A metagenomic study of the gut microbiome in Behcet's disease - PubMed (original) (raw)

doi: 10.1186/s40168-018-0520-6.

Ni Zhang 1, Chunyan Wu 2, Xinyuan Zhang 3, Qingfeng Wang 1, Xinyue Huang 1, Liping Du 1, Qingfeng Cao 1, Jihong Tang 1, Chunjiang Zhou 1, Shengping Hou 1, Yue He 1, Qian Xu 2 4, Xiao Xiong 2, Aize Kijlstra 5, Nan Qin 2 6, Peizeng Yang 7

Affiliations

A metagenomic study of the gut microbiome in Behcet's disease

Zi Ye et al. Microbiome. 2018.

Abstract

Background: Behcet's disease (BD) is a recalcitrant, multisystemic inflammatory disease that can lead to irreversible blindness. Microbial agents have been considered to contribute to the pathogenesis of this disease, but the underlying mechanisms remain unclear. In this study, we investigated the association of gut microbiome composition with BD as well as its possible roles in the development of this disease.

Methods: Fecal and saliva samples were collected from 32 active BD patients and 74 healthy controls. DNA extracted from fecal samples was subjected to metagenomic analysis, whereas DNA extracted from saliva samples was subjected to 16S rRNA gene sequencing analysis. The results were used to compare the composition and biological function of the microbiome between patients and healthy controls. Lastly, transplantation of pooled fecal samples from active BD patients into B10RIII mice undergoing experimental autoimmune uveitis (EAU) was performed to determine the causal relationship between the gut microbiome and BD.

Results: Fecal samples from active BD patients were shown to be enriched in Bilophila spp., a sulfate-reducing bacteria (SRB) and several opportunistic pathogens (e.g., Parabacteroides spp. and Paraprevotella spp.) along with a lower level of butyrate-producing bacteria (BPB) Clostridium spp. and methanogens (Methanoculleus spp. Methanomethylophilus spp.). Analysis of microbial functions revealed that capsular polysaccharide transport system, oxidation-reduction process, type III, and type IV secretion systems were also increased in active BD patients. Network analysis showed that the BD-enriched SRB and opportunistic pathogens were positively correlated with each other, but they were negatively associated with the BPB and methanogens. Animal experiments revealed that fecal microbiota transplantation with feces from BD patients significantly exacerbated EAU activity and increased the production of inflammatory cytokines including IL-17 and IFN-γ.

Conclusions: Our findings revealed that BD is associated with considerable gut microbiome changes, which is corroborated by a mouse study of fecal microbiota transplants. A model explaining the association of the gut microbiome composition with BD pathogenesis is proposed.

Keywords: Behcet’s disease; Fecal microbiota transplant; Gut microbiome; Metagenomic analysis.

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Conflict of interest statement

All procedures followed the tenets of the Declaration of Helsinki and were approved by the Ethics Committee of Chongqing Medical University with written informed consent.

We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service, and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled, “A metagenomic study of the gut microbiome in Behcet’s disease”.

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

Figures

Fig. 1

Fig. 1

Phyla (a), genera (b), and species (c) showing significant differences in fecal metagenome profiles when comparing BD patients with healthy controls. Differentially abundant phylotypes were identified by Wilcoxon rank sum test (FDR < 0.1, corrected by the Benjamini and Hochberg for multiple comparisons). Only the top 5 phyla and top 10 genera are shown. The phylotypes enriched in healthy group are colored red. The relative abundance was shown by boxplot. Boxes represent the inter quartile ranges, lines inside the boxes denote medians, and ‘+’ denotes means

Fig. 2

Fig. 2

Linear discrimination analysis (LDA) effect size (LEfSe) analysis results comparing the BD and healthy groups. a Histogram of the LDA scores computed for genera differentially abundant between BD subjects and healthy controls. The LDA scores (log10) > 2 are listed. b SparCC network plot of co-abundance and co-exclusion correlations between differentially abundant SRB, BPB, methanogens, and opportunistic pathogens. Each node represents one species, and two nodes are linked if the correlation was significant (two-sided pseudo p ≤ 0.1 based on bootstrapping of 100 repetitions). Lines between nodes show positive correlations (solid lines) or negative correlations (dashed lines). The node size is proportional to the mean relative abundance of species in the enriched population. Nodes were colored as follows: orange, sulfate-reducing bacteria; purple, lactate-producing bacteria; blue, butyrate-producing bacteria; green, methanogens

Fig. 3

Fig. 3

MGSs analysis. a The heatmap of 25 ‘tracer’ genes abundance for each MGS were shown. Individuals are represented along the horizontal axis. Abundance of genes in rows is indicated by color gradient (white, not detected), and the enrichment significance is shown on the right with P value by Wilcoxon test. b The relative importance of each MGS in the predictive random forest model using the mean decreasing accuracy. c Relationship between the numbers of MGSs included in random forest model and the corresponding predictive performance (estimated by 10-fold cross-validation). d The ROC curve for the random forest model using 13 MGSs

Fig. 4

Fig. 4

Effect of transplantation of feces from BD patients on EAU. Pooled feces from active BD patients transferred to B10RIII mice by oral gavage. Pooled feces from healthy individuals and PBS were transferred to mice as control groups. EAU was induced by immunization with IRBP161–180. On day 14 after EAU induction, clinical and histological scores of BD patients’ feces-treated group (a and d), healthy’ feces-treated group (b and e), and PBS-treated group (c and f) were determined. Combined data in (g) for clinical score and (h) for histological score. Each point represents an individual eye. The horizontal bars denote the average scores of each group. The spleens were also removed from EAU mice on day 14 after induction. IFN-γ (i) and IL-17 (j) mRNA levels were evaluated by real-time PCR

Fig. 5

Fig. 5

Chart of possible mechanisms explaining the relation between gut microbiome composition and development of Behcet’s disease. a Dysbiosis of the gut microbiome might be caused via dietary intake in individuals carrying the susceptibility genes for BD. The dysbiosis of the gut microbiome in BD is characterized by enriched sulfate-reducing bacteria (SRB) and some opportunistic pathogens in association with depleted butyrate-producing bacteria (BPB) and methanogens. b Gut metabolism in BD shows an overwhelming presence of H2S and shortage of butyrate and methane. This abnormal environment can contribute to the intestinal epithelial barrier damage and facilitate effector molecules or pathogen-associated molecular pattern (PAMP) to invade the intestinal epithelial cells (IEC). c The PAMPs including PNG/LPS combine with their corresponding pattern recognition receptors (PRR) TLR2/TLR4 on IEC. This process leads to chronic inflammation involving hyperactivation of T helper 1 (TH1) and T helper 17 (TH17) cells in the gut. d The effector molecules or PAMP migrate to blood vessels through the hepatic circulation. Then, they recognize the receptors of TLR/TLR4 on vascular endothelial cells (VEC) and induce systemic vasculitis via the subsequent activation of TH1 and TH17 cells. e A damaged vascular endothelial barrier due to the systemic vasculitis. The effector molecules or PAMP can further migrate to organs or tissues such as the eye, joint, skin, oral, and genital mucosa though the damaged vascular endothelial barrier. Subsequently, the PAMP recognize the receptors TLR2/TLR4 in these organs or tissues, which result in various clinical manifestations of BD, such as uveitis, arthritis, skin lesions, oral, or genital ulcers. f Since oral ulcers (aphthosis) can be induced by both disturbances of the oral microbiome and dysbiosis of the gut microbiome, it presents as the most common clinical feature in BD

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