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首页> 外文期刊>EURASIP journal on bioinformatics and systems biology >From microscopy data to in silico environments for in vivo-oriented simulations
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From microscopy data to in silico environments for in vivo-oriented simulations

机译:从显微镜数据到计算机环境,以进行体内模拟

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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 ( D nro) and the anomaly in the tracer diffusion ( α ). For D nro=21.96 to 44.49 μ m 2/ 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.
机译:在我们以前的研究中,我们引入了荧光相关光谱(FCS)和透射电子显微镜(TEM)的组合方法,这对于研究细胞内环境对生化反应过程的影响非常有力。现在,我们基于TEM图像开发了一种逼真的模拟空间的重构方法。该空间的交互式射线追踪可视化可以感知整个3D结构,而这不能从2D TEM图像中直接访问。仿真结果表明,这种生成的结构中的扩散很大程度上取决于图像后处理。与带噪图像相对应的磨损结构比由降噪图像产生的平滑表面更阻碍扩散。这意味着对噪声或结构的正确识别对于在计算机上重建适当的反应环境,以估计反应物在体内的实际行为具有重要意义。由于局部限制,静态结构导致异常扩散。相反,流动拥挤剂在中等拥挤水平下不会导致异常扩散。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(D nro )与示踪剂扩散异常(DRO)之间的关系。 α)。对于D nro = 21.96至44.49μm 2 / s,仿真结果与从FCS测量获得异常。来自模拟的扩散系数的范围与细胞质中结构蛋白的扩散系数的范围兼容。另外,通过不同模拟之间的比较,我们研究了NRO半径与示踪剂反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的半径必须为58 nm,该速度接近细胞中功能蛋白复合物的半径。

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