, a plant belonging to the Lamiaceae family. Modern pharmacological studies have demonstrated that Salvia miltiorrhiza possesses significant effects in lowering blood pressure, reducing blood lipids, and exhibiting anti-inflammatory and anticoagulant properties. Furthermore, current research has confirmed that DSS extracts and its main monomers have strong antifibrotic effects [16, 17]. Previous studies in our laboratory found that treatment with DSS alleviates peritoneal fibrosis induced by 4.25% peritoneal dialysis solution in human peritoneal mesothelial cells and mice, with STAT3 identified as the key target for the disease and the drug [18]. STAT3 and HIF expression are involved in the metabolism, proliferation, and migration processes of various cells to maintain cellular homeostasis. Consistent with this, the expression of histone deacetylase 8 was increased in PD effluent from long-term PD patients, and histone deacetylase 8 promotes EMT in peritoneal fibrosis through the activation of STAT3/HIF-1α [19]. The expression of VEGF and HIF-1α could also be abolished by inhibiting STAT3 activation.

Against this background, we investigated whether exosomes derived from DSS-preconditioned human mesenchymal stem cells could enhance the antifibrotic effects of regular exosomes and further elucidated the potential mechanisms underlying their differential effects. This study proposes a novel application of active components from herb, providing a reference for clinical development (flow chart as follow).

This flowchart outlines the comprehensive research process from exosome characterization to in vitro, in vivo, and mechanistic studies.

Material

Animals

C57BL/6 J mice, weighted 30 g ± 5 g, aged 10–12 weeks, half male and half female, were purchased from Guangzhou Reagent Biotech Co., Ltd. (Guangzhou, China). The mice were housed in a specific pathogen-free animal facility at Guangzhou Yungnovo Biotechnology Co., Ltd. (Guangzhou, China) with controlled lighting and temperature, and had free access to food and water. All experimental protocols (IACUC-AEWC-F2211019) were approved by the Guangzhou Forevergen Biosciences for Laboratory Animal Welfare and Ethical review board, and the study was conducted in accordance with the national guidelines for the use of laboratory animals.

Exosome and HMrSV5 cells

The human umbilical cord MSCs were purchased from the Guangdong Cord Blood Bank (Guangzhou, China). These cells were derived from umbilical cord tissue donated by healthy pregnant women, with written informed consent signed by the donors or their legal representatives permitting the use of the umbilical cords for scientific research. The cells used in the experiment were at passage 4. After purchase, the MSCs were identified by the Guangdong Cord Blood Bank to meet the standard phenotype of human mesenchymal stem cells, ensuring their purity and quality. MSCs were cultured in 10% low glucose DMEM medium until the third passage, and then the culture medium was replaced with fresh serum-free medium. After an additional 48 h of incubation, the supernatant was collected. HMrSV5 cells at passage 4 was purchased from Guangzhou Jennio Biotech Co., Ltd (Guangzhou, China). This cell line is internationally recognized as an immortalized human peritoneal mesothelial cell line used for research experiments. HMrSV5 cells were cultured in 10% DMEM complete culture medium and incubated at 37 °C with 5% CO2 in a CO2 incubator. The fresh culture medium was replaced every 2 days. The overall research project, including the use of human cells, was approved by the Ethics Committee of the Affiliated Panyu Central Hospital of Guangzhou Medical University on November 23, 2020 (PYRC-2020-016).

Reagent

Glucose peritoneal dialysis including 1.5%, 2.5%, and 4.25% concentrations were sourced from Baxter Healthcare Ltd. (Guangzhou, China). Danshensu (HPLC purity > 98%, CAS:76,822-21-4, molecular weight: 198.17) was purchased from Selleck Chemicals LLC (USA). Standard fetal bovine serum, DMEM culture medium, penicillin and streptomycin, and 0.25% trypsin were purchased from Gibco (USA). Dimethyl Sulphoxide was obtained from Sigma (USA). Trizol reagent was purchased from Thermo Fisher Scientific (Carlsbad, USA). RNA extraction auxiliary reagent (chloroform substitute) was sourced from ECOTOP Science Company (Guangzhou). Hifair® II 1st Strand cDNA Synthesis Kit was purchased from Yeasen Biotechnology Co., Ltd. (Shanghai, China). PrimeScript RT Kit and AceQ qPCR SYBR Green Master Mix (Low ROX) were obtained from Vazyme Biotech Co., Ltd. (Nanjing, China). CCK8 assay kit was purchased from Dojindo Chemical Corporation (Japan). Whole protein extraction reagent and BCA protein assay kit were sourced from KGI (Jiangsu, China). E-cadherin, VEGF-A (BS6496), STAT3 (BS1336), p-STAT3 (S727) (AP0248), p-STAT3 (T705) (AP0247), CTGF, FN, and HIF-1A rabbit monoclonal antibodies were purchased from Santa Cruz Biotechnology. High-sensitivity chemiluminescent detection solution was obtained from Amersham Life Sciences (Buckinghamshire, UK). CD14, CD29, CD34, CD44, CD73, CD45, CD90, CD105, and HLA-DR, along with FITC and PE isotype controls, were purchased from BioLegend (USA). The ELISA kit of IL-2, IL-6 and IL-8 was purchased from Jiangsu Meimian Industrial Co., Ltd. The inhibitor NC and hsa-miR-27a-5p_R-1 inhibitor were custom and synthesized by Huzhou Hippo Biotechnology Co., Ltd. The instruments used include a full-wavelength multifunctional microplate reader (Thermo, Varioskan LUX), a cell constant-temperature incubator (Thermo Scientific), a tabletop refrigerated centrifuge (Eppendorf, 5804R, 5418R), an inverted optical microscope (Leica, DM1000 LED), an automatic incubator (Bioworld, China), and a Bio-Rad ChemiDoc XRS system (Bio-Rad, USA).

Method

Cell viability

MSCs treated with 200 μM DSS were seeded into a 96-well plate. After incubation for 0 h, 24 h, 48 h, and 72 h, 10 μL of CCK8 solution was added to each well and incubated for 2 h. The optical density (OD) was measured using a microplate reader. CCK8 assays were performed after treating MSCs with 0-400 μM DSS for 48 h. Exo were collected after treating MSCs with 200 μM DSS for 48 h. HMrSV5 cells were incubated in a CO₂ incubator for 24 h. The old culture medium was aspirated, and 10% DMEM complete medium containing 0 μg/mL, 1 μg/mL, 3 μg/mL, or 5 μg/mL of DSS-Exo and Exo were added to each group with 3 replicates. After treatment for 48 h, CCK8 solution was added to each well for 2 h. The OD at 450 nm was measured. All experiments were performed at least three biological times.

Flow cytometry analysis

Cells were seeded into 6-well plates, and at 0 h, 24 h, 48 h, and 72 h, cell morphology, density, and adhesion status were observed using an inverted microscope. Cells were then collected at each time point, washed twice with PBS, and adjusted to a concentration of 1 × 10⁶ cells/mL. Fluorescently labeled antibodies were used, including CD29 (303,003), CD44 (397,517), CD73 (344,015), CD90 (328,109), CD105 (323,203), CD14 (325,603), CD34 (303,103), CD45 (304,006), HLA-DR (980,402), and isotype controls FITC (403,507) and PE (403,503). Cells were incubated with the antibodies at 4 °C in the dark for 30 min, followed by washing with PBS to remove unbound antibodies. Flow cytometry was performed, with at least 10,000 events collected per sample.

Enzyme-linked immunosorbent assay (ELISA)

ELISA was used to measure the concentrations of inflammatory cytokines (IL-2, IL-6, and IL-8). Samples were added to 96-well plates pre-coated with capture antibodies, followed by incubation with detection antibodies and streptavidin-HRP. After substrate development and stopping with sulfuric acid, absorbance was measured at 450 nm, and calculated the concentration. All measurements were performed in triplicate.

Quantitative real-time reverse transcription PCR (qRT-PCR)

HMrSV5 cells were cultured to 80% confluence and treated with 4.25% peritoneal dialysis fluid along with complete medium containing 0 μg/mL, 1 μg/mL, 3 μg/mL, or 5 μg/mL of DSS-Exo and Exo. After 48 h, RNA was extracted using the Trizol method, followed by cDNA synthesis and qRT-PCR experiments to observe the expression of VEGF-A, E-cadherin, and FN mRNA. The primers were synthesized by Bgi Genomics Co., Ltd. (Table 1). Human GAPDH gene was used as an internal reference gene. ΔΔCt = (target gene Ct value—reference gene Ct value)—(control target gene Ct value—reference gene Ct value); relative mRNA expression = 2^(-ΔΔCt) × 100%. All experiments were performed at least three biological times.

Table 1 Primer sequences

Characterization and concentration determination

Extraction

Resuscitate MSCs in a 10 cm culture dish. Once the cells are confluent, digest and count them, then seed 1 × 10^7 cells in a bioreactor containing 200 mL of complete culture medium with 20 microcarriers. Culture in a 37 °C, 5% CO₂ incubator for 3D culture. After 48 h, add 200 mL of medium to the Exo group and 200 mL of medium (IMMOCELL, IMP-H122-1) containing 200 μM DSS to the DSS-Exo group. Continue culturing for another 48 h, then remove the bioreactor, let it stand to allow the microcarriers and cells to settle, and collect the supernatant. Repeat this process to collect enough supernatant. The collected supernatant was added to an ultrafiltration centrifuge tube and centrifuged at 2000 × g, 4 °C for 30 min. The supernatant was then collected and centrifuged again at 10,000 × g, 4 °C for 45 min to remove larger vesicles. The supernatant was collected and filtered through a 0.45 μm filter membrane to collect the filtrate. The filtrate was transferred to a new centrifuge tube and centrifuged at 4 °C, 100,000 × g for 70 min. After removing the supernatant, the pellet was resuspended in 10 mL of pre-chilled PBS, and centrifuged again at 4 °C, 100,000 × g for 70 min at high speed. The supernatant was removed, and the pellet was resuspended in 100 μL of pre-chilled PBS. Then, 20 μL was used for electron microscopy, 10 μL for particle size analysis, and the remaining exosomes were stored at − 80 °C.

Characterization

The exosomes were observed for their overall morphology using transmission electron microscopy. Around 10 μL of the exosome suspension mentioned above was dropped onto a carbon-coated copper grid with a mesh size of 200, placed in a clean bench for 15 min, followed by adding 1% uranyl acetate for negative staining for 5 min. Excess negative staining solution was removed using sterile filter paper, and the grid was air-dried at room temperature for 30 min. The morphology and size of the exosomes were observed using transmission electron microscopy, and the concentration was preliminarily estimated.

Nanoparticle tracking analysis

10 μL of the exosomes were removed and diluted to 30μL. Exsome samples after instrument performance test with standard. The particle size distribution range of exosome membranes were measured using the ParticleMetrix nanoparticle tracking analysis instrument.

Markers of exosomes by western blot

The exosomes concentration was determined using the BCA assay kit following the protocol. Cells were lysed with RIPA buffer containing protease inhibitors, phosphatase inhibitors, and PMSF. The collected protein samples were electrophoresed on a 10% sodium dodecyl sulfate–polyacrylamide gel, transferred onto a polyvinylidene fluoride membrane, and blocked with 5% skim milk at room temperature. The membrane was then incubated with primary antibodies against GAPDH, CD9, CD81 and CD63 (1:1000) overnight at 4 °C, followed by washing and incubation with horseradish peroxidase-conjugated goat anti-rabbit secondary antibody (1:3000) at room temperature for 1 h. The protein expression was detected using chemiluminescence substrate on a gel imaging system. All experiments were performed at least three biological times.

Animal and experimental design

After one week of adaptation to appropriate temperature, water, and food conditions, three mice per cage, 24 mice were randomly divided into four groups (n = 6). The mice were placed in an induction chamber and anesthetized with 3–5% isoflurane, followed by maintenance of anesthesia at 1–3% isoflurane via a face mask, while continuously monitoring their vital signs. The treatments were applied according to the following groups: (1) NC group (equal volume of normal saline [NS], intraperitoneal injection); (2) PF group (3 ml of 4.25% peritoneal dialysis [PD] + NS, intraperitoneal injection); (3) Exo group (15 μg/day + PD, intraperitoneal injection); (4) DSS-Exo group (15 μg/day + PD, intraperitoneal injection). To reduce the potential risks of peritoneal infection and mechanical injury caused by multiple injections, a mixture of exosomes and PD was administered simultaneously every day for four weeks, followed by subsequent sampling and experimentation. At the end of the experiment, the mice were euthanized by exsanguination following anesthesia. The daily treatment regimen and timing were consistent. The experimental design was conducted by HWC and CH, with injections performed daily using the JY method. Sampling and measurements were conducted by FHL. Data analysis was performed using JXH software. Our preliminary experiments indicated that intraperitoneal injection of 4.25% PD for four weeks induced PF. Mice that survived without infection at the end of four weeks were included in further experiments. If they died or were lost, the missing data were treated as the average for the entire group. If more than three data points were missing, new mice and molds were created. The sample size for all experiments was predetermined based on calculations from our experience. No samples were excluded in this study. All animals were allocated using simple randomization. Data analysis was conducted single-blind, with researchers unaware of group assignments during both the experiments and the assessment of results. The work has been reported in line with the ARRIVE guidelines 2.0.

Peritoneal equilibrium test

Measurement of peritoneal dialysis ultrafiltration and drain fluid protein concentration

Each group of mice were injected with 2.5 mL of 4.25% peritoneal dialysis solution intraperitoneally. After retaining the solution in the peritoneal cavity for one dialysis cycle (120 min), a size 4.5 medical syringe needle was used to puncture the lower left abdomen of the mice to drain the peritoneal dialysis fluid. The abdominal wall was then cut along the midline, and the abdominal fluid was absorbed and weighed using sterile gauze. The weight of the dry gauze was subtracted to calculate the ultrafiltration volume (UF), and the protein concentration in the drain fluid was measured. UF = (weight of absorbed water by gauze—weight of gauze) × 1 mL·mg -1 + drain volume—2.5 mL.

Measurement of urea nitrogen and glucose clearance

Mice blood specimens and peritoneal fluid were collected from the mice. The peritoneal permeability was assessed by the ratio of blood urea nitrogen (BUN) in the dialysis fluid and blood (D/P) and the absorption of glucose in the dialysis fluid, i.e., the ratio of glucose in the 120-min dialysis fluid to the 0-min dialysis fluid (D/D0). The blood specimens were centrifuged at 3000 rpm for 10 min, and the peritoneal dialysis fluid specimens were centrifuged at 1500 rpm for 5 min. The concentrations of BUN and glucose in plasma and dialysis fluid were measured using an automated biochemical analyzer.

Masson, HE and Sirius Red staining

Performed HE and Masson staining to observe peritoneal mesothelial cell morphology and measure thickness. Fixed the parietal peritoneum with 4% paraformaldehyde, dehydrated, and embedded it in paraffin. Measured ten high-power fields per slide, averaging for thickness determination. Deparaffinized sections in xylene and ethanol, then rehydrated. For Masson's staining, used hematoxylin, Light Green, and Aniline Blue, while HE staining used hematoxylin and eosin. Applied a 0.1% Sirius Red solution in saturated picric acid for additional staining. Dehydrated, cleared, mounted, acquired, and analyzed images to observe cell morphology, peritoneal thickness, and interstitial vascular condition. Each section contained two tissue pieces, with eight high-power fields measured per piece to determine parietal peritoneum thickness.

Immunohistochemical (IHC) analysis

Performed IHC analysis on paraffin-embedded sections to observe the expression of specific proteins. The following primary antibodies were used: Rabbit polyclonal VEGFA (19,003-1-AP; Proteintech), α-SMA (14,395-1-AP; Proteintech), HIF-1α (20,960-1-AP; Proteintech), E-cadherin (20,874-1-AP; Proteintech), STAT3 (10,253-2-AP; Proteintech), and p-STAT3 (AP0705; ABclonal). Capture and measure images of the microsections.

Immunofluorescence (IF)

Paraffin sections underwent 60-min room temperature incubation, xylene immersion, ethanol rehydration. Sequential treatment: 3% H2O2, 5% BSA, 3% blocking serum (in PBS) for blocking. Incubated overnight at 4 °C with primary antibodies (in 3% BSA in PBS). Fluorescent secondary antibodies added, 1-h room temperature incubation in the dark (species-specific, concentrations: Alexa488/Alexa555 1:500, Cy3/FITC 1:200; foil-wrapped, light-protected). Hoechst: Dilute 1000 × in PBS, 50ul/slide, 10-min dark staining. Mount with Mounting Medium, invert, and capture microscope images after solidification.

Western blot (WB) analysis

Total protein was extracted using a lysis buffer. The protein concentration was determined using a BCA protein assay kit. SDS-PAGE gel electrophoresis was performed to separate the proteins, followed by transfer onto a membrane. After blocking with 5% skimmed milk for 1 h, the membrane was incubated with specific primary antibodies, including STAT3, p-STAT3, p-STAT3, HIF-1α, VEGFA, and α-SMA, CTGF diluted at a 1:1000 concentration. GAPDH was diluted at 1:2000, and the corresponding secondary antibodies were diluted at 1:5000. Band density was observed using ECL chemiluminescent reagent and the Bio-Rad ChemidOC XRS system (Bio-Rad, USA). The protein band densities were converted to grayscale values, and the relative expression levels were normalized to the grayscale values of GAPDH. All experiments were performed at least three biological times.

To investigate the relationship between treatment and STAT3/HIF-1α/VEGF signaling and epithelial-mesenchymal transition markers, we separately treated fibrotic HMrSV5 cells with the STAT3 inhibitor Stattic (MCE, HY-13818), HIF-1α inhibitor LW6 (MCE, HY-13671), STAT3 activator Colivelin (Selleck, s9664), and HIF-1α activator Fenbendazole-d3 (MCE, HY-B04135). All experiments were performed at least three biological times.

Due to the similar size of the target proteins, it could not display all bands on a single membrane. For clarity and simplicity, the manuscript showed cropped gels and imprints. Full-length blots were presented in Supplementary Figure S1.

ChIP-seq and bioinformatics analysis

We performed experiments using the Chromatin Immunoprecipitation Kit (BersinBio) and STAT3 antibody (Santa Cruz Biotechnology, sc-8019) in Exo and DSS-Exo on fibroblastic HMrSV5 cells. The immunoprecipitated DNA was quantified using the Qubit 3.0 Fluorometer (Invitrogen) and validated by GeneEngine Biotech (Shanghai) Co., Ltd.

The distribution of identified peaks on the genome was statistically analyzed. The computeMatrix tool in deepTools was used to calculate the distribution of peaks in the upstream and downstream regions of gene features, such as transcript start site (TSS). Based on the genomic annotation information, ChIP peaks were annotated by the nearest gene position, and the distribution of peaks on gene elements was counted. Motif prediction was performed using the software MEME. Gene ontology (GO), eukaryotic orthologous groups (KOG) and kyoto encyclopedia of genes and genomes (KEGG) functional enrichment analysis was analyzed.

Dual-Luciferase reporter assays

We used 293 T cells for this assay, purchased from Guangzhou Jennio Biotech Co., Ltd (Guangzhou, China). Cells were seeded at 2 × 10^5 per well in antibiotic-free medium until 80% confluence. Using Lipofectamine 2000, cells were transfected and the medium was replaced after 4–6 h, followed by an additional 48 h of cultivation. RNA was extracted using the Trizol method to check STAT3 overexpression. After transfection, cells were washed twice with PBS and lysed in 1 × Cell Lysis Buffer at room temperature for 10 min. The lysate was transferred to an opaque 96-well plate. 100 µL of Luciferase Reaction Reagent was added to the plate, followed by 20 µL of the lysate. After mixing, firefly luciferase activity was measured using a luminometer. Next, 100 µL of Luciferase Reaction Reagent II was added to measure Renilla luciferase activity. The assay included a STAT3 overexpression plasmid and control plasmids (pGL4 and RL-TK). Plasmid details are shown in Table 2.

Table 2 Plasmid information

MicroRNA sequencing analysis

MicroRNA (18–30 nt) were extracted from DSS-Exo and Exo. The RNAs were then amplified via RT-PCR, libraries were constructed, and sequencing was performed. For expression quantification and differential expression analysis, the expression levels of each miRNA in different samples were calculated, and differential expression analysis was conducted with selection criteria set to |log2FC|> 1 and P < 0.05. miRNA target gene annotation was performed to predict the potential target genes of miRNAs and their binding sites by using TargetScan (v5.0) and miRanda (v3.3a). The threshold for selecting target genes was set as TargetScan_score ≥ 50 and miranda_Energy < -10. The interaction networks of differentially expressed miRNAs with SHANK2 and STAT3 were constructed using Cytoscape (v3.9.1)A comprehensive gene-protein-miRNA network was created using STRING data, with visualization and analysis through Cytoscape plugins like ClueGO and CytoHubba. The hsa-miR-27a-5p_R-1 inhibitor were applied to further investigate the role of this miRNA in PF and its effects on STAT3 and SHANK2. Four groups were established: NC (normal HMrSV5), PF (4.25% PD induced HMrSV5), PF + DSS-Exo-hsa-miR-27a-5p_R-1inhibitor NC, and PF + DSS-Exo-hsa-miR-27a-5p_R-1 inhibitor, with treatments applied for 48 h. Protein levels of fibrosis markers (FN, α-SMA, E-Cadherin, VEGFA) and key therapeutic targets (SHANK2, p-STAT3, STAT3) were evaluated.

Statistical analysis

Statistical analysis was performed using SPSS 26.0 and GraphPad Prism 9. Data are presented as mean ± SEM. Unless otherwise stated, all experiments were independently performed three times. Non-parametric Mann–Whitney U test was employed. The significance level was set at α = 0.05.

Results

DSS-Exo improves fibrosis in HMrSV5 cells

CCK8 assays showed that cell viability gradually increased over time, with a significant proliferation trend observed at 48 h and 72 h (P < 0.05) (Fig. 1A). Microscopic images revealed that MSCs maintained a stable morphology at different time points (0 h, 24 h, 48 h, and 72 h), consistently exhibiting a typical spindle-shaped structure. No significant effect of DSS treatment on cell morphology was observed. Meanwhile, cell density gradually increased over time, indicating continuous cell proliferation (Fig. 1B). Flow cytometry results demonstrated that the duration of DSS treatment had no significant effect on the expression of MSC markers (CD29, CD44, CD73, CD90, and CD105), which remained highly expressed at all time points. In contrast, non-mesenchymal markers, including CD14, CD34, CD45, and HLA-DR, were consistently expressed at low levels throughout the experiment, suggesting that DSS did not affect the phenotypic stability of MSCs (Fig. 1C). CCK8 assays showed no significant effect on MSCs viability after 48 h treatments of 0, 50, and 100 μM DSS (P > 0.05), while 200 and 400 μM DSS significantly increased MSCs viability after 48 h (P < 0.01). Our preliminary research found that 200 μM DSS had the best effect on reducing peritoneal fibrosis, so we used this concentration for MSCs treatment in subsequent experiments. Therefore, exosomes were collected from MSCs treated with 200 μM DSS for 48 h (Fig. 1D).

Fig. 1

DSS-Exo Improves Fibrosis in HMrSV5 Cells. A Cell viability of 200 μM DSS treated MSCs on 0 h, 24 h, 48 h, 72 h; B MSCs Cell morphology and density at different time points treated by DSS; C MSCs and non-MSCs markers analyzed by flow cytometry; D Cell viability of 0–400 μM treated MSCs; E Nanoparticle tracking analysis; F Markers of exosomes by western blot; G The morphology and size of the exosomes in transmission electron microscopy; H Concentration toxicity by CCK8; I–K Effective concentration by RT-PCR; L, M Biomarkers of fibrosis by western blot; N Inflammatory cytokines concentrations by ELISA. ns: P > 0.05; *: P < 0.05; **: P < 0.01; ***: P < 0.001; #: P < 0.0001

Exosomes were isolated using ultracentrifugation. Nanoparticle tracking analysis showed exosome diameters ranged from 30 to 150 nm, peaking at 72.75 nm and 57.24 nm (Fig. 1E). Electron microscopy confirmed their uniform cup-shaped morphology (Fig. 1G). The exosomes tested positive for surface markers CD81, CD63, and CD9 (Fig. 1F), confirming successful extraction [20].

Using CCK8 assays, we tested different concentrations (0, 1, 3, 5 μg/mL) of DSS-Exo and Exo on HMrSV5 cell viability at 24 and 48 h. At 24 h, no significant effects on cell viability were observed (Fig. 1H). However, at 48 h, both DSS-Exo and Exo significantly increased cell viability at all concentrations (P < 0.05), with no significant difference between the two (P > 0.05) (Fig. 1H).

Compared to the NC group, the PF group showed a significant increase in fibronectin and VEGFA mRNA and a significant decrease in E-Cadherin mRNA. Compared to the PF group, Exo intervention reduced fibronectin mRNA expression levels (P < 0.05) and significantly decreased VEGFA mRNA and increased E-Cadherin mRNA expression at a concentration of 5 μg/mL (P < 0.05). DSS-Exo intervention improved the changes induced by peritoneal dialysis. At 5 μg/mL and 48 h, both DSS-Exo and Exo significantly reduced mRNA levels of fibrosis markers fibronectin and VEGFA, and increased E-cadherin levels (P < 0.05). And DSS-Exo was more effective than Exo (P < 0.05) (Figs. 1I–K). Protein levels of CTGF, VEGFA, and α-SMA were also reduced after 48 h of treatment, with DSS-Exo showing greater improvement in HMrSV5 cell fibrosis (Figs. 1L, M). Additionally, immunotropic cytokines IL-2, multifunctional cytokine IL-6, chemokines IL-8 across all groups revealed no significant differences (Fig. 1N), indicating that this study may capture the early stages of EMT improvement by DSS-Exo and Exo, when the role of inflammatory cytokines is not yet significant (Fig. 1K). Therefore, we chose 4.25% PD with 5 μg/mL DSS-Exo and Exo treated HMrSV5 for 48 h for further experiments.

DSS-Exo improves function and morphology of the peritoneum

Based on the in vitro findings, DSS-Exo and Exo showed antifibrotic potential by regulating EMT-related markers at both mRNA and protein levels. These results suggested that DSS-Exo and Exo may improve EMT in peritoneal dialysis-induced cell damage. To confirm these findings, we further evaluated their effects on peritoneal structure and function in an in vivo model.

Under light microscopy, normal peritoneal tissue exhibited a dense, intact layer of flat mesothelial cells, with a thin basement membrane connected to the connective tissue (Fig. 2C). After treatment with 4.25% glucose peritoneal dialysis solution, mice peritoneal tissue showed thickening of the wall layer, discontinuity, and detachment of surface mesothelial cells, thickening of the submesothelial dense layer, and infiltration of inflammatory factors. Compared to the PF group, Exo and DSS-Exo treatments reduced nuclear density, with DSS-Exo showing the most significant reduction, indicating decreased inflammation or fibrosis (Fig. 2D). Masson staining revealed significant collagen deposition in the peritoneal wall layer of the PF group, indicated by intense blue staining (Fig. 2A). After exosome treatment, collagen deposition was reduced, with DSS-Exo showing slightly better effects than Exo (Fig. 2B). Sirius Red staining showed extensive fibrosis and significant collagen deposition in the PF group, as evidenced by intense red staining in the peritoneal layer (Fig. 2E). Exo and DSS-Exo treatments significantly reduced the collagen area percentage compared to PF, with DSS-Exo being the most effective (Fig. 2F).

Fig. 2

Function and morphology of peritoneal. A Masson staining for collagen (blue); B Collagen area percentage (Masson); C HE staining for general tissue morphology; D Nuclear counting (HE); E Sirius Red staining for collagen (red); F Collagen area percentage (Sirius Red); G Peritoneal thickness; H Ultrafiltration volume; I BUN clearance rate; J Glucose clearance rate; K Fibronectin concentration; L–Q Immunohistochemical analysis; L, M α-SMA expression; N, O E-Cadherin expression; P, Q VEGFA expression. Ns: P > 0.05; *:P < 0.05; **:P < 0.01; ***:P < 0.001; #:P < 0.0001

Masson staining measured the peritoneum thickness as (23.49 ± 2.12) μm in the NC group and (38.41 ± 1.65) μm in the PF group. Compared with the NC group, the peritoneal fibrous tissue significantly increased after peritoneal dialysis fluid treatment (P < 0.05). The peritoneum thickness in the DSS-Exo group was (27.72 ± 0.28) μm and in the Exo group was (29.29 ± 1.70) μm. Compared with the PF group, exosome intervention significantly reduced fibrous tissue and collagen deposition in the submesothelial layer of the peritoneal wall in mice (P < 0.05), with the DSS-Exo group showing even more significant improvement (P < 0.05) (Fig. 2G).

Peritoneal ultrafiltration volume, drained protein concentration, BUN, and glucose clearance rate all reflect the peritoneal dialysis capacity of the mice. Compared with the NC group, mice undergoing 4 weeks of peritoneal dialysis showed a significant decrease in peritoneal ultrafiltration volume, BUN clearance rate, and glucose clearance rate, and a significant increase in drained protein concentration in the dialysate (P < 0.05). Compared with the PF group, intervention with DSS-Exo and Exo increased peritoneal ultrafiltration volume (Fig. 2H), BUN clearance rate (Fig. 2I), and glucose clearance rate (Fig. 2J), and decreased drained protein concentration in the dialysate (Fig. 2K) (P < 0.05). The DSS-Exo group showed better improvement than the Exo group.

IHC showed that compared with the NC group, the PF group had significantly increased expression of α-SMA and VEGFA and significantly decreased expression of E-cadherin (P < 0.05) (Fig. 2L–Q). After DSS-Exo and Exo treatment, the positive areas of α-SMA and VEGFA were significantly reduced, and E-cadherin expression significantly increased (P < 0.05), with DSS-Exo showing more significant improvement than Exo (P < 0.05). This indicates that DSS can enhance the effect of Exo in alleviating structural and morphological changes and improving peritoneal dialysis capacity in peritoneal tissue caused by peritoneal fibrosis.

DSS-Exo reduces the expression of STAT3, p-STAT3, and HIF-1α in vivo

STAT3 has been implicated in the development of peritoneal fibrosis. IHC analysis revealed that DSS-Exo and Exo significantly reduced the increased expression of STAT3, p-STAT3, and HIF-1α induced by 4.25% PD (P < 0.05), as shown in Fig. 3A–F.

Fig. 3

The expression of STAT3, HIF-1α and VEGFA in vivo. A–F Immunohistochemical analysis of tissue sections; A STAT3 expression, C p-STAT3 expression, E HIF-1α expression; B, D, F Quantitative analysis of mean density (IOD value) for STAT3, STAT3 (S727), and HIF-1α, respectively; G–I Immunofluorescence, G DAPI (nuclei, blue), STAT3 (green), VEGFA (red), and overlay images; H DAPI (nuclei, blue), HIF-1α (green), STAT3 (red), and overlay images; I DAPI (nuclei, blue), HIF-1α (green), VEGFA (red), and overlay images. Ns: P > 0.05; *: P < 0.05; **: P < 0.01; ***: P < 0.001; #: P < 0.0001

HIF-1α is commonly believed to be downstream of STAT3 and upstream of VEGFA. We primarily observed the correlation of these three biomarkers in the peritoneal layer. Using IF co-expression experiments, we observed significant expression of STAT3 and VEGFA in both the peritoneal and muscle layers, while HIF-1α was primarily expressed in the muscle layer and less so in the peritoneal layer. The co-expression pattern of STAT3 and VEGFA was similar. Compared with the PF group, the DSS-Exo and Exo groups significantly reduced the expression levels of STAT3, HIF-1α, and VEGFA in the peritoneal layer, with DSS-Exo showing a more significant reduction than the Exo group (Fig. 3G–I).

STAT3 is a key target for DSS-Exo in ameliorating PF

Our in vivo experiments demonstrated that DSS-Exo could improve peritoneal function and ameliorate PF better than Exo. To further investigate whether DSS-Exo improves PF by regulating the STAT3/HIF-1α/VEGF pathway, we performed in rescue experiments on HMrSV5 cells using DSS-Exo.

PD-induced HMrSV5 cells were treated with DSS-Exo, the STAT3 activator Colivelin, the HIF-1α activator Fenbendazole-d3, and their combination for 48 h. The results showed that the protein expression levels of VEGFA, HIF-1α, STAT3 (T721), and STAT3 (S727) were significantly higher in the PF group compared with the NC group (P < 0.05) (Fig. 4 Aa, Ab, Fa, Fb). Treatment with DSS-Exo significantly reduced the expression of these proteins (P < 0.05) (Fig. 4 Ab, Ac, Fb, Fc). This indicates that DSS-Exo can reduce STAT3 (T721), HIF-1α, and VEGFA expression to improve PF, likely not through the activation of p-STAT3 (S727) (Fig. 4A–E). Activating STAT3 can affect HIF-1α expression, but activating HIF-1α does not affect STAT3 expression.

Fig. 4

The expression of STAT3/HIF-1α/VEGFA in vitro. A Western blot images for STAT3 (T721 and S727), HIF-1α, VEGFA expression with different treatments: (a) Control, (b) PD, (c) PD + DSS-Exo, (d) PD + DSS-Exo + Colivelin, (e) PD + Colivelin, (f) PD + DSS-Exo + Fenbendazole-d3, (g) PD + Fenbendazole-d3, (h) PD + DSS-Exo + Colivelin + Fenbendazole-d3, (i) PD + Colivelin + Fenbendazole-d3. B–E Quantitative analysis of the relative expression levels of proteins: B STAT3 (T721), C STAT3 (S727), D HIF-1α, E VEGFA. F Western blot images for STAT3 (T721 and S727), HIF-1α, and VEGFA expression with different treatments: (a) Control, (b) PD, (c) PD + DSS-Exo, (d) PD + DSS-Exo + Stattic + LW6, (e) PD + Stattic + LW6, (f) PD + DSS-Exo + Stattic, (g) PD + Stattic, (h) PD + DSS-Exo + LW6, (i) PD + LW6. G–J Quantitative analysis of the relative expression levels of proteins: G STAT3 (T721), H STAT3 (S727), I HIF-1α, J VEGFA. ns:P > 0.05; *:P < 0.05; **:P < 0.01;***:P < 0.001; #:P < 0.0001

Next, PD-induced fibrotic HMrSV5 cells were treated with DSS-Exo, the STAT3 inhibitor Stattic, the HIF-1α inhibitor LW6, and their combination for 48 h. Inhibition of STAT3 affected HIF-1α expression, but not vice versa. These findings suggest that DSS-Exo primarily improves PF through key targets of STAT3. In addition to inhibiting the STAT3/HIF-1α signaling pathway, DSS-Exo likely engages other signaling pathways to reduce VEGFA expression (Fig. 4F–J).

STAT3 binding sites and association with transmembrane transporters and gated channel activity in HMrSV5 cells

To identify the STAT3 binding sites in HMrSV5 cells after DSS-Exo and Exo interventions in PF, we conducted STAT3 ChIP-seq analysis to pinpoint the direct targets of STAT3. Model-based analysis of ChIP-seq (MACS) was used to identify peaks. We identified 45 STAT3 binding sites in Exo-treated PF HMrSV5 cells and 23,851 sites in DSS-Exo-treated cells, suggesting that DSS-Exo treatment directly regulates more genes via STAT3 compared to Exo treatment after 48 h. The specific numbers and overall distribution of binding sites on chromosomes are shown in Fig. 5A, B. Among these binding sites, 5,522 (23.15%) and 9,109 (38.19%) were located in intronic or intergenic regions, and 1,185 (4.97%) and 6,154 (25.8%) were situated at transcription start sites (TSS) and promoter regions, respectively, after DSS-Exo treatment, indicating that STAT3 may regulate genes by directly binding to promoters. In contrast, only 2.22% of binding sites were located in promoter regions after Exo treatment (Fig. 5C).

Fig. 5

ChIP-sequencing analysis and validation. A Histogram of the number of peaks on the chromosome; B Circos graph of the overall distribution of the peak on the genome; C Pie chart of peak distribution on gene elements; D Heatmap of the signal distribution near the peak; E Peak figure of differential sites; F GO functional enrichmen; G KEGG pathway enrichmen; H Peak Motif calculate; I Alignment of the DNA-binding sequences; J Dual-Luciferase Reporter Assay; L Molecular Docking

We noted differences between the DSS-Exo and Exo groups, with only 17 intersecting genes. We chose the union genes for subsequent functional analysis (Fig. 5D). Further analysis revealed that 31.3% and 33% of STAT3 binding sites were within 10 kb upstream or downstream of the TSS in DSS-Exo PF HMrSV5 cells (Fig. 5E). Functional annotation of 5,681 genes showed significant enrichment of terms related to transmembrane transporters and gated channel activity (Fig. 5F). Major pathways included Glutamatergic synapse, Calcium signaling pathway, Cholinergic synapse, and Axon guidance (Fig. 5G).

Additionally, de novo motif analysis using HOMER on all STAT3 binding peaks showed highly conserved STAT3 homodimer motifs in DSS-Exo and Exo PF HMrSV5 cells, with top-ranking motifs from the KLF family, including KLF1, KLF2, KLF7, KLF9, KLF14, and KLF10 (Fig. 5H). The KLF family, as transcription factors, may play a synergistic role in transcription in this experiment. No clear peaks of the STAT3 gene promoter itself were found in DSS-Exo and Exo-treated cells (Fig. 5I), suggesting that STAT3 protein is negatively regulated, consistent with our previous results (Figs. 3, 4). This indicated that DSS-Exo and Exo treatments may regulate transmembrane transporter and gated channel activity in HMrSV5 cells via a negative feedback loop, thereby improving the transport of glucose or small molecule metabolites across the peritoneum.

Among all binding sites, we found 135 STAT3 binding sites with SHANK2. We selected four sequences in the promoter region for DLR assays, which showed that overexpressing STAT3 in 293 T cells significantly increased SHANK2 luciferase expression, indicating that STAT3 binds to and promotes transcription of SHANK2 promoter regions 1–3 and 1–4 (Fig. 5J,K). To further understand the interaction between STAT3 and SHANK2, we performed molecular docking of the DNA sequence of the 1–3 SHANK2 promoter. As shown in Fig. 5L, hydrogen bonds form during the STAT3-DNA complex formation, with interactions between GLN-344, HIS-332, LYS-340, ASN-466, GLN-469 on the STAT3 protein, and DG-258, DG-261, DG-262, DG-263, DT-253, DC-252 on the DNA. These hydrogen bonds are the main forces of interaction between STAT3 protein and SHANK2 promoter DNA, indicating a strong STAT3-SHANK2 binding.

DSS-Exo regulates PF by hsa-miR-27a-5p_R-1-STAT3-SHANK2 axis

To explore the potential mechanisms by which DSS-Exo enhances the therapeutic effect of Exo on PF through molecular biological processes, we performed microRNA sequencing on the contents of exosomes from both groups. The aim was to more comprehensively elucidate the mechanisms by which DSS enhances exosome therapy. Annotation using Rfam (https://rfam.org/) revealed that both exosomes predominantly contain more than 50% ribosomal RNA (rRNA), with DSS-Exo having nearly twice the proportion of transfer RNA (tRNA) compared to Exo (Fig. 6A). We excluded other non-miRNA RNAs from the analysis. After differential analysis of miRNAs, clustering analysis and visualization were performed (Fig. 6C). Among the top 10 differentially expressed miRNAs, hsa-miR-126-3p_R-1, hsa-miR-223-3p, hsa-miR-122-5p_R-1, mmu-mir-6236-p5_1ss4CG_1, mmu-mir-6236-p5_1ss4CG_3, mmu-mir-6236-p5_1ss4CG_2, and hsa-miR-26a-5p were significantly downregulated, while bta-miR-1246_L-1R + 3, hsa-miR-889-3p, and hsa-miR-27a-5p_R-1 were significantly upregulated (Fig. 6D, E). Annotation revealed 466 common genes between DSS-Exo and Exo (Fig. 6B). KEGG pathway enrichment analysis of these common genes indicated significant enrichment in metabolic pathways (such as glucose metabolism and purine metabolism), suggesting their crucial roles in the study. An interaction network between the SHANK2 gene and all differentially expressed miRNAs revealed associations with three top 10 miRNAs: hsa-miR-27a-5p_R-1, hsa-miR-122-5p_R-1, and hsa-miR-26a-5p (Fig. 6G). Similarly, the network for the STAT3 protein identified an association with hsa-miR-27a-5p_R-1 (Fig. 6I). Further analysis of hsa-miR-27a-5p_R-1 enriched 102 genes, with the top 30, which included STAT3, shown in Fig. 6J. Finally, we developed a gene-protein-differential miRNA interaction network, further supporting the observation that hsa-miR-27a-5p_R-1 as a key mediator in the regulatory network involving STAT3 and SHANK2, influencing processes like EMT and fibrosis. GO functional enrichment analysis highlighted metabolic pathways and protein binding (Fig. 6K), consistent with our previous findings.

Fig. 6

miRNA-sequencing analysis and network analysis. A Annotation of Rfam; B Gene Venn diagram of the differential miRNA; C Cluster analysis of the differential miRNA; D Volcano plot of RNA expression differences; E Correlation analysis of RNA expression; F KEGG pathway enrichment analysis; G hsa-miR-27a-5p_R-1-SHANK2 network; H hsa-miR-27a-5p_R-1-target gene interaction network; I hsa-miR-27a-5p_R-1-STAT3 network; J miRNA-gene-protein network; K GO enrichment analysis; L Western blot results of targets and EMT-related proteins, STAT3, p-STAT3, SHANK2, FN, α-SMA, VEGFA, E-cadherin; M Quantification of protein expression from panel L. P < 0.05, P < 0.01, P < 0.001, P < 0.0001

We applied hsa-miR-27a-5p_R-1 inhibitor to DSS-treated MSC, using inhibitor NC as the control group. Compared to the NC group, the protein expression levels of p-STAT3, SHANK2, FN, α-SMA, and VEGFA were significantly increased in the PF group, while the expression level of E-cadherin was decreased. After intervention with DSS-Exo-hsa-miR-27a-5p_R-1 inhibitor NC, these trends were reversed, indicating the antifibrotic effect of the DSS-Exo. However, when the hsa-miR-27a-5p_R-1 inhibitor was applied, the antifibrotic effect of the DSS-Exo was partially attenuated (Fig. 6L, M), suggesting that hsa-miR-27a-5p_R-1 played a critical role in the exosome-mediated reversal of EMT and improvement of fibrosis through the STAT3-SHANK2 axis.

The mechanism diagram highlights the potential mechanisms of DSS-pretreated MSC exosomes, emphasizing the hsa-miR-27a-5p_R-1-STAT3-SHANK2 axis. miRNAs such as hsa-miR-27a-5p_R-1 in exosomes regulate STAT3 gene expression, subsequently influencing the activity of the SHANK2 promoter region. This regulatory axis is crucial in biological processes like EMT, fibrosis, adhesion, and glucose metabolism. Through this pathway, hsa-miR-27a-5p_R-1 indirectly affects the expression of various target genes and proteins, such as α-SMA, CTGF, E-cadherin, fibronectin, VEGFA, and HIF-1α, thereby modulating cellular functions and disease states (Fig. 7).

Fig. 7

Mechanism diagram. Annotation: Specific miRNAs upregulated or downregulated by DSS-Exo include hsa-miR-126-3p_R-1, hsa-miR-223-3p, hsa-miR-122-5p_R-1, among others, which modulate genes related to fibrosis such as α-SMA, CTGF, E-cadherin, Fibronectin, VEGFA, and HIF-1α. DSS-Exo modulate the STAT3 transcription factor, which binds to the SHANK2 promoter, influencing gene transcription

Discussion

PF is a pathological change in the peritoneum caused by mechanical injury, chronic inflammation, and long-term incompatible peritoneal dialysis. During the process of peritoneal fibrosis, peritoneal cells undergo EMT, losing epithelial cell markers and acquiring mesenchymal cell markers [21, 22]. Organ fibrosis was regulated by a complex signaling network controlling their expression. Most impressively, inhibition of HIF-1 or STAT3 could treat and reverse fibrotic diseases and has become a promising therapeutic target [23], such as renal fibrosis [24], and pulmonary fibrosis [25]. Compared with new PD patients, p-STAT3 expression was significantly increased in chronic PD effluent, considered associated with STAT3 phosphorylation [26], tyrosine phosphorylation of STAT3 at tyrosine705 was activated, p-STAT3 forms a dimer and then translocated to the nucleus, which directly binds to DNA sequence and regulates the expression of target genes.

Our study demonstrated that DSS-Exo offer significant therapeutic advantages over regular Exo in treating PF. This effect is likely due to modulation of the STAT3/HIF-1α/VEGFA signaling pathway, crucial in PF pathophysiology [27]. STAT3 is highly expressed in peritoneal mesothelial cells exposed to high-glucose PD. Its downstream targets, such as HIF and VEGFA, contribute to angiogenesis, EMT, and PF [26, 28, 29]. In vivo experiments showed that DSS-Exo and Exo improved the fibrotic peritoneum's structure and restored peritoneal filtration function. Double immunofluorescence staining revealed positive correlations between STAT3 and HIF, VEGF expression, aligning with previous research [30]. Using STAT3 and HIF-1α agonists and inhibitors, we observed changes in downstream targets and EMT markers, suggesting STAT3 as a key therapeutic target. STAT3 ChIP-seq analysis identified key gene sequences related to hMSC-Exosome therapy, including SHANK2, TYK2, and FKL, which associated with transmembrane transporters and gated channel activity. miRNA-seq analysis of exosome identified that hsa-miR-126-3p_R-1, hsa-miR-223-3p, hsa-miR-122-5p_R-1, mmu-mir-6236-p5_1ss4CG_1 and hsa-miR-26a-5p were significantly downregulated, while bta-miR-1246_L-1R + 3, hsa-miR-889-3p, and hsa-miR-27a-5p_R-1 were significantly upregulated. By regulating the STAT3-SHANK2 axis, hsa-miR-27a-5p_R-1 indirectly affects the expression of various target genes and proteins, such as α-SMA, CTGF, E-cadherin, FN, VEGFA, and HIF-1α, thereby modulating cellular functions and disease states.

Previous studies have shown that mesenchymal stem cell-derived exosomes prevent liver fibrosis by delivering miR-148a to macrophages through the KLF6/STAT3 pathway [31] and alleviate steatotic scar fibrosis through the miR-192-5p/IL-17RA/Smad axis [32]. Additionally, miR-21a-5p attenuates glycolysis and reduces renal fibrosis by targeting PFKM [33]. Inhalation of alveolar epithelial cell-derived exosomes promotes lung repair in pulmonary fibrosis [34]. Our study further elucidated the STAT3/HIF-1α/VEGFA signaling pathway involved in mesenchymal stem cell-derived exosome therapy for peritoneal fibrosis. Interestingly, we observed contrasting results to two studies that utilized mesenchymal stem cells or modified exosomes in fibrosis treatment, where VEGFA expression was upregulated [35, 36]. We believed that the effects of exosomes may be mediated by multiple miRNAs working synergistically and reaching a balanced state. In other words, exosomes may promote angiogenesis in the early stages of the disease and inhibit angiogenesis in later stages, or the role of the same exosomes in fibrosis in different organs may vary.

Our results revealed the molecular mechanism of DSS-Exo treatment for PF. Among these, hsa-miR-27a-5p_R-1 emerged as a critical regulator. hsa-miR-27a-5p_R-1 was found to influence STAT3 expression, which in turn affects SHANK2 promoter activity. The miR-27 family includes microRNA precursors found in animals and humans [37]. The mature miR-27 plays a role in cholesterol and fatty acid metabolism [38]. When overexpressed, it blocks fat cell development by inhibiting key regulators [39]. miR-27a and miR-27b specifically reduce fat cell differentiation by targeting PPARγ and C/EBP alpha [40], acting as inhibitors of fat formation and contributing to obesity [39]. miR-27 also activates the Wnt signaling pathway, which helps stem cells become bone cells [41]. It targets and reduces the APC protein, affecting bone cell differentiation. This pathway is activated when β-catenin builds up in the nucleus, which happens when miR-27 inhibits the β-catenin destruction complex through APC suppression [41]. SHANK2 is a protein encoded by the human SHANK2 gene, and it exists in two different splice variants [42]. Mutations in SHANK2 are primarily associated with autism spectrum disorder and schizophrenia. It plays a role in synapse formation by linking metabotropic glutamate receptors to NMDA receptor pools through PSD-95 and HOMER1 [42]. SHANK2 also interacts with ARHGEF7 [43], Cortactin [44], DLG4 [45, 46], DLGAP1 [45, 46] and DNM2 [47]. Our study is the first to identify the relationship between STAT3 and SHANK2, providing novel insights into the regulation of SHANK2 by STAT3 in the context of fibrosis. Complements the knowledge of human SHANK2 genes and lays the foundation for future targeted drug development.

Research has explored the potential of MSCs in reducing fibrosis in organs like the liver, lungs, and kidneys [48,49,50,51]. However, there are only three clinical trials using MSCs for treating PF. Jiang et al. [52] reported that MSCs treatment significantly increased hemoglobin, erythropoietin, and albumin levels in CAPD patients. Alatab et al. [53] found MSCs therapy feasible for CAPD patients with no adverse events, and Ahmadi et al. [8] noted slight improvements in UF capacity and peritoneal function. Challenges persist, such as dosage discrepancies between animal and clinical trials leading to varied outcomes [54], unique extraction methods required for different MSC sources, and a lack of standardized guidelines. Additionally, MSC storage and transport conditions can affect their clinical efficacy. Given these issues, MSC-derived exosomes present a promising alternative for treating PF. Initially, it was thought MSCs repaired tissue by differentiating into various cells [55,56,57,58,59], but recent studies show their primary action is through paracrine signaling and direct interactions. For instance, Jiao et al. [60] demonstrated that MSC-conditioned media can inhibit EMT in HPMCs, possibly by regulating PTEN gene inhibition through lnc-CDHR and miR-3149 binding. Our study shows that Danshensu enhances the anti-fibrotic effects of exosomes, offering new insights into their clinical application. This underscores the potential of exosome-based therapies as viable alternatives in clinical settings.

DSS, a major active compound extracted from Salvia miltiorrhiza, has been traditionally used in Chinese medicine for its blood-activating and stasis-resolving properties. Modern pharmacological studies have demonstrated its significant effects in lowering blood pressure, reducing blood lipids, and exhibiting anti-inflammatory and anticoagulant properties [61, 62]. However, the clinical application of DSS and other traditional chinese medicine (TCM) monomers in humans is often limited by concerns about bioavailability, toxicity, and the lack of comprehensive clinical trials. Our study highlights a novel application of DSS, showing its potential in enhancing the therapeutic properties of MSC-derived exosomes. This underscores the importance of TCM as a rich source of bioactive compounds with potential applications in modern medical therapies. By integrating TCM with advanced stem cell technologies, we can develop innovative treatments that leverage the best of both worlds. The innovative aspect of our research is that it utilizes TCM monomers without involving ethical issues typically associated with direct human clinical trials, thus providing a viable pathway for the clinical application of these compounds in a safe and ethical manner.

Our study has several limitations. First, while our in vitro and in vivo models provide valuable insights, they may not fully replicate the complex environment of human PF. Future independent studies are still needed to conduct pharmacokinetic and pharmacodynamic research on exosomes in the abdomen to evaluate the absorption, distribution, metabolism, and excretion of DSS-Exo. Second, investigate the long-term effects and safety profile of DSS-Exo in various models of fibrosis to ensure its potential for clinical application. Finally, we had at least 3 biological replicates per group, which might lead to insufficient statistical power. We recommend increasing the sample size in future studies to validate the current results.

Additionally, the reduction trend in IL-6 and IL-8 levels in the DSS-Exo treatment group, though not statistically significant. We acknowledge that inflammatory responses are dynamic and may require more time points or additional markers to fully capture the effects of DSS-Exo. Future studies with a broader range of biomarkers and more experimental conditions are necessary to clarify these effects. This study selected HMrSV5 cells as the in vitro model due to their key role in the early stages of peritoneal fibrosis. As the primary peritoneal cells, mesothelial cells drive fibrosis through EMT, generating fibroblast-like cells and secreting extracellular matrix. Single-cell models simplify experimental conditions, making them ideal for initial studies on fibrosis mechanisms. While co-culturing mesothelial cells with fibroblasts and immune cells better replicates the complex microenvironment of later fibrosis stages, future experiments can adopt such systems to examine cell interactions further. Immune cell profiling in the peritoneal microenvironment is also crucial for understanding the broader therapeutic effects of DSS-Exo. Immune cells, such as macrophages and lymphocytes, play pivotal roles in tissue repair and fibrosis modulation, with exosomes known to influence macrophage polarization and lymphocyte infiltration. The expression profiles of key subsets, such as macrophages (CD68, CD206, CD86) and lymphocytes (CD3, CD4, CD8), provide a promising approach for future research to understand comprehensively how DSS-Exo regulate immune responses to ameliorate peritoneal fibrosis.

Conclusion

Our study highlights the therapeutic potential of DSS-MSC-Exo in treating PF, providing a potential mechanism of regulating the hsa-miR-27a-5p_R-1-STAT3-SHANK2 axis and a foundation for future clinical investigations. This is the first study to reveal the STAT3 and SHANK2 relationship, expanding our understanding of their roles in fibrosis and suggesting new avenues for targeted therapies. Additionally, using Danshensu from TCM to enhance MSC exosome therapy underscores the potential of integrating traditional and modern medical practices for innovative treatments.