Collaborative Research: The Dynamics of the Innate Immune Systems: A Study of the Toll-like Receptors (TLR) Network

智力优势：抵御微生物感染或组织损伤的第一道防线是先天免疫系统，它通过引发炎症来应对有害刺激，这是一种对组织修复和病原体清除至关重要的防御性反应。然而，过度的炎症是有害的，因为它会产生进一步的组织损伤；因此，必须通过抗炎反应来对抗炎症。因此，了解免疫系统的促炎和抗炎反应的动态是如何调节的是至关重要的。该项目的主要目的是阐明Toll样受体家族(TLR)的调节动力学，TLR是识别微生物病原体的天然免疫系统的组成部分。该项目是一项初步研究，探索使用系统和控制理论以及形式方法来研究先天免疫系统的动力学。形式化方法是数学和理论计算机科学的一个分支，它的发展是为了验证复杂工程系统的执行。研究人员将利用已发表的TLR激发实验的实验数据，开发一个结合信号和转录网络动力学的综合数学模型。此外，他们将开发新的形式化方法来分析这个模型。由于TLR网络的预期复杂性，调查人员将首先使用Silico产生的数据以及来自其他信令网络(如NF-kB网络)的现有较小数据集来测试他们的框架。预计这一项目的成功完成将建立一个框架，能够产生可用于TLR后续研究的可检验的预测。更广泛的影响：虽然该项目侧重于TLR网络的动力学特性的定量研究，但将开发的理论预计将广泛适用于与先天免疫相关的其他现象，包括自身免疫、慢性炎症和肥胖。此外，由于其普遍性，本项目中开发的框架将有助于研究其他细胞信号机制和相关的转录调控系统，如生长因子信号系统和细胞周期调控系统。作为该项目的一部分，研究生和本科生将接受培训，并为在生物学和工程学之间的前沿领域从事学术和工业职业做好准备。研究人员将把研究活动纳入研究生和本科生的课程。在波士顿大学波士顿大学学院和伦斯勒大学学前教育倡议中心(CIPCE)的赞助下，将开展面向K-12学生和教师的外联活动，特别是针对代表人数不足的少数族裔的学生。

Intellectual Merit: The first line of defense to microbial infections or tissue damage is the innate immune system, which responds to harmful stimuli by triggering inflammation, a defensive response that is essential for tissue repair and pathogen removal. However, excessive inflammation is harmful because it can produce further tissue damage; inflammation must therefore be countered by anti-inflammatory responses. Hence, it is crucial to understand how the dynamics of the pro- and anti-inflammatory responses of the immune system are regulated. The overarching aim of this project is to elucidate the regulation dynamics of the Toll-like family of receptors (TLR), which are components of the innate immune system that recognize microbial pathogens. The project constitutes a pilot study exploring the use of systems and control theory and formal methods to study the dynamics of the innate immune system. Formal methods is a branch of mathematics and theoretical computer science that has been developed to verify the execution of complex engineering systems. The investigators will use existing published experimental data from TLR excitation experiments, to develop an integrated mathematical model combining the dynamics of signaling and transcription networks. Further, they will develop novel formal methods to analyze this model. Because of the anticipated complexity of the TLR network, the investigators will initially test their framework using data generated in silico, as well as existing, smaller data sets from other signaling networks, such as the NF-kB network. It is anticipated that successful completion of this project will create a framework capable of producing testable predictions that can be used in subsequent studies of the TLR. Broader Impacts: While the project focuses on quantitative study of the dynamical properties of the TLR network, the theory that will be developed is expected to be broadly applicable to other phenomena related to the innate immunity, including, autoimmunity, chronic inflammation, and obesity. Furthermore, because of its generality, the framework developed in this project should lend itself to the study of other cellular signaling mechanisms and the related transcriptional regulation systems, for example, the growth-factor signaling system and the cell-cycle regulatory system. As part of this project, graduate and undergraduate students will be trained and prepared for academic and industrial careers at the leading edge of the interface between biology and engineering. The investigators will integrate the research activity into graduate and undergraduate curriculum. Outreach activities to K-12 students and teachers, particularly targeting students from underrepresented minorities, will be carried out under the auspices of BU Academy at Boston University and the Center for Initiatives in Pre-College Education (CIPCE) at Rensselaer.