Research Centre of Basic Intergrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China.
The First College of Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China.
Int J Immunopathol Pharmacol. 2024 Jan-Dec;38:3946320241265945. doi: 10.1177/03946320241265945.
This study aimed to explore the unique transcriptional feature of fibroblasts subtypes and the role of ferroptosis in diabetic foot ulcers (DFUs).
The GEO (Gene Expression Omnibus) was searched to obtain the DFUs single-cell and transcriptional datasets. After identifying cell types by classic marker genes, the integrated single-cell dataset was used to run trajectory inference, RNA velocity, and ligand-receptor interaction analysis. Next, bulk RNA-seq datasets of DFUs were analyzed to the key ferroptosis genes.
Here, we profile 83529 single transcriptomes from the foot samples utilizing single-cell sequencing (scRNA-seq) data of DFU from GEO database and identified 12 cell types, with fibroblasts exhibiting elevated levels of ferroptosis activity and substantial cellular heterogeneity. Our results defined six main fibroblast subsets that showed mesenchymal, secretory-reticular, secretory-papillary, pro-inflammatory, myogenesis, and healing-enriched functional annotations. Trajectory inference and cell-cell communication analysis revealed two major cell fates with subpopulations of fibroblasts and altered ligand-receptor interactions. Bulk RNA sequencing data identified CGNL1 as a distinctive diagnostic signature in fibroblasts. Notably, CGNL1 positively correlated with pro-inflammatory fibroblasts.
Overall, our analysis delineated the heterogeneity present in cell populations of DFUs, showing distinct fibroblast subtypes characterized by their own unique transcriptional features and enrichment functions. Our study will help us better understand DFUs pathogenesis and identifies CGNL1 as a potential target for DFUs therapies.
本研究旨在探索成纤维细胞亚型的独特转录特征以及铁死亡在糖尿病足溃疡(DFU)中的作用。
通过 GEO(基因表达综合数据库)搜索,获取 DFU 的单细胞和转录组数据集。通过经典标记基因识别细胞类型后,使用整合的单细胞数据集进行轨迹推断、RNA 速度和配体-受体相互作用分析。然后,分析 DFU 的批量 RNA-seq 数据集,以确定关键的铁死亡基因。
本研究利用 GEO 数据库中 DFU 的单细胞测序(scRNA-seq)数据,对 83529 个来自足部样本的单细胞转录组进行了分析,共鉴定出 12 种细胞类型,其中成纤维细胞表现出高水平的铁死亡活性和显著的细胞异质性。我们的结果定义了六个主要的成纤维细胞亚群,这些亚群具有间充质、分泌网状、分泌乳突、促炎、肌生成和愈合富集的功能注释。轨迹推断和细胞间通讯分析揭示了两个主要的细胞命运,伴随着成纤维细胞亚群和改变的配体-受体相互作用。批量 RNA 测序数据确定 CGNL1 是成纤维细胞中一个独特的诊断特征。值得注意的是,CGNL1 与促炎成纤维细胞呈正相关。
总体而言,我们的分析描绘了 DFU 细胞群体中存在的异质性,显示了具有独特转录特征和富集功能的不同成纤维细胞亚型。我们的研究将帮助我们更好地理解 DFU 的发病机制,并确定 CGNL1 作为 DFU 治疗的潜在靶点。