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. 2024 Oct 25:15:1449090.
doi: 10.3389/fmicb.2024.1449090. eCollection 2024.

Metagenome-based characterization of the gut bacteriome, mycobiome, and virome in patients with chronic hepatitis B-related liver fibrosis

Wenlin Chen #  1 , Fang Liang #  1 , Yue Zhang #  2 , Yuncheng Zhang  1 , Jinzhen Lv  1 , Xiande Jin  1 , Yun Ran  1 , Shenghui Li  2 , Wen Sun  3   4
Affiliations

Metagenome-based characterization of the gut bacteriome, mycobiome, and virome in patients with chronic hepatitis B-related liver fibrosis

Wenlin Chen et al. Front Microbiol. .

Abstract

Introduction: The gut microbiota is believed to be directly involved in the etiology and development of chronic liver diseases. However, the holistic characterization of the gut bacteriome, mycobiome, and virome in patients with chronic hepatitis B-related liver fibrosis (CHB-LF) remains unclear.

Methods: In this study, we analyzed the multi-kingdom gut microbiome (i.e., bacteriome, mycobiome, and virome) of 25 CHB-LF patients and 28 healthy individuals through whole-metagenome shotgun sequencing of their stool samples.

Results: We found that the gut bacteriome, mycobiome, and virome of CHB-LF patients were fundamentally altered, characterized by a panel of 110 differentially abundant bacterial species, 16 differential fungal species, and 90 differential viruses. The representative CHB-LF-enriched bacteria included members of Blautia_A (e.g., B. wexlerae, B. massiliensis, and B. obeum), Dorea (e.g., D. longicatena and D. formicigenerans), Streptococcus, Erysipelatoclostridium, while some species of Bacteroides (e.g., B. finegoldii and B. thetaiotaomicron), Faecalibacterium (mainly F. prausnitzii), and Bacteroides_A (e.g., B. plebeius_A and B. coprophilus) were depleted in patients. Fungi such as Malassezia spp. (e.g., M. japonica and M. sympodialis), Candida spp. (e.g., C. parapsilosis), and Mucor circinelloides were more abundant in CHB-LF patients, while Mucor irregularis, Phialophora verrucosa, Hortaea werneckii, and Aspergillus fumigatus were decreases. The CHB-LF-enriched viruses contained 18 Siphoviridae, 12 Myoviridae, and 1 Podoviridae viruses, while the control-enriched viruses included 16 Siphoviridae, 9 Myoviridae, 2 Quimbyviridae, and 1 Podoviridae_crAss-like members. Moreover, we revealed that the CHB-LF-associated gut multi-kingdom signatures were tightly interconnected, suggesting that they may act together on the disease. Finally, we showed that the microbial signatures were effective in discriminating the patients from healthy controls, suggesting the potential of gut microbiota in the prediction of CHB-LF and related diseases.

Discussion: In conclusion, our findings delineated the fecal bacteriome, mycobiome, and virome landscapes of the CHB-LF microbiota and provided biomarkers that will aid in future mechanistic and clinical intervention studies.

Keywords: chronic hepatitis B-related liver fibrosis; gut microbiome; gut mycobiome; gut virome; microbial dysbiosis; whole-metagenome sequencing.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Figures

Figure 1
Figure 1
Difference in gut bacteriome between CHB-LF patients and healthy controls. (A) Rarefaction analysis of the species richness (estimated by the observed number of species) on each group of samples. The number of species in different groups is calculated based on 30 replacements. (B) Boxplot shows the Shannon diversity index (left panel) and the Simpson index (right panel) of gut bacteriome that differ between two groups. (C) PCoA analysis of Bray-Curtis distance based on the composition of gut bacteriome, revealing the separations between CHB-LF patients and healthy individuals. (D) Composition of gut bacteriome at the genus level. (E) Boxplot shows the differential gut bacterial genera when compared between patients and controls. The significance level is calculated based on the Wilcon rank-sum test: *, q < 0.05; **, q < 0.01; ***, q < 0.001. (F) Volcano plot shows the fold change vs. q for all bacterial species. The X-axis shows the ratio of species abundance in patients compared with that in controls. The Y-axis shows the q (−log10 transformed) of the species. (G) Detailed information of 110 CHB-LF-associated species. Innermost circle, phylogenetic tree analysis of species based on their genome sequences. The colors in the tree indicate the phylum-level taxonomic assignment of the species. Medium circle: taxonomic assignment of the species at the family level. Outermost circle: barplot shows the fold changes of species abundance in patients compared with that in healthy subjects.
Figure 2
Figure 2
Difference in gut mycobiome between CHB-LF patients and healthy controls. (A) Rarefaction analysis of the number of observed species on each group of samples. The number of species in different groups is calculated based on 30 replacements. (B) Boxplot shows the Shannon diversity index (left panel) and the Simpson index (right panel) of gut mycobiome that differ between two groups. (C) PCoA analysis of Bray-Curtis distance based on the composition of gut mycobiome, revealing the separations between two groups. The location of samples (represented by nodes) in the first two principal coordinates is shown. Lines connect samples in the same group, and circles cover samples near the center of gravity for each group. (D) Composition of gut mycobiome at the genus level. (E) Boxplot shows the differential gut fungal species when compared between patients and controls. The significance level is calculated based on the Wilcon rank-sum test: *, q < 0.05; **, q < 0.01.
Figure 3
Figure 3
Characteristics of the gut virus catalogue and gut virome. (A,B) Pie plot shows the quality (A) and family-level taxonomic annotation (B) of the non-redundancy virus catalogue. (C) The bacterial host assignment of the non-redundancy virus catalogue. (D) Rarefaction curve analysis of the number of observed viruses on each group of samples. The number of viruses in different groups is calculated based on 30 replacements. (E) Boxplot shows the Shannon diversity index (left panel) and the Simpson index (right panel) of gut virome that differ among two groups. (F) PCoA analysis of Bray-Curtis distance based on the composition of gut virome, revealing the separations between two groups. (G) Composition of gut mycobiome at the family level. (H) Volcano plot shows the fold change vs. q for all viruses. The X-axis shows the ratio of viral abundance in patients compared with that in controls. The Y-axis shows the q (−log10 transformed) of the viruses. (I) Detailed information of 90 CHB-LF-associated viruses. Innermost circle, phylogenetic tree analysis of species based on their genome sequences. Medium circle: taxonomic assignment of the viruses at the family level. Outermost circle: bar plot shows the fold changes of viral abundance in patients compared with that in healthy subjects. (J) Genome structure of several viruses contained genes involving lipopolysaccharide biosynthesis and sulfur metabolism.
Figure 4
Figure 4
Correlation analysis among multi-kingdom microbial signatures. (A) Network showing the multi-kingdom microbial correlations within CHB-LF patients (upper panel) and healthy controls (bottle panel). (B) Sharing correlations between CHB-LF and control networks. Gut bacteria and viruses are colored based on their family-level taxonomic assignment. The microbial names are colored by their enrichment in CHB-LF patients (red) and healthy controls (green).
Figure 5
Figure 5
Classification of CHB-LF patients and healthy controls by gut multi-kingdom signatures. (A) ROC analysis for classification of disease status using the gut bacterial, fungal, and viral signatures. (B–D) The 20 most discriminant bacterial (B), fungal (C), and viral signatures (D) in the models for classifying patients and controls. The bar lengths indicate the importance of the microbes.
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References

    1. Almeida A., Nayfach S., Boland M., Strozzi F., Beracochea M., Shi Z. J., et al. . (2020). A unified catalog of 204,938 reference genomes from the human gut microbiome. Nat. Biotechnol. 39, 105–114. doi: 10.1038/s41587-020-0603-3 - DOI - PMC - PubMed
    1. Aykut B., Pushalkar S., Chen R., Li Q., Abengozar R., Kim J. I., et al. . (2019). The fungal mycobiome promotes pancreatic oncogenesis via activation of MBL. Nature 574, 264–267. doi: 10.1038/s41586-019-1608-2, PMID: - DOI - PMC - PubMed
    1. Bajaj J. S., Ridlon J. M., Hylemon P. B., Thacker L. R., Heuman D. M., Smith S., et al. . (2012). Linkage of gut microbiome with cognition in hepatic encephalopathy. Am. J. Physiol. Gastrointestinal Liver Physiol. 302, G168–G175. doi: 10.1152/ajpgi.00190.2011 - DOI - PMC - PubMed
    1. Bataller R., Brenner D. A. (2005). Liver fibrosis. J. Clin. Invest. 115, 209–218. doi: 10.1172/JCI24282, PMID: - DOI - PMC - PubMed
    1. Beghini F., McIver L. J., Blanco-Míguez A., Dubois L., Asnicar F., Maharjan S., et al. . (2021). Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. eLife 10:e65088. doi: 10.7554/eLife.65088, PMID: - DOI - PMC - PubMed

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by grant from the Shenzhen Science and Technology Plan Project (ID: JCYJ2018302150216419).

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