ArticleInternational journal of molecular sciences2021
Detection of Coronaviruses Using RNA Toehold Switch Sensors.
Article in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed, 38 citations in OpenAlex.
- Trends of nucleic acid - based point-of-care diagnostics for infectious diseases.Journal of biological engineering · 2026Review
- De novo-designed ribozyme-controlled riboregulator for cell-free diagnostics.Nature communications · 2026Article
- Genomic diversity analysis enables development of pan-Dengue Toehold RNA sensors.PLoS neglected tropical diseases · 2026Article
- Toehold-VISTA: a machine learning approach to decipher programmable RNA sensor-target interactions.Nucleic acids research · 2026Article
- Synthetic toehold biosensors for detectingFrontiers in microbiology · 2026Article
- Detection of TuMV by a toehold switch sensor coupled with NASBA amplification in Pseudostellaria heterophylla.Plant methods · 2025Article
- Synthetic cell preservation strategies enable their storage and activation at the point of use.Chemical communications (Cambridge, England) · 2025Article
- Untranslated region engineering strategies for gene overexpression, fine-tuning, and dynamic regulation.Journal of microbiology (Seoul, Korea) · 2025Review
- Improved RNA toehold switch sensitivity using the NanoLuc complementation reporter.microPublication biology · 2025Article
- A Novel Approach Using LuxSit-i Enhanced Toehold Switches for the Rapid Detection ofBiosensors · 2024Article
- Circular single-stranded DNA as a programmable vector for gene regulation in cell-free protein expression systems.Nature communications · 2024Article
- RNA-Based Sensor Systems for Affordable Diagnostics in the Age of Pandemics.ACS synthetic biology · 2024Review
- Toehold switch plus signal amplification enables rapid detection.Biotechnology journal · 2023Article
- Harnessing synthetic biology for advancing RNA therapeutics and vaccine design.NPJ systems biology and applications · 2023Review
- How does precursor RNA structure influence RNA processing and gene expression?Bioscience reports · 2023Review
- Article
- Transcription Factor-Based Biosensors for Detecting Pathogens.Biosensors · 2022Review
- Toehold switch based biosensors for sensing the highly trafficked rosewoodSynthetic and systems biotechnology · 2022Article
- Update on the Development of Toehold Switch-Based Approach for Molecular Diagnostic Tests of COVID-19.Journal of nucleic acids · 2022Review
- Detection ofLife (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
A rapid, sensitive and simple point-of-care (POC) nucleic acid diagnostic test is needed to prevent spread of infectious diseases. Paper-based toehold reaction, a recently emerged colorimetric POC nucleic acid diagnostic test, has been widely used for pathogen detection and microbiome profiling. Here, we introduce an amplification method called reverse transcription loop-mediated amplification (RT-LAMP) prior to the toehold reaction and modify it to enable more sensitive and faster colorimetric detection of RNA viruses. We show that incorporating the modified RT-LAMP to the toehold reaction detects as few as 120 copies of coronavirus RNA in 70 min. Cross-reactivity test against other coronaviruses indicates this toehold reaction with the modified RT-LAMP is highly specific to the target RNA. Overall, the paper-based toehold switch sensors with the modified RT-LAMP allow fast, sensitive, specific and colorimetric coronavirus detection.
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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.