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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
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
The ability to find evidence of life on early Earth and other planets is constrained by the current understanding of biosignatures and our ability to differentiate fossils from abiotic mimics. When organisms transition from the living realm to the fossil record, their morphological and chemical characteristics are modified, usually resulting in the loss of information. These modifications can happen during early and late diagenesis and differ depending on local geochemical properties. These post-depositional modifications need to be understood to better interpret the fossil record. Siliceous hot spring deposits (sinters) are of particular interest for biosignature research as they are early Earth analog environments and targets for investigating the presence of fossil life on Mars. As silica-supersaturated fluids flow from the vent to the distal apron, they precipitate non-crystalline opal-A that fossilizes microbial communities at a range in scales (μm-cm). Therefore, many studies have documented the ties between the active microbial communities and the morphological and chemical biosignatures in hot springs. However, far less attention has been placed on understanding preservation in systems with complex mineralogy or how post-depositional alteration affects the retention of biosignatures. Without this context, it can be challenging to recognize biosignatures in ancient rocks. This dissertation research aims to refine our current understanding of biosignature preservation and retention in sinters. Biosignatures of interest include organic matter, microfossils, and biofabrics. The complex nature of hot springs requires a comprehensive understanding of biosignature preservation that is representative of variable chemistries and post-depositional alterations. For this reason, this dissertation research chapters are field site-based. Chapter 2 investigates biosignature preservation in an unusual spring with mixed opal-A-calcite mineralogy at Lýsuhóll, Iceland. Chapter 3 tracks how silica diagenesis modifies microfossil morphology and associated organic matter at Puchuldiza, Chile. Chapter 4 studies the effects of acid fumarolic overprinting on biosignatures in Gunnuhver, Iceland. To accomplish this, traditional geologic methods (mapping, petrography, X-ray diffraction, bulk elemental analyses) were combined with high-spatial-resolution elemental mapping to better understand diagenetic effects in these systems. Preservation models were developed to predict the types and styles of biosignatures that can be present depending on the depositional and geochemical context. Recommendations are also made for the types of deposits that are most likely to preserve biosignatures.
ContributorsJuarez Rivera, Marisol (Author) / Farmer, Jack D (Thesis advisor) / Hartnett, Hilairy E (Committee member) / Shock, Everett (Committee member) / Garcia-Pichel, Ferran (Committee member) / Trembath-Reichert, Elizabeth (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
I present results of field and laboratory experiments investigating the habitability of one of Earth’s driest environments: the Atacama Desert. This Desert, along the west coast of South America spanning Perú and Chile, is one of the driest places on Earth and has been exceedingly arid for millions of years. These conditions create the perfect natural laboratory for assessing life at the extremes of habitability. All known life needs water; however, the extraordinarily dry Atacama Desert is inhabited by well-adapted microorganisms capable of colonizing this hostile environment. I show field and laboratory evidence of an environmental process, water vapor adsorption, that provides a daily, sustainable input of water into the near (3 - 5 cm) subsurface through water vapor-soil particle interactions. I estimate that this water input may rival the yearly average input of rain in these soils (~2 mm).
I also demonstrate, for the first time, that water vapor adsorption is dependent on mineral composition via a series of laboratory water vapor adsorption experiments. The results of these experiments provide evidence that mineral composition, and ultimately soil composition, measurably and significantly affect the equilibrium soil water content. This suggests that soil microbial communities may be extremely heterogeneous in distribution depending on the distribution of adsorbent minerals.
Finally, I present changes in biologically relevant gasses (i.e., H2, CH4, CO, and CO2) over long-duration incubation experiments designed to assess the potential for biological activity in soils collected from a hyperarid region in the Atacama Desert. These long-duration experiments mimicked typical water availability conditions in the Atacama Desert; in other words, the incubations were performed without condensed water addition. The results suggest a potential for methane-production in the live experiments relative to the sterile controls, and thus, for biological activity in hyperarid soils. However, due to the extremely low biomass and extremely low rates of activity in these soils, the methods employed here were unable to provide robust evidence for activity. Overall, the hyperarid regions of the Atacama Desert are an important resource for researchers by providing a window into the environmental dynamics and subsequent microbial responses near the limit of habitability.
ContributorsGlaser, Donald M (Author) / Hartnett, Hilairy E (Thesis advisor) / Anbar, Ariel (Committee member) / Shock, Everett (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
Dissolved inorganic carbon (DIC) and dissolved organic carbon (DOC) are crucial nutrients for autotrophic and heterotrophic microbial life, respectively, in hydrothermal systems. Biogeochemical processes that control amounts of DIC and DOC in Yellowstone hot springs can be investigated by measuring carbon abundances and respective isotopic values. A decade and a half of field work in 10 regions within Yellowstone National Park and subsequent geochemical lab analyses reveal that sulfate-dominant acidic regions have high DOC (Up to 57 ppm C) and lower DIC (up to 50 ppm C) compared to neutral-chloride regions with low DOC (< 2 ppm C) and higher DIC (up to 100 ppm C). Abundances and isotopic data suggest that sedimentary rock erosion by acidic hydrothermal fluids, fresh snow-derived meteoric water, and exogenous carbon input allowed by local topography may affect DOC levels. Evaluating the isotopic compositions of DIC and DOC in hydrothermal fluids gives insight on the geology and microbial life in the subsurface between different regions. DIC δ13C values range from -4‰ to +5‰ at pH 5-9 and from -10‰ to +3‰ at pH 2-5 with several springs lower than -10‰. DOC δ13C values parkwide range from -10‰ to -30‰. Within this range, neutral-chloride regions in the Lower Geyser Basin have lighter isotopes than sulfate-dominant acidic regions. In hot springs with elevated levels of DOC, the range only varies between -20‰ and -26‰ which may be caused by local exogenous organic matter runoff. Combining other geochemical measurements, such as differences in chloride and sulfate concentrations, demonstrates that some regions contain mixtures of multiple fluids moving through the complex hydrological system in the subsurface. The mixing of these fluids may account for increased levels of DOC in meteoric sulfate-dominant acidic regions. Ultimately, the foundational values of dissolved carbon and their isotopic composition is provided in a parkwide study, so results can be combined with future studies that apply different sequencing analyses to understand specific biogeochemical cycling and microbial communities that occur in individual hot springs.
ContributorsBarnes, Tanner (Author) / Shock, Everett (Thesis advisor) / Meyer-Dombard, D'Arcy (Committee member) / Hartnett, Hilairy (Committee member) / Arizona State University (Publisher)
Created2023