Synthetic cell-based materials extract positional information from morphogen gradients

Abstract

Dynamic biomaterials composed of synthetic cellular structures have the potential to adapt and functionally differentiate guided by physical and chemical cues from their environment. Inspired by developing biological systems, which efficiently extract positional information from chemical morphogen gradients in the presence of environmental uncertainties, we here investigate the analogous question: how well can a synthetic cell determine its position within a synthetic multicellular structure? In order to calculate positional information in such systems, we created and analyzed a large number of replicas of synthetic cellular assemblies, which were composed of emulsion droplets connected via lipid bilayer membranes. The droplets contained cell-free two-node feedback gene circuits that responded to gradients of a genetic inducer acting as a morphogen. We found that in our system, simple anterior-posterior differentiation is possible, but positional information is limited by gene expression noise, and is also critically affected by the temporal evolution of the morphogen gradient and the life-time of the cell-free expression system contained in the synthetic cells. Using a 3D printing approach, we demonstrate morphogen-based differentiation also in larger tissue-like assemblies.