Feedback regulation and transcirptional coupling in bacterial stress-response

描述（由申请人提供）：活细胞的一个关键特性是它们对内部或外部刺激产生特定生化反应的能力。细菌已经进化到通过基因表达的变化来感知和快速适应环境刺激。调控这些反应的应激反应网络的分子细节已经在许多模式细菌中被发现。然而，我们仍然缺乏跨物种的这些反应的网络级知识，这对于更深入地了解细胞功能和最好地将模型细菌获得的结果应用于特征不佳或无法在实验室培养的致病菌物种是必要的。在本应用中，我们将重点关注细菌应激反应网络的两个常见基本构建块：双组分系统和替代西格玛因子网络。结合理论、计算和实验方法，我们的多学科团队将探索网络组织的两个重要方面-转录自调节引起的反馈回路和同一操纵子中网络基因的共转录。具体目的是：（SA1）了解单个操纵子的细菌基因共表达与相应网络信息处理随机性之间的关系；（SA2）评估反馈调节在备选西格玛因子和双组分系统网络中的作用。对于每个特定目标，研究计划将包括三个基本组成部分：(1)制定和分析生物物理上现实但分析上易于处理的压力反应网络主调节模块模型，(2)模拟和分析模式生物中特定网络的详细模型，以及(3)对耻垢分枝杆菌的预测进行实验测试。这将导致理论/模型和实验之间的迭代和协同反馈。这项工作的结果有望揭示新的进化设计原则，描述跨细菌物种的网络结构和动态性能之间的关系，这对于操纵自然发生的网络和设计合成基因电路至关重要。

DESCRIPTION (provided by applicant): A key property of living cells is their ability to react to internal or external stimuli with specific biochemical responses. Bacteria have evolved to sense and rapidly adapt to environmental stimuli by changes in gene expression. Molecular details of the stress response networks regulating these responses have been uncovered for many model bacteria. However, we still lack network-level knowledge of these responses across species, which is necessary to obtain a deeper understanding of cellular functions and to best apply results obtained with model bacteria to pathogenic bacterial species that are poorly characterized or cannot be cultured in a laboratory. In this application we focus on two of the common basic building blocks of bacterial stress-response networks: two-component systems and alternative sigma-factor networks. Combining theoretical, computational and experimental approaches, our multi-disciplinary team will explore two important aspects of network organization - feedback loops due to transcriptional autoregulation and co-transcription of network genes in the same operon. The Specific Aims are (SA1) To understand the relationship between co-expression of bacterial genes from a single operon and stochasticity in information processing of the corresponding networks and (SA2) To assess the role of feedback regulation in alternative sigma factor and two-component system networks. For each Specific Aim the research plan will involve three essential components: (1) formulation and analysis of biophysically realistic but analytically tractable models of master-regulation modules of stress-response networks, (2) simulations and analysis of detailed models of particular networks in the model organism Mycobacterium smegmatis, and (3) experimental tests of predictions in M. smegmatis. This will lead to iterative and synergistic feedback between theories/models and experiments. The results of the proposed work are expected to reveal novel evolutionary design principles characterizing relationships between network architecture and dynamical performance across bacterial species, which are essential for the manipulation of naturally occurring networks and for designing synthetic gene circuits.