Quantitative structured illumination microscopy via a physical model-based background filtering algorithm reveals actin dynamics

Yanquan Mo, Kunhao Wang, Liuju Li, Shijia Xing, Shouhua Ye, Jiayuan Wen, Xinxin Duan, Ziying Luo, Wen Gou, Tongsheng Chen, Yu-Hui Zhang, Changliang Guo, Junchao Fan () and Liangyi Chen ()
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Yanquan Mo: Peking University
Kunhao Wang: South China Normal University
Liuju Li: Peking University
Shijia Xing: Peking University
Shouhua Ye: Guangzhou Computational Super-resolution Biotech Co., Ltd
Jiayuan Wen: Guangzhou Computational Super-resolution Biotech Co., Ltd
Xinxin Duan: Huazhong University of Science and Technology
Ziying Luo: Guangzhou Computational Super-resolution Biotech Co., Ltd
Wen Gou: Chongqing University of Posts and Telecommunications
Tongsheng Chen: South China Normal University
Yu-Hui Zhang: Huazhong University of Science and Technology
Changliang Guo: Peking University
Junchao Fan: Chongqing University of Posts and Telecommunications
Liangyi Chen: Peking University

Nature Communications, 2023, vol. 14, issue 1, 1-10

Abstract: Abstract Despite the prevalence of superresolution (SR) microscopy, quantitative live-cell SR imaging that maintains the completeness of delicate structures and the linearity of fluorescence signals remains an uncharted territory. Structured illumination microscopy (SIM) is the ideal tool for live-cell SR imaging. However, it suffers from an out-of-focus background that leads to reconstruction artifacts. Previous post hoc background suppression methods are prone to human bias, fail at densely labeled structures, and are nonlinear. Here, we propose a physical model-based Background Filtering method for living cell SR imaging combined with the 2D-SIM reconstruction procedure (BF-SIM). BF-SIM helps preserve intricate and weak structures down to sub-70 nm resolution while maintaining signal linearity, which allows for the discovery of dynamic actin structures that, to the best of our knowledge, have not been previously monitored.

Date: 2023
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DOI: 10.1038/s41467-023-38808-8

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