Dataset Information

Next Generation Sequencing Facilitates Quantitative Analysis of dermal Transcriptomes of Imiquimod (IMQ)-Induced Psoriasis-Like Dermatitis Treated by Xiao-Yin-Fang (XYF) Therapy

ABSTRACT: Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare dermal transcriptomes of control group (wild-type IMQ-untreated C57/BL6 mice), model group (wild-type IMQ-treated C57/BL6 mice) and XYF group (model group mice treated by XYF). Methods: Dermal mRNA profiles of control group, model group and XYF group mice were generated by deep sequencing. Total RNA samples were prepared from intact dermal ear sheets of mouse ear skin from two mice. Double-strand cDNA was generated from equal amounts of total RNA by following TruSeq8 RNA Library Prep Kit v2 (#RS-122-2001/2002, Illumina). The cDNA libraries were sequenced using Illumina Hi-seq2500. STAR software was utilized for sequence alignment between the preprocessing sequence and reference genome sequence of mice downloaded from the Ensembl database(Mus_musculus.GRCm38.90,ftp://ftp.ensembl.org/pub/release-90/gtf/mus_musculus/ Mus_musculus.GRCm38.90.chr.gtf.gz). Transcript assembly of mRNA sequencing data was performed by StringTie software. The expression levels for each of the genes were normalized to FPKM (fragments per kilobase of transcript per million fragments mapped). DESeq 2 was applied to conduct the analysis of differentially expressed genes (DEG). The cutoffs of DEG method were determined as the P value < = 0.05, the FDR value < = 0.05 and the Fold Change (FC) value > = 2. Results: Heatmap analysis of differentially expressed genes (DEG) revealed distinct transcriptomes between different groups, which displayed a partial reversal of pathological gene-expressing modifications by the treatment of XYF. Detailed comparison identified shared DEGs of opposite deviations between control group versus model group and model group versus XYF group. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis uncovered the dermis from disease-model group was greatly disturbed in cytokine-cytokine receptor interaction, chemokine signaling pathways, IL-17 signaling pathway, TNF signaling pathway, Wnt signaling pathway and PI3K-Akt signaling pathway. As for XYF therapy, several metabolic pathways, Calcium signaling, cAMP signaling pathway and cGMP-PKG signaling pathway were affected within the dermis. Further Gene Set Enrichment Analysis (GSEA) exposed multiple metabolic pathways, which involved ether lipid metabolism, alpha linolenic acid metabolism, arachidonic acid metabolism, linoleic acid metabolism, glycerophospholipid metabolism, glycosaminoglycan biosynthesis heparan sulfate, along with VEGF signaling and cell cycle were considerably suppressed in the dermal tissue when given XYF. Conclusions: XYF might regulate various inflammatory signaling, metabolic processes and microvascular formation to influence γδT cell biology.

ORGANISM(S): Mus musculus

PROVIDER: GSE161350 | GEO | 2020/11/13

REPOSITORIES: GEO

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Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare epidermal transcriptomes of control group (wild-type IMQ-untreated C57/BL6 mice), model group (wild-type IMQ-treated C57/BL6 mice) and XYF group (model group mice treated by XYF). Methods: Epidermal mRNA profiles of control group, model group and XYF group mice were generated by deep sequencing. Total RNA samples were prepared from intact epidermal ear sheets of mouse ear skin from two mice. Double-strand cDNA was generated from equal amounts of total RNA by following TruSeq8 RNA Library Prep Kit v2 (#RS-122-2001/2002, Illumina). The cDNA libraries were sequenced using Illumina Hi-seq2500. STAR software was utilized for sequence alignment between the preprocessing sequence and reference genome sequence of mice downloaded from the Ensembl database(Mus_musculus.GRCm38.90,ftp://ftp.ensembl.org/pub/release-90/gtf/mus_musculus/ Mus_musculus.GRCm38.90.chr.gtf.gz). Transcript assembly of mRNA sequencing data was performed by StringTie software. The expression levels for each of the genes were normalized to FPKM (fragments per kilobase of transcript per million fragments mapped). DESeq 2 was applied to conduct the analysis of differentially expressed genes (DEG). The cutoffs of DEG method were determined as the P value < = 0.05, the FDR value < = 0.05 and the Fold Change (FC) value > = 2. Results: Heatmap analysis of differentially expressed genes (DEG) revealed distinct transcriptomes between different groups, which displayed a partial reversal of pathological gene-expressing modifications by the treatment of XYF. Detailed comparison identified shared DEGs of opposite deviations between control group versus model group and model group versus XYF group. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis uncovered the epidermis from disease-model group was highly enriched in multiple inflammatory signaling, involving cytokine-cytokine receptor interaction, PI3K-Akt signaling pathway, IL-17 signaling pathway and cGMP-PKG signaling pathway. As for XYF therapy, PI3K-Akt signaling pathway, Calcium signaling, Hippo signaling pathway and cGMP-PKG signaling pathway were modulated in the epidermis. Further Gene Set Enrichment Analysis (GSEA) exposed downregulations in focal adhesion, ECM receptor interaction, TGF-β signaling pathway and glyoxylate and dicarboxylate metabolism in XYF-treated psoriasis-like epidermis. Conclusions: XYF might regulate various inflammatory signaling, metabolic processes and microvascular formation to influence γδT cell biology.

Project description:Background: Imiquimod (IMQ) produces a cutaneous phenotype in mice frequently studied as an acute model of human psoriasis. Whether this phenotype depends on strain or sex has never been systematically investigated on a large scale. Such effects, however, could lead to conflicts among studies, while further impacting study outcomes and efforts to translate research findings. Methods: RNA-seq was used to evaluate the psoriasiform phenotype elicited by IMQ in both sexes of 7 mouse strains (C57BL/6J, BALB/cJ, CD1, DBA/1J, FVB/NJ, 129X1/SvJ and MOLF/EiJ). Results: In most strains, IMQ altered gene expression in a manner consistent with human psoriasis, partly due to innate immune activation and decreased homeostatic gene expression. The IMQ response of MOLF males was aberrant, however, with decreased expression of differentiation-associated genes (elevated in other strains). Key aspects of the IMQ response differed between the two most commonly studied strains (BALB/c and C57BL/6). Compared with BALB/c, the C57BL/6 phenotype showed increased expression of genes associated with DNA replication, IL-17A activation and CD8+ T cells, but decreased expression of genes associated with interferon signaling and CD4+ T cells. Surprisingly, although IMQ-induced expression shifts mirrored psoriasis, correspondence was similar or better for other human skin diseases (e.g., eschars, acne, atopic dermatitis). For BALB/c, MOLF, and 129X1 strains, genes altered by IMQ corresponded better to those altered in human skin infections or wounds compared with those altered in psoriasis lesions. Conclusions: These findings demonstrate strain-dependent aspects of IMQ dermatitis that warrant consideration in planning and interpreting experimental studies. We have further shown that IMQ does not uniquely model psoriasis but in fact triggers a core set of pathways active in diverse skin diseases. These observations challenge the view of IMQ dermatitis as a mouse phenotype uniquely appropriate for studying psoriasis as opposed to other human skin conditions.

Project description:Segmental instillation of lipopolysaccharide (LPS) by bronchoscopy can be used as a model to safely induce transient airway inflammation in the human lung. The LPS challenge model enables investigation of cellular mechanisms involved in pulmonary inflammatory processes as well as pharmacodynamic analysis of investigational drugs for the treatment of respiratory diseases. Aim of this work was to describe the transcriptomic profile of the human segmental LPS challenge model with contextualization to major respiratory diseases. Pre-challenge bronchoalveolar lavage fluid (BAL) and biopsies were sampled from twenty-eight smoking, healthy subjects, followed by segmental LPS challenge and saline control challenge. Twenty-four hours post instillation, BAL and biopsies were collected from the challenged lung segments. Total RNA of cells from BAL and biopsy samples were sequenced for subsequent data analysis. Differential gene expression analysis resulted in 6316 upregulated differentially expressed genes (DEGs) and 241 downregulated DEG in BAL, but only one downregulated DEG in biopsy samples after LPS challenge compared to saline challenge. Upregulated DEG in BAL were related to molecular functions such as “Inflammatory response” or “antimicrobial humoral immune response mediated by antimicrobial peptide”, enriched biological processes such as “chemokine receptor activity”, and upregulated pro-inflammatory pathways such as “Wnt signaling pathway”, “Ras signaling pathway” or “JAK-STAT signaling pathway”. Furthermore, the segmental LPS challenge model resembled aspects of the five most prevalent respiratory diseases chronic obstructive pulmonary disease (COPD), asthma, pneumonia, tuberculosis and lung cancer and featured similarities with acute exacerbations in COPD (AECOPD) and community-acquired pneumonia (CAP). Overall, our study provides extensive information about the transcriptomic profile from BAL cells and mucosal biopsies following LPS challenge in healthy smokers. It expands the knowledge about the LPS challenge model providing potential overlap with respiratory diseases in general and infection-triggered respiratory insults such as AECOPD in particular.

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Next Generation Sequencing Facilitates Quantitative Analysis of dermal Transcriptomes of Imiquimod (IMQ)-Induced Psoriasis-Like Dermatitis Treated by Xiao-Yin-Fang (XYF) Therapy

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