Detecting Cell Contact-dependent Gene Expression from Spatial Transcriptomics Data
Cells have evolved communication methods to sense their microenvironments and send biological signals. In addition to the communication using ligands and receptors, cells use diverse channels including gap junctions to communicate with their immediate neighbors. Current approaches, however, cannot effectively capture the influence of various microenvironments. Here, we propose a novel approach that identifies cell neighbor-dependent gene expression (CellNeighborEX). After categorizing cells based on their microenvironment from spatial transcriptomics (ST) data, CellNeighborEX identifies diverse gene sets associated with partnering cell types, providing further insight. To categorize cells along with their environment, CellNeighborEX uses direct cell location or the mixture of transcriptome from multiple cells depending on the ST technology. We show that cells express different gene sets depending on the neighboring cell types in various tissues including mouse embryos, brain, and liver cancer. These genes were associated with development (in embryos) or metastases (liver cancer). We further validate that gene expression can be induced by neighboring partners. The neighbor-dependent gene expression suggests new potential genes involved in cell-cell interactions beyond what ligand-receptor co-expression can discover.