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 - 5 of 5
Filtering by
- All Subjects: Biology
Description
The portability of genetic tools from one organism to another is a cornerstone of synthetic biology. The shared biological language of DNA-to-RNA-to-protein allows for expression of polypeptide chains in phylogenetically distant organisms with little modification. The tools and contexts are diverse, ranging from catalytic RNAs in cell-free systems to bacterial proteins expressed in human cell lines, yet they exhibit an organizing principle: that genes and proteins may be treated as modular units that can be moved from their native organism to a novel one. However, protein behavior is always unpredictable; drop-in functionality is not guaranteed.
My work characterizes how two different classes of tools behave in new contexts and explores methods to improve their functionality: 1. CRISPR/Cas9 in human cells and 2. quorum sensing networks in Escherichia coli.
1. The genome-editing tool CRISPR/Cas9 has facilitated easily targeted, effective, high throughput genome editing. However, Cas9 is a bacterially derived protein and its behavior in the complex microenvironment of the eukaryotic nucleus is not well understood. Using transgenic human cell lines, I found that gene-silencing heterochromatin impacts Cas9’s ability to bind and cut DNA in a site-specific manner and I investigated ways to improve CRISPR/Cas9 function in heterochromatin.
2. Bacteria use quorum sensing to monitor population density and regulate group behaviors such as virulence, motility, and biofilm formation. Homoserine lactone (HSL) quorum sensing networks are of particular interest to synthetic biologists because they can function as “wires” to connect multiple genetic circuits. However, only four of these networks have been widely implemented in engineered systems. I selected ten quorum sensing networks based on their HSL production profiles and confirmed their functionality in E. coli, significantly expanding the quorum sensing toolset available to synthetic biologists.
My work characterizes how two different classes of tools behave in new contexts and explores methods to improve their functionality: 1. CRISPR/Cas9 in human cells and 2. quorum sensing networks in Escherichia coli.
1. The genome-editing tool CRISPR/Cas9 has facilitated easily targeted, effective, high throughput genome editing. However, Cas9 is a bacterially derived protein and its behavior in the complex microenvironment of the eukaryotic nucleus is not well understood. Using transgenic human cell lines, I found that gene-silencing heterochromatin impacts Cas9’s ability to bind and cut DNA in a site-specific manner and I investigated ways to improve CRISPR/Cas9 function in heterochromatin.
2. Bacteria use quorum sensing to monitor population density and regulate group behaviors such as virulence, motility, and biofilm formation. Homoserine lactone (HSL) quorum sensing networks are of particular interest to synthetic biologists because they can function as “wires” to connect multiple genetic circuits. However, only four of these networks have been widely implemented in engineered systems. I selected ten quorum sensing networks based on their HSL production profiles and confirmed their functionality in E. coli, significantly expanding the quorum sensing toolset available to synthetic biologists.
ContributorsDaer, René (Author) / Haynes, Karmella (Thesis advisor) / Brafman, David (Committee member) / Nielsen, David (Committee member) / Kiani, Samira (Committee member) / Arizona State University (Publisher)
Created2017
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
Cardiovascular disease (CVD) remains the leading cause of mortality, resulting in 1 out of 4 deaths in the United States at the alarming rate of 1 death every 36 seconds, despite great efforts in ongoing research. In vitro research to study CVDs has had limited success, due to lack of biomimicry and structural complexity of 2D models. As such, there is a critical need to develop a 3D, biomimetic human cardiac tissue within precisely engineered in vitro platforms. This PhD dissertation involved development of an innovative anisotropic 3D human stem cell-derived cardiac tissue on-a-chip model (i.e., heart on-a-chip), with an enhanced maturation tissue state, as demonstrated through extensive biological assessments. To demonstrate the potential of the platform to study cardiac-specific diseases, the developed heart on-a-chip was used to model myocardial infarction (MI) due to exposure to hypoxia. The successful induction of MI on-a-chip (heart attack-on-a-chip) was evidenced through fibrotic tissue response, contractile dysregulation, and transcriptomic regulation of key pathways.This dissertation also described incorporation of CRISPR/Cas9 gene-editing to create a human induced pluripotent stem cell line (hiPSC) with a mutation in KCNH2, the gene implicated in Long QT Syndrome Type 2 (LQTS2). This novel stem cell line, combined with the developed heart on-a-chip technology, led to creation of a 3D human cardiac on-chip tissue model of LQTS2 disease.. Extensive mechanistic biological and electrophysiological characterizations were performed to elucidate the mechanism of R531W mutation in KCNH2, significantly adding to existing knowledge about LQTS2. In summary, this thesis described creation of a LQTS2 cardiac on-a-chip model, incorporated with gene-edited hiPSC-cardiomyocytes and hiPSC-cardiac fibroblasts, to study mechanisms of LQTS2.
Overall, this dissertation provides broad impact for fundamental studies toward cardiac biological studies as well as drug screening applications. Specifically, the developed heart on-a-chip from this dissertation provides a unique alternative platform to animal testing and 2D studies that recapitulates the human myocardium, with capabilities to model critical CVDs to study disease mechanisms, and/or ultimately lead to development of future therapeutic strategies.
ContributorsVeldhuizen, Jaimeson (Author) / Nikkhah, Mehdi (Thesis advisor) / Brafman, David (Committee member) / Ebrahimkhani, Mo (Committee member) / Migrino, Raymond Q (Committee member) / Plaisier, Christopher (Committee member) / Arizona State University (Publisher)
Created2021
Description
Resistance to existing anti-cancer drugs poses a key challenge in the field of medical oncology, in that it results in the tumor not responding to treatment using the same medications to which it responded previously, leading to treatment failure. Adaptive therapy utilizes evolutionary principles of competitive suppression, leveraging competition between drug resistant and drug sensitive cells, to keep the population of drug resistant cells under control, thereby extending time to progression (TTP), relative to standard treatment using maximum tolerated dose (MTD). Development of adaptive therapy protocols is challenging, as it involves many parameters, and the number of parameters increase exponentially for each additional drug. Furthermore, the drugs could have a cytotoxic (killing cells directly), or a cytostatic (inhibiting cell division) mechanism of action, which could affect treatment outcome in important ways. I have implemented hybrid agent-based computational models to investigate adaptive therapy, using either a single drug (cytotoxic or cytostatic), or two drugs (cytotoxic or cytostatic), simulating three different adaptive therapy protocols for treatment using a single drug (dose modulation, intermittent, dose-skipping), and seven different treatment protocols for treatment using two drugs: three dose modulation (DM) protocols (DM Cocktail Tandem, DM Ping-Pong Alternate Every Cycle, DM Ping-Pong on Progression), and four fixed-dose (FD) protocols (FD Cocktail Intermittent, FD Ping-Pong Intermittent, FD Cocktail Dose-Skipping, FD Ping-Pong Dose-Skipping). The results indicate a Goldilocks level of drug exposure to be optimum, with both too little and too much drug having adverse effects. Adaptive therapy works best under conditions of strong cellular competition, such as high fitness costs, high replacement rates, or high turnover. Clonal competition is an important determinant of treatment outcome, and as such treatment using two drugs leads to more favorable outcome than treatment using a single drug. Switching drugs every treatment cycle (ping-pong) protocols work particularly well, as well as cocktail dose modulation, particularly when it is feasible to have a highly sensitive measurement of tumor burden. In general, overtreating seems to have adverse survival outcome, and triggering a treatment vacation, or stopping treatment sooner when the tumor is shrinking seems to work well.
ContributorsSaha, Kaushik (Author) / Maley, Carlo C (Thesis advisor) / Forrest, Stephanie (Committee member) / Anderson, Karen S (Committee member) / Cisneros, Luis H (Committee member) / Arizona State University (Publisher)
Created2023
Cancer autoantibody biomarker discovery and validation using nucleic acid programmable protein array
Description
Currently in the US, many patients with cancer do not benefit from the population-based screening, due to challenges associated with the existing cancer screening scheme. Blood-based diagnostic assays have the potential to detect diseases in a non-invasive way. Proteins released from small early tumors may only be present intermittently and get diluted to tiny concentrations in the blood, making them difficult to use as biomarkers. However, they can induce autoantibody (AAb) responses, which can amplify the signal and persist in the blood even if the antigen is gone. Circulating autoantibodies is a promising class of molecules that have potential to serve as early detection biomarkers for cancers. This Ph.D thesis aims to screen for autoantibody biomarkers for the early detection of two deadly cancer, basal-like breast cancer and lung adenocarcinoma. First, a method was developed to display proteins in both native and denatured conformation on protein array. This method adopted a novel protein tag technology, called HaloTag, to covalently immobilize proteins on glass slide surface. The covalent attachment allowed these proteins to endure harsh treatment without getting dissociated from slide surface, which enabled the profiling of antibody responses against both conformational and linear epitopes. Next, a plasma screening protocol was optimized to significantly increase signal to noise ratio of protein array based AAb detection. Following this, the AAb responses in basal-like breast cancer were explored using nucleic acid programmable protein arrays (NAPPA) containing 10,000 full-length human proteins in 45 cases and 45 controls. After verification in a large sample set (145 basal-like breast cancer cases / 145 controls / 70 non-basal breast cancer) by ELISA, a 13-AAb classifier was developed to differentiate patients from controls with a sensitivity of 33% at 98% specificity. Similar approach was also applied to the lung cancer study to identify AAbs that distinguished lung cancer patients from computed-tomography positive benign pulmonary nodules (137 lung cancer cases, 127 smoker controls, 170 benign controls). In this study, two panels of AAbs were discovered that showed promising sensitivity and specificity. Six out of eight AAb targets were also found to have elevated mRNA level in lung adenocarcinoma patients using TCGA data. These projects as a whole provide novel insights on the association between AAbs and cancer, as well as general B cell antigenicity against self-proteins.
ContributorsWang, Jie (Author) / LaBaer, Joshua (Thesis advisor) / Anderson, Karen S (Committee member) / Lake, Douglas F (Committee member) / Chang, Yung (Committee member) / Arizona State University (Publisher)
Created2015