Alzheimer's disease (AD) is a progressive, irreversible, neurodegenerative disease. The key to understanding AD is to elucidate the pathogenesis of neuron degeneration in specific brain regions.We hypothesize that there is increased DNA oxidation in AD brain compared to age-matched control subjects, especially in mitochondrial DNA (mtDNA), and that the changes in DNA bases will affect protein expression in mitochondria and contribute to neurodegeneration in AD. To test this hypothesis:1) We quantified multiple oxidized bases in nuclear DNA (nDNA) and mtDNA of frontal, parietal, and temporal lobes and cerebellum from late-stage AD (LAD), mild cognitive impairment (MCI), and age-matched control subjects using gas chromatography/mass spectrometry with selective ion monitoring (GC/MS-SIM). Also, we quantified oxidized DNA bases in cortex of APP/PS1 transgenic mice. (a) nDNA and mtDNA were extracted from eight LAD and eight control subjects. We found levels of multiple oxidized bases were significantly higher in frontal, parietal, and temporal lobes and that mtDNA had approximately 10-fold higher levels of oxidized bases than nDNA. Eight-hydroxyguanine was approximately 10-fold higher than other oxidized base adducts in both LAD and control subjects. These results suggest that oxidative damage to mtDNA may contribute to the neurodegeneration of AD. (b) Mild Cognitive Impairment (MCI), the phase between normal aging and early dementia, is a common problem in the elderly with many subjects going on to develop AD. Results from eight amnestic MCI and six control subjects suggest oxidative damage to DNA occurs in the earliest detectable phase of AD. (c) Analysis of nDNA from the cortex of four groups (3m, 6m, 9m, 12m) of APP/PS1 and wild type mice showed elevations of 8-hydroxyguanine in 12 month old APP/PS1 mice.2) To analyze mitochondrial protein changes in LAD, 2D gels were run to separate proteins and MALDI-TOF mass spectrometry was used to identify proteins.Five mitochondrial proteins were significantly decreased in LAD. This proteomic study provides a proteome map of mitochondria in LAD brain and an insight into the pathogenesis of neuron degeneration in Alzheimer's disease.

Olfactory sensory decline has been associated with normal aging as well as neurodegenerative disorders, yet the underlying mechanisms are unclear. The overall aim of this dissertation was to investigate the fundamental molecular and cellular mechanisms associated with olfactory neurodegeneration. This investigation uses an integrative approach, combining proteomics and gene expression analyses with cellular and tissuelevel characterization. Using these approaches, two model systems were investigated: 1) normally aging C57BL/6 mice of ages 1.5-, 6- and 20-months; and 2) a mouse model of elevated endogenous oxidative stress-associated neurodegeneration, namely, the Harlequin mutant mouse. The first specific aim was to test the hypothesis that oxidative stress is associated with aging of the olfactory system. Using proteomics, I demonstrated that olfactory aging was accompanied primarily by increased oxidative stress-, mitochondrial metabolism- and synaptic/transport-associated changes. The second specific aim was to test the hypothesis that the olfactory system accumulates oxidative stress-mediated macromolecular damage over time, predisposing it to neurodegeneration. Two types of protein oxidation, namely, carbonylation and nitration, accumulated with aging in the olfactory system. Protein and cellular targets of oxidative stress-associated damage were identified using redox proteomics coupled with immunohistochemical localization. The third specific aim was to test the hypothesis that elevated oxidative stress in the olfactory system results in apoptosis/neurodegeneration. The Harlequin mutant mouse was critically selected and validated as a model for studies of oxidative stress-associated olfactory neurodegeneration at both the cellular and molecular levels. The Harlequin mouse had decreased levels and altered distribution of apoptosis inducing factor protein in mature olfactory sensory neurons, increased oxidative DNA damage and apoptosis in the olfactory epithelium, and pronounced cytoskeletal disorganization. The molecular studies confirmed and extended our cellular data and identified several significantly regulated genes associated with elevated oxidative stress and apoptosis. This novel study, by combining contemporary proteomics and genomics with cellular and tissue-level analyses, has provided a road map for understanding fundamental molecular mechanisms of olfactory degeneration.

<p>In this thesis, methods to study gene and protein expression in cells and tissues were developed and utilized in combination with protein-specific antibodies, with the overall objective to attain greater understanding of protein function.</p><p>To analyze protein expression in <i>in vitro</i> cultured cell lines, a cell microarray (CMA) was developed, facilitating antibody-based protein profiling of cell lines using immunohistochemistry (IHC). Staining patterns in cell lines were analyzed using image analysis, developed to automatically identify cells and immunohistochemical staining, providing qualitative and quantitative measurements of protein expression. Quantitative IHC data from CMAs stained with nearly 3000 antibodies was used to evaluate the adequacy of using cell lines as models for cancer tissue. We found that cell lines are homogenous with respect to protein expression profiles, and generally more alike each other, than corresponding cancer cells <i>in vivo</i>. However, we found variability between cell lines in regards to the level of retained tumor phenotypic traits, and identified cell lines with a preserved link to corresponding cancer, suggesting that some cell lines are appropriate model systems for specific tumor types. </p><p>Specific gene expression patterns were analyzed in vitiligo vulgaris and malignant melanoma. Transcriptional profiling of vitiligo melanocytes revealed dysregulation of genes involved in melanin biosynthesis and melanosome function, thus highlighting some mechanisms possibly involved in the pathogenesis of vitiligo. Two new potential markers for infiltrating malignant melanoma, Syntaxin-7 and Discs large homolog 5, were identified using antibody-based protein profiling of melanoma in a tissue microarray format. Both proteins were expressed with high specificity in melanocytic lesions, and loss of Syntaxin-7 expression was associated with more high-grade malignant melanomas.</p><p>In conclusion, the combination of antibody-based proteomics and microarray technology provided valuable information of expression patterns in cells and tissues, which can be used to better understand associations between protein signatures and disease.</p>

Mining of datasets obtained from proteomics experiments was performed to investigate the dissociation pathways of protonated peptides activated in the gas phase under low energy collision-induced dissociation (CID). Intensity patterns in ion trap tandem mass spectra were exploited and different statistical approaches were employed to elucidate the dissociation mechanisms.Chapter 2 describes a study of 506 doubly-protonated tryptic peptides that shows the presence of an internal basic residue can increase the preferential fragmentation C-terminal to aspartic acid (Asp-Xxx) significantly. The degree of enhancement varies with the identity of the basic residues. The result corroborates a previously published mechanism based on studies from model peptides, and was incorporated into an existing peptide sequencing algorithm. A preliminary test on a separate dataset of 119 spectra shows that implementing rules to predict enhanced cleavages at Asp-Xxx improves the ability of the algorithm to identify the correct sequence from a list of candidates.Chapters 3-4 describe much more elaborate analyses on 28,330 peptides of different sequences and charge states. Extensive sorting based on prior knowledge was first performed to probe the correlation of fragmentation patterns with structural features. Pair-wise fragmentation maps reveal that the difference in basicity between Arg and Lys results in different dissociation patterns among singly-protonated tryptic peptides. While one dominant protonation form (proton localized) exists for Arg-ending peptides, a heterogeneous population of two or more protonated forms (proton partially-mobile) exist for Lys-ending peptides. Asp/Glu-Xxx dominates spectra from peptides that have a localized proton(s) and Xxx-Pro dominates those that have a mobile or partially mobile proton(s). When Pro is absent from peptides that have a mobile or partially mobile proton(s), cleavage at each peptide bond becomes more prominent. A fundamental dependence of gas phase peptide fragmentation on conformational constraints was found.A knowledge mining scheme was proposed in Chapter 5 to bypass the prior knowledge constraints and cluster the dissociation behaviors of 28,330 peptides into four distinct categories. The most influential factors in the fragmentation process are: the mobility of the proton(s), the presence and the location of Pro and Arg. Structural motifs responsible for each dissociation behavior are also elucidated.

Early detection of prostate cancer is problematic due to the lack of a marker that has high diagnostic sensitivity and specificity. The prostate specific antigen test, in combination with digital rectal examination, is the gold standard for prostate cancer diagnosis. However, this modality suffers from low specificity. Therefore, specific markers for clinically relevant prostate cancer are needed. Our objective was to proteomically characterize the conditioned media from human prostate cancer cell lines to identify secreted proteins that could serve as novel prostate cancer biomarkers. An initial proof of principle study of the PC3 prostate cancer cell line was conducted. From this study over 200 proteins were identified in the conditioned media. Through gene ontology analysis and literature searches Mac-2 binding protein was selected as a candidate biomarker for validation in the serum of prostate cancer patients. A preliminarily validation showed that Mac-2 binding protein has discriminatory ability in prostate cancer diagnosis. However, an extended validation did not confirm this. Based on our proof of principle study we optimized our workflow and extended our analysis by culturing three different prostate cell lines [PC3 (bone metastasis), LNCaP (lymph node metastasis), and 22Rv1 (localized to prostate)]. We conducted a bottom-up analysis of each cell line by 2-dimensional liquid chromatography and tandem mass spectrometry. Of the 2124 proteins identified, 12% (329) were classified as extracellular and 18% (504) as membrane-bound. Among the identified proteins were known prostate cancer biomarkers such as PSA and KLK2. To select the most promising candidates for further investigation, tissue specificity, biological function, disease association based on literature searches, and comparison of protein overlap with the proteome of seminal plasma and serum were examined. Based on these results, several candidates were selected for validation in serum of patients with and without prostate cancer. Of these four novel candidates: follistatin, chemokine (C-X-C motif) ligand 16, pentraxin 3 and spondin 2 showed discriminatory ability. Of the four candidates, follistatin was further studied in an extended validation in serum of patients with biopsy confirmed prostate cancer and tissues of prostate cancer patients of low and high grade tumours by immunohistochemistry. In addition, follistatin was also investigated in the tissue of colon and lung cancer where intense staining was observed in one specimen of lung squamous carcinoma.

In all sequenced genomes, a large fraction of predicted genes encodes proteins of unknown biochemical function and up to 15% of the genes with ‘‘known’’ function are mis-annotated. Several global approaches are being employed to predict function, including sequence similarity searches, analysis of gene expression, protein interaction, and protein structure. Enzymes comprise a group of target proteins that require experimental characterization for accurate functional annotations. Here I applied enzyme genomics to identify new enzymes by screening individually purified proteins for enzymatic activity under relaxed reaction conditions, which allowed me to identify the subclass or sub-subclasses of enzymes to which the unknown protein belongs. Further biochemical characterization of proteins was facilitated by the application of secondary screens with natural substrates (substrate profiling). Application of general enzymatic screens and substrate profiling greatly sped up the identification of biochemical function of unknown proteins and the experimental verification of functional predictions produced by other functional genomics approaches. As a test case, I used this approach to characterize the members of the haloacid dehalogenase (HAD)-like hydrolase superfamily, which consists mainly of uncharacterized enzymes, with a few members shown to possess phosphatase, beta-phosphoglucomutase, phosphonatase, and dehalogenase activities. Low sequence similarity between the members of the HAD superfamily precludes the computational prediction of their substrates and functions. Using a representative set of 80 phosphorylated substrates I characterized the phosphatase activities of 21 soluble HADs from Escherichia coli and seven soluble HADs from Saccharomyces cerevisiae. E. coli HADs show broad and overlapping substrate specificity against a wide range of phosphorylated metabolites. The yeast enzymes were more specific, and one protein also showed protein phosphatase activity. Comparison of HAD substrate profiles from two model organisms showed several “functional niches” that are occupied by HADs, which include hydrolysis of nucleotides, phosphoglycolate, phosphoserine, and pyridoxal phosphate. I proposed the cellular function for a number of HADs from both organisms based on substrate specificities. The physiological relevance of the phosphatase activity with the preferred substrate was validated in vivo for one of the HADs, E. coli YniC.

Glycosylation, the addition of one or more carbohydrates molecules to a protein, is crucial for many cellular processes. Aberrant glycosylation is a key marker for various diseases such as cancer and rheumatoid arthritis. It has also recently been discovered that glycosylation is important in the ability of the Human Immunodeficiency Virus (HIV) to evade recognition by the immune system. Given the importance of glycosylation in disease, major efforts are underway in life science research to investigate the glycome, the entire glycosylation profile of an organelle, cell or tissue type. To date, little bioinformatics research has been performed in glycomics due to the complexity of glycan structures and the low throughput of carbohydrate analysis. Recent advances in mass spectrometry (MS) have greatly facilitated the analysis of the glycome. Increasingly, this technology is preferred over traditional methods of carbohydrate analysis which are often laborious and unsuitable for low abundance glycoproteins. When subject to mass spectrometry with collision-induced dissociation, glycopeptides produce characteristic MS/MS spectra that can be detected by visual inspection. However, given the high volume of data output from proteome studies today, manually searching for glycopeptides is an impractical task. In this thesis, we present a tool to automate the identification of glycopeptide spectra from MS/MS data. Further, we discuss some methodologies to automate the elucidation of the structure of the carbohydrate moiety of glycopeptides by adapting traditional MS/MS ion searching techniques employed in peptide sequence determination. MS/MS ion searching, a common technique in proteomics, aims to interpret MS/MS spectra by correlating structures from a database to the patterns represented in the spectrum. The tool was tested on high throughput proteomics data and was shown to identify 97% of all glycopeptides present in the test data. Further, the tool assigned correct carbohydrate structures to many of these glycopeptide MS/MS spectra. Applications of the tool in a proteomics environment for the analysis of glycopeptide expression in cancer tissue are also be presented.

Protein identification and quantitation using mass spectrometry has evolved as the dominant technique for studying the protein complement of a system: cell, tissue or organism. The proteomics of body fluids is a very active research area as there is great potential for protein biomarker discovery; application of such technologies would revolutionise medical practice and treatment. Saliva, through its non intrusive nature of sampling, is an ideal body fluid for disease diagnosis, screening and monitoring. Gingivitis is a gum disease with symptoms including bleeding, swollen, and receding gums. After dental decay, gingivitis is estimated to be the most common disease worldwide, and around 40% of the population in the US are reported to have gingivitis. The end point goal of this project was to identify salivary biomarkers for gingivitis. This dissertation presents an investigation of: 1) the salivary proteome; 2) developments and applications of a mass spectrometry kinase assay; and 3) salivary biomarkers for gingivitis using proteomics and kinase activities. The soluble portion of the human salivary proteome (saliva supernatant) has been studied by several research groups but very few proteomic studies have been performed on the insoluble, cellular and bacterial portion of saliva. Presented here, is the first global proteomics study performed on the saliva residue and supernatant from the same test subject. A total of 834 and 1426 proteins were identified in the saliva supernatant and residue, respectively. A global analysis of protein complexes in saliva was also performed and is the first study, to date, of such an analysis. KAYAK (‘Kinase ActivitY Assay for Kinome analysis’) was further developed for its application on a number of cell types, tissue types, and a variety of organisms. Proof of concept work for in-gel kinase activity/kinase abundance correlation profiling using blue native gels was performed, and experiments using anion exchange chromatographic kinase activity/kinase abundance correlation profiling were performed to identify kinase-substrate pairs. KAYAK applications included the analysis of kinase activities in Saccharomyces cervisiae, Drosophila, mouse, and human saliva in which significant kinase activity was detected in the saliva supernatant, a novel finding. Finally, gingivitis was induced in patients, and the saliva samples were analysed using proteomics and kinase activity profiling. Although this work is ongoing, preliminary data indicate that there are increases in various inflammatory proteins, certain bacteria and also in the activity of particular kinases as a result of the induction of gingivitis. The overall study provided insights into the salivary proteome for both the human and bacterial complement, as well as discovering the presence of significant kinase activity in saliva. In the induced gingivitis study, almost half of all the proteins identified in the residue were from bacteria (1274 bacterial proteins, 198 species identified) and there may be more potential for biomarker discovery for certain diseases in the saliva residue than in the supernatant. A very large overlap was observed between the human proteins in the saliva supernatant and residue, indicating that many of the salivary proteins originate from lysed cells. The origin of the kinase activity in the saliva supernatant is not known but is also proposed to originate predominantly from lysed cells. A range of novel KAYAK applications have been investigated, demonstrating that KAYAK has a wide variety of future uses ranging from target compound evaluation in Pharmaceutical companies to patient testing in the clinic.

Shiga toxin-producing Escherichia coli (STEC) are extensive contributors to foodborne illness, causing renal and central nervous system damage due to production of Shiga toxin (Stx). Rapid Stx detection is important to distinguish STEC from other enteric pathogens. Current detection techniques are time consuming, expensive, and lack sensitivity. We have developed and evaluated a novel targeted mass spectrometry-based assay for detection of Stx using parallel reaction monitoring (PRM). The PRM assay used 11 target tryptic peptides and was validated using STEC and non-STEC bacterial cultures. Stx was detected in 56 of 62 STEC isolates and did not detect Stx in any of the 29 non-STEC isolates. The PRM assay successfully determined the Stx2 subtype in 32 of 46 Stx2-positive isolates. By applying a targeted proteomics assay, we were able to simultaneously detect Stx toxins 1 and 2 and subtype Stx2 into six toxin subgroups in Stx2-positive isolates. / February 2017

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