A robust, library-based, optimization-driven method for automatic gene circuit design

Automatic design of synthetic circuits is a major challenge in synthetic biology, which promises rapid development of standardized, scalable, and modular designs. Current methods in the field mostly rely on heuristic algorithms for finding synthetic circuits that function within a specific parameter range, and user-defined constraints. Here, we introduce a three-phase framework, and the technique of mixed integer nonlinear programming (MINLP) to find the optimal assignment of biological parts to a fixed circuit topology, given user-defined constraints and a desired steady-state or temporal profile. We evaluated the proposed framework in a toggle switch and a band detector circuit, two non-linear synthetic circuits that have been experimentally constructed before. By using experimentally characterized mutant promoter libraries and a user defined topology as inputs, our optimization framework results in a rapid and reproducible convergence to a synthetic circuit that exhibits the desired characteristics and temporal expression profiles. The work described here is a step towards a unifying, biologically-relevant framework for the automated design of biological circuits with user-defined temporal profiles and constraints.