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Description
Alzheimer’s Disease (AD) affects over 5 million individuals in the U.S. and has a direct cost estimated in excess of $200 billion per year. Broadly speaking, there are two forms of AD—early-onset, familial AD (FAD) and late-onset-sporadic AD (SAD). Animal models of AD, which rely on the overexpression of FAD-related mutations, have provided important insights into the disease. However, these models do not display important disease-related pathologies and have been limited in their ability to model the complex genetics associated with SAD.
Advances in cellular reprogramming, have enabled the generation of in vitro disease models that can be used to dissect disease mechanisms and evaluate potential therapeutics. To that end, efforts by many groups, including the Brafman laboratory, to generated patient-specific hiPSCs have demonstrated the promise of studying AD in a simplified and accessible system. However, neurons generated from these hiPSCs have shown some, but not all, of the early molecular and cellular hallmarks associated with the disease. Additionally, phenotypes and pathological hallmarks associated with later stages of the human disease have not been observed with current hiPSC-based systems. Further, disease relevant phenotypes in neurons generated from SAD hiPSCs have been highly variable or largely absent. Finally, the reprogramming process erases phenotypes associated with cellular aging and, as a result, iPSC-derived neurons more closely resemble fetal brain rather than adult brain.
It is well-established that in vivo cells reside within a complex 3-D microenvironment that plays a significant role in regulating cell behavior. Signaling and other cellular functions, such as gene expression and differentiation potential, differ in 3-D cultures compared with 2-D substrates. Nonetheless, previous studies using AD hiPSCs have relied on 2-D neuronal culture models that do not reflect the 3-D complexity of native brain tissue, and therefore, are unable to replicate all aspects of AD pathogenesis. Further, the reprogramming process erases cellular aging phenotypes. To address these limitations, this project aimed to develop bioengineering methods for the generation of 3-D organoid-based cultures that mimic in vivo cortical tissue, and to generate an inducible gene repression system to recapitulate cellular aging hallmarks.
Advances in cellular reprogramming, have enabled the generation of in vitro disease models that can be used to dissect disease mechanisms and evaluate potential therapeutics. To that end, efforts by many groups, including the Brafman laboratory, to generated patient-specific hiPSCs have demonstrated the promise of studying AD in a simplified and accessible system. However, neurons generated from these hiPSCs have shown some, but not all, of the early molecular and cellular hallmarks associated with the disease. Additionally, phenotypes and pathological hallmarks associated with later stages of the human disease have not been observed with current hiPSC-based systems. Further, disease relevant phenotypes in neurons generated from SAD hiPSCs have been highly variable or largely absent. Finally, the reprogramming process erases phenotypes associated with cellular aging and, as a result, iPSC-derived neurons more closely resemble fetal brain rather than adult brain.
It is well-established that in vivo cells reside within a complex 3-D microenvironment that plays a significant role in regulating cell behavior. Signaling and other cellular functions, such as gene expression and differentiation potential, differ in 3-D cultures compared with 2-D substrates. Nonetheless, previous studies using AD hiPSCs have relied on 2-D neuronal culture models that do not reflect the 3-D complexity of native brain tissue, and therefore, are unable to replicate all aspects of AD pathogenesis. Further, the reprogramming process erases cellular aging phenotypes. To address these limitations, this project aimed to develop bioengineering methods for the generation of 3-D organoid-based cultures that mimic in vivo cortical tissue, and to generate an inducible gene repression system to recapitulate cellular aging hallmarks.
ContributorsBounds, Lexi Rose (Author) / Brafman, David (Thesis director) / Wang, Xiao (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Synthetic biology is an emerging engineering disciple, which designs and controls biological systems for creation of materials, biosensors, biocomputing, and much more. To better control and engineer these systems, modular genetic components which allow for highly specific and high dynamic range genetic regulation are necessary. Currently the field struggles to demonstrate reliable regulators which are programmable and specific, yet also allow for a high dynamic range of control. Inspired by the characteristics of the RNA toehold switch in E. coli, this project attempts utilize artificial introns and complementary trans-acting RNAs for gene regulation in a eukaryote host, S. cerevisiae. Following modification to an artificial intron, splicing control with RNA hairpins was demonstrated. Temperature shifts led to increased protein production likely due to increased splicing due to hairpin loosening. Progress is underway to demonstrate trans-acting RNA interaction to control splicing. With continued development, we hope to provide a programmable, specific, and effective means for translational gene regulation in S. cerevisae.
ContributorsDorr, Brandon Arthur (Author) / Wang, Xiao (Thesis director) / Green, Alexander (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The parameters of microwave-assisted acid hydrolysis (MAAH) and 1H NMR highly affect the quantitative analysis of protein hydrolysates. Microwave-induction source, NMR spectral resolution, and data analysis are key parameters in the nuclear magnetic resonance – amino acid analysis (NMR-AAA) workflow where errors accrue due to lack of an optimized protocol. Hen egg white lysozyme was hydrolyzed using an 800W domestic microwave oven for varying time points between 10-25 minutes, showing minimal protein hydrolysis after extended time periods. Studies on paramagnetic doping with varying amounts of gadolinium chloride for increased NMR resolution resulted in little T1 reduction in a majority of amino acids and resulted in significant line broadening in concentrations above 1µM. The use of the BAYESIL analysis tool with HOD suppressed 1H-NMR spectra resulted in misplaced template peaks and errors greater than 1% for 10 of 13 profiled amino acids with the highest error being 7.6% (Thr). Comparatively, Chenomx NMR Suite (v7.1) analysis resulted in errors of less than 1% for 9 of 13 profiled amino acids with a highest error value of 3.6% (Lys). Using the optimized protocol, hen egg white lysozyme C was identified at rank 1 with a score of 64 in a Gallus gallus species wide AACompIdent search. This technique reduces error associated with sample handling relative to previously used amino acid analysis (AAA) protocols and requires no derivatization or additional processing of the sample prior to analysis.
ContributorsJordan, Jacob Smith (Author) / Yarger, Jeffery (Thesis director) / Van Horn, Wade (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Many systems in the world \u2014 such as cellular networks, the post service, or transportation pathways \u2014 can be modeled as networks or graphs. The practical applications of graph algorithms generally seek to achieve some goal while minimizing some cost such as money or distance. While the minimum linear arrangement (MLA) problem has been widely-studied amongst graph ordering and embedding problems, there have been no developments into versions of the problem involving degree higher than 2. An application of our problem can be seen in overlay networks in telecommunications. An overlay network is a virtual network that is built on top of another network. It is a logical network where the links between nodes represent the physical paths connecting the nodes in the underlying infrastructure. The underlying physical network may be incomplete, but as long as it is connected, we can build a complete overlay network on top of it. Since some nodes may be overloaded by traffic, we can reduce the strain on the overlay network by limiting the communication between nodes. Some edges, however, may have more importance than others so we must be careful about our selection of which nodes are allowed to communicate with each other. The balance of reducing the degree of the network while maximizing communication forms the basis of our d-degree minimum arrangement problem. In this thesis we will look at several approaches to solving the generalized d-degree minimum arrangement d-MA problem where we embed a graph onto a subgraph of a given degree. We first look into the requirements and challenges of solving the d-MA problem. We will then present a polynomial-time heuristic and compare its performance with the optimal solution derived from integer linear programming. We will show that a simple (d-1)-ary tree construction provides the optimal structure for uniform graphs with large requests sets. Finally, we will present experimental data gathered from running simulations on a variety of graphs to evaluate the efficiency of our heuristic and tree construction.
ContributorsWang, Xiao (Author) / Richa, Andrea (Thesis director) / Nakamura, Mutsumi (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Regional and geographical differences may explain variability in menopausal symptom occurrence due to development of climate-specific thermoneutral zones leading to population-specific hot flash frequencies. Limited information available regarding menopausal symptoms in underserved women living in extreme heat.
Understanding the perception of menopausal symptoms in underserved women living in extreme heat regions to identify if heat impacts perception of menopausal symptoms was the objective of this study. Women in free, low-income, and homeless clinics in Phoenix were surveyed during summer and winter months using a self-administered, written questionnaire including demographic, climate and menopause related questions, including the Green Climacteric Scale (GCS).
A total of 139 predominantly Hispanic (56 %), uninsured (53 %), menopausal (56 %), mid-aged (mean 49.9, SD 10.3) women were surveyed— 36% were homeless or in shelters. Most women were not on menopausal hormone therapy (98 %). Twenty-two percent reported hot flashes and 26% night sweats. Twenty-five percent of women reported previously becoming ill from heat. More women thought season influenced menopausal symptoms during summer than winter (41 % vs. 14 %, p = 0.0009). However, majority of women did not think temperature outside influenced their menopausal symptoms and that did not differ by season (73 % in winter vs. 60% in summer, p=0.1094). No statistically significant differences seen for vasomotor symptoms between winter and summer months.
Regional and geographical differences may be key in understanding the variability in menopausal symptoms. Regardless of season, the menopausal, underserved and homeless women living in Arizona reported few vasomotor symptoms. In the summer, they were more likely to report that the season influenced their menopausal symptoms rather than temperature suggesting an influence of the season on symptom perception.
ContributorsMukarram, Mahnoor (Author) / Hondula, David M. (Thesis director) / Kling, Juliana (Committee member) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The City of Phoenix Street Transportation Department partnered with the Rob and Melani Walton Sustainability Solutions Service at Arizona State University (ASU) and researchers from various ASU schools to evaluate the effectiveness, performance, and community perception of the new pavement coating. The data collection and analysis occurred across multiple neighborhoods and at varying times across days and/or months over the course of one year (July 15, 2020–July 14, 2021), allowing the team to study the impacts of the surface treatment under various weather conditions.
ContributorsMiddel, Ariane (Author) / Vanos, Jennifer K. (Author) / Hondula, David M. (Author) / Kaloush, Kamil (Author) / Sailor, David (Author) / Medina, Jose R. (Jose Roberto) (Author) / Schneider, Florian (Author) / Ortiz, Johny Cordova (Author) / Campbell, Bill (Author) / Epel, Erin (Contributor) / Rice, Brendan (Contributor) / Garcia, Ruth (Contributor) / Phoenix (Ariz.). Street Transportation Department (Contributor) / City of Phoenix (Funder) / Industrial Development Authority of the County of Maricopa (Funder) / Julie Ann Wrigley Global Institute of Sustainability (Funder) / Arizona State University. Healthy Urban Environments Program (Contributor)
Created2021-09
Description
Transition metal oxides are used for numerous applications, includingsemiconductors, batteries, solar cells, catalysis, magnetic devices, and are commonly
observed in interstellar media. However, the atomic-scale properties which dictate the
overall bulk material activity is still lacking fundamental details. Most importantly, how
the electron shells of metals and O atoms mix is inherently significant to reactivity. This
thesis compares the binding and excited state properties of highly correlated first-row
transition metal oxides using four separate transition metal systems of Ti, Cr, Fe and Ni.
Laser ablation coupled with femtosecond pump-probe spectroscopy is utilized to resolve
the time-dependent excited state relaxation dynamics of atomically precise neutral
clusters following 400 nm (3.1 eV) photoexcitation. All transition metal oxides form
unique stable stoichiometries with excited state dynamics that evolve due to oxidation,
size, or geometry. Theoretical calculations assist in experimental analysis, showing
correlations between charge transfer characteristics, electron and hole localization, and
magnetic properties to the experimentally determined excited state lifetimes.
This thesis finds that neutral Ti and Cr form stable stoichiometries of MO2 (M =
Ti, Cr) which easily lose up to two O atoms, while neutral Fe and Ni primarily form MO
(M = Fe, Ni) geometries with suboxides also produced. TiO2 clusters possess excited
state lifetimes that increase with additional cluster units to ~600 fs, owing to a larger
delocalization of excited charge carriers with cluster size. CrO2 clusters show a unique
inversed metallic behavior with O content, where the fast (~30 fs) metallic relaxation
component associated with electron scattering increases with higher O content, connected
to the percent of ligand-to-metal charge transfer (LMCT) character and higher density of
states. FeO clusters show a decreased lifetime with size, reaching a plateau of ~150 fs at
the size of (FeO)5 related to the density of states as clusters form 3D geometries. Finally,
neutral (NiO)n clusters all have similar fast lifetimes (~110 fs), with suboxides possessing
unexpected electronic transitions involving s-orbitals, increasing excited state lifetimes
up to 80% and causing long-lived states lasting over 2.5 ps. Similarities are drawn
between each cluster system, providing valuable information about each metal oxide
species and the evolution of excited state dynamics as a result of the occupied d-shell.
The work presented within this thesis will lead to novel materials of increased reactivity
while facilitating a deeper fundamental understanding on the effect of electron
interactions on chemical properties.
ContributorsGarcia, Jacob M. (Author) / Sayres, Scott G (Thesis advisor) / Yarger, Jeffery (Committee member) / Steimle, Timothy (Committee member) / Arizona State University (Publisher)
Created2021
Description
The advent of CRISPR/Cas9 revolutionized the field of genetic engineering and gave rise to the development of new gene editing tools including prime editing. Prime editing is a versatile gene editing method that mediates precise insertions and deletions and can perform all 12 types of point mutations. In turn, prime editing represents great promise in the design of new gene therapies and disease models where editing was previously not possible using current gene editing techniques. Despite advancements in genome modification technologies, parallel enrichment strategies of edited cells remain lagging behind in development. To this end, this project aimed to enhance prime editing using transient reporter for editing enrichment (TREE) technology to develop a method for the rapid generation of clonal isogenic cell lines for disease modeling. TREE uses an engineered BFP variant that upon a C-to-T conversion will convert to GFP after target modification. Using flow cytometry, this BFP-to-GFP conversion assay enables the isolation of edited cell populations via a fluorescent reporter of editing. Prime induced nucleotide engineering using a transient reporter for editing enrichment (PINE-TREE), pairs prime editing with TREE technology to efficiently enrich for prime edited cells. This investigation revealed PINE-TREE as an efficient editing and enrichment method compared to a conventional reporter of transfection (RoT) enrichment strategy. Here, PINE-TREE exhibited a significant increase in editing efficiencies of single nucleotide conversions, small insertions, and small deletions in multiple human cell types. Additionally, PINE-TREE demonstrated improved clonal cell editing efficiency in human induced pluripotent stem cells (hiPSCs). Most notably, PINE-TREE efficiently generated clonal isogenic hiPSCs harboring a mutation in the APOE gene for in vitro modeling of Alzheimer’s Disease. Collectively, results gathered from this study exhibited PINE-TREE as a valuable new tool in genetic engineering to accelerate the generation of clonal isogenic cell lines for applications in developmental biology, disease modeling, and drug screening.
ContributorsKostes, William Warner (Author) / Brafman, David (Thesis advisor) / Jacobs, Bertram (Committee member) / Lapinaite, Audrone (Committee member) / Tian, Xiaojun (Committee member) / Wang, Xiao (Committee member) / Arizona State University (Publisher)
Created2022
Description
Infrastructure systems are facing non-stationary challenges that stem from climate change and the increasingly complex interactions between the social, ecological, and technological systems (SETSs). It is crucial for transportation infrastructures—which enable residents to access opportunities and foster prosperity, quality of life, and social connections—to be resilient under these non-stationary challenges. Vulnerability assessment (VA) examines the potential consequences a system is likely to experience due to exposure to perturbation or stressors and lack of the capacity to adapt. Post-fire debris flow and heat represent particularly challenging problems for infrastructure and users in the arid U.S. West. Post-fire debris flow, which is manifested with heat and drought, produces powerful runoff threatening physical transportation infrastructures. And heat waves have devastating health effects on transportation infrastructure users, including increased mortality rates. VA anticipates the potential consequences of these perturbations and enables infrastructure stakeholders to improve the system's resilience. The current transportation climate VA—which only considers a single direct climate stressor on the infrastructure—falls short of addressing the wildfire and heat challenges. This work proposes advanced transportation climate VA methods to address the complex and multiple climate stressors and the vulnerability of infrastructure users. Two specific regions were chosen to carry out the progressive transportation climate VA: 1) the California transportation networks’ vulnerability to post-fire debris flows, and 2) the transportation infrastructure user’s vulnerability to heat exposure in Phoenix.
ContributorsLi, Rui (Author) / Chester, Mikhail V. (Thesis advisor) / Middel, Ariane (Committee member) / Hondula, David M. (Committee member) / Pendyala, Ram (Committee member) / Arizona State University (Publisher)
Created2022
Description
Over the past 20 years, the fields of synthetic biology and synthetic biosystems engineering have grown into mature disciplines, leading to significant breakthroughs in cancer research, diagnostics, cell-based medicines, biochemical production, etc. Application of mathematical modelling to biological and biochemical systems have not only given great insight into how these systems function, but also have lent enough predictive power to aid in the forward-engineering of synthetic constructs. However, progress has been impeded by several modes of context-dependence unique to biological and biochemical systems that are not seen in traditional engineering disciplines, resulting in the need for lengthy design-build-test cycles before functional prototypes are generated.In this work, two of these universal modes of context dependence – resource competition and growth feedback –their effects on synthetic gene circuits and potential control mechanisms, are studied and characterized. Results demonstrate that a novel competitive control architecture can be utilized to mitigate the effects of winner-take-all resource competition (a form of context dependence where distinct gene modules influence each other by competing over a shared pool of transcriptional/translational resources) in synthetic gene circuits and restore circuits to their intended function. Application of the fluctuation-dissipation theorem and rigorous stochastic simulations demonstrate that realistic resource constraints present in cells at the transcriptional and translational levels influence noise in gene circuits in a nonmonotonic fashion, either increasing or decreasing noise depending on the transcriptional/translational capacity.
Growth feedback on the other hand links circuit function to cellular growth rate via increased protein dilution rate during exponential growth phase. This in turn can result in the collapse of bistable gene circuits as the accelerated dilution rate forces switches in a high stable state to fall to a low stable state. Mathematical modelling and experimental data demonstrate that application of repressive links can insulate sensitive parts of gene circuits against growth-fluctuations and can in turn increase the robustness of multistable circuits in growth contexts.
The results presented in this work aid in the accumulation of understanding of biological and biochemical context dependence, and corresponding control strategies and design principles engineers can utilize to mitigate these effects.
ContributorsStone, Austin (Author) / Tian, Xiao-jun (Thesis advisor) / Wang, Xiao (Committee member) / Smith, Barbara (Committee member) / Kuang, Yang (Committee member) / Cheng, Albert (Committee member) / Arizona State University (Publisher)
Created2023