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- Genre: Academic theses
Description
Rabies disease remains enzootic among raccoons, skunks, foxes and bats in the United States. It is of primary concern for public-health agencies to control spatial spread of rabies in wildlife and its potential spillover infection of domestic animals and humans. Rabies is invariably fatal in wildlife if untreated, with a non-negligible incubation period. Understanding how this latency affects spatial spread of rabies in wildlife is the concern of chapter 2 and 3. Chapter 1 deals with the background of mathematical models for rabies and lists main objectives. In chapter 2, a reaction-diffusion susceptible-exposed-infected (SEI) model and a delayed diffusive susceptible-infected (SI) model are constructed to describe the same epidemic process -- rabies spread in foxes. For the delayed diffusive model a non-local infection term with delay is resulted from modeling the dispersal during incubation stage. Comparison is made regarding minimum traveling wave speeds of the two models, which are verified using numerical experiments. In chapter 3, starting with two Kermack and McKendrick's models where infectivity, death rate and diffusion rate of infected individuals can depend on the age of infection, the asymptotic speed of spread $c^\ast$ for the cumulated force of infection can be analyzed. For the special case of fixed incubation period, the asymptotic speed of spread is governed by the same integral equation for both models. Although explicit solutions for $c^\ast$ are difficult to obtain, assuming that diffusion coefficient of incubating animals is small, $c^\ast$ can be estimated in terms of model parameter values. Chapter 4 considers the implementation of realistic landscape in simulation of rabies spread in skunks and bats in northeast Texas. The Finite Element Method (FEM) is adopted because the irregular shapes of realistic landscape naturally lead to unstructured grids in the spatial domain. This implementation leads to a more accurate description of skunk rabies cases distributions.
ContributorsLiu, Hao (Author) / Kuang, Yang (Thesis advisor) / Jackiewicz, Zdzislaw (Committee member) / Lanchier, Nicolas (Committee member) / Smith, Hal (Committee member) / Thieme, Horst (Committee member) / Arizona State University (Publisher)
Created2013
Description
Bacteriophage (phage) are viruses that infect bacteria. Typical laboratory experiments show that in a chemostat containing phage and susceptible bacteria species, a mutant bacteria species will evolve. This mutant species is usually resistant to the phage infection and less competitive compared to the susceptible bacteria species. In some experiments, both susceptible and resistant bacteria species, as well as phage, can coexist at an equilibrium for hundreds of hours. The current research is inspired by these observations, and the goal is to establish a mathematical model and explore sufficient and necessary conditions for the coexistence. In this dissertation a model with infinite distributed delay terms based on some existing work is established. A rigorous analysis of the well-posedness of this model is provided, and it is proved that the susceptible bacteria persist. To study the persistence of phage species, a "Phage Reproduction Number" (PRN) is defined. The mathematical analysis shows phage persist if PRN > 1 and vanish if PRN < 1. A sufficient condition and a necessary condition for persistence of resistant bacteria are given. The persistence of the phage is essential for the persistence of resistant bacteria. Also, the resistant bacteria persist if its fitness is the same as the susceptible bacteria and if PRN > 1. A special case of the general model leads to a system of ordinary differential equations, for which numerical simulation results are presented.
ContributorsHan, Zhun (Author) / Smith, Hal (Thesis advisor) / Armbruster, Dieter (Committee member) / Kawski, Matthias (Committee member) / Kuang, Yang (Committee member) / Thieme, Horst (Committee member) / Arizona State University (Publisher)
Created2012
Description
In vertebrate outer retina, changes in the membrane potential of horizontal cells affect the calcium influx and glutamate release of cone photoreceptors via a negative feedback. This feedback has a number of important physiological consequences. One is called background-induced flicker enhancement (BIFE) in which the onset of dim background enhances the center flicker response of horizontal cells. The underlying mechanism for the feedback is still unclear but competing hypotheses have been proposed. One is the GABA hypothesis, which states that the feedback is mediated by gamma-aminobutyric acid (GABA), an inhibitory neurotransmitter released from horizontal cells. Another is the ephaptic hypothesis, which contends that the feedback is non-GABAergic and is achieved through the modulation of electrical potential in the intersynaptic cleft between cones and horizontal cells. In this study, a continuum spine model of the cone-horizontal cell synaptic circuitry is formulated. This model, a partial differential equation system, incorporates both the GABA and ephaptic feedback mechanisms. Simulation results, in comparison with experiments, indicate that the ephaptic mechanism is necessary in order for the model to capture the major spatial and temporal dynamics of the BIFE effect. In addition, simulations indicate that the GABA mechanism may play some minor modulation role.
ContributorsChang, Shaojie (Author) / Baer, Steven M. (Thesis advisor) / Gardner, Carl L (Thesis advisor) / Crook, Sharon M (Committee member) / Kuang, Yang (Committee member) / Ringhofer, Christian (Committee member) / Arizona State University (Publisher)
Created2012
Description
The splicing of precursor messenger RNAs (pre-mRNAs) plays an essential role in dictating the mature mRNA profiles of eukaryotic cells. Mis-regulation of splicing, due to mutations in pre-mRNAs or in components of the splicing machinery, is associated with many diseases. Therefore, knowledge of pre-mRNA splicing mechanisms is required to understand gene expression regulation during states of homeostasis and disease, and for the development of therapeutic interventions.Splicing is catalyzed by the spliceosome, a dynamic and protein-rich ribozyme composed of five small nuclear ribonucleoproteins (snRNPs) and ~170 auxiliary factors. Early interactions that occur in prespliceosomal complexes formed by the 5′- and 3′-splice-site bound U1 and U2 snRNPs are responsible for committing introns for removal. However, the mechanisms underlying these early interactions remain to be fully characterized for understanding the influence of alternative splicing factors and the impact of recurrent disease-associated mutations in prespliceosomal proteins. The goal of my dissertation research was to delineate the role of the U1 small nuclear RNA (snRNA) during prespliceosome assembly. By applying a cellular minigene reporter assay and a variety of in vitro techniques including cell-free protein expression, UV-crosslinking, electrophoretic mobility shift assays, surface plasmon resonance, and RNA affinity purification, my work establishes critical roles for the U1 snRNA stem-loops 3 (SL3) and 4 (SL4) in formation of intron definition interactions during prespliceosome assembly. Previously, the SL4 of the U1 snRNA was shown to form a molecular bridge across introns by contacting the U2-specific splicing factor 3A1 (SF3A1). I identified the Ubiquitin-like domain of SF3A1 as a non-canonical RNA binding domain responsible for U1-SL4 binding. I also determined a role for the SL3 region of the U1 snRNA in splicing and characterized the spliceosomal RNA helicase UAP56 as an SL3 interacting protein. By knocking-down the SL3- and SL4-interacting proteins, I confirmed that U1 splicing activity in vivo relies on UAP56 and SF3A1 and that their functions are interdependent. These findings, in addition to the observations made using in vitro splicing assays, support a model whereby UAP56, through its interaction with U1-SL3, enhances the cross-intron interaction between U1-SL4 and SF3A1 to promote prespliceosome formation.
ContributorsMartelly, William (Author) / Sharma, Shalini (Thesis advisor) / Mangone, Marco (Thesis advisor) / Gustin, Kurt (Committee member) / Chen, Julian (Committee member) / Arizona State University (Publisher)
Created2021
Description
Glioblastoma (GBM), the most common and aggressive primary brain tumor affecting adults, is characterized by an aberrant yet druggable epigenetic landscape. The Histone Deacetylases (HDACs), a major family of epigenetic regulators, favor transcriptional repression by mediating chromatin compaction and are frequently overexpressed in human cancers, including GBM. Hence, over the last decade there has been considerable interest in using HDAC inhibitors (HDACi) for the treatment of malignant primary brain tumors. However, to date most HDACi tested in clinical trials have failed to provide significant therapeutic benefit to patients with GBM. This is because current HDACi have poor or unknown pharmacokinetic profiles, lack selectivity towards the different HDAC isoforms, and have narrow therapeutic windows. Isoform selectivity for HDACi is important given that broad inhibition of all HDACs results in widespread toxicity across different organs. Moreover, the functional roles of individual HDAC isoforms in GBM are still not well understood. Here, I demonstrate that HDAC1 expression increases with brain tumor grade and is correlated with decreased survival in GBM. I find that HDAC1 is the essential HDAC isoform in glioma stem cells and its loss is not compensated for by its paralogue HDAC2 or other members of the HDAC family. Loss of HDAC1 alone has profound effects on the glioma stem cell phenotype in a p53-dependent manner and leads to significant suppression of tumor growth in vivo. While no HDAC isoform-selective inhibitors are currently available, the second-generation HDACi quisinostat harbors high specificity for HDAC1. I show that quisinostat exhibits potent growth inhibition in multiple patient-derived glioma stem cells. Using a pharmacokinetics- and pharmacodynamics-driven approach, I demonstrate that quisinostat is a brain-penetrant molecule that reduces tumor burden in flank and orthotopic models of GBM and significantly extends survival both alone and in combination with radiotherapy. The work presented in this thesis thereby unveils the non-redundant functions of HDAC1 in therapy- resistant glioma stem cells and identifies a brain-penetrant HDACi with higher selectivity towards HDAC1 as a potent radiosensitizer in preclinical models of GBM. Together, these results provide a rationale for developing quisinostat as a potential adjuvant therapy for the treatment of GBM.
ContributorsLo Cascio, Costanza (Author) / LaBaer, Joshua (Thesis advisor) / Mehta, Shwetal (Committee member) / Mirzadeh, Zaman (Committee member) / Mangone, Marco (Committee member) / Paek, Andrew (Committee member) / Arizona State University (Publisher)
Created2022
Description
Advances in sequencing technology have generated an enormous amount of data over the past decade. Equally advanced computational methods are needed to conduct comparative and functional genomic studies on these datasets, in particular tools that appropriately interpret indels within an evolutionary framework. The evolutionary history of indels is complex and often involves repetitive genomic regions, which makes identification, alignment, and annotation difficult. While previous studies have found that indel lengths in both deoxyribonucleic acid and proteins obey a power law, probabilistic models for indel evolution have rarely been explored due to their computational complexity. In my research, I first explore an application of an expectation-maximization algorithm for maximum-likelihood training of a codon substitution model. I demonstrate the training accuracy of the expectation-maximization on my substitution model. Then I apply this algorithm on a published 90 pairwise species dataset and find a negative correlation between the branch length and non-synonymous selection coefficient. Second, I develop a post-alignment fixation method to profile each indel event into three different phases according to its codon position. Because current codon-aware models can only identify the indels by placing the gaps between codons and lead to the misalignment of the sequences. I find that the mouse-rat species pair is under purifying selection by looking at the proportion difference of the indel phases. I also demonstrate the power of my sliding-window method by comparing the post-aligned and original gap positions. Third, I create an indel-phase moore machine including the indel rates of three phases, length distributions, and codon substitution models. Then I design a gillespie simulation that is capable of generating true sequence alignments. Next I develop an importance sampling method within the expectation-maximization algorithm that can successfully train the indel-phase model and infer accurate parameter estimates from alignments. Finally, I extend the indel phase analysis to the 90 pairwise species dataset across three alignment methods, including Mafft+sw method developed in chapter 3, coati-sampling methods applied in chapter 4, and coati-max method. Also I explore a non-linear relationship between the dN/dS and Zn/(Zn+Zs) ratio across 90 species pairs.
ContributorsZhu, Ziqi (Author) / Cartwright, Reed A (Thesis advisor) / Taylor, Jay (Committee member) / Wideman, Jeremy (Committee member) / Mangone, Marco (Committee member) / Arizona State University (Publisher)
Created2022
Description
Protein-nucleic acid interactions are ubiquitous in biological systems playing a pivotal role in fundamental processes such as replication, transcription and translation. These interactions have been extensively used to develop biosensors, imaging techniques and diagnostic tools.This dissertation focuses on design of a small molecule responsive biosensor that employs transcription factor/deoxyribonucleic acid (DNA) interactions to detect 10 different analytes including antibiotics such as tetracyclines and erythromycin. The biosensor harnesses the multi-turnover collateral cleavage activity of Cas12a to provide signal amplification in less than an hour that can be monitored using fluorescence as well as on paper based diagnostic devices. In addition, the functionality of this assay was preserved when testing tap water and wastewater spiked with doxycycline. Overall, this biosensor has potential to expand the range of small molecule detection and can be used to identify environmental contaminants.
In second part of the dissertation, interactions between nonribosomal peptide synthetases (NRPS) and ribonucleic acid (RNA) were utilized for programming the synthesis of nonribosomal peptides. RNA scaffolds harboring peptide binding aptamers and interconnected using kissing loops to guide the assembly of NRPS modules modified with corresponding aptamer-binding peptides were built. A successful chimeric assembly of Ent synthetase modules was shown that was characterized by the production of Enterobactin siderophore. It was found that the programmed RNA/NRPS assembly could achieve up to 60% of the yield of wild-type biosynthetic pathway of the iron-chelator enterobactin.
Finally, a cas12a-based detection method for discriminating short tandem repeats where a toehold exchange mechanism was designed to distinguish different numbers of repeats found in Huntington’s disease, Spinocerebellar ataxia type 10 and type 36. It was observed that the system discriminates well when lesser number of repeats are present and provides weaker resolution as the size of DNA strands increases. Additionally, the system can identify Kelch13 mutations such as P553L, N458Y and F446I from the wildtype sequence for Artemisinin resistance detection.
This dissertation demonstrates the great utility of harnessing protein-nucleic acid interactions to construct biomolecular devices for detecting clinically relevant nucleic acid mutations, a variety of small molecule analyte and programming the production of useful molecules.
ContributorsChaudhary, Soma (Author) / Green, Alexander (Thesis advisor) / Stephanopoulos, Nicholas (Committee member) / Mangone, Marco (Committee member) / Arizona State University (Publisher)
Created2022
Description
The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic, declared in March 2020 resulted in an unprecedented scientific effort that led to the deployment in less than a year of several vaccines to prevent severe disease, hospitalizations, and death from coronavirus disease 2019 (COVID-19). Most vaccine models focus on the production of neutralizing antibodies against the spike (S) to prevent infection. As the virus evolves, new variants emerge that evade neutralizing antibodies produced by natural infection and vaccination, while memory T cell responses are long-lasting and resilient to most of the changes found in variants of concern (VOC). Several lines of evidence support the study of T cell-mediated immunity in SARS-CoV-2 infections. First, T cell reactivity against SARS-CoV-2 is found in both (cluster of differentiation) CD4+ and CD8+ T cell compartments in asymptomatic, mild, and severe recovered COVID-19 patients. Second, an early and stronger CD8+ T cell response correlates with less severe COVID-19 disease [1-4]. Third, both CD4+ and CD8+ T cells that are reactive to SARS-CoV-2 viral antigens are found in healthy unexposed individuals suggesting that cross-reactive and conserved epitopes may be protective against infection.
The current study is focused on the T cell-mediated response, with special attention to conserved, non-spike-cross-reactive epitopes that may be protective against SARS-CoV-2. The first chapter reviews the importance of epitope prediction in understanding the T cell-mediated responses to a pathogen. The second chapter centers on the validation of SARS-CoV-2 CD8+ T cell predicted peptides to find conserved, immunodominant, and immunoprevalent epitopes that can be incorporated into the next generation of vaccines against severe COVID-19 disease. The third chapter explores pre-existing immunity to SARS-CoV-2 in a pre-pandemic cohort and finds two highly immunogenic epitopes that are conserved among human common cold coronaviruses (HCoVs). To end, the fourth chapter explores the concept of T cell receptor (TCR) cross-reactivity by isolating SARS-CoV-2-reactive TCRs to elucidate the mechanisms of cross-reactivity to SARS-CoV-2 and other human coronaviruses (HCoVs).
ContributorsCarmona, Jacqueline (Author) / Anderson, Karen S (Thesis advisor) / Lake, Douglas (Thesis advisor) / Maley, Carlo (Committee member) / Mangone, Marco (Committee member) / LaBaer, Joshua (Committee member) / Arizona State University (Publisher)
Created2023
Description
Climate change is one of the most pressing issues affecting the world today. One of the impacts of climate change is on the transmission of mosquito-borne diseases (MBDs), such as West Nile Virus (WNV). Climate is known to influence vector and host demography as well as MBD transmission. This dissertation addresses the questions of how vector and host demography impact WNV dynamics, and how expected and likely climate change scenarios will affect demographic and epidemiological processes of WNV transmission. First, a data fusion method is developed that connects non-autonomous logistic model parameters to mosquito time series data. This method captures the inter-annual and intra-seasonal variation of mosquito populations within a geographical location. Next, a three-population WNV model between mosquito vectors, bird hosts, and human hosts with infection-age structure for the vector and bird host populations is introduced. A sensitivity analysis uncovers which parameters have the most influence on WNV outbreaks. Finally, the WNV model is extended to include the non-autonomous population model and temperature-dependent processes. Model parameterization using historical temperature and human WNV case data from the Greater Toronto Area (GTA) is conducted. Parameter fitting results are then used to analyze possible future WNV dynamics under two climate change scenarios. These results suggest that WNV risk for the GTA will substantially increase as temperature increases from climate change, even under the most conservative assumptions. This demonstrates the importance of ensuring that the warming of the planet is limited as much as possible.
ContributorsMancuso, Marina (Author) / Milner, Fabio A (Thesis advisor) / Kuang, Yang (Committee member) / Kostelich, Eric (Committee member) / Eikenberry, Steffen (Committee member) / Manore, Carrie (Committee member) / Arizona State University (Publisher)
Created2023
Description
Mutation is the source of heritable variation of genotype and phenotype, on which selection may act. Mutation rates describe a fundamental parameter of living things, which influence the rate at which evolution may occur, from viral pathogens to human crops and even to aging cells and the emergence of cancer. An understanding of the variables which impact mutation rates and their estimation is necessary to place mutation rate estimates in their proper contexts. To better understand mutation rate estimates, this research investigates the impact of temperature upon transcription rate error estimates; the impact of growing cells in liquid culture vs. on agar plates; the impact of many in vitro variables upon the estimation of deoxyribonucleic acid (DNA) mutation rates from a single sample; and the mutational hazard induced by expressing clustered regularly interspaced short palindromic repeat (CRISPR) proteins in yeast. This research finds that many of the variables tested did not significantly alter the estimation of mutation rates, strengthening the claims of previous mutation rate estimates across the tree of life by diverse experimental approaches. However, it is clear that sonication is a mutagen of DNA, part of an effort which has reduced the sequencing error rate of circle-seq by over 1,000-fold. This research also demonstrates that growth in liquid culture modestly skews the mutation spectrum of MMR- Escherichia coli, though it does not significantly impact the overall mutation rate. Finally, this research demonstrates a modest mutational hazard of expressing Cas9 and similar CRISPR proteins in yeast cells at an un-targeted genomic locus, though it is possible the indel rate has been increased by an order of magnitude.
ContributorsBaehr, Stephan (Author) / Lynch, Michael (Thesis advisor) / Geiler-Samerotte, Kerry (Committee member) / Mangone, Marco (Committee member) / Wilson, Melissa (Committee member) / Arizona State University (Publisher)
Created2023