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Identification of HBEGF+ fibroblasts in the remission of rheumatoid arthritis by integrating single-cell RNA sequencing datasets and bulk RNA sequencing datasets
Arthritis Research & Therapy ( IF 4.4 ) Pub Date : 2022-09-06 , DOI: 10.1186/s13075-022-02902-x
Nachun Chen 1 , Baoying Fan 1 , Zhiyong He 1 , Xinping Yu 1 , Jinjun Wang 1
Affiliation  

Fibroblasts are important structural cells in synovium and play key roles in maintaining the synovial homeostasis. By single-cell RNA sequencing (scRNA-seq), subpopulation of synovium-resident cells has been reported to protect intra-articular structures from chronic inflammation and promote tissue repair. However, a significant number of researchers have concentrated on the role of fibroblasts in the progress of rheumatoid arthritis (RA) while few reports had described the contribution of distinct fibroblast subsets in the RA remission. It is helpful to understand the role of fibroblast subpopulations in the RA process to provide predictive biomarkers and address RA remission mechanisms. Here, we found HBEGF+ fibroblasts that contributed to RA remission by integrating scRNA-seq datasets and bulk RNA sequencing (bulk RNA-seq) datasets. Three single-cell RNA datasets of cells harvested from RA patients were processed and integrated by Seurat and Harmony R packages. After identifying cell types by classic marker genes, the integrated dataset was used to run CellChat for analysis of cell-cell communication. Specially, EGF signaling pathway was found and HBEGF+ fibroblasts were identified based on HBEGF expression. Differential expressed genes of HBEGF+ were shown in heatmap and volcano plot and used to run gene ontology (GO) enrichment analysis. Next, bulk RNA-seq datasets of synovium under different conditions (health, osteoarthritis (OA), rheumatoid arthritis, before and after classical treatment) were compared to show expression change of HBEGF and gene markers that are mainly expressed by HBEGF+ fibroblasts such as CLIC5, PDGFD, BDH2, and ENPP1. Finally, two single-cell RNA sequencing datasets of synovial cells from mice were integrated to identify Hbegf+ fibroblasts and calculate the population of Hbegf+ fibroblasts under different joint conditions (health, K/BxN serum transfer arthritis (STA), and remission of STA). After integrating three single-cell RNA sequencing datasets, we identified 11 clusters of synovial cells, such as fibroblasts, mural cells, endothelial cells, CD4+ T cells, CD8+ T cells, natural killer cells, synovium macrophage, peripheral blood macrophages, plasma cells, B cells, and STMN1+ cells. We found fibroblasts had an extensive communication network with other clusters and interacted with synovial macrophages through EGF signaling pathway via analysis of cell-cell communication between synovial cells. HBEGF, ligand to EGF signaling pathway, was highly expressed by a subset of fibroblasts and macrophages, and EGFR, receptor to EGF signaling pathway, was highly expressed by fibroblasts and meniscus cells. Moreover, HBEGF was downregulated under RA state and it had an increase after classical treatment. We then defined fibroblasts with high expression of HBEGF as HBEGF+ fibroblasts. In addition, we also found that HBEGF+ fibroblasts highly expressed CRTAC1, ITGB8, SCARA5, THBS4, and ITGBL1, genes relative to encoding extracellular matrix proteins and engaged in positive regulation of cell migration and motility, cellular component movement, and cell growth by GO enrichment analysis. We eventually identified HBEGF+ fibroblasts specially expressed CLIC5, PDGFD, BDH2, and ENPP1, which positively correlated with the expression of HBEGF. Moreover, the expression of CLIC5, PDGFD, BDH2, and ENPP1 was downregulated under RA state and elevated by classical therapy. On the contrary, the HBEGF+ macrophages specially expressed SLAMF8, GK, L1RN, and JAK2, which negatively correlated with the expression of HBEGF. The expression was upregulated in SLAMF8, GK, L1RN, and JAK2 under the RA state, whereas it was decreased after classical treatment. In mice, the number of Hbegf+ fibroblasts was reduced in the RA synovium but increased in the RA remitting synovium. HBEGF+ fibroblasts play a role in the remission of rheumatoid arthritis, and HBEGF has potential to become a novel biomarker for prediction of RA progress.

中文翻译:

通过整合单细胞 RNA 测序数据集和批量 RNA 测序数据集鉴定 HBEGF+ 成纤维细胞在类风湿性关节炎缓解中的作用

成纤维细胞是滑膜中重要的结构细胞,在维持滑膜稳态中起关键作用。据报道,通过单细胞 RNA 测序 (scRNA-seq),滑膜驻留细胞亚群可保护关节内结构免受慢性炎症的影响并促进组织修复。然而,大量研究人员专注于成纤维细胞在类风湿关节炎 (RA) 进展中的作用,而很少有报道描述不同成纤维细胞亚群在 RA 缓解中的作用。了解成纤维细胞亚群在 RA 过程中的作用有助于提供预测性生物标志物和解决 RA 缓解机制。在这里,我们发现 HBEGF+ 成纤维细胞通过整合 scRNA-seq 数据集和批量 RNA 测序 (bulk RNA-seq) 数据集有助于 RA 缓解。Seurat 和 Harmony R 软件包处理并整合了从 RA 患者身上采集的三个单细胞 RNA 数据集。通过经典标记基因识别细胞类型后,集成数据集用于运行 CellChat 以分析细胞间通讯。特别是发现了EGF信号通路,并根据HBEGF表达鉴定了HBEGF+成纤维细胞。HBEGF+ 的差异表达基因显示在热图和火山图中,并用于运行基因本体 (GO) 富集分析。接下来,比较不同条件(健康、骨关节炎 (OA)、类风湿性关节炎、经典治疗前后)下滑膜的大量 RNA-seq 数据集,以显示 HBEGF 和主要由 HBEGF+ 成纤维细胞如 CLIC5 表达的基因标记的表达变化、PDGFD、BDH2 和 ENPP1。最后,整合了来自小鼠滑膜细胞的两个单细胞 RNA 测序数据集,以识别 Hbegf+ 成纤维细胞并计算不同关节条件(健康、K/BxN 血清转移性关节炎 (STA) 和 STA 缓解)下的 Hbegf+ 成纤维细胞群。在整合三个单细胞 RNA 测序数据集后,我们确定了 11 个滑膜细胞簇,例如成纤维细胞、壁细胞、内皮细胞、CD4+ T 细胞、CD8+ T 细胞、自然杀伤细胞、滑膜巨噬细胞、外周血巨噬细胞、浆细胞、 B 细胞和 STMN1+ 细胞。我们通过分析滑膜细胞之间的细胞间通信,发现成纤维细胞与其他簇具有广泛的通信网络,并通过 EGF 信号通路与滑膜巨噬细胞相互作用。HBEGF,EGF信号通路的配体,在成纤维细胞和巨噬细胞亚群中高表达,而 EGF 信号通路的受体 EGFR 在成纤维细胞和半月板细胞中高表达。此外,HBEGF在RA状态下下调,经典治疗后HBEGF升高。然后,我们将 HBEGF 高表达的成纤维细胞定义为 HBEGF+ 成纤维细胞。此外,我们还发现 HBEGF+ 成纤维细胞高表达 CRTAC1、ITGB8、SCARA5、THBS4 和 ITGBL1,这些基因与编码细胞外基质蛋白相关,并通过 GO 富集参与细胞迁移和运动、细胞成分运动和细胞生长的正向调节。分析。我们最终鉴定出 HBEGF+ 成纤维细胞特别表达 CLIC5、PDGFD、BDH2 和 ENPP1,它们与 HBEGF 的表达呈正相关。此外,CLIC5、PDGFD、BDH2、并且 ENPP1 在 RA 状态下下调,在经典治疗下升高。相反,HBEGF+巨噬细胞特异表达SLAMF8、GK、L1RN和JAK2,与HBEGF的表达呈负相关。在 RA 状态下,SLAMF8、GK、L1RN 和 JAK2 中的表达上调,而在经典治疗后下降。在小鼠中,RA 滑膜中 Hbegf+ 成纤维细胞的数量减少,但在 RA 缓解滑膜中增加。HBEGF+ 成纤维细胞在类风湿性关节炎的缓解中发挥作用,HBEGF 有可能成为预测 RA 进展的新型生物标志物。在 RA 状态下,SLAMF8、GK、L1RN 和 JAK2 中的表达上调,而在经典治疗后下降。在小鼠中,RA 滑膜中 Hbegf+ 成纤维细胞的数量减少,但在 RA 缓解滑膜中增加。HBEGF+ 成纤维细胞在类风湿性关节炎的缓解中发挥作用,HBEGF 有可能成为预测 RA 进展的新型生物标志物。在 RA 状态下,SLAMF8、GK、L1RN 和 JAK2 中的表达上调,而在经典治疗后下降。在小鼠中,RA 滑膜中 Hbegf+ 成纤维细胞的数量减少,但在 RA 缓解滑膜中增加。HBEGF+ 成纤维细胞在类风湿性关节炎的缓解中发挥作用,HBEGF 有可能成为预测 RA 进展的新型生物标志物。
更新日期:2022-09-06
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