Understanding Gene Regulatory Networks in Hypersaline-adapted Archaea: Toward Synthetic Biology for Industrial Applications

了解适应高盐的古细菌中的基因调控网络：面向工业应用的合成生物学

• 批准号: 1417750
• 负责人: Amy Schmid
• 金额: $ 70万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-01 至 2018-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1417750&HistoricalAwards=false
• 关键词: Understanding; Gene; Regulatory; Networks; Hypersaline

The project seeks to understand how gene circuits function and evolve in microorganisms living under extreme conditions. This knowledge will be used to enable the construction of synthetic prototype strains that efficiently produce biodegradable plastic from inexpensive feedstock. Synthetic biology has yet to explore the use of archaeal genetic circuitry and metabolic pathways despite their potential value for applications in industrial chemical and biofuel production. Archaea are single-celled microbes that thrive at the limits of life, found in deep-sea hydrothermal vents under high pressure and temperature, saturated salt lakes, and polar icecaps. Survival in these environments requires unique genetic and metabolic strategies, the natural chemical byproducts of which are attractive to industry (biofuels, biodegradable plastics). Strategies that engineer archaeal gene circuits or swap these circuits between archaeal strains to boost chemical production are attractive for biomanufacturing of fuels and chemicals. The NSF funded research will also contribute to education, training, and outreach at the high school and undergraduate levels. Specifically, the PI will collaborate with teachers to continue offering weeklong science immersion courses for high school students from North Carolina School of Science and Math. This public high school in Durham, NC, draws the top students from each congressional district in the state, providing even representation across cultural and socioeconomic backgrounds. The PI's ongoing "Introduction to Systems Biology" will engage biology and engineering undergraduates in collaborative active learning projects to build and analyze gene networks from data generated through the research. Several interested students from the class, together with HBCU summer students recruited through established Duke programs, will engage in research projects in the PI's lab. Through these activities, high school and undergraduate students will contribute directly to generating and analyzing research data. This work will engage students in research earlier in their careers and retain them in STEM fields. These activities are expected to have lasting effects on the recruitment and retention of researchers, especially from underrepresented groups.TECHNICAL DESCRIPTION: Synthetic biology has yet to explore the use of archaeal transcriptional systems and metabolic pathways despite their potential value for applications in industry and biofuel production. The hypersaline-adapted group of archaeal microbes, hereafter referred to as halophiles, hold significant promise because they naturally produce chemicals attractive to industry (isoprenoid lipids for fuels, polyhydroxyalkanoate for biodegradable plastics). Strategies that engineer halophile gene regulatory networks (GRNs) or swap gene circuits between halophile strains are attractive for biofuel or other industrial applications. However, before halophile networks can be customized and controlled, additional basic understanding of GRNs and transcription factor (TF) function is required. This plan has three objectives: (1) Characterize the topology, dynamics, and phenotypic output of small-scale GRN motifs that regulate stress and metabolic responses in halophiles. GRN motifs known to regulate important metabolic pathways and extreme stress resistance across four related halophile species using time course gene expression and TF-DNA binding measurements. (2) Build predictive genome-scale statistical models for each halophile to quantify and compare GRN motif architecture and dynamics. Data generated from objective 1 will be integrated into predictive models at two levels of detail: small-scale dynamical models and genome-scale gene regulatory interaction network models. Models will be compared across organisms. (3) Test model predictions in proof-of-principle synthetic biology experiments. Model tests will include three stages of molecular biology experiments: promoter-reporter fusions to test predictions regarding TF-cis-regulatory sequence interactions, high-resolution time course gene expression experiments, and building prototype synthetic biology circuits for increasing production of polyhydroxyalkanoate in halophiles. The products of this research will include predictive GRN models for four related species and prototype synthetic circuits. These gene circuits will test model predictions and increase the production of biodegradable plastic in halophiles. In the long term, the PI aims to exploit halophile GRNs to extend options for biotechnology and bioenergy.

该项目旨在了解基因回路如何在极端条件下的微生物中发挥作用和进化。这些知识将用于合成原型菌株的构建，从而有效地从廉价的原料中生产可生物降解的塑料。合成生物学尚未探索古细菌遗传电路和代谢途径的使用，尽管它们在工业化学和生物燃料生产中的应用具有潜在价值。古生菌是一种单细胞微生物，在生命极限条件下茁壮成长，存在于高压高温的深海热液喷口、饱和盐湖和极地冰盖中。在这些环境中生存需要独特的遗传和代谢策略，其天然化学副产品对工业（生物燃料，可生物降解塑料）具有吸引力。设计古细菌基因回路或在古细菌菌株之间交换这些回路以促进化学品生产的策略对燃料和化学品的生物制造具有吸引力。美国国家科学基金会资助的研究也将有助于高中和本科水平的教育、培训和推广。具体而言，PI将与教师合作，继续为北卡罗来纳州科学与数学学院的高中生提供为期一周的科学浸入式课程。这所位于北卡罗来纳州达勒姆的公立高中吸引了该州每个国会选区的优秀学生，在文化和社会经济背景方面提供了均匀的代表性。PI正在进行的“系统生物学导论”将让生物学和工程学本科生参与合作主动学习项目，从研究产生的数据中构建和分析基因网络。几名对该课程感兴趣的学生，以及通过杜克大学已建立的项目招募的HBCU暑期学生，将在PI的实验室参与研究项目。通过这些活动，高中生和本科生将直接参与生成和分析研究数据。这项工作将使学生在职业生涯的早期参与研究，并将他们留在STEM领域。预计这些活动将对征聘和留住研究人员，特别是来自代表性不足群体的研究人员产生持久影响。技术描述：合成生物学尚未探索古细菌转录系统和代谢途径的使用，尽管它们在工业和生物燃料生产中的应用具有潜在价值。适应高盐环境的古菌微生物，以下简称为嗜盐菌，具有重要的前景，因为它们自然产生对工业有吸引力的化学物质（用于燃料的类异戊二烯脂，用于生物降解塑料的聚羟基烷酸酯）。设计嗜盐基因调控网络（GRNs）或在嗜盐菌株之间交换基因电路的策略对生物燃料或其他工业应用具有吸引力。然而，在定制和控制亲盐网络之前，需要对grn和转录因子（TF）功能有更多的基本了解。该计划有三个目标：(1)表征在嗜盐菌中调节应激和代谢反应的小尺度GRN基序的拓扑结构、动力学和表型输出。通过时间过程基因表达和TF-DNA结合测量，已知GRN基序调节四种相关的嗜盐菌物种的重要代谢途径和极端抗逆性。(2)为每种嗜盐菌建立预测基因组规模的统计模型，量化和比较GRN基序结构和动态。从目标1中产生的数据将在两个细节层面上集成到预测模型中：小规模动态模型和基因组尺度的基因调控相互作用网络模型。模型将在生物体之间进行比较。(3)在原理证明合成生物学实验中测试模型预测。模型试验将包括分子生物学实验的三个阶段：启动子-报告子融合以测试关于tf顺式调控序列相互作用的预测，高分辨率时间过程基因表达实验，以及构建原型合成生物学电路以增加嗜盐菌中聚羟基烷酸盐的产量。本研究的成果将包括四种相关物种的预测GRN模型和原型合成电路。这些基因回路将测试模型预测，并增加嗜盐菌中可生物降解塑料的产量。从长远来看，PI的目标是开发亲盐grn，以扩大生物技术和生物能源的选择。