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| Status |
Public on Nov 01, 2019 |
| Title |
Dissection of intercellular communication using the transcriptome-based framework ICELLNET |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by array
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| Summary |
Cell-to-cell communication can be inferred from ligand-receptor expression in cell transcriptomic datasets. However, important challenges remain: 1) global integration of cell-to-cell communication, 2) biological interpretation, and 3) 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 3 datasets generated through RNA-seq, single-cell RNA-seq, and microarray. ICELLNET reveal 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 profile(s).
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| Overall design |
transcriptomes of 6 different donors (biological replicates) were studied at 2 different time points : H4 and H8. 4 conditions were generated at both time points : medium + IgG, LPS + IgG, LPS + anti-TNFR, LPS + anti-IL10R. Microarray analysis were performed at both time points to decipher the contribution of TNF and IL-10 auto-regulatory loops in the control of cell-cell communication
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| Contributor(s) |
Noël F, Massenet-Regad L, Carmi-Levy I, Cappuccio A, Grandclaudon M, Trichot C, Kieffer Y, Mechta-Grigoriou F, Soumelis V |
| Citation(s) |
33597528 |
| Submission date |
Oct 31, 2016 |
| Last update date |
Mar 10, 2021 |
| Contact name |
Vassili Soumelis |
| Organization name |
INSERM
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| Department |
U976 - HIPI
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| Lab |
Human systems immunology and inflammatory networks
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| Street address |
1 avenue Claude Vellefaux
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| City |
Paris |
| ZIP/Postal code |
75010 |
| Country |
France |
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| Platforms (1) |
| GPL17692 |
[HuGene-2_1-st] Affymetrix Human Gene 2.1 ST Array [transcript (gene) version] |
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| Samples (64)
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| Relations |
| BioProject |
PRJNA351847 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE89342_RAW.tar |
308.7 Mb |
(http)(custom) |
TAR (of CEL) |
| Processed data included within Sample table |
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