Matching Items (47)
Description
Induced pluripotent stem cells (iPSCs) are an intriguing approach for neurological disease modeling, because neural lineage-specific cell types that retain the donors' complex genetics can be established in vitro. The statistical power of these iPSC-based models, however, is dependent on accurate diagnoses of the somatic cell donors; unfortunately, many neurodegenerative diseases are commonly misdiagnosed in live human subjects. Postmortem histopathological examination of a donor's brain, combined with premortem clinical criteria, is often the most robust approach to correctly classify an individual as a disease-specific case or unaffected control. We describe the establishment of primary dermal fibroblasts cells lines from 28 autopsy donors. These fibroblasts were used to examine the proliferative effects of establishment protocol, tissue amount, biopsy site, and donor age. As proof-of-principle, iPSCs were generated from fibroblasts from a 75-year-old male, whole body donor, defined as an unaffected neurological control by both clinical and histopathological criteria. To our knowledge, this is the first study describing autopsy donor-derived somatic cells being used for iPSC generation and subsequent neural differentiation. This unique approach also enables us to compare iPSC-derived cell cultures to endogenous tissues from the same donor. We utilized RNA sequencing (RNA-Seq) to evaluate the transcriptional progression of in vitro-differentiated neural cells (over a timecourse of 0, 35, 70, 105 and 140 days), and compared this with donor-identical temporal lobe tissue. We observed in vitro progression towards the reference brain tissue, supported by (i) a significant increasing monotonic correlation between the days of our timecourse and the number of actively transcribed protein-coding genes and long intergenic non-coding RNAs (lincRNAs) (P < 0.05), consistent with the transcriptional complexity of the brain, (ii) an increase in CpG methylation after neural differentiation that resembled the epigenomic signature of the endogenous tissue, and (iii) a significant decreasing monotonic correlation between the days of our timecourse and the percent of in vitro to brain-tissue differences (P < 0.05) for tissue-specific protein-coding genes and all putative lincRNAs. These studies support the utility of autopsy donors' somatic cells for iPSC-based neurological disease models, and provide evidence that in vitro neural differentiation can result in physiologically progression.
ContributorsHjelm, Brooke E (Author) / Craig, David W. (Thesis advisor) / Wilson-Rawls, Norma J. (Thesis advisor) / Huentelman, Matthew J. (Committee member) / Mason, Hugh S. (Committee member) / Kusumi, Kenro (Committee member) / Arizona State University (Publisher)
Created2013
Description
The lack of substantive, multi-dimensional perspectives on civic space planning and design has undermined the potential role of these valuable social and ecological amenities in advancing urban sustainability goals. Responding to these deficiencies, this dissertation utilized mixed quantitative and qualitative methods and synthesized multiple social and natural science perspectives to inform the development of progressive civic space planning and design, theory, and public policy aimed at improving the social, economic, and environmental health of cities. Using Phoenix, Arizona as a case study, the analysis was tailored to arid cities, yet the products and findings are flexible enough to be geographically customized to the social, environmental, built, and public policy goals of other urbanized regions. Organized into three articles, the first paper applies geospatial and statistical methods to analyze and classify urban parks in Phoenix based on multiple social, ecological, and built criteria, including landuse-land cover, `greenness,' and site amenities, as well as the socio- economic and built characteristics of park neighborhoods. The second article uses spatial empirical analysis to rezone the City of Phoenix following transect form-based code. The current park system was then assessed within this framework and recommendations are presented to inform the planning and design of civic spaces sensitive to their social and built context. The final paper culminates in the development of a planning tool and site design guidelines for civic space planning and design across the urban-to-natural gradient augmented with multiple ecosystem service considerations and tailored to desert cities.
ContributorsIbes, Dorothy (Author) / Talen, Emily (Thesis advisor) / Boone, Christopher (Committee member) / Crewe, Katherine (Committee member) / Arizona State University (Publisher)
Created2013
Description
Well-established model systems exist in four out of the seven major classes of vertebrates. These include the mouse, chicken, frog and zebrafish. Noticeably missing from this list is a reptilian model organism for comparative studies between the vertebrates and for studies of biological processes unique to reptiles. To help fill in this gap the green anole lizard, Anolis carolinensis, is being adapted as a model organism. Despite the recent release of the complete genomic sequence of the A. carolinensis, the lizard lacks some resources to aid researchers in their studies. Particularly, the lack of transcriptomic resources for lizard has made it difficult to identify genes complete with alternative splice forms and untranslated regions (UTRs). As part of this work the genome annotation for A. carolinensis was improved through next generation sequencing and assembly of the transcriptomes from 14 different adult and embryonic tissues. This revised annotation of the lizard will improve comparative studies between vertebrates, as well as studies within A. carolinensis itself, by providing more accurate gene models, which provide the bases for molecular studies. To demonstrate the utility of the improved annotations and reptilian model organism, the developmental process of somitogenesis in the lizard was analyzed and compared with other vertebrates. This study identified several key features both divergent and convergent between the vertebrates, which was not previously known before analysis of a reptilian model organism. The improved genome annotations have also allowed for molecular studies of tail regeneration in the lizard. With the annotation of 3' UTR sequences and next generation sequencing, it is now possible to do expressional studies of miRNA and predict their mRNA target transcripts at genomic scale. Through next generation small RNA sequencing and subsequent analysis, several differentially expressed miRNAs were identified in the regenerating tail, suggesting miRNA may play a key role in regulating this process in lizards. Through miRNA target prediction several key biological pathways were identified as potentially under the regulation of miRNAs during tail regeneration. In total, this work has both helped advance A. carolinensis as model system and displayed the utility of a reptilian model system.
ContributorsEckalbar, Walter L (Author) / Kusumi, Kenro (Thesis advisor) / Huentelman, Matthew (Committee member) / Rawls, Jeffery (Committee member) / Wilson-Rawls, Norma (Committee member) / Arizona State University (Publisher)
Created2012
Description
The explicit role of soil organisms in shaping soil health, rates of pedogenesis, and resistance to erosion has only just recently begun to be explored in the last century. However, much of the research regarding soil biota and soil processes is centered on maintaining soil fertility (e.g., plant nutrient availability) and soil structure in mesic- and agro- ecosystems. Despite the empirical and theoretical strides made in soil ecology over the last few decades, questions regarding ecosystem function and soil processes remain, especially for arid areas. Arid areas have unique ecosystem biogeochemistry, decomposition processes, and soil microbial responses to moisture inputs that deviate from predictions derived using data generated in more mesic systems. For example, current paradigm predicts that soil microbes will respond positively to increasing moisture inputs in a water-limited environment, yet data collected in arid regions are not congruent with this hypothesis. The influence of abiotic factors on litter decomposition rates (e.g., photodegradation), litter quality and availability, soil moisture pulse size, and resulting feedbacks on detrital food web structure must be explicitly considered for advancing our understanding of arid land ecology. However, empirical data coupling arid belowground food webs and ecosystem processes are lacking. My dissertation explores the resource controls (soil organic matter and soil moisture) on food web network structure, size, and presence/absence of expected belowground trophic groups across a variety of sites in Arizona.
ContributorsWyant, Karl Arthur (Author) / Sabo, John L (Thesis advisor) / Elser, James J (Committee member) / Childers, Daniel L. (Committee member) / Hall, Sharon J (Committee member) / Stromberg, Juliet C. (Committee member) / Arizona State University (Publisher)
Created2014
Description
The processes of a human somatic cell are very complex with various genetic mechanisms governing its fate. Such cells undergo various genetic mutations, which translate to the genetic aberrations that we see in cancer. There are more than 100 types of cancer, each having many more subtypes with aberrations being unique to each. In the past two decades, the widespread application of high-throughput genomic technologies, such as micro-arrays and next-generation sequencing, has led to the revelation of many such aberrations. Known types and subtypes can be readily identified using gene-expression profiling and more importantly, high-throughput genomic datasets have helped identify novel sub-types with distinct signatures. Recent studies showing usage of gene-expression profiling in clinical decision making in breast cancer patients underscore the utility of high-throughput datasets. Beyond prognosis, understanding the underlying cellular processes is essential for effective cancer treatment. Various high-throughput techniques are now available to look at a particular aspect of a genetic mechanism in cancer tissue. To look at these mechanisms individually is akin to looking at a broken watch; taking apart each of its parts, looking at them individually and finally making a list of all the faulty ones. Integrative approaches are needed to transform one-dimensional cancer signatures into multi-dimensional interaction and regulatory networks, consequently bettering our understanding of cellular processes in cancer. Here, I attempt to (i) address ways to effectively identify high quality variants when multiple assays on the same sample samples are available through two novel tools, snpSniffer and NGSPE; (ii) glean new biological insight into multiple myeloma through two novel integrative analysis approaches making use of disparate high-throughput datasets. While these methods focus on multiple myeloma datasets, the informatics approaches are applicable to all cancer datasets and will thus help advance cancer genomics.
ContributorsYellapantula, Venkata (Author) / Dinu, Valentin (Thesis advisor) / Scotch, Matthew (Committee member) / Wallstrom, Garrick (Committee member) / Keats, Jonathan (Committee member) / Arizona State University (Publisher)
Created2014
Description
Like individual organisms, complex social groups are able to maintain predictable trajectories of growth, from initial colony foundation to mature reproductively capable units. They do so while simultaneously responding flexibly to variation in nutrient availability and intake. Leafcutter ant colonies function as tri-trophic systems, in which the ants harvest vegetation to grow a fungus that, in turn, serves as food for the colony. Fungal growth rates and colony worker production are interdependent, regulated by nutritional and behavioral feedbacks. Fungal growth and quality are directly affected by worker foraging decisions, while worker production is, in turn, dependent on the amount and condition of the fungus. In this dissertation, I first characterized the growth relationship between the workers and the fungus of the desert leafcutter ant Acromyrmex versicolor during early stages of colony development, from colony foundation by groups of queens through the beginnings of exponential growth. I found that this relationship undergoes a period of slow growth and instability when workers first emerge, and then becomes allometrically positive. I then evaluated how mass and element ratios of resources collected by the ants are translated into fungus and worker population growth, and refuse, finding that colony digestive efficiency is comparable to digestive efficiencies of other herbivorous insects and ruminants. To test how colonies behaviorally respond to perturbations of the fungus garden, I quantified activity levels and task performance of workers in colonies with either supplemented or diminished fungus gardens, and found that colonies adjusted activity and task allocation in response to the fungus garden size. Finally, to identify possible forms of nutrient limitation, I measured how colony performance was affected by changes in the relative amounts of carbohydrates, protein, and phosphorus available in the resources used to grow the fungus garden. From this experiment, I concluded that colony growth is primarily carbohydrate-limited.
ContributorsClark, Rebecca, 1981- (Author) / Fewell, Jennifer H (Thesis advisor) / Mueller, Ulrich (Committee member) / Liebig, Juergen (Committee member) / Elser, James (Committee member) / Harrison, Jon (Committee member) / Arizona State University (Publisher)
Created2011
Description
The technology expansion seen in the last decade for genomics research has permitted the generation of large-scale data sources pertaining to molecular biological assays, genomics, proteomics, transcriptomics and other modern omics catalogs. New methods to analyze, integrate and visualize these data types are essential to unveil relevant disease mechanisms. Towards these objectives, this research focuses on data integration within two scenarios: (1) transcriptomic, proteomic and functional information and (2) real-time sensor-based measurements motivated by single-cell technology. To assess relationships between protein abundance, transcriptomic and functional data, a nonlinear model was explored at static and temporal levels. The successful integration of these heterogeneous data sources through the stochastic gradient boosted tree approach and its improved predictability are some highlights of this work. Through the development of an innovative validation subroutine based on a permutation approach and the use of external information (i.e., operons), lack of a priori knowledge for undetected proteins was overcome. The integrative methodologies allowed for the identification of undetected proteins for Desulfovibrio vulgaris and Shewanella oneidensis for further biological exploration in laboratories towards finding functional relationships. In an effort to better understand diseases such as cancer at different developmental stages, the Microscale Life Science Center headquartered at the Arizona State University is pursuing single-cell studies by developing novel technologies. This research arranged and applied a statistical framework that tackled the following challenges: random noise, heterogeneous dynamic systems with multiple states, and understanding cell behavior within and across different Barrett's esophageal epithelial cell lines using oxygen consumption curves. These curves were characterized with good empirical fit using nonlinear models with simple structures which allowed extraction of a large number of features. Application of a supervised classification model to these features and the integration of experimental factors allowed for identification of subtle patterns among different cell types visualized through multidimensional scaling. Motivated by the challenges of analyzing real-time measurements, we further explored a unique two-dimensional representation of multiple time series using a wavelet approach which showcased promising results towards less complex approximations. Also, the benefits of external information were explored to improve the image representation.
ContributorsTorres Garcia, Wandaliz (Author) / Meldrum, Deirdre R. (Thesis advisor) / Runger, George C. (Thesis advisor) / Gel, Esma S. (Committee member) / Li, Jing (Committee member) / Zhang, Weiwen (Committee member) / Arizona State University (Publisher)
Created2011
Description
Recombinases are powerful tools for genome engineering and synthetic biology, however recombinases are limited by a lack of user-programmability and often require complex directed-evolution experiments to retarget specificity. Conversely, CRISPR systems have extreme versatility yet can induce off-target mutations and karyotypic destabilization. To address these constraints we developed an RNA-guided recombinase protein by fusing a hyperactive mutant resolvase from transposon TN3 to catalytically inactive Cas9. We validated recombinase-Cas9 (rCas9) function in model eukaryote Saccharomyces cerevisiae using a chromosomally integrated fluorescent reporter. Moreover, we demonstrated cooperative targeting by CRISPR RNAs at spacings of 22 or 40bps is necessary for directing recombination. Using PCR and Sanger sequencing, we confirmed rCas9 targets DNA recombination. With further development we envision rCas9 becoming useful in the development of RNA-programmed genetic circuitry as well as high-specificity genome engineering.
ContributorsStandage-Beier, Kylie S (Author) / Wang, Xiao (Thesis advisor) / Brafman, David A (Committee member) / Tian, Xiao-jun (Committee member) / Arizona State University (Publisher)
Created2018
Description
Cancer is a heterogeneous disease with discrete oncogenic mechanisms. P53 mutation is the most common oncogenic mutation in many cancers including breast cancer. This dissertation focuses on fundamental genetic alterations enforced by p53 mutation as an indirect target. p53 mutation upregulates the mevalonate pathway genes altering cholesterol biosynthesis and prenylation. Prenylation, a lipid modification, is required for small GTPases signaling cascades. Project 1 demonstrates that prenylation inhibition can specifically target cells harboring p53 mutation resulting in reduced tumor proliferation and migration. Mutating p53 is associated with Ras and RhoA activation and statin prevents this activity by inhibiting prenylation. Ras-related pathway genes were selected from the transcriptomic analysis for evaluating correlation to statin sensitivity. A gene signature of seventeen genes and TP53 genotype (referred to as MPR signature) is generated to predict response to statins. MPR signature is validated through two datasets of drug screening in cell lines. As advancements in targeted gene modification are rising, the CRISPR-Cas9 technology has emerged as a new cancer therapeutic strategy. One of the important risk factors in gene therapy is the immune recognition of the exogenous therapeutic tool, resulting in obstruction of treatment and possibly serious health consequences. Project 2 describes a method development that can potentially improve the safety and efficacy of gene-targeting proteins. A cohort of 155 healthy individuals was screened for pre-existing B cell and T cell immune response to the S. pyogenes Cas9 protein. We detected antibodies against Cas9 in more than 10% of the healthy population and identified two immunodominant T cell epitopes of this protein. A de-immunized Cas9 that maintains the wild-type functionality was engineered by mutating the identified T cell epitopes. The gene signature and method described here have the potential to improve strategies for genome-driven tumor targeting.
ContributorsRoshdi Ferdosi, Shayesteh (Author) / Anderson, Karen S (Thesis advisor) / LaBaer, Joshua (Thesis advisor) / Woodbury, Neel (Committee member) / Borges, Chad (Committee member) / Arizona State University (Publisher)
Created2017
Description
Valley Fever, also known as coccidioidomycosis, is a respiratory disease that affects 10,000 people annually, primarily in Arizona and California. Due to a lack of gene annotation, diagnosis and treatment of Valley Fever is severely limited. In turn, gene annotation efforts are also hampered by incomplete genome sequencing. We intend to use proteogenomic analysis to reannotate the Coccidioides posadasii str. Silveira genome from protein-level data. Protein samples extracted from both phases of Silveira were fragmented into peptides, sequenced, and compared against databases of known and predicted proteins sequences, as well as a de novo six-frame translation of the genome. 288 unique peptides were located that did not match a known Silveira annotation, and of those 169 were associated with another Coccidioides strain. Additionally, 17 peptides were found at the boundary of, or outside of, the current gene annotation comprising four distinct clusters. For one of these clusters, we were able to calculate a lower bound and an estimate for the size of the gap between two Silveira contigs using the Coccidioides immitis RS transcript associated with that cluster's peptides \u2014 these predictions were consistent with the current annotation's scaffold structure. Three peptides were associated with an actively translated transposon, and a putative active site was located within an intact LTR retrotransposon. We note that gene annotation is necessarily hindered by the quality and level of detail in prior genome sequencing efforts, and recommend that future studies involving reannotation include additional sequencing as well as gene annotation via proteogenomics or other methods.
ContributorsSherrard, Andrew (Author) / Lake, Douglas (Thesis director) / Grys, Thomas (Committee member) / Mitchell, Natalie (Committee member) / Computing and Informatics Program (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12