IntBIO Collaborative Research: Assessing drivers of the nitrogen-fixing symbiosis at continental scales

IntBIO 合作研究：评估大陆尺度固氮共生的驱动因素

• 批准号: 2316269
• 负责人: Claudia Solis-Lemus
• 金额: $ 23.92万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2027-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2316269&HistoricalAwards=false
• 关键词: IntBIO; Collaborative; Research; Assessing; drivers

Nitrogen is an essential nutrient for all life on earth. It is also the most abundant element in the atmosphere, but most organisms cannot access it from the air directly. Only certain specialized microbes have the ability to convert nitrogen in the atmosphere into a biologically useful form in a process known as nitrogen fixation. Some of these microbes are free-living, but most live in a close symbiotic association within the roots of plants, exchanging nitrogen for carbon. This nitrogen-fixing symbiosis is a central component of the global nitrogen cycle, and it is central to agricultural systems because nitrogen is often the limiting factor for crop growth. It is therefore imperative to understand how nitrogen-fixing plant-bacterial partnerships form in nature and how they respond to an environment filled with challenges and in constant flux. The purpose of this project is to provide a data-intensive framework to learn how plants and bacteria choose their partners and how this choice influences and responds to surrounding species, soil, and climate. A second purpose of the project is to train students from groups underrepresented in science. Students will be prepared for the data-intensive careers now needed across STEM disciplines using an innovative mentorship program and interdisciplinary research including fieldwork, laboratory work, and computational biology.The project will investigate the diversity of nitrogen-fixing bacteria and other microbes associating with plant roots across the North American continent using NSF-sponsored ecological monitoring resources through NEON (the National Ecological Observatory Network). At each of 45 NEON sites, environmental data will be combined with data on the nitrogen-fixing symbiosis. Specifically, investigators will sample the microbiome in the soil and root nodules, and will assay leaf isotopes to determine the level of function of nitrogen-fixing symbionts. Leveraging data from these different sources, the PIs will be able to determine whether microorganisms and plant partners are each limited by the same environmental factors, such as aridity. They will also be able to determine the extent to which choosiness of plant or microbe partners limit the extent of the association. In addition, by examining patterns in the tree of life, the PIs will be able to infer whether highly specific partnerships have persisted across evolutionary time. Finally, models will be used to address synthetic questions across all data sources. For example, a model can test the prediction that arid environments favor highly specific associations, in which both microbes and plants choose specific partners in those stressful settings.This project is jointly funded by the BIO Emerging Frontiers Program and the Established Program to Stimulate Competitive Research (EPSCoR).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.

氮是地球上所有生命的必需营养素。它也是大气中最丰富的元素，但大多数生物体无法直接从空气中获取它。 只有某些特殊的微生物才有能力将大气中的氮转化为生物有用的形式，这一过程称为固氮。 其中一些微生物是自由生活的，但大多数微生物在植物根部内紧密共生，以氮交换碳。 这种固氮共生是全球氮循环的核心组成部分，也是农业系统的核心，因为氮通常是作物生长的限制因素。因此，必须了解固氮植物-细菌伙伴关系如何在自然界中形成，以及它们如何应对充满挑战和不断变化的环境。该项目的目的是提供一个数据密集型框架，以了解植物和细菌如何选择它们的伙伴，以及这种选择如何影响和响应周围的物种、土壤和气候。 该项目的第二个目的是培训来自科学领域代表性不足的群体的学生。 学生将通过创新的指导计划和跨学科研究（包括实地考察、实验室工作和计算生物学）为 STEM 学科现在所需的数据密集型职业做好准备。该项目将研究固氮细菌和其他与植物相关的微生物的多样性通过 NEON（国家生态观测站网络）使用 NSF 赞助的生态监测资源，扎根于整个北美大陆。在 45 个 NEON 站点中的每一个站点，环境数据都将与固氮共生数据相结合。 具体来说，研究人员将对土壤和根瘤中的微生物组进行采样，并检测叶片同位素以确定固氮共生体的功能水平。 利用这些不同来源的数据，PI 将能够确定微生物和植物伙伴是否都受到相同环境因素（例如干旱）的限制。 他们还能够确定植物或微生物伙伴的选择性在多大程度上限制了关联的程度。 此外，通过检查生命树中的模式，PI 将能够推断高度特定的伙伴关系是否在整个进化过程中持续存在。 最后，模型将用于解决所有数据源的综合问题。 例如，一个模型可以测试干旱环境有利于高度特异性关联的预测，其中微生物和植物在这些压力环境中都会选择特定的合作伙伴。该项目由 BIO 新兴前沿计划和刺激竞争研究既定计划共同资助(EPSCoR)。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。