ABI Innovation: A framework to predictably manipulate a microbial gene regulatory program

生物体必须适应环境的变化，以优化资源利用，尽量减少压力并保持稳定。该提案旨在揭示指导生物体如何调整其生理反应以适应环境变化的基本原则。 理解为什么某些反应发生需要一个精确的图谱，显示哪些基因在给定的反应中受到调节，以及它们是如何协调的。 利用之前NSF ABI的支持，系统生物学研究所的Baliga实验室开发了一种方法，可以为任何微生物物种创建精确的基因调控图谱。使用这种方法，他们绘制了一组重要生物体的基因调控，包括铀还原脱硫弧菌，脂质积累的莱茵衣藻，酵母，硅藻和结核分枝杆菌。下一个目标是看看地图作为工具在操纵复杂行为时预测结果的效果如何。有效的工具对生物技术、农业和医学具有广泛的影响。最初，将开发新的算法和软件，以进一步完善基因调控图谱，并确定环境变化期间影响基因调控的因素。重点将是了解生物体如何打开或关闭特定的行为，以响应环境线索。这项工作将在两种生物体中进行-E。大肠杆菌，一个众所周知的，广泛研究的细菌，和盐生盐杆菌，一种极端微生物，在高盐环境中茁壮成长;它将很容易适用于所有测序的微生物，是显着的工业，农业和医疗重要性。该项目的一部分是开发和传播新的高中课程，介绍计算建模在解决粮食短缺和气候变化等真实的世界问题中的重要性。来自不同背景的学生和教师，包括目前在科学，技术，工程和数学（STEM）方面代表性不足的学生和教师，将在学习这门跨学科科学时接受培训和持续支持。该课程和培训是一个名为系统教育体验（SEE）的计划的一部分，该计划每月覆盖数千名学生和教师。SEE致力于培养能够解决问题的系统思考者，为STEM素养的公民做出贡献，并帮助建立更多样化的STEM专业人员群体。该项目的主要目标是开发一个框架，以阐明和可预测地操纵任何微生物的基因调控程序。在之前ABI资助的研究中，Baliga实验室开发了一种系统方法，直接从转录组图谱的概要中对环境和基因调控影响网络v2.0（EGRIN 2.0）模型进行逆向工程。EGRIN 2.0模型以前所未有的核苷酸水平分辨率阐明了所有基因的环境特异性转录调控机制，包括典型启动子位置，甚至编码序列和操纵子内部。在这里，将开发一种方法来阐明EGRIN 2.0内的转录因子相互作用，并表征这些相互作用的拓扑结构（即，"网络基序"）产生全基因组范围的、时间上协调的转录应答。这些研究将在理解两种遗传学上遥远的生物体-大肠杆菌（一种细菌）和盐杆菌（一种古细菌）-如何使用不同的调节剂来介导从有氧生长到厌氧静止的生理学上不同但表型相似的转变的背景下进行。首先，将开发一种方法来精确地映射转录因子的条件结合到基因组中所有基因的启动子内的序列元件（EGRIN 3.0）。接下来，EGRIN 3.0将用于识别、表征和操纵转录因子相互作用的拓扑结构（即，网络基序）以可预测地改变H中的氧（O2）响应状态转变。salinarum和E.杆菌除了开发一个通用的框架来操纵任何生物体中的微生物基因调控程序外，这些活动还将测试这样一个假设，即类似的环境强迫驱动了遗传学上遥远的生物体中拓扑相似的网络基序的趋同进化。这个跨学科小组使用的高层次思维和过程将以高中教师和学生真实案例研究的形式转化为课程和培训经验。目标之一将是让学生使用实验和建模，以更好地了解环境参数（如氧气，硝酸盐，pH值，光等）的影响。生产力和粮食系统的稳定性，如鱼菜共生系统。学生，教师和STEM专业人员将共同努力，通过修改后的Dick和Carey教学设计模型迭代开发和测试课程和经验。所有课程都将与公布的国家教育标准相结合。所有需要的技术，软件，课程计划和学习辅助工具将通过多个在线资源，资源中心，面对面和在线培训提供给教师和学生。有关该项目及其产品的更多信息，请访问Baliga实验室的网站www.example.com和www.example.com。

Living organisms have to adjust to changes in their environment in order to optimize their use of resources, minimize stress and maintain stability. This proposal aims to uncover the basic principles that direct how organisms tailor their physiological responses to environmental changes. Understanding why certain responses occur requires a precise map showing which genes are regulated in a given response and how they are coordinated. Using prior NSF ABI support, the Baliga Laboratory at the Institute for Systems Biology developed an approach to create precise maps of gene regulation for any microbial species. Using this approach, they mapped gene regulation in a set of important organisms including uranium-reducing Desulfovibrio vulgaris, lipid-accumulating Chlamydomonas reinhardtii, yeast, diatoms, and Mycobacterium tuberculosis. The next goal is to see how well the maps work as tools to predict the results when manipulating complex behaviors. Effective tools have wide-ranging implications for biotechnology, agriculture and medicine. Initially, new algorithms and software will be developed to further refine the gene regulation maps and identify factors affecting gene regulation during environmental changes. The focus will be understanding how organisms switch on or off specific behaviors in response to environmental cues. The work will be performed in two organisms - E. coli, a well-known, widely studied bacterium, and Halobacterium salinarum, an extremophile that thrives in high salt environments; it will be readily applicable to all sequenced microorganisms that are of significant industrial, agricultural, and medical importance. Part of the project is to develop and disseminate new high school curriculum to introduce the importance of computational modeling in solving real world problems such as food scarcity and climate change. Diverse populations of students and teachers from a variety of backgrounds, including those currently underrepresented in science, technology, engineering and math (STEM), will receive training and sustained support as they learn this interdisciplinary science. This curriculum and training is part of a program called Systems Education Experiences (SEE) that reaches thousands of students and teachers each month. SEE works toward cultivating systems thinkers who can tackle problems, contribute to a STEM-literate citizenry, and help build a more diverse population of STEM professionals.The primary objective of this project is to develop a framework to elucidate and predictably manipulate the gene regulatory program of any microbe. In previous ABI-funded research, the Baliga lab developed a systems approach to reverse engineer the environment and gene regulatory influence network v2.0 (EGRIN 2.0) model directly from a compendium of transcriptome profiles. The EGRIN 2.0 model elucidates mechanisms for environment-specific transcriptional regulation of all genes with unprecedented nucleotide-level resolution, at canonical promoter locations and even within coding sequences and inside operons. Here, an approach will be developed to elucidate transcription factor interactions within EGRIN 2.0 and characterize how the topology of these interactions (i.e., 'network motifs') generates genome-wide, temporally coordinated transcriptional responses. These studies will be performed in the context of understanding how two phylogenetically distant organisms --Escherichia coli (a bacterium) and Halobacterium salinarum (an archaeaon)-- use distinct regulators to mediate physiologically different yet phenotypically similar transitions from aerobic growth to anaerobic quiescence. First, an approach will be developed to precisely map conditional binding of transcription factors to sequence elements within promoters of all genes in the genome (EGRIN 3.0). Next, EGRIN 3.0 will be used to identify, characterize, and manipulate topologies of transcription factor interactions (i.e., network motifs) to predictably alter oxygen (O2)-responsive state transitions in H. salinarum and E. coli. In addition to developing a generalized framework for manipulating a microbial gene regulatory program within any organism, the activities will test the hypothesis that similar environmental forcing drives convergent evolution of topologically similar network motifs in phylogenetically distant organisms. The high-level thinking and process used by this interdisciplinary group will be translated into curriculum and training experiences in the form of real-word cases studies for high school teachers and students. One of the goals will be for students to use experimentation and modeling to better understand the influence of environmental parameters (such as oxygen, nitrates, pH, light, etc.) on productivity and stability of food systems, such as aquaponic systems. Students, teachers, and STEM professionals will work together to iteratively develop and test curriculum and experiences through a modified Dick and Carey Instructional Design model. All curricula will be integrated with published national education standards. All needed technology, software, lesson plans and learning aides will be provided to teachers and students through multiple online sources, resource centers, and in-person and online trainings. For further information about this project and its products, visit the Baliga Laboratory's website at http://baliga.systemsbiology.net and http://see.systemsbiology.net.