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使用细胞培养的细胞自动机模型对细胞间相互作用进行计算机模拟表征。

In silico characterization of cell-cell interactions using a cellular automata model of cell culture.

作者信息

Kihara Takanori, Kashitani Kosuke, Miyake Jun

机构信息

Department of Life and Environment Engineering, Faculty of Environmental Engineering, The University of Kitakyushu, 1-1 Hibikino, Wakamatsu, Kitakyushu, Fukuoka, 808-0135, Japan.

Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama, Toyonaka, Osaka, 560-8531, Japan.

出版信息

BMC Res Notes. 2017 Jul 14;10(1):283. doi: 10.1186/s13104-017-2613-x.

Abstract

BACKGROUND

Cell proliferation is a key characteristic of eukaryotic cells. During cell proliferation, cells interact with each other. In this study, we developed a cellular automata model to estimate cell-cell interactions using experimentally obtained images of cultured cells.

RESULTS

We used four types of cells; HeLa cells, human osteosarcoma (HOS) cells, rat mesenchymal stem cells (MSCs), and rat smooth muscle A7r5 cells. These cells were cultured and stained daily. The obtained cell images were binarized and clipped into squares containing about 10 cells. These cells showed characteristic cell proliferation patterns. The growth curves of these cells were generated from the cell proliferation images and we determined the doubling time of these cells from the growth curves. We developed a simple cellular automata system with an easily accessible graphical user interface. This system has five variable parameters, namely, initial cell number, doubling time, motility, cell-cell adhesion, and cell-cell contact inhibition (of proliferation). Within these parameters, we obtained initial cell numbers and doubling times experimentally. We set the motility at a constant value because the effect of the parameter for our simulation was restricted. Therefore, we simulated cell proliferation behavior with cell-cell adhesion and cell-cell contact inhibition as variables. By comparing growth curves and proliferation cell images, we succeeded in determining the cell-cell interaction properties of each cell. Simulated HeLa and HOS cells exhibited low cell-cell adhesion and weak cell-cell contact inhibition. Simulated MSCs exhibited high cell-cell adhesion and positive cell-cell contact inhibition. Simulated A7r5 cells exhibited low cell-cell adhesion and strong cell-cell contact inhibition. These simulated results correlated with the experimental growth curves and proliferation images.

CONCLUSIONS

Our simulation approach is an easy method for evaluating the cell-cell interaction properties of cells.

摘要

背景

细胞增殖是真核细胞的一个关键特征。在细胞增殖过程中,细胞相互作用。在本研究中,我们开发了一种细胞自动机模型,以利用培养细胞的实验获得图像来估计细胞间相互作用。

结果

我们使用了四种类型的细胞;人宫颈癌细胞(HeLa细胞)、人骨肉瘤(HOS)细胞、大鼠间充质干细胞(MSCs)和大鼠平滑肌A7r5细胞。这些细胞每天进行培养和染色。所获得的细胞图像进行二值化处理,并裁剪成包含约10个细胞的正方形。这些细胞呈现出特征性的细胞增殖模式。从细胞增殖图像生成这些细胞的生长曲线,并从生长曲线确定这些细胞的倍增时间。我们开发了一个具有易于访问的图形用户界面的简单细胞自动机系统。该系统有五个可变参数,即初始细胞数量、倍增时间、运动性、细胞间粘附和细胞间接触抑制(增殖)。在这些参数范围内,我们通过实验获得了初始细胞数量和倍增时间。由于该参数对我们模拟的影响有限,我们将运动性设置为恒定值。因此,我们以细胞间粘附和细胞间接触抑制为变量模拟细胞增殖行为。通过比较生长曲线和增殖细胞图像,我们成功确定了每种细胞的细胞间相互作用特性。模拟的HeLa细胞和HOS细胞表现出低细胞间粘附和弱细胞间接触抑制。模拟的MSCs表现出高细胞间粘附和阳性细胞间接触抑制。模拟的A7r5细胞表现出低细胞间粘附和强细胞间接触抑制。这些模拟结果与实验生长曲线和增殖图像相关。

结论

我们的模拟方法是一种评估细胞间相互作用特性的简便方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/722b/5513360/09a29e7d17d0/13104_2017_2613_Fig1_HTML.jpg

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