Synthetic Biochemical Devices for Programmable Dynamic Behavior

The ability to harness biomolecules as tools for systematic engineering is fundamental to future developments of biotechnology and nanotechnology. Especially suitable for such applications are nucleic acid-based circuits with predictable interactions, allowing for rational design of circuit functions and dynamics. Here, we focus on synthetic transcriptional circuits utilizing the modular architecture of nucleic acid templates and the catalytic power of natural enzymes. The programmability of dynamic behaviors for synthetic circuits is illustrated through elementary circuits such as an adapter, a bistableBistable switch, and several oscillators. Further, the effect of downstream processes on the central dynamical system illustrates the need for systematic methods of composing biomolecular circuits. We present insulating and amplifying devices as a solution for scaling up biomolecular networks much as in electronic circuits. Future applications of biomolecular programs will open up new possibilities in nanorobotics, nanomedicine, and artificial cells

Automated design of programmable enzyme-driven DNA circuits

Molecular programming allows for the bottom-up engineering of biochemical reaction networks in a controlled in vitro setting. These engineered biochemical reaction networks yield important insight in the design principles of biological systems and can potentially enrich molecular diagnostic systems. The DNA polymerase–nickase–exonuclease (PEN) toolbox has recently been used to program oscillatory and bistable biochemical networks using a minimal number of components. Previous work has reported the automatic construction of in silico descriptions of biochemical networks derived from the PEN toolbox, paving the way for generating networks of arbitrary size and complexity in vitro. Here, we report an automated approach that further bridges the gap between an in silico description and in vitro realization. A biochemical network of arbitrary complexity can be globally screened for parameter values that display the desired function and combining this approach with robustness analysis further increases the chance of successful in vitro implementation. Moreover, we present an automated design procedure for generating optimal DNA sequences, exhibiting key characteristics deduced from the in silico analysis. Our in silico method has been tested on a previously reported network, the Oligator, and has also been applied to the design of a reaction network capable of displaying adaptation in one of its components. Finally, we experimentally characterize unproductive sequestration of the exonuclease to phosphorothioate protected ssDNA strands. The strong nonlinearities in the degradation of active components caused by this unintended cross-coupling are shown computationally to have a positive effect on adaptation quality