TY - JOUR
T1 - Dissecting cellular crosstalk by sequencing physically interacting cells
AU - Giladi, Amir
AU - Cohen, Merav
AU - Medaglia, Chiara
AU - Baran, Yael
AU - Li, Baoguo
AU - Zada, Mor
AU - Bost, Pierre
AU - Blecher-Gonen, Ronnie
AU - Salame, Tomer Meir
AU - Mayer, Johannes U.
AU - David, Eyal
AU - Ronchese, Franca
AU - Tanay, Amos
AU - Amit, Ido
N1 - Publisher Copyright:
© 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/5/1
Y1 - 2020/5/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85081649625&partnerID=8YFLogxK
U2 - 10.1038/s41587-020-0442-2
DO - 10.1038/s41587-020-0442-2
M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???
C2 - 32152598
AN - SCOPUS:85081649625
SN - 1087-0156
VL - 38
SP - 629
EP - 637
JO - Nature Biotechnology
JF - Nature Biotechnology
IS - 5
ER -