Electronic Thesis and Dissertation Repository

Degree

Doctor of Philosophy

Program

Biology

Supervisor

Dr. Frédéric Marsolais

2nd Supervisor

Dr. Jim Karagiannis

Co-Supervisor

Abstract

Maintaining the proper balance between carbon (C) and nitrogen (N) metabolism is critical to the sustained growth of organisms. In plant leaves, this balance is achieved by photoperiod dependent cross-talk between the processes of photosynthesis, respiration, and amino acid metabolism. A crucial mechanism in maintaining C/N balance is the GS/GOGAT cycle, which is well known to serve as a cross-road between C and N metabolism. Importantly, non-photosynthetic tissues (e.g. roots, germinating seeds) lack a sufficient supply of carbon skeletons under high N conditions and hence may resort to other mechanisms, along with the GS/GOGAT cycle, to achieve proper C/N balance. Our understanding of the pathways involved in this aspect of plant regulation is limited. Considering the importance of asparagine as a major storage form of nitrogen, this study examines C and N partitioning within Arabidopsis roots upon asparagine treatment. Based on this work, I propose a role for the enzyme GAT1_2.1 in hydrolyzing excess glutamine to glutamic acid (Glu), which may serve as a carbon skeleton for channeling C to the TCA cycle under high N conditions. GAT1_2.1, a gene coding for a class I glutamine amidotransferase of unknown substrate specificity, was shown to be highly responsive to N status and has a root specific expression in Arabidopsis. The protein localizes to the mitochondria and the gene is found to be highly co-expressed with Glutamate Dehydrogenase 2 (GDH2). Metabolite profiling data using a gat1_2.1 mutant of Arabidopsis suggests that, in the absence of GAT1_2.1, the GABA shunt pathway is activated to replenish the depleted levels of Glu. This Glu may then be deaminated to 2-oxoglutarate by GDH2 and channeled into the TCA cycle, thus providing a cross-roads between C and N metabolism in root mitochondria. In addition to this work, I also elucidate optimal methods for reliable metabolomics experiments and propose the use of isotopic labelling for the detection of unknown pathways.

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