DNA-based point accumulation in nanoscale topography (DNA-PAINT) is a well-established technique for single-molecule localization microscopy (SMLM), enabling resolution of up to a few nanometers. Traditionally, DNA-PAINT involves the utilization of tens of thousands of single-molecule fluorescent images to generate a single super-resolution image. This process can be time-consuming, which makes it unfeasible for many researchers. Here, we propose a simplified DNA-PAINT labeling method and a deep learning-enabled fast DNA-PAINT imaging strategy for subcellular structures, such as microtubules. By employing our method, super-resolution reconstruction can be achieved with only one-tenth of the raw data previously needed, along with the option of acquiring the widefield image. As a result, DNA-PAINT imaging is significantly accelerated, making it more accessible to a wider range of biological researchers.
Publications
- Article type
- Year
Article type
Year
Open Access
Protocol
Issue
Biophysics Reports 2023, 9 (4): 177-187
Published: 31 August 2023
Downloads:5
Open Access
Rapid Communication
Issue
Genes & Diseases 2023, 10 (5): 1787-1790
Published: 03 February 2023
Downloads:5
Total 2