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- All Subjects: Chemistry
- All Subjects: Biology
- Creators: Stephanopoulos, Nicholas
- Member of: Theses and Dissertations
- Resource Type: Text
- 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
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
Cocaine induces long-lasting changes in mesolimbic ‘reward’ circuits of the brain after cessation of use. These lingering changes include the neuronal plasticity that is thought to underlie the chronic relapsing nature of substance use disorders. Genes involved in neuronal plasticity also encode circular RNAs (circRNAs), which are stable, non-coding RNAs formed through the back-splicing of pre-mRNA. The Homer1 gene family, which encodes proteins associated with cocaine-induced plasticity, also encodes circHomer1. Based on preliminary evidence from shows cocaine-regulated changes in the ratio of circHomer1 and Homer1b mRNA in the nucleus accumbens (NAc), this study examined the relationship between circHomer1 and incentive motivation for cocaine by using different lengths of abstinence to vary the degree of motivation. Male and female rats were trained to self-administer cocaine (0.75 mg/kg/infusion, IV) or received a yoked saline infusion. Rats proceeded on an increasingly more difficult variable ratio schedule of lever pressing until they reached a variable ratio 5 schedule, which requires an average of 5 lever presses, and light and tone cues were delivered with the drug infusions. Rats were then tested for cocaine-seeking behavior in response to cue presentations without drug delivery either 1 or 21 days after their last self-administration session. They were sacrificed immediately after and circHomer1 and Homer1b expression was then measured from homogenate and synaptosomal fractions of NAc shell using RT-qPCR. Lever pressing during the cue reactivity test increased from 1 to 21 days of abstinence as expected. Results showed no group differences in synaptic circHomer1 expression, however, total circHomer1 expression was downregulated in 21d rats compared to controls. Lack of change in synaptic circHomer1 was likely due to trends toward different temporal changes in males versus females. Total Homer1b expression was higher in females, although there was no effect of cocaine abstinence. Further research investigating the time course of circHomer1 and Homer1b expression is warranted based on the inverse relationship between total circHomer1and cocaine-seeking behavior observed in this study.
ContributorsJohnson, Michael Christian (Author) / Neisewander, Janet L (Thesis advisor) / Perrone-Bizzozero, Nora (Thesis advisor) / Mangone, Marco (Committee member) / Arizona State University (Publisher)
Created2022
Description
Molecular recognition forms the basis of all protein interactions, and therefore is crucial for maintaining biological functions and pathways. It can be governed by many factors, but in case of proteins and peptides, the amino acids sequences of the interacting entities play a huge role. It is molecular recognition that helps a protein identify the correct sequences residues necessary for an interaction, among the vast number of possibilities from the combinatorial sequence space. Therefore, it is fundamental to study how the interacting amino acid sequences define the molecular interactions of proteins. In this work, sparsely sampled peptide sequences from the combinatorial sequence space were used to study the molecular recognition observed in proteins, especially monoclonal antibodies. A machine learning based approach was used to study the molecular recognition characteristics of 11 monoclonal antibodies, where a neural network (NN) was trained on data from protein binding experiments performed on high-throughput random-sequence peptide microarrays. The use of random-sequence microarrays allowed for the peptides to be sparsely sampled from sequence space. Post-training, a sequence vs. binding relationship was deduced by the NN, for each antibody. This in silico relationship was then extended to larger libraries of random peptides, as well as to the biologically relevant sequences (target antigens, and proteomes). The NN models performed well in predicting the pertinent interactions for 6 out of the 11 monoclonal antibodies, in all aspects. The interactions of the other five monoclonal antibodies could not be predicted well by the models, due to their poor recognition of the residues that were omitted from the array. Furthermore, NN predicted sequence vs. binding relationships for 3 other proteins were experimentally probed using surface plasmon resonance (SPR). This was done to explore the relationship between the observed and predicted binding to the arrays and the observed binding on different assay platforms. It was noted that there was a general motif dependent correlation between predicted and SPR-measured binding. This study also indicated that a combined reiterative approach using in silico and in vitro techniques is a powerful tool for optimizing the selectivity of the protein-binding peptides.
ContributorsBisarad, Pritha (Author) / Woodbury, Neal W (Thesis advisor) / Green, Alexander A (Committee member) / Stephanopoulos, Nicholas (Committee member) / Arizona State University (Publisher)
Created2022
Description
Without a doubt, protein is the most crucial biomolecule performing life and biological functions of any living cell. Profiling various protein expression in individual cells has raised a great interest for scientist and researchers over decades in attempts to reveal cell-to-cell variation, which used to be masked in many previous population average measurement methods. Immunofluorescence (IF) has been a well-established single cell protein analysis technique as for its fast and high-resolution detection and localization, simple and adaptable workflows, and affordable instrumentation. However, inadequate detection sensitivity and multiplexing capability are the two limitation of this platform that remain incompletely addressed in many decades. In this work, several improvements have been proposed and demonstrated to improve existing drawbacks of conventional immunofluorescence. An azide-based linker featured in the novel fluorescent probes synthesis has enable iterative protein staining on the same tissue sample, which subsequently increase the multiplex capacity of IF. Additionally, the multiple fluorophore introduction to the proteins target via either layer by layer biotin-cleavable fluorescent streptavidin or tyramide signal amplification (TSA) have significantly increase the detection sensitivity of the platform. With these advances, IF has the potential to detect, image and quantify up to 100 protein targets in single cell in the tissue sample. In addition of desirable features of IF, these improvements have further turned the technique into a powerful proteomic study platform for not only research setting but also clinical study setting. It is anticipated this highly sensitive and multiplexed, renovated IF method will soon be translated into biomedical studies.
ContributorsPham, Thai Huy (Author) / Guo, Jia (Thesis advisor) / Stephanopoulos, Nicholas (Committee member) / Chiu, Po-Lin (Committee member) / Arizona State University (Publisher)
Created2023
Description
Cyclodextrins are known for their pharmaceutical applications in a range of pathologies. Beta(ꞵ)-cyclodextrins have been suggested to be effective scaffolds that can ligate to peptides when chemically modified, which has the potential to be cost-effective in comparison to other available treatments for antiviral therapeutics. It is hypothesized that a ꞵ-cyclodextrin platform can be modified through a few-step reaction process to develop a ꞵ-cyclodextrin-DBCO-GFP nanobody. The findings of this few-step reaction support the general approach of conjugating the ꞵ-cyclodextrin derivative to GPF nanobody for developing a cyclodextrin antiviral scaffold.
ContributorsTaniguchi, Tohma (Author) / Hariadi, Rizal (Thesis director) / Stephanopoulos, Nicholas (Committee member) / Sasmal, Ranjan (Committee member) / Barrett, The Honors College (Contributor) / School of Molecular Sciences (Contributor)
Created2023-05
Description
Molecular tessellation research aims to elucidate the underlying principles that govern intricate patterns in nature and to leverage these principles to create precise and ordered structures across multiple scales, thereby facilitating the emergence of novel functionalities. DNA origami technology enables the fabrication of nearly arbitrary DNA architectures with nanoscale precision, which can serve as excellent building blocks for the construction of tessellation patterns. However, the size and complexity of DNA origami tessellation systems are currently limited by several unexplored factors relevant to the accuracy of essential design parameters, the applicability of design strategies, and the compatibility between different tiles. Here, a general design and assembly method are described for creating DNA origami tiles that grow into tessellation patterns with micrometer-scale order and nanometer-scale precision. A critical design parameter, interhelical distance (D), was identified, which determined the conformation of monomer tiles and the outcome of tessellation. Finely tuned D facilitated the accurate geometric design of monomer tiles with minimized curvature and improved tessellation capability. To demonstrate the generality of the design method, 9 tile geometries and 15 unique tile designs were generated. The designed tiles were assembled into single-crystalline lattices ranging from tens to hundreds of square micrometers with micrometer-scale, nearly defect-free areas readily visualized by atomic force microscopy. Two strategies were applied to further increase the complexity of DNA origami tessellation, including reducing the symmetry of monomer tiles and co-assembling tiles of various geometries. The designed 6 complex tilings that includes 5 Archimedean tilings and a 12-fold quasicrystal tiling yielded various tiling patterns that great in size and quality, indicating the robustness of the optimized tessellation system. The described design and assembly approach can also be employed to create square DNA origami units for algorithmic self-assembly. As the square units assembled and expanded, they executed the binary function XOR, which generated the Sierpinski triangular pattern according to the predetermined instructions. This study will promote DNA-templated, programmable molecular and material patterning and open up new opportunities for applications in metamaterial engineering, nanoelectronics, and nanolithography.
ContributorsTang, Yue (Author) / Yan, Hao (Thesis advisor) / Guo, Jia (Committee member) / Stephanopoulos, Nicholas (Committee member) / Arizona State University (Publisher)
Created2023
Description
Proteins are among the important macromolecules in living systems, with diverse biological functions and properties that make them greatly interesting to study in both structure and function. The chemical synthesis of proteins allows researchers to incorporate a wide variety of post-translation modifications that can diversify protein functions. It also allows the incorporation of many noncanonical amino acids that enable the study of protein structure and function, as well as the control of their activity in living cells. The work presented in this dissertation focuses on two DNA-templated chemical synthesis approaches for the synthesis of proteins: i) DNA-templated native chemical ligation (NCL), and ii) DNA-templated click chemistry. NCL and its extended version has been used as a powerful tool to obtain proteins; however, it still struggles to make longer proteins due to aggregation and poor yield. To address these issues, a DNA-templated approach is being developed where two peptide fragments are brought into proximity by an oligonucleotide to facilitate the NCL reaction. The sequential ligation of the peptide fragments will result in full-length proteins with increased yield and improved solubility. This research involves synthesis of small molecule auxiliaries, thioester peptides, DNA-peptide conjugates, and ligation of peptides through NCL. This method has the potential to be applied to synthesize large hydrophobic proteins.
A DNA-templated click chemistry method was also reported where duplex DNA was utilized as a template for enhancing the copper click reaction between peptide fragments into functional mini-proteins. As a proof of principle, peptide fragments were synthesized with click functional groups and conjugated with distinct DNA handles through a disulfide exchange bioconjugation reaction. The DNA-peptide conjugates were assembled with the template to bring the two peptides into proximity and enhance the effective molarities of the functional groups. The peptides were coupled efficiently using a copper click reaction. The designed DNA-templated method is being implemented to synthesize a designed mini-protein (called LCB1), which can bind tightly to the spike protein of SARS-CoV-2 and inhibit its interaction with the human angiotensin-converting enzyme 2 (ACE2) receptor. This method allows researchers to introduce multiple non-natural amino acids in the protein and has the potential to extend to larger proteins, synthetic polymers, and DNA-peptide biomaterials.
ContributorsAl-Amin, Md (Author) / Stephanopoulos, Nicholas (Thesis advisor) / Gould, Ian (Committee member) / Ghirlanda, Giovanna (Committee member) / Arizona State University (Publisher)
Created2024