Tensor-cell2cell v2 unravels coordinated dynamics of protein- and metabolite-mediated cell-cell communication.

Abstract

Cell-cell communication dynamically changes across time while involving diverse cell populations and ligand types such as proteins and metabolites. While single-cell transcriptomics enables its inference, existing tools typically analyze ligand types separately and overlook their coordinated activity. Here, we present Tensor-cell2cell v2, a computational tool that can jointly analyze protein- and metabolite-mediated communication over time using coupled tensor component analysis, while preserving each modality of inferred communication scores independently, as well as their data structures and distributions. Applied to brain organoid development, Tensor-cell2cell v2 uncovers dynamic, coordinated communication programs involving key proteins and metabolites across relevant cell types across specific time points.