Mapping the heterogeneity of pDCs and Monocytes of systemic sclerosis at single cell level [scRNA-seq]

Systemic sclerosis (SSc) is an uncommon disease characterized by elevated autoantibody production, vasculopathy and fibrosis of the skin and internal organs. pDCs are the core cell type to produce type I IFN and contributes to the ISG signature and SSc progression. Using single-cell RNA sequencing, we profiled 32529 pDCs enriched and T cell depleted peripheral blood mononuclear cells (PBMCs) from 4 patients with SSc and 4 matched controls. Increased CD16+ monocytes and decreased cDCs are the major changes in the cell composition between SSc and heathy controls. Increased expression of interferon-stimulated genes (ISGs) and apoptotic genes distinguished cells from patients with SSc from healthy control cells. The high ISG expression signature (ISGhi) derived from a small number of transcriptionally defined subpopulations within major cell types, including monocytes, natural killer cells, conventional and plasmacytoid dendritic cells, B cells. Profiling of 10976 pDCs revealed a newly identified PTGDS+ population and a clear increased ISG hi clusters in SSc pDCs. Profiling of 13317 Monocytes revealed increased CD16+ Monocytes and a clear increased ISG hi clusters in SSc monocytes. We then compared the TLRs-IFN response of the pDCs from SSc and Healthy control. RNASeq revealed SSc pDCs enables an unexpected TLR8-IFN signaling to increase the IFN signature. This study lays the groundwork for resolving the origin of the SSc transcriptional signatures and the disease heterogeneity towards precision medicine applications. Overall design: Frozen PBMCs from 4 healthy and 4 SSc patient donors were sorted to obtain enriched pDCs (CD3-CD14-CD123+BDCA4+) and T/pDC cell depleted PBMCs (CD3-CD123-BDCA4-) fractions, the two fractions were then remerged at 1:2 ratio. Cell viability of all donors are above 85%. 8000 cells from each donor were loaded to 10x single cell microfluidic chip to obtain around 5000 recovery cells. Libraries were constructed by following the instructions of 10x company (Chromium Single Cell 3' Reagent kits v3). The 8 libraries were quantified by NEBNext Library Quant Kit (E7630S) and equally merged and sequenced by Novaseq. The sequenced data were analyzed in Cellranger to align reads, generate feature-barcode matrices. A merged dataset were obtained and batch corrected using FastMNN17 in a base of Seurat pipeline18 (https://satijalab.org/seurat/articles/get_started.html). Doublets were removed manually by excluding cells with more than two cell type markers. The trimmed dataset are visualized by UMAP plot.