COS 146-10
Multiple mutualist effects: Combining transcriptomics and experimental ecology to determine the genomic basis of synergistic interactions between mycorrhizal fungi, rhizobia, and legumes

Friday, August 14, 2015: 11:10 AM
339, Baltimore Convention Center
Michelle E. Afkhami, Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada
John Stinchcombe, Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada

In nature, most organisms interact simultaneously with multiple mutualistic species (e.g., plants with pollinators, microbial symbionts, and ants), however mutualism studies have traditionally focused on bipartite interactions between a single partner and host. Bipartite studies will underestimate the importance of mutualism for ecological and evolutionary dynamics if synergism occurs among functionally different partners, and overestimate it if partners are in conflict. In a recent synthesis paper, we merged two important, but disparate, research approaches (network and consumer-resource models) to define and provide a predictive framework for the multiple mutualist effects – MMEs – that occur when a species interacts with multiple partners. Here, we integrate this ecological framework with whole genome transcriptomics (RNA-seq) to understand the mechanistic basis of mutualist diversity. Using the tripartite mutualism between arbuscular mycorrhizal fungi, nitrogen-fixing bacteria, and the model legume (Medicago truncatula), we grew plants in a factorial experiment independently manipulating rhizobia and mycorrhizal fungi and then simultaneously examined the fitness consequences as well as any changes to the gene expression for the host plant and symbionts.


Interactions with multiple mutualistic species had important consequences for both performance and gene expression of the plants. We found that mycorrhizal fungi and rhizobia had synergistic effects on host performance. In fact, plants gained no fitness benefits from growing with a single partner (e.g., increased size) but grew ~20% larger when both partner mutualists were present. Microbial treatments also resulted in significant chances to gene expression of the host plant. For example, ordinations of transcriptome profiles showed significant clustering by treatment, indicating strong similarities in expression based on microbial interactions. We identified thousands of genes that are up or down-regulated depending on the microbial environment with ~1300 genes differentially expressed depending on the presence/absence of mycorrhizal fungi and ~1600 depending on the presence of rhizobia. Interestingly, ~75 genes showed dramatic changes in expression or were uniquely expressed in the presence of multiple partners, which makes them key candidate genes underlying host sanctions and/or partner choice -- i.e. genes involved in promoting cooperation and reducing conflict among partners in these complex associations. Our results provide some of the first insights into the mechanistic basis of synergistic multispecies mutualisms and demonstrate how integrating genomics tools can help address fundamental ecological questions.