Exploiting Noise to Engineer Adaptability in Synthetic Multicellular Systems

Abstract Multicellular systems feature a stunning array of complex emergent behaviors that are compelling engineering targets. These behaviors often arise from cells taking on different roles as dictated by their phenotypes. To generate phenotypic heterogeneity, the metazoan systems usually of interest to biomedical engineers primarily exploit stable differentiation. In contrast, multicellular microbial systems often employ reversible differentiation to allow for plasticity in coping with changing environmental conditions. These microbial systems often exploit molecular stochasticity, or noise, to drive differentiation into new cell phenotypes for emergent multicellular properties such as antibiotic resistance or collective motility. We review the role noise plays in natural and synthetic expression systems and advocate for continued investment in new synthetic biology tools to precisely control noise to engineer multicellular systems. Exploiting these tools will allow us to create robust and scalable synthetic multicellular systems that both recreate natural functions and create new behaviors and features.