Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
Displaying 1 - 10 of 88
Description
Spinal muscular atrophy (SMA) is a neurodegenerative disease that results in the loss of lower body muscle function. SMA is the second leading genetic cause of death in infants and arises from the loss of the Survival of Motor Neuron (SMN) protein. SMN is produced by two genes, smn1 and smn2, that are identical with the exception of a C to T conversion in exon 7 of the smn2 gene. SMA patients lacking the smn1 gene, rely on smn2 for production of SMN. Due to an alternative splicing event, smn2 primarily encodes a non-functional SMN lacking exon 7 (SMN D7) as well as a low amount of functional full-length SMN (SMN WT). SMN WT is ubiquitously expressed in all cell types, and it remains unclear how low levels of SMN WT in motor neurons lead to motor neuron degradation and SMA. SMN and its associated proteins, Gemin2-8 and Unrip, make up a large dynamic complex that functions to assemble ribonucleoproteins. The aim of this project was to characterize the interactions of the core SMN-Gemin2 complex, and to identify differences between SMN WT and SMN D7. SMN and Gemin2 proteins were expressed, purified and characterized via size exclusion chromatography. A stable N-terminal deleted Gemin2 protein (N45-G2) was characterized. The SMN WT expression system was optimized resulting in a 10-fold increase of protein expression. Lastly, the oligomeric states of SMN and SMN bound to Gemin2 were determined. SMN WT formed a mixture of oligomeric states, while SMN D7 did not. Both SMN WT and D7 bound to Gemin2 with a one-to-one ratio forming a heterodimer and several higher-order oligomeric states. The SMN WT-Gemin2 complex favored high molecular weight oligomers whereas the SMN D7-Gemin2 complex formed low molecular weight oligomers. These results indicate that the SMA mutant protein, SMN D7, was still able to associate with Gemin2, but was not able to form higher-order oligomeric complexes. The observed multiple oligomerization states of SMN and SMN bound to Gemin2 may play a crucial role in regulating one or several functions of the SMN protein. The inability of SMN D7 to form higher-order oligomers may inhibit or alter those functions leading to the SMA disease phenotype.
ContributorsNiday, Tracy (Author) / Allen, James P. (Thesis advisor) / Wachter, Rebekka (Committee member) / Ghirlanda, Giovanna (Committee member) / Arizona State University (Publisher)
Created2012
Description
Creative design lies at the intersection of novelty and technical feasibility. These objectives can be achieved through cycles of divergence (idea generation) and convergence (idea evaluation) in conceptual design. The focus of this thesis is on the latter aspect. The evaluation may involve any aspect of technical feasibility and may be desired at component, sub-system or full system level. Two issues that are considered in this work are: 1. Information about design ideas is incomplete, informal and sketchy 2. Designers often work at multiple levels; different aspects or subsystems may be at different levels of abstraction Thus, high fidelity analysis and simulation tools are not appropriate for this purpose. This thesis looks at the requirements for a simulation tool and how it could facilitate concept evaluation. The specific tasks reported in this thesis are: 1. The typical types of information available after an ideation session 2. The typical types of technical evaluations done in early stages 3. How to conduct low fidelity design evaluation given a well-defined feasibility question A computational tool for supporting idea evaluation was designed and implemented. It was assumed that the results of the ideation session are represented as a morphological chart and each entry is expressed as some combination of a sketch, text and references to physical effects and machine components. Approximately 110 physical effects were identified and represented in terms of algebraic equations, physical variables and a textual description. A common ontology of physical variables was created so that physical effects could be networked together when variables are shared. This allows users to synthesize complex behaviors from simple ones, without assuming any solution sequence. A library of 16 machine elements was also created and users were given instructions about incorporating them. To support quick analysis, differential equations are transformed to algebraic equations by replacing differential terms with steady state differences), only steady state behavior is considered and interval arithmetic was used for modeling. The tool implementation is done by MATLAB; and a number of case studies are also done to show how the tool works. textual description. A common ontology of physical variables was created so that physical effects could be networked together when variables are shared. This allows users to synthesize complex behaviors from simple ones, without assuming any solution sequence. A library of 15 machine elements was also created and users were given instructions about incorporating them. To support quick analysis, differential equations are transformed to algebraic equations by replacing differential terms with steady state differences), only steady state behavior is considered and interval arithmetic was used for modeling. The tool implementation is done by MATLAB; and a number of case studies are also done to show how the tool works.
ContributorsKhorshidi, Maryam (Author) / Shah, Jami J. (Thesis advisor) / Wu, Teresa (Committee member) / Gel, Esma (Committee member) / Arizona State University (Publisher)
Created2014
Description
This thesis explores a wide array of topics related to the protein folding problem, ranging from the folding mechanism, ab initio structure prediction and protein design, to the mechanism of protein functional evolution, using multi-scale approaches. To investigate the role of native topology on folding mechanism, the native topology is dissected into non-local and local contacts. The number of non-local contacts and non-local contact orders are both negatively correlated with folding rates, suggesting that the non-local contacts dominate the barrier-crossing process. However, local contact orders show positive correlation with folding rates, indicating the role of a diffusive search in the denatured basin. Additionally, the folding rate distribution of E. coli and Yeast proteomes are predicted from native topology. The distribution is fitted well by a diffusion-drift population model and also directly compared with experimentally measured half life. The results indicate that proteome folding kinetics is limited by protein half life. The crucial role of local contacts in protein folding is further explored by the simulations of WW domains using Zipping and Assembly Method. The correct formation of N-terminal β-turn turns out important for the folding of WW domains. A classification model based on contact probabilities of five critical local contacts is constructed to predict the foldability of WW domains with 81% accuracy. By introducing mutations to stabilize those critical local contacts, a new protein design approach is developed to re-design the unfoldable WW domains and make them foldable. After folding, proteins exhibit inherent conformational dynamics to be functional. Using molecular dynamics simulations in conjunction with Perturbation Response Scanning, it is demonstrated that the divergence of functions can occur through the modification of conformational dynamics within existing fold for β-lactmases and GFP-like proteins: i) the modern TEM-1 lactamase shows a comparatively rigid active-site region, likely reflecting adaptation for efficient degradation of a specific substrate, while the resurrected ancient lactamases indicate enhanced active-site flexibility, which likely allows for the binding and subsequent degradation of different antibiotic molecules; ii) the chromophore and attached peptides of photocoversion-competent GFP-like protein exhibits higher flexibility than the photocoversion-incompetent one, consistent with the evolution of photocoversion capacity.
ContributorsZou, Taisong (Author) / Ozkan, Sefika B (Thesis advisor) / Thorpe, Michael F (Committee member) / Woodbury, Neal W (Committee member) / Vaiana, Sara M (Committee member) / Ghirlanda, Giovanna (Committee member) / Arizona State University (Publisher)
Created2014
Description
Vehicles powered by electricity and alternative-fuels are becoming a more popular form of transportation since they have less of an environmental impact than standard gasoline vehicles. Unfortunately, their success is currently inhibited by the sparseness of locations where the vehicles can refuel as well as the fact that many of the vehicles have a range that is less than those powered by gasoline. These factors together create a "range anxiety" in drivers, which causes the drivers to worry about the utility of alternative-fuel and electric vehicles and makes them less likely to purchase these vehicles. For the new vehicle technologies to thrive it is critical that range anxiety is minimized and performance is increased as much as possible through proper routing and scheduling. In the case of long distance trips taken by individual vehicles, the routes must be chosen such that the vehicles take the shortest routes while not running out of fuel on the trip. When many vehicles are to be routed during the day, if the refueling stations have limited capacity then care must be taken to avoid having too many vehicles arrive at the stations at any time. If the vehicles that will need to be routed in the future are unknown then this problem is stochastic. For fleets of vehicles serving scheduled operations, switching to alternative-fuels requires ensuring the schedules do not cause the vehicles to run out of fuel. This is especially problematic since the locations where the vehicles may refuel are limited due to the technology being new. This dissertation covers three related optimization problems: routing a single electric or alternative-fuel vehicle on a long distance trip, routing many electric vehicles in a network where the stations have limited capacity and the arrivals into the system are stochastic, and scheduling fleets of electric or alternative-fuel vehicles with limited locations to refuel. Different algorithms are proposed to solve each of the three problems, of which some are exact and some are heuristic. The algorithms are tested on both random data and data relating to the State of Arizona.
ContributorsAdler, Jonathan D (Author) / Mirchandani, Pitu B. (Thesis advisor) / Askin, Ronald (Committee member) / Gel, Esma (Committee member) / Xue, Guoliang (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2014
Interactions driving the collapse of islet amyloid polypeptide: implications for amyloid aggregation
Description
Human islet amyloid polypeptide (hIAPP), also known as amylin, is a 37-residue intrinsically disordered hormone involved in glucose regulation and gastric emptying. The aggregation of hIAPP into amyloid fibrils is believed to play a causal role in type 2 diabetes. To date, not much is known about the monomeric state of hIAPP or how it undergoes an irreversible transformation from disordered peptide to insoluble aggregate. IAPP contains a highly conserved disulfide bond that restricts hIAPP(1-8) into a short ring-like structure: N_loop. Removal or chemical reduction of N_loop not only prevents cell response upon binding to the CGRP receptor, but also alters the mass per length distribution of hIAPP fibers and the kinetics of fibril formation. The mechanism by which N_loop affects hIAPP aggregation is not yet understood, but is important for rationalizing kinetics and developing potential inhibitors. By measuring end-to-end contact formation rates, Vaiana et al. showed that N_loop induces collapsed states in IAPP monomers, implying attractive interactions between N_loop and other regions of the disordered polypeptide chain . We show that in addition to being involved in intra-protein interactions, the N_loop is involved in inter-protein interactions, which lead to the formation of extremely long and stable β-turn fibers. These non-amyloid fibers are present in the 10 μM concentration range, under the same solution conditions in which hIAPP forms amyloid fibers. We discuss the effect of peptide cyclization on both intra- and inter-protein interactions, and its possible implications for aggregation. Our findings indicate a potential role of N_loop-N_loop interactions in hIAPP aggregation, which has not previously been explored. Though our findings suggest that N_loop plays an important role in the pathway of amyloid formation, other naturally occurring IAPP variants that contain this structural feature are incapable of forming amyloids. For example, hIAPP readily forms amyloid fibrils in vitro, whereas the rat variant (rIAPP), differing by six amino acids, does not. In addition to being highly soluble, rIAPP is an effective inhibitor of hIAPP fibril formation . Both of these properties have been attributed to rIAPP's three proline residues: A25P, S28P and S29P. Single proline mutants of hIAPP have also been shown to kinetically inhibit hIAPP fibril formation. Because of their intrinsic dihedral angle preferences, prolines are expected to affect conformational ensembles of intrinsically disordered proteins. The specific effect of proline substitutions on IAPP structure and dynamics has not yet been explored, as the detection of such properties is experimentally challenging due to the low molecular weight, fast reconfiguration times, and very low solubility of IAPP peptides. High-resolution techniques able to measure tertiary contact formations are needed to address this issue. We employ a nanosecond laser spectroscopy technique to measure end-to-end contact formation rates in IAPP mutants. We explore the proline substitutions in IAPP and quantify their effects in terms of intrinsic chain stiffness. We find that the three proline mutations found in rIAPP increase chain stiffness. Interestingly, we also find that residue R18 plays an important role in rIAPP's unique chain stiffness and, together with the proline residues, is a determinant for its non-amyloidogenic properties. We discuss the implications of our findings on the role of prolines in IDPs.
ContributorsCope, Stephanie M (Author) / Vaiana, Sara M (Thesis advisor) / Ghirlanda, Giovanna (Committee member) / Ros, Robert (Committee member) / Lindsay, Stuart M (Committee member) / Ozkan, Sefika B (Committee member) / Arizona State University (Publisher)
Created2013
Description
Telomerase is a unique reverse transcriptase that has evolved specifically to extend the single stranded DNA at the 3' ends of chromosomes. To achieve this, telomerase uses a small section of its integral RNA subunit (TR) to reiteratively copy a short, canonically 6-nt, sequence repeatedly in a processive manner using a complex and currently poorly understood mechanism of template translocation to stop nucleotide addition, regenerate its template, and then synthesize a new repeat. In this study, several novel interactions between the telomerase protein and RNA components along with the DNA substrate are identified and characterized which come together to allow active telomerase repeat addition. First, this study shows that the sequence of the RNA/DNA duplex holds a unique, single nucleotide signal which pauses DNA synthesis at the end of the canonical template sequence. Further characterization of this sequence dependent pause signal reveals that the template sequence alone can produce telomerase products with the characteristic 6-nt pattern, but also works cooperatively with another RNA structural element for proper template boundary definition. Finally, mutational analysis is used on several regions of the protein and RNA components of telomerase to identify crucial determinates of telomerase assembly and processive repeat synthesis. Together, these results shed new light on how telomerase coordinates its complex catalytic cycle.
ContributorsBrown, Andrew F (Author) / Chen, Julian J. L. (Thesis advisor) / Jones, Anne (Committee member) / Ghirlanda, Giovanna (Committee member) / Arizona State University (Publisher)
Created2014
Description
Accelerated life testing (ALT) is the process of subjecting a product to stress conditions (temperatures, voltage, pressure etc.) in excess of its normal operating levels to accelerate failures. Product failure typically results from multiple stresses acting on it simultaneously. Multi-stress factor ALTs are challenging as they increase the number of experiments due to the stress factor-level combinations resulting from the increased number of factors. Chapter 2 provides an approach for designing ALT plans with multiple stresses utilizing Latin hypercube designs that reduces the simulation cost without loss of statistical efficiency. A comparison to full grid and large-sample approximation methods illustrates the approach computational cost gain and flexibility in determining optimal stress settings with less assumptions and more intuitive unit allocations.
Implicit in the design criteria of current ALT designs is the assumption that the form of the acceleration model is correct. This is unrealistic assumption in many real-world problems. Chapter 3 provides an approach for ALT optimum design for model discrimination. We utilize the Hellinger distance measure between predictive distributions. The optimal ALT plan at three stress levels was determined and its performance was compared to good compromise plan, best traditional plan and well-known 4:2:1 compromise test plans. In the case of linear versus quadratic ALT models, the proposed method increased the test plan's ability to distinguish among competing models and provided better guidance as to which model is appropriate for the experiment.
Chapter 4 extends the approach of Chapter 3 to ALT sequential model discrimination. An initial experiment is conducted to provide maximum possible information with respect to model discrimination. The follow-on experiment is planned by leveraging the most current information to allow for Bayesian model comparison through posterior model probability ratios. Results showed that performance of plan is adversely impacted by the amount of censoring in the data, in the case of linear vs. quadratic model form at three levels of constant stress, sequential testing can improve model recovery rate by approximately 8% when data is complete, but no apparent advantage in adopting sequential testing was found in the case of right-censored data when censoring is in excess of a certain amount.
Implicit in the design criteria of current ALT designs is the assumption that the form of the acceleration model is correct. This is unrealistic assumption in many real-world problems. Chapter 3 provides an approach for ALT optimum design for model discrimination. We utilize the Hellinger distance measure between predictive distributions. The optimal ALT plan at three stress levels was determined and its performance was compared to good compromise plan, best traditional plan and well-known 4:2:1 compromise test plans. In the case of linear versus quadratic ALT models, the proposed method increased the test plan's ability to distinguish among competing models and provided better guidance as to which model is appropriate for the experiment.
Chapter 4 extends the approach of Chapter 3 to ALT sequential model discrimination. An initial experiment is conducted to provide maximum possible information with respect to model discrimination. The follow-on experiment is planned by leveraging the most current information to allow for Bayesian model comparison through posterior model probability ratios. Results showed that performance of plan is adversely impacted by the amount of censoring in the data, in the case of linear vs. quadratic model form at three levels of constant stress, sequential testing can improve model recovery rate by approximately 8% when data is complete, but no apparent advantage in adopting sequential testing was found in the case of right-censored data when censoring is in excess of a certain amount.
ContributorsNasir, Ehab (Author) / Pan, Rong (Thesis advisor) / Runger, George C. (Committee member) / Gel, Esma (Committee member) / Kao, Ming-Hung (Committee member) / Montgomery, Douglas C. (Committee member) / Arizona State University (Publisher)
Created2014
Description
ABSTRACT
Post Translational Modifications (PTMs) are a series of chemical modifications with the capacity to expand the structural and functional repertoire of proteins. PTMs can regulate protein-protein interaction, localization, protein turn-over, the active state of the protein, and much more. This can dramatically affect cell processes as relevant as gene expression, cell-cell recognition, and cell signaling. Along these lines, this Ph.D. thesis examines the role of two of the most important PTMs: glycosylation and phosphorylation.
In chapters 2, 3 and 4, a 10,000 peptide microarray is used to analyze the glycan variations in a series lipopolysaccharides (LPS) from Gram negative bacteria. This research was the first to demonstrate that using a small subset of random sequence peptides, it was possible to identify a small subset with the capacity to bind to the LPS of bacteria. These peptides bound to LPS not only in the solid surface of the array but also in solution as demonstrated with surface plasmon resonance (SPR), isothermal titration calorimetry (ITC) and flow cytometry. Interestingly, some of the LPS binding peptides also exhibit antimicrobial activity, a property that is also analyzed in this work.
In chapters 5 and 6, the role of protein phosphorylation, another PTM, is analyzed in the context of human cancer. High risk neuroblastoma, a very aggressive pediatric cancer, was studied with emphasis on the phosphorylations of two selected oncoproteins: the transcription factor NMYC and the adaptor protein ShcC. Both proteins were isolated from high risk neuroblastoma cells, and a targeted-directed tandem mass spectrometry (LC-MS/MS) methodology was used to identify the phosphorylation sites in each protein. Using this method dramatically improved the phosphorylation site detection and increased the number of sites detected up to 250% in comparison with previous studies. Several of the novel identified sites were located in functional domain of the proteins and that some of them are homologous to known active sites in other proteins of the same family. The chapter concludes with a computational prediction of the kinases that potentially phosphorylate those sites and a series of assays to show this phosphorylation occurred in vitro.
Post Translational Modifications (PTMs) are a series of chemical modifications with the capacity to expand the structural and functional repertoire of proteins. PTMs can regulate protein-protein interaction, localization, protein turn-over, the active state of the protein, and much more. This can dramatically affect cell processes as relevant as gene expression, cell-cell recognition, and cell signaling. Along these lines, this Ph.D. thesis examines the role of two of the most important PTMs: glycosylation and phosphorylation.
In chapters 2, 3 and 4, a 10,000 peptide microarray is used to analyze the glycan variations in a series lipopolysaccharides (LPS) from Gram negative bacteria. This research was the first to demonstrate that using a small subset of random sequence peptides, it was possible to identify a small subset with the capacity to bind to the LPS of bacteria. These peptides bound to LPS not only in the solid surface of the array but also in solution as demonstrated with surface plasmon resonance (SPR), isothermal titration calorimetry (ITC) and flow cytometry. Interestingly, some of the LPS binding peptides also exhibit antimicrobial activity, a property that is also analyzed in this work.
In chapters 5 and 6, the role of protein phosphorylation, another PTM, is analyzed in the context of human cancer. High risk neuroblastoma, a very aggressive pediatric cancer, was studied with emphasis on the phosphorylations of two selected oncoproteins: the transcription factor NMYC and the adaptor protein ShcC. Both proteins were isolated from high risk neuroblastoma cells, and a targeted-directed tandem mass spectrometry (LC-MS/MS) methodology was used to identify the phosphorylation sites in each protein. Using this method dramatically improved the phosphorylation site detection and increased the number of sites detected up to 250% in comparison with previous studies. Several of the novel identified sites were located in functional domain of the proteins and that some of them are homologous to known active sites in other proteins of the same family. The chapter concludes with a computational prediction of the kinases that potentially phosphorylate those sites and a series of assays to show this phosphorylation occurred in vitro.
ContributorsMorales Betanzos, Carlos (Author) / LaBaer, Joshua (Thesis advisor) / Allen, James (Committee member) / Ghirlanda, Giovanna (Committee member) / Arizona State University (Publisher)
Created2014
Description
The utilization of solar energy requires an efficient means of its storage as fuel. In bio-inspired artificial photosynthesis, light energy can be used to drive water oxidation, but catalysts that produce molecular oxygen from water are required. This dissertation demonstrates a novel complex utilizing earth-abundant Ni in combination with glycine as an efficient catalyst with a modest overpotential of 0.475 ± 0.005 V for a current density of 1 mA/cm2 at pH 11. The production of molecular oxygen at a high potential was verified by measurement of the change in oxygen concentration, yielding a Faradaic efficiency of 60 ± 5%. This Ni species can achieve a current density of 4 mA/cm2 that persists for at least 10 hours. Based upon the observed pH dependence of the current amplitude and oxidation/reduction peaks, the catalysis is an electron-proton coupled process. In addition, to investigate the binding of divalent metals to proteins, four peptides were designed and synthesized with carboxylate and histidine ligands. The binding of the metals was characterized by monitoring the metal-induced changes in circular dichroism spectra. Cyclic voltammetry demonstrated that bound copper underwent a Cu(I)/Cu(II) oxidation/reduction change at a potential of approximately 0.32 V in a quasi-reversible process. The relative binding affinity of Mn(II), Fe(II), Co(II), Ni(II) and Cu(II) to the peptides is correlated with the stability constants of the Irving-Williams series for divalent metal ions. A potential application of these complexes of transition metals with amino acids or peptides is in the development of artificial photosynthetic cells.
ContributorsWang, Dong (Author) / Allen, James P. (Thesis advisor) / Ghirlanda, Giovanna (Committee member) / Redding, Kevin (Committee member) / Arizona State University (Publisher)
Created2014
Description
Proteins and peptides fold into dynamic structures that access a broad functional landscape, however, designing artificial polypeptide systems continues to be a great chal-lenge. Conversely, deoxyribonucleic acid (DNA) engineering is now routinely used to build a wide variety of two dimensional and three dimensional (3D) nanostructures from simple hybridization based rules, and their functional diversity can be significantly ex-panded through site specific incorporation of the appropriate guest molecules. This dis-sertation describes a gentle methodology for using short (8 nucleotide) peptide nucleic acid (PNA) linkers to assemble polypeptides within a 3D DNA nanocage, as a proof of concept for constructing artificial catalytic centers. PNA-polypeptide conjugates were synthesized directly using microwave assisted solid phase synthesis or alternatively PNA linkers were conjugated to biologically expressed proteins using chemical crosslinking. The PNA-polypeptides hybridized to the preassembled DNA nanocage at room tempera-ture or 11 ⁰C and could be assembled in a stepwise fashion. Time resolved fluorescence anisotropy and gel electrophoresis were used to determine that a negatively charged az-urin protein was repelled outside of the negatively charged DNA nanocage, while a posi-tively charged cytochrome c protein was retained inside. Spectroelectrochemistry and an in-gel luminol oxidation assay demonstrated the cytochrome c protein remained active within the DNA nanocage and its redox potential decreased modestly by 10 mV due to the presence of the DNA nanocage. These results demonstrate the benign PNA assembly conditions are ideal for preserving polypeptide structure and function, and will facilitate the polypeptide-based assembly of artificial catalytic centers inside a stable DNA nanocage. A prospective application of assembling multiple cyclic γ-PNA-peptides to mimic the oxygen-evolving complex (OEC) catalytic active site from photosystem II (PSII) is described. In this way, the robust catalytic capacity of PSII could be utilized, without suffering the light-induced damage that occurs by the photoreactions within PSII via triplet state formation, which limits the efficiency of natural photosynthesis. There-fore, this strategy has the potential to revolutionize the process of designing and building robust catalysts by leveraging nature's recipes, and also providing a flexible and con-trolled artificial environment that might even improve them further towards commercial viability.
ContributorsFlory, Justin David (Author) / Fromme, Petra (Thesis advisor) / Yan, Hao (Committee member) / Buttry, Daniel (Committee member) / Ghirlanda, Giovanna (Committee member) / Arizona State University (Publisher)
Created2014