Systems genetics of symbiotic quality in legume-rhizobium mutualism

非技术性：植物和微生物之间的互惠互动是地球生态系统的组成部分。这些互惠关系对于稳定原始的自然群落、恢复退化的环境和农业系统中的植物生产力是重要的。根瘤菌(根瘤菌)通过将大气中的氮固定为可用的形式，使豆科寄主植物(豌豆、豆类、大豆)受益，本质上使它们的植物宿主肥沃。因此，豆类富含氮素，并提供丰富的植物来源蛋白质。然而，根瘤菌菌株在性质上是多样化的，在伙伴质量或它们为植物宿主提供的好处的水平上有很大的差异。该项目以一个遗传模型系统(豆科植物紫花苜蓿及其伙伴细菌Sinorhizobium Meliloti)为重点，结合包括全基因组DNA测序、基因表达和代谢组学在内的各种方法，研究根瘤菌伴侣质量变异的范围及其潜在的分子基础。这些技术提供了对遗传决定因素和细胞水平新陈代谢的洞察，这些基因决定因素和细胞水平的新陈代谢特征是高度有益的相互作用，而不是对植物寄主不太有益的低质量相互作用。在机械水平上了解是什么决定了合作伙伴的质量，这是至关重要的基础知识，有助于将植物微生物组作为植物改良计划和可持续作物生产的一部分进行设计。此外，基本了解是什么决定了合作伙伴的质量，对于理解互惠关系如何随时间演变以及关键的互惠关系如何在当前环境中持续存在至关重要。该项目提供本科生和研究生水平的生物和计算培训，为当地社区大学生提供实习机会，并生成在线推广和分析工具。技术：互助者在自然界中的伴侣质量差异很大，通常对自然和管理系统具有重要影响，但互助者伴侣质量差异的分子基础尚不清楚。最近的研究表明，由于伴侣的分离、生态向互惠程度较低的物种的转变或平均伴侣质量的进化下降，环境变化导致了互惠关系的衰落。要了解它们的共同进化、持续和潜在的衰落，就需要对互惠关系有一个预见性的理解。该项目将把自然遗传变异与生理和分子特征整合到共生网络中，以揭示根瘤菌(Sinorhizobium)Meliloti与其宿主紫花苜蓿(Medicago Truncatula)之间互惠共生的遗传和分子结构。中心假设是，自然发生的变异可以用来更好地解决有助于高质量共生的植物和根瘤菌代谢途径的遗传调节。该项目将根瘤菌基因组范围的核苷酸变异与根瘤菌和寄主植物的表型和分子特性相结合，以解决根瘤菌伙伴质量的分子基础(根瘤菌对植物寄主有多少好处)，这一特性与自然和管理的生态系统都有关。转录组和代谢组数据的网络分析将产生高质量和低质量共生的比较模型，使对豆科植物和固氮根瘤菌之间生态和进化上重要的共生关系的基因到性状的预测成为可能。通过网络分析产生的假说将在根瘤菌和寄主植物系统中得到验证，以确定重要伴侣质量性状的生理和分子表型。

Non-technical:Mutually-beneficial interactions between plants and microbes are integral aspects of Earth's ecosystems. These mutualisms are important for stabilizing pristine natural communities, restoring degraded environments, and plant productivity in agricultural systems. Rhizobial bacteria (rhizobia) benefit leguminous host plants (peas, beans, soybean) by fixing atmospheric nitrogen into usable forms, essentially fertilizing their plant hosts. As a result, legumes are high in nitrogen and provide an abundant source of plant-derived protein. Rhizobial strains, however, are diverse in nature and vary quite a bit in partner quality, or the level of benefits they provide to the plant host. This project focuses on a genetic model system (the legume Medicago truncatula and its partner bacterium Sinorhizobium meliloti) to investigate the range of partner quality variation and its underlying molecular basis in rhizobia, integrating various approaches including whole-genome DNA sequencing, gene expression, and metabolomics. These techniques provide insight into the genetic determinants and cellular-level metabolism that characterizes highly-beneficial interactions, versus low-quality interactions that are less beneficial for plant hosts. Understanding what determines partner quality at a mechanistic level is critical foundational knowledge that informs efforts to engineer the plant microbiome as part of plant improvement programs and sustainable crop production. Moreover a basic understanding of what determines partner quality is important for understanding how mutualisms evolve through time and how crucial mutualisms persist in current environments. This project provides biological and computational training at the undergraduate and graduate level, provides internships for local community college students, and generates online outreach and analysis tools.Technical:Mutualists in nature vary widely in partner quality, often with important implications for natural and managed systems, yet the molecular basis of mutualist partner quality variation is not well-understood. Recently studies have demonstrated mutualism decline in response to environmental changes, resulting from dis-association of partners, ecological shifts towards less-mutualistic species, or evolutionary decreases in mean partner quality. A predictive understanding of mutualisms is needed to understand their coevolution, persistence, and potential decline. This project will integrate natural genetic variation with physiological and molecular traits into symbiosis networks to uncover the genetic and molecular architecture underlying the mutualism between the rhizobium Ensifer (Sinorhizobium) meliloti and its host plant Medicago truncatula. The central hypothesis is that naturally-occurring variation can be used to better resolve the genetic regulation of plant and rhizobium metabolic pathways that contribute to high-quality symbiosis. This project integrates rhizobium genome-wide nucleotide variation with both rhizobia and host plant phenotypic and molecular traits to address the molecular basis of rhizobium partner quality (how much rhizobia benefit their plant hosts), a trait relevant to both natural and managed ecosystems. Network analysis of transcriptomic and metabolomic data will result in comparative models of high and low quality symbiosis, enabling gene-to-trait predictions for the ecologically- and evolutionarily- important symbiosis between leguminous plants and nitrogen-fixing rhizobium bacteria. Hypotheses generated by network analysis will be validated in both rhizobia and host plant systems for physiological and molecular phenotypes underlying important partner quality traits.