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.
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- All Subjects: Biology
- Creators: Kusumi, Kenro
- Creators: Wang, Xiao
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). 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
Skeletal muscles arise from the myotome compartment of the somites that form during vertebrate embryonic development. Somites are transient structures serve as the anlagen for the axial skeleton, skeletal muscle, tendons, and dermis, as well as imposing the metameric patterning of the axial musculoskeletal system, peripheral nerves, and vasculature. Classic studies have described the role of Notch, Wnt, and FGF signaling pathways in controlling somite formation and muscle formation. However, little is known about the transformation of myotome compartments into identifiable post-natal muscle groups. Using a mouse model, I have undertaken an evaluation of morphological events, including hypertrophy and hyperplasia, related to the formation of several muscles positioned along the dorsal surface of the vertebrae and ribs. Lunatic fringe (Lfng) deficient embryos and neonates were also examined to further understand the role of the Notch pathway in these processes as it is a modulator of the Notch receptor and plays an important role in defining somite borders and anterior-posterior patterning in many vertebrates. Lunatic fringe deficient embryos showed defects in muscle fiber hyperplasia and hypertrophy in the iliocostalis and longissimus muscles of the erector spinae group. This novel data suggests an additional role for Lfng and the Notch signaling pathway in embryonic and fetal muscle development.
ContributorsDe Ruiter, Corinne (Author) / Rawls, J. Alan (Thesis advisor) / Wilson-Rawls, Jeanne (Committee member) / Kusumi, Kenro (Committee member) / Fisher, Rebecca E. (Committee member) / Arizona State University (Publisher)
Created2012
Description
The most abundantly studied societies, with the exception of humans, are those of the eusocial insects, which include all ants. Eusocial insect societies are typically composed of many dozens to millions of individuals, referred to as nestmates, which require some form of communication to maintain colony cohesion and coordinate the activities within them. Nestmate recognition is the process of distinguishing between nestmates and non-nestmates, and embodies the first line of defense for social insect colonies. In ants, nestmate recognition is widely thought to occur through olfactory cues found on the exterior surfaces of individuals. These cues, called cuticular hydrocarbons (CHCs), comprise the overwhelming majority of ant nestmate profiles and help maintain colony identity. In this dissertation, I investigate how nestmate recognition is influenced by evolutionary, ontogenetic, and environmental factors. First, I contributed to the sequencing and description of three ant genomes including the red harvester ant, Pogonomyrmex barbatus, presented in detail here. Next, I studied how variation in nestmate cues may be shaped through evolution by comparatively studying a family of genes involved in fatty acid and hydrocarbon biosynthesis, i.e., the acyl-CoA desaturases, across seven ant species in comparison with other social and solitary insects. Then, I tested how genetic, developmental, and social factors influence CHC profile variation in P. barbatus, through a three-part study. (1) I conducted a descriptive, correlative study of desaturase gene expression and CHC variation in P. barbatus workers and queens; (2) I explored how larger-scale genetic variation in the P. barbatus species complex influences CHC variation across two genetically isolated lineages (J1/J2 genetic caste determining lineages); and (3) I experimentally examined how CHC development is influenced by an individual’s social environment. In the final part of my work, I resolved discrepancies between previous findings of nestmate recognition behavior in P. barbatus by studying how factors of territorial experience, i.e., spatiotemporal relationships, affect aggressive behaviors among red harvester ant colonies. Through this research, I was able to identify promising methodological approaches and candidate genes, which both broadens our understanding of P. barbatus nestmate recognition systems and supports future functional genetic studies of CHCs in ants.
ContributorsCash, Elizabeth I (Author) / Gadau, Jürgen (Thesis advisor) / Liebig, Jürgen (Thesis advisor) / Fewell, Jennifer (Committee member) / Hölldobler, Berthold (Committee member) / Kusumi, Kenro (Committee member) / Arizona State University (Publisher)
Created2016
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 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.
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
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
Description
Next-generation sequencing is a powerful tool for detecting genetic variation. How-ever, it is also error-prone, with error rates that are much larger than mutation rates.
This can make mutation detection difficult; and while increasing sequencing depth
can often help, sequence-specific errors and other non-random biases cannot be de-
tected by increased depth. The problem of accurate genotyping is exacerbated when
there is not a reference genome or other auxiliary information available.
I explore several methods for sensitively detecting mutations in non-model or-
ganisms using an example Eucalyptus melliodora individual. I use the structure of
the tree to find bounds on its somatic mutation rate and evaluate several algorithms
for variant calling. I find that conventional methods are suitable if the genome of a
close relative can be adapted to the study organism. However, with structured data,
a likelihood framework that is aware of this structure is more accurate. I use the
techniques developed here to evaluate a reference-free variant calling algorithm.
I also use this data to evaluate a k-mer based base quality score recalibrator
(KBBQ), a tool I developed to recalibrate base quality scores attached to sequencing
data. Base quality scores can help detect errors in sequencing reads, but are often
inaccurate. The most popular method for correcting this issue requires a known
set of variant sites, which is unavailable in most cases. I simulate data and show
that errors in this set of variant sites can cause calibration errors. I then show that
KBBQ accurately recalibrates base quality scores while requiring no reference or other
information and performs as well as other methods.
Finally, I use the Eucalyptus data to investigate the impact of quality score calibra-
tion on the quality of output variant calls and show that improved base quality score
calibration increases the sensitivity and reduces the false positive rate of a variant
calling algorithm.
This can make mutation detection difficult; and while increasing sequencing depth
can often help, sequence-specific errors and other non-random biases cannot be de-
tected by increased depth. The problem of accurate genotyping is exacerbated when
there is not a reference genome or other auxiliary information available.
I explore several methods for sensitively detecting mutations in non-model or-
ganisms using an example Eucalyptus melliodora individual. I use the structure of
the tree to find bounds on its somatic mutation rate and evaluate several algorithms
for variant calling. I find that conventional methods are suitable if the genome of a
close relative can be adapted to the study organism. However, with structured data,
a likelihood framework that is aware of this structure is more accurate. I use the
techniques developed here to evaluate a reference-free variant calling algorithm.
I also use this data to evaluate a k-mer based base quality score recalibrator
(KBBQ), a tool I developed to recalibrate base quality scores attached to sequencing
data. Base quality scores can help detect errors in sequencing reads, but are often
inaccurate. The most popular method for correcting this issue requires a known
set of variant sites, which is unavailable in most cases. I simulate data and show
that errors in this set of variant sites can cause calibration errors. I then show that
KBBQ accurately recalibrates base quality scores while requiring no reference or other
information and performs as well as other methods.
Finally, I use the Eucalyptus data to investigate the impact of quality score calibra-
tion on the quality of output variant calls and show that improved base quality score
calibration increases the sensitivity and reduces the false positive rate of a variant
calling algorithm.
ContributorsOrr, Adam James (Author) / Cartwright, Reed (Thesis advisor) / Wilson, Melissa (Committee member) / Kusumi, Kenro (Committee member) / Taylor, Jesse (Committee member) / Pfeifer, Susanne (Committee member) / Arizona State University (Publisher)
Created2020
Description
Satellite cells are adult muscle stem cells that activate, proliferate, and differentiate into myofibers upon muscle damage. Satellite cells can be cultured and manipulated in vitro, and thus represent an accessible model for studying skeletal muscle biology, and a potential source of autologous stem cells for regenerative medicine. This work summarizes efforts to further understanding of satellite cell biology, using novel model organisms, bioengineering, and molecular and cellular approaches. Lizards are evolutionarily the closest vertebrates to humans that regenerate entire appendages. An analysis of lizard myoprogenitor cell transcriptome determined they were most transcriptionally similar to mammalian satellite cells. Further examination showed that among genes with the highest level of expression in lizard satellite cells were an increased number of regulators of chondrogenesis. In micromass culture, lizard satellite cells formed nodules that expressed chondrogenic regulatory genes, thus demonstrating increased musculoskeletal plasticity. However, to exploit satellite cells for therapeutics, development of an ex vivo culture is necessary. This work investigates whether substrates composed of extracellular matrix (ECM) proteins, as either coatings or hydrogels, can support expansion of this population whilst maintaining their myogenic potency. Stiffer substrates are necessary for in vitro proliferation and differentiation of satellite cells, while the ECM composition was not significantly important. Additionally, satellite cells on hydrogels entered a quiescent state that could be reversed when the cells were subsequently cultured on Matrigel. Proliferation and gene expression data further indicated that C2C12 cells are not a good proxy for satellite cells. To further understand how different signaling pathways control satellite cell behavior, an investigation of the Notch inhibitor protein Numb was carried out. Numb deficient satellite cells fail to activate, proliferate and participate in muscle repair. Examination of Numb isoform expression in satellite cells and embryonic tissues revealed that while developing limb bud, neural tube, and heart express the long and short isoforms of NUMB, satellite cells predominantly express the short isoforms. A preliminary immunoprecipitation- proteomics experiment suggested that the roles of NUMB in satellite cells are related to cell cycle modulation, cytoskeleton dynamics, and regulation of transcription factors necessary for satellite cell function.
ContributorsPalade, Joanna (Author) / Wilson-Rawls, Norma (Thesis advisor) / Rawls, Jeffrey (Committee member) / Kusumi, Kenro (Committee member) / Newbern, Jason (Committee member) / Stabenfeldt, Sarah (Committee member) / Arizona State University (Publisher)
Created2020
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 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
Description
Structural Equation Modeling (SEM) is a multivariate analysis methodology that could potentially be utilized to examine the barrier effect that river systems have on genetic differentiation. In this project, river systems are split into the variables of Daily Average Discharge, Average River Width, and Seasonality measurements and regressed onto the genetic differentiation, measured as Fst. This data was collected from the USGS database (U.S. Geological Survey, 2020), sequencing files from differing literature, or Google Earth measurements. Different Structural Equation Modeling models are used to model different system structures as well as compare it to more traditional methodologies like Generalized Linear Modeling and Generalized Linear Mixed Modeling. Ultimately results were limited by the small sample size, however, interesting patterns still emerged from the models. The SE models indicate that Discharge plays a primary role in the genetic differentiation of adjacent river populations. In addition to this, the results demonstrate how quantification of indirect effects, particularly those relating to discharge, give more informative interpretations than traditional multivariate statistics alone. These findings prompt further investigations into this potential methodology.
ContributorsMaag, Garett (Author) / Dolby, Greer A. (Thesis advisor) / Kusumi, Kenro (Thesis advisor) / Stokes, Maya F. (Committee member) / Barly, Anthony (Committee member) / Arizona State University (Publisher)
Created2023