Abstract

   graphic file with name ao2c07366_0013.jpg

   Asthma is a chronic respiratory disease. Bergamot essential oil (BEO)
   is extracted from the bergamot peel, which is widely used as a
   medicinal and food plant in China. Modern pharmacological studies have
   confirmed that BEO has anti-inflammatory properties, suggesting
   potential in treating asthma. First, the main active ingredients of BEO
   were detected and analyzed by gas chromatography–mass spectrometry
   (GC-MS). Network pharmacology methods were used to explore the possible
   core targets and main pathways of BEO in asthma treatment. Then
   ovalbumin (OVA)-induced in vivo and lipopolysaccharide (LPS)-induced in
   vitro models were established to investigate the antiasthmatic effects
   of BEO. BEO showed a good antiasthmatic effect by improving lung
   inflammation and inhibiting collagen deposition. Then, enzyme-linked
   immunosorbent assay (ELISA) and quantitative real-time polymerase chain
   reaction (qPCR) were used to explore the possible mechanism of BEO in
   asthma treatment. Furthermore, experimental verification showed that
   BEO could suppress the release of inflammatory factors in vitro and
   inhibit the activation of MAPK and JAK-STAT signaling pathways. This
   study demonstrated the anti-inflammatory effects of BEO against asthma.
   Moreover, it supplies a theoretical basis for the clinical application
   of BEO.

1. Introduction

   Asthma is a chronic inflammatory airway disease that can develop onset
   in all age groups and is characterized by airway inflammation and
   hyperresponsiveness. During the second half of the past century, the
   number of asthma cases rapidly increased worldwide, causing at least
   495000 deaths per year.^[32]1,[33]2 The factors that play a role in
   asthma pathogenesis are mainly viral or bacterial respiratory tract
   infections, allergy or defective antiviral immunity, allergen exposure,
   and environmental factors.^[34]3 Childhood asthma is more common in
   boys, while adult asthma is more common in women, which might may be
   related to sex hormones.^[35]4 It is currently believed that the
   pathogenesis of asthma is related to inflammation and immune
   regulation.^[36]5 Current asthma treatments utilize inhaled
   corticosteroids, long-acting β-agonists, and leukotriene antagonists to
   control and reduce asthma exacerbations.^[37]3 However, these
   approaches do not eliminate all exacerbations, particularly in patients
   with severe asthma.^[38]6 Targeted biological therapy is also being
   developed, such as anti-IgE (omalizumab) and anti-interleukin (IL)-5
   medications.^[39]3 Moreover, the current treatment methods are
   insufficient due to drug resistance and side effects.^[40]7 Thus,
   because existing approaches are insufficient for asthma management, the
   need for new interventions is urgent.

   Traditional Chinese medicine (TCM) has a long history in the treatment
   of asthma, called “Xiao Zheng”. Numerous clinical cases have confirmed
   the therapeutic effect of Chinese medicine on asthma due to the
   synergistic effect of each component and target of Chinese medicine and
   the low level of toxic side effects.^[41]8

   Natural products have potential advantages in anti-inflammation. As an
   increasing number of studies are performed, more and more mechanisms of
   anti-inflammatory action of herbal medicines are being
   discovered.^[42]9−[43]12 In recent years, essential oils have been
   greatly developed for their remarkable biological activity and health
   benefits, playing a huge role as a safe alternative therapy.^[44]13
   Bergamot (Citrus medica L. var. sarcodactylis Swingle) is an important
   edible and medicinal plant.^[45]14 Bergamot essential oil (BEO),
   extracted from the bergamot peel, has significant antiallergic,
   anti-inflammatory, analgesic, and anticancer effects.^[46]15,[47]16

   Terpenoids such as d-limonene and γ-pinene are the main components of
   BEO. d-Limonene relaxes the tracheal smooth muscle of guinea
   pigs.^[48]17 Inhaling d-limonene reduces peribronchial and perivascular
   inflammatory cell infiltration and prevents bronchial
   obstruction.^[49]18 Molecular docking and animal studies have revealed
   that d-limonene reduces airway reactivity and inflammation through the
   activation of A[2A] and A2B.^[50]19 Combined with the anti-inflammatory
   effect of BEO, we speculate that d-limonene has a certain role in
   treating asthma and relieving airway inflammation.

   TCM offers distinct advantages in disease treatment because it
   emphasizes the holistic concept. The composition of TCM drugs is
   complicated, and there has been a lack of effective research
   methods.^[51]20 Network pharmacology is an effective method for us to
   understand Chinese medicine treating different diseases.^[52]21 Gene
   targets predicted by chemical components of TCM drugs have been
   associated with disease genes by building a relevant disease gene
   library. Constructing protein–protein interaction (PPI) networks to
   identify protein–drug relationships and selecting components and
   regulatory gene targets that play a role in a disease can be used to
   understand the mechanisms of action of herbal medicines in treating
   that disease.^[53]22,[54]23 With network pharmacology, we can
   understand and utilize drugs more precisely to intervene in
   diseases.^[55]24 Cyber pharmacology is an effective way to understand
   how we can treat diseases with TCM. By building a library of relevant
   disease genes, gene targets predicted by the chemical composition of
   TCM are associated with disease genes.

   In this study, gas chromatography–mass spectrometry (GC-MS) was used to
   qualitatively and quantitatively analyze the chemical composition of
   BEO. GC-MS is a more precise and accurate method of compositional
   analysis than high-performance liquid chromatography (HPLC) and liquid
   chromatography–mass spectrometry (LC-MS).^[56]25 Then, a network
   pharmacology strategy was applied to obtain the potential targets,
   underlying pathways, and the therapeutic mechanism of BEO against
   asthma. Finally, we validated the predicted pharmacologic mechanism of
   BEO in vivo and in vitro. Our study is the first to demonstrate the
   effect of BEO on asthma using a network pharmacology method combined
   with experiments. Currently, there is a limited number of drugs for the
   treatment of asthma, which cannot fully meet the needs of clinical
   treatment and have many side effects after prolonged use. Thus, there
   is an urgent need for new drugs, and BEO from natural plants is a safer
   and effective option, providing prospects for the development of new
   drugs.

2. Results

2.1. Identification of Main Components of BEO and Comparison with the
Standard

   There was a total of 27 components identified, the majority of which
   were terpene components. The proportion of d-limonene and γ-terpinene
   in BEO was 42.5% and 18.9%, respectively. The main components were
   compared with the standard d-limonene (S1) and γ-pinene (S2) to ensure
   the quality of the BEO, and the main components and total ion
   chromatogram monitored are shown in [57]Figure S1 and [58]Table S1.

2.2. Obtained BEO Component Targets and Asthma Disease Targets

   After removing duplicates, 365 putative targets of BEO components were
   obtained from the Swiss Target Prediction and Drugbank databases. By
   intersecting disease targets with the constituent targets of BEO, 224
   targets were obtained. These are thought to be potential targets for
   BEO asthma treatment.

2.3. PPI Network Construction and Key Target Selection

   The PPI network was visualized and analyzed by Cytoscape software, and
   the values of Betweenness Centrality, Closeness Centrality, and Degree
   were calculated by using plug-in network analysis. The median values
   were calculated separately, and the genes with topological feature
   values greater than the median were selected as the core genes
   (Betweenness Centrality > 0.001018, Closeness Centrality > 0.301724,
   and Degree > 3). The PPI networks are shown in [59]Figures [60]1
   and [61]2.

Figure 1.

   [62]Figure 1
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   PPI network diagram with interaction score set to 0.9.

Figure 2.

   Figure 2
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   Diagram of PPI key targets. Larger circles and darker red in the figure
   represent more important targets.

2.4. GO Enrichment Analysis and KEGG Pathway Enrichment Analysis

   The above-mentioned 46 key targets were recorded into the DAVID
   database for Gene Ontology (GO) enrichment analysis and Kyoto
   Encyclopedia of Genes and Genomes (KEGG) pathway enrichment to
   investigate the potential mechanism of BEO in asthma treatment. As
   shown in the graph, biological process (BP), cellular component (CC),
   and molecular function (MF) were among the top ten processes. Thus, the
   biological processes involved in BEO action in asthma were the JAK-STAT
   cascade reaction involved in the growth hormone signaling pathway, the
   positive regulation of transcription by RNA polymerase II promoter, the
   cellular response to lipopolysaccharide, signal transduction, cell
   differentiation, intracellular signaling, protein phosphorylation, the
   cellular response to reactive oxygen species, the interleukin-6
   mediated signaling pathway.

   The data from the KEGG enrichment analysis obtained in the DAVID
   database were processed. As the disease was caused by an underlying
   biological dysfunction, the enriched disease fraction was removed. The
   top 20 pathways were selected as the main pathways for the treatment of
   asthma with BEO. The smaller the value of P adjusted, the more
   significant the pathway, suggesting a higher correlation with the
   disease. The enriched pathways were classified into inflammatory
   immune-related pathways (JAK-STAT signaling pathway, IL-17 signaling
   pathway, tumor necrosis factor signaling pathway, T-cell receptor
   signaling pathway, nuclear factor-kappa B signaling pathway, Fc epsilon
   RI signaling pathway, chemokine signaling pathway, natural killer
   cell-mediated cytotoxicity, nod-like receptor signaling pathway,
   adipocytokine signaling pathway, and toll-like receptor signaling
   pathway), signal transduction-related pathways (PI3K-Akt signaling
   pathway, FoxO signaling pathway, Ras signaling pathway, ErbB signaling
   pathway, MAPK signaling pathway, Rap1 signaling pathway, and cAMP
   signaling pathway), and circulatory system-related pathways (VEGF
   signaling pathway and HIF-1 signaling pathway), as shown in [65]Figures
   [66]3
   and [67]4.

Figure 3.

   Figure 3
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   Bubble diagram of KEGG enrichment analysis. Analyses of the 46 key
   targets using the KEGG database.

Figure 4.

   [69]Figure 4
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   Histogram of GO enrichment analyses. GO enrichment analyses of 46 key
   targets by the DAVID database. Green represented the biological process
   (BP), orange represented the cellular component (CC), and blue
   represented the molecular function (MF).

2.5. Compound-Target-Pathway Network Analysis

   Compounds, gene targets, and the top 20 pathways were imported into
   Cytoscape software, and a network was drawn for visual analysis. The
   compounds and targets were sorted by Degree value, from the highest to
   the lowest, with higher values indicating greater importance in the
   network. Among them, the key targets were mainly concentrated in the
   MAPK and JAK-STAT signaling pathways. The top ten key active
   ingredients, as predicted by the network pharmacology, were linoleic
   acid, α-linolenic acid, methyl linoleate, 11,14,17-eicosatrienoic acid,
   methyl ester, neryl acetate, n-hexadecanoic acid, dodecanoic acid,
   tetradecanoic acid, α-bisabolene, and α-terpineol, as shown in
   [71]Figure [72]5
   .

Figure 5.

   [73]Figure 5
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   Compound-target-pathway network diagram. The green octagon represents
   the 27 compounds in BEO, the pink circular represents the key targets,
   the orange target represents the gene targets, and the violet diamond
   represents the top 20 pathways The key signaling pathways, i.e., MAPK
   and JAK-STAT signaling pathways, are listed separately in the blue
   diamond.

2.6. BEO Can Alleviate OVA-Induced Asthma In Vivo

   An ovalbumin (OVA)-induced mouse model was constructed to verify the
   effect of inhaled BEO on asthma relief. [75]Figure [76]6
   shows a significant infiltration of inflammatory cells around the
   bronchi, narrowing of the airways, thickened bronchial airway walls,
   and collagen deposition around the airways in the model group compared
   to the control group. In the control group, lung tissue structure was
   normal, with no obvious inflammatory changes. After inhaling BEO,
   different degrees of improvement in lung inflammation and airway
   narrowing were observed by staining the inflammatory cells in
   bronchoalveolar lavage fluid (BALF). As shown in [77]Figure [78]7, the
   amount of inflammatory cells in the model group was significantly
   higher than that in the control group. There were significantly fewer
   positive cells in the BEO and budesonide groups. These findings
   suggested that inhaling BEO could significantly reduce lung
   inflammation. IL-4, IL-5, and IL-13 levels in BALF and lung tissue were
   measured using enzyme-linked immunosorbent assay (ELISA) and
   quantitative polymerase chain reaction (qPCR). When compared to the
   model group, different doses of BEO could reduce cytokine release and
   mRNA expression as shown in [79]Figure [80]8 A-F. IL-6, IL-1β, and
   tumor necrosis factor (TNF)-α were common inflammatory factors. The
   ameliorating effect of BEO on airway inflammation in asthma could be
   revealed by measuring the release of inflammatory factors by ELISA as
   shown in [81]Figure [82]8G–I. The detection of immunoglobulin (Ig)E in
   serum revealed that the BEO group had markedly decreased serum IgE
   levels as shown in [83]Figure [84]8J. These findings provide additional
   evidence that BEO could be used to treat asthma.

Figure 6.

   Figure 6
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   Lung tissue sections of each group with hematoxylin–eosin (HE) (A) and
   Masson staining (B).

Figure 7.

   Figure 7
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   Total inflammatory cells in mice BALF were isolated and quantified
   using a Diff-Quick-stained reagent.

Figure 8.

   [87]Figure 8
   [88]Open in a new tab

   Cytokines detected by qPCR and ELISA. Effect of inhaled BEO on the
   levels of IL-4, IL-5, and IL-13 in BALF (A–F) and IL-6, IL-1β, and
   TNF-α in BALF (G–I). Measurement of IgE levels in serum (J). Data are
   presented as the mean ± standard deviation (n = 3). ^#p < 0.05 and
   ^###p < 0.001 vs the control group; *p < 0.05, **p < 0.01, and ***p <
   0.001 vs the model group.

2.7. Exploration of the Potential Mechanism of BEO in the Treatment of Asthma

   We then performed a further experimental analysis of the core targets,
   combining the above-demonstrated network pharmacology results, to
   investigate the possible mechanism of BEO against asthma. BEO
   concentrations above 100 μg/mL could not be completely dissolved in the
   solvent, and large doses could also be considered ineffective drugs.
   Therefore, a BEO concentration of 100 μg/mL was chosen as the highest
   dose for the experiment. The CCK8 experiment demonstrated that there
   was no significant effect of BEO on MH-S at concentrations of 0–100
   μg/mL, no significant decrease in cell viability, and no statistical
   difference between the groups, as shown in [89]Figure [90]9
   A. Chronic inflammation is the underlying cause of asthma, and IL-6,
   IL-1β, and TNF-α are key proinflammatory factors. Thus, after
   lipopolysaccharide (LPS) treatment, there was a considerable increase
   in the mRNA and protein expression of IL-6, IL-1β, and TNF-α. According
   to results from qPCR and ELISA, the mRNA and protein expression of
   IL-6, IL-1β, and TNF-α were dramatically reduced after the addition of
   BEO. BEO could therefore effectively prevent the increase in of
   inflammatory factors, as shown in [91]Figure [92]9B–G.

Figure 9.

   [93]Figure 9
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   (A) Effect of BEO on cell viability of MH-S cells. MH-S cells were
   incubated with absolute ethanol (solvents for BEO) for 24 h as the
   control group. MH-S cells were incubated with different concentrations
   (0.01, 0.1, 1, 10, and 100 μg/mL) of BEO for 24 h as the administration
   group. CCK-8 assay was used to detect cell viability. Data are
   presented as the mean ± SD (n = 10) and compared with the control
   group. (B–D) Effect of BEO on mRNA expression of IL-6, IL-1β, and TNF-α
   in MH-S cells as detected by qPCR. (E–G) The effect of BEO on the
   expression of inflammatory factors IL-6, IL-1β, and TNF-α in MH-S cells
   was detected by ELISA. MH-S cells were incubated with absolute ethanol
   as the control group. MH-S cells were incubated with BEO (1, 10, and
   100 μg/mL) and LPS (0.1 μg/mL) for 24 h as the administration group.
   Data are presented as the mean ± SD (n = 3). ^#p < 0.05, ^##p < 0.01,
   and ^###p < 0.001 vs the control group; *p < 0.05, **p < 0.01, and ***p
   < 0.001 vs the model group.

2.8. Verification of Targets

   By using qPCR, the major targets of BEO for asthma treatment that
   network pharmacology predicted were validated. MAPK1, MAPK3, MAPK8,
   MAPK14, PPARA, PTGS2, STAT3, and JAK2 had a significantly greater mRNA
   expressions in the cells following LPS stimulation compared to the
   control group, and all mRNA expressions of the above-mentioned genes
   decreased to varying degrees after BEO administration. The findings
   showed that TCM has multi-pathway effects in asthma treatment and that
   the targets predicted by network pharmacology were trustworthy, as
   shown in [95]Figure [96]10
   .

Figure 10.

   [97]Figure 10
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   Effects of BEO on mRNA expression of key genes in MH-S cells. (A–H) The
   mRNA expressions of MAPK1, MAPK3, MAPK8, MAPK14, JAK2, STAT3, PTGS2,
   and PPARA were detected by qPCR. MH-S cells were incubated with
   absolute ethanol as a control group. MH-S cells were incubated with BEO
   (1, 10, and 100 μg/mL) and LPS (0.1 μg/mL) for 24 h as the
   administration group. Data are present the mean ± SD (n = 3). ^#p <
   0.05, ^##p < 0.01, and ^###p < 0.001 vs the control group; *p < 0.05,
   **p < 0.01, and ***p < 0.001 vs the LPS group.

3. Discussion

   The inflammatory response is an important molecular mechanism in
   asthma, and controlling the inflammatory response is the main treatment
   approach for asthma.^[99]26−[100]28 Currently, steroid hormones are
   considered the best way to control asthma inflammation, but they also
   do not cure or alter disease progression and have side effects with
   long-term use.^[101]8 There is a lack of experimental validation and
   mechanistic exploration of the mechanisms of Chinese herbal medicine in
   asthma treatment. BEO is a sesquiterpene compound derived from
   bergamot—a traditional Chinese herb commonly used to treat asthma,
   cough, and other respiratory disorders. BEO has demonstrated good
   anti-inflammatory effects in asthmatic mice.^[102]29

   In this study, we verified the effect of BEO in the treatment of
   OVA-induced asthma in mice. After OVA induction, mice showed increased
   inflammatory exudation and collagen deposition around the airways. We
   found that BEO effectively ameliorated the inflammatory changes around
   the airways and reduced the levels of inflammatory factors in BALF and
   IgE levels in serum. BEO also reduced the expression levels of
   asthma-related cytokines IL-4, IL-5, and IL-13. Combining compositional
   analysis, network pharmacology, and in vitro experiments, we explored
   the potential mechanisms of BEO for asthma treatment. The predicted
   relevant pathways and targets were mainly focused on MAPK and JAK-STAT
   signaling pathways. In asthma, the MAPK signaling pathway is primarily
   involved in inflammatory cell infiltration and immune response
   activation. Activation of the MAPK signaling pathway stimulates immune
   cells to produce a response releasing inflammatory factors and
   activating goblet cells to produce mucus, leading to airway
   hyperresponsiveness and mucus obstruction of the
   airway.^[103]30−[104]35 Bai et al. have found that OVA-induced
   inflammatory response to asthma could be attenuated by inhibiting MAPK
   activation.^[105]36 JAK-STAT is involved in inflammatory responses and
   immune regulation in asthma.^[106]37 A large body of clinical evidence
   also supports the idea that inhibiting the activation of targets in the
   JAK-STAT pathway can reduce asthma airway inflammation and
   hyperresponsiveness.^[107]38,[108]39 Calbet et al. have demonstrated
   that the inhalation of Pan-JAK inhibitor reduced airway inflammation
   and improved lung function in a rat OVA model^[109]40 Southworth et al.
   have demonstrated that JAK inhibitors reduce the production of
   inflammatory cytokines in asthma.^[110]41 Prostaglandin endoperoxide
   synthase 2 (PTGS2)/COX-2 is a key enzyme in prostaglandin
   biosynthesis.^[111]42−[112]44 Reducing the expression of PTGS2 further
   reduces the production of prostaglandin E2, decreases the inflammatory
   response, and reduces the possibility of inducing airway spasms and
   airway hyperresponsiveness.^[113]45,[114]46 Peroxisome
   proliferator-activated receptor alpha (PPARA) influences the expression
   of target genes involved in immune and inflammatory
   responses.^[115]47,[116]50 Previous studies have shown that PPARA is
   involved in lipid mediators common in the inflammatory
   response.^[117]48,[118]49 PPARA plays an important role in controlling
   the duration of the inflammatory response by regulating the metabolism
   of fatty acids and oxidative degradation of derivatives, which can
   subside.^[119]50,[120]51 Based on the experimental results, we found
   that BEO may have a positive effect on the treatment of asthma by
   downregulating MAPK, JAK-STAT pathway, and key genes PPARA and PTGS2.

Figure 11.

   [121]Figure 11
   [122]Open in a new tab

   Description of the main putative target of BEO for the treatment of
   airway inflammation of asthma. Through this analysis, the predicted
   targets in this project all regulate immune response and inflammatory
   factor secretion. The key targets are colored with yellow, and the pink
   prisms represent the BEO. BEO alleviates asthma by inhibiting these
   targets.

4. Conclusion

   In summary, the animal experiment has shown that BEO can be used to
   treat asthma. As the key targets predicted by network pharmacology and
   experimental validation, BEO might suppress the inflammation in asthma
   by modulating the MAPK pathway, JAK-STAT pathway PPARA, and PTGS2.
   However, there are shortcomings in our study, and further research is
   needed to determine whether there is a link between the active
   ingredient content of BEO and its antiasthma effects. Additionally, the
   safety of inhaled BEO needs to be investigated over the long term. BEO,
   a plant essential oil derived from a natural product, has great
   potential in relieving asthma. Our study provides a useful theoretical
   basis for investigating the antiasthma mechanism of BEO and offers new
   ideas for the development of asthma drugs.

5. Materials and Methods

5.1. Preparation of Bergamot Essential Oil

   Bergamot was purchased from Lingnan Chinese Medicine (Guangzhou, China)
   and identified by Doctor Ding Qi (Shenzhen Research Institute, Beijing
   University of Chinese Medicine, Beijing, China) as the dried fruit of
   Citrus medica L. var. sarcodactylis Swingle. Bergamot was crushed,
   soaked in 10 times the amount of purified water for 30 min, and then
   distilled by hydrodistillation for 2 h to obtain BEO. BEO was stored at
   −4 °C and used for detection and experimental validation.

5.2. GC-MS

   Component identification was performed by gas chromatography–mass
   spectrometry. GC conditions in a Shimadzu gas chromatograph (GC 2010
   plus, Kyoto, Japan) were column DB-5MS, carrier gas high-purity helium,
   flow rate inlet temperature 280 °C, 15 °C/min until 150 °C, and 20
   °C/min until 280 °C. Injection method: split; detector FID1 split
   ratio: 10:1. MS conditions were ion source temperature 230 °C,
   interface temperature 280 °C, and solvent delay time 1.5 min.

5.3. Target Prediction of Identified Components in BEO

   The 2D structure of the chemical composition was obtained by searching
   the composition of BEO in Pubchem
   ([123]https://pubchem.ncbi.nlm.nih.gov/).^[124]52 The structures were
   obtained by searching in Swiss target prediction
   ([125]http://swisstargetprediction.ch/),^[126]53 and Drugbank
   ([127]https://go.drugbank.com)^[128]54 was used to obtain the targets.
   Swiss Target Prediction is based on the known 2D and 3D structural
   similarities of compounds to predict the targets of compounds.
   Prediction can be performed in three different species: humans, rats,
   and mice. DrugBank is a bioinformatics and cheminformatics database
   provided by the University of Alberta that combines detailed drug data
   with comprehensive drug target information to predict drug targets and
   chemical composition. Detailed information is provided in [129]Table
   S2.

5.4. Target Prediction in Asthma

   By searching the keywords “asthma” in the Genecard and CTD databases, a
   total of 3829 asthma-related targets were identified. The Genecards
   database ([130]https://www.genecards.org/)^[131]55 contains disease
   relationships, gene expression, gene function, and protein–protein
   interactions and is a comprehensive database providing human genetic
   predictions. The CTD database ([132]http://ctdbase.org/)^[133]56 is an
   integrated database of a large number of chemicals, genes, functional
   phenotypes, and disease interactions. Detailed information is provided
   in [134]Table S3.

5.5. Protein–Protein Interaction Network Construction and Core Target
Selection

   The above-mentioned potential targets of BEO for asthma were imported
   into the String database ([135]https://cn.string-db.org/)^[136]57 to
   construct PPI protein interaction networks. Then the obtained PPI
   networks were imported into Cytoscape 3.9.0 software (Boston, MA) to
   construct visual networks. A network analyzer plug-in was used to
   calculate Betweenness Centrality, Closeness Degree, and Degree.
   Detailed information is provided in [137]Table S4.

5.6. GO and KEGG Signaling Pathway Analysis

   The collected potential targets were imported into the DAVID database
   ([138]https://david.ncifcrf.gov/)^[139]58 for GO enrichment and KEGG
   enrichment analyses. The GO enrichment analysis included BP, CC, and
   MF. We selected P(adjusted) < 0.05 as the confidence gene enrichment
   threshold setting.

5.7. Animal Experiments

   Balb/c female mice aged 6–8 weeks were purchased from Guangzhou Ruige
   Biological Technology Co., Ltd. (Guangzhou, China; animal license: SCXK
   (Yue) 2021-0059). Mice were divided into six groups 1 week after
   acclimatization: control, model, budesonide (AstraZeneca Pty Ltd.
   H20140475, North Ryde, Australia, 0.2 mg/mL), BEO low dose (20 mg/kg),
   BEO medium dose (40 mg/kg), and BEO high dose (80 mg/kg). The method of
   administration was inhalation. Each group had five mice. During the
   experiment, the mice were fed and watered as needed and kept in a 12/12
   h light/dark cycle. Except for the control group, mice were sensitized
   on days 0, 7, and 14 via intraperitoneal injection of 200 μL
   phosphate-buffered saline (PBS) (Gibco, New York) containing 10 μg of
   OVA (Sigma, St. Louis, MO) and 1 mg of aluminum hydroxide (Aladdin,
   Shanghai, China).^[140]59 On days 21–27, mice were nebulized for 30 min
   per day with 1% OVA and budesonide, with three BEO dose groups
   administered 30 min before each nebulization. On the 28th day, mice
   were sacrificed, and lung tissue, BALF, and blood were collected. The
   modeling method is shown in [141]Figure [142]12
   .

Figure 12.

   [143]Figure 12
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   Process of OVA-induced allergic asthma.

5.8. Histopathology and Stained Inflammatory Cells in BALF

   Lung tissue samples were fixed in a 4% paraformaldehyde (Biosharp,
   Shanghai, China) solution for 48 h and then embedded in paraffin wax
   for fixation. Paraffin-embedded sections were stained using
   hematoxylin–eosin (HE) and Masson trichrome staining to assess
   pathological changes in the lungs. The cell precipitate obtained after
   centrifugation of the collected BALF was resuspended in 100 μL of PBS
   to make smears, which were then stained with Diff-Quick Stain
   (Solarbio, Beijing, China) according to the manufacturer’s
   instructions. Inflammatory cells were observed under a light
   microscope.

5.9. Cell Culture and Treatment

   Mouse alveolar macrophages (MH-S) were purchased from Shanghai Fu Heng
   Bio, (Shanghai, China). MH-S were cultured in 1640 medium (Gibco, New
   York) with 10% fetal bovine serum (FBS) (Gibco, New York) at 37 °C and
   5% CO[2] in an incubator. The inflammation model was induced using LPS
   (Sigma, St. Louis, MO, 0.1 mg/mL).^[145]60,[146]61

5.10. BEO Toxicity Test

   The Cell Counting Kit-8 (CCK-8, MCE, Monmouth Junction, NJ) assay was
   used to detect the effect of BEO on the growth of MH-S cells and test
   whether BEO has toxic effects on MH-S cells. MH-S cells were inoculated
   in 96-well plates with 10000 cells per well at 100 μL medium. After 24
   h of inoculation and 4 h of starvation, the cells were treated with
   0.01, 0.1, 1, 10, and 100 μg/mL of BEO, and 10 μL of CCK-8 solution was
   added to each well after 24 h of incubation. The cells were incubated
   for 1 h at 37 °C in a 5% CO[2] incubator, and the absorbance was
   measured at 450 nm on an enzyme marker.

5.11. Quantitative Real-Time Polymerase Chain Reaction

   MH-S cells were inoculated in the six-well plate at 4 × 10^5 per well,
   cultured overnight, starved for 4 h, and then administered at 0, 1, 10,
   and 100 μg/mL. After stimulating the cells with LPS (0.1 μg/mL) for 24
   h, lung tissue samples were extracted using an RNA extraction kit.
   Total RNA was extracted with an RNA extraction kit (Tian Gen, Beijing,
   China) from the MH-S cells, and RNA concentration was measured before
   reverse transcription (HiScript II Q RT SuperMix, Vazyme, Nanjing,
   China). Total RNA (1000 ng) was further reverse transcribed into cDNA.
   The reversed samples were cyclically amplified with ChamQ SYBR qPCR
   Master Mix (Vazyme, Nanjing, China) in a RocheLightCycler 480 (Roche,
   Basel, Switzerland) using GAPDH as the internal reference gene. The
   relative expression levels of the target genes were determined using
   the 2^–ΔΔct calculation method. Primers were purchased from Sangon
   Biotech (Shanghai, China), and detailed information is shown in
   [147]Table [148]1
   .

Table 1. Primers Used for Quantitative Real-Time Polymerase Chain Reaction
(QPCR) Assay.

   target     forward (5′–3′)         reverse (5′–3′)
   GADPH  AAATGGTGAAGGTCGGTGTGAAC CAACAATCTCCACTTTGCCACTG
   IL-1β  GCAACTGTTCCTGAACTCAACT  ATCTTTTGGGGTCCGTCAACT
   IL-6   AGTCCTTCCTACCCCAATTTCC  TGGTCTTGGTCCTTAGCCAC
   TNF-α  CCCTCACACTCAGATCATCTTCT GCTACGACGTGGGCTACAG
   MAPK1  GGTTGTTCCCAAATGCTGACT   CAACTTCAATCCTCTTGTGAGGG
   MAPK3  TCCGCCATGAGAATGTTATAGGC GGTGGTGTTGATAAGCAGATTGG
   PPARA  AGAGCCCCATCTGTCCTCTC    ACTGGTAGTCTGCAAAACCAAA
   PTGS2  TTCAACACACTCTATCACTGGC  AGAAGCGTTTGCGGTACTCAT
   MAPK8  AGCAGAAGCAAACGTGACAAC   GCTGCACACACTATTCCTTGAG
   JAK2   TTGTGGTATTACGCCTGTGTATC ATGCCTGGTTGACTCGTCTAT
   MAPK14 TGACCCTTATGACCAGTCCTTT  GTCAGGCTCTTCCACTCATCTAT
   STAT3  CAATACCATTGACCTGCCGAT   GAGCGACTCAAACTGCCCT
   IL-4   GGTCTCAACCCCCAGCTAGT    GCCGATGATCTCTCTCAAGTGAT
   IL-5   CTCTGTTGACAAGCAATGAGACG TCTTCAGTATGTCTAGCCCCTG
   IL-13  CCTGGCTCTTGCTTGCCTT     GGTCTTGTGTGATGTTGCTCA
   [149]Open in a new tab

5.12. Enzyme-Linked Immunosorbent Assay

   MH-S cells were inoculated in a 12-well plate at 1 × 10^5 per well,
   cultured overnight, and starved of cells for 4 h. Then, BEO was
   administered at 0, 1, 10, and 100 μg/mL after the cells were stimulated
   with LPS (0.1 μg/mL) for 24 h prior to cell supernatant collection.
   BALF was processed as required by the ELISA kit. The cytokine content
   was measured using an ELISA kit (ABclonal double antibody sandwich,
   Wuhan, China; Proteintech, ELISA kit, Chicago, IL; Biolegend, ELISA
   kit, California).

5.13. Statistical Analysis

   All experimental data for this study were obtained from the standard
   deviation of three independent experiments. Statistical analysis was
   performed using GraphPad Prism 8 (GraphPad, San Diego, CA). One-way
   ANOVA was used for multiple samples. A p of <0.05 indicated a
   statistically significant difference between the groups.

Acknowledgments