Functional Genomics of Stress Defense in Yeast

描述(由申请人提供)： 当外部条件或内部缺陷扰乱细胞动态平衡时，就会产生细胞应激。如果放任不管，这种压力会极大地改变正常生理，导致细胞死亡。 或者在没有正常控制机制的情况下疯狂生长。因此，细胞有复杂的信号网络，整合和传输适当的信号，以调节多方面的反应。这些反应通常涉及细胞周期进程、基因表达、蛋白质定位和功能以及新陈代谢的协调变化。人们对细胞如何协调多个下游过程知之甚少。此外，这一重要监管网络中的许多参与者以及它们之间的互动仍然未知。该建议旨在阐明在真核生物酿酒酵母模型中协调应激反应的复杂的全球信号网络。这项工作将应用突变转录组图谱、磷酸蛋白质组分析、计算生物学以及遗传学和分子生物学。一个关键的创新是生成在胁迫条件下收集的功能基因组和蛋白质组数据，以帮助从可用的大规模酵母数据集进行计算网络推断。目标1将改进和应用整数线性规划方法，该方法采用转录组图谱和功能数据来推断在渗透胁迫或DTT还原应激后协调基因组表达的全球调控网络。结合网络的分子验证，最终结果将是一个详细的、定向的全球信号分子网络，协调基因组表达以应对不同的压力。比较和对比对两种不同压力源的反应将揭示特定条件的调节者和网络中的共同参与者。目标2将采取一种补充的方法来询问磷酸蛋白质组网络。当细胞对渗透压或DTT胁迫做出反应时，野生型和突变型细胞中缺乏相关蛋白的野生型和突变型细胞的磷酸化蛋白质组的定量变化将通过质谱学进行鉴定。由此产生的磷酸网络将与AIM 1中的信号网络重叠，但将包括对不同生理过程的独特调节。将这两个目标的结果结合起来，将为协调基因表达、蛋白质磷酸化和对几种条件的生理反应的信号网络提供一个统一的视图。总之，这项工作将通过识别真核细胞应激反应的新调节因子，揭示它们之间的联系，并阐明协调应激反应的网络重写和信息流的机制，为应激生物学和信号转导提供许多新的见解。由于许多酵母信号蛋白具有与疾病相关的人类同源基因，这些结果将为在人类细胞中进行定向研究提供重要的背景。

DESCRIPTION (provided by applicant): Cellular stress results when external conditions or internal defects perturb cellular homeostasis. If left unattended, this stress can dramatically alter normal physiology, causing either cell death or rampant growth without normal control mechanisms. Cells therefore have intricate signaling networks that integrate and transmit the proper signals to mediate a multi-faceted response. These responses often involve coordinated changes in cell-cycle progression, gene expression, protein localization and function, and metabolism. How cells orchestrate multiple downstream processes is poorly understood. Furthermore, many of the players in this important regulatory network, and the interactions between them, remain unknown. This proposal aims to elucidate the complex global signaling network that orchestrates stress responses in the model eukaryote Saccharomyces cerevisiae. The work will apply mutant transcriptome profiling, phosphoproteomic analysis, computational biology, and genetics and molecular biology. A key innovation is generation of functional genomic and proteomic data collected under stress conditions, to aid in the computational network inference from available large-scale yeast datasets. Aim 1 will refine and apply an integer linear programming approach that takes transcriptome profiles and functional data to infer the global regulatory network that coordinates genomic expression after osmotic or DTT reductive stress. Combined with molecular validation of the network, the end result will be a detailed, directional global network of signaling molecule that coordinate genomic expression in response to different stresses. Comparing and contrasting the responses to two distinct stressors will reveal condition-specific regulators and common players in the network. Aim 2 will take a complementary approach to interrogate phospho-proteomic networks. Quantitative changes in the phospho-proteome will be identified by mass spectrometry, in wild-type and mutant cells lacking implicated kinases as cells respond to osmotic or DTT stress. The resulting phospho-networks will overlap with the signaling networks from Aim 1 but will include unique regulators of diverse physiological processes. Integrating the results from both aims will present a unified view of the signaling network that coordinates gene expression, protein phosphorylation, and physiological responses to several conditions. Together, this work will provide many new insights into stress biology and signaling, by identify new regulators of eukaryotic stress responses, uncovering the connections between them, and illuminating the mechanisms of network rewriting and information flow that coordinate stress responses. Because many yeast signaling proteins have human orthologs linked to disease, these results will provide an important backdrop for directed study in human cells.