A central goal of synthetic biology is to implement diverse cellular functions by predictably controlling gene expression. Though research has focused more on protein regulators than RNA regulators, recent advances in our understanding of RNA folding and functions have motivated the use of RNA regulators. RNA regulators provide an advantage because they are easier to design and engineer than protein regulators, potentially have a lower burden on the cell and are highly orthogonal. Here, we combine the CRISPR system from Streptococcus pyogenes and synthetic antisense RNAs (asRNAs) in Escherichia coli strains to repress or derepress a target gene in a programmable manner. Specifically, we demonstrate for the first time that the gene target repressed by the CRISPR system can be derepressed by expressing an asRNA that sequesters a small guide RNA (sgRNA). Furthermore, we demonstrate that tunable levels of derepression can be achieved (up to 95%) by designing asRNAs that target different regions of a sgRNA and by altering the hybridization free energy of the sgRNA–asRNA complex. This new system, which we call the combined CRISPR and asRNA system, can be used to reversibly repress or derepress multiple target genes simultaneously, allowing for rational reprogramming of cellular functions.

Synthetic small RNA regulators have emerged as a versatile tool to predictably control bacterial gene expression. Owing to their simple design principles, small size, and highly orthogonal behavior, these engineered genetic parts have been incorporated into genetic circuits. However, efforts to achieve more sophisticated cellular functions using RNA regulators have been hindered by our limited ability to integrate different RNA regulators into complex circuits. Here, we present a combined RNA regulatory system in Escherichia coli that uses small transcription activating RNA (STAR) and antisense RNA (asRNA) to activate or deactivate target gene expression in a programmable manner. Specifically, we demonstrated that the activated target output by the STAR system can be deactivated by expressing two different types of asRNAs: one binds to and sequesters the STAR regulator, affecting the transcription process, while the other binds to the target mRNA, affecting the translation process. We improved deactivation efficiencies (up to 96%) by optimizing each type of asRNA and then integrating the two optimized asRNAs into a single circuit. Furthermore, we demonstrated that the combined STAR and asRNA system can control gene expression in a reversible way and can regulate expression of a gene in the genome. Lastly, we constructed and simultaneously tested two A AND NOT B logic gates in the same cell to show sophisticated multigene regulation by the combined system. Our approach establishes a methodology for integrating multiple RNA regulators to rationally control multiple genes.

The toehold switch consists of a cis-repressing switch RNA hairpin and a trans-acting trigger RNA. The binding of the trigger RNA to an unpaired toehold sequence of the switch hairpin allows for a branch migration process, exposing the start codon and ribosome binding site for translation initiation. In this work, we demonstrate that responses of toehold switches can be modulated by introducing an inhibitory hairpin that shortens the length of the unpaired toehold region. First, we investigated the effect of the toehold region length on output gene expression and showed that the second trigger RNA, which binds to the inhibitory hairpin, is necessary for output gene activation when the hairpin-to-hairpin spacing is short. Second, the apparent Hill coefficient was found generally to increase with decreasing hairpin-to-hairpin spacing or increasing hairpin number. This work expands the utility of toehold switches by providing a new way to modulate their response.

Recent advances in our understanding of RNA folding and functions have facilitated the use of regulatory RNAs such as synthetic antisense RNAs (asRNAs) to modulate gene expression. However, despite the simple and universal complementarity rule, predictable asRNA-mediated repression is still challenging due to the intrinsic complexity of native asRNA-mediated gene regulation. To address this issue, we present a multivariate model, based on the change in free energy of complex formation (ΔG CF ) and percent mismatch of the target binding region, which can predict synthetic asRNA-mediated repression efficiency in diverse contexts. First, 69 asRNAs that bind to multiple target mRNAs were designed and tested to create the predictive model. Second, we showed that the same model is effective predicting repression of target genes in both plasmids and chromosomes. Third, using our model, we designed asRNAs that simultaneously modulated expression of a toxin and its antitoxin to demonstrate tunable control of cell growth. Fourth, we tested and validated the same model in two different biotechnologically important organisms: Escherichia coli Nissle 1917 and Bacillus subtilis 168. Last, multiple parameters, including target locations, the presence of an Hfq binding site, GC contents, and gene expression levels, were revisited to define the conditions under which the multivariate model should be used for accurate prediction. Together, 434 different strain-asRNA combinations were tested, validating the predictive model in a variety of contexts, including multiple target genes and organisms. The result presented in this study is an important step toward achieving predictable tunability of asRNA-mediated repression.

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