Application of Enterobacter spp. and their metabolites in ARDS or lung injury risk assessment

Abstract

This invention belongs to the field of biomedicine and relates to the application of *Bacteroides* bacteria and their metabolites in risk assessment of ARDS or lung injury. This invention provides reagents for detecting the level of 3-(3-hydroxyphenyl)propionic acid sulfate and / or reagents for detecting the abundance of *Bacteroides massiliensis* in the preparation of kits for risk assessment of ARDS or lung injury. This invention reveals for the first time the mechanism by which the gut microbiome *Bacteroides massiliensis* and its metabolite 3-(3-hydroxyphenyl)propionic acid sulfate exacerbate lung injury by targeting KDR to activate the VEGF signaling pathway, inhibiting macrophage apoptosis, and promoting macrophage migration. Based on this mechanism, this invention provides biomarkers for the diagnosis of ARDS.

Description

Technical Field

[0001] This invention belongs to the field of biomedicine and relates to the application of Bacteroides spp. and their metabolites in the risk assessment of ARDS or lung injury. Background Technology

[0002] Acute respiratory distress syndrome (ARDS) is a life-threatening respiratory disease characterized by acute, progressive respiratory distress, refractory hypoxemia, and uncontrolled pulmonary inflammation. It typically occurs after systemic inflammatory responses such as sepsis, trauma, or infection, with pulmonary infections caused by Gram-negative bacteria being the most common. The pathogenesis of ARDS is complex, involving inflammatory responses, oxidative stress, coagulation abnormalities, and damage to alveolar epithelial and endothelial cells. Despite increased understanding of ARDS in recent years, its mortality rate remains high, approximately 30%-40%. Current treatment strategies primarily focus on mechanical ventilation and fluid management, but these measures only alleviate symptoms and do not cure ARDS.

[0003] In recent years, the concept of the "gut-lung axis" has opened up new directions for ARDS research. The gut microbiota, as the largest microbial community in the human body, forms a bidirectional regulatory network with the lungs through its metabolites and immune regulation. Studies have shown that gut microbiota dysbiosis can lead to the translocation of microorganisms and their metabolites, activating systemic inflammatory responses and thus participating in the occurrence and development of lung diseases. In ARDS patients, the diversity and composition of the gut microbiota are significantly altered. Furthermore, metabolites in serum and feces are closely related to the occurrence and progression of ARDS. Certain metabolites may affect the pulmonary inflammatory response by regulating immune cell function and inflammatory signaling pathways.

[0004] Biomarkers play a crucial role in the early diagnosis, risk stratification, and prognostic assessment of ARDS. Several ARDS-related biomarkers have been reported in recent studies. For example, a team at Zhongshan Hospital affiliated with Fudan University screened a combination of 12 specific serum protein biomarkers through a multicenter cohort study for ARDS inflammatory phenotype classification. Other patented technologies disclose eight protein biomarkers, including vascular cell adhesion molecule 1 (VCAM1) and lactate dehydrogenase B (LDHB), for ARDS diagnosis and prognostic assessment. Furthermore, sIL-2Rα has also been reported for early prediction of ARDS. However, these biomarkers primarily focus on the protein level, and research on ARDS biomarkers based on gut microbiota and their metabolites is still lacking. Summary of the Invention

[0005] The purpose of this invention is to provide the application of Bacteroides spp. and their metabolites in the risk assessment of ARDS or lung injury.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] The use of reagents for detecting the level of 3-(3-hydroxyphenyl)propionic acid sulfate and / or reagents for detecting the abundance of Bacteroides massiliensis in the preparation of kits for risk assessment of ARDS or lung injury.

[0008] Bacteroides massiliensis (now known as Phocaeicola massiliensis, a strain deposited at the China Marine Microbiological Culture Collection Center (MCCC) with accession number 1A05469) is an obligate anaerobic, Gram-negative, rod-shaped bacterium primarily found in the human gut. It is an important member of the gut microbiome in maintaining gut health, but can also become pathogenic under certain conditions. Its abundance is significantly reduced in the gut of patients with various diseases, particularly inflammatory bowel disease and neurodegenerative diseases.

[0009] This invention, through the establishment of an LPS-induced acute respiratory distress syndrome (ARDS) mouse model, combined with fecal microbiota transplantation (FMT), 16S rRNA sequencing, metabolomics analysis, and in vitro and in vivo functional validation, has for the first time discovered:

[0010] Fecal microbiota transplantation from ARDS patients remodeled the gut microbiota composition in mice, with a significant increase in the abundance of Bacteroides massiliensis (Phocaeicola massiliensis) and a significant increase in the levels of its related metabolite 3-(3-hydroxyphenyl)propionate sulfate (and its sodium salt Na-3SPP).

[0011] In vivo animal experiments confirmed that combined treatment with Na-3SPP synergistically exacerbated LPS-induced lung injury, manifested as more significant weight loss, increased lung injury scores, and elevated expression of inflammatory cytokines. Mechanistic studies revealed that this bacterium and its metabolites exacerbate lung injury by inhibiting total macrophage apoptosis and promoting monocyte / macrophage (M-Mac) migration.

[0012] Based on the above findings, the present invention provides the use of reagents for determining the level of 3-(3-hydroxyphenyl)propionic acid sulfate and / or reagents for detecting the abundance of Bacteroides massiliensis in the preparation of kits for risk assessment of ARDS or lung injury.

[0013] According to embodiments of the present invention, the present invention can be further optimized, and the optimized technical solution is as follows:

[0014] In one preferred embodiment, the test sample is selected from blood, serum, feces, or bronchoalveolar lavage fluid.

[0015] In one preferred embodiment, elevated levels of 3-(3-hydroxyphenyl)propionate sulfate suggest an increased risk of ARDS or lung injury.

[0016] In one preferred embodiment, a serum sample with a 3-(3-hydroxyphenyl)propionate sulfate level >12.5 ng / mL indicates an increased risk of ARDS or lung injury.

[0017] In one preferred embodiment, a level of 3-(3-hydroxyphenyl)propionate sulfate in the intestinal contents >15.2 ng / g suggests an increased risk of ARDS or lung injury.

[0018] In one preferred embodiment, increased abundance of Bacteroides massiliensis suggests an increased risk of ARDS or lung injury.

[0019] In one preferred embodiment, a relative abundance of Bacteroides massiliensis > 0.018% in a fecal sample suggests an increased risk of ARDS or lung injury.

[0020] In one preferred embodiment, a relative abundance of Bacteroides massiliensis in the intestinal contents > 0.020% suggests an increased risk of ARDS or lung injury.

[0021] Based on the same inventive concept, this invention also claims a kit for the auxiliary diagnosis of ARDS or lung injury, comprising:

[0022] (a) A reagent for detecting the level of 3-(3-hydroxyphenyl)propionic acid sulfate or its salts; and / or

[0023] (b) Reagents for detecting the abundance of Bacteroides massiliensis.

[0024] In one preferred embodiment, the reagent for detecting the level of 3-(3-hydroxyphenyl)propionic acid sulfate is selected from: liquid chromatography-mass spectrometry detection reagents, enzyme-linked immunosorbent assay (ELISA) detection reagents, colorimetric detection reagents, or fluorescent detection reagents.

[0025] In one preferred embodiment, the reagent for detecting the abundance of Bacteroides massiliensis is selected from: 16S rRNA sequencing reagents, quantitative PCR detection reagents, fluorescence in situ hybridization detection reagents, or specific antibody detection reagents.

[0026] Based on the same inventive concept, this invention also claims protection for a detection system for ARDS or lung injury risk assessment, characterized by comprising:

[0027] (a) Sample collection unit: used to collect blood, serum, feces or bronchoalveolar lavage fluid samples;

[0028] (b) Detection unit: used to detect the level of 3-(3-hydroxyphenyl)propionic acid sulfate and / or the abundance of Bacteroides massiliensis in the sample;

[0029] (c) Assessment unit: used to compare test results with reference values ​​to assess the risk of ARDS or lung injury.

[0030] In one preferred embodiment, the detection unit includes a liquid chromatography-mass spectrometry system or a quantitative PCR instrument.

[0031] Compared with the prior art, the beneficial effects of the present invention are:

[0032] This invention reveals for the first time the mechanism by which the gut microbiota *Bacteroides massiliensis* and its metabolite 3-(3-hydroxyphenyl)propionate sulfate exacerbate lung injury by targeting the KDR pathway to activate the VEGF signaling pathway, inhibit macrophage apoptosis, and promote macrophage migration. Based on this mechanism, this invention provides biomarkers for the diagnosis of ARDS. Attached Figure Description

[0033] Figure 1 These are the results of lung wet / dry weight ratio and body weight changes in each group of mice in Example 1; among them Figure 1 A is a statistical graph showing the wet / dry weight ratio of the lungs of mice in each group; Figure 1 B is a graph showing the changes in body weight of mice in each group.

[0034] Figure 2 These are the HE staining and lung injury scoring results of the mice in each group in Example 1; among them Figure 2 A shows HE staining images of mice in each group; Figure 2 B is a statistical chart of the various lung injury scores.

[0035] Figure 3 This is a statistical graph showing the expression levels of inflammatory cytokines TNF-α, IL-1β, and IL-6 in the lung tissue of mice in each group.

[0036] Figure 4 This is a statistical graph showing the proportions of neutrophils / CD45+, AM / CD45+ (alveolar macrophages), IM / CD45+ (interstitial macrophages), and M-Mac / CD45+ (monocytes / macrophages) in the lungs of mice in each group, analyzed by flow cytometry.

[0037] Figure 5 This is a statistical graph analyzing the proportions of neutrophils / CD45+, M-Mac / CD45+, AM / CD45+, and IM / CD45+ in the lungs of mice in each group using flow cytometry, comparing the LPS+ARDS-FMT+IgG group, the LPS+ARDS-FMT+anti-Ly6G group, and the LPS+ARDS-FMT+CLD-Lp group.

[0038] Figure 6 These are the statistical results of the lung wet / dry weight ratio and body weight changes in each group of mice during the immune cell depletion experiment; among them Figure 6 A is a statistical graph showing the wet / dry weight ratio of the lungs of mice in each group; Figure 6 B is a graph showing the changes in body weight of mice in each group.

[0039] Figure 7 These are the statistical results of lung injury scores in each group of mice during the immune cell depletion experiment, and the expression levels of inflammatory cytokines TNF-α, IL-1β, IL-6, IL-17A, and IL-22 in the lung tissue of each group of mice; among them Figure 7 A shows the lung injury score of each group of mice; Figure 7 B is a statistical graph showing the expression levels of inflammatory cytokines TNF-α, IL-1β, IL-6, IL-17A, and IL-22 in the lung tissue of mice in each group.

[0040] Figure 8 HE staining of lung injury in mice in each group during the immune cell depletion experiment.

[0041] Figure 9 These are representative HE-stained images of mouse lung tissue from each group in Example 2, showing the pathological changes in lung tissue before 9 weeks, after 9 weeks, and at weeks 10, 12, and 14.

[0042] Figure 10 This is a statistical graph showing the changes in lung injury scores of mice in each group over time in Example 2 (before week 9, after week 9, week 10, week 12, and week 14).

[0043] Figure 11 This is a statistical graph showing the changes over time in the ratio of neutrophils / CD45+ and the ratio of M-Mac / CD45+ in the lung tissue of mice in each group of Example 2, analyzed by flow cytometry.

[0044] Figure 12 This is an alpha diversity analysis of 16S rRNA sequencing from mouse fecal samples in each group, showing statistical plots of the Shannon and Simpson indices, and comparing the LPS group, LPS+Normal-FMT group, and LPS+ARDS-FMT group.

[0045] Figure 13 This is a statistical graph of the Shannon and Simpson indices for healthy subjects and ARDS patients.

[0046] Figure 14 This is a graph showing the Beta diversity analysis between healthy subjects and ARDS patients.

[0047] Figure 15 This is a species-level analysis diagram comparing healthy subjects and ARDS patients.

[0048] Figure 16 This is a Venn diagram analysis of healthy subjects and ARDS patients.

[0049] Figure 17 This is a statistical graph showing the levels of 3-(3-hydroxyphenyl)propionic acid sulfate in the feces and serum metabolites of mice in each group, comparing the LPS+Normal-FMT group and the LPS+ARDS-FMT group.

[0050] Figure 18 This is a statistical graph showing the changes in body weight of mice in the Control group, LPS+Bacteroides massiliensis group, LPS+Bacteroides massiliensis+phenylalanine supplementation (Phe-sup) group, and LPS+Bacteroides massiliensis+phenylalanine restriction (Phe-res) group.

[0051] Figure 19 This is a statistical graph showing the levels of 3-(3-hydroxyphenyl)propionic acid sulfate in the blood, feces, liver, lung tissue, and colon of mice in each group, analyzed using targeted metabolomics.

[0052] Figure 20 These are the lung injury scores and representative HE-stained lung tissue images of each group of mice; among them Figure 20 A is a statistical graph of lung injury scores in each group of mice; Figure 20 Image B shows representative HE-stained lung tissue images of mice in each group, illustrating the pathological state of the lung tissue.

[0053] Figure 21 This is a statistical graph showing the proportions of AM / CD45+, IM / CD45+, and M-Mac / CD45+ in the lungs of mice in each group, analyzed by flow cytometry.

[0054] Figure 22 These are statistical graphs showing the changes in body weight and lung injury scores of mice in each group during the Na-3SPP dose screening experiment, comparing the Normal+antib group, LPS group, LPS+L-Na-3SPP group, LPS+M-Na-3SPP group, and LPS+H-Na-3SPP group; among them Figure 22 A is a statistical graph showing the changes in body weight of mice in each group; Figure 22 B is a statistical chart of lung injury scores for each group of mice.

[0055] Figure 23 This is a statistical graph showing the expression levels of inflammatory cytokines TNF-α, IL-1β, IL-6, IL-17A, and IL-22 in the lung tissue of mice in each group during the Na-3SPP dose screening experiment, as well as a statistical graph showing the ratio of M-Mac / CD45+ in the lungs; among which... Figure 23 A is a statistical graph showing the expression levels of inflammatory cytokines TNF-α, IL-1β, IL-6, IL-17A and IL-22 in the lung tissue of mice in each group; Figure 23 B is a statistical graph showing the ratio of M-Mac / CD45+ in the lungs of mice in each group.

[0056] Figure 24 These are statistical graphs of mouse body weight changes and lung injury scores in each group, comparing the Normal+antib group, LPS group, LPS+Na-3SPP group, LPS+Bacteroides massiliensis group, and LPS+Bacteroides massiliensis+Na-3SPP group; among them Figure 24 A is a statistical graph showing the changes in body weight of mice in each group; Figure 24 B is a statistical chart of lung injury scores for each group of mice.

[0057] Figure 25 This is a statistical graph showing the expression levels of inflammatory cytokines TNF-α, IL-1β, IL-6, IL-17A, and IL-22 in the lung tissue of mice in each group.

[0058] Figure 26 This is a statistical graph showing the proportions of M-Mac / CD45+, IM / CD45+, and AM / CD45+ in the lungs of mice in each group, analyzed by flow cytometry.

[0059] Figure 27 This is a statistical graph showing the effect of different concentrations of Na-3SPP on the expression level of KDR in J774A.1 and RAW 264.7 cells analyzed by Western blot.

[0060] Figure 28 This is a statistical graph showing the effect of different concentrations of Na-3SPP on the apoptosis rate of J774A.1 and RAW 264.7 cells as detected by flow cytometry.

[0061] Figure 29 These are representative images and statistical graphs of the migration ability of J774A.1 and RAW 264.7 cells detected by Transwell assay, comparing the control group, Na-3SPP group, LPS group and LPS+Na-3SPP group.

[0062] Figure 30 This is a statistical graph showing the relative expression levels of key VEGF signaling pathway markers PTK2, Src, eNOS, RAF1, and MAP2K1 in J774A.1 and RAW 264.7 cells analyzed by Western blot, comparing the control group, Na-3SPP group, LPS group, and LPS+Na-3SPP group.

[0063] Figure 31 This is a statistical graph showing the expression levels of PTK2, Src, and eNOS in J774A.1 and RAW 264.7 cells after sh- / oe-KDR treatment, analyzed by Western blot.

[0064] Figure 32 This is a statistical graph showing the apoptosis and migration abilities of J774A.1 and RAW 264.7 cells after sh- / oe-KDR treatment, as detected by flow cytometry and Transwell assay.

[0065] Figure 33 These are representative HE-stained images of mouse lung tissue from each group, comparing the Bacteroides massiliensis+Na-3SPP group and the Bacteroides massiliensis+Na-3SPP+Heparin group.

[0066] Figure 34 These are statistical charts of lung injury scores in each group of mice, and statistical charts of the proportions of AM / CD45+, M-Mac / CD45+, and IM / CD45+ in the mouse lungs; among them Figure 34 A is a statistical graph of lung injury scores in each group of mice; Figure 34 B is a statistical graph showing the proportions of AM / CD45+, M-Mac / CD45+, and IM / CD45+ in the lungs of mice in each group.

[0067] Figure 35 This is a statistical graph showing the expression levels of KDR, Src, eNOS, and PTK2 in the lung tissue of mice in each group, analyzed by Western blot.

[0068] Figure 36This is a statistical graph of the expression levels of KDR, Src, eNOS and PTK2 in M-Mac of ARDS patients analyzed by Western blot, comparing the control group and the heparin treatment group (10 U / L, 12 hours).

[0069] Figure 37 These are representative images and statistical graphs of M-Mac migration ability in ARDS patients as detected by the Transwell assay, comparing the control group and the heparin-treated group.

[0070] Figure 38 This is a scatter plot of Pearson correlation analysis, showing the correlation between baseline information (SOFA score, APACHE-II score, PaO2 / FiO2 ratio) and Bacteroides massiliensis in ARDS patients.

[0071] Figure 39 This is the ROC curve of the relative abundance of Bacteroides massiliensis in human fecal samples.

[0072] Figure 40 This is the ROC curve of the concentration of 3-(3-Hydroxyphenyl)propionic acid sulfate in mouse serum samples.

[0073] Figure 41 This is the ROC curve of the relative abundance of Bacteroides massiliensis in mouse intestinal contents.

[0074] Figure 42 This is the ROC curve of the concentration of 3-(3-Hydroxyphenyl)propionic acid sulfate in the intestinal contents of mice. Detailed Implementation

[0075] This invention is not limited to the specific embodiments listed below. Those skilled in the art can implement this invention using various other specific embodiments based on the content disclosed herein. Any modifications or alterations made to the design structure and concept of this invention fall within the protection scope of this invention. It should be noted that, unless otherwise specified, the embodiments and features described in this invention can be combined with each other.

[0076] The information regarding the reagents involved in this invention is as follows:

[0077] IgG: Product number BE0089, brand bioxcell (USA).

[0078] Bacteroides_massiliensis: (Phocaeicola massiliensis), CCUG 48901T, other aliases: DSM 17679, JCM 13223.

[0079] LPS: Product number HY-D1056, brand MCE.

[0080] RPMI-164 culture medium: catalog number iCell-0002, brand iCell.

[0081] Male C57BL / 6 mice, 6 weeks old, were purchased from Hunan Slack Jingda Experimental Animal Co., Ltd.

[0082] The biomarkers described in this invention are used for the auxiliary diagnosis and risk assessment of ARDS or lung injury. Clinical diagnosis can also be made by combining the patient's clinical manifestations, imaging examinations, and other laboratory indicators. Those skilled in the art will understand that the detection result of a single biomarker should not be used as the sole basis for disease diagnosis.

[0083] The collection and analysis of clinical samples for this invention were approved by the Biomedical Research Ethics Committee of Nanhua University (2024077), and all participants provided written informed consent. The inclusion criteria for samples were: meeting the Berlin definition of ARDS, age ≥18 years, onset of illness ≤7 days, and signing informed consent. The exclusion criteria for samples were any one or more of the following: predominantly cardiogenic pulmonary edema, chronic respiratory failure, end-stage multiple organ failure, advanced cancer, pregnancy, inability to cooperate / family refusal.

[0084] All mouse experiments were approved by the Biomedical Research Ethics Committee of Nanhua University (2024-491).

[0085] Statistical analysis of the experimental data in this invention was performed using Graphpad Prism 8.0 software. Quantitative data are expressed as mean ± standard deviation. Student's t-test or paired t-test was used for comparisons between two groups, and one-way ANOVA was used for comparisons among multiple groups. Pearson correlation analysis was used to assess the correlation between serum differentially expressed metabolites and lung tissue immune cells (IM, NK cells, AM, B / T cells, CD4+ / CD8+ T cells, M-Mac, and macrophages). Furthermore, Pearson correlation analysis was used to assess the relationship between gut microbiota (Bacteroides massiliensis) and fecal differentially expressed metabolites (phenylacetaldehyde). Additionally, Pearson correlation analysis was used to investigate the correlation between baseline information of ARDS patients (including pneumonia scores (SOFA score, APACHE-II score, PaO2 / FiO2 ratio)) and Bacteroides massiliensis. P < 0.05 indicated statistical significance.

[0086] The steps for cell treatment are as follows:

[0087] 1. The steps for cell resuscitation are as follows:

[0088] ① Preparation: Turn on the 37℃ water bath and preheat; put 8ml of basal culture medium into a 15ml centrifuge tube and preheat it in the incubator; add 3ml of culture medium (complete culture medium) to the culture dish where cells need to be inoculated and preheat it.

[0089] ② Quickly locate the cells that need to be revived from the liquid nitrogen tank and rapidly transfer them to a 37°C water bath to thaw (generally 1-2 minutes is sufficient for thawing).

[0090] ③ After wiping the surface of the cryovial with alcohol, transfer it to a clean bench and aspirate the cells from the cryovial into a preheated 15ml centrifuge tube.

[0091] ④ Centrifuge at 900 rpm for 5 minutes.

[0092] ⑤ The obtained precipitate was resuspended in a preheated culture medium and then inoculated into a culture dish, which was then placed in an incubator (37℃, 5% CO2) for incubation.

[0093] ⑥ Observe the cell condition on the second day and change the medium.

[0094] 2. Cell passage steps (the cells do not require digestion) are as follows:

[0095] ① Gently blow on the cells to detach them from the culture dish or flask.

[0096] ④ Transfer the cells to a 15ml centrifuge tube and centrifuge at 1000rpm for 5min.

[0097] ⑤ Resuspend the complete culture medium and divide it in half, then spread it into two petri dishes.

[0098] ⑥ Incubate in a 5% CO2 incubator at 37°C.

[0099] 3. The steps for cell cryopreservation are as follows:

[0100] ① Gently blow on the cells to detach them from the culture dish or flask.

[0101] ④ Transfer the cells to a 15ml centrifuge tube and centrifuge at 1000rpm for 5min.

[0102] ⑤ Discard the supernatant, resuspend the cells in 450µl of FBS, transfer the cell suspension to a cryovial, and add 50µl of DMSO.

[0103] ⑥ Quickly transfer the cells to 4℃ for 30 min; -20℃ for 30 min; -80℃ overnight, then transfer them to a liquid nitrogen tank.

[0104] The steps for using the Transwell assay to detect cell invasion ability are as follows:

[0105] ① One day in advance, pre-cool the sterile pipette tip, EP tube, Matrigel, and Transwell chamber at 4°C overnight.

[0106] ② Add 100µl of ice-cold, serum-free DMEM medium to each well to dilute Matrigel, to a final concentration of 200µg Matrigel per well. Incubate at 37°C for 30 minutes, then aspirate the supernatant.

[0107] ③ Place 500µl of 10% fetal bovine serum complete culture medium in the lower layer of the chamber.

[0108] ④ The cells treated above were digested with trypsin to form single cells, and the cells were resuspended in serum-free medium to a concentration of 2*102. 6 100µl of cells per well.

[0109] ⑤ Place in a 37℃ incubator for 48 hours.

[0110] ⑥ Remove the upper chamber and place it in a new well containing PBS. Wash the upper chamber three times with PBS and wipe the cells in the upper chamber clean with a cotton ball.

[0111] ⑦ Fix with 4% paraformaldehyde for 20 minutes, then remove the membrane.

[0112] ⑧ Stain with 0.1% crystal violet for 5 minutes, then wash 5 times with water.

[0113] ⑨ Place the membrane on a glass slide and observe the cells on the outer surface of the upper window under an inverted microscope. Take three fields of view and count the cells.

[0114] The steps for processing and detecting cell migration ability using Transwell are as follows:

[0115] Place 500 μL of 10% Gibco fetal bovine serum complete culture medium in the lower layer of the chamber.

[0116] The cells were digested with trypsin to form single cells, and then resuspended in serum-free medium to a concentration of 2 x 10⁻⁶ cells / mL. 6 Add 100 μL of cells per well.

[0117] Place in an incubator at 37°C for 48 hours.

[0118] Remove the upper chamber and place it in a new well containing PBS. Wash the upper chamber three times with PBS and wipe the cells in the upper chamber clean with a cotton ball.

[0119] Fix with 4% paraformaldehyde for 20 minutes, then remove the membrane.

[0120] Stain with 0.1% crystal violet for 5 minutes, then wash 5 times with water.

[0121] Place the film on a glass slide and take a picture under a microscope.

[0122] Cell photography: Observe the cells on the outer surface of the upper chamber under an inverted microscope, take 3 fields of view from each chamber and count them.

[0123] The steps for the live / dead cell staining experiment are as follows:

[0124] ① Digest and count the grouped cells, in groups of 10-1 4 / cm 2 Density seeding was performed in 12-well plates, 300 μL per well.

[0125] ② After the culture cells adhere to the culture vessel and are processed for the appropriate time, live and dead cell staining is performed.

[0126] ③ Take out the original solutions of calcein AM and PI reagent and allow them to equilibrate at room temperature for 30 minutes.

[0127] ④ Add 5 μL of 16 mM PI stock solution to 10 mL of PBS, vortex to mix, and obtain an 8 μM PI solution.

[0128] ⑤ Add 5 μL of 4 mM calcein AM stock solution to 10 mL of PI solution, vortex to mix thoroughly.

[0129] ⑥ The obtained working solution (2 μM calcein AM and 8 μM PI) was used directly to stain cells.

[0130] ⑦ Gently wash adherent cells with PBS, remove the supernatant, add sufficient working solution to ensure that the monolayer of cells is submerged, and incubate at room temperature for 30-45 minutes. For adherent cells, aspirate the staining working solution to terminate the incubation, and observe the labeled cells under a fluorescence microscope.

[0131] The steps for apoptosis detection are as follows:

[0132] ① The cells were collected by digestion with trypsin without EDTA.

[0133] ② Wash the cells twice with PBS, centrifuge at 2000 rpm for 5 min each time, and collect the cells.

[0134] ③ Add 500µl of binding buffer to suspend the cells.

[0135] ④ After adding 5µl Annexin V-APC and mixing well, add 5µl Propidium Iodide and mix well.

[0136] ⑤ React at room temperature and in the dark for 10 minutes.

[0137] ⑥ Observe and detect the cells using a flow cytometer within 1 hour.

[0138] The steps for 16S rRNA sequencing are as follows:

[0139] Mouse fecal samples were grouped as follows: LPS group (9 weeks old: before FMT), LPS+normal-FMT group (14 weeks old), and LPS+ARDS-FMT group (14 weeks old). Human fecal samples were divided into control and ARDS groups. First, total DNA was extracted from fecal samples, and the V3-V4 region was selected for PCR amplification using specific primer pairs (forward: CTACGGGNGGCWGCAG, reverse: GACTACHVGGGTATCTAATCC). The amplified PCR products were purified and used to construct sequencing libraries. Subsequently, the libraries were quantified and quality-checked, and then paired-end sequencing was performed on the Illumina platform. After sequencing, the data underwent quality control, removing low-quality and adapter sequences, followed by operational taxonomic unit (OTU) clustering and species annotation. Next, Shannon and Simpson indices were calculated to assess α-diversity, and principal coordinate analysis (PCoA) was used to assess β-diversity. In addition, differential microbial community analysis was performed, and Venn diagrams were used to visualize the differentially expressed bacteria between ARDS patients and mice.

[0140] The steps of non-targeted metabolomics are as follows:

[0141] The experimental subjects were mice whose fecal and peripheral blood samples were collected at 9 weeks of age (before FMT started, after receiving antibiotic and LPS intervention) and 14 weeks of age. The experimental groups were: LPS group (9 weeks old: before FMT started), LPS + normal-FMT group (14 weeks old), and LPS + ARDS-FMT group (14 weeks old). First, samples were collected and processed, including freeze-dried fecal samples and centrifuged serum. Then, metabolites were extracted from the fecal powder and serum, followed by chromatographic separation and mass spectrometry analysis. Metabolites were separated using high-performance liquid chromatography (HPLC) or gas chromatography (GC) systems. The separated metabolites were detected using mass spectrometry (MS) systems to obtain their mass-to-charge ratio (m / z) and intensity information. Data acquisition was performed in both positive and negative ion modes to cover a wider range of metabolites. Next, data preprocessing (including peak detection, peak alignment, and normalization) and statistical analysis were performed using metabolomics data processing software (such as XCMS and MetaboAnalyst) to screen differentially expressed metabolites and create heatmaps of these metabolites in serum and feces. Furthermore, correlation analysis was performed on differentially expressed metabolites in feces and serum, and a heatmap was created to display the top 50 differentially expressed metabolites. Specifically, statistical analysis was conducted on the levels of differentially expressed metabolites in feces and serum, and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis was performed on the differentially expressed metabolites.

[0142] The steps of targeted metabolomics are as follows:

[0143] Targeted metabolomics was used to analyze the levels of 3-(3-hydroxyphenyl)propionic acid sulfate in the blood, feces, liver, lung tissue, and colon of mice. Experiments were conducted at 9 weeks of age (after antibiotic and LPS intervention prior to the start of fecal microbiota transplantation) and 14 weeks of age, involving four groups: LPS group, LPS + *Bacteroides muscarinii* group, LPS + *Bacteroides muscarinii* + Phe-sup group, and LPS + *Bacteroides muscarinii* + Phe-res group. First, blood, lung tissue, colon, liver, and fecal samples were collected from mice and processed, including centrifugation to separate serum, rapid tissue freezing, and fecal lyophilization. Subsequently, 3-(3-hydroxyphenyl)propionic acid sulfate was extracted from these samples using appropriate solvents. The extracts were then separated chromatographically by HPLC or GC systems, followed by detection using MS systems. For accurate quantification, standard solutions of 3-(3-hydroxyphenyl)propionic acid sulfate were prepared, and calibration curves were established. Data processing was performed using specialized software, including peak detection, peak alignment, and normalization. Statistical analysis will be conducted to compare the differences in 3-(3-hydroxyphenyl)propionic acid sulfate levels among different groups.

[0144] The steps of flow cytometry analysis are as follows:

[0145] Flow cytometry was used to quantitatively analyze the proportions of different immune cell populations in the lungs, including neutrophils, alveolar macrophages (AM), interstitial macrophages (IM), monocyte-derived macrophages (M-Mac), natural killer (NK) cells, B cells, and CD4+. + T cells and CD8 + T cells. First, mouse lung tissue was collected and a single-cell suspension was prepared by digestion with collagenase and DNase, followed by filtration through a mesh sieve. Cells were then counted and labeled with specific surface marker antibodies, including CD45, CD11b, Ly6G (neutrophils), F4 / 80 (macrophages), CD11c (monocytes), CD3, CD4, CD8, CD19 (B cells), and NK1.1 (NK cells). Cells were incubated in the dark for an appropriate time to allow the antibodies to bind to the cell surface markers. Cells were washed with PBS to remove unbound antibodies and then analyzed by flow cytometry, collecting forward scatter (FSC), side scatter (SSC), and fluorescence signals. Specific gating strategies were used to distinguish different cell populations.

[0146] In addition, apoptosis in total macrophages (sorted from lung) and J774A.1 and RAW 264.7 cells was analyzed using flow cytometry. Cells treated as described above were collected and digested with EDTA-free trypsin. Cells were washed twice with PBS and centrifuged at 2000 rpm for 5 minutes each time, and the cell pellet was collected. Cells were resuspended in 500 μL of binding buffer. Then, 5 μL of Annexin V-APC was added, and the mixture was mixed, followed by 5 μL of propidium iodide, and mixed again. The mixture was incubated at room temperature in the dark for 10 minutes. Cells were observed and analyzed by flow cytometry within 1 hour.

[0147] To identify melanocyte-macrophages (M-Macs) in bronchoalveolar lavage fluid (BALF) from ARDS patients, flow cytometry analysis was employed. First, sufficient BALF samples were collected from ARDS patients, and M-Macs were isolated from the BALF using centrifugation and cell sorting techniques. Subsequently, these cells were washed and counted, and labeled with specific surface marker antibodies (CD45, CD11b, and CD14) for identification on flow cytometry. The labeled cells were washed again to remove any unbound antibodies and then loaded into the flow cytometer for analysis. FSC, SSC, and fluorescence signals for each cell were collected, and data were analyzed using flow cytometry analysis software. Leukocytes were circled based on CD45 expression, and M-Macs were identified based on CD11b and CD14 expression. Finally, CD45 expression was calculated. + CD11b + CD14 + The percentage of cells in the total number of cells.

[0148] Hematoxylin and eosin (H&E) staining

[0149] Mouse lung tissue was fixed by immersion in 4% paraformaldehyde solution for 48 hours. After fixation, the tissue was dehydrated by a series of gradient ethanol solutions (100%, 100%, 95%, 85%, and 75%). It was then cleared with xylene and embedded in a suitable medium. 4 μm thick sections were prepared, stained with hematoxylin solution for 10 minutes, and then washed with distilled water. Subsequently, it was stained with eosin solution for 5 minutes and rinsed again with distilled water. For preparing sections for mounting, they were dehydrated in 95% and 100% ethanol solutions for 5 minutes each. After dehydration, they were mounted with neutral resin. Lung tissue damage was carefully observed and analyzed using a BA210T optical microscope system manufactured by Motic (China). In the figures, the scale bar is 500 μm for 20× fields of view (top row), 100 μm for 100× fields of view (middle row), and 25 μm for 400× fields of view (bottom row).

[0150] Quantitative real-time polymerase chain reaction (qRT-PCR)

[0151] Total RNA was extracted from lung tissue, HBE, and Beas-2B cells using TRIzol reagent (15596026, ThermoFisher, USA). cDNA was synthesized using the Script cDNA Synthesis Kit (CW2569, CWBio, China). mRNA expression levels were detected by qRT-PCR using UltraSYBR Mixture (CW2601, CWBio, China). Further analysis was performed using ABI Manager (QuantStudio1, USA) after detection. β-actin was used as an internal reference gene.

[0152] Western blot

[0153] Proteins were extracted using RIPA buffer (Cell Signaling Technology, USA) containing protease / phosphatase inhibitors, quantified by BCA assay, and separated by SDS-PAGE (P1200, Solarbio). After transfer, membranes were blocked with 5% skim milk / TBST and incubated with primary antibody (4°C, overnight), followed by incubation with HRP-conjugated secondary antibody (room temperature, 90 min). Protein bands were visualized by ECL (K-12049-D50, Advansta, USA) and quantified using ImageJ (National Institutes of Health, USA).

[0154] The data statistics method of this invention is as follows:

[0155] Independent samples t-test or paired t-test was used for comparisons between two groups; one-way ANOVA was used for comparisons among multiple groups; Pearson analysis was used for correlations between targets.

[0156] Example 1

[0157] Fecal microbiota transplantation (FMT) from ARDS patients exacerbates lung injury in mice.

[0158] Mice were randomly assigned to six groups: normal group, normal + antibiotic group, normal + LPS group, LPS group, LPS + normal-FMT group (fecal microbiota transplantation in healthy subjects), and LPS + ARDS-FMT group (fecal microbiota transplantation in ARDS patients). From the start of the experiment, except for the normal group and the normal + LPS group, the other mice were given drinking water containing antibiotics (0.2 g / L ampicillin, neomycin, metronidazole, and 0.1 g / L vancomycin) for two weeks. After the last antibiotic administration, mice in the LPS-labeled groups were intraperitoneally injected with LPS at a dose of 5 mg / kg and a volume of 10 ml / kg. Twenty-four hours after LPS injection, mice in the LPS + normal-FMT group and the LPS + ARDS-FMT group began fecal microbiota transplantation (FMT), administered twice weekly by gavage for four weeks. During FMT treatment, fecal samples were randomly collected from three ARDS patients and healthy individuals, mixed in equal weight proportions, and 1 gram of the mixed fecal sample was suspended in 5 ml of PBS. The initial gavage volume was 100 μL, with subsequent gavage volumes of 200 μL. Mice were weighed and observed weekly during the experiment. After four weeks of FMT, mice were sacrificed, and lung tissue was collected for further analysis: some tissue was fixed in 4% paraformaldehyde (AWI0056b, Abiowell) for pathological analysis, some was soaked in culture medium for flow cytometry, and the remainder was stored at -80℃. Simultaneously, the wet and dry weights of the lung tissue were recorded (wet weight was measured immediately after sampling, and dry weight was measured after drying in a 60℃ oven overnight), and the wet / dry weight ratio was calculated. Histopathological examination (HE staining) was performed, and lung injury scores were calculated. The expression levels of inflammatory cytokines (TNF-α, IL-1β, IL-6, IL-17A, and IL-22) in the lung tissue were detected. The proportion of immune cells in the lungs was analyzed by flow cytometry: based on CD45-gated leukocytes, the neutrophil / CD45 ratio was calculated. + AM / CD45 + (Alveolar macrophages), IM / CD45 + (interstitial macrophages) and M-Mac / CD45 + Percentage of (monocytes / macrophages).

[0159] After mice were treated with antibiotics, LPS, and ARDS-FMT, serum and lung tissue were collected from the LPS+ARDS-FMT group at 9 weeks of age (before and after FMT initiation), 10 weeks of age, 12 weeks of age, and 14 weeks of age (i.e. weeks 1, 2, 4, and 6 of intervention).

[0160] In the immune cell depletion assay, mice were treated with ARDS-FMT and simultaneously injected intraperitoneally with either anti-Ly6G (depleted neutrophils, BE0075-1, bioxcell) or CLD-Lp (depleted macrophages, HY-172202, MedChemExpress), with the LPS+ARDS-FMT+IgG group serving as a control. Mice were divided into four groups: LPS+ARDS-FMT, LPS+ARDS-FMT+IgG, LPS+ARDS-FMT+anti-Ly6G, and LPS+ARDS-FMT+CLD-Lp. Mice in the immune cell depletion groups received antibiotics, LPS, and ARDS-FMT intervention. One day before LPS intervention, mice were intraperitoneally injected with anti-Ly6G (250 μg, BE0075-1, bioxcell, every two days) to deplete neutrophils, and injected with clophosphamide liposomes (CLD-Lp, 200 μL, 5 mg / mL, HY-172202, MedChemExpress, twice a week) or isotype control antibody (IgG, BE0089, bioxcell) to deplete macrophages. The intervention in the LPS+ARDS-FMT group was as described above. After the experiment, the lung wet / dry weight ratio, lung injury score, lung histopathological features, and inflammatory cytokine expression levels were measured, and changes in the proportion of immune cells were detected by flow cytometry.

[0161] The results showed that, compared with the Normal-antib group, the LPS group mice had significantly increased lung wet / dry weight ratio, lung injury score, and expression of various cytokines (TNF-α, IL-1β, IL-6, IL-17A, and IL-22), and decreased body weight. Figure 1 A, Figure 1 B Figure 3 , Figure 2 B). Histopathological examination showed that the lung tissue of LPS group mice had obvious inflammation and tissue damage (incomplete alveolar walls, thickened alveolar septa, diffuse interstitial edema, and inflammatory cell infiltration). Figure 2 A). Compared with the LPS group, mice in the LPS+Normal-FMT group had significantly lower wet-to-dry weight ratio, lung injury score, and cytokine expression, indicating reduced lung inflammation and increased body weight; while mice in the LPS+ARDS-FMT group had significantly higher wet-to-dry weight ratio, lung injury score, and cytokine expression, indicating increased lung inflammation and decreased body weight. Figures 1-3 ).

[0162] Flow cytometry analysis showed that, compared with the Normal+antib group, the proportions of neutrophils / CD45+, AM / CD45+, IM / CD45+, and M-Mac / CD45+ in the lungs of mice in the LPS group were all increased. Figure 4 Compared to the LPS group, the LPS+Normal-FMT group showed a decrease in the ratio of neutrophils / CD45+ and M-Mac / CD45+ in the lungs of mice, while the ratios of AM / CD45+ and IM / CD45+ did not change significantly. Figure 4 In LPS+ARDS-FMT mice, the ratio of neutrophils / CD45+ in the lungs was decreased, while the ratios of IM / CD45+ and M-Mac / CD45+ were increased, and the ratio of AM / CD45+ did not change significantly. Figure 4 ).

[0163] The results of the immune cell depletion assay showed that, compared with the LPS+ARDS-FMT+IgG group, intraperitoneal injection of anti-Ly6G significantly reduced the ratios of neutrophils / CD45+ and M-Mac / CD45+; after intraperitoneal injection of CLD-Lp, the ratio of M-Mac / CD45+ was significantly reduced, while the ratios of neutrophils / CD45+ and AM / CD45+ did not change significantly. Figure 5 There was no significant change in IM / CD45+ among the groups. Figure 5 Compared with the LPS+ARDS-FMT+IgG group, intraperitoneal injection of anti-Ly6G and CLD-Lp both resulted in a decrease in lung wet / dry weight ratio, lung injury score, and improved lung tissue pathological characteristics. The expression of inflammatory cytokines (TNF-α, IL-1β, IL-6, IL-17A, and IL-22) in lung tissue was significantly reduced. Figure 6 A, Figure 6 B Figure 7 A, Figure 7 B Figure 8 Among them, intraperitoneal injection of CLD-Lp showed better results.

[0164] Therefore, the results showed that FMT from ARDS patients exacerbated LPS-induced lung inflammation and damage in mice, while FMT from healthy individuals showed an ameliorative effect. The proportion of lung macrophage subsets changed after ARDS-FMT, with an increase in the M-Mac ratio. Immune cell exhaustion assays confirmed that macrophages (rather than neutrophils) are the core effector cells that exacerbate lung injury in ARDS-FMT. Targeting macrophages (e.g., using CLD-Lp) significantly reduced lung injury, indicating that macrophages play a crucial role in promoting lung inflammation through ARDS-FMT.

[0165] Example 2

[0166] ARDS-FMT from ARDS patients promotes lung injury in mice with macrophage infiltration.

[0167] To investigate the long-term dynamic effects of ARDS-FMT on LPS-induced lung inflammation, lung tissues from mice were collected at different time points after ARDS-FMT intervention.

[0168] The experiment began in week 6 and lasted until week 14. During this period, mice received intraperitoneal injections of 5 mg / kg LPS to induce lung injury. Starting in week 9, mice received ARDS-FMT treatment twice weekly until week 14. After the experiment, bronchoalveolar lavage fluid (BALF), peripheral blood, lung tissue, and intestinal tissue were collected from the mice for analysis.

[0169] Lung tissue inflammation and damage were assessed at different time points (before week 9, after week 9, week 10, week 12, and week 14) using histopathological examination (HE staining). Lung injury scores were calculated at each time point. Neutrophil / CD45 ratio in lung tissue was detected by flow cytometry at each time point. + The proportions and M-Mac / CD45 + The proportion.

[0170] Histopathological examination revealed significant inflammation and tissue damage in the lung tissue of mice after week 9 compared to before week 9. This damage progressively worsened after ARDS-FMT treatment (weeks 10, 12, and 14). Figure 9 ).

[0171] Statistical results of lung injury scoring showed a significant increase in lung injury scores after week 9 compared to before week 9. Following ARDS-FMT at weeks 10, 12, and 14, the lung injury scores further gradually increased. Figure 10 ).

[0172] Flow cytometry analysis of the dynamic changes in immune cells showed a sharp increase in neutrophils after week 9. At weeks 10, 12, and 14, the proportion of neutrophils began to decline over time. Figure 11 After week 9, M-Mac infiltration in lung tissue significantly increased compared to before week 9, reaching its peak infiltration level before week 10. At weeks 10, 12, and 14, M-Mac levels in lung tissue began to decline. Figure 11 ).

[0173] These findings suggest that neutrophils are the first cells to respond rapidly when mouse lungs are stimulated by LPS and treated with ARDS-FMT, while macrophages (M-Macs) persist in the later stages of injury and may become major contributors. ARDS-FMT promotes the progression of lung injury in mice, accompanied by infiltration of macrophages, particularly M-Macs.

[0174] Example 3

[0175] Identification of the key enterobacterium Bacteroides massiliensis and its metabolite 3-(3-hydroxyphenyl)propionic acid sulfate

[0176] Fecal samples were collected from mice in the LPS, LPS+Normal-FMT, and LPS+ARDS-FMT groups for 16S rRNA sequencing. Shannon and Simpson indices were calculated for alpha diversity analysis. Fecal samples were collected from healthy subjects and ARDS patients, and gut microbiota were analyzed via 16S rRNA sequencing, performing alpha diversity, beta diversity, and species-level difference analyses. A Venn diagram was used to visualize the shared differential gut microbiota between ARDS patients and mice.

[0177] Untargeted metabolomics analysis was performed on peripheral blood and feces from mice to identify upregulated and downregulated metabolites. Pearson correlation analysis was used to assess the correlation between serum differentially expressed metabolites and the proportions of immune cells (IM, NK cells, AM, B / T cells, CD4+ / CD8+ T cells, monocytes, and macrophages) in lung tissue. The levels of 3-(3-hydroxyphenyl)propionate sulfate in fecal and serum metabolites were measured. KEGG functional analysis was performed on fecal differentially expressed metabolites associated with 3-(3-hydroxyphenyl)propionate sulfate (serum). Pearson correlation analysis was used to assess the relationship between gut microbiota (Bacteroides massiliensis) and fecal differentially expressed metabolites (phenylacetaldehyde).

[0178] Alpha diversity analysis showed that, compared with the LPS group, the Shannon and Simpson indices of the LPS+Normal-FMT and LPS+ARDS-FMT groups were significantly increased; compared with the LPS+Normal-FMT group, the Shannon and Simpson indices of the LPS+ARDS-FMT group were significantly decreased. Figure 12 Comparison of healthy subjects with ARDS patients showed that, compared with the control group, the ARDS group had significantly lower Shannon and Simpson indices ( ). Figure 13 Beta diversity analysis showed a clear separation in the microbial community structure between the two groups. Figure 14 Species-level analysis showed that *Bacteroides massiliensis* was significantly enriched in the LPS+ARDS-FMT group. Figure 15 Venn diagram analysis identified two shared differential gut microbiota: *Trichinellapseudospiralis* and *Bacteroides massiliensis*. Figure 16 ).

[0179] Metabolomics analysis showed that, compared with the LPS+Normal-FMT group, the levels of 3-(3-hydroxyphenyl)propionic acid sulfate in fecal and serum metabolites increased after ARDS-FMT intervention. Figure 17 Pearson correlation analysis showed a significant positive correlation between macrophages and serum differential metabolite 3-(3-hydroxyphenyl)propionate sulfate. KEGG functional analysis revealed that fecal differential metabolites associated with serum 3-(3-hydroxyphenyl)propionate sulfate were enriched in pathways involving ABC transporters, protein digestion and absorption, neuroactive ligand-receptor interactions, tryptophan metabolism, tyrosine metabolism, and phenylalanine metabolism. Among these, phenylacetaldehyde, associated with the shared differential flora *Bacteroides massiliensis*, was involved in phenylalanine metabolism.

[0180] FMT from ARDS patients remodeled the gut microbiota and metabolic composition in mice. Increased abundance of *Bacteroides massiliensis* and elevated levels of 3-(3-hydroxyphenyl)propionate sulfate were significantly associated with macrophage infiltration. The phenylalanine metabolic pathway (with phenylacetaldehyde as an intermediate) may be a bridge connecting *Bacteroides massiliensis* and 3-(3-hydroxyphenyl)propionate sulfate. These results suggest that specific gut microbiota and metabolites may be key links connecting gut and lung inflammation.

[0181] Example 4

[0182] Phenylalanine metabolism exacerbates lung damage and upregulates 3-(3-hydroxyphenyl)propionate sulfate levels.

[0183] The experiment began in week 6 and lasted until week 14. During this period, mice received intraperitoneal injections of 5 mg / kg LPS. Mice were divided into four groups: control group, LPS + Bacteroides muscarinicus group, LPS + Bacteroides muscarinicus + phenylalanine supplementation group, and LPS + Bacteroides muscarinicus + phenylalanine restriction group. After antibiotic and LPS intervention, mice were administered 2 × 10⁻⁶ LPS orally twice weekly. 7CFU of *Bacteroides massiliensis* (48901T, CCUG) or PBS. Dietary intervention was administered concurrently with LPS and *Bacteroides massiliensis* intervention. The control group received an unmodified basal diet (AIN-93G Amino Acid Rats, catalog number AIN93G-LAA). The phenylalanine-restricted (Phe-res) diet was similar to the unmodified basal diet but with 75% casein removed (or phenylalanine removed outright) and balanced with corn starch (or compensated with a phenylalanine-free synthetic amino acid mixture). For phenylalanine supplementation (Phe-sup, catalog number HY-N0215, brand MedChemExpress (MCE), CAS number 63-91-2), mice received a normal diet and 200 mg / kg of phenylalanine daily. The LPS+*Bacteroides massiliensis* group received a basal diet and an equal volume of PBS, administered orally once daily. The control group served as a control sample at week 8 (9 weeks of age, before the start of FMT). Lung, colon, liver, feces, and blood samples were collected from mice until the end of week 14. Mouse weight changes were measured. Targeted metabolomics analysis was used to detect the levels of 3-(3-hydroxyphenyl)propionic acid sulfate in blood, feces, liver, lung tissue, and colon. Lung tissue pathology was assessed using HE staining, and lung injury scores were calculated. Flow cytometry was used to analyze AM / CD45 in the lungs. + IM / CD45 + and M-Mac / CD45 + The proportion.

[0184] The results showed that, compared with the control group, the mice in the LPS+Bacteroides massiliensis group had a significant decrease in body weight. Figure 18 The levels of 3-(3-hydroxyphenyl)propionic acid sulfate in serum, feces, liver, lungs, and colon were significantly increased. Figure 19 Mice that received additional Phe-sup experienced a more significant decrease in body weight and a more significant increase in 3-(3-hydroxyphenyl)propionic acid sulfate levels; while mice that received Phe-res experienced a significant increase in body weight and a significant decrease in 3-(3-hydroxyphenyl)propionic acid sulfate levels.

[0185] Histological examination showed that, compared with the control group, mice in the LPS+Bacteroides massiliensis group had significant inflammation and tissue damage in their lung tissue, and the lung injury score was significantly increased. Figure 20 A, Figure 20 B). Mice that received additional Phe-sup showed increased inflammation and tissue damage, with a more significant increase in lung injury scores; conversely, mice that received Phe-res showed reduced lung inflammation and lower lung injury scores.

[0186] Flow cytometry analysis showed that, compared with the control group, the M-Mac / CD45+ ratio in the lungs of mice in the LPS+Bacteroides massiliensis group was significantly increased. Figure 21 Compared with the LPS+Bacteroides massiliensis group, the proportion of M-Mac / CD45+ in the lung tissue of mice treated with Phe-res was reduced, while the proportions of IM / CD45+ and AM / CD45+ did not change significantly. Figure 21 ).

[0187] Example 5

[0188] The metabolite 3-(3-hydroxyphenyl)propionate sulfate regulates the VEGF signaling pathway by targeting KDR, inhibiting macrophage apoptosis and promoting migration.

[0189] The experiment began in week 6 and lasted until week 14, with mice receiving intraperitoneal injections of 5 mg / kg LPS. Starting in week 9, mice were treated with low-dose sodium 3-(3-(sulfonyloxy)phenyl)propionate Na-3SPP (L-Na-3SPP, BD01426697, Bioderm, 95% purity), medium-dose Na-3SPP (M-Na-3SPP), and high-dose Na-3SPP (H-Na-3SPP), respectively. Sodium 3-(3-(sulfonyloxy)phenyl)propionate is the sodium salt of 3-(3-hydroxyphenyl)propionate sulfate, which is more stable than 3-(3-hydroxyphenyl)propionate sulfate itself and was used for intervention. Mice were divided into five groups: normal group, LPS group, LPS+L-Na-3SPP group, LPS+M-Na-3SPP group, and LPS+H-Na-3SPP group. Following LPS intervention, mice in the LPS+L-Na-3SPP, LPS+M-Na-3SPP, and LPS+H-Na-3SPP groups were intraperitoneally injected with saline containing low (1 mg / kg / day), medium (5 mg / kg / day), and high (10 mg / kg / day) Na-3SPP, respectively, until the intervention ended. The normal control group served as the LPS control and did not receive LPS or Na-3SPP intervention. Lung samples were collected from mice at 14 weeks of age (6 weeks after intervention). Before tissue collection, mice were weighed, and changes in body weight, lung injury scores, expression of inflammatory cytokines (TNF-α, IL-1β, IL-6, IL-17A, and IL-22) in lung tissue, lung histopathological features, and the M-Mac / CD45+ ratio were measured by flow cytometry.

[0190] The results showed that, compared with the LPS group, mice treated with L-Na-3SPP, M-Na-3SPP, and H-Na-3SPP experienced more significant weight loss, gradually increased lung injury scores, and significantly increased expression of inflammatory cytokines in lung tissue, along with an increased M-Mac / CD45 ratio. + The proportion increased more significantly ( Figure 22 A, Figure 22 B Figure 23 A, Figure 23 B). H-Na-3SPP treatment showed the most significant aggravating effect and was selected as the concentration for subsequent studies.

[0191] Mice were treated with *Bacteroides muscarinicus* and Na-3SPP, and divided into five groups: normal + antibiotic group, LPS group, LPS + Na-3SPP group, LPS + *Bacteroides muscarinicus* group, and LPS + *Bacteroides muscarinicus* + Na-3SPP group. After antibiotic and LPS intervention, mice were administered 2 × 10^7 CFU of *Bacteroides muscarinicus* or PBS by gavage twice a week. Simultaneously, after LPS intervention, mice in the LPS + Na-3SPP group and the LPS + *Bacteroides muscarinicus* + Na-3SPP group received intraperitoneal injections of saline containing a high dose (10 mg / kg / day) of Na-3SPP until the end of the intervention. The normal group served as the LPS control group and received only antibiotic intervention. Lung samples were collected from mice at 14 weeks of age (6 weeks after intervention). Mice were weighed before tissue collection to detect changes in body weight, lung injury scores, expression of inflammatory cytokines in lung tissue, pathological features of lung tissue, and the proportions of M-Mac / CD45+, IM / CD45+ and AM / CD45+ and total macrophage apoptosis were detected by flow cytometry.

[0192] The results showed that, compared with the LPS group, mice treated with Na-3SPP, Bacteroides massiliensis, and Bacteroides massiliensis + Na-3SPP experienced more significant weight loss. Figure 24 A) The increase in lung injury score was more significant ( Figure 24 B), inflammatory cytokine expression was significantly increased ( Figure 25 The increase in the proportion of M-Mac / CD45+ is more significant. Figure 26 Compared with the LPS group, total macrophage apoptosis was significantly reduced after treatment with Na-3SPP, Bacteroides massiliensis, and Bacteroides massiliensis + Na-3SPP.

[0193] The common targets between the metabolite 3-(3-hydroxyphenyl)propionate sulfate and diseases (ARDS and sepsis) were analyzed using Venn diagrams to construct a target interaction network. MCODE clustering analysis was used to screen key targets, identifying KDR as a key target. Molecular docking was performed between 3-(3-hydroxyphenyl)propionate sulfate and KDR proteins (human and mouse origins), and the binding energy was calculated. Molecular dynamics simulations (30-100 ns) were conducted to detect RMSD, RMSF, Rg, and SASA values.

[0194] Venn diagram and MCODE clustering analysis confirmed KDR as the key target. Molecular docking results showed that 3-(3-hydroxyphenyl)propionic acid sulfate had a binding energy of -6.5 kcal / mol with human KDR protein and -6.6 kcal / mol with mouse KDR protein, both less than -5 kcal / mol, indicating that the compound can spontaneously bind to the protein well, mainly through hydrogen bonding and hydrophobic interactions. Molecular dynamics simulations showed that the RMSD values ​​of the protein-small molecule complex and the free protein tended to stabilize after 30 ns. The RMSD value of the protein-small molecule complex (30-100 ns) was 2.125517 ± 0.03912274 nm, and the RMSD value of the free protein was 2.062554 ± 0.03403726 nm. The SASA value of the protein-small molecule complex was 273.105 ± 6.253225 nm, which was smaller than the SASA value of the free protein (276.6024 ± 6.382336 nm), indicating that the complex structure was more compact after the protein bound to the small molecule.

[0195] Mouse macrophage lines J774A.1 (iCell-m024, iCell) and RAW 264.7 (iCell-m047, iCell) were cultured in DMEM (iCell-0001, iCell) medium containing 10% fetal bovine serum and 1% penicillin / streptomycin. Macrophages (J774A.1 and RAW 264.7) were treated with different concentrations of Na-3SPP (0, 5, 25, 50, 100, and 200 μM) for 12 hours, while simultaneously being intervened with 1 μg / mL LPS (HY-D1056, MCE). Control cells were cultured without LPS and Na-3SPP intervention.

[0196] Apoptosis rate was detected by flow cytometry to screen for the optimal Na-3SPP concentration (25 μM). KDR expression level was detected by Western blot. Cell migration ability was detected by Transwell assay. The relative expression levels of VEGF signaling pathway-related proteins PTK2, Src, eNOS, RAF1, and MAP2K1 were detected by Western blot.

[0197] The results showed that, compared with the control group, the expression of KDR in J774A.1 and RAW 264.7 cells was significantly increased in the Na-3SPP group; compared with the LPS group, the expression of KDR in the LPS+Na-3SPP group was also significantly increased. Figure 27 The most significant inhibitory effect on macrophage apoptosis was observed at a concentration of 25 μM Na-3SPP. Figure 28 Na-3SPP significantly reduced LPS-induced apoptosis and significantly increased LPS-induced cell migration. Figure 29 Western blot analysis showed that, compared with the LPS group, the expression of PTK2 and MAP2K1 was significantly decreased, while the expression of Src and eNOS was significantly increased, and the expression of RAF1 remained unchanged. Figure 30 ).

[0198] After selecting appropriate concentrations, cells were grouped into: control group, Na-3SPP group, LPS group, and LPS+Na-3SPP (25 μM Na-3SPP) group. J774A.1 and RAW 264.7 cells were treated with sh- / oe-KDR and then intervened with LPS or Na-3SPP, resulting in the following groupings: LPS group, LPS+Na-3SPP group, LPS+Na-3SPP+sh-NC group, LPS+Na-3SPP+sh-KDR group, LPS+Na-3SPP+oe-NC group, and LPS+Na-3SPP+oe-KDR group. Based on M-Macs isolated from BALF of ARDS patients, macrophages isolated from each patient were considered independent samples and divided into two groups: one as the control group and the other treated with heparin as the heparin group. M-Macs were treated with 10 U / L heparin for 12 hours. The KDR-targeting shRNA (HG-shMO010612, HonorGene, target sequence: 5'-GCCCGTATGCTTGTAAAGAAT-3') and control shRNA (target sequence: 5'-TTCTCCGAACGTGTCACGT-3'), as well as the plasmid for KDR overexpression (HG-MO010612) and control plasmid, were synthesized by HonorGene (Changsha, China). Transfection of shRNA and plasmids was performed using Lipofectamine™ 2000 (11668019, Invitrogen) according to the manufacturer's instructions. The transfection steps (5 µl of siRNA and mimic, etc.) are as follows:

[0199] ①Take out the required oe-KDR plasmid and oe-NC plasmid, and thaw them on ice.

[0200] ② Take four sterile centrifuge tubes. Take two of them and add 95 µL of serum-free culture medium to each tube. Then add 3 µg of oe-KDR plasmid (HG-shMO010612, HonorGene) and 5 µL of Lip2000 to each centrifuge tube, respectively. Add the oe-NC plasmid (HG-MO010612, HonorGene) to the corresponding centrifuge tubes in the same manner.

[0201] ③ Mix gently, let stand at room temperature for 5 minutes, then mix the two tubes together, about 200 µL in total, and let stand at room temperature for 20 minutes.

[0202] ④ Finally, add the mixture evenly to the wells to be transfected and mix well.

[0203] ⑤ After incubating in a 37 ℃ incubator for 6 hours, replace with fresh complete culture medium.

[0204] After LPS or Na-3SPP intervention, changes in PTK2, Src, and eNOS expression, as well as changes in cell apoptosis and migration ability, were detected.

[0205] The results showed that after KDR knockdown, PTK2 expression increased in the LPS+Na-3SPP group (compared to the non-knockdown group), while Src and eNOS expression decreased; after KDR overexpression, PTK2 expression decreased, while Src and eNOS expression increased. Figure 31 KDR knockdown increased apoptosis and decreased migration in J774A.1 and RAW 264.7 cells; KDR overexpression decreased apoptosis and increased migration. Figure 32 ).

[0206] In summary, the differential metabolite 3-(3-hydroxyphenyl)propionate sulfate can directly target and bind to KDR (binding energy < -5 kcal / mol), thereby exacerbating lung injury by regulating the VEGF signaling pathway (inhibiting PTK2 and MAP2K1, activating Src and eNOS) to inhibit macrophage apoptosis and promote macrophage migration. KDR is a key functional receptor for this metabolite, mediating its anti-apoptotic and pro-migration effects.

[0207] Example 6

[0208] Heparin alleviates lung injury induced by the combined effects of Bacteroides massiliensis and Na-3SPP and affects VEGF signaling pathways and cell migration.

[0209] Animal experiments: Heparin and Na-3SPP were used for intervention, with mice divided into two groups: *Bacteroides muscarinii* + Na-3SPP group and *Bacteroides muscarinii* + Na-3SPP + heparin group. Six-week-old mice received antibiotics and LPS intervention, followed by *Bacteroides muscarinii* via gavage and intraperitoneal injection of Na-3SPP until the end of the intervention period. One hour after each Na-3SPP intervention, heparin (9041-08-1, aladdin) was injected intraperitoneally at a dose of 400 U / kg, or an equal volume of physiological saline was used as a control. Lung samples were collected from mice at 14 weeks of age (6 weeks after intervention), and mice were weighed before tissue collection. Inflammation and tissue damage were assessed by histopathological examination, and lung injury scores were calculated. AM / CD45 was detected by flow cytometry. + M-Mac / CD45 + and IM / CD45 + The proportions of KDR, Src, eNOS, and PTK2 were measured using Western blot.

[0210] Histopathological examination showed that, compared with the Bacteroides massiliensis + Na-3SPP group, the Bacteroides massiliensis + Na-3SPP + Heparin group significantly reduced lung inflammation and tissue damage. Figure 33 ), lung injury score significantly reduced ( Figure 34 A). Flow cytometry analysis showed that, compared with the Bacteroides massiliensis + Na-3SPP group, the heparin group mice had significantly lower AM / CD45+ and M-Mac / CD45+ ratios and significantly higher IM / CD45+ ratios in the lungs. Figure 34 B). Western blot analysis showed that, compared with the Bacteroides massiliensis + Na-3SPP group, the expression of KDR, Src, and eNOS was significantly decreased in the heparin group, while the expression of PTK2 was significantly increased. Figure 35 ).

[0211] Human cell experiments: Bronchoalveolar lavage fluid (BALF) was collected from ARDS patients, and monocytes / macrophages (M-Macs) were isolated and identified by flow cytometry. Cells were treated with 10 U / L heparin for 12 hours, with the untreated group serving as a control. Western blot was used to detect the expression of KDR, Src, eNOS, and PTK2. The migration ability of M-Macs was assessed using a Transwell assay.

[0212] Flow cytometry confirmed the successful isolation of M-Mac. Compared with the control group, the expression of KDR, Src, and eNOS in M-Mac of ARDS patients treated with heparin was significantly reduced, while the expression of PTK2 was significantly increased. Figure 36 Compared with the control group, the migration ability of M-Mac was reduced in the heparin group. Figure 37 ).

[0213] Clinical correlation analysis: Pearson correlation analysis was used to study the correlation between baseline information (SOFA score, APACHE-II score, PaO2 / FiO2 ratio) and Bacteroides massiliensis in ARDS patients. Figure 38 ).

[0214] The results showed that SOFA score, APACHE-II score, and PaO2 / FiO2 were positively correlated with Bacteroides massiliensis. Figure 38 ).

[0215] In summary, heparin can alleviate lung injury induced by the combined effects of Bacteroides massiliensis and Na-3SPP. The mechanism is related to the inhibition of VEGF signaling pathway-related proteins (downregulation of KDR / Src / eNOS and upregulation of PTK2) and reduction of M-Mac migration capacity. In M-Macs derived from ARDS patients, heparin also inhibited VEGF signaling pathway protein expression and reduced cell migration capacity.

[0216] Example 7

[0217] A new LPS-induced mouse lung injury model was constructed. After confirming successful model construction, the LPS+Normal-FM group and the LPS+ARDS-FMT group were prepared according to the above embodiments. The LPS+Normal-FMT group served as the control, and the LPS+ARDS-FMT group served as the experimental group. Fecal samples from mice were collected for 16S rRNA sequencing, and serum samples from mice were collected for non-targeted metabolomics studies. For example, total fecal DNA was extracted using the QIAamp DNA Stool Mini Kit, and the 16S rRNA gene was amplified using the bacterial universal primers 11F / 1512R. After sequencing on the Illumina platform, the results were compared with the Silva database to annotate the relative abundance of *Bacteroides massiliensis*.

[0218] We collected fecal and serum samples from a new cohort of healthy subjects and ARDS patients, using the same inclusion and exclusion criteria as above. Gut microbiota analysis was performed using 16S rRNA sequencing. Fecal samples were collected for 16S rRNA sequencing, and serum samples were collected for untargeted metabolomics studies.

[0219] The concentration of 3-(3-Hydroxyphenyl)propionic acid sulfate was determined using liquid chromatography-tandem mass spectrometry (LC-MS / MS). Qualitative analysis was performed using the mass-to-charge ratio (m / z) and retention time, while absolute quantification was achieved using a standard curve. After protein precipitation with acetonitrile, the sample was separated using a C18 column. Data was acquired in ESI negative ion mode using MRM mode (mother ion m / z 245.0 - daughter ion m / z 165.0). Method validation results showed a linear range of 0.5–200 ng / mL (R0.0). 2 =0.997), the limit of quantitation was 0.5 ng / mL, the intra- and inter-batch precision RSDs were both less than 10%, and the spiked recovery rate was 88.2%-106.5%, which met the requirements of the guidelines for biological sample analysis and detection.

[0220] Using clinical diagnosis of ARDS as the gold standard, ROC curve analysis was performed on the relative abundance of Bacteroides massiliensis in human fecal samples. The results are as follows: Figure 39 As shown in the figure. The results show that the area under the curve (AUC) is 0.7063, the P-value is 0.0440, the cutoff value corresponding to the maximum point of the Youden index is relative abundance > 0.018%, the corresponding sensitivity is about 68.2%, and the corresponding specificity is about 64.5%.

[0221] The above results indicate that the relative abundance of Bacteroides massiliensis in human feces has moderate and statistically significant diagnostic value for ARDS (P < 0.05) and can be used as a candidate microbial biomarker for the auxiliary diagnosis of ARDS.

[0222] Using the diagnostic results of the mouse ARDS model as the gold standard, ROC curve analysis was performed on the concentration of 3-(3-Hydroxyphenyl)propionic acid sulfate in mouse serum samples. The results are as follows: Figure 40 As shown.

[0223] The results showed that the area under the curve (AUC) was 0.8800, the P-value was 0.0041, the cutoff value corresponding to the maximum Youden index was >12.5 ng / mL, the corresponding sensitivity was about 85.0%, and the corresponding specificity was about 82.0%.

[0224] The above results indicate that the concentration of 3-(3-Hydroxyphenyl)propionic acid sulfate in mouse serum has high diagnostic value for ARDS (AUC = 0.88, P < 0.01), and its diagnostic efficacy is significantly better than that of fecal microbial markers. It can be used as a core metabolite marker for the diagnosis of ARDS.

[0225] Using the diagnostic results of a mouse ARDS model as the gold standard, ROC curve analysis was performed on the relative abundance of Bacteroides massiliensis in the intestinal contents of mice. The results are as follows: Figure 41 As shown.

[0226] The results showed that the area under the curve (AUC) was 0.7000, the P-value was 0.1306, the cutoff value corresponding to the maximum point of the Youden index was relative abundance > 0.020%, the corresponding sensitivity was about 65.0%, and the corresponding specificity was about 70.0%.

[0227] The above results indicate that the relative abundance of Bacteroides massiliensis in the mouse gut has a moderate ability to distinguish ARDS models (AUC = 0.70).

[0228] Using the diagnostic results of the mouse ARDS model as the gold standard, ROC curve analysis was performed on the concentration of 3-(3-Hydroxyphenyl)propionic acid sulfate in the intestinal contents of mice. The results are as follows: Figure 42 As shown.

[0229] The results showed that the area under the curve (AUC) was 0.9700, the P-value was 0.0004, the cutoff value corresponding to the maximum point of the Youden index was a relative abundance > 15.2 ng / g, the corresponding sensitivity was about 94.0%, and the corresponding specificity was about 92.0%.

[0230] The above results indicate that the concentration of 3-(3-Hydroxyphenyl)propionic acid sulfate in the mouse intestine has extremely strong and highly significant diagnostic value for ARDS models (AUC = 0.97, P < 0.001), which is close to the level of ideal diagnostic biomarkers, providing strong animal model validation evidence for the core metabolite biomarkers of this invention.

[0231] It should be noted that the above embodiments are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art can make other variations or modifications based on the above description. It is impossible to exhaustively list all possible implementations here. All obvious variations or modifications derived from the technical solutions of this invention are still within the scope of protection of this invention.

Claims

1. The use of reagents for detecting the level of 3-(3-hydroxyphenyl)propionic acid sulfate and / or reagents for detecting the abundance of Bacteroides massiliensis in the preparation of kits for risk assessment of ARDS or lung injury.

2. The application according to claim 1, characterized in that, The test samples are selected from blood, serum, feces or bronchoalveolar lavage fluid.

3. The application according to claim 1, characterized in that, Elevated levels of 3-(3-hydroxyphenyl)propionate sulfate suggest an increased risk of ARDS or lung injury.

4. The application according to claim 3, characterized in that, A serum level of 3-(3-hydroxyphenyl)propionate sulfate > 12.5 ng / mL indicates an increased risk of ARDS or lung injury; a gut content level of 3-(3-hydroxyphenyl)propionate sulfate > 15.2 ng / g also indicates an increased risk of ARDS or lung injury.

5. The application according to claim 1, characterized in that, Increased abundance of Bacteroides massiliensis suggests an increased risk of ARDS or lung injury.

6. The application according to claim 5, characterized in that, A relative abundance of Bacteroides massiliensis > 0.018% in fecal samples suggests an increased risk of ARDS or lung injury; a relative abundance of Bacteroides massiliensis > 0.020% in intestinal contents also suggests an increased risk of ARDS or lung injury.

7. A kit for the auxiliary diagnosis of ARDS or lung injury, characterized in that, It includes: (a) A reagent for detecting the level of 3-(3-hydroxyphenyl)propionic acid sulfate or its salts; and / or (b) Reagents for detecting the abundance of Bacteroides massiliensis.

8. The reagent kit according to claim 7, characterized in that, The reagents for detecting 3-(3-hydroxyphenyl)propionic acid sulfate levels are selected from: liquid chromatography-mass spectrometry reagents, enzyme-linked immunosorbent assay reagents, colorimetric reagents, or fluorescent reagents; the reagents for detecting Bacteroides massiliensis abundance are selected from: 16S rRNA sequencing reagents, quantitative PCR reagents, fluorescence in situ hybridization reagents, or specific antibody reagents.

9. A detection system for assessing the risk of ARDS or lung injury, characterized in that, Include: (a) Sample collection unit: used to collect blood, serum, feces or bronchoalveolar lavage fluid samples; (b) Detection unit: used to detect the level of 3-(3-hydroxyphenyl)propionic acid sulfate and / or the abundance of Bacteroides massiliensis in the sample; (c) Assessment unit: used to compare test results with reference values ​​to assess the risk of ARDS or lung injury.

10. The detection system according to claim 9, characterized in that, The detection unit includes a liquid chromatography-mass spectrometry system or a quantitative PCR instrument.

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