Study of the anti-inflammatory effect of the Traditional Mongolian Medicine Hohgardi-9 in acute lung injury

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Submit a manuscript: https://www.tmrjournals.com/tmr Background Acute lung injury (ALI) is a respiratory disease with high morbidity and mortality, and its clinical manifestations include refractory hypoxemia, acute respiratory distress, and non-cardiogenic pulmonary edema [1]. Its pathogenesis mainly involves the release and activation of inflammatory factors in the lungs induced by various etiologies, damaging the alveolar epithelial cells, increasing alveolar permeability, and eventually causing pulmonary edema and even respiratory failure [1,2]. Therefore, controlling the inflammatory response can limit the progression of ALI.
According to the traditional Mongolian medicine theory, diseases usually weaken the body and immunity by disturbing the balance between the three elements of life (Heyi (frequent yawning, insomnia, wandering pain, shiver, dizziness, tinnitus, retching, and red and dry tongue), Xila, (headache, stomach, thirst, fever, local pain, thick, tongue coating, yellow urine with a strong smell, and arrhythmia) and Badagan (loss of appetite, indigestion, gustatory disorder, nausea, stomach bilges frowsty, depression, feeling of cold, and lethargy)), invading the body by "Nian" (pathogenic microorganisms), which affects Heyi, Xila, and Badagan, and finally damages the organs [3][4][5]. According to traditional Mongolian medicine, ALI is considered a plague fever (fever caused by plague) and an acute infectious disease caused by "Nian" [3].
In this study, we used plasma pharmacochemistry and network pharmacology to explore the active components in Hohgardi-9 that act against ALI. First, we identified the constituents of Hohgardi-9 from rat plasma using ultra-high-performance liquid chromatography coupled with Q-Exactive mass spectrometry (UHPLC-QE-MS). Using network pharmacology, we predicted its targets, disease network, interaction with key targets, and signal pathways. Finally, we used lipopolysaccharide (LPS)-induced ALI model to verify its underlying therapeutic mechanism.

Network pharmacology-based analysis
The nine medicinal herbs in Hohgardi-9 were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform and literature search. To screen the compounds, we incorporated their oral bioavailability and drug-likeness in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform and Swiss ADME databases as drug screening conditions. The targets of the candidate compounds were obtained from the Swiss Target Prediction database (http://www.swisstargetprediction.ch/) [9]. The relevant target human genes were obtained from the DisGeNET (https://www.disgenet.org/), NCBI Genetic (https://www.ncbi.nlm.nih.gov/), and GeneCard (https://www.genecards.org/) using the keyword "acute lung injury" [10,11]. Finally, we performed Venn analysis with Hohgardi-9's target genes and disease-related genes to obtain the common targets for subsequent studies. To further characterize the molecular mechanism underlying Hohgardi-9's therapeutic effect on ALI, we generated a network of common target genes using Cytoscape 3.8.0 software. Additionally, the protein-protein interaction (PPI) network was constructed using the STRING database (https://string-db.org/cgi/input.pl). Then, the network topology was analyzed using a plugin in Cytoscape 3.8.0 [12]. The gene ontology-biological process (GO-BP) and pathway enrichment analyses were conducted using the String database. Collection and processing of plasma samples: After one week of adaptive feeding, all male SD rats were divided into two groups: blank control and Hohgardi-9. In the Hohgardi-9 group, all rats were administered five times, twice daily, for the first two days. Then, they were fasted on the second night, and their blood was drawn one hour after administration on the third day. The blood samples were centrifuged at 3,000 g/min for 10 mins on ice to obtain the plasma. Then, 50 μL of plasma was transferred into a 1.5 mL Eppendorf tube, mixed with 200 μL of cold methanol (with internal standard), vortexed for 2 mins, and allowed to stand at low temperature for 10 min. The supernatant was obtained by centrifuging at 14,000 g for 15 min at 4°C. Then, 200 μL of supernatant was taken in a new Eppendorf tube, centrifuged and concentrated at low temperature, and mixed with 100 μL of 20% methanol/aqueous solution for positive and negative ion pattern analysis.
A Q-Exactive Focus mass spectrometer coupled with Xcalibur software was used to obtain the MS and MS/MS data based on the HESI-Positive ion mode, full scanning, and DDA Secondary ion scanning mode. The conditions were: spray voltage (kV): + 3.

Highlights
Network pharmacology was used to explore the mechanism of Hohgardi-9 in treating acute lung injury, and in vivo, experiment was used to clarify the therapeutic effects of Hohgardi-9 in acute lung injury.

Medical history of objective
Hohgardi-9 was recorded in the "Tongajide", one of the most important collections of Traditional Mongolian Medicine prescriptions written in 1888 by Jigemuddanzengzhamsu. Hohgardi-9 is used to treat respiratory tract inflammation in Mongolian Medicine. Submit a manuscript: https://www.tmrjournals.com/tmr Co., Ltd.; LPS (Sigma-Aldrich). Treatment: We randomly divided male SD rats (n = 50) weighing 180-220 g into the following groups (n = 6/group): blank control, LPS model, traditional Chinese medicine positive control (Lianhua Qingwen, 4 g/kg), the Hohgardi-9 group, High Dosage (equivalent of ten times the human dosage, 2 g/kg), the Hohgardi-9 group, low dosage (equivalent of five times the human dosage, 1 g/kg) [13][14][15]. After one week of adaptive feeding, all rats were administered the respective treatment once daily for seven consecutive days. The blank and model groups were administered with the same volume of normal saline. Excluding the blank group, all groups were intraperitoneally injected with LPS (5 mg/kg) one hour after administration on the seventh day to create the ALI rat models. Six hours after modeling, the lung tissues were obtained and subjected to experiments ( Figure 1).

Histological analysis of the lungs
The lung tissues were fixed in 10% formaldehyde, dehydrated with ethyl alcohol, paraffin-embedded, cut into 5 mm-thick slices, and stained with hematoxylin and eosin to observe the pathological changes in lung tissues. The lung injury score was used to evaluate the histological lung injury. The scored items were the degree of edema, inflammation, hemorrhage, hyaline membrane formation and thickness of alveolar wall. Each item was scored from 0 to 4 as follows: 0, absent and appears normal; 1, light; 2, mild; 3, severe; 4, intense. The lung injury of five × 400 magnification images was graded and calculated by the mean score of the above parameters.

Wet-to-dry (W/D) lung weight ratio
To assess pulmonary edema, the left lung was collected, rinsed with PBS, aspirated, and weighed to obtain the wet weight. The lung tissues were then placed in a thermostatic oven at 68°C for 48 h to obtain the dry weight. The ratio of the W/D weight was calculated to determine the degree of pulmonary edema as follows [16] : W/D=Wet weight/dry weight × 100%

Real-time quantitative fluorescence polymerase chain reaction (PCR) experiment
The total RNA was extracted from the lung tissues using Trizol (Invitrogen) and reverse transcribed into cDNA using the Revert Aid First Strand cDNA Synthesis Kit (Thermo scientific fermentas). The templates were amplified by real-time PCR using TransStart Top Green qPCR superMix (+ DyeⅡ) (TransGen biotech). The reaction conditions were 94°C for 30 s, 94°C for 5 s and 62°C for 34 s (45 cycles). Using β-actin as the internal reference, the Ct values were obtained using the 2 -ΔCT method. Table 1 lists the primers used.

Statistical analysis
Statistical significance was determined using unpaired t-test or oneway analysis of variance with a Dunnett's multiple comparisons test. P values of < 0.05 were considered statistical significance.All the results were expressed as mean ± SD. The analysis was performed using GraphPad Prism 9.4.0.

Component-target network diagram analysis
The Venn diagrams were drawn using 2005 disease-related targets and 848 potential targets of Hohgardi-9 ( Figure 2A). The intersection revealed 379 significant common targets of Hohgardi-9 against ALI. The relationship between the candidate compounds and common targets was constructed into a compound-target protein network ( Figure 2B)  Schmidt ex Miq., and ellagic acid in Polygonum bistorta L. were all higher than the average value of 29.7. Therefore, these compounds are considered the key compounds of Hohgardi-9 that exert therapeutic effect against ALI (Table 2).

PPI network diagram analysis
To understand Hohgardi-9's effects, 379 common targets were input into the STRING data platform and analyzed to obtain a PPI action network. A total of 328 interaction nodes and 2013 interaction relationships were received, with an average degree value of 12.3 ( Figure 2C). In the graphical results, the size of nodes represents their degree value. The larger and darker nodes with higher corresponding degree values are considered more important for the predicted disease. Based on the results, STAT3, MAPK1, AKT1, JUN, RELA, TNF, TLR4, IL-1β and ICAM-1 were identified as key targets for the inflammatory pathways and might also be potential therapeutic targets of Hohgardi-9.

GO-BP enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis
To further explore the mechanism of action by Hohgardi-9, GO-BP, and KEGG pathway enrichment analyses were conducted. We screened out the key target proteins whose corrected values were below 0.05 using GO-BP enrichment analysis, revealing 101 biological processes, including inflammatory response, response to lipopolysaccharides and hypoxia, viral entry into the host cell, apoptotic process, positive regulation of NF-κB transcription factor activity, positive regulation of TNF production, response to interleukin-1 ( Figure 2D). We obtained 122 pathways from the KEGG pathway enrichment analysis (P < 0.05), including apoptosis, COVID-19 disease, and signaling pathways for PI3K-Akt, HIF-1, TNF, TLR, and NF-κB ( Figure 2E).

Constituents of Hohgardi-9 in the plasma
After oral administration of Hohgardi-9, we identified 31 compounds in the rat plasma using high-resolution MS, the same as network pharmacologic analysis (Table 3).   Effects of Hohgardi-9 on lung tissues As shown in Figure 3, the blank group showed no obvious morphological damage. However, the model group showed significant lung injury with alveolar wall thickening, septal edema, numerous neutrophils, a few eosinophils, mast cells around the plasma vessels, foam cells, and hemorrhage in a few alveolar lumens. Treatment with Hohgardi-9 and Lianhua Qingwen significantly improved the tissue damage ( Figure 4C-4E). In addition, we also calculated the lung injury score, Figure 4F shows that LPS significantly increased the lung injury score compared to the control value. Hohgardi-9 and Lianhua Qingwen significantly decreased the lung injury score in rats treated with LPS.

Hohgardi-9's effects on the lung wet-dry ratio induced by lipopolysaccharide
To further verify the modeling success, we quantified the pulmonary W/D to detect pulmonary edema. Compared with the blank control group, after LPS stimulation, the lung W/D ratio increases significantly ( # p < 0.05) ( Figure 5), but these symptoms are relieved considerably after treatment ( * p < 0.05).

Validation of key target mRNA expression with PCR
Based on the network prediction results, we verified four key targets, TRL4, TNF-α, IL-1β, and ICAM1, using real-time quantitative PCR. The results show that the mRNA expression levels of TRL4, TNF-α, IL-1β, and ICAM1 in lung tissues were significantly higher in the model group than in the control group ( ** P < 0.01). However, these levels were significantly lower in the Hohgardi-9-treated groups than in the model group ( * P < 0.05, ** P < 0.01) (Figure 3). These results were consistent with the ones predicted.

Discussion
ALI is commonly involved in many diseases, including COVID-19 [17]. Despite numerous studies on ALI, no effective pharmacological therapies have been reported to treat ALI. Therefore, developing novel drugs to treat ALI is urgently required, which might also help treat COVID-19. Natural products, including flavonoids, alkaloids, and terpenoids, such as, have shown potential therapeutic effects against ALI and are hence, widely studied [18]. In traditional Mongolian medicine, Hohgardi-9 is used to treat respiratory tract inflammation. Currently, 78 candidate compounds have been obtained from Hohgardi-9. Based on the composition-target network diagrams, 63 compounds have been identified among all candidate compounds from Hohgardi-9, of which those with higher degree values may play the key role in gene regulation during the development of ALI. These compounds, including flavonoids such as quercetin, kaempferol, luteolin, herbacerin, and 3-hydroxy-9,10-dimethoxypterocarpan, which are a class of molecules characterized by a C6-C3-C6 skeleton structure, might be involved in gene regulation during ALI development. Hohgardi-9 has potent antioxidant and anti-inflammatory effects against conditions such as ALI [19,20]. The alkaloids n-feruloyltyramine, izoteolin, and cheilanthifoline, the terpenoids scrophuloside A_qt, tussilagone, and diosbulbin B, and the coumarins, columbianetin acetate, and cnidilin, also have higher degrees. These alkaloids, terpenoids, and coumarins have significant pharmacological activities [21][22][23].
To verify these predictions, we analyzed the rat plasma using UHPLC-QE-MS and found 436 and 276 compounds in cationic and anionic modes, respectively. Of these, the network pharmacology predictions revealed that 31 compounds (main 10 component's UHPLC-QE-MS image shown at supplemental data Supplementary Figure S1), including flavonoids such as quercetin, herbacerin, and ellagic acid, could enter the blood, might have therapeutic effects. Previous studies have reported various pharmacological activities of these flavonoids, including anti-inflammatory, antioxidant, antibacterial, antiviral, and immunoregulatory effects [24][25][26][27][28]. Particularly, quercetin shows a protective role in LPS-induced ALI in rats. It has improved pulmonary edema, lung histological changes, and survival. Suppression of inflammation and oxidative stress are amongst its most notable effects [29]. Similarly, ellagic acid significantly ameliorated CCl4-induced ALI in mice by regulating the inflammatory response, oxidative stress, and apoptosis [30].
Regarding mechanism, the effects of quercetin and ellagic acid were associated with NF-κB and Nrf-2/ HO-1 signaling pathway and Bcl-2/Bax downregulation.
Several terpenoids predicted by network pharmacology were also detected in the plasma, such as tussilagone, diosbulbin B, andrographolide, and costunolide. Previously, tussilagone has been shown to effectively alleviate lung tissue damage and reduce the expression of inflammatory cytokines by suppressing Hif-1α levels and NF-κB activation in a PM2.5 exposure mouse lung injury model [35]. Further, andrographolide could suppress pulmonary oedema, inflammatory cell infiltration, myeloperoxidase activity, and pro-inflammatory cytokine expression in LPS-induced ALI mice. In terms of mechanism, the effects of andrographolide were associated with the downregulation of the NF-κB signaling pathway [36]. These studies suggest that Hohgardi-9 can treat ALI by modulating multiple mechanisms, such as inflammation, oxidative stress, and apoptosis.
The PPI network analysis revealed multiple associations between targets, and those with a higher degree have better target potential therapeutic effects. TP53, MAPK3, STAT3, MAPK1, RELA, JUN, MAPK14, TNF, CASP3, TLR4, IL-1β, and BCL2 were found to be important targets for inflammatory and apoptosis pathways, and hence, the key therapeutic targets for Hohgardi-9. TP53, CASP3, and BCL2 regulate the signal transduction during apoptosis, which has been implicated in ALI [37]. Inhibiting the activation of TLR-4/NF-κB signal pathways can reduce the secretion and expression of inflammatory cytokines, such as TNF-α and IL-1β, and reduce the inflammatory cascade reaction, alleviating lung inflammation [38,39]. The GO and KEGG pathways analyses showed that apoptosis, COVID-19 disease, and signaling pathways for NF-κB, TNF, and MAPK were the key targets. Based on this, we demonstrated that Hohgardi-9 could treat ALI by reducing the inflammatory response and oxidative stress, inhibiting apoptosis, and controlling viral infections.
Furthermore, animal studies confirmed that Hohgardi-9 could reduce lung injury in rats and alleviate LPS-induced pulmonary edema without influencing body weight (Supplementary Table S1). Since uncontrolled inflammation of the lung or whole body is believed to be the main pathogenesis of ALI, we investigated the mRNA for several inflammation-associated genes (ICAM-1, TLR4, IL-1β, and TNF-α) to validate the above predictions. We will continue to investigate its role in regulating inflammation, oxidative stress, and apoptosis in our future studies.
In conclusion, this study investigated the active ingredients, potential targets, and related pathways of Hohgardi-9 for ALI treatment using network pharmacology. Further, we used animal models to verify the plasma components, efficacy, and regulatory mechanisms of Hohgardi-9. Our results will facilitate in-depth investigations into the mechanism underlying the therapeutic effects of Hohgardi-9 against ALI.