Single-cell multimodal analysis identifies common regulatory programs in synovial fibroblasts of rheumatoid arthritis patients and modeled TNF-driven arthritis

Abstract

Background Synovial fibroblasts (SFs) are specialized cells of the synovium that provide nutrients and lubricants for the proper function of diarthrodial joints. Recent evidence appreciates the contribution of SF heterogeneity in arthritic pathologies. However, the normal SF profiles and the molecular networks that govern the transition from homeostatic to arthritic SF heterogeneity remain poorly defined. Methods We applied a combined analysis of single-cell (sc) transcriptomes and epigenomes (scRNA-seq and scATAC-seq) to SFs derived from naïve and hTNFtg mice (mice that overexpress human TNF, a murine model for rheumatoid arthritis), by employing the Seurat and ArchR packages. To identify the cellular differentiation lineages, we conducted velocity and trajectory analysis by combining state-of-the-art algorithms including scVelo, Slingshot, and PAGA. We integrated the transcriptomic and epigenomic data to infer gene regulatory networks using ArchR and custom-implemented algorithms. We performed a canonical correlation analysis-based integration of murine data with publicly available datasets from SFs of rheumatoid arthritis patients and sought to identify conserved gene regulatory networks by utilizing the SCENIC algorithm in the human arthritic scRNA-seq atlas. Results By comparing SFs from healthy and hTNFtg mice, we revealed seven homeostatic and two disease-specific subsets of SFs. In healthy synovium, SFs function towards chondro- and osteogenesis, tissue repair, and immune surveillance. The development of arthritis leads to shrinkage of homeostatic SFs and favors the emergence of SF profiles marked by Dkk3 and Lrrc15 expression, functioning towards enhanced inflammatory responses and matrix catabolic processes. Lineage inference analysis indicated that specific Thy1+ SFs at the root of trajectories lead to the intermediate Thy1+/Dkk3+/Lrrc15+ SF states and culminate in a destructive and inflammatory Thy1− SF identity. We further uncovered epigenetically primed gene programs driving the expansion of these arthritic SFs, regulated by NFkB and new candidates, such as Runx1. Cross-species analysis of human/mouse arthritic SF data determined conserved regulatory and transcriptional networks. Conclusions We revealed a dynamic SF landscape from health to arthritis providing a functional genomic blueprint to understand the joint pathophysiology and highlight the fibroblast-oriented therapeutic targets for combating chronic inflammatory and destructive arthritic disease.

Repurposing of Amisulpride, a known antipsychotic drug, to target synovial fibroblasts activation in arthritis

“…Notably, hTNFtg pathogenic SFs were capable of initiating disease when transferred to the knees of healthy mice (7) , thus underlining the dominant and autonomous role of SFs in RA pathology initiation and progression. Notably, hTNFtg SFs, have been found to highly correlate with RA human Fibroblast Like Synoviocytes (FLS) not only in their gene expression profile (8) but also in their distinct roles in the joint area, with CD90 - SFs of synovial lining driving mainly bone destruction and CD90 + SFs of sublining area driving mainly inflammation (9–11) .…”

SCALA: A web application for multimodal analysis of single cell next generation sequencing data

“…To demonstrate SCALA’s functionality, we utilized two previously published datasets (45) (scRNA-seq and scATAC-seq) regarding the single cell transcriptome and chromatin dynamics of Synovial Fibroblasts transitioning from homeostasis to pathology in modeled TNF-driven arthritis. For this purpose, the human TNF ( hTNFtg ) transgene overexpressing mouse model Tg197 (46) was used and compared against healthy wild type (Wt) mice.…”

“…For this purpose, the human TNF ( hTNFtg ) transgene overexpressing mouse model Tg197 (46) was used and compared against healthy wild type (Wt) mice. As reported previously (45), for the generation of 10x Genomics scRNA-seq libraries (Single Cell 3’ v3 reagent kits), 6,667 sorted non-hematopoietic stromal cells ( Cd45 -, Cd31 -, Ter119 -, Pdpn +) were isolated from whole ankle joint synovium. These libraries were sequenced at a depth of 400 million reads, using one lane of an Illumina NextSeq 500 machine.…”

Integrative Single-Cell RNA-Seq and ATAC-Seq Analysis of Mouse Corneal Epithelial Cells

“…Peak to gene linkage analysis has been proved to be a good predictor of enhancer activity. 62 , 63 In this study, we provided a reference map of enhancers for mouse corneal epithelial cells through this method. Moreover, we nominated positive TFs driving corneal epithelial cells differentiation.…”