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Description
Nucleosomes are the basic repetitive unit of eukaryotic chromatin and are responsible for packing DNA inside the nucleus of the cell. They consist of a complex of eight histone proteins (two copies of four proteins H2A, H2B, H3 and H4) around which 147 base pairs of DNA are wrapped in ~1.67 superhelical turns. Although the nucleosomes are stable protein-DNA complexes, they undergo spontaneous conformational changes that occur in an asynchronous fashion. This conformational dynamics, defined by the "site-exposure" model, involves the DNA unwrapping from the protein core and exposing itself transiently before wrapping back. Physiologically, this allows regulatory proteins to bind to their target DNA sites during cellular processes like replication, DNA repair and transcription. Traditional biochemical assays have stablished the equilibrium constants for the accessibility to various sites along the length of the nucleosomal DNA, from its end to the middle of the dyad axis. Using fluorescence correlation spectroscopy (FCS), we have established the position dependent rewrapping rates for nucleosomes. We have also used Monte Carlo simulation methods to analyze the applicability of FRET fluctuation spectroscopy towards conformational dynamics, specifically motivated by nucleosome dynamics. Another important conformational change that is involved in cellular processes is the disassembly of nucleosome into its constituent particles. The exact pathway adopted by nucleosomes is still not clear. We used dual color fluorescence correlation spectroscopy to study the intermediates during nucleosome disassembly induced by changing ionic strength. Studying the nature of nucleosome conformational change and the kinetics is very important in understanding gene expression. The results from this thesis give a quantitative description to the basic unit of the chromatin.
ContributorsGurunathan, Kaushik (Author) / Levitus, Marcia (Thesis advisor) / Lindsay, Stuart (Committee member) / Woodbury, Neal (Committee member) / Yan, Hao (Committee member) / Arizona State University (Publisher)
Created2011
Description
In this thesis I introduce a new direction to computing using nonlinear chaotic dynamics. The main idea is rich dynamics of a chaotic system enables us to (1) build better computers that have a flexible instruction set, and (2) carry out computation that conventional computers are not good at it. Here I start from the theory, explaining how one can build a computing logic block using a chaotic system, and then I introduce a new theoretical analysis for chaos computing. Specifically, I demonstrate how unstable periodic orbits and a model based on them explains and predicts how and how well a chaotic system can do computation. Furthermore, since unstable periodic orbits and their stability measures in terms of eigenvalues are extractable from experimental times series, I develop a time series technique for modeling and predicting chaos computing from a given time series of a chaotic system. After building a theoretical framework for chaos computing I proceed to architecture of these chaos-computing blocks to build a sophisticated computing system out of them. I describe how one can arrange and organize these chaos-based blocks to build a computer. I propose a brand new computer architecture using chaos computing, which shifts the limits of conventional computers by introducing flexible instruction set. Our new chaos based computer has a flexible instruction set, meaning that the user can load its desired instruction set to the computer to reconfigure the computer to be an implementation for the desired instruction set. Apart from direct application of chaos theory in generic computation, the application of chaos theory to speech processing is explained and a novel application for chaos theory in speech coding and synthesizing is introduced. More specifically it is demonstrated how a chaotic system can model the natural turbulent flow of the air in the human speech production system and how chaotic orbits can be used to excite a vocal tract model. Also as another approach to build computing system based on nonlinear system, the idea of Logical Stochastic Resonance is studied and adapted to an autoregulatory gene network in the bacteriophage λ.
ContributorsKia, Behnam (Author) / Ditto, William (Thesis advisor) / Huang, Liang (Committee member) / Lai, Ying-Cheng (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2011
Description
Healthy mitochondria are essential for cell survival. Described herein is the synthesis of a family of novel aminoquinone antioxidants designed to alleviate oxidative stress and prevent the impairment of cellular function. In addition, a library of bleomycin disaccharide analogues has also been synthesized to better probe the tumor targeting properties of bleomycin. The first study involves the synthesis of a benzoquinone natural product and analogues that closely resemble the redox core of the natural product geldanamycin. The synthesized 5-amino-3-tridecyl-1,4-benzoquinone antioxidants were tested for their ability to protect Friedreich's ataxia (FRDA) lymphocytes from induced oxidative stress. Some of the analogues synthesized conferred cytoprotection in a dose-dependent manner in FRDA lymphocytes at micromolar concentrations. The biological assays suggest that the modification of the 2-hydroxyl and N-(3-carboxypropyl) groups in the natural product can improve its antioxidant activity and significantly enhance its ability to protect mitochondrial function under conditions of oxidative stress. The second project focused on the synthesis of a library of bleomycin disaccharide-dye conjugates and monitored their cellular uptake by fluorescence microscopy. The studies reveal that the position of the carbamoyl group plays an important role in modulating the cellular uptake of the disaccharide. It also led to the discovery of novel disaccharides with improved tumor selectivity.
ContributorsMathilakathu Madathil, Manikandadas (Author) / Hecht, Sidney M. (Thesis advisor) / Rose, Seth (Committee member) / Woodbury, Neal (Committee member) / Arizona State University (Publisher)
Created2013
Description
Complex dynamical systems consisting interacting dynamical units are ubiquitous in nature and society. Predicting and reconstructing nonlinear dynamics of units and the complex interacting networks among them serves the base for the understanding of a variety of collective dynamical phenomena. I present a general method to address the two outstanding problems as a whole based solely on time-series measurements. The method is implemented by incorporating compressive sensing approach that enables an accurate reconstruction of complex dynamical systems in terms of both nodal equations that determines the self-dynamics of units and detailed coupling patterns among units. The representative advantages of the approach are (i) the sparse data requirement which allows for a successful reconstruction from limited measurements, and (ii) general applicability to identical and nonidentical nodal dynamics, and to networks with arbitrary interacting structure, strength and sizes. Another two challenging problem of significant interest in nonlinear dynamics: (i) predicting catastrophes in nonlinear dynamical systems in advance of their occurrences and (ii) predicting the future state for time-varying nonlinear dynamical systems, can be formulated and solved in the framework of compressive sensing using only limited measurements. Once the network structure can be inferred, the dynamics behavior on them can be investigated, for example optimize information spreading dynamics, suppress cascading dynamics and traffic congestion, enhance synchronization, game dynamics, etc. The results can yield insights to control strategies design in the real-world social and natural systems. Since 2004, there has been a tremendous amount of interest in graphene. The most amazing feature of graphene is that there exists linear energy-momentum relationship when energy is low. The quasi-particles inside the system can be treated as chiral, massless Dirac fermions obeying relativistic quantum mechanics. Therefore, the graphene provides one perfect test bed to investigate relativistic quantum phenomena, such as relativistic quantum chaotic scattering and abnormal electron paths induced by klein tunneling. This phenomenon has profound implications to the development of graphene based devices that require stable electronic properties.
ContributorsYang, Rui (Author) / Lai, Ying-Cheng (Thesis advisor) / Duman, Tolga M. (Committee member) / Akis, Richard (Committee member) / Huang, Liang (Committee member) / Arizona State University (Publisher)
Created2012
Description
It has been well established that mitochondria play a critical role in the pathology of Friedreich's Ataxia. This disease is believed to be caused by a deficiency of frataxin, which research suggests is responsible for iron sulfur cluster assembly. This incomplete assembly of iron sulfur clusters is believed to be linked with dysfunctional complexes in the mitochondrial respiratory chain, increased oxidative stress, and potential cell death. Increased understanding of the pathophysiology of this disease has enabled the development of various therapeutic strategies aimed at restoring mitochondrial respiration. This thesis contains an analysis of the biological activity of several classes of antioxidants against oxidative stress induced by diethyl maleate in Friedreich's Ataxia lymphocytes and CEM leukemia cells. Analogues of vitamin E α-tocopherol have been shown to protect cells under oxidative stress. However, these same analogues show various levels of inhibition towards the electron transport chain complex I. Bicyclic pyridinols containing a ten carbon substituent provided favorable cytoprotection. N-hydroxy-4-pyridone compounds were observed to provide little protection. Similarly, analogues of CoQ10 in the form of pyridinol and pyrimidinol compounds also preserved cell viability at low concentrations.
ContributorsJaruvangsanti, Jennifer (Author) / Hecht, Sidney (Thesis advisor) / Woodbury, Neal (Committee member) / Skibo, Edward (Committee member) / Arizona State University (Publisher)
Created2012
Description
What can classical chaos do to quantum systems is a fundamental issue highly relevant to a number of branches in physics. The field of quantum chaos has been active for three decades, where the focus was on non-relativistic quantumsystems described by the Schr¨odinger equation. By developing an efficient method to solve the Dirac equation in the setting where relativistic particles can tunnel between two symmetric cavities through a potential barrier, chaotic cavities are found to suppress the spread in the tunneling rate. Tunneling rate for any given energy assumes a wide range that increases with the energy for integrable classical dynamics. However, for chaotic underlying dynamics, the spread is greatly reduced. A remarkable feature, which is a consequence of Klein tunneling, arise only in relativistc quantum systems that substantial tunneling exists even for particle energy approaching zero. Similar results are found in graphene tunneling devices, implying high relevance of relativistic quantum chaos to the development of such devices. Wave propagation through random media occurs in many physical systems, where interesting phenomena such as branched, fracal-like wave patterns can arise. The generic origin of these wave structures is currently a matter of active debate. It is of fundamental interest to develop a minimal, paradigmaticmodel that can generate robust branched wave structures. In so doing, a general observation in all situations where branched structures emerge is non-Gaussian statistics of wave intensity with an algebraic tail in the probability density function. Thus, a universal algebraic wave-intensity distribution becomes the criterion for the validity of any minimal model of branched wave patterns. Coexistence of competing species in spatially extended ecosystems is key to biodiversity in nature. Understanding the dynamical mechanisms of coexistence is a fundamental problem of continuous interest not only in evolutionary biology but also in nonlinear science. A continuous model is proposed for cyclically competing species and the effect of the interplay between the interaction range and mobility on coexistence is investigated. A transition from coexistence to extinction is uncovered with a non-monotonic behavior in the coexistence probability and switches between spiral and plane-wave patterns arise. Strong mobility can either promote or hamper coexistence, while absent in lattice-based models, can be explained in terms of nonlinear partial differential equations.
ContributorsNi, Xuan (Author) / Lai, Ying-Cheng (Thesis advisor) / Huang, Liang (Committee member) / Yu, Hongbin (Committee member) / Akis, Richard (Committee member) / Arizona State University (Publisher)
Created2012
Description
The field of biomedical research relies on the knowledge of binding interactions between various proteins of interest to create novel molecular targets for therapeutic purposes. While many of these interactions remain a mystery, knowledge of these properties and interactions could have significant medical applications in terms of understanding cell signaling and immunological defenses. Furthermore, there is evidence that machine learning and peptide microarrays can be used to make reliable predictions of where proteins could interact with each other without the definitive knowledge of the interactions. In this case, a neural network was used to predict the unknown binding interactions of TNFR2 onto LT-ɑ and TRAF2, and PD-L1 onto CD80, based off of the binding data from a sampling of protein-peptide interactions on a microarray. The accuracy and reliability of these predictions would rely on future research to confirm the interactions of these proteins, but the knowledge from these methods and predictions could have a future impact with regards to rational and structure-based drug design.
ContributorsPoweleit, Andrew Michael (Author) / Woodbury, Neal (Thesis director) / Diehnelt, Chris (Committee member) / Chiu, Po-Lin (Committee member) / School of Molecular Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Lung cancer is the leading cause of cancer-related deaths in the US. Low-dose computed tomography (LDCT) scans are speculated to reduce lung cancer mortality. However LDCT scans impose multiple risks including false-negative results, false- positive results, overdiagnosis, and cancer due to repeated exposure to radiation. Immunosignaturing is a new method proposed to screen and detect lung cancer, eliminating the risks associated with LDCT scans. Known and blinded primary blood sera from participants with lung cancer and no cancer were run on peptide microarrays and analyzed. Immunosignatures for each known sample collectively indicated 120 peptides unique to lung cancer and non-cancer participants. These 120 peptides were used to determine the status of the blinded samples. Verification of the results from Vanderbilt is pending.
ContributorsNguyen, Geneva Trieu (Author) / Woodbury, Neal (Thesis director) / Zhao, Zhan-Gong (Committee member) / Stafford, Phillip (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Department of Psychology (Contributor)
Created2015-05
Description
With a quantum efficiency of nearly 100%, the electron transfer process that occurs within the reaction center protein of the photosynthetic bacteria Rhodobacter (Rh.) sphaeroides is a paragon for understanding the complexities, intricacies, and overall systemization of energy conversion and storage in natural systems. To better understand the way in which photons of light are captured, converted into chemically useful forms, and stored for biological use, an investigation into the reaction center protein, specifically into its cascade of cofactors, was undertaken. The purpose of this experimentation was to advance our knowledge and understanding of how differing protein environments and variant cofactors affect the spectroscopic aspects of and electron transfer kinetics within the reaction of Rh. sphaeroides. The native quinone, ubiquinone, was extracted from its pocket within the reaction center protein and replaced by non-native quinones having different reduction/oxidation potentials. It was determined that, of the two non-native quinones tested—1,2-naphthaquinone and 9,10- anthraquinone—the substitution of the anthraquinone (lower redox potential) resulted in an increased rate of recombination from the P+QA- charge-separated state, while the substitution of the napthaquinone (higher redox potential) resulted in a decreased rate of recombination.
ContributorsSussman, Hallie Rebecca (Author) / Woodbury, Neal (Thesis director) / Redding, Kevin (Committee member) / Lin, Su (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
Advances in peptide microarray technology have allowed for the creation of fast-paced and modular experiments within affinity ligand discovery. Previously, low density peptide arrays of 10,000 peptides were used to identify low affinity peptide ligands for a target protein; an approach that can be subsequently improved upon with a number of techniques. VDAP[a] offers more information about the relative affinity of protein-peptide interactions via signal intensity in contrast to high throughput screening (HTS) and display technologies which offer binary data. Now, high density peptide arrays with 130,000 to 330,000 peptides are available that allow screening across peptide libraries of greater diversity. With this increase in scale and diversity, faster analytical tools are needed to adequately characterize array data. Using the statistical power available in the R programming language, we have created a flexible analysis package that efficiently processes high density peptide array data from a variety of layouts, rank existing peptide hits, and utilize signal intensity data to generate new hits. This analysis provides a user-friendly method to efficiently analyze high density peptide array data, generate peptide leads for targeted therapeutic development, and further improve peptide array technologies.
ContributorsMoore, Cody Allen (Author) / Woodbury, Neal (Thesis director) / Diehnelt, Chris (Committee member) / Barrett, The Honors College (Contributor)
Created2015-12