NicheNet: modeling intercellular communication by linking ligands to target genes

Browaeys, Robin; Saelens, Wouter; Saeys, Yvan

doi:10.1038/s41592-019-0667-5

Cited by 1,176 publications

(1,396 citation statements)

References 57 publications

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“…To explore this possibility, we adapted a tool initially designed to explore intercellular communication in bulk and single-cell expression data to test autocrine signal activation (Browaeys et al, 2019). With this approach, and using genes associated with both demethylation clusters with significant expression differences (abs(log 2(FC)) ≥ 1 and adjusted P < 0.05) as input, we inferred potential ligands that can explain these differences in expression ( Figure 4A).…”

Section: Vdr Induces Il-6 Upregulation In Toldcs Leading To Stat3 Acmentioning

confidence: 99%

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Vitamin D receptor and STAT3 cooperate to establish TET2-mediated tolerogenesis

Català-Moll

Ciudad

et al. 2020

Preprint

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The active form of vitamin D, 1,25-dihydroxyvitamin D3 (1,25(OH)2D3), induces stable tolerogenesis in dendritic cells (DCs). This process involves the vitamin D receptor (VDR), which translocates to the nucleus, binds its cognate genomic sites, and promotes epigenetic and transcriptional remodeling. In this study, we investigated the interplay between the VDR and other transcription factors to induce DNA methylation changes that might provide phenotypic stability to the tolerogenic phenotype of DCs.Our study reveals the occurrence of vitamin D-specific DNA demethylation and transcriptional activation at VDR binding sites associated with the acquisition of tolerogenesis. Tolerogenic properties in DCs are acquired together with activation of the IL6-JAK-STAT3 pathway. In fact, VDR directly binds the IL6 gene, and JAK2-mediated STAT3 phosphorylation is specific to vitamin D stimulation. VDR and the phosphorylated form of STAT3 interact with each other and with methylcytosine dioxygenase TET2 following vitamin D treatment. Most importantly, pharmacological inhibition of STAT3 phosphorylation reverts the vitamin-induced tolerogenic properties of DCs. Our results reveal an interplay between VDR and STAT3 leading to the DNA demethylation-dependent induction of tolerogenesis by vitamin D.

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Section: Vdr Induces Il-6 Upregulation In Toldcs Leading To Stat3 Acmentioning

confidence: 99%

“…Inference of TF activities from expression values were calculated using DoRothEA (Garcia-Alonso et al, 2019). We used the nichenetr package (Browaeys et al, 2019) to predict ligand activity.…”

Section: Co-immunoprecipitation (Co-ip)mentioning

confidence: 99%

Vitamin D receptor and STAT3 cooperate to establish TET2-mediated tolerogenesis

Català-Moll

Ciudad

et al. 2020

Preprint

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“…Existing tools infer communication between cells from scRNAseq datasets 4,5,7 . We have designed ICELLNET as a versatile tool, which can be applied to bulk cell profiles (Affymetrix or RNAseq) widely available in public databases, but also to fully documented scRNAseq datasets to infer communication between clusters or groups of cells.…”

Section: Discussionmentioning

confidence: 99%

ICELLNET: a transcriptome-based framework to dissect intercellular communication

Noël

Massenet-Regad

Carmi-Levy

et al. 2020

Preprint

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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 developed ICELLNET, a transcriptomic-based framework integrating: 1) an original expertcurated 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 (BioGPS), and 4) three visualization modes to facilitate biological interpretation. We applied ICELLNET to uncover different communication in breast cancer associated fibroblast (CAF) subsets. ICELLNET also revealed autocrine IL-10 as a switch to control human dendritic cell communication with up to 12 other cell types, four of which were experimentally validated. In summary, ICELLNET is a global, versatile, biologically validated, and easy-to-use framework to dissect cell communication from single or multiple cell-based transcriptomic profile(s). IntroductionCell-to-cell communication is at the basis of the higher order organization observed in tissues, organs, and organisms, at steady-state and in response to stress. It involves a "messenger" or "sender" cell, which transmits information signals to a "receiving" or "target" cell. Information is generally coded in the form of a chemical molecule that is sensed by the target cell through a cognate receptor.Multiple cells or cell types communicating with each other form cell communication networks.In mammalian organisms, endocrine communication involves cells that may be at very distant anatomical sites. However, cell communication also takes place locally through cell-to-cell contacts, or through inflammatory molecules. Cytokines and other mediators can be involved in distant as well as local communication 1-3 . Hence, when deciphering cell-to-cell communication, one should account for potential signals coming both from spatially proximal and distal cells.Most studies in the past decades have focused on a limited number of communication molecules in a given anatomical site or physiological process. The availability of large-scale transcriptomic datasets from several cell types, tissue locations, and cell activation states, opened the possibility of reconstructing cell-to-cell interactions based on the expression of specific ligand-receptor pairs on sender and target cells, respectively. Many of them exploit single cell RNAseq datasets to infer communication between groups of cells within the same dataset 4-7 . Despite leading to interesting and often innovative hypotheses 4,6,8 , these methods do not integrate putative signals that may come from more distant cells. Also, they cannot be applied to bulk transcriptomic data derived from a given cell population. Such datasets are numerous in public databases, and can be a source of novel insights into how...

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“…We compared CytoTalk to six published algorithms, four designed for predicting ligand-receptor pairs 1-4 and two designed for predicting full signaling pathways based on known pathway annotations 7,8 . Since a comprehensive list of true ligand-receptor pairs are not available for the three cell type pairs, we first asked what fractions of the predicted ligand-receptor pairs are shared among the six methods.…”

Section: Performance Evaluation Using Spatial Transcriptomics Datamentioning

confidence: 99%

“…Due to these two features, simply examining expression levels of ligand and receptor genes cannot reliably capture the overall activities of signaling pathways and interactions among them 5,6 . As a step forward, Wang et al 7 developed SoptSC and Browaeys et al 8 developed NicheNet to identify both ligandreceptor pairs and genes downstream of them. However, these methods are based on known annotations of signaling pathways.…”

Section: Introductionmentioning

confidence: 99%

CytoTalk:De novoconstruction of signal transduction networks using single-cell RNA-Seq data

Peng

Gao

et al. 2020

Preprint

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Single-cell technology has opened the door for studying signal transduction in a complex tissue at unprecedented resolution. However, there is a lack of analytical methods for de novo construction of signal transduction pathways using single-cell omics data. Here we present CytoTalk, a computational method for de novo constructing cell type-specific signal transduction networks using single-cell RNA-Seq data. CytoTalk first constructs intracellular and intercellular gene-gene interaction networks using an information-theoretic measure between two cell types. Candidate signal transduction pathways in the integrated network are identified using the prizecollecting Steiner forest algorithm. We applied CytoTalk to a single-cell RNA-Seq data set on mouse visual cortex and evaluated predictions using high-throughput spatial transcriptomics data generated from the same tissue. Compared to published methods, genes in our inferred signaling pathways have significantly higher spatial expression correlation only in cells that are spatially closer to each other, suggesting improved accuracy of CytoTalk. Furthermore, using single-cell RNA-Seq data with receptor gene perturbation, we found that predicted pathways are enriched for differentially expressed genes between the receptor knockout and wild type cells, further validating the accuracy of CytoTalk. In summary, CytoTalk enables de novo construction of signal transduction pathways and facilitates comparative analysis of these pathways across tissues and conditions.

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NicheNet: modeling intercellular communication by linking ligands to target genes

Cited by 1,176 publications

References 57 publications

Vitamin D receptor and STAT3 cooperate to establish TET2-mediated tolerogenesis

Vitamin D receptor and STAT3 cooperate to establish TET2-mediated tolerogenesis

ICELLNET: a transcriptome-based framework to dissect intercellular communication

CytoTalk:De novoconstruction of signal transduction networks using single-cell RNA-Seq data

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