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 - 7 of 7
Filtering by
- All Subjects: Biology
- Creators: Wang, Xiao
- Creators: Brownell, Sara E
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
Teaching evolution has been shown to be a challenge for faculty, in both K-12 and postsecondary education. Many of these challenges stem from perceived conflicts not only between religion and evolution, but also faculty beliefs about religion, it's compatibility with evolutionary theory, and it's proper role in classroom curriculum. Studies suggest that if educators engage with students' religious beliefs and identity, this may help students have positive attitudes towards evolution. The aim of this study was to reveal attitudes and beliefs professors have about addressing religion and providing religious scientist role models to students when teaching evolution. 15 semi-structured interviews of tenured biology professors were conducted at a large Midwestern universiy regarding their beliefs, experiences, and strategies teaching evolution and particularly, their willingness to address religion in a class section on evolution. Following a qualitative analysis of transcripts, professors did not agree on whether or not it is their job to help students accept evolution (although the majority said it is not), nor did they agree on a definition of "acceptance of evolution". Professors are willing to engage in students' religious beliefs, if this would help their students accept evolution. Finally, professors perceived many challenges to engaging students' religious beliefs in a science classroom such as the appropriateness of the material for a science class, large class sizes, and time constraints. Given the results of this study, the author concludes that instructors must come to a consensus about their goals as biology educators as well as what "acceptance of evolution" means, before they can realistically apply the engagement of student's religious beliefs and identity as an educational strategy.
ContributorsBarnes, Maryann Elizabeth (Author) / Brownell, Sara E (Thesis advisor) / Brem, Sarah K. (Thesis advisor) / Lynch, John M. (Committee member) / Ellison, Karin (Committee member) / Arizona State University (Publisher)
Created2014
Description
Guided by Tinto’s Theory of College Student Departure, I conducted a set of five studies to identify factors that influence students’ social integration in college science active learning classes. These studies were conducted in large-enrollment college science courses and some were specifically conducted in undergraduate active learning biology courses. Using qualitative and quantitative methodologies, I identified how students’ identities, such as their gender and LGBTQIA identity, and students’ perceptions of their own intelligence influence their experience in active learning science classes and consequently their social integration in college. I also determined factors of active learning classrooms and instructor behaviors that can affect whether students experience positive or negative social integration in the context of active learning. I found that students’ hidden identities, such as the LGBTQIA identity, are more relevant in active learning classes where students work together and that the increased relevance of one’s identity can have a positive and negative impact on their social integration. I also found that students’ identities can predict their academic self-concept, or their perception of their intelligence as it compares to others’ intelligence in biology, which in turn predicts their participation in small group-discussion. While many students express a fear of negative evaluation, or dread being evaluated negatively by others when speaking out in active learning classes, I identified that how instructors structure group work can cause students to feel more or less integrated into the college science classroom. Lastly, I identified tools that instructors can use, such as name tents and humor, which can positive affect students’ social integration into the college science classroom. In sum, I highlight inequities in students’ experiences in active learning science classrooms and the mechanisms that underlie some of these inequities. I hope this work can be used to create more inclusive undergraduate active learning science courses.
ContributorsCooper, Katelyn M (Author) / Brownell, Sara E (Thesis advisor) / Stout, Valerie (Committee member) / Collins, James (Committee member) / Orchinik, Miles (Committee member) / Zheng, Yi (Committee member) / Arizona State University (Publisher)
Created2018
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
Exploring the Relationship Between Depression and Graduate School Among Life Sciences Ph.D. Students
Description
Depression is one of the top mental health concerns among biology graduate students and has contributed to the “graduate student mental health crisis” declared in 2018. Prominent science outlets have called for interventions to improve graduate student mental health, but few studies have examined the relationship between depression and graduate school among life sciences Ph.D. students. In this coupled set of qualitative interview studies, 50 life sciences Ph.D. students from 28 institutions across the United States were interviewed. The first study explored how research and teaching affect depression in Ph.D. students and how depression in turn also affects students’ experiences in graduate school. Using inductive coding, four overarching aspects of graduate school that influenced student depression were highlighted, (1) structure in teaching and research, (2) positive and negative reinforcement, (3) success and failure, and (4) social support and isolation. The second study explored depression as a concealable stigmatized identity (CSI) by examining (1) to what extent and why graduate students revealed their depression to faculty advisors, graduate students, and undergraduate researchers, and (2) the consequences or benefits that they perceive are associated with revealing one’s depression through a hybrid approach of deductive and inductive coding. Graduate students most commonly revealed their depression to other graduate students; however, most were reluctant to share their depression with undergraduate researchers. These qualitative interview studies provide insights into creating more inclusive life science graduate programs for students with depression.
ContributorsWiesenthal, Nicholas John (Author) / Cooper, Katelyn M (Thesis advisor) / Brownell, Sara E (Committee member) / Maienschein, Jane (Committee member) / Arizona State University (Publisher)
Created2022
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