Decoding Stress-Activated Protein Kinase pathways through the comprehensive modeling and experimental systems biology

 描述(申请人提供)：在人类中，丝裂原活化蛋白激酶(MAPK)保护细胞免受缺血、高渗透、紫外线辐射和其他应激因素的影响。异常调节的MAPK通路导致阿尔茨海默病、肌萎缩侧索硬化症和癌症等疾病。在这个提案中，我们详细介绍了一个多学科的研究计划，该计划结合了数学建模、生化和遗传实验以及活细胞成像，以更好地了解MAPK如何协调细胞对环境压力的反应。利用一种创新的生化技术，我们最近积累的实验证据有力地表明，酵母高渗透压甘油(HOG)途径中的快速信号激活是通过正反馈编码的，而途径失活是通过延迟的负反馈发生的。HOG途径通过与哺乳动物MAPKs p38和JNK同源的MAPK Hog1将高渗应激传递到细胞核。两个不同的信号分支(Sho1和Sln1)激活Hog1。在目标1a)中，我们使用数学模型来识别最有可能的HOG通路反馈网络，该网络动态地调节MAPK以响应持续的高渗透胁迫。我们通过提供一个与我们的初步实验数据相一致的模型来证明我们的建模方法到目前为止是成功的。在目标1b)中，我们扩展了我们的数学模型，以预测MAPK将如何对瞬时高渗透胁迫做出反应。我们通过实验将酵母暴露在盐诱导的高渗应激的瞬时应用中，并通过活细胞成像测量MAPK-GFP结构的MAPK磷酸化水平和核转位，以检验模型预测。在目标2a)中，我们通过删除激活Sho1分支的Sho1跨膜渗透压传感器构建了一个缺乏反馈调节的酵母菌株。我们使用这个结构(Sho1MAPK)来检测Δ在SLN1分支中的磷酸化。然后，我们使用我们的初步数据、数学模型和参数敏感性分析来了解每个分支(Sho1和SLn1)是如何促进MAPK磷酸化的。最后，我们测量了每个菌株中MAPK-GFP的核转移率，以确定每个分支是如何单独促进MAPK激活的。最终，这些目标的结合将使我们能够更好地理解反馈调节和分支途径如何促进MAPK活动。这项工作意义重大，因为它将建立信号机制，允许多条途径对压力适应做出贡献。由于最初在酵母中发现的许多信号机制已被证明在包括人类在内的许多细胞类型中都是保守的，我们预计我们的结果将影响我们对人类疾病的理解。

 DESCRIPTION (provided by applicant): In humans, Mitogen-Activated Protein Kinases (MAPKs) protect cells against ischemia, hyper-osmolarity, uv-irradiation and other stressors. Dysregulated MAPK pathways contribute to diseases such as Alzheimer's Disease, Amyotrophic Lateral Sclerosis and cancer. In this proposal we detail a multi-disciplinary research plan that combines mathematical modeling, biochemical and genetic experimentation, and live-cell imaging to better understand how MAPKs coordinate cellular responses to environmental stress. Using an innovative biochemical technique, we have recently accumulated experimental evidence that strongly suggests that rapid signal activation in the yeast High-Osmolarity Glycerol (HOG) Pathway is encoded via positive feedback, and that pathway deactivation occurs via delayed negative feedback. The HOG pathway transmits the presence of hyper-osmotic stress to the nucleus of a cell through the MAPK Hog1, a homolog to the mammalian MAPKs p38 and JNK. Two distinct signaling branches (Sho1 and Sln1) activate Hog1. In Aim 1a) we use mathematical modeling to identify the most likely HOG pathway feedback network that dynamically regulates the MAPK in response to sustained hyper-osmotic stress. We demonstrate that our modeling approach has thus far been successful by presenting a model that agrees with our preliminary experimental data. In Aim 1b) we then extend our mathematical models to predict how the MAPK will respond to transient hyper-osmotic stress. We test the model predictions by experimentally exposing yeast to transient applications of salt induced hyper-osmotic stress and measure MAPK phosphorylation levels and nuclear translocation of a MAPK-GFP construct through live-cell imaging. In Aim 2a) we construct a yeast strain that is absent feedback regulation by deleting the Sho1 trans-membrane osmo-sensor that activates the Sho1 branch. We use this construct (sho1Δ) to measure MAPK phosphorylation in the Sln1 branch. We then use our preliminary data, mathematical models and parametric sensitivity analysis to understand how each branch (Sho1 and Sln1) contributes to MAPK phosphorylation. Finally, we measure the MAPK-GFP nuclear translocation rate in each strain to determine how each branch individually contributes to MAPK activation. Ultimately, the combination of these aims will allow us to better understand how feedback regulation and branched pathways contribute to MAPK activity. This work is significant because it will establish signaling mechanisms that allow multiple pathways to contribute to stress adaptation. Because many signaling mechanisms initially discovered in yeast have proven to be conserved across many cell types, including human, we expect our results to impact our understanding of human disease.