Department of Bioengineering, Rice University, 6100 Main St., Houston, TX 77005, USA.
J Theor Biol. 2013 Jun 7;326:43-57. doi: 10.1016/j.jtbi.2012.11.030. Epub 2012 Dec 22.
Cell behavior patterns that lead to distinct tissue or capillary phenotypes are difficult to identify using existing approaches. We present a strategy to characterize the form, frequency, magnitude and sequence of human endothelial cell activity when stimulated by vascular endothelial growth factor (VEGF) and brain-derived neurotrophic factor (BDNF). We introduce a "Rules-as-Agents" method for rapid comparison of cell behavior hypotheses to in vitro angiogenesis experiments. Endothelial cells are represented as machines that transition between finite behavior states, and their properties are explored by a search algorithm. We rank and quantify differences between competing hypotheses about cell behavior during the formation of unique capillary phenotypes. Results show the interaction of tip and stalk endothelial cells, and predict how migration, proliferation, branching, and elongation integrate to form capillary structures within a 3D matrix in the presence of varying VEGF and BDNF concentrations. This work offers the ability to understand - and ultimately control - human cell behavior at the microvasculature level.
导致不同组织或毛细血管表型的细胞行为模式很难用现有的方法来识别。我们提出了一种策略,用于描述人内皮细胞在受到血管内皮生长因子(VEGF)和脑源性神经营养因子(BDNF)刺激时的形态、频率、幅度和顺序。我们引入了一种“规则即代理”方法,用于快速比较细胞行为假说与体外血管生成实验。内皮细胞被表示为在有限的行为状态之间转换的机器,并且通过搜索算法来探索它们的特性。我们对形成独特毛细血管表型过程中细胞行为的竞争假说之间的差异进行排序和量化。结果显示了尖端和茎干内皮细胞的相互作用,并预测了在不同的 VEGF 和 BDNF 浓度下,迁移、增殖、分支和伸长如何整合形成 3D 基质内的毛细血管结构。这项工作提供了理解 - 并最终控制 - 微脉管水平人类细胞行为的能力。