从显微镜数据到体内定向模拟的计算机环境。

Noriko Hiroi1, Michael Klann, Keisuke Iba, Pablo de Heras Ciechomski, Shuji Yamashita, Akito Tabira, Takahiro Okuhara, Takeshi Kubojima, Yasunori Okada, Kotaro Oka, Robin Mange, Michael Unger, Akira Funahashi, Heinz Koeppl
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引用次数: 5

摘要

摘要:在之前的研究中,我们介绍了一种荧光相关光谱(FCS)和透射电子显微镜(TEM)相结合的方法,该方法可以有效地研究细胞内环境对生化反应过程的影响。现在,我们开发了一种基于透射电镜图像的真实模拟空间重建方法。该空间的交互式光线追踪可视化允许感知整体3D结构,这是无法从2D TEM图像直接访问的。仿真结果表明,这种生成结构的扩散很大程度上依赖于图像后处理。噪声图像对应的磨损结构比去噪图像对应的光滑表面对扩散的阻碍要大得多。这意味着正确识别噪声或结构对于重建适当的硅反应环境,以估计反应物在体内的真实行为具有重要意义。静态结构由于局部约束导致了异常扩散。相反,在中等拥挤水平下,移动拥挤因子不会导致异常扩散。通过改变这些非反应性障碍物(NRO)的迁移率,我们估计了NRO扩散系数(Dnro)与示踪剂扩散异常(α)之间的关系。在Dnro=21.96 ~ 44.49 μm2/s范围内,模拟结果与FCS测量结果吻合。模拟得到的扩散系数范围与细胞质中结构蛋白的扩散系数范围是一致的。此外,通过不同模拟结果的对比,探讨了NRO半径与示踪剂异常扩散系数之间的关系。当聚合物以与反应物相同的扩散速度移动时,NRO半径必须为58 nm,这与细胞中功能蛋白复合物的半径接近。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

From microscopy data to in silico environments for in vivo-oriented simulations.

From microscopy data to in silico environments for in vivo-oriented simulations.

From microscopy data to in silico environments for in vivo-oriented simulations.

From microscopy data to in silico environments for in vivo-oriented simulations.

Abstract: : In our previous study, we introduced a combination methodology of Fluorescence Correlation Spectroscopy (FCS) and Transmission Electron Microscopy (TEM), which is powerful to investigate the effect of intracellular environment to biochemical reaction processes. Now, we developed a reconstruction method of realistic simulation spaces based on our TEM images. Interactive raytracing visualization of this space allows the perception of the overall 3D structure, which is not directly accessible from 2D TEM images. Simulation results show that the diffusion in such generated structures strongly depends on image post-processing. Frayed structures corresponding to noisy images hinder the diffusion much stronger than smooth surfaces from denoised images. This means that the correct identification of noise or structure is significant to reconstruct appropriate reaction environment in silico in order to estimate realistic behaviors of reactants in vivo. Static structures lead to anomalous diffusion due to the partial confinement. In contrast, mobile crowding agents do not lead to anomalous diffusion at moderate crowding levels. By varying the mobility of these non-reactive obstacles (NRO), we estimated the relationship between NRO diffusion coefficient (Dnro) and the anomaly in the tracer diffusion (α). For Dnro=21.96 to 44.49 μm2/s, the simulation results match the anomaly obtained from FCS measurements. This range of the diffusion coefficient from simulations is compatible with the range of the diffusion coefficient of structural proteins in the cytoplasm. In addition, we investigated the relationship between the radius of NRO and anomalous diffusion coefficient of tracers by the comparison between different simulations. The radius of NRO has to be 58 nm when the polymer moves with the same diffusion speed as a reactant, which is close to the radius of functional protein complexes in a cell.

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