Computational design of orthogonal operators and synthetic repressors for transcriptional logic gates

Orthogonal repressor-based logic gates have enabled the predictive design of genetic circuits using automated design algorithms. However, engineering complex genetic circuits has been limited by the availability of transcriptional logic gates that are orthogonal, exhibit low cytotoxicity, and have a large dynamic range. Here, we present an algorithmic approach to design orthogonal synthetic repressors and logic gates de novo . To demonstrate the approach, we used programmable DNA-binding proteins called “transcription activator-like effectors” (TALEs) to build orthogonal transcriptional logic gates. We automated the design of synthetic repressors by developing a Python script that implements a search algorithm and genetic design rules to generate a set of operator sequences that are orthogonal from one another, the specified host genome, and an optional set of other heterologous sequences. We demonstrate this approach by creating a library of 20 characterized synthetic repressors for Escherichia coli that complements natural TetR-family repressors used to build genetic circuits. TALE repressors were built from monomer DNA modules to enable prototyping of any 19 bp DNA-binding sequence and then recoded to remove repetitive sequences for final use in logic gates. A library of 20 orthogonal NOT logic gates was tuned and characterized. Synthetic logic gates were used to construct genetic circuits for sequential logic in combination with existing natural repressor gates and genetic circuit design algorithms. This study demonstrates a computational approach to designing orthogonal operator and repressor sequences for creating logic gates and scalable genetic circuit construction.