{Reference Type}: Journal Article
{Title}: Identifying Spatial Co-occurrence in Healthy and InflAmed tissues (ISCHIA).
{Author}: Lafzi A;Borrelli C;Baghai Sain S;Bach K;Kretz JA;Handler K;Regan-Komito D;Ficht X;Frei A;Moor A;
{Journal}: Mol Syst Biol
{Volume}: 20
{Issue}: 2
{Year}: 2024 Feb 15
{Factor}: 13.068
{DOI}: 10.1038/s44320-023-00006-5
{Abstract}: Sequencing-based spatial transcriptomics (ST) methods allow unbiased capturing of RNA molecules at barcoded spots, charting the distribution and localization of cell types and transcripts across a tissue. While the coarse resolution of these techniques is considered a disadvantage, we argue that the inherent proximity of transcriptomes captured on spots can be leveraged to reconstruct cellular networks. To this end, we developed ISCHIA (Identifying Spatial Co-occurrence in Healthy and InflAmed tissues), a computational framework to analyze the spatial co-occurrence of cell types and transcript species within spots. Co-occurrence analysis is complementary to differential gene expression, as it does not depend on the abundance of a given cell type or on the transcript expression levels, but rather on their spatial association in the tissue. We applied ISCHIA to analyze co-occurrence of cell types, ligands and receptors in a Visium dataset of human ulcerative colitis patients, and validated our findings at single-cell resolution on matched hybridization-based data. We uncover inflammation-induced cellular networks involving M cell and fibroblasts, as well as ligand-receptor interactions enriched in the inflamed human colon, and their associated gene signatures. Our results highlight the hypothesis-generating power and broad applicability of co-occurrence analysis on spatial transcriptomics data.