Dynamically compartmentalized control of gene expression by messenger ribonucleoprotein granules

项目摘要 细胞通过复杂信号介导的适应在快速变化的环境中生存 和基因调控过程。信使核糖核蛋白（mRNP）的转录后调节 颗粒在响应环境变化的蛋白质组调节中起重要作用。 加工体（PB）和应激颗粒（SG）是由应激诱导的mRNP颗粒，它们是从酵母中保存下来的 对于哺乳动物，它们协调调节mRNA的定位、翻译、降解和储存。 它们对基因表达的不同影响，PB和SG与许多疾病有关，特别是 神经退行性疾病和癌症。虽然PB/SG在本质上是高度动态的，这证明了 对于它们的功能至关重要，大多数以前的研究只集中在生物化学特征上 在静态时间点进行测量。PB/SG如何动态调节， 它们在生理条件下的功能性作用仍然很不清楚。我们最近的研究结果显示， 蛋白激酶A（PKA）调节的PB和SGs的形成在调节应激反应中起着重要作用 基因表达，促进持久的细胞记忆，以促进未来的压力适应。基础上 基于这些发现，我们将联合收割机实验与模型相结合，系统地研究PB/SG的加工过程 动态输入和控制基因表达以及酵母细胞中的长期应激反应。在目标1中，我们 跟踪PB/SGs，mRNA和蛋白质的动态，为代表性的压力响应基因在单一的 细胞响应各种动态环境/信号输入。根据这些动态数据，我们将 开发一个计算模型来模拟和预测PB/SG如何解码输入动态并控制 在快速变化的环境中mRNA命运和蛋白质表达动态。在目标2中，我们将跟踪 利用我们最近的研究， 开发了酵母母装置，并将评估颗粒遗传在基因表达和胁迫中的作用 细胞谱系中的抗性。利用这些数据，我们将构建一个随机模型来定量评估 mRNP颗粒遗传对细胞谱系和克隆群体异质性的贡献。 在目标3中，我们将系统地表征酵母蛋白质组动态响应环境 改变和评估的作用PB和SG在控制这些动态使用高通量“2K DynOMICS”微流体平台。这些数据将用于建立基因的系统级动态模型 通过PB/SG进行表达控制。这些目标的完成将大大促进我们的理解 关于PB/SG如何在快速变化的环境下运行和运作，并将导致产生 预测模型，将提供PB/SG介导的基因表达控制的机制见解。

Project Summary Cells survive rapidly changing environments through adaptation mediated by sophisticated signaling and gene regulatory processes. Posttranscriptional regulation by messenger ribonucleoprotein (mRNP) granules plays an important role in the modulation of the proteome in response to environmental changes. Processing bodies (PBs) and stress granules (SGs) are stress-induced mRNP granules, conserved from yeast to mammals, that coordinate to regulate the localization, translation, degradation and storage of mRNAs.Given their diverse effects on gene expression, PBs and SGs are implicated in many diseases, especially neurodegenerative diseases and cancers. Although PBs/SGs are highly dynamic in nature, which proves crucial for their functions, the majority of previous studies have focused only on the biochemical characteristics of these granules with measurements made at static time points. How PBs/SGs are dynamically regulated and their functional roles under physiological conditions remain largely unclear. Our recent results revealed that the protein kinase A (PKA)-regulated formation of PBs and SGs plays a central role in regulating stress responsive gene expression, promoting a long-lasting cellular memory to facilitate future stress adaptation. Building upon these findings, we will combine experiments with modeling to systematically investigate how PBs/SGs process dynamic inputs and control gene expression and long-term stress responses in yeast cells. In Aim 1, we will track the dynamics of PBs/SGs, mRNAs, and proteins for representative stress responsive genes in single cells in response to various dynamic environmental/signaling inputs. Based on these dynamic data, we will develop a computational model to simulate and predict how PBs/SGs decode input dynamics and control the mRNA fates and protein expression dynamics under rapidly changing environments. In Aim 2, we will track inheritance of PBs/SGs from mother cells by their progenies over many generations using our recently- developed yeast mother device, and will evaluate the role of granule inheritance in gene expression and stress resistance in cell lineages. Using these data, we will construct a stochastic model to quantitatively evaluate the contributions of mRNP granule inheritance to the heterogeneity across cell lineages and in clonal populations. In Aim 3, we will systematically characterize the yeast proteome dynamics in response to environmental changes and evaluate the roles of PBs and SGs in controlling these dynamics using a high-throughput "2K DynOMICS" microfluidic platform. These data will be used to develop a systems-level dynamic model of gene expression control by PBs/SGs. The completion of these aims will significantly advance our understanding about how PBs/SGs operate and function under rapidly changing environments and will lead to the generation of predictive models that will provide mechanistic insights into the PB/SG-mediated control of gene expression.