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Cell-cell communication involves multiple classes of molecules, diverse interacting cells, and complex spatiotemporal dynamics. While this communication can be inferred from single-cell RNA-seq, no computational methods can account for both protein and metabolite ligands simultaneously, while also accounting for the temporal dynamics. We adapted Tensor-cell2cell here to study several time points simultaneously and jointly incorporate both ligand types. Our approach detects temporal dynamics of cell-cell communication during brain development, allowing for the detection of the concerted use of key protein and metabolite ligands by pertinent interacting cells.