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  Systematic Identification of Cell-Cell Communication Networks in the Developing Brain

Sheikh, B. N., Bondareva, O., Guhathakurta, S., Tsang, T. H., Sikora, K., Aizarani, N., et al. (2019). Systematic Identification of Cell-Cell Communication Networks in the Developing Brain. iScience, 21, 273-287. doi:org/10.1016/j.isci.2019.10.026.

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Sheikh, Bilal N.1, Author
Bondareva, Olga2, Author
Guhathakurta, Sukanya1, Author
Tsang, Tsz Hong1, Author
Sikora, Katarzyna1, Author
Aizarani, Nadim1, Author
Sagar, Sagar1, Author
Holz, Herbert1, Author
Grün, Dominic1, Author           
Hein, Lutz2, Author
Akhtar, Asifa1, Author           
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1Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society, ou_2243642              
2External Organizations, ou_persistent22              

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 Abstract: Since the generation of cell-type specific knockout models, the importance of inter-cellular communication between neural, vascular, and microglial cells during neural development has been increasingly appreciated. However, the extent of communication between these major cell populations remains to be systematically mapped. Here, we describe EMBRACE (embryonic brain cell extraction using FACS), a method to simultaneously isolate neural, mural, endothelial, and microglial cells to more than 94% purity in ∼4 h. Utilizing EMBRACE we isolate, transcriptionally analyze, and build a cell-cell communication map of the developing mouse brain. We identify 1,710 unique ligand-receptor interactions between neural, endothelial, mural, and microglial cells in silico and experimentally confirm the APOE-LDLR, APOE-LRP1, VTN-KDR, and LAMA4-ITGB1 interactions in the E14.5 brain. We provide our data via the searchable “Brain interactome explorer”, available at https://mpi-ie.shinyapps.io/braininteractomeexplorer/. Together, this study provides a comprehensive map that reveals the richness of communication within the developing brain.

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Language(s): eng - English
 Dates: 2019-11-22
 Publication Status: Issued
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 Rev. Type: Peer
 Identifiers: DOI: org/10.1016/j.isci.2019.10.026
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Title: iScience
Source Genre: Journal
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Pages: - Volume / Issue: 21 Sequence Number: - Start / End Page: 273 - 287 Identifier: -