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 - Funding Information: We thank G. Brodsky for artwork. The research of I.A. and A.T. is supported by the Seed Networks for the Human Cell Atlas of the Chan Zuckerberg Initiative and by Merck KGaA, Darmstadt. I.A. is an Eden and Steven Romick Professorial Chair, supported by the HHMI International Scholar Award, the European Research Council Consolidator Grant (no. 724471-HemTree2.0), an MRA Established Investigator Award (no. 509044), DFG (no. SFB/TRR167), the Ernest and Bonnie Beutler Research Program for Excellence in Genomic Medicine, the Helen and Martin Kimmel awards for innovative investigation, and the SCA award of the Wolfson Foundation and Family Charitable Trust. The Thompson Family Foundation Alzheimer’s Research Fund and the Adelis Foundation also provided support. A.T.’s laboratory is supported by the European Research Council, the I-CORE for chromatin and RNA regulation, and a grant from the Israel Science Foundation. A.T. is a Kimmel investigator. A.G. is a recipient of the Clore fellowship. M.C. is supported by a postdoctoral fellowship in Applied and Engineering Science, Israeli Government, Ministry of Science and Technology.
PY - 2020/5/1
Y1 - 2020/5/1
N2 - 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.
AB - 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.
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 - مقالة
C2 - 32152598
SN - 1087-0156
VL - 38
SP - 629
EP - 637
JO - Nature biotechnology
JF - Nature biotechnology
IS - 5
ER -