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通过误差估计提取亚细胞纤维排列:应用于微管

Extracting Subcellular Fibrillar Alignment with Error Estimation: Application to Microtubules.

作者信息

Tsugawa Satoru, Hervieux Nathan, Hamant Oliver, Boudaoud Arezki, Smith Richard S, Li Chun-Biu, Komatsuzaki Tamiki

机构信息

Research Institute for Electronic Science, Hokkaido University, Sapporo 001-0020 Japan.

Plant Reproduction and Development Lab., INRA, CNRS, ENS Lyon, UCB Lyon 1, Université de Lyon, Lyon, France.

出版信息

Biophys J. 2016 Apr 26;110(8):1836-1844. doi: 10.1016/j.bpj.2016.03.011.

Abstract

The order and orientation of cortical microtubule (CMT) arrays and their dynamics play an essential role in plant morphogenesis. To extract detailed CMT alignment structures in an objective, local, and accurate way, we propose an error-based extraction method that applies to general fluorescence intensity data on three-dimensional cell surfaces. Building on previous techniques to quantify alignments, our method can determine the statistical error for specific local regions, or the minimal scales of local regions for a desired accuracy goal. After validating our method with synthetic images with known alignments, we demonstrate the ability of our method to quantify subcellular CMT alignments on images with microtubules marked with green fluorescent protein in various cell types. Our method could also be applied to detect alignment structures in other fibrillar elements, such as actin filaments, cellulose, and collagen.

摘要

皮层微管(CMT)阵列的排列顺序、方向及其动态变化在植物形态发生过程中起着至关重要的作用。为了以客观、局部且准确的方式提取详细的CMT排列结构,我们提出了一种基于误差的提取方法,该方法适用于三维细胞表面的一般荧光强度数据。基于先前用于量化排列的技术,我们的方法可以确定特定局部区域的统计误差,或为达到所需精度目标的局部区域的最小尺度。在用具有已知排列的合成图像验证我们的方法后,我们展示了该方法量化标记有绿色荧光蛋白的微管的各种细胞类型图像中亚细胞CMT排列的能力。我们的方法还可应用于检测其他纤维状元件中的排列结构,如肌动蛋白丝、纤维素和胶原蛋白。

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