BR Biomedical Reports 2049-9434 2049-9442 D.A. Spandidos BR-23-6-02071 10.3892/br.2025.2071 Articles Gut microbiota involvement in the alteration of inflammatory cell infiltration and gut barrier integrity in liver cirrhosis XieKaiduan 1 * ZhangYiwang 2 * TanShuyan 1 LuoJiajie 1 OuXingtong 1 TanSiwei 1 Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong 510630, P.R. China Department of Pathology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong 510630, P.R. China Correspondence to: Professor Siwei Tan, Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-sen University, 600 Tianhe Road, Guangzhou, Guangdong 510630, P.R. China tansw@mail.sysu.edu.cn

*Contributed equally

Abbreviations: OTU, operational taxonomic unit; LDA, linear discriminant analysis; LEfSe, linear discriminant analysis effect size; DAO, diamine oxidase; ZO-1, zonula occludens-1

 122025 20102025 23 6 193 08 03 2025 12 09 2025 Copyright: © 2025 Xie et al. 2025 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

The gut microbiota is essential for the development and regulation of the immune and intestinal homeostasis of the host. The present study aimed to investigate the composition, diversity and functional features of the microbiota in patients with liver cirrhosis. and healthy volunteers using high-throughput sequencing of the 16S rRNA gene, and evaluated inflammatory cell infiltration and the gut barrier in both the colonic mucosa and liver sections using histological analysis. Diversity and metagenome function of the gut microbiota significantly differed between healthy volunteers and patients with liver cirrhosis. Patients with cirrhosis showed decreased microbial richness, evenness, and diversity, with functional prediction indicating enrichment of phosphotransferase and membrane transport pathways, while amino acid and energy metabolism pathways were predominant in healthy controls. Furthermore, gut microbial dysbiosis associated with liver cirrhosis augmented inflammatory cell infiltration in the colonic mucosa and liver sections, impaired gut barrier function and enhanced intestinal permeability and bacterial translocation. The gut microbiota contributes to the pathophysiology of liver cirrhosis, which may impact prevention and treatment strategies for patients with liver cirrhosis.

 liver cirrhosis gut microbiota immune response inflammation gut barrier Funding: The present study was supported by the Natural Science Foundation of Guangdong Province (grant no. 2023A1515011204), the National Natural Science Foundation of China (grant no. 82170569) and the Science and Technology Planning Projects of Guangzhou City (grant nos. 2024A04J6565 and 2025A03J3193). Introduction

Liver cirrhosis is a global health challenge, responsible for ~1.47 million deaths (2.4% of all deaths) in 2019, with the greatest burden occurring in Southeast Asia and the Western Pacific regions (1). Chronic hepatitis B virus (HBV) infection, affecting an estimated 296 million people worldwide, remains the leading cause of cirrhosis and hepatocellular carcinoma, accounting for ~331,000 cirrhosis-related deaths in 2019 and contributing to more than half of hepatocellular carcinoma cases in endemic areas (2). The most recent WHO estimates further indicate that HBV caused ~1.1 million deaths in 2022, mainly attributable to cirrhosis and hepatocellular carcinoma (3). Pathologically, HBV-associated cirrhosis is characterized by progressive fibrosis, distortion of hepatic architecture and sustained infiltration of diverse immune cell populations, including neutrophils, hepatic macrophages, T and B lymphocytes and natural killer cells, accompanied by a pro-inflammatory cytokine milieu rich in IL-1, IL-6, IL-17, IL-22, IL-35, TGF-β and TNF-α (4,5). Persistent hepatic inflammation promotes stellate cell activation and extracellular matrix deposition, perpetuating fibrogenesis and facilitating the transition to decompensated disease (6).

Gut-derived microbiota and their metabolites, together with nutrients and other signals, reach the liver via the portal vein, a process referred to as the gut-liver axis (7,8). Inflammatory cytokines and immune responses mediated by infiltrating cells are key contributors to the initiation and progression of liver fibrosis (9). In recent years, growing attention (10-12) has been directed toward the gut microbiota as a key regulator of liver physiology, particularly via the gut-liver axis. These complex microbial communities regulate both physiological and immunological functions of the host, influencing not only local intestinal processes but also systemic responses. Numerous microbiome-wide association studies have demonstrated a link between gut microbial dysbiosis and chronic diseases, including metabolic syndrome, inflammatory bowel disease and liver pathologies (13,14). Microbiota-derived metabolites and pathogen-associated molecular patterns directly influence hepatic immune responses and metabolic processes. In liver diseases such as non-alcoholic fatty liver disease (NAFLD), alcoholic liver disease and cirrhosis, consistent shifts in microbial composition have been documented (15,16). Notably, in cirrhosis, enrichment of taxa such as Fusobacterium, Veillonella and members of the Enterobacteriaceae family is associated with heightened systemic inflammation and greater disease severity, with several studies also indicating that these changes are more pronounced in decompensated patients (17,18).

Mechanistic studies have begun to clarify how microbial alterations influence liver health (7,19). The gut microbiota produces a broad repertoire of bioactive metabolites, including short-chain fatty acids (SCFAs), lipopolysaccharides (LPS), bile acids, choline derivatives, indole compounds, vitamins, lipids and niacin, which that regulate hepatic immune signaling and metabolic balance (19,20). Among these, SCFAs such as butyrate, acetate and propionate are particularly notable for their ability to strengthen epithelial tight junctions, enhance mucosal barrier integrity, suppress intestinal inflammation and limit overgrowth of pathogenic bacteria, in part via activation of free FA receptors 2 and 3(20). In experimental NAFLD models, enrichment of SCFA-producing taxa is associated with reduced hepatic lipid accumulation and attenuation of inflammatory responses (21,22). Other microbial products such as bile acids, tryptophan metabolites and LPS further modulate macrophage polarization, antimicrobial peptide production and fibrotic remodeling through receptors such as farnesoid X Receptor), TGR5(Takeda G-protein coupled receptor 5) and AhR(Aryl Hydrocarbon receptor), thereby linking gut dysbiosis to the pathophysiology of both cirrhosis and hepatocellular carcinoma (8,23,24).

In parallel with these metabolic and immunomodulatory functions, the gut microbiota is key for preserving intestinal homeostasis. It achieves this by maintaining the integrity of the mucus layer, sustaining the expression and spatial organization of tight junction proteins and coordinating mucosal immune responses. In cirrhosis, this equilibrium is disrupted, characterized by diminished tight junction protein expression, increased intestinal permeability and translocation of bacterial products, which collectively exacerbate hepatic inflammation, accelerate fibrogenesis and foster conditions that facilitate pathogenic biofilm formation, aberrant immune activation and chronic inflammation (25-27). Histopathological analyses of cirrhotic livers typically demonstrate dense infiltration by neutrophils, macrophages, T and B lymphocytes and dendritic cells, indicative of a sustained pro-inflammatory microenvironment (28,29). Within this immune landscape, CD4+ T helper (Th) cell subsets, including Th1, Th2 and Th17, and regulatory T cells serve a central role in orchestrating immune responses: They regulate CD8+ T cell expansion, promote B cell activation and modulate multiple immune effectors throughout disease progression (30,31). Although evidence links gut microbial dysbiosis to immune activation in cirrhosis, most studies are observational, and the precise mechanistic interplay between microbiota alterations, systemic inflammation and barrier dysfunction, particularly in HBV-associated cirrhosis, remains to be elucidated (32-34).

The present study aimed to systematically characterize the composition, diversity and predicted functions of the gut microbiota in patients with HBV-associated liver cirrhosis. By integrating microbial profiling with histological assessment of immune infiltration and intestinal barrier integrity, the present study aimed to elucidate the mechanistic underpinnings of the gut-liver axis in cirrhosis progression and provide a basis for microbiome-based diagnostic and therapeutic strategies.

 Materials and methods <sec> <title>Study population and sample collection

A total of 31 individuals with HBV-associated liver cirrhosis (21 male, 10 female; median age, 48 years; age range, 28-65 years) were enrolled between April 2023 and April 2024, before receiving any therapeutic intervention. Inclusion criteria were as follows: age between 18 and 70 years; a confirmed diagnosis of liver cirrhosis based on histology or imaging as described above; chronic HBV infection; no prior receipt of antiviral therapy for HBV. Exclusion criteria included: hepatocellular carcinoma; human immunodeficiency virus infection; pregnancy or severe cardiac; pulmonary; renal diseases. Cirrhosis was diagnosed by liver biopsy or by concordant findings from at least two imaging modalities (ultrasound, computed tomography, or magnetic resonance imaging). Disease severity was assessed using the Child-Pugh classification (35), which evaluates serum total bilirubin and albumin, prothrombin time, ascites and hepatic encephalopathy, categorizing patients as class A (5-6 points), B (7-9 points) or C (≥10 points). The control group included 15 healthy volunteers (8 male, 7 female; median age, 46 years; age range, 30-58 years) with no history of physical or psychological disorder, confirmed through annual comprehensive health evaluations including blood, urine and fecal analyses, liver function and biochemical tests, hepatitis virus markers, chest radiography and abdominal ultrasound. All participants were recruited from the Third Affiliated Hospital of Sun Yat-Sen University (Guangzhou, China).

Fecal sample collection was performed using a TinyGene fecal collection box according to the manufacturer's instructions. Boxes were placed on ice and stored at -80˚C before further analysis.

A total of six normal liver tissue sections were from para-hemangioma sites of patients with hepatic hemangioma without hepatitis (three male, three female; median age, 45 years; age range, 32-60 years). Paired samples of liver cirrhosis were obtained from six separate patients with HBV-infected liver cirrhosis during operations (four male, 2 female; median age, 48 years; age range, 30-65 years) before any therapeutic intervention. Colonic mucosal specimens of 10 patients with untreated liver cirrhosis (6 male, 4 female; median age, 47 years; age range, 27-63 years) and 10 healthy volunteers (5 male, 5 female; median age, 45 years; age range, 27-57 years) were obtained from the Endoscopic Center of the Third Affiliated Hospital of Sun Yat-Sen University. All tissues were verified by histopathology. The acquisition of these tissues was approved by the Clinical Research Ethics Committee of the Third Affiliated Hospital of Sun Yat-Sen University (approval no. RG2023-033-01).

 16S rRNA sequencing

The 16S rRNA gene was amplified using primers as follows: Forward, 5'-GTGCCAGCMGCCGCGGTAA-3' and reverse, 5'-CCGTCAATTCMTTTGAGTTT-3' targeting the V5-V6 hyper-variable regions (M were degenerate bases, representing A or C) and sequenced using the Illumina, Inc. platform following the manufacturer's protocols. The library was constructed by using the two-step PCR amplification method with the following thermocycling conditions: Initial preamplification stage at 94˚C for 2 min and then 22 cycles at 94˚C for 30 sec, 55˚C for 30 sec, and 72˚C for 30 sec. The second step preamplification stage at 94˚C for 2 min and then 8 cycles at 94˚C for 30 sec, 55˚C for 30 sec, and 72˚C for 30 sec. QIAamp DNA Stool Mini Kit (51604, QIAGEN) and Phusion™ High-Fidelity DNA Polymerase (M0530L, New England Biolabs were used. The quality and integrity of the extracted DNA were verified using agarose gel electrophoresis and a Bioanalyzer 2100 (Agilent Technologies). Sequencing libraries were quantified using a Qubit fluorometer (Thermo Fisher Scientific) and the final loading concentration was adjusted to 4 nM. Paired-end sequencing (2x300 bp) was performed on an Illumina MiSeq platform using the MiSeq Reagent Kit v3 (600-cycl, MS-102-300, Illumin). Raw reads were processed using Trimmomatic v0.39 (usadellab.org/cms/?page=trimmomatic), FLASH v1.2.11 (ccb.jhu.edu/software/FLASH/), and Mothur v1.39.5 (mothur.org/). After demultiplexing, dereplication, and filtering, operational taxonomic units (OTUs) were clustered at 97% similarity using UCLUST v1.2.22q (drive5.com/usearch/) against the SILVA v128 (arb-silva.de/) and Greengenes v13_8 databases (greengenes.secondgenome.com). α-diversity (Chao1, ACE, Shannon, Simpson) was calculated using Mothur v1.39.5 and QIIME v1.9.1 (qiime.org/), while β-diversity (Jaccard, unweighted UniFrac, weighted UniFrac) was assessed and visualized by PCoA with FastTree v2.1.3 (microbesonline.org/fasttree/). Differentially abundant taxa were identified using MetaStats (metastats.cbcb.umd.edu/), and LEfSe (huttenhower.sph.harvard.edu/lefse/) was used to detect taxa differing significantly between groups. β-diversity clustering was evaluated by analysis of similarity (ANOSIM) and correlations between distance matrices were examined with the Mantel test.

 Functional metagenome prediction

The USEARCH v9.2.64 global alignment command (drive5.com/usearch/) was used to capture OTU representative sequences from the Greengenes database v13_8 (greengenes.secondgenome.com). Functional metagenome reconstruction was then performed using PICRUSt v1.1.4 (picrust.github.io/picrust/). The predicted metagenome functions were annotated against the Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology (kegg.jp/).

 Histological staining

Hematoxylin-eosin (H&E), Sirius red, immunohistochemical and immunofluorescence staining were performed as previously described (36-38). The cell index was determined by dividing the number of histological staining signal-positive cells by the total number of cells in ≥20 randomly selected fields of view (magnification, x200). The antibodies were as follows: Anti-myeloperoxidase (MPO; cat. no. A1374, Abclonal), -CD4 (cat. no. sc-19641), -CD19 (cat. no. sc-19650; both Santa Cruz Biotechnology, Inc.), -CD68 (cat. no. ab31630), -α-smooth muscle actin (cat. no. ab5694; both Abcam), -claudin-1 (cat. no. 13255S), -zonula occludens-1 (ZO-1; cat. no. 8193T) and -E-cadherin (cat. no. 14472S; all Cell Signaling Technology, Inc.).

 ELISA

DAO and endotoxin levels from peripheral superficial vein blood were examined with ELISA kits (cat. nos. JL-T0829 and JL52002D, respectively; both J&L Biological) to estimate intestinal permeability and bacterial translocation according to the manufacturer's instructions.

 Statistical analysis

Data were analyzed using R software (version 3.4.1) and GraphPad Prism 6 (Dotmatics) software, including richness estimators, the Ace, Chao and Shannon index, a diversity estimator and rank dissimilarity and abundance distribution. Microbiome compositional dissimilarity was represented by PCoA plots, and quantified by unweighted or weighted UniFrac distance values. The significant separation of the microbiome composition was determined by ANOSIM and the significance differences in α and β diversity and taxonomy between groups were analyzed using Wilcox test. Continuous data are expressed as the mean ± SEM of ≥3 independent experimental repeats and analyzed by Student's two-tailed paired t-test or one- or two-way ANOVA followed by Bonferroni correction as described previously (39). P<0.05 was considered to indicate a statistically significant difference.

 Results <sec> <title>Gut microbiota profile differs between healthy volunteers and patients with liver cirrhosis

The present study compared the gut microbiota of healthy volunteers with that of patients with liver cirrhosis using Illumina MiSeq high-throughput sequencing of the 16S rRNA gene. In total, ~1,466,285 sequence reads of 16S rRNA genes, with an average length of ~410 bp, and 432 OTUs were obtained after sequencing and quality filtering (Fig. 1A). On average, healthy volunteers had more OTUs than patients with liver cirrhosis (371 vs. 362 OTUs, respectively; 301 core OTUs were shared). The average number of reads was not significantly different between healthy and cirrhosis group (31,643 vs. 31,988 reads, respectively).

To evaluate the alterations in the microbiota structure between healthy volunteers and patients with liver cirrhosis, α diversity was measured. Patients with liver cirrhosis had notably decreased microbial species richness and evenness in comparison with volunteers, based on the Chao and Shannon index and OTU rank abundance analysis (Fig. 1A). Furthermore, rank dissimilarity revealed that the between-group difference was greater than the within-group difference (Fig. 1B), and the Chao and Shannon indices analyzed using the Wilcoxon test showed that patients with liver cirrhosis had significantly lower gut microbial diversity than healthy volunteers (Fig. 1B). β diversity based on OTUs or phylogenetic analysis was calculated using Jaccard and unweighted and weighted UniFrac phylogenetic distance matrices; microbial composition of patients with liver cirrhosis was different from that of healthy volunteers (Fig. 1C). Core bacterial genus analysis using a heatmap demonstrated that the two groups had similar microbiota structures or communities, but different richness and abundance (Fig. 2A). The relative bacterial community richness and abundance at the family and genus levels were similar between groups (Fig. 2B and C).

LEfSe was conducted to determine the most relevant microbial taxa responsible for the differences between the groups (Fig. 3A). This analysis identified 29 taxa that were differentially abundant between the two groups. The microbiota of patients with liver cirrhosis was enriched in Fusobacterium (genus), Veillonellaceae (family), Lactobacillales (family), Negativicutes (class), Gammaproteobacteria (class), and Enterobacteriaceae (family), whereas healthy the microbiota of healthy volunteers was enriched in Clostridiales (order), Ruminococcaceae (family), Bacteroides (species), Subdoligranulum (genus) and Subdoligranulum (genus; Fig. 3A and B). Moreover, the differentially abundant features of the microbial taxa at the genus level verified that the abundance of Fusobacterium, Megamonas, Streptococcus, Lachnoclostridium, Veillonella and other bacteria was increased in the fecal samples of patients with liver cirrhosis (Fig. 4A).

Based on the differences in community richness and abundance, metagenome functional content based on the 16S rRNA gene sequences was predicted using PICRUSt. Predicted KEGG orthology pathways significantly enriched in liver cirrhosis included ‘starch and sucrose metabolism’, ‘butanoate metabolism’, ‘fructose and mannose metabolism’, ‘propanoate metabolism’ and ‘phosphotransferase system (PTS)’, indicating that these metabolic pathways participated in the progression of liver cirrhosis (Fig. 4B). Moreover, to verify the most relevant functional pathways based on the microbial differences between healthy volunteers and patients with liver cirrhosis, LEfSe analysis was performed. Functional composition of the total gut microbiota in patients with liver cirrhosis was primarily associated with ‘phosphotransferase system (PTS)’ and ‘membrane transport’ involved in environmental information processing, in contrast to ‘amino acid metabolism’ and ‘energy metabolism’ functions enriched in healthy volunteers (Fig. 5A-C). Collectively, these data demonstrated the gut microbiota profile differs between healthy volunteers and patients with liver cirrhosis, and that a specific microbial community, diversity, and associated metagenome function are present in those with liver cirrhosis.

 Gut microbiota of cirrhotic patients influences the host immune response and the gut barrier

The bacterial species with increased abundance in liver cirrhosis contribute to environmental information and metabolic pathway components, which may instigate inflammation of the host (17). Moreover, the gut microbiota participates in the preservation of tolerance and immunity of mucosal surfaces by regulating organic inflammatory responses (40). Based on these findings, the colonic mucosal specimens from patients with liver cirrhosis and healthy volunteers were analyzed, which demonstrated increased infiltration of inflammatory cells, including T lymphocytes (CD4), B lymphocytes (CD19), macrophages (CD68) and neutrophils (MPO), in the colonic tissues of patients with liver cirrhosis. However, there was no notable histological architectural alterations between the two groups based on H&E staining (Fig. 6A and B). As expected, upregulated T and B lymphocyte, macrophage and neutrophil infiltration, as well as excess collagen deposition, was found in the liver tissues of cirrhotic patients compared with those of healthy volunteers (Fig. 6C and D). On this basis, the present study investigated how gut microbial changes relate to barrier dysfunction and inflammatory responses in cirrhosis.

The functional composition of the total gut microbiota in patients with liver cirrhosis primarily involved ‘phosphotransferase system (PTS)’ and ‘membrane transport’. Changes in the gut microbiota modulate systemic microbe-derived metabolite levels by altering intestinal permeability and the gut barrier, especially tight junctions between epithelial cells (16). Claudin-1, ZO-1 and E-cadherin were downregulated in colonic samples from patients with cirrhosis whose liver tissues showed excess collagen deposition by Sirius red staining (Fig. 7A-C). Intestinal permeability, based on blood DAO determination, was significantly increased, and blood endotoxin detection showed enhanced bacterial translocation analysis in cirrhotic liver sections (Fig. 7D). In addition, the blood DAO and endotoxin levels showed a positive correlation with collagen deposition, as indicated by Sirius red staining of the liver tissue (Fig. 7E). The results demonstrated that the gut microbiota influences colonic and hepatic immune responses, intestinal permeability and the gut barrier, which would contribute to the progression of liver cirrhosis (Fig. 7F).

 Discussion

The gut microbiome serves a key role in immune development and function in the host, and in determining the host metabolic state. An increasing number of studies have suggested that the gut-derived microbiota and their components, metabolites, nutrients and other signals can be delivered to the liver via the portal vein circulation to serve as a bioreactor for autonomous metabolic and immunological regulation and regulate responses within the host environment (8,23,24). Here, patients with HBV-associated cirrhosis exhibit distinct gut microbial profiles compared with healthy individuals, characterized by decreased diversity, enrichment of pro-inflammatory taxa, functional shifts toward environmental information processing pathways, compromised intestinal barrier function and marked hepatic immune cell infiltration.

By comparing the gut microbiota between healthy volunteers and patients with liver cirrhosis using high-throughput sequencing of the 16S rRNA gene, the present study demonstrated that patients with liver cirrhosis had decreased microbial species richness, evenness, and diversity, although they had similar microbial structures and communities according to core bacterial genus analysis. This is supported by several studies (41,42) indicating a disordered gut microbial community and decreased diversity and species richness associated with cirrhosis. Decreased microbial diversity is now recognized as a feature of disease states, including inflammatory disorder, colorectal cancer, and gastric carcinoma (43-46). Furthermore, LEfSe analysis showed that the gut microbiota of patients with liver cirrhosis was enriched in Fusobacterium, Veillonellaceae, Lactobacillales, Negativicutes, Gammaproteobacteria, Enterobacteriaceae, whereas the proportion of phylum Bacteroides, Clostridiales, Ruminococcaceae, and Subdoligranulum was decreased compared with that of the healthy volunteers. These results align with a previous study that observed a marked loss of Bacteroides and significant increases in Veillonella, Enterobacteriaceae and Fusobacterium abundance in cirrhosis (47). This suggest that dysbiosis, or an unfavorable change in the composition of the microbiome in liver cirrhosis, is central to the pathophysiology of the onset, progression and development of complications of liver cirrhosis. Nonetheless, inconsistencies remain; for example, Chen et al (47) reported decreased Bacteroidetes and increased Proteobacteria and Fusobacteria, whereas Sarangi et al (48) observed no significant differences in microbial abundance. The differences in findings emphasize the need for more research to clarify the specific roles of microbial taxa in cirrhosis progression and treatment.

To explore functional consequences, KEGG orthology analysis was performed on metagenomic sequencing data and found that the total microbiota of patients with liver cirrhosis was predominantly enriched in ‘phosphotransferase system (PTS)’ and ‘membrane transport’, pathways involved in environmental information processing, whereas the microbiota of healthy controls showed enrichment in ‘amino acid metabolism’ and ‘energy metabolism’. Consistent with the present data, a previous study also reported enhanced transport- and metabolism-associated pathways, along with a marked loss of cell cycle-associated gene functions, in cirrhotic patients (7,47). Notably, the depletion of SCFA-producing taxa, such as Faecalibacterium, Eubacterium hallii, Ruminococcus and Agathobacter, has also been observed in cirrhotic patients (49). These butyrate-producing bacteria are key suppliers of energy for colonocytes and contribute to maintaining mucosal integrity. Their loss may compromise epithelial energy metabolism, attenuate butyrate-mediated anti-inflammatory signaling and disrupt the regulation of immune homeostasis. This depletion may aggravate the decrease in tight junction proteins and the increased intestinal permeability, thereby weakening barrier function and facilitating microbial translocation to the liver (22,40). These findings highlight the association between the gut microbiota and host metabolism in liver cirrhosis, with the microbial balance shifted toward a dysbiosis during the process of liver cirrhosis.

The activation of inflammatory cells to produce inflammatory cytokines and components is a key contributor to the initiation and development of liver cirrhosis (28,29). Increased T and B lymphocyte, macrophage and neutrophil infiltration was detected in patients with liver cirrhosis compared with healthy volunteers, and this was accompanied by excess collagen deposition in liver tissue. These data indicated that various inflammatory cells and responses are affected by gut-derived microbiota, and their components, metabolites or signals participate in the initiation and development of liver fibrosis.

The dysbiotic microbial community associated with liver cirrhosis is essential for the development and regulation of the immune and metabolism systems of the host (7,19,20). Changes in the gut microbiota modulate systemic microbe-derived metabolite levels or signals by altering intestinal permeability and the gut barrier, thus contributing to disease development (23).

A critical mechanistic link between the dysbiotic microbial community and the immune and metabolic systems of the host is the structural compromise of the intestinal epithelial barrier, which relies on tight junction proteins such as claudin-1 and ZO-1 and the adherens junction protein E-cadherin. To identify potential associations between tight junctions in colonic epithelial cells and microbial dysbiosis, the present study analyzed colonic sections and found that claudin-1, ZO-1 and E-cadherin levels were suppressed in colonic samples from cirrhotic patients; this was associated with enhanced intestinal permeability and bacterial translocation, suggesting that the tight junctions between colonic epithelial cells were damaged during liver fibrogenesis. In radiation-induced enteritis, gut dysbiosis disrupts the localization of claudin-1, occludin and ZO-1, weakening epithelial cohesion (50). Therapeutic modulation of the microbiota can mitigate such injury; for example, Yu-Ping-Feng-San (a traditional Chinese medicine decoction) treatment restores ZO-1, occludin and claudin-1 expression in LPS-induced barrier damage while decreasing inflammatory responses (51). At the molecular level, claudin-1 expression is regulated via the Piezo1/ROCK1/2 pathway, whereby Piezo1 activation by mechanical or inflammatory cues decreases claudin-1 protein expression and thereby impairs junctional integrity (52). Similarly, loss of SLC26A3 results in downregulation of ZO-1, occludin and E-cadherin alongside microbial imbalance, underscoring the reciprocal association between junctional protein expression and microbiota composition (53). In metabolic liver diseases such as NAFLD and NASH, breakdown of tight junctions allows endotoxin influx to the liver, promoting inflammatory and fibrotic changes (54). These data highlight that gut barrier impairment, mediated by altered junctional proteins in the context of dysbiosis, is a key driver of microbial translocation and hepatic injury in cirrhosis.

While the present findings provide insights into the gut microbiota-immune-barrier axis in HBV-associated cirrhosis, several limitations should be noted. First, the cross-sectional design precludes causal inference between microbiota dysregulation and inflammation or barrier dysfunction, and the contribution of HBV infection cannot be excluded; interventional approaches such as probiotics, fecal microbiota transplantation or other microbiota-targeted strategies are needed to test whether restoring microbial balance can ameliorate these changes. Second, the sample size may have limited the detection of subtle associations, and data on diet, medication and antiviral therapy, important microbiome modulators, were incomplete; these should be collected in future longitudinal and interventional studies. Finally, functional predictions based on 16S rRNA sequencing lack the resolution of shotgun metagenomics, metatranscriptomics or targeted metabolomics, which should be integrated to define microbiota-host interactions in HBV-related cirrhosis. To address these issues, future studies should adopt longitudinal designs with larger and well-characterized cohorts, integrate clinical and dietary information with multi-omics approaches, and evaluate interventional strategies such as probiotic or prebiotic supplementation, dietary modulation and fecal microbiota transplantation to determine whether restoring microbial balance can mitigate inflammation, reinforce barrier function and slow disease progression.

In conclusion, the gut microbiota profile in patients with HBV-associated liver cirrhosis differs markedly from that of healthy individuals, showing enrichment of taxa such as Fusobacterium, Veillonella and members of the Enterobacteriaceae family, alongside depletion of beneficial butyrate-producing genera including Faecalibacterium, Ruminococcus and Agathobacter. These compositional shifts, together with decreased overall diversity and altered functional potential, particularly enrichment in ‘phosphotransferase system (PTS)’ and ‘membrane transport’ and depletion of ‘amino acid metabolism’ and ‘energy metabolism’, are closely associated with impaired colonic and hepatic immune responses, increased intestinal permeability and compromised gut barrier integrity. Gut microbiota dysbiosis contributes to the pathophysiology of HBV-associated cirrhosis. Understanding these microbial alterations may provide a basis for microbiota-targeted strategies to mitigate hepatic inflammation and preserve barrier function in affected patients. Future longitudinal and interventional studies are warranted to establish causality and evaluate the therapeutic potential of microbiota-targeted interventions in HBV-associated cirrhosis.

 Acknowledgements

Not applicable.

 Availability of data and materials

The data generated in the present study may be found in the ScienceDB under accession number 31253.11.sciencedb.28999 or at the following URL: doi.org/10.57760/sciencedb.28999.

 Authors' contributions

KX and YZ designed the methodology and analyzed data. KX and YZ confirm the authenticity of all the raw data. ShT, XO and JL designed the methodology. SiT conceived the study and wrote and edited the manuscript. All authors have read and approved the final manuscript.

 Ethics approval and consent to participate

Informed consent was obtained from all participants before the initiation of the study. The present study protocol was approved by the Institute Research Ethics Committee of the Third Affiliated Hospitals of Sun Yat-sen University (Guangzhou, China; approval no. RG2023-033-01).

 Patient consent for publication

Not applicable.

 Competing interests

The authors declare that they have no competing interests.

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Characteristics of the gut microbiota in healthy volunteers and patients with liver cirrhosis. (A) Rarefaction (Chao and Shannon index) and rank abundance distribution curves, based on the 16S rRNA gene sequencing of fecal samples from healthy volunteers and patients with liver cirrhosis. (B) Rank dissimilarity revealed that the between-group difference was greater than the within-group difference. Chao and Shannon index measures of diversity suggested that patients with liver cirrhosis had significantly decreased microbial index compared with healthy volunteers. (C) PC analysis plots of β index (based on OTU, left) and unweighted (middle) and weighted UniFrac distances (right). PC, principal component; OTU, operational taxonomic unit; ANOSIM, analysis of similarity.

Bacterial community structures. (A) Heatmap of the core genera in healthy volunteers and patients with cirrhosis. (B) Relative abundance at the family level. (C) Relative abundance at the genus level in terms of total effective bacterial sequences.

Microbial taxa composition in healthy volunteers and patients with liver cirrhosis. (A) Cladogram of the fecal microbiota taxa associated with healthy volunteers and patients with liver cirrhosis. (B) Association of specific microbiota taxa with the healthy and liver cirrhosis groups based on LDA effect size. LDA, linear discriminant analysis.

Taxonomic and functional classification of microbiota between healthy volunteers and patients with liver cirrhosis. (A) Differential abundance of fecal microbiota genera between healthy volunteers and patients with liver cirrhosis. (B) Functional classification differences of gut microbiota determined by Kyoto Encyclopedia of Genes and Genomes analysis of healthy volunteers and patients with liver cirrhosis. *P<0.05; **P<0.01; ***P<0.001 vs. healthy.

Gut microbiota in liver cirrhosis is associated with environmental information processing. (A) Cladogram representation of the gut microbiota functional classification using the KEGG orthology revealed that liver cirrhosis was associated with ‘membrane transport’ and ‘phosphotransferase system (PTS)’ of environmental information processing. (B) Association between environmental information processing and gut microbiota of liver cirrhosis using LDA effect size. (C) Functional classification differences in the gut microbiota between healthy volunteers and cirrhotic patients. KEGG, Kyoto Encyclopedia of Genes and Genome; LDA, linear discriminant analysis; Class B/Z, internal confidence level classification labels.

Gut microbiota of patients with cirrhosis participates in the regulation of colonic and hepatic immune response. (A) Colonoscopic images and H&E and related inflammatory cell staining, including T lymphocytes (CD4), B lymphocytes (CD19), macrophages (CD68) and neutrophils (MPO) of the colon mucosa of healthy volunteers and patients with liver cirrhosis. (B) Cell indices were analyzed using histopathological staining. (C) H&E and (D) α-SMA, CD4, CD19, CD68 and MPO histopathological staining were performed on liver sections of healthy volunteers and patients with liver cirrhosis. *P<0.05 vs. healthy. H&E, hematoxylin-eosin staining; MPO, myeloperoxidase; SMA, smooth muscle actin.

Gut microbiota from patients with liver cirrhosis influences the gut barrier and intestinal permeability. (A) Colonoscopic images and histopathological staining of claudin-1, ZO-1 and E-cadherin in healthy volunteers and patients with liver cirrhosis. Collagen deposition was determined by Sirius red staining of liver tissue sections. (B) Claudin-1 and ZO-1. (C) E-cadherin and Sirius red staining. (D) Intestinal permeability analysis based on blood DAO detection and bacterial translocation analysis based on blood endotoxin detection were performed using ELISA. (E) Positive correlation between the blood DAO levels and collagen deposition (determined by Sirius red staining), endotoxin levels and collagen deposition. (F) Schematic diagram of gut microbiota involves in liver cirrhosis. *P<0.05 vs. healthy. ZO-1, zonula occludens-1; DAO, diamine oxidase.