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. Here we develop 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. Our results demonstrate that CIM-seq is broadly applicable to unsupervised profiling of cell-type interactions in different tissue types.

复杂多细胞生物中的细胞特性部分取决于细胞的物理组织。然而，对细胞相互作用组的大规模研究在技术上仍然具有挑战性。在这里，我们通过多重测序 (CIM-seq) 开发细胞相互作用，这是一种无监督的高通量方法，用于分析组织中存在的细胞类型之间的直接物理细胞-细胞相互作用。CIM-seq 基于对不完全解离的细胞进行 RNA 测序，然后通过计算反卷积为组成细胞类型。CIM-seq 直接从测序数据估计每个多重基因组中的细胞数量和细胞类型等参数，使其与基于液滴的高通量方法兼容。当应用于肠上皮或整个分离的肺和脾脏时，CIM-seq 可以正确识别已知的相互作用，包括不同细胞谱系和免疫细胞之间的那些。在结肠中，CIM-seq 识别出以前未被识别的杯状细胞亚型，表达伤口愈合标记Plet1与结肠干细胞直接相邻。我们的结果表明，CIM-seq 广泛适用于不同组织类型中细胞类型相互作用的无监督分析。