A role for the mevalonate pathway in early plant symbiotic signaling.

Rhizobia and arbuscular mycorrhizal fungi produce signals that are perceived by host legume receptors at the plasma membrane and trigger sustained oscillations of the nuclear and perinuclear Ca(2+) concentration (Ca(2+) spiking), which in turn leads to gene expression and downstream symbiotic responses. The activation of Ca(2+) spiking requires the plasma membrane-localized receptor-like kinase Does not Make Infections 2 (DMI2) as well as the nuclear cation channel DMI1. A key enzyme regulating the mevalonate (MVA) pathway, 3-Hydroxy-3-Methylglutaryl CoA Reductase 1 (HMGR1), interacts with DMI2 and is required for the legume-rhizobium symbiosis. Here, we show that HMGR1 is required to initiate Ca(2+) spiking and symbiotic gene expression in Medicago truncatula roots in response to rhizobial and arbuscular mycorrhizal fungal signals. Furthermore, MVA, the direct product of HMGR1 activity, is sufficient to induce nuclear-associated Ca(2+) spiking and symbiotic gene expression in both wild-type plants and dmi2 mutants, but interestingly not in dmi1 mutants. Finally, MVA induced Ca(2+) spiking in Human Embryonic Kidney 293 cells expressing DMI1. This demonstrates that the nuclear cation channel DMI1 is sufficient to support MVA-induced Ca(2+) spiking in this heterologous system.

Leveraging proteomics to understand plant-microbe interactions.

Understanding the interactions of plants with beneficial and pathogenic microbes is a promising avenue to improve crop productivity and agriculture sustainability. Proteomic techniques provide a unique angle to describe these intricate interactions and test hypotheses. The various approaches for proteomic analysis generally include protein/peptide separation and identification, but can also provide quantification and the characterization of post-translational modifications. In this review, we discuss how these techniques have been applied to the study of plant-microbe interactions. We also present some areas where this field of study would benefit from the utilization of newly developed methods that overcome previous limitations. Finally, we reinforce the need for expanding, integrating, and curating protein databases, as well as the benefits of combining protein-level datasets with those from genetic analyses and other high-throughput large-scale approaches for a systems-level view of plant-microbe interactions.