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- Member of: ASU Electronic Theses and Dissertations
- Status: Published
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
Globally, about two-thirds of the population is latently infected with herpes simplex virus type 1 (HSV-1). HSV-1 is a large double stranded DNA virus with a genome size of ~150kbp. Small defective genomes, which minimally contain an HSV-1 origin of replication and packaging signal, arise naturally via recombination during viral DNA replication. These small defective genomes can be mimicked by constructing a bacterial plasmid containing the HSV-1 origin of replication and packaging signal, transfecting these recombinant plasmids into mammalian cells, and infecting with a replicating helper virus. The absence of most viral genes in the amplicon vector allows large pieces of foreign DNA (up to 150kbp) to be incorporated. The HSV-1 amplicon is replicated and packaged by the helper virus to form HSV-1 particles containing the amplicon DNA. We constructed a novel HSV-1 amplicon vector system containing lambda phage-derived attR sites to facilitate insertion of transgenes by Invitrogen Gateway recombination. To demonstrate that the amplicon vectors work as expected, we packaged the vector constructs expressing Emerald GFP using the replication-competent helper viruses OK-14 or HSV-mScartlet-I-UL25 in Vero cells and demonstrate that the vector stock can subsequently transduce and express Emerald GFP. In further work, we will insert transgenes into the amplicon vector using Invitrogen Gateway recombination to study their functionality.
ContributorsVelarde, Kimberly (Author) / Hogue, Ian B (Thesis advisor) / Manfredsson, Fredric (Committee member) / Sandoval, Ivette (Committee member) / Varsani, Arvind (Committee member) / Arizona State University (Publisher)
Created2021
Description
Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (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
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
Description
Scientists are entrusted with developing novel molecular strategies for effective prophylactic and therapeutic interventions. Antivirals are indispensable tools that can be targeted at viral domains directly or at cellular domains indirectly to obstruct viral infections and reduce pathogenicity. Despite their transformative potential in healthcare, to date, antivirals have been clinically approved to treat only 10 out of the greater than 200 known pathogenic human viruses. Additionally, as obligate intracellular parasites, many virus functions are intimately coupled with host cellular processes. As such, the development of a clinically relevant antiviral is challenged by the limited number of clear targets per virus and necessitates an extensive insight into these molecular processes. Compounding this challenge, many viral pathogens have evolved to evade effective antivirals. Therefore, a means to develop virus- or strain-specific antivirals without detailed insight into each idiosyncratic biochemical mechanism may aid in the development of antivirals against a larger swath of pathogens. Such an approach will tremendously benefit from having the specific molecular recognition of viral species as the lowest barrier. Here, I modify a nanobody (anti-green fluorescent protein) that specifically recognizes non-essential epitopes (glycoprotein M-pHluorin chimera) presented on the extra virion surface of a virus (Pseudorabies virus strain 486). The nanobody switches from having no inhibitory properties (tested up to 50 μM) to ∼3 nM IC50 in in vitro infectivity assays using porcine kidney (PK15) cells. The nanobody modifications use highly reliable bioconjugation to a three-dimensional wireframe deoxyribonucleic acid (DNA) origami scaffold. Mechanistic studies suggest that inhibition is mediated by the DNA origami scaffold bound to the virus particle, which obstructs the internalization of the viruses into cells, and that inhibition is enhanced by avidity resulting from multivalent virus and scaffold interactions. The assembled nanostructures demonstrate negligible cytotoxicity (<10 nM) and sufficient stability, further supporting their therapeutic potential. If translatable to other viral species and epitopes, this approach may open a new strategy that leverages existing infrastructures – monoclonal antibody development, phage display, and in vitro evolution - for rapidly developing novel antivirals in vivo.
ContributorsPradhan, Swechchha (Author) / Hariadi, Rizal (Thesis advisor) / Hogue, Ian (Committee member) / Varsani, Arvind (Committee member) / Chen, Qiang (Committee member) / Arizona State University (Publisher)
Created2022
Description
Monkeypox virus (MPXV) is an orthopoxvirus that causes smallpox-like disease and has up to a 10% mortality rate, depending on the infectious strain. The global eradication of the smallpox virus has led to the decrease in smallpox vaccinations, which has led to a drastic increase in the number of human MPXV cases. MPXV has been named the most important orthopoxvirus to infect humans since the eradication of smallpox and has been the causative agent of the 2022 world-wide MPXV outbreak. Despite being highly pathogenic, MPXV contains a natural truncation at the N-terminus of its E3 homologue. Vaccinia virus (VACV) E3 protein has two domains: an N- terminus Z-form nucleic acid binding domain (Z-BD) and a C-terminus double stranded RNA binding domain (dsRBD). Both domains are required for pathogenesis, interferon (IFN) resistance, and protein kinase R (PKR) inhibition. The N-terminus is required for evasion of Z-DNA binding protein 1 (ZBP1)-dependent necroptosis. ZBP1 binding to Z- form deoxyribonucleic acid/ribonucleic acid (Z-DNA/RNA) leads to activation of receptor-interacting protein kinase 3 (RIPK3) leading to mixed lineage kinase domain- like (MLKL) phosphorylation, aggregation and cell death. This study investigated how different cell lines combat MPXV infection and how MPXV has evolved ways to circumvent the host response. MPXV is shown to inhibit necroptosis in L929 cells by degrading RIPK3 through the viral inducer of RIPK3 degradation (vIRD) and by inhibiting MLKL aggregation. Additionally, the data shows that IFN treatment efficiently inhibits MPXV replication in a ZBP1-, RIPK3-, and MLKL- dependent manner, but independent of necroptosis. Also, the data suggests that an IFN inducer with a pancaspase or proteasome inhibitor could potentially be a beneficial treatment against MPXV infections. Furthermore, it reveals a link between PKR and pathogen-induced necroptosis that has not been previously described.
ContributorsWilliams, Jacqueline (Author) / Jacobs, Bertram (Thesis advisor) / Langland, Jeffrey (Committee member) / Lake, Douglas (Committee member) / Varsani, Arvind (Committee member) / Arizona State University (Publisher)
Created2022