Measurement of the persistence length of cytoskeletal filaments using curvature distributions.
Measurement of the persistence length of cytoskeletal filaments using curvature distributions.
复制标题
使用曲率分布测量细胞骨架丝的持久长度。
DOI：
10.1016/j.bpj.2022.04.020
复制
发表时间：
2022
影响因子：
3.4
通讯作者：
Tüzel,Erkan
中科院分区：
文献类型：
--
作者：
Wisanpitayakorn,Pattipong;Mickolajczyk,KeithJ;Hancock,WilliamO;Vidali,Luis;Tüzel,Erkan
细胞骨架细丝，如微管和肌动蛋白细丝，在细胞的机械完整性和细胞对环境的反应能力中起着重要作用。测量细胞骨架结构的机械特性对于深入了解细胞内机械应力及其在调节细胞过程中的作用至关重要。表征这些机械性能的方法之一是测量它们的持续长度，即细丝保持直线的平均长度。文献中有几种方法用于测量灯丝变形，例如使用荧光显微镜获得的图像的傅里叶分析。在这里，我们展示了曲率分布如何被用作量化生物丝变形的替代工具，并研究了丝的表观刚度如何取决于成像系统的分辨率和噪声。我们提出了作为灯丝离散化函数的尺度曲率分布的分析计算，并通过比较蒙特卡罗模拟与现有技术的结果来测试我们的预测。我们还将我们的方法应用于从高密度非功能马达的体外滑行实验中获得的微管和肌动蛋白丝，并计算这些丝的持续长度。与现有的小数据集方法相比，所提出的曲率分析明显更准确，并且可以很容易地通过使用我们提供的开源代码应用于体外和体内纤维数据。
Cytoskeletal filaments, such as microtubules and actin filaments, play important roles in the mechanical integrity of cells and the ability of cells to respond to their environment. Measuring the mechanical properties of cytoskeletal structures is crucial for gaining insight into intracellular mechanical stresses and their role in regulating cellular processes. One of the ways to characterize these mechanical properties is by measuring their persistence length, the average length over which filaments stay straight. There are several approaches in the literature for measuring filament deformations, such as Fourier analysis of images obtained using fluorescence microscopy. Here, we show how curvature distributions can be used as an alternative tool to quantify biofilament deformations, and investigate how the apparent stiffness of filaments depends on the resolution and noise of the imaging system. We present analytical calculations of the scaling curvature distributions as a function of filament discretization, and test our predictions by comparing Monte Carlo simulations with results from existing techniques. We also apply our approach to microtubules and actin filaments obtained from in vitro gliding assay experiments with high densities of nonfunctional motors, and calculate the persistence length of these filaments. The presented curvature analysis is significantly more accurate compared with existing approaches for small data sets, and can be readily applied to both in vitro and in vivo filament data through the use of the open-source codes we provide.