2018
DOI: 10.1021/acs.nanolett.7b05354
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Optical Voltage Sensing Using DNA Origami

Abstract: We explore the potential of DNA nanotechnology for developing novel optical voltage sensing nano-devices that convert a local change of electric potential into optical signals. As a proof-of-concept of the sensing mechanism, we assembled voltage responsive DNA origami structures labelled with a single pair of FRET dyes. The DNA structures were reversibly immobilised on a nanocapillary tip and underwent controlled structural changes upon application of an electric field. The applied field was monitored through … Show more

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Cited by 48 publications
(43 citation statements)
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“…For example, the fluorescence lifetimes of a quantum dot could be tuned by coupling it to metal nanoparticles in a well-defined geometry [ 7 ]. Moreover, voltage sensing was achieved by using voltage sensitive DNA origami structures, which convert voltages into optical signals [ 8 ]. These examples show that the precise positioning of nanoscale particles opens promising possibilities for the interconversion of optical and electronic signals at the nanoscale.…”
Section: Introductionmentioning
confidence: 99%
“…For example, the fluorescence lifetimes of a quantum dot could be tuned by coupling it to metal nanoparticles in a well-defined geometry [ 7 ]. Moreover, voltage sensing was achieved by using voltage sensitive DNA origami structures, which convert voltages into optical signals [ 8 ]. These examples show that the precise positioning of nanoscale particles opens promising possibilities for the interconversion of optical and electronic signals at the nanoscale.…”
Section: Introductionmentioning
confidence: 99%
“…Bellot et al developed a nanoactuator using DNA origami (Figure d), which can sense and actuate in response to a number of different biological cues such as metal ions (K + ), enzymes (BamHI), or nucleic acids (miR‐210) . Keyser et al constructed voltage‐dependent dynamic DNA nanopores with single‐molecule fluorescence resonance energy transfer (FRET) as the optical readout for voltage detection, which has the application potential for live‐cell imaging of transmembrane potentials (Figure e) . Super‐resolution imaging was achieved by utilizing the dynamic and transient binding of fluorophore‐tagged short DNA strands onto targets, a technique called DNA points accumulation for imaging in nanoscale topography (DNA‐PAINT) (Figure f).…”
Section: Biological Sensing and Imagingmentioning
confidence: 99%
“…e) Optical voltage sensing device based on DNA origami nanopore with responsive deformation upon eletrical stimulation. Reproduced with permission . Copyright 2018, ACS and f) transient binding of fluorophore DNA (DNA‐PAINT) for optical imaging at sub‐10 nm resolution.…”
Section: Biological Sensing and Imagingmentioning
confidence: 99%
“…7 and Supporting Animation 12. The spatial distribution of the electrostatic potential near the pipette under a 300-mV applied bias was obtained using the Comsol continuum model, as described previously 20 . The potential was applied to each bead in the system with a weight proportional to the number of nucleotides represented by the bead.…”
Section: Integration With Continuum Modelsmentioning
confidence: 99%
“…In our mrdna simulation, we observe one leg of the DNA nanostructure to be captured initially, followed by a collapse of the wireframe mesh, which allowed the object to pass fully through the aperture of the pipette. While the above simulation is just an illustrative example, we have previously used similar multiscale/multiphysics simulations to obtain a quantitatively correct description of the voltage-dependent deformation of a DNA nanostructure subject to applied electric field of various magnitudes 20 . We expect the combination of particle-based simulations with continuum modeling to bring much anticipated advances in the field of plasmonic DNA nanostructures, DNA nanostructures that respond to fluid flow and, eventually, modeling DNA nanostructures in the crowded environment of a biological cell.…”
Section: Integration With Continuum Modelsmentioning
confidence: 99%