Collective polarization model for gradient sensing via Dachsous-Fat intercellular signaling

Significance Morphogenesis is a biological process that generates the physical form and structure of multicellular organisms. Although many of the genes controlling morphogenesis are known, little is understood of the mechanisms that define tissue shape and size. Prominent among these mechanisms is the contact signaling between cells mediated by two cell adhesion-type proteins Dachsous and Fat, which regulate cell division in response to the spatially graded distribution of morphogens, factors governing tissue patterning and growth. Here, based on the known behavior of this signaling pathway, we develop a model of the underlying mechanism that relates signaling to the polarization of Dachsous/Fat heterodimers on cell interfaces. This model explains observed phenotypes, makes quantitative predictions, and provides a framework for further experimental studies. Dachsous-Fat signaling via the Hippo pathway influences proliferation during Drosophila development, and some of its mammalian homologs are tumor suppressors, highlighting its role as a universal growth regulator. The Fat/Hippo pathway responds to morphogen gradients and influences the in-plane polarization of cells and orientation of divisions, linking growth with tissue patterning. Remarkably, the Fat pathway transduces a growth signal through the polarization of transmembrane complexes that responds to both morphogen level and gradient. Dissection of these complex phenotypes requires a quantitative model that provides a systematic characterization of the pathway. In the absence of detailed knowledge of molecular interactions, we take a phenomenological approach that considers a broad class of simple models, which are sufficiently constrained by observations to enable insight into possible mechanisms. We predict two modes of local/cooperative interactions among Fat–Dachsous complexes, which are necessary for the collective polarization of tissues and enhanced sensitivity to weak gradients. Collective polarization convolves level and gradient of input signals, reproducing known phenotypes while generating falsifiable predictions. Our construction of a simplified signal transduction map allows a generalization of the positional value model and emphasizes the important role intercellular interactions play in growth and patterning of tissues.