Chylek Lily A, Holowka David A, Baird Barbara A, Hlavacek William S
Department of Chemistry and Chemical Biology, Cornell University , Ithaca, NY , USA ; Los Alamos National Laboratory, Theoretical Division, Center for Non-linear Studies , Los Alamos, NM , USA.
Department of Chemistry and Chemical Biology, Cornell University , Ithaca, NY , USA.
Front Immunol. 2014 Apr 15;5:172. doi: 10.3389/fimmu.2014.00172. eCollection 2014.
Antigen receptors play a central role in adaptive immune responses. Although the molecular networks associated with these receptors have been extensively studied, we currently lack a systems-level understanding of how combinations of non-covalent interactions and post-translational modifications are regulated during signaling to impact cellular decision-making. To fill this knowledge gap, it will be necessary to formalize and piece together information about individual molecular mechanisms to form large-scale computational models of signaling networks. To this end, we have developed an interaction library for signaling by the high-affinity IgE receptor, FcεRI. The library consists of executable rules for protein-protein and protein-lipid interactions. This library extends earlier models for FcεRI signaling and introduces new interactions that have not previously been considered in a model. Thus, this interaction library is a toolkit with which existing models can be expanded and from which new models can be built. As an example, we present models of branching pathways from the adaptor protein Lat, which influence production of the phospholipid PIP3 at the plasma membrane and the soluble second messenger IP3. We find that inclusion of a positive feedback loop gives rise to a bistable switch, which may ensure robust responses to stimulation above a threshold level. In addition, the library is visualized to facilitate understanding of network circuitry and identification of network motifs.
抗原受体在适应性免疫反应中发挥核心作用。尽管与这些受体相关的分子网络已得到广泛研究,但目前我们仍缺乏对非共价相互作用和翻译后修饰的组合在信号传导过程中如何被调控以影响细胞决策的系统层面的理解。为填补这一知识空白,有必要将关于个体分子机制的信息形式化并整合起来,以形成信号网络的大规模计算模型。为此,我们开发了一个用于高亲和力IgE受体FcεRI信号传导的相互作用库。该库由蛋白质 - 蛋白质和蛋白质 - 脂质相互作用的可执行规则组成。这个库扩展了早期的FcεRI信号传导模型,并引入了以前在模型中未被考虑的新相互作用。因此,这个相互作用库是一个工具包,利用它可以扩展现有模型并构建新模型。例如,我们展示了来自衔接蛋白Lat的分支途径模型,这些途径影响质膜上磷脂PIP3和可溶性第二信使IP3的产生。我们发现包含一个正反馈环会产生一个双稳态开关,这可能确保对高于阈值水平的刺激产生稳健反应。此外,该库以可视化方式呈现,便于理解网络电路和识别网络基序。