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Nanomaterials 2019, 9(2), 233; https://doi.org/10.3390/nano9020233

Intracellular Imaging with Genetically Encoded RNA-Based Molecular Sensors

Department of Chemistry, University of Massachusetts Amherst, Amherst, MA 01003, USA
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Received: 22 January 2019 / Revised: 5 February 2019 / Accepted: 5 February 2019 / Published: 8 February 2019
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Abstract

Genetically encodable sensors have been widely used in the detection of intracellular molecules ranging from metal ions and metabolites to nucleic acids and proteins. These biosensors are capable of monitoring in real-time the cellular levels, locations, and cell-to-cell variations of the target compounds in living systems. Traditionally, the majority of these sensors have been developed based on fluorescent proteins. As an exciting alternative, genetically encoded RNA-based molecular sensors (GERMS) have emerged over the past few years for the intracellular imaging and detection of various biological targets. In view of their ability for the general detection of a wide range of target analytes, and the modular and simple design principle, GERMS are becoming a popular choice for intracellular analysis. In this review, we summarize different design principles of GERMS based on various RNA recognition modules, transducer modules, and reporting systems. Some recent advances in the application of GERMS for intracellular imaging are also discussed. With further improvement in biostability, sensitivity, and robustness, GERMS can potentially be widely used in cell biology and biotechnology. View Full-Text
Keywords: RNA aptamers; biosensors; live-cell imaging; fluorogenic RNA; riboswitch; ribozyme RNA aptamers; biosensors; live-cell imaging; fluorogenic RNA; riboswitch; ribozyme
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Sun, Z.; Nguyen, T.; McAuliffe, K.; You, M. Intracellular Imaging with Genetically Encoded RNA-Based Molecular Sensors. Nanomaterials 2019, 9, 233.

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