Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
Program in Quantitative Biomedical Sciences, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
Arthritis Res Ther. 2019 Feb 6;21(1):49. doi: 10.1186/s13075-019-1816-z.
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.
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).
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.
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.
感染因子长期以来一直被推测是全身性硬皮病（SSc）的疾病触发因素，但尚未发现明确的联系。高通量数据的宏基因组分析允许在 SSc 患者的皮肤活检中对潜在的微生物组病原体进行无偏鉴定，并深入了解与宿主基因表达的关系。
我们通过 RNA-seq 检查了来自 23 名 SSc 患者（包括病变前臂和非病变背部样本）的多样化队列的皮肤活检。使用集成宏基因组测序分析（IMSA）进行宏基因组过滤和注释。使用单样本基因集富集分析（ssGSEA）分析微生物组组成与基因表达之间的关联。
我们发现 SSc 患者的皮肤相对于对照组表现出微生物组成的显著变化，其特征是亲脂性分类群（如丙酸杆菌）急剧减少，同时广泛的革兰氏阴性分类群（包括伯克霍尔德菌、柠檬酸杆菌和弧菌）增加。
微生物组失调与疾病持续时间和炎症基因表达增加有关。这些数据提供了 SSc 皮肤微生物组及其与局部基因表达的关联的全面描述，与病变皮肤中的分子变化相吻合。
