A Model-Driven Approach to Improving Cooperativity and Reducing Toxicity of dCas9 Logic Circuits

The execution of combinational digital logic programs through genetic circuits is a powerful method of exerting control over bacterial systems. Currently, the largest published genetic circuit utilizes 7 orthogonal repressor proteins to enact computation [1]. However, further scaling of repressor-based circuits is constrained by limited orthogonal parts, large DNA synthesis requirements, and toxicity due to cellular resource loading and nonspecific repressor binding.

The use of dCas9-based logic computation has recently been proposed as a method of surmounting all of these issues. The design of hundreds of orthogonal gates is easily achieved through the mutation of bacterial promoters and their cognate sgRNAs. In addition, the DNA footprint of a dCas9-based gate is much smaller than a repressor-based gate. Finally, the actuation of a sgRNA on its cognate promoter requires no translational action and thus has a much lower resource load on its host cell. However, several challenges still remain before dCas9 logic can be implemented at scales comparable to repressor-based digital computation. Overexpression of dCas9 in Escherichia coli results in significant cell growth toxicity [1]. Additionally, simple dCas9 NOT gates exhibit non-cooperative log-linear input/output steady-state transfer curves [2]. This is an issue because a NOT gate without a saturable low-input region lacks a robust ON state and is difficult to layer into larger circuits.

In this work, we take a model-driven approach to solve the issues of dCas9 non-cooperativity and toxicity in bacterial systems. Natural systems have evolved many methods of obtaining cooperative input/output responses including transcription factor multimerization, effector sequestration, and positive feedback motifs [3]. Beginning with a low-order kinetic model of a dCas9 logic circuit, we evaluated several of these naturally-inspired cooperativity methodologies in silico and derived a set of parameter regions for which they are biologically feasible. The problem of dCas9 toxicity may be due to nonspecific binding exacerbated by the overexpression required to actuate over large circuits. Through feedback, we show that the level of free dCas9 can be controlled such that it remains low enough to prevent toxicity, but is still capable of acting in digital logic circuits. This work will facilitate the implementation of robust dCas9-based logic circuits in bacterial systems which could result in highly-scalable genetic logic programs.

References

[1] Nielsen AA, Der BS, Shin J, et al. Genetic circuit design automation. Science. 2016;352(6281):aac7341.

[2] Nielsen AA, Voigt CA. Multi-input CRISPR/Cas genetic circuits that interface host regulatory networks. Mol Syst Biol. 2014;10:763.

[3] Bradley RW, Buck M, Wang B. Recognizing and engineering digital-like logic gates and switches in gene regulatory networks. Curr Opin Microbiol. 2016;33:74-82.