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

植物与细菌密切共生。其中一些对植物生长影响不大，一些对植物有害，而一些则通过提供必需的营养或其他益处而对植物有益。这些最重要的有益联系发生在根瘤菌细菌和它们的豆科寄主之间，其中包括农业上重要的物种，如大豆、豌豆和苜蓿。这种联系很重要，因为当细菌与植物一起生活时，通过一种称为固氮的过程为植物提供氮。由于氮是一种通常限制植物生长的必需养分，该协会支持自然和农业环境下的植物生产力，同时大大减少对氮肥的需求，氮肥是农业系统中经济和环境上昂贵的投入。本项目将采用综合方法鉴定豆科植物和根瘤菌共同控制固氮效率的基因。研究人员将使用可操作的实验来测量18种宿主在与两种根瘤菌中的每一种一起生长时所获得的益处。这些相同的实验还将用于测定每个植物-根瘤菌对中哪些植物和根瘤菌基因正在表达，然后通过统计分析确定具有相似表达模式的基因组。该实验有望鉴定出含有控制根瘤菌基因的植物基因和控制植物基因的根瘤菌基因的基因模块。通过研究多种植物物种和多种环境，本研究将确定固氮所必需的基因，以及在特定环境中可以通过修饰来操纵固氮的基因。为了验证基因功能，研究人员将用感兴趣的基因改造细菌基因组，然后测量这些改造过的细菌如何影响植物生长。这项工作的结果将为控制豆科植物与根瘤菌的共生关系提供工具，以增加它对农业系统的好处。该项目将在新的方法和数据分析方面培训科学家，并为本科生开发动手STEM课程的材料。豆科植物与根瘤菌共生的大多数遗传分析都是在不现实的环境中进行的，在这种环境中，植物完全依赖于单一根瘤菌菌株提供的氮。这些研究的结果在多大程度上可以跨物种和环境进行外推，这仍然是一个悬而未决的问题，这对于完善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。本项目将利用不同农田氮肥水平下广泛的紫花苜蓿寄主物种（18种）和两种紫花苜蓿寄主物种的双序列转录组数据，以药用紫花苜蓿- meliloti Sinorhizobium共生的基础知识为基础。研究人员将使用差异表达分析和两种共表达网络来识别宿主和共生体的基因，这些基因的表达与共生体的表现有关。特别令人感兴趣的是富含植物和微生物基因以及植物-微生物基因对协调表达的共表达模块（即共表达网络中的强边缘）。候选子集的功能将通过将它们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，可以获得功能分析。通过识别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-微生物共生的种间遗传串扰的目标，并掌握优化植物健康共生的关键。所有项目成果将通过长期数据和资源库免费提供。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。

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.