Dissecting cellular crosstalk by sequencing physically interacting cells.
IF: 68.164
Cited by: 159


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.


Gene Expression

MeSH terms

Animals, Newborn
Cell Communication
Cells, Cultured
Computational Biology
Dendritic Cells
Flow Cytometry
Gene Expression Profiling
Sequence Analysis, RNA
Single-Cell Analysis


Giladi, Amir
Cohen, Merav
Medaglia, Chiara
Baran, Yael
Li, Baoguo
Zada, Mor
Bost, Pierre
Blecher-Gonen, Ronnie
Salame, Tomer-Meir
Mayer, Johannes U
David, Eyal
Ronchese, Franca
Tanay, Amos
Amit, Ido

Recommend literature

Similar data