Inferring a spatial code of cell-cell interactions across a whole animal bodys

Abstract

SummaryCell-cell interactions shape cellular function and ultimately organismal phenotype. However, the spatial code embedded in the molecular interactions driving and sustaining spatial organization remains to be elucidated. Here we present a computational framework to infer the spatial code underlying cell-cell interactions in a whole animal. Using the transcriptomes of the cell types composing Caenorhabditis elegans’ body, we compute the potential for intercellular interactions from the coexpression of ligand-receptor pairs. Leveraging a 3D atlas of C. elegans’ cells and a genetic algorithm we identify the ligand-receptor pairs most informative of the spatial organization of cells. The resulting intercellular distances are negatively correlated with the potential for cell-cell interaction, validating this strategy. Further, for selected ligand-receptor pairs, we experimentally confirm the algorithm-generated cell-cell interactions. Thus, our computational framework helps identify a code associated with spatial organization and cellular functions across a whole-animal body, showing that single-cell molecular measurements provide spatial information that may help elucidate organismal phenotypes and disease.Highlights-A cell-cell interaction network in the whole body of C. elegans is presented.-Intercellular distance and interactions are negatively correlated.-A combination of ligand-receptor pairs carries a spatial code of cell-cell interactions.-Spatial expression of specific ligand-receptor pairs is validated in vivo.Graphical abstract