Delays and variability in single-cell NFkB signaling

描述(由申请人提供)： NFkB是一种可诱导的转录因子，在应激、细胞因子以及细菌和病毒病原体的作用下被激活，是免疫反应的主要调节因子。NFkB调控网络处理来自各种细胞膜受体的信号，以控制参与免疫和炎症反应、细胞增殖和生存的基因的转录。NFkB信号与许多人类炎症性疾病有关，如关节炎和哮喘，由于其活性在肿瘤中经常上调，NFkB信号正被积极作为癌症治疗的靶点。对最终导致NFkB激活的信号通路的详细了解将对发现有效的NFkB抑制剂至关重要。为此，该项目将开发和实验验证具有预测能力的计算模型，这些模型可以用来理解哺乳动物细胞中NFkB信号的复杂性。每个目标都将通过在受控微流控环境中进行的建模和定量单细胞实验相结合的方式来研究NFkB信号的一个特定方面。具体地说，第一个目标是开发一个基于随机延迟的计算模型，用于研究由瞬时肿瘤坏死因子信号驱动的NFkB动力学。为此，将创建新的细胞系，允许通过荧光显微镜实时跟踪ikk和NFkB的表达。建模将用于预测网络对各种驱动条件和网络体系结构突变的响应。第二个目标将集中在IKK调节周期在放大或过滤受体发出的信号波动中的作用。周期内IKK周转率将有所不同，以研究上游波动向NFkB模块核心的传播。第三个目标将解决两个平行的途径(MyD88和TRIF)的作用，这些途径由病原体来源的脂多糖(LPS)信号启动。涉及精心控制的外部内毒素或侵袭性大肠杆菌脉冲的实验将与数学建模结合使用，以表征内毒素-NFkB途径的动力学和变异性。在第四个目标中，细胞间信号在产生NFkB介导的反应中的作用将通过检测自分泌和旁分泌的肿瘤坏死因子信号来解决。该项目的成功完成不仅将导致NFkB信号的预测计算模型，而且还将深入了解这个中央调控网络如何处理信息以响应刺激、抑制和药物调制。 公共卫生相关性： 核因子B(NFB)是先天和获得性免疫反应的关键调节因子。NFB的错误调节可能导致广泛的人类疾病，如癌症、神经退行性疾病和病理性炎症条件。这项建议的中心目标是开发和实验验证一种可靠的定量建模方法，该方法可以用于描述NFB信令网络并预测其在动态自然环境中的行为。1

DESCRIPTION (provided by applicant): NFkB is an inducible transcription factor that is activated in response to stress, cytokines and bacterial and viral pathogens, and is a major regulator of immune responses. The NFkB regulatory network processes signals that originate at a variety of cell membrane receptors to control the transcription of genes involved in immune and inflammatory responses, cell proliferation and survival. NFkB signaling has been linked to a number of human inflammatory diseases, such as arthritis and asthma, and because its activity is often up- regulated in tumors, NFkB signaling is actively being pursued as a target for cancer therapies. A detailed understanding of the signaling pathways that culminate in NFkB activation will be crucial for the discovery of effective NFkB inhibitors. To this end, this project will develop and experimentally validate computational models with predictive capabilities that can be used to understand the complexities of NFkB signaling in mammalian cells. Each aim will investigate a particular aspect of NFkB signaling through a combination of modeling and quantitative single-cell experiments performed in controlled microfluidic environments. Specifically, the first aim will develop a stochastic delay-based computational model of NFkB dynamics driven by transient TNF signals. For this, novel cell lines will be created that allow IKK and NFkB expression to be tracked in real time by fluorescence microscopy. Modeling will be used to predict the network response to various driving conditions and mutations in network architecture. The second aim will focus on the role of the IKK regulatory cycle in amplifying or filtering fluctuations in signals emanating from receptors. The rate of IKK turnover within the cycle will be varied to study the propagation of upstream fluctuations into the core of the NFkB module. The third aim will address the role of two parallel pathways (MyD88 and TRIF) initiated by pathogen-derived lipopolysaccharide (LPS) signals. Experiments involving either carefully controlled pulses of external LPS or invasive E. coli will be used in conjunction with mathematical modeling to characterize the dynamics and variability of the LPS-NFkB pathways. In the fourth aim, the role of cell-to-cell signaling in generating NFkB-mediated responses will be addressed by examining autocrine and paracrine TNF signaling. The successful completion of this project will result not only in a predictive computational model for NFkB signaling but also in insights into how this central regulatory network processes information in response to stimulation, inhibition, and drug modulation. PUBLIC HEALTH RELEVANCE: Project Narrative Nuclear factor B (NFB) is a key regulator of innate and adaptive immune responses. Misregulation of NFB may lead to a wide range of human diseases such as cancer, neurodegenerative disorders, and pathological inflammatory conditions. The central goal of this proposal is to develop and experimentally validate a reliable quantitative modeling approach that can be used to describe the NFB signaling network and predict its behavior in dynamic natural environments. 1