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Genetic Characterization Of Antimicrobial Activities Of Endophytic Bacteria Burkholderia Strains Ms455 And Ms389, Jiayuan Jia

Theses and Dissertations

Strains MS455 and MS389, endophytic bacteria, were isolated from healthy soybean plant growing adjacent to a patch of plants affected by charcoal rot disease, caused by the fungal pathogen Macrophomina phaseolina. The complete genomes of both strains were sequenced and identified as Burkholderia species Strain MS455 exhibits broad-spectrum antifungal activities against economically important pathogens, including Aspergillus flavus. Random and site-specific mutations were employed in discovery of the genes that share high homology to the ocf gene cluster of Burkholderia contaminans strain MS14, which is responsible for production of the antifungal compound occidiofungin. RNA-seq analysis demonstrated ORF1, a …

Identifying Inhibitors Targeting The Nonstructural Protein 15 And Main Protease Of Coronaviruses Using Molecular Docking And Molecular Dynamics Simulation, Nakoa Kristen Webber

Theses and Dissertations

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2020 has impacted daily life globally for over a year. While multiple vaccines have been authorized for emergency use and one oral medication has entered clinical trials, we are still seeking antiviral drugs for a long-term treatment for SARS-CoV-2 as well as other coronaviruses. Computational drug screenings of two SARS-CoV-2 protein target candidates are presented in this thesis: the nidoviral RNA uridylate-specific endoribonuclease (Nsp15) and the main protease (Mpro) of SARS-CoV-2. Nonstructural proteins of coronaviruses were selected as targets as they are more conserved across coronavirus strains than …

Insights Into Halophilic Microbial Adaptation: Analysis Of Integrons And Associated Genomic Structures And Characterization Of A Nitrilase In Hypersaline Environments, Sarah Sonbol

Theses and Dissertations

Hypersaline environments are extreme habitats that can be exploited as biotechnological resources. Here, we characterized a nitrilase (NitraS-ATII) isolated from Atlantis II Deep brine pool. It showed higher thermal stability and heavy metal tolerance compared to a closely related nitrilase.

We also studied integrons in halophiles and hypersaline environments. Integrons are genetic platforms in which an integron integrase (IntI) mediates the excision and integration of gene cassettes at specific recombination sites. In order to search for integrons in halophiles and hypersaline metagenomes, we used a PCR-based approach, in addition to different bioinformatics tools, mainly IntegronFinder.

We found that integrons and …

Predicting Factors Of Re-Hospitalization After Medically Managed Intensive Inpatient Services In Opioid Use Disorder, Brian Kay

Theses and Dissertations

IntroductionOpioid use disorder has continued to rise in prevalence across the United States, with an estimated 2.5 million Americans ailing from the condition (NIDA, 2020). Medically managed detoxification incurs substantial costs and, when used independently, may not be effective in preventing relapse (Kosten & Baxter, 2019). While numerous studies have focused on predicting the factors of developing opioid use disorder, few have identified predictors of readmission to medically managed withdrawal at an inpatient level of care. Utilizing a high-fidelity dataset from a large multi-site behavioral health hospital, these predictors are explored.

MethodsPatients diagnosed with Opioid Use Disorder and hospitalized in …

Deep Learning For Multi-Tissue Cancer Classification Of Gene Expressions, Tarek Khorshed

Theses and Dissertations

We contribute in saving the lives of cancer patients through early detection and diagnosis, since one of the major challenges in cancer treatment is that patients are diagnosed at very late stages when appropriate medical interventions become less effective and full curative treatment is no longer achievable. Cancer classification using gene expressions is extremely challenging given the complexity and high dimensionality of the data. Current classification methods typically rely on samples collected from a single tissue type and perform a prerequisite of gene feature selection to avoid processing the full set of genes. These methods fall short in taking advantage …

Mining Selected Metagenomes/Metatranscriptomes For Biosynthetic Gene Clusters And Antimicrobial Resistance Genes, Ahmed Yamany

Theses and Dissertations

Antimicrobial resistance is one of the serious global challenges in the current century. The fact that resistance genes transfer between bacteria, coupled with the fact that the world is connected through complex dynamics. Studying microbial behavior and understanding the different factors coffering microbial resistance to a broad spectrum of the available drug classes, parallel with a comprehensive analysis of the natural microbial products as the primary source of the novel antibiotics, might shed some light on solutions for this problem. Microbial environments harbor a wide range of secondary metabolites (SM) with different functional groups. SMs are not directly involved in …

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 …