Schultz - Proj 5

项目总结 我们对抗生素耐药性的传统理解几乎完全基于细菌的概念 在稳定的药物条件下，人口保持增长的能力。然而，它正变得越来越多 显然，药物治疗的结果取决于需要复杂的高度动态反应 监管。尽管关于管理不同人的行为的监管电路的知识越来越多 抗生素耐药机制的分类，对这些体系结构如何演变的定量理解 而在不同的环境下进行多样化的优化表达还很欠缺。全面了解 基因调控的设计原理对于解释控制机制如何缓解 抗生素耐药性的成本，并允许在整个细菌种群中固定。最近的这一发现 课题组研究表明，四环素抗药性、tet、操纵子在大肠杆菌中突然暴露时 四环素通过快速表达外排泵阻遏蛋白(TetR)来优化基因表达。 此外，基因表达动态的变化揭示了单细胞水平上细胞命运的多样性。 认识到细胞反应的时间相关成分对 有机体的适合度，这项研究的目的是研究进化优化的过程 在应对需要快速采取行动的环境压力时，抗生素的反应(“动态功效”)。 聚焦于tet操纵子，这个项目将测试抗病基因调控的概念 机制针对基因表达的动态进行了优化。通过以下具体目标，这 这项研究将结合生物信息学、数学建模和实验方法来确定 各种优化的监管架构应运而生，以响应给定的环境约束，并 解释如何使基因调控多样化，以应对生态挑战。建议的目标是： 目的1.探索自然回路中抗生素反应的动力学：设计、最优化和 可变性。这个目标将分析全基因组数据库，以调查自然变异将 确定有效抵抗的关键监管战略。 目标2.开发针对特定动态机制进行优化的合成电路。以此为目标的工作将 开发抗生素耐药性的定量模型，以设计和实施最优的监管架构 并研究自然界中发现的基因调节针对特定环境进行优化的假设。 目的3.在不同的药物方案中进行耐药机制的实验进化。这 AIM将在不同的动态环境下实验进化出一种抗性机制，以探索基因如何 为了应对新的环境挑战，监管发生了变化。 对基因调控变化如何定义细胞过程动力学的理解将 直接为新的抗菌疗法的开发提供信息，并解释监管不当可能是 人类疾病的起因，如癌症。 好了！

PROJECT SUMMARY Our conventional understanding of antibiotic resistance is based almost entirely on the notion of a bacterial population’s ability to maintain growth under steady-state drug conditions. Yet, it is becoming increasingly apparent that the outcome of drug treatment depends on highly-dynamic responses that require complex regulation. Despite a growing body of knowledge on the regulatory circuits governing the behavior of different classes of antibiotic-resistance mechanisms, a quantitative understanding of how these architectures evolved and diversified to optimize expression in different environments is still lacking. A comprehensive understanding of the design principles of gene regulation is essential to explain how control mechanisms can mitigate the costs of antibiotic resistance and allow fixation throughout bacterial populations. Recent findings from this research group show that the tetracycline resistance, tet, operon in E. coli, when suddenly exposed to tetracycline, optimizes gene expression by rapidly expressing the repressor (TetR) of the efflux pump (TetA). Moreover, variations in the dynamics of gene expression reveal a diversity of cell fates at the single-cell level. Recognizing that the time-dependent component of cell responses makes an important contribution to the fitness of an organism, the goal of this study is to investigate the process by which evolution optimizes antibiotic responses when addressing environmental pressures that require fast action (“dynamical efficacy”). Focusing on the tet operon, this project will test the concept that gene regulation of a resistance mechanism is optimized for the dynamics of gene expression. Through the following specific aims, this study will combine bioinformatics, mathematical modeling, and experimental approaches to determine what kinds of optimized regulatory architectures emerge in response to given environmental constrains, and to explain how gene regulation can be diversified in response to ecological challenges. The proposed aims are: Aim 1. Explore the dynamics of antibiotic response in natural circuits: design, optimality, and variability. This aim will analyze whole-genome databases to investigate the idea that natural variation will identify key regulatory strategies for effective resistance. Aim 2. Develop synthetic circuits optimized for specific dynamical regimes. Work in this aim will develop quantitative models of antibiotic resistance to design and implement optimal regulatory architectures and investigate the hypothesis that gene regulation found in nature is optimized to specific environments. Aim 3. Perform experimental evolution of resistance mechanisms in different drug regimes. This aim will experimentally evolve a resistance mechanism under different dynamical settings to explore how gene regulation changes in response to new environmental challenges. The understanding of how changes in gene regulation define the dynamics of cellular processes will directly inform the development of new antimicrobial therapies and explain how misregulation may be the cause of human disease, such as cancer. !