Editor’s note: The human gastrointestinal tract hosts trillions of microbes, including bacteria, fungi, and viruses, which play essential roles in physiological functions and disease mechanisms. Extensive research has demonstrated that gut microbiota significantly influence the progression of cirrhosis. However, fungi, which are less abundant in the gut, have often been overlooked. A recent study published in Frontiers in Microbiology utilized 16S ribosomal RNA sequencing, internal transcribed spacer (ITS) sequencing, and untargeted metabolomics to reveal the characteristics of gut microbiota in cirrhotic patients. The study explored the composition and interactions of gut bacteria, fungi, and metabolites in these patients.The research included 75 participants: 45 with decompensated cirrhosis (LC group) and 30 healthy controls (C group). Patients in the LC group exhibited elevated serum levels of ALT, TBIL, PT, and INR, while WBC, HB, PLT, ALB, and PTA levels were reduced (P<0.05). The median CTP score was 5, and the MELD score was 9. The underlying causes of cirrhosis included HBV/HCV infection (25 cases), alcoholic liver disease (ALD, 10 cases), metabolic-associated fatty liver disease (MAFLD, 5 cases), and autoimmune hepatitis (AIH, 5 cases).
Characteristics of the Gut Microbiome and Mycobiome
1. Gut Bacteria A total of 10,274,244 high-quality 16S rRNA sequences were obtained from fecal samples, yielding 6,861 amplicon sequence variants (ASVs). The alpha diversity, based on the Shannon index, was significantly lower in the LC group compared to the C group (P<0.01). Beta diversity analysis using Bray-Curtis distances (PCoA) indicated significant differences in gut bacterial community structure between the LC and C groups (P=0.001).
Both groups’ gut microbiota were predominantly composed of the phylum Firmicutes. At the genus level, Faecalibacterium, Blautia, and Bifidobacterium had the highest average relative abundances. Further analysis identified significant differences in the relative abundance of specific bacterial genera. In the LC group, Streptococcus, Akkermansia, Lactobacillus, and Pseudomonas were significantly enriched, whereas Blautia, Anaerobutyricum, Gemmiger, Ruminococcus, and Dorea were notably decreased.
2. Gut Fungi A total of 9,594,331 high-quality ITS rRNA sequences were obtained, resulting in 901 ASVs. The alpha diversity of gut fungi in the LC group was also significantly lower than in the C group (P<0.01). Beta diversity analysis (Bray-Curtis distances) showed notable differences in fungal community structure between the two groups (P=0.004).
The primary fungal phylum in both groups was Ascomycota. At the genus level, Saccharomyces, Candida, and Aspergillus were the most prevalent. In the LC group, Saccharomyces was significantly enriched, while Aspergillus, Penicillium, Auricularia, and Cladosporium were markedly reduced.
Characteristics of the Gut Metabolome
Using untargeted metabolomics, researchers detected 11,382 variables in fecal samples from the LC and C groups. The LC group had 727 enriched variables, while the C group had 814. The study identified 130 differential metabolites, with 68 enriched in the LC group and 62 in the C group. Notably enriched metabolites in the LC group included 5,6-dihydroxybergamottin, glycyrrhetinic acid, and bilirubin. These metabolites primarily participated in porphyrin and fatty acid metabolism pathways, with the porphyrin pathway significantly enriched in the LC group.
Effects of Endoscopic Therapy on Gut Microbiota and Metabolites
1. Changes in Bacteria and Fungi Analysis of pre- and post-treatment fecal samples from 15 LC patients who underwent endoscopic therapy showed no significant changes in the diversity or structure of gut bacteria and fungi. However, relative abundances of certain genera, such as Acinetobacter (increased) and Megamonas (decreased), showed changes. The fungal genus Cutaneotrichosporon was also reduced.
2. Changes in Metabolites Endoscopic therapy resulted in significant changes in metabolite composition. Nandrolone was enriched in the post-treatment group, while 15 metabolites were enriched in the pre-treatment group. The differential metabolites mainly participated in butyrate metabolism pathways.
Multi-Omics Integration and Diagnostic Model Development
Significant correlations were observed between clinical parameters (such as ALB, HGB, MELD, PLT) and gut bacteria, fungi, and metabolites in the LC group. Additionally, complex interaction networks were found among bacterial and fungal genera and enriched metabolites, with tighter connections between bacteria and metabolites.
The researchers developed a random forest model using 16S data, ITS data, metabolite data, clinical parameters, and their combinations to differentiate LC patients from healthy controls. A diagnostic model based on these features achieved an AUC of 0.938.
The study provides insights into the gut microbiota composition and its complex internal interactions in cirrhotic patients, offering a foundation for exploring the potential role of gut microbiota in cirrhosis.
