Collaborative Research: RESEARCH-PGR: Deciphering Host- and Environment-dependencies in the Legume-Rhizobia Symbiosis by Dual-Seq Transcriptomics and Directed Genome Engineering

合作研究：RESEARCH-PGR：通过双序列转录组学和定向基因组工程破译豆科植物-根瘤菌共生中的宿主和环境依赖性

• 批准号: 2243819
• 负责人: Liana Burghardt
• 金额: $ 31万
• 依托单位: Pennsylvania State Univ University Park
• 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: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2243819&HistoricalAwards=false
• 关键词: Collaborative; Research; RESEARCH; PGR; Deciphering

Plants live in close association with bacteria. Some of these associations have little effect on plant growth, some are harmful to plants, and some benefit plants by providing essential nutrients or other benefits. The most important of these beneficial associations occurs between rhizobia bacteria and their legume hosts, which include agriculturally important species such as soybeans, peas, and alfalfa. This association is important because the bacteria, when living with plants, provide plants with nitrogen through a process called nitrogen fixation. Because nitrogen is an essential nutrient that often limits plant growth, this association supports plant productivity in both natural and agricultural settings while greatly reducing the need for nitrogen fertilizer, an economically and environmentally expensive input to agricultural systems. This project will use an integrative approach to identify the plant legume and rhizobia genes that work together to control the efficacy of nitrogen fixation. The researchers will use manipulative experiments to measure the benefits that each of eighteen host species gain when growing in association with each of two species of rhizobia bacteria. These same experiments will also be used to assay which plant and rhizobial genes are being expressed in each plant-rhizobia pair, and then statistical analyses will identify groups of genes that have similar expression patterns. The experiment promises to identify gene modules that contain plant genes that control rhizobia genes and rhizobia genes that control plant genes. By examining multiple plant species and multiple environments, the proposed work will identify genes essential for nitrogen fixation and genes that can be modified to manipulate nitrogen fixation in specific environments. To verify gene function, the researchers will engineer bacteria genomes with genes of interest and then measure how these engineered bacteria affect plant growth. The results of the work will provide tools to manipulate the legume-rhizobia symbiosis to increase the benefits it provides to agricultural systems. The project will train scientists in new approaches and data analyses and develop materials for hands-on STEM courses for undergraduate students. Most genetic analyses of the legume-rhizobia symbiosis have been conducted in unrealistic environments, where plants rely entirely on nitrogen supplied by a single rhizobium strain. The extent to which results from these studies can be extrapolated across species and environments remains an open question that is critical for refining predictions about symbiosis genomics, including the societal goal of improving plant health. This project will build on the foundational knowledge from the Medicago truncatula-Sinorhizobium meliloti symbiosis by using dual-seq host-symbiont transcriptome data from a broad range of Medicago host species (18 species) and two Sinorhizobium species, across a range of field-relevant nitrogen fertilizer levels. The researchers will use differential expression analyses and two-species coexpression networks to identify both host and symbiont genes with expression that is associated with symbiotic performance. Of particular interest are coexpression modules that are enriched for both plant and microbe genes as well as plant-microbe gene pairs with coordinated expression (i.e., strong edges in the coexpression network). The function of a subset of candidates will be validated by adding them to a minimum symbiotic genome, a powerful genomic engineering approach for gain of function assays. By identifying genes that play a role in adaptation to specific hosts and nitrogen environments, the project will contribute to the goal of untangling the interspecific genetic crosstalk that control plant-microbe symbiosis and that hold the key to optimizing this symbiosis for plant health. All project outcomes will be freely available through long term data and resource repositories.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.

植物与细菌密切相关。其中一些关联对植物的生长几乎没有影响，有些对植物有害，而有些通过提供必需的营养或其他益处来使植物受益。这些有益的关联中最重要的是根瘤菌细菌与其豆科植物宿主之间，其中包括农业重要的物种，例如大豆，豌豆和苜蓿。这种关联很重要，因为当与植物一起生活时，细菌通过称为氮固定的过程为植物提供氮。由于氮是一种经常限制植物生长的必不可少的营养素，因此这种关联支持自然和农业环境中的植物生产力，同时大大减少了对氮肥的需求，氮肥是对农业系统的经济和环境昂贵的投入。该项目将使用一种综合方法来识别植物豆类和根瘤菌基因，这些基因共同控制氮的固定功效。研究人员将使用操纵实验来衡量十八种宿主物种与两种根瘤菌细菌中的每一种相关的益处。 这些相同的实验还将用于测定每个植物 - 鼠疫对中植物和根茎基因的表达，然后统计分析将识别具有相似表达模式的基因组。 该实验有望鉴定包含控制根瘤基因和控制植物基因的根茎基因的植物基因的基因模块。 通过检查多种植物物种和多种环境，该提议的工作将确定可以修改以在特定环境中操纵氮固定的基因所必需的基因。为了验证基因功能，研究人员将使用感兴趣的基因来设计细菌基因组，然后测量这些工程细菌如何影响植物的生长。这项工作的结果将提供工具来操纵豆科植物共生，以增加其对农业系统的收益。该项目将培训科学家的新方法和数据分析，并为本科生的动手STEM课程开发材料。大多数对豆科植物共生的遗传分析都是在不现实的环境中进行的，在不现实的环境中，植物完全依赖于单个根茎菌株提供的氮。这些研究的结果可以在物种和环境中推断出的程度仍然是一个开放的问题，这对于完善有关共生基因组学的预测至关重要，包括改善植物健康的社会目标。该项目将基于Medicago truncatula-Sinorhizobium Meliloti共生的基础知识，通过使用双seq宿主 - 宿主 - 伴侣转录体数据，来自广泛的Medicago宿主物种（18种）和两种sinorhizobium物种，跨越了一系列野生型硝基硝基氮肥。研究人员将使用差异表达分析和两个物种共表达网络来识别与共生性能相关的表达的宿主和共生基因。特别令人感兴趣的是共表达模块，这些模块富含植物和微生物基因以及具有协调表达的植物微生物基因对（即共表达网络中的强边）。一部分候选者的功能将通过将其添加到最小共生基因组中来验证，这是一种强大的基因组工程方法，以获得功能分析的增益。通过鉴定在适应特定宿主和氮环境中发挥作用的基因，该项目将有助于解开控制植物菌群共生的种间遗传串扰，并构成优化这种对植物健康的共生的关键。所有项目成果将通过长期数据和资源存储库免费获得。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，被认为值得通过评估来获得支持。