EAGER: Systems Analysis of Signaling Pathway towards Robust Differentiation

EAGER：实现稳健分化的信号通路系统分析

• 批准号: 1455800
• 负责人: Ipsita Banerjee
• 金额: $ 10万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2016-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1455800&HistoricalAwards=false
• 关键词: EAGER; Systems; Analysis; Signaling; Pathway

1455800 Banerjee, Ipsita Pluripotent stem cells have the unique capability of giving rise to any tissue-specific cell type at an unlimited quantity. These outstanding properties make them a promising candidate as a renewable source of human tissue for research, pharmaceutical testing and cell-based therapies. The feasibility of obtaining organ-specific cell types by modulation of associated signaling pathways has already been demonstrated. However, the differentiated cell types at present remain limited in their yield and mature functionality. The next challenge in realizing the potential of stem cells is to ensure functional and homogenous maturation of these cells to the desired lineage. This goal can be achieved through a quantitative understanding of signal transduction and noise propagation through the signaling pathway. The topic of this EAGER proposal is to develop a quantitative and predictive representation of a critical signal transduction pathway driving stem cell differentiation. Once it is known how signals are transduced and how uncertainty is propagated during differentiation, it will be possible to design targeted interventions to achieve homogenous and efficient differentiation. The predictive platform to be developed in this project will inform the design of targeted interventions for efficient and homogenous differentiation of stem cells.In this proposal, the Transforming Growth Factor beta (TGF beta) signaling pathway will be analyzed for differentiating pluripotent stem cells by integrating quantitative experiments with predictive modeling and systems analysis. The TGF beta pathway plays a central role in inducing definitive endoderm differentiation in human pluripotent stem cell. Key components of the experimental platform will be the development of techniques for quantitative single cell level analysis of stem cell dynamics, in order to ensure accurate representation of a cell¡¦s dynamic response, unbiased by heterogeneity in the population. Specifically, the dynamics of TGF beta effectors molecules will be quantified in individual cell compartment using Green Fluorescent Protein fused effector proteins. The nucleo-cytoplasmic shuttling of these proteins will be quantified using Fluorescence Recovery after Photobleaching (FRAP) assay. Experimentally obtained single cell dynamics will be used to train the mathematical model of the pathway. Ensemble modeling will be used to integrate the single cell information to represent heterogeneity in cell population. Computational efficiency of this integration will be enhanced by a meta-modeling technique. Global sensitivity analysis of the ensemble model will allow identification of key mechanisms governing signal transduction. The model predictions will be experimentally validated at every step of the model development. The validated model will be further analyzed for propagation of uncertainty through the system by (i) experimental measurement of input variability and (ii) in-silico simulation of propagation of input variability to output molecules. The final outcome of the proposed project will be an experimentally validated predictive platform which will allow design of targeted perturbations to enhance differentiation efficiency while reducing heterogeneity in the differentiated population.

1455800 Banerjee, Ipsita 多能干细胞具有无限数量产生任何组织特异性细胞类型的独特能力，这些出色的特性使它们成为组织研究、药物测试和细胞基础的人类可再生来源的有前途的候选者。通过调节相关信号通路获得器官特异性细胞类型的可行性已经得到证实，然而，目前分化的细胞类型在产量和成熟功能方面仍然有限，这是实现干细胞潜力的下一个挑战。是为了确保这些细胞的功能和同质成熟到所需的谱系，这个目标可以通过对信号转导和噪声传播的信号通路的定量理解来实现。一旦了解信号如何转导以及分化过程中不确定性如何传播，就可以设计有针对性的干预措施以实现同质且高效的分化。将告知设计在该提案中，将通过定量整合实验与预测模型和系统分析来分析转化生长因子β（TGFβ）信号通路在分化多能干细胞中的核心作用。在诱导人类多能干细胞定形内胚层分化方面，实验平台的关键组成部分将是干细胞动力学的单细胞水平分析技术的开发，以确保细胞的准确表达。具体而言，将使用绿色荧光蛋白融合效应蛋白在单个细胞区室中量化 TGF β 效应分子的动态。将使用荧光恢复来量化这些蛋白质的核-细胞质穿梭。光漂白（FRAP）测定后，将使用实验获得的单细胞动力学来训练该通路的数学模型，该模型将用于整合单细胞信息。通过元建模技术来表示细胞群的异质性，将能够识别控制信号转导的关键机制。模型预测将在每个步骤中得到实验验证。模型开发将通过（i）输入变异性的实验测量和（ii）输入变异性到输出分子的计算机模拟来进一步分析不确定性在系统中的传播。项目将是一个经过实验验证的预测平台，将允许设计有针对性的扰动，以提高分化效率，同时减少分化群体的异质性。