Cao Youfang, Liang Claire, Naveed Hammad, Li Yingzi, Chen Meng, Nie Qing
Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:5502-5. doi: 10.1109/EMBC.2012.6347240.
Understanding the dynamics of cell population allows insight into the control mechanism of the growth and development of mammalian tissues. It is well known that the proliferation and differentiation among stem cells (SCs), intermediate progenitor cells (IPCs), and fully differentiated cells (FDCs) are under different activation and inhibition controls. Secreted factors in negative feedback loops have already been identified as major elements in regulating the numbers of different cell types and in maintaining the equilibrium of cell populations. We have developed a novel spatial dynamic model of cells. We can characterize not only overall cell population dynamics, but also details of temporal-spatial relationship of individual cells within a tissue. In our model, the shape, growth, and division of each cell are modeled using a realistic geometric model. Furthermore, the inhibited growth rate, proliferation and differentiation probabilities of individual cells are modeled through feedback loops controlled by secreted factors of neighboring cells within a proper diffusion radius. With specific proliferation and differentiation probabilities, the actual division type that each cell will take is chosen by a Monte Carlo sampling process. With simulations we found that with proper strengths of inhibitions to growth and stem cell divisions, the whole tissue is capable of achieving a homeostatic size control. We discuss our findings on control mechanisms of the stability of the tissue development. Our model can be applied to study broad issues on tissue development and pattern formation in stem cell and cancer research.
了解细胞群体的动态变化有助于深入了解哺乳动物组织生长和发育的控制机制。众所周知，干细胞（SCs）、中间祖细胞（IPCs）和完全分化细胞（FDCs）之间的增殖和分化受到不同的激活和抑制控制。负反馈回路中的分泌因子已被确定为调节不同细胞类型数量和维持细胞群体平衡的主要因素。我们开发了一种新型的细胞空间动态模型。我们不仅可以表征整体细胞群体动态，还可以表征组织内单个细胞的时空关系细节。在我们的模型中，每个细胞的形状、生长和分裂都使用逼真的几何模型进行建模。此外，单个细胞的抑制生长速率、增殖和分化概率通过由适当扩散半径内相邻细胞的分泌因子控制的反馈回路进行建模。根据特定的增殖和分化概率，每个细胞将采取的实际分裂类型通过蒙特卡罗采样过程来选择。通过模拟我们发现，在对生长和干细胞分裂有适当抑制强度的情况下，整个组织能够实现稳态大小控制。我们讨论了我们关于组织发育稳定性控制机制的发现。我们的模型可应用于研究干细胞和癌症研究中关于组织发育和模式形成的广泛问题。
