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Highly efficient expression of circular RNA aptamers in cells using autocatalytic transcripts.

ABSTRACT: RNA aptamers and RNA aptamer-based devices can be genetically encoded and expressed in cells to probe and manipulate cellular function. However, their usefulness in the mammalian cell is limited by low expression and rapid degradation. Here we describe the Tornado (Twister-optimized RNA for durable overexpression) expression system for achieving rapid RNA circularization, resulting in RNA aptamers with high stability and expression levels. Tornado-expressed transcripts contain an RNA of interest flanked by Twister ribozymes. The ribozymes rapidly undergo autocatalytic cleavage, leaving termini that are ligated by the ubiquitous endogenous RNA ligase RtcB. Using this approach, protein-binding aptamers that otherwise have minimal effects in cells become potent inhibitors of cellular signaling. Additionally, an RNA-based fluorescent metabolite biosensor for S-adenosyl methionine (SAM) that is expressed at low levels when expressed as a linear RNA achieves levels sufficient for detection of intracellular SAM dynamics when expressed as a circular RNA. The Tornado expression system thus markedly enhances the utility of RNA-based approaches in the mammalian cell.

SUBMITTER: Litke JL

PROVIDER: S-EPMC6554452 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Highly efficient expression of circular RNA aptamers in cells using autocatalytic transcripts.

Litke Jacob L JL Jaffrey Samie R SR

Nature biotechnology 20190408 6

RNA aptamers and RNA aptamer-based devices can be genetically encoded and expressed in cells to probe and manipulate cellular function. However, their usefulness in the mammalian cell is limited by low expression and rapid degradation. Here we describe the Tornado (Twister-optimized RNA for durable overexpression) expression system for achieving rapid RNA circularization, resulting in RNA aptamers with high stability and expression levels. Tornado-expressed transcripts contain an RNA of interest ...[more]

PMID: 30962542

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Project description:Circular RNAs (circRNAs) are a unique class of endogenous RNAs which could be used as potential diagnostic and prognostic biomarkers of many diseases. Our study aimed to investigate circRNA profiles in human granulosa cells (GCs) during maternal aging and to uncover age-related circRNA variations that potentially reflect decreased oocyte competence. CircRNAs in GCs from in vitro fertilization (IVF) patients with young age (YA, ≤ 30 years) and advanced age (AA, ≥ 38 years) were profiled by microarray, and validated in 20 paired samples. The correlation between circRNAs expression and clinical characteristics was analyzed in additional 80 samples. Chip-based analysis revealed 46 up-regulated and 11 down-regulated circRNAs in AA samples (fold change > 2.0). Specifically, circRNA_103829, circRNA_103827 and circRNA_104816 were validated to be up-regulated, while circRNA_101889 was down-regulated in AA samples. After adjustment for gonadotropin treatment, only circRNA_103827 and circRNA_104816 levels were positively associated with maternal age (partial r = 0.332, P = 0.045; partial r = 0.473, P = 0.003; respectively). Moreover, circRNA_103827 and circRNA_104816 expressions in GCs were negatively correlated with the number of top quality embryos (r = -0.235, P = 0.036; r = -0.221, P = 0.049; respectively). Receiver operating characteristic (ROC) curve analysis indicated that the performance of circRNA_103827 for live birth prediction reached 0.698 [0.570-0.825], with 77.2% sensitivity and 60.9% specificity (P = 0.006), and that of circRNA_104816 was 0.645 [0.507-0.783] (P = 0.043). Bioinformatics analysis revealed that both circRNAs were potentially involved in glucose metabolism, mitotic cell cycle, and ovarian steroidogenesis. Therefore, age-related up-regulation of circRNA_103827 and circRNA_104816 might be potential indicators of compromised follicular micro-environment which could be used to predict IVF prognosis, and improve female infertility management.

Project description:Applications of synthetic biology spanning human health, industrial bioproduction, and ecosystem monitoring often require small molecule sensing capabilities, typically in the form of genetically encoded small molecule biosensors. Critical to the deployment of greater numbers of these systems are methods that support the rapid development of such biosensors against a broad range of small molecule targets. Here, we use a previously developed method for selection of RNA biosensors against unmodified small molecules (DRIVER) to perform a selection against a densely multiplexed mixture of small molecules, representative of those employed in high-throughput drug screening. Using a mixture of 5,120 target compounds randomly sampled from a large diversity drug screening library, we performed a 95-round selection and then analyzed the enriched RNA biosensor library using next generation sequencing (NGS). From our analysis, we identified RNA biosensors with at least 2-fold change in signal in the presence of at least 217 distinct target compounds with sensitivities down to 25 nM. Although many of these biosensors respond to multiple targets, clustering analysis indicated at least 150 different small-molecule sensing patterns. We also built a classifier that was able to predict whether the biosensors would respond to a new compound with an average precision of 0.82. Since the target compound library was designed to be representative of larger diversity compound libraries, we expect that the described approach can be used with similar compound libraries to identify aptamers against other small molecules with a similar success rate. The new RNA biosensors (or their component aptamers) described in this work can be further optimized and used in applications such as biosensing, gene control, or enzyme evolution. In addition, the data presented here provide an expanded compendium of new RNA aptamers compared to the 82 small molecule RNA aptamers published in the literature, allowing further bioinformatic analyses of the general classes of small molecules for which RNA aptamers can be found.

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Highly efficient expression of circular RNA aptamers in cells using autocatalytic transcripts.

Publications

Highly efficient expression of circular RNA aptamers in cells using autocatalytic transcripts.

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