Stimulus design for model selection and validation in cell signaling
Stimulus design for model selection and validation in cell signaling
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DOI：
10.1371/journal.pcbi.0040030
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发表时间：
2008-02-01
影响因子：
4.3
通讯作者：
Tidor, Bruce
中科院分区：
文献类型：
--
作者：
Apgar, Joshua F.;Toettcher, Jared E.;Tidor, Bruce
基于机制的化学动力学模型越来越多地用于描述生物信号传导。这些模型有助于概括当前对途径的理解，并能够洞察复杂的生物过程。模型开发的一大挑战是，在实验数据有限的情况下，多个模型如何与已知机制和现有数据保持一致。在这里，我们通过提供一种设计动态刺激的方法来解决模型模糊性的问题，该方法在刺激-响应实验中区分具有不同拓扑的参数化模型，即反应机制，其中只能测量某些物种。我们通过提出用于设计动态刺激的基于模型的控制器的两种公式来开发该方法。在这两种公式中，都为每个候选模型和参数化设计了输入信号，以便通过目标轨迹驱动模型输出。然后，模型的质量通过相应控制器的能力进行评估，该控制器根据该模型驱动实验系统。我们在抗体-配体结合、丝裂原激活蛋白激酶 (MAPK) 磷酸化和去磷酸化模型以及表皮生长因子受体 (EGFR) 途径的更大模型上评估了我们的方法。对于这些系统中的每一个，由正确模型通知的控制器在设计刺激以产生所需行为方面是最成功的。使用这些刺激，我们能够区分具有细微机械差异的模型，或者输入和输出是从模型差异中删除的多个反应。这种模型区分方法的优点是它不需要新的试剂或改变的测量技术；实验的唯一变化是刺激的时间过程。总而言之，这些结果为使用设计的输入刺激作为开发细胞信号传导模型的工具提供了坚实的基础。
Mechanism-based chemical kinetic models are increasingly being used to describe biological signaling. Such models serve to encapsulate current understanding of pathways and to enable insight into complex biological processes. One challenge in model development is that, with limited experimental data, multiple models can be consistent with known mechanisms and existing data. Here, we address the problem of model ambiguity by providing a method for designing dynamic stimuli that, in stimulus - response experiments, distinguish among parameterized models with different topologies, i.e., reaction mechanisms, in which only some of the species can be measured. We develop the approach by presenting two formulations of a model-based controller that is used to design the dynamic stimulus. In both formulations, an input signal is designed for each candidate model and parameterization so as to drive the model outputs through a target trajectory. The quality of a model is then assessed by the ability of the corresponding controller, informed by that model, to drive the experimental system. We evaluated our method on models of antibody - ligand binding, mitogen-activated protein kinase (MAPK) phosphorylation and de-phosphorylation, and larger models of the epidermal growth factor receptor (EGFR) pathway. For each of these systems, the controller informed by the correct model is the most successful at designing a stimulus to produce the desired behavior. Using these stimuli we were able to distinguish between models with subtle mechanistic differences or where input and outputs were multiple reactions removed from the model differences. An advantage of this method of model discrimination is that it does not require novel reagents, or altered measurement techniques; the only change to the experiment is the time course of stimulation. Taken together, these results provide a strong basis for using designed input stimuli as a tool for the development of cell signaling models.