Interpretable Mechanistic And Machine Learning Models For Pre-Dicting Cardiac Remodeling From Biochemical And Biomechanical Features, Anamul Haque

All Dissertations

Biochemical and biomechanical signals drive cardiac remodeling, resulting in altered heart physiology and the precursor for several cardiac diseases, the leading cause of death for most racial groups in the USA. Reversing cardiac remodeling requires medication and device-assisted treatment such as Cardiac Resynchronization Therapy (CRT), but current interventions produce highly variable responses from patient to patient. Mechanistic modeling and Machine learning (ML) approaches have the functionality to aid diagnosis and therapy selection using various input features. Moreover, 'Interpretable' machine learning methods have helped make machine learning models fairer and more suited for clinical application. The overarching objective of this doctoral …

Determining The Effects Of Glycocalyx Modifications On The Electrophysical Properties Of Human Mesenchymal Stem Cells, Rominna E. Valentine Ico

Electronic Theses, Projects, and Dissertations

Human mesenchymal stem cells (hMSCs) have gained popularity in clinical trials due to their multipotent differentiation characteristics, ability to secrete bioactive molecules, migrate into diseased or damaged tissues, and their immunosuppressive properties. HMSC cultures are heterogeneous, containing stem cells, partially differentiated progenitor cells, and fully differentiated cells. One of the major challenges with hMSCs therapeutic potential is the inability to select specific cell subpopulations due to an insufficient number of biomarkers. Often the biomarkers used, like those for fluorescence-activated cell sorting, are not sufficient to define hMSCs because they overlap with other cell types. Consequently, there is a need to …

Gene Expression–Based Algorithms For The Identification Of Drug Combinations In Personalized Medicine, Lon Fong

Dissertations & Theses (Open Access)

Three of the major problems facing cancer therapeutics are 1) drug resistance, the intrinsic or acquired ability of cancer cells to evade the effect of the therapies used to treat them; 2) heterogeneity among individual patients’ disease at the molecular level and the resulting variability in therapeutic response; and 3) the limitations of genomics biomarkers in matching patients to the most effective therapy. One possible solution to drug resistance is the use of combination therapies rather than monotherapies. Use of multiple drugs, each with a different mechanism of action, lowers the chances that the cancer cells will develop or have …

Leveraging Mass Spectrometry-Based Proteomics And Post-Translational Modifications For System-Wide Understanding Of Bioenergy Plants And Their Environment, Him K. Shrestha

Doctoral Dissertations

Bioenergy research focuses on utilizing renewable biomass feedstocks to produce biofuels and bioproducts to address growing concerns about energy security and climate change. To better understand the details of bioenergy crop production and conversion to bioproducts, it is essential to characterize bioenergy plants and their environments at a molecular systems level. Mass spectrometry has emerged as a promising technique for detailed proteomic information, including post-translational modifications (PTMs), of molecular processes and cellular functions of biological systems. In this dissertation, proteomic approaches have been optimized and implemented to deepen our understanding of the interaction of plants and their environment in a …

Data-Driven Biomarker Panel Discovery In Ovarian Cancer Using Heterogenous Data Fusion On Exosomal And Non-Exosomal Microrna Expression Data, Paritra Mandal

All Dissertations

Ovarian cancer (OC) is an aggressive gynecological cancer and is currently the 5th leading cause of deaths due to cancer in women. High mortality rates are attributable to the vague pathogenesis and asymptomatic nature of the early stages. The development of a liquid biopsy for routine OC screening could help identify the disease at an earlier stage, making treatments more likely to be effective thereby increasing survival rates. Exosomes, small (~100nm) extracellular vesicles present in body fluids, have been shown to contain cancer-progression, onset, and related factors, making them good candidates for use in liquid biopsies. However, to date, only …

Methods And Tools To Improve Performance Of Plant Genome Analysis, Drew Ferrell

Theses and Dissertations

Multi -omics data analysis and integration facilitates hypothesis building toward an understanding of genes and pathway responses driven by environments. Methods designed to estimate and analyze gene expression, with regard to treatments or conditions, can be leveraged to understand gene-level responses in the cell. However, genes often interact and signal within larger structures such as pathways and networks. Complex studies guided toward describing dynamic genetic pathways and networks require algorithms or methods designed for inference based on gene interactions and related topologies. Classes of algorithms and methods may be integrated into generalized workflows for comparative genomics studies, as multi -omics …

Efficient Network Domination For Life Science Applications, Stephen K. Grady

Doctoral Dissertations

With the ever-increasing size of data available to researchers, traditional methods of analysis often cannot scale to match problems being studied. Often only a subset of variables may be utilized or studied further, motivating the need of techniques that can prioritize variable selection. This dissertation describes the development and application of graph theoretic techniques, particularly the notion of domination, for this purpose. In the first part of this dissertation, algorithms for vertex prioritization in the field of network controllability are studied. Here, the number of solutions to which a vertex belongs is used to classify said vertex and determine its …

The Effects Of Host-Like Environmental Signals And Gene Expression On Capsule Growth In Cryptococcus Neoformans, Yu Min Jung

McKelvey School of Engineering Theses & Dissertations

Cryptococcus neoformans is a fungal pathogen that causes cryptococcosis, a disease that kills almost 200,000 people worldwide each year. A unique feature of this deadly yeast is its polysaccharide capsule, which is known to be associated with its virulence. Here, we systematically explore the effects of all possible combinations of 4 capsule-inducing signals on gene expression, cell size, and capsule size. These signals are medium (YPD, DMEM or RPMI), temperature (30°C or 37°C), CO₂ (room air or 5%), cAMP (0 mM or 20 mM), and pH buffer (HEPES/no HEPES). We explore the effects of exogenous cAMP at a range …

Computational Analysis Of Transcriptional And Post-Transcriptional Feedback Loops In Development And Cell Differentiation, Benjamin Rigel Nordick

Masters Theses

Regulation of gene expression is critical to organism development and health. Positive and negative feedback in networks of gene regulatory interactions are associated with the maintenance of distinct cell states/types or oscillations, respectively. Recent computational studies identified two structures of positive feedback relevant to establishment of cell type: interconnected transcriptional “high-feedback” loops and a purely post-transcriptional feedback loop arising from multiple microRNA molecules cooperatively regulating one mRNA. The goals of this work were to develop methods for analyzing often-unintuitive high-feedback loops in large networks, generalize the two new regulatory structures to consider oscillation, and further explore the ability of post-transcriptional …

Multi-Omic Systems Biological Analysis Of Host-Microbe Interactions, Piet Jones

Doctoral Dissertations

Systems biology offers the opportunity to understand the complex mechanisms of various biological phenomena. The wealth of data that is produced, at an increasing rate, provides the potential to meet this opportunity. Here we take an applied approach to integrate multiple omic level data sources in order to generate biologically relevant hypotheses. We apply a novel analysis pipeline to model both, in concert, the microbial and transcriptomic signature from COVID-19 positive patients. We show patients may suffer from an increased microbial burden, with an increased pathogen potential. Gene expression evidence further shows patients may exhibit a compromised barrier immunity, owing …

Exploiting Chemogenetic And Genetic Interactions In Human Cells As An Avenue For New Therapeutic Opportunities, Medina Colic

Dissertations & Theses (Open Access)

The advent of CRISPR technology and its adaptation to the mammalian genome made whole-genome knockout screens possible directly in human cells. Gene knockout answers how essential that gene is for cell fitness and proliferation. Genes showing moderate to severe fitness defects are called essential genes and provide insights into disease-specific candidate therapeutic targets. Additionally, CRISPR offers other applications for genome editing. Two applications this dissertation is based on are 1) combination of gene knockout and drug treatment, which enables the identification of chemogenetic interactions, or gene mutations that enhance or suppress the activity of a drug, and 2) combinatorial editing, …

Bone Marrow Stroma-Induced Transcriptome Signatures Of Multiple Myeloma As Modulated By Junb, Jasleen Kaur Gandhi

Graduate Theses, Dissertations, and Problem Reports

The bone marrow (BM) microenvironment acts as a breeding ground for drug resistance in multiple myeloma (MM). The interaction with bone marrow stromal cells (BMSCs) confer environment-mediated drug resistance (EMDR) to multiple myeloma. We investigated BM stroma-induced transcriptome signatures of MM cells through a sophisticated analysis of gene expression. In particular, we defined transcription program modulated by JunB, an emerging regulator of MM pathogenesis and a member of the transcription factor superfamily activator protein 1 (AP-1), in response to BM stimulation. The data and results lay down a foundation for future studies to illustrate the regulatory role of JunB in …

Immunological Factors Associated With Siv/ Shiv Persistence In Diverse Tissue Niches, Omalla A. Olwenyi

Theses & Dissertations

The significant challenge towards a successful HIV cure lies in eradicating persistent viral reservoirs across diverse tissue niches. As a result, HIV-infected individuals have to resort to lifelong antiretroviral therapy. Recent news of supposed HIV eradication in a second patient has further re-invigorated the fields of HIV cure. However, a few barriers remain, such as the lack of currently available assays to accurately quantify viral reservoirs, limited information on cellular factors associated with persistence, and varied dynamics of the viral reservoir in various body compartments. Lastly, HIV-infected individuals live different lifestyles stemming from comorbid substance abuse including consumption of morphine, …

Analytical Considerations And Methods For Comprehensive Analysis Of Bacterial Phospholipidomics Using Hilic-Ms/Ms, David Thomas Reeves

Doctoral Dissertations

Omics technologies have rapidly evolved over the last half century through vast improvements in efficient extraction methodologies, advances in instrumentation for data collection, and a wide assortment of informatics tools to help deconvolute sample data sets. However, there are still untapped pools of molecules that warrant further analytical attention. As the frontline defense of the cell against exterior influences, the phospholipid membrane is key in structure, defense, and signaling, but current omics studies are only just now catching up to the potential hidden within cellular lipid profiles. Examination of shifts in phospholipid speciation and character could provide researchers with a …

Machine Learning-Based Risk Factor Analysis And Prevalence Prediction Of Intestinal Parasitic Infections, Ahmet Ay

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Investigation Of Arabidopsis Extremophyte Relatives, Schrenkiella Parvula And Eutrema Salsugineum Reveals Different Roads Leading To Salt Stress Tolerance, Kieu-Nga Thi Tran

LSU Doctoral Dissertations

How plants adapt to salt stress has been a central question in plant biology for decades. Yet we have not been able to fully understand the molecular networks and genetic mechanisms underlying this complex trait. Most of the genetic work on salinity stress has focused on understanding salt stress responses in the leading, yet a salt-sensitive model Arabidopsis thaliana. With the recent availability of genomes for wild-relatives of A. thaliana, we can now investigate how naturally salt adapted plants may have evolved modified or novel molecular networks to adapt to salt stress. Therefore, my research utilizes a comparative …

Understanding Potassium Toxicity Stress Responses Of The Extremophyte Schrenkiella Parvula Using Systems Biology Approaches, Pramod Pantha

LSU Doctoral Dissertations

Schrenkiella parvula is an extremophyte model closely related to Arabidopsis thaliana and Brassica crops. Its natural habitat includes shores of saline lakes in the Irano-Turanian region. It has adapted to grow in soils rich in multiple salts including Na⁺ and K⁺. I have investigated the genetic basis for high K⁺ tolerance in plants using S. parvula as a stress tolerant model compared to the premier plant model, Arabidopsis thaliana which is highly sensitive to salt stresses using physiological, ionomic, transcriptomic, and metabolomic approaches. Under high K⁺ stress, root system architecture changes significantly compared to control …

The Neurological Asymmetry Of Self-Face Recognition, Aleksandra Janowska, Brianna Balugas, Matthew Pardillo, Victoria Mistretta, Katherine Chavarria, Janet Brenya, Taylor Shelansky, Vanessa Martinez, Kitty Pagano, Nathira Ahmad, Samantha Zorns, Abigail Straus, Sarah Sierra, Julian Keenan

Department of Biology Faculty Scholarship and Creative Works

While the desire to uncover the neural correlates of consciousness has taken numerous directions, self-face recognition has been a constant in attempts to isolate aspects of self-awareness. The neuroimaging revolution of the 1990s brought about systematic attempts to isolate the underlying neural basis of self-face recognition. These studies, including some of the first fMRI (functional magnetic resonance imaging) examinations, revealed a right-hemisphere bias for self-face recognition in a diverse set of regions including the insula, the dorsal frontal lobe, the temporal parietal junction, and the medial temporal cortex. In this systematic review, we provide confirmation of these data (which are …

Impact Of Intratumor Heterogeneity And The Tumor Microenvironment In Shaping Tumor Evolution And Response To Therapy, Akash Mitra

Dissertations & Theses (Open Access)

Intratumor heterogeneity (ITH) is a crucial challenge in cancer treatment. The genotypic and phenotypic heterogeneity underlying diverse cancer types leads to subclonal variation, which may result in mixed or failed response to therapy. The heterogeneity at the tumor level, along with the tumor microenvironment (TME), often shapes tumor evolution and ultimately clinical outcome. Given that modern treatment paradigms increasingly expose patients with metastatic disease to multiple treatment modalities through the course of their disease, there exists a need to characterize robust and predictive biomarkers of response to therapy. In order to accurately characterize tumor evolution, we need to account for …

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 …

Engineering Modularity Of Ester Biosynthesis Across Biological Scales, Hyeongmin Seo

Doctoral Dissertations

Metabolic engineering and synthetic biology enable controlled manipulation of whole-cell biocatalysts to produce valuable chemicals from renewable feedstocks in a rapid and efficient manner, helping reduce our reliance on the conventional petroleum-based chemical synthesis. However, strain engineering process is costly and time-consuming that developing economically competitive bioprocess at industrial scale is still challenging. To accelerate the strain engineering process, modular cell engineering has been proposed as an innovative approach that harnesses modularity of metabolism for designing microbial cell factories. It is important to understand biological modularity and to develop design principles for effective implementation of modular cell engineering. In this …

Biases And Blind-Spots In Genome-Wide Crispr-Cas9 Knockout Screens, Merve Dede

Dissertations & Theses (Open Access)

Adaptation of the bacterial CRISPR-Cas9 system to mammalian cells revolutionized the field of functional genomics, enabling genome-scale genetic perturbations to study essential genes, whose loss of function results in a severe fitness defect. There are two types of essential genes in a cell. Core essential genes are absolutely required for growth and proliferation in every cell type. On the other hand, context-dependent essential genes become essential in an environmental or genetic context. The concept of context-dependent gene essentiality is particularly important in cancer, since killing cancer cells selectively without harming surrounding healthy tissue remains a major challenge. The toxicity of …

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 …

The Feasibility Of Renewable Natural Gas In New Jersey, Anneliese Dyer, Amelia Christine Miller, Brianna Chandra, Juan Galindo Maza, Carley Tran, Justin Bates, Vicky Olivier, Amy Tuininga

Publications

With traditional natural gas being one of the top options for heating in the United States and the present threat of climate change, there is a demand for an alternative clean fuel source. A Renewable Natural Gas Implementation Decision-Making Conceptual Model was created to provide a framework for considering the feasibility of renewable natural gas (RNG) projects and applied to New Jersey, specifically investigating landfills and wastewater treatment plants (WWTPs). Data from the US EPA’s Landfill Methane Outreach Program and New Jersey’s Department of Environmental Protection Sewage Sludge databases were used to identify seven landfills and 22 WWTPs as possible …

Development Of Tools For Atom-Level Interpretation Of Stable Isotope-Resolved Metabolomics Datasets, Huan Jin

Theses and Dissertations--Toxicology and Cancer Biology

Metabolomics is the global study of small molecules in living systems under a given state, merging as a new ‘omics’ study in systems biology. It has shown great promise in elucidating biological mechanism in various areas. Many diseases, especially cancers, are closely linked to reprogrammed metabolism. As the end point of biological processes, metabolic profiles are more representative of the biological phenotype compared to genomic or proteomic profiles. Therefore, characterizing metabolic phenotype of various diseases will help clarify the metabolic mechanisms and promote the development of novel and effective treatment strategies.

Advances in analytical technologies such as nuclear magnetic resonance …

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 …

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

Dissertations & 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 …

Investigation Of Proliferation Suppressors In Genetic Fitness Screens, Walter Frank Lenoir Iv

Dissertations & Theses (Open Access)

Innovation of CRISPR gene-editing technology has provided scientists genome manipulation tools that allowed rapid advancement of scientific capabilities and thus improved our ability to systematically study mammalian genetic functional profiles. Genome-wide CRISPR knockout screens conducted in collections of human cell lines can knock out genes at multiple loci, and have provided new insights into functional roles for independent genes. This method has launched massive efforts in looking across genetic backgrounds for context specific genetic vulnerabilities within cancer. Much of the research effort thus far has been spent on optimizing phenotype distinctions between essential, genes required for cell fitness, and non-essential, …

Molecular Mechanisms Of Boron Toxicity Tolerance In Plants, Guannan Wang

LSU Doctoral Dissertations

Boron toxicity is a worldwide agricultural problem that limits crop productivity and quality. However, our understanding on the genetic responses and adaption mechanisms to boron toxicity in plants is very limited. To address this gap in our knowledge, I compared boron stress-sensitive model, Arabidopsis thaliana and its stress-adapted relative Schrenkiella parvula to study how plants respond and adapt to excess boron at physiological, genomic, transcriptomic, and metabolic levels.

The overall project goal involved integration of multi-omics datasets to develop genome to phenome interpretations. To achieve this, I developed a python package, GOMCL, to facilitate the extraction of biologically meaningful information …

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 …