Biophysics Reports >> 2023, Vol.9 >> Issue (4) : 206 - 214 https://doi.org/10.52601/bpr.2023.230010
 

Live-cell super-resolution imaging unconventional dynamics and assemblies of nuclear pore complexes

Xianxin Ye, Minzhu Guan, Yaorong Guo, Xiang Liu, Kunhao Wang, Tongsheng Chen, Shiqun Zhao, Liangyi Chen
1 National Biomedical Imaging Center, State Key Laboratory of Membrane Biology, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing 100871, China
2 PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China
3 Key Laboratory of Laser Life Science, Ministry of Education, College of Biophotonics, South China Normal University, Guangzhou 510631, China
 
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Abstract

Super-resolution microscopy has promoted the development of cell biology, but imaging proteins with low copy numbers in cellular structures remains challenging. The limited number of designated proteins within nuclear pore complexes (NPCs) impedes continuous observation in live cells, although they are often used as a standard for evaluating various SR methods. To address this issue, we tagged POM121 with Halo-SiR and imaged it using structured illumination microscopy with sparse deconvolution (Sparse-SIM). Remarkably, POM121-SiR exhibited more than six-fold fluorescence intensity and four-fold enhanced contrast compared to the same protein labeled with tandem-linked mCherry, while showing negligible photo-bleaching during SR imaging for 200 frames. Using this technique, we discovered various types of NPCs, including ring-like and cluster-like structures, and observed dynamic remodeling along with the sequential appearance of different Nup compositions. Overall, Halo-SiR with Sparse-SIM is a potent tool for extended SR imaging of dynamic structures of NPCs in live cells, and it may also help visualize proteins with limited numbers in general.

Keywords : Super-resolution microscopy, Sparse deconvolution, Nuclear pore complexes, Halo-SiR, Dual-color imaging
Corresponding Author(s): Shiqun Zhao,Liangyi Chen
Issue Date: 31 Aug 2023
 
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