Molecular mechanisms of An-Chuan Granule for the treatment of asthma based on a network pharmacology approach and experimental validation

Abstract

An-Chuan Granule (ACG), a traditional Chinese medicine (TCM) formula, is an effective treatment for asthma but its pharmacological mechanism remains poorly understood. In the present study, network pharmacology was applied to explore the potential mechanism of ACG in the treatment of asthma. The tumor necrosis factor (TNF), Toll-like receptor (TLR), and Th17 cell differentiation-related, nucleotide-binding oligomerization domain (NOD)-like receptor, and NF-kappaB pathways were identified as the most significant signaling pathways involved in the therapeutic effect of ACG on asthma. A mouse asthma model was established using ovalbumin (OVA) to verify the effect of ACG and the underlying mechanism. The results showed that ACG treatment not only attenuated the clinical symptoms, but also reduced inflammatory cell infiltration, mucus secretion and MUC5AC production in lung tissue of asthmatic mice. In addition, ACG treatment notably decreased the inflammatory cell numbers in bronchoalveolar lavage fluid (BALF) and the levels of pro-inflammatory cytokines (including IL-6, IL-17, IL-23, TNF-alpha, IL-1beta and TGF-beta) in lung tissue of asthmatic mice. In addition, ACG treatment remarkably down-regulated the expression of TLR4, p-P65, NLRP3, Caspase-1 and adenosquamous carcinoma (ASC) in lung tissue. Further, ACG treatment decreased the expression of receptor-related orphan receptor (RORγt) in lung tissue but increased that of Forkhead box (Foxp3). In conclusion, the above results demonstrate that ACG alleviates the severity of asthma in a ´multi-compound and multi-target' manner, which provides a basis for better understanding of the application of ACG in the treatment of asthma.

Keywords: An-Chuan Granule; Asthma; Inflammation; Network pharmacology; Th17/Treg balance.

Figure 1. Construction of the ACG compound-putative target network

The compound-putative target network was constructed by linking the candidate compounds and their putative targets, the seven herbal constituents of ACG. The nodes representing candidate compounds are shown as polychrome5 polygons and the targets are indicated by yellow squares.

Figure 2. ACG shared 31 putative targets with known pathological course related targets of asthma

(A) The active ingredients-candidate targets network was constructed by linking the overlapped targets (between ACG putative and known asthma-related) and the homologous candidate compounds of ACG. The nodes representing candidate compounds are shown as green rectangles and the targets are presented as red triangles. (B and C) 31 candidate targets were searched in Omicshare to gain more insights into their involvement in various GO terms and KEGG pathways. We considered a P-value cut-off of < 0.05 as significant and applied a hypergeometric test to identify enriched terms.

Figure 3. Effects of ACG on the behavioral scores

(A) lung index (B) wet/dry ratio of lung weight (C) lung inflammation, mucus secretion and reduced MUC5AC (D–G) in asthmatic mice. (D) Top: histopathological changes of the lung tissue were observed by HE staining. Middle: the mucus secretion in the bronchus was observed by AB-PAS staining. Bottom: immunohistochemical staining for MUC5AC. (E–G) The inflammation score, mucus secretion score and mean optical density (MOD) in each group were shown. All images are shown at 100× magnification. Data are presented as the mean ± SD; n = 8 per group. One-way ANOVA and Dunnett’s post hoc test were used to compare data between all groups. ^∗∗P<0.01, compared with the control group; ^##P<0.01, compared with the model group.

Figure 4. Effects of ACG on the numbers of inflammatory cells

(A) and pro-inflammatory cytokines (B) in BALF, and Th17 cell differentiation-related pathway (C) in lung tissue of asthmatic mice. (C) Left: immunoblot assay of RORγt and Foxp3 in lung tissues. Right: quantitative analysis of panel. Data are presented as the mean ± SD. n = 8 per group. One-way ANOVA and Dunnett’s post hoc test were used to compare data between all groups. ^∗∗P<0.01, compared with the control group; ^#P<0.05 and ^##P<0.01, compared with the model group.

Figure 5. Effects of ACG on TLR4/NF-kappaB pathway in lung tissue of asthmatic mice

(A) Immunoblot assay of TLR4, P65 and p-P65 in lung tissues. (B) Quantitative analysis of panel. Data are presented as the mean ± SD. n = 8 per group. One-way ANOVA and Dunnett's post hoc test were used to compare data between all groups. ^∗∗P<0.01, compared with the control group; ^##P<0.01, compared with the model group.

Figure 6. Effects of ACG on the expression of NLRP3 inflammasome in lung tissue of asthmatic mice

(A) The mRNA levels of NLRP3, ASC and Caspase-1 in the lung tissue were detected by RT-PCR. (B) Left: immunoblot assay of NLRP3, ASC and Caspase-1 in lung tissues. Right: quantitative analysis of panel. Data are presented as the mean ± SD. n = 8 per group. One-way ANOVA and Dunnett's post hoc test were used to compare data between all groups. ^∗∗P<0.01, compared with the control group; ^##P<0.01, compared with the model group.