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.

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Description
Random peptide microarrays are a powerful tool for both the treatment and diagnostics of infectious diseases. On the treatment side, selected random peptides on the microarray have either binding or lytic potency against certain pathogens cells, thus they can be synthesized into new antimicrobial agents, denoted as synbodies (synthetic antibodies).

Random peptide microarrays are a powerful tool for both the treatment and diagnostics of infectious diseases. On the treatment side, selected random peptides on the microarray have either binding or lytic potency against certain pathogens cells, thus they can be synthesized into new antimicrobial agents, denoted as synbodies (synthetic antibodies). On the diagnostic side, serum containing specific infection-related antibodies create unique and distinct "pathogen-immunosignatures" on the random peptide microarray distinct from the healthy control serum, and this different mode of binding can be used as a more precise measurement than traditional ELISA tests. My thesis project is separated into these two parts: the first part falls into the treatment side and the second one focuses on the diagnostic side. My first chapter shows that a substitution amino acid peptide library helps to improve the activity of a recently reported synthetic antimicrobial peptide selected by the random peptide microarray. By substituting one or two amino acids of the original lead peptide, the new substitutes show changed hemolytic effects against mouse red blood cells and changed potency against two pathogens: Staphylococcus aureus and Pseudomonas aeruginosa. Two new substitutes are then combined together to form the synbody, which shows a significantly antimicrobial potency against Staphylococcus aureus (<0.5uM). In the second chapter, I explore the possibility of using the 10K Ver.2 random peptide microarray to monitor the humoral immune response of dengue. Over 2.5 billion people (40% of the world's population) live in dengue transmitting areas. However, currently there is no efficient dengue treatment or vaccine. Here, with limited dengue patient serum samples, we show that the immunosignature has the potential to not only distinguish the dengue infection from non-infected people, but also the primary dengue infection from the secondary dengue infections, dengue infection from West Nile Virus (WNV) infection, and even between different dengue serotypes. By further bioinformatic analysis, we demonstrate that the significant peptides selected to distinguish dengue infected and normal samples may indicate the epitopes responsible for the immune response.
ContributorsWang, Xiao (Author) / Johnston, Stephen Albert (Thesis advisor) / Blattman, Joseph (Committee member) / Arntzen, Charles (Committee member) / Arizona State University (Publisher)
Created2013
Description
The ability to tolerate bouts of oxygen deprivation varies tremendously across the animal kingdom. Adult humans from different regions show large variation in tolerance to hypoxia; additionally, it is widely known that neonatal mammals are much more tolerant to anoxia than their adult counterparts, including in humans. Drosophila melanogaster are

The ability to tolerate bouts of oxygen deprivation varies tremendously across the animal kingdom. Adult humans from different regions show large variation in tolerance to hypoxia; additionally, it is widely known that neonatal mammals are much more tolerant to anoxia than their adult counterparts, including in humans. Drosophila melanogaster are very anoxia-tolerant relative to mammals, with adults able to survive 12 h of anoxia, and represent a well-suited model for studying anoxia tolerance. Drosophila live in rotting, fermenting media and a result are more likely to experience environmental hypoxia; therefore, they could be expected to be more tolerant of anoxia than adults. However, adults have the capacity to survive anoxic exposure times ~8 times longer than larvae. This dissertation focuses on understanding the mechanisms responsible for variation in survival from anoxic exposure in the genetic model organism, Drosophila melanogaster, focused in particular on effects of developmental stage (larval vs. adults) and within-population variation among individuals.

Vertebrate studies suggest that surviving anoxia requires the maintenance of ATP despite the loss of aerobic metabolism in a manner that prevents a disruption of ionic homeostasis. Instead, the abilities to maintain a hypometabolic state with low ATP and tolerate large disturbances in ionic status appear to contribute to the higher anoxia tolerance of adults. Furthermore, metabolomics experiments support this notion by showing that larvae had higher metabolic rates during the initial 30 min of anoxia and that protective metabolites were upregulated in adults but not larvae. Lastly, I investigated the genetic variation in anoxia tolerance using a genome wide association study (GWAS) to identify target genes associated with anoxia tolerance. Results from the GWAS also suggest mechanisms related to protection from ionic and oxidative stress, in addition to a protective role for immune function.
ContributorsCampbell, Jacob B (Author) / Harrison, Jon F. (Thesis advisor) / Gadau, Juergen (Committee member) / Call, Gerald B (Committee member) / Sweazea, Karen L (Committee member) / Rosenberg, Michael S. (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Isolation-by-distance is a specific type of spatial genetic structure that arises when parent-offspring dispersal is limited. Many natural populations exhibit localized dispersal, and as a result, individuals that are geographically near each other will tend to have greater genetic similarity than individuals that are further apart. It is important to

Isolation-by-distance is a specific type of spatial genetic structure that arises when parent-offspring dispersal is limited. Many natural populations exhibit localized dispersal, and as a result, individuals that are geographically near each other will tend to have greater genetic similarity than individuals that are further apart. It is important to identify isolation-by-distance because it can impact the statistical analysis of population samples and it can help us better understand evolutionary dynamics. For this dissertation I investigated several aspects of isolation-by-distance. First, I looked at how the shape of the dispersal distribution affects the observed pattern of isolation-by-distance. If, as theory predicts, the shape of the distribution has little effect, then it would be more practical to model isolation-by-distance using a simple dispersal distribution rather than replicating the complexities of more realistic distributions. Therefore, I developed an efficient algorithm to simulate dispersal based on a simple triangular distribution, and using a simulation, I confirmed that the pattern of isolation-by-distance was similar to other more realistic distributions. Second, I developed a Bayesian method to quantify isolation-by-distance using genetic data by estimating Wright’s neighborhood size parameter. I analyzed the performance of this method using simulated data and a microsatellite data set from two populations of Maritime pine, and I found that the neighborhood size estimates had good coverage and low error. Finally, one of the major consequences of isolation-by-distance is an increase in inbreeding. Plants are often particularly susceptible to inbreeding, and as a result, they have evolved many inbreeding avoidance mechanisms. Using a simulation, I determined which mechanisms are more successful at preventing inbreeding associated with isolation-by-distance.
ContributorsFurstenau, Tara N (Author) / Cartwright, Reed A (Thesis advisor) / Rosenberg, Michael S. (Committee member) / Taylor, Jesse (Committee member) / Wilson-Sayres, Melissa (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Synthetic gene networks have evolved from simple proof-of-concept circuits to

complex therapy-oriented networks over the past fifteen years. This advancement has

greatly facilitated expansion of the emerging field of synthetic biology. Multistability is a

mechanism that cells use to achieve a discrete number of mutually exclusive states in

response to environmental inputs. However, complex

Synthetic gene networks have evolved from simple proof-of-concept circuits to

complex therapy-oriented networks over the past fifteen years. This advancement has

greatly facilitated expansion of the emerging field of synthetic biology. Multistability is a

mechanism that cells use to achieve a discrete number of mutually exclusive states in

response to environmental inputs. However, complex contextual connections of gene

regulatory networks in natural settings often impede the experimental establishment of

the function and dynamics of each specific gene network.

In this work, diverse synthetic gene networks are rationally designed and

constructed using well-characterized biological components to approach the cell fate

determination and state transition dynamics in multistable systems. Results show that

unimodality and bimodality and trimodality can be achieved through manipulation of the

signal and promoter crosstalk in quorum-sensing systems, which enables bacterial cells to

communicate with each other.

Moreover, a synthetic quadrastable circuit is also built and experimentally

demonstrated to have four stable steady states. Experiments, guided by mathematical

modeling predictions, reveal that sequential inductions generate distinct cell fates by

changing the landscape in sequence and hence navigating cells to different final states.

Circuit function depends on the specific protein expression levels in the circuit.

We then establish a protein expression predictor taking into account adjacent

transcriptional regions’ features through construction of ~120 synthetic gene circuits

(operons) in Escherichia coli. The predictor’s utility is further demonstrated in evaluating genes’ relative expression levels in construction of logic gates and tuning gene expressions and nonlinear dynamics of bistable gene networks.

These combined results illustrate applications of synthetic gene networks to

understand the cell fate determination and state transition dynamics in multistable

systems. A protein-expression predictor is also developed to evaluate and tune circuit

dynamics.
ContributorsWu, Fuqing (Author) / Wang, Xiao (Thesis advisor) / Haynes, Karmella (Committee member) / Marshall, Pamela (Committee member) / Nielsen, David (Committee member) / Brafman, David (Committee member) / Arizona State University (Publisher)
Created2017
Description
Leprosy and tuberculosis are age-old diseases that have tormented mankind and left behind a legacy of fear, mutilation, and social stigmatization. Today, leprosy is considered a Neglected Tropical Disease due to its high prevalence in developing countries, while tuberculosis is highly endemic in developing countries and rapidly re-emerging in several

Leprosy and tuberculosis are age-old diseases that have tormented mankind and left behind a legacy of fear, mutilation, and social stigmatization. Today, leprosy is considered a Neglected Tropical Disease due to its high prevalence in developing countries, while tuberculosis is highly endemic in developing countries and rapidly re-emerging in several developed countries. In order to eradicate these diseases effectively, it is necessary to understand how they first originated in humans and whether they are prevalent in nonhuman hosts which can serve as a source of zoonotic transmission. This dissertation uses a phylogenomics approach to elucidate the evolutionary histories of the pathogens that cause leprosy and tuberculosis, Mycobacterium leprae and the M. tuberculosis complex, respectively, through three related studies. In the first study, genomes of M. leprae strains that infect nonhuman primates were sequenced and compared to human M. leprae strains to determine their genetic relationships. This study assesses whether nonhuman primates serve as a reservoir for M. leprae and whether there is potential for transmission of M. leprae between humans and nonhuman primates. In the second study, the genome of M. lepraemurium (which causes leprosy in mice, rats, and cats) was sequenced to clarify its genetic relationship to M. leprae and other mycobacterial species. This study is the first to sequence the M. lepraemurium genome and also describes genes that may be important for virulence in this pathogen. In the third study, an ancient DNA approach was used to recover M. tuberculosis genomes from human skeletal remains from the North American archaeological record. This study informs us about the types of M. tuberculosis strains present in post-contact era North America. Overall, this dissertation informs us about the evolutionary histories of these pathogens and their prevalence in nonhuman hosts, which is not only important in an anthropological context but also has significant implications for disease eradication and wildlife conservation.
ContributorsHonap, Tanvi Prasad (Author) / Stone, Anne C (Thesis advisor) / Rosenberg, Michael S. (Thesis advisor) / Clark-Curtiss, Josephine E (Committee member) / Krause, Johannes (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Fusion proteins that specifically interact with biochemical marks on chromosomes represent a new class of synthetic transcriptional regulators that decode cell state information rather than deoxyribose nucleic acid (DNA) sequences. In multicellular organisms, information relevant to cell state, tissue identity, and oncogenesis is often encoded as biochemical modifications of histones,

Fusion proteins that specifically interact with biochemical marks on chromosomes represent a new class of synthetic transcriptional regulators that decode cell state information rather than deoxyribose nucleic acid (DNA) sequences. In multicellular organisms, information relevant to cell state, tissue identity, and oncogenesis is often encoded as biochemical modifications of histones, which are bound to DNA in eukaryotic nuclei and regulate gene expression states. In 2011, Haynes et al. showed that a synthetic regulator called the Polycomb chromatin Transcription Factor (PcTF), a fusion protein that binds methylated histones, reactivated an artificially-silenced luciferase reporter gene. These synthetic transcription activators are derived from the polycomb repressive complex (PRC) and associate with the epigenetic silencing mark H3K27me3 to reactivate the expression of silenced genes. It is demonstrated here that the duration of epigenetic silencing does not perturb reactivation via PcTF fusion proteins. After 96 hours PcTF shows the strongest reactivation activity. A variant called Pc2TF, which has roughly double the affinity for H3K27me3 in vitro, reactivated the silenced luciferase gene by at least 2-fold in living cells.
ContributorsVargas, Daniel A. (Author) / Haynes, Karmella (Thesis advisor) / Wang, Xiao (Committee member) / Mills, Jeremy (Committee member) / Arizona State University (Publisher)
Created2019
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Description
A notable challenge when assembling synthetic gene circuits is that modularity often fails to function as intended. A crucial underlying reason for this modularity failure is the existence of competition for shared and limited gene expression resources. By designing a synthetic cascading bistable switches (Syn-CBS) circuit in a single strain

A notable challenge when assembling synthetic gene circuits is that modularity often fails to function as intended. A crucial underlying reason for this modularity failure is the existence of competition for shared and limited gene expression resources. By designing a synthetic cascading bistable switches (Syn-CBS) circuit in a single strain with two coupled self-activation modules to achieve successive cell fate transitions, nonlinear resource competition within synthetic gene circuits is unveiled. However, in vivo it can be seen that the transition path was redirected with the activation of one switch always prevailing over that of the other, contradictory to coactivation theoretically expected. This behavior is a result of resource competition between genes and follows a ‘winner-takes-all’ rule, where the winner is determined by the relative connection strength between the two modules. Despite investigation demonstrating that resource competition between gene modules can significantly alter circuit deterministic behaviors, how resource competition contributes to gene expression noise and how this noise can be controlled is still an open issue of fundamental importance in systems biology and biological physics. By utilizing a two-gene circuit, the effects of resource competition on protein expression noise levels can be closely studied. A surprising double-edged role is discovered: the competition for these resources decreases noise while the constraint on resource availability adds its own term of noise into the system, denoted “resource competitive” noise. Noise reduction effects are then studied using orthogonal resources. Results indicate that orthogonal resources are a good strategy for eliminating the contribution of resource competition to gene expression noise. Noise propagation through a cascading circuit has been considered without resource competition. It has been noted that the noise from upstream genes can be transmitted downstream. However, resource competition’s effects on this cascading noise have yet to be studied. When studied, it is found that resource competition can induce stochastic state switching and perturb noise propagation. Orthogonal resources can remove some of the resource competitive behavior and allow for a system with less noise.
ContributorsGoetz, Hanah Elizabeth (Author) / Tian, Xiaojun (Thesis advisor) / Wang, Xiao (Committee member) / Lai, Ying-Cheng (Committee member) / Arizona State University (Publisher)
Created2022