Systems genetics of symbiotic quality in legume-rhizobium mutualism

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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.