The number and types of diagnostic ions obtained by infrared multiphoton dissociation (IRMPD) and collision induced dissociation (CID) were evaluated for supercharged peptide ions created by electrospray ionization of solutions spiked with mnitrobenzyl alcohol. IRMPD of supercharged peptide ions increased the sequence coverage compared to that obtained by CID for all charge states investigated. Multiply charged, N-terminally derivatized peptides were subjected to electron transfer reactions to produce singly charged, radical species. Upon subsequent “soft” CID, highly abundant z-type ions were formed nearly exclusively, which yielded simplified fragmentation patterns amenable to de novo sequencing methods. Furthermore, the simplified series of z ions were shown to retain labile phosphoric acid moieties. Infrared multiphoton dissociation (IRMPD) was implemented in a novel dual pressure linear ion trap for rapid “top-down” proteomics. Due to secondary dissociation, IRMPD yielded product ions in significantly lower charge states as compared to CID, thus facilitating more accurate mass identification and streamlining product ion assignment. This outcome was especially useful for database searching of larger proteins (~29 kDa) as IRMPD substantially improved protein identification and scoring confidence. Also, IRMPD showed an increased selectivity towards backbone cleavages N-terminal to proline and C-terminal to acidic residues (especially for the lowest precursor charge states). Ultraviolet photodissociation (UVPD) at 193 nm was implemented on a linear ion trap mass spectrometer for high-throughput proteomic workflows. Upon irradiation by a single 5 ns laser pulse, efficient photodissociation of tryptic peptides was achieved with production of a, b, c, x, y, and z sequence ions, in addition to immonium ions and v and w side-chain loss ions. The factors that influence the UVPD mass spectra and subsequent in silico database searching via SEQUEST were evaluated. 193 nm ultraviolet photodissociation (UVPD) was employed to sequence singly and multiply charged peptide anions. Upon dissociation by this method, a-/x-type, followed by d and w side-chain loss ions, were the most prolific and abundant sequence ions, often yielding 100% sequence coverage. LC-MS/UVPD analysis using high pH mobile phases yielded efficient characterization of acidic peptides from mitogen-activated protein kinases. / text

published_or_final_version / abstract / toc / Botany / Master / Master of Philosophy

published_or_final_version / abstract / toc / Zoology / Master / Master of Philosophy

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No description available.

Specialized metabolism (secondary metabolism) in glandular trichomes of sweet basil (Ocimum basilicum L.) and accumulation of specialized metabolites (secondary metabolites) in rhizomes of turmeric (Curcuma longa L.) was investigated using proteomic and metabolomic approaches, respectively. In an effort to further clarify the regulation of metabolism in the glandular trichomes of sweet basil, we utilized a proteomics-based approach that applied MudPIT (multidimensional protein identification technology) and GeLC-MS/MS (gel enhanced LC-MS/MS) to protein samples from isolated trichomes of four different basil lines: MC, SW, SD, and EMX-1. Phosphorylation, ubiquitination and methylation of proteins in these samples were detected using X!tandem. Significant differences in distribution of the 755 non-redundant protein entries demonstrated that the proteomes of the glandular trichomes of the four basil lines were quite distinct. Correspondence between proteomic, EST, and metabolic profiling data demonstrated that both transcriptional regulation and post-transcriptional regulation contribute to the chemical diversity. One very interesting finding was that precursors for different classes of terpenoids, including mono- and sesquiterpenoids, appear to be almost exclusively supplied by the MEP (2-C-methyl-D-erythritol 4- phosphate) pathway, but not the mevolonate pathway, in basil glandular trichomes. Our results suggest that carbon flow can be readily redirected between the phenylpropanoid and terpenoid pathways in this specific cell type. To investigate the impact of genetic, developmental and environmental factors on the accumulation of phytochemicals in rhizomes of turmeric, we performed metabolomic analysis in a 2x2x4 full factorial design experiment using GC-MS, LC-MS, and LC-PDA. Our results showed that growth stage had the largest effect on levels of the three major curcuminoids. Co-regulated metabolite modules were detected, which provided valuable information for identification of phytochemicals and investigation of their biosynthesis. Based on LC-MS/MS data, 4 new diarylheptanoids were tentatively identified in turmeric rhizomes using Tandem-MSASC, a home-made software tool that automatically recognizes spectra of unknown compounds using three approaches. Based on our metabolomic results, we proposed two new strategies, “metabolomics-guided discovery” and “correlation bioassay”, to identify bioactive constituents from plant extracts based on information provided by metabolomic investigation.

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.

Among the factors important for maintaining productivity of recombinant proteins in mammalian cells, culture lifetime, cell density and cell viability are three simple but essential aspects that can greatly influence the final yield. During cell culturing, the degradation of environmental conditions such as nutrient depletion and accumulation of toxic waste products, often lead to premature apoptotic cell death in cultures and suboptimal protein yield. Although apoptosis has been extensively researched, the changes in the whole cell proteome during prolonged cultivation, where apoptosis is a major mode of cell death, have not been examined. The work presented in this thesis is the first whole cell proteome analysis of non-induced apoptosis in mammalian cells. Flow cytometry analyses of the level of activated executioner caspases, caspase 3 and 7, demonstrated the onset of apoptosis in CHO batch cultures after the exponential phase. The monitoring of apoptotic cell death assesses the culture conditions at different time points and allows the association of changes in the protein abundances to the degradation of culture conditions, in particular the degree of apoptosis in the whole cultures. The detection of activated caspase 8 and caspase 9, which trigger the extrinsic and intrinsic pathway respectively, has shown that the onset of apoptosis in CHO cells during prolonged cultivation predominantly is via the intrinsic pathway. To examine the proteomic changes in a monoclonal antibody-producing CHO cell culture at various phases of a batch culturing process, a differential in gel electrophoresis proteomic approach was employed in this study. CHO protein samples at four time points during cultivation were compared. A total of 40 differentially expressed protein spots were successfully identified by mass spectrometry sequencing, resulting in 28 unique protein identifications. These proteins include four structural proteins of the cytoskeleton, ten endoplasmic reticulum and cytosolic chaperones and folding proteins, seven metabolic enzymes and seven other proteins of varied function. The cleavage of cytoskeletal proteins is a known consequence of apoptosis and the activation of executioner caspases. On the other hand, the induction of seven ER chaperone and foldases is a solid indication for the onset of unfolded protein response, which is triggered by cellular and ER stresses, many of which are present during prolonged batch cultures. In addition, the upregulation of six glycolytic enzymes and another metabolic protein emphasizes a change in the energy metabolism likely occurred when culture conditions degraded and apoptosis advanced. Interestingly, although a significant portion of proteins identified are well known housekeeping proteins, recent studies have shown that many of them exhibit a wide variety of other roles, including apoptosis regulation and execution. Overall, this study shows that the most drastic changes in aging CHO cultures, where apoptosis is known to be part of, involve the onset of UPR and upregulation of proteins catalyzing glucose metabolism.

One of the best ways to diagnose breast cancer early or to predict therapeutic response is to use serum biomarkers. Unfortunately, for breast cancer, we do not have effective serological biomarkers. We hypothesized that novel candidate tumor markers for breast cancer may be secreted or shed proteins that can be detected in tissue culture supernatants of human breast cancer cell lines. A two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) strategy was utilized to identify and compare levels of extracellular and membrane-bound proteins in the conditioned media. Proteomic analysis of the media identified in excess of 600, 500 and 700 proteins in MCF-10A, BT474 and MDA-MB-468, respectively. We successfully identified the internal control proteins, kallikreins 5, 6 and 10 (ranging in concentration from 2-50 µg/L), as validated by ELISA and confidently identified HER-2/neu in BT474 cells. Sub-cellular localization was determined based on Genome Ontology (GO) for the 1,139 proteins, of which 34% were classified as extracellular and membrane-bound. Tissue specificity, functional classifications and label-free quantification were performed. The levels of eleven promising molecules were measured in biological samples to determine its discriminatory ability for control versus cases. This screen yielded activated leukocyte cell adhesion molecule (ALCAM) as a promising candidate. The levels of ALCAM, in addition to the classical breast cancer tumor markers carbohydrate antigen 15-3 (CA 15-3) and carcinoembryonic antigen (CEA) were examined in 300 serum samples by quantitative ELISA. All three biomarkers effectively separated cancer from non-cancer groups. ALCAM, with area under the curve (AUC) of 0.78 [95% CI: 0.73, 0.84] outperformed CA15-3 (AUC= 0.70 [95% CI: 0.64, 0.76]) and CEA (AUC= 0.63 [95% CI: 0.56, 0.70]). The incremental values of AUC for ALCAM over that for CA15-3 were statistically significant (Delong test, p <0.05). Serum ALCAM appears to be a new biomarker for breast cancer and may have value for disease diagnosis.

Mitochondria are eukaryotic organelles derived in evolution from within the ? subdivision of Proteobacteria. Although mitochondria are structurally and metabolically complex, modern-day mitochondrial genomes (mtDNA) encode only a small number of RNAs and proteins predominantly involved in adenosine triphosphate (ATP) formation through electron transport coupled to oxidative phosphorylation, as well as translation of mtDNA-encoded proteins. In humans, only 13 of the >1000 polypeptides that constitute the complete mitochondrial protein complement (proteome) are encoded in mtDNA; the remainder is encoded by nuclear DNA (nuDNA). It is therefore imperative to comprehensively catalog nuDNA-encoded mitochondrial proteins in order to understand holistically the evolution of mitochondria. Mitochondrial proteome investigations of animals, fungi and land plants have dramatically altered our conception of mitochondrial evolution: in contrast to mtDNA-encoded proteins, few nuDNA-encoded mitochondrial proteins are demonstrably derived from the eubacterial progenitor of mitochondria, and many are found only in eukaryotes. Notably, however, little is known about the mitochondria of eukaryotic microbes (protists), which constitute the bulk of biochemical and genetic diversity within the domain Eucarya. The proteomic characterization of protist mitochondria is therefore crucial to fully elucidating mitochondrial function and evolution. Employing tandem mass spectrometry (MS/MS), I have analyzed highly purified mitochondria from Acanthamoeba castellanii (Amoebozoa). In combination, nearly 750 nuDNA- and mtDNA-encoded proteins were identified. These data were used to catalog metabolic pathways and protein complexes, and to infer functional and evolutionary profiles of A. castellanii mitochondria. My analyses suggest that while A. castellanii mitochondria have many features in common with other eukaryotes, they possess several novel attributes and pronounced metabolic versatility. An analysis of the A. castellanii electron transport chain (ETC) was also performed, utilizing a combination of blue native polyacrylamide gel electrophoresis (BN-PAGE), MS/MS and bioinformatic queries. A significant proportion of A. castellanii ETC proteins was identified, yielding several insights into ETC evolution in eukaryotes. Lastly, I present two unusual cases of ‘split’ mitochondrial proteins: the iron-sulfur subunit SdhB of succinate:ubiquinone oxidoreductase (Complex II), in the phylum Euglenozoa and Cox1 of cytochrome c:O2 oxidoreductase (Complex IV) in various eukaryotes, including A. castellanii. Functional and evolutionary implications of these findings are discussed.