Browsing by Subject "Proteomics"
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Item Blending of Procream with Functionally Enhanced Whey Protein Concentrate: A Structure-Function Approach to Whey Coproduct Utilization(2020-12) Hinnenkamp, ChelseyWhey protein ingredients namely isolates (WPI), concentrates (WPC), and hydrolysates (WPH), as nutritionally complete protein sources with versatile functionality, are key players in the global protein ingredient market. However, the production of these high protein ingredients generates coproducts, such as Procream, a phospholipid-rich coproduct, that are underutilized due to lower protein content and functionality. A potential valorizing opportunity for Procream is to blend it with functionally enhanced WPC for high value applications like microencapsulation of oils rich in omega 3 fatty acids, such as fish oil. By leveraging inherent characteristics, blending Procream with hydrolyzed whey protein has the potential to improve interfacial activity and antioxidant activity of whey protein, which have an augmentative effect on microcapsule stability and overall success. There exists a need to not only understand the performance of these blended systems in microcapsule systems but to understand the interactions between Procream and intact and hydrolyzed WPC driving that performance. This project employed a combination of proteomics and bioinformatics to better characterize whey protein hydrolysis and relate protein structural characteristics with inherent properties of the blends to understand the impact of blending on emulsion and encapsulation systems. Thus, this “molecular-to-applied” approach provided an overall framework for increasing the value of underutilized dairy whey streams.Item Defining AMD disease mechanisms: a comparative analysis of proteins and mitochondrial DNA(2010-08) Karunadharma, Pabalu Pussellage RanminiAge-related macular degeneration (AMD) is the leading cause of blindness in the elderly in the developed world. Current treatments are limited due to our inadequate understanding of the pathogenic events leading to AMD. Early clinical symptoms occur in the retinal pigment epithelium (RPE), suggesting RPE as the potential site of defect in AMD. This research evaluated the RPE proteome and mitochondrial DNA (mtDNA) to test the hypothesis that molecular changes in the RPE contributes to AMD. Human donor eyes categorized into four progressive stages of AMD were utilized in these investigations. Two proteomic analyses using 2D gel electrophoresis and mass spectrometry were performed to define changes in the RPE proteome. In the first proteomic study, analysis of the mitochondrial proteome revealed significant changes that suggested potential damage to mtDNA with AMD. These results prompted an analysis of mtDNA lesions associated with aging and AMD. These results suggest a potential link between mt dysfunction due to increased mtDNA damage and altered proteins and AMD pathology. In the second study, we tested the hypothesis that mt dysfunction is communicated to the nucleus via retrograde signaling and consequently alters the protein profile to reflect a major shift in metabolism and stress response. Our results suggest not only adjusted metabolism, response to stress and cellular redox regulation but also show major differences in the protein profile with AMD compared to aging. In summary, our investigations distinguished between normal and pathologic aging by identifying key macromolecules and pathways affected with each process. Furthermore, our data indicate a potential link between mitochondrial dysfunction and AMD pathology, thus providing a point of intervention for the treatment of AMD.Item Fundamentals of a systems biology approach to In Vitro tissue growth(2013-05) Beck, Richard JosephTissue engineering needs a paradigm shift in order to generate clinically useful products. The field has yet to regularly produce implantable tissue-engineered products. The conventional manner in which input stimuli are applied without consideration of current cellular activity level is certainly suboptimal. The objective of this line of research is to produce a method for rationally choosing input stimuli that drive the cells toward optimal tissue growth. Transient phosphorylation of signaling proteins after a perturbation in stimuli contains biological information concerning downstream tissue growth. The overall project aims to build a statistical model predictive of tissue growth via information of the upstream phosphoproteome minutes after a change in stimuli. The validity of such a statistical model can be tested based on its utility to direct tissue growth: stimuli will be chosen on the basis of which corresponding phosphoproteome profile(s) is predicted to yield the best downstream tissue growth; this can be directly compared to conventional tissue engineering methods. This doctoral project focused on obtaining sample types and tailoring methods appropriate for a systems biology and statistical approach, especially in regard to the label-free quantification of phosphopeptide enrichments. Neonatal human dermal fibroblasts (nhDF) were expanded to near confluence, at which point basal medium for tissue production was applied. After two days, nhDF were perturbed with basal medium supplemented with 1 or 10 ng/mL TGF-β1. Cells were harvested at 10, 20, or 30 minutes for intracellular proteins. Resultant protein lysates were digested to peptides via trypsin and enriched for phosphopeptides via Iron Immobilized Metal Affinity Chromatography (IMAC). Phosphopeptide enrichments were analyzed by tandem mass spectrometry. A total of 1689 peptides were both identified with phosphorylation and quantified using distinct algorithms. Under strict statistical tests, 22 of these peptides were found to differ between treatments/time. Corresponding downstream collagen deposition was also found to differ between treatments. These results indicate that the type of quantitative data needed for the overall project can be acquired. The methods developed can be used in finding a statistical relationship between tissue growth and upstream phosphoproteome profiles.Item A Fungal secretome tailored to enable a radical (oxidative) wood decay mechanism in brown rot fungi(2021-07) Castano Uruena, JesusWood is one of the most important carbon sinks on earth, and it is composed mainly of cellulose, hemicellulose, and lignin, which together form what is known as the lignocellulosic complex. The lignin component in wood is highly recalcitrant and prevents wood from being degraded by most organisms. Wood degrading fungi have evolved mechanisms to handle the lignin barrier effectively and harness the carbon present in wood, which makes them also plausible biological templates for industry-related applications such as the production of biofuels. However, there are still several knowledge gaps about how fungi orchestrate the complex mechanisms behind wood decay, which prevents further usage of these fungi in biotechnological fields. Wood degrading fungi were initially classified by the physical properties of the rotted wood as white, brown, and soft rot fungi – with brown and white rot fungi being the most efficient. These properties are correlated with important genetic and regulatory differences that distinguish the different modes of decay. Recently, it was shown that brown rot fungi evolved from white rot fungi losing an important number of carbohydrate-degrading enzymes (CAZy) and oxidoreductases. This loss was accompanied by regulatory changes that included the overexpression of retained CAZys, and the development of a two-step mechanism that segregated a Fenton-based oxidative phase from a hydrolytic phase in early and late wood decay, respectively. However, although some main differences between white and brown rot fungi have been identified, several details remain obscure. For example, it is unknown how brown rot fungi manage to produce highly oxidative and unspecific hydroxyl radicals while producing some glycosyl hydrolases necessary for the depolymerization of pectin and hemicellulose at early decay stages. It seems reasonable, that brown rot fungi could protect their enzymes by making them more naturally tolerant of reactive oxygen species (ROS) radicals than other wood degraders associated with a different rot type. Also, although transcriptomics and proteomics data suggest brown rot fungi use some Fenton chemistry at early decay, there is little information about how these fungi regulate the concentration of the chemical species that enable this chemistry. This dissertation contributes to widen the knowledge about fungal wood decay mechanisms, especially those used by brown rot fungi. For starters, by studying the wood decay progression with the brown rot fungus Rhodonia placenta, we found that this fungus displays different mechanisms to harness the use of ROS during wood decay without inflicting damage on itself. First, R. placenta controls the extracellular production of ROS by regulating the concentrations of H2O2 and Fe2+ in the media (avoidance mechanism). Second, this fungus presents a high antioxidant capacity as decay progresses, potentially to quench any possible leaks of ROS from earlier decay stages (suppression mechanism). Thirdly, several R. placenta secreted CAZys, important for early wood decay, displayed tolerance of high concentrations of ROS compared to the soft rot fungus Trichoderma reesei (an industrially relevant cellulase producer), which enables these enzymes to work under harsh operating conditions (tolerance mechanism). Collectively, this indicates that R. placenta uses avoidance, suppression and tolerance mechanisms, extracellularly, to complement intracellular differential expression, enabling this brown rot fungus to use ROS to degrade wood. After finding these results, we decided to incorporate a white rot fungus (Trametes versicolor) in the tolerance comparison and observed similar results, with tolerance of ROS only present in the side-chain hemicellulases of R. placenta. Proteomics analysis, meant to examine the presence of oxidative modifications induced after an in-vitro oxidative treatment, revealed that not only side-chain hemicellulases but also several other enzymes such as laccases, glutathione-S-transferases, and proteases were differentially tolerant of ROS compared to white and soft rot fungi. This suggest that the fungal secretome in brown rot fungi has been tailored as a whole to better endure the presence of ROS. Also, we found that several of the oxidative modifications that occurred in the glycosyl hydrolases of T. reesei and T. versicolor happened in amino acid residues in the vicinity of the active site, which can be linked to the loss of enzyme activity after the oxidative treatment. In a follow-up study addressing the effects of these modifications, we used molecular dynamics to understand the effect of some of the oxidative modifications in an α-L-arabinofuranosidase of T. reesei. Even though the number of oxidative modifications that we could include in the modeled protein was limited due to the lack of force field parameters, the simulations still showed some of the negative potential outcomes when a number of amino acid residues become oxidized. For instance, there were significant alterations of the conformational stability of the protein when oxidized, as evidenced by changes in root mean square deviation (RMSD) and principal component analyses (PCA) trajectories. Likewise, enzyme-ligand interactions such as hydrogen bonds were greatly reduced in quantity and quality in the oxidized protein. In addition, free energy landscape plots showed that there was a more rugged energy surface in the oxidized protein, implying a less favorable reaction pathway. Collectively, these results revealed the basis for the loss of function in the α-L-arabinofuranosidase of the commercially-relevant fungus T. reesei. Finally, metabolomics experiments were carried to find out whether the different modes of decay translated into signature metabolite profiles that could be assigned to either brown or white rot fungi. For this purpose, we cultured two brown rot fungi (R. placenta and Gloephylum trabeum) and two white rot fungi (Pleurotus ostreatus and T. versicolor). The results showed that brown rot fungi have a distinct metabolite pattern at late decay stages that clearly distinguish them from white rot fungi. Different metabolites such as organic acids, sugars, pyranones, and furanones contributed to this result. The finding of several pyranones and furanones being differentially more abundant in brown rot fungi was interesting since it agrees with the expansion of polyketide synthase genes in brown rot fungi. In contrast to brown rot fungi, we could not find a lot of similarities in white rot fungi as deduced by the PCA plots and heatmaps. However, some commonalities were evident such as the presence of galactitol as a potential biomarker, and the higher efficiency of these fungi at removing phenolic compounds originally found in undecayed wood. When focusing on both types of decay, we found that wood degrading fungi tend to accumulate sugars and carboxylic acids at late decay stages. Also, as fungal decay progresses, we observed an accumulation of different furans such as furfural or 5-methylfurfural in all fungi.Item The importance of being proportional: a paradigm shift for intensity-based label free relative quantification in mass spectrometry proteomics(2013-05) Van Riper, Susan KayeBiological variation not only provides insight into the molecular machinery of disease progression, but accurately informs clinicians about a patient's health status, both current and future. Researchers discover biological variation by conducting large scale comparative studies aimed at detecting differences in the molecular makeup (biomarkers) of samples in different states. Ideally suited for biomarkers are proteins because their cellular composition (proteome) and their degraded parts, endogenous peptides (peptidome), change in response to their environment and disease progression. For comparative proteomic studies, researchers commonly employ high performance liquid chromatography, coupled with electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS) and labeled quantification. However, intensity-based label free relative quantification (iLFRQ) is more desirable than labeled quantification because iLFRQ is more cost effective and does not limit the number of samples in a study. Unfortunately, iLFRQ for proteins, and especially peptides, is challenging. Here, I highlight three challenges. 1) I contend that the current relative abundance paradigm is ill-suited to detect biological variation using iLFRQ. 2) HPLC-ESI-MS/ MS analyses produce poorly repeatable and reproducible results, and current normalization methods fail to mitigate localized extraneous variability (complex variability in measurements) from transient stochastic events occurring during an HPLC-ESI-MS/MS run. 3) Current software frameworks report protein level quantification rather than peptide level quantification. To overcome these challenges, I offer three contributions. 1) I propose to use the proportionality paradigm for iLFRQ instead of the relative abundance paradigm. 2) Proximity-based Intensity Normalization (PIN), an embodiment of the proportionality paradigm, normalizes a peptide's signal intensity by constructing its temporal neighborhood and computing its relative proportion within that neighborhood. 3) RIPPER, a new software framework that reports normalized peptide signal intensities rather than protein intensities. Evaluation results demonstrate that PIN dominates current normalization methods in reducing systematic bias and complex variability. Furthermore, RIPPER/PIN finds statistically significant biological variation which is now falsely reported or missed. I expect the proportionality paradigm for iLFRQ, embodied in PIN, and implemented in RIPPER, to change the way researchers analyze HPLC-ESI-MS/MS experimental data. The upshot will, I expect, will be reproducibility and repeatability improved, and otherwise falsely reported or missed, statistically significant biological variation discovered.Item Improving the detection of carbonylated peptides by mass spectrometry via solid-phase hydrazide enrichment and selective labeling with Oxygen-18 (18O)(2010-01) Roe, Mikel RobertProtein carbonylation is a post-translational oxidative protein modification known to alter protein function and impair cellular mechanisms. It is a relatively complex modification, characterized by a variety of structurally distinct reactive carbonyls that target a number of amino acid residues and originate via several different oxidative mechanisms. While identification of specific carbonylated proteins by mass spectrometry has provided insight regarding the protein pathways and complexes affected, the specific sites of carbonyl modification, necessary for determining the oxidative mechanisms involved as well as for explaining any associated functional consequences, are not routinely identified due to the relatively low abundance of carbonylated proteins. To address this issue, a number of methods for enriching carbonylated peptides have been developed, all of which involve derivatization with bulky reagents that often complicate the identification of peptides by tandem mass spectrometry. As an alternative to these label-based approaches, I have developed a label-free method for enriching carbonylated peptides that is based on their selective capture and controlled release from a novel solid-phase hydrazide reagent (SPH). The value of the SPH reagent method is demonstrated using a yeast lysate treated with the reactive lipid carbonyl 4-hydroxynonenal (HNE), where the use of pulsed-Q-dissociation (PQD) and neutral-loss triggered MS/MS/MS was employed for the first time to assist the identification of HNE-modified peptides by mass spectrometry. To further improve the confidence by which carbonylated peptides are identified via mass spectrometry, a novel 18O-labeling method that selectively introduces an 18O molecule into the carbonyl oxygen of carbonylated peptides was developed. The resulting 18O isotope signature enables carbonylated peptide precursor ions and carbonylated MS/MS fragment ions to be tracked in the full-scan MS and MS/MS spectra, respectively, thus providing an independent validation of the MS/MS spectra matched to carbonylated peptides by proteomic database searching. The value of 18O-labeling for both improving the accuracy and measuring the efficiency of database-based identification of carbonylated peptides is demonstrated in an HNE-treated lysate from rat skeletal muscle homogenate. In conclusion, the development of the SPH reagent and the 18O-labeling method are useful tools for identifying carbonylated peptides in complex biological mixtures and represent important steps forward in the field of redox proteomics.Item Informing the Oral Squamous Cell Carcinoma Biomarker Search by Exudate Proteomics(2013-04) Kooren, Joel AllanOral cancer is the sixth most common cancer worldwide ahead of Hodgkin's lymphoma, leukemia, brain, stomach, or ovarian cancers, with about 41,000 Americans being diagnosed annually. More than 90% of oral cancers are oral Squamous cell carcinomas (OSCC). While the overall 5-year survival rate is about 60%, the survival rate when diagnosed early is higher than 80%. Currently the standard for diagnosis of OSCC is early visual detection of a suspicious oral lesion followed by scalpel biopsy with histology. However, the invasiveness, expense, and required expertise involved prevents consistent application on at risk individuals. Chapter 1 discusses the methods that are being investigated for sampling and discovering biomarkers of OSCC that address some of these limitations. Protein biomarkers contained in samples collected non-invasively and directly from at-risk oral premalignant lesions (OPML) would address current needs in a uniquely targeted fashion. Chapter 2 of this thesis describes work evaluating the potential of a novel method using commercial PerioPaper absorbent strips for the collection of oral lesion exudate fluid coupled with mass spectrometry based proteomics for OSCC biomarker discovery. This research focuses on demonstrating the feasibility of using oral lesion exudates in proteomic research, exploring the proteome of exudate samples, discriminating between exudates collected from clinically different sources, with supplemental table 1 showing which proteins distinguish healthy and OPML sources. Furthermore, to ensure that the best possible marker candidates are selected given clinical sample availability, multiple methods were explored enable and improve quantitative proteomic analysis of exudates in chapter 3 (Identified proteins in supplemental files 2 and 3). Our label-free quantitative proteomics strategy analyzed paired control and OPML exudates (figure 8), identifying differentially abundant proteins between sample types. Next, we selected several [exudate] differentially abundant proteins for testing in while saliva, comparing their relative abundance levels in healthy, OPML and oral Squamous cell carcinoma (OSCC) subjects. Two proteins, CK10 and A1AT, showed differences in saliva. Our results provide a demonstration of the value of tissue exudate analysis for guiding salivary biomarker discovery in oral cancer, as well as providing promising biomarker candidates for future evaluation.Item Integration of Biodescriptors and Chemodescriptors for Predictive Toxicology: A Mathematical / Computational Approach(University of Minnesota Duluth, 2001-08-28) Basak, Subhash Ci) Attempts have been made to develop quantitative biodescriptors to characterize the effects of chemicals on the proteomics patterns of cells. Applications of biodescriptors to proteomics patterns derived from normal liver cells and cells exposed to peroxisome proliferators showed that quantitative descriptors defined for D/D matrices are capable of rationalizing effects of different types of peroxisome proliferators on the cellular proteome. Such descriptors may find application in predicting the biochemical effects of toxicants from their proteomics patterns. ii) A novel approach to biodescriptor formulation has been taken, using the concept of partial ordering. The embedded graphs derived thereby have been used to develop new types of invariants for the quantification of proteomics maps. Biodescriptors developed and reported in the above two manuscripts show reasonable power of discriminating the proteomics patterns resulting from different toxicants. Biodescriptors already developed in this project and those currently under development will provide a battery of such parameters for predictive toxicology. When a certain number of (say n) of such descriptors are calculated for a proteomics map, the map is characterized by a vector consisting of n entries. Elements of such vectors may be used in: a) predicting toxicity using statistical methods such as PCR, PLS, RR or non-linear methods such as neural networks; b) classifying chemicals into various subsets; or c) quantifying the similarity / dissimilarity of toxicants. In light of our earlier study on the prediction of the mode of action (MOAs) of toxicants from chemodescriptors, it is realistic to speculate that the battery of biodescriptors will be useful in predicting the MOAs of toxicants. Chemodescriptors: i) Chemodescriptors calculated by POLLY and Molconn-Z have been used to predict the cell level toxicity data of halocarbons determined at the Wright Patterson AFB laboratory by Kevin Geiss (unpublished results). The high quality of these models indicate that similar models using calculated chemodescriptors may find application in the prediction of cellular toxicity arising from exposure to pollutants and xenobiotics. ii) In collaboration with Dr. Hawkins, PCR, RR and PLS analyses have been applied-to the prediction of the property / activity / toxicity of various groups of chemicals from their structural descriptors, vis., topostructural indices, topochemical indices, 3-D or shape parameters, and semi-empirical quantum chemical descriptors. This research has resulted in the formulation of robust and useful QSTR methods. iii) Successful quantitative structure-toxicity relationship (QSTR) models have been developed for the exposure assessment of volatile organic chemicals (VOCs), such as halocarbons, using chemodescriptors with the ridge regression statistical technique. These models will be useful in the physiologically-based pharmacokinetic modeling of VOCs. iv) Novel molecular shape descriptors have been developed and applied to predicting properties dependant on molecular shape. These new molecular shape parameters will be useful in QSAR/QSTR studies where molecular shape is a critical determinant of ligand-biotarget interaction in the cellular milieu. v) New methods have been developed to characterize DNA sequences and their modifications as a result of exposure to toxicants using matrix invariants. Such invariants were defined from newly formulated matrices used to represent macromolecular sequences in a condensed manner. These invariants will be useful tools for research in genomics and bioinformatics.Item Mass Spectrometry-Based Characterization, Quantitation, And Repair Investigations Of Complex DNA Lesions(2018-03) Groehler IV, ArnoldDNA is constantly under the threat of damage by various endogenous and exogenous agents, leading to the structural modification of nucleobases (DNA adducts). These DNA adducts can range from smaller nucleoside monoadducts and exocyclic adducts, to the helix distorting and super-bulky DNA-DNA cross-links and DNA-protein cross-links. If not repaired, DNA adducts can inhibit crucial biological processes such as DNA replication, leading to adverse consequences such as mutagenesis and carcinogenesis. Therefore, understanding the atomic connectivity, extent of formation, and repair of DNA adducts is crucial to fully elucidating the biological consequences of the adduct. DNA-protein cross-links (DPCs) are ubiquitous, super-bulky DNA lesions that form when proteins become irreversibly trapped on chromosomal DNA. The structural complexity of cross-linking and the diversity of proteins susceptible to DPC formation represents significant challenges to studying the biological consequence of these adducts. In the first part of the thesis, we identified the protein constituents, structural characterized and quantified, and investigated the repair mechanism of bis-electrophile (Chapter 2) and reactive oxygen species (ROS, Chapters 3 and 4)-induced DPCs. In Chapter 2, we investigated DPC formation after exposure to N,N-bis-(2-chloroethyl)-phosphorodiamidic acid (phosphoramide mustard, PM) and N,N-bis-(2-chloroethyl)-ethylamine (nornitrogen mustard, NOR), the two biologically active metabolites of the antitumor agent cyclophosphamide. A mass spectrometry-based proteomics approach was employed to characterize the protein constituents of PM- and NOR-mediated DNA-protein cross-linking in human fibrosarcoma (HT1080) cells. HPLC-ESI+-MS/MS analysis of proteolytic digests of DPC-containing DNA from NOR-treated cells revealed a concentration-dependent formation of N-[2-[cysteinyl]ethyl]-N-[2-(guan-7-yl)ethyl]amine (Cys-NOR-N7G) conjugates, confirming that it cross-links cysteine thiols of proteins to the N-7 position of guanines in DNA. A sensitive and accurate Cys-NOR-N7G isotope dilution tandem mass spectrometry assay was developed to quantify PM-induced DPC formation and repair in mammalian cells proficient or deficient in a DNA repair pathway. In Chapters 3, we employed the model of left anterior descending artery ligation/reperfusion surgery in rat to show that ischemia/reperfusion injury is associated with the formation of hydroxyl radical-induced DNA-protein cross-links (DPCs) in cardiomyocytes. Mass spectrometry based experiments revealed that these conjugates were formed by a free radical mechanism and involved thymidine residues of DNA and tyrosine side chains of proteins (dT-Tyr). Quantitative proteomics experiments utilizing Tandem mass tags (TMT) revealed that radical-induced DPC formation increase after LAD-ligation/reperfusion compared to the control sham surgery. Using the developed dT-Tyr nanoLC-ESI+-MS/MS assay, we investigated the role of the metalloprotease Spartan (SPRTN) in the repair of radical-induced DPCs (Chapter 4). Analysis of the brain, liver, heart, and kidneys of wild type (SPRTN+/+) and hypomorphic (SPRTN f/-) mice revealed a 1.5 – 2-fold increase in dT-Tyr in the hypomorphic mice, providing direct evidence that Spartan plays a role in the repair of radical-induced DPCs. Finally, we investigated the formation of formamidopyrimidine (FAPy) adducts after exposure to 3,4-epoxybutene, an epoxide metabolite of the known carcinogen 1,3-butadiene (Chapter 5). We successfully synthesized and structurally characterized a novel BD-induced DNA adduct EB-FAPy-dG, and developed a sensitive isotope dilution tandem mass spectrometry assay for its detection in vitro and in cells. To our knowledge, this is the first report of a BD-induced FAPy adduct, and future studies will examine whether BD-induced FAPy adducts In summary, during the course of this Thesis, we utilized mass spectrometry-based proteomics techniques to identify the proteins susceptible to PM- and ROS-induced DPC formation. After structurally characterizing the atomic connectivity of these adduces, we developed sensitive and accurate isotope dilution tandem mass spectrometry assays to perform absolute quantitation of PM- and ROS-induced DPC formation in cells and tissues. These assays were further utilized to begin investigating the repair mechanism of DPCs in cells and tissues, including providing direct evidence that the metalloprotease Spartan is involved in the repair of radical-induced DPCs. Finally, we detected EB-FAPy-dG formation in vitro and in vivo, the first evidence of 1,3-butadiene induced formamidopyrimidine formation.Item Mass Spectrometry-Centered Multi-Omic Applications In The Analysis Of Inflammation And Exposure(2022-10) Rajczewski, AndrewBottom-up proteomics represents an exciting technology which has found great utility across multiple fields of biological research. Using high-resolution mass spectrometry coupled with sophisticated bioinformatic software applications, bottom-up proteomics affords qualitative and quantitative information that reflects the actual molecular phenotype of a system in ways that next-generation sequencing technologies do not. Despite this, there are also blind spots in conventional bottom-up proteomics experiments; many of these limitations can be abrogated via the integration of bottom-up proteomics with other forms of ‘omics technologies and data. Through supplemental bioinformatic workflows, putative identifications of non-canonical peptides or non-host peptides (e.g microbial, viral) can be validated. The use of RNA-Seq data can be used to generate protein sequence databases files for proteogenomics, where non-canonical peptide sequences arising from genomic mutations, translocations, aberrant splicing events, etc. which are invisible to conventional proteomics experiments can be readily detected. In addition, by integrating and directly comparing proteomics data with transcriptomic data, levels of epigenetic and/or post-transcriptional control can be examined in a system in response to stimuli of interest that are invisible to both technologies. These supplemental approaches expand the power of bottom-up proteomics to where it becomes a highly useful tool for studying systems in which multiple levels of gene product expression response are regulated, including viral infections, tissues undergoing long-term inflammation, and exposure to endogenous and exogenous electrophiles.The first chapter of this thesis provides an overview of the current state of proteomics-centered multi-omic technologies and their potential utility in biological research. The review begins with outlining the improvements to bottom-up proteomics technologies which have enabled a greater depth of information, such as isobaric peptide tagging, data-independent acquisition, ion mobility applications, and other instrumental advances. From there, bioinformatic tools are discussed that are of use in the analysis of proteomics data, with a focus on integrating mass spectrometry-based data with other forms of ‘omics data. Specific applications of using RNA-Seq data to inform the data analysis of proteomics, proteogenomics, are also addressed. The chapter concludes with notable instances of proteomics-centered multi-omics analysis as well as potential future applications of these technologies. The second chapter of this thesis addresses the analysis of open-source proteomics datasets with customized multi-omic bioinformatic tools to determine the optimal targets for the detection of SARS-CoV-2 infections in patients. Through the use of in vitro and patient datasets, a panel of potential viral peptides were established, was used to search patient datasets. Ultimately, we found four peptides in the viral nucleocapsid which were reliably detected in patients and were unique to the SARS-CoV-2 virus. The third chapter of this thesis utilizes proteogenomics workflows to examine the consequences of long-term inflammation in the proximal colon tissue of a murine model of inflammatory bowel disease. In this model, Rag2-/-Il-10-/- mice were subjected to five months of Helicobacter hepaticus infection in their colon to trigger chronic infection. For these analyses, RNA-Seq data acquired from these test subjects in an earlier study were converted into a FASTA protein sequence database containing variant sequences stemming from this treatment. Through quantitative proteogenomic analysis we noted significant changes in abundances of proteins consistent with an inflammatory response; through bioinformatic analysis of our data, we also validated and confirmed the presence of 39 non-canonical peptides across our infected and control samples, demonstrating the importance of validation of targets of interest in proteogenomic studies. The fourth chapter of this thesis integrates multiple levels of ‘omic analysis to examine the effects of inflammation on murine Type II pneumocytes, a constituent cell within alveoli which serve as the source of lung adenocarcinomas. Mice were exposed to intranasal dosages of LPS or to whole-body cigarette smoke exposure for variable amounts of time before being sacrificed and the Type II cells isolated for analysis. Bottom-up proteomics of cells subjected to LPS for 3 weeks revealed a phenotype consistent with inflammation; this was reinforced when compared to transcriptomic data from the same cells, as these showed. Global proteomics analyses of Type II pneumocytes of mice subjected to exposure to cigarette smoke revealed significant changes in protein abundances occurring after after 10 weeks of exposure with a 4-week recovery period post exposure, encompassing biological processes such as nucleotide and amide metabolism as well as synthesis and acetyl CoA synthesis, which demonstrated a greater degree of disjuncture with the associated RNA-Seq data as compared to our LPS study. The fifth chapter of this thesis examines the utility of bottom-up proteomics in examining the formation of amino acid adducts in hemoglobin, which serves as a valuable reservoir for exposome studies due to its longevity and high concentration within the blood. We were able to validate the presence of 4-hydroxybenzyl adducts at the N-terminal valine of hemoglobin and demonstrate their formation at nucleophilic side chains within the protein. In addition, we compared bottom-up proteomics to the FIRE method, an experimental procedure which serves to isolate N-terminal adducts in hemoglobin for LC-MS detection, with a panel of electrophilic compounds incubated with blood at various concentrations and incubation times. Ultimately, we found that a proteomics-based approach to untargeted adductomics allowed for the detection of novel adducts at a number of sites within hemoglobin. In this thesis we have applied mass spectrometry-based ‘omics technologies to complicated biological systems. We have utilized publicly available proteomics datasets to determine the optimal targets for MS-based detection of SARS-CoV-2 in patient samples. Using RNA-Seq data, we performed quantitative proteogenomic analysis of a murine model of IBD and validated the presence of several non-canonical peptide sequences. We also used multi-omic analyses to compare LPS-driven and cigarette smoke-driven inflammation of murine Type II pneumocytes. Finally, we demonstrated the utility of bottom-up proteomics in detecting and characterizing adducts in human hemoglobin as a record of the exposome. Overall, this work expands the utility of proteomics-centered analyses in characterizing systems subjected to viral infection, inflammatory stimuli, and exposure to environmental contaminants.Item Multi-omic analysis of hibernator skeletal muscle and calcium handling regulation(2016-05) Anderson, KyleMammalian hibernation is a strategy employed by many species to survive fluctuations in resource availability and environmental conditions. Hibernating mammals endure conditions of dramatically depressed heart rate, body temperature, and oxygen consumption; yet do not show the typical pathological responses. Because of the high abundance and metabolic cost of skeletal muscle, not only must it adjust to the constraints of hibernation, but it is also positioned to play a more active role in the initiation and maintenance of the hibernation phenotype. My M.S. thesis research has primarily focused on the generation and analysis of two high-throughput ‘omics screens in thirteen-lined ground squirrel skeletal muscle. A transcriptomic analysis using Illumina HiSeq2000 technology identified 1,466 differentially expressed genes throughout their circannual cycle. This RNAseq data allowed for greater protein identifications in an iTRAQ based proteogeomic analysis of the same animals. Of the 1,563 proteins identified by this proteogenomic approach, 232 were differentially expressed. These data support previously reported physiological transitions, while also offering new insight into specific mechanisms of how hibernator muscles might be reducing nitrogenous waste, preserving mass and function, and signaling to other tissues. Sarcolipin is a specific gene of interest that shows a 10-fold difference in expression between hibernation and spring collection points. Because of sarcolipin’s interaction with the SERCA pump and their role in muscle-based thermogenesis and calcium homeostasis bioenergetics, I have developed methods to measure the consequences of this differential expression.Item Novel binding partners of Mu-opioid receptor and their regulatory roles.(2009-12) Ge, XinG-protein-coupled receptors (GPCRs) represent a super-family of proteins in the human genome (>900), which include at least one third of current drug targets. Associated proteins of GPCRs consist of the down-stream signaling pathway, which convert the external stimulus to the final signal of cellular function change. Some useful methods have been used to explore the sophisticated network of GPCR-associated proteins, such as yeast-two hybridization and GST fusion protein pull-down assay. However, in both methods, only one or two domains of the receptor were used to construct a fusion protein for identifying scaffolding proteins. This cannot reflect the conditions in which an agonist/antagonist mediates the opioid receptors' conformational change that leads to protein recruitment. To identify the binding partners of MOR, a member of GPCR rhodopsin subfamily that clarified to be important in regulating drug tolerance and addiction, we purified MOR complexes from (His)6-tagged MOR stably expressing neuroblastma neuro2A (N2A) cells. Combine with Mass Spectrometry and LC MS/MS (Liquid chromatography-electrospray ionization tandem mass spectrometry), some novel MOR binding partners were found. Two of them are studied further about their important roles in regulating MOR functions. Ribophorin I (RPNI), a component of the oligosaccharidetransferase complex, could directly interact with MOR. RPNI can be shown to participate in MOR export by the intracellular retention of the receptor after siRNA knocking-down of endogenous RPNI. Over-expression of RPNI rescued the surface expression of the MOR 344KFCTR348 deletion mutant (C2) independent of calnexin. Furthermore, RPNI regulation of MOR trafficking is dependent on the glycosylation state of the receptor, as reflected in the inability of over-expression of RPNI to affect the trafficking of the N-glycosylation deficient mutants, or GPCR such as k-opioid receptor that has minimal glycosylation sites. Hence, this novel RPNI chaperone activity is a consequence of N-glycosylation-dependent direct interaction with MOR. G protein-regulated inducer of neurite outgrowth 1 (GRIN1) can influence MOR lipid raft location by tethering the receptor with the heterotrimeric G protein ?-subunit. GST fusion pull-down and receptor mutational analyses indicated the 267GSKEK271 sequence within the MOR 3rd intracellular loop was involved in interacting with the GRIN1 sequence distinct from that participated in the G? binding. The uncoupling of G? from MOR with PTX reduced the amount of GRIN1 co-immunoprecipitated with MOR while the amount of GRIN1 coimmunoprecipitated with G? was unchanged. Furthermore, over-expression of GRIN1 significantly enhanced the amount of MOR in lipid raft and the receptor signaling magnitude as measured by Src kinase activation. Such increase in MOR signaling was demonstrated further by determining the GRIN1-dependent neurite outgrowth. In contrast to minimal neurite outgrowth induced by etorphine in control cells, over-expression of GRIN1 and the increase in GRIN1-MOR interaction resulted in the increase in etorphine- and not-morphine-induced neurite outgrowth in the neuroblastoma N2A cell that was PTX sensitive. Knocking-down of endogenous GRIN1 by siRNA attenuated the agonist-induced neurite outgrowth. Disrupting lipid raft by M?CD also blocked neurite outgrowth. Hence, by serving as a tether between G? and MOR, GRIN1 stabilizes the receptor within the lipid rafts and potentiates the receptor signaling in the neurite outgrowth process.Item Optimization Of Mass Spectrometry-Based Proteomic Identification Of Ovarian Cancer Biomarkers From Residual Pap Test Samples(2018-11) Rogers, AnnaCurrent screening methods to detect ovarian cancer are not adequately sensitive or specific to detect early disease. In contrast, cervical cancer screening with Pap tests has been routinely performed for decades. The liquid-based Pap test involves collecting cervical cells and placing them into an alcohol-based fixative for later identification of premalignant and malignant cells. We hypothesize that proteins shed by ovarian cancer cells are detectable in residual Pap test fixatives by mass spectrometry (MS)-based proteomic techniques. This biospecimen source is ideal for biomarker discovery since the samples are routinely collected, derived from a site near the tumor, and may not contain high abundance proteins that mask potential biomarkers. We have optimized a protocol for obtaining “mock Pap tests” from patients with ovarian cancer and patients with benign or normal conditions. Multiple workflows were tested to determine optimal methods of protein sample preparation. The results suggest that liquid-based Pap tests can be used for the identification of ovarian cancer protein biomarkers.Item Protein expression profile of rat type two alveolar epithelial cells during hyperoxic stress and recovery(2013-05) Bhargava, ManeeshRationale: In rodent model systems, the sequential changes in lung morphology resulting from hyperoxic injury are well characterized, and are similar to changes in human acute respiratory distress syndrome (ARDS). In the injured lung, alveolar type two (AT2) epithelial cells play a critical role restoring the normal alveolar structure. Thus characterizing the changes in AT2 cells will provide insights into the mechanisms underpinning the recovery from lung injury. Methods: We applied an unbiased systems level proteomics approach to elucidate molecular mechanisms contributing to lung repair in a rat hyperoxic lung injury model. AT2 cells were isolated from rat lungs at predetermined intervals during hyperoxic injury and recovery. Protein expression profiles were determined by using iTRAQ® with tandem mass spectrometry. Results: Of 959 distinct proteins identified, 183 significantly changed in abundance during the injury-recovery cycle. Gene Ontology enrichment analysis identified cell cycle, cell differentiation, cell metabolism, ion homeostasis, programmed cell death, ubiquitination, and cell migration to be significantly enriched by these proteins. Gene Set Enrichment Analysis of data acquired during lung repair revealed differential expression of gene sets that control multicellular organismal development, systems development, organ development, and chemical homeostasis. More detailed analysis identified activity in two regulatory pathways, JNK and miR 374. A Short Time-series Expression Miner (STEM) algorithm identified protein clusters with coherent changes during injury and repair. Conclusion: Coherent changes occur in the AT2 cell proteome in response to hyperoxic stress. These findings offer guidance regarding the specific molecular mechanisms governing repair of the injured lung.Item Proteomic Studies in Acute Respiratory Failure(2015-08) Bhargava, ManeeshRespiratory failure is a syndrome of impaired gas exchange resulting in abnormal oxygenation and carbon dioxide elimination. Lung damage seen in Acute Respiratory Distress Syndrome (ARDS) and Idiopathic Pneumonia Syndrome (IPS) cause acute respiratory failure and result in a high mortality and morbidity. Our objective is to gain novel insights into the pathways and biological processes that occur in response to diffuse lung injury by using comprehensive protein expression profiling in combination with bioinformatics tools. We characterized the protein expression in the Bronchoalveolar lavage fluid (BALF) from subjects with ARDS and also in hematopoietic stem cell transplantation (HSCT) recipients. For our studies, ARDS cases were grouped into survivors and non-survivors. The HSCT recipients were assigned to either infectious lung injury or IPS, i.e. non-infectious lung injury. The BALF samples were processed by desalting, concentration and removal of high abundance proteins. Enriched medium and low abundant protein fractions were trypsin digested and labeled with the iTRAQ reagent for mass spectrometry (MS). The complex mixture of iTRAQ labeled peptides was analyzed by 2D capillary LC-MS/MS on an Orbitrap Velos system in HCD mode for data-dependent peptide tandem MS. Protein identification employed a target decoy strategy using ProteinPilot. To determine the biologic relevance of the differentially expressed proteins we used Database for Visualization and Annotation for Integrated Discovery (DAVID) and Ingenuity Pathway Analysis (IPA). In the studies done on pooled BALF described in Chapter 3, we identified 792 proteins at a global FDR of <= 1%. The proteins that were more abundant in early phase survivors represented the GO groups involved in coagulation, fibrinolysis and wound healing, cation homeostasis and activation of the immune response. In contrast, non-survivors had evidence of carbohydrate catabolism, collagen deposition and actin cytoskeleton reorganization. These proof of concept studies identified early differences in the BALF from ARDS survivors compared to non-survivors. As a follow-up, we characterized BALF from the individual subject with ARDS, 20 survivors and 16 non-survivors (Chapter 4). To accomplish this we performed six eight-plex iTRAQ LC-MS/MS experiments, and we identified 1122 unique proteins in the BALF. The proteins that had a differential expression between survivors and non-survivors represented three canonical pathways -- acute phase response signaling, complement system activation, LXR/RXR activation- and four IPA Diseases and Functions- cellular movement, immune cell trafficking, hematological system development and inflammatory response. Similar to our prior studies, GO biological processes annotated to these proteins included programmed cell death, collagen metabolic processes, and acute inflammatory response. The sparse logistic regression model identified twenty proteins that predicted survival in ARDS. For the studies conducted in HSCT recipients (Chapter 5), we performed five eight-plex iTRAQ LC-MS/MS experiments and identified 1125 unique proteins. The proteins that had a differential expression between IPS and infectious lung injury enrich GO biological terms of immune response, leucocyte adhesion, coagulation, wound healing, cell migration, glycolysis, and apoptosis. In summary, the BALF protein expression profile identifies key differences in the biological processes in different subgroups of patients with diffuse lung injury. These differences position us to develop diagnostic and prognostic biomarkers and identify new targets for pharmacological therapy.Item Synthesis and evaluation of parthenolide analogues: chemical probes and therapeutic agents(2013-03) Wang, DanCancer stem cells (CSCs), also known as tumor-propagating cells or tumor-initiating cells, are subpopulations of undifferentiated, highly tumorigenic cells found within bulk tumors. The rapid advances of cancer research and development of relative technologies have provided more and more evidence for the existence of CSCs, as well as the important roles they play in drug resistance and disease relapse of cancer. However, because of their quiescent nature and the similarities to normal stem cells, eradicating CSCs presents a challenging task. Chapter one provides an overview of cell surface markers of CSCs. Those markers are potential diagnostic macromolecules and targets for drug delivery.Parthenolide (PTL) is a sesquiterpene lactone natural product isolated from Mexican Indian medicinal herb Tanacetum parthenum (feverfew plant), a known medical herb utilized for centuries. PTL has been extensively studied as an anticancer agent, showing significant efficacy towards a wide spectrum of human cancer cells. In 2005, the identification of PTL as the first stand-alone and selective cytotoxic agent against the acute myeloid leukemia CSCs further heightened its therapeutic potential. However, the mechanism of action of PTL's CSC inhibitory activity is still an area of debate. Our efforts to elucidate the molecular targets of PTL is described in chapter two. The design and synthesis of two PTL affinity probes with diverse biological activity as well as their utilization in comparative and competitive protein pull-down experiments to enrich the cellular protein targets of PTL is presented. Although exhibiting promising anticancer and anti-CSC activities, the modest biological potency and poor water solubility prevent further development of PTL. Chapter three describes our efforts to synthesize PTL analogues, as well as our strategy to prepare water-soluble PTL prodrugs.Item Use of Biodescriptors and Chemodescriptors in Predictive Toxicology: A Mathematical/Computational Approach(University of Minnesota Duluth, 2002) Basak, Subhash CDevelopment and applications of biodescriptors for predictive toxicology by our NRRI team has been expanded to incorporate three major types of biodescriptors: a) global descriptors from invariants of matrices associated with proteomics maps, b) a set of local invariants describing various aspects of each map (instead of one global biodescriptor), and c) spectrum-like descriptors for the characterization of proteomics patterns.A successful HiQSAR model has been developed for a set of 55 halocarbons for which cellular level toxicity data is available. It may be noted that this is the "superset" of compounds from which the "subset" of twenty halocarbons, currently being tested by WPAFB and Dr. Witzmann using the DNA microarray and proteomics analysis, was selected. Selection of parameters for the HiQSAR was based on the mechanistic hypothesis that dissociate electron attachment and subsequent formation of free radical$, leading to lipid peroxidation, is a major factor in halocarbon toxicity. This conclusion was derived from Dr. Balasubramanian's previous research, based on high-level quantum chemical calculations. If the hypothesis is correct, calculated parameters such as vertical electron aftinity(VEA) should be strongly related to a chemical's toxicity.