CIM-seq – an unsupervised method for physical cell interaction profiling of complex tissues

Cellular identity in complex multicellular organisms is determined in part by the physical organization of cells. However, large-scale investigation of the cellular interactome remains technically challenging. Researchers from the Karolinska Institutet have developed cell interaction by multiplet sequencing (CIM-seq), an unsupervised and high-throughput method to analyze direct physical cell–cell interactions between cell types present in a tissue. CIM-seq is based on RNA sequencing of incompletely dissociated cells, followed by computational deconvolution into constituent cell types. CIM-seq estimates parameters such as number of cells and cell types in each multiplet directly from sequencing data, making it compatible with high-throughput droplet-based methods. When applied to gut epithelium or whole dissociated lung and spleen, CIM-seq correctly identifies known interactions, including those between different cell lineages and immune cells. In the colon, CIM-seq identifies a previously unrecognized goblet cell subtype expressing the wound-healing marker Plet1, which is directly adjacent to colonic stem cells. These results demonstrate that CIM-seq is broadly applicable to unsupervised profiling of cell-type interactions in different tissue types.

CIM-seq allows determining physically interacting cell types

Each multiplet is computationally deconvoluted into its most likely single-cell constituents, based on its transcriptional profile and singlet cell types from the same tissue. Statistical enrichment of co-occurring cells in a large cohort of multiplets indicates physical interaction in the tissue. The results are summarized in the circos plot on the right, where cell classes are shown as colored blocks, connected by lines representing interactions, with the color of the line indicating whether the interaction is significant or not significant (NS) (purple or gray), as well as the fold enrichment of significant interactions. The width of the line connecting to a cell class is proportional to the relative frequency of that connection and the height of the boxes at the circumference is proportional to the frequency of cell types. Obs., observed; exp., expected.

Availability – The CIM-seq R package is available under the LGPL-3 license on GitHub: https://github.com/EngeLab/CIMseq.