Doctor of Philosophy, The Ohio State University, 2024, Biochemistry Program, Ohio State

Mass spectrometry-based proteomics has reached a renaissance in the past 20 years, as acquisition software and methods have exponentially increased. Simultaneously, the demand for high-throughput tumor models has increased with the passing of the 2020 FDA Modernization Act, which removed the need for animal testing before clinical trials. 3-dimension tumor models, such as spheroids, are an attractive preclinical model, as they are relatively cheap to generate, easy to grow, and scalable. Spheroid models have traditionally been formed with one cell line, which greatly reduces the complexity of the model compared to actual patient tumors. Within this work, we sought to develop a coculture 3D tumor model, which incorporates fibroblast and colon cancer cell lines into spheroids, then profile the spheroid proteome with data-independent acquisition (DIA). Additionally, we have developed methodology to build target assays using parallel reaction monitoring (PRM) for both high-throughput models for applications in cancer and immunology. We have further optimized PRM methods on a compact, unit-resolution mass spectrometer for analyzing low-input samples. We have described detailed applications of proteomics for the tumor microenvironment, as well as low-abundant immune cell populations for use in immunological studies.

Committee: Amanda Hummon (Advisor); Heather Powell (Committee Member); Maria Mihaylova (Committee Member); Brian Searle (Committee Member) Subjects: Analytical Chemistry; Biochemistry; Biomedical Research; Chemistry

Doctor of Philosophy, The Ohio State University, 2016, Biochemistry Program, Ohio State

This dissertation describes the research that was conducted on the development of label-free quantitation procedures for the identification and quantitation of proteome differences determined from shotgun proteomics experiments. Chapter 1 introduces common approaches of which their basic understanding of is imperative for all proteomic scientists. This introductory chapter also describes label-free quantitation approaches, which is built upon in following chapters. Chapter 2 outlines a novel approach to perform label-free spectral count quantitation from shotgun proteomic experiments. This approach, termed MultiSpec, utilizes open-source statistical platforms; namely edgeR, DESeq and baySeq, to statistically select protein candidates for further investigation. The results from these three statistical approaches are combined to provide a single ranked list of differentially expressed proteins. The statistical results from multiple proteomic pipelines are integrated and cross-validated by means of collapsing protein groups. Chapter 3 highlights the efficient application of negative binomial based tag-count analysis of large-scale proteomics. This chapter illustrates the efficacy of edgeR to perform spectral count quantitation across a large number of samples. Chapter 4 demonstrates the use of precursor abundance (MS1) quantitation, an alternative to spectral count quantitation, to quantitate proteome differences in chromatin-bound androgen receptor protein complexes pivotal in directing proper gene expression in the context of localized human prostate cancer. Also presented in chapter 4, precursor intensities were used to determine proteome differences between the prostate proteomes of a transgenic mouse model of prostatic intraepithelial neoplasia (PIN). In a collaborative effort, these data were overlaid with RNA sequencing and Chromatin-Immunoprecipitation sequencing data to identify a proteome set of putative androgen receptor regulated proteins.

Committee: Michael Freitas (Advisor) Subjects: Biochemistry

Master of Science, The Ohio State University, 2008, Graduate School

Committee: Not Provided (Other) Subjects:

PhD, University of Cincinnati, 2024, Medicine: Biomedical Informatics

The advent of sequencing technologies has revolutionized our understanding of disease. Researchers can now investigate the complex processes involved in the multi-layered transcription of genetic content, which regulates cell activity, homeostasis, and ultimately the organism's health. A disease can be conceived as a deviation from a homeostatic state, leading to cascading negative effects. A disease state, or more generally a disrupting factor (sometimes called a "perturbagen"), can be characterized by how it impacts the organism. This information constitutes its "signature", such as a list of differentially expressed genes or vectors of abundance of proteins or lipids. Significant efforts have focused on gathering these signatures into connectivity maps (CMAPs), which allow the identification of related disrupting factors based on the similarity of their signatures. CMAPs can overcome some limitations of traditional enrichment analysis. However, challenges remain. The integrative analysis of multi-domain data, as opposed to concurrent or sequential analysis, is still a challenge. The complexity of multi-omics analysis, involving retrieving datasets, annotations, and applying analytical pipelines, requires advanced programming skills, which can be a barrier for researchers without dedicated resources. Additionally, analysis pipelines need to scale up as assays become clinically available and more data is generated. To address these challenges, we developed machine learning tools to predict health outcomes, ranging from sepsis to dementia. Our goal is to build knowledge and expertise about integrative and extensible analytical pipelines for clinical, transcriptomics, and proteomics data. Specifically, we developed a statistical and machine learning model to classify patients by phenotype and predict mortality risk. We analyzed a prospective cohort of sepsis patients, selected predictive features, built and validated models, and then refined a robust model u (open full item for complete abstract)

Committee: Jaroslaw Meller Ph.D. (Committee Chair); Michal Kouril Ph.D. (Committee Member); Robert Smith M.D. Ph.D. (Committee Member); Faheem Guirgis Ph.D M.A B.A. (Committee Member); Michael Wagner Ph.D. (Committee Member) Subjects: Bioinformatics

Doctor of Philosophy in Clinical-Bioanalytical Chemistry, Cleveland State University, 2024, College of Sciences and Health Professions

Colorectal cancer is the third leading cause of cancer-related mortality worldwide. Prognosis is favorable if detected early, however, current screening methods have major limitations. There is an urgent need to develop new non-invasive screening tests that are more sensitive and specific to improve outcomes at every stage. Advances in mass spectrometry-based proteomics provide insights into molecular changes driving CRC and can uncover potential biomarker candidates that have diagnostic or prognostic utility. Mass spectrometry is an ideal platform for the development of assays to serve as first line screening tests and to monitor disease progression and response to treatment. The aim of this research was to develop a sensitive and specific mass spectrometry-based method to quantify two protein biomarkers of colorectal cancer in stool that exceeds the performance of current biochemical methods for the quantification of these proteins. The second part of this work aimed to uncover predictive markers that identify individuals at risk of relapse for patients with stage II colon adenocarcinoma. A proteolysis assisted workflow was optimized to quantify peptides of hemoglobin and calprotectin in human stool samples by LC-MS/MS. The multiplexed LC-MS/MS assay for fecal hemoglobin and calprotectin had sensitivities 2 ng and 0.5 ng, respectively and demonstrated linearity from 20 – 1000 µg/g feces for hemoglobin and 6 – 800 µg/g feces for calprotectin. The assay is accurate and precise over the analytical measuring range and highly correlated with measured values from the enzymatic immunoassays. The LC-MS/MS assay was able to distinguish colorectal cancer stool samples from healthy controls with 100% sensitivity and 100% specificity with the combination of both hemoglobin and calprotectin. An untargeted analysis of proteomic data of stage II colon adenocarcinoma tissue samples was conducted. Overexpression of eosinophil peroxidase was associated with lymphovascular invasi (open full item for complete abstract)

Committee: Baochuan Guo (Committee Chair); Michael Kalafatis (Committee Member); Valentin Gogonea (Committee Member); Yan Xu (Committee Member); Anton Komar (Committee Member) Subjects: Bioinformatics; Biomedical Research; Health Sciences

Doctor of Philosophy, Case Western Reserve University, 2024, Pharmacology

Globally, an estimated 420 million people today suffer from debilitating vision loss caused by age-related macular degeneration (AMD), diabetic retinopathy (DR), retinitis pigmentosa (RP), or glaucoma; a large majority of these cases (up to 90%) have only minimally effective or no treatment options available. These chronic, progressive retinal diseases arise from a complex interplay of genetic and environmental factors that disrupt, and eventually compromise, cellular and tissue stability. Such disruptions accumulate with repeated exposures to stress over time, leading to progressive visual impairment and, in many cases, legal blindness. Despite decades of research, effective treatments to preserve eyesight have remained elusive for the millions of patients suffering from these debilitating disorders, especially in the vast majority of cases that are in early stages of disease progression, wherein lies the greatest opportunity to slow or halt vision loss. In the coming decades, population aging will exacerbate the increase in global prevalence of vision impairment and blindness, thus underscoring a critical, unmet need for innovative, new ophthalmic medications. In pre-clinical studies, we demonstrated the efficacy of prototypical ‘stress resilience-enhancing drugs' (SREDs) that preserved both retinal morphology and function across a variety of genetic and environmental animal models of AMD, DR, RP, and glaucoma. These small-molecule therapies can be subdivided according to primary mechanism of action, resulting in two distinct subclasses of SREDs: 1) epigenetic modulators that include inhibitors of select histone deacetylases (HDACi) or methyltransferases (SUVi); and 2) selective inhibitors of cyclic nucleotide phosphodiesterases (PDEi). With pharmacological inhibition of histone deacetylase 11 (HDAC11) or suppressor of variegation 3-9 homolog 2 (SUV39H2), key histone-modifying enzymes involved in promoting reduced chromatin accessibility, stress-induced retinal (open full item for complete abstract)

Committee: Krzysztof Palczewski (Advisor); Philip Kiser (Advisor); Walter Boron (Committee Member); Johannes von Lintig (Committee Member); George Dubyak (Committee Member); John Mieyal (Committee Chair) Subjects: Medicine; Ophthalmology; Pharmaceuticals; Pharmacology

Doctor of Philosophy, Case Western Reserve University, 2024, Biomedical Engineering

Intracortical microelectrodes (IMEs) are a type of brain-computer interface that allows for the recording of neural signals to communicate between the brain and computers. IMEs can be used to restore motor function in people with spinal cord injury, treatment of neurological disorders, and are a strong basic science tool for understanding the brain. Unfortunately, implanted IMEs consistently see a steady decline in recording ability over time, leading to failure of the device. Damage to the blood-brain barrier (BBB) from IME implantation is a key contributor to device failure. After BBB breach, neurotoxic molecules invade the brain and cause a downstream cascade of neuroinflammation and oxidative stress that further damages the BBB, brain tissue, and the IME itself. Attempts to minimize BBB damage to improve neuroinflammation and IME longevity have shown limited success. Given the lack of solutions to the chronic stability of neural recordings, further investigation into understanding and minimizing the effects of BBB damage is warranted. In my dissertation, I investigate multiple strategies to mitigate and expand our understanding of how BBB damage can impact IME performance. Thermal damage to underlying vasculature because of cranial drilling has been shown to impact BBB permeability. To combat this, I developed a standardized surgical approach to limit surgeon variability and reduce thermal damage on the BBB. Next, I utilized the antioxidant dimethyl fumarate to promote BBB healing and reduce oxidative stress, resulting in acute improvements to IME function without long-term stability. Lastly, I investigated what unknown molecules enter the brain through the permeable BBB and contribute to neuroinflammation. I was the first to discover that gut-derived bacteria invade the site of implantation through the damaged BBB, which can be modulated with antibiotics to alter neuroinflammation and IME performance. New therapeutics can be developed utilizing this connecti (open full item for complete abstract)

Committee: Jeffrey Capadona (Advisor); Anirban Sen Gupta (Committee Chair); A. Bolu Ajiboye (Committee Member); Andrew Shoffstall (Committee Member); Gary Wnek (Committee Member) Subjects: Biomedical Engineering; Engineering

Master of Science (MS), Bowling Green State University, 2023, Biological Sciences

All epithelia are characterized by keratins, which make up a type of intermediate filament (IF). In epithelial tumors, which account for the majority of clinical cancers, the loss of cytoskeletal integration is considered one of the first alterations in epithelial metaplasia. This may have something to do with the expression of keratins or rearrangement of keratin filaments. In this study, I employed shotgun proteomic analysis and bioinformatic tools to identify proteins that interact with keratin filaments and thus may contribute to the disintegration of cytoskeleton. Using four airway epithelial cell lines in culture, I confirmed they highly expressed Keratin 14 (K14) and its obligatory partners, Keratin 5 (K5) or Keratin 6A (K6A). This suggests that the predominant IF is made up of K14 paired with K5/K6A. Although samples were enriched in keratin-associated proteins by immunoprecipitation (IP) with an antibody directed against K14 and K17, additional keratins not specifically targeted were also captured. Proteomic analysis revealed a list of non-keratin proteins enriched by IP. Some were associated with actin and microtubules, 23 and 6 proteins, respectively. Most of these were not linearly related to keratin content by abundance, but the motor protein, dynein I heavy chain, showed a Pearson correlation coefficient (CC) of -0.84 with keratin. Similarly, of 54 proteins associated with focal adhesions, intercellular junctions, or membranes, only septin-9 had a CC suggesting its abundance tracked with that of keratins. Finally, I analyzed IP-specific proteins that were cytosolic or had unknown subcellular distribution. A CC of -0.91 was found for one of these proteins, namely 26S proteasome regulatory subunit 8 (Psmc5). Further investigation and validation of the dataset was done by GO Enrichment Analysis. Using a subset of proteins highly concentrated by IP, compared to controls, I found the GO functions predicted were intracellular transport, (open full item for complete abstract)

Committee: Carol Heckman Ph.D (Committee Chair); Michael Geusz Ph.D (Committee Member); Xiaohong Tan Ph.D (Committee Member) Subjects: Bioinformatics; Biology; Biomedical Research; Cellular Biology; Molecular Biology; Oncology

Doctor of Philosophy, Case Western Reserve University, 2023, EECS - Computer and Information Sciences

This dissertation presents a comprehensive approach to advancing proteomics and under-studied proteins in network biology, emphasizing the development of reliable algorithms, fair evaluation practices, and accessible computational tools. A key contribution of this work is the introduction of RoKAI, a novel algorithm that integrates multiple sources of functional information to infer kinase activity. By capturing coordinated changes in signaling pathways, RoKAI significantly improves kinase activity inference, facilitating the identification of dysregulated kinases in diseases. This enables deeper insights into cellular signaling networks, supporting targeted therapy development and expanding our understanding of disease mechanisms. To ensure fairness in algorithm evaluation, this research carefully examines potential biases arising from the under-representation of under-studied proteins and proposes strategies to mitigate these biases, promoting a more comprehensive evaluation and encouraging the discovery of novel findings. Additionally, this dissertation focuses on enhancing accessibility by developing user-friendly computational tools. The RoKAI web application provides a convenient and intuitive interface to perform RoKAI analysis. Moreover, RokaiXplorer web tool simplifies proteomic and phospho-proteomic data analysis for researchers without specialized expertise. It enables tasks such as normalization, statistical testing, pathway enrichment, provides interactive visualizations, while also offering researchers the ability to deploy their own data browsers, promoting the sharing of findings and fostering collaborations. Overall, this interdisciplinary research contributes to proteomics and network biology by providing robust algorithms, fair evaluation practices, and accessible tools. It lays the foundation for further advancements in the field, bringing us closer to uncovering new biomarkers and potential therapeutic targets in diseases like cancer, Alzheimer' (open full item for complete abstract)

Committee: Mehmet Koyutürk (Committee Chair); Mark Chance (Committee Member); Vincenzo Liberatore (Committee Member); Kevin Xu (Committee Member); Michael Lewicki (Committee Member) Subjects: Bioinformatics; Biomedical Research; Computer Science

Master of Science, The Ohio State University, 2023, Chemistry

Multicellular Tumor Spheroids (MCTS) are a three-dimensional cancer model system that better mimics the physiological microenvironment of in vivo tumors compared to two-dimensional cell culture. As spheroids grow radially from a central nexus of cells, different chemical and biological gradients begin to form. The chemical and biological gradients result in three distinct layers forming in a spheroid. The layers include an outer proliferating layer, a middle quiescent layer, and an apoptotic core. Cells in the different layers can be separated by a method known as ‘serial trypsinization'. Serial trypsinization sequentially removes the layers of a spheroid in a manner resembling the process of ‘peeling an onion'. After separation, the cells from each layer can be regrown, either as two-dimensional monolayers or as second-generation three-dimensional spheroids. Cells from different layers regrown in two-dimensional cell culture have been shown to retain some phenotypical traits related to their origin layer. Second-generation spheroids regrown from different layers also have different characteristics depending on the layer which the cells were derived. Once the spheroid derived monolayer or second-generation spheroids had fully matured, a bottom-up proteomic analysis was performed to compare the second-generation cell culture derived from either distinct layers or fully dissociated spheroids to their first-generation precursor spheroids. This analysis revealed differentially expressed proteins in all second-generation cell cultures compared to their first-generation cell culture. Several proteins which were differentially expressed were related to the epithelial-to-mesenchymal transition. Second-generation cell culture could be helpful in better understanding the EMT transition along with helping in drug discovery in drug resistant tumors.

Committee: Abraham Badu-Tawiah (Committee Member); Amanda Hummon (Advisor) Subjects: Chemistry

Master of Science (M.S.), University of Dayton, 2023, Biology

The critical role that the nervous system plays in driving amphibian limb regeneration underscores the impact that the brain may also have in this fascinating process. Earlier studies have suggested that unique protein synthesis occurs in the brain of regenerating newts upon limb amputation and have also exposed the prominent regenerative potential of brain-derived neural extracts from adult newts and chicken embryos. In the context of the current thesis, we employed a combination of in vivo axolotl limb amputation models, neurochemical and high-throughput proteomics approaches, as well as fluorescent immunohistochemistry to capture the temporal neuromolecular alterations that occur in the brain of regenerating axolotls. In our experimental setup, amputation and subsequent regeneration of the forelimbs affected the central proteomic signatures and neurochemistry in a time-dependent fashion into the regeneration program. To our knowledge this is the first study to systematically investigate the molecular and cellular dynamics underlying the activation of the limb-brain axis during amphibian limb regeneration, laying the groundwork for considering the role of the brain in the regulation of limb regeneration activity.

Committee: Pothitos Pitychoutis (Advisor); Mrigendra Rajput (Committee Member); Jennifer Hellmann (Committee Member); Katia Del Rio-Tsonis (Committee Member) Subjects: Biology; Neurosciences

Doctor of Philosophy, Case Western Reserve University, 0, Systems Biology and Bioinformatics

Mouse models of Alzheimer's Disease (AD) show progression through stages reflective of human pathology. Omics identification of temporal and sex-linked factors driving AD related pathways can be used to dissect initiating and propagating events of AD stages to develop biomarkers or design interventions. In this dissertation, we conducted label-free proteome and phosphoproteome measurements of mouse hippocampus tissue with variables of time (three, six, and nine months), genetic background (5XFAD vs. WT), and sex (equal males and females). These time points are associated with well-defined phenotypes with respect to: Aβ42 plaque deposition, memory deficits, and neuronal loss, allowing correlation of proteome based molecular signatures with the mouse model stages. I identified twenty-three novel AD-related proteins, six of which are differentially expressed between male and female 5XFAD. At a pathway level the 5XFAD specific upregulated proteins are significantly enriched for DNA damage and stress-induced senescence at 3-months only, while at 6-months the AD-specific proteome signature is altered and significantly enriched for membrane trafficking and vesicle-mediated transport protein annotations. By 9-months AD-specific dysregulation is also characterized by significant neuro- inflammation with innate immune system, platelet activation and hyper- reactive astrocyte related enrichments. Complementing these findings, the phosphoproteome is also marked by early DNA damage control (including cell survival and mRNA regulation signatures), however at six months these signatures are substituted by striking disruption of synaptic signalling and cell cycle regulation. Lastly, global MSOx profiling exposed the connection between increased Met(O) peptides and the selective downregulation of antioxidant defenses. This dissertation offers a novel systems-based understanding of AD dynamics, our multi-layered characterization of translational and post- translational pathways (open full item for complete abstract)

Committee: Mark R. Chance, PhD (Advisor); Xin Qi, PhD (Committee Member); Janna Kiselar, PhD (Committee Member); Mehmet Koyutürk, PhD (Committee Chair) Subjects: Aging; Bioinformatics; Gender Studies; Neurology; Systems Science

Master of Science, The Ohio State University, 2021, Chemistry

The lack of primary tumor samples for cancer research has resulted in the development of various in vitro model systems. While the most common of these, two-dimensional cell culture models, are fast and cheap, they lack the biological complexity of in vivo tumors. Another model, three-dimensional multicellular spheroids, provide a more accurate depiction of the tumor microenvironment compared to 2D cultures. Spheroids possess chemical and pathophysiological gradients similar to in vivo tumors that result in distinct cell populations: a proliferative outer layer, quiescent middle layer, and a necrotic core. The gradual removal of cells using trypsin, a technique called serial trypsinization, allows for the dissociation of spheroids into these populations. Once these cell populations are separated, they can be characterized through a variety of methods. Flow cytometry is a technique that measures the fluorescence emission of fluorophores attached to biological components in cells. For spheroids, labelling proteins associated with the cell populations, Ki67 for proliferation, beta-galactosidase for quiescence, and annexin V for the necrotic core, allows for the visualization of the gradients that define this tumor model and the validation of serial trypsinization as a spheroid dissociation technique. In addition to flow cytometry, mass spectrometry is another technique used to characterize the proteomes of these cell populations. By comparing the protein abundances of the individual populations to the abundances in the whole spheroids, up and down-regulated proteins can be identified for each, allowing for the identification of proteins that could play a large role in tumor formation, structure, and survival.

Committee: Abraham Badu-Tawiah (Committee Member); Amanda Hummon (Advisor) Subjects: Chemistry

Doctor of Philosophy, Case Western Reserve University, 2021, Biology

Schistosome infection affects over 250 million people worldwide, leading to extensive morbidity and death. Although this parasitic helminth immiserates millions annually, significant gaps exist in our understanding of translational regulation. Further analysis of the basic biology of schistosomes is required to develop new, more effective treatment modalities. In this thesis, we perform global translational analysis of cercariae and early schistosomula and transcriptomic and proteomic analysis of cercariae. The cercariae are comprised of two macrostructures, the head and the tail. The cercarial head has limited motility but contains proteases and mucins required for host invasion. The cercarial tail is highly motile and is necessary for swimming and motility. Given the cercarial tail functions, we hypothesize that the tail requires translation to maintain metabolism for motility. Given that cercarial transformation is not affected by translational inhibition, we hypothesize that the cercarial head is translationally repressed. In this thesis, we present two major studies. The first study directly tested the global translation rates in cercarial heads and tails. We found that neither the head nor tail undergoes transcription, translation is also severely limited in the cercarial head, but to the contrary, the cercarial tail has extensive translational activity. We also found that translation is required for swimming behavior. The global translation analysis did not identify the mechanisms that control these differences in translation, so we performed transcriptomic and proteomic analyses of cercarial heads and tails. In the second study, we analyze heads' and tails' transcriptomes and proteomes. We found that the probable drivers of translational differences in heads and tails are the storage and ratios of ribosomal components. The pattern of increased ribosomal component proteins extends into schistosomula and paired adults as well. We also report that transcri (open full item for complete abstract)

Committee: Emmitt Jolly PhD (Advisor); Blanton Tolbert PhD (Committee Member); Brian McDermott PhD (Committee Member); Chris Cullis PhD (Committee Member); Yolanda Fortenberry PhD (Committee Chair) Subjects: Biology; Biomedical Research

Doctor of Philosophy, The Ohio State University, 2021, Biochemistry Program, Ohio State

This dissertation evaluates the current methods utilized in label-free bottom-up proteomics to quantify proteins and describes best practices for analyzing this type of data and applying the methodology to perform multi-omics experiments across different biological data. Chapter 1 introduces background that will be expanded upon in the later application chapters. It also introduces key concepts in proteomics that will be the groundwork of the first two chapters of this dissertation. Chapter 2 addresses the missing value problem common in peak abundance analysis by evaluating the performance of different imputation methods. The most common sources of missing values in proteomics experiments are: 1) the biology and/or technical sample preparation, 2) actual presence below the instrument's limit of detection (LOD) and 3) presence above the LOD but error in data preprocessing. This chapter presents a case of the use of hybrid left-censored missing value imputation approaches common in proteomics data. Chapter 3 is an analysis of public data with immunoprecipitations of EZH2 and SUZ12, components of the repressive PRC2 complex. A co-interaction analysis was performed, combining the results from spectral counting and peakabundance. This type of analysis is extremely powerful for isolating protein interactions shared by co-interaction partners with much higher confidence than either alone. Secondly, mining the data in this manner can generate hypothesis testing and novel validation targets, as evidenced by the results. Chapters 4 and 5 are multi-omics projects that are an amalgamation of all of the interdisciplinary techniques and informatics skills that I have accumulated over the last 5 years in the laboratory of Dr. Michael A. Freitas. Chapter 4 describes the histone methyltransferase, EZH2, and the downstream effects of mutations occurring within the active site and substrate-binding channel of the protein on histone modifications and transcription. We also (open full item for complete abstract)

Committee: Michael Freitas PhD (Advisor); Robert Baiocchi MD, PhD (Committee Member); Brandon Biesiadecki PhD (Committee Member); Kotaro Nakanishi PhD (Committee Member); Mark Parthun PhD (Committee Member) Subjects: Biochemistry; Bioinformatics

Master of Science, Miami University, 2020, Microbiology

SLAMF9 is a cell surface protein expressed on the surface of a wide variety of cells. It is a peculiar but compelling molecule due to its lack of a known receptor, ligand, or signaling adapter. While there is little known about this protein, there is evidence suggesting SLAMF9 enhances clearance of bacterial pathogens but makes the host more susceptible to viral pathogens. This dual phenotype is thought to be the result of inflammatory cytokine crosstalk. Stimulation of SLAMF9 Knockdown and Control THP-1 cells with lipopolysaccharide (LPS) mimicking an early response to infection resulted in higher proinflammatory cytokine production in cells with normal SLAMF9 expression. A proteomic analysis was performed to determine which proteins, other than cytokines, were differentially expressed between the SLAMF9 Knockdown and Control THP-1 cells. It was determined that the expression of SLAMF9 influences several components of Ras signaling, which is a complex network regulating proliferation, survival signals, and cytokine transcription. A combination of differential proteomics and a phosphosite analysis indicated other proteins of interest to pursue in future research. Determining new regulatory mechanisms may give rise to new potential drug targets to resolve inflammatory disease.

Committee: Timothy Wilson PhD (Advisor); Eileen Bridge PhD (Committee Chair); Xin Wang PhD (Committee Member) Subjects: Immunology; Microbiology

Master of Science (MS), Ohio University, 2020, Chemistry and Biochemistry (Arts and Sciences)

Cucurbit[n]urils (CB[n]) are pumpkin-shaped molecular containers with a hollow inner cavity which in aqueous solution can act as molecular hosts to certain guest molecules, self-assembling into host-guest inclusion complexes. They exhibit versatile molecular recognition properties. In this work, we explored the potential applications of Cucubit[n]urils in proteomics research by developing CB[7] guests which are capable of derivatizing carbonylated peptides, allowing for enrichment harnessing CB[7] based affinity. Protein carbonylation is a harmful, irreversible, post translational modification, and is considered a biomarker for oxidative stress, which has been linked to a variety of human health disorders including Diabetes Mellitus and Alzheimer's. Current studies into protein carbonylation rely on affinity enrichment based on biotin-avidin affinity, which is limited in number of ways, reducing its utility in sensitive LC-MS based proteomics. Here, we exhibit two novel derivatization agents which lay the foundation for a method which can bypass these limiting factors and potentially provide a more efficient, practical and versatile form of affinity enrichment. Furthermore, we build upon the information elucidated by this work and present with a new optimized tag for use in further studies.

Committee: Eric Masson PhD (Advisor) Subjects: Analytical Chemistry; Biochemistry; Chemistry; Organic Chemistry

Doctor of Philosophy (PhD), Ohio University, 2020, Chemistry and Biochemistry (Arts and Sciences)

Traumatic brain injury (TBI) effects millions of Americans every year. Despite its relative commonality and frequency, there are no approved clinical treatments available for post-traumatic disease processes, which can lead to further pathologies such as post- traumatic epilepsy and chronic neurodegeneration. Further exacerbating the problem is the accidental nature of the insult. Thus, trying to understand the processes following mechanical insult and how they may develop into pathological processes is a promising general approach to developing new treatment strategies. Nitric oxide (NO), a small, gaseous messenger molecule, is released by both neural, glial, and vascular cells differentially following insult and is likely one of the most immediate responses the brain has to mechanical injury. Here, we use specialized nanonsensors implanted in mouse hippocampus to measure the real time in vivo production of NO and ONOO- following a modified controlled cortical impact injury. We then performed a proteomic analysis of S- nitrosylated proteins to examine the functional effects NO and ONOO- generated on the surrounding proteins. We found that post-traumatic NO and ONOO- generation has a significant impact on diverse cellular processes such as metabolism, autophagy and cell adhesion following TBI and may represent important proteins of interest for developing future treatments in the secondary phase following insult. At the same time, supplementation with NOS substrates like L-arginine may provide an effective prophylactic strategy by manipulating the post-traumatic redox environment, preventing secondary oxidative processes that can lead to neurodegeneration.

Committee: Tadeusz Malinski (Advisor); Michael Held (Committee Member); Lauren McMills (Committee Member); Sergio Ulloa (Committee Member) Subjects: Biochemistry; Chemistry; Neurosciences

MS, University of Cincinnati, 2019, Engineering and Applied Science: Computer Science

Proteins are large molecules made of amino acids that perform many of the functions that sustain life. Amino acid coevolution data describes evolutionary links between two different residues in the same protein sequence. Coevolution data are derived from multiple sequence alignments to many proteins across many species, and are therefore rich in information. While they can be interpreted as a traditional data structure, such as a weighted undirected graph or similarity matrix, these simplifications can lose information important to the domain of bioinformatics. Effective visualization requires interpreting the data using multiple simplified interpretations so that the user can relate to the data through traditional means while maintaining important information. Towards this end, CoeViz offers a dynamic, interconnected, interactive suite of tools for effective visualization of coevolution data. Coevolution data can provide contextual information about evolutionary relationships within proteins. This data can be useful in comparing residues across proteins and in predicting important residues for protein structure or function. Additionally, residues have measures of individual importance based on their position in the protein sequence and the entropy of that position across the multiple sequence alignment. Towards this end, CoevFeat offers an adjusted nearest-neighbor subgraph approach to representing residues based on their coevolutionary neighborhoods. The usefulness of these features is demonstrated with CoevMetal, a set of machine learning tools for identifying metal-binding residues in proteins and the specific metal that they bind. CoevMetal-SVM and CoevMetal-NN both perform better than existing bioinformatics benchmarks.

Committee: Alexey Porollo Ph.D. (Committee Chair); Gowtham Atluri Ph.D. (Committee Member); Kenneth Berman Ph.D. (Committee Member) Subjects: Computer Science

Doctor of Philosophy (PhD), Ohio University, 2019, Molecular and Cellular Biology (Arts and Sciences)

Gravitropism is a fundamental growth response in plants. The signal transduction process converts the perception of gravity to the response which causes the roots to bend toward and shoots to bend away from the direction of gravity. On Earth, the 1g gravitational force is ubiquitous, but in space, the force of gravity is negligible providing the ultimate control environment for gravity experiments. To identify the proteins and possible biochemical pathways participating in the signal transduction process, a proteomic study was designed to compare the proteins expressed in seedlings germinated on the International Space Station (ISS) to those germinated on Earth. Arabidopsis Col-0 seeds were sterilized and plated on 60mm petri plates, which were packed in spaceflight hardware and flown to the ISS. Duplicate sets of WT Col-0 seeds were kept at the Kennedy Space Center as ground controls and at Ohio University as additional controls for hardware and preservative. After return from the ISS, proteins were extracted and fractionated into membrane and soluble. Both fractions were analyzed using labeled tandem mass spectrometry at the Donald Danforth Plant Science Center. Differential abundance analysis revealed 129 soluble proteins and 137 membrane proteins that differed in seedlings germinated in ISS versus ground control (p < 0.05). Comparing the differentially abundant proteins from the current study with two previous proteomic experiments identified two membrane proteins and twelve soluble proteins that were differentially expressed in the three experiments. Network analysis of the fourteen proteins using STRING identified a potential interaction between PCAP1, a membrane bound protein with a phosphatidyl inositol binding site, and PATL2, a soluble protein that functions in membrane trafficking. PCAP1 and PATL2 were selected for further study as possible candidate genes for gravity signal transduction. Phenotypic analysis of pcap1 knockout mutants showed that infloresc (open full item for complete abstract)

Committee: Sarah Wyatt (Advisor); Morgan Vis-Chiasson (Committee Member); Alan Showalter (Committee Member); Michael Held (Committee Member) Subjects: Cellular Biology; Molecular Biology; Plant Biology