RS was purchased from Purechemland Inc. (Chengdu, Sichuan, China). Prof. Fei Ge (Jiangxi University of Chinese Medicine, China) checked and authenticated the samples. Voucher specimens (no. 21101601) were kept at the herbarium of Jiangxi University of Chinese Medicine, Nanchang, China.

50 g of RS decoction pieces were first macerated in 20% (10 ml) glutinous rice wine (Guyue Longshan, Shaoxing, Zhejiang, China) for 1 h, then, stir-fried for 18 min at a temperature of 120°C ± 10°C to obtain WRS.

After that 20 g of WRS was immersed in 200 ml water, followed by reflux extraction for 2 h. The extract was then filtered under vacuum to a concentration of 1 g/ml.

Female C57BL/6 mice (20 ± 2 g), 8 weeks of age, were obtained from Changzhou Cavens Experimental Animals Co., Ltd. (Changzhou, Jiangsu, China). Animal experiments were performed according to the animal experimentation guidelines, and the study protocols were approved by the animal ethics committee of Jiangxi University of Chinese Medicine, Nanchang, China (SCXK_2016-0010). Animals were housed in an animal laboratory room with temperature (22°C ± 2°C), humidity (50 ± 10%), and 12-h light/dark cycle. The animals were provided with pathogen-free food and water. Animals were acclimatized to their new environment 1 week prior to the experiment.

SEB was used in double doses to induce ARDS. Briefly, 25 μL of SEB (Toxin, Sarasota, FL, United States) was administered intranasally by micropipette at a dose of 5 μg per mouse. The second dose of SEB was administered intraperitoneally to the mice 2 hours after the first dose at a dose of 2 μg per animal.

After 1 week of adaptive feeding, mice were randomly grouped (10 mice per group) as normal control group (NC group), SEB-induced ARDS model group (SEB group), WRS treated groups (WRS group, 10 and 15 mg/kg) and the positive drug group dexamethasone (DXMS group, 5 mg/kg). As a preventive intervention, before SEB exposure, mice in WRS groups were orally administered with WRS extract for 14 days, while NC and SEB groups were treated with purified water simultaneously. Mice in the DXMS group were treated with purified water for the first 13 days, and then DXMS was administered intraperitoneally on the 14th day. Afterward, SEB was administered to mice in the WRS, SEB and DXMS groups. Tissue samples were harvested from the lungs, colon, thymus, and spleen 72 h following exposure to the second SEB dose.

Healthy donor mice (n = 10) faeces were collected (Mohammed et al., 2020), diluted 1:10 (w/v) with saline, and homogenized for 1 min using a vertex mixer. Afterwards, particulate matter was removed by centrifuging the liquid slurry for 5 min at 200 × g. Afterwards, the supernatant was then aspirated in anaerobic conditions and immediately frozen, and was then administered to the mice, according to the experimental design, every day at a dose of 200 μL per animal.

Firstly, broad-spectrum antibiotics (ABX, containing 1 g/L of bacitracin, 0.5 g/L of gentamycin, 0.2 g/L of ciprofloxacin, 1 g/L of neomycin, 1 g/L of metronidazole, 0.5 g/L of ceftazidime, 1 g/L of penicillin, 2 g/L of streptomycin and 0.5 g/L of vancomycin) in drinking water were given to the recipient mice for 4 weeks to ensure that the endogenous microbiota was completely depleted. Next, they were transplanted daily with fresh faeces from healthy donor mice for 28 days. Then, the recipient mice received SEB exposure, as described above.

The right upper lobe of mouse lung tissue (n = 3) was fixed in 4% paraformaldehyde solution (Meilunbio, Dalian, Liaoning, China) for 48 h at room temperature, and then embedded in paraffin and sectioned. The lung sections (5 μm of thickness) were stained with hematoxylin and eosin (H&E) (Solarbio, Beijing, China), and digital images of lung morphology were obtained using a Leica fluorescence microscope system (WETZLAR, Germany).

Lung tissue injuries were scored according to a four-stage grading system of pathology: no injury, within the normal range, 0; very slight, the change is just outside the range of change, one; mild, lesions can be observed, but not serious, two; moderate, the lesion is obvious and likely to be more severe, three; serious, the lesion is very serious, 4.

The right lower lung lobe (n = 6) was removed, rinsed with normal saline, and then the excess water and blood on the surface of lung tissue were absorbed with filter paper, and weighted W). Dry mass D) was measured after drying at a 60°C incubator for 72 h. Wet/dry ratio (W/D) of lung tissue is calculated as wet weight g)/dry weight g) × 100%.

After being cleaned with saline and excess water removed, the spleen and thymus (n = 10) were weighed accurately to evaluate the organ index of mice. The formula used for the calculation of organ index is organ weight (mg)/mouse weight g)×100%.

Extraction of total RNA from lung tissue (n = 6–8) was performed with TRIzol reagent (Aidlab, Beijing, China). RNA concentration was equilibrated and transformed into cDNA with the kit (HiScript reverse transcription, Vazyme, Nanjing, China). BIO-RAD Real-Time System detection system was used for qPCR analysis. The expression of target genes and β-actin was calculated by 2^−ΔΔCT. Primer sequences of the target gene used in this experiment are listed in Table 1.

Serum samples (n = 6–10) were used to detect cytokines, including of transforming growth factor-beta (TGF-β), interferon-gama (IFN-γ) and tumor necrosis factor-alpha (TNF-α). These cytokine levels were determined according to the instructions provided in the ELISA kits (Meimian, Yancheng, Jiangsu, China).

20 mg of faeces were homogenized with 120 μL of methanol, and centrifuged at 4°C and 14,000 r/min for 10 min. Then the supernatant was immediately transferred and filtered through a 0.22 µm membrane before analyzing by a liquid chromatograph-mass spectrometer (LC-MS). To ensure the data quality of metabolic profiling, we prepared quality control samples (n = 8).

We used a Phenomenex Kinetex C18 column (100 mm × 2.1 mm, 2.6 μm) and Triple TOFTM 5600 (AB Sciex, Foster City, CA, United States of America) LC-MS with DuoSprayTM ion source to perform the liquid chromatographic separation. The mobile phase was 0.1% formic acid in water (v/v, A)-acetonitrile B) at a 0.3 ml/min flow rate and 40°C column temperature. Gradient elution was applied as follows: 0–4 min, 5–25% B; 4–10 min, 25–45% B; 10–22 min, 45–95% B. Mass spectrometer parameters: drying gas, N₂; gas temperature, 500°C; ion spray voltage, 5500 V; collision energy, 20 eV; declustering potential voltage, 100 or -100 V; sheath and auxiliary gas flow rate, 55 psi; scanning range, 50–1250 m/z were applied.

Peakview (ver 1.2), Markerview (ver 1.3.1) and SIMCA-P 14.0 software were used to process UPLC-MS data. After data preprocessing (baseline correction, peak alignment and scaling), metabolites were identified by KEGG (http://www.kegg.ca/) and Human Metabolome Database (HMDB, http://www.hmdb.ca/). Metabolic pathway analysis and potential biomarker screening were performed through Metaboanalyst 5.0 (http://www.MetaboAnalyst.ca).

Faecal genomic DNA (n = 4–6) was extracted with a DNA kit and quantified by agarose gel electrophoresis. We used specific primer 341 F (5′-CCTACGGGRBGCASCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) to amplify the V3-V4 regions of the 16s rRNA genes. We used a Qiagen Gel extraction kit (Qiagen, Germany) to purify the PCR products. We generated the sequencing libraries following the recommendations of the manufacturer of TruSeq^® DNA PCR-Free sample preparation kit (Illumina, United States). We sequenced this library using a paired-end sequencing strategy on the Illumina NovaSeq6000 platform (Illumina, California, United States).

To preserve volatile SCFAs in faeces, sample extraction was performed at 4°C. 30 mg of faeces samples (n = 4–5) and 1 ml 0.005 M of NaOH aqueous solution (containing 5 μg/ml 2-ethylbutyric acid as an internal standard) were homogenized and centrifuged for 10 min at 14000 rpm. Supernatants were treated through the derivatization reaction method as previously described (Singh et al., 2019).

Gas chromatography-mass spectrometry (GC-MS) was performed using an Agilent 7890A gas chromatography system and an Agilent 5975C mass spectrometric detector (MSD, Agilent Technologies, Santa Clara, CA, United States). 1 μL of each sample derivative was injected into an HP-5ms capillary column (30.0 m × 250 µm i. d., 0.25 µm film thickness, Agilent J and W Scientific, Folsom, CA, United States). Helium was used as a carrier gas at a 1 ml/min flow rate, operating in a 10:1 split mode ratio and 2.5 min solvent delay time. The oven temperature program was set as follows: 50°C for 2 min, 70°C at a rate of 10°C/min, 90°C at a rate of 3°C/min, 110°C at a rate of 10°C/min, 290°C at a rate of 20°C/min; 260°C front inlets, 280°C transfer line, and 230°C electron impact ion source; 70 eV electron energy, and selected ion monitoring (SIM) mode. Agilent MSD Chemstation (Santa Clara, CA, United States) was used for the data analysis.

The targets of the different chemical components of WRS were retrieved and collected from two online target prediction platforms: Swiss Target Prediction (http://www.swisstargetprediction.ch/) and Stitch (http://stitch.embl.de/) database. Subsequently, intersection processing was performed with the targets derived from the metabolic pathway to screen the common targets of the component and metabolism. The number of targets involved in the component accounted for 100% of the total number of targets in the corresponding pathway were selected as the main active constituents.

All data requiring statistical calculations were processed using GraphPad Prism (version 7.0, San Diego, United States) and presented as mean ± SD. Statistical analysis was performed using Student’s t-test and one-way ANOVA. Differential metabolites were filtered by variable importance in the projection (VIP) > 1.0 and p < 0.05.

SEB, a superantigen, could cause acute inflammation. The current study investigated whether WRS treatment would improve acute lung inflammation prior to SEB sensitization. Pathological changes in lung tissue are a major feature of mouse models, therefore ARDA mice model was developed and treated according to the treatment protocols mentioned earlier in the experiment section. In the NC group, the lung tissue sections of mice were clear, and no obvious pathological changes were observed (Figure 1A). After SEB exposure, lung tissue structure was damaged, the alveolar walls were thickened, and there was marked infiltration of inflammatory cells (Figure 1A). Interestingly, after WRS treatment, lung tissue structure was substantially improved and inflammatory cell infiltration was significantly reduced (Figure 1A). A four-stage grading system of the pathology of the lung histopathological changes indicated that either treated with 10 or 15 mg/kg WRS improved the progress of lung tissue injuries (Figure 1B).

Many studies have shown that the primitive foregut is the embryonic origin of respiratory and gastrointestinal epithelial cells (Ramalho-Santos et al., 2000; Shu et al., 2007). This similarity is thought to be partly responsible for lung-gut crosstalk during inflammation (Keely et al., 2012). We also observed the pathological sections of colon tissue, as shown in Figure 1C. SEB group showed surface epithelial erosion, crypt destruction, muscularis mucosa destruction, submucosa edema, and inflammatory cell infiltration. However, these symptoms were greatly relieved in WRS-treated mice.

Prevention or suppression of cytokine storm may be one of the strategies for treating severe pneumonia patients. To determine if WRS could have a better effect on calming cytokine storm, the levels of pro-inflammatory cytokines (TNF-α, IFN-γ) and anti-inflammatory mediator (TGF-β) in serum and lung tissue were measured (Figures 1D, E). These cytokines were significantly improved after WRS treatment compared with the SEB group. Encouragingly, WRS had a remarkable regulatory effect which was similar to or even better than the positive drug DXMS, indicating that WRS efficiently inhibited cytokine storms.

WRS significantly reduced the lung edema (lung wet/dry ratio) compared with the SEB group (Figure 1F). The spleen and thymus are the main immune organs that drive most immune responses (Checker et al., 2008). WRS significantly raised the thymus and spleen indices, indicating an enhancement of immune function by WRS (Figure 1G). These results together demonstrated that WRS ameliorated the inflammatory response and possibly induced lung immune hemostasis.

Gut microbiota plays an important role in the evolution of lung disease, and microbiota modulation is a potential therapeutic approach to prevent ARDS (Dickson et al., 2016; Sultan et al., 2021). We investigated the role of WRS (15 mg/kg) in regulating microbial dysregulation in ARDS. 16s rRNA-seq analysis revealed that more than 99.9% of the sequence exhibited good coverage values, indicating the sequencing results’ reliability. WRS significantly altered the composition and relative abundance of faecal microbiota, according to the principal co-ordinator analysis (PCoA) and a-diversity index (Figure 2A, Supplementary Table S1). 10 most abundant phylum and genus were presented in Figure 2B. At the phylum level, Deferribacteres and Tenericutes were enriched in SEB group. At the genus level, Helicobacter were enriched in the SEB group, while Desulfovibrionaceae and Muribaculaceae were more abundant in the WRS group (Figures 2B–D).

To further determine the dominant microbial species, linear discriminant analysis (LDA) effect size (LEfSe) analysis was used. The relative abundance of Verrucomicrobia at the phylum level, Ruminococcaceae and Muribaculaceae at the family level, Akkermansia at the genus level was remarkably increased after giving WRS, while decreasing the abundance of Rikenellaceae at the family level and Desulfovibrio at the genus level from ARDS mice (Figures 2E, F). These data demonstrated that alterations in microbial composition and function caused by SEB-induced ARDS (Supplementary Figures S1–4) could be effectively regulated with WRS treatment.

As major bacterial metabolites, SCFAs interact with receptors on host cells that can activate or inhibit signaling pathways and regulate multiple metabolic pathways in the gut and at distances. To clarify the correlation between SCFAs and ARDS, we measured SCFAs concentrations in the faeces by GC-MS. As shown in Figure 3A, acetic acid, propionic acid, butyric acid and valeric acid were significantly increased after WRS treatment compared with the SEB group (Figure 3A). Recent studies have shown that SCFAs modulate epithelial cells or neutrophil immune responses that depend on the sensing receptors, FFAR3 and FFAR2 (Kim et al., 2013; Zhao, 2013). However, the effect of WRS on FFAR3/FFAR2 has not been reported before. Consequently, we detected the mRNA expression of FFAR3 and FFAR2 in lung tissue by qRT-PCR. As shown in Figure 3B, the mRNA expression of FFAR3 and FFAR2 was strikingly lowered upon SEB compared with the NC group, and the reduction of FFAR3 and FFAR2 mRNA expression by SEB was significantly reversed by WRS treatment (Figure 3B). Our results suggested that WRS treatment increased production of SCFAs in the gut, and then the increased the SCFAs may migrate to the lung and activate FFAR3 and FFAR2 in lung epithelial cells to fight against ARDS infection.

To confirm whether the changed gut microbiota after WRS treatment was responsible for the alleviation of ARDS, FMT was used to test the role of gut microbiota in the treatment of ARDS. After being treated with a cocktail of antibiotics for 4 weeks, gut microbes were effectively depleted (Supplementary Figures S5, 6). Microbiota from healthy mice was transplanted into recipient ABX mice. After 4 weeks of colonization, then the recipient mice were exposed to SEB (Figure 4A). As shown in Figure 4, FMT treatment demonstrated similar lung inflammation protective effects as observed in WRS groups. Recipient mice showed improved lung tissue structure, inflammatory factors and organ index (Figures 4B–E). Besides, SCFA concentrations and FFAR3 and FFAR2 mRNA expression were also restored (Figures 4F,G). Together, these results demonstrated that the homeostasis of gut microbes played an important role in protecting lung health, and WRS alleviates ARDS by reconstructing the microbial microenvironment.

The effect of gut microorganisms on the host is closely related to the complex interactions of a series of host-microbial metabolic axes (Zeng et al., 2020). Untargeted metabolomic analysis of faeces samples by LC-MS was performed to assess the metabolic role of WRS-reconstituted (15 mg/kg) gut microbiota. The results of quality control samples are shown in Supplementary Table S2. PCA plot showed that metabolite clustering was evident among NC, WRS, DXMS and SEB groups by PCA plot (Figure 5A). Orthogonal partial least squares-discriminant analysis (OPLS-DA) also revealed an obvious separation among these groups, with R²X, R²Y and Q² being 0.588, 0.905 and 0.624 between NC and SEB groups (Figure 5B). SEB treatment was sufficient to induce a wide range of changes in metabolites, with 74 and 44 metabolites significantly up-regulated and down-regulated, respectively (Figure 5C). Notably, after administration of WRS, some metabolites in the SEB group were regulated, and 12 metabolite changes induced by SEB were eliminated (5 up-regulated and seven down-regulated) (Table 2).

Furthermore, differential metabolites with a fold change larger than 1.2 or less than 0.8 were analyzed for screening potential metabolic pathways by MetaboAnalyst (p < 0.05, impact value >0.01). Between healthy and SEB mice, as shown in Figure 5D, 26 metabolic pathways were identified as significant metabolic pathways (Figure 5D). Among these 26 potential pathways, WRS mainly regulated amino acid metabolism, including tryptophan metabolism, lysine degradation and arginine biosynthesis (Figure 5E). The most enriched pathway for differential metabolites with the largest impact value was the tryptophan metabolism, in which 2-aminobenzoic acid, oxoadipic acid, tryptamine, tryptophanol and kynurenic acid were enriched (Figure 5F).

According to our previous research, 10 compounds were identified as chemical markers in WRS (Supplementary Table S3; Hu et al., 2020). Among the 10 chemical markers, 226 gene targets were retrieved from the Swiss Target and Stitch Prediction database. Then, gene intersections were generated by mapping the targets of the 10 chemical markers with the selected tryptophan metabolism using the KEGG database. Consequently, three targets of eight components in WRS associated with tryptophan metabolism were screened out (Figure 6B). WRS constituent-target-pathway network was constructed to reveal the intersections of the three target symbols using Cytoscape software (Figure 6C). If the target number involved in each component accounted for 100% of the target number of all eight chemical markers, it was selected as bioactive marker. Finally, three potential bioactive markers (baicalin, oroxylin A-7-O-glucuronide, skullcapflavon II) in WRS were screened (Table 3). In this study, we found for the first time that WRS could exert a profound therapeutic effect on ARDS by acting on MAoa, MAob, Ido one through baicalin, oroxylin A-7-O-glucuronide and skullcapflavon II.