Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Open Access

Peer-reviewed

Research Article

Evaluation of the mechanism of Gong Ying San activity on dairy cows mastitis by network pharmacology and metabolomics analysis

  • Shuang Gao ,

    Contributed equally to this work with: Shuang Gao, Liyun Tang, Jiayi Ma

    Roles Data curation, Visualization, Writing – original draft

    Affiliation Animal Science and Technology College, Beijing University of Agriculture, Beijing, P.R. China

    ⨯
  • Liyun Tang ,

    Contributed equally to this work with: Shuang Gao, Liyun Tang, Jiayi Ma

    Roles Validation, Writing – review & editing

    Affiliation Animal Science and Technology College, Beijing University of Agriculture, Beijing, P.R. China

    ⨯
  • Jiayi Ma ,

    Contributed equally to this work with: Shuang Gao, Liyun Tang, Jiayi Ma

    Roles Validation, Writing – review & editing

    Affiliation Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, P.R. China

    ⨯
  • Kaiming Wang,

    Roles Software

    Affiliation Animal Science and Technology College, Beijing University of Agriculture, Beijing, P.R. China

    ⨯
  • Hua Yao,

    Roles Conceptualization, Data curation

    Affiliation Animal Science and Technology College, Beijing University of Agriculture, Beijing, P.R. China

    ⨯
  • Jinjin Tong,

    Roles Methodology, Project administration, Supervision, Writing – review & editing

    Affiliation Animal Science and Technology College, Beijing University of Agriculture, Beijing, P.R. China

    ⨯
  • Hua Zhang

    Roles Formal analysis, Methodology, Supervision, Validation, Writing – review & editing

    huazhang0914@163.com

    Affiliation Animal Science and Technology College, Beijing University of Agriculture, Beijing, P.R. China

    ⨯

Abstract

Objectives

The goal of this investigation was to identify the main compounds and the pharmacological mechanism of the traditional Chinese medicine formulation, Gong Ying San (GYS), by infrared spectral absorption characteristics, metabolomics, network pharmacology, and molecular-docking analysis for mastitis. The antibacterial and antioxidant activities were determined in vitro.

Methods

The chemical constituents of GYS were detected by ultra-high-performance liquid chromatography Q-extractive mass spectrometry (UHPLC-QE-MS). Related compounds were screened from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP, http://tcmspw.com/tcmsp.php) and the Encyclopedia of Traditional Chinese Medicine (ETCM, http://www.tcmip.cn/ETCM/index.php/Home/) databases; genes associated with mastitis were identified in DisGENT. A protein-protein interaction (PPI) network was generated using STRING. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment screening was conducted using the R module. Molecular-docking analyses were performed with the AutoDockTools V1.5.6.

Results

Fifty-four possible compounds in GYS with forty likely targets were found. The compound-target-network analysis showed that five of the ingredients, quercetin, luteolin, kaempferol, beta-sitosterol, and stigmasterol, had degree values >41.6, and the genes TNF, IL-6, IL-1β, ICAM1, CXCL8, CRP, IFNG, TP53, IL-2, and TGFB1 were core targets in the network. Enrichment analysis revealed that pathways associated with cancer, lipids, atherosclerosis, and PI3K-Akt signaling pathways may be critical in the pharmacology network. Molecular-docking data supported the hypothesis that quercetin and luteolin interacted well with TNF-α and IL-6.

Conclusions

An integrative investigation based on a bioinformatics-network topology provided new insights into the synergistic, multicomponent mechanisms of GYS’s anti-inflammatory, antibacterial, and antioxidant activities. It revealed novel possibilities for developing new combination medications for reducing mastitis and its complications.

Citation: Gao S, Tang L, Ma J, Wang K, Yao H, Tong J, et al. (2024) Evaluation of the mechanism of Gong Ying San activity on dairy cows mastitis by network pharmacology and metabolomics analysis. PLoS ONE 19(4): e0299234. https://doi.org/10.1371/journal.pone.0299234

Editor: Nesrein M. Hashem, Alexandria University, EGYPT

Received: October 11, 2023; Accepted: February 2, 2024; Published: April 17, 2024

Copyright: © 2024 Gao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are available on Dryad and Figshare: https://doi.org/10.5061/dryad.sxksn039n https://doi.org/10.6084/m9.figshare.25323277.v1 https://doi.org/10.6084/m9.figshare.25323280.v1

Funding: Financial Disclosure Statement Project #1: Specific grant numbers: 32272904 Initials of authors who received each award: Jinjin Tong Full names of commercial companies that funded the study or authors: National Natural Science Foundation of China URLs to sponsors’ websites: https://www.nsfc.gov.cn/ Project #2: Specific grant numbers: 31802263 Initials of authors who received each award: Hua Zhang Full names of commercial companies that funded the study or authors: National Natural Science Foundation of China URLs to sponsors’ websites: https://www.nsfc.gov.cn/ Also state whether any sponsors or funders (other than the named authors) played any role in: N/A

Competing interests: The authors have declared that no competing interests exist.

Introduction

Mastitis is a complex disease with imperfectly known etiology. As dairy cows’ most widespread infectious disease, it harms animal health, reduces milk quality, and represents a global economic problem for milk producers [1]. The susceptibility to and development of mastitis is associated with the degree to which mammary glands suffer exposure to pathogenic bacteria. How severe the infection will be depends on a number of host-specific elements, such as nutrient intake, genetic susceptibility, oxidant levels, and the changes in mammary tissues associated with the switch from involution to lactation [2]. Escherichia coli, Staphylococcus aureus, Streptococcus agalactiae, and Klebsiella pneumoniae are the main pathogenic bacteria in bovine mastitis [3]. Current mastitis treatments include antibiotics [4], antimicrobial peptides [5], bacteriophage therapy [6], probiotics [7], and nanoparticle-based treatments [8]. The broad effectiveness of antibiotics makes them the most popular therapy. However, overreliance on antibiotics contributes to the development of multidrug-resistant bacteria [9]. Because of this disadvantage, exploring traditional Chinese medicine (TCM) for practical, green formulas that can be used in place of antibiotics is worthwhile. The discovery of safe, efficient antibacterial or anti-mastitis drugs for use by dairy farmers in milk production is urgently needed. TCM has been receiving more attention and scrutiny worldwide for providing new options.

Gong Ying San (GYS) is a classic TCM herbal formulation, composed of Zhe Bei Mu (Fritillariae thunbergii bulbus), Jin Yin Hua (Lonicerae japonicae flos), Lian Qiao (Forsythiae fructus), Tong Cao (Medulla tetrapanacis), Si Gua Lao (loofah) and Pu Gong Ying (dandelion) that has been widely used for mastitis in dairy cows in China [10]. GYS has been recognized as exerting clearing heat and detoxification, eliminating redness and swelling in acute and chronic inflammatory conditions. The alkaloid and flavonoid compounds contained in GYS can play a resistance role in the pathogenic bacteria causing bovine mastitis, promoting the formation of lymphocytes in the body, enhancing immune capability, preventing the occurrence and development of inflammation, promoting the growth of mammary epithelial cells, enhancing the metabolic capacity of the mammary tissue and encouraging milk secretion [11]. A previous study indicated that dandelion, one of GYS’s main ingredients, could alleviate LPS-induced oxidant stress by scavenging reactive oxygen species (ROS); the compound promoted antioxidant enzyme activity by up-regulating gene expression through the Nrf2 signaling pathwa/y [12]. Anti-inflammatory effects are an essential pharmacological activity of Fritillariae thunbergii bulbus, inhibiting the immunological response of T lymphocytes and reducing the NF-κB pathway [13]. Lonicerae Japonicae Flos and Forsythiae Fructus can inhibit the expression of α-SMA, COX2, FPR2, PTGS1, NCOA2, IL-1β,TNF-α, CXCL14, and TGF-β1and reduce inflammatory responses and cellular oxidant levels [14]. Moreover, it was shown that an aqueous extract of Medulla tetrapanacis possessed anti-inflammatory and bactericidal effects and prevented polarization of macrophages, which reduced the level of inflammatory mediators and phagocytosis inactivating the MAPK pathway. It also inhibited the growth of S. aureus [15]. Treatments with a course of antibiotics are expensive, and overuse of antibiotics may increase the number of humans and animals infected by antibiotic-resistant bacteria [16]. Interestingly, feeding GYS powder to dairy cows with subclinical mastitis significantly improved milk quality, reduced the somatic cell count (SCC), and increased milk yield in mid-lactation dairy cows compared to conventional antibiotic treatment [17]. Although several researchers have studied the anti-inflammatory effect of GYS and its components in dairy cows [18, 19], the underlying comprehensive pharmacological mechanism of GYS’s action has not been elucidated because of its complex composition and the problem of determining the several targets of TCM formulations.

Network pharmacology, which integrates multi-omics, is a useful technique for studying the activities and functional pathways of TCM formulations. It provides a novel strategy for determining the network of TCM-compound-protein/gene-disease interactions and the primary active molecules with therapeutic properties [20]. Network pharmacology methods differ from those of the conventional one-target-one-drug approach. This analytical tool targets the diversity of interactions in living systems between the active compounds and the pathophysiological conditions associated with the disease [1]. Molecular docking is a widely accepted technique utilizing a computer-generated molecular structure model, with which we can deduce the interactions between active components and physiological systems [21]. Studies have shown that molecular-docking assays can measure the binding strength between the drugs and critical targets, improving the molecular network’s accuracy [22].

In this study, we used metabolomics technology to determine the chemical composition of GYS. Network pharmacology software and databases were employed to pinpoint the likeliest targets and biological pathways of the active components of GYS in dairy cow mastitis. Molecular docking were used to determine the interaction of potential gene targets and to identify the principle compounds and the mechanism of GYS activity in mastitis. We also determined the antibacterial and antioxidant capacity of GYS, further supporting the results obtained by network pharmacology. These results will help in screening potential mastitis drugs, improving the formulation of GYS, and providing new insights into ways to improve dairy cow health by preventing mastitis.

Materials and methods

Sample preparation

GYS was obtained from Beijing Tongrentang Co., Ltd, China, and consisted of dandelion 60.00 g, Lonicerae japonicae flos 60.00 g, Forsythiae fructus 60.00 g, loofah 30.00 g, Tetrapanacis medulla 25.00 g, cottonrose hibiscus leaf 25.00g, and Fritillariae thunbrgii bulbus 30.00 g. A portion of GYS was powdered with a milling machine (HBM-109, Hanbo Electromechanical Co., Ltd, China), and kept sealed for later use. The powder was placed in extraction medium (ultrapure water) for 30 min, then extracted in an ultrasonic extraction instrument (KQ-700DE, Kun Shan Ultrasonic Instruments Co., Ltd, China) at 35°C for 60 min. The mixture was cooled to 25°C, centrifuged at 999 g for 15 min. The supernatant is stored at 4°C and prepared into freeze-dried powder, which can be stored at -20°C and sealed for a long time. To prepare a GYS stock solution for later analysis, 5.76 g of lyophilized GYS powder was dissolved in 10 mL of ultrapure water.

Metabolomics profiling using ultra-high-performance liquid chromatography with Q-extractive mass spectrometry (UHPLC-QE-MS)

An aqueous extract of GYS was centrifuged at 15,984 g for fifteen minutes at 4°C, and 300 μL of supernatant was mixed with 1 mL of extract buffer containing 10 μg/mL of internal standard. Tubes were vortexed for 30 s and sonicated for five minutes at 4°C. After one hour at -40°C, the samples were re-centrifuged at 15,984g for fifteen minutes at 4°C. The supernatants were passed through a 0.22 μm filter and analyzed by UHPLC-MS/MS with QC samples (100 μL) included periodically to monitor performance. The UHPLC-MS/MS separation step was carried out with a high-performance liquid chromatograph (Vanquish, Thermo-Fisher Scientific Inc., Germany). For chromatography, a UHPLC BEH-C18 column (1.7 μm × 2.1 × 100 mm) from (Watsch/Waters Tech Co., Ltd, Shanghai, China) was used for separations. The injection volume was 5 μL, and the flow rate was 0.4 mL/min. The optimal mobile phase consisted of 0.1% formic acid in water (A) and 0.1% formic acid in acetonitrile (B). The multi-step linear elution gradient program was as follows: 0–3.5 min, 95–85% A; 3.5–6 min, 85–70% A; 6–6.5 min, 70–70% A; 6.5–12 min, 70–30% A; 12–12.5 min, 30–30% A.

An Orbitrap Exploris 120 mass spectrometer (Orbitrap Exploris 120, Thermo-Fisher Scientific Inc., Germany) equipped with Xcalibur software was used to acquire MS and MS/MS data based in the IDA-acquisition mode. The sheath-gas flow rate was 30 Arb, the auxiliary gas flow rate was 10 Arb, the capillary T was 350°C, the full millisecond resolution was 60,000, the MS/MS resolution was 15,000, the collision energy was 16/38/42 in NCE mode, and the spray V was 5.5 kV (positive) or -4 kV (negative). The caloric value standard for screening effective metabolites was VIP>1, p<0.05.

Screening GYS for bioactive compounds

The TCM pharmacological database (TCMSP) and platform was employed to determine the most likely active components [23, 24]. Accordingly, two indicators, oral bioavailability (OB) and drug likeness (DL), were selected. OB is the rate of absorption and appearance of a drug in the blood after administration. DL refers to the degree to which compounds are similar to drugs already on the market [25]. An OB of ≥ 30% [26] and DL ≥ 0.18 [27] were chosen as threshold values for selecting the core active components for screening GYS.

Prediction of candidate targets of GYS in inflammatory disease

The names of the target proteins were translated into their corresponding gene symbols with the UniProt dbase (https://www.uniprot.org) [28]; ‘mastitis’ was set as the search term to collect related targets from the DisGENT (https://www.disgenet.org/) database [29] with Bos taurus as the designated species. The final group of hits was acquired after deleting repetitions; the selected GYS targets and mastitis-related hits were depicted as a Venn diagram (https://bioinfogp.cnb.csic.es/tools/venny/) to illustrate the inter-relationship of specific targets with the active compounds. Lastly, these common targets were organized for subsequent network analyses.

Functional enrichment analysis

The likely GYS targets for mastitis treatment were uploaded to the database for annotation, visualization, and integrated discovery (DAVID, https://david.ncifcrf.gov/) [30]. Then, GO and KEGG analyses were performed to identify the essential signaling pathways in mastitis treatment. The output was ranked according to the top scores of GO and KEGG evaluations. A p< 0.05 was used to define a significant difference between means.

Construction of the protein-protein interaction (PPI) network

The overlapping genes interacting with GYS ingredients and inflammatory pathways were accepted as hub genes. The GYS-target-mastitis network was constructed by Cytoscape 3.9.1 software, an open-source platform for depicting network complexity and integrating multiple groups of information for analysis. The hub gene names were input to the STRING database (https://string-db.org/) after setting the combination score to >0.9 to construct the PPI network. The data were obtained as a TSV file and imported into Cytoscape V3.9.1 for further analysis. CytoHub, a Cytoscape V3.9.1 module, was employed to determine the degree of centrality. The most prominent protein targets involved in the most biological pathways were considered the most promising therapeutic targets.

Construction of the GYS active component-target network

The screened active components and target information were uploaded to Cytoscape V3.9.1 to generate the compounds-targets-diseases (CTD) network to better display the interactions between functional components and targets. ‘Nodes’ represent drugs, compounds, and targets. ‘Edges’ show the association between one node and another. The correlation degree of nodes was determined based on the degree value.

Molecular docking

Molecular docking capability was assessed using AutoDockTools V1.5.6 to confirm the interaction of compounds with targets [31]. The top two core targets were evaluated to verify the method’s reliability, and receptor proteins were selected. The core protein crystal structures were obtained from the protein data bank (PDB, http://www.rcsb.org/), and the PyMol program was used to optimize the protein structures by deleting H2O. Hydrogens were inserted into the proteins, and the resulting charge was calculated with AutoDockTools V1.5.6 and exported as a PDBQT file. The molecular docking results were presented as docking scores; the higher the score, the greater the likelihood that a protein was a target of a component from the GYS formulation.

Antibacterial activity

E. coli CVCC 1450, S. agalactiae CVCC 3940, and S. aureus CVCC 2257 were obtained from the National Center for Veterinary Culture Collection (CVCC). Microdilution assays were used as previously described to calculate minimum inhibitory concentration (MIC) [32]. Briefly, serial two-fold dilutions of GYS extract ranging from 288 mg/mL to 0.56 mg/mL were incubated with the test bacterial cultures seeded in a 96-well plate at 3–6×106 CFU/mL. The bacterial cultures were incubated with the different concentrations of GYS extract at a ratio of 1:1 (v/v) for 24 h at 37°C. The positive control was 0.2 mL of bacterial suspension with no GYS and the negative control was 0.2 mL of medium alone. The absorbance at 492 nm was measured using a microplate spectrophotometer (Tecan GENios F129004, Austria). The minimum inhibitory concentration (MIC) values were defined as the lowest concentration of GYS extract that resulted in no increase in A492. In addition to determining the MIC, the minimum bactericidal concentration (MBC), the lowest concentration of GYS that resulted in the death of 99.9% of the bacteria, was measured. Aliquots of 50 μL from all tubes with no visible bacterial growth were seeded on agar plates and incubated for 24 h at 37°C. The lowest concentration of an antimicrobial agent killing 99.9% of a bacterial population is termed the minimum bactericidal concentration (MBC). This was done by observing pre- and post-incubated agar plates for the presence or absence of bacteria. Each experiment was repeated three times.

Disk diffusion bacteriostatic assay

For the Kirby-Bauer disc diffusion method, 0.1 mL (3–6 ×106 CFU/ml) of bacterial suspension was uniformly spread on nutrient agar. Afterwards, filter paper disks (6 mm diam.) containing the antibiotics, penicillin, cephalexin, vancomycin, and gentamicin, and GYS extract at high (144 mg/mL) or low (36 mg/mL) concentration were placed on the agar surface using sterile forceps and the plates were incubated at 37°C overnight. The bacteriostatic activity was quantified by measuring the diameter of the zone of inhibition around each disc. The data are given as mean ± SEM of three independent experiments.

Bacteriostatic growth curves

A time-kill kinetics method was used to calculate the bacteriostatic effect of GYS on a panel of target bacteria. GYS extract at 1 × MIC, 2 × MIC, or 4 × MIC (for the respective isolate) was mixed with 3–6 × 106 CFU/mL of bacterial suspension to be tested in a 96-well plate. The plate was incubated at 37°C and the A492 was read at time 0, 1, 2, 6, 12, 24 and 36 h of incubation. Also, samples of the bacterial cultures were taken, serially diluted, spread on nutrient agar in triplicate, and incubated overnight at 37°C. Colony counts were done and means ± SEM were calculated. A control with no antimicrobial compound was run, as well as a sterility control. The bacteriostatic kill-curve experiments were run in triplicate.

1,1-Diphenyl-2-picrylhydrazyl (DPPH) free-radical scavenging activity

GYS’s capability for scavenging 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radicals was quantitated using a previously published method [33]. In brief, 1.0 mL of GYS at a concentration of 0.5 mg/mL to 3.0 mg/mL, was added to 2 mL of 0.1 mM DPPH in EtOH at RT for 30 min, and the absorbance was read at 517 nm. A vitamin C (Vc) solution (0.20–1.20 mg/mL) was used as positive control. The results are given as percent DPPH radicals scavenged by Eq (1): (1) where AI = sample; AII = anhydrous ethanol solution; AIII `= blank control.

Hydroxyl radical scavenging capacity

The hydroxyl radical scavenging capability of GYS was determined using the salicylic acid reaction. Different concentrations of GYS (0.5–3.0 mg/mL) were mixed with 9.0 mM ferrous sulfate, 9.0 mM salicylic acid in anhydrous ethanol, or 8.8 mM hydrogen peroxide. After 30 min at 37°C, the absorbance at 510 nm was read. Vitamin C (0.2–1.2 mg/mL) acted as the positive control. The results are expressed as a percentage of radicals scavenged (Eq 2): (2) where AI = sample, AII = hydrogen peroxide solution, and AIII = blank control.

Statistical analyses

The data were analyzed and graphed using GraphPad Prism 8.0 and Origin 2021. The data are the means of at least three independent experiments ± SD. To establish whether differences were significant, an unpaired two-tailed Student’s t test or one-way ANOVA with Duncan’s multiple comparisons was employed. The 95% significance level was met by p ≤ 0.05, while p ≤ 0.01 was considered extremely significant.

Results

Chemical profiling of GYS

UHPLC-QE-MS analysis was employed to characterize the chemical profile. Seventy-two compounds from GYS were detected and tentatively characterized by the intersection between positive and negative modes (Fig 1). The data for these components is shown in S1 Table. These compounds include different types of constituents, such as phenols, terpenes, alkaloids, organic acids and their derivatives, flavonoids, etc.

thumbnail
Download:
Fig 1. Identification of chemical components of GYS by UHPLC-QE-MS.

Total ion chromatography in positive (A) and negative (B) ion modes.

https://doi.org/10.1371/journal.pone.0299234.g001

Target prediction and validation of GYS compounds

A total of 446 active GYS compounds were found by reference to the TCMSP and ETCM databases. The ETCM search yielded dandelion and loofah, including 236 in Lonicerae japonica floss, 150 in Forsythiae fructus, 32 in Tetrapanacis medulla, 17 in Fritillaria thunbergia bulbs, 9 in loofah and 2 in dandelion. With OB≥30% and DL≥0.18 as the screening criteria, 68 potential active compounds were found. Of the 59 results, 55 active compounds were eligible for further study after the exclusion of duplicates (S2 Table). The 343 genes associated with the identified components were obtained using UniProt databases.

Acquisition of disease target data and screening of intersecting targets

Using the DisGENT database, we collected 273 potential mastitis-related GYS targets. Based on this data, we used the Venn Atlas platform to show the forty common intersecting targets (Fig 2).

thumbnail
Download:
Fig 2. Venn diagram showing the intersection of targets of GYS active components with potential mastitis-associated targets.

https://doi.org/10.1371/journal.pone.0299234.g002

Functional enrichment analysis of the active ingredient targets

To show enrichment of the anti-mastitis function of GYS, we used 40 overlapping targets. In the GO analysis, all targets were significantly enriched in biological processes (BPs), cellular components (CCs), and molecular functions (MFs) (Fig 3A). The enriched BPs included: positive regulation of transcription from RNA polymerase II promoter; negative regulation of apoptosis; cellular responses to organic cyclic compound and positive regulation of MAPK kinase activity. The extracellular space and the cell surface represented the enriched CCs. In terms of MF enrichment, the identified genes were significantly involved in protein interactions, homologous protein binding, and enzyme binding. The results also showed positive modulation of transcription from the RNA polymerase II promoter, which could positively regulate gene expression.

thumbnail
Download:
Fig 3. GO and KEGG enrichment analysis for identifying mechanism of the anti-mastitis activity of GYS.

(A) Distribution of GO elements in biological processes, molecular functions, and cellular composition (for FDR<0.05). The x-axis shows counts of enriched targets, while the y-axis shows the GO category of the target gene. (B) The top 20 KEGG pathways (FDR<0.05). The color corresponds to p-value threshold, and the dot size indicates the number of genes for each term. The x-axis shows the enrichment score, and the y-axis gives the main pathways.

https://doi.org/10.1371/journal.pone.0299234.g003

KEGG enrichment screening of the 40 common targets and top 20 enriched pathways are depicted as bubble plots (Fig 3B) generated with the R program. The results indicate that these targets are highly correlated with cancer-related pathways, and pathways in cancer are the most significantly enriched (Fig 3C). The NF-κB pathway is essential for the development and progression of mastitis, and it was shown to be a likely target for anti-inflammatory and anticancer treatments. Five mastitis-related pathways were found, including the signaling pathways for TNF, MAPK, PI3K-Akt, and IL-17. The AGE-RAGE pathway, which is associated with diabetes severity, was also over-represented. The downstream signals of AGE-RAGE, the p38, and JNK MAPKs altered NF-κB action, affecting the inflammatory response.

Protein-protein interaction (PPI) network analysis

The STRING database was used to construct a PPI network to elucidate the molecular mechanisms of the effects of GYS on mastitis and the activities of specific proteins (Fig 4A). Based on topological analysis, the target genes (degree score ≥16), in order from high to low, were: TNF, IL-6, IL-1β, ICAM1, CXCL8, CRP, IFNG, TP53, IL-2 and TGFB1 (Table 1). These target genes interacted most closely with other targets, and the results suggested that they included the core target (hub) genes. To visualize and identify core targets, we utilized Cytoscape to construct a network based on target degree. We obtained five core targets from this model: TNF, IL-6, IL-1β, ICAM1, and CXCL8 (Fig 4B). These targets probably reflect the principle functional sites of GYS for mastitis therapy and show that GYS influences mastitis via multiple targets.

thumbnail
Download:
Fig 4. Construction of PPI network and core targets.

(A) PPI network showing the relationship among common GYS targets associated with the anti-inflammatory activity. (B) TSV files were obtained from the STRING dbase and imported into Cytoscape 3.8.0 for visualization. The colors represent the importance of the network from most (red) to least (yellow).

https://doi.org/10.1371/journal.pone.0299234.g004

thumbnail
Download:
Table 1. Mastitis about the core target hub genes.

https://doi.org/10.1371/journal.pone.0299234.t001

Establishment of a comprehensive interaction network of GYS against mastitis

The Cytoscape network diagram of C-T-D is shown in Fig 5A. The GYS-mastitis network consists of 497 nodes (448 target nodes, 42 active compound nodes, one inflammatory disease node, and 6 TCM nodes) and 1290 edges; network analyses showed that the average degree of the 48 candidate components was 41.6. The top ten active ingredients based on degree-value are shown in Table 2. Five components had degree values greater than 41.6: quercetin (371), luteolin (146), kaempferol (96), beta-sitosterol (55), and stigmasterol (47), and these were regarded as the key GYS components that are active against mastitis. The GO analyses were used to generate a network showing the relationships between the top 20 pathways and protein-encoding genes (Fig 5B).

thumbnail
Download:
Fig 5. Compound-Disease-Target network and GO, KEGG association network.

(A) Network of specific compounds-targets-diseases of the anti-inflammatory ingredients of GYS. The orange nodes show the potential therapeutic targets of GYS against mastitis, and the blue nodes stand for the network’s compounds. The green square nodes show the TCM ingredients, and the red nodes are those associated with mastitis. (B) Interaction networks showing core biotargets, pharmacological functions, and signaling pathways of GYS compounds against mastitis. The yellow nodes show the hub targets of GYS against mastitis, and the nodes in grey are the enriched BPs from hub targets. The yellow ellipse nodes show the enriched CCs and the blue nodes are enriched MFs. The violet nodes show the KEGG enrichment analysis of GYS against mastitis.

https://doi.org/10.1371/journal.pone.0299234.g005

thumbnail
Download:
Table 2. The top ten active compounds in degree-value.

https://doi.org/10.1371/journal.pone.0299234.t002

Molecular docking results

Molecular-docking analysis was performed to confirm that TNF and IL-6 bound to quercetin and luteolin, respectively. Quercetin forms four H-bonds with TNF at Leu233, Leu133, Tyr227 and Tyr195 (Fig 6A). Five H-bonds were detected between quercetin and IL-6 (Fig 6B), and one H-bond between luteolin and TNF (Fig 6C). Luteolin and IL-6 were linked with three H-bonds at Arg179, Met67, Lys66 and Glu55 (Fig 6D). The binding energies were measured to determine the degree of complementarity between the active compounds and the proteins.

thumbnail
Download:
Fig 6. The protein ligands of the docking simulation.

(A) Docking of quercetin with TNF. (B) Docking of quercetin with IL-6. (C) Docking of luteolin with TNF. (D) Docking of luteolin with IL-6.

https://doi.org/10.1371/journal.pone.0299234.g006

Low binding energy indicates greater stability. The binding energy of TNF and quercetin, TNF, and luteolin were −8.8 and −9.1 kJ/mol, respectively. The binding energies of IL-6, quercetin, IL-6, and luteolin were −6.7 and −6.7 kJ/mol, respectively (Table 3). The results indicated that the compounds bound to the active sites of the targets.

thumbnail
Download:
Table 3. Binding energy of active compounds with core-targets.

https://doi.org/10.1371/journal.pone.0299234.t003

Antimicrobial activity of GYS extract

The MIC and MBC values of GYS against S. aureus, E. coli, and S. agalactiae are shown in Table 4. GYS’ strongest inhibitory effect was on S. aureus (CVCC 2257), while growth of E. coli (CVCC 1450) was only slightly affected. The antimicrobial activities of GYS extract against S. aureus, E. coli, and S. agalactiae are tested with the bacteriostatic circle approach (Table 5). The high concentrations of GYS diameters of the antibacterial ring are 24.04 ± 0.20, 15.07 ± 0.19, and 18.11 ± 0.59 mm against S. aureus, E. coli, and S. agalactiae, respectively, which are between vancomycin (17.01 ± 0.16 mm) and cephalexin (25.07 ± 0.15 mm). The Time bacteriostatic curve of GYS against the three pathogenic pathogens has a better inhibitory effect on Gram-positive bacteria (S.agalactiae CVCC 3940, S. aureus CVCC 2257) than on Gram-negative bacteria (E. coli CVCC 1450). The Lg CFU/mL value reduces bacteria within one hour, and the Lg CFU/mL value increases slowly after two hours (Fig 7).

thumbnail
Download:
Fig 7.

Time-dependent bacteriostatic growth curve of GYS on (A) S. aureus ATCC 29740, (B) S. agalactiae CVCC 3940 and (C) E. coli CVCC 1450.

https://doi.org/10.1371/journal.pone.0299234.g007

thumbnail
Download:
Table 4. Antimicrobial activity of GYS extract against common bacterial species.

https://doi.org/10.1371/journal.pone.0299234.t004

thumbnail
Download:
Table 5. Bacteriostatic activity of GYS extract against common bacterial species.

https://doi.org/10.1371/journal.pone.0299234.t005

In Vitro antioxidant activity

The antioxidant action of GYS in vitro were investigated by DPPH free-radical scavenging (Fig 8A). The DPPH scavenging ability of the GYS extract was lower than that of the positive control (Vc). Both were concentration-dependent and in the range of 0.20–1.00 mg/mL. The GYS concentration capable of 50% removal of DPPH radicals (IC50) was 0.38 mg/mL by GYS, while for vitamin C it was 0.15 mg/mL. However, at 1.00 mg/mL, the •OH-scavenging activity of GYS was 78.70 ± 2.17%. The •OH-scavenging activity (IC50) of GYS was 0.24 mg/mL and for Vc it was 0.06 mg/mL (Fig 8B).

thumbnail
Download:
Fig 8. Antioxidant activity of the GYS extract in vitro.

(A) DPPH radical scavenging assay. Assays were run in triplicate in three independent experiments. (B) The •OH-scavenging activity of GYS extract compared with Vc (vitamin C) as positive control.

https://doi.org/10.1371/journal.pone.0299234.g008

Discussion

The Chinese traditional medicine formulation, Gong Ying San has been used as a mastitis treatment for many years [34, 35]. The Dandelion, Lonicera japonica flos, and Forsythia fructus in this recipe are cooling and thus detoxify the body, disperse wind, and reduce heat. Several other herbs include loofah, Medulla tetraparesis, and Fritillaria thunbergia bulbs, which ventilate milk, reduce swelling and disintegrate [11]. However, the mechanism of GYS’s pharmacological action on mastitis has yet to be completely worked out. Here, we performed a comprehensive evaluation using non-targeted metabolomics, network pharmacology, and molecular-docking assays to delineate the underlying mechanisms and therapeutic targets of GYS in mastitis. The antibacterial inhibitory zone measurements, antibacterial growth curve plotting, and assays for DPPH and hydroxyl free radical scavenging experiments verified the antibacterial and antioxidant capability of GYS.

The primary active compounds in GYS were identified by UHPLC-QE-MS. We identified 40 compounds, including phenols, terpenes, alkaloids, organic acids and their derivatives, flavonoids, etc., that contain some antibacterial properties. Streptococcus spp., Corynebacterium spp., and Enterococcus spp., S. aureus spp. arre colonizers of skin and mucosa, and the primary cause of bovine mastitis [36]. Research showed that mammary gland infection decreased antioxidant capacity of the milk and reduced the activity of catalase, lactoperoxidase, glutathione peroxidase, and superoxide dismutase, and the level of antioxidant vitamins [37]. Flavonoids exert antibacterial effects by active synergy against bacterial virulence factors, such as quorum-sensing signal receptors, enzymes, and toxins [38]. However, enhanced antioxidant activity may be the primary mechanism, including binding pro-oxidant iron, scavenging reactive nitrogen, chlorine, and oxygen species, and potentially inhibiting cyclooxygenases and lipoxygenases [39]. When bovine mastitis occurs, decreased KEAP1 and increased Nrf2, HO1, NQO1, and reactive oxygen species (ROS) indicate increased oxidative stress [40]. Thus, the presence of the isolated antioxidant compounds may explain why GYS extract reduces inflammation and has other anti-mastitis properties.

Using our network pharmacology model, we identified 55 active ingredients in GYS. Quercetin, luteolin, kaempferol, beta-sitosterol, and stigmasterol were the main active components in GYS for mastitis treatment as they affected the most mastitis-related symptoms. Quercetin is a flavonol widely distributed in the plant kingdom with multiple biological activities, including maintaining normal bone metabolism and slowing the progression of inflammatory disease [41]. It has been reported that quercetin can be used as a non-antibiotic therapy for mastitis by inhibiting NF-κB transcription in the Nrf2-ARE signaling pathway [42], which aligns with our results on the anti-inflammatory properties of GYS. Our results show that quercetin reduces mastitis by regulating the TNF signaling pathway [43]. The antioxidant luteolin showed potent anti-inflammatory activity and inhibited mast cell activation when administered with the anti-inflammatory cytokine IL-38. IL-38 acts through a different pathway, and significantly increased the observed anti-inflammatory effect [44]. Kaempferol, a natural polyphenol, reduced T-cell proliferation, and nitric oxide release, and inhibited ROS formation. Xiang [45] reported that kaempferol down-regulated the mRNA expression of TNF-α and IL-6 in a murine model of non-alcoholic steatohepatitis induced by a high-fat diet and exhibited excellent antioxidant and anti-inflammatory activities [46]. Beta-sitosterol showed in vivo anti-inflammatory and antioxidant activities. Previous tests of beta-sitosterol showed a specific antibacterial ability and significant reduction in apoptosis, oxidative stress, and inflammation by activation of the hypoxia-inducible factor-1(HIF-1a) / mammalian target of rapamycin (mTOR) signal pathway [47, 48]. These findings suggest that beta-sitosterol can potentially reduce mastitis-induced inflammatory responses in mammary glands. Studies have shown that stigmasterol inhibited the infiltration of inflammatory cells and the over-secretion of mucus. The anti-inflammatory effects resulted from a decrease in IL-6 and NF-κB, and an increase in antioxidant activity [49]. The active components of GYS were found to bind to core proteins, and this was verified by molecular-docking analyses. Thus, GYS’ inflammation-lowering activity resulted from inhibiting the expression of proinflammatory cytokines.

Previous studies demonstrated that luteolin could suppress inflammation mediated by IL-1β, IL-6, IL-8, IL-17, IL-22, TNF-α and COX-2, which act through the NF-κB, JAK–STAT, and TLR pathways [50]. In addition, luteolin exhibited a potentially effective new function by protecting tissues from mastitis damage caused by S. aureus infection [51]. Kaempferol suppressed phosphorylation of the NF-κB p65 subunit and the degradation of its inhibitor, IκBα, in the NF-κB signal pathway for the treatment of mastitis; this was accompanied by decreased myeloperoxidase (MPO) production and ANGPTL2 expression, as well as a reduction in TNF-α and IL-6 [52]. The TNF-α-induced inflammation corresponded to an increase in ICAM-1 mRNA and protein, significantly inhibited by kaempferol treatment in A549 cells [53].

In summary, the main GYS ingredients targeted multiple functions, and many overlapping targets were found for each of the principle components, indicating that the activity of GYS could be amplified through synergy between its compounds. These studies support the hypothesis that GYS can effectively treat mastitis by eliminating inflammation through the synergistic interaction of its bioactive components. However, as the interaction between the various GYS components plays an essential anti-mastitis role, it still needs to be determined if specific doses and proportions of quercetin, luteolin, and kaempferol would have anti-mastitis effects similar to GYS.

GO enrichment screening showed that the effectiveness of GYS therapy was primarily a result of its influence on the inflammatory response through the processes of apoptosis, hypoxia, and cellular response to LPS. In the present study, most of the proteins involved were distributed in the extracellular space, and the primary molecular functions included protein binding, enzyme binding, and cytokine activity. Moreover, using PPI network analysis, we determined that TNF, IL-6, IL-1β, CXCL8, and ICAM1 proteins were the main targets of GYS for mastitis treatment. Previous reports emphasized the central role of TNF-α as a regulator of immunity, and confirmed that the TNF-α signaling pathway was essential for regulating the inflammatory response [54, 55]. In line with our hub gene identification, studies have reported that the cytokines TNF-α and IL-6 were most frequently associated with the inflammatory response. TNF-α increased the secretion of IL-6 and other cytokines and exacerbated mastitis-induced tissue damage through excess ROS [56]. Additionally, according to our KEGG pathway results, eleven pathways were significantly enriched. We found that GYS mainly interfered with mastitis through the PI3K-Akt signal pathway [57], the MAPK pathway [56], the TNF signaling [58], the AGE-RAGE pathway, and the fluid-shear stress and atherosclerosis pathways, which are closely related to the reported pathology of mastitis [59, 60].

The KEGG enrichment report revealed that the AGE-RAGE pathway was another player in the anti-mastitis activity of GYS, as it was correlated with the progression of mastitis in diabetic complications [61]. Additional investigations showed significant anti-inflammatory effects of AGE-RAGE inhibition in diabetic complications [61, 62]. Notably, the three target genes, COL1, MMP2, and SELE, in AGE-RAGE signaling can all be affected by quercetin [63], which suggests that quercetin may be the most promising GYS compound for mastitis therapy. The AGE-RAGE pathway in diabetes plays a vital role in developing mastitis, including the expression and release of proinflammatory cytokines causing tissue destruction [64].

It was also claimed that the downstream PI3K/Akt signal transduction pathway can be activated by AGE and RAGE. The PI3K/Akt pathway is crucial for growth, survival, metabolism, proliferation, transcription, and protein synthesis [65]. The study revealed that the PI3K/Akt pathway altered the expression of tight-junction proteins, protected the integrity of the blood-milk barrier, and reduced murine mastitis [66]. Intriguingly, GYS was also beneficial in other inflammatory diseases, such as intrauterine adhesion and suppurative otitis media [67, 68]. The inflammatory response to intrauterine adhesions can increase IL-6 and TNF-α in menstrual effluent in the uterus [18], and GYS treatment significantly reduced expression of the pro-inflammatory cytokines in rats with endometritis [69]. Our molecular docking analysis revealed that TNF and IL-6 were primary targets for interaction with the active GYS constituents, quercetin, and luteolin, against mastitis. The results revealed that the binding energy between GYS components and relevant targets was less than -5 kcal/mol [70], which suggested that TNF and IL-6 might be the primary targets of GYS in mastitis treatment. Thus, GYS may be one of the best TCM formulations for treating inflammatory conditions involving elevated TNF and IL-6 levels.

In animal metabolism, the production and elimination of ROS requires a dynamic balance [71]. The enzymatic defense system is one of the two systems with high free-radical scavenging capability. It is comprised principally of superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px), which effectively remove free radicals and terminate free radical chain reaction [72]. Zhao et al. [73] found that the body’s defensive antioxidant capacity against free radicals was closely related to overall health status. Yin et al. [74] found that the SOD, GSH-Px, and CAT activity in the serum of cows with mastitis were significantly inhibited compared with the control group. It is speculated that the decreased antioxidant activity in the serum of diseased cows results in the accumulation of free radicals, and more severe pathological outcomes of mastitis. Jin et al. [75] treated cows with latent mastitis with anti-inflammatory lactation granules (composed of dandelion, honeysuckle vine, forsythias, etc.), and showed a dramatic decrease in MDA content compared to control treatment. At the same time, T-AOC and SOD were significantly increased. Thus, dandelion, honeysuckle, and other traditional Chinese medicines have an excellent scavenging effect on MDA produced in the body and can improve SOD activity and T-AOC ability of the body to a certain extent. Improving the body’s antioxidant capacity indicates that the damaged mammary gland is gradually recovering [76].

Regarding limitations, some target genes and compounds may have been excluded from the public database because of the nature of the network pharmacology methodology. Although we identified quercetin, luteolin, kaempferol, beta-sitosterol, and stigmasterol as the active components of GYS, their comparability to GYS might be lacking. Additional in vivo and in vitro research must be done to test this hypothesis.

Our study was the first to identify the primary components, targets, and pathways of GYS responsible for its anti-inflammatory effects using network pharmacology and experimentation in a comprehensive manner. The data support the use of GYS as an effective add-on therapy for treating mastitis-related diseases.

Conclusions

In this paper, network pharmacology and molecular-docking analyses showed that quercetin, luteolin, and kaempferol were the main active components of GYS in mastitis treatment. The key targets, including TNF, IL-6, IL1β, ICAM1, and CXCL8, were obtained using Cytoscape and verified by molecular docking, which supported their essential role as anti-inflammatory agents. The identified targets were intimately associated with physiological functions such as inflammation, positive gene expression and apoptosis regulation, and the responses to hypoxia and LPS. GYS appears to act against mastitis primarily via the TNF and PI3K-Akt signaling pathways. This research establishes a strong foundation for further investigation into the anti-inflammatory effects of GYS and enhances our understanding of the underlying mechanisms.

References

  1. 1. Li X, Tang H, Tang Q, Chen W. Decoding the mechanism of huanglian jiedu decoction in treating pneumonia based on network pharmacology and molecular docking[J]. Front Cell Dev Biol. 2021;9:638366. pmid:33681222
  2. 2. Aitken SL, Corl CM, Sordillo LM. Immunopathology of mastitis: insights into disease recognition and resolution[J]. J Mammary Gland Biol Neoplasia. 2011;16(4):291–304. pmid:21938490
  3. 3. Mao J. Detection of main pathogenic bacteria of cow mastitis based on PCR technique[J].The Chinese Livestock and Poultry Breeding. 2023;19(10):170–174.
  4. 4. McDougall S, Clausen L, Hintukainen J, Hunnam J. Randomized, controlled, superiority study of extended duration of therapy with an intramammary antibiotic for treatment of clinical mastitis[J]. J Dairy Sci. 2019;102(5):4376–4386. pmid:30879816
  5. 5. Gurao A, Kashyap SK, Singh R. β-defensins: An innate defense for bovine mastitis[J]. Vet World. 2017;10(8):990–998.
  6. 6. Ngassam-Tchamba C, Duprez JN, Fergestad M, De Visscher A, L’Abee-Lund T, De Vliegher S, et al. In vitro and in vivo assessment of phage therapy against Staphylococcus aureus causing bovine mastitis[J]. J Glob Antimicrob Resist. 2020;22:762–770. pmid:32645442
  7. 7. Pellegrino MS, Frola ID, Natanael B, Gobelli D, Nader-Macias MEF, Bogni CI. In vitro characterization of lactic acid bacteria isolated from bovine milk as potential probiotic strains to prevent bovine mastitis[J]. Probiotics Antimicrob Proteins. 2019;11(1):74–84. pmid:29297159
  8. 8. Orellano MS, Isaac P, Breser ML, Bohl LP, Conesa A, Falcone RD, et al. Chitosan nanoparticles enhance the antibacterial activity of the native polymer against bovine mastitis pathogens[J]. Carbohydr Polym. 2019;213:1–9. pmid:30879647
  9. 9. Karaman R, Jubeh B, Breijyeh Z. Resistance of gram-positive bacteria to current antibacterial agents and overcoming approaches[J]. Molecules. 2020;25(12):2888. pmid:32586045
  10. 10. Deng HX, Zhang CS, Yong K, Tang HQ, Yang DY, Yao XP, et al. The effect of gongying power and astragalus to acute phase proteins concentrations in serum of rabbits with experimental mastitis[J]. China Animal Husbandry & Veterinary Medicine. 2011;38(5):170–173.
  11. 11. Zhang T. Preliminary study on the treatment of mastitis in dairy cow with “Gong Yingsan”[J]. China Dairy. 2020(4):73–75.
  12. 12. Deng XX, Jiao YN, Hao HF, Xue D, Bai CC, Han SY. Taraxacum mongolicum extract inhibited malignant phenotype of triple-negative breast cancer cells in tumor-associated macrophages microenvironment through suppressing IL-10 / STAT3 / PD-L1 signaling pathways[J]. J Ethnopharmacol. 2021;274:113978. pmid:33716082
  13. 13. Li H, Hung A, Li M, Yang AWH. Fritillariae thunbergii bulbus: traditional uses, phytochemistry, pharmacodynamics, pharmacokinetics and toxicity[J]. Int J Mol Sci. 2019;20(7):1667. pmid:30987173
  14. 14. Zhang JB, Jin HL, Feng XY, et al. The combination of Lonicerae Japonicae Flos and Forsythiae Fructus herb-pair alleviated inflammation in liver fibrosis. Front Pharmacol. 2022;13:984611. Published 2022 Aug 19. pmid:36059967
  15. 15. Kwok CT, Chow FW, Cheung KY, Zhang X, Mok DK, Kwan Y, et al. Medulla Tetrapanacis water extract alleviates inflammation and infection by regulating macrophage polarization through MAPK signaling pathway[J]. Inflammopharmacology. pmid:37429999
  16. 16. Leitner G, Zilberman D, Papirov E, Shefy S. Assessment of acoustic pulse therapy (APT), a non-antibiotic treatment for dairy cows with clinical and subclinical mastitis[J]. PLoS One. 2018;13(7):e0199195. pmid:29990317
  17. 17. Sun Y, Wu Y, Wang Z, Chen J, Yang Y, Dong G. Dandelion extract alleviated lipopolysaccharide-induced oxidative stress through the Nrf2 pathway in bovine mammary epithelial cells[J]. Toxins (Basel). 2020;12(8):496. pmid:32752301
  18. 18. Wang FL. Treatment of suppurative otitis media with Longmukufan Bingpian Gongying powder. China’s Naturopathy 2015;23(30): 30–31.
  19. 19. He RX,Cao YQ,Wang ZY, Sun Y, Shen HY, Zhang SZ, et al. Study on response surface method optimization of ultrasonic-assisted extraction process parameters for gongying powder and its antibacterial and antioxidant properties[J].Chinese Journal of Animal Nutrition. 1–13[2023-12-11].
  20. 20. Pan KS, Dai DH, Hou JQ, Xin YL, Tang X, Li QY, et al. Clinical treatment efficacy of gongying qiaolu powder on dairy cow mastitis[J]. Progress in Veterinary Medicine. 2022, 43(8): 138–141.
  21. 21. Guo B, Zhao C, Zhang C, Xiao Y, Yan G, Liu L, et al. Elucidation of the anti-inflammatory mechanism of Er Miao San by integrative approach of network pharmacology and experimental verification[J]. Pharmacol Res. 2022;175:106000. pmid:34838694
  22. 22. Pinzi L, Rastelli G. Molecular docking: shifting paradigms in drug discovery[J]. Int J Mol Sci. 2019;20(18):4331. pmid:31487867
  23. 23. Abdelsattar AS, Dawoud A, Helal MA. Interaction of nanoparticles with biological macromolecules: a review of molecular docking studies[J]. Nanotoxicology. 2021;15(1):66–95. pmid:33283572
  24. 24. Ru J, Li P, Wang J, Zhou W, Li B, Huang C, et al. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines[J]. J Cheminform. 2014;6:13. pmid:24735618
  25. 25. Ai Z, Zhou S, Li W, Zhou SS, Wang MF, Wang LQ, et al. "Fei Yan No. 1" as a combined treatment for COVID-19: an efficacy and potential mechanistic study[J]. Front Pharmacol. 2020;11:581277. pmid:33132913
  26. 26. Xu HY, Zhang YQ, Liu ZM, Chen T, Lv CY, Tang SH, et al. ETCM: an encyclopaedia of traditional Chinese medicine[J]. Nucleic Acids Res. 2019;47(D1):D976–D982. pmid:30365030
  27. 27. Xu X, Zhang W, Huang C, Li Y, Yu H, Wang Y, et al. A novel chemometric method for the prediction of human oral bioavailability[J]. Int J Mol Sci. 2012;13(6):6964–6982. pmid:22837674
  28. 28. Jia CY, Li JY, Hao GF, Yang GF. A drug-likeness toolbox facilitates ADMET study in drug discovery[J]. Drug Discov Today. 2020;25(1):248–258. pmid:31705979
  29. 29. Huang S, Zhang Z, Li W, Kong F, Yi P, Huang J, et al. Network pharmacology-based prediction and verification of the active ingredients and potential targets of zuojinwan for treating colorectal cancer[J]. Drug Des Devel Ther. 2020;14:2725–2740. pmid:32764874
  30. 30. Stelzer G, Rosen N, Plaschkes I, Zimmerman S, Twik M, Fishilevich S, et al. The genecards suite: from gene data mining to disease genome sequence analyses[J]. Curr Protoc Bioinformatics. 2016;54:1.30.1–1.30.33. pmid:27322403
  31. 31. Huang da W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources[J]. Nat Protoc. 2009;4(1):44–57. pmid:19131956
  32. 32. Trott O, Olson AJ. AutoDock vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading[J]. J Comput Chem. 2010;31(2):455–61. pmid:19499576
  33. 33. Lai Z, Jian Q, Li G, Shao C, Zhu Y, Yuan X, et al. Self-assembling peptide dendron nanoparticles with high stability and a multimodal antimicrobial mechanism of action[J]. ACS Nano. 2021;15(10):15824–15840. pmid:34549935
  34. 34. Zhu HX, Li TG, Zhao JY. Clinicl effect of “Gong Ying San” for cow mastitis[J]. China Animal Health. 2011;13(2): 14–17.
  35. 35. Jiang M, Lv Z, Huang Y, Cheng Z, Meng Z, Yang T, et al. Quercetin alleviates lipopolysaccharide-induced inflammatory response in bovine mammary epithelial cells by suppressing TLR4/NF-κB signaling pathway[J]. Front Vet Sci. 2022;9:915726. pmid:35865878
  36. 36. Rimoldi SG, Pileri P, Mazzocco MI, Romeri F, Bestetti G, Calvagna N, et al. The role of staphylococcus aureus in mastitis: a multidisciplinary working group experience[J]. J Hum Lact. 2020;36(3):503–509. pmid:31593644
  37. 37. Novac CS, Andrei S. The impact of mastitis on the biochemical parameters, oxidative and nitrosative stress markers in goat’s milk: a review[J]. Pathogens. 2020;9(11):882. pmid:33114454
  38. 38. Cushnie TP, Lamb AJ. Recent advances in understanding the antibacterial properties of flavonoids[J]. Int J Antimicrob Agents. 2011;38(2):99–107. pmid:21514796
  39. 39. Halliwell B, Rafter J, Jenner A. Health promotion by flavonoids, tocopherols, tocotrienols, and other phenols: direct or indirect effects? Antioxidant or not[J]? Am J Clin Nutr. 2005;81(1 Suppl):268S–276S. pmid:15640490
  40. 40. Chen P, Yang J, Wu N, Han B, Kastelic JP, Gao J. Streptococcus lutetiensis induces autophagy via oxidative stress in bovine mammary epithelial cells[J]. Oxid Med Cell Longev. 2022;2022:2549772. pmid:35178153
  41. 41. Ramesh P, Jagadeesan R, Sekaran S, Dhanasekaran A, Vimalraj S. Flavonoids: classification, function, and molecular mechanisms involved in bone remodelling[J]. Front Endocrinol (Lausanne). 2021;12:779638. pmid:34887836
  42. 42. Cao L, Wang T, Mi X, Ji P, Zhao X, Zhang Y. Exploring the action mechanism of the active ingredient of quercetin in ligustrum lucidum on the mouse mastitis model based on network pharmacology and molecular biology validation[J]. Evid Based Complement Alternat Med. 2022;2022:4236222. pmid:35722145
  43. 43. Kashyap D, Mittal S, Sak K, Singhal P, Tuli HS. Molecular mechanisms of action of quercetin in cancer: recent advances[J]. Tumour Biol. 2016;37(10):12927–12939. pmid:27448306
  44. 44. Conti P, Caraffa A, Gallenga CE, Ross R, Kritas SK, Fradas I, et al. Powerful anti-inflammatory action of luteolin: potential increase with IL-38[J]. Biofactors. 2021;47(2):165–169. pmid:33755250
  45. 45. Xiang H, Shao M, Lu Y, Wang J, Wu T, Ji G. Kaempferol alleviates steatosis and inflammation during early non-alcoholic steatohepatitis associated with liver X receptor α-lysophosphatidylcholine acyltransferase 3 signaling pathway[J]. Front Pharmacol. 2021;12:690736.
  46. 46. Wang J, Fang X, Ge L, Cao F, Zhao L, Wang ZZ, et al. Antitumor, antioxidant and anti-inflammatory activities of kaempferol and its corresponding glycosides and the enzymatic preparation of kaempferol[J]. PLoS One. 2018;13(5):e0197563. pmid:29771951
  47. 47. Mushtaq S, Aga MA, Qazi PH, Ali MN, Shah AM, Lone SA, et al. Isolation, characterization and HPLC quantification of compounds from Aquilegia fragrans Benth: Their in vitro antibacterial activities against bovine mastitis pathogens[J]. J Ethnopharmacol. 2016;178:9–12. pmid:26631757
  48. 48. Fan Y, Shen J, Liu X, Cui J, Liu J, Peng DQ, et al. β-Sitosterol suppresses lipopolysaccharide-induced inflammation and lipogenesis disorder in bovine mammary epithelial cells[J]. Int J Mol Sci. 2023;24(19):14644.
  49. 49. Sampath SJP, Rath SN, Kotikalapudi N, Venkatesan V. Beneficial effects of secretome derived from mesenchymal stem cells with stigmasterol to negate IL-1β-induced inflammation in-vitro using rat chondrocytes-OA management[J]. Inflammopharmacology. 2021;29(6):1701–1717. pmid:34546477
  50. 50. Fei J, Liang B, Jiang C, Ni H, Wang L. Luteolin inhibits IL-1β-induced inflammation in rat chondrocytes and attenuates osteoarthritis progression in a rat model[J]. Biomed Pharmacother. 2019;109:1586–1592. pmid:30551412
  51. 51. Guo YF, Xu NN, Sun W, Zhao Y, Li CY, Guo MY. Luteolin reduces inflammation in Staphylococcus aureus-induced mastitis by inhibiting NF-kB activation and MMPs expression[J]. Oncotarget. 2017;8(17):28481–28493. pmid:28415707
  52. 52. Cao R, Fu K, Lv X, Li W, Zhang N. Protective effects of kaempferol on lipopolysaccharide-induced mastitis in mice[J]. Inflammation. 2014;37(5):1453–8. pmid:24743918
  53. 53. Chen CC, Chow MP, Huang WC, Lin YC, Chang YJ. Flavonoids inhibit tumor necrosis factor-alpha-induced up-regulation of intercellular adhesion molecule-1 (ICAM-1) in respiratory epithelial cells through activator protein-1 and nuclear factor-kappaB: structure-activity relationships[J]. Mol Pharmacol. 2004;66(3):683–93.
  54. 54. Willemsen J, Neuhoff MT, Hoyler T, Noir E, Tessier C, Sarret S, et al. TNF leads to mtDNA release and cGAS/STING-dependent interferon responses that support inflammatory arthritis[J]. Cell Rep. 2021;37(6):109977. pmid:34758308
  55. 55. Zhou Y, Zhang M, Zhao X, Feng J. Ammonia exposure induced intestinal inflammation injury mediated by intestinal microbiota in broiler chickens via TLR4/TNF-α signaling pathway[J]. Ecotoxicol Environ Saf. 2021;226:112832. pmid:34583273
  56. 56. Ge Q, Chen L, Tang M, Zhang S, Liu L, Gao L, et al. Analysis of mulberry leaf components in the treatment of diabetes using network pharmacology[J]. Eur J Pharmacol. 2018;833:50–62. pmid:29782863
  57. 57. Chung JY, Lu M, Yin Q, Wu H. Structural revelations of TRAF2 function in TNF receptor signaling pathway[J]. Adv Exp Med Biol. 2007;597:93–113. pmid:17633020
  58. 58. Ding F, Luo X, Tu Y, Duan X, Liu J, Jia L, et al. Alpk1 sensitizes pancreatic beta cells to cytokine-induced apoptosis via upregulating TNF-α signaling pathway[J]. Front Immunol. 2021;12:705751. pmid:34621265
  59. 59. Gan XX, Zhong LK, Shen F, Feng JH, Li YY, Li SJ, et al. Network pharmacology to explore the molecular mechanisms of prunella vulgaris for treating hashimoto’s thyroiditis[J]. Front Pharmacol. 2021;12:700896. pmid:34690752
  60. 60. Noack M, Miossec P. Selected cytokine pathways in rheumatoid arthritis[J]. Semin Immunopathol. 2017;39(4):365–383. pmid:28213794
  61. 61. Linton MF, Moslehi JJ, Babaev VR. Akt signaling in macrophage polarization, survival, and atherosclerosis[J]. Int J Mol Sci. 2019;20(11):2703. pmid:31159424
  62. 62. Wang S, Wang Y, Han B, Chen Y, Bai X, Yu S, et al. Huanglian ointment alleviates eczema by maintaining the balance of c-Jun and JunB and inhibiting AGE-RAGE-mediated pro-inflammation signaling pathway[J]. Phytomedicine. 2022;105:154372. pmid:35932609
  63. 63. Yu W, Tao M, Zhao Y, Hu X, Wang M. 4’-Methoxyresveratrol alleviated aGE-Induced inflammation via RAGE-mediated NF-κB and NLRP3 inflammasome pathway[J]. Molecules. 2018;23(6):1447. pmid:29903983
  64. 64. Wang W, Chen Z, Zheng T, Zhang M. Xanthohumol alleviates T2DM-induced liver steatosis and fibrosis by mediating the NRF2/RAGE/NF-κB signaling pathway[J]. Future Med Chem. 2021;13(23):2069–2081. pmid:34551612
  65. 65. Xiong W, Zhao J, Ma X, Feng Z. Mechanisms and molecular targets of BuShenHuoXue Formula for Osteoarthritis[J]. ACS Omega. 2022;7(5):4703–4713. pmid:35155962
  66. 66. Wu Z, Yang Q, Ma H. Study the mechanism of gualou niubang decoction in treating plasma cell mastitis based on network pharmacology and molecular docking[J]. Biomed Res Int. 2022;2022:5780936. pmid:35757473
  67. 67. Hou Y, Wang K, Wan W, Cheng Y, Pu X, Ye X. Resveratrol provides neuroprotection by regulating the JAK2/STAT3/PI3K/AKT/mTOR pathway after stroke in rats[J]. Genes Dis. 2018;5(3):245–255. pmid:30320189
  68. 68. Yuan FL, Jia SH and Jiang Y. The curative effect of hysteroscopic adhesion resection combined with compound Gonging powder for treating woman with intrauterine adhesion, and the changes of serum IL- 6, IL-10 and TNF-α[J]. Chinese Journal of Family Planning. 2021;29(1): 25–27+32.
  69. 69. Min L. Effect of compound Gongying powder on expression of IL-8 and TNF-A in intrauterine adhesions of rats[J]. Journal of Practical Traditional Chinese Medicine. 2018;34(7): 756–757.
  70. 70. Zhang J, Zhou Y, Ma Z. Multi-target mechanism of Tripteryguim wilfordii Hook for treatment of ankylosing spondylitis based on network pharmacology and molecular docking[J]. Ann Med. 2021;53(1):1090–1098. pmid:34259096
  71. 71. Floyd RA. Serendipitous findings while researching oxygen free radicals[J]. Free Radic Biol Med. 2009;46(8):1004–13. pmid:19439210
  72. 72. Li JX, Yang ZQ and Wang XZ. Biological function of reactive oxygen free radicals in animals[J]. Progress in Veterinary Medicine. 2006(10):33–36.
  73. 73. Zhao CY. Effects of flavonoids from allium mongolicum on antioxidant capacity in mice[J]. Feed Industry. 2009;30(24): 10–13.
  74. 74. Yi BS, Li JY, Hu XS, Cui YZ, Hao JF. Activity of antioxidant enzyme in serum of cow with mastitis[J]. Chinese Journal of Veterinary Science. 2012;32(7): 1053–1055.
  75. 75. Jin LM, Wu QL, Jin BF, Xu SY, Ma GM, Ge JM. Effect of lactation & anti-infLammatory granuLe on the metaboLism of certain serum free radicaLs of dairy cattLe showing subcLinicaL mastitis[J]. Chinese Journal of Veterinary Medicine. 2010;46(12): 59–61.
  76. 76. Deng HX, Yong K, Zhang CS, Yang QW. Effect of lipopolysaccharide (LPS) infusion via teat canal on antioxidant capacity in rabbits[J]. Journal of Southern Agriculture. 2012;43(7): 1046–1048.