Collaborative Research: Information Processing by Gene Regulatory Network Controlling Bacterial Sporulation

合作研究：控制细菌孢子形成的基因调控网络的信息处理

• 批准号: 1244135
• 负责人: Oleg Igoshin
• 金额: $ 26.15万
• 依托单位: William Marsh Rice University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-02-01 至 2017-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1244135&HistoricalAwards=false
• 关键词: Collaborative; Research; Information; Processing; Gene

Collaborative research: Information processing by gene regulatory network controlling bacterial sporulation Intellectual Merit: The ability of an organism to change its phenotype in response to various environmental cues is of fundamental biological importance, but the detailed mechanisms are not fully understood even for the best studied systems. The soil bacterium Bacillus subtilis detects currently unidentified starvation cues and processes this information via its gene regulatory networks, resulting in formation of a spore. Using this simple unicellular organism as a model, the long-term goal of this research is to discover general principles underlying the information processing by gene regulatory networks. Specifically, this project will uncover how B. subtilis processes information under conditions of environmental uncertainty and makes appropriate cell-fate decisions at the systems level. The cornerstone of the approach is a combination of in vivo and in vitro experiments as well as deterministic (population-average) and stochastic (single-cell) mathematical models. The key to success is the construction of synthetic strains which perturb various processes in the networks and the comparison of their responses to one another and to those in the wild-type strain. The experimental results will be analyzed using integrative mathematical models. The interdisciplinary nature of this research will uncover how signal-response characteristics and cell-fate decisions of the network are affected by its architecture. Broader Impacts: As a model system, B. subtilis offers significant experimental advantages including powerful genetic tools, large collections of mutant strains, and a fully sequenced genome. Unraveling the mechanisms of information processing by the sporulation network is a key step towards understanding the molecular basis of cell-fate decision at the unicellular level. Thus, the innovative approaches in this project may be applicable for addressing similar problems in other organisms and can be used for teaching system-level concepts to students of various levels and backgrounds. In particular, the resulting collection of synthetic strains can be used for educational purposes in the undergraduate laboratory setting because their networks are easy to perturb by varying the inducer levels. As a result, students will gain an understanding of the relationship between network architecture and system level properties. In addition, mathematical models can be used as a cornerstone for systems biology curriculum. The project will also provide abundant interdisciplinary training opportunities for the participating students from various backgrounds working together on experimental and/or mathematical modeling.

合作研究：基因调控网络控制细菌孢子形成的信息处理智力优势：生物体响应各种环境线索改变其表型的能力具有基本的生物学重要性，但即使是最好的研究系统也没有完全了解详细的机制。土壤细菌枯草芽孢杆菌检测到目前未知的饥饿线索，并通过其基因调控网络处理这些信息，从而形成孢子。使用这个简单的单细胞生物作为模型，本研究的长期目标是发现基因调控网络信息处理的一般原则。具体来说，这个项目将揭示如何B。subtilis在环境不确定性的条件下处理信息，并在系统水平上做出适当的细胞命运决定。该方法的基石是体内和体外实验以及确定性（群体平均）和随机（单细胞）数学模型的组合。成功的关键是构建干扰网络中各种过程的合成菌株，并比较它们彼此之间的反应以及与野生型菌株的反应。实验结果将使用综合数学模型进行分析。这项研究的跨学科性质将揭示网络的信号响应特征和细胞命运决定如何受到其架构的影响。更广泛的影响：作为一个模型系统，B。枯草芽孢杆菌提供了显著的实验优势，包括强大的遗传工具，大量的突变菌株和完全测序的基因组。解开孢子形成网络的信息处理机制是理解单细胞水平细胞命运决定的分子基础的关键一步。因此，本项目中的创新方法可能适用于解决其他生物体中的类似问题，并可用于向不同层次和背景的学生教授系统级概念。特别是，合成菌株的所得集合可用于本科实验室设置中的教育目的，因为它们的网络容易通过改变诱导剂水平而受到干扰。因此，学生将获得网络架构和系统级属性之间的关系的理解。此外，数学模型可以作为系统生物学课程的基石。该项目还将为来自不同背景的参与学生提供丰富的跨学科培训机会，共同进行实验和/或数学建模。