Single-cell RNA-seq of rheumatoid arthritis synovial tissue using low cost microfluidic instrumentation

Abstract

Droplet-based single cell RNA-seq has emerged as a powerful technique for massively parallel cellular profiling. While these approaches offer the exciting promise to deconvolute cellular heterogeneity in diseased tissues, the lack of cost-effective, reliable, and user-friendly instrumentation has hindered widespread adoption of droplet microfluidic techniques. To address this, we have developed a microfluidic control instrument that can be easily assembled from 3D printed parts and commercially available components costing approximately $540. We adapted this instrument for massively parallel scRNA-seq and deployed it in a clinical environment to perform single cell transcriptome profiling of disaggregated synovial tissue from a rheumatoid arthritis patient. We sequenced 8,716 single cells from a synovectomy, revealing 16 transcriptomically distinct clusters. These encompass a comprehensive and unbiased characterization of the autoimmune infiltrate, including inflammatory T and NK subsets that contribute to disease biology. Additionally, we identified fibroblast subpopulations that are demarcated via THY1 (CD90) and CD55 expression. Further experiments confirm that these represent synovial fibroblasts residing within the synovial intimal lining and subintimal lining, respectively, each under the influence of differing microenvironments. We envision that this instrument will have broad utility in basic and clinical settings, enabling low-cost and routine application of microfluidic techniques, and in particular single-cell transcriptome profiling.

Reporters of TCR signaling identify arthritogenic T cells in murine and human autoimmune arthritis

“…Indeed, we find an enrichment of intracellular Nur77 + CD4 T cells in both human RA and murine autoimmune arthritis. Although RA synovial tissue has recently been phenotyped with attention placed on infiltrating 'peripheral helper' T (Tph) cells, little data exists on infiltrating T cell antigen-reactivity or specificity (49)(50)(51)(52)(53)(54).…”

Identification of Three Rheumatoid Arthritis Disease Subtypes by Machine Learning Integration of Synovial Histologic Features and RNA Sequencing Data

“…com/doi/10.1002/art.40428/abstract). These genes included markers of lining layer fibroblasts such as CD55, transforming growth factor b (TGFb) superfamily genes (TGFBR1, TGFBR2, TGFB2, and BMP6), and genes involved in the regulation of extracellular glycoproteins such as GCNT3 (a glycosyltransferase that mediates core O-glycan branching, a critical step in mucin synthesis) (26)(27)(28)(29)(30). Another enriched pathway in the low inflammatory subtype included cell adhesion ( Figure 4B).…”

Leveraging blood and tissue CD4+ T cell heterogeneity at the single cell level to identify mechanisms of disease in rheumatoid arthritis

“…T PH cells, characterized as PD-1 hi CXCR5 − CD4+, display a unique capacity to infiltrate inflamed tissues and enhance local B cell antibody production and differentiation into plasma cells. A preliminary single-cell RNA-seq analysis of a single RA synovial sample has also demonstrated multiple T cell subsets, including a population of T PH cells, in the RA T cell infiltrate [70]. …”