Reconstruction and Modeling of Networks Involved in Cardiomyocyte Differentiation

描述（由申请人提供）：心脏祖细胞如何分化为心肌细胞？在过去的二十年里，这个问题一直是众多调查的主题。虽然这些实验已经确定了在分化的一个或多个阶段参与信号或转录调节途径的几个分子参与者，但导致心肌形成的细胞网络的全面和定量图像尚未出现。这是我们提案的主要目标。我们将从特定阶段分化过程初始化的粗粒度图像的遗留知识开始，并进行信息丰富的分析，以获得所涉及的参与者和信号模块的定性和定量知识。第一组检测将结合信号模块知识和模块特异性抑制剂的介绍，以初步了解哪些模块在分化的哪个阶段被激活或抑制。随后将进行磷酸化蛋白质组学分析，以确定特定的磷酸化级联反应，并为我们提供更详细的信号网络图像。我们将进一步使用阶段特异性基因表达测量和分析综合数据集来扩展这一研究，以获得导致心肌形成的更细粒度的途径。最重要的是，我们将使用细胞内钙的时空测量来开发信号网络的定量模型，这将有助于绘制前体细胞激活对心肌形成的反应。这种定量系统生物学方法有助于理解再生医学中最重要的过程之一，即ESCs形成心脏的过程，它有可能首先提供对细胞在心肌形成过程中运作的信号模块组合复杂性的见解。这将为我们提供有效地将ESCs分化为心肌细胞所需的特定触发和激活因子的重要信息。其次，我们将在分化的每个阶段开发一个部件列表和详细的事件网络地图，以建立分化的系统生物学视角。第三，也是最重要的，我们将提供定量框架映射输入到响应，即心肌生成的表型。最后，与我们的实验相关的配体和分子的鉴定将提供有趣的治疗靶点。该项目汇集了干细胞生物学、基因表达和定量系统生物学方面的专家，以一种非常协同的方式，将为社区提供宝贵的数据、模型和生物医学假设。心脏病是人类最常见的先天缺陷。这一建议的成功完成将极大地有助于我们目前对心脏发育和疾病的理解，并从长远来看，为未来的研究突出特定的分子途径，从而为未来的心脏药物治疗提供潜在的靶点。

DESCRIPTION (provided by applicant): How are cardiac progenitor cells primed to differentiate into cardiomyocytes? This question has been the subject of numerous investigations over the past two decades. While, these experiments have identified several molecular players that are involved in signaling or transcription regulation pathways at one or more stages of differentiation, a comprehensive and quantitative picture of the cellular networks leading to cardiomyogenesis is yet to emerge. This is a primary goal of our proposal. We will begin with a legacy knowledge of the coarse-grained picture of initiation of stage-specific differentiation processes and conduct information-rich assays to obtain qualitative and quantitative knowledge of the players and signaling modules involved. The first set of assays will combine signaling module knowledge with introduction of module-specific inhibitors to get a first glimpse at which modules are activated or repressed at which stages of differentiation. This will be followed by phosphoproteomic analysis to identify specific phosphorylation cascades and provide us a more detailed picture of the signaling networks. We will expand this further using stage-specific gene- expression measurements and analyze the integrated sets of data to obtain more fine-grained pathways that lead to cardiomyogenesis. Most importantly, we will use spatio-temporal measurements of intracellular calcium to develop a quantitative model of the signaling networks that will help map input to response in activation of precursor cells towards cardiomyogenesis. This quantitative systems biology approach towards understanding one of the most important processes in regenerative medicine, that of cardiac formation from ESCs has the potential first to provide insights into the combinatorial complexity of signaling modules that operate as cells progress through the cardiomyogenic program. This will provide us vital information on specific triggers and activators needed to efficiently differentiate ESCs into cardiomyocytes. Second, we will develop both a parts list and a detailed network map of events at each stage of differentiation to build a systems biology perspective on differentiation. Third and most important, we will provide the quantitative framework for mapping input to response, i.e. phenotype in cardiomyogenesis. Finally, identification of ligands and molecules associated with our experiments will provide interesting therapeutic targets. The project brings together experts in stem cell biology, gene expression and quantitative systems biology in an exceptionally synergistic manner and will provide the community with invaluable data, models and hypotheses for biomedicine. Heart disease is the most common birth defect in humans. Successful completion of this proposal would greatly aid in our current understanding of heart development and disease and in the longer term highlight specific molecular pathways for future studies and thus, potential targets for future cardiac drug therapies.