Dextran sulfate sodium salt (DSS) was obtained from MP Biomedicals. All of the herbs were purchased from Shaanxi Xingshengde Pharmaceutical Co., Ltd. (Xi’an, China). Primary antibodies tumor necrosis factor-α (TNF-α), interleukin-10 (IL-10), transforming growth factor-β1 (TGF-β), arginase-1 (Arg-1), and F4/80 were purchased from Affinity Biosciences (OH, United States). Primary antibodies interleukin-1 (IL-1β), interleukin-6 (IL-6), extracellular regulated proteinhnase1/2 (Erk1/2), phosphorylated extracellular regulated proteinhnase1/2 (p-Erk1/2), p38mitogen-activated protein kinases (p38MAPK), phosphorylated p38mitogen-activated protein kinases (p-p38MAPK), inhibitor kappa B alpha (IkBα), signal transducers and activators of transcription-6 (STAT-6), and phosphorylated nuclear factor-kappa Bp65 (p-NF-kBp65) were purchased from Cell Signaling Technology (Beverly, MA, United States). Primary antibodies phosphorylated inhibitor kappa B alpha (p-IkBα), nuclear factor-kappa Bp65 (NF-kBp65), c-jun N-terminal kinase1/2 (JNK1/2), phosphorylated c-jun N-terminal kinase1/2 (p-JNK1/2), and phosphorylated signal transducers and activators of transcription-6 (p-STAT-6) were purchased from Abcam (Cambridge, MA, United States). Primary antibodies CD206 and CD80 were purchased from Santa Cruz (Santa Cruz, CA, United States). APC anti-mouse F4/80 antibody, FITC anti-mouse CD80 antibody, and PE anti-mouse CD206 (MMR) antibody were purchased from Biolegend (San Diego, CA, United States). The secondary antibodies were purchased from Boster (Wuhan, China), and enzyme-linked immunosorbent assay (ELISA) kits for IL-6, IL-1β, TNF-α, and interferon regulatory factor 5 (IRF-5) were purchased from Elabscience Biotechnology (Wuhan, China). All reagents and chemicals were of analytical grade.

The composition of WMW is shown in Table 1. The identification and deposition of the herbs and the preparation of WMW were completed by the College of Pharmacy, Shaanxi University of Chinese Medicine. Briefly, crude herbs were macerated in 80% aqueous ethanol for 2 h and then heated to reflux twice in a water bath (1 h each time). Then, the filtered and mixed suspensions were collected and concentrated. Finally, the extract mixture was vacuum dried for reserve.

HPLC fingerprinting analysis was used to verify the main chemical constituents of the WMW extract. The extracts were dissolved in water at a concentration of 3.6 g/ml (w/v) and further diluted with methanol water (50:50) to 1.8 g/ml (w/v). Samples were separated on an Agilent ZORBAX SB-C18 column (250 mm × 4.6 mm, 5.0 μm) with a mobile phase consisting of A (Methanol)-B (0.1% phosphoric acid) (0.0–120.0 min, 8%–65% A; 120.0–121.0 min, 65%–8% A; 121.0–130 min, 8% A) at a flow rate of 1.0 ml/min with gradient elution. The column temperature was set at 30°C, the injection volume was 10 μL, and the detection wavelength was set to 242 nm.

Male C57BL/6 mice (20–23 g, aged 6–8 weeks) were obtained from Changzhou Cavens Laboratory Animals Co., LTD. (Jiangsu, China) with license No. SCXK (SU) 2016–0010. All mice were housed under specific pathogen-free conditions. The mice received humane care in accordance with the Shaanxi University of Chinese Medicine Animal Care Committee guidelines.

To induce acute colitis, mice were given drinking water containing 2.5% DSS for 1 week, followed by normal drinking water for 1 week. The mice were randomly divided into four groups: normal control group (NC, 10 ml/kg, 0.9% saline), model control group (MC, 10 ml/kg, 0.9% saline), and WMW group (WMW, 27 g/kg, 54 g/kg, weight ratio between crude drug and mice). The schematic diagram is presented in Figure 2A. To induce chronic colitis, mice received DSS (2.5% w/v) dissolved in drinking water. The mice were subjected to four cycles of DSS. Each cycle included 1 week of DSS administration followed by 1 week of recovery with normal drinking water (Sun et al., 2020). The mice were randomly divided into three groups: normal control group (NC; 10 ml/kg, 0.9% saline), model control group (MC; 10 ml/kg, 0.9% saline), and WMW group (WMW: 54 g/kg, weight ratio between crude drug and mice). The schematic diagram is presented in Figure 3A.

To evaluate the severity of colitis, body weight, fecal occult blood, and fecal consistency were examined every week to generate a disease activity index (DAI) score (Table 2). All mice were sacrificed, the serum and colon were collected, and the length of the colon was measured.

To observe morphological and mucus secretion changes in the colon, colon sections were subjected to hematoxylin and eosin (H&E) and periodic acid Schiff (PAS) staining. Samples were dehydrated and embedded in paraffin and sectioned (3 μm) after fixation in a 4% formaldehyde solution for 12 h. Images were collected using an optical microscope. The tissue expression of neutral mucins in goblet cells was determined as a function of PAS staining. Histological scores were examined according to previously studies (Table 3) (Kiyohara et al., 2018).

Paraformaldehyde-fixed colon slides were dewaxed and rehydrated according to the standard protocol. Subsequently, endogenous peroxidase activity was blocked with a 3% H2O2 solution after antigen retrieval. Then, the slides were blocked with 10% normal goat serum for 30 min. The sections were incubated with Rabbit anti-F4/80 (1:100) overnight at 4°C and biotinylated secondary antibody (1:100), for 30 min. Boundper oxidase was visualized after a 3,3 diaminobenzidine reaction for 25 min and after light counterstaining with hematoxylin, dehydration, and mounting. Images were collected using a fluorescent microscope (Olympus BX53, Shinjukuku, Tokyo, Japan).

The 4% paraformaldehyde-fixed colon was cut into 3-µm sections for double immunostaining analysis. The sections were incubated with primary antibody (CD206, CD80, IL-10, IL-1β, all at 1:50 dilutions) overnight at 4°C in the dark and FITC-labeled and Cy3-labeled secondary antibody (1:100) for 1 h. DAPI (1:1,000) was used to counterstain the nuclei for 5 min, and the slides were mounted on cover slips with an anti-fade mounting medium. Images were collected using a fluorescent microscope (Olympus BX53, Shinjukuku, Tokyo, Japan).

The mice were anesthetized and sacrificed at the end of the experiment. Serum was obtained after centrifugation at 3,000 rpm for 15 min. Levels of IL-6, IL-1β, TNF-α, IRF-5 were determined using ELISA kits according to the manufacturer’s protocol.

The colon tissue was lysed and homogenized in radio immunoprecipitation assay (RIPA) buffer containing 1% phenylmethylsulfonyl fluoride (PMSF) and phosphatase inhibitors. The homogenate was then lysed on ice for 30 min and centrifuged at 12,000 g for 5 min at 4°C. The protein concentration was determined by the bicinchoninic acid (BCA) method. The proteins (40 μg/lane) were separated by 10% sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS/PAGE) and transferred to PVDF membranes for 2 h (Millipore, Billerica, MA, United States). After blocking with 5% nonfat milk in TBST for 2 h, the membrane was incubated with primary antibody (IL-1β, TNF-α,IL-6, IL-10, TGF-β, Arg-1, Erk1/2, p38MAPK, p-p38MAPK, IkBα, p-IkBα, p-NF-kBp65, JNK1/2, STAT-6, p-STAT-6,β-actin all at 1:1,000 dilutions; p-Erk1/2, NF-kBp65, p-JNK1/2 all at 1:2000 dilutions) at 4°C overnight. Secondary antibodies against HRP-conjugated rabbit or mouse IgG (dilution 1:5,000, Boster, Wuhan, China) were added for 2 h at 37°C. An enhanced chemiluminescence plus detection system (Glyko Biomedical Limited, United States) was used for detection, and Band Scan software was used to analyze the optical density of the bands.

Total RNA from colon tissue was extracted with TRIzol reagent (Ambion, CA, United States). cDNA synthesis was accomplished with HiScript® II Q RT SuperMix for qPCR (VAZYME, Nanjing, China). Quantitative real-time PCR was performed on an ABI QuantStudio 6 (Applied Biosystems, Waltham, MA). Relative mRNA expression was determined by the 2^−ΔΔCt method, with β-actin as the internal control. The primer sequences used for PCR are listed in Table 4.

Fresh colon tissues were harvested, minced, and then digested with a 0.5% collagenase (Yuanye Bio, Shanghai, China) and 0.25% trypsin solution (Procell, Wuhan, China), filtered, cleaned, and centrifuged to obtain single cells. Single cell suspensions were stained and fluorescently conjugated against mouse CD80, CD206, and F4/80 at the recommended dilutions for 30 min at 4°C in the dark. Each flow tube contained 1 ml of 0.5% bovine serum albumin (BSA) PBS and 1 × 10⁶ cells, Cells were detected using a Beckmancoulter Cyto FLEX and analyzed with FlowJo software.

The chemical composition information in WMW was collected from the published literature (Wu et al., 2020a; Jiang et al., 2020; Wu MM. et al., 2021) as well as from the Traditional Chinese Medicine Systems Pharmacology (TCMSP, https://tcmspw.com/tcmsp.php) database. According to the pharmacokinetic parameters of absorption, distribution, metabolism, and excretion (ADME), compounds with oral bioavailability (OB) ≥ 30% and drug likeness (DL) ≥ 0.18 were selected for further research. The potential targets of the abovementioned compounds were collected from the Swiss Target Prediction (http://www.swisst-argetprediction.ch/) website. Targets related to “ulcerative colitis” were found in the pharmGKB database (https://www.pharmgkb.org/), Uniprot database (https://www.uniprot.org/), DisGeNET database (http://www.dis-genet.org/home/), OMIM database (https://www.omim.org/), DrugBank database (https://www.drugbank.ca/), and TTD database (http://db.idrblab.net/ttd/). Information regarding the intersection of WMW and disease targets was obtained from the Venny database (Venny 2.1.0), and the intersection targets were imported into the STRING database (https://string-db.org/) to determine the protein interaction relationship using Cytoscape 3.7.1 software for protein–protein interaction (PPI) analysis. Genes whose degree, betweenness centrality, and closeness centrality were greater than their respective medians were selected as core target genes. The DAVID database (NCIFCrf.gov) was used for the KEGG pathway enrichment analysis. The bubble map of the first 20 channels was generated using the bioinformatics. com.cn website.

The statistical analysis was performed using GraphPad Prism 7.0 (San Diego, CA, United States). Data are presented as the mean ± SD and were analyzed using an unpaired Student’s t test and a one-way analysis of variance (commonly known as an ANOVA). A p-value of <0.05 was considered to indicate statistical significance.

The HPLC results are shown in Figures 1A–C. A total of eleven chemical components in WMW were determined, including citric acid, phellodendrine, ferulic acid, coptisine, jatrorrhizine, berberine, hesperidin, cinnamaldehyde, aconitine, ginsenoside Rb1, and 6-gingerol.

To observe the effects of WMW on DSS-induced chronic UC in mice, mice were allowed ad libitum access to DSS for four cycles to construct a chronic UC model. At the end of the third cycle (week 6), gavage was carried out with a WMW dose of 54 g/kg. Mouse weight was measured and DAI scoring was performed once every week. In weeks 7, 8, and 9, colon length was measured and a statistical analysis of weight and DAI data was conducted (Figure 3A). As expected, compared with the model group, the results in the treatment group showed that WMW can prevent weight loss in colitis mice (Figure 3C) and decrease DAI (Figure 3D). As the dosing period increased, this effect became more significant. Similarly, the colon length of mice in the WMW group was significantly longer than in the model group (Figure 3B). This indicates that WMW can alleviate DSS-induced chronic UC in mice.

To observe the effects of WMW on colonic tissue damage in DSS-induced chronic colitis in mice, we carried out H&E and PAS staining of mouse colonic tissues and conducted histopathological scoring of the results. The mean number of goblet cells in every crypt was enumerated. Immunohistochemistry and flow cytometry were used to measure macrophage infiltration and counts in inflammation sites. The H&E staining analysis results showed that colitis mice developed typical inflammatory cell infiltration and crypt damage. The aforementioned pathological presentations in the WMW group significantly improved, and the histopathological score of the WMW group was lower than that of the model group (Figure 4A). PAS staining analysis showed that the goblet cell count in the colons of colitis mice significantly decreased and that mucosal secretion decreased. In the WMW group, goblet cell count significantly increased, and mucosal secretion also increased (Figure 4B). The immunohistochemical results showed extensive infiltration of F4/80-positive macrophages in the colonic mucosa and infiltration even in the muscular layer. The flow cytometry results further proved that the number of activated macrophages was significantly increased in inflammatory damage sites. After WMW treatment, the number of F4/80-positive macrophages in inflammatory damage sites gradually decreased, and the degree of infiltration gradually decreased (Figures 4C,D). These changes became more significant as the treatment duration increased. These data show that WMW could alleviate intestinal inflammation and tissue damage in DSS-induced colitis mice.

To observe the effects of WMW on intestinal inflammation in DSS-induced colitis mice, we utilized quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western blot to measure the levels of pro-inflammatory factors TNF-α, IL-1β, and IL-6 and anti-inflammatory factors IL-10, Arg-1, and TGF-β1 in serum and colon tissues. The results showed that, compared with the control group, the levels and expression of pro-inflammatory factors TNF-α, IL-1β, and IL-6 in colon tissues from colitis mice were significantly increased. Compared with the model group, the WMW treatment group had significantly decreased levels and expression of these factors (Figure 5A). Compared with the control group, the levels and expression of anti-inflammatory factors IL-10, Arg-1, and TGF-β1 in colon tissues were increased in the treatment group. This finding is consistent with the results reported in the literature showing that the release of considerable amounts of pro-inflammatory factors worsens inflammation. However, the body also secretes anti-inflammatory factors to alleviate the damage caused by these pro-inflammatory factors (Cao et al., 2019). After WMW treatment, the levels and expression of IL-10, Arg-1, and TGF-β1 were further increased. These effects became more significant as the treatment duration increased (Figure 5B). Thus, WMW can inhibit the secretion of pro-inflammatory factors and promote the secretion of anti-inflammatory factors. Inflammatory factors are intimately associated with UC pathogenesis, in which macrophages are the major immune cells secreting inflammatory factors. Macrophages can be a double-edged sword, depending on their phenotype, as they can secrete pro-inflammatory factors that aggravate inflammation but also anti-inflammatory factors that alleviate inflammation (Locati et al., 2020). This result shows that WMW participates in the regulation of macrophage activation and phenotype.

To study whether the effects of WMW on inflammatory factors are related to macrophage M1/M2 polarization, we employed double immunofluorescence to observe the co-expression of M1 macrophages and related pro-inflammatory factor IL-1β and of M2 macrophages and anti-inflammatory factor IL-10. CD80 was used as a marker for M1-positive macrophages, and CD206 was used as a marker for M2-positive macrophages. The CD80 and IL-1β double immunofluorescence results showed that, in the control group, there was minimal CD80 expression, and IL-1β was not expressed. In the model group, CD80 and IL-1 co-expression was significantly increased. Compared with the model group, CD80 and IL-1β co-expression was gradually reduced in the WMW group in direct proportion to the treatment duration (Figure 6A). This result shows that the pro-inflammatory factor IL-1β is secreted by M1-polarized macrophages and that WMW could inhibit M1 macrophage polarization and secretion of the pro-inflammatory factor IL-1β. In the control group, the CD206 and IL-10 double immunofluorescence results showed that there was minimal CD206 expression, and IL-10 was not expressed. In the model group, CD206 and IL-10 co-expression increased. Compared with the model group, CD206 and IL-10 co-expression was further increased in the WMW group in direct proportion to the treatment duration (Figure 6B). This result shows that the anti-inflammatory factor IL-10 is secreted by M2-polarized macrophages and that WMW could promote M2 macrophage polarization and secretion of the anti-inflammatory factor IL-10. Hence, WMW can promote the conversion of colonic M1 macrophages to M2 in DSS-induced colitis mice and simultaneously inhibit the activation of pro-inflammatory factors and promote the activation of anti-inflammatory factors.

To further study the effects of WMW on the M1/M2 macrophage ratio in colonic tissues from DSS-induced mouse colitis, we employed flow cytometry to measure the proportions of M1 and M2 macrophages. F4/80 was used as a macrophage marker, CD80 was used as a marker for M1-positive macrophages, and CD206 was used as a marker for M2-positive macrophages. The results showed that, compared with the control group, the percentage of CD80-labeled M1-positive macrophages was significantly increased in colonic tissues from the colitis mouse group, reaching a peak at week 7 and persisting until week 9. The percentage of CD206-labeled M2-positive macrophages significantly increased. After WMW treatment, the percentage of CD80-labeled M1-positive macrophages gradually decreased and was inversely proportional to the treatment duration (Figure 7A), while the percentage of CD206-labeled M2-positive macrophages further increased in direct proportion to the treatment duration (Figure 7B). To intuitively reflect the inhibition of macrophage M1 polarization and promotion of M2 polarization by WMW through the reduction of colonic and serum pro-inflammatory factor levels and increase of anti-inflammatory factor levels, we calculated the M1/M2 macrophage ratio at different time points. The proportion of M1 macrophages was far higher than that of M2 macrophages in the model group. After WMW treatment, the ratio of M2 macrophages gradually increased, while that of M1 macrophages gradually decreased as the treatment duration increased (Figure 7C). These data further prove that WMW could inhibit M1 polarization and promote M2 polarization in colonic macrophages in DSS-induced colitis mice.

To examine the therapeutic effector mechanism of WMW in UC, we employed network pharmacology to analyze the potential effector targets of WMW in UC. The results showed that there were 43 cross-targets between WMW and UC (Figure 8A). Protein–protein interaction (PPI) network analysis of the 43 cross-targets found that WMW acts on 13 core target genes in DSS-induced UC (Figures 8B,C). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis results showed that nine core target genes were enriched in cytokine and cytokine receptor interactions, six target genes were enriched in the mitogen-activated protein kinase (MAPK) pathway, and five target genes were enriched in the NF-κB pathway (Figure 8D). The results showed that WMW may treat DSS-induced UC through multiple pathways and multiple targets and that the MAPK and NF-κB pathways may be intimately associated with DSS-induced UC.

Based on the network pharmacology analysis results, we further verified changes in the MAPK and NF-κB pathways and core target-related pathways in DSS-induced UC. The results showed that MAPK and NF-κB are core pathways in macrophage M1 polarization, while STAT6 participates in macrophage M2 polarization (Murray, 2017). We employed Western blotting to measure changes in the protein levels of P38MAPK, jun N-terminal kinase (JNK), and extracellular signal-regulated kinase (ERK) in the MAPK signaling pathway and related proteins in the NF-κB and STAT6 signaling pathways. The Western blotting results showed that NF-κBp65, P38 MAPK, ERK1/2, and JNK1/2 expression and phosphorylation were significantly increased in the model group, IκBα protein expression was significantly decreased and phosphorylation significantly increased (Figures 9A,B), and STAT6 protein expression and phosphorylation were increased (Figure 9C). These changes were directly proportional to the model construction duration. After WMW intervention, the expression and phosphorylation of NF-κBp65 and P38 MAPK gradually decreased with the treatment duration, while IκBα protein expression gradually increased and phosphorylated IκBα gradually decreased. STAT6 protein expression and phosphorylation also significantly increased, but there were no significant changes in ERK1/2 or JNK1/2 expression and phosphorylation. This shows that DSS gradually activates the P38MAPK, JNK, ERK, and NF-κB signaling pathways and that it also activates the STAT6 signaling pathway but to a lesser degree. WMW gradually inhibits the activation of the P38MAPK and NF-κB signaling pathways and further activates the STAT6 signaling pathway.