Unraveling trajectories of diffusive particles on networks
Unraveling trajectories of diffusive particles on networks
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揭示网络上扩散粒子的轨迹
DOI：
10.1103/physrevresearch.4.023182
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发表时间：
2022
影响因子：
4.2
通讯作者：
Koslover, Elena F.
中科院分区：
文献类型：
--
作者：
Sun, Yunhao;Yu, Zexi;Obara, Christopher J.;Mittal, Keshav;Lippincott-Schwartz, Jennifer;Koslover, Elena F.
对单粒子轨迹的分析在阐明复杂环境中的动力学方面发挥着重要作用，例如在活细胞中发现的那些环境。然而，细胞内粒子运动的特征经常被限制在非平凡的亚细胞几何中而混淆。在这里，我们特别关注粒子在细管网络中经历布朗运动的情况，就像在一些细胞细胞器中发现的那样。开发了一种计算解开算法，将粒子运动从限制网络结构中分离出来，允许准确地提取潜在的一维扩散系数，以及区分布朗运动和分数朗之万运动。我们用模拟的轨迹验证了算法的有效性，然后重点介绍了它在一个例子系统中的应用：分析哺乳动物细胞外周内质网小管中膜蛋白的运动。我们发现这些蛋白质经历了扩散运动，并提供了它们扩散系数的定量估计。我们的算法为网络体系结构中几何形态和粒子动力学的解缠提供了一种普遍适用的方法。
The analysis of single-particle trajectories plays an important role in elucidating dynamics within complex environments such as those found in living cells. However, the characterization of intracellular particle motion is often confounded by confinement of the particles within nontrivial subcellular geometries. Here we focus specifically on the case of particles undergoing Brownian motion within a network of narrow tubules, as found in some cellular organelles. A computational unraveling algorithm is developed to uncouple particle motion from the confining network structure, allowing for an accurate extraction of the underlying one-dimensional diffusion coefficient, as well as differentiating between Brownian and fractional Langevin motion. We validate the algorithm with simulated trajectories and then highlight its application to an example system: analyzing the motion of membrane proteins confined in the tubules of the peripheral endoplasmic reticulum in mammalian cells. We show that these proteins undergo diffusive motion and provide a quantitative estimate of their diffusion coefficient. Our algorithm provides a generally applicable approach for disentangling geometric morphology and particle dynamics in networked architectures.
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