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, Yuhui Zhang, Changliang Guo, Junchao Fan, Liangyi Chen
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.