ArticleNucleic acids research2018
Synthetic negative feedback circuits using engineered small RNAs.
Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed, 95 citations in OpenAlex.
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- Design of orthogonal and portable RNA devices for post-transcriptional regulation by reverse engineering type I toxin-antitoxin systems.Nucleic acids research · 2025Article
- DNA Vaccines in the Post-mRNA Era: Engineering, Applications, and Emerging Innovations.International journal of molecular sciences · 2025Review
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- Transfer learning for cross-context prediction of protein expression from 5'UTR sequence.Nucleic acids research · 2024Article
- Regulation strategies for two-output biomolecular networks.Journal of the Royal Society, Interface · 2023Article
- A blueprint for a synthetic genetic feedback optimizer.Nature communications · 2023Article
- A cybergenetic framework for engineering intein-mediated integral feedback control systems.Nature communications · 2023Article
- Dynamic feedback regulation for efficient membrane protein production using a small RNA-based genetic circuit in Escherichia coli.Microbial cell factories · 2022Article
- Frequency spectra and the color of cellular noise.Nature communications · 2022Article
- Regulation of neutrophil myeloperoxidase inhibitor SPIN by the small RNA Teg49 in Staphylococcus aureus.Molecular microbiology · 2022Article
- Diversity of bacterial small RNAs drives competitive strategies for a mutual chaperone.Nature communications · 2022Article
- A hierarchy of biomolecular proportional-integral-derivative feedback controllers for robust perfect adaptation and dynamic performance.Nature communications · 2022Article
- Dichotomous feedback: a signal sequestration-based feedback mechanism for biocontroller design.Journal of the Royal Society, Interface · 2022Article
- Double-edged role of resource competition in gene expression noise and control.Advanced genetics (Hoboken, N.J.) · 2022Article
- A modular RNA interference system for multiplexed gene regulation.Nucleic acids research · 2022Article
- Building an RNA-Based Toggle Switch Using Inhibitory RNA Aptamers.ACS synthetic biology · 2022Article
- Biomolecular mechanisms for signal differentiation.iScience · 2021Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Negative feedback is known to enable biological and man-made systems to perform reliably in the face of uncertainties and disturbances. To date, synthetic biological feedback circuits have primarily relied upon protein-based, transcriptional regulation to control circuit output. Small RNAs (sRNAs) are non-coding RNA molecules that can inhibit translation of target messenger RNAs (mRNAs). In this work, we modelled, built and validated two synthetic negative feedback circuits that use rationally-designed sRNAs for the first time. The first circuit builds upon the well characterised tet-based autorepressor, incorporating an externally-inducible sRNA to tune the effective feedback strength. This allows more precise fine-tuning of the circuit output in contrast to the sigmoidal, steep input-output response of the autorepressor alone. In the second circuit, the output is a transcription factor that induces expression of an sRNA, which inhibits translation of the mRNA encoding the output, creating direct, closed-loop, negative feedback. Analysis of the noise profiles of both circuits showed that the use of sRNAs did not result in large increases in noise. Stochastic and deterministic modelling of both circuits agreed well with experimental data. Finally, simulations using fitted parameters allowed dynamic attributes of each circuit such as response time and disturbance rejection to be investigated.
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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.