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。信使核糖核蛋白的转录后调控 颗粒在蛋白质组对环境变化的调节中起着重要作用。 加工体(PBS)和应激颗粒(SGS)是应激诱导的mRNP颗粒，从酵母中保守 对哺乳动物来说，它协调调节mRNAs的定位、翻译、降解和存储。 它们对基因表达的不同影响，PBS和SGS与许多疾病有关，特别是 神经退行性疾病和癌症。虽然PBS/SGS本质上是高度动态的，这证明了 对于它们的功能至关重要，以前的大多数研究都只集中在生化特性上 这些颗粒与在静态时间点进行的测量。如何动态监管PBS/SGs以及 它们在生理条件下的功能作用在很大程度上仍不清楚。我们最近的结果显示， 蛋白激酶A(PKA)调节的PBS和SGS的形成在调节应激反应中起核心作用 基因表达，促进持久的细胞记忆，促进未来的压力适应。建立在 这些发现，我们将结合实验和建模来系统地研究PBS/SGS过程 酵母细胞中的动态输入和控制基因表达和长期应激反应。在目标1中，我们将 追踪代表应激反应基因的PBS/SGS、mRNAs和蛋白质在单个 细胞对各种动态环境/信号输入的响应。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PBS/SGS如何解码输入动态并控制 快速变化环境下的mRNA命运和蛋白质表达动态。在《目标2》中，我们将追踪 利用我们的新近发现的PBS/SGS在母细胞中的遗传 开发了酵母母设备，并将评估颗粒遗传在基因表达和应激中的作用 细胞系中的抗性。利用这些数据，我们将构建一个随机模型来定量评估 MRNP颗粒遗传对细胞系间和克隆种群异质性的贡献。 在目标3中，我们将系统地描述酵母蛋白质组对环境的响应。 使用高通量“2K”改变和评估PBS和SGS在控制这些动态方面的作用 这些数据将被用来开发系统级的基因动态模型 PBS/SGS调控基因的表达。这些目标的实现将极大地促进我们对 关于PBS/SGS如何在快速变化的环境下运营和运作，并将导致 预测模型将提供对PB/SG介导的基因表达控制的机械性见解。

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.