Dissecting cellular crosstalk by sequencing physically interacting cells

Giladi, Amir; Cohen, Michal; 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

doi:10.1038/s41587-020-0442-2

Cited by 210 publications

(240 citation statements)

References 60 publications

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“…The study of spatial proximity in interacting cells is an emerging approach 129 . One technology for profiling these physical interactions, PIC-seq, uses cell sorting to acquire and transcriptionally profile physically interacting cells (PICs) through massively parallel single-cell RNA-seq 130 . The study authors presented an algorithm for deconvolving the data to capture signals from intercellular physical interactions.…”

Section: Challenges and Future Directionsmentioning

confidence: 99%

Deciphering cell–cell interactions and communication from gene expression

et al. 2020

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Section: Challenges and Future Directionsmentioning

confidence: 99%

Deciphering cell–cell interactions and communication from gene expression

et al. 2020

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“…Signaling crosstalk via soluble and membrane-bound factors is critical for informing diverse cellular decisions, including decisions to activate mitotic division or programmed cell death, undergo migration or differentiate along the lineage [1][2][3] . Single-cell RNAsequencing (scRNA-seq) technologies have led to discovery of cellular heterogeneity and differentiation trajectories at unprecedented resolution level 4,5 .…”

Section: Introductionmentioning

confidence: 99%

Inference and analysis of cell-cell communication using CellChat

Jin¹,

Guerrero‐Juarez²,

Zhang³

et al. 2020

Preprint

254

417

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Understanding global communications among cells requires accurate representation of cell-cell signaling links and effective systems-level analyses of those links. We constructed a database of interactions among ligands, receptors and their cofactors that accurately represents known heteromeric molecular complexes. Based on mass action models, we then developed CellChat, a tool that is able to quantitively infer and analyze intercellular communication networks from single-cell RNA-sequencing (scRNA-seq) data. CellChat predicts major signaling inputs and outputs for cells and how those cells and signals coordinate for functions using network analysis and pattern recognition approaches. Through manifold learning and quantitative contrasts, CellChat classifies signaling pathways and delineates conserved and context-specific pathways across different datasets. Applications of CellChat to several mouse skin scRNA-seq datasets for embryonic development and adult wound healing shows its ability to extract complex signaling patterns, both previously known as well as novel. Our versatile and easy-to-use toolkit CellChat and a web-based Explorer (http://www.cellchat.org/) will help discover novel intercellular communications and build a cell-cell communication atlas in diverse tissues.

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“…A small fraction of CD45.1 + MHCII + doublet events was detected, indicative of the stable interactions between the CD45.1 + OT-II cells and the MHCII-expressing host cells ( Figure 4G and Continued on next page S6A). The majority of these doublets were formed in vivo in the dLN and not ex vivo in the cell suspension, as no fluorochrome exchange was observed when two sets of LN cells were separately stained for CD45.1 and MHCII with a different set of fluorochromes and mixed together in vitro as previously described ( Figure S6B) (Giladi et al, 2020;Reinhardt et al, 2009). The CD45.1 + MHCII + doublets were significantly reduced when the mice were immunized with papain alone, indicating the antigendependency of this interaction ( Figure S6C-S6E).…”

Section: Cd301b + Dcs Directly Present Soluble Foreign Antigens To CDmentioning

confidence: 81%

Optimal CD4T Cell Priming in Lymph Nodes Requires Repertoire Scanning by CD301b⁺Migratory cDC2 Cells

Tatsumi

Codrington

Kumamoto

2020

Preprint

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SummaryActivation of CD4T cells by conventional dendritic cells (cDC) is pivotal in adaptive immunity. However, while the activation mechanism of antigen-specific CD4T cells has been extensively studied, the cellular mechanism that leads to the selection of cognate CD4T cell clones out of the polyclonal pool is incompletely understood. Here, we show that, in the reactive lymph nodes, newly homed naive polyclonal CD4T cells are temporarily retained before leaving the lymph node. This stop-and-go traffic of CD4T cells provides an adequate time window for efficient scanning and timely priming of antigen-specific clones. Mechanistically, upon immunization, CD301b+ DCs, a major subset of migratory cDC2 cells, quickly migrate to the draining lymph node and settle in the areas near the high endothelial venules, where they retain incoming polyclonal CD4T cells through MHCII-dependent but antigen-independent mechanisms while concurrently providing cognate stimuli to prime antigen-specific CD4T cells. These results indicate that CD301b+ DCs function as an immunological “display window” for CD4T cells to efficiently scan their antigen specificity.Graphical AbstractHighlightsNewly homed polyclonal CD4T cells are temporarily retained in the reactive lymph nodes.Depletion of CD301b+ DCs results in shorter dwell time of CD4T cells in the draining lymph node and delayed priming of antigen-specific clones.The transient retention of polyclonal CD4T cells in the draining lymph node requires MHCII expression on CD301b+ DCs but not cognate antigen.CD301b+ DCs are required for robust expansion of rare antigen-specific CD4T cell clones and their skewing toward Th2 cells.

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Dissecting cellular crosstalk by sequencing physically interacting cells

Cited by 210 publications

References 60 publications

Deciphering cell–cell interactions and communication from gene expression

Deciphering cell–cell interactions and communication from gene expression

Inference and analysis of cell-cell communication using CellChat

Optimal CD4T Cell Priming in Lymph Nodes Requires Repertoire Scanning by CD301b⁺Migratory cDC2 Cells

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Dissecting cellular crosstalk by sequencing physically interacting cells

Cited by 210 publications

References 60 publications

Deciphering cell–cell interactions and communication from gene expression

Deciphering cell–cell interactions and communication from gene expression

Inference and analysis of cell-cell communication using CellChat

Optimal CD4T Cell Priming in Lymph Nodes Requires Repertoire Scanning by CD301b+Migratory cDC2 Cells

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Product

Resources

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Optimal CD4T Cell Priming in Lymph Nodes Requires Repertoire Scanning by CD301b⁺Migratory cDC2 Cells