Engineering synthetic RNA devices for cell control

Dykstra, Peter B.; Kaplan, Matias; Smolke, Christina D.

doi:10.1038/s41576-021-00436-7

Cited by 59 publications

(41 citation statements)

References 152 publications

(179 reference statements)

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“…The goal of this study was to develop small molecule-based methods to control CRISPR-mediated gene editing and expression. It is known that nucleic acids can be programmed to adopt pre-defined structures by modifying their primary sequence ( 33 ). The reliance of Cas9 on gRNAs suggests that they may serve as a viable platform for our purpose ( 19 ).…”

Section: Resultsmentioning

confidence: 99%

G-quadruplex-guided RNA engineering to modulate CRISPR-based genomic regulation

Liu

Cui

et al. 2022

Nucleic Acids Research

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It is important to develop small moelcule-based methods to modulate gene editing and expression in human cells. The roles of the G-quadruplex (G4) in biological systems have been widely studied. Here, G4-guided RNA engineering is performed to generate guide RNA with G4-forming units (G4-gRNA). We further demonstrate that chemical targeting of G4-gRNAs holds promise as a general approach for modulating gene editing and expression in human cells. The rich structural diversity of RNAs offers a reservoir of targets for small molecules to bind, thus creating the potential to modulate RNA biology.

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Section: Resultsmentioning

confidence: 99%

G-quadruplex-guided RNA engineering to modulate CRISPR-based genomic regulation

Liu

Cui

et al. 2022

Nucleic Acids Research

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“…Inspired by naturally occurring receptors, synthetic ligand-binding devices have emerged as versatile components of supramolecular tools that can find different applications including sensing and drug delivery. , Among the different synthetic ligand-binding devices that have been developed so far, such as host–guest complexes, , molecular imprinted polymers, , and dendrimers, , the use of synthetic oligonucleotides has emerged as particularly advantageous. − Nucleic acid receptors can be in fact rationally designed to recognize and bind a specific complementary sequence through Watson–Crick–Franklin (W–C–F) interactions , or, as in the case of aptamers, in vitro selected to recognize a small molecule or a protein. , The programmability, predictability of interactions, and the chemical versatility of DNA allow finely modulating the binding affinity of these receptors in a highly controllable fashion using different stimuli with a precision similar to that of natural receptors. For example, inspired by allosterically regulated proteins, nucleic acid-based switches have been rationally designed to be controlled by different molecular activators or inhibitors. − Similarly, taking advantage of the pH-dependence of Hoogsteen interactions, , the affinity of DNA receptors has been also finely modulated using pH. − …”

Section: Introductionmentioning

confidence: 99%

Thermo-Programmed Synthetic DNA-Based Receptors

2023

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Herein, we present a generalizable and versatile strategy to engineer synthetic DNA ligand-binding devices that can be programmed to load and release a specific ligand at a defined temperature. We do so by re-engineering two model DNA-based receptors: a triplex-forming bivalent DNA-based receptor that recognizes a specific DNA sequence and an ATPbinding aptamer. The temperature at which these receptors load/release their ligands can be finely modulated by controlling the entropy associated with the linker connecting the two ligand-binding domains. The availability of a set of receptors with tunable and reversible temperature dependence allows achieving complex load/release behavior such as sustained ligand release over a wide temperature range. Similar programmable thermo-responsive synthetic ligand-binding devices can be of utility in applications such as drug delivery and production of smart materials.

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“…In addition to their natural functions, these ribozymes have been used as the basis for engineering biological systems. For example, several small ribozymes (hammerhead, twister, pistol, and HDV) have been used as genetically encoded gene regulatory elements by combining them with RNA aptamer and embedding them into untranslated regions of genes ( Groher and Suess, 2014 ; Dykstra et al, 2022 ). This approach continues to gain attention because of the central importance of controlling gene expression and the simple design and build cycles of these small RNA elements.…”

Section: Introductionmentioning

confidence: 99%

Predicting higher-order mutational effects in an RNA enzyme by machine learning of high-throughput experimental data

Beck

Roberts

Kitzhaber

et al. 2022

Front. Mol. Biosci.

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Ribozymes are RNA molecules that catalyze biochemical reactions. Self-cleaving ribozymes are a common naturally occurring class of ribozymes that catalyze site-specific cleavage of their own phosphodiester backbone. In addition to their natural functions, self-cleaving ribozymes have been used to engineer control of gene expression because they can be designed to alter RNA processing and stability. However, the rational design of ribozyme activity remains challenging, and many ribozyme-based systems are engineered or improved by random mutagenesis and selection (in vitro evolution). Improving a ribozyme-based system often requires several mutations to achieve the desired function, but extensive pairwise and higher-order epistasis prevent a simple prediction of the effect of multiple mutations that is needed for rational design. Recently, high-throughput sequencing-based approaches have produced data sets on the effects of numerous mutations in different ribozymes (RNA fitness landscapes). Here we used such high-throughput experimental data from variants of the CPEB3 self-cleaving ribozyme to train a predictive model through machine learning approaches. We trained models using either a random forest or long short-term memory (LSTM) recurrent neural network approach. We found that models trained on a comprehensive set of pairwise mutant data could predict active sequences at higher mutational distances, but the correlation between predicted and experimentally observed self-cleavage activity decreased with increasing mutational distance. Adding sequences with increasingly higher numbers of mutations to the training data improved the correlation at increasing mutational distances. Systematically reducing the size of the training data set suggests that a wide distribution of ribozyme activity may be the key to accurate predictions. Because the model predictions are based only on sequence and activity data, the results demonstrate that this machine learning approach allows readily obtainable experimental data to be used for RNA design efforts even for RNA molecules with unknown structures. The accurate prediction of RNA functions will enable a more comprehensive understanding of RNA fitness landscapes for studying evolution and for guiding RNA-based engineering efforts.

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Engineering synthetic RNA devices for cell control

Cited by 59 publications

References 152 publications

G-quadruplex-guided RNA engineering to modulate CRISPR-based genomic regulation

G-quadruplex-guided RNA engineering to modulate CRISPR-based genomic regulation

Thermo-Programmed Synthetic DNA-Based Receptors

Predicting higher-order mutational effects in an RNA enzyme by machine learning of high-throughput experimental data

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