System Dynamics of the Salmonella Virulence Regulatory Network

描述(由申请人提供)：本提案的中心目标是确定编码复杂分子机器的基因簇的组织和调节所依据的设计原则。作为一个模型系统，我们将研究沙门氏菌致病岛1(SPI-1)编码的III型分泌系统(T3SS)。T3SS是一台分子机器，起到了“注射器”的作用，将蛋白质注入宿主细胞。T3SS需要以正确的比例表达~18蛋白，才能正确地组装和发挥功能。关于相对表达水平、表达顺序和表达噪声的变化如何影响这一过程，人们知之甚少。我们建议通过自下而上重建SPI-1，使用生物物理模型和描述良好的遗传部分来研究SPI-1。这一过程被称为“重构”，用合成变种取代了所有的监管，并消除了未知的和特征不佳的监管。重组的SPI-1由实现基因表达动态的合成遗传电路控制。在目标1中，重构系统将被用作一个平台，以确定基因顺序和翻译耦合如何影响簇对表达水平扰动的稳健性。在目标2中，将确定不同调控计划对T3SS正确组装和功能的影响。将构建合成遗传电路，实现不同的前馈和反馈环路，数学模型预测这些环路会影响基因表达的噪音和动态。这使得能够检验假设，即控制表达的时间顺序和内在噪声对组装很重要 大分子复合体。总之，这些研究将确定许多人类病原体共有的共同毒力机制的健壮和脆弱方面。

DESCRIPTION (provided by applicant): The central objective of this proposal is to identify the design principles by which gene clusters encoding complex molecular machines are organized and regulated. As a model system, we will study the type III secretion system (T3SS) encoded in Salmonella Pathogenicity Island 1 (SPI-1). The T3SS is a molecular machine that acts a "syringe" to inject proteins into host cells. The T3SS requires the expression of ~18 proteins at the correct ratios to properly assemble and function. Little is known as to how changes in the relative expression levels, the order of expression, and expression noise impact this process. We propose to study SPI-1 by rebuilding it from the bottom-up, using biophysical models and well-characterized genetic parts. This process, known as "refactoring," replaces all of the regulation with synthetic variants and eliminates unknown and poorly characterized regulation. The refactored SPI-1 is controlled by synthetic genetic circuits that implement the dynamics of gene expression. In Aim 1, the refactored system will be used as a platform to determine how gene order and translational coupling impact the robustness of the cluster to perturbations in expression levels. In Aim 2, the impact of different regulatory programs on the proper assembly and function of the T3SS will be determined. Synthetic genetic circuits will be constructed that implement different feed forward and feedback loops that are predicted by mathematical models to affect the noise and dynamics of gene expression. This enables the testing of hypotheses that controlling the temporal order and intrinsic noise of expression is important for the assembly of macromolecular complexes. Together, these studies will identify robust and fragile aspects of common virulence mechanism shared by many human pathogens.