Protective Effects of the Wenfei Buqi Tongluo Formula on the Inflammation in Idiopathic Pulmonary Fibrosis through Inhibiting the TLR4/MyD88/NF‐κB Pathway

BLM and pirfenidone (PFD) were purchased from MedChemExpress (Monmouth Junction, NJ, USA). Antibodies against TLR4 (95/120 kDa, sc-293072), MyD88 (33 kDa, sc-74532), p-NF-κB p65 (65 kDa, sc-166748), and fibronectin (FN, 220 kDa, sc-8422) were purchased from Santa Cruz Biotechnology (Rosemont, IL, USA). IκBα (39 kDa, #4814) and NF-κB p65 (65 kDa, #8242) were obtained from Cell Signaling Technology (Beverly, MA, USA). Tubulin (50 kDa, 11224-1-AP) was purchased from ProteinTech (Rosemont, IL, USA).

The potential gene targets of the 13 Chinese medicines in the WBT formula were identified via network pharmacology analysis. The monomer chemicals in the WBT formula were retrieved from Traditional Chinese Medicine databases (TCMSP, http://tcmspw.com/tcmsp.php↗) [19] and Traditional Chinese Medicine Information Database (TCMID, http://www.megabionet.org/tcmid/↗) [20]. In the TCMSP database, oral bioavailability ≥30% and drug-likeness ≥0.18 were conditioned to the absorption parameters for the compound screening. To collect the potential gene targets of these components of the WBT formula, the following two databases, TCMSP and SwissTargetPrediction Database (STPD, http://old.swisstargetprediction.ch/↗), were used [21]. Then, the Universal Protein Resource Knowledgebase (UniProt Knowledgebase, http://www.uniprot.org/↗, entering at Jan 2021) was applied to unify the official gene symbol, which was a collection from the candidates above. The IPF-associated target genes were acquired from GeneCards (https://www.genecards.org/↗) [22], the screening parameter was “relevance score ≥ 4.56.” Protein-protein interaction (PPI) data were obtained from STRING (https://cn.string-db.org/↗) with parameter conditions filtered by “Homo sapiens” (confidence score > 0.9) and visualized using Cytoscape. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were enriched by using the Metascape (http://metascape.org/↗) tool.

The 13 Chinese medicines present in the WBT formula were purchased from the Hongjian Pharmacy (Changchun, China), which were deposited in the Jilin Ginseng Academy, Changchun University of Chinese Medicine (Changchun, China). Raw materials of the WBT formula were codecocted in the distilled water for 1 h twice using 10 times of the total weight of the medicine mixture to obtain the aqueous extract. After filtering and centrifuging at 3,500 rpm for 15 min, the supernatants of WBT were subjected to vacuum to obtain the powder for further experiments.

All mice (the Vital River Laboratory Animal Technology Co. Ltd, Beijing, China) were housed under standard conditions at the Experimental Animal Center, Changchun University of Chinese Medicine (Changchun, China). All experiments were approved by the Experimental Animal Administration Committee of Changchun University of Chinese Medicine (Approval No. 2021230). After three days of acclimatization, a total of 60 male C57BL/6N mice with body weight about 20 ± 2 g, aged 6–8 weeks, were randomly divided into six groups (n = 10): sham, BLM (3 mg/kg), WBT (3, 6, and 12 g/kg), and PFD (200 mg/kg) groups. The pulmonary inflammation and fibrosis model was established by intratracheal injection with BLM (3 mg/kg) under anesthesia by 0.3% pentobarbital sodium on day 0. The sham group was instilled with an equal volume of normal saline only. After BLM administration, mice were intragastrically administered with different doses of the WBT formula or PFD once a day for 7 consecutive days. On day 8, all the mice were sacrificed to collect serum, bronchoalveolar lavage fluid (BALF), and lung tissues for further analysis.

According to the instructions, the IL-6 level in the serum and TNF-α and IL-1β in BALF from the mice of different groups were determined by the enzyme-linked immunosorbent assay kit (Sinobest Bio, Shanghai, China).

The mouse lung tissue was fixed using 4% formaldehyde, was embedded in paraffin, and then was cut into the slices at 4 μm thickness. The lung sections were deparaffinized with xylene after being rehydrated in water by graded concentrations of ethanol solution. The sections were stained to estimate lung inflammation and fibrotic changes using H&E and Masson's trichrome stainings. For immunohistochemical (IHC) staining, the slides were submerged with a citric acid solution (pH 6.0, 0.01 mol/L; Servicebio, Wuhan, China) for 10 min for antigen retrieval. After incubation with 3% hydrogen peroxide for 25 min, the slides were incubated with primary antibodies against TLR4, MyD88, and p-NF-κB overnight at 4°C and secondary antibody for 1 h. The positive staining was determined with a 3,3′-diaminobenzidine substrate and counterstained with hematoxylin. Histological images were acquired using an M8 microscope (PreciPoint, Thüringen, Germany).

Proteins from mouse lung tissues were extracted, separated on 12% SDS-PAGE gels, and transferred to the PVDF membranes (Roche, Basel, Switzerland). After blocking with 5% BSA or nonfat milk for 1.5 h, the membranes were incubated with primary antibodies against TLR4, MyD88, IκBα, NF-κB p65, p-NF-κB p65, and Tubulin overnight at 4°C. After the incubation with HRP-conjugated secondary antibody (ProteinTech, IL, USA) for 1 h at room temperature, the membranes were washed three times with Tris-buffered saline with 0.1% Tween 20. The protein brands were visualized and detected using the ECL Moon kit (Beyotime Biotechnology, Shanghai, China) by a chemiluminescence detection system (ChemiDoc XRS, Bio-Rad, CA, USA). The quantification of the bands was performed using the ImageJ software (National Institutes of Health, Bethesda, MD, USA).

Data were analyzed on the Prism software version 8 (GraphPad, San Diego, CA, USA). All values are expressed as the mean ± SEM. The significant differences among the groups were evaluated by one-way ANOVA with Tukey's post hoc test. The results are accepted as the level of significance was set at P value of < 0.05.

Using the TCMSP and TCMID databases, 243 candidate compounds were found in the WBT formula. Among these components, 20, 36, 65, 10, 2, 7, 23, 10, 19, 22, 13, 7, and 9 compounds were identified in Astragalus membranaceus (Fisch.) Bunge, Scutellaria baicalensis Georgi, Bunge Salvia miltiorrhiza Bunge, Polygonum cuspidatum Siebold & Zucc, Angelica sinensis (Oliv.) Diels, Ligusticum striatum DC., Prunus persica (L.) Batsch, Pheretima aspergillum (E. Perrier), Aster tataricus L.f., Tussilago farfara L., Pinellia ternata (Thunb.) Makino, Clematis chinensis Osbeck, and Siegesbeckia orientalis L., respectively (Table 2). Among these compounds, 40 compounds with the repeated names and 38 compounds without targets were deleted to obtain 165 compounds for further analysis. In the WBT formula, 352 targets of these 165 components (Supplementary Table 1) were predicted at TCMID and STPD websites. Then, we input 352 targets into the UniProt Knowledgebase website to unify the standard nomenclature. Meanwhile, 1,531 pathogenic genes-related with IPF were collected from the databases mentioned above (Supplementary Table 2). After the overlapping analysis, 167 intersection targets, as the potential targets of the WBT formula for treating IPF, were acquired and shown in a Venn diagram (Figure 1(a)). Furthermore, two compounds not for 167 targets of IPF were screened out to obtain 163 candidate compounds. In addition, those intersection targets were used to build the network diagram of the components of the WBT formula and their targets, which were composed of 330 nodes and 999 edges (Figure 1(b) and Supplementary Table 3). Collectively, 163 candidate compounds and 167 potential targets of the WBT formula against IPF were predicted by a network pharmacology-based method.

The GO annotation and KEGG pathway enrichments for 167 overlapping targets showed the top 20 significantly enriched terms in the biological process (BP), and cell component (CC) and molecular function (MF) categories are shown in Figure 2(a) and Supplementary Figure 1. As suggested from the results, 167 key targets showed tight relations to the major BP, such as inflammatory response, response to wounding, response to oxidative stress, and regulation of cell adhesion. The WBT formula was reported for integrating multiple signaling pathways in the fibrosis process, inflammatory response, and cancers. The enrichment of target-pathway was built to delve into the mechanisms of potential targets acting on their corresponding signal pathways (Figure 2(b)). The PPI network for therapeutic targets of the WBT formula against IPF was constructed (Figure 2(c)). Furthermore, the therapeutic effect of the WBT formula on IPF was most likely achieved through modulating multiple pathways such as the PI3K-Akt, TNF, and NF-κB pathways. Among these pathways, the NF-κB pathway might be the core potential pathway of the WBT formula for inhibiting the inflammatory response, wounding response, and subsequent fibrosis. The targets of the NF-κB pathway subnetwork were built and are shown in Figure 2(d). Based on the results of the network pharmacology enrichment analysis, we further examined whether the protective effect of the WBT formula against inflammation and subsequent fibrosis were dependent on the regulation of the NF-κB-mediated inflammatory pathways.

To further validate the mechanism of the WBT formula for preventing inflammatory response during lung fibrosis, the protocol for animal group, drug administration, and mechanism experiment were designed and are visualized in Figure 3(a). As shown in Figures 3(b) and 3(c), histopathological changes with inflammatory and fibrotic responses due to BLM induction showed the gathering of multiple inflammatory cells and collagen fibrogenesis in alveolar spaces after 7 days. Alveolar infiltration in the model group was suppressed in a dose-dependent manner after treatment with the WBT formula (Figure 3(b)). Masson's trichrome staining reflected collagen accumulation, as an indicator for lung fibrosis. The newly formed collagen fibers were decreased by the treatment of the WBT formula and PFD. The WBT formula at the dose of 12 g/kg and PFD effectively inhibited the formation of collagen fiber in the alveoli (Figure 3(c)), compared to the BLM-induced group. Subsequently, we examined the content of the IL-6 level in the serum and the levels of IL-1β and TNF-α in BALF from different groups. We found that WBT or PFD treatment significantly inhibited serum IL-6 level, compared with the BLM-induced group (Figure 3(d)). Importantly, the contents of IL-1β and TNF-α in BALF induced by BLM were lower than that of WBT or PFD treatment (Figures 3(e) and 3(f)). In addition, Western blot analysis showed that the expression of FN, a key molecule involved in fibrosis, was upregulated by BLM induction, which was obviously suppressed by WBT or PFD treatment (Figures 3(g) and 3(h)). Together, these data indicated that the WBT formula can inhibit inflammatory and fibrotic responses in the BLM-induced mouse model.

To further validate the mechanism of the WBT formula for inflammatory response from the prediction, Western blot and IHC staining methods were used to analyze the NF-κB inflammatory pathway for clarifying the mechanism of the WBT formula. Western blotting revealed that IκBα was reduced by BLM, while NF-κB p-p65/p65 was upregulated in the BLM-induced lung tissues (Figures 4(a)–4(c)). WBT treatment promoted the expression of IκBα and inhibited the phosphorylation of NF-κB p65, compared with the BLM group (Figures 4(a)–4(c)). Similarly, the increased phosphorylation of NF-κB p65 induced by BLM in lung tissues was inhibited by the WBT formula according to IHC staining (Figure 4(d)). Recent studies have shown that TLR4 activity is crucial for inflammation and PF [23], which is upstream of the NF-κB pathway. MyD88 can be recruited to mediate the release of proinflammatory cytokines when the TLR4 pathway is activated [24, 25]. Therefore, we used Western blot and IHC staining to further investigate the effect of the WBT formula on the levels of TLR4 and MyD88 in the BLM-induced lung tissues. As shown in Figures 5(a)–5(c), Western blot analysis showed that BLM increased the expressions of TLR4 and MyD88 in the lung tissues, which were significantly downregulated after WBT formula intervention. For the IHC staining shown in Figure 5(d), similar results were found that WBT treatment significantly suppressed the BLM-induced increases of TLR4 and MyD88. Taken together, the WBT formula can inhibit the TLR4/MyD88/NF-κB signaling pathway to reduce inflammatory response in a BLM-induced mouse model with IPF.

The datasets used and/or investigated during the current study are available from the corresponding authors upon reasonable request.