@article{pmid36735241,
title = {DNA Origami Curvature Sensors for Nanoparticle and Vesicle Size Determination with Single-Molecule FRET Readout},
author = {Ece Büber and Tim Schröder and Michael Scheckenbach and Mihir Dass and Henri G Franquelim and Philip Tinnefeld},
doi = {10.1021/acsnano.2c11981},
issn = {1936-086X},
year = {2023},
date = {2023-02-01},
urldate = {2023-02-01},
journal = {ACS Nano},
abstract = {Particle size is an important characteristic of materials with a direct effect on their physicochemical features. Besides nanoparticles, particle size and surface curvature are particularly important in the world of lipids and cellular membranes as the cell membrane undergoes conformational changes in many biological processes which leads to diverging local curvature values. On account of that, it is important to develop cost-effective, rapid and sufficiently precise systems that can measure the surface curvature on the nanoscale that can be translated to size for spherical particles. As an alternative approach for particle characterization, we present flexible DNA nanodevices that can adapt to the curvature of the structure they are bound to. The curvature sensors use Fluorescence Resonance Energy Transfer (FRET) as the transduction mechanism on the single-molecule level. The curvature sensors consist of segmented DNA origami structures connected via flexible DNA linkers incorporating a FRET pair. The activity of the sensors was first demonstrated with defined binding to different DNA origami geometries used as templates. Then the DNA origami curvature sensors were applied to measure spherical silica beads having different size, and subsequently on lipid vesicles. With the designed sensors, we could reliably distinguish different sized nanoparticles within a size range of 50-300 nm as well as the bending angle range of 50-180°. This study helps with the development of more advanced modular-curvature sensing devices that are capable of determining the sizes of nanoparticles and biological complexes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
