Design and Implementation of Genetic Circuits for Complex Biological Functions in Plants

Plants and photosynthetic organisms provide a means towards sustainable life on Earth through the production of bio-based systems for food, materials, energy and more. Efficient and predictable plant-based production systems must rely on the implementation of complex synthetic biological circuits for gene regulation and decision-making strategies in cells and tissues, especially through use of digital and analog computation. Achieving predictable function of these circuits is further complicated by the multicellular nature of plants. Using computational models and quantitatively defined genetic parts, we have designed and implemented synthetic genetic circuits that function in whole plants with predictability. Computationally re-designed ligand-binding proteins are powerful tools for the development of biosensors for small molecules. By linking the ligand binding event to transcriptional activation of downstream genes, we have shown that plants can be engineered with sensitive and specific biosensing capabilities. In the absence of ligand, the sensing protein is rendered unstable, and does not accumulate in the cell. Upon ligand binding, the protein is stabilized and binds specifically to operator sequences in the promoter region of genes of interest. The system is modular, in the sense that input can be provided by newly re-designed small molecule binding proteins. Reporter genes, as well as functional genes, can be used as output. This biosensing system can be used to detect hazards in the environment, as well as a controllable component of more complex genetic circuits. Biosensors in multicellular organisms may suffer from a high detection limit, where high concentrations or long exposures to the ligand are necessary for triggering a response. To circumvent this limitation, we have also engineered positive feedback genetic circuits that amplify the input signal several fold in Arabidopsis plants. These circuits may also provide “memory” of detection, i.e., transient exposure to the ligand results in a permanent response. The next generation of transgenic crops will contain small gene networks that have decision-making properties, with the ability to reshape patterns of plant metabolism and growth, for applications that range from security to bio-manufacturing.