Image analysis of fibroblast movement regulation and dynamic simulation

通过将荧光标记到特定的蛋白质或细胞器，已经产生了大量的图像数据来观察细胞内的各种现象。图像分析系统的发展为分子生物学的发展带来了巨大的变革。通过使用先进的图像分析技术，我们成功地观察到WAVE与IRSp53在成纤维细胞内的结合，发现了细胞运动的信号转导途径，另一方面，基于图像分析的结果，对生化网络的动态行为进行时间和空间模拟是非常重要的。因此，我们已经开发出一种新的方法，数值模拟的时间和空间变化的细胞内集成扩散过程。除此之外，该建模还考虑了采用吉莱斯皮算法的随机过程。为了验证该数值方法的可行性，我们模拟了果蝇胚胎发育过程中mRNA、蛋白质（如bicoid和hunchback）的时空动态，并研究了随机波动对动态行为的影响。模拟再现了这些蛋白质的随机行为，这与实验观察相当一致。这种建模技术不仅导致细胞动力学的真实的模拟，而且还阐明了如何消除细胞内的噪声以及如何通过复杂的生物化学网络产生鲁棒性的机制。由于计算复杂性，模拟模型假设扩散发生在一个方向上。为了再现真实的细胞行为，需要对细胞进行高维建模。

By labeling fluorescence to specific proteins or organelles, lots of image data have been produced to observe various phenomena within a cell. Development of the image analysis systems provides a great innovation to molecular biology. By using such advanced image analysis techniques, we successfully observed how WAVE binds to IRSp53 within fibroblast cells and found a signal transduction pathway regarding cell movement.On the other hand, it is very important to temporally and spatially simulate the dynamic behaviors of biochemical networks based on results of the image analysis. Thus, we have developed a novel method that numerically simulates the temporal and spatial changes within a cell by integrating diffusion processes. In addition to that, this modeling considers stochastic processes by employing the Gillespie algorithm. To demonstrate the feasibility of this numerical method, we simulated the spatial and temporal dynamics of mRNAs, proteins, such as bicoid and hunchback, in the embryogenesis of Drosophila, and investigated the effects of stochastic fluctuations to the dynamic behaviors. The simulation reproduced the stochastic behaviors of these proteins, which were fairly consistent with experimental observations. This modeling technology not only to leads to a real simulation of cell dynamics but also elucidates the mechanism of how noise is cancelled within a cell and of how robustness is generated by complicated biochemical networks. The simulation model assumes that diffusion occurs in one direction due to calculation complexity. It is required to approach to a high-dimensional modeling to reproduce the real cells behaviors.