Dissecting cellular crosstalk by 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, w...

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Published inNature biotechnology Vol. 38; no. 5; pp. 629 - 637
Main Authors 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
Format Journal Article
LanguageEnglish
Published New York Nature Publishing Group US 01.05.2020
Nature Publishing Group
Subjects
631/250/516
631/337/2019
631/61/191/2018
631/61/212/2019
Agriculture
Algorithms
Analysis
Animals
Animals, Newborn
Bioinformatics
Biological activity
Biomedical and Life Sciences
Biomedical Engineering/Biotechnology
Biomedicine
Biotechnology
Cell Communication
Cell differentiation
Cell interactions
Cell migration
Cell proliferation
Cells, Cultured
Computational Biology
Computer applications
Crosstalk
Dendritic cells
Dendritic Cells - chemistry
Dendritic Cells - cytology
Female
Flow Cytometry
Gene Expression Profiling - methods
Gene mapping
Gene sequencing
Genomics
Immunoregulation
Life Sciences
Lung - chemistry
Lung - cytology
Lymph nodes
Lymphocytes
Lymphocytes T
Mice
Neonates
Ribonucleic acid
RNA
Sequence Analysis, RNA
Single-Cell Analysis - methods
T cells
T-Lymphocytes - chemistry
T-Lymphocytes - cytology
Canada
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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. PIC-seq characterizes cellular crosstalk by sorting and sequencing physically interacting cells.
AbstractList 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.
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.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. PIC-seq characterizes cellular crosstalk by sorting and sequencing physically interacting cells.
Audience Academic
Author David, Eyal
Medaglia, Chiara
Baran, Yael
Li, Baoguo
Blecher-Gonen, Ronnie
Salame, Tomer-Meir
Zada, Mor
Cohen, Merav
Mayer, Johannes U.
Giladi, Amir
Amit, Ido
Ronchese, Franca
Bost, Pierre
Tanay, Amos
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  fullname: Medaglia, Chiara
  organization: Department of Immunology, Weizmann Institute of Science, Department of Microbiology and Molecular Medicine, University of Geneva Medical School
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  surname: Baran
  fullname: Baran, Yael
  organization: Department of Computer Science and Applied Mathematics, Department of Biological Regulation, Weizmann Institute of Science
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  organization: Department of Immunology, Weizmann Institute of Science
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  organization: Flow Cytometry Unit, Department of Biological Services, Weizmann Institute of Science
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  orcidid: 0000-0001-9419-3824
  surname: Tanay
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  orcidid: 0000-0003-2968-877X
  surname: Amit
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  organization: Department of Immunology, Weizmann Institute of Science
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Snippet Crosstalk between neighboring cells underlies many biological processes, including cell signaling, proliferation and differentiation. Current single-cell...
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StartPage 629
SubjectTerms 631/250/516
631/337/2019
631/61/191/2018
631/61/212/2019
Agriculture
Algorithms
Analysis
Animals
Animals, Newborn
Bioinformatics
Biological activity
Biomedical and Life Sciences
Biomedical Engineering/Biotechnology
Biomedicine
Biotechnology
Cell Communication
Cell differentiation
Cell interactions
Cell migration
Cell proliferation
Cells, Cultured
Computational Biology
Computer applications
Crosstalk
Dendritic cells
Dendritic Cells - chemistry
Dendritic Cells - cytology
Female
Flow Cytometry
Gene Expression Profiling - methods
Gene mapping
Gene sequencing
Genomics
Immunoregulation
Life Sciences
Lung - chemistry
Lung - cytology
Lymph nodes
Lymphocytes
Lymphocytes T
Mice
Neonates
Ribonucleic acid
RNA
Sequence Analysis, RNA
Single-Cell Analysis - methods
T cells
T-Lymphocytes - chemistry
T-Lymphocytes - cytology
Title Dissecting cellular crosstalk by sequencing physically interacting cells
URI https://link.springer.com/article/10.1038/s41587-020-0442-2
https://www.ncbi.nlm.nih.gov/pubmed/32152598
https://www.proquest.com/docview/2401058699
https://www.proquest.com/docview/2476756815
https://search.proquest.com/docview/2375911708
Volume 38
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