Collaborative research: Information integration by gene regulatory networks controlling bacterial cell fate decisions

合作研究：通过控制细菌细胞命运决定的基因调控网络进行信息整合

• 批准号: 1616761
• 负责人: Masaya Fujita
• 金额: $ 66.49万
• 依托单位: University of Houston
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1616761&HistoricalAwards=false
• 关键词: Collaborative; research; Information; integration; gene

Bacterial biofilms, which are surface associated aggregates of cells, are highly resistant to toxic chemicals such as chlorine and to many antibiotics that are used to treat human infections. This project aims to understand how cells decide to form a biofilm by analyzing a gene regulatory network that is crucial for the decision-making process. The mechanisms underlying these decision-making processes are not fully understood, even for the best-studied gene regulatory networks. Using the biofilm-forming bacterium Bacillus subtilis as a model, this research will define general principles underlying decision making by regulatory networks. B. subtilis is closely related to and shares many regulatory networks with medically important pathogenic bacteria, including Clostridium sp., B. cereus, and B. anthracis. Hence, this work may serve as a model for understanding how such bacteria decide to initiate biofilm formation. This project will provide students with interdisciplinary training in microbiology and mathematical modeling. A special emphasis will be placed on engaging underrepresented students from the University of Houston, which has been designated as a Hispanic-Serving Institution. This proposal aims to obtain a systems-level understanding of how B. subtilis cells sense starvation and make the decision to initiate either a unicellular (sporulation) or a multicellular (biofilm) differentiation program for survival. The proposal will test whether gene-regulatory networks are able to assess nutrient availability by sensing the cell growth rate. Further, it will investigate how different dynamics (i.e. modulation of activity in time) of a single master transcriptional regulator can direct cells to alternative cell fates. These questions will be addressed with a synergistic combination of systems and synthetic biology tools, including synthetic network perturbations and rewiring, single-cell imaging, statistical data analysis, and mathematical modeling. Thus, this project will illustrate various fundamental concepts of complex (but not too complex) living systems. The project will also provide abundant interdisciplinary training opportunities for the participating students and postdocs working together on experiments and/or mathematical modeling.

细菌生物膜是表面相关的细胞聚集体，对有毒化学物质如氯和用于治疗人类感染的许多抗生素具有高度抗性。 该项目旨在通过分析对决策过程至关重要的基因调控网络来了解细胞如何决定形成生物膜。即使对于研究最深入的基因调控网络，这些决策过程的机制也尚未完全了解。本研究将以生物膜形成菌枯草芽孢杆菌为模型，通过调控网络确定决策的一般原则。B。枯草杆菌与医学上重要的病原菌密切相关，并共享许多监管网络，包括梭菌属，B。cereus和B.炭疽病因此，这项工作可以作为一个模型，了解这些细菌如何决定启动生物膜形成。 该项目将为学生提供微生物学和数学建模的跨学科培训。 一个特别的重点将放在从事休斯顿大学，这已被指定为西班牙裔服务机构代表性不足的学生。 此建议旨在从系统层面了解B。枯草杆菌细胞感觉到饥饿，并决定启动单细胞（孢子形成）或多细胞（生物膜）分化程序以存活。该提案将测试基因调控网络是否能够通过感知细胞生长速率来评估营养物质的可用性。此外，它将研究如何不同的动力学（即调制活动的时间）的一个单一的主转录调节可以直接细胞的替代细胞的命运。这些问题将通过系统和合成生物学工具的协同组合来解决，包括合成网络扰动和重新布线，单细胞成像，统计数据分析和数学建模。因此，这个项目将说明复杂（但不太复杂）生命系统的各种基本概念。该项目还将为参与实验和/或数学建模的学生和博士后提供丰富的跨学科培训机会。