Grant: Discovery Grants Program - Individual

My long-term research goal is to identify the molecular, regulatory, and functional properties of key enzymes of plant carbohydrate and phosphate (Pi) metabolism. Our detailed biochemical characterization of purified enzymes was recently augmented by various innovative proteomic and genomic tools, resulting in several fascinating discoveries concerning the control of phosphoenolpyruvate (PEP) metabolism in the triglyceride-rich endosperm of developing castor oilseeds, and the biochemical adaptations of Pi-deprived (-Pi) Arabidopsis thaliana. PEP carboxylase (PEPC) is an important and 'multi-faceted' allosteric enzyme situated at the core of primary plant metabolism that participates in the control of seed carbohydrate partitioning to agronomically important end-products such as storage oils and proteins, but also helps plants to cope with suboptimal Pi, one of the least available macronutrients in many soils. Proposed research is focused on the: (A) functional properties, protein interactions, and subcellular localization of novel Class-1 & Class-2 PEPC isoforms of developing oilseeds, & (B) properties and Pi-scavenging functions of a PEPC isozyme that is reversibly accumulated and phosphorylated by -Pi Arabidopsis (hypothesized to result in excretion of Pi-solubilizing organic acids by roots of -Pi plants), as well as the predominant intra- & extracellular purple acid phosphatase isozymes upregulated by -Pi Arabidopsis (hypothesized to help recycle Pi from intracellular and soil-localized Pi-esters). Our studies have significant applications to problems in Canadian agriculture including the: (i) targeted modification of storage oil vs. protein levels in oilseeds such as canola or soybean, & (ii) development of Pi-efficient transgenic crops, urgently needed to reduce mankind's rampant but inefficient use of non-renewable, unsustainable, and polluting Pi fertilizers. During this granting period we will continue to integrate new proteomic and genomic tools into our research. These innovations require retooling, training, and optimization, but provide quantitative advances in the types of data that we can gather, and a solid foundation for HQP training in modern plant metabolic biochemistry.