%0 Journal Article %A Kevin Simpson %A Juan Keymer %A Fernán Federici %T Spatial biology of Ising-like synthetic genetic networks %D 2023 %R 10.1101/2023.05.10.540292 %J bioRxiv %P 2023.05.10.540292 %X Understanding how spatial patterns of gene expression emerge from the interaction of individual gene networks is a fundamental challenge in biology. Developing a synthetic experimental system with a common theoretical framework that captures the emergence of short- and long-range spatial correlations (and anti-correlations) from interacting gene networks could serve to uncover generic scaling properties of these ubiquitous phenomena. Here, we combine synthetic biology, statistical mechanics models and computational simulations to study the spatial behavior of synthetic gene networks (SGNs) in Escherichia coli colonies. Guided by the combined mechanisms of the contact process lattice simulation and two-dimensional Ising model (CPIM), we describe the spatial behavior of bi-stable and chemically-coupled SGNs that self-organize into patterns of long-range correlations with power-law scaling or short-range anti-correlations. These patterns, resembling ferromagnetic and anti-ferromagnetic configurations of the Ising model near critical points, maintain their scaling properties upon changes in growth rate and cell shape. This robust spatial behavior could provide insights into the study and engineering of self-organizing patterns of genetic networks in eukaryotic tissues and bacterial consortia.Competing Interest StatementThe authors have declared no competing interest. %U https://www.biorxiv.org/content/biorxiv/early/2023/05/11/2023.05.10.540292.full.pdf