Huangqi [Astragalus membranaeus (Fisch.) Bge.], Tusizi (Cuscuta chinensis Lam.), Baizhu (Atractylodes macrocephala Koidz.), Shudihuang (Rehmannia glutinosa Libosch.), Shanyao (Dioscorea opposita Thunb.), Fuling [Poria cocos (Schw.) Wolf], Fupenzi (Rubus chingii Hu), and Jinyingzi (Rosa laevigata Michx.) were purchased from Bozhou Medicine Company (batch number: 180609), Anhui, China. The JPZS formulation comprises eight types of processed Chinese medicinal herbs. First, a precise amount of the aforementioned Chinese medicinal herbs were meticulously weighed. Subsequently, the herbs were immersed in water at a volume 10-fold their weight and left to soak for 1 h. They then underwent two rounds of extraction using boiling water, with each round lasting 1.5 h. The resulting extracts from both rounds were combined and filtered. Finally, the filtered solution was concentrated to 2.522 g/mL of raw dry material using a rotary evaporator. The concentrated extract (2.522 g raw herb/mL) was aliquoted and stored at -80°C. High-performance liquid chromatography (HPLC) fingerprinting ( Figure 1 ) was employed to ensure batch consistency for this study. Future investigations will incorporate quantitative standardization based on key marker compounds identified in the HPLC profile.

The main constituents of the JPZS formulation were analyzed and quantified using HPLC. The preparation substances used for analysis included catechin (B21722), gallic acid (B20851), 5-hydroxymethylfural (B21382), acteoside (B20715), rutin (B20711), hyperoside (B20631), quercetin (B20257), tiliroside (B21587), kaempferol (B21126), formononetin (B20836), atractylenolide III (B20056), astragaloside A (B20564), dioscin (B1176), atractylodin (B20128), pachytic acid (B20400), and atractylone (B20129). These substances were obtained from Shanghai Yuanye Biotechnology Co., Ltd. at Shim-pack GIST C18 column (2×100mm, particle size 2.0 μm) using reverse phase HPLC. B methanol (0.01% formic acid) - A water (0.01% ammonium formate) was used as the mobile phase during the following gradient elution procedure for 14 min: 0 min, 50% B; 5 min, 100% B; 8 min, 100% B; 8.1 min: 50% B. Flow rate: 0.3 mL/min. With the column temperature at 40°C, the detection wavelength was adjusted to 218 nm.

A total of 48 SPF-grade female MRL/lpr mice and 8 SPF-grade female C57BL/6 mice (6 weeks old) were purchased from Shanghai Slac Laboratory Animal Co., Ltd. (Animal license number: SCXK [Hu] 2022-0004). All mice were housed in the animal facility of the First Affiliated Hospital of Anhui University of Chinese Medicine, where the temperature was maintained at 23 ± 2°C, humidity was kept between 40–60%, and a 12-hour light/dark cycle was followed. Adaptive feeding was conducted for 2 weeks before the start of the experiments. 48 MRL/lpr mice were randomly divided into six groups with eight mice: model group, low-dose JPZS group (6.305 g/kg, JPZS-L), medium-dose JPZS group (12.61 g/Kg, JPZS-M), high-dose JPZS group (25.22 g/kg, JPZS-H), 5-aza-CdR inhibitor group, and DC_517 inhibitor group, with eight mice in each group. eight female C57BL/6 mice were used as controls. JPZS group (Low, medium, and high doses) is administered with corresponding doses of JPZS, the control, model, 5-aza-CdR inhibitor, and DC_517 inhibitor groups were given the same volume of physiological saline solution, once a day for 8 weeks.

5-Aza-2-deoxycytidine (Selleck, cat. S1200) is a DNMT inhibitor while DC_517 (DAC; MCE, cat. HY-A0004) is a DNMT1 inhibitor. The 5-aza-CdR inhibitor group and DC_517 inhibitor group mice were intraperitoneally injected with 5-aza-CdR inhibitor (0.2 mg/mL) and DC_517 inhibitor (1.7 μM) 200 µL respectively, administered once every 2 days, starting from week 5 and lasting for 4 weeks. The control group, model group, and JPZS group were intraperitoneally injected with an equal volume of physiological saline. After 8 weeks of treatment, fresh blood samples were collected from the orbit and fresh spleen for further analysis. Initially, there were 8 mice in each group. Due to insufficient tissue quantity, technical limitations or outlier elimination in some samples during detection, the actual n value of different experiments was different. All reported n values represent the number of independent biological repeats actually included in statistics. All animal procedures were approved by the Animal Ethics Committee of Anhui University of Chinese Medicine (AHUCM-mouse-2022130).

To detect Th17 cells, 100 μL of fresh mouse whole blood or a suspension containing 1×10⁶ single-spleen-cells were taken and placed in a flow cytometry tube. Monoclonal antibodies such as CD4 (BioLegend, 100510) and IL-17A (BioLegend, 506903) were added, vortexed, and stained in dark at 4°C for 15 min. Following staining, 1 mL of hemolysin was added and incubated in the dark for 15 minutes. To detect Treg cells, 100 μL of fresh mouse whole blood or a suspension containing 1×10⁶ single-spleen-cells were taken and placed in a flow cytometry tube. Monoclonal antibodies such as CD4 (BioLegend, 100510), CD25 (BioLegend, 102027), and Foxp3 (BioLegend, 320011) were added, vortexed, and stained in dark at 4°C for 15 min. After staining, 1 mL of hemolysin was added and incubated for 15 min in the dark (27, 28). Cell detection was performed using CytoFLEX flow cytometry (Beckman Coulter, Brea, CytoFLEX, USA), and the data were analyzed with FlowJo software (BD Biosciences, Franklin Lakes, NJ, USA).

Suspensions of mouse splenocytes were prepared under aseptic conditions. Subsequently, CD4⁺ T cells were isolated from the freshly prepared splenocyte suspension using the magnetic-activated cell sorting method (Miltenyi, Germany, 130-104-454), following a negative selection strategy as per the manufacturer’s instructions. Isolated CD4⁺ T cells were collected and preserved for subsequent analyses, including quantitative real-time PCR (qPCR), western blotting (WB), flow cytometry, and measurement of DNA methylation levels.

Subsequent methylation analysis of the Foxp3 gene was performed on CD4+T cells from five experimental groups: Control (n=4 mice), Model and Model+JPZS (n=8 each), and Model+5-Aza-CdR and Model+DC-517 (n=5 each). Genomic DNA was extracted from CD4+T cells using the TIANamp Genomic DNA Kit (Tiangen Biotech, China; Cat. DP304), followed by bisulfite conversion with the EZ DNA Methylation-Gold™ Kit (Zymo Research, USA) per manufacturer protocols. Methylation levels of cytosine-phosphate-guanine (CpG) dinucleotides within the Foxp3 transcription start site region were quantified via MethylTarget™ targeted bisulfite sequencing (Genesky Biotech, China) using primers designed with FastTarget V4.1 software (Genesky, China): Foxp3-TSDR forward 5′-TTGGGTTTTTTTGGTATTTAAGA-3′ and reverse 5′-AAATCTACATCTAAACCCTATTATCACAA-3′. Bisulfite-converted DNA underwent PCR amplification followed by high-throughput sequencing on the Illumina HiSeq 2500 platform (Illumina, USA) with 150-bp paired-end reads.

Total RNA was isolated from CD4⁺ T cells using a TRIzol kit (Life Technologies, cat. 15596018). cDNA was generated using the PrimeScript™RT reagent Kit with gDNA Eraser (TaKaRa, cat. RR047A). qPCR was performed using the Novostart SYBR qPCR SuperMix Plus Kit (Novoprotein, E096-01B) and detected using a PikoReal PCR cycler (Thermo Fisher Scientific, PIKOREAL 96) (29). The primer sequences were as follows: Foxp3, primer-F 5′-TGCCCATCTCTGTCTCAATC-3′ and primer-R 5′-GAAGTTGCTGCTTTAGGTGG-3′; β-actin, primer-F 5′-AGTGTGACGTTGACATCCGT-3′ and primer-R 5′-TGCTAGGAGCCAGAGCAGTA-3′; Dnmt1, primer-F 5′-ACAGTGACACCCTTTCAGTT-3′ and primer-R 5′-TCTGTGTCTACAACTCTGCG-3′; RORγt, primer-F 5′-TGGCACACAATCTCTTCCTT-3′ and primer-R 5′-CGGTCCTCTGCTTCTCTTAG-3′.

Using RIPA lysis buffer (Beyotime, P0013B), CD4⁺ T cells were lysed and centrifuged at 14,000 rpm for 15 minutes to extract total protein. Protein levels were measured with the BCA Protein Assay Kit (Beyotime, P00150). Gels were created following the guidelines provided by the SDS-PAGE Gel Preparation Kit (Beyotime, PG111). Using SDS-polyacrylamide gels (10% SDS), proteins were separated and transferred onto polyvinylidene fluoride membranes. After transferring, the membranes were treated with a 10% skim milk solution in Tris-buffered saline with Tween and then exposed to primary antibodies targeting Dnmt1 (1:1000, Bioss Inc, bs-0678R) at 4°C for 12 hours. A horseradish peroxidase-conjugated secondary antibody (1:20000; Zsbio) was then applied to the membranes for 1 hour. GAPDH antibody (1:5000; Zsbio) was used as the reference protein for normalization. After washing with TTBS, signals were detected using an ECL detection kit (Thermo, 340958). The obtained data were analyzed using ImageJ software.

Following the manufacturer’s guidelines, serum levels of IL-17, IL-23, TGF-β1, and IFN-γ, anti-dsDNA antibodies, Immunoglobulin G (IgG) and C3 were measured using an enzyme-linked immunosorbent assay (ELISA) kit. The IL-17 (JYM0554Mo), IL-23 (JYM0394Mo), TGF-β1 (JYM0215Mo), IFN-γ (JYM0540Mo), anti-dsDNA antibodies (JYM1061Mo), IgG (JYM0031Mo) and C3 antibodies (JYM0293Mo) ELISA kits were purchased from Wuhan Gene Beauty Biotechnology Co., Ltd. The absorbance values were measured at a wavelength of 450 nm using a microplate reader (Rayto RT-6000, China). To determine Dnmt1, Dnmt3A, and Dnmt3B enzyme activity, nuclear proteins from CD4⁺ T cells were purified using a nuclear extraction kit (Epigentek, Brooklyn, NY, USA). EpiQuik DNMT assay kit (Epigentek, Brooklyn, NY, USA) was used to assess the enzyme activity of Dnmt1, Dnmt3A, and Dnmt3B.

Mouse spleen tissues (4 μM) were sectioned and subjected to immunofluorescence staining. Sections were treated with mouse anti-FOXP3 (Santa, sc-53876) and anti-IL-17A antibodies (Bioss, bs-2140R) and incubated for 60 minutes at 37°C. The sections were then incubated for 30 minutes in a dark 37°C incubator using immunofluorescence secondary antibodies (goat anti-rabbit IgG [FITC] and goat anti-mouse IgG [CY3]/1:400). Nuclei were counterstained with DAPI. The images were captured using a panoramic MIDI scanner (3DHISTECH, Budapest, Hungary).

Statistical analyses were performed using IBM SPSS software (version 26.0; IBM, Armonk, NY, USA), and graphs were created using GraphPad Prism 8.0 software (GraphPad Software Inc., San Diego, CA, USA). Student’s t-tests were used to compare data between two groups. A one-way analysis of variance followed by Tukey’s post-hoc test was used to assess statistical significance among multiple groups. Statistical significance was set at P<0.05.

The chromatogram of the mixed standard and JPZS is shown in Figure 1 . The chemical components of the JPZS samples were analyzed using HPLC-MS. In a negative ion mode, we could detect the existence of gallic acid (found at 169.1 m/z), acteoside (623.15 m/z), catechin (289.1 m/z), hyperoside (463.05 m/z), rutin (609.1 m/z), quercetin (301 m/z), tiliroside (593.1 m/z), kaempferol (284.85 m/z), formononetin (267.05 m/z), astragaloside A (829.25 m/z), dioscin (913.4 m/z), and pachymic acid (527.35 m/z). In a positive ion mode, we could detect the existence of 5-hydroxymethylfurfural (found at 127.1 m/z), atractylenolide III (249.1 m/z), atractylone (217.25 m/z), and atractylodin (183.15 m/z).While this analysis confirmed the presence of key bioactive constituents previously associated with immunomodulation, future studies employing untargeted metabolomic approaches (e.g., UPLC-QTOF-MS/MS) will be undertaken to comprehensively characterize the entire chemical profile of JPZS, including potential minor yet potent components.

Female MRL/lpr mice (6-weeks-old) were acclimatized for 2 weeks and randomly allocated to six groups (n=8/group).MRL/lpr mice were administered saline, JPZS at low/medium/high doses (6.305/12.61/25.22 g/kg/day), 5-aza-CdR (0.2 mg/mL intraperitoneal injection), or DC_517 (1.7 μM intraperitoneal injection) from Week 8 to Week 16 ( Figure 2A ), with C57BL/6 mice serving as the healthy control group. All mice were sacrificed at Week 8 for serum and spleen analyses. To investigate the effect of JPZS on the disease progression of MRL/lpr mice, we measured the levels of cytokines (TGF-β, IFN-γ, IL-17, and IL-23), dsDNA, IgG, and C3 in the mouse serum. TGF-β levels declined significantly in the model group (P <0.01), while IFN-γ, IL-17, and IL-23 levels increased significantly (P <0.01) ( Figures 2B–E ). TGF-β levels increased significantly following JPZS intervention (P <0.01), while IFN-γ, IL-17, and IL-23 levels decreased significantly (P <0.01). Compared to the normal control group, the spleen index of the model group was significantly higher, but decreased significantly after the intervention (P <0.01) ( Figure 2I ). Immune system disorders in SLE are characterized by increased dsDNA and IgG levels and decreased C3 levels (30, 31). Figures 2F, H show that the levels of dsDNA and IgG in the serum of the model group were significantly elevated (P<0.01). After JPZS intervention, both dsDNA and IgG levels decreased significantly in a dose-dependent manner (P<0.01). As shown in Figure 2G , C3 levels in the serum of the model group were significantly reduced. Following JPZS intervention, C3 levels significantly increased in a dose-dependent manner (P<0.01). Compared to the normal control group, the spleen index of the model group was significantly elevated; however, after JPZS intervention, it decreased significantly in a dose-dependent manner (P<0.01) ( Figure 2I ). These data confirm that JPZS effectively alleviated disease progression in MRL/lpr mice, with JPZS-H demonstrating the most significant effects.

The Th17/Treg ratio can directly reflect the autoimmune status of SLE (32, 33). As demonstrated in Figures 3A–D , the proportion of Th17 cells in the spleen of the model group mice significantly increased, while the proportion of Treg cells significantly decreased (P <0.01); JPZS intervention resulted in a dose-dependent reduction in the proportion of Th17 cells and an increase in the proportion of Treg cells (P <0.01). We further observed FOXP3/IL-17A in the spleen using an immunofluorescence assay ( Figures 3G, H ) and found that it was consistent with the flow cytometry results. The expression of the transcription factors RORγt and Foxp3 mRNA in CD4⁺ T cells was further analyzed based on these findings. We observed that mRNA levels of RORγt in CD4⁺ T cells from the model group were elevated compared to the control group, while the transcription level of Foxp3 mRNA was significantly reduced (P <0.01). After JPZS intervention, these changes were reversed in a dose-dependent manner ( Figures 3E, F ). As shown in Figures 1 , 2 , the imbalance in the Treg/Th17 ratio is associated with disease progression in SLE, and JPZS effectively alleviates disease progression in MRL/lpr mice. Additionally, the effects of JPZS were dose-dependent, with JPZS-H demonstrating the most significant improvement in disease condition; therefore, subsequent studies will utilize high doses of JPZS for further investigation.

To investigate the DNA methylation reduction effect of JPZS on the TSDR region of Foxp3, we used Methylation-specific PCR (MSP) sequencing to analyze the average Foxp3 methylation levels in the CD4⁺ T cells in each group. There were 10 CpG loci in the TSDR region of Foxp3 in the CD4⁺ T cells of MRL/lpr mice in the model group ( Figure 4A ). As demonstrated in Figure 4B , the level of Foxp3 methylation in the peripheral blood CD4⁺ T cells of the model group mice significantly increased, while after intervention with JPZS and 5-aza-CdR (DNMT inhibitor), the Foxp3 methylation level significantly decreased (P <0.01). Figure 4C also indicates that the methylation levels of the 10 CpG sites in the TSDR region of the Foxp3 gene in the model group were significantly increased, while the methylation levels of the 10 CpG sites were significantly downregulated after JPZS and 5-aza-CdR intervention (P <0.01). We found that the transcription level of Foxp3 mRNA was significantly upregulated after 5-aza-CdR intervention (P <0.01) ( Figure 4D ). The above experiments indicate that JPZS has a reducing effect on Foxp3-TSDR methylation, whereas the regulation of DNMT can mediate Foxp3-TSDR demethylation.

Mammals have three types of DNMTs with catalytic activity: DNMT1, DNMT3A, and DNMT3B. We further investigated whether DNMT is dependent on the demethylation of Foxp3 in CD4⁺ T cells. First, we determined the enzymatic activity of DNMT1, DNMT3A, and DNMT3B. As demonstrated in Figure 4E , the activity of all three enzymes in the model group was upregulated, whereas the activity was significantly reduced after 5-aza-CdR intervention (P <0.01). DC_517 is a Dnmt1-specific inhibitor, and after DC_517 intervention, only DNMT1 enzyme activity significantly decreased (P <0.01) ( Figure 4F ). We further investigated and found that after DC_517 intervention, the expression of DNMT1 protein was significantly reduced (P <0.01) ( Figure 4G ), and the transcription level of Foxp3 mRNA was significantly upregulated (P <0.01) ( Figure 4H ).

After confirming that Foxp3-TSDR methylation primarily relies on Dnmt1 mediation, we further examined whether the effect of JPZS on Foxp3-TSDR methylation also depends on Dnmt1 mediation. Figures 5A, B show that after JPZS intervention, Dnmt1 activity and DNMT1 protein expression levels were significantly lower (P <0.01). Foxp3-TSDR methylation levels decreased significantly ( Figure 5C ) following DC_517 intervention ( Figure 5C ). Simultaneously, the methylation levels of CpG1, CpG3, CpG7, CpG9, and CpG10 at the 10 CpG sites of Foxp3-TSDR were significantly reduced (P <0.05; P <0.01) ( Figure 5D ), Foxp3 mRNA level significantly upregulated (P <0.01) ( Figure 5E ), which was consistent with the trend observed after JPZS intervention. These results indicate that JPZS reduces Foxp3-TSDR methylation, mainly through Dnmt1 mediation.

We investigated whether JPZS promoted the Treg/Th17 balance by inhibiting DNMT1-mediated Foxp3 methylation. In Figures 6A–C , compared with the model group, the proportion of Th17 cells to CD4⁺ T cells decreased in the model+DC_517 group, while the proportion of Treg cells to CD4⁺ CD25⁺ T cells increased (P <0.05). The above experimental results are consistent with the effect of the model+JPZS group on the distribution of Tregs and Th17 cell subsets in CD4⁺ T cells of MRL/lpr mice in Figures 3A–C .

Figures 6D, E shows that, in comparison with the model group, the transcription level of RORγt mRNA was significantly reduced in the model+DC_517 group peripheral blood CD4⁺ T cells, while Foxp3 mRNA was significantly increased (P <0.05). These results are consistent effect of JPZS on the transcription levels of Foxp3 and RORγt mRNA in the peripheral blood CD4⁺ T cells of MRL/lpr mice in Figures 3F, G .

As shown in Figure 6F , the serum concentrations of TGF-β1 were higher in the model+JPZS and model+DC_517 groups of mice compared to the model group (P <0.01), whereas the levels of IFN-γ, IL-17, and IL-23 were lower (P <0.01). This indicate that JPZS and DC_517 have similar effects on the levels of cytokines in the serum of MRL/lpr mice, both promoting the production of anti-inflammatory factors and inhibiting inflammatory responses.

As shown in Figures 6G–I , compared with the model group, the levels of IgG and dsDNA in the serum of MRL/lpr mice in the model+JPZS and model+DC_517 groups were significantly reduced (P <0.01), whereas the levels of C3 were significantly increased (P <0.01), indicating that both DC_517 and JPZS can improve disease activity in MRL/lpr mice by reducing IgG and dsDNA levels and increasing C3 levels.