Knowledge Resource Center for Ecological Environment in Arid Area
| 项目编号 | 1936024 |
| Causes and consequences of regulatory network rewiring under extreme environmental selection | |
| Amy Schmid | |
| 主持机构 | Duke University |
| 开始日期 | 2019-09-01 |
| 结束日期 | 2023-08-31 |
| 资助经费 | 900000(USD) |
| 项目类别 | Standard Grant |
| 资助机构 | US-NSF（美国国家科学基金会） |
| 项目所属计划 | Systems and Synthetic Biology |
| 语种 | 英语 |
| 国家 | 美国 |
| 英文简介 | This project seeks to understand how gene circuits evolve under extreme conditions. Microorganisms that live in extreme environments, called extremophiles, are remarkable examples of life's resilience, thriving in hot springs at boiling temperatures, in brine lakes saturated with salt, and in deserts once thought to be sterile. This research uses halophiles, extremophiles that live in high salt, as a test system to map complex gene circuits that enable survival. Circuit maps are compared across halophile species resistant to different levels of salt and stress to understand how extreme conditions rewire gene circuits, and how rewiring enables adaptation in the face of stress. The high salt extremophiles of interest are members of the domain of life Archaea. Because the molecules that make up gene circuits in archaea resemble those of other domains of life, this research has the potential to reveal general principles of gene circuit evolution across the tree of life. The education plan involves collaborating with students to build solutions for analysis and visualization of archaeal data. The PI and her group mentor undergraduates through the summer Duke Data+ program to create interactive web-accessible tools for data analysis and visualization. Teams of Duke students contribute directly to the research by developing these tools. The resultant graphical user interface (GUI) serve as an entry point for experimental biologists into computational biology in archaea, reducing the barrier for otherwise intimidating genome-scale analyses. Duke Masters in Data Science (MIDS) students and graduate students from the PI's lab co-mentor the Data+ team and provide support for these tools throughout the academic year. This vertically integrated mentorship structure provides critical training in research mentorship, team project management, and communication skills. The team-based learning approach encourages recruitment and retention of underrepresented groups in STEM. The overarching goal of this project is to understand how extreme environments select for regulatory network architecture and function. Transcription regulatory networks (TRNs) vary gene expression dynamically in response to stress. Such expression adapts physiology to improve fitness in the short term and leads to phenotypic diversity over evolutionary time scales. However, the selective forces causing such rewiring of gene circuits, and whether such rewiring is adaptive, remain unclear. In recent work on halophiles, hypersaline-adapted representatives of the archaeal domain of life, the PI discovered archaeal TRNs that regulate critical cellular decisions such as nutrient use and damage repair. Halophiles provide a unique model for investigating the evolution of TRNs given their experimental tractability in the lab and adaptability during continual exposure to multiple extreme conditions in the natural environment. Previous research compared the architecture and dynamic function of TRNs across related species of halophiles. More recent research has led to the hypothesis that extreme conditions select for more highly interconnected TRNs, enabling rapid physiological adjustment in response to variable environments. To test this hypothesis, the research: (a) uses an integrated experimental and computational systems biology approach pioneered in the PI's lab to map and compare small-scale TRNs across four species of halophiles; (b) jointly infers global TRNs across species using multi-task machine learning to ctract-Sompare genome-scale networks; and (c) forces TRN rewiring with in-lab evolution experiments. This approach combines genetics, genomics, quantitative phenotyping, and statistical modeling, yielding rapid and unprecedented insight into the dynamic function of archaeal regulatory networks and their impact on cell physiology. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. |
| 来源学科分类 | Biological Sciences |
| URL | https://www.nsf.gov/awardsearch/showAward?AWD_ID=1936024 |
| 资源类型 | 项目 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/341676 |
| 推荐引用方式 GB/T 7714 | Amy Schmid.Causes and consequences of regulatory network rewiring under extreme environmental selection.2019. |
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