Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA.
Nat Methods. 2012 Jan 29;9(3):283-9. doi: 10.1038/nmeth.1861.
Cellular signaling processes depend on spatiotemporal distributions of molecular components. Multicolor, high-resolution microscopy permits detailed assessment of such distributions, providing input for fine-grained computational models that explore mechanisms governing dynamic assembly of multimolecular complexes and their role in shaping cellular behavior. However, it is challenging to incorporate into such models both complex molecular reaction cascades and the spatial localization of signaling components in dynamic cellular morphologies. Here we introduce an approach to address these challenges by automatically generating computational representations of complex reaction networks based on simple bimolecular interaction rules embedded into detailed, adaptive models of cellular morphology. Using examples of receptor-mediated cellular adhesion and signal-induced localized mitogen-activated protein kinase (MAPK) activation in yeast, we illustrate the capacity of this simulation technique to provide insights into cell biological processes. The modeling algorithms, implemented in a new version of the Simmune toolset, are accessible through intuitive graphical interfaces and programming libraries.
细胞信号转导过程依赖于分子成分的时空分布。多色、高分辨率显微镜可以详细评估这些分布,为精细的计算模型提供输入,这些模型探索了控制多分子复合物动态组装的机制及其在塑造细胞行为中的作用。然而,将复杂的分子反应级联和信号成分在动态细胞形态中的空间定位纳入到这些模型中是具有挑战性的。在这里,我们介绍了一种方法,通过基于简单的双分子相互作用规则,自动生成复杂反应网络的计算表示,这些规则嵌入到细胞形态的详细、自适应模型中,从而解决这些挑战。我们使用了受体介导的细胞黏附和信号诱导的局部有丝分裂原激活蛋白激酶 (MAPK) 激活的例子来说明这种模拟技术提供对细胞生物学过程的见解的能力。建模算法在 Simmune 工具集的新版本中实现,可通过直观的图形界面和编程库访问。