Quantitative structured illumination microscopy via a physical model-based background filtering algorithm reveals actin dynamics.
Quantitative structured illumination microscopy via a physical model-based background filtering algorithm reveals actin dynamics.
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DOI：
10.1038/s41467-023-38808-8
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发表时间：
2023-05-29
影响因子：
16.6
通讯作者：
Chen, Liangyi
中科院分区：
文献类型：
--
作者：
Mo, Yanquan;Wang, Kunhao;Li, Liuju;Xing, Shijia;Ye, Shouhua;Wen, Jiayuan;Duan, Xinxin;Luo, Ziying;Gou, Wen;Chen, Tongsheng;Zhang, Yu-Hui;Guo, Changliang;Fan, Junchao;Chen, Liangyi
尽管超分辨率(SR)显微镜的流行，但维持精细结构的完整性和荧光信号的线性的定量活细胞SR成像仍然是一个未知的领域。结构照明显微镜(SIM)是活体细胞SR成像的理想工具。然而，它的背景失焦会导致重建伪影。以往的后自组织背景抑制方法容易受到人的偏见，对密集标记的结构无效，并且是非线性的。在这里，我们提出了一种基于物理模型的背景滤波方法，用于活细胞SR成像，并结合2D-SIM重建过程(BF-SIM)。BF-SIM有助于保存复杂和微弱的结构，分辨率低至70 nm以下，同时保持信号线性，这使得我们能够发现动态肌动蛋白结构，就我们所知，这些结构以前从未被监测过。维持荧光信号线性的定量活细胞超分辨率成像仍然很困难。在此，作者提出了一种基于物理模型的2D-SIM背景滤波方法，该方法允许定量成像和高信号完整性。
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. Quantitative live-cell superresolution imaging that maintains the linearity of fluorescence signals remains difficult. Here, the authors propose a physical model-based background filtering method for 2D-SIM, which allows for quantitative imaging and high signal completeness.
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影响因子：
16.6
作者：
Jin, Luhong;Liu, Bei;Hahn, Klaus M.
通讯作者：
Hahn, Klaus M.
DOI：
10.1073/pnas.0907866106
发表时间：
2009-12-29
影响因子：
11.1
作者：
Dertinger, T.;Colyer, R.;Enderlein, J.
通讯作者：
Enderlein, J.
酵母中皮质肌动蛋白斑块的运动。
影响因子：
7.8
作者：
Waddle, J A;Karpova, T S;Waterston, R H;Cooper, J A
通讯作者：
Cooper, J A
ImageJ中超分辨率结构化照明显微镜数据的开源图像重建。
影响因子：
16.6
作者：
Müller M;Mönkemöller V;Hennig S;Hübner W;Huser T
通讯作者：
Huser T
涂有网状蛋白涂层坑的前五秒钟。
影响因子：
64.5
作者：
Cocucci E;Aguet F;Boulant S;Kirchhausen T
通讯作者：
Kirchhausen T