%0 Journal Article
%T Deep learning-enabled fast DNA-PAINT imaging in cells.
%A Zhu M
%A Zhang L
%A Jin L
%A Chen Y
%A Yang H
%A Ji B
%A Xu Y
%J Biophys Rep
%V 9
%N 4
%D 2023 Aug 31
%M 38516619
暂无%R 10.52601/bpr.2023.230014
%X 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.