Crosstalk between neighboring cells underlies many biological processes, including cell signaling, proliferation and differentiation. Current single-cell genomic technologies profile each cell separately after tissue dissociation, losing information on cell–cell interactions. In the present study, we present an approach for sequencing physically interacting cells (PIC-seq), which combines cell sorting of physically interacting cells (PICs) with single-cell RNA-sequencing. Using computational modeling, PIC-seq systematically maps in situ cellular interactions and characterizes their molecular crosstalk. We apply PIC-seq to interrogate diverse interactions including immune–epithelial PICs in neonatal murine lungs. Focusing on interactions between T cells and dendritic cells (DCs) in vitro and in vivo, we map T cell–DC interaction preferences, and discover regulatory T cells as a major T cell subtype interacting with DCs in mouse draining lymph nodes. Analysis of T cell–DC pairs reveals an interaction-specific program between pathogen-presenting migratory DCs and T cells. PIC-seq provides a direct and broadly applicable technology to characterize intercellular interaction-specific pathways at high resolution.

相邻细胞之间的串扰是许多生物过程的基础，包括细胞信号传导、增殖和分化。目前的单细胞基因组技术在组织解离后分别对每个细胞进行分析，从而丢失了细胞间相互作用的信息。在本研究中，我们提出了一种对物理相互作用细胞 (PIC-seq) 进行测序的方法，该方法将物理相互作用细胞 (PIC) 的细胞分选与单细胞 RNA 测序相结合。使用计算模型，PIC-seq 系统地映射原位细胞相互作用并表征它们的分子串扰。我们应用 PIC-seq 来研究多种相互作用，包括新生鼠肺中的免疫-上皮 PIC。专注于 T 细胞和树突状细胞 (DC) 在体外和体内的相互作用，我们绘制了 T 细胞与 DC 相互作用的偏好图，并发现调节性 T 细胞作为主要的 T 细胞亚型与小鼠引流淋巴结中的 DC 相互作用。T 细胞-DC 对的分析揭示了病原体呈递迁移性 DC 和 T 细胞之间的相互作用特异性程序。PIC-seq 提供了一种直接且广泛适用的技术，用于以高分辨率表征细胞间相互作用的特定途径。