Breast cancer (BC) is the second leading cause of death in Canadian women. Detection of the disease at an early stage greatly increases the average 5-year survival rate, however non-invasive early detection methods are not available to-date. Cells release various types of extracellular vesicles (EVs) to mediate intercellular communication by transferring signals in the form of bioactive molecules such as proteins, metabolites, and nucleic acids. Understanding the composition of these biomolecules may shed light on the physiological state of the cell of origin. Therefore, EVs are a promising source of biomarkers for non-invasive detection of BC. However, the surface proteome of EVs is not yet understood well enough to propose BC biomarkers that could be detected directly from biofluids. In this study, small EVs (sEVs) and medium EVs (mEVs) were isolated by differential ultracentrifugation from breast cancer MDA-MB-231 and MCF7, and non-cancerous breast epithelial MCF10A cell lines and analyzed by nano-liquid chromatography coupled to tandem mass spectrometry. EV proteins were analyzed by two approaches: (1) global proteomic analysis and (2) enrichment of EV surface proteins by labelling surface-accessible proteins with a Sulfo-NHS-SS-Biotin reagent. Potential BC biomarkers were obtained from the first approach (1) by identifying the presence of cell line specific sEV proteins, filtering for membrane/surface proteins using UniProt annotations, and predicting the co-localization of proteins on sEVs with known EV marker proteins (CD63, CD9, CD81) by correlation analysis. This resulted in 11 potential BC sEV biomarkers (C8A, AXL, ST14, FAM20B, PROM2, CLDN3, ITGA7, MEGF10, SHISA2, GJC1, IFNGR1); the presence of ST14, CLDN3 and ITGA7 was validated by Western blot analysis. The surface labelling approach (2) enriched proteins previously not identified using the first approach (1). Potential general BC biomarkers were selected from surface proteins commonly identified from MDA-MB-231 and MCF7, but not identified in MCF10A EVs. Annotation with known BC disease associations from DisGeNET yielded 9 and 2 potential surface proteins on sEVs and mEVs, respectively. This study demonstrates the emerging role of EVs as a rich source of known and novel biomarkers which may be used for non-invasive detection of BC.

Understanding species-specific physiological tolerances to environmental extremes is key in determining the factors that contribute to regulating species distribution. This understanding will aid in determining which species will manage to thrive in a changing global climate. According to the IPCC (2013) it is expected that, in the coming years, many different types of abiotic factors will change as a result of global climate change. The intertidal habitat is a model habitat for studying environmental extremes as it is located at the interface between the marine and terrestrial environments, making it one of the most stressful marine habitats. It is characterized by a 24 hr light: dark cycle and a 12.4 tidal ebb and flow that exposes animals inhabiting this habitat to a wide array of aerial-associated stressors such as changes in temperature, aerial exposure, low oxygen or hypoxic conditions and desiccation stress. Sessile organisms such as marine mussels of the genus Mytilus, are an ideal study species for studying physiological tolerance at the environmental extremes of the intertidal habitat. In particular, M. trossulus and M. galloprovincialis are an excellent study system for examining physiological tolerance at environmental extremes due to the recent change in biogeographic range of both species. M. galloprovincialis, a native of the Mediterranean, has been taking over the coast of California and has been displacing the heat sensitive native M. trossulus. The effects of salinity stress and heat stress on the physiologies of these species have been investigated by Braby and Somero (2006a and 2006b), Tomanek and Zuzow (2010) and Tomanek et al. (2012). The results of these studies indicate that the invasive M. galloprovincialis is more heat tolerant but is sensitive to hyposalinity while the reverse is true for the native M. trossulus.. The next logical environmental stress to study is low tide or aerial-emersion as both species can be found both tidally and subtidally. According to Grieshaber et al. (1994) and Müller et al. (2012) Mytilus edulis mussels have mechanisms for mitigating aerial-emersion hypoxia; however, very few studies have been performed using the study system of M. trossulus and M. galloprovincialis in regard to aerial-emersion hypoxia. This study aimed to observe the responses of both M. trossulus and M. galloprovincialis to aerial-emersion hypoxic stress or low tide. The study also looked to see if the recent habitat history (tidal or subtidal) can play a role in the response of the mussels to hypoxia. The results of the experiment indicate that the invasive M. galloprovincialis may be less sensitive to hypoxic stress when compared to the native M. trossulus. This difference in sensitivity may be due to the difference in mechanisms of energy metabolism proteins and proteostasis proteins used to mitigate the effects of hypoxic stress. Moreover, tidal acclimation appears to better prepare the mussels for subsequent aerial exposure in both species, possibly based upon the principles of stress-hardening outlined by Kültz (2005).

Thesis advisor: Jianmin . Gao / Cysteine residues perform many essential cellular functions, including nucleophilic and redox catalysis, metal coordination, structural stabilization and cellular protection. Cysteine-related mutations are oftentimes related to diseases due to the amino acid’s functional importance. This has led cysteine to become a focus of small molecule drug discovery. A comparison of the cysteine proteome of diseased cells versus healthy cells can elucidate novel cysteine residues that play an important role in progressing the disease state. Two disease models were chosen to be the focus of this proteomic study; breast cancer through the human epithelial MCF10 progression series and immunoactivation through the Raw 246.7 mouse macrophage cell line. Comparative proteomics with mass spectrometry revealed several changes within the cysteine proteome when the cells were diseased. Some cysteines had changes in reactivity, most likely indicating a loss or gain of a modification or disulfide bond. Other cysteines showed increased labeling due to an increase in the overall expression of the protein encompassing the cysteine residue. Further follow-up of an interesting hit from the Raw cell comparison, immune responsive gene 1 (IRG1), was conducted. IRG1 produces itaconate from cis-aconitate under inflammatory conditions, disrupting the citric acid cycle. IRG1 was confirmed to have increased expression following activation of the macrophage cells by lipopolysaccharides. It was also successfully recombinantly expressed in and purified from Escherichia coli for use in an activity assay to determine if the cysteine labeled in the mass spectrometry experiment is essential for the protein function. With additional knowledge of cysteines that help progress disease states, new small molecule inhibitors can be developed to target these cysteines and impede the function that is beneficial for the disease. / Thesis (MS) — Boston College, 2019. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Chemistry.

Indiana University-Purdue University Indianapolis (IUPUI) / Because label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) shotgun proteomics infers the peptide sequence of each measurement, there is inherent uncertainty in the identity of each peptide and its originating protein. Removing misidentified peptides can improve the accuracy and power of downstream analyses when differences between proteins are of primary interest. In this dissertation I present classCleaner, a novel algorithm designed to identify misidentified peptides from each protein using the available quantitative data. The algorithm is based on the idea that distances between peptides belonging to the same protein are stochastically smaller than those between peptides in different proteins. The method first determines a threshold based on the estimated distribution of these two groups of distances. This is used to create a decision rule for each peptide based on counting the number of within-protein distances smaller than the threshold. Using simulated data, I show that classCleaner always reduces the proportion of misidentified peptides, with better results for larger proteins (by number of constituent peptides), smaller inherent misidentification rates, and larger sample sizes. ClassCleaner is also applied to a LC-MS/MS proteomics data set and the Congressional Voting Records data set from the UCI machine learning repository. The later is used to demonstrate that the algorithm is not specific to proteomics.

Although the cell wall is an essential plant cell structure influencing several important aspects of plant development, little is known about the genes and proteins that regulate its structure and function. In this dissertation, we first examined the regulation of the nuclear proteome of rice (Oryza sativa) in response to cell wall removal. Using labelree comparative proteome analysis we found that, upon removal of the cell wall, 142 nuclear proteins were up regulated and 112 nuclear proteins were down regulated. The differentially expressed proteins included transcription factors, histones, histone domain containing proteins, and histone modification enzymes. This study led to a novel discovery that removal of the cell wall results in dynamic changes in the nuclear proteome affecting the regulation of proteins involved in various molecular processes such as chromatin and nucleosome assembly, protein-DNA complex assembly, and DNA packaging. To further study cell wall development, we utilized the unique features of cotton fiber and performed a proteomic study using four stages during cotton fiber cell wall development including 10 days post anthesis (dpa), 15 dpa, 25 dpa, and 35 dpa. In addition, we aimed to improve protein extraction for recalcitrant fiber stages using pressure cycling technology (PCT). To our knowledge, this study identified the largest number of proteins and differentially expressed proteins in the G. hirsutum cotton species including the 35 dpa fiber proteome which has not been examined in prior reports. Additionally, in order to identify key genes regulating cell wall cellulose content, a mutant with a substantial reduction in cellulose was characterized in Arabidopsis. It was found that the mutated gene was VHA-E1. We found that the VHA-E1 protein formed a distinct plate in the boundary of two fusion-destined vacuoles to tether vacuoles together. The eventual vacuole fusion was achieved by pinching off the vacuole-boundary plate producing a stable membrane-bound intravacuolar globoid. These observations demonstrate that VHA-E1 may be involved in a novel cellular process regulating fusion of vacuoles by forming a cellular structure referred to as the vacuole boundary plate. Altogether, these findings suggest plant vacuole fusion and central vacuole biogenesis involve an unprecedented mechanism in Arabidopsis.

This experiment was conducted to determine the differences in meat quality (cooking loss and shear force), descriptive sensory characteristics, consumer acceptance, and whole muscle proteomes between normal and Pale, Soft, and Exudative (PSE) broiler breast meat. Male Hubbard × Cobb 500 birds (n = 1,050) were raised in commercial houses. Prior to harvest, a sample of the broilers (n = 900) were subjected to short-term stress (38 °C for 2 h), and the remaining broilers (n = 150) were maintained at control conditions (21 °C for 2 h). From the stressed and control condition broilers, breast samples were characterized by pH24 and L*24 as normal (pH24 5.8-6.2, L*24 45-55) or PSE (pH24 5.4-5.7, L*24 55-65). Normal chicken breast meat had lower shear force values than PSE meat (P < 0.05). Based on sensory descriptive analysis, normal cooked chicken breast was more tender and juicier than PSE breast meat (P < 0.05). Consumer sensory analysis results indicated that 81% of consumer panelists liked normal breast meat whereas 62% of the panelists liked PSE breast meat. Whole muscle proteome profiling identified fifteen differentially abundant proteins (P < 0.05) in normal and PSE meat samples. Actin alpha, myosin heavy chain, phosphoglycerate kinase, creatine kinase M type, beta-enolase, carbonic anhydrase 2, proteasome subunit alpha, pyruvate kinase, and malate dehydrogenase were over-abundant in PSE meat whereas phosphoglycerate mutase-1, alpha-enolase, ATP-dependent 6-phosphofructokinase, and fructose 1, 6-bisphosphatase were over-abundant in normal meat. In addition, normal and PSE broiler breast meat were sampled from commercial plants and evaluated for meat quality attributes (pH, color, cooking loss, and tenderness) and their whole muscle proteome. Normal chicken breast meat had lower shear force values than PSE meat (P < 0.05). Proteome analysis revealed five differentially abundant proteins (P < 0.05) between the normal and PSE chicken breast samples. Glycolytic enzymes (beta-enolase and fructose-bisphosphate aldolase C) were over-abundant in PSE breast meat. Myofibrillar protein (myosin heavy chain) was over-abundant in PSE breast meat. In conclusion, results indicated that differences in proteome abundance could be related to the meat quality differences between normal and PSE breast meat.

Listeria monocytogenes is a Gram-positive facultative anaerobe that is the causative agent of the disease listeriosis and is responsible for nearly 20% of all food-related deaths in the United States. The ability of this bacterium to cause infections is proposed to correlate to its ability to resist the bactericidal properties of bile acids found in bile. Bile resistance mechanisms have exhibited increased activity under anaerobic conditions. Therefore, we hypothesized that limited oxygen could enhance the bile resistance of L. monocytogenes. Upon survival analysis, viability for virulent strains F2365, EGD-e, and 10403S increased upon 10% porcine bile extract under anaerobic conditions. However, avirulent strain HCC23 depicted no difference in bile resistance. The proteomic analysis revealed increased expression of proteins associated with DNA repair and virulence factors under anaerobic conditions in a strain dependent manner. Therefore, oxygen availability may contribute to bile resistance through the regulation of the SOS response.

The study of proteomics holds the hope for detecting serious diseases earlier than is currently possible by analyzing blood samples in a mass spectrometer. Unfortunately, the statistics involved in comparing a control group to a diseased group are not trivial, and these difficulties have led others to incorrect decisions in the past. This paper considers a nested design that was used to quantify and identify the sources of variation in the mass spectrometer at BYU, so that correct conclusions can be drawn from blood samples analyzed in proteomics. Algorithms were developed which detect, align, correct, and cluster the peaks in this experiment. The variation in the m/z values as well as the variation in the intensities was studied, and the nested nature of the design allowed us to estimate the sources of that variation. The variation due to the machine components, including the mass spectrometer itself, was much greater than the variation in the preprocessing steps. This conclusion inspires future studies to investigate which part of the machine steps is causing the most variation.

The reliability of biomarker discovery by means of proteomics has been called into question. It was speculated that "background noise" variation resulting from differences in preparation and handling of samples and proteome dynamics may mask subtle, yet important, differences due to the biological condition. Little is understood about complex proteomes and their variability. A critical aspect of proteomic biomarker research that is largely unexplored is the comparative reproducibility of certain methods such as two-dimensional gel electrophoresis and liquid chromatography/mass spectrometry. In particular, with liquid chromatography/mass spectrometry, it is not known whether variability in peptide quantitation is dependent on any of their several properties such as size, abundance, or hydrophobicity. Such determinations may be critical in properly assessing the value of proteomics data. The fruit fly Drosophila melanogaster was used as a well-controlled multicellular animal model to study the relationship between the background variation and expected changes induced by environmental or genetic factors. The data, gathered by two different proteomics methods, were used to compare and evaluate the reproducibility of the methods. It is reported that there was on average 15 to 18% variability in quantitative measurements of protein abundance using 2-dimensional gel electrophoresis or liquid chromatography/mass spectrometry. Using liquid chromatography/mass spectrometry, peptides with a smaller mass-to-charge ratio were shown to be measured less reproducibly than peptides with a larger ratio. Statistically significant proteomic differences between fly populations could be demonstrated between males and females. In dynamic experiments, less than 0.5% of proteins measured were shown to change after 24 hour starvation of the flies. However, no significant difference in peptide composition could be found for flies fed on a second diet consisting of the standard diet augmented with 10% ethanol. These results suggest that proteomic variability while evident allowed for biomarker discovery using either method for this model system.

<p>Cell-derived extracellular vesicles (EVs) are increasingly being recognized as an important mediator of intercellular communication, immune response and waste disposal. Due to the prevalent dissemination in most biofluids, EVs provide a promising alternative for non-invasive liquid biopsy in clinics. With internal cargoes well-preserved by EV membranes, EV-containing DNA, RNA, proteins, lipids and metabolites are widely investigated for biomarker discovery and disease progression and therapeutics monitoring. Among them, proteins and their post-translational modifications (PTMs), are the direct phenotypic indicators of pathophysiological states. Besides, development of liquid chromatography-tandem mass spectrometry (LC-MS/MS) has allowed high-throughput and discovery-driven bioanalysis on proteomics, including EV proteomics. Nevertheless, the translational research and clinical applications on EVs are severely hampered due to the lack of suitable and efficient isolation methods as well as robust and sensitive proteomic approaches. This dissertation proposes EV proteomic strategies for therapeutic surveillance by using a novel EV isolation technique. Chapter One introduces overall status of proteomics and phosphoproteomics in translational and clinical analysis for to-date medical sciences. Chapter Two highlights a novel EV isolation method termed EV total recovery and purification (EVtrap). Chapter Three delves into the development of a pipeline proteomic strategy that utilizes EV P450 enzymes to monitor drug metabolic behaviors. Finally, Chapter Four explores the possibility of leveraging protein PTMs in EVs, especially tyrosine phosphorylation, to indicate drug therapeutic efficacy in a clinical setting. This dissertation primarily proposes EV-based liquid biopsy for revolutionary clinical analysis, especially on longitudinal monitoring for <em>in vivo</em> treatment response.</p>