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Immunosignature is a technology that retrieves information from the immune system. The technology is based on microarrays with peptides chosen from random sequence space. My thesis focuses on improving the Immunosignature platform and using Immunosignatures to improve diagnosis for diseases. I first contributed to the optimization of the immunosignature platform

Immunosignature is a technology that retrieves information from the immune system. The technology is based on microarrays with peptides chosen from random sequence space. My thesis focuses on improving the Immunosignature platform and using Immunosignatures to improve diagnosis for diseases. I first contributed to the optimization of the immunosignature platform by introducing scoring metrics to select optimal parameters, considering performance as well as practicality. Next, I primarily worked on identifying a signature shared across various pathogens that can distinguish them from the healthy population. I further retrieved consensus epitopes from the disease common signature and proposed that most pathogens could share the signature by studying the enrichment of the common signature in the pathogen proteomes. Following this, I worked on studying cancer samples from different stages and correlated the immune response with whether the epitope presented by tumor is similar to the pathogen proteome. An effective immune response is defined as an antibody titer increasing followed by decrease, suggesting elimination of the epitope. I found that an effective immune response usually correlates with epitopes that are more similar to pathogens. This suggests that the immune system might occupy a limited space and can be effective against only certain epitopes that have similarity with pathogens. I then participated in the attempt to solve the antibiotic resistance problem by developing a classification algorithm that can distinguish bacterial versus viral infection. This algorithm outperforms other currently available classification methods. Finally, I worked on the concept of deriving a single number to represent all the data on the immunosignature platform. This is in resemblance to the concept of temperature, which is an approximate measurement of whether an individual is healthy. The measure of Immune Entropy was found to work best as a single measurement to describe the immune system information derived from the immunosignature. Entropy is relatively invariant in healthy population, but shows significant differences when comparing healthy donors with patients either infected with a pathogen or have cancer.
ContributorsWang, Lu (Author) / Johnston, Stephen (Thesis advisor) / Stafford, Phillip (Committee member) / Buetow, Kenneth (Committee member) / McFadden, Grant (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Understanding changes and trends in biomedical knowledge is crucial for individuals, groups, and institutions as biomedicine improves people’s lives, supports national economies, and facilitates innovation. However, as knowledge changes what evidence illustrates knowledge changes? In the case of microbiome, a multi-dimensional concept from biomedicine, there are significant increases in publications,

Understanding changes and trends in biomedical knowledge is crucial for individuals, groups, and institutions as biomedicine improves people’s lives, supports national economies, and facilitates innovation. However, as knowledge changes what evidence illustrates knowledge changes? In the case of microbiome, a multi-dimensional concept from biomedicine, there are significant increases in publications, citations, funding, collaborations, and other explanatory variables or contextual factors. What is observed in the microbiome, or any historical evolution of a scientific field or scientific knowledge, is that these changes are related to changes in knowledge, but what is not understood is how to measure and track changes in knowledge. This investigation highlights how contextual factors from the language and social context of the microbiome are related to changes in the usage, meaning, and scientific knowledge on the microbiome. Two interconnected studies integrating qualitative and quantitative evidence examine the variation and change of the microbiome evidence are presented. First, the concepts microbiome, metagenome, and metabolome are compared to determine the boundaries of the microbiome concept in relation to other concepts where the conceptual boundaries have been cited as overlapping. A collection of publications for each concept or corpus is presented, with a focus on how to create, collect, curate, and analyze large data collections. This study concludes with suggestions on how to analyze biomedical concepts using a hybrid approach that combines results from the larger language context and individual words. Second, the results of a systematic review that describes the variation and change of microbiome research, funding, and knowledge are examined. A corpus of approximately 28,000 articles on the microbiome are characterized, and a spectrum of microbiome interpretations are suggested based on differences related to context. The collective results suggest the microbiome is a separate concept from the metagenome and metabolome, and the variation and change to the microbiome concept was influenced by contextual factors. These results provide insight into how concepts with extensive resources behave within biomedicine and suggest the microbiome is possibly representative of conceptual change or a preview of new dynamics within science that are expected in the future.
ContributorsAiello, Kenneth (Author) / Laubichler, Manfred D (Thesis advisor) / Simeone, Michael (Committee member) / Buetow, Kenneth (Committee member) / Walker, Sara I (Committee member) / Arizona State University (Publisher)
Created2018
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Description
In most diploid cells, autosomal genes are equally expressed from the paternal and maternal alleles resulting in biallelic expression. However, as an exception, there exists a small number of genes that show a pattern of monoallelic or biased-allele expression based on the allele’s parent-of-origin. This phenomenon is termed genomic imprinting

In most diploid cells, autosomal genes are equally expressed from the paternal and maternal alleles resulting in biallelic expression. However, as an exception, there exists a small number of genes that show a pattern of monoallelic or biased-allele expression based on the allele’s parent-of-origin. This phenomenon is termed genomic imprinting and is an evolutionary paradox. The best explanation for imprinting is David Haig's kinship theory, which hypothesizes that monoallelic gene expression is largely the result of evolutionary conflict between males and females over maternal involvement in their offspring. One previous RNAseq study has investigated the presence of parent-of-origin effects, or imprinting, in the parasitic jewel wasp Nasonia vitripennis (N. vitripennis) and its sister species Nasonia giraulti (N. giraulti) to test the predictions of kinship theory in a non-eusocial species for comparison to a eusocial one. In order to continue to tease apart the connection between social and eusocial Hymenoptera, this study proposed a similar RNAseq study that attempted to reproduce these results in unique samples of reciprocal F1 Nasonia hybrids. Building a pseudo N. giraulti reference genome, differences were observed when aligning RNAseq reads to a N. vitripennis reference genome compared to aligning reads to a pseudo N. giraulti reference. As well, no evidence for parent-of-origin or imprinting patterns in adult Nasonia were found. These results demonstrated a species-of-origin effect. Importantly, the study continued to build a repository of support with the aim to elucidate the mechanisms behind imprinting in an excellent epigenetic model species, as it can also help with understanding the phenomenon of imprinting in complex human diseases.
ContributorsUnderwood, Avery Elizabeth (Author) / Wilson, Melissa (Thesis advisor) / Buetow, Kenneth (Committee member) / Gile, Gillian (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Many factors are at play within the genome of an organism, contributing to much of the diversity and variation across the tree of life. While the genome is generally encoded by four nucleotides, A, C, T, and G, this code can be expanded. One particular mechanism that we examine in

Many factors are at play within the genome of an organism, contributing to much of the diversity and variation across the tree of life. While the genome is generally encoded by four nucleotides, A, C, T, and G, this code can be expanded. One particular mechanism that we examine in this thesis is modification of bases—more specifically, methylation of Adenine (m6A) within the GATC motif of Escherichia coli. These methylated adenines are especially important in a process called methyl-directed mismatch repair (MMR), a pathway responsible for repairing errors in the DNA sequence produced by replication. In this pathway, methylated adenines identify the parent strand and direct the repair proteins to correct the erroneous base in the daughter strand. While the primary role of methylated adenines at GATC sites is to direct the MMR pathway, this methylation has also been found to affect other processes, such as gene expression, the activity of transposable elements, and the timing of DNA replication. However, in the absence of MMR, the ability of these other processes to maintain adenine methylation and its targets is unknown.
To determine if the disruption of the MMR pathway results in the reduced conservation of methylated adenines as well as an increased tolerance for mutations that result in the loss or gain of new GATC sites, we surveyed individual clones isolated from experimentally evolving wild-type and MMR-deficient (mutL- ;conferring an 150x increase in mutation rate) populations of E. coli with whole-genome sequencing. Initial analysis revealed a lack of mutations affecting methylation sites (GATC tetranucleotides) in wild-type clones. However, the inherent low mutation rates conferred by the wild-type background render this result inconclusive, due to a lack of statistical power, and reveal a need for a more direct measure of changes in methylation status. Thus as a first step to comparative methylomics, we benchmarked four different methylation-calling pipelines on three biological replicates of the wildtype progenitor strain for our evolved populations.
While it is understood that these methylated sites play a role in the MMR pathway, it is not fully understood the full extent of their effect on the genome. Thus the goal of this thesis was to better understand the forces which maintain the genome, specifically concerning m6A within the GATC motif.
ContributorsBoyer, Gwyneth (Author) / Lynch, Michael (Thesis director) / Behringer, Megan (Committee member) / Geiler-Samerotte, Kerry (Committee member) / School of Life Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Description
Background: Noninvasive MRI methods that can accurately detect subtle brain changes are highly desirable when studying disease-modifying interventions. Texture analysis is a novel imaging technique which utilizes the extraction of a large number of image features with high specificity and predictive power. In this investigation, we use texture analysis to

Background: Noninvasive MRI methods that can accurately detect subtle brain changes are highly desirable when studying disease-modifying interventions. Texture analysis is a novel imaging technique which utilizes the extraction of a large number of image features with high specificity and predictive power. In this investigation, we use texture analysis to assess and classify age-related changes in the right and left hippocampal regions, the areas known to show some of the earliest change in Alzheimer's disease (AD). Apolipoprotein E (APOE)'s e4 allele confers an increased risk for AD, so studying differences in APOE e4 carriers may help to ascertain subtle brain changes before there has been an obvious change in behavior. We examined texture analysis measures that predict age-related changes, which reflect atrophy in a group of cognitively normal individuals. We hypothesized that the APOE e4 carriers would exhibit significant age-related differences in texture features compared to non-carriers, so that the predictive texture features hold promise for early assessment of AD. Methods: 120 normal adults between the ages of 32 and 90 were recruited for this neuroimaging study from a larger parent study at Mayo Clinic Arizona studying longitudinal cognitive functioning (Caselli et al., 2009). As part of the parent study, the participants were genotyped for APOE genetic polymorphisms and received comprehensive cognitive testing every two years, on average. Neuroimaging was done at Barrow Neurological Institute and a 3D T1-weighted magnetic resonance image was obtained during scanning that allowed for subsequent texture analysis processing. Voxel-based features of the appearance, structure, and arrangement of these regions of interest were extracted utilizing the Mayo Clinic Python Texture Analysis Pipeline (pyTAP). Algorithms applied in feature extraction included Grey-Level Co-Occurrence Matrix (GLCM), Gabor Filter Banks (GFB), Local Binary Patterns (LBP), Discrete Orthogonal Stockwell Transform (DOST), and Laplacian-of-Gaussian Histograms (LoGH). Principal component (PC) analysis was used to reduce the dimensionality of the algorithmically selected features to 13 PCs. A stepwise forward regression model was used to determine the effect of APOE status (APOE e4 carriers vs. noncarriers), and the texture feature principal components on age (as a continuous variable). After identification of 5 significant predictors of age in the model, the individual feature coefficients of those principal components were examined to determine which features contributed most significantly to the prediction of an aging brain. Results: 70 texture features were extracted for the two regions of interest in each participant's scan. The texture features were coded as 70 initial components andwere rotated to generate 13 principal components (PC) that contributed 75% of the variance in the dataset by scree plot analysis. The forward stepwise regression model used in this exploratory study significantly predicted age, accounting for approximately 40% of the variance in the data. The regression model revealed 5 significant regressors (2 right PC's, APOE status, and 2 left PC by APOE interactions). Finally, the specific texture features that contributed to each significant PCs were identified. Conclusion: Analysis of image texture features resulted in a statistical model that was able to detect subtle changes in brain integrity associated with age in a group of participants who are cognitively normal, but have an increased risk of developing AD based on the presence of the APOE e4 phenotype. This is an important finding, given that detecting subtle changes in regions vulnerable to the effects of AD in patients could allow certain texture features to serve as noninvasive, sensitive biomarkers predictive of AD. Even with only a small number of patients, the ability for us to determine sensitive imaging biomarkers could facilitate great improvement in speed of detection and effectiveness of AD interventions..
ContributorsSilva, Annelise Michelle (Author) / Baxter, Leslie (Thesis director) / McBeath, Michael (Committee member) / Presson, Clark (Committee member) / School of Life Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
Mammary gland development in humans during puberty involves the enlargement of breast tissue, but this is not true in non-human primates. To identify potential causes of this difference, I examined variation in substitution rates across genes related to mammary development. Genes undergoing purifying selection show slower-than-average substitution rates, while genes

Mammary gland development in humans during puberty involves the enlargement of breast tissue, but this is not true in non-human primates. To identify potential causes of this difference, I examined variation in substitution rates across genes related to mammary development. Genes undergoing purifying selection show slower-than-average substitution rates, while genes undergoing positive selection show faster rates. These may be related to the difference between humans and other primates. Three genes were found to be accelerated were FOXF1, IGFBP5, and ATP2B2, but only the latter one was found in humans and it seems unlikely that it would be related to the differences between mammary gland development at puberty between humans and non-human primates.
ContributorsArroyo, Diana (Author) / Cartwright, Reed (Thesis director) / Wilson Sayres, Melissa (Committee member) / Schwartz, Rachel (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
microRNAs (miRNAs) are short ~22nt non-coding RNAs that regulate gene output at the post-transcriptional level. Via targeting of degenerate elements primarily in 3'untranslated regions (3'UTR) of mRNAs, miRNAs can target thousands of varying genes and suppress their protein translation. The precise mechanistic function and bio- logical role of miRNAs is

microRNAs (miRNAs) are short ~22nt non-coding RNAs that regulate gene output at the post-transcriptional level. Via targeting of degenerate elements primarily in 3'untranslated regions (3'UTR) of mRNAs, miRNAs can target thousands of varying genes and suppress their protein translation. The precise mechanistic function and bio- logical role of miRNAs is not fully understood and yet it is a major contributor to a pleth- ora of diseases, including neurological disorders, muscular disorders, and cancer. Cer- tain model organisms are valuable in understanding the function of miRNA and there- fore fully understanding the biological significance of miRNA targeting. Here I report a mechanistic analysis of miRNA targeting in C. elegans, and a bioinformatic approach to aid in further investigation of miRNA targeted sequences. A few of the biologically significant mechanisms discussed in this thesis include alternative polyadenylation, RNA binding proteins, components of the miRNA recognition machinery, miRNA secondary structures, and their polymorphisms. This thesis also discusses a novel bioinformatic approach to studying miRNA biology, including computational miRNA target prediction software, and sequence complementarity. This thesis allows a better understanding of miRNA biology and presents an ideal strategy for approaching future research in miRNA targeting.
ContributorsWeigele, Dustin Keith (Author) / Mangone, Marco (Thesis director) / Katchman, Benjamin (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Life Sciences (Contributor)
Created2014-12
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Description
Schizophrenia is a disease that affects 15.2/100,000 US citizens, with about 0.6-1.9% of the total population being afflicted with some range of severity of the disease. A lot of research has been done on the progression of the disease and its differences between males and females; however, the true underlying

Schizophrenia is a disease that affects 15.2/100,000 US citizens, with about 0.6-1.9% of the total population being afflicted with some range of severity of the disease. A lot of research has been done on the progression of the disease and its differences between males and females; however, the true underlying cause of the disease remains unknown. In the literature, however, there is a lot of indication that a genetic cause for schizophrenia is the primary origin for the disorder. In order to establish a foundation in differential gene expression and isoform expression between males and females, we utilized the Genotype-Tissue Expression Project data set (which contains samples from healthy individuals at their time of death) for the amygdala, anterior cingulate cortex, and frontal cortex. We performed quality control on the data with Trimmomatic and visualized it with FastQC and MultiQC. We then aligned to a sex-specific reference genome with Hisat2. Finally, we performed a differential expression analysis dthrough the limma/voom package with inputs from featureCounts. An isoform level analysis was run on the anterior cingulate cortex with the IsoformSwitchAnalyzeR package. We were able to identify a few differentially expressed genes in the three tissue sites, which included XIST and other highly conserved, Y-linked genes. As for the isoform level analysis, we were able to identify 13 genes with significant levels of differential isoform usage and expression, two of which have clinical relevance (DAB1 and PACRG). These findings will allow for a comparison to be made by future studies on gene expression in brain tissue samples from patients that had been diagnosed with schizophrenia in their life. By identifying any unique genes in these patients, gene therapies can be developed to target and correct any misexpression that may be occurring.
ContributorsEvanovich, Austin Phillip (Author) / Wilson, Melissa (Thesis director) / Buetow, Kenneth (Committee member) / Natri, Heini Maaret (Committee member) / School of Life Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
Methane (CH4) is very important in the environment as it is a greenhouse gas and important for the degradation of organic matter. During the last 200 years the atmospheric concentration of CH4 has tripled. Methanogens are methane-producing microbes from the Archaea domain that complete the final step in breaking down

Methane (CH4) is very important in the environment as it is a greenhouse gas and important for the degradation of organic matter. During the last 200 years the atmospheric concentration of CH4 has tripled. Methanogens are methane-producing microbes from the Archaea domain that complete the final step in breaking down organic matter to generate methane through a process called methanogenesis. They contribute to about 74% of the CH4 present on the Earth's atmosphere, producing 1 billion tons of methane annually. The purpose of this work is to generate a preliminary metabolic reconstruction model of two methanogens: Methanoregula boonei 6A8 and Methanosphaerula palustris E1-9c. M. boonei and M. palustris are part of the Methanomicrobiales order and perform hydrogenotrophic methanogenesis, which means that they reduce CO2 to CH4 by using H2 as their major electron donor. Metabolic models are frameworks for understanding a cell as a system and they provide the means to assess the changes in gene regulation in response in various environmental and physiological constraints. The Pathway-Tools software v16 was used to generate these draft models. The models were manually curated using literature searches, the KEGG database and homology methods with the Methanosarcina acetivorans strain, the closest methanogen strain with a nearly complete metabolic reconstruction. These preliminary models attempt to complete the pathways required for amino acid biosynthesis, methanogenesis, and major cofactors related to methanogenesis. The M. boonei reconstruction currently includes 99 pathways and has 82% of its reactions completed, while the M. palustris reconstruction includes 102 pathways and has 89% of its reactions completed.
ContributorsMahendra, Divya (Author) / Cadillo-Quiroz, Hinsby (Thesis director) / Wang, Xuan (Committee member) / Stout, Valerie (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor) / School of Life Sciences (Contributor) / Biomedical Informatics Program (Contributor)
Created2014-05
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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

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