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Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by progressive autoimmune destruction of insulin-producing pancreatic β-cells. Genetic, immunological and environmental factors contribute to T1D development. The focus of this dissertation is to track the humoral immune response in T1D by profiling autoantibodies (AAbs) and anti-viral antibodies using an

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by progressive autoimmune destruction of insulin-producing pancreatic β-cells. Genetic, immunological and environmental factors contribute to T1D development. The focus of this dissertation is to track the humoral immune response in T1D by profiling autoantibodies (AAbs) and anti-viral antibodies using an innovative protein array platform called Nucleic Acid Programmable Protein Array (NAPPA).

AAbs provide value in identifying individuals at risk, stratifying patients with different clinical courses, improving our understanding of autoimmune destructions, identifying antigens for cellular immune response and providing candidates for prevention trials in T1D. A two-stage serological AAb screening against 6,000 human proteins was performed. A dual specificity tyrosine-phosphorylation-regulated kinase 2 (DYRK2) was validated with 36% sensitivity at 98% specificity by an orthogonal immunoassay. This is the first systematic screening for novel AAbs against large number of human proteins by protein arrays in T1D. A more comprehensive search for novel AAbs was performed using a knowledge-based approach by ELISA and a screening-based approach against 10,000 human proteins by NAPPA. Six AAbs were identified and validated with sensitivities ranged from 16% to 27% at 95% specificity. These two studies enriched the T1D “autoantigenome” and provided insights into T1D pathophysiology in an unprecedented breadth and width.

The rapid rise of T1D incidence suggests the potential involvement of environmental factors including viral infections. Sero-reactivity to 646 viral antigens was assessed in new-onset T1D patients. Antibody positive rate of EBV was significantly higher in cases than controls that suggested a potential role of EBV in T1D development. A high density-NAPPA platform was demonstrated with high reproducibility and sensitivity in profiling anti-viral antibodies.

This dissertation shows the power of a protein-array based immunoproteomics approach to characterize humoral immunoprofile against human and viral proteomes. The identification of novel T1D-specific AAbs and T1D-associated viruses will help to connect the nodes in T1D etiology and provide better understanding of T1D pathophysiology.
ContributorsBian, Xiaofang (Author) / LaBaer, Joshua (Thesis advisor) / Mandarino, Lawrence (Committee member) / Chang, Yung (Committee member) / Arizona State University (Publisher)
Created2015
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Description
MicroRNAs (miRNAs) are short non-coding RNAs that play key roles during metazoan development, and are frequently misregulated in human disease. MiRNAs regulate gene output by targeting degenerate elements primarily in the 3´ untranslated regions of mRNAs. MiRNAs are often deeply conserved, but have undergone drastic expansions in higher metazoans, leading

MicroRNAs (miRNAs) are short non-coding RNAs that play key roles during metazoan development, and are frequently misregulated in human disease. MiRNAs regulate gene output by targeting degenerate elements primarily in the 3´ untranslated regions of mRNAs. MiRNAs are often deeply conserved, but have undergone drastic expansions in higher metazoans, leading to families of miRNAs with highly similar sequences. The evolutionary advantage of maintaining multiple copies of duplicated miRNAs is not well understood, nor has the distinct functions of miRNA family members been systematically studied. Furthermore, the unbiased and high-throughput discovery of targets remains a major challenge, yet is required to understand the biological function of a given miRNA.

I hypothesize that duplication events grant miRNA families with enhanced regulatory capabilities, specifically through distinct targeting preferences by family members. This has relevance for our understanding of vertebrate evolution, as well disease detection and personalized medicine. To test this hypothesis, I apply a conjunction of bioinformatic and experimental approaches, and design a novel high-throughput screening platform to identify human miRNA targets. Combined with conventional approaches, this tool allows systematic testing for functional targets of human miRNAs, and the identification of novel target genes on an unprecedented scale.

In this dissertation, I explore evolutionary signatures of 62 deeply conserved metazoan miRNA families, as well as the targeting preferences for several human miRNAs. I find that constraints on miRNA processing impact sequence evolution, creating evolutionary hotspots within families that guide distinct target preferences. I apply our novel screening platform to two cancer-relevant miRNAs, and identify hundreds of previously undescribed targets. I also analyze critical features of functional miRNA target sites, finding that each miRNA recognizes surprisingly distinct features of targets. To further explore the functional distinction between family members, I analyze miRNA expression patterns in multiple contexts, including mouse embryogenesis, RNA-seq data from human tissues, and cancer cell lines. Together, my results inform a model that describes the evolution of metazoan miRNAs, and suggests that highly similar miRNA family members possess distinct functions. These findings broaden our understanding of miRNA function in vertebrate evolution and development, and how their misexpression contributes to human disease.
ContributorsWolter, Justin M (Author) / Mangone, Marco (Thesis advisor) / LaBaer, Joshua (Committee member) / Kusumi, Kenro (Committee member) / Anderson, Karen (Committee member) / Arizona State University (Publisher)
Created2016
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Description
This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems

This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems biology level, I provide new targets to explore for the research community. Furthermore I present a new online web resource that unifies various bioinformatics databases to enable discovery of relevant features in 3D protein structures.
ContributorsMielke, Clinton (Author) / Mandarino, Lawrence (Committee member) / LaBaer, Joshua (Committee member) / Magee, D. Mitchell (Committee member) / Dinu, Valentin (Committee member) / Willis, Wayne (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The pathogenesis of type 1 diabetes (T1D) is still not fully understood in the scientific community. Evidence has shown that viral infections are one of the important environmental factors associated with the disease development. Seven of the top T1D related viruses were selected to study the prevalence of viral humoral

The pathogenesis of type 1 diabetes (T1D) is still not fully understood in the scientific community. Evidence has shown that viral infections are one of the important environmental factors associated with the disease development. Seven of the top T1D related viruses were selected to study the prevalence of viral humoral response in T1D patients using our innovative protein array platform called Nucleic Acid Programmable Protein Array (NAPPA). In this study, each viral gene was individually captured using various PCR based techniques, cloned into a protein expression vector, and assembled as the first version of T1D viral protein array. Humoral responses of IgG, IgA, and IgM were examined. Although each class of immunoglobulin generated a wide-range of reactivity, responses to various viral proteins from different proteins were observed. In summary, we captured most of the T1D related viral genes, established viral protein expression on the protein array, and displayed the serum response on the viral protein array. The successful progress will help to fulfill the long term goal of testing the viral infection hypothesis in T1D development.
ContributorsDavis, Amy Darlene (Author) / LaBaer, Joshua (Thesis director) / Qiu, Ji (Committee member) / Desi, Paul (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2013-05