Model-guided combinatorial optimization of complex synthetic gene networks.

ABSTRACT: Constructing gene circuits that satisfy quantitative performance criteria has been a long-standing challenge in synthetic biology. Here, we show a strategy for optimizing a complex three-gene circuit, a novel proportional miRNA biosensor, using predictive modeling to initiate a search in the phase space of sensor genetic composition. We generate a library of sensor circuits using diverse genetic building blocks in order to access favorable parameter combinations and uncover specific genetic compositions with greatly improved dynamic range. The combination of high-throughput screening data and the data obtained from detailed mechanistic interrogation of a small number of sensors was used to validate the model. The validated model facilitated further experimentation, including biosensor repr

SUBMITTER: Schreiber J 

PROVIDER: S-EPMC5199127 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature