Identifying The Cell Composition And Clonal Diversity Of Supratentorial Ependymoma Using Single Cell Rna-Sequencing, James He

Honors Scholar Theses

Ependymoma is a primary solid tumor of the central nervous system. Supratentorial ependymoma (ST-EPN), a subtype of ependymomas, is driven by an oncogenic fusion between the ZFTA and RELA genes in 70% of cases. We introduced this fusion into neural progenitor cells of mice embryos via in utero electroporation of a non-viral binary piggyBac transposon system containing ZFTA-RELA. From preliminary data in the LoTurco lab, inducing the expression of ZFTA-RELA into different neural progenitor cells produces tumors of varying lethality and cellular composition. To define the cellular composition and subclonal diversity of ST-EPN tumors, we used single cell RNA-sequencing …

Dynamic Mechanisms Of Multidrug Resistance In Human Cancers And Gram Negative Pathogens, Lauren Ammerman

Biological Sciences Theses and Dissertations

This dissertation focuses upon dynamic agents of multidrug resistance (MDR). We used a combination of in silico and in vitro techniques to investigate two membrane transporters that confer MDR – P-glycoprotein, which confers MDR in human cancers, and MtrD, which confers MDR in Neisseria gonorrhoeae. Inhibitors targeting both proteins have tremendous potential for use as co-therapeutics in the treatment of multidrug resistant cancers, or of multidrug resistant infections. However, previously identified inhibitors of P-gp have failed clinical trials due to off-target effects and associated toxicities. Furthermore, the molecular mechanism of antibiotic transport by MtrD is poorly understood, and this dearth …

Development Of In-Silico Pipelines For Identification And Characterization Of Biomarker Panels And Therapeutic Interventions In Gastro-Intestinal (Gi) Cancers, Pranita Atri

Theses & Dissertations

Gastro-intestinal (GI) malignancies, including gastric, colorectal, and pancreatic cancers, have maintained their high overall mortality due to a lack of prognostic and diagnostic biomarkers and potential therapeutic modalities. While efforts have been made to improve both early detection and therapeutic interventions in these cancers, failure of conventional approaches have proven to be a big challenge, and alternate approaches are needed. Computational biology approaches owing to lesser time and more per target success rate offer a unique solution here. The current study explored the use of computational biology techniques to study the various aspects relating to GI malignancies. First, we sought …

Mucin And Splice Variant Profiles Of Pancreatic Adenocarcinoma Predict Patient Survival And Subtyping, Christopher M. Thompson

Theses & Dissertations

PDAC is a pancreatic epithelial malignancy and demonstrates aggressive progression and bleak patient prognosis. Despite decades of research, the evolution of novel diagnostics and intervention modalities for PDAC is stagnant. This dissertation explores the characteristic aberrant and elevated expression of mucins in PDAC. Beginning with the hypothesis that mucins are associated with disease aggressiveness, analysis of PDAC patient survival in TCGA revealed no associations between single mucin expression and patient survival. This led to the underlying issue of PDAC tumor cellularity since this disease demonstrates variability in the proportion of cancer cells within the tumor. Tumor purity assessed with the …

Discovery Of Novel Ubiquitin- And Methylation-Dependent Interactions Using Protein Domain Microarrays, Jianji Chen

Dissertations and Theses (Open Access)

Post-translational modifications (PTMs) drive signal transduction by interacting with "reader" proteins. Protein domain microarray is a high throughput platform to identify novel readers for PTMs. In this dissertation, I applied two protein domain microarrays identifying novel readers for histone H2Aub1 and H2Bub1, and H3TM K4me3. Ubiquitinations of histone H2A at K119 (H2Aub1) and histone H2B at K120 (H2Bub1) function in distinct transcription regulation and DNA damage repair pathways, likely mediated by specific "reader" proteins. There are only two H2Aub1-specific readers identified and no known H2Bub1-specific readers. Using a ubiquitin-binding domain microarray, I discovered the phospholipase A2-activating protein (PLAA) PFU domain …

Construction And Analysis Of Three Multi-Partite Synthetic Microbial Communities, Alexander J. Lazzara, Jacob K. Fanning

Honors Theses

Microbial Communities are of interest to molecular biologists hoping to understand the nature of metabolic interactions between co-existing, or possibly mutualistic, organisms. These interactions are ubiquitous in nature, but understanding the molecular mechanisms involved remains challenging and not well understood. Here, we design three tri-partite microbial circuits based on possible interactions among involved microbes, which are discussed and may suggest mutualistic interactions. Carbon and nitrogen molecular pathways and the intracellular metabolism of each microbe is discussed. We present minimal growth media that will ensure that organisms utilize available resources, which may originate from metabolic processes in neighboring microbes, simulating a …

Machine Learning Models For Deciphering Regulatory Mechanisms And Morphological Variations In Cancer, Saman Farahmand

Graduate Doctoral Dissertations

The exponential growth of multi-omics biological datasets is resulting in an emerging paradigm shift in fundamental biological research. In recent years, imaging and transcriptomics datasets are increasingly incorporated into biological studies, pushing biology further into the domain of data-intensive-sciences. New approaches and tools from statistics, computer science, and data engineering are profoundly influencing biological research. Harnessing this ever-growing deluge of multi-omics biological data requires the development of novel and creative computational approaches. In parallel, fundamental research in data sciences and Artificial Intelligence (AI) has advanced tremendously, allowing the scientific community to generate a massive amount of knowledge from data. Advances …

Simulation Of The Interaction Between Striated Muscle Unc-45 And Transcription Factor Gata-4, Drake Alexander Duncan

Electronic Theses and Dissertations

Striated Muscle UNC-45, also known as UNC-45b, is an important protein that acts as a chaperone for myosin in cardiac and skeletal muscles, binding to myosin at its C-terminal UCS domain and regulating its assembly into thick filaments and sarcomeric structures. The UCS domain contains a large loop that is believed to be the first point of interaction between myosin and UNC-45b. GATA-4 is an essential transcription factor that facilitates transcription of several genes in cardiac development, particularly alpha-heavy chain myosin in heart tissue. Recently, studies have shown that there is interaction of GATA-4 with UNC-45b and that GATA-4 binds …

Toward The Discovery Of Biological Functions Associated With The Mechanosensor Mtl1p Of Saccharomyces Cerevisiae Via Integrative Multi-Omics Analysis, Nelson Martínez-Matías, Nataliya Chorna, Sahily González-Crespo, Lilliam Villanueva, Ingrid Montes-Rodríguez, Loyda M. Melendez-Aponte, Abiel Roche-Lima, Kelvin Carrasquillo-Carrión, Ednalise Santiago-Cartagena, Brian C. Rymond, Mohan Babu, Igor Stagljar, José R. Rodríguez-Medina

Biology Faculty Publications

Functional analysis of the Mtl1 protein in Saccharomyces cerevisiae has revealed that this transmembrane sensor endows yeast cells with resistance to oxidative stress through a signaling mechanism called the cell wall integrity pathway (CWI). We observed upregulation of multiple heat shock proteins (HSPs), proteins associated with the formation of stress granules, and the phosphatase subunit of trehalose 6-phosphate synthase which suggests that mtl1Δ strains undergo intrinsic activation of a non-lethal heat stress response. Furthermore, quantitative global proteomic analysis conducted on TMT-labeled proteins combined with metabolome analysis revealed that mtl1Δ strains exhibit decreased levels of metabolites of carboxylic acid metabolism, decreased …

Computational And Experimental Investigation Into The Determinants Of Protein Structure, Folding, And Stability In The Β-Grasp Superfamily, John T. Bedford Ii

Chemistry & Biochemistry Theses & Dissertations

Elucidating the mechanisms of protein folding and unfolding is one of the greatest scientific challenges in basic science. The overarching goal is to predict three-dimensional structures from their amino acid sequences. Understanding the determinants of protein folding and stability can be facilitated through the study of evolutionarily related but diverse proteins. Insights can also be gained through the study of proteins from extremophiles that may more closely resemble the primordial proteins. In this doctoral research, three aims were accomplished to characterize the structure, folding and unfolding behavior within the β-grasp superfamily. We propose that the determinants of structure, stability, and …

A Test Of Rad Capture Sequencing On Ethanol-Preserved Centennial And Contemporary Specimens Of Philippine Fishes, Madeleine I. Kenton

Biological Sciences Theses & Dissertations

Understanding the relationship between ecological characteristics and genetic change in natural populations in different time scales can reveal how anthropogenic stressors affect natural populations and can improve the success of conservation strategies. The purpose of the Philippines Partnerships for International Research and Education (PIRE) project is to examine levels of genetic change between historical fish samples collected by the USS Albatross expedition in the early 1900s in the Philippines and contemporary populations collected at the same localities. This study tests genetic protocols to process historical and contemporary DNA for simultaneous comparison. Two DNA library preparation methods, single digest RADseq (“un-baited” …

Biological Activity And Solubility Of 5-Methoxy-1,4-Benzoquinone Having Bromoheptyl And Bromodecyl Substituents In The N-Octanol/Water System, Siti Mariyah Ulfa, Fath Dwisari, Laras Pangesti, Mohammad Farid Rahman

Makara Journal of Science

The biological activity and solubility of compounds are influenced by its chemical structure. These properties can be improved by substituting alkyl, alkoxy, and/or haloalkane in the parent skeleton. In this research, the synthesis of 3-(7-bromoheptyl)-2-methyl-5-methoxy-1,4-benzoquinone (3a) and 3-(10-bromodecyl)-2-methyl-5-methoxy-1,4-benzoquinone (3b) was achieved through the decarboxylation reaction. The solubility and biological activity of 3a and 3b were compared with that of thymoquinone (TQ), which acts as an anti-inflammatory agent. Compounds 3a and 3b were successfully synthesized and analyzed using Fourier Transform Infra-Red (FTIR) and Nuclear Magnetic Resonance (NMR). The FTIR spectrum showed the increasing intensity of …

A Comparison Of Intertidal Metazoan Biodiversity Between Previously Oiled Sheared And Intact Marsh Margins And Between Multiple Salinity Zones In The Coastal Marshes Of Louisiana, Patrick M. Rayle

LSU Master's Theses

Marshes in Louisiana are under threat from numerous natural and anthropogenic sources. A consequence of these threats are sheared marsh margins, which result from the impact of storm surge on previously oiled, weakened marsh. These conditions occurred in Louisiana marshes after Hurricane Isaac in 2012 followed the Deepwater Horizon oil spill in 2010, particularly in the shorelines surrounding Bay Jimmy. The second and third chapters of this thesis focus on the differences in biodiversity between the sheared and intact marsh margins in impacted sites in Bay Jimmy. Metabarcoding methods were used to determine community composition of the sediment within marsh …

Machine Learning And Bioinformatic Insights Into Key Enzymes For A Bio-Based Circular Economy, Japheth E. Gado

Theses and Dissertations--Chemical and Materials Engineering

The world is presently faced with a sustainability crisis; it is becoming increasingly difficult to meet the energy and material needs of a growing global population without depleting and polluting our planet. Greenhouse gases released from the continuous combustion of fossil fuels engender accelerated climate change, and plastic waste accumulates in the environment. There is need for a circular economy, where energy and materials are renewably derived from waste items, rather than by consuming limited resources. Deconstruction of the recalcitrant linkages in natural and synthetic polymers is crucial for a circular economy, as deconstructed monomers can be used to manufacture …

Purification And Activity Analysis Of A Highly Active Recombinant Catalase From Psychrophilic Bacterium Psychrobacter Cryohaloentis, Andrew Stewart

Honors Program Theses

To date, the genus Psychrobacter includes 37 recognized bacterial species isolated from different sources ranging from Siberian permafrost (P. cryohalolentis) to seal feces (P. lutiphocae). Due to its diverse ecological niches, several species belonging to the genus have different enzymatic activities with potential applications in bioremediation and the food industry. In this study, a bioprospecting approach was used to perform a in depth analysis of a Psychrobacter-like bacterial strain isolated from goose feces (designated as Psychrobacter unknown). The phylogenetic analysis of 16S rRNA gene and homologous sequence studies suggest that the strain may represent a novel species of the Psychrobacter …

A Bioinformatic Analysis Of The Biosynthesis Of Carotenoids In The Copepod Tigriopus Californicus, Anchalya Balasubramaniam

Theses and Dissertations (Comprehensive)

Abstract

Biological pigments, also called biochromes, are coloured compounds which are displayed by a variety of life forms, including animals, due to selective colour absorption. The combination of light absorption and reflection enables each pigment to portray a distinct colour which results in the broad spectrum of colours we observe in our surroundings. Carotenoids are a large group of yellow, orange, and red biological pigments found in living organisms. Our current biomolecular knowledge of carotenoids is heavily derived from studying the pathway in photosynthetic prokaryotes, bacteria, fungi, and plants. Carotenoid pigments are exceptionally multifunctional as they act as photo-protectors against …

Structure Based Prediction Of A Novel Gpr120 Antagonist Based On Pharmacophore Screening And Molecular Dynamics Simulations, Ajay Pal Mr, Gemma K. Kinsella, James Curtin

Articles

The G-protein coupled receptor, GPR120, has ubiquitous expression and multifaceted roles in modulating metabolic and anti-inflammatory processes. Recent implications of its role in cancer progression have presented GPR120 as an attractive oncogenic drug target. GPR120 gene knockdown in breast cancer studies revealed a role of GPR120-induced chemoresistance in epirubicin and cisplatin-induced DNA damage in tumour cells. Higher expression and activation levels of GPR120 is also reported to promote tumour angiogenesis and cell migration in colorectal cancer. Some agonists targeting GPR120 have been reported, such as TUG891 and Compound39, but to date development of small-molecule inhibitors of GPR120 is limited. …

Computational Analysis And Prediction Of Intrinsic Disorder And Intrinsic Disorder Functions In Proteins, Akila I. Katuwawala

Theses and Dissertations

COMPUTATIONAL ANALYSIS AND PREDICTION OF INTRINSIC DISORDER AND INTRINSIC DISORDER FUNCTIONS IN PROTEINS

By Akila Imesha Katuwawala

A dissertation submitted in partial fulfillment of the requirements for the degree of Engineering, Doctor of Philosophy with a concentration in Computer Science at Virginia Commonwealth University.

Virginia Commonwealth University, 2021

Director: Lukasz Kurgan, Professor, Department of Computer Science

Proteins, as a fundamental class of biomolecules, have been studied from various perspectives over the past two centuries. The traditional notion is that proteins require fixed and stable three-dimensional structures to carry out biological functions. However, there is mounting evidence regarding a “special” class …

Cryogenic Electron-Microscopy (Cryo-Em) Analysis Of Mscs, Ynai, Connexin 26 And Bioinformatic Analysis Of Cysteine And Serine In Experimental Protein Structures, Claudio Catalano

Theses and Dissertations

Functional insights into macromolecules lie in the arrangement of their molecular structures. Investigating the atomic framework of a biomolecule could unwind its biochemical mechanism, providing aid to many relevant biological questions, thus facilitating drug discovery processes. Two approaches have been used to gain knowledge at the atomic level of a protein function: experimental and computational methodologies.

From an experimental perspective, membrane proteins (MPs) were investigated. Such proteins represent ~20% of the human proteome, and ~60% of them are drug targets since they are exposed to the surface of cells and are responsible for a wide range of fundamental functions like …

Molecular And Genetic Studies On A Sipd/Ipad-Related Virulence Spike Protein From Immune-Suppressive Particles Of A Drosophila Parasitoid, Carlo Miguel A. Sevilla

Dissertations and Theses

Parasitoid wasps are effective biological control agents that have evolved intricate host immune suppression strategies to overcome host immune defenses. The most important anti-parasite defense mechanism is encapsulation, where the host’s blood cells surround the wasp egg. In the Drosophila/Leptopilina host-parasitoid system, extracellular vesicles (EVs) are oviposited along with the wasp egg. The EVs possess spikes and contain hundreds of proteins, some of which enable wasp eggs to escape encapsulation by changing the morphology and function of hemocytes, or killing them. Previous studies have identified an abundant surface/spike protein (SSp40) from Leptopilina heterotoma EVs. While p40, a predicted …

Applications Of Machine Learning In Microbial Forensics, Ryan B. Ghannam

Dissertations, Master's Theses and Master's Reports

Microbial ecosystems are complex, with hundreds of members interacting with each other and the environment. The intricate and hidden behaviors underlying these interactions make research questions challenging – but can be better understood through machine learning. However, most machine learning that is used in microbiome work is a black box form of investigation, where accurate predictions can be made, but the inner logic behind what is driving prediction is hidden behind nontransparent layers of complexity.

Accordingly, the goal of this dissertation is to provide an interpretable and in-depth machine learning approach to investigate microbial biogeography and to use micro-organisms as …

Comparison Of Standard And Environmental Dna Methods For Estimating Chinook Salmon Smolt Abundance In The Klamath River, California, Doyle Joseph Coyne

Cal Poly Humboldt theses and projects

Evaluating abundance of juvenile salmonids is critical to conservation and management. Current abundance estimation involves use of rotary screw traps and mark-recapture studies. Use of environmental DNA (eDNA) in water samples offers a noninvasive and less expensive approach that may potentially improve or eventually replace traditional monitoring. Here I evaluate the utility of eDNA to predict weekly abundance estimates of outmigrating Chinook salmon (Oncorhynchus tshawytscha) smolts in the Klamath River, California. A total of 15 water samples were collected per week over the 17-week smolt outmigration in both 2019 and 2020. Chinook salmon eDNA concentration in each water …

Pathway‐Extended Gene Expression Signatures Integrate Novel Biomarkers That Improve Predictions Of Patient Responses To Kinase Inhibitors, Ashis Bagchee‐Clark, Eliseos J. Mucaki, Tyson Whitehead, Peter Rogan

Biochemistry Publications

Cancer chemotherapy responses have been related to multiple pharmacogenetic biomarkers, often for the same drug. This study utilizes machine learning to derive multi‐gene expression signatures that predict individual patient responses to specific tyrosine kinase inhibitors, including erlotinib, gefitinib, sorafenib, sunitinib, lapatinib and imatinib. Support vector machine (SVM) learning was used to train mathematical models that distinguished sensitivity from resistance to these drugs using a novel systems biology‐based approach. This began with expression of genes previously implicated in specific drug responses, then expanded to evaluate genes whose products were related through biochemical pathways and interactions. Optimal pathway‐extended SVMs predicted responses in …

A Context-Forward In Vivo Functional Genomics Platform For Target Discovery And Establishing Vulnerability Context In Pancreatic Cancer, Johnathon Rose, Johnathon Lynn Rose

Dissertations and Theses (Open Access)

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a very poor patient prognosis (5-year survival of ≤ 7%). While transcriptional profiling has aided in the classification of this disease into at least two broader subtypes, this alone has so far been insufficient to inform on more nuanced patterns of oncogenic dependency. We hypothesized that a more comprehensive and granular characterization of PDAC disease diversity is required to establish relevant context for targeted therapy. To this end, we sought to establish an integrated platform to: i) more comprehensively characterize differential oncogenic signaling across our tumor models, and ii) establish …

Development Of Computational To Ols To Target Microrna, Luo Song

Dissertations and Theses (Open Access)

MicroRNAs (a.k.a, miRNAs) play an important role in disease development. However, few of their structures have been determined and structure-based computational methods remain challenging in accurately predicting their interactions with small molecules. To address this issue, my thesis is to develop integrated approaches to screening for novel inhibitors by targeting specific structure motifs in miRNAs. The project starts with implementing a tool to find potential miRNA targets with desired motifs. I combined both sequence information of miRNAs and known RNA structure data from Protein Data Bank (PDB) to predict the miRNA structure and identify the motif to target, then I …

New Methods For Deep Learning Based Real-Valued Inter-Residue Distance Prediction, Jacob Barger

Theses

Background: Much of the recent success in protein structure prediction has been a result of accurate protein contact prediction--a binary classification problem. Dozens of methods, built from various types of machine learning and deep learning algorithms, have been published over the last two decades for predicting contacts. Recently, many groups, including Google DeepMind, have demonstrated that reformulating the problem as a multi-class classification problem is a more promising direction to pursue. As an alternative approach, we recently proposed real-valued distance predictions, formulating the problem as a regression problem. The nuances of protein 3D structures make this formulation appropriate, allowing predictions …

Pathway-Extended Gene Expression Signatures Integrate Novel Biomarkers That Improve Predictions Of Patient Responses To Kinase Inhibitors, Ashis Jem Bagchee-Clark, Eliseos J. Mucaki, Tyson Whitehead, Peter Rogan

Biochemistry Publications

No abstract provided.

Atom Identifiers Generated By A Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization Across Metabolic Databases, Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley

Molecular and Cellular Biochemistry Faculty Publications

Metabolic flux analysis requires both a reliable metabolic model and reliable metabolic profiles in characterizing metabolic reprogramming. Advances in analytic methodologies enable production of high-quality metabolomics datasets capturing isotopic flux. However, useful metabolic models can be difficult to derive due to the lack of relatively complete atom-resolved metabolic networks for a variety of organisms, including human. Here, we developed a neighborhood-specific graph coloring method that creates unique identifiers for each atom in a compound facilitating construction of an atom-resolved metabolic network. What is more, this method is guaranteed to generate the same identifier for symmetric atoms, enabling automatic identification of …

Current Scenario Of Covid-19 With Epidemiological And Phylogenetic Analysis Of Pakistani Coronavirus: A Review, Asma Altaf, Wafa Iqbal, Sidra Younis, Farah Deeba

Journal of Bioresource Management

A novel corona virus named as 2019 n-CoV was identified to be the actual cause of an outbreak of respiratory illness in Wuhan, China beginning in late December 2019. This respiratory disease was named as COVID-19 by WHO. There are many countries affected by COVID-19 including Pakistan. In this review we have provided a brief introduction of COVID-19 and discussed epidemiological and phylogenetic analysis of Pakistani novel corona virus strain. Our epidemiological analysis of data till 16^th May 2020 showed rapidly increasing number of new cases, while at the same time a higher recovery rate than number of deaths …

Machine Learning Applications For Drug Repurposing, Hansaim Lim

Dissertations, Theses, and Capstone Projects

The cost of bringing a drug to market is astounding and the failure rate is intimidating. Drug discovery has been of limited success under the conventional reductionist model of one-drug-one-gene-one-disease paradigm, where a single disease-associated gene is identified and a molecular binder to the specific target is subsequently designed. Under the simplistic paradigm of drug discovery, a drug molecule is assumed to interact only with the intended on-target. However, small molecular drugs often interact with multiple targets, and those off-target interactions are not considered under the conventional paradigm. As a result, drug-induced side effects and adverse reactions are often neglected …