Abstract
Abstract Background Single-cell transcriptomic data of the human intestine has shed new light on the cellular composition and heterogeneity present in healthy and diseased tissues. Nonetheless, little information is currently available on their spatial distribution within tissue structures and cellular neighborhoods, which is particularly relevant to infer the function of disease-specific cell types. Here, we apply spatial transcriptomics to healthy control (HC) and Crohn’s disease (CD) intestinal samples and provide a map of cell types across healthy and diseased colon. Methods Fresh frozen colonic sections from HC (n=1) and CD (n=3) patients were placed onto 10X Visium slides, which feature thousands of spatially barcoded spots, each capable of capturing RNA from 10-15 cells. To retrieve single-cell resolution, spots were deconvoluted according to the Cell2location approach using our previously generated human single cell RNA sequencing (scRNAseq) dataset1 as a reference. For validation and further analysis at single-cell resolution, a panel of 100 genes was measured using single molecule fluorescent in situ hybridization (Molecular Cartography) (Fig. 1A). Results Deconvolution analysis revealed the cellular composition of each spot across all four different tissue sections including epithelial, stromal and immune cell types. Here, we focused on studying the location and diversity of fibroblasts and macrophages given their plasticity during inflammation1,2. The most abundant fibroblast cell type in CD were the inflammation-associate (IAFs) and the GREM1+ subepithelial fibroblasts. These two subsets showed a distinct gene signature and location, suggesting different functions (Fig. 1B). Most GREM1+ fibroblasts co-expressed FGFR1 and were in proximity with endothelial cells (VWF+) expressing the VEGF receptor 2 KDR, highlighting a potential pro-angiogenic role of GREM1+ fibroblasts3 (Fig. 1C). Remarkably, GREM1 was abundantly expressed by CCL19+ fibroblastic reticular cells and TNC+ stromal cells, underlying the potential heterogeneity of GREM1+ fibroblasts. Regarding macrophages, we could identify an inflammation-specific population expressing PLA2G2D and PTGDS. These macrophages were mainly localized within granulomas surrounding M1 macrophages (Fig. 1D). While their function is unknown, their signature suggests they might be modulating inflammation through the production of anti-inflammatory lipid mediators4. Conclusion Using two different ST technologies, we resolved the tissue distribution of cell populations previously identified by scRNAseq and reveal their potential function based on their spatial location.
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