QUANTITATIVE CHARACTERIZATION OF PROTEINS AND POST-TRANSLATIONAL MODIFICATIONS IN COMPLEX PROTEOMES USING HIGH-RESOLUTION MASS SPECTROMETRY-BASED PROTEOMICS

Mass spectrometry-based proteomics is focused on identifying the entire suite of proteins and their post-translational modifications (PTMs) in a cell, organism, or community. In particular, quantitative proteomics measures abundance changes of thousands of proteins among multiple samples and provides network-level insight into how biological systems respond to environmental perturbations. Various quantitative proteomics methods have been developed, including label-free, metabolic labeling, and isobaric chemical labeling. This dissertation starts with systematic comparison of these three methods, and shows that isobaric chemical labeling provides accurate, precise, and reproducible quantification for thousands of proteins. Based on these results, we applied this approach to characterizing the proteome of Arabidopsis seedlings treated with Strigolactones (SLs), a new class of plant hormones that modulate various developmental processes. Our study reveals that SLs regulate the expression of a range of proteins that have not been assigned to SL pathways, which provides novel targets for follow-up genetic and biochemical characterization of SL signaling. The same approach was also used to measure how elevated temperature impacts the physiology of individual microbial groups in an acid mine drainage (AMD) microbial community, and shows that related organisms differed in their abundance and functional responses to temperature. Elevated temperature repressed carbon fixation by two Leptospirillum genotypes, whereas carbon fixation was significantly up-regulated at higher temperature by a third member of this genus. Further, we developed a new proteomic approach that harnessed high-resolution mass spectrometry and supercomputing for direct identification and quantification of a broad range of PTMs from an AMD microbial community. We find that PTMs are extraordinarily diverse between different growth stages and highly divergent between closely related bacteria. The findings of this study motivate further investigation of the role of PTMs in the ecology and evolution of microbial communities. Finally, a computational approach has been developed to improve the sensitivity of phosphopeptide identification. Overall, the research presented in the dissertation not only reveals biological insights with existing quantitative proteomics methods, but also develops novel methodologies that open up new avenues in studying PTMs of proteins (e.g. PTM cross-talk).