Bifidobacterium bifidum-derived nanoparticles attenuate alcoholic liver disease via enhanced hepatic phagocytosis and gastrointestinal homeostasis

Zelin Gu; Shuhan Meng; Boqing Yao; Boya Gao; Siye Chen; Fazheng Ren; Pinglan Li; Tuo Shao; Nan Shang

doi:10.1038/s41467-026-72211-3

. 2026 Apr 30;17:5905. doi: 10.1038/s41467-026-72211-3

Bifidobacterium bifidum-derived nanoparticles attenuate alcoholic liver disease via enhanced hepatic phagocytosis and gastrointestinal homeostasis

Zelin Gu ^1,^2,³, Shuhan Meng ⁴, Boqing Yao ¹, Boya Gao ¹, Siye Chen ⁵, Fazheng Ren ³, Pinglan Li ^1,^✉, Tuo Shao ^5,^✉, Nan Shang ^2,^3,^✉

PMCID: PMC13338232 PMID: 42062274

Abstract

Alcohol-associated liver disease (ALD) has limited therapeutic options due to its complex pathogenesis. This study demonstrates the ALD-protective effects of extracellular nanoparticles derived from Bifidobacterium bifidum (BNPs), focusing on the concept of gut microbiota-derived nanoparticles (GNPs) in disease pathogenesis. When isolated BNPs were administered in an ALD mouse model, they upregulated Vsig4 receptor expression in liver macrophages, improving phagocytic clearance of harmful GNPs that contained bacterial DNA. GNPs activated liver inflammation via the cGAS-STING pathway, exacerbating ALD and liver fibrosis in Vsig4-deficient mice. BNP treatment suppressed the inflammatory cascade, modulated macrophage polarization, and reduced hepatic steatosis and liver injury, while also restoring the balance of the gut microbiota and enhancing intestinal barrier function. These findings reveal the role of GNPs in ALD pathogenesis and present targeted microbial nanoparticle postbiotics as potential therapeutics for treatment of alcohol-associated and other liver diseases.

Subject terms: Hepatitis, Alcoholic liver disease, Experimental models of disease, Nutritional supplements

Here, the authors show that extracellular nanoparticles derived from Bifidobacterium bifidum (BNPs) have a protective effect in alcohol associated liver disease (ALD) through immunomodulatory effects, while restoring the gut microbiota balance.

Introduction

Alcohol-associated liver disease (ALD) is a major cause of morbidity and premature mortality worldwide, contributing significantly to the global burden of liver disease¹. ALD encompasses a spectrum of conditions ranging from simple steatosis to steatohepatitis, liver fibrosis, and, ultimately, cirrhosis, which affects 15–40% of ALD patients². Abstinence remains the most effective treatment for ALD; however, the disease may continue to progress in severely affected patients despite their abstaining from alcohol, with limited effective treatment options being available^3,4. There is an urgent need for more effective therapeutic strategies for ALD.

The bacterial ecosystem within the human intestinal tract involves a complex and dynamic mutualistic relationship between gut microbiota and host^5–7. Extracellular nanoparticles (NPs) produced by commensal, probiotic, and pathogenic bacteria are crucial in the modulation of intestinal microbial symbiosis and host health⁸. These bacterial NPs are predominantly spherical in shape, range from 20 to 400 nm in diameter, and can encapsulate a diverse array of genetic materials (DNA, RNA, and non-coding RNA) as well as proteins, peptidoglycan, membrane components (lipopolysaccharides [LPS], lipoteichoic acid [LTA]), and metabolites⁹. Recent research indicates that microbiota-derived NPs function as natural signal effectors, facilitating communication within the microbial community and between microbiota and host cells by transferring their cargo between tissues^9–11.

Alcohol consumption causes gut dysbiosis^12–14, which contributes to the development and progression of ALD^15–18. Gut dysbiosis induces dysfunction in the intestinal barrier, which facilitates the translocation of bacterial components and bacterial NPs from the gastrointestinal tract to the liver^19,20. Pathogenic Escherichia coli (E. coli) and cytolysin-positive Enterococcus faecalis (E. faecalis) have been shown to induce severe alcoholic hepatitis and increase the risk of mortality^17,21–23. However, the role of disturbed intestinal flora-derived extracellular NPs in the progression of ALD requires further investigation.

The translocation of bacteria and bacterial NPs from a compromised gut barrier into the circulatory or lymphatic systems allows their entry into the liver through the portal vein. Kupffer cells (KCs)—the largest population of macrophages in the liver—play a crucial role in removing blood-borne pathogens and serve as an essential “second firewall” to impede further dissemination²⁴. Hepatic KCs that express the complement receptor of the immunoglobulin superfamily (V-set and immunoglobulin domain-containing 4, known as Vsig4 or CRIg) are a subset of innate immune cells that are vital for phagocytosis of circulating pathogens^25,26. These cells are highly effective at clearing microbiota and microbial NPs from the portal vein that drains the intestine, relying on complement component C3-mediated opsonization^27–29. However, the role of Vsig4+ KCs in preventing the development of alcohol-associated liver inflammation and hepatic steatosis via the clearance of microbial NPs remains unknown.

Several studies have observed that probiotics can be effective in treating ALD; however, stability and viability are essential prerequisites for their beneficial effects^7,30–32. Not all gut environments are conducive to colonization by probiotics. Probiotic-generated NPs (a type of postbiotic) offer a promising approach to the treatment of ALD. Previous investigations have demonstrated that postbiotic NPs can positively affect intestinal flora homeostasis and exhibit health-promoting properties, including enhanced epithelial barrier function, modulation of brain health and metabolic functions, and regulation of local and systemic immune responses^8,9,33. Recent studies have provided evidence that exosome-like NPs from Lactobacillus rhamnosus GG protect against alcohol-associated liver injury by modulating gut microbiota and intestinal mucosal permeability^34,35. However, the bioactivities and underlying mechanisms related to the beneficial effects of postbiotic NPs in ALD are not fully clear.

The present study investigates how bacterial NPs promote the progression of ALD in experimental ALD model mice treated with Bifidobacterium bifidum-derived NPs (BNPs) and if Vsig4 is involved. Our findings demonstrate that BNPs enhance the clearance of gut microbiota-derived nanoparticles (GNPs) by liver macrophages through the upregulation of Vsig4 expression in the liver. This mechanism also reduces the hepatic immune response associated with the accumulation of bacterial DNA contained within the GNPs. BNPs also regulate the community structure of intestinal flora, thereby reducing the production of bacterial NPs and enhancing intestinal barrier function to limit their passage into the circulatory systems. Our findings suggest that Vsig4 has a crucial role in mediating the protective effects of BNPs against alcoholic liver injury.

Results

Characterization and tracking of BNPs in circulation

BNPs were isolated from bacterial culture supernatant and purified (OD₆₀₀ = 1.8) via serial centrifugation and characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM), and a nanoparticle tracking analysis (NTA) system. SEM of the surface of B. bifidum revealed distinct round protrusions, identified as BNPs (Fig. 1a, left). TEM showed these to be encapsulated within a spherical membrane (Fig. 1a, middle). NTA demonstrated that BNP diameter ranged from 60.3 to 140.5 nm (mean 103.8 nm; Fig. 1a, right). Label-free proteomic analysis was employed to characterize and quantify proteins in the BNPs. A total of 854 proteins were identified, 828 being cytoplasmic and 26 extracellular (Fig. 1b). SDS-PAGE revealed the most abundant protein bands were at 10, 50, and 70 kDa, likely corresponding to bacteriocin, p75, and p40, which have previously been identified as signature proteins produced by Lactobacillus^36,37. All identified proteins were annotated using five major databases (Fig. S1a). Gene Ontology (GO) analysis showed that BNPs were associated with various biological phenomena, including multiple metabolic and cellular processes, molecular functions, and cellular components (Fig. S1b and Supplementary Data 1). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that BNPs had crucial roles in signaling pathways associated with Metabolism, Genetic Information Processing, Environmental Information Processing, Cellular Processes, and Human Diseases (Fig. S1c). Detailed KEGG pathway information is provided in Fig. S1d and Supplementary Data 2.

Fig. 1 — a Scanning electron micrograph (left) and transmission electron micrograph (middle) of BNPs, and size distribution of BNPs determined by nanoparticle tracking analysis (right). b Characterization of protein in BNPs using label-free proteomics. c In vivo imaging of BNP biodistribution in male C57BL/6 mice administered DiR-labeled BNPs (2 × 10⁹ NPs/mouse in 200 μL PBS) by gavage and monitored over 48 h. d Confocal immunostaining of PKH67-labeled BNPs in mouse ileum, mesenteric adipose tissue (MAT), and liver at 24 h. Yellow arrows indicate PKH67-positive green staining of BNPs. Scale bar, 100 µm. e Immunofluorescence co-localization of F4/80 hepatic macrophages (stained red) with PKH67-labeled BNPs. Scale bar, 100 µm (top) and 50 µm (bottom). f Immunofluorescence images of PKH67-labeled BNP uptake by primary hepatic macrophages. 4’,6-diamidino-2-phenylindole (DAPI) is used for nuclear counterstaining (blue). Scale bar, 50 µm. All experiments were repeated independently at least three times with similar results. n = 3 (f), 5 (**c–e**) independent biological samples. Statistical comparisons were performed using one-way ANOVA with Tukey’s test (c) or two-sided unpaired Student’s t-test (e). Data are mean ± SEM. Source data were provided as a Source data file.

The in vivo tissue biodistribution of BNPs was determined following oral administration of DiR-labelled BNPs to mice. BNPs were detected in the gastrointestinal tract (GI tract), liver, mesenteric adipose tissue (MAT), and, to a lesser extent, the spleen. DiR fluorescence was observed most strongly in MAT (maximum intensity 12 h post-administration) and liver (maximum intensity after 24 h). Notably, no fluorescence was detected in the lungs, heart, or kidneys (Fig. 1c). The presence of PKH67-labelled BNPs in tissues was confirmed through confocal immunostaining. BNPs were observed in MAT, liver, and the intestinal villi and lamina propria of the ileum (Fig. 1d), with little being detected in the stomach tissue (Fig. S2). We then examined the immunofluorescent co-localization of PKH67-labelled BNPs and F4/80+ macrophages in liver tissue. Most of the BNPs were co-localized with the F4/80+ macrophages, and co-localization with F4/80- hepatocytes was infrequent (Fig. 1e). To validate this finding, an in vitro uptake assay was conducted and demonstrated uptake of BNPs by primary hepatic macrophages (Fig. 1f). These findings suggest that macrophages are the primary targets of BNPs in the liver following oral administration.

BNPs alleviate alcohol-induced liver injury by modulating hepatic macrophage polarization

Probiotic-derived NPs have been shown to enhance the immune response, improving intestinal barrier function and alleviating liver disease^33,34. To determine if BNP treatment can ameliorate ALD, we employed the Gao-binge model in mice, also known as the National Institute on Alcohol Abuse and Alcoholism (NIAAA) binge-on-chronic alcohol exposure model. Mice were fed the Lieber DeCarli diet containing 5% ethanol (v/v) for 10 d, followed by a bolus of ethanol administered via gavage on the final day, 9 h prior to sacrifice. BNPs were administered orally at a dose of 2 × 10⁹ NP/mouse once daily for the final seven days (Fig. 2a). Prior to this trial, it was demonstrated that administration of BNPs did not affect food intake or body weight in the model (Fig. S3). Analyses of serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activities, liver triglyceride (TG) concentrations, and liver/body weight ratio indicated that BNP supplementation significantly alleviated ALD in mice (Fig. 2b–e). Analysis of liver tissue pathology revealed that BNPs substantially reduced liver steatosis, as evidenced by Hematoxylin and Eosin (H&E) and Oil red O staining (Fig. 2f–g).

Fig. 2 — a Design of NIAAA alcohol exposure mouse model. b Serum alanine aminotransferase (ALT) and c serum aspartate aminotransferase (AST) activity levels in mouse model groups. d Hepatic triglyceride concentrations in mouse model groups. Liver-to-body weight ratio in mouse model groups as an indicator of liver health (e). Photomicrographs of hematoxylin and eosin (f) and Oil red O-stained (g) liver tissue sections. Scale bar, 100 µm. h Schematic of the experimental scRNA-seq process. C57BL/6J mice received a pair-fed or alcohol-fed diet in the NIAAA model before livers were isolated for genomic analysis. i Uniform manifold approximation and projection (UMAP) plot of non-parenchymal mouse hepatocytes analyzed using droplet-based 10× Genomics single-cell RNA sequencing. j Clustering of 11 cell types within the combined UMAP plot based on differential marker gene expression. k Cell types in the non-parenchymal mouse hepatocytes UMAP plot differentiated by NIAAA model group. l Proportion of non-parenchymal cell types in each NIAAA model group. m Histogram of the proportion of CD68+ macrophages in the murine hepatic non-parenchymal cells (NPC). n UMAP plots of selected marker genes associated with M1 and M2 macrophages. Intensity of gene expression is indicated by color saturation. o Proportions of pro-inflammatory M1 macrophages and anti-inflammatory M2 macrophages in NIAAA model groups as a percentage of the murine hepatic non-parenchymal cells. p Relative proportions of Kupffer cells and monocyte-derived macrophages in the macrophage subcluster in each NIAAA model group. All experiments were repeated independently at least three times with similar results. n = 3 (**i–p**), 5-7 (**b–d**), 5-10 (e) independent biological samples. Statistical comparisons were performed using one-way ANOVA with Tukey’s test (**b-e, m, o**). Data are mean ± SEM. Source data were provided as a Source data file.

To elucidate the effects of BNPs on liver immune cell heterogeneity and changes during ALD pathogenesis, droplet-based 10× Genomics Chromium single-cell RNA sequencing (scRNA-seq) was performed on hepatic non-parenchymal cells isolated from mice in the pair-fed (PF), alcohol-fed (AF), and alcohol-fed plus BNPs (AF+BNPs) model groups (Fig. 2h). A total of 97,212 single-cell transcriptomes were obtained from nine mice (31,822 from the PF group, 32,608 from AF, and 32,782 from AF+BNPs) (Fig. S4a). These clustered into 34 populations based on differential expression of hallmark genes visualized using a uniform manifold approximation and projection (UMAP) plot (Figs. 2i and S4b). UMAP visualization of the combined PF, AF, and AF+BNPs data revealed 11 major clusters corresponding to B cells, cholangiocytes, dendritic cells (DCs), endothelial cells, fibroblast, hepatocytes, macrophages, monocytes, natural killer (NK) cells, neutrophils, and T cells, based on marker gene expression (Fig. 2j).

All 11 clusters contained cells derived from the livers of PF, AF, and AF+BNPs mice. The AF diet was associated with dramatic changes in hepatic endothelial cells, macrophages, monocytes, neutrophils, and fibroblasts. Notably, the populations in clusters 4, 11, 15, 23, and 32 exhibited significant changes in the AF and AF+BNPs livers (Fig. 2k–l). Macrophages comprised over 30% of cells in the CD68⁺ macrophage cluster in AF mice (Fig. 2m), while there were fewer in clusters 11, and more in clusters 4, 15, 23, and 32 (Fig. 2i, l, m). Further assessment of marker expression revealed that clusters 11 expressed Cd68, Cd163, Timd4, and Marco markers (associated with M2 macrophages), whereas clusters 4, 15, 23 and 32 expressed Cd68, Cd14, and Trem2 (associated with M1 macrophages) (Fig. 2n). This indicates that alcohol exposure alters the polarization of macrophages, causing an increase in pro-inflammatory M1 macrophages and a reduction in anti-inflammatory M2 macrophages (Fig. 2o). Cluster 8, 26, and 29 expressing S100a8 and S100a9, was also elevated in the AF group (Fig. S4c). Notably, treatment with BNPs restored the balance of macrophage composition, reducing M1 cells and neutrophils and increasing M2 cells.

Subcluster UMAP visualization of the combined macrophage clusters revealed two major subclusters corresponding to KCs (subclusters 2, 3, 4, and 6) and monocyte-derived macrophages (MDMs) (subclusters 0, 1, 5, 7, and 8) (Fig. S4d). KCs were distinguished by high expression of Clec4f, Timd4, and Cd163, while MDMs were characterized by high expression of Ly6c2, Trem2, S100a4, and Cd14. The AF diet induced fewer liver-resident KCs but recruited a large number of MDMs—an effect that was suppressed by BNP supplementation (Fig. 2p). Previous studies have demonstrated that ALD patients exhibit reduced expression of KC marker genes and upregulated expression of MDM marker genes²⁶. Additionally, we examined the immunofluorescent co-localization of IBA1 and CLEC4F staining in liver tissue. The results shown that alcohol exposure significantly decreased the number of IBA1+ CLEF4F+ Kupffer cells and induced an increase in IBA1 + CLEC4F- MDMs in the liver, while BNPs treatment reversed this (Fig. S5a). Our findings indicate that BNPs inhibit alcohol-induced inflammation through modulation of macrophage polarization and protection of the hepatic KCs.

BNPs increase macrophage phagocytosis by induction of Vsig4 expression via increased complement components

A prominent feature of the KCs subcluster is its marked enrichment during BNP supplementation. GO enrichment analysis was conducted to investigate how BNPs affect the functional properties of KCs. This revealed significant regulation of factors involved in the positive regulation of phagocytosis, defense responses to pathogenic bacterial infection, immunoglobulin-mediated immune responses, and the negative regulation of inflammatory responses in the AF+BNPs group (Fig. 3a). The fundamental role of KCs (phagocytosis of pathogens) is closely related to the KC and hepatic immune responses. Notably, the expression of the Vsig4 gene in KCs was considerably elevated following BNP treatment (Fig. 3b). We then examined the expression of complement component receptor genes and complement component genes. Alcohol exposure dramatically reduced expression of Vsig4, C1qa, C1qb, and C1qc genes, while increasing expression of C3ar1 and C3. Notably, treatment with BNP markedly enhanced expression of Vsig4, C1qa, C1qb, C1qc, and C3 (Fig. 3c). Another cohort of mice (three PF, three AF, three AF+BNPs) was profiled by flow cytometry to confirm changes in the hepatic Vsig4+ KC population (Fig. 3d) and gating strategy was provided in Supplementary Information (Figure. S17). This corroborated the scRNA-seq findings, revealing a decrease in the proportion of Vsig4+ macrophages in AF livers and a reversal in AF+BNPs livers. Immunofluorescence staining and qPCR also demonstrated that BNPs upregulated Vsig4 protein expression (Fig. 3e) and mRNA levels in liver (Fig. 3f), consistent with the scRNA-seq findings. In vitro studies also demonstrated that expression of Vsig4 mRNA in primary hepatic macrophages (PHM) and bone marrow-derived macrophages (BMDM) increased in line with escalating doses of BNPs (Fig. S6a, b). Intriguingly, previous study demonstrated that non-stimulatory synthesized particles enhanced the phagocytic ability of specialized immune cells³⁸. However, our results have shown that electroporation treatment significantly decreased BNPs-induced Vsig4 protein and mRNA expression in primary hepatic macrophages, indicating that the contents of BNPs were essential for the Vsig4 expression (Fig. S6c, d).

Potential mechanisms by which BNPs could regulate Vsig4 expression in hepatic KCs were then investigated. PHM were isolated and co-cultured with PKH67-labelled BNPs. This showed that BNPs co-localized with Vsig4 and that BNPs enhanced Vsig4 expression (Fig. 3g). Notably, BNP treatment increased the expression of mRNA of complement components C1qa and C1qb. Lipopolysaccharide (LPS) treatment decreased C3 expression, but this was restored by BNP treatment (Fig. 3h). Previous studies confirm that C3-mediated opsonization is crucial to the phagocytic capabilities of Vsig4+ macrophages^29,39.

We then demonstrated that BNPs elevated C3 protein levels considerably in PHM and BMDM supernatants (Fig. 3i). Moreover, when BMDMs were cultured with a cell culture supernatant containing C3, Western blot analysis showed that Vsig4 protein expression increased (Fig. 3j), indicating that BNPs regulate Vsig4 through C3. Taken together, these findings suggest that BNPs enhance C3 expression by modulating complement components C1qa and C1qb, which influence Vsig4 expression and the functional characteristics of macrophages.

BNPs inhibit translocation of GNPs into the circulation and liver in ALD mice

Alcohol-induced intestinal permeability facilitates the translocation of substantial quantities of bacterial components into the bloodstream. Given their nanoscale dimensions, GNPs are readily translocated into the circulation. We further investigated whether alcohol consumption led to accumulation of microbial DNA in the liver using 16S rRNA probes. Microbial DNA was rarely detected in PF or PF+BNPs livers but was highly enriched in AF livers (Fig. 4a). However, BNP supplementation enhanced the phagocytic capability of macrophages through induction of Vsig4 expression. qPCR also showed that ethanol led to a greater abundance of microbial DNA in the liver, but this was reduced by BNP treatment (Fig. 4b). To determine if 16S rRNA is translocated into the circulation via GNPs, we assessed the abundance of 16S rRNA in plasma NPs. The highest amount of bacterial DNA was detected in plasma NPs in the AF group (Fig. 4c), while bacterial DNA was markedly reduced following NP depletion (Fig. 4d). More bacterial DNA was consistently observed in the plasma NPs of human patients with alcoholic hepatitis than in healthy controls (Fig. 4e). Importantly, a deficiency of Vsig4 increased accumulation of microbial 16S rRNA in the liver and the recruitment of a greater number of F4/80+ macrophages compared to wild-type (WT) mice (Fig. 4f). These results suggest that alcohol suppresses Vsig4 expression, thereby facilitating the translocation of bacterial DNA-containing NPs from the gut to the liver.

Fig. 4 — a Immunofluorescence staining of microbial 16S rRNA (green) and Vsig4 (red) in mouse liver tissue in the NIAAA model groups. Scale bar, 100 µm. b qPCR analysis of the abundance of microbial 16S rRNA in mouse liver. c qPCR analysis of the abundance of microbial 16S rRNA within mouse plasma NPs. d qPCR comparison of abundance of microbial 16S rRNA in plasma, NPs, and NP-depleted plasma fraction of ALD-model mice. e qPCR comparison of microbial 16S rRNA abundance in plasma NPs from human patients with alcohol-induced hepatitis and healthy controls. f Immunofluorescence staining of 16S rRNA (green) and F4/80+ hepatic macrophages (red) in liver of Vsig4^flox/flox (wild-type) and Vsig4^-/- mice in the NIAAA model. Scale bar, 100 µm. g Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of differentially expressed genes (DEGs) in monocyte-derived macrophage (MDM) subclusters, showing upregulation due to the AF diet. Enrichment p values were assessed using a one-sided Fisher’s exact test with Benjamini–Hochberg FDR correction (adjusted p < 0.05 were considered significant). h Heatmaps of expression of selected genes crucial in the nucleotide sensing pathway. i Western blot analysis of cGAS, STING, phosphorylated STING (p-STING), NFκB, phosphorylated NFκB (p-NFκB), and GAPDH in mice liver. j Bubble plot illustrating the expression of selected genes for pro-inflammatory cytokines, chemokines, and their receptors in MDM subclusters. Color saturation indicates the average intensity of gene expression, while bubble size reflects the percentage of each cell cluster expressing the respective gene. **k-n** Concentrations of inflammatory cytokines and chemokines Tnf-α, IL-1β, Cxcl1, and Cxcl2 in liver tissue. Samples for Western blot were derived from the same experiment, and gels/blots were processed in parallel. All experiments were repeated independently at least three times with similar results. n = 3 (g, h, j), 5 (a–d, f, i, k–n) independent biological samples, and 6 healthy controls and 10 alcoholic hepatitis patients (e). Statistical comparisons were performed using one-way ANOVA with Tukey’s test (b–d, f, k–n) or two-sided unpaired Student’s t-test (e). Data are mean ± SEM. Source data were provided as a Source data file.

We then investigated if accumulation of 16S rRNA in the liver was responsible for the recruitment of large numbers of MDMs. We performed KEGG pathway enrichment analysis of the differentially expressed genes (DEGs) in MDM subclusters. Notably, the AF diet significantly upregulated pathways involved in NFκB signaling and TNF signaling related to environmental information processing, as well as pathways associated with cytosolic DNA sensing, chemokine signaling, Toll-like receptor signaling, and other inflammatory signaling pathways relevant to organismal systems (Fig. 4g). We also assessed the expression of DNA sensor genes within the cytosolic DNA sensing and NOD-like receptor signaling pathways (Fig. 4h). The cGAS-STING pathway acts as a primary effector in sensing abnormal double-stranded DNA in the cytoplasm⁴⁰. Alcohol induced the expression of cGAS and STING1, while expression of oligoadenylate synthases 2 and 3 was unaffected. Western blot analysis confirmed that concentrations of cGAS, phosphorylated STING (p-STING), and phosphorylated NFκB (p-NFκB) proteins were markedly increased in the AF group but decreased following BNP treatment (Fig. 4i). BNPs also prevented the alcohol-induced expression of pro-inflammatory cytokine and chemokine genes in the liver (Fig. 4j). Hepatic cytokine (Fig. 4k–l) and chemokine (Fig. 4m–n) protein levels corroborated the scRNA-seq findings. These results indicate that the enrichment of alcohol-induced bacterial DNA-containing GNPs in the liver can activate cGAS-STING signaling, leading to the recruitment, proliferation, and activation of hepatic immune cells.

Extracellular nanoparticles containing gut microbe DNA play an important role in progression of ALD

Dysbiosis of the intestinal flora accelerates progression of alcohol-associated liver diseases via the gut–liver axis^41,42. To determine if BNP treatment influences composition of gut microbes in ALD mice, 16S rRNA sequencing was performed on genomic DNA extracted from colon contents. One-way ANOVA revealed that alcohol decreased alpha diversity (Shannon index), but this increased under BNP supplementation (Fig. S7a). However, no significant differences were observed in the Simpson and Chao indices (Fig. S7b, c). Principal coordinate analysis (PCoA) revealed distinct clustering of the microbiota in the PF, PF+BNPs, AF, and AF+BNPs groups (Fig. S7d). Microbial dysbiosis and gut microbiome health indices also indicated that alcohol consumption triggered bacterial imbalance, which was subsequently mitigated by BNP treatment (Fig. S7e, f). BNP treatment of the AF group increased the abundance of several beneficial bacteria, including Akkermansia, Faecalibaculum, Lactobacillus, and Bifidobacterium, while reducing the abundance of pathogenic species such as Enterococcus and Escherichia-Shigella (Fig. S7g, h). Notably, the pathogenic bacterium Enterococcus faecalis has been observed in patients suffering from alcoholic hepatitis (AH)¹⁷, and Escherichia fergusonii is enriched in feces of patients with non-alcoholic fatty liver disease⁴³. These findings suggest that BNP treatment of AF mice leads to improvements in both the richness and diversity of the gut microbiota. BNPs reversed alcohol-induced gut microbe imbalances by upregulating beneficial bacteria and reducing the abundance of opportunistic pathogens.

To investigate further if the development of ALD is associated with bacteria-derived NPs under gut microbiota dysbiosis, we isolated GNPs from fresh feces from PF (PFGNPs), AF (AFGNPs), and AF + BNP (AF-BGNPs) mice using centrifugation. GNP sizes were characterized using TEM and the NTA system (Figs. S8a and 5a). Average sizes of the PFGNPs, AFGNPs, and AF-BGNPs did not differ significantly (Fig. S8b), however, the number of NPs per gram of feces was significantly elevated in the AF group, but felled following BNP treatment (Figs. 5b and S8c). Notably, AFGNPs were the most highly enriched in bacterial DNA (Figs. 5c and S8d), and LPS and LTA concentrations were also elevated (Fig. 5d, e). We also examined human gut microbiota-derived NPs (hGNPs) in feces from patients with AH. The abundance of NPs was higher in AH patients than healthy controls (HC) (Fig. 5f), while ALT and AST activities exhibited similar positive correlations with the number of hGNPs (Fig. S9a, b). Notably, the abundance of bacterial DNA was markedly elevated in AH patients (Fig. 5g), and LPS and LTA were also higher than the healthy controls (Fig. 5h, i). These results indicate that alcohol consumption induces gut microbiota dysbiosis, resulting in the generation of more GNPs that harbor bacterial DNA from the overgrowth of pathogenic bacteria.

Fig. 5 — a Size distribution of GNPs in feces from mice in NIAAA model groups determined by nanoparticle tracking analysis. b Concentration of GNPs in feces from mice in model groups. c Changes in microbial DNA in fecal GNPs in mouse model groups. Concentrations of d, e lipopolysaccharides (LPS) and lipoteichoic acid (LTA) in fecal GNPs in mouse model groups. f Quantification of GNPs (hGNPs) in feces from humans with alcoholic hepatitis (AH) and healthy controls (HC). g-i Changes in microbial DNA within hGNPs from AH and healthy controls. Concentrations of LPS and LTA in hGNPs from AH and healthy controls. j Immunofluorescence staining (green) of microbial DNA (16S rRNA) in primary hepatic macrophages treated with GNPs. k, l Relative expression of mRNA of *Tnf-α* and *Il-1β* in primary hepatic macrophages in mouse model groups. m Design of mouse treatment protocol to examine the role of GNPs in alcohol-induced liver steatosis, including administration of ABx, a non-absorbable combination of antibiotics. n Photomicrographs of H&E and Oil red O-stained liver sections from AF mice administered ABx antibiotics and AFGNPs. o–q Hepatic triglyceride (TG) concentrations, serum ALT and AST activity in AF mice administered ABx and AFGNPs. r Immunofluorescence staining (green) of microbial 16S rRNA in liver of AF mice administered ABx and AFGNPs. s, t Changes in abundance of bacterial DNA (16S rRNA) in intestinal mucosa NPs and liver of AF mice administered ABx and AFGNPs. u–x Changes in expression of mRNA of *Tnf-α* and *Il-1β* cytokines and *Cxcl1* and *Cxcl2* chemokines in liver of AF mice administered ABx and AFGNPs. All experiments were repeated independently at least three times with similar results. Scale bar, 50 µm (j), 100 µm (n, r). n = 3 (k, l, s, t), 5 (c, e, o–q), 5–6 (u–x), 6 (b, d) independent biological samples, and 6 healthy controls and 10 alcoholic hepatitis patients (**f-i**). Statistical comparisons were performed using one-way ANOVA with Tukey’s test (**b–e, k**, l, o–q, s–x) or two-sided unpaired Student’s t-test (f–i). Data are mean ± SEM. Source data were provided as a Source data file.

To elucidate the impact of mouse GNPs on the liver inflammatory response, we performed an in vitro study of GNPs in primary KCs. An abundance of 16S rRNA was observed in the AFGNPs group, with only a minimal amount evident in the PFGNPs and AF-BGNPs groups (Fig. 5j). This consistently higher uptake of bacterial DNA by KCs (Fig. S10a) coincided with an increase in inflammation, as evidenced by elevated mRNA expression of the pro-inflammatory cytokines Tnf-α and Il-1β (Fig. 5k, l). Crucially, we subsequently used Sparstolonin B (a selective antagonist of TLR2 and TLR4) to inhibit these toll-like receptor proteins. Blocking TLR2 and TLR4 did not affect the expression of Tnf-α and Il-1β induced by AFGNPs (Fig. S11a, b). Our findings suggest that the bacterial DNA contained in AFGNPs is the primary driver of this inflammatory response.

To examine further the role of GNPs in alcohol-induced liver steatosis, a non-absorbable combination of the antibiotics polymyxin B and neomycin (ABx) was administered to mice one week prior to establishment of the NIAAA model and maintained throughout the experiment. GNPs were administered orally at 2 × 10⁹ NP per mouse once daily for the final seven days (Fig. 5m). ABx treatment resulted in decreased hepatic fat accumulation (demonstrated by H&E and Oil red O staining), but this markedly increased under AFGNP supplementation (Fig. 5n). Histological observations of hepatic steatosis were corroborated by changes in hepatic TG concentrations (Fig. 5o). Serum ALT and AST were also reduced by ABx and increased by AFGNP administration (Fig. 5p, q). Moreover, bacterial DNA in liver (Fig. 5r, s) and intestinal mucosal NPs (Fig. 5t) was considerably reduced following ABx treatment, but this reduction was wiped out in the ABx+AFGNPs group, which also displayed elevated expression of mRNA of inflammatory cytokines (Fig. 5u, v) and chemokines (Fig. 5w, x).

We then evaluated if AFGNPs exacerbate alcohol-induced liver injury. AFGNPs and PFGNPs were administered orally at 2 × 10⁹ NP/mouse once daily for 7 days in the ALD model (Fig. S12a). AFGNPs accelerated hepatic steatosis (Fig. S12b, c) and elevated ALT and AST levels compared to PFGNP treatment (Fig. S12d, e). By contrast, PFGNPs did not have a significant effect on liver damage. Hepatic inflammation was more pronounced in mice treated with AFGNPs than with PFGNPs (Fig. S12f–i), and was associated with induction of cGAS, p-STING, and p-NFκB expression (Fig. S12j). Collectively, these results suggest that AFGNPs facilitate the progression of ALD, with the microbial DNA being the crucial component that triggers hepatic inflammatory responses in KCs through activation of the cGAS-STING pathway.

BNPs mitigate ALD by inhibiting microbial DNA-containing nanoparticles that induce intestinal barrier dysfunction and inflammation

Alcohol alters microbiota composition and compromises intestinal integrity and barrier function^2,42. The phenomenon of GNPs transporting microbial DNA into the circulation and onward to the liver suggests that GNPs also influence intestinal barrier function. To confirm this, we used Caco-2 cells in trans-well inserts to form a polarized monolayer that mimicked the intestinal epithelium. Barrier function was assessed by measuring the permeability of the monolayer to FITC-dextran (4 kDa) by quantifying fluorescence in the basolateral chamber (Fig. 6a). GNPs derived from AF mice induced greater monolayer permeability than those from PF mice; however, treatment with BNPs reversed the effects of AFGNPs (Fig. 6b). We then examined the expression of tight junction (TJ) proteins in Caco-2 cells using immunofluorescence staining. BNP supplementation increased the expression of occludin and claudin-1, reversing the decrease in abundance of these TJ proteins induced by AFGNPs (Fig. 6c). Intriguingly, culturing of intestinal organoids demonstrated that organoid size increased significantly following BNP treatment but was reduced by AFGNPs (Fig. S13).

Fig. 6 — a Schematic of in vitro permeability experiment using a Caco-2 cells monolayer to mimic the intestinal epithelium. b Quantification of fluorescence in Caco-2 monolayer permeability experiment showing protective effect of BNPs. c Immunofluorescence showing expression of tight junction (TJ) proteins occludin and claudin-1 in Caco-2 cells. d Western blot analysis of cGAS, STING, p-STING, and β-actin protein levels in Caco-2 cells exposed to AFGNPs before and after DNA depletion. e Effect of DNA depletion of AFGNPs on mRNA expression of pro-inflammatory cytokines *IL-1β* and *IL-6* by Caco-2 cells. f Light micrographs of H&E-stained sections of mouse colon. g Immunofluorescence staining showing expression of the TJ proteins occludin and claudin-1 in mouse colon sections. h 16S rRNA microbial DNA analysis of mouse colon tissue sections from the model groups. **i–k** Relative expression of cytokine *TNF-α*, *IL-1β*, and *IL-6* mRNA, respectively, in mouse colon samples. l Changes in 16S rRNA microbial DNA content of mouse intestinal mucosa NPs. m qPCR analysis of relative *Vsig4* mRNA expression in mouse colon. n Immunofluorescence of microbial 16S rRNA (green) and PKH26-labeled AFGNPs (red) in colon tissues of Vsig4^flox/flox and Vsig4^−/− mice with ALD. o Relative mRNA expression of *TNF-α* and *IL-1β* cytokines and *Cxcl1* and *Cxcl2* chemokines in colon tissues of Vsig4^flox/flox and Vsig4^−/− mice with ALD. Samples for Western blot were derived from the same experiment, and gels/blots were processed in parallel. All experiments were repeated independently at least three times with similar results. Scale bar, 20 µm (c), 100 µm (g, h, n). n = 5 (c–h, n), 6 (b), 5–7 (**i–k**, l, m, o) independent biological samples. Statistical comparisons were performed using one-way ANOVA with Tukey’s test (b, e, **i–m**) or two-sided unpaired Student’s t-test (o). Data are mean ± SEM. Source data were provided as a Source data file.

To investigate further the effects of bacterial DNA on intestine epithelial cells, we generated microbial DNA-depleted AFGNPs using electroporation followed by incubation with DNase (Fig. S10b). Western blotting revealed that cGAS and p-STING protein levels were markedly elevated in the AFGNPs group but decreased following microbial DNA depletion (Fig. 6d). Depletion also prevented the AFGNPs-induced elevated expression of the pro-inflammatory cytokines Il-1β and Il-6 (Fig. 6e).

Having confirmed the versatility and efficacy of BNPs in mitigating the effects of DNA containing-GNPs via modulation of gut microbiota and liver immune response in ALD mice, we next focused on the capacity of BNPs to mediate the reversal of alcohol-induced disruption of intestine homeostasis. H&E staining revealed that alcohol induced leukocyte infiltration and crypt swelling, and destruction in the colon of mice with ALD. These impacts were markedly reduced by BNP treatment (Fig. 6f). We investigated further the expression of occludin and claudin-1 in mouse colon sections through immunofluorescent staining. BNPs significantly improved the expression of these TJ proteins, which had fallen due to alcohol consumption (Fig. 6g). We also performed 16S rRNA probe analysis to assess the concentration of bacterial DNA in colon sections of AF mice (Fig. 6h). Intestines of these ALD-affected mice exhibited higher concentrations of bacterial DNA than the PF controls, along with increased inflammation that was reduced following BNP treatment (Fig. 6i–k). Moreover, there was considerably more 16S rRNA inside the intestinal mucosa-derived NPs in the AF group than in the PF group, and this elevation was abolished by BNP supplementation (Fig. 6l).

We then explored the role of Vsig4 in the protection of intestinal barrier function in ALD mice. The expression of Vsig4 mRNA in the colon fell significantly after alcohol exposure but increased markedly with BNP treatment (Fig. 6m). To investigate the correlation between this decrease in Vsig4 and the increase in bacterial DNA, we orally administered PKH26-labeled AFGNPs to WT and Vsig4^−/− mice with ALD. Absence of Vsig4 led to increased infiltration of AFGNPs into the intestinal tissue (Fig. 6n), which is consistent with the observed elevated concentrations of microbial 16S rRNA. Also, the Vsig4 knockout (KO) mice expressed more pro-inflammatory cytokines and chemokines in the colon than the WT mice (Fig. 6o). Taken together, these findings demonstrate that BNPs restore intestinal permeability and TJ protein expression while reducing inflammatory responses in ALD mice. Vsig4 also has a crucial role in maintaining intestinal integrity, with its absence leading to increased infiltration of gut microbial NPs and heightened pro-inflammatory cytokine expression induced by microbial DNA.

Vsig4 deficiency abolishes the protective effects of BNPs against alcohol-induced liver injury following AFGNP supplementation

Whole-body knockout of Vsig4 was used to investigate if the beneficial effects of BNPs in liver pathology are diminished in Vsig4-deficient mice. Vsig4^−/− and Vsig4^flox/flox mice were fed a Lieber-DeCarli liquid diet in the ALD model, with BNPs being administered daily on the last seven days (Fig. 7a). Vsig4 deficiency did not influence liver fat accumulation in the PF group (Fig. S14a). However, Vsig4^−/− mice exhibited greater mucosal injury and inflammatory cell infiltration, and the protective effects of BNPs were diminished in the absence of Vsig4 (Fig. S14b, c). Notably, the beneficial effects of BNP treatment on alcohol-induced hepatic steatosis and liver injury were also abolished in the Vsig4^−/− mice, whereas these effects remained in the Vsig4^flox/flox controls (Fig. 7b–d). Vsig4 deficiency resulted in more severe steatosis and liver damage. Importantly, we showed that alcohol consumption induces hepatic steatosis in WT mice without causing liver fibrosis in the model. However, alcohol consumption exacerbated liver fibrosis in Vsig4^−/− mice, as evidenced by Sirius red staining (Fig. 7b, e). Moreover, alcohol exposure markedly increased the expression of profibrotic genes, including collagen a1(I) (Col1a1), Col3a1, transforming growth factor b1 (Tgfb1), and smooth muscle α-actin (Acta2), in liver of Vsig4^−/− mice compared to Vsig4^flox/flox mice (Fig. 7f–i).

Fig. 7 — a Schematic of mouse Vsig4 knockout experiment design. b Light micrographs of H&E (top), Oil red O (middle), and Sirius red (bottom) staining of liver sections of AF mice with Vsig4 knockout and BNP treatment. c Activities of ALT and AST in mouse serum. d Triglyceride (TG) concentrations in mouse liver. e Quantification of Sirius red staining in mouse liver sections. Relative expression of profibrotic mRNA of (f) collagen type I alpha 1 (*Col1a1*), (g) collagen type III alpha 1 (*Col3a1*), (h) transforming growth factor beta (*TGF-β*), and (i) actin alpha 2 (*Acta2*) in liver of wild-type and Vsig4 knockout mice in the presence and absence of BNPs. j Schematic of experiment design for role of AFGNPs in liver injury. k Light micrographs of H&E (top), Oil red O (middle), and Sirius red (bottom) staining of liver sections of AF mice with Vsig4 knockout and AFGNP/BNP treatment. l Activities of ALT and AST in mouse serum. m TG concentrations in mouse liver. n Quantification of Sirius red staining in mouse liver sections. Relative expression of mRNA of (o) *Col1a1*, (p) *Col3a1*, (q) *TGF-β*, and (r) *Acta2* in liver of AFGNP-treated wild-type and Vsig4 knockout mice in the presence and absence of BNPs. s Changes in microbial 16S rRNA content of AFGNP-treated AF mice liver. t Immunofluorescence staining of microbial 16S rRNA and PKH26-labeled BNPs in liver of AFGNP-treated AF Vsig4^flox/flox and Vsig4^−/− mice in NIAAA model. u Flow cytometry analysis of CD11b+ F4/80+ hepatic macrophage populations in AF mice. v Flow cytometry analysis showing effect of AFGNP treatment on Ly6c+ CD11b+ F4/80− hepatic macrophage populations in AF mice. w Relative expression of pro-inflammatory cytokine and chemokine mRNA in AF mouse liver, showing effects of Vsig4 knockout and AFGNP treatment. All experiments were repeated independently at least three times with similar results. n = 5 (**u–w**), 6–7 (**b–i**, **k–t**) independent biological samples. Statistical comparisons were performed using one-way ANOVA with Tukey’s test (u–w) or two-way ANOVA with Sidak’s test (**c–i**, **l–s**). Data are mean ± SEM. Source data were provided as a Source data file.

We then examined further the role of AFGNPs in the progression of liver injury. BNPs were administered to Vsig4^flox/flox and Vsig4^−/− mice at the start of the NIAAA model, followed by AFGNPs 3 d later (Fig. 7j). Vsig4^−/− mice exhibited greater hepatic steatosis and liver damage following AFGNP treatment than WT mice (Fig. 7k–m). Notably, BNPs did not mitigate fatty liver and hepatic fibrogenesis in Vsig4^−/− mice, but they did in Vsig4^flox/flox mice (Fig. 7k, n–r). This supports the idea that Vsig4 deficiency led to a loss of BNP-mediated protection via the clearance of bacterial DNA from AFGNPs, as evidenced by the increased abundance of microbial DNA in liver tissue (Fig. 7s). Immunofluorescence staining also demonstrated that Vsig4 deficiency was associated with a greater infiltration of PKH26-labeled AFGNPs into the liver, which was consistent with higher concentrations of microbial 16S rRNA (Fig. 7t). These findings suggest that the preventive effects of BNPs against ALD are partially dependent upon Vsig4.

To investigate further the inflammatory response induced by AFGNPs, we examined the hepatic macrophage population in Vsig4^−/− and Vsig4^flox/flox mice using flow cytometry, and gating strategy was provided in Supplementary Information (Fig. S18). An increased proportion of CD11b+ F4/80+ macrophages was observed in the liver of Vsig4^−/− mice compared to Vsig4^flox/flox mice (Fig. 7u). AFGNP treatment further elevated the proportion of liver macrophage in the Vsig4^−/− group, with a particular increase in Ly6c+ CD11b+ macrophage (Fig. 7v). Compared with Vsig4^flox/flox mice, Vsig4^−/− mice exhibited a significantly higher proportion of IBA1+ CLEC4F− MDMs. Moreover, AFGNP treatment further increased the proportion of MDMs while concurrently reducing the resident Kupffer cells in the liver (Fig. S5b).

Vsig4 deficiency also influenced hepatic macrophage polarization, shifting activation toward a pro-inflammatory M1-like state in the liver (Fig. S15). There was also a significant increase in expression of pro-inflammatory cytokine and chemokine mRNA under Vsig4 deficiency, with the administration of AFGNPs resulting in even greater inflammation (Fig. 7w). Collectively, these findings suggest that a deficiency of Vsig4 results in enhanced transport of AFGNPs containing bacterial DNA into the liver and the recruitment of a substantial number of MDM that contribute to liver inflammation.

Discussion

Probiotics are used in the management of ALD to restore gut microbiota balance and reduce liver injury^31,32,44. However, the interactions between gut microbes and host cells are complex and not fully understood. Recent research indicates that GNPs have a significant role in mediating interactions among microbiota and between microbiota and host cells. While several studies demonstrate an association between probiotic-derived NPs and liver diseases (via modulation of host intestinal function), the effects of Bifidobacterium bifidum-derived NPs (BNPs) on gut microbiota and the mechanisms behind their anti-ALD properties require further investigation. This study yields insight into the mechanisms of BNP protection against alcohol-induced liver injury, highlighting the intricate relationship between gut microbiota, intestinal barrier function, and liver health. This protection is mediated primarily via (i) modulation of intestinal barrier function, and (ii) enhancement of liver macrophage (Kupffer cell) phagocytic capabilities (Fig. 8). Importantly, we observed that BNPs suppressed the accumulation of microbial DNA in the liver—a crucial factor in the progression of ALD.

Fig. 8 — BNPs derived from *Bifidobacterium bifidum* can restore alcohol-induced imbalanced gut microbiota by selectively inhibiting the proliferation of harmful bacteria, improve intestinal permeability by up-regulating the expression of tight junctions, and suppress translocation of microbial DNA-containing GNPs into the circulation and liver; BNPs can also enhance resident Kupffer cell phagocytic capabilities through the upregulation of Vsig4 expression and alleviate microbial DNA-containing GNPs-induced liver inflammation. Created in BioRender (Gu, Z. (2026) https://BioRender.com/f35d077).

Alcohol consumption induces gut dysbiosis, which imbalances the gut microbiota, potentially favoring the growth of harmful bacteria over beneficial ones². BNPs modulate gut dysbiosis by promoting the restoration of beneficial gut microbes such as Akkermansia, Faecalibaculum, Lactobacillus, and Bifidobacterium, and reducing pathogenic bacteria such as Enterococcus and Escherichia-Shigella. In vitro single-strain cultures also demonstrated that BNPs inhibit the growth of Enterococcus faecalis and E. coli, which are the dominant pathogenic bacteria in the feces of mice with ALD (Fig. S16). These effects may be attributable to antimicrobial components enriched in BNPs. However, further investigation is needed to elucidate the mechanisms by which such components exert their effects on particular microbial species.

NPs secreted by the microbiota can encapsulate a broad range of cargo, including genetic elements (e.g., microRNA, small RNA, and DNA), proteins, lipids, and metabolites that can have significant effects on disease development^8,9. Alcohol consumption increases intestinal permeability, facilitating movement of bacterial components across the gut barrier⁴². Elevated levels of bacterial DNA have been observed in the circulatory systems and hepatic tissues of mice exposed to alcohol and in individuals diagnosed with severe AH^45,46. While the intestinal lumen and outer mucus layer are the primary habitats for most gut bacteria, the exact processes by which microbial DNA enters intestinal tissues and moves beyond the lumen remain open to debate. The current study reveals that most of the microbial DNA was concentrated within mucosal NPs in ALD mice and in circulating NPs in both ALD mice and AH patients, indicating that microbial DNA is transported via GNPs. Additional research is needed to examine potential differences in DNA delivery mechanisms among different microorganisms. Previous studies have suggested a connection between certain gut microorganisms and impaired intestinal barrier function^33,47. Our research demonstrates that AFGNPs compromise the intestinal mucosa by reducing the production of TJ proteins, which facilitates movement of bacterial NPs into intestinal tissues and the bloodstream. AFGNPs also elevate the inflammatory factors TNF-a, IL-1b, IL-6, Cxcl1, and Cxcl2, which are crucial to the recruitment, proliferation, and activation of intestinal and hepatic immune cells. Treatment with BNPs restores the balance of the gut microbiota and reduces generation of microbial DNA-containing GNPs. Notably, a recent study demonstrated that the odd-chain fatty acid pentadecanoic acid protects against intestinal inflammation and barrier dysfunction in ulcerative colitis through inhibition of the NF-κB pathway and induction of TJ protein expression⁴⁸. The enhancement of intestinal barrier function by BNPs is particularly noteworthy, as this limits the translocation of microbial NPs into the intestine and systemic circulation. This effect may be attributable to several tryptophan derivatives and fatty acids within the BNPs^48,49, but further study is needed to elucidate the specific pathways by which BNPs influence the gut microbiota and improve intestinal barrier function.

The transmembrane receptor Vsig4 plays a crucial role in the clearance of complement-opsonized pathogens and cellular debris. The enhanced expression of Vsig4 in KCs contributes to their improved phagocytic capabilities, facilitating more efficient removal of microbial components from the liver²⁸. This is consistent with previous studies highlighting the importance of KCs in liver homeostasis and their involvement in the progression of ALD^50,51. Our study indicates that the contribution of ethanol to liver disease is multifaceted. Beyond its direct hepatotoxic effects, ethanol also diminishes the population of liver-resident KCs and suppresses Vsig4 expression. This impairs the clearance of bacterial components from the liver, leading to the recruitment of MDM and liver inflammation. A major finding in this study is the upregulation of Vsig4 in KCs following BNP treatment, which is mediated by the enhancement of complement components (C1qa, C1qb, and C1qc). The functional significance of Vsig4 in BNP-mediated protection against ALD was confirmed by experiments with Vsig4-deficient mice. In the absence of Vsig4, BNPs were ineffective in mitigating alcohol-induced liver injury and inflammation, underscoring the importance of this macrophage receptor. Vsig4 deficiency also exacerbated the infiltration of microbial DNA-containing NPs into the liver, leading to greater inflammation and fibrosis. These findings highlight the crucial role of Vsig4 in liver homeostasis and the therapeutic properties of BNPs. Our study finds that BNPs modulate KC function via Vsig4 upregulation and bridge a gap between probiotics research and liver immunology. The specific identification of this molecular target could lead to the design, via engineered bacteria, of treatments that mimic or enhance the beneficial effects of BNPs on liver function, potentially yielding more targeted and effective therapies for ALD.

Consistent with the crucial role of the cGAS-STING pathway in sensing bacterial DNA and triggering cellular inflammatory responses⁵², microbial DNA-containing GNPs activated cGAS-STING signaling in both in vivo and in vitro experiments²⁹. The involvement of microbial DNA in inflammation induction via this pathway has been documented in various liver diseases^29,53,54. Our findings indicate that alcohol consumption increases production of GNPs that contain microbial DNA, LPS, and LTA. They also reveal the pivotal role of GNPs in activating hepatic immune responses, particularly via the cGAS-STING pathway, which drives expression of pro-inflammatory cytokines. Moreover, AFGNPs still induce inflammation when the TLR2 and TLR4 receptors are blocked, suggesting that surface LPS and LTA play supplementary roles in the inflammatory response. Emerging evidence highlights the crucial functions of pattern recognition receptors in immune regulation and microbial NP detection, with particular emphasis on TLRs and nucleotide oligomerization domain-like receptors (NLRs)^8,11,55,56. However, the precise components of microbial NPs that TLRs and NLRs recognize still need to be identified, as do the underlying mechanisms by which cellular damage and inflammatory cascades are initiated. Our study has shown the significance of NP-mediated transport of microbial DNA in ALD development. This provides a perspective on the gut–liver axis in ALD and may explain why previous interventions targeting single bacterial products (e.g., LPS) have shown limited efficacy in clinical trials. Further studies are warranted to explore the long-term safety and efficacy of BNP interventions in human populations, and possible synergies with other therapies targeting gut–liver axis dysfunction.

In conclusion, this study provides compelling evidence for the protective effects of probiotic-derived extracellular nanoparticles against alcohol-induced liver injury. By elucidating the role of GNPs in ALD pathogenesis and demonstrating the multifaceted impact of BNPs, we have uncovered a therapeutic possibility for this challenging condition. While further research is needed to translate these findings into clinical applications, our work represents additional insights into the mechanisms and application in treating alcohol-associated liver disease.

Methods

Ethical statement

This study received approval from the Clinical Research Ethics Committee of the Second Norman Bethune Hospital of Jilin University (Jilin, China) (82220367) and adhered to the ethical guidelines of the Declaration of Helsinki. All participants provided informed consent. The study collected serum, stool, and clinical test data from 6 healthy controls (male n = 4, female n = 2) and 15 ALD patients (male n = 12, female n = 3). All animal experiments were conducted with the approval of the Animal Care and Use Committee of China Agricultural University (Beijing, China) under the protocol number of AA60223204.

Human clinical patient data and sample collection

Healthy controls were recruited from individuals without underlying medical conditions who underwent evaluation at the Physical Examination Center of the Second Norman Bethune Hospital, Jilin University (Jilin, China). ALD patients were selected based on three criteria: (1) an extensive history of alcohol abuse, with an average consumption of more than 3 drinks (>40 g) per day, (2) clinical evidence of liver injury, indicated by hepatomegaly and biochemical abnormalities, including total bilirubin (>3 mg/dL), AST (>50 IU/L), and AST to alanine aminotransferase (ALT) ratio of >1.5, and (3) absence of viral hepatitis or other liver disorders. The diagnostic characteristics of patients with AH from NIAAA consortium⁵⁷ and the detailed patient information were provided in Supplementary Tables S1 and S2. Biological specimens were collected, transported to the laboratory on dry ice, and stored at −80 °C for subsequent analysis.

Animal experiments

All animals used in this study were 6–8-week-old male C57BL/6J mice purchased from Charles River Laboratories (Beijing, China). Vsig4-flox (Strain S-CKO-17997) and Vsig4-KO (Strain S-KO-08959) mice were purchased from Cyagen (Suzhou, China). The Gao-Binge model (NIAAA model) has been previously described⁵⁸. In brief, the mice were administered either a Lieber-DeCarli diet (TP 4030D, Trophic Animal Feed High-Tech Co. Ltd., Nantong, China) containing 5% (v/v) ethanol or an isocaloric control diet (TP 4030C) for 10 days. The food consumption of the ethanol-fed mice was documented, and the calculated volume was utilized to adjust the amount of control liquid diet given to pair-fed mice such that ethanol-fed and pair-fed mice consumed equal amounts of dSufficient Mice were euthanized 9 h later for tissue collection. BNPs were supplemented in the last 7 days by daily gavage with 200 µL of 2 × 10⁹ BNPs, PFGNPs, or AFGNPs. A group of mice was treated with non-absorbable antibiotics (Polymyxin B, 150 mg/kg BW/day and Neomycin, 200 mg/kg BW/day) one week prior to the 5% alcohol-feeding period and maintained throughout the experiment. Control mice were gavaged with an equal volume of the vehicle (PBS).

Bifidobacterium bifidum 18-3 culture and preparation of Bifidobacterium bifidum derived nanoparticles (BNPs)

Bifidobacterium bifidum 18–3 was isolated from the feces of healthy elderly people and cultured in autoclaved deMan, Rogosa, and Sharpe Man Rogosa Sharp with 0.05% L-cysteine (MRSC) broth and incubated at 37 °C for 40 h. The culture density was measured using a spectrophotometer at OD600. The culture suspension (2 × 10⁹ CFU/mL) was centrifuged at 2000 × g for 10 min, 5000 × g for 20 min, and 10,000 × g for 30 min to eliminate debris, including dead cells and other waste materials. The obtained supernatant was filtered and ultracentrifuged at 150,000 × g for 70 min (Optima L-100XP Ultra Centrifuge; Beckman Coulter, Atlanta, GA, USA). After ultracentrifugation, the supernatants were collected and stored, and the pellet containing BNPs was washed in phosphate-buffered saline (PBS), ultracentrifuged, resuspended in PBS, and stored at −80 °C for later use.

Purification of gut microbiota-derived NPs, and plasma NPs

Gut microbial nanoparticles (GNPs) were isolated from fresh fecal samples of the mice. Mucosal NPs were prepared from the mucosal contents of the intestine, which were retrieved by gently flushing the intestine with 10 mL ice-cold phosphate-buffered saline (PBS). Debris and dead cells were eliminated via centrifugation at 1000 × g for 10 min and then filtered through a 0.2 µm filter. Subsequently, the supernatant was subjected to ultracentrifugation at 100,000 × g for 4 h at 4 °C, using a Type 70 Ti fixed-angle rotor (Beckman Coulter). The pellet containing the NPs was resuspended in 1 mL of sterile PBS and passed through a 0.2 µm filter to remove large particles.

Plasma nanoparticles (NPs) were isolated from the plasma of mice or humans. To extract NPs from plasma, plasma (0.5 mL) was diluted with 2 mL of sterile phosphate-buffered saline (PBS) and subsequently passed through a 0.2 µm filter. The resulting supernatant was subjected to ultracentrifugation at 100,000 × g for 4 h at 4 °C using an SW60 Ti swinging bucket rotor (Beckman Coulter). Following ultracentrifugation, both the NP pellets and NP-free supernatant were analyzed to quantify the abundance of bacterial DNA. In addition, an additional plasma sample (0.5 mL) was diluted with sterile PBS (0.5 mL of sterile PBS, filtered through a 0.2 µm filter, and used for bacterial DNA content analysis. The isolated NPs were resuspended in PBS and stored at −80 °C for subsequent experiments.

Imaging of NPs by transmission electron microscopy (TEM)

The sample preparation and imaging of NPs by TEM were performed as previously described⁵⁹. Briefly, BNPs/PFGNPs/AFGNPs/AF-BGNPs were fixed with 2% paraformaldehyde (PFA) for 5 min, and 5–7 µL of nanoparticle suspension solution was loaded onto formvar/carbon-coated copper grids (Electron Microscopy Sciences, Hatfield, PA) and incubated for 1 min before staining with filtered 1% uranyl acetate (UA) solution. Excess UA solution on the grid was removed by contacting the grid edge with filter paper, and the grid was quickly rinsed with a drop of water and allowed to dry for 10 min at room temperature. Finally, the grids were viewed using a Philips CM12 transmission electron microscope at 80 KV. Digital images were acquired using an SIA-7C side-mounted CCD digital camera.

NPs labeling

BNPs/AFGNPs were labeled with fluorescent dye PKH67 or PKH26, included in the PKH67 or PKH26 Fluorescent Cell Linker Kits (Sigma, St. Louis, MO, USA), according to the manufacturer’s instructions. The labeled BNP/AFGNP preparation was then gavaged to mice (5 × 10⁹ NPs), and the tissues were collected 24 h later for analysis. Primary hepatic macrophages were incubated with PKH67-labled BNPs (10 μg/ml) for 12 h. The deposition of BNPs in tissues and cells was evaluated under a fluorescence microscope by counting the number of PKH67-postitive stained cells.

For DiR labelling, 2 mg of BNPs in 1 mL of PBS was mixed with 1 μL of a 5 mM DiR dye solution (Invitrogen; prepared in DMSO) and incubated at room temperature for 20 min. The mixture was then centrifuged at 150,000 × g for 2 h, and the pellet was resuspended in PBS and stored at −80 °C.

Histological analysis

Liver and small intestine tissues were collected in 4% paraformaldehyde and embedded in paraffin. Tissues were cut into 5 μm sections and stained with hematoxylin and eosin (H&E), and analyzed by light microscopy. For hepatic lipid accumulation analysis, frozen liver sections were stained with Oil Red O to visualize neutral lipids. Nuclei were counterstained with hematoxylin.

Immunofluorescence

Cryosections were cut at 10 μm thickness and then fixed in acetone: methanol (1:1) at −20 °C for 2 min and rehydrated in phosphate-buffered saline (PBS) (137 mM sodium chloride, 2.7 mM potassium chloride, 10 mM disodium hydrogen phosphate, and 1.8 mM potassium dihydrogen phosphate). Sections were permeabilized with 0.2% Triton X-100 in PBS for 10 min, blocked in 4% nonfat milk in Triton-Tris buffer (150 mM sodium chloride containing 10% Tween-20 and 20 mM Tris, pH 7.4), and then incubated for 24 h with the primary antibody Vsig4 (Thermo Fisher, Cat. No.17-5752-82; 1:100 dilution), F4/80 (Abcam, Cat. No. ab90247, 1:100 dilution), Occludin (Cell Signaling, Cat. No. 91131, 1:200 dilution), Claudin-1 (Cell Signaling, Cat. No. 13255T, 1:200 dilution), IBA1 (Proteintech, Cat. No. CL-81728, 1:200 dilution) and CLEC4F (R&D systems, Cat. No. AF2784-SP, 1:200 dilution), followed by incubation with secondary antibodies for 1 h (Alexa Fluor 594-conjugated anti-rabbit IgG and Alexa fluor 488-affinipure anti-rabbit IgG, 1:100 dilution). DAPI (Invitrogen) was used for nuclear counterstaining. The slides were mounted using ProLong Gold (Invitrogen) for imaging.

RNAscope in situ hybridization combined with Immunofluorescence

We performed RNAscope in situ hybridization to detect 16S rRNA. Frozen sections of the liver and colonic tissues from mice and primary hepatic macrophage cell slides were prepared for antigen retrieval and hybridized according to the manufacturer’s instructions (Cat. No. d0016, Focofish). 16S rRNA-targeted oligonucleotide probes (Cat. No. EUB338I, Focofish) was diluted 1:100 in 35% hybridization buffer. Subsequently, the samples were immediately processed for immunofluorescence, and images were captured using a Leica SP8 Confocal microscope.

Cell culture

The human intestinal epithelial cells Caco-2 were maintained in DMEM-high glucose (Corning; 10-009CV). Primary hepatic macrophages and bone marrow-derived macrophages (BMDM) were isolated from mice, as previously described^26,60. Isolated KCs and BMDM were cultured in modified RPMI 1640 medium and DMEM with macrophage colony-stimulating factor (M-CSF), respectively. The medium was supplemented with 10% fetal bovine serum, 1X penicillin-streptomycin solution (100 U/ml penicillin and 100 µg/ml streptomycin; Sigma-Aldrich) in a humidified atmosphere (5% CO2, 95% air, 37 °C). Cells were used for experimentation at 70–80% confluence. KCs and BMDMs were pretreated with BNPs/AFGNPs/AF-BGNPs (2 µg/mL for 24 h), LPS (O55:B5; Sigma) (100 ng/mL for 4 h), or Sparstolonin B (Cat. No. T38261; Topscience) (20 µM for 24 h). Caco-2 cells at 70–80% confluence were treated with BNP/PFGNP/AF-BGNPs (1 × 10⁸ NPs) for 24 h.

Depletion DNA of GNPs

The GNPs pellet was dissolved in 100 µL of PBS. As previously described⁶¹, the NPs were loaded into Gene Pulser/micropulser Cuvettes (Bio-Rad) for electroporation (GenePulser Xcell electroporator, Bio-Rad) and then treated with DNase I (300U) for 30 min at 37 °C.

Quantification of bacterial DNA using real-time PCR

Total DNA was extracted from GNPs, feces, tissues, or cells. As previously described²⁹, the concentration of DNA concentration was measured using a Nanodrop 2000C and then adjusted to ensure consistency between different samples. Bacterial DNA levels were assessed by qPCR using a Femto Bacterial DNA Quantification Kit (Cat No. HY-138682, Zymo Research) according to the manufacturer’s instructions. The 2^−ΔΔCt method was used to quantify relative expression levels.

Flow cytometry

Flow cytometry was used to analyze the expression of surface markers and intracellular effector molecules in hepatic immune cells. Fluorochrome-conjugated monoclonal antibodies specific to mouse CD45.2 (Cat. No. 109830), CD11b (Cat. No. 982614), F4/80 (Cat. No. 123113), CD206 (Cat. No. 141706), and Ly-6C (Cat. No. 982614) were purchased from BioLegend. Vsig4 (Cat. No. 17-5757-42) was purchased from eBiosciences. Mouse Fc Block (anti-mouse CD16/32; Cat. No. 553142) was purchased from BD Biosciences. iNOS (Cat. No. 404-5920-82) and FVD eFluor 506 (Cat. No. 65-0866-14) were purchased from Thermo Fisher Scientific. All the antibodies were used at 1:200 dilution. Data were analyzed using the FlowJo software. The gating strategies used for flow cytometry analysis were provided in Supplementary Information.

16S ribosomal RNA (16S rRNA) gene library preparation and sequencing on the Illumina MiSeq

Fecal pellets were collected in sterile tubes at the end of the experiment and stored at −80 °C. Microbial genomic DNA was extracted from frozen fecal samples using a QIAamp DNA Stool Mini Kit (Cat No. 51504, Qiagen, Hilden, Germany), according to the manufacturer’s instructions. The composition of fecal microbiota was analyzed using Illumina MiSeq technology targeting the V3 and V4 regions of 16S ribosomal RNA. 16S variable regions were amplified using 12.5 ng microbial genomic DNA. PCR conditions were as follows: 95 °C for 3 min; 25 cycles of 95 °C for 30 s, 55 °C for 30 s, and then 72 °C for 30 s; and 72 °C for 5 min. The primers used for 16S Amplicon PCR were as follows: forward, 5′-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG; Reverse, 5′-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC. Index PCR was performed to attach dual indices and Illumina sequencing adapters using a Nextera Index Kit (Cat No. FC-121-1012, Illumina, San Diego, CA, USA). Each step was followed by PCR cleanup using AMPure XP beads to obtain a purified library. After libraries were normalized, pooled, and denatured, sequencing was performed using the Illumina MiSeq Reagents kit v3 (600 cycles, read lengths up to 2 × 300 bp) (Cat No. MS-102-3003; Illumina, San Diego, CA, USA) using an Illumina MiSeq instrument.

Mouse intestinal organoid culture

Intestinal organoids were isolated and cultured in vitro as described previously⁶². Briefly, 20 cm of the small intestine proximal to the stomach was harvested and opened longitudinally. The tissue was cut into 2 mm pieces and washed with ice-cold PBS 15–20 times with gentle shaking until the supernatant was clear. The tissue was then digested with a gentle cell dissociation reagent for 15 min at room temperature on a rocking platform at 20 rpm. Tissue pieces were collected and resuspended in PBS containing 0.1% BSA. Crypts were isolated by gentle shaking and then filtered through a 70 mm strainer. The supernatant containing the crypts was collected and pelleted by centrifugation at 200 × g for 3 min. Approximately 200–500 crypts were embedded in Matrigel (Sigma) per well of a 24-well plate and submerged in IntestiCult Organoid Growth Medium (OGM; Stem Cell Technologies) with supplements. Organoids were subcultured every 6–7 days at 37 °C in a 5% CO₂ environment with a 1:4 splitting ratio.

Western blotting

Proteins were extracted from frozen intestinal and hepatic tissues. Western blotting was performed as described previously²⁰. GAPDH (Cat. No. 2118 S; 1:2000 dilution) and pSTING (Cat. No. 72971; 1:2000 dilution), STING (Cat. No. 50494; 1:2000 dilution), NF-κB p65 (Cat. No. 3033; 1:2000 dilution), pNF-κB p65 (Cat. No. 8242; 1:2000 dilution) and cGAS (Cat. No. 316595; 1:2000 dilution) antibodies were obtained from Cell Signaling Technology. Vsig4 (Cat. No. 17-5752-82; 1:2000 dilution) and β-actin (Cat. No. MA5-15739; 1:2000 dilution) were received from ThermoFisher.

Real-time quantitative PCR

Total mRNA was extracted from mouse liver and intestinal tissues using TRIzol according to the manufacturer’s protocol. Total RNA was reverse transcribed using a cDNA cycle kit (Invitrogen). The primers used for the experiment are listed in Tables S3 and S4. GAPDH was used as an internal control. Real-time PCR was performed using the SYBR green reaction mixture in an ABI 7300 Fast Real-Time PCR System (Applied Biosystems). The relative gene expression was determined using the ΔΔCT method.

Signal cell RNA-sequencing analysis of hepatic NPC

The hepatic tissues were digested with 0.25% trypsin (Thermo Fisher, Cat. No. 25200-072) and 10 µg/mL DNase I (Sigma, Cat. No. 11284932001) dissolved in PBS containing 5% Fetal Bovine Serum (FBS; Thermo Fisher, Cat. No. SV30087.02). Liver tissues were dissociated at 37 °C with a shaking speed of 50 r.p.m for about 40 min. Cell suspensions were filtered using a 40 μm nylon cell strainer, and red blood cells were removed by 1X Red Blood Cell Lysis Solution (Thermo Fisher, Cat. no. 00-4333-57). Dissociated cells were washed with 1x DPBS containing 0.4% FBS. The resulting NPCs were subjected to scRNA-seq analysis using 10X Genomics Chromium Single-Cell 3ʹ, according to the manufacturer’s instructions (Chromium Single Cell 3ʹ v3.1). The merged digital expression matrix generated by Cell Ranger was analyzed using Seurat (v.4.0.0). Differentially expressed genes (DEGs) between two different samples or clusters were identified using FindMarkers in Seurat^63,64.

Proteomics analysis

Total protein extraction

The three samples were removed in the frozen state and placed on ice. An appropriate amount of protein lysate (8 M urea, 1% SDS) containing protease inhibitors was used to inhibit protease activity. The mixture was ultrasonicated for 2 min at a low temperature, followed by splitting for 30 min. After centrifugation at 12,000 × g at 4 °C for 30 min, the concentration of the protein supernatant was determined by the bicinchoninic acid (BCA) method using a BCA Protein Assay Kit (Pierce, Thermo, USA). Protein quantification was performed according to the kit instructions.

Protein reductive alkylation and digestion

Protein samples (100 μg) were added TEAB (triethylammonium bicarbonate buffer (TEAB), and the final concentration of TEAB was 100 mM. Then add TCEP (tris (2-carboxyethyl) phosphine (TCEP) was added to a final concentration of 10 mM and reacted for 60 min at 37 °C. Iodoacetamide (IAM) was added to a final concentration of 40 mM and allowed to react for 40 min at room temperature in the dark. A certain percentage (acetone: sample v/v = 6:1) of pre-cooled acetone was added to each sample and incubated for 4 h at −20 °C. After centrifugation for 20 min at 10000 g, the sediment was collected, and 100 µL of 100 mM TEAB solution was added to dissolve the precipitate. Finally, the mixture was digested overnight with trypsin at 37 °C and added at a 1:50 trypsin-to-protein mass ratio.

Peptide desalination and quantification

The peptides were vacuum-dried and resuspended in 0.1% TFA. The samples were desalted with HLB and vacuum dried. Peptide concentrations were determined by peptide quantification kit (Thermo, Cat. 23275). Loading buffer was added to each tube to prepare the samples for mass spectrometry analysis, and the concentration of each sample was 0.25 µg/µL.

LC-MS/MS analysis

Trypsin-digested peptides were analyzed using an EASY nLC-1200 system (Thermo, USA) coupled with a Q Exactive HF-X quadrupole orbitrap mass spectrometer (Thermo, USA) at Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China). Briefly, the C18-reversed phase column (75 μm × 25 cm, Thermo, USA) was equilibrated with solvent A (2% ACN with 0.1% formic acid) and solvent B (80% ACN with 0.1% formic acid).The peptides were eluted using the following gradient: 0–56 min, 5–23% B; 56–62 min, 23−29%B; 62–63 min, 29−38% B; 63−63:30 min, 38−48% B; and 63:30–64 min, 48–100% B; 64–90 min, 100–100%B. Tryptic peptides were separated at a flow rate of 300 nL/min. The Q Exactive HF-X instrument was operated in data-dependent acquisition mode (DDA) to automatically switch between full scan MS and MS/MS acquisition. Full scan MS spectra (m/z 300–1500) were acquired in Orbitrap at 60,000 resolution. The automatic gain control (AGC) target was 3e6, and the maximum fill time was 20 ms. The top 20 most intense precursor ions were then selected into the collision cell for fragmentation by high-energy collision dissociation (HCD). The MS/MS resolution was set at 15,000 (at m/z 100), automatic gain control (AGC) target at 1e5, maximum fill time of 50 ms, and dynamic exclusion of 18 s.

Protein identification

MS/MS spectra were searched using ProteomeDiscovererTM Software 2.4 software. The highest score for a given peptide mass (best match to that predicted in the database) was used to identify parent proteins. The parameters for protein searching were set as follows: tryptic digestion with up to two missed cleavages, carbamidomethylation of cysteines as a fixed modification, and oxidation of methionine and protein N-terminal acetylation as variable modifications. The false discovery rate (FDR) for peptide identification was set at FDR ≤ 0.01. A minimum of one unique peptide was used for protein identification.

Statistical analyses

Bioinformatics analysis of proteomic data was performed using the Majorbio Cloud platform (https://cloud.majorbio.com). P-values and Fold changes (FC) for the proteins between the two groups were calculated using the R package “t-test.” The thresholds of fold change (>1.2 or <0.83) and P-value < 0.05 were used to identify differentially expressed proteins (DEPs). Functional annotation of all identified proteins was performed using GO (http://geneontology.org/) and KEGG pathways (http://www.genome.jp/kegg/). DEPs were further used for GO and KEGG enrichment analyses. Protein-protein interaction analysis was performed using String v11.5.

Statistical analysis

Statistical analysis was performed using GraphPad Prism software (version 9.0). All experiments were conducted at least in triplicate, and data are presented as the mean ± standard error of the mean, with error bars in scatter plots, line charts, and bar graphs. The significance of two groups or multiple groups was evaluated using two-sided unpaired Student’s t-test, one-way analysis of variance (ANOVA) with Tukey’s test, two-way ANOVA with Sidak’s test, and two-tailed Pearson’s r correlation test. Differences were considered significant at p less than or equal to 0.05. Significance was noted as p ≤ 0.05, p ≤ 0.01, and p ≤ 0.001 among the groups.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Supplementary information

Supplementary Information^{(7.6MB, pdf)}

41467_2026_72211_MOESM2_ESM.pdf^{(79.8KB, pdf)}

Description of Additional Supplementary File

Supplementary Data 1^{(23.7KB, xlsx)}

Supplementary Data 2^{(162.7KB, xlsx)}

Reporting summary^{(3.8MB, pdf)}

Transparent Peer Review file^{(2.2MB, pdf)}

Source data

Source Data file^{(3.5MB, xlsx)}

Acknowledgements

This study was supported by National Natural Science Foundation of China under Grant 32201994 (N.S.), 32172172 (P.L.) and 82372144 (T.S.), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (23KJA310006) (T.S.), and the Natural Science Foundation of Jiangsu Province under Grant BK20230491 (T.S.). The authors would like to express their gratitude to EditSprings (https://www.editsprings.cn) for the expert linguistic services provided.

Author contributions

Conceptualization (Z.G., N.S. and P.L.); Methodology (Z.G., S.M., T.S. and F.R.); Formal analysis (Z.G., S.M., B.Y., B.G. and S.C.); Investigation (Z.G., B.Y., B.G. and S.C.); Resources (N.S., P.L., Z.G., T.S., S.M. and F.R.); Wrote the manuscript (Z.G., N.S.); Critical revisions of the draft (Z.G., N.S., T.S. and P.L.); Supervision (N.S. and P.L.); Funding acquisition (N.S. and P.L.).

Peer review

Peer review information

Nature Communications thanks Bryan Mackowiak, Pieter Dorrestein and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

Data availability

The original raw single-cell RNA-seq data, 16S rRNA sequencing data, whole genome sequencing data were available in the NCBI SRA database under the accession numbers PRJNA1230575 [https://www.ncbi.nlm.nih.gov/bioproject/1230575] and PRJNA935917. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the iProX partner repository under the accession number IPX0011244000 (with the ProteomeXchange dataset identifier PXD061375). The output of the proteomics analysis and other relevant data generated in this study are provided in the Source Data file. Source data are provided with this paper.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Pinglan Li, Email: lipinglan@cau.edu.cn.

Tuo Shao, Email: shaotuo@suda.edu.cn.

Nan Shang, Email: nshang@cau.edu.cn.

Supplementary information

The online version contains supplementary material available at 10.1038/s41467-026-72211-3.

References

1.Asrani, S. K., Devarbhavi, H., Eaton, J. & Kamath, P. S. Burden of liver diseases in the world. J. Hepatol.70, 151–171 (2019). [DOI] [PubMed] [Google Scholar]
2.Schnabl, B. & Brenner, D. A. Interactions between the intestinal microbiome and liver diseases. Gastroenterology146, 1513–1524 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Mackowiak, B., Fu, Y., Maccioni, L. & Gao, B. Alcohol-associated liver disease. J. Clin. Investig.134, 10.1172/jci176345 (2024). [DOI] [PMC free article] [PubMed]
4.Seitz, H. K. et al. Alcoholic liver disease. Nat. Rev. Dis. Prim.4, 16 (2018). [DOI] [PubMed] [Google Scholar]
5.Zhang, T. et al. Free fatty acid receptor 4 modulates dietary sugar preference via the gut microbiota. Nat. Microbiol.10, 348–361 (2025). [DOI] [PubMed] [Google Scholar]
6.Shen, H. et al. Dietary fiber alleviates alcoholic liver injury via Bacteroides acidifaciens and subsequent ammonia detoxification. Cell Host Microbe32, 1331–1346.e1336 (2024). [DOI] [PubMed] [Google Scholar]
7.Bajaj, J. S. Alcohol, liver disease and the gut microbiota. Nat. Rev. Gastroenterol. Hepatol.16, 235–246 (2019). [DOI] [PubMed] [Google Scholar]
8.Gu, Z. et al. A novel bioactive postbiotics: from microbiota-derived extracellular nanoparticles to health promoting. Crit. Rev. Food Sci. Nutr.63, 6885–6899 (2023). [DOI] [PubMed] [Google Scholar]
9.Toyofuku, M., Schild, S., Kaparakis-Liaskos, M. & Eberl, L. Composition and functions of bacterial membrane vesicles. Nat. Rev. Microbiol.21, 415–430 (2023). [DOI] [PubMed] [Google Scholar]
10.Xie, J., Li, Q., Haesebrouck, F., Van Hoecke, L. & Vandenbroucke, R. E. The tremendous biomedical potential of bacterial extracellular vesicles. Trends Biotechnol.40, 1173–1194 (2022). [DOI] [PubMed] [Google Scholar]
11.Díaz-Garrido, N., Badia, J. & Baldomà, L. Microbiota-derived extracellular vesicles in interkingdom communication in the gut. J. Extracell. Vesicles10, e12161 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Jiang, L. et al. Intestinal virome in patients with alcoholic hepatitis. Hepatology72, 2182–2196 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Lang, S. et al. Intestinal fungal dysbiosis and systemic immune response to fungi in patients with alcoholic hepatitis. Hepatology71, 522–538 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Gao, B. et al. Functional microbiomics reveals alterations of the gut microbiome and host co-metabolism in patients with alcoholic hepatitis. Hepatol. Commun.4, 1168–1182 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Lang, S. et al. Changes in the fecal bacterial microbiota associated with disease severity in alcoholic hepatitis patients. Gut Microbes12, 1785251 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Chu, H. et al. The Candida albicans exotoxin candidalysin promotes alcohol-associated liver disease. J. Hepatol.72, 391–400 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Duan, Y. et al. Bacteriophage targeting of gut bacterium attenuates alcoholic liver disease. Nature575, 505–511 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Zhong, W. et al. Paneth cell dysfunction mediates alcohol-related steatohepatitis through promoting bacterial translocation in mice: role of zinc deficiency. Hepatology71, 1575–1591 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Lang, S. & Schnabl, B. Microbiota and fatty liver disease-the known, the unknown, and the future. Cell Host Microbe28, 233–244 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Shao, T. et al. Intestinal HIF-1α deletion exacerbates alcoholic liver disease by inducing intestinal dysbiosis and barrier dysfunction. J. Hepatol.69, 886–895 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Llorente, C. et al. Gastric acid suppression promotes alcoholic liver disease by inducing overgrowth of intestinal Enterococcus. Nat. Commun.8, 837 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Ahmadi, A. R. et al. Discovery and characterization of cross-reactive intrahepatic antibodies in severe alcoholic hepatitis. eLife12, 10.7554/eLife.86678 (2023). [DOI] [PMC free article] [PubMed]
23.Wu, X. et al. Recent advances in understanding of pathogenesis of alcohol-associated liver disease. Annu. Rev. Pathol.18, 411–438 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Balmer, M. L. et al. The liver may act as a firewall mediating mutualism between the host and its gut commensal microbiota. Sci. Transl. Med.6, 237ra266 (2014). [DOI] [PubMed] [Google Scholar]
25.Helmy, K. Y. et al. CRIg: a macrophage complement receptor required for phagocytosis of circulating pathogens. Cell124, 915–927 (2006). [DOI] [PubMed] [Google Scholar]
26.Duan, Y. et al. CRIg on liver macrophages clears pathobionts and protects against alcoholic liver disease. Nat. Commun.12, 7172 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Wiesmann, C. et al. Structure of C3b in complex with CRIg gives insights into regulation of complement activation. Nature444, 217–220 (2006). [DOI] [PubMed] [Google Scholar]
28.Zeng, Z. et al. CRIg functions as a macrophage pattern recognition receptor to directly bind and capture blood-borne gram-positive bacteria. Cell Host Microbe20, 99–106 (2016). [DOI] [PubMed] [Google Scholar]
29.Luo, Z. et al. CRIg(+) macrophages prevent gut microbial DNA-containing extracellular vesicle-induced tissue inflammation and insulin resistance. Gastroenterology160, 863–874 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Ding, Q. et al. Lactobacillus plantarum ZY08 relieves chronic alcohol-induced hepatic steatosis and liver injury in mice via restoring intestinal flora homeostasis. Food Res Int157, 111259 (2022). [DOI] [PubMed] [Google Scholar]
31.Yin, R. et al. Postbiotics from Lactobacillus johnsonii activate gut innate immunity to mitigate alcohol-associated liver disease. Adv. Sci.12, e2405781 (2024). [DOI] [PMC free article] [PubMed]
32.Wang, Y. et al. Lactobacillus rhamnosus GG culture supernatant ameliorates acute alcohol-induced intestinal permeability and liver injury. Am. J. Physiol. Gastrointest. Liver Physiol.303, G32–G41 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Wang, X. et al. Versatility of bacterial outer membrane vesicles in regulating intestinal homeostasis. Sci. Adv.9, eade5079 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Gu, Z. et al. Exosome-like nanoparticles from Lactobacillus rhamnosus GG protect against alcohol-associated liver disease through intestinal aryl hydrocarbon receptor in mice. Hepatol. Commun.5, 846–864 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Jiang, M. et al. Probiotic-derived nanoparticles inhibit ALD through intestinal miR194 suppression and subsequent FXR activation. Hepatology77, 1164–1180 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Yan, F. et al. Soluble proteins produced by probiotic bacteria regulate intestinal epithelial cell survival and growth. Gastroenterology132, 562–575 (2007). [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Gu, Z., Wang, Y., Li, P. & Shang, N. Lactobacillus plantarum derived nanoparticles deliver class IIa bacteriocin as a potential natural food preservatives. LWT207, 116675 (2024). [Google Scholar]
38.Sharma, P. et al. Particle uptake driven phagocytosis in macrophages and neutrophils enhances bacterial clearance. J. Control Release343, 131–141 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Reis, E. S., Mastellos, D. C., Hajishengallis, G. & Lambris, J. D. New insights into the immune functions of complement. Nat. Rev. Immunol.19, 503–516 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Decout, A., Katz, J. D., Venkatraman, S. & Ablasser, A. The cGAS-STING pathway as a therapeutic target in inflammatory diseases. Nat. Rev. Immunol.21, 548–569 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Gao, B. & Bataller, R. Alcoholic liver disease: pathogenesis and new therapeutic targets. Gastroenterology141, 1572–1585 (2011). [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Szabo, G. Gut-liver axis in alcoholic liver disease. Gastroenterology148, 30–36 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Xin, F. Z. et al. Escherichia fergusonii promotes nonobese nonalcoholic fatty liver disease by interfering with host hepatic lipid metabolism through its own msRNA 23487. Cell Mol. Gastroenterol. Hepatol.13, 827–841 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Kirpich, I. A. et al. Probiotics restore bowel flora and improve liver enzymes in human alcohol-induced liver injury: a pilot study. Alcohol42, 675–682 (2008). [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Tuomisto, S. et al. Changes in gut bacterial populations and their translocation into liver and ascites in alcoholic liver cirrhotics. BMC Gastroenterol.14, 40 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Hendrikx, T. et al. Bacteria engineered to produce IL-22 in intestine induce expression of REG3G to reduce ethanol-induced liver disease in mice. Gut68, 1504–1515 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Liang, X. et al. Gut bacterial extracellular vesicles: important players in regulating intestinal microenvironment. Gut Microbes14, 2134689 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
48.Wu, Y. et al. Galactooligosaccharides and Limosilactobacillus reuteri synergistically alleviate gut inflammation and barrier dysfunction by enriching Bacteroides acidifaciens for pentadecanoic acid biosynthesis. Nat. Commun.15, 9291 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Laursen, M. F. et al. Bifidobacterium species associated with breastfeeding produce aromatic lactic acids in the infant gut. Nat. Microbiol.6, 1367–1382 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
50.Ju, C. & Tacke, F. Hepatic macrophages in homeostasis and liver diseases: from pathogenesis to novel therapeutic strategies. Cell Mol. Immunol.13, 316–327 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Guilliams, M. & Scott, C. L. Liver macrophages in health and disease. Immunity55, 1515–1529 (2022). [DOI] [PubMed] [Google Scholar]
52.Ablasser, A. & Chen, Z. J. cGAS in action: expanding roles in immunity and inflammation. Science363, 10.1126/science.aat8657 (2019). [DOI] [PubMed]
53.Szabo, G. & Iracheta-Vellve, A. Inflammasome activation in the liver: focus on alcoholic and non-alcoholic steatohepatitis. Clin. Res. Hepatol. Gastroenterol.39, S18–S23 (2015). [DOI] [PubMed] [Google Scholar]
54.Nie, S. et al. CRIg+ macrophages deficiency enhanced inflammation damage in IBD due to gut extracellular vesicles containing microbial DNA. Gut Microbes16, 2379633 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
55.Cañas, M. A., Fábrega, M. J., Giménez, R., Badia, J. & Baldomà, L. Outer Membrane vesicles from probiotic and commensal escherichia coli activate NOD1-mediated immune responses in intestinal epithelial cells. Front. Microbiol.9, 498 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
56.Chatterjee, D. & Chaudhuri, K. Vibrio cholerae O395 outer membrane vesicles modulate intestinal epithelial cells in a NOD1 protein-dependent manner and induce dendritic cell-mediated Th2/Th17 cell responses. J. Biol. Chem.288, 4299–4309 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
57.Crabb, D. W. et al. Standard definitions and common data elements for clinical trials in patients with alcoholic hepatitis: recommendation from the NIAAA alcoholic hepatitis consortia. Gastroenterology150, 785–790 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
58.Bertola, A., Mathews, S., Ki, S. H., Wang, H. & Gao, B. Mouse model of chronic and binge ethanol feeding (the NIAAA model). Nat. Protoc.8, 627–637 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
59.Jung, M. K. & Mun, J. Y. Sample preparation and imaging of exosomes by transmission electron microscopy. J. Vis. Exp. 10.3791/56482 (2018). [DOI] [PMC free article] [PubMed]
60.Ying, W., Cheruku, P. S., Bazer, F. W., Safe, S. H. & Zhou, B. Investigation of macrophage polarization using bone marrow derived macrophages. J. Vis. Exp. 10.3791/50323 (2013). [DOI] [PMC free article] [PubMed]
61.Lamichhane, T. N., Raiker, R. S. & Jay, S. M. Exogenous DNA loading into extracellular vesicles via electroporation is size-dependent and enables limited gene delivery. Mol. Pharm.12, 3650–3657 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
62.Lei, C. et al. Enteric VIP-producing neurons maintain gut microbiota homeostasis through regulating epithelium fucosylation. Cell Host Microbe30, 1417–1434.e1418 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
63.Satija, R., Farrell, J. A., Gennert, D., Schier, A. F. & Regev, A. Spatial reconstruction of single-cell gene expression data. Nat. Biotechnol.33, 495–502 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
64.Stuart, T. et al. Comprehensive integration of single-cell data. Cell177, 1888–1902.e1821 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Information^{(7.6MB, pdf)}

41467_2026_72211_MOESM2_ESM.pdf^{(79.8KB, pdf)}

Description of Additional Supplementary File

Supplementary Data 1^{(23.7KB, xlsx)}

Supplementary Data 2^{(162.7KB, xlsx)}

Reporting summary^{(3.8MB, pdf)}

Transparent Peer Review file^{(2.2MB, pdf)}

Source Data file^{(3.5MB, xlsx)}

Data Availability Statement

[CR1] 1.Asrani, S. K., Devarbhavi, H., Eaton, J. & Kamath, P. S. Burden of liver diseases in the world. J. Hepatol.70, 151–171 (2019). [DOI] [PubMed] [Google Scholar]

[CR2] 2.Schnabl, B. & Brenner, D. A. Interactions between the intestinal microbiome and liver diseases. Gastroenterology146, 1513–1524 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR3] 3.Mackowiak, B., Fu, Y., Maccioni, L. & Gao, B. Alcohol-associated liver disease. J. Clin. Investig.134, 10.1172/jci176345 (2024). [DOI] [PMC free article] [PubMed]

[CR4] 4.Seitz, H. K. et al. Alcoholic liver disease. Nat. Rev. Dis. Prim.4, 16 (2018). [DOI] [PubMed] [Google Scholar]

[CR5] 5.Zhang, T. et al. Free fatty acid receptor 4 modulates dietary sugar preference via the gut microbiota. Nat. Microbiol.10, 348–361 (2025). [DOI] [PubMed] [Google Scholar]

[CR6] 6.Shen, H. et al. Dietary fiber alleviates alcoholic liver injury via Bacteroides acidifaciens and subsequent ammonia detoxification. Cell Host Microbe32, 1331–1346.e1336 (2024). [DOI] [PubMed] [Google Scholar]

[CR7] 7.Bajaj, J. S. Alcohol, liver disease and the gut microbiota. Nat. Rev. Gastroenterol. Hepatol.16, 235–246 (2019). [DOI] [PubMed] [Google Scholar]

[CR8] 8.Gu, Z. et al. A novel bioactive postbiotics: from microbiota-derived extracellular nanoparticles to health promoting. Crit. Rev. Food Sci. Nutr.63, 6885–6899 (2023). [DOI] [PubMed] [Google Scholar]

[CR9] 9.Toyofuku, M., Schild, S., Kaparakis-Liaskos, M. & Eberl, L. Composition and functions of bacterial membrane vesicles. Nat. Rev. Microbiol.21, 415–430 (2023). [DOI] [PubMed] [Google Scholar]

[CR10] 10.Xie, J., Li, Q., Haesebrouck, F., Van Hoecke, L. & Vandenbroucke, R. E. The tremendous biomedical potential of bacterial extracellular vesicles. Trends Biotechnol.40, 1173–1194 (2022). [DOI] [PubMed] [Google Scholar]

[CR11] 11.Díaz-Garrido, N., Badia, J. & Baldomà, L. Microbiota-derived extracellular vesicles in interkingdom communication in the gut. J. Extracell. Vesicles10, e12161 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR12] 12.Jiang, L. et al. Intestinal virome in patients with alcoholic hepatitis. Hepatology72, 2182–2196 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR13] 13.Lang, S. et al. Intestinal fungal dysbiosis and systemic immune response to fungi in patients with alcoholic hepatitis. Hepatology71, 522–538 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR14] 14.Gao, B. et al. Functional microbiomics reveals alterations of the gut microbiome and host co-metabolism in patients with alcoholic hepatitis. Hepatol. Commun.4, 1168–1182 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR15] 15.Lang, S. et al. Changes in the fecal bacterial microbiota associated with disease severity in alcoholic hepatitis patients. Gut Microbes12, 1785251 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR16] 16.Chu, H. et al. The Candida albicans exotoxin candidalysin promotes alcohol-associated liver disease. J. Hepatol.72, 391–400 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR17] 17.Duan, Y. et al. Bacteriophage targeting of gut bacterium attenuates alcoholic liver disease. Nature575, 505–511 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR18] 18.Zhong, W. et al. Paneth cell dysfunction mediates alcohol-related steatohepatitis through promoting bacterial translocation in mice: role of zinc deficiency. Hepatology71, 1575–1591 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR19] 19.Lang, S. & Schnabl, B. Microbiota and fatty liver disease-the known, the unknown, and the future. Cell Host Microbe28, 233–244 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR20] 20.Shao, T. et al. Intestinal HIF-1α deletion exacerbates alcoholic liver disease by inducing intestinal dysbiosis and barrier dysfunction. J. Hepatol.69, 886–895 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR21] 21.Llorente, C. et al. Gastric acid suppression promotes alcoholic liver disease by inducing overgrowth of intestinal Enterococcus. Nat. Commun.8, 837 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR22] 22.Ahmadi, A. R. et al. Discovery and characterization of cross-reactive intrahepatic antibodies in severe alcoholic hepatitis. eLife12, 10.7554/eLife.86678 (2023). [DOI] [PMC free article] [PubMed]

[CR23] 23.Wu, X. et al. Recent advances in understanding of pathogenesis of alcohol-associated liver disease. Annu. Rev. Pathol.18, 411–438 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR24] 24.Balmer, M. L. et al. The liver may act as a firewall mediating mutualism between the host and its gut commensal microbiota. Sci. Transl. Med.6, 237ra266 (2014). [DOI] [PubMed] [Google Scholar]

[CR25] 25.Helmy, K. Y. et al. CRIg: a macrophage complement receptor required for phagocytosis of circulating pathogens. Cell124, 915–927 (2006). [DOI] [PubMed] [Google Scholar]

[CR26] 26.Duan, Y. et al. CRIg on liver macrophages clears pathobionts and protects against alcoholic liver disease. Nat. Commun.12, 7172 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR27] 27.Wiesmann, C. et al. Structure of C3b in complex with CRIg gives insights into regulation of complement activation. Nature444, 217–220 (2006). [DOI] [PubMed] [Google Scholar]

[CR28] 28.Zeng, Z. et al. CRIg functions as a macrophage pattern recognition receptor to directly bind and capture blood-borne gram-positive bacteria. Cell Host Microbe20, 99–106 (2016). [DOI] [PubMed] [Google Scholar]

[CR29] 29.Luo, Z. et al. CRIg(+) macrophages prevent gut microbial DNA-containing extracellular vesicle-induced tissue inflammation and insulin resistance. Gastroenterology160, 863–874 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR30] 30.Ding, Q. et al. Lactobacillus plantarum ZY08 relieves chronic alcohol-induced hepatic steatosis and liver injury in mice via restoring intestinal flora homeostasis. Food Res Int157, 111259 (2022). [DOI] [PubMed] [Google Scholar]

[CR31] 31.Yin, R. et al. Postbiotics from Lactobacillus johnsonii activate gut innate immunity to mitigate alcohol-associated liver disease. Adv. Sci.12, e2405781 (2024). [DOI] [PMC free article] [PubMed]

[CR32] 32.Wang, Y. et al. Lactobacillus rhamnosus GG culture supernatant ameliorates acute alcohol-induced intestinal permeability and liver injury. Am. J. Physiol. Gastrointest. Liver Physiol.303, G32–G41 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR33] 33.Wang, X. et al. Versatility of bacterial outer membrane vesicles in regulating intestinal homeostasis. Sci. Adv.9, eade5079 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR34] 34.Gu, Z. et al. Exosome-like nanoparticles from Lactobacillus rhamnosus GG protect against alcohol-associated liver disease through intestinal aryl hydrocarbon receptor in mice. Hepatol. Commun.5, 846–864 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR35] 35.Jiang, M. et al. Probiotic-derived nanoparticles inhibit ALD through intestinal miR194 suppression and subsequent FXR activation. Hepatology77, 1164–1180 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR36] 36.Yan, F. et al. Soluble proteins produced by probiotic bacteria regulate intestinal epithelial cell survival and growth. Gastroenterology132, 562–575 (2007). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR37] 37.Gu, Z., Wang, Y., Li, P. & Shang, N. Lactobacillus plantarum derived nanoparticles deliver class IIa bacteriocin as a potential natural food preservatives. LWT207, 116675 (2024). [Google Scholar]

[CR38] 38.Sharma, P. et al. Particle uptake driven phagocytosis in macrophages and neutrophils enhances bacterial clearance. J. Control Release343, 131–141 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR39] 39.Reis, E. S., Mastellos, D. C., Hajishengallis, G. & Lambris, J. D. New insights into the immune functions of complement. Nat. Rev. Immunol.19, 503–516 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR40] 40.Decout, A., Katz, J. D., Venkatraman, S. & Ablasser, A. The cGAS-STING pathway as a therapeutic target in inflammatory diseases. Nat. Rev. Immunol.21, 548–569 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR41] 41.Gao, B. & Bataller, R. Alcoholic liver disease: pathogenesis and new therapeutic targets. Gastroenterology141, 1572–1585 (2011). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR42] 42.Szabo, G. Gut-liver axis in alcoholic liver disease. Gastroenterology148, 30–36 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR43] 43.Xin, F. Z. et al. Escherichia fergusonii promotes nonobese nonalcoholic fatty liver disease by interfering with host hepatic lipid metabolism through its own msRNA 23487. Cell Mol. Gastroenterol. Hepatol.13, 827–841 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR44] 44.Kirpich, I. A. et al. Probiotics restore bowel flora and improve liver enzymes in human alcohol-induced liver injury: a pilot study. Alcohol42, 675–682 (2008). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR45] 45.Tuomisto, S. et al. Changes in gut bacterial populations and their translocation into liver and ascites in alcoholic liver cirrhotics. BMC Gastroenterol.14, 40 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR46] 46.Hendrikx, T. et al. Bacteria engineered to produce IL-22 in intestine induce expression of REG3G to reduce ethanol-induced liver disease in mice. Gut68, 1504–1515 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR47] 47.Liang, X. et al. Gut bacterial extracellular vesicles: important players in regulating intestinal microenvironment. Gut Microbes14, 2134689 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR48] 48.Wu, Y. et al. Galactooligosaccharides and Limosilactobacillus reuteri synergistically alleviate gut inflammation and barrier dysfunction by enriching Bacteroides acidifaciens for pentadecanoic acid biosynthesis. Nat. Commun.15, 9291 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR49] 49.Laursen, M. F. et al. Bifidobacterium species associated with breastfeeding produce aromatic lactic acids in the infant gut. Nat. Microbiol.6, 1367–1382 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR50] 50.Ju, C. & Tacke, F. Hepatic macrophages in homeostasis and liver diseases: from pathogenesis to novel therapeutic strategies. Cell Mol. Immunol.13, 316–327 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR51] 51.Guilliams, M. & Scott, C. L. Liver macrophages in health and disease. Immunity55, 1515–1529 (2022). [DOI] [PubMed] [Google Scholar]

[CR52] 52.Ablasser, A. & Chen, Z. J. cGAS in action: expanding roles in immunity and inflammation. Science363, 10.1126/science.aat8657 (2019). [DOI] [PubMed]

[CR53] 53.Szabo, G. & Iracheta-Vellve, A. Inflammasome activation in the liver: focus on alcoholic and non-alcoholic steatohepatitis. Clin. Res. Hepatol. Gastroenterol.39, S18–S23 (2015). [DOI] [PubMed] [Google Scholar]

[CR54] 54.Nie, S. et al. CRIg+ macrophages deficiency enhanced inflammation damage in IBD due to gut extracellular vesicles containing microbial DNA. Gut Microbes16, 2379633 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR55] 55.Cañas, M. A., Fábrega, M. J., Giménez, R., Badia, J. & Baldomà, L. Outer Membrane vesicles from probiotic and commensal escherichia coli activate NOD1-mediated immune responses in intestinal epithelial cells. Front. Microbiol.9, 498 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR56] 56.Chatterjee, D. & Chaudhuri, K. Vibrio cholerae O395 outer membrane vesicles modulate intestinal epithelial cells in a NOD1 protein-dependent manner and induce dendritic cell-mediated Th2/Th17 cell responses. J. Biol. Chem.288, 4299–4309 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR57] 57.Crabb, D. W. et al. Standard definitions and common data elements for clinical trials in patients with alcoholic hepatitis: recommendation from the NIAAA alcoholic hepatitis consortia. Gastroenterology150, 785–790 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR58] 58.Bertola, A., Mathews, S., Ki, S. H., Wang, H. & Gao, B. Mouse model of chronic and binge ethanol feeding (the NIAAA model). Nat. Protoc.8, 627–637 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR59] 59.Jung, M. K. & Mun, J. Y. Sample preparation and imaging of exosomes by transmission electron microscopy. J. Vis. Exp. 10.3791/56482 (2018). [DOI] [PMC free article] [PubMed]

[CR60] 60.Ying, W., Cheruku, P. S., Bazer, F. W., Safe, S. H. & Zhou, B. Investigation of macrophage polarization using bone marrow derived macrophages. J. Vis. Exp. 10.3791/50323 (2013). [DOI] [PMC free article] [PubMed]

[CR61] 61.Lamichhane, T. N., Raiker, R. S. & Jay, S. M. Exogenous DNA loading into extracellular vesicles via electroporation is size-dependent and enables limited gene delivery. Mol. Pharm.12, 3650–3657 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR62] 62.Lei, C. et al. Enteric VIP-producing neurons maintain gut microbiota homeostasis through regulating epithelium fucosylation. Cell Host Microbe30, 1417–1434.e1418 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR63] 63.Satija, R., Farrell, J. A., Gennert, D., Schier, A. F. & Regev, A. Spatial reconstruction of single-cell gene expression data. Nat. Biotechnol.33, 495–502 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR64] 64.Stuart, T. et al. Comprehensive integration of single-cell data. Cell177, 1888–1902.e1821 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Bifidobacterium bifidum-derived nanoparticles attenuate alcoholic liver disease via enhanced hepatic phagocytosis and gastrointestinal homeostasis

Zelin Gu

Shuhan Meng

Boqing Yao

Boya Gao

Siye Chen

Fazheng Ren

Pinglan Li

Tuo Shao

Nan Shang

Abstract

Introduction

Results

Characterization and tracking of BNPs in circulation

Fig. 1. Identification and characterization of bacterial nanoparticles (BNPs).

BNPs alleviate alcohol-induced liver injury by modulating hepatic macrophage polarization

Fig. 2. Reversal/prevention of alcoholic liver disease in model mice by BNP treatment.

BNPs increase macrophage phagocytosis by induction of Vsig4 expression via increased complement components

Fig. 3. Effects of alcohol and BNPs on the phagocytic function of hepatic macrophages.

BNPs inhibit translocation of GNPs into the circulation and liver in ALD mice

Fig. 4. Alcohol-induced translocation of nanoparticles containing bacterial DNA from the gut into the circulation.

Extracellular nanoparticles containing gut microbe DNA play an important role in progression of ALD

Fig. 5. Gut microbiota-derived nanoparticles (GNPs) alleviate progression of alcohol-induced liver disease.

BNPs mitigate ALD by inhibiting microbial DNA-containing nanoparticles that induce intestinal barrier dysfunction and inflammation

Fig. 6. Effects of probiotic-derived nanoparticles and DNA-containing gut microbe-derived nanoparticles on intestinal barrier function.

Vsig4 deficiency abolishes the protective effects of BNPs against alcohol-induced liver injury following AFGNP supplementation

Fig. 7. Beneficial effects of BNPs on alcohol-induced liver injury in mice and abolition by Vsig4 deficiency.

Discussion

Fig. 8. Schematic illustration of the versatility of BNPs in regulating gastrointestinal homeostasis and hepatic phagocytosis.

Methods

Ethical statement

Human clinical patient data and sample collection

Animal experiments

Bifidobacterium bifidum 18-3 culture and preparation of Bifidobacterium bifidum derived nanoparticles (BNPs)

Purification of gut microbiota-derived NPs, and plasma NPs

Imaging of NPs by transmission electron microscopy (TEM)

NPs labeling

Histological analysis

Immunofluorescence

RNAscope in situ hybridization combined with Immunofluorescence

Cell culture

Depletion DNA of GNPs

Quantification of bacterial DNA using real-time PCR

Flow cytometry

16S ribosomal RNA (16S rRNA) gene library preparation and sequencing on the Illumina MiSeq

Mouse intestinal organoid culture

Western blotting

Real-time quantitative PCR

Signal cell RNA-sequencing analysis of hepatic NPC

Proteomics analysis

Total protein extraction

Protein reductive alkylation and digestion

LC-MS/MS analysis

Protein identification

Statistical analyses

Statistical analysis

Reporting summary

Supplementary information

Source data

Acknowledgements

Author contributions

Peer review

Peer review information

Data availability

Competing interests

Footnotes

Contributor Information

Supplementary information

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases