| Literature DB >> 32152598 |
Amir Giladi1, Merav Cohen1,2, Chiara Medaglia1,3, Yael Baran4, Baoguo Li1, Mor Zada1, Pierre Bost1,5,6, Ronnie Blecher-Gonen1,7, Tomer-Meir Salame8, Johannes U Mayer9, Eyal David1, Franca Ronchese9, Amos Tanay10, Ido Amit11.
Abstract
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.Entities:
Mesh:
Year: 2020 PMID: 32152598 DOI: 10.1038/s41587-020-0442-2
Source DB: PubMed Journal: Nat Biotechnol ISSN: 1087-0156 Impact factor: 68.164