A synthetic multi-cellular network of coupled self-sustained oscillators

• Published in: PloS one Vol. 12; no. 6; p. e0180155
• Main Authors: Fernández-Niño, Miguel, Giraldo, Daniel, Gomez-Porras, Judith Lucia, Dreyer, Ingo, González Barrios, Andrés Fernando, Arevalo-Ferro, Catalina
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 29.06.2017; Public Library of Science (PLoS)
• Subjects: Artificial neural networks; Bacterial Physiological Phenomena; Bacterial Proteins - genetics; Bacterial Proteins - metabolism; Behavior; Biology and Life Sciences; Cellular communication; Cellular signal transduction; Circuits; Clustering; Communication; E coli; Engineering; Engineering and Technology; Gene expression; Green Fluorescent Proteins - genetics; Integration; Mathematical models; Models, Biological; Modular design; Modular engineering; Neural Networks (Computer); Oscillators; Physical Sciences; Population; Quorum Sensing; Research and Analysis Methods; Switches; Switching theory; Synchronization; Synthetic biology; Germany; Colombia
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0180155

Engineering artificial networks from modular components is a major challenge in synthetic biology. In the past years, single units, such as switches and oscillators, were successfully constructed and implemented. The effective integration of these parts into functional artificial self-regulated networks is currently on the verge of breakthrough. Here, we describe the design of a modular higher-order synthetic genetic network assembled from two independent self-sustained synthetic units: repressilators coupled via a modified quorum-sensing circuit. The isolated communication circuit and the network of coupled oscillators were analysed in mathematical modelling and experimental approaches. We monitored clustering of cells in groups of various sizes. Within each cluster of cells, cells oscillate synchronously, whereas the theoretical modelling predicts complete synchronization of the whole cellular population to be obtained approximately after 30 days. Our data suggest that self-regulated synchronization in biological systems can occur through an intermediate, long term clustering phase. The proposed artificial multicellular network provides a system framework for exploring how a given network generates a specific behaviour.