Emergent properties of collective gene-expression patterns in multicellular systems

Abstract

Multicellular organisms contain diverse tissues built from multiple cell types. It remains unclear how large numbers of interacting cells can precisely coordinate their gene expression during tissue self-organization. We develop a generalized model of multicellular gene expression that includes intracellular and intercellular gene interactions in tissue-like collectives. Motivated by modern transcriptomics, we represent multistable cellular phenotypes by mapping the binarized transcriptional patterns of individual cells onto Hopfield networks. We incorporate spatial cell-cell signaling by coupling transcriptional states of adjacent cells on a square lattice. We show that tuning the intercellular signaling strength results in a cascade of transitions toward different collective states with emergent single-cell phenotypes. Despite an enormous number of possible tissue states, we find that intercellular signaling tends to stabilize a small number of compositionally and spatially simple tissue types. These results establish a theoretical framework to investigate how cell collectives self-organize into distinct stable patterns.