ArticleNucleic acids research2020
Programmable cross-ribosome-binding sites to fine-tune the dynamic range of transcription factor-based biosensor.
Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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Who cites it
51 citing papers in PubMed.
- Advances and perspectives in genetically encoded biosensors for biomarker detection and theranostic circuits.Synthetic and systems biotechnology · 2027Review
- Deep learning-drivenSynthetic and systems biotechnology · 2027Article
- Synthesis and Biological Activity Characterization of Vascular Endothelial Growth Factor Using an Optimized Wheat Germ Cell-Free System.Current issues in molecular biology · 2026Article
- Genetically encoded biosensors enabled high-throughput screening of microbial cell factories.Engineering microbiology · 2026Review
- Beyond the niche - unlocking the full potential of synthetic riboswitches.Nature communications · 2025Review
- Extending dynamic and operational range of the biosensor responding to l-carnitine by directed evolution.Synthetic and systems biotechnology · 2025Article
- Deep learning guided programmable design of Escherichia coli core promoters from sequence architecture to strength control.Nucleic acids research · 2025Article
- Engineered TtgR-Based Whole-Cell Biosensors for Quantitative and Selective Monitoring of Bioactive Compounds.Biosensors · 2025Article
- Advancing lignocellulosic conversion though biosensor-enabled metabolic engineering.Green chemistry : an international journal and green chemistry resource : GC · 2025Review
- Nucleotide-level characterization and improvement of l-arabinose- and l-rhamnose-inducible systems in E. coli using a high-throughput approach.Nucleic acids research · 2025Article
- Microbial Transcription Factor-Based Biosensors: Innovations from Design to Applications in Synthetic Biology.Biosensors · 2025Review
- Fine-Tuning Genetic Circuits via Host Context and RBS Modulation.ACS synthetic biology · 2025Article
- Genetically encoded biosensors for the circular plastics bioeconomy.Metabolic engineering communications · 2024Article
- Highly multiplexed design of an allosteric transcription factor to sense new ligands.Nature communications · 2024Article
- Cell factories for biosynthesis of D-glucaric acid: a fusion of static and dynamic strategies.World journal of microbiology & biotechnology · 2024Review
- Dynamic and Static Regulation of Nicotinamide Adenine Dinucleotide Phosphate: Strategies, Challenges, and Future Directions in Metabolic Engineering.Molecules (Basel, Switzerland) · 2024Review
- AI-Assisted Rational Design and Activity Prediction of Biological Elements for Optimizing Transcription-Factor-Based Biosensors.Molecules (Basel, Switzerland) · 2024Review
- Enhancing glucaric acid production fromApplied and environmental microbiology · 2024Article
- Highly multiplexed design of an allosteric transcription factor to sense novel ligands.bioRxiv : the preprint server for biology · 2024Article
- Growth-Coupled Evolutionary Pressure Improving Epimerases for D-Allulose Biosynthesis Using a Biosensor-Assisted In Vivo Selection Platform.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
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6 authors.
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Abstract
Currently, predictive translation tuning of regulatory elements to the desired output of transcription factor (TF)-based biosensors remains a challenge. The gene expression of a biosensor system must exhibit appropriate translation intensity, which is controlled by the ribosome-binding site (RBS), to achieve fine-tuning of its dynamic range (i.e. fold change in gene expression between the presence and absence of inducer) by adjusting the translation level of the TF and reporter. However, existing TF-based biosensors generally suffer from unpredictable dynamic range. Here, we elucidated the connections and partial mechanisms between RBS, translation level, protein folding and dynamic range, and presented a design platform that predictably tuned the dynamic range of biosensors based on deep learning of large datasets cross-RBSs (cRBSs). In doing so, a library containing 7053 designed cRBSs was divided into five sub-libraries through fluorescence-activated cell sorting to establish a classification model based on convolutional neural network in deep learning. Finally, the present work exhibited a powerful platform to enable predictable translation tuning of RBS to the dynamic range of biosensors.
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