Skip to main content
  • Research article
  • Open access
  • Published:

Duhuo Jisheng decoction alleviates neuroinflammation and neuropathic pain by suppressing microglial M1 polarization: a network pharmacology research

Abstract

Background

Neuropathic pain (NP) is the most prevalent form of chronic pain resulting from nerve damage or injury. Despite the widespread use of Duhuo Jisheng decoction (DHJSD) in traditional Chinese medicine (TCM) to treat chronic pain, the mechanism underlying its analgesic action remains unclear.

Methods

Using network pharmacology, we obtained DHJSD and NP-related target information from public databases to construct protein–protein interactions (PPI) and compound-target networks based on common target genes. These networks were further analyzed using gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG). The interaction between molecules was verified through molecular docking using AutoDock Tools software. Additionally, we treated a chronic constriction injury (CCI) rat model with DHJSD and determined the mechanical withdrawal threshold (MWT). We used an enzyme-linked immunosorbent assay kit to determine the levels of inflammatory cytokines. Furthermore, qRT-PCR was employed to analyze ACHE, NOS2, MAPK3, PTGS2, AKT1, and PPARG mRNA expression, and immunofluorescence was used to evaluate changes in microglia.

Results

Our screening of compounds and targets identified 252 potential targets of DHJSD associated with NP. PPI analysis, along with GO and KEGG analyses, revealed that the potential mechanism of DHJSD in NP treatment may be related to inflammatory reactions, the IL-17 signaling pathway, MAP kinase activity, and endocrine activity. Based on molecular docking, the core target showed significant affinity for DHJSD's active components. Moreover, DHJSD treatment repaired the CCI-induced inflammatory reaction in the spinal cord while regulating the expression of ACHE, NOS2, MAPK3, PTGS2, AKT1, and PPARG mRNA. Immunofluorescence results indicated that the active components of DHJSD may regulate microglial M1 polarization to improve neuroinflammation, PPARG may have been involved in the process.

Conclusion

The multi-component, multi-target, and multi-pathway actions of DHJSD provide new insights into its therapeutic mechanism in NP.

Introduction

Chronic pain is a common health condition that affects 6.2% of the general population worldwide. Neuropathic pain (NP) is the most common form of chronic pain caused by nerve damage or injury [1]. Various clinical drugs are prescribed for the treatment of NP, such as antidepressants, antiepileptics, opioids, and local anesthetics [2]; however, these drugs have limited therapeutic effects and intense side effects. Therefore, new analgesic drugs with relatively high efficiency and mild or no side effects are needed.

Traditional Chinese Medicine (TCM) monomers and compounds have been shown to be effective in treating NP [3]. For instance, Wu-tou decoction causes analgesia by inhibiting the activation of hippocampal microglia, alleviating the imbalance between hippocampal glutamatergic and gamma-aminobutyric acid (GABA)ergic neurons [4], and alleviates mechanical pain by modulating the inflammatory response through the TREM2-autophagic axis in the chronic constriction injury (CCI) model [5]. Moreover curcumin and puerarin can alleviate peripheral neuropathic pain by inhibiting oxidative stress-mediated NF-κB activation, thereby reducing inflammation [6, 7].

Angelicae Pubescentis Radix (APR), known as Duhuo Jisheng Decoction (DHJSD), is a medicinal herb widely used to treat sciatica, rheumatoid arthritis, and osteoporosis. APR Extracts and their constituent compounds have potent analgesic and anti-inflammatory effects [8]. For instance, inflammatory factors and TRPV1 mediate coumarins in damaged dorsal root ganglion neurons, decreasing pro-inflammatory cytokines (TNF-a, IL-1β, and IL-6) levels as well as TRPV1 and pERK expressions [9]. DHJSD includes numerous other components with unknown actions that need to be studied to expand its use in Traditional Chinese Medicine (TCM) (Additional file 1).

Network pharmacology uses biological networks as targets to analyze the links among drugs, targets, and diseases. A comprehensive and systematic study using network pharmacology is consistent with its holistic nature; thus, it is an important tool for screening active components and elucidating their underlying mechanisms of action. Molecular docking was originally used to detect recognition mechanisms between small and large molecules. In recent years, analytical docking has been applied to drug discovery [10], where it is used to identify innovative treatment compounds of interest, predict ligand–target interactions, or describe structure–activity associations at the molecular level. Advances in technology and dramatic increases in chemical and biological information have led to a surge in the use of analytical docking in the medical field, particularly for developing novel drugs [11, 12]. Herein, analytical docking was used to analyze the core target genes, and chemo-small analyses of a network pharmacological screen were used to identify chemo-small molecules that play a role in DHJSD (Additional file 2).

In this study, we aimed to identify and analyze the active components, target genes, and related signaling pathways of DHJSD and validate the results in a CCI rat model to elucidate the mechanism of action of DHJSD on NP (Fig. 1). Our data may help develop new analgesic drugs for the effective treatment of NP.

Fig. 1
figure 1

Flowchart of the study

Materials and methods

Identification of active compounds and target genes

By accessing the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), the chemical components of DHJSD were identified, and their possible targets were predicted. The criteria for identifying active components were oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.18 in the following processes: absorption, metabolism, distribution, and excretion. The potential target genes were identified using GeneCards (http://www.genecards.org/) and DisGeNET (https://www.disgenet.org/home/). Target protein names and their corresponding genes were identified and corrected using UniProt (http://www.uniprot.org). Common target genes from the two databases were analyzed using STRING 11 (https://string-db.org) to determine potential protein interactions with protein–protein interaction (PPI) scores > 0.4, indicating significance. Cytoscape 3.8.2 (http://www.cytoscape.org) was used to visualize the PPI network and Wiki pathways. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to evaluate target genes at the biological functional level, and key signaling pathways were selected based on enrichment scores. Active compounds, target genes, and prominent signaling pathways were used to construct a compound-target pathway network using Cytoscape 3.8.2. Visualization was performed using https://www.bioinformatics.com.cn and https://www.chiplot.online/

Molecular docking

The affinity of the active components for the crystal structures of the target proteins was verified using PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the Protein Data Bank (PDB, http://www.rcsb.org/pdb). Receptor proteins were retrieved from the PDB. By utilizing PyMOL 2.3.4 (https://pymol.org/2/) and AutoDock Tools (http://autodock.scripps.edu/resources/adt), receptors were modified by running these processes: dehydration, de-liganding, hydrogenation, and equilibrium charge. AutoDock Vina 1.1.2 (http://vina.scripps.edu) was used to dock the receptors to small-molecule ligands.

Preparation of DHJSD

The 15 herbs used in DHJSD were purchased from Beijing Tong Ren Tang (Beijing, China), ground into a powder, and mixed in relative proportions, as described in the Chinese Pharmacopoeia (http://wp.chp.org.cn/front/chpint/en/, Table 1). Stock solutions were prepared by DHJSD powder decoction in water to a 2 g/mL concentration and kept at -20 °C until further use.

Table 1 The 15 herbs of Duhuo Jisheng decoction

Chronic constriction injury (CCI) rat models and treatment

Forty male Sprague Dawley rats (200–250 g) were procured from Jinan Ponyue Experimental Animal Breeding (Jinan, China) and housed under a 12-h diurnal cycle. The rats were provided with water and food ad libitum. The CCI rat models were designed using previously described procedures [13]. Briefly, 1% sodium pentobarbital (40 mg/kg body weight) was administered intraperitoneally to anesthetize rats, followed by loose tying of three knots around the exposed left sciatic nerve at the mid-thigh by 4–0 chromic catgut ligation at 1 mm intervals, while the exposed left sciatic nerve in the sham group was not ligated. The rats were randomized into the sham (control), CCI, and CCI + DHJSD groups. The CCI + DHJSD group was treated daily with DHJSD at 10.3 g/kg [14] body weight, starting on day 1 postoperatively. The CCI group received an equal concentration of saline for seven days, starting on postoperative day 1. This study was approved by the Animal Ethics Committee of JiNing Medical College (2021B099).

Behavioral analysis

The rats were then transferred to a vitreous chamber with a wired-mesh floor and allowed to acclimate for 30 min. Mechanical allodynia was assessed using the mechanical withdrawal threshold (MWT) at 0, 1, 4, and 7-day postoperation between 8:00 and 17:00. Measurement of 50% was done with von Frey filaments (0.6 g, 1.0 g, 1.4 g, 2.0 g, 4.0 g, 6.0 g, 8.0 g, 10.0 g, and 15.0 g) (North Coast Medical Company, USA) using an up-down approach [15, 16].

Reverse transcription quantitative PCR (RT-qPCR)

Following the behavioral testing seven days post-operation, rats (n = 3/group) were subjected to anesthetize intraperitoneally by administration of 1% sodium pentobarbital (40 mg/kg body weight); the ipsilateral L4-6 spinal cord tissue was rapidly excised, succeeded by using cold phosphate-buffered saline (PBS) for wash and allowed to snap-freeze in liquid nitrogen and − 80 °C storage to be used in further analyses. RNA from the ipsilateral spinal cord was extracted using TRIzol reagent (Ambion, Austin, TX, USA) following the manufacturer’s protocols, and its quantity and purity were assessed at 260/280 nm using a NanoDrop 2000 (Thermo Fisher Scientific, Waltham, MA, USA). The reverse transcription kit (Biosharp, Anhui, China) was used for synthesizing cDNA, conducting RT-qPCR on a Bio-Rad iQ5 real-time system (Bio-Rad, Hercules, CA, USA) using SYBR mixture (Cwbio, Beijing, China) following the protocols, setting the thermal conditions to 25 °C, 55 °C, and 85 °C for 10, 30, and 5 min, respectively, using GAPDH as the reference gene. Primers (Table 2) were procured from Sangon Biotech (Shanghai, China).

Table 2 The primer sequence for RT-PCR

Enzyme-linked immunosorbent assay (ELISA)

ELISA was conducted using the L4–6 spinal cords ipsilateral to the nerve injury site. To assess the supernatant collected by homogenizing the spinal cord tissues in cold phosphate buffer, followed by sonication and 15 min of centrifugation at 10,000 rpm, the corresponding rat ELISA kits (Enzyme-linked Biotechnology, China) were used.

Immunofluorescence

The anesthetized rats (described above) were perfused with 200 mL of cold PBS. The ipsilateral L4-6 spinal cord tissue was rapidly excised, fixed in 4% PFA, embedded in paraffin, and sectioned. Paraffin sections were then sequentially dewaxed in xylene, anhydrous ethanol, 85% alcohol, and 75% alcohol, and placed in antigen retrieval buffer (100 × EDTA, pH 8.0). PBS (pH 7.4) was then used to wash the sections three times (5 min each), followed by 30 min of permeabilization with 0.3% Triton X-100 and a second wash with PBS, after which the sections were blocked for 1 h using 3% BSA. For co-staining, PPARG (1:100; Abcam), Iba-1 (1:500, Abcam, Cambridge, United Kingdom) and CD86 (1:100, Abcam) were co-incubated at 4 °C overnight, followed by 3 times of washing (5 min each) and 2 h of incubation in the dark at 20 °C in the presence of Alexa Fluor-488 or -594 goat anti-rabbit (1:500, Abcam), and counterstained with DAPI at 20 °C for 10 min in the dark. The analysis was performed using a 3DHISTECH slide scan system (CaseViewer; 3DHISTECH Ltd., Hungary).

Statistical analysis

GraphPad Prism 9.0 was utilized for conducting the statistical analysis, reporting the data as mean ± SD. One-way ANOVA followed by the Bonferroni post hoc test was used for comparing means among groups. p ≤ 0.05 indicated statistical significance.

Results

Network pharmacology analysis

Identification of active components and target genes

We identified 180 active components (Additional file 1: Table S1), and 252 potential DHJSD targets were the TCMSP. In addition, 711 and 714 target genes were identified using GeneCards and DisGeNET, respectively (relevance score range: 0.602–113.104, median: 3.418). Of these, 83 target genes were common to the two datasets and were used for further analysis (Fig. 2) (Additional file 1: Table S2).

Fig. 2
figure 2

Venn diagram of DHJSD potential targets and NP genes

Construction of PPI network

The PPI network of the 83 target genes revealed 1177 interactions between the targets (Fig. 3A). The average number of nodes was 28.361, with 37 nodes having a higher degree than the average (Fig. 3B) (Additional file 1: Table S3).

Fig. 3
figure 3

Protein–protein interaction network of DHJSD and NP common targets: A the PPI network of DHJSD and NP common targets. B The PPI network generated in this study includes 37 nodes larger than the average degree (> 28.361). Among all the core targets, the darker the blue, the larger the circle, the more important it was

GO enrichment analysis

Based on the GO enrichment analysis, 83 target genes were significantly enriched in 1,525 biological processes (BP), 96 molecular functions (MF), and 55 cell components (CC) (p < 0.01) (Additional file 1: Table S4). The top ten terms in each category are shown in Fig. 4A. The potential key pathways and therapeutic targets are shown in Fig. 4B. The top five terms in MFs were catecholamine binding (GO:1901338), G protein-coupled amine receptor activity (GO:0008227), MAP kinase activity (GO:0004707), cytokine receptor binding (GO:0005126), cytokine activity (GO:0005125); in CCs were membrane raft (GO:0045121), membrane microdomain (GO:0098857), membrane region (GO:0098589), caveola (GO:0005901), and presynaptic membrane integral component (GO:0099056); and in BPs were a lipopolysaccharide response (GO:0032496), bacterial origin molecule response (GO:0002237), a circulatory system vascular process (GO:0003018), chemical stress cellular response (GO:0062197), and regulation of tube diameter (GO:0035296).

Fig. 4
figure 4

Results of gene ontology and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis. A, C The histogram chart of GO and KEGG enrichment analysis of treating NP targets. B The potential key pathways and therapeutic targets for DHJSD treatment of NP. D Top 21 of KEGG pathway. E Top 20 of WIKI pathway

KEGG pathway enrichment analysis

Based on KEGG analysis (Additional file 1: Table S5), 83 target genes were found to be enriched in 163 pathways. Figure 4C, D shows the top 20 KEGG signaling pathways: AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, Chagas disease, tumor necrosis factor (TNF) signaling pathway, fluid shear stress and atherosclerosis, lipid and atherosclerosis, C-type lectin receptor signaling pathway, Pertussis, Yersinia infection, T-cell receptor signaling pathway, and IL-17 signaling pathway were key pathways (Fig. 5). According to the WIKI database, neuroinflammation was an important physiological process (Fig. 4E).

Fig. 5
figure 5

IL-17 signaling pathway (red represents up-regulated genes)

Construction of the compound-target pathway network

Using 155 active components, 83 target genes, and the top 30 pathways, a compound-target pathway network comprising 268 nodes and 1462 edges was constructed with an average of 10.910 neighbors and a path length of 2.608 (Fig. 6) (Additional file 1: Table S6), revealing the multi-component, -target, and -pathway potential action in neuropathic pain (NP).

Fig. 6
figure 6

Compound-target-pathway network (blue represents active compounds, red represents common targets, and green represents pathways)

Molecular docking

The top 10 active components and top 15 target genes in the compound-target pathway network were screened and sorted based on docking scores (Fig. 7) (Additional file 1: Table S7). The six genes with the lowest scores and their corresponding active compounds are shown in Fig. 8. Molecular docking studies indicated that hydrophobic interactions mainly maintain them. Stigmasterol interacted with PHE-338, PHE-297, TYR-341, TYR-124, TRP-86, TRP-286, and LEU-76 on the ACHE protein by hydrophobic interactions. Stigmasterol interacts with GLU-228 and ALA-230 on the AKT1 protein by hydrogen bonding and with ALA-177, VAL-164, THR-291, LEU-181, and PHE-161 via hydrophobic interactions. In PPARG/Stigmasterol, Stigmasterol interacts with GLN-283 on PPARG via hydrogen bonding and with ILE-262, PHE-287, TYR-473, TYR-477, and LYS-263 via hydrophobic interactions. beta-sitosterol hydrophobic interaction with ILE-48, ILE-73, TYR-53, VAL-56, ARG-84. Beta-sitosterol interacts with TRP-194, ALA-197, ARG-199, ILE-201, and GLN-205 on NOS2 via hydrophobic interactions and with TYR-489 via hydrogen bonding. Isorhamnetin formed hydrogen bonds with CYS-36, AGR-44, CYS-47, and TYR-130 on PTGS2, and LEU-152 and PRO-153 formed hydrophobic interactions.

Fig. 7
figure 7

Heat maps of the docking scores

Fig. 8
figure 8

Display of docking results between active components and target genes. A ACHE/Stigmasterol; B AKT1/Stigmasterol; C PPARG/Stigmasterol; D MAPK3/beta-sitosterol; E NOS2/beta-sitosterol; F PTGS2/ Isorhamnetin

Experimental validation

DHJSD improves cci-induced mechanical allodynia

CCI was performed in rats to evaluate the therapeutic effects of DHJSD on NP. Based on behavioral analysis, the CCI group had significantly lower WMT values on days 1, 4, 7, 10 and 14 postoperation than the sham group (p < 0.01). In contrast, the CCI + DHJSD group had significantly higher MWT values on days 4, 7, 10 and 14 postoperation than the CCI group (p < 0.05) (Fig. 10C), indicating that DHJSD treatment alleviated mechanical allodynia in CCI rats.

Core target verification

Molecular docking results showed that ACHE, NOS2, MAPK3, PTGS2, AKT1, and PPARG might be key genes associated with DHJSD analgesic effect. RT-qPCR, all ACHE, NOS2, MAPK3, PTGS2, and AKT1 transcriptional levels showed significantly elevated in the CCI group compared to the sham group (p < 0.05) and significantly decreased in the CCI + DHJSD group compared to the CCI group (p < 0.05). Nevertheless, PPARG had a more significant elevation in the CCI + DHJSD group than in the CCI group (p < 0.05) (Fig. 9).

Fig. 9
figure 9

Core target validation. AF RT-qPCR analysis of ACHE, NOS2, MAPK3, PTGS2, AKT, and PPARG expression in ipsilateral spinal dorsal horns. (*p =  < 0.05, **p =  < 0.01, ***p =  < 0.001 compared to the sham group, #p =  < 0.05, and ##p =  < 0.01 compared to the CCI group.)

DHJSD ameliorated inflammatory response in CCI rats

Based on network pharmacology, DHJSD treatment of NP was proposed to achieve its therapeutic effects by modulating neuroinflammation, revealing that the inflammatory factors IL-1 and IL-6 were significantly elevated in the CCI group compared to the sham group (p < 0.05) and significantly decreased in the CCI + DHJSD group compared to the CCI group (p < 0.05) (Fig. 10D, E, F, G). Immunofluorescence microscopy revealed that both Iba-1 and CD86 were significantly overexpressed in the CCI group compared with the sham group (p < 0.05). However, CD86 upregulation was reversed in the CCI + DHJSD group (Figs. 10B, 11). On the contrary, PPARG had a more significant elevation in the CCI + DHJSD group than in the CCI group (Fig. 12). Overall, these results suggest that DHJSD can reduce microglial activation and that the inhibition of microglial M1 polarization may mediate the relief of inflammation by DHJSD (Additional file 2: Fig S1), PPARG may have been involved in the process.

Fig. 10
figure 10

Effect of DHJSD on microglial activation and inflammation in the L4-L6 spinal cord at 7 days post-CCI. After CCI, rats were treated with DHJSD (10.3 mg/kg body weight) for 7 days. In spinal dorsal horns, Iba-1 levels were assessed by immunofluorescence. A The timeline of Experiment B Iba-1 labeled microglia (red) in spinal dorsal horn. Scale bars, 50 µm. C Effects of DHJSD on CCI-induced mechanical allodynia D, E RT-qPCR analysis of IL-1β and IL-6 expression in the ipsilateral spinal dorsal horns. F, G ELISA analysis of IL-1β and IL-6 expression in the ipsilateral spinal dorsal horns. H quantification of mean fluorescence intensity (*p =  < 0.05, **p =  < 0.01, ***p =  < 0.001 compared to the sham group, #p =  < 0.05 and ##p =  < 0.01 compared to CCI group)

Fig. 11
figure 11

Effect of DHJSD on polarization of microglia in the L4-L6 spinal cord at 7 days post-CCI. In spinal dorsal horns, Iba-1 and CD86 levels were assessed by immunofluorescence. Iba-1 labeled microglia (red) and CD86 labeled M1 (green), quantitative analysis of the positive cell percentage in the spinal cord dorsal horn. Scale bar, 50 μm. (***p =  < 0.001 compared to the sham group, #p =  < 0.05 and ##p =  < 0.01 compared to CCI group)

Fig. 12
figure 12

Effects of DHJSD on PPARG levels in L4-L6 spinal cords at 7 days post-CCI. PPARG levels in spinal dorsal horns were assessed by immunofluorescence. PPARG labeled green. Scale bar, 50 µm (***p =  < 0.001 compared to the sham group, ###p =  < 0.01 compared to CCI group)

Discussion

Neuropathic pain (NP) refers to pain directly caused by an injury or disease involving the somatosensory system [2]; its treatment remains controversial. The etiology of NP is diverse, its pathogenesis is complex, and it is associated with neuroinflammation following nerve injury and may lead to NP [17]. Inflammatory mediators are released by activated microglia, creating a closed-loop system that continually exacerbates damage to peripheral neuronal cells [18, 19]. In addition, microglial activation alone can cause pain hypersensitivity even without neuronal damage or other cellular injuries [20, 21]. Therefore, the modulation of microglial activation via pharmacological approaches is a promising research direction.

TCM is a holistic and systemic approach to treating complex health conditions [22]. DHJSD is a well-known treatment for chronic neuralgia. In the Qianjin Yaofang of the Tang Dynasty, Sun Simiao mentions its usefulness for “dispelling wind and dampness, relieving arthralgia, strengthening the liver and kidney, and replenishing blood and qi” [23]. However, there is a lack of systematic studies on DHJSD for NP; therefore, we aimed to explore the potential analgesic mechanisms of DHJSD by identifying and analyzing the active components, target genes, and related signaling pathways and validating the results in a CCI rat model.

Network pharmacology is a useful tool for revealing the mechanisms of action of TCMs in disease treatment. In our study, 83 target genes identified through multiple database searches were subjected to GO and KEGG analyses, revealing that DHJSD might affect NP by governing numerous BP, CC, and MF besides signaling pathways, and wiki pathways, suggesting the importance of neuroinflammation. Furthermore, DHJSD may synergistically regulate key target genes in the interleukin (IL)-17, tumor necrosis factor (TNF), cAMP, T-cell receptor, Toll-like receptor, HIF-1, and MAPK signaling pathways, also involving response to lipopolysaccharide, cellular response to chemical stress, catecholamine binding, and MAP kinase activity. Previous studies found that IL-17A leads to NF-κB, MAPK, and C/EBP cascades activation, inducing IL-6, IL-1β, and TNFα proinflammatory effects following binding to the corresponding target cell receptors (macrophages, T cells, and epithelial cells) [24,25,26]. Moreover, MAPK signaling pathway activation is involved in NP by inhibiting ERK1/2, p38, and JNK1/2 activation and decreasing the expression of inflammatory mediators [27, 28]. Wogonin inhibits TLR4-MyD88-TAK1-mediated NF-κB, and MAPK signaling pathways and consequently attenuates iNOS and COX-2 expression, inhibiting neuroinflammation in dorsal root ganglion neurons and improving NP [29]. In conclusion, based on our findings and those of previous studies, we propose that DHJSD treatment of NP may exert its therapeutic effects by modulating neuroinflammation. In our study, we successfully established a CCI rat model and examined spinal cord inflammation levels, revealing that DHJSD improved neuroinflammation by decreasing the expression of inflammatory factors in the spinal cord, in line with previous reports on the anti-inflammatory effects of DHJSD.

The PPI and compound-target pathway networks allowed us to identify the top 10 active components and 15 target genes subjected to molecular docking. The results showed that five ingredients, stigmasterol, beta-sitosterol, formononetin, naringenin, and quercetin, were predicted to be functional ingredients of DHJSD in the treatment of NP with ACHE, NOS2, AKT1, MAPK3, PTGS2, and PPARG.

NOS2 is one of the three nitric oxide synthase (NOS) isoforms, and its end product modulates NP [30]. Both 5-fluoro-2-oxindole and balneotherapy reduce NO production by inhibiting the upregulation of NOS2, which acts as an analgesic [31, 32]. Importantly, iNOS is a marker of M1 polarization in microglia that is upregulated in injured neural macrophages and Schwann cells along with other pain mediators (i.e., COX2) [33, 34]. PPAR is a nuclear hormone receptor superfamily ligand-activated transcription factor with 3 isoforms: PPAR-α, PPAR-δ, and PPARG [35]. PPARG is an endogenous anti-inflammatory factor that inhibits the intra-inflammatory response mainly through NF-κB signaling pathway competitive inhibition; thus, it can be used to reduce NP by regulating macrophage infiltration and pro-inflammatory molecule production at the inflammation site [36]. PPARG has also been reported to reverse neuroinflammation by increasing anti-inflammatory factor levels and decreasing spinal pro-inflammatory factor levels [37]. In addition, its overexpression inhibited oligosaccharide-induced CX3CR1 expression and M1-type activation in BV-2 microglia, exerting a protective effect against NP [38]. Moreover, isorhamnetin, a quercetin derivative, regulates M1/M2 macrophage polarization and enhances functional recovery in spinal cord injury rats [39]. In conclusion, these findings indicate that the inhibition of microglial M1 polarization may mediate the anti-inflammatory effects of DHJSD.

Microglia are the immune cells of the CNS. Neuroinflammation caused by microglia is also involved in NP development [40]. When external stimulus signals are received, microglia undergo two polarization states: pro-inflammatory (m1) and anti-inflammatory (m2) [41]. In the early stages of neuroinflammation, m1-like microglia secrete TNF, IL-1, and IL-6 as pro-inflammatory substances, which damage neural networks [42,43,44]. Notably, suppression of M1 polarization in microglia attenuates NP [37, 45].

In our study, ACHE, MAPK3, and PTGS2 were significantly downregulated, whereas PPARG was upregulated in the CCI + DHJSD group compared to the CCI group. Moreover, DHJSD significantly suppressed NOS2 expression in the spinal cord and decreased CD86/Iba-1 positive cell number in the dorsal horn. These results showed that DHJSD markedly improved neuroinflammation, partly by reducing microglial M1 polarization in the L4–6 spinal cord and the expression of inflammatory factors.

But there are limitations to our experiments, we focused only on changes in microglia. Recent studies have found that astrocyte-microglia interactions are particularly important for the treatment of neuropathic pain, and bidirectional communication between astrocytes and microglia can modulate central nervous system responses through the secretion of multiple cytokines and inflammatory mediators [46]. Astrocytes are abundant in the central nervous system (CNS). Although glial cells were initially thought to provide trophic support for neurons only, it is now evident that astrocytes are important for developing and maintaining neuropathic pain. Astrocytes appear to proliferate after nerve injury, and the intrathecal injection of reagents that inhibit the proliferation of astrocytes in nerve-injured rats results in the restoration of tactile tenderness [47]. The modulation of M1-type microglial polarization can similarly affect astrocytes. Reactive astrocytes exhibit heterogeneous and multifaceted functions in SCI, such as providing trophic and metabolic support to neurons, inhibiting axonal growth, and modulating inflammation [48, 49]. Necrotic astrocytes provide limited support for neuronal survival, and astrocyte necrosis inhibition can rescue the reactive astrocyte neurotrophic function of glial cells. Researchers have found that inhibition of M1 microglia may induce astrocyte necrosis by activating TLR4/MyD88 signaling, thereby favoring neuronal cell survival [50]. MpHE can regulate microglial phagocytic activity and prevent the pro-inflammatory M1 phenotype through PPAR-r/CD36-dependent mechanisms, inhibiting astrocyte proliferation and neuroinflammation amelioration [51]. Thus, we speculate that DHJSD may inhibit M1-type microglial polarization, thereby reducing astrocyte proliferation and treating neuropathic pain.

In conclusion, using network pharmacology, we systematically analyzed the analgesic mechanism of DHJSD and found that stigmasterol, beta-sitosterol, formononetin, naringenin, and quercetin were the active chemical components responsible for its action, while ACHE, NOS2, AKT1, MAPK3, PTGS2, and PPARG were the core targets. The results of the in vivo experiments also suggested that DHJSD significantly ameliorated neuroinflammation following NP treatment, in part by decreasing M1 polarization and inflammatory factor expression in the microglia. In future studies, we will focus on exploring the specific therapeutic mechanisms of DHJSD in NP, thereby contributing to developing new analgesic drugs for the effective treatment of NP with mild or no side effects.

Conclusions

Network pharmacology, molecular docking, and animal experiments were combined to study the analgesic mechanisms of DHJSD. Based on our data, DHJSD may regulate microglial polarization in the spinal cord to alleviate neuroinflammation; however, further research is required to validate our results. Overall, exploring the active components of DHJSD and the regulatory mechanisms underlying microglial cell activation in the rat spinal cord may help develop new analgesic drugs to effectively treat NP.

Data availability

The data used to support the findings of this study are available from the corresponding author upon request.

Abbreviations

DHJSD:

Duhuo Jisheng decoction

NP:

Neuropathic pain

TCM:

Traditional Chinese medicine

PPI:

Protein–protein interaction

GO:

Gene ontology

KEGG:

Kyoto encyclopedia of genes and genomes

CCI:

Chronic constriction injury

MWT:

Mechanical withdrawal threshold

GABA:

Gamma-aminobutyric acid

APR:

Angelicae Pubescentis Radix

IL-6:

Interleukin 6

IL-1β:

Interleukin 1 beta

TCMSP:

Traditional Chinese Medicine Systems Pharmacology

PDB:

Protein data bank

PBS:

Phosphate-buffered saline

BP:

Biological processes

CC:

Cell components

MF:

Molecular functions

References

  1. Scholz J, Finnerup NB, Attal N, Aziz Q, Baron R, Bennett MI, Benoliel R, Cohen M, Cruccu G, Davis KD, et al. The IASP classification of chronic pain for ICD-11: chronic neuropathic pain. Pain. 2019;160(1):53–9.

    PubMed  PubMed Central  Google Scholar 

  2. Abeck D. Morphological variants forgotten. Dtsch Arztebl Int. 2016;113(26):460.

    PubMed  PubMed Central  Google Scholar 

  3. Li SH, Li L, Yang RN, Liang SD. Compounds of traditional Chinese medicine and neuropathic pain. Chin J Nat Med. 2020;18(1):28–35.

    CAS  PubMed  Google Scholar 

  4. Zhu C, Xu Q, Mao Z, Lin N. The Chinese medicine Wu-Tou decoction relieves neuropathic pain by inhibiting hippocampal microglia activation. Sci Rep. 2018;8(1):12292.

    PubMed  PubMed Central  Google Scholar 

  5. Wang Y, Shi Y, Huang Y, Liu W, Cai G, Huang S, Zeng Y, Ren S, Zhan H, Wu W. Resveratrol mediates mechanical allodynia through modulating inflammatory response via the TREM2-autophagy axis in SNI rat model. J Neuroinflammation. 2020;17(1):311.

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Wu Y, Chen J, Wang R. Puerarin suppresses TRPV1, calcitonin gene-related peptide and substance P to prevent paclitaxel-induced peripheral neuropathic pain in rats. NeuroReport. 2019;30(4):288–94.

    CAS  PubMed  Google Scholar 

  7. Zhang X, Guan Z, Wang X, Sun D, Wang D, Li Y, Pei B, Ye M, Xu J, Yue X. Curcumin alleviates oxaliplatin-induced peripheral neuropathic pain through inhibiting oxidative stress-mediated activation of NF-kappaB and mitigating inflammation. Biol Pharm Bull. 2020;43(2):348–55.

    CAS  PubMed  Google Scholar 

  8. Lu Y, Wu H, Yu X, Zhang X, Luo H, Tang L, Wang Z. Traditional Chinese medicine of Angelicae Pubescentis Radix: a review of phytochemistry. Pharmacol Pharmacokinetics Front Pharmacol. 2020;11:335.

    CAS  PubMed  Google Scholar 

  9. Li R, Zhao C, Yao M, Song Y, Wu Y, Wen A. Analgesic effect of coumarins from radix angelicae pubescentis is mediated by inflammatory factors and TRPV1 in a spared nerve injury model of neuropathic pain. J Ethnopharmacol. 2017;195:81–8.

    CAS  PubMed  Google Scholar 

  10. Pinzi L, Rastelli G. Molecular docking: shifting paradigms in drug discovery. Int J Mol Sci. 2019;20:18.

    Google Scholar 

  11. Scotti L, Scotti MT. Recent advancement in computer-aided drug design. Curr Pharm Des. 2020;26(15):1635–6.

    CAS  PubMed  Google Scholar 

  12. Kitchen DB, Decornez H, Furr JR, Bajorath J. Docking and scoring in virtual screening for drug discovery: methods and applications. Nat Rev Drug Discov. 2004;3(11):935–49.

    CAS  PubMed  Google Scholar 

  13. Bennett GJ, Xie YK. A peripheral mononeuropathy in rat that produces disorders of pain sensation like those seen in man. Pain. 1988;33(1):87–107.

    PubMed  Google Scholar 

  14. Liu W, Jin S, Huang M, Li Y, Wang Z, Wang P, Zhao X, Xia P, Feng J. Duhuo jisheng decoction suppresses matrix degradation and apoptosis in human nucleus pulposus cells and ameliorates disc degeneration in a rat model. J Ethnopharmacol. 2020;250: 112494.

    CAS  PubMed  Google Scholar 

  15. Chaplan SR, Bach FW, Pogrel JW, Chung JM, Yaksh TL. Quantitative assessment of tactile allodynia in the rat paw. J Neurosci Methods. 1994;53(1):55–63.

    CAS  PubMed  Google Scholar 

  16. Galeano Niño JL, Wu H, LaCourse KD, Kempchinsky AG, Baryiames A, Barber B, Futran N, Houlton J, Sather C, Sicinska E, et al. Effect of the intratumoral microbiota on spatial and cellular heterogeneity in cancer. Nature. 2022;611(7937):810–7.

    PubMed  PubMed Central  Google Scholar 

  17. Austin PJ, Moalem-Taylor G. The neuro-immune balance in neuropathic pain: involvement of inflammatory immune cells, immune-like glial cells and cytokines. J Neuroimmunol. 2010;229(1–2):26–50.

    CAS  PubMed  Google Scholar 

  18. Zhang J, Zheng Y, Luo Y, Du Y, Zhang X, Fu J. Curcumin inhibits LPS-induced neuroinflammation by promoting microglial M2 polarization via TREM2/ TLR4/ NF-kappaB pathways in BV2 cells. Mol Immunol. 2019;116:29–37.

    CAS  PubMed  Google Scholar 

  19. Wang L, Yin C, Liu T, Abdul M, Zhou Y, Cao JL, Lu C. Pellino1 regulates neuropathic pain as well as microglial activation through the regulation of MAPK/NF-kappaB signaling in the spinal cord. J Neuroinflammation. 2020;17(1):83.

    PubMed  PubMed Central  Google Scholar 

  20. Tsuda M. Microglia in the spinal cord and neuropathic pain. J Diabetes Investig. 2016;7(1):17–26.

    CAS  PubMed  Google Scholar 

  21. Yi MH, Liu YU, Liu K, Chen T, Bosco DB, Zheng J, Xie M, Zhou L, Qu W, Wu LJ. Chemogenetic manipulation of microglia inhibits neuroinflammation and neuropathic pain in mice. Brain Behav Immun. 2021;92:78–89.

    CAS  PubMed  Google Scholar 

  22. Wang X, Wang ZY, Zheng JH, Li S. TCM network pharmacology: a new trend towards combining computational, experimental and clinical approaches. Chin J Nat Med. 2021;19(1):1–11.

    PubMed  Google Scholar 

  23. Wang R, Yu C, Wang N, Yang J. Angelicae Pubescentis Radix (Umbelliferae): systematic review of traditional Chinese medicine for treating rheumatoid arthritis, including traditional usage, chemical components, active components, related inflammatory factors. Phytomed Plus. 2023;3:1.

    Google Scholar 

  24. Fujino S, Andoh A, Bamba S, Ogawa A, Hata K, Araki Y, Bamba T, Fujiyama Y. Increased expression of interleukin 17 in inflammatory bowel disease. Gut. 2003;52(1):65–70.

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Song X, Qian Y. IL-17 family cytokines mediated signaling in the pathogenesis of inflammatory diseases. Cell Signal. 2013;25(12):2335–47.

    CAS  PubMed  Google Scholar 

  26. Song X, Qian Y. The activation and regulation of IL-17 receptor mediated signaling. Cytokine. 2013;62(2):175–82.

    CAS  PubMed  Google Scholar 

  27. Wang Z, Ren Z, Hu Z, Hu X, Zhang H, Wu H, Zhang M. Angiotensin-II induces phosphorylation of ERK1/2 and promotes aortic adventitial fibroblasts differentiating into myofibroblasts during aortic dissection formation. J Mol Histol. 2014;45(4):401–12.

    PubMed  Google Scholar 

  28. Tse KH, Chow KB, Leung WK, Wong YH, Wise H. Lipopolysaccharide differentially modulates expression of cytokines and cyclooxygenases in dorsal root ganglion cells via Toll-like receptor-4 dependent pathways. Neuroscience. 2014;267:241–51.

    CAS  PubMed  Google Scholar 

  29. Chen S, Xiong J, Zhan Y, Liu W, Wang X. Wogonin inhibits LPS-induced inflammatory responses in rat dorsal root ganglion neurons via inhibiting TLR4-MyD88-TAK1-mediated NF-kappaB and MAPK signaling pathway. Cell Mol Neurobiol. 2015;35(4):523–31.

    PubMed  Google Scholar 

  30. Chun YH, Auh QS, Lee J, Ro JY. Masseter inflammation differentially regulates three nitric oxide synthases in the rat trigeminal subnucleus caudalis. Arch Oral Biol. 2012;57(8):1141–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Redondo A, Riego G, Pol O. The antinociceptive, antioxidant and anti-inflammatory effects of 5-fluoro-2-oxindole during inflammatory pain. Antioxidants (Basel). 2020;9:12.

    Google Scholar 

  32. de Brito RN, Ludtke DD, de Oliveira BH, de Oliveira GT, Fernandes PF, Van Den Berge S, Salgado ASI, Cidral-Filho FJ, Horewicz VV, Bobinski F, et al. Balneotherapy decreases mechanical hyperalgesia by reversing BDNF and NOS2 immunocontent in spinal cord of mice with neuropathic pain. J Neuroimmunol. 2020;348: 577360.

    PubMed  Google Scholar 

  33. Ma W, Eisenach JC. Morphological and pharmacological evidence for the role of peripheral prostaglandins in the pathogenesis of neuropathic pain. Eur J Neurosci. 2002;15(6):1037–47.

    PubMed  Google Scholar 

  34. Durrenberger PF, Facer P, Gray RA, Chessell IP, Naylor A, Bountra C, Banati RB, Birch R, Anand P. Cyclooxygenase-2 (Cox-2) in injured human nerve and a rat model of nerve injury. J Peripher Nerv Syst. 2004;9(1):15–25.

    CAS  PubMed  Google Scholar 

  35. Bensinger SJ, Tontonoz P. Integration of metabolism and inflammation by lipid-activated nuclear receptors. Nature. 2008;454(7203):470–7.

    CAS  PubMed  Google Scholar 

  36. Liu Y, Qu Y, Liu L, Zhao H, Ma H, Si M, Cheng L, Nie L. PPAR-gamma agonist pioglitazone protects against IL-17 induced intervertebral disc inflammation and degeneration via suppression of NF-kappaB signaling pathway. Int Immunopharmacol. 2019;72:138–47.

    CAS  PubMed  Google Scholar 

  37. Li X, Guo Q, Ye Z, Wang E, Zou W, Sun Z, He Z, Zhong T, Weng Y, Pan Y. PPAR gamma prevents neuropathic pain by down-regulating CX3CR1 and attenuating M1 activation of microglia in the spinal cord of rats using a sciatic chronic constriction injury model. Front Neurosci. 2021;15: 620525.

    PubMed  PubMed Central  Google Scholar 

  38. Zhang ZJ, Jiang BC, Gao YJ. Chemokines in neuron-glial cell interaction and pathogenesis of neuropathic pain. Cell Mol Life Sci. 2017;74(18):3275–91.

    CAS  PubMed  Google Scholar 

  39. Chen F, Hu M, Shen Y, Zhu W, Cao A, Ni B, Qian J, Yang J. Isorhamnetin promotes functional recovery in rats with spinal cord injury by abating oxidative stress and modulating M2 macrophages/microglia polarization. Eur J Pharmacol. 2021;895: 173878.

    CAS  PubMed  Google Scholar 

  40. Guan Z, Kuhn JA, Wang X, Colquitt B, Solorzano C, Vaman S, Guan AK, Evans-Reinsch Z, Braz J, Devor M, et al. Injured sensory neuron-derived CSF1 induces microglial proliferation and DAP12-dependent pain. Nat Neurosci. 2016;19(1):94–101.

    CAS  PubMed  Google Scholar 

  41. Piotrowska A, Kwiatkowski K, Rojewska E, Makuch W, Mika J. Maraviroc reduces neuropathic pain through polarization of microglia and astroglia—evidence from in vivo and in vitro studies. Neuropharmacology. 2016;108:207–19.

    CAS  PubMed  Google Scholar 

  42. Inoue K, Tsuda M. Microglia in neuropathic pain: cellular and molecular mechanisms and therapeutic potential. Nat Rev Neurosci. 2018;19(3):138–52.

    CAS  PubMed  Google Scholar 

  43. Chen G, Zhang YQ, Qadri YJ, Serhan CN, Ji RR. Microglia in pain: detrimental and protective roles in pathogenesis and resolution of pain. Neuron. 2018;100(6):1292–311.

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Ji RR, Nackley A, Huh Y, Terrando N, Maixner W. Neuroinflammation and central sensitization in chronic and widespread pain. Anesthesiology. 2018;129(2):343–66.

    PubMed  Google Scholar 

  45. Wu W, Zhang X, Wang S, Li T, Hao Q, Li S, Yao W, Sun R. Pharmacological inhibition of the cGAS-STING signaling pathway suppresses microglial M1-polarization in the spinal cord and attenuates neuropathic pain. Neuropharmacology. 2022;217: 109206.

    CAS  PubMed  Google Scholar 

  46. Linnerbauer M, Wheeler MA, Quintana FJ. Astrocyte crosstalk in CNS inflammation. Neuron. 2020;108(4):608–22.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Tsuda M, Kohro Y, Yano T, Tsujikawa T, Kitano J, Tozaki-Saitoh H, Koyanagi S, Ohdo S, Ji RR, Salter MW, et al. JAK-STAT3 pathway regulates spinal astrocyte proliferation and neuropathic pain maintenance in rats. Brain. 2011;134(Pt 4):1127–39.

    PubMed  PubMed Central  Google Scholar 

  48. Pekny M, Wilhelmsson U, Pekna M. The dual role of astrocyte activation and reactive gliosis. Neurosci Lett. 2014;565:30–8.

    CAS  PubMed  Google Scholar 

  49. Mayo L, Trauger SA, Blain M, Nadeau M, Patel B, Alvarez JI, Mascanfroni ID, Yeste A, Kivisakk P, Kallas K, et al. Regulation of astrocyte activation by glycolipids drives chronic CNS inflammation. Nat Med. 2014;20(10):1147–56.

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Fan H, Zhang K, Shan L, Kuang F, Chen K, Zhu K, Ma H, Ju G, Wang YZ. Reactive astrocytes undergo M1 microglia/macrohpages-induced necroptosis in spinal cord injury. Mol Neurodegener. 2016;11:14.

    PubMed  PubMed Central  Google Scholar 

  51. Medrano-Jimenez E, Jimenez-Ferrer Carrillo I, Pedraza-Escalona M, Ramirez-Serrano CE, Alvarez-Arellano L, Cortes-Mendoza J, Herrera-Ruiz M, Jimenez-Ferrer E, Zamilpa A, Tortoriello J, et al. Malva parviflora extract ameliorates the deleterious effects of a high fat diet on the cognitive deficit in a mouse model of Alzheimer’s disease by restoring microglial function via a PPAR-gamma-dependent mechanism. J Neuroinflammation. 2019;16(1):143.

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We would like to thank Editage (www.editage.cn) for English language editing.

Funding

This study was supported by the National Science Foundation of China (No. 81572205 and 81974345).

Author information

Authors and Affiliations

Authors

Contributions

CYM and CCG conceived and designed the experiments and prepared the paper; CCG, YLZ, and TY performed the experiments; YLZ, XG, and CCG analyzed the data.

Corresponding author

Correspondence to Chunyang Meng.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1. Table S1

: Chemical compounds of 15 herbs in DHJSD. Table S2: Targets of DHJSD and NPs. Table S3: PPI analysis. Table S4. GO enrichment analysis data. Table S5. KEGG pathway enrichment analysis data. Table S6. C-T-P analysis data. Table S7: Molecular docking data.

Additional file 2.

 Fig S1: M2 polarisation.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gao, C., Zhao, Y., Yang, T. et al. Duhuo Jisheng decoction alleviates neuroinflammation and neuropathic pain by suppressing microglial M1 polarization: a network pharmacology research. J Orthop Surg Res 18, 629 (2023). https://doi.org/10.1186/s13018-023-04121-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13018-023-04121-9

Keywords