Staff Scientist Max Planck Institute of Molecular Cell Biology and Genetics Dresden, Sachsen, Germany
Abstract: Single-cell RNA sequencing has been a prevailing method to identify and discover cell types in an organ and has been generated a vast amount of data across tissues and species. However, some caveats, such as loss of positional arrangements of cells and under- and/or over-representation of certain cell types, are inevitable due to cell dissociation. Spatial transcriptomics is an emerging, cutting-edge technology enabling not only transcriptional profiling but also spatial mapping of cells in an organ. Recent advancement of this method has resulted in data visualization in single-cell resolution. Pancreas is an organ consisting of exocrine and endocrine cells, which arise from pancreatic progenitor cells during development. Architectural organization of branched pancreas with terminal acini connected to ductal network and nearby islets of Langerhans coincides with cell differentiation in embryos. Although snapshots of different cell type emergence in pancreas have been shown by multiple techniques and animal models, spatial transcriptomics in high resolution has not yet been tested. Here, we use Visium HD (10X Genomics) with formalin-fixed paraffin-embedded sections of embryonic pancreata (E12.5, E14.5, E16.5, E18.5) for spatiotemporal mapping of morphogenesis and differentiation in development. We are in the process of cell type analysis and mapping after clustering of transcriptomics data based on cell segmentation in hematoxylin-and-eosin stained images. Our preliminary data confirm lineage progression of bi-potent progenitors, early acinar progenitors, early and late islets, and surrounding mesenchyme. One of technical difficulties is to prepare samples with a good RNA quality, especially later stages of pancreas at E16.5 and E18.5, due to the prevalent expression of RNases in acinar cells and slow penetration of fixative. We are seeking enhanced sample preparation procedures for the late stages of pancreas samples. When samples are ready at different stages, spatial transcriptomics will be an excellent benchmark for unbiased spatiotemporal development of the organ.
