ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
Displaying 1 - 10 of 75
Description
In recent years we have witnessed a shift towards multi-processor system-on-chips (MPSoCs) to address the demands of embedded devices (such as cell phones, GPS devices, luxury car features, etc.). Highly optimized MPSoCs are well-suited to tackle the complex application demands desired by the end user customer. These MPSoCs incorporate a constellation of heterogeneous processing elements (PEs) (general purpose PEs and application-specific integrated circuits (ASICS)). A typical MPSoC will be composed of a application processor, such as an ARM Coretex-A9 with cache coherent memory hierarchy, and several application sub-systems. Each of these sub-systems are composed of highly optimized instruction processors, graphics/DSP processors, and custom hardware accelerators. Typically, these sub-systems utilize scratchpad memories (SPM) rather than support cache coherency. The overall architecture is an integration of the various sub-systems through a high bandwidth system-level interconnect (such as a Network-on-Chip (NoC)). The shift to MPSoCs has been fueled by three major factors: demand for high performance, the use of component libraries, and short design turn around time. As customers continue to desire more and more complex applications on their embedded devices the performance demand for these devices continues to increase. Designers have turned to using MPSoCs to address this demand. By using pre-made IP libraries designers can quickly piece together a MPSoC that will meet the application demands of the end user with minimal time spent designing new hardware. Additionally, the use of MPSoCs allows designers to generate new devices very quickly and thus reducing the time to market. In this work, a complete MPSoC synthesis design flow is presented. We first present a technique \cite{leary1_intro} to address the synthesis of the interconnect architecture (particularly Network-on-Chip (NoC)). We then address the synthesis of the memory architecture of a MPSoC sub-system \cite{leary2_intro}. Lastly, we present a co-synthesis technique to generate the functional and memory architectures simultaneously. The validity and quality of each synthesis technique is demonstrated through extensive experimentation.
ContributorsLeary, Glenn (Author) / Chatha, Karamvir S (Thesis advisor) / Vrudhula, Sarma (Committee member) / Shrivastava, Aviral (Committee member) / Beraha, Rudy (Committee member) / Arizona State University (Publisher)
Created2013
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
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
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
In this thesis we deal with the problem of temporal logic robustness estimation. We present a dynamic programming algorithm for the robust estimation problem of Metric Temporal Logic (MTL) formulas regarding a finite trace of time stated sequence. This algorithm not only tests if the MTL specification is satisfied by the given input which is a finite system trajectory, but also quantifies to what extend does the sequence satisfies or violates the MTL specification. The implementation of the algorithm is the DP-TALIRO toolbox for MATLAB. Currently it is used as the temporal logic robust computing engine of S-TALIRO which is a tool for MATLAB searching for trajectories of minimal robustness in Simulink/ Stateflow. DP-TALIRO is expected to have near linear running time and constant memory requirement depending on the structure of the MTL formula. DP-TALIRO toolbox also integrates new features not supported in its ancestor FW-TALIRO such as parameter replacement, most related iteration and most related predicate. A derivative of DP-TALIRO which is DP-T-TALIRO is also addressed in this thesis which applies dynamic programming algorithm for time robustness computation. We test the running time of DP-TALIRO and compare it with FW-TALIRO. Finally, we present an application where DP-TALIRO is used as the robustness computation core of S-TALIRO for a parameter estimation problem.
ContributorsYang, Hengyi (Author) / Fainekos, Georgios (Thesis advisor) / Sarjoughian, Hessam S. (Committee member) / Shrivastava, Aviral (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
Software has a great impact on the energy efficiency of any computing system--it can manage the components of a system efficiently or inefficiently. The impact of software is amplified in the context of a wearable computing system used for activity recognition. The design space this platform opens up is immense and encompasses sensors, feature calculations, activity classification algorithms, sleep schedules, and transmission protocols. Design choices in each of these areas impact energy use, overall accuracy, and usefulness of the system. This thesis explores methods software can influence the trade-off between energy consumption and system accuracy. In general the more energy a system consumes the more accurate will be. We explore how finding the transitions between human activities is able to reduce the energy consumption of such systems without reducing much accuracy. We introduce the Log-likelihood Ratio Test as a method to detect transitions, and explore how choices of sensor, feature calculations, and parameters concerning time segmentation affect the accuracy of this method. We discovered an approximate 5X increase in energy efficiency could be achieved with only a 5% decrease in accuracy. We also address how a system's sleep mode, in which the processor enters a low-power state and sensors are turned off, affects a wearable computing platform that does activity recognition. We discuss the energy trade-offs in each stage of the activity recognition process. We find that careful analysis of these parameters can result in great increases in energy efficiency if small compromises in overall accuracy can be tolerated. We call this the ``Great Compromise.'' We found a 6X increase in efficiency with a 7% decrease in accuracy. We then consider how wireless transmission of data affects the overall energy efficiency of a wearable computing platform. We find that design decisions such as feature calculations and grouping size have a great impact on the energy consumption of the system because of the amount of data that is stored and transmitted. For example, storing and transmitting vector-based features such as FFT or DCT do not compress the signal and would use more energy than storing and transmitting the raw signal. The effect of grouping size on energy consumption depends on the feature. For scalar features energy consumption is proportional in the inverse of grouping size, so it's reduced as grouping size goes up. For features that depend on the grouping size, such as FFT, energy increases with the logarithm of grouping size, so energy consumption increases slowly as grouping size increases. We find that compressing data through activity classification and transition detection significantly reduces energy consumption and that the energy consumed for the classification overhead is negligible compared to the energy savings from data compression. We provide mathematical models of energy usage and data generation, and test our ideas using a mobile computing platform, the Texas Instruments Chronos watch.
ContributorsBoyd, Jeffrey Michael (Author) / Sundaram, Hari (Thesis advisor) / Li, Baoxin (Thesis advisor) / Shrivastava, Aviral (Committee member) / Turaga, Pavan (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