Spatially informed phenotyping by cyclic-in-situ-hybridisation identifies novel fibroblast populations and their pathogenic niches in systemic sclerosis.

Abstract

Spatially nonresolved transcriptomic data identified several functionally distinct populations of fibroblasts in health and disease. However, in-depth transcriptional profiling in situ at the single-cell resolution has not been possible so far. We thus aimed to profile these populations by single-cell spatial transcriptomics using cyclic in situ hybridisation (cISH). We studied fibroblast subpopulations in the skin of systemic sclerosis (SSc) patients and heathy individuals using cISH as a novel approach for transcriptional phenotyping with subcellular resolution. Clustering was performed using Building Aggregates with a Neighbourhood Kernel and Spatial Yardstick (BANKSY) as a novel approach for spatially informed transcriptional phenotyping. The findings were further validated by integration with single-cell RNA sequencing in distinct SSc cohorts. BANKSY-based spatially informed clustering identified 9 fibroblast (FB) subpopulations, with SFRP2+ reticular dermis (RetD) FB and CCL19+ nonperivascular (nonPV) FBs as novel subpopulations that reside in specific cellular niches and display unique gene expression profiles. SFRP2+ RetD FBs and CCL19+ nonPV FBs as well as COL8A1+ FBs display altered frequencies in SSc skin and play specific, disease-promoting roles for extracellular matrix release and leukocyte recruitment as revealed by their transcriptional profile, their cellular interactions, and ligand-receptor analyses. The frequencies of COL8A1+ FBs and their interactions with monocytic cells and B cells are associated with the progression of skin fibrosis in SSc. Our cISH-based, spatially resolved transcriptomic approach identified novel fibroblast subpopulations deregulated in SSc skin with specific pathogenic roles. COL8A1+ FBs and their immune interactions may also have potential as biomarkers for future progression of skin fibrosis.