Single-Molecule FRET X

Fluorescence resonance energy transfer (FRET) is a photophysical phenomenon that has been repurposed as a biophysical tool to measure nanometer distances. With FRET by DNA eXchange, or FRET X, many points of interest (POIs) in a single object can be probed, overcoming a major limitation of conventional single-molecule FRET. In FRET X, short...

Next-Generation Protein Identification: Advancing Single-Molecule Fluorescence Approaches

Proteins are the workhorses of the cell, as such, they form the basis of all living systems. In order to fully understand biological processes, the ability to identify and quantify the proteins in cells is crucial. Identification can be achieved by determining the amino acid sequence of proteins, since this sequence is unique for each protein....

High-Resolution Single-Molecule FRET via DNA eXchange (FRET X)

Single-molecule FRET is a versatile tool to study nucleic acids and proteins at the nanometer scale. However, currently, only a couple of FRET pairs can be reliably measured on a single object, which makes it difficult to apply single-molecule FRET for structural analysis of biomolecules. Here, we present an approach that allows for the...

High-Speed Super-Resolution Imaging Using Protein-Assisted DNA-PAINT

Super-resolution imaging allows for the visualization of cellular structures on a nanoscale level. DNA-PAINT (DNA point accumulation in nanoscale topology) is a super-resolution method that depends on the binding and unbinding of DNA imager strands. The current DNA-PAINT technique suffers from slow acquisition due to the low binding rate of...

Completing the canvas: advances and challenges for DNA-PAINT super-resolution imaging

Single-molecule localization microscopy (SMLM) is a potent tool to examine biological systems with unprecedented resolution, enabling the investigation of increasingly smaller structures. At the forefront of these developments is DNA-based point accumulation for imaging in nanoscale topography (DNA-PAINT), which exploits the stochastic and...