W346
Proteomic Studies in Monocot and Eudicot Crassulacean Acid Metabolism (CAM) Species

Date: Saturday, January 10, 2015
Time: 11:50 AM
Room: Towne - Meeting House
Paul E. Abraham , Oak Ridge National Laboratory, Oak Ridge, TN
Given the rising availability of -omic resources, plant systems can now be investigated at an unprecedented level. This is especially relevant to the study of crassulacean acid metabolism (CAM), which requires a comprehensive investigation of cellular processes, their dynamic timing, regulatory control, and interactions with environmental perturbations. To obtain a systems-level perspective on the coordinated set of processes underpinning CAM and those essential to maintaining cellular homeostasis, we integrated multiple -omic resources (i.e., transcriptomic, proteomic, and metabolomic) that profiled constitutive CAM species A. americana and facultative CAM species M. crystallinum mature leaves across a diurnal cycle. Although a subset of individual mRNAs, proteins, and metabolites exhibited diurnal patterns, the integrative framework of this study afforded a means to provide a formal representation of proteins comprising period-specific CAM modules. For example, the analysis revealed major changes in the metabolic state across the diurnal cycle in A. americana coincided with dynamic regulation of cellular redox state. Moreover, significant changes at the protein level appear functionally related to two bursts in redox potential (i.e., high NADPH/NADP ratios), with an increase following photosynthesis and a second increase occurring during peak nocturnal carbon fixation. Upon investigating temporal relationships between a subset of mRNAs and proteins, our data further supports the consensus that cellular abundances of mRNA weakly correlate with abundances of their corresponding proteins, with Pearson correlation coefficients around 0.30. Beyond global comparisons, we further characterized the temporal dynamics of individual relationships between mRNA and their corresponding protein by performing a trending and time-delay analysis.