A draft network of ligand–receptor-mediated multicellular signalling in human

By Jordan A. Ramilowski, Tatyana Goldberg, J. Harshbarger, Edda Kloppman, M. Lizio, Venkata P. Satagopam, M. Itoh, H. Kawaji, Piero Carninci, Burkhard Rost and 1 more. Nature Communications, 2015

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Cell-to-cell communication across multiple cell types and tissues strictly governs proper functioning of metazoans and extensively relies on interactions between secreted ligands and cell-surface receptors. Herein, we present the first large-scale map of cell-to-cell communication between 144 human primary cell types. We reveal that most cells express tens to hundreds of ligands and receptors to create a highly connected signalling network through multiple ligand–receptor paths. We also observe extensive autocrine signalling with approximately two-thirds of partners possibly interacting on the same cell type. We find that plasma membrane and secreted proteins have the highest cell-type specificity, they are evolutionarily younger than intracellular proteins, and that most receptors had evolved before their ligands. We provide an online tool to interactively query and visualize our networks and demonstrate how this tool can reveal novel cell-to-cell interactions with the prediction that mast cells signal to monoblastic lineages via the CSF1–CSF1R interacting pair. Cell-to-cell communication relies upon interactions between secreted ligands and cell surface receptors. Here, Ramilowski et al.present a draft cell-to-cell communication network based on expression of ligand-receptor pairs in 144 different human cell types.

Subfields: Cell Biology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/9c31565327e83f87bcee3e03d87f402141c8e6cb

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Citations in the corpus

Cellular and inter-cellular rewiring of the human colon during ulcerative colitis (2019, methodology): “To more generally chart the rewiring of cell-cell interactions during colitis, we mapped receptor-ligand pairs (Ramilowski et al., 2015) onto cell subsets to construct a putative cellcell interaction network across disease states (Figure 6A–C), and identified pairs of cell Smillie et al.”
Fibroblast Heterogeneity and Immunosuppressive Environment in Human Breast Cancer. (2018, neutral): “10 Cancer Cell 33, 1–17, March 12, 2018 Segura et al., 2013; Barreira da Silva et al., 2015; Ramilowski et al., 2015).”
CellPhoneDB: inferring cell–cell communication from combined expression of multi-subunit ligand–receptor complexes (2020, methodology): “To improve the speed and efficiency of our protocol and facilitate its broad accessibility, we integrated subsampling as described in Hie et al.(2).”
The Human Cell Atlas (2017, background): “Cell-cell interactomes have also been inferred from profiles of purified cell populations, based on the secreted and cell surface molecules that they express (Ramilowski et al., 2015).”
Spatial components of molecular tissue biology (2022, neutral): “Spatial assays are also used to profile the effects of cell–cell communication occurring at short length scales ( µ m) in cellular neighborhoods 20,21 via physical contact, compound exchange via tight junctions and synapses, and paracrine or autocrine signaling.”
Single-Cell Analysis of Crohn’s Disease Lesions Identifies a Pathogenic Cellular Module Associated with Resistance to Anti-TNF Therapy (2019, methodology): “Ligand-Receptor Analysis—We examined specific ligand-receptor pairs by restricting our analysis to cytokine/chemokine-receptor pairs validated experimentally (Ramilowski et al., 2015).”
A Cancer Cell Program Promotes T Cell Exclusion and Resistance to Checkpoint Blockade (2018, neutral): “Cell-cell interaction network—We generated genome-scale cell-cell interactions networks by integrating (1) protein-protein interactions that were previously assembled by (Ramilowski et al., 2015) as cognate ligand- receptor pairs, with (2) cell subtype specific signatures from the singlecell profile”