Modelling multicellular coordination by bridging cell-cell communication and intracellular regulation through multilayer networks

In multicellular organisms, cells with various roles and locations coordinate to provide systemic and cohesive response to perturbations. These complex behaviors emerge from a complex interplay between intracellular regulation and intercellular signals that mediate cell-cell communication. While single-cell technologies opened the possibility of studying both, most methods focus solely on one of these aspects. Thus, they are only able to partially recover in vivo and multicellular behaviors.

We here introduce ReCoN (REconstruction of multicellular COordination Networks from single-cell data), a framework combining intracellular gene regulation and cell-cell communication to provide insights into multicellular coordination from single-cell data. First, ReCoN infers from single-cell data a heterogeneous multilayer network containing both cell-type-specific intracellular subnetworks and ligand-receptor interactions. Through random walk with restart explorations, ReCoN then infers the response of each cell type to both intra- and extracellular perturbations, such as a gene knock-out or a cytokine, respectively.

ReCoN was evaluated on predicting the in vivo response of immune cell-types to different cytokines and on recovering cardiac cell-type response in heart failure. It highlighted the role of indirect effects, where cells emit secondary messengers in response to the initial perturbation to coordinate multicellular transcriptomic responses. Additionally, ReCoN predicted distinct fibroblast states emerging in different microenvironments reconstructed from spatial data. ReCoN provides an interpretable modeling framework for multicellular systems that allows for the simulation of perturbations, including the assessment of the cellular selectivity of these treatments in vivo . Ultimately, it can help design patient-specific molecular therapies.

Graphical abstract

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