Dendritic Cell Heterogeneity in Toll-like receptor 4 Signaling: Concept Validatio

由于无法解释与Toll样受体信号相关的定量信号参数的多变量变化，因此无法理解个体对先天免疫触发因素的敏感性的基础。因此，迫切需要多学科的方法来评估和解释Toll样受体信号的变异性对感染性病原体易感性的影响。我们的长期目标是通过建立预测技术的科学基础来改进传染病的临床管理，以帮助合理设计针对个别患者量身定做的治疗策略。 因此，拟议的研究与NIH使命中与发展基础知识相关的部分相关，这可能有助于减轻人类残疾的负担。该R21应用程序的总体目标是确定与感染剂敏感性相关的信号蛋白的独特模式，并应用反应途径分析的计算工具来解释这些蛋白表达模式的重要性。我们的中心假设是，来自不同近交系小鼠品系的树突状细胞对革兰氏阴性细菌的细胞膜成分的反应表现出异质性。 此外，这种异质性是由于组成Toll样受体4(TLR4)信号通路的蛋白质表达的差异。提出这项研究作为R21的基本原理是，我们希望通过建立近交系小鼠之间TLR4信号的动态差异是可测量的，并可以使用反应路径分析来解释，从而消除在R01水平上存在的潜在失败风险。为了验证这一假设，我们将追求两个具体目标：1)建立一个物种的遗传变异中存在的细胞对内毒素反应的动态差异；以及2)建立如何使用反应路径分析来解释细胞信号网络中蛋白质表达的差异模式。在第一个目标下，我们的工作假设是，表型相似的细胞，如来自两个不同近交系小鼠品系的树突状细胞，其参与TLR4信号的蛋白质表达存在差异，这赋予了对脂多糖(LPS)的不同敏感性。在第二个目标下，我们的工作假设是，可以使用计算机辅助组装反应机制的算法来创建TLR4信令网络中早期信号事件的无偏模型。这个模型可以用来解释蛋白质表达的差异如何影响细胞对内毒素的反应。这项拟议的研究具有创新性，因为它提供了一种新的方法，结合了计算系统生物学和多色流式细胞术的尖端技术，以解决了解传染病易感性的机制基础这一紧迫问题。

Understanding the basis for individual sensitivity to triggers of innate immunity is inhibited by the inability to interpret multivariate changes in quantitative signaling parameters that are related to Toll-like receptor signaling. Thus there is urgent need for multidisciplinary approaches to assess and interpret variability in Toll-like receptor signaling in terms of its impact on susceptibility to infectious agents. Our long-term goal is to improve the clinical management of infectious diseases by establishing the scientific foundation for a prognostic technology to aid in the rational design of therapeutic strategies tailored to individual patients. Thus, the proposed research is relevant to that part of NIH's mission that pertains to developing fundamental knowledge that will potentially help to reduce the burdens of human disability. The overall objective of this R21 application is to identify unique patterns of signaling proteins associated with sensitivity to infectious agents and to apply the computational tools of reaction pathway analysis to interpret the significant of these patterns of protein expression. Our central hypothesis is that dendritic cells derived from different inbred mouse strains exhibit heterogeneity in response to a cell membrane component of gram-negative bacteria. Furthermore, this heterogeneity is due to variations in expression of proteins that comprise the Toll-like receptor 4 (TLR4) signaling pathway. The rationale that underlies proposing this research as an R21 is that we expect to remove the risk of potential failure that would otherwise exist at the R01 level by establishing that dynamic differences in TLR4 signaling among inbred mouse strains is measurable and can be interpreted using reaction pathway analysis. To test this hypothesis, we will pursue two specific aims: 1) Establish that dynamic differences in cellular response to LPS exist within genetic variants of a species; and 2) Establish how reaction pathway analysis can be used to interpret differential patterns of protein expression within cellular signaling networks. Under the first aim, our working hypothesis is that cells that are phenotypically similar, as represented by dendritic cells derived from two different inbred mouse strains, exhibit variations in expression of proteins involved in TLR4 signaling that confer differential sensitivity to lipopolysaccharide (LPS). Under the second aim, our working hypothesis is that an algorithm for the computer-assisted assembly of reaction mechanisms can be used to create an unbiased model of the early signaling events in the TLR4 signaling network. This model can be used to interpret how differences in protein expression influence the cellular response to LPS. The proposed research is innovative as it provides a novel approach that combines cutting-edge techniques in computational systems biology and polychromatic flow cytometry to address the pressing issue of understanding the mechanistic basis for susceptibility to infectious disease.