A renaissance in RNA synthetic biology: new mechanisms, applications and tools for the future

Chappell, James; Watters, Kyle E.; Takahashi, Melissa K.; Lucks, Julius B.

doi:10.1016/j.cbpa.2015.05.018

Cited by 146 publications

(136 citation statements)

References 60 publications

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“…In addition, because of evolution, discovered alleles can be species specific. These difficulties and the importance of hypomorphic alleles have prompted the development of several methods to generate hypomorphic mutations directly in various model organisms234567891011. However, these methods again are usually specific to one organism, can have unpredictable alterations in gene activity (separation of function, gain of function), or can change other aspects of regulation that affect interpretation of phenotype, such as spatial-temporal gene expression.…”

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confidence: 99%

Rapid generation of hypomorphic mutations

et al. 2017

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Hypomorphic mutations are a valuable tool for both genetic analysis of gene function and for synthetic biology applications. However, current methods to generate hypomorphic mutations are limited to a specific organism, change gene expression unpredictably, or depend on changes in spatial-temporal expression of the targeted gene. Here we present a simple and predictable method to generate hypomorphic mutations in model organisms by targeting translation elongation. Adding consecutive adenosine nucleotides, so-called polyA tracks, to the gene coding sequence of interest will decrease translation elongation efficiency, and in all tested cell cultures and model organisms, this decreases mRNA stability and protein expression. We show that protein expression is adjustable independent of promoter strength and can be further modulated by changing sequence features of the polyA tracks. These characteristics make this method highly predictable and tractable for generation of programmable allelic series with a range of expression levels.

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confidence: 99%

Rapid generation of hypomorphic mutations

et al. 2017

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“…We anticipate this approach to enable rapid discovery of RNA structure-function design principles for a diverse array of regulators in nature and to accelerate the engineering of RNAs for a broad array of synthetic biology applications (Chappell et al 2015b). …”

Section: Discussionmentioning

confidence: 99%

Using in-cell SHAPE-Seq and simulations to probe structure–function design principles of RNA transcriptional regulators

Takahashi

Watters

Gasper

et al. 2016

RNA

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Antisense RNA-mediated transcriptional regulators are powerful tools for controlling gene expression and creating synthetic gene networks. RNA transcriptional repressors derived from natural mechanisms called attenuators are particularly versatile, though their mechanistic complexity has made them difficult to engineer. Here we identify a new structure-function design principle for attenuators that enables the forward engineering of new RNA transcriptional repressors. Using in-cell SHAPE-Seq to characterize the structures of attenuator variants within Escherichia coli, we show that attenuator hairpins that facilitate interaction with antisense RNAs require interior loops for proper function. Molecular dynamics simulations of these attenuator variants suggest these interior loops impart structural flexibility. We further observe hairpin flexibility in the cellular structures of natural RNA mechanisms that use antisense RNA interactions to repress translation, confirming earlier results from in vitro studies. Finally, we design new transcriptional attenuators in silico using an interior loop as a structural requirement and show that they function as desired in vivo. This work establishes interior loops as an important structural element for designing synthetic RNA gene regulators. We anticipate that the coupling of experimental measurement of cellular RNA structure and function with computational modeling will enable rapid discovery of structure-function design principles for a diverse array of natural and synthetic RNA regulators.

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“…For example, the new molecular diagnostic platform based on synthetic biology and the light-inducible system for control of gene activation have the potential to develop the biosensors [17] and can offer large tools to speed up the discovery and [18]. Although some related technologies are still in their infancy, they may still become great protection ways to improve global health in the future.…”

Section: Discussionmentioning

confidence: 99%

Synthetic Tet-inducible small hairpin RNAs targeting hTERT or Bcl-2 inhibit malignant phenotypes of bladder cancer T24 and 5637 cells

et al. 2015

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Small hairpin RNA (shRNA) can inhibit the malignant phenotypes of tumor cell through ribonucleic acid interference (RNAi). However, it is hardly to be regulated and it may induce few phenotypic changes. Here, we build a type of tetracycline (Tet)-inducible vectors which can achieve regulatable expression of shRNA in a time-dependent manner by using synthetic biology approach. In order to prove the effectiveness of this device, we chose hTERT and Bcl-2 as target genes and test the utility of the device on 5637 and T24 cell lines. The experiments show that the Tet-inducible small hairpin RNA can effectively suppress their target genes and generate anti-cancer effects on both 5637 and T24 cell lines. The device we build not only can inhibit proliferation but also can induce apoptosis and suppress migration of the bladder cancer cell lines 5637 and T24. The Tet-inducible small hairpin RNAs may provide a novel strategy for the treatment of human bladder cancer in the future.

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A renaissance in RNA synthetic biology: new mechanisms, applications and tools for the future

Cited by 146 publications

References 60 publications

Rapid generation of hypomorphic mutations

Rapid generation of hypomorphic mutations

Using in-cell SHAPE-Seq and simulations to probe structure–function design principles of RNA transcriptional regulators

Synthetic Tet-inducible small hairpin RNAs targeting hTERT or Bcl-2 inhibit malignant phenotypes of bladder cancer T24 and 5637 cells

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