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Dissecting cellular crosstalk by sequencing physically interacting cells

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

Research output: Contribution to journalArticlepeer-review

Abstract

PIC-seq characterizes cellular crosstalk by sorting and sequencing physically interacting cells.

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.

Original languageEnglish
Pages (from-to)629-637
Number of pages9
JournalNature biotechnology
Volume38
Issue number5
Early online date9 Mar 2020
DOIs
StatePublished - 1 May 2020

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Bioengineering
  • Applied Microbiology and Biotechnology
  • Molecular Medicine
  • Biomedical Engineering

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