Fan, Kai-Ting2016-10-252016-10-252015-08https://hdl.handle.net/11299/182834University of Minnesota Ph.D. dissertation. August 2015. Major: Plant Biological Sciences. Advisors: William Gray, Adrian Hegeman. 1 computer file (PDF);xii, 373 pages.Protein turnover, the balance between protein synthesis and degradation, is an important aspect of the regulation of cellular processes for organisms as they respond to developmental or environmental cues. How proteome turnover will be influenced in plants when exposed to abiotic stress, especially moderately high temperature, has not been studied systematically. The study of protein turnover in plants, contrary to that of rapidly growing unicellular organismal cultures, is made more complicated by the high degree of amino acid recycling, which results in significant transient isotope incorporation distributions that must be dealt with computationally for high throughput analysis to be practical. In this study, an algorithm implemented in the statistical programing language R, ProteinTurnover, was developed to calculate protein turnover with transient stable isotope incorporation distributions in a high-throughput automated manner using high resolution mass spectrometry and proteomic analysis of stable isotopically labeled plant material. ProteinTurnover extracts isotopic distribution information for peptides identified by tandem MS from raw MS datasets of either isotopic label dilution or incorporation experiments. Variable isotopic distributions were modeled by maximum likelihood estimation using binomial or beta-binomial distributions to (1) unlabeled, (2) newly-synthesized (partially-labled) and (3) fully-labeled peptide distributions. The distribution abundance proportions of old to newly synthesized peptide distributions were calculated using quantities derived from the models. Half-lives and turnover rates were calculated by fitting the change in the distribution abundance prorportions over time to a first-order decay function using non-linear regression. Using ProteinTurnover, turnover rates of hundreds of proteins were measured in soluble, organellar, and microsomal fractions of Arabidopsis seedling roots, using isotopic incorporation. In a second study, ProteinTurnover was used to measure changes in proteome turnover in soluble, organelle, and microsomal fraction of Arabidopsis seedling shoots or roots comparing 22°C and 30°C growth conditions. A total of 571 proteins as exhibiting significant changes in turnover rate in response to elevated temperature were identified in Arabidopsis seedling tissues. In general, soluble proteins extracted from root tissue displayed relatively smaller changes in turnover. Proteins involved in photorespiration, protein folding, stress response, secondary metabolism, and redox signaling pathways exhibited the greatest changes in turnover under heat stress.enArabidopsis thalianaheat stressmetabolic labelingprotein turnover ratesproteome dynamicsstable isotopeThesis or Dissertation