Computational design of Small Transcription Activating RNAs (STARs) for versatile and dynamic gene regulation

Chappell, James; Westbrook, Alexandra; Verosloff, Matthew S.; Lucks, Julius B.

doi:10.1101/169391

Cited by 2 publications

(1 citation statement)

References 63 publications

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“…Studies have shown that RNA sequences shape the sensitivity and threshold of riboswitch dose-response curves [52,5], yet the precise tuning of riboswitch function remains a significant challenge. Computational methods have proven powerful for the design of RNA devices [13] and mathematical modelling has revealed insights on the tunability of the riboswitch function in terms of biophysical parameters [6]. Integration of sequence design algorithms with mathematical models may facilitate the discovery of new metabolite-responsive riboswitches, and thus expand the repertoire of pathways in which dynamic control can be used [7].…”

Section: § 1 Introductionmentioning

confidence: 99%

Dynamic metabolic control: towards precision engineering of metabolism

Liu

Mannan

Han

et al. 2018

Journal of Industrial Microbiology and Biotechnology

103

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Advances in metabolic engineering have led to the synthesis of a wide variety of valuable chemicals in microorganisms. The key to commercializing these processes is the improvement of titer, productivity, yield, and robustness. Traditional approaches to enhancing production use the "push-pull-block" strategy that modulates enzyme expression under static control. However, strains are often optimized for specific laboratory set-up and are sensitive to environmental fluctuations. Exposure to sub-optimal growth conditions during large-scale fermentation often reduces their production capacity. Moreover, static control of engineered pathways may imbalance cofactors or cause the accumulation of toxic intermediates, which imposes burden on the host and results in decreased production. To overcome these problems, the last decade has witnessed the emergence of a new technology that uses synthetic regulation to control heterologous pathways dynamically, in ways akin to regulatory networks found in nature. Here, we review natural metabolic control strategies and recent developments in how they inspire the engineering of dynamically regulated pathways. We further discuss the challenges of designing and engineering dynamic control and highlight how model-based design can provide a powerful formalism to engineer dynamic control circuits, which together with the tools of synthetic biology, can work to enhance microbial production.

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Section: § 1 Introductionmentioning

confidence: 99%

Dynamic metabolic control: towards precision engineering of metabolism

Liu

Mannan

Han

et al. 2018

Journal of Industrial Microbiology and Biotechnology

103

View full text Add to dashboard Cite

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Cell-free prototyping of AND-logic gates based on heterogeneous RNA activators

Lehr

Hanst

Vogel

et al. 2019

Preprint

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RNA-based devices controlling gene expression bear great promise for synthetic biology, as they o↵er many advantages like short response times and light metabolic burden compared to protein-circuits. However, little work has been done regarding their integration to multi-level regulated circuits. In this work, we combined a variety of small transcriptional activator RNAs (STARs) and toehold switches to build highly e↵ective AND-gates. To characterise the components and their dynamic range, we used an Escherichia coli (E. coli ) cell-free transcription-translation (TX-TL) system dispensed via nanoliter droplets. We analysed a prototype gate in vitro as well as in silico, employing parameterised ordinary di↵erential equations (ODEs), where parameters were inferred via parallel tempering, a Markov chain Monte Carlo (MCMC) method. Based on this analysis, we created nine additional AND-gates and tested them in vitro. The functionality of the gates was found to be highly dependent on the concentration of the activating RNA for either the STAR or the toehold switch. All gates were successfully implemented in vivo, o↵ering a dynamic range comparable to the level of protein circuits. This study shows the potential of a rapid prototyping approach for RNA circuit design, using cell-free systems in combination with a model prediction. AbbreviationsTX-TL (transcription-translation), ODEs (ordinary differential equations), STARs (small transcriptional activator RNAs), MCMC (Markov chain Monte Carlo).

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Computational design of Small Transcription Activating RNAs (STARs) for versatile and dynamic gene regulation

Cited by 2 publications

References 63 publications

Dynamic metabolic control: towards precision engineering of metabolism

Dynamic metabolic control: towards precision engineering of metabolism

Cell-free prototyping of AND-logic gates based on heterogeneous RNA activators

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