ArticleNature chemical biology2012
Rationally designed families of orthogonal RNA regulators of translation.
Article in Nature chemical biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers.
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Who cites it
77 citing papers in PubMed.
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- Base gap switches as transcriptional regulators and their applications as biosensors.Nature sensors · 2026Article
- Intelligent molecular logic computing toolkits: nucleic acid-based construction, functionality, and enhanced biosensing applications.Chemical science · 2025Review
- Regulatory RNAs inSynthetic and systems biotechnology · 2024Review
- Design of artificial small regulatorySynthetic and systems biotechnology · 2023Article
- Biosensor-driven, model-based optimization of the orthogonally expressed naringenin biosynthesis pathway.Microbial cell factories · 2022Article
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- Synthetic Biological Circuits within an Orthogonal Central Dogma.Trends in biotechnology · 2021Review
- Analyzing genomic data using tensor-based orthogonal polynomials with application to synthetic RNAs.NAR genomics and bioinformatics · 2020Article
- Pyruvate-responsive genetic circuits for dynamic control of central metabolism.Nature chemical biology · 2020Article
- Sequence-to-function deep learning frameworks for engineered riboregulators.Nature communications · 2020Article
- The Impact of Leadered and Leaderless Gene Structures on Translation Efficiency, Transcript Stability, and Predicted Transcription Rates in Mycobacterium smegmatis.Journal of bacteriology · 2020Article
- Article
- Regulatory systems for gene expression control in cyanobacteria.Applied microbiology and biotechnology · 2020Review
- Probing the operability regime of an engineered ribocomputing unit in terms of dynamic range maintenance with extracellular changes and time.Journal of biological engineering · 2020Article
- De novo-designed translation-repressing riboregulators for multi-input cellular logic.Nature chemical biology · 2019Article
- Synthetic bionanotechnology: synthetic biology finds a toehold in nanotechnology.Emerging topics in life sciences · 2019Article
- Advances in engineered trans-acting regulatory RNAs and their application in bacterial genome engineering.Journal of industrial microbiology & biotechnology · 2019Review
- Riboregulated toehold-gated gRNA for programmable CRISPR-Cas9 function.Nature chemical biology · 2019Article
- Rapid generation of sequence-diverse terminator libraries and their parameterization using quantitative Term-Seq.Synthetic biology (Oxford, England) · 2019Article
17 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Our ability to routinely engineer genetic networks for applications is limited by the scarcity of highly specific and non-cross-reacting (orthogonal) gene regulators with predictable behavior. Though antisense RNAs are attractive contenders for this purpose, quantitative understanding of their specificity and sequence-function relationship sufficient for their design has been limited. Here, we use rationally designed variants of the RNA-IN-RNA-OUT antisense RNA-mediated translation system from the insertion sequence IS10 to quantify >500 RNA-RNA interactions in Escherichia coli and integrate the data set with sequence-activity modeling to identify the thermodynamic stability of the duplex and the seed region as the key determinants of specificity. Applying this model, we predict the performance of an additional ~2,600 antisense-regulator pairs, forecast the possibility of large families of orthogonal mutants, and forward engineer and experimentally validate two RNA pairs orthogonal to an existing group of five from the training data set. We discuss the potential use of these regulators in next-generation synthetic biology applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.