Akkermansia muciniphila and Its Extracellular Vesicles Alleviate LPS-Induced Acute Respiratory Distress Syndrome in Rats: Integrated Microbiome, Metabolomic, and Transcriptomic Analyses

Abstract

Purpose

Akkermansia muciniphila (AKK) and its extracellular vesicles (EVs) have immunomodulatory and metabolic effects, but their protective effects in acute respiratory distress syndrome (ARDS) remain unclear. This study compared live AKK with AKK-EVs and investigated their effects on LPS-induced ARDS using integrated microbiome, metabolome, and lung transcriptome analyses.

Methods

An ARDS rat model was established by intratracheal instillation of lipopolysaccharide (LPS). Rats were randomly allocated to the control, ARDS, AKK, and EVs groups. Following model establishment, AKK or AKK-EVs were administered orally once daily for 7 consecutive days. Lung injury was evaluated by body weight, hematoxylin and eosin staining, lung wet/dry weight ratio, and bronchoalveolar lavage fluid (BALF) analysis. Fecal 16S rRNA sequencing, untargeted metabolomics, lung transcriptomics, and integrated multi-omics analyses were performed. The pulmonary expression of Il17a, Cxcl1, Tnf, and Il6 was validated by qRT-PCR.

Results

Compared with the ARDS group, AKK and AKK-EVs attenuated weight loss and lung histopathological injury and reduced the lung wet/dry weight ratio, BALF total cell count and protein concentration, and BALF IL-17A and TNF-α levels. Both interventions partially remodeled the gut microbial community, including changes in Lachnospiraceae_NK4A136_group, norank_f_Muribaculaceae, Bacteroides, and Escherichia-Shigella. Metabolomic changes mainly involved lipid, amino acid, and bile acid metabolism. Lung transcriptomic analysis identified differential enrichment of the IL-17, TNF, chemokine, and cytokine–cytokine receptor interaction pathways. qRT-PCR further showed increased Il17a, Cxcl1, Tnf, and Il6 expression in the ARDS group and reduced expression following AKK or AKK-EVs intervention. Integrated analyses identified associations among alterations in gut microbiota, metabolites, and pulmonary gene expression.

Conclusion

AKK and AKK-EVs alleviated LPS-induced ARDS, accompanied by remodeling of gut microbial and metabolic profiles and attenuation of pulmonary IL-17- and TNF-related inflammatory signaling. AKK-EVs may represent a potential cell-free intervention for ARDS.

Introduction

Acute respiratory distress syndrome (ARDS) is a critical syndrome induced by various factors such as infection, trauma, and severe pancreatitis. Its main pathological features include damage to the alveolar epithelium and pulmonary microvascular endothelial barrier, leading to pulmonary edema, severe hypoxemia, and excessive pulmonary inflammatory response.^1,2 Despite advances in intensive care and supportive treatment, ARDS still lacks effective specific drug therapy, and the mortality rate remains high.^1,3 It is currently believed that the occurrence and development of ARDS are closely related to inflammatory response imbalance, abnormal immune cell infiltration, and activation of multiple inflammatory signaling pathways.^4,5 However, therapeutic strategies targeting a single inflammatory target have limited clinical efficacy, suggesting the complexity and heterogeneity of the pathological mechanisms of ARDS.⁶

In recent years, the role of the gut–lung axis in ARDS has received increasing attention. The gut microbiota may influence pulmonary inflammation through alterations in intestinal barrier function, translocation of microorganisms and their products, microbial metabolites, and systemic immune responses.^7,8 During critical illness, gut microbial dysbiosis may disrupt the intestinal mucosal barrier, promote bacterial and endotoxin translocation, amplify systemic inflammation, and exacerbate lung injury.^9,10 Gut-derived metabolites, including short-chain fatty acids, bile acids, and amino acid derivatives, also contribute to pulmonary immune homeostasis, and their dysregulation may be associated with ARDS progression.^11,12 However, much of the current evidence remains associative, and the causal links among microbial alterations, metabolic changes, and pulmonary injury require further investigation.

Akkermansia muciniphila (AKK) is a Gram-negative anaerobic commensal bacterium that resides in the intestinal mucus layer and contributes to the maintenance of mucus barrier integrity, host metabolism, and immune homeostasis.^13,14 Reduced AKK abundance has been associated with inflammatory bowel disease, metabolic syndrome, and other inflammation-related diseases.^15–17 In experimental lung injury, AKK has been regarded as a potentially protective gut bacterium. Epigallocatechin-3-gallate (EGCG) pretreatment attenuated LPS-induced lung injury in mice, accompanied by an increase in AKK abundance.¹¹ Direct administration of AKK also reduced pulmonary inflammation and oxidative injury, improved intestinal barrier function, remodeled the gut microbiota, and increased short-chain fatty acid production in LPS-induced acute lung injury, potentially through butyrate-mediated modulation of TLR2/MyD88/NF-κB signaling.¹⁸ However, these effects do not necessarily indicate persistent intestinal engraftment of the administered AKK. The observed pulmonary protection may also be associated with transient microbial exposure, broader microbiota remodeling, microbial metabolites, and host immune–metabolic responses.

In addition to live bacteria, extracellular vesicles derived from Akkermansia muciniphila (AKK-EVs) have attracted increasing attention. AKK-EVs are nanoscale vesicles containing proteins, lipids, nucleic acids, and other bioactive molecules and may mediate bacterial–host communication without requiring live bacterial colonization.¹⁹ Previous studies have shown that AKK-EVs can alleviate smoking-related prostate inflammation and fibrosis, improve metabolic disorders and tissue inflammation in obesity and liver injury models, and regulate antitumor immune responses.^20–23 Live and pasteurized A. muciniphila and its EVs attenuated pulmonary inflammation and fibrosis in an HFD/CCl4-induced pulmonary fibrosis model.²⁴ Although these findings support the potential pulmonary protective effects of AKK-EVs, evidence in ARDS remains limited. Moreover, direct comparisons between live AKK and AKK-EVs and their associated changes across the gut microbiome, metabolome, and pulmonary transcriptome have not been adequately investigated.

Accordingly, the present study compared the effects of AKK and AKK-EVs on lung injury and inflammation in an LPS-induced rat model of ARDS. Fecal 16S rRNA sequencing, untargeted metabolomics, and lung transcriptomics were integrated to characterize associated changes in the gut microbiota, metabolic profiles, and pulmonary inflammatory signaling, while selected IL-17- and TNF-related genes were validated by qRT-PCR. This study aimed to provide integrated experimental evidence supporting the potential application of AKK and AKK-EVs in ARDS.

Materials and Methods

Culture of AKK

Akkermansia muciniphila (TS263615) was purchased from Taistobio Company. The culture medium used was chopped meat carbohydrate broth (DSMZ Medium 110 CMC), supplemented with cooked meat particles (Solarbio, LA0890), vitamin K1 solution (Solarbio, V8151), and hemin solution (Solarbio, H8132). The strain was cultured under anaerobic conditions at 37°C for 72 hours. Bacterial concentration was determined by measuring optical density (OD) at 600 nm (OD₆₀₀ ≈ 1). The bacterial suspension was centrifuged at 4°C and 4000 × g for 10 min to collect the bacterial pellet, which was washed twice with sterile PBS (Solarbio, B0015-500mL), resuspended, and adjusted to a concentration of 1 × 10⁹ CFU/mL using a turbidity tube for subsequent use.

Extraction and Characterization of AKK-EVs

The cultured bacterial suspension was centrifuged at 4°C and 2000 × g for 30 min, and the supernatant was collected and then centrifuged at 10,000 × g for 45 min. The supernatant was subsequently filtered through a 0.22 μm membrane, and the filtrate was ultracentrifuged at 4°C and 100,000 × g for 70 min. After discarding the supernatant, the pellet was resuspended in pre-cooled 1×PBS and washed again by ultracentrifugation at 100,000 × g for 70 min. The final pellet was resuspended in 100 μL of pre-cooled PBS to obtain AKK-EVs. The morphology of AKK-EVs was observed using a transmission electron microscope (Hitachi, HT-7700), and their particle size distribution was measured using a nanoparticle tracking analyzer (NanoFCM, N30E). Protein concentration was determined using a BCA protein assay kit (Beyotime, P0010) and adjusted to 1 μg/μL with PBS, then aliquoted and stored at −80°C for subsequent use.²¹

Animal Grouping and Model Establishment

Male specific-pathogen-free Sprague–Dawley rats (4–6 weeks old, 150–200 g) were purchased from Hunan SJA Laboratory Animal Co., Ltd. Twenty-four rats were randomly assigned using a random number table to the control, ARDS, AKK, and EVs groups (n=6 per group). The rats were acclimatized for 1 week under a 12-h light/dark cycle at 23–25°C, with free access to food and water. The study was approved by the Animal Ethics Committee of Liuzhou People’s Hospital (approval no. LRYIACU2025022).

For ARDS induction, rats were anesthetized by intraperitoneal injection of 20% urethane (0.6 mL/100 g body weight). After adequate anesthesia was confirmed, the rats were placed in the supine position and intubated intratracheally under direct visualization. Lipopolysaccharide (LPS; Merck, catalog no. L2880-25MG) was freshly dissolved in sterile PBS at a concentration of 5 mg/mL. Rats in the ARDS, AKK, and EVs groups received LPS intratracheally at 5 mg/kg body weight, with an administration volume of 1 mL/kg. Control rats received an equivalent volume of sterile PBS through the same procedure.

Following model induction, the AKK group received 2 mL of freshly prepared AKK suspension (1 × 10⁹ CFU/mL), and the EVs group received AKK-EVs containing 100 μg protein in 2 mL by oral gavage once daily for 7 consecutive days. The control and ARDS groups received 2 mL PBS according to the same schedule. At 24 h after the final intervention, the rats were deeply anesthetized with 20% urethane (0.6 mL/100 g, intraperitoneally) and euthanized according to the approved protocol. Bronchoalveolar lavage fluid, lung tissues, and fecal samples were subsequently collected for further analyses.

General Observation of Rats in Each Group

During the experiment, the mental activity, body weight changes, food intake, water intake, fur color, respiration, and responses to external stimuli of rats in each group were monitored.

Lung Wet/Dry Weight Ratio

The right lower lung lobe of rats was collected, blotted dry with absorbent paper, and immediately weighed to obtain the wet weight (W). It was then placed in an oven at 80°C for 48 hours to dry, and the dry weight (D) was measured. The wet/dry weight ratio was calculated to assess the degree of pulmonary edema.

Histopathological Analysis

Left lung tissue of rats was fixed in 4% paraformaldehyde (Solarbio, P1110) for 24 hours, dehydrated, embedded in paraffin, and sectioned into 3 μm slices. The sections were deparaffinized, rehydrated, stained with hematoxylin (Sigma-Aldrich, H3136) for 8 minutes, and then with eosin (Sigma-Aldrich, E4009) for 1 minute. Stained sections were examined under a light microscope (Leica, DM2000) and photographed at ×200 magnification.

BALF Analysis

BALF was collected from rats: the neck and chest were dissected, the trachea and right lung lobes were ligated, and the left lung was lavaged. The collected BALF was centrifuged at 4°C and 500 × g for 5 min. The supernatant was aliquoted and stored at −80°C for subsequent analysis. The cell pellet was resuspended in PBS and diluent (Mindray, V-52D), and white blood cell differential counts were performed using a cell analyzer (Mindray, BC-5000Vet). Total protein content in BALF was measured using a BCA protein assay kit. Additionally, levels of IL-17A and TNF-α in BALF were detected using ELISA kits according to the manufacturer’s instructions.¹⁸

16S rRNA Gene Sequencing and Bioinformatic Analysis

Total DNA was extracted from rat fecal samples using the FastPure Stool DNA Isolation Kit (MJYH, Shanghai, China). The V3–V4 region of the 16S rRNA gene was amplified using primers 338F and 806R.²⁵ After detection, purification, and quantification of PCR products by 2% agarose gel electrophoresis, sequencing libraries were constructed using the NEXTFLEX Rapid DNA-Seq Kit and subjected to high-throughput sequencing on the Illumina NextSeq 2000 PE300 platform. Raw data were quality-controlled, assembled, denoised, and chimeras removed to obtain amplicon sequence variants (ASVs). Species annotation was performed based on the Silva database (version 138.2), and taxonomic analysis was completed using QIIME2. Alpha diversity was assessed using Sobs, Chao, and Shannon indices, and beta diversity was evaluated by Principal Coordinates Analysis (PCoA) based on Bray–Curtis distance. Differences between groups were tested using ANOSIM or PERMANOVA. Further, BugBase was used for microbial phenotype prediction, and PICRUSt2 was used to predict potential functional pathways of the gut microbiota.²⁶

Non-Targeted Metabolomics Analysis

A 100 mg sample of rat feces was taken, and metabolites were extracted using pre-cooled extraction solution (methanol: water = 4:1, v/v, containing internal standards). After low-temperature grinding, sonication, and centrifugation, the supernatant was collected for detection. Non-targeted metabolomics analysis was performed using a UHPLC-Q Exactive HF-X system (Thermo Fisher Scientific, USA), with chromatographic separation on an HSS T3 column and mass spectrometry data acquisition in positive and negative ion modes. Raw data were processed using Progenesis QI software for peak identification, alignment, normalization, and metabolite annotation, combined with HMDB and Metlin databases for identification. Principal component analysis (PCA) was used to analyze overall metabolic profile differences among groups. Differentially expressed metabolites were screened with criteria of VIP > 1 and P < 0.05, and visualized using volcano plots, Venn diagrams, and cluster heatmaps. Differentially expressed metabolites were further subjected to pathway annotation and enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.

Transcriptome Sequencing and Bioinformatic Analysis

Total RNA was extracted from rat lung tissue using the MJZol total RNA extraction kit. RNA concentration and purity were detected using NanoDrop 2000, and RNA integrity was assessed using Agilent 5300. Qualified RNA samples were used to construct mRNA sequencing libraries and subjected to high-throughput sequencing on the NovaSeq X Plus platform. After quality control of raw sequencing data with fastp, reads were aligned to the rat reference genome using HISAT2, and gene expression quantification was performed using RSEM. Differentially expressed genes were screened using DESeq2 with criteria of |log2FC| ≥ 1 and adjusted P ≤ 0.05. Subsequently, GO and KEGG enrichment analyses were performed to evaluate biological functions and signaling pathways related to differentially expressed genes, and GSEA was further used to analyze the trend of major enriched pathways.

Quantitative Real-Time PCR

Total RNA was extracted from rat lung tissues using an Animal Total RNA Isolation Kit (Foregene) and reverse-transcribed using the SweScript RT I First Strand cDNA Synthesis Kit (Servicebio). qRT-PCR was performed using 2× SYBR Green qPCR Master Mix (Servicebio), with three technical replicates for each sample. The amplification conditions were 95°C for 5 min, followed by 40 cycles of 95°C for 10s and 60°C for 30s. Gapdh was used as the internal reference gene, and relative gene expression was calculated using the 2−ΔΔCt method. The mRNA expression levels of Il17a, Cxcl1, Tnf, and Il6 were determined.

Multi-Omics Integrative Analysis

To further explore the relationships among gut microbiota, metabolites, and lung tissue gene expression, Spearman correlation analysis was used to evaluate correlations between differential genera, differential metabolites, and differentially expressed genes. Correlation screening criteria were |r| ≥ 0.7 and P < 0.05, and Cytoscape software was used to construct correlation network diagrams to visualize associations among these multi-omics features.

Statistical Analysis

All data are presented as mean ± standard deviation (SD). Statistical analysis was performed using SPSS 27.0, GraphPad Prism 8.0, and R software. Comparisons between two groups were performed using Student’s t-test, and comparisons among multiple groups were performed using one-way ANOVA; data not following a normal distribution were analyzed using the Kruskal–Wallis test. P < 0.05 was considered statistically significant. Differences in microbial beta diversity were analyzed using ANOSIM or PERMANOVA; screening criteria for differentially expressed metabolites were VIP > 1 and P < 0.05; screening criteria for differentially expressed genes were |log2FC| ≥ 1 and adjusted P ≤ 0.05. GO, KEGG, and metabolic pathway enrichment analyses were performed using Fisher’s exact test. Correlations among microorganisms, metabolites, and genes were analyzed using Spearman analysis, with screening criteria of |r| ≥ 0.7 and P < 0.05.

Results

AKK and Its EVs Alleviate Lung Injury in ARDS Rats

To evaluate the protective effects of AKK and its EVs on LPS-induced lung injury in ARDS rats, we first designed an animal experiment (Figure 1a). It was observed that rats in the ARDS group showed poor mental state and severe tachypnea, while these changes were alleviated in the AKK and EVs groups. The results showed that the body weight of rats in the ARDS group significantly decreased on day 15 of the experiment, whereas the body weight increased in the AKK and EVs intervention groups (Figure 1b), indicating that AKK and its EVs can alleviate weight loss in ARDS model rats. Measurement of the lung wet/dry weight ratio further showed that pulmonary edema was significantly increased in the ARDS group, while the lung wet/dry weight ratio significantly decreased after AKK and EVs treatment, approaching the level of the control group (Figure 1c), suggesting that AKK and its EVs have a beneficial effect on pulmonary edema. H&E staining (Figure 1d) showed that the lung tissue structure in the control group was intact, with thin alveolar septa and clear alveolar spaces; the lung tissue in the ARDS group showed obvious alveolar collapse, septal thickening, and massive infiltration of inflammatory cells; while the lung tissue morphology in the AKK and EVs treatment groups was improved, with partial restoration of alveolar structure, reduced septal thickening, and decreased inflammatory cell infiltration. These results suggest that AKK and its EVs can significantly alleviate lung tissue injury induced by LPS in ARDS rats.

Figure 1.

AKK and its EVs alleviate lung injury in ARDS rats. (a) Schematic diagram of animal experiment grouping and procedure; (b) Body weight changes of rats in each group before and after intervention; (c) Lung wet/dry weight (W/D) ratio; (d) Representative images of lung histopathological changes, stained with H&E (magnification 200×, scale bar = 60 μm). Data are presented as mean ± standard deviation (n = 6). Compared with the ARDS group, ***p < 0.001, **p < 0.01.

AKK and Its EVs Alleviate Pulmonary Inflammation in ARDS Rats

To evaluate the regulatory effects of AKK and its EVs on the pulmonary inflammatory response in ARDS rats, we collected BALF for total cell count, total protein quantification, and inflammatory factor measurement. The results showed that, compared with the control group, the total cell count in BALF was significantly increased in the ARDS group (Figure 2a), along with significantly increased levels of IL-17A and TNF-α (Figure 2c and d), and a significant increase in BALF total protein concentration (Figure 2b), indicating severe inflammatory response and alveolar barrier damage. Compared with the ARDS group, the above indicators were significantly improved in the AKK and EVs groups (Figure 2a-d), manifested as reduced inflammatory cell infiltration, decreased levels of inflammatory factors, and reduced protein exudation, suggesting that AKK and its EVs have significant anti-inflammatory and lung-protective effects.

Figure 2.

AKK and its EVs alleviate pulmonary inflammation in ARDS rats. (a) Total cell count in BALF of rats in each group; (b) Total protein concentration in BALF; (c and d) Levels of IL-17A and TNF-α in BALF; Data are presented as mean ± standard deviation (n = 6). Compared with the ARDS group, *p < 0.05,**p < 0.01, ***p < 0.001.

AKK and Its EVs Improve Gut Microbial Diversity in ARDS Rats

Using 338F-806R primers, 16S rRNA high-throughput sequencing was performed on 24 fecal samples from the control, ARDS, AKK, and EVs groups, and the gut microbiota composition was analyzed at the ASV level. The results showed that the control group obtained a total of 1548 ASVs, with an average of 258 ASVs per sample; the number of ASVs in the ARDS group decreased to 1110, with an average of 185 ASVs per sample, suggesting that ARDS leads to a significant reduction in gut microbiota richness. After AKK intervention, the number of ASVs increased to 1878, with an average of 313 ASVs per sample; the number of ASVs in the EVs group was 1404, with an average of 234 ASVs per sample, both showing significant recovery compared to the ARDS group, with the AKK group showing a more pronounced recovery effect (Figure 3a). The Sobs and Chao indices were further used to evaluate species richness in gut microbiota α-diversity. The results showed that the Sobs and Chao indices in the ARDS group were significantly lower than those in the control group, while they significantly increased after AKK intervention, with statistical significance compared to the ARDS group (P < 0.001); meanwhile, the AKK group also showed a significant increase compared to the EVs group (P < 0.05) (Figure 3b and c). Shannon index analysis showed that the microbial diversity in the ARDS group showed a decreasing trend compared to the control group, while the AKK group showed some recovery, but the differences between groups did not reach statistical significance (P > 0.05) (Figure 3d). This suggests that ARDS mainly affects gut microbiota richness, with a relatively minor impact on evenness. Subsequently, PCoA analysis based on Bray-Curtis distance at the ASV level was performed to evaluate β-diversity. The results showed that samples from the control and ARDS groups were clearly separated, indicating that ARDS leads to significant changes in gut microbiota structure; the sample distribution of the AKK and EVs groups was similar and approached that of the control group, and was clearly distinguished from the ARDS group, indicating that both AKK and its EVs can partially restore the microbial structural disorder caused by ARDS (Figure 3e). Further β-diversity difference analysis showed that the ARDS group was significantly higher than the control group, indicating significant changes in gut microbiota structure due to ARDS; compared with the ARDS group, the distance values in both the AKK and EVs groups decreased, suggesting that both can improve the microbial disorder caused by ARDS (Figure 3f). Collectively, these results indicate that both AKK and its EVs can improve gut microecological imbalance and reshape microbial structure in ARDS rats, with the AKK intervention being more effective than EVs.

Figure 3.

AKK and its EVs improve gut microbial diversity in ARDS rats. (a) α-diversity evaluation indices; (b–d) α-diversity analysis based on ASV level, including Sobs index, Chao index, and Shannon index; (e) PCoA analysis based on Bray-Curtis distance showing β-diversity differences in gut microbiota among groups; (f) β-diversity difference analysis among groups. Data are presented as mean ± standard deviation (n=6); *P < 0.05, **P < 0.01, ***P < 0.001. ASV: Amplicon Sequence Variant; PCoA: Principal Coordinate Analysis.

AKK and Its EVs Improve Gut Microbial Composition Disorder in ARDS Rats

To investigate the regulatory effects of AKK and its EVs on the gut microbiota structure of ARDS rats, 16S rRNA sequencing and microbial community analysis were performed on fecal samples from the control, ARDS, AKK, and EVs groups. Venn diagram results showed that a total of 174 shared ASVs were identified among the four groups, with obvious specific microbial distribution between different groups (Figure 4a). Among them, the AKK group had the highest number of specific ASVs (483), followed by the control group (441) and the EVs group (383), while the ARDS group had a relatively low number of specific ASVs (282), suggesting that ARDS leads to a decrease in gut microbiota richness, while AKK and its EVs intervention can partially restore microbial diversity and specific composition. In the community composition analysis at the ASV level, there were obvious differences in the dominant microbial structure among groups (Figure 4b). The ARDS group was mainly enriched with ASV71, ASV1, ASV6, and ASV25, while the AKK and EVs groups were dominated by ASV3, ASV2, and ASV16, indicating that AKK and its EVs can significantly reshape the ARDS-related gut dominant microbial structure. Phylum-level analysis showed that the gut microbiota of the four groups was mainly composed of Firmicutes, Bacteroidetes, Verrucomicrobia, and Proteobacteria (Figure 4c). Compared with the control group, the relative abundance of Firmicutes in the ARDS group significantly decreased, while Proteobacteria significantly increased, suggesting that ARDS induces gut microecological imbalance and potential pathogen proliferation. After AKK and EVs intervention, the abundance of Firmicutes significantly recovered, while the proportion of Proteobacteria decreased, and the overall microbial structure gradually approached normal. Among them, the EVs group showed a more pronounced effect in restoring Firmicutes abundance and inhibiting the abnormal proliferation of Proteobacteria. Further genus-level analysis showed (Figure 4d) that Bacteroides was significantly enriched in the ARDS group, while norank_f__Muribaculaceae and Lachnospiraceae_NK4A136_group were significantly reduced. In contrast, the relative abundance of Bacteroides in the control, AKK, and EVs groups significantly decreased, while norank_f__Muribaculaceae and Lachnospiraceae_NK4A136_group significantly increased. Additionally, after AKK and EVs intervention, potentially beneficial bacteria such as Ligilactobacillus, unclassified_c__Bacilli, and unclassified_f__Lachnospiraceae also showed varying degrees of enrichment. These bacteria are often associated with short-chain fatty acid production, intestinal mucosal barrier maintenance, immune homeostasis regulation, and anti-inflammatory responses.^27,28 In summary, AKK and AKK-EVs ameliorated ARDS-associated gut microbial dysbiosis, characterized by enrichment of potentially beneficial taxa and reduction of opportunistic pathogens. These changes were accompanied by attenuation of inflammatory responses and lung injury, indicating that modulation of the gut microbiota may be associated with the beneficial effects of AKK and AKK-EVs.

Figure 4.

AKK and its EVs improve gut microbial composition disorder in ARDS rats. (a) Venn diagram showing the shared and specific distribution of ASVs among the control, ARDS, AKK, and EVs groups, with the central area representing shared ASVs among the four groups and the peripheral areas representing the number of specific ASVs in each group; (b) Bar chart of community composition at the ASV level, showing the relative abundance distribution of dominant ASVs in each group; (c) Bar chart of community composition at the phylum level, showing the relative abundance changes of major bacterial phyla in each group; (d) Bar chart of community composition at the genus level, showing the relative abundance changes of dominant gut genera in different groups. n = 6 per group.

AKK and Its EVs Regulate Gut Microbial Phenotypes and Functional Pathways in ARDS Rats

To further investigate the effects of AKK and its EVs on the functional aspects of the gut microbiota in ARDS rats, BugBase was used to predict microbial phenotypes, and PICRUSt2 was used to analyze microbial functional pathways. Analysis of differential microbiota between groups showed (Figure 5a) that opportunistic pathogens such as Bacteroides and Escherichia-Shigella were significantly enriched in the ARDS group, while potentially beneficial bacteria such as norank_f__Muribaculaceae, Lachnospiraceae_NK4A136_group, Lactobacillus, Ruminococcus, and Parabacteroides were significantly decreased; compared with the ARDS group, beneficial bacteria such as norank_f__Muribaculaceae, Ligilactobacillus, Lachnospiraceae_NK4A136_group, and Ruminococcus were significantly increased in the AKK and EVs groups, while Bacteroides and Escherichia-Shigella were significantly decreased. Kruskal–Wallis H-test further confirmed that, compared with the EVs group, norank_f__Muribaculaceae was significantly decreased in the ARDS group, while Bacteroides and Escherichia-Shigella were significantly increased (P < 0.05; Figure 5b, c and e). Compared with the AKK group, the abundance of Lachnospiraceae_NK4A136_group was significantly decreased in the ARDS group (P < 0.05; Figure 5d). Additionally, unclassified_f__Oscillospiraceae was significantly decreased in the ARDS group (P < 0.05; Figure 5f), suggesting that ARDS leads to a reduction in anaerobic beneficial bacteria and disruption of microbial homeostasis. BugBase phenotype prediction results showed that the gut microbiota of each group mainly included phenotypes such as Anaerobic, Gram_Positive, Potentially_Pathogenic, Gram_Negative, and Facultatively_Anaerobic (Figure 5g). Compared with the control group, the relative abundance of Potentially_Pathogenic and Gram_Negative phenotypes increased in the ARDS group, while Anaerobic and Gram_Positive phenotypes decreased, suggesting that ARDS induces gut microbiota imbalance and potential pathogen proliferation. After AKK and EVs intervention, the Anaerobic and Gram_Positive phenotypes significantly recovered, while the Potentially_Pathogenic phenotype decreased, suggesting that AKK and its EVs can improve gut microecological homeostasis. PICRUSt2 functional prediction analysis showed (Figure 5h) that key metabolic pathways such as amino acid biosynthesis, carbon metabolism, glycolysis/gluconeogenesis, and pyruvate metabolism were significantly downregulated in the ARDS group, while these metabolic functions were restored after AKK and EVs intervention. These results indicate that AKK and its EVs can alleviate ARDS-induced gut microecological functional disorder by regulating key genus composition, restoring anaerobic beneficial bacteria, and improving metabolic functional pathways.

Figure 5.

AKK and its EVs regulate gut microbial phenotypes and functional pathways in ARDS rats. (a) Multi-group comparative analysis of differential microbiota at the genus level, showing significantly changed dominant genera among different groups (*p < 0.05, **p < 0.01, ***p < 0.001); (b–f) Kruskal–Wallis H-test analysis of differential microbiota at the genus level, showing the relative abundance differences of norank_f__Muribaculaceae, Bacteroides, Lachnospiraceae_NK4A136_group, Escherichia-Shigella, and unclassified_f__Oscillospiraceae in each group (*p < 0.05, **p < 0.01); (g) BugBase microbial phenotype prediction analysis; (h) Functional prediction heatmap based on PICRUSt2, showing changes in metabolic functional pathways of the gut microbiota in each group. n = 6 per group.

AKK and Its EVs Improve Metabolic Disorder and Regulate Immune-Related Pathways in ARDS Rats

To investigate the effects of AKK and its EVs on ARDS-related metabolic abnormalities, LC–MS non-targeted metabolomics analysis was performed on fecal samples from the control, ARDS, AKK, and EVs groups. In positive ion mode (POS), 1270 metabolites were identified, while in negative ion mode (NEG), 1105 metabolites were identified. PCA analysis showed clear separation of metabolic profiles among groups, with the ARDS group being clearly distinguished from the other groups and showing greater intra-group dispersion, while the overall metabolic characteristics of the AKK and EVs groups were similar and gradually approached the control group (Figure 6a), suggesting that AKK and its EVs can partially correct ARDS-induced metabolic disorder. Differential metabolite analysis showed that, compared with the control group, there were 666 significantly different metabolites in the ARDS group, predominantly downregulated metabolites (Figure 6b). Compared with the ARDS group, there were 711 and 483 differential metabolites in the AKK and EVs groups, respectively, predominantly upregulated metabolites (Figure 6c and d). Further comparison revealed only 72 differential metabolites between the AKK and EVs groups (Figure 6e), suggesting high similarity in metabolic regulation between AKK and its EVs, and their ability to restore ARDS-induced metabolic abnormalities. Venn analysis showed a total of 159 common differential metabolites among groups, along with obvious group-specific metabolic changes (Figure 6f). KEGG pathway enrichment analysis indicated that the differential metabolites were mainly involved in lipid metabolism, amino acid metabolism, and immune system-related pathways. Compared with the control group, the lysine degradation pathway was upregulated in the ARDS group, while lipid metabolism pathways such as arachidonic acid metabolism, linoleic acid metabolism, steroid biosynthesis, and primary bile acid biosynthesis were significantly downregulated (Figure 6g). After AKK and EVs intervention, multiple lipid metabolism-related pathways were restored, while immune-related pathways were significantly enriched, including the B cell receptor signaling pathway, T cell receptor signaling pathway, and natural killer cell-mediated cytotoxicity (Figure 6h and i), suggesting that AKK and its EVs may participate in the improvement of ARDS by regulating immune inflammation and metabolic networks. Metabolite clustering heatmap further showed that the overall metabolic profiles of the AKK and EVs groups were closer to the control group and clearly distinct from the ARDS group (Figure 6j), further indicating that AKK and its EVs can effectively reverse ARDS-induced metabolic disorder and reshape metabolic homeostasis.

Figure 6.

AKK and its EVs improve metabolic disorder and regulate immune-related pathways in ARDS rats. (a) Principal component analysis (PCA) based on LC–MS non-targeted metabolomics data; (b) Volcano plot of differential metabolites between the ARDS group and the control group; (c) Volcano plot of differential metabolites between the AKK group and the ARDS group; (d) Volcano plot of differential metabolites between the EVs group and the ARDS group; (e) Volcano plot of differential metabolites between the EVs group and the AKK group. Red indicates significantly upregulated metabolites, blue indicates significantly downregulated metabolites, and gray indicates metabolites with no significant difference; (f) Venn diagram showing the distribution of common and specific differential metabolites among groups; (g–i) KEGG pathway enrichment analysis of differential metabolites in each group; (j) Clustering heatmap of differential metabolites. n = 6 per group.

AKK and Its EVs Regulate Gene Expression and Signaling Pathways in ARDS Rats

Transcriptome sequencing analysis was performed on lung tissues of rats in the control group, ARDS group, AKK group, and EVs group, with three biological replicates per group, totaling 12 samples. Sequencing results showed that an average of approximately 44,376,004 raw reads were obtained per sample, and after quality control, approximately 44,137,141 high-quality reads were obtained, indicating good sequencing data quality suitable for subsequent analysis. PCA results showed that the samples in each group were clearly separated in the principal component space, suggesting significant differences in the overall transcriptional expression profiles of lung tissues under different treatment conditions (Figure 7a). Among them, the ARDS group was far from the control group, while the AKK group and EVs group clustered toward the control group, with similar distributions between the two groups, suggesting that AKK and its EVs could partially reverse the abnormal transcriptional expression patterns induced by ARDS. Statistical results of differentially expressed genes showed that there were a large number of significantly differentially expressed genes between the ARDS group and the control group, while after intervention with the AKK group and EVs group, many differentially expressed genes were also detected compared with the ARDS group, but the overall change trend tended to return to a normal state, and the number of differentially expressed genes among the control group, AKK group, and EVs group was significantly reduced (Figure 7b). Volcano plot analysis identified 1,240 differentially expressed genes (DEGs) in the control-versus-ARDS comparison, including 440 upregulated and 800 downregulated genes (Figure 7d). In addition, 859 DEGs were identified in the ARDS-versus-AKK comparison, including 527 upregulated and 332 downregulated genes (Figure 7e), while 786 DEGs were identified in the ARDS-versus-EVs comparison, including 462 upregulated and 324 downregulated genes (Figure 7f). Notably, the inflammation-related genes Il17a, Cxcl1, Tnf, and Il6 showed overall increased expression in the ARDS group compared with the control group (Figure 7d–f), whereas their expression showed a decreasing trend in both the AKK and EVs groups compared with the ARDS group, suggesting partial reversal of ARDS-associated inflammatory gene dysregulation following AKK and EVs intervention. Hierarchical clustering heatmap based on differentially expressed genes showed that there were significantly different gene expression patterns between the ARDS group and the control group, while the expression profiles of the AKK group and EVs group were generally closer to the control group (Figure 7c). These results indicate that both AKK and its EVs can significantly improve the ARDS-induced abnormalities in lung tissue transcriptome, and EVs show high similarity to AKK in overall regulatory trends.

Figure 7.

Differential expression analysis of lung tissue transcriptome in each group of rats. (a) PCA analysis shows clear separation of overall gene expression profiles among groups; (b) Statistics of the number of differentially expressed genes in each comparison group, with red indicating upregulated genes and blue indicating downregulated genes; (c) Clustering heatmap of differentially expressed genes, with different colors representing relative expression levels; (d) Volcano plot of differentially expressed genes between the control group and ARDS group; (e) Volcano plot of differentially expressed genes between the ARDS group and AKK group; (f) Volcano plot of differentially expressed genes between the ARDS group and EVs group. Red indicates significantly upregulated genes, blue indicates significantly downregulated genes, and gray indicates genes with no significant difference. n = 3 per group.

GO enrichment analysis results showed that compared with the control group, differentially expressed genes in the ARDS group were mainly enriched in biological processes related to inflammatory response, immune regulation, and cell cycle, including immune response, inflammatory response, response to stimulus, and cell cycle (Figure 8a), suggesting significant inflammation and immune activation during ARDS. KEGG analysis further showed that differentially expressed genes were mainly enriched in inflammation-related pathways such as the IL-17 signaling pathway, TNF signaling pathway, Chemokine signaling pathway, and Cytokine-cytokine receptor interaction (Figure 8b), indicating significant inflammatory response and immune imbalance in ARDS lung tissue. Further analysis found that after intervention with AKK and its EVs, differentially expressed genes were mainly enriched in processes such as immune response, defense response, neutrophil chemotaxis, and response to stress (Figure 8c and e), while KEGG pathways were mainly enriched in the IL-17 signaling pathway, TNF signaling pathway, Chemokine signaling pathway, and Cytokine-cytokine receptor interaction (Figure 8d and f). These results suggest that AKK and its EVs can alleviate ARDS-related lung inflammatory damage by regulating inflammatory response, immune cell chemotaxis, and cytokine signaling pathways. At the same time, the enrichment of the cell cycle pathway suggests that it may also be involved in lung tissue injury repair. Overall, it indicates that AKK and its EVs have significant immunoinflammatory regulation and lung protection effects on ARDS.

Figure 8.

GO and KEGG enrichment analysis of differentially expressed genes in lung tissue transcriptome of each group of rats. (a) GO enrichment analysis of differentially expressed genes (DEGs) between the ARDS group and control group; (b) KEGG pathway enrichment analysis of DEGs between the ARDS group and control group; (c) GO enrichment analysis of DEGs between the AKK group and ARDS group; (d) KEGG pathway enrichment analysis of DEGs between the AKK group and ARDS group; (e) GO enrichment analysis of DEGs between the EVs group and ARDS group; (f) KEGG pathway enrichment analysis of DEGs between the EVs group and ARDS group. n = 3 per group.

GSEA analysis further validated the transcriptome enrichment results. In the comparison between the ARDS group and control group, the IL-17 signaling pathway, TNF signaling pathway, and Cell cycle pathway were all significantly positively enriched (NES > 0, p < 0.05) (Figure 9a–c), suggesting that inflammatory response, immune activation, and cell proliferation-related processes were significantly enhanced during ARDS. Further comparison of the AKK group and EVs group with the ARDS group found that the IL-17 signaling pathway, TNF signaling pathway, and Cell cycle pathway showed a trend of negative enrichment (NES < 0, p < 0.05) (Figure 9d–i), indicating that after intervention with AKK and its EVs, the above inflammatory and cell cycle-related signaling pathways were significantly inhibited. These results suggest that AKK and its EVs may alleviate ARDS-related immunoinflammatory responses by regulating inflammatory signaling pathways such as IL-17 and TNF, as well as cell cycle-related processes, thereby exerting lung protection effects.

Figure 9.

GSEA analysis validates the enrichment of signaling pathways related to differentially expressed genes in lung tissue. (a–c) GSEA enrichment results of the IL-17 signaling pathway, Cell cycle, and TNF signaling pathway in the comparison between the ARDS group and control group; (d–f) GSEA enrichment results of the IL-17 signaling pathway, Cell cycle, and TNF signaling pathway in the comparison between the AKK group and ARDS group; (g–i) GSEA enrichment results of the IL-17 signaling pathway, Cell cycle, and TNF signaling pathway in the comparison between the EVs group and ARDS group. The green curve represents the trend of the enrichment score (ES), the black vertical lines indicate the distribution positions of target genes in the sorted gene set, and the gray area represents the correlation scores of the sorted genes. n = 3 per group.

AKK and Its EVs Reduced the Expression of IL-17/TNF-Related Inflammatory Genes in Lung Tissue

To validate the inflammation-related transcriptional changes identified by RNA sequencing, the expression of selected genes was examined by qRT-PCR. Compared with the control group, the ARDS group exhibited significantly increased pulmonary mRNA expression of Il17a, Cxcl1, Tnf, and Il6 (Figure 10a–d). Both AKK and AKK-EVs interventions significantly reduced the expression of these genes (all P < 0.001). These findings were consistent with the RNA-sequencing results and further supported the attenuation of IL-17/TNF-related inflammatory activity following AKK or AKK-EVs intervention.

Figure 10.

AKK and its EVs reduced the expression of IL-17/TNF-related inflammatory genes in lung tissue. The relative mRNA expression levels of (a) Il17a, (b) Cxcl1, (c) Tnf, and (d) Il6 in lung tissue were determined by qRT-PCR. Data are presented as the mean ± SD (n = 3 per group). ***P < 0.001.

Comprehensive Analysis of the Microbiome and Metabolome in ARDS Rats

To further reveal the interaction between the gut microbiome and metabolome during ARDS, a comprehensive correlation analysis of the two omics data was performed. Procrustes analysis results showed that the microbiome and metabolome had high consistency in overall structure (M² = 0.419, p = 0), suggesting a significant synergistic change relationship between the two omics (Figure 11a). O2PLS analysis further showed that the control group, ARDS group, AKK group, and EVs group were clearly separated in the latent variable space, with the most significant difference between the ARDS group and control group, while the AKK group and EVs group overall approached the control group (Figure 11b and c), indicating that intervention with AKK and its EVs could partially restore ARDS-related microecological and metabolic abnormalities.

Figure 11.

Comprehensive correlation analysis of the gut microbiome and metabolome. (a) Procrustes analysis shows high consistency between the microbiome and metabolome; (b and c) O2PLS analysis shows the distribution of samples from each group in the latent variable space and the contribution of microbiome and metabolome variables to the joint model; (d) Spearman correlation heatmap shows the correlation between key flora and differential metabolites; (e) Flora-metabolite network analysis shows positive correlations (red lines) and negative correlations (green lines) between differential flora and metabolites. n = 6 per group.

Further correlation analysis was performed between differential flora and differential metabolites at the genus level. Spearman correlation heatmap showed a wide range of correlations between gut microbiota changes and metabolite alterations during ARDS (Figure 11d). Among them, beneficial bacteria such as Akkermansia, Roseburia, and Lachnospiraceae_NK4A136_group were significantly positively correlated with metabolites such as fatty acids, bile acids, and amino acids, while pathogenic bacteria such as Escherichia-Shigella were negatively correlated with various metabolites, suggesting that gut microbiota imbalance is closely related to metabolic disorders.

Flora-metabolite network analysis further showed that flora such as Akkermansia, Ruminococcus, Parabacteroides, Ligilactobacillus, and Lachnospiraceae_NK4A136_group were located in the core region of the network and formed extensive associations with various metabolites (Figure 11e). Among them, most associations were positive correlations, mainly involving bile acid, lipid, and amino acid metabolism-related pathways, suggesting that these core flora may participate in the occurrence and development of ARDS by regulating the host metabolic network.

Overall results indicate that AKK and its EVs can improve ARDS-related immunoinflammatory responses and metabolic disorders by remodeling gut microbiota structure and regulating key metabolic pathways, thereby exerting lung protection effects.

Comprehensive Analysis of Transcriptome and Metabolome in ARDS Rats

To further reveal the potential molecular mechanisms by which AKK and its EVs alleviate ARDS, this study performed an integrated analysis of lung tissue transcriptome and fecal metabolome data from ARDS rats. Procrustes analysis results showed high consistency between the transcriptome and metabolome (M² = 0.376, p = 0.002), suggesting a significant correlation and synergistic change trend between the two omics data (Figure 12a). O2PLS analysis further showed clear clustering and significant separation between groups, with the ARDS group clearly separated from the control group, indicating that ARDS induced significant transcriptome and metabolome abnormalities; while the AKK group and EVs group gradually approached the control group in overall distribution, indicating that AKK and its EVs could partially reverse ARDS-related molecular abnormalities and have a certain protective effect on ARDS (Figure 12b).

Figure 12.

Comprehensive analysis of transcriptomics and metabolomics in ARDS rats. (a) Procrustes analysis shows high consistency between transcriptomics and metabolomics datasets; (b) O2PLS analysis shows clear separation between samples from each group; (c and d) Correlation heatmaps of differential genes and metabolites for the AKK-versus-ARDS and EVs-versus-ARDS comparisons; (e and f) KEGG joint enrichment analyses of differential genes and metabolites for the AKK-versus-ARDS and EVs-versus-ARDS comparisons. n = 3 per group.

Correlation heatmap analysis results showed that both the AKK group and EVs group significantly altered the association patterns between ARDS-related genes and metabolites (Figure 12c and d). Among them, most inflammation and immune-related genes, such as S100a8, S100a9, Lcn2, Saa1, and Cxcl1, were significantly negatively correlated with some lipid metabolites, while positively correlated with other metabolites, suggesting that AKK and its EVs may further affect immune-inflammatory gene expression by regulating lipid metabolism and inflammation-related metabolic pathways, thereby improving ARDS-related molecular disorders.

KEGG joint enrichment analysis results showed that differential genes and differential metabolites in the AKK group and EVs group were mainly enriched in inflammation, immune, and lipid metabolism-related pathways (Figure 12e and f). Among them, transcriptomics was significantly enriched in inflammatory immune pathways such as the IL-17 signaling pathway, TNF signaling pathway, Cytokine-cytokine receptor interaction, and Chemokine signaling pathway; metabolomics was mainly enriched in lipid metabolism-related pathways such as Arachidonic acid metabolism, Linoleic acid metabolism, Primary bile acid biosynthesis, and Sphingolipid metabolism. Notably, the enrichment degree of the EVs group in inflammatory pathways such as the IL-17 signaling pathway and Cytokine-cytokine receptor interaction was more pronounced, suggesting that AKK-EVs may play a stronger role in regulating immunoinflammatory responses. These results indicate that AKK and its EVs may jointly improve ARDS-related pathological damage by synergistically regulating immunoinflammatory responses and lipid metabolism reprogramming.

Integrated Multi-Omics Analyses Revealed Coordinated Microbial, Metabolic, and Pulmonary Inflammatory Changes Following AKK or AKK-EVs Intervention

Collectively, post-modeling administration of AKK or AKK-EVs partially remodeled the gut microbial community and altered fecal metabolic profiles, particularly pathways related to lipid, amino acid, and bile acid metabolism (Figure 13). Lung transcriptomic analysis revealed differential enrichment of the IL-17, TNF, chemokine, and cytokine–cytokine receptor interaction pathways. Consistent with these findings, qRT-PCR showed reduced pulmonary expression of Il17a, Cxcl1, Tnf, and Il6 following AKK or AKK-EVs intervention. BALF IL-17A and TNF-α levels were also decreased. These coordinated changes were accompanied by attenuation of body-weight loss, pulmonary edema, inflammatory cell infiltration, and histopathological lung injury. Overall, the findings support an association between AKK or AKK-EVs intervention and reduced IL-17/TNF-related pulmonary inflammation, although causal mediation among the microbial, metabolic, and pulmonary changes remains to be established.

Figure 13.

Proposed effects of AKK and AKK-EVs on IL-17/TNF-related inflammation in LPS-induced ARDS.

Discussion

In recent years, the involvement of the gut microbiota in the development and resolution of ARDS has attracted increasing attention. Akkermansia muciniphila (AKK), regarded as a next-generation probiotic candidate with immunomodulatory potential, has shown protective effects in various inflammatory disease models.²⁹ Previous studies reported that AKK and its extracellular vesicles (EVs) attenuated liver fibrosis-associated injury in parallel with changes in gut microbial composition, intestinal barrier function, and inflammatory responses.²² AKK-derived outer membrane vesicles have also demonstrated anti-inflammatory and barrier-protective effects in experimental models of colitis and mastitis.^19,30 However, direct comparisons between live AKK and AKK-EVs in ARDS remain limited. The present study therefore compared their effects in an LPS-induced rat model of ARDS. Both interventions attenuated lung histopathological injury, pulmonary edema, and inflammatory responses, consistent with the protective effects of AKK and its derivatives reported in other inflammatory models.

Against this background, the present study found that ARDS was associated with marked disruption of the gut microbial community, characterized primarily by reduced microbial richness and diversity. This finding is consistent with the dysbiosis previously reported in patients with sepsis-associated ARDS and in experimental ARDS models.^31,32 Administration of AKK or AKK-EVs was associated with partial restoration of α-diversity, shifts in β-diversity patterns, and changes in microbial composition. Following the interventions, potentially beneficial taxa associated with short-chain fatty acid (SCFA) production, including norank_f__Muribaculaceae and Lachnospiraceae_NK4A136_group, were enriched, whereas opportunistic taxa such as Bacteroides and Escherichia–Shigella were reduced. SCFAs, particularly propionate, have been reported to modulate immune responses and attenuate pulmonary inflammation.^11,32 These microbial changes may therefore contribute to the restoration of gut microbial homeostasis and may be relevant to the observed improvement in ARDS-associated lung inflammation.^33,34 However, they do not provide direct evidence of causal regulation through the gut–lung axis. Previous studies have associated reduced Akkermansia abundance with more severe pulmonary inflammation and poorer clinical outcomes.³⁵ Despite oral administration of live AKK, the endpoint fecal relative abundance of the genus Akkermansia was not significantly higher in the AKK group than in the ARDS group, and the sample-level values are provided in Supplementary Table S1. The ASV-level taxonomic annotations and raw read counts underlying the 16S rRNA sequencing analysis are provided in Supplementary Table S2. Thus, the present data do not demonstrate persistent fecal enrichment or stable intestinal engraftment of the administered AKK. The observed protective effects may instead be associated with transient exposure to AKK, broader community-level microbiota remodeling, microbial metabolites, or host immune responses. Increases in taxa such as norank_f__Muribaculaceae and Lachnospiraceae_NK4A136_group may contribute to host immune homeostasis through SCFA-related functions, although this possibility requires validation through targeted metabolite quantification and functional experiments.

Furthermore, through untargeted metabolomics analysis, this study found that the fecal metabolic profile of ARDS rats was significantly disrupted, while the metabolic profile gradually approached that of the normal control group after AKK and EVs intervention. This suggests that both can improve ARDS-related metabolic imbalance to a certain extent, consistent with previous research results showing that microbial intervention improves disease-related metabolic disorders.³⁶ Pathway analysis revealed that AKK and its EVs primarily affect lipid metabolism, bile acid metabolism, and immune-related pathways. Among these, the arachidonic acid metabolism and linoleic acid metabolism pathways, which were inhibited under ARDS conditions, were restored after intervention. Arachidonic acid and its derived lipid mediators, such as prostaglandins and leukotrienes, play important roles in both the initiation and resolution of lung inflammation.³⁷ Therefore, the restoration of these pathways may reflect improvements in lipid metabolic homeostasis and inflammatory regulation capacity. Meanwhile, the restoration of linoleic acid metabolism also suggests that AKK and its EVs may participate in the alleviation of inflammatory responses in ARDS by regulating lipid nutrition and immunometabolic status.³⁸ Additionally, AKK and its EVs can partially restore the primary bile acid biosynthesis pathway. Bile acids are not only involved in lipid metabolism but also possess immunomodulatory effects. Previous studies have shown that changes in the bile acid profile are closely related to ARDS inflammatory damage, and primary bile acids such as cholic acid may exert lung-protective effects by inhibiting macrophage inflammatory activation and pyroptosis.³³ This study also found that immune-related pathways such as the B cell receptor signaling pathway, T cell receptor signaling pathway, and natural killer cell-mediated cytotoxicity were significantly enriched in the EVs group, suggesting that AKK-EVs may participate in the regulation of gut immune homeostasis. Previous studies have also shown that bacteria-derived EVs can exert anti-inflammatory effects by regulating macrophage polarization and inhibiting inflammatory signaling pathways such as NF-κB and STAT3;^39,40 EVs derived from Lactobacillus plantarum have also been confirmed to alleviate ARDS lung injury and inflammation by inhibiting macrophage ferroptosis.⁴¹ In summary, AKK and AKK-EVs were associated with coordinated changes in lipid, bile acid, and immune-related metabolic pathways, which may contribute to an improved gut metabolic and immune environment and the attenuation of ARDS-related pulmonary inflammation.

Lung transcriptomic analysis showed that the differentially expressed genes in ARDS rats were predominantly enriched in inflammation- and immune-related pathways, including IL-17 signaling, TNF signaling, chemokine signaling, and cytokine–cytokine receptor interactions.⁴² These pathways are consistent with key pathological features of ARDS, including inflammatory-cell infiltration, excessive release of pro-inflammatory mediators, and disruption of the alveolar–capillary barrier. IL-17, produced mainly by Th17 cells and certain innate immune cells, promotes chemokine expression and neutrophil recruitment, thereby contributing to inflammatory lung injury.^43,44 TNF signaling similarly promotes inflammatory mediator release, increases pulmonary vascular permeability, and contributes to pulmonary edema and tissue damage through downstream pathways such as NF-κB and MAPK.⁴⁵ Chemokine signaling further facilitates the recruitment of neutrophils and macrophages to the lungs, thereby amplifying pulmonary inflammation. Following AKK or AKK-EVs intervention, the ARDS-associated gene-expression profile shifted toward a less inflammatory pattern, with reduced expression of genes involved in IL-17, TNF, and chemokine signaling. GSEA further showed significant negative enrichment of IL-17- and TNF-related pathways after both interventions.⁴⁶ Consistent with these transcriptomic findings, qRT-PCR demonstrated increased expression of Il17a, Cxcl1, Tnf, and Il6 in the ARDS group, whereas their expression was reduced following AKK or AKK-EVs treatment. These molecular changes were concordant with the observed reductions in lung histopathological injury, BALF inflammatory-cell infiltration, and IL-17A and TNF-α levels. Previous studies have similarly shown that inhibition of IL-17-related signaling reduces neutrophil recruitment and lung injury,⁴⁷ while blockade of TNF signaling or its receptors ameliorates experimental lung injury.⁴⁸ Collectively, the transcriptomic, GSEA, and qRT-PCR results indicate that the protective effects of AKK and AKK-EVs were associated with attenuation of IL-17/TNF-related inflammatory activity and chemokine-mediated inflammatory-cell recruitment. However, these findings do not establish functional dependence on these pathways, which requires further validation using pathway-specific inhibition or rescue experiments.

Compared with previous studies focusing on individual bacterial taxa or metabolites, the present study integrated microbiome, metabolome, and lung transcriptome data to characterize coordinated microbial, metabolic, and pulmonary inflammatory changes following AKK or AKK-EVs intervention. This multi-omics approach provides complementary evidence for understanding the potential involvement of gut microbial and metabolic alterations in ARDS. Previous studies have associated gut dysbiosis with systemic inflammation and lung injury during ARDS. In patients with sepsis-associated ARDS, potentially beneficial bacteria such as Akkermansia, Ligilactobacillus, and Ruminococcus were reduced, whereas opportunistic pathogens such as Klebsiella were increased.³¹ Mendelian randomization analysis further suggested a potential protective association between the genus Akkermansia and 28-day mortality in severe pneumonia, while Akkermansia abundance was negatively correlated with lactate levels and ICU length of stay in patients with septic ARDS.³⁵ Experimental studies have linked AKK and related microbiota-targeted interventions to changes in SCFAs, bile acids, and inflammatory signaling. For example, AKK-associated propionate attenuated neuroinflammation and ARDS-related behavioral abnormalities through modulation of TLR4/NF-κB signaling.³² EGCG treatment increased AKK abundance and SCFA production and reduced LPS-induced pulmonary inflammation through JAK2/STAT3-related signaling.¹¹ In addition, outer membrane vesicles derived from Parabacteroides goldsteinii attenuated acute lung injury in association with increased AKK abundance, elevated systemic cholic acid levels, and reduced NF-κB-mediated macrophage pyroptosis.³³ Consistent with these studies, our multi-omics findings identified coordinated changes in microbial composition, metabolic profiles, and pulmonary IL-17-, TNF-, and chemokine-related inflammatory activity following AKK or AKK-EVs intervention. These findings are compatible with a putative network involving microbiota remodeling, metabolic regulation, and attenuation of pulmonary inflammation. However, because the multi-omics analyses were primarily correlative and intestinal barrier function and causal mediators were not directly assessed, the present results should be regarded as hypothesis-generating evidence rather than confirmation of a causal gut–lung axis mechanism.

Several limitations should be acknowledged. First, stable intestinal engraftment of the orally administered AKK was not established because endpoint 16S rRNA sequencing showed no significant fecal enrichment of Akkermansia, and longitudinal or strain-specific quantification was not performed. Second, lung transcriptomic sequencing and transcriptome–metabolome integration included only three animals per group, limiting statistical power; therefore, these findings should be considered exploratory. Third, because AKK and AKK-EVs were administered for seven days following LPS challenge, the observed effects primarily reflect post-modeling or recovery-phase modulation rather than acute rescue therapy for ARDS. Fourth, the multi-omics analyses were mainly correlative, and intestinal barrier function and causal mediators were not directly assessed; thus, a causal gut–lung axis mechanism cannot be confirmed. Finally, the active components of AKK-EVs and candidate metabolites require further functional and targeted validation, and their optimal dose, safety, and administration route remain to be investigated.

Conclusion

In conclusion, post-modeling administration of live AKK or AKK-EVs attenuated lung injury, pulmonary edema, and inflammatory responses in rats with LPS-induced ARDS. These effects were accompanied by changes in the gut microbial composition and fecal metabolic profile, together with reduced pulmonary IL-17/TNF-related inflammatory activity, supporting potential microbiota–metabolite–lung inflammatory crosstalk. Although stable AKK engraftment and causal mediation through the gut–lung axis remain to be established, our findings highlight the potential of AKK-EVs as a cell-free strategy for recovery-phase modulation of experimental ARDS. Further studies are needed to identify the active components of AKK-EVs, validate the causal mechanisms, and evaluate their optimal dose, safety, therapeutic timing, and translational efficacy.

Funding Statement

This study was supported by the Research Start-up Fund Project for Doctoral Students at Liuzhou People’s Hospital (No. LRYGCC-ZD202507), the University Sponsored Research Program of Southwest Medical University (No. 2025LCYXZX39), and the Internal Scientific Research Project of Liuzhou People’s Hospital (Contract No. lry202409). The funding sources had no role in the study design, data collection and analysis, interpretation of the results, manuscript preparation, or the decision to submit the manuscript for publication.

Animal Welfare Statement

All animal experiments in this study followed national and institutional guidelines for the management and humane treatment of laboratory animals and complied with the relevant requirements of the National Institutes of Health Guide for the Care and Use of Laboratory Animals. The study was designed, conducted, and reported in accordance with the ARRIVE 2.0 guidelines. All efforts were made to minimize animal pain and distress and to reduce the number of animals used.

Abbreviations

AKK, Akkermansia muciniphila; EVs, Extracellular vesicles; ALI, acute lung injury; ARDS, Acute respiratory distress syndrome; LPS, lipopolysaccharide; OD, optical density; BALF, bronchoalveolar lavage fluid; PCoA, Principal Coordinates Analysis; SCFAs, short-chain fatty acids; ASVs, amplicon sequence variants; AKK-EVs, extracellular vesicles derived from Akkermansia muciniphila; PCA, principal component analysis; DEGs, Differentially expressed genes; GO, Gene Ontology; GSEA, Gene set enrichment analysis; POS, positive ion mode; NEG, negative ion mode; EGCG, epigallocatechin-3-gallate; KEGG, Kyoto Encyclopedia of Genes and Genomes.

Data Sharing Statement

The original data supporting the conclusions of this study are available from the corresponding author upon reasonable request. The authors confirm that the data used in this study are authentic and accurate, and all relevant analyses were performed in accordance with the established experimental design and statistical standards to ensure the reliability, transparency, and reproducibility of the research findings.

Ethics Approval

The animal experiment protocol involved in this study was reviewed and approved by the Animal Experiment Ethics Committee of Liuzhou People’s Hospital, with ethics approval number LRYIACU2025022. All animal experiments were strictly conducted in accordance with the experimental protocol approved by the Ethics committee.

Author Contributions

Longxiong Liao: Conceptualization, Methodology, Investigation, Data curation, Formal analysis, Visualization, Writing—original draft, and Writing—review and editing. Biying Dong: Investigation, Data curation, Formal analysis, and Writing—review and editing. Weitong Zeng: Investigation, Data curation, Validation, and Writing—review and editing. Bing Zhong: Investigation, Resources, Data curation, Formal analysis, and Writing—review and editing. Yumei Zhang: Investigation, Data curation, Formal analysis, and Writing—review and editing. Guiji Liu: Investigation, Data curation, Formal analysis, and Writing—review and editing. Dongwei Zhang: Supervision, Methodology, and Writing—review and editing. Xianming Fan: Conceptualization, Supervision, Project administration, Resources, Methodology, and Writing—review and editing.

All authors made a significant contribution to the work reported, whether in the conception, study design, execution, acquisition of data, analysis and interpretation, or in any of these areas; took part in drafting, revising, or critically reviewing the article; gave final approval of the version to be published; agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors declare that there are no potential conflicts of interest that could be perceived as influencing the study design, data analysis, result interpretation, or manuscript writing in relation to this study, its authorship, or the publication process.