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SITS-NSF-UKRI: Reverse engineering the soil microbiome: detecting, modeling, and optimizing signal impacts on microbiome metabolic functions

SITS-NSF-UKRI: Reverse engineering the soil microbiome: detecting, modeling, and optimizing signal impacts on microbiome metabolic functions
SITS-NSF-UKRI:土壤微生物组逆向工程:检测、建模和优化信号对微生物组代谢功能的影响
批准号:
1935458
负责人:
Linda Kinkel
金额:
$79.93万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-01-15 至 2024-12-31

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中文摘要
翻译
土壤中微生物之间的化学信号决定了微生物的行为,包括土壤微生物是否抑制植物病害,促进作物生长,或在特定的土壤养分上生长。然而,对介导这些行为的特定化学信号知之甚少,这限制了优化微生物活动以支持健康作物和生态系统的实际管理潜力。明尼苏达大学和英国曼彻斯特大学的这个项目的目标是开发和测试一套100个新颖的微生物记录仪,这些记录仪可以感知特定的信号,并报告微生物中100个特定基因中的每一个是否有反应。该项目将为识别土壤微生物之间的特定化学信号提供有价值的手段,这些信号可以优化有益功能或抑制有害功能。这项研究将揭示复杂的化学和代谢相互作用,这些相互作用决定了土壤微生物群对健康作物和生态系统的支持程度,并为利用微生物群发挥有益功能的新颖实用方法提供见解。这里创建的工具还将指导改进对农业和自然栖息地土壤微生物群的生态学和功能潜力的理解。美国和英国科学家之间的交流将是研究工作取得成功不可或缺的一部分,将加强两国科学家的能力和产出。该研究将为信号在调节土壤微生物生态和抑制植物病害中的作用提供基础见解。本研究为精准农业土壤微生物组的工程化功能研究奠定了基础。具体目标是:1)开发和测试遗传记录(GR)菌株,以“聆听和报告”从疾病抑制土壤中分离出来的链霉菌(Streptomyces spp.)中调节初级和次级代谢途径的土壤信号;2)模拟和测试依赖初级和次级代谢诱导的物种间相互作用如何影响多物种群落;3)发现潜在信号对链霉菌代谢的影响,利用信号优化土壤微生物功能。方法:1)利用丝氨酸整合酶介导的重组技术,建立土壤微生物基因组,检测土壤微生物中相关基因或途径的激活情况。GRs将使用下一代测序技术进行量化,并将能够在单个高通量实验中同时记录数百种代谢活动的激活。2)基因组尺度的代谢模型、转录组学和代谢组学将用于将信号与功能联系起来。现有的代谢建模平台将被扩展到包含新的功能,以了解信号如何影响单个细菌的生理和改变新兴的生态系统动力学。3)筛选潜在信号对链霉菌体外抗生素抑制和养分利用表型的直接影响,为信号发现提供平台,并与表型数据进行直接比较。该项目通过“土壤信号”机会获得,这是一项合作征集,涉及美国国家科学基金会(NSF)的ENG/CBET和BIO/IOS部门,美国农业部国家食品和农业研究所(USDA NIFA)和以下英国研究与创新(UKRI)研究委员会:1)自然环境研究委员会(NERC), 2)生物技术和生物科学研究委员会(BBSRC), 3)工程和物理科学研究委员会(EPSRC)和科学技术设施委员会(STFC)。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
Chemical signaling among microorganisms in the soil determines microbial behavior, including whether or not soil microbes suppress plant diseases, enhance crop growth, or grow on particular soil nutrients. However, little is known about the specific chemical signals that mediate these behaviors, limiting the potential for practical management to optimize microbial activities to support healthy crops and ecosystems. The objectives of this project at the University of Minnesota and the University of Manchester in the UK are to develop and test a set of 100 novel, microbial recorders that can sense specific signals and report on whether each of 100 particular genes in the microbe responds. This project will provide a valuable means of identifying specific chemical signals among soil microbes that can optimize beneficial functions or suppress detrimental functions. The research will shed light on the complex chemical and metabolic interactions that determine how well soil microbiomes can support healthy crops and ecosystems, and provide insight into novel, practical ways to harness microbiomes for beneficial functions. Tools created here will also guide improvements in understanding the ecology and functional potential of soil microbiomes in agricultural and natural habitats. Exchanges between U.S. and U.K. scientists will be integral to the success of the research effort, strengthening the capacities and output of scientists in both countries. The research will provide fundamental insights into the roles of signals in mediating the ecology of soil microbes and suppression of plant diseases. This work establishes a foundation for engineering functional soil microbiomes for precision agriculture. Specific objectives are to: 1) Develop and test genetic recorder (GR) strains to "listen and report" on signals in the soil that regulate primary and secondary metabolic pathways in Streptomyces spp. isolated from disease suppressive soils; 2) Model and test how species-species interactions that rely on primary and secondary metabolic induction impact multi-species communities; and 3) Discover effects of potential signals on Streptomyces metabolism and harness signals to optimize microbial functional capacities in soil. Methods: 1) GRs will be created to detect the activation of genes/pathways of interest in soil microbes using serine integrase-mediated recombination. The GRs will be quantified using Next-Generation Sequencing technology, and will be able to simultaneously record the activation of hundreds of metabolic activities in a single high-throughput experiment. 2) Genome-scale metabolic models, transcriptomics, and metabolomics will be used to connect signals to functions. Existing metabolic modeling platforms will be extended to incorporate novel functionality to understand how signals influence the physiology of individual bacteria and alter emergent ecosystem dynamics. 3) Potential signals will be screened for their direct effects on Streptomyces antibiotic inhibitory and nutrient use phenotypes in vitro, providing both a signal discovery platform and a direct comparison with phenotypic data. This project was awarded through the "Signals in the Soil (SitS) opportunity, a collaborative solicitation that involves the ENG/CBET and BIO/IOS divisions of the National Science Foundation (NSF), the United States Department of Agriculture National Institute of Food and Agriculture (USDA NIFA) and the following United Kingdom Research and Innovation (UKRI) research councils: 1) The Natural Environment Research Council (NERC), 2) the Biotechnology and Biological Sciences Research Council (BBSRC), 3) the Engineering and Physical Sciences Research Council (EPSRC), and the Science and Technology Facilities Council (STFC).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.
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会议论文
Workshop: Deciphering the Microbiome: Exploiting theory, cross-system analyses, and innovative analytics to propel advances in microbiome science; Dec. 8-10, 2019; Alexandria, VA
  • 批准号:
    1944020
  • 项目类别:
    Standard Grant
  • 资助金额:
    $9.9万
  • 财政年份:
    2019
  • 负责人:
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RCN: AgMicrobiomes: An Interdisciplinary Research Network to Advance Microbiome Science in Agriculture
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    1714276
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Competitive and Coevolutionary Dynamics of Antibiotic Interactions Within Streptomyces Communities in Soil
  • 批准号:
    0543213
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    Standard Grant
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    2006
  • 负责人:
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Spatial Scales of Genetic and Phenotypic Diversity Among Streptomycetes in Native Soils
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    9977907
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  • 资助金额:
    $99.0万
  • 财政年份:
    1999
  • 负责人:
    Linda Kinkel
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