Resolving cell-cell interaction networks and their molecular logic in complex tissues

Cells in complex organisms function through extensive interactions, yet mapping these interaction networks at scale remains challenging. Here, we present CCI-seq, a high-throughput method to unbiasedly capture cell-cell interactions by combining cell clump combinatorial indexing with single-cell sequencing. CCI-seq identified known interactions and fine-grained cellular organization in the mouse kidney and intestine, and uncovered aberrant interactions and disrupted spatial organization in adenomatous polyposis coli knockout (Apc-KO) mouse intestines. Its application to human colorectal cancer (CRC) revealed subtype-specific interactions linked to clinical classifications. Leveraging a single-cell RNA-seq backbone, CCI-seq achieves deep transcriptome coverage, enabling analysis of the molecular states arising from these interactions. This functional resolution revealed that interacting cells associate with distinct transcriptional programs—driving ion transport in the kidney, antigen presentation in Apc-KO villi, and NF-κB inflammatory activation in CRC. Thus, CCI-seq provides a scalable platform to unveil large-scale interaction networks and dissect their molecular and functional impacts, enhancing our understanding of complex multicellular systems.