Dataset Information

Microbiome dysbiosis is associated with disease duration and increased inflammatory gene expression in systemic sclerosis skin.

ABSTRACT:

Background

Infectious agents have long been postulated to be disease triggers for systemic sclerosis (SSc), but a definitive link has not been found. Metagenomic analyses of high-throughput data allows for the unbiased identification of potential microbiome pathogens in skin biopsies of SSc patients and allows insight into the relationship with host gene expression.

Methods

We examined skin biopsies from a diverse cohort of 23 SSc patients (including lesional forearm and non-lesional back samples) by RNA-seq. Metagenomic filtering and annotation was performed using the Integrated Metagenomic Sequencing Analysis (IMSA). Associations between microbiome composition and gene expression were analyzed using single-sample gene set enrichment analysis (ssGSEA).

Results

We find the skin of SSc patients exhibits substantial changes in microbial composition relative to controls, characterized by sharp decreases in lipophilic taxa, such as Propionibacterium, combined with increases in a wide range of gram-negative taxa, including Burkholderia, Citrobacter, and Vibrio.

Conclusions

Microbiome dysbiosis is associated with disease duration and increased inflammatory gene expression. These data provide a comprehensive portrait of the SSc skin microbiome and its association with local gene expression, which mirrors the molecular changes in lesional skin.

SUBMITTER: Johnson ME

PROVIDER: S-EPMC6366065 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Publications

Microbiome dysbiosis is associated with disease duration and increased inflammatory gene expression in systemic sclerosis skin.

Johnson Michael E ME Franks Jennifer M JM Cai Guoshuai G Mehta Bhaven K BK Wood Tammara A TA Archambault Kimberly K Pioli Patricia A PA Simms Robert W RW Orzechowski Nicole N Arron Sarah S Whitfield Michael L ML

Arthritis research & therapy 20190206 1

<h4>Background</h4>Infectious agents have long been postulated to be disease triggers for systemic sclerosis (SSc), but a definitive link has not been found. Metagenomic analyses of high-throughput data allows for the unbiased identification of potential microbiome pathogens in skin biopsies of SSc patients and allows insight into the relationship with host gene expression.<h4>Methods</h4>We examined skin biopsies from a diverse cohort of 23 SSc patients (including lesional forearm and non-lesio ...[more]

PMID: 30728065

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Project description:ObjectiveTo examine the heterogeneity of global transcriptome patterns in systemic sclerosis (SSc) skin in a large sample of patients with SSc and control subjects.MethodsSkin biopsy specimens obtained from 61 patients enrolled in the Genetics versus Environment in Scleroderma Outcome Study (GENISOS) cohort and 36 unaffected control subjects with a similar demographic background were examined by Illumina HumanHT-12 bead arrays. Followup experiments using quantitative polymerase chain reaction and immunohistochemical analysis were also performed.ResultsWe identified 2,754 differentially expressed transcripts in SSc patients compared with controls. Clustering analysis revealed 2 prominent transcriptomes in SSc patients: the keratin and fibroinflammatory signatures. Higher keratin transcript scores were associated with shorter disease duration and interstitial lung disease, while higher fibroinflammatory scores were associated with diffuse cutaneous involvement, a higher skin score at the biopsy site, and a higher modified Rodnan skin thickness score. A subgroup of patients with significantly longer disease duration had a normal-like transcript pattern. Analysis of cell type-specific signature scores revealed remarkable heterogeneity across patients. Significantly higher scores were calculated for fibroblasts (72% of patients), microvascular cells (61%), macrophages (54%), and dendritic cells (DCs) (49%). The majority of samples with significantly higher fibroblast scores (35 of 44 [80%]) had significantly increased macrophage and/or DC scores. Further analysis and immunohistochemical staining indicated that the keratin signature was not a general marker of keratinocyte activation but was in fact associated with an activation pattern in hair and adnexal structures.ConclusionProminent fibroinflammatory and keratin signatures are present in SSc skin. Expression profiles of SSc skin show significant heterogeneity, and this finding might be useful for stratifying patients for targeted therapies or predicting the response to immunosuppression.

Project description:ObjectiveWe undertook this hypothesis-generating study to identify skin transcripts correlating with severity of interstitial lung disease (ILD) in systemic sclerosis (SSc).MethodsSkin biopsy samples from 59 patients enrolled in the Genetics versus Environment in Scleroderma Outcome Study (GENISOS) cohort or an open-label imatinib study (baseline visit) were examined by global gene expression analysis using Illumina HT-12 arrays. Skin transcripts correlating with concomitantly obtained forced vital capacity (FVC) values and the modified Rodnan skin thickness score (MRSS) were identified by quantitative trait analysis. Also, immunofluorescence staining for selected transcripts was performed in affected skin and lung tissue. Plasma levels of CCL2, soluble SELP, and soluble P-selectin glycoprotein ligand 1 (sPSGL-1) were examined in all patients enrolled in the GENISOS cohort (n = 266).ResultsEighty-two skin transcripts correlated significantly with FVC. This gene list distinguished patients with more severe ILD (FVC <70% predicted) in unsupervised hierarchical clustering analysis (P < 0.001). These genes included SELP, CCL2, and matrix metalloproteinase 3, which are involved in extravasation and adhesion of inflammatory cells. Among the FVC correlates, 8 genes (CCL2, HAPLN3, GPR4, ADCYAP1, WARS, CDC25B, PLP1, and STXBP6) also correlated with the MRSS. Immunofluorescence staining revealed that SELP and CCL2 were also overexpressed in affected skin and lung tissue from SSc patients compared to those from controls. Plasma levels of CCL2 and sPSGL-1 correlated with concomitantly obtained FVC values (r = -0.22, P = 0.001 and r = 0.17, P = 0.015, respectively). This relationship was independent of potential confounders (age, sex, ethnicity, smoking status, anti-topoisomerase I positivity, treatment with immunosuppressive agents, MRSS, disease type, and disease duration).ConclusionA limited number of skin transcripts including genes involved in extravasation and adhesion of inflammatory cells correlate with severity of ILD.

Project description:BackgroundThe microbiome alterations are associated with cancer growth and may influence the immune system and response to therapy. Particularly, the gut microbiome has been recently shown to modulate response to melanoma immunotherapy. However, the role of the skin microbiome has not been well explored in the skin tumour microenvironment and the link between the gut microbiome and skin microbiome has not been investigated in melanoma progression. Therefore, the aim of the present study was to examine associations between dysbiosis in the skin and gut microbiome and the melanoma growth using MeLiM porcine model of melanoma progression and spontaneous regression.ResultsParallel analysis of cutaneous microbiota and faecal microbiota of the same individuals was performed in 8 to 12 weeks old MeLiM piglets. The bacterial composition of samples was analysed by high throughput sequencing of the V4-V5 region of the 16S rRNA gene. A significant difference in microbiome diversity and richness between melanoma tissue and healthy skin and between the faecal microbiome of MeLiM piglets and control piglets were observed. Both Principal Coordinate Analysis and Non-metric multidimensional scaling revealed dissimilarities between different bacterial communities. Linear discriminant analysis effect size at the genus level determined different potential biomarkers in multiple bacterial communities. Lactobacillus, Clostridium sensu stricto 1 and Corynebacterium 1 were the most discriminately higher genera in the healthy skin microbiome, while Fusobacterium, Trueperella, Staphylococcus, Streptococcus and Bacteroides were discriminately abundant in melanoma tissue microbiome. Bacteroides, Fusobacterium and Escherichia-Shigella were associated with the faecal microbiota of MeLiM piglets. Potential functional pathways analysis based on the KEGG database indicated significant differences in the predicted profile metabolisms between the healthy skin microbiome and melanoma tissue microbiome. The faecal microbiome of MeLiM piglets was enriched by genes related to membrane transports pathways allowing for the increase of intestinal permeability and alteration of the intestinal mucosal barrier.ConclusionThe associations between melanoma progression and dysbiosis in the skin microbiome as well as dysbiosis in the gut microbiome were identified. Results provide promising information for further studies on the local skin and gut microbiome involvement in melanoma progression and may support the development of new therapeutic approaches.

Dataset Information

Microbiome dysbiosis is associated with disease duration and increased inflammatory gene expression in systemic sclerosis skin.

Background

Methods

Results

Conclusions

Publications

Microbiome dysbiosis is associated with disease duration and increased inflammatory gene expression in systemic sclerosis skin.

Similar Datasets

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