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Dissection of intercellular communication using the transcriptome-based framework ICELLNET
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DOI：10.1038/s41467-021-21244-x.png)
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Abstract
En 中文
Cell-to-cell communication can be inferred from ligand-receptor expression in cell transcriptomic datasets. However, important challenges remain: global integration of cell-to-cell communication; biological interpretation; and application to individual cell population transcriptomic profiles. We develop ICELLNET, a transcriptomic-based framework integrating: 1) an original expert-curated database of ligand-receptor interactions accounting for multiple subunits expression; 2) quantification of communication scores; 3) the possibility to connect a cell population of interest with 31 reference human cell types; and 4) three visualization modes to facilitate biological interpretation. We apply ICELLNET to three datasets generated through RNA-seq, single-cell RNA-seq, and microarray. ICELLNET reveals autocrine IL-10 control of human dendritic cell communication with up to 12 cell types. Four of them (T cells, keratinocytes, neutrophils, pDC) are further tested and experimentally validated. In summary, ICELLNET is a global, versatile, biologically validated, and easy-to-use framework to dissect cell communication from individual or multiple cell-based transcriptomic profiles. Bulk and single-cell transcriptomic data can be a source of novel insights into how cells interact with each other. Here the authors develop ICELLNET, a global, biologically validated, and easy-to-use framework to dissect cell communication from individual or multiple cell-based transcriptomic profiles.
Keywords:
PLASMACYTOID DENDRITIC CELLS
CYTOKINE
RECEPTOR
IL-10
INTERLEUKIN-10
NEUTROPHILS
DISCOVERY
RESPONSES
BLOCKADE
GAMMA
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