Spatially resolved transcriptomics provides insights into gene expression profiles and the spatial information of cells in their native state. Kanemaru et al. integrated existing single-cell datasets with newly generated spatial transcriptomic data to identify cellular niches in eight anatomical regions of the adult human heart. Combining targeted dissection and histology, the authors generated transcriptomic profiles of cells from the cardiac conduction system, mapped cells into microanatomical locations, and characterized cellular niches in an unbiased manner. They analyzed gene regulatory networks in pacemaker cells and nodal niche interactions. Spatial analyses using the CellPhoneDB cell-interaction database with a custom neural and G-protein-coupled receptor module highlighted synaptic connections between pacemaker cells and neighboring glial cells. The authors developed a ‘drug2cell’ pipeline, which uses drug–target interactions and single-cell and single-nuclei RNA-sequencing data to identify specific cellular targets. Further analysis indicated that pacemaker cells express targets for non-cardiac drugs with chronotropic effects. The computational tools could be applied to other cell atlases to improve in silico screening. Overall, the study sheds light on the cellular profiles of human cardiac niches and provides the potential for defining cell-specific drug targets.
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