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: Wang, Xiao
- Creators: Chen, Qiang
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
Infections caused by the Hepatitis C Virus (HCV) are very common worldwide, affecting up to 3% of the population. Chronic infection of HCV may develop into liver cirrhosis and liver cancer which is among the top five of the most common cancers. Therefore, vaccines against HCV are under intense study in order to prevent HCV from harming people's health. The envelope protein 2 (E2) of HCV is thought to be a promising vaccine candidate because it can directly bind to a human cell receptor and plays a role in viral entry. However, the E2 protein production in cells is inefficient due to its complicated matured structure. Folding of E2 in the endoplasmic reticulum (ER) is often error-prone, resulting in production of aggregates and misfolded proteins. These incorrect forms of E2 are not functional because they are not able to bind to human cells and stimulate antibody response to inhibit this binding. This study is aimed to overcome the difficulties of HCV E2 production in plant system. Protein folding in the ER requires great assistance from molecular chaperones. Thus, in this study, two molecular chaperones in the ER, calreticulin and calnexin, were transiently overexpressed in plant leaves in order to facilitate E2 folding and production. Both of them showed benefits in increasing the yield of E2 and improving the quality of E2. In addition, poorly folded E2 accumulated in the ER may cause stress in the ER and trigger transcriptional activation of ER molecular chaperones. Therefore, a transcription factor involved in this pathway, named bZIP60, was also overexpressed in plant leaves, aiming at up-regulating a major family of molecular chaperones called BiP to assist protein folding. However, our results showed that BiP mRNA levels were not up-regulated by bZIP60, but they increased in response to E2 expression. The Western blot analysis also showed that overexpression of bZIP60 had a small effect on promoting E2 folding. Overall, this study suggested that increasing the level of specific ER molecular chaperones was an effective way to promote HCV E2 protein production and maturation.
ContributorsHong, Fan (Author) / Mason, Hugh (Thesis advisor) / Gaxiola, Roberto (Committee member) / Chang, Yung (Committee member) / Chen, Qiang (Committee member) / Arizona State University (Publisher)
Created2011
Description
Immunotherapy has been revitalized with the advent of immune checkpoint blockade
treatments, and neo-antigens are the targets of immune system in cancer patients who
respond to the treatments. The cancer vaccine field is focused on using neo-antigens from
unique point mutations of genomic sequence in the cancer patient for making
personalized cancer vaccines. However, we choose a different path to find frameshift
neo-antigens at the mRNA level and develop broadly effective cancer vaccines based on
frameshift antigens.
In this dissertation, I have summarized and characterized all the potential frameshift
antigens from microsatellite regions in human, dog and mouse. A list of frameshift
antigens was validated by PCR in tumor samples and the mutation rate was calculated for
one candidate – SEC62. I develop a method to screen the antibody response against
frameshift antigens in human and dog cancer patients by using frameshift peptide arrays.
Frameshift antigens selected by positive antibody response in cancer patients or by MHC
predictions show protection in different mouse tumor models. A dog version of the
cancer vaccine based on frameshift antigens was developed and tested in a small safety
trial. The results demonstrate that the vaccine is safe and it can induce strong B and T cell
immune responses. Further, I built the human exon junction frameshift database which
includes all possible frameshift antigens from mis-splicing events in exon junctions, and I
develop a method to find potential frameshift antigens from large cancer
immunosignature dataset with these databases. In addition, I test the idea of ‘early cancer
diagnosis, early treatment’ in a transgenic mouse cancer model. The results show that
ii
early treatment gives significantly better protection than late treatment and the correct
time point for treatment is crucial to give the best clinical benefit. A model for early
treatment is developed with these results.
Frameshift neo-antigens from microsatellite regions and mis-splicing events are
abundant at mRNA level and they are better antigens than neo-antigens from point
mutations in the genomic sequences of cancer patients in terms of high immunogenicity,
low probability to cause autoimmune diseases and low cost to develop a broadly effective
vaccine. This dissertation demonstrates the feasibility of using frameshift antigens for
cancer vaccine development.
treatments, and neo-antigens are the targets of immune system in cancer patients who
respond to the treatments. The cancer vaccine field is focused on using neo-antigens from
unique point mutations of genomic sequence in the cancer patient for making
personalized cancer vaccines. However, we choose a different path to find frameshift
neo-antigens at the mRNA level and develop broadly effective cancer vaccines based on
frameshift antigens.
In this dissertation, I have summarized and characterized all the potential frameshift
antigens from microsatellite regions in human, dog and mouse. A list of frameshift
antigens was validated by PCR in tumor samples and the mutation rate was calculated for
one candidate – SEC62. I develop a method to screen the antibody response against
frameshift antigens in human and dog cancer patients by using frameshift peptide arrays.
Frameshift antigens selected by positive antibody response in cancer patients or by MHC
predictions show protection in different mouse tumor models. A dog version of the
cancer vaccine based on frameshift antigens was developed and tested in a small safety
trial. The results demonstrate that the vaccine is safe and it can induce strong B and T cell
immune responses. Further, I built the human exon junction frameshift database which
includes all possible frameshift antigens from mis-splicing events in exon junctions, and I
develop a method to find potential frameshift antigens from large cancer
immunosignature dataset with these databases. In addition, I test the idea of ‘early cancer
diagnosis, early treatment’ in a transgenic mouse cancer model. The results show that
ii
early treatment gives significantly better protection than late treatment and the correct
time point for treatment is crucial to give the best clinical benefit. A model for early
treatment is developed with these results.
Frameshift neo-antigens from microsatellite regions and mis-splicing events are
abundant at mRNA level and they are better antigens than neo-antigens from point
mutations in the genomic sequences of cancer patients in terms of high immunogenicity,
low probability to cause autoimmune diseases and low cost to develop a broadly effective
vaccine. This dissertation demonstrates the feasibility of using frameshift antigens for
cancer vaccine development.
ContributorsZhang, Jian (Author) / Johnston, Stephen Albert (Thesis advisor) / Chang, Yung (Committee member) / Stafford, Phillip (Committee member) / Chen, Qiang (Committee member) / Arizona State University (Publisher)
Created2018
Description
Antibodies are naturally occurring proteins that protect a host during infection through direct neutralization and/or recruitment of the innate immune system. Unfortunately, in some infections, antibodies present unique hurdles that must be overcome for a safer and more efficacious antibody-based therapeutic (e.g., antibody dependent viral enhancement (ADE) and inflammatory pathology). This dissertation describes the utilization of plant expression systems to produce N-glycan specific antibody-based therapeutics for Dengue Virus (DENV) and Chikungunya Virus (CHIKV). The Fc region of an antibody interacts with Fcγ Receptors (FcγRs) on immune cells and components of the innate immune system. Each class of immune cells has a distinct action of neutralization (e.g., antibody dependent cell-mediated cytotoxicity (ADCC) and antibody dependent cell-mediated phagocytosis (ADCP)). Therefore, structural alteration of the Fc region results in novel immune pathways of protection. One approach is to modulate the N-glycosylation in the Fc region of the antibody. Of scientific significance, is the plant’s capacity to express human antibodies with homogenous plant and humanized N-glycosylation (WT and GnGn, respectively). This allows to study how specific glycovariants interact with other components of the immune system to clear an infection, producing a tailor-made antibody for distinct diseases. In the first section, plant-produced glycovariants were explored for reduced interactions with specific FcγRs for the overall reduction in ADE for DENV infections. The results demonstrate a reduction in ADE of our plant-produced monoclonal antibodies in in vitro experiments, which led to a greater survival in vivo of immunodeficient mice challenged with lethal doses of DENV and a sub-lethal dose of DENV in ADE conditions. In the second section, plant-produced glycovariants were explored for increased interaction with specific FcγRs to improve ADCC in the treatment of the highly inflammatory CHIKV. The results demonstrate an increase ADCC activity in in vitro experiments and a reduction in CHIKV-associated inflammation in in vivo mouse models. Overall, the significance of this dissertation is that it can provide a treatment for DENV and CHIKV; but equally importantly, give insight to the role of N-glycosylation in antibody effector functions, which has a broader implication for therapeutic development for other viral infections.
ContributorsHurtado, Jonathan (Author) / Chen, Qiang (Thesis advisor) / Arntzen, Charles (Committee member) / Borges, Chad (Committee member) / Lake, Douglas (Committee member) / Arizona State University (Publisher)
Created2019
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
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