Clostridium thermocellum is a fermentative, Gram-positive, thermophile capable of cellulosome-mediated breakdown of hemicellulose and simultaneous biofuels (ethanol and H2) production, and is thus an excellent candidate for consolidated bioprocessing. However, ethanol and/or H2 production yields are below theoretical maxima due to branched product pathways. Biofuel yields may be improved by manipulation of fermentation conditions or implementation of rational metabolic engineering strategies. However, the latter relies on a thorough understanding of gene content, gene product expression, enzyme activity, and intracellular metabolite levels, which can all influence carbon and electron flux. The thesis work represents the first large-scale attempt in combining bioinformatic, enzymatic, proteomic, and culture perturbation approaches to systematically understand these interactions. C. thermocellum was used to investigate how these parameters affect end-product yields. Enzyme activities involved in conversion of pyruvate to end-products were consistent with end-product profiles and draft genome annotation. NADH and NADPH-dependent alcohol dehydrogenase (ADH) activities were comparable, whereas NADPH-dependent hydrogenase activities were higher than NADH and ferredoxin-dependent hydrogenase activities. While product yields changed in response to exogenous end-product additions, most core fermentative enzyme activities did not, suggesting that these changes may be governed by thermodynamics. The lack of major changes (>2-fold) in expression in response to growth and gas sparging was further confirmed by proteomics and RT-qPCR, respectively, although the latter revealed that ADH expression changes in response to gas sparging. Improved genome curation allowed refinement of metabolic pathways. A genomic and end-product meta-analysis of ethanol and/or H2 producing fermentative bacteria revealed that presence/absence of genes encoding hydrogenases and aldehyde dehydrogenases/ADHs had the greatest impacts on biofuel yields. However, genome content alone did not necessarily explain end-product yields. Given that genomic analysis of C. thermocellum revealed the presence of redundant genes encoding enzymes with analogous functions, shotgun and multiple reaction monitoring proteomics was used to refine which proteins are expressed. Absence/low expression of aldehyde dehydrogenase, ferredoxin-dependent hydrogenase and NADH:ferredoxin oxidoreductase suggest that these enzymes may not play a significant role in metabolism. An alternative electron flow pathway is proposed to explain end-product synthesis patterns in response to pyruvate addition or presence of protein inhibitors (CO, hypophosphite).

Pulmonary arterial hypertension (PAH) is a lethal disease characterized by excessive proliferation of pulmonary vascular cells, such as endothelial cells (ECs). Hereditary (H) PAH is mainly caused by ―loss-of-function‖ mutations in the gene coding for the bone morphogenetic protein type II receptor (BMPR2). However, the mechanisms by which these mutations cause PAH remain unclear. The hypothesis of this thesis was that BMPR2 mutations produce an imbalance in EC protein expression and/or activity that is integrally related to the development of abnormalities in lung vascular function and structure in HPAH. Patient-specific blood-outgrowth endothelial cells (BOECs) expanded ex vivo from peripheral blood mononuclear cells from patients with HPAH and healthy subjects were used to examine the consequences of BMPR2 mutations on the BOEC protein expression profile as well as on their functionality. Functional analyses of the BOECs revealed that HPAH-derived BOECs are more susceptible to apoptosis and more proliferative compared with healthy controls. Protein isolates of BOECs from patients with HPAH and from healthy subjects were subjected to 2-D gel electrophoresis and stained for total proteins and phosphoproteins, and to a quantitative computerassisted analysis. Differentially regulated proteins were identified by mass spectrometry (LC-MS/MS). Of the 416 total proteins detected under basal conditions, 11 were significantly downregulated in HPAH-derived BOECs and 11, including the translationally controlled tumor protein (TCTP), were upregulated. TCTP has previously been shown to be involved in systemic arteriolar remodeling, inflammation and growth. Therefore, the potential role of TCTP in PAH was studied in vivo in the SU5416 rat model of severe angioproliferative PAH. Immunofluorescence staining revealed high expression of TCTP in arteriolar ECs of PAH lungs tightly localized to proliferating cells within occlusive intimal lesions; whereas, only minimal TCTP expression was seen in vascular ECs of normal lungs. Similarly, abundant TCTP immunostaining was also seen in human PAH lung sections, again associated with complex vascular lesions. In BOECs, TCTP was found to participate in cell growth and survival. These data suggest that TCTP could play an important role in PAH by mediating pro-survival and growth signaling in vascular cells, contributing to occlusive pulmonary vascular remodeling triggered by EC apoptosis.

The ubiquitin-like proteins (Ubls) are small polypeptides that function as post-translational modifiers. Like ubiquitin, most Ubls are covalently attached to a lysine residue on target proteins. The small ubiquitin-related modifiers (SUMO) play important roles in a number of critical biological processes, such as proliferation and regulation of the cell cycle, yet their specific cellular functions have remained poorly understood. Like ubiquitin, SUMO proteins can also form oligomeric “chains”, but the functions of these structures were even less well understood. To this end, I created the first spectral library for the identification of Ub/Ubl proteins and Ub/Ubl chain linkages in mass spectrometry experiments. This tool has dramatically improved our ability to use MS to analyze the contents of biological samples for Ub and Ubls, and to identify specific types of Ub and Ubl chains in model organisms. I also used MS to conduct the first comprehensive SUMO system protein-protein interactome in any organism. In total, 452 high confidence protein-protein interactions were detected for S. cerevisiae SUMO system proteins, encompassing a total of 321 interacting partners. Yeast SUMO system components were found to interact with proteins involved in a number of different biological processes, and my mapping effort increased the number of known SUMO system interacting partners >50-fold. This study revealed that a number of transcriptional co-repressors and chromatin remodelling proteins interact physically with specific SUMO system components, with a clear division of labour between SUMO system enzymes. Finally, I conducted the first global analysis of SUMO chain function, using a combination of genetic, high-content microscopy, and high-density transcriptomics screens. Consistent with my interactomics work, this study demonstrated that inhibition of SUMO chain synthesis leads to severe chromatin condensation defects, which in-turn leads to chromosome missegregation, unscheduled transcription of stress-and nutrient-regulated genes, and aberrant intragenic transcription. Together, my work thus revealed a major role for the SUMO system in the maintenance of higher order chromatin structure and transcriptional repression.

The ubiquitin-like proteins (Ubls) are small polypeptides that function as post-translational modifiers. Like ubiquitin, most Ubls are covalently attached to a lysine residue on target proteins. The small ubiquitin-related modifiers (SUMO) play important roles in a number of critical biological processes, such as proliferation and regulation of the cell cycle, yet their specific cellular functions have remained poorly understood. Like ubiquitin, SUMO proteins can also form oligomeric “chains”, but the functions of these structures were even less well understood. To this end, I created the first spectral library for the identification of Ub/Ubl proteins and Ub/Ubl chain linkages in mass spectrometry experiments. This tool has dramatically improved our ability to use MS to analyze the contents of biological samples for Ub and Ubls, and to identify specific types of Ub and Ubl chains in model organisms. I also used MS to conduct the first comprehensive SUMO system protein-protein interactome in any organism. In total, 452 high confidence protein-protein interactions were detected for S. cerevisiae SUMO system proteins, encompassing a total of 321 interacting partners. Yeast SUMO system components were found to interact with proteins involved in a number of different biological processes, and my mapping effort increased the number of known SUMO system interacting partners >50-fold. This study revealed that a number of transcriptional co-repressors and chromatin remodelling proteins interact physically with specific SUMO system components, with a clear division of labour between SUMO system enzymes. Finally, I conducted the first global analysis of SUMO chain function, using a combination of genetic, high-content microscopy, and high-density transcriptomics screens. Consistent with my interactomics work, this study demonstrated that inhibition of SUMO chain synthesis leads to severe chromatin condensation defects, which in-turn leads to chromosome missegregation, unscheduled transcription of stress-and nutrient-regulated genes, and aberrant intragenic transcription. Together, my work thus revealed a major role for the SUMO system in the maintenance of higher order chromatin structure and transcriptional repression.

Lysine acetylation is a post-translational modification (PTM) studied extensively in the context of histone proteins as a regulator of chromatin dynamics. Recent proteomic studies have revealed that as much as 10% of prokaryotic and mammalian proteins undergo lysine acetylation, and as such, the study of its biological consequences is rapidly expanding to include virtually all cellular processes. Unravelling the complex regulatory network governed by lysine acetylation will require an in depth knowledge of the lysine acetyltransferase enzymes that mediate catalysis, and moreover the development of methods that can identify enzyme-substrate relationships in vivo. This is complex task and will be aided significantly through the use of model organisms and systems biology approaches. The work presented in this thesis explores the function of the highly conserved NuA4 lysine acetyltransferase enzyme complex in the model organism Saccharomyces cerevisiae using systems biology approaches. By exploiting genetic screening tools available to the budding yeast model, I have systematically assessed the cellular roles of NuA4, thereby identifying novel cellular processes impacted by the function of the complex, such as vesicle-mediated transport and the stress response, and moreover identified specific pathways and proteins that are impacted by NuA4 KAT activity, including cytokinesis through the regulation of septin protein dynamics. Moreover, I have developed a mass spectrometry-based technique to identify NuA4-dependent acetylation sites amongst proteins that physically interact with NuA4 in vivo. Together this work demonstrates the diversity of processes impacted by NuA4 function in vivo and moreover highlights the utility of global screening techniques to characterize KAT function.

This dissertation consists of four different topics in the areas of proteomics, genomics, and cardiology. First, a data-based method was developed to assign the subcellular localization of proteins. We applied the method to data on the bacteria Rhodobacter sphaeroides 2.4.1 and compared the results to PSORTb v.3.0. We found that the method compares well to PSORTb and a simulation study revealed that the method is sound and produces accurate results. Next, we investigated genomic features involved in the lethality of the knockout mouse using the random forest technique. We achieved an accuracy rate of 0.725 and found that among other features, the evolutionary age of the gene was a good predictor of lethality. Third, we analyzed DNA breakpoints across eight different cancer types to determine if common hotspots or cancer-type specific hotspots can be well-predicted by various genomic features and investigated which of the genomic features best predict the number of breakpoints. Using the random forest technique, we found that cancer- type specific hotspots are poorly predicted by genomic features but common hotspots can be predicted using the relevant genomic features. Additionally, we found that among the genomic features analyzed, indel rate and substitution rate were consistently chosen as the top predictors of breakpoint frequency. Lastly, we developed a method to predict the hypothetical heart age of a subject based on the subject’s electrocardiogram (ECG). The heart age predictions are consistent with current ECG science and knowledge of cardiac health.

The fungal pathogen Sclerotinia sclerotiorum (Lib.) de Bary is capable of infecting over 400 plant species including canola (Brassica napus L.). The fungus secretes oxalic acid (OA), which plays an important role in infection and disease progression. An analysis of proteome-level changes associated with infection of susceptible canola leaves by S. sclerotiorum revealed significant changes in the abundance of 32 proteins, including proteins involved in photosynthesis and metabolism, hormone signaling, and antioxidant defense. A similar subset of 37 proteins was affected when leaves were treated with OA alone; this compound also caused a reduction in the activities of a number of antioxidant enzymes, suggesting an OA-mediated suppression of the oxidative burst. To further understand the mechanisms of pathogenesis, the role of Sssp, a predicted secreted protein from S. sclerotiorum, was targeted for analysis. Mutant strains of S. sclerotiorum were generated by disruption of the Sssp gene and characterized for virulence on canola. Based on the extent of symptom development, the virulence of the Sssp-disrupted mutants was significantly reduced relative to the wild-type, indicating that Sssp may play a role in the infection process. Finally, the development of sclerotia, long-term survival structures that serve as a primary source of inoculum for the fungus, was examined. A total of 88 proteins were found to exhibit temporal changes in abundance during sclerotium formation and maturation, including proteins involved in the regulation of melanogenesis. A total of 56 proteins were also identified in the sclerotial exudates, providing a basis for future studies. Collectively, the studies described in this dissertation represent the most comprehensive proteome-level analysis of the canola/S. sclerotiorum interaction and sclerotial development, and could contribute to the development of novel strategies for the management of S. sclerotiorum. / Plant Science

Wheat plants are affected by water-deficit stress in various regions of the world resulting in reduced crop productivity and thus decreased food production. To better understand the protein changes of water-deficit stress in wheat roots, comparative proteomics was performed using 2D gel electrophoresis followed by HPLC-MS/MS. Forty proteins were identified, twenty-nine of which are non-redundant. Cell walls root proteins were identified using SDS-PAGE followed by mass spectrometry, resulting in the identification of seventeen proteins. Cell wall polysaccharides were extracted from roots to identify the polysaccharide metabolic changes that occurred under water-deficit stress conditions. Using FT-IR, cellulose was found to increase while hemicellulose and pectin content decreased. Further analysis by PCA showed changes in overall polysaccharide content over time. Overall, proteins identified in wheat whole roots and cell walls, combined with indications of polysaccharide modifications in the root cell walls, give us a better understanding of wheat responses to water-deficit stress. / Plant Biology

Contemporary proteomics studies require computational approaches to deal with both the complexity of the data generated, and with the volume of data produced. The amalgamation of mass spectrometry -- the analytical tool of choice in proteomics -- with the computational and statistical sciences is still recent, and several avenues of exploratory data analysis and statistical methodology remain relatively unexplored. The current study focuses on three broad analytical domains, and develops novel exploratory approaches and practical tools in each. Data transform approaches are the first explored. These methods re-frame data, allowing for the visualization and exploitation of features and trends that are not immediately evident. An exploratory approach making use of the correlation transform is developed, and is used to identify mass-shift signals in mass spectra. This approach is used to identify and map post-translational modifications on individual peptides, and to identify SILAC modification-containing spectra in a full-scale proteomic analysis. Secondly, matrix decomposition and projection approaches are explored; these use an eigen-decomposition to extract general trends from groups of related spectra. A data visualization approach is demonstrated using these techniques, capable of visualizing trends in large numbers of complex spectra, and a data compression and feature extraction technique is developed suitable for use in spectral modeling. Finally, a general machine learning approach is developed based on conditional random fields (CRFs). These models are capable of dealing with arbitrary sequence modeling tasks, similar to hidden Markov models (HMMs), but are far more robust to interdependent observational features, and do not require limiting independence assumptions to remain tractable. The theory behind this approach is developed, and a simple machine learning fragmentation model is developed to test the hypothesis that reproducible sequence-specific intensity ratios are present within the distribution of fragment ions originating from a common peptide bond breakage. After training, the model shows very good performance associating peptide sequences and fragment ion intensity information, lending strong support to the hypothesis.

Thesis (Ph. D.)--University of Hong Kong, 2007. / Also available online.