Systems-level analysis of the regulation and function of p53 dynamics

在这个项目中，我们将使用计算和实验技术的组合来表征健康细胞和癌细胞对重要细胞应激的p53动力学。为了测量电路组件的动态，我们将使用活细胞的长期延时荧光显微镜。我们将使用化学和遗传扰动来改变p53动力学，并确定对p53靶基因表达和细胞命运的影响。使用计算建模，我们将这些数据与细胞结果的测量相结合，以预测响应特定扰动的通路行为。通过允许我们研究在小尺度相互作用水平上不明显的涌现性质，这种类型的方法将提供操纵电路功能的新策略，以及对抗p53动力学失调的癌症的新方法。根据p53刺激确定p53动力学的类别：虽然对p53对γ辐射的反应有很大的兴趣，但它只是可以激活p53的众多应激之一，包括其他形式的DNA损伤，核糖体应激和致癌基因。我们已经表明，p53显示出显着不同的动力学行为时，暴露于紫外线辐射的梯度脉冲。我们的初步研究还发现，某些化学物质激活p53可以产生无阻尼脉冲或分级脉冲。我们将确定p53对广泛刺激的动态反应，并根据p53动态对应激进行分类。我们将使用长时间的延时荧光显微镜来测量单细胞中荧光标记的p53在高时间分辨率下的动态。识别不同的动力学类别和每个类别中聚集的压力将为理解p53网络的先前未知的调节水平提供基础，并将为研究p53动力学的功能提供信息。2.使用合成生物学方法控制p53动力学：越来越多的新工具和方法可用于直接调节活细胞中信号分子的表达和活性。我们将使用这种方法来扰动p53动力学的各种特性（例如，p53脉冲幅度，持续时间和频率），并确定这种扰动对p53下游功能的影响。这种合成方法将补充上述依赖于自然应力来激活p53.3的动态表达的方法。基于p53动力学识别靶基因表达模式：我们对p53动力学类别的发现表明，p53靶基因可能显示出影响细胞反应的复杂动力学表达模式。例如，当p53经历γ型动力学时，某些促凋亡基因可能以逐步方式表达，但当p53经历UV型动力学时，以快速饱和动力学表达。这可以被转化为细胞凋亡的差异触发，这是一致的事实，即不同的细胞命运发生在响应γ或UV radiation.Since p53调节超过100个基因，我们将首先采取qPCR方法来探测p53动力学的功能。将使用荧光转录报告基因进行单细胞水平分析，通过对重要靶基因进行更详细的研究进行验证。我们将分析基因表达谱的刺激内个别p53动态类和跨不同的类。我们预测，依赖于p53动态的表达模式的基因将集群的动态类。为了验证基因表达对p53动力学的依赖性，我们将比较压力反应曲线和我们扰动p53动力学的条件下的曲线。在初步研究中，我们已经使用小分子、反馈调节剂的RNAi和合成工程反馈来干扰对伽马或UV的动态响应。2012财年的进展：NCI病理学实验室的系统生物学部门成立于2011年5月。在过去的一年里，我为这个部门雇用了我的三名工作人员。一名生物学家于2012财年初抵达，并帮助采购了拟议研究所需的设备和试剂。我已经聘请了两名博士后研究员，一位是具有“湿实验室”专业知识的生物药理学家，另一位是具有生物调节电路计算建模经验的电气工程师。他们将在下个财政年度开始时到达实验室。我还指导了两名暑期实习生，并开始指导病理学实验室的临床研究员。此外，在本财政年度采购了该科用于研究的主要设备，即一个长期延时荧光显微镜系统，目前正在采购第二个系统。在过去的一年里，我一直是一篇文章的撰稿人（Purvis等人，2012，Science. 336：1440-4），其显示至少响应于DNA双链断裂的p53动力学的扰动可影响细胞命运。通过改变p53的自然振荡反应，使p53保持恒定的高水平，细胞在早期激活了衰老程序。我们目前正在跟进这项研究，开发合成生物学工具，使用各种蛋白融合来确定更精确地控制p53动力学的方法。我们还开始研究p53的广泛天然刺激，并确定了p53响应新压力的独特动力学调节。我们目前正在描述这些新的反应，并确定产生它们的监管机制。

PURPOSE:In this project, we will use a combination of computational and experimental techniques to characterize p53 dynamics in healthy and cancerous cells in response to important cellular stresses. To measure the dynamics of circuit components, we will use long-term time-lapse fluorescence microscopy of living cells. We will use chemical and genetic perturbations to alter p53 dynamics and determine the effect on p53 target gene expression and cell fate. Using computational modeling, we will integrate these data with measurements of cellular outcomes to predict pathway behavior in response to specific perturbations. By allowing us to study emergent properties that are not evident at the level of smaller-scale interactions, this type of approach will provide novel strategies for manipulating circuit functions, as well as new ways to combat cancers in which p53 dynamics are dysregulated.MATERIALS AND METHODS:1. Determining classes of p53 dynamics based on p53 stimuli:While there has been a great deal of interest in the p53 response to gamma radiation, it is only one of numerous stresses that can activate p53, including additional forms of DNA damage, ribosomal stress, and oncogenes. We have shown that p53 shows the strikingly distinct dynamical behavior of graded pulses when exposed to UV radiation. Our preliminary studies have also found that activation of p53 by certain chemicals can generate either undamped pulses or graded pulses. We will determine the p53 dynamical response to a broad range of stimuli and classify stresses based on p53 dynamics. We will use long-term time-lapse fluorescence microscopy to measure the dynamics of fluorescently-tagged p53 at high temporal resolution in single cells. Identifying the different dynamical classes and the stresses that cluster in each class will provide a foundation for understanding a previously unknown level of regulation of the p53 network, and will inform research into the function of p53 dynamics. 2. Using synthetic biology approaches to control p53 dynamics:New tools and approaches are increasingly becoming available to directly regulate the expression and activities of signaling molecules in live cells. We will use such approaches to perturb various characteristics of p53 dynamics (for example, p53 pulse amplitude, duration, and frequency), and determine the effect that such perturbations have on p53's downstream functions. This synthetic approach will complement the above approaches that rely on natural stresses to activate dynamical expression of p53.3. Identifying target gene expression patterns based on p53 dynamics:Our discovery of p53 dynamical classes suggests that p53 target genes may show complex dynamical expression patterns that impact cellular responses. For example, it may be that certain pro-apoptotic genes are expressed in a step-wise manner when p53 undergoes gamma-type dynamics, but are expressed with fast saturation kinetics when p53 undergoes UV-type dynamics. This could be translated into differential triggering of apoptosis, which is consistent with the fact that distinct cell fates occur in response to gamma or UV radiation.Since p53 regulates over 100 genes, we will initially take a qPCR approach to probe the function of p53 dynamics. Validation by more detailed studies of important target genes will be performed using single-cell level analysis with fluorescent transcriptional reporters. We will analyze gene expression profiles for stimuli within individual p53 dynamical classes and across distinct classes. We predict that genes with expression patterns that are dependent on p53 dynamics will cluster by the dynamical classes. To verify the dependence of gene expression on p53 dynamics, we will compare stress-response profiles to profiles for conditions in which we have perturbed p53 dynamics. In preliminary studies, we have used small molecules, RNAi of feedback regulators, and synthetic engineered feedbacks to perturb the dynamical response to gamma or UV. PROGRESS IN FY2012:The Systems Biology Section of the NCI Laboratory of Pathology was established in May 2011. In the past year, I have hired the full three members of my staff for this section. A staff biologist arrived at the beginning of FY2012, and has helped with the procurement of the equipment and reagents required for the proposed research. I have hired two postdoctoral research fellows, one a biophysicist with "wet-lab" expertise, and the other an electrical engineer with experience in the computational modeling of biological regulatory circuits. they will be arriving in the lab at the start of the next fiscal year. I have also mentored two summer interns, and have started mentoring a Laboratory of Pathology clinical research fellow. Additionally, the major equipment for the research in the section, a long-term time-lapse fluorescence microscopy system, has been procured in this fiscal year, with a second system currently in the process of being procured. In the past year, I have been a contributing author on an article (Purvis et al, 2012, Science. 336: 1440-4) that showed that perturbation of p53 dynamics, at least in response to DNA double strand breaks, can affect cellular fate. By changing the natural oscillatory response of p53 to a response in which p53 remained constantly high, cells activated the senescence program at early times. We are currently following up with this research, developing synthetic biology tools using various protein fusions to identify ways to more precisely control p53 dynamics.We have also begun looking at a broad range of natural stimuli of p53, and have identified unique dynamical regulation of p53 in response to novel stresses. We are currently characterizing these new responses and identifying the regulatory mechanisms that generate them.