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Description
In an effort to begin validating the large number of discovered candidate biomarkers, proteomics is beginning to shift from shotgun proteomic experiments towards targeted proteomic approaches that provide solutions to automation and economic concerns. Such approaches to validate biomarkers necessitate the mass spectrometric analysis of hundreds to thousands of human samples. As this takes place, a serendipitous opportunity has become evident. By the virtue that as one narrows the focus towards "single" protein targets (instead of entire proteomes) using pan-antibody-based enrichment techniques, a discovery science has emerged, so to speak. This is due to the largely unknown context in which "single" proteins exist in blood (i.e. polymorphisms, transcript variants, and posttranslational modifications) and hence, targeted proteomics has applications for established biomarkers. Furthermore, besides protein heterogeneity accounting for interferences with conventional immunometric platforms, it is becoming evident that this formerly hidden dimension of structural information also contains rich-pathobiological information. Consequently, targeted proteomics studies that aim to ascertain a protein's genuine presentation within disease- stratified populations and serve as a stepping-stone within a biomarker translational pipeline are of clinical interest. Roughly 128 million Americans are pre-diabetic, diabetic, and/or have kidney disease and public and private spending for treating these diseases is in the hundreds of billions of dollars. In an effort to create new solutions for the early detection and management of these conditions, described herein is the design, development, and translation of mass spectrometric immunoassays targeted towards diabetes and kidney disease. Population proteomics experiments were performed for the following clinically relevant proteins: insulin, C-peptide, RANTES, and parathyroid hormone. At least thirty-eight protein isoforms were detected. Besides the numerous disease correlations confronted within the disease-stratified cohorts, certain isoforms also appeared to be causally related to the underlying pathophysiology and/or have therapeutic implications. Technical advancements include multiplexed isoform quantification as well a "dual- extraction" methodology for eliminating non-specific proteins while simultaneously validating isoforms. Industrial efforts towards widespread clinical adoption are also described. Consequently, this work lays a foundation for the translation of mass spectrometric immunoassays into the clinical arena and simultaneously presents the most recent advancements concerning the mass spectrometric immunoassay approach.
ContributorsOran, Paul (Author) / Nelson, Randall (Thesis advisor) / Hayes, Mark (Thesis advisor) / Ros, Alexandra (Committee member) / Williams, Peter (Committee member) / Arizona State University (Publisher)
Created2011
Description
The use of synthetic cathinones or "bath salts" has risen dramatically in recent years with one of the most popular being Methylendioxypyrovalerone (MDPV). Following the temporary legislative ban on the sale and distribution of this compound , a multitude of other cathinone derivatives have been synthesized. The current study seeks to compare the abuse potential of MDPV with one of the emergent synthetic cathinones 4-methylethcathinone (4-MEC), based on their respective ability to lower current thresholds in an intracranial self-stimulation (ICSS) paradigm. Following acute administration (0.1, 0.5, 1 and 2 mg/kg i.p.) MDPV was found to significantly lower ICSS thresholds at all doses tested (F4,35=11.549, p<0.001). However, following acute administration (0.3,1,3,10,30 mg/kg i.p) 4-MEC produced no significant ICSS threshold depression (F5,135= 0.622, p = 0.684). Together these findings suggest that while MDPV may possess significant abuse potential, other synthetic cathinones such as 4-MEC may have a drastically reduced potential for abuse.
ContributorsWegner, Scott Andrew (Author) / Olive, M. Foster (Thesis director) / Presson, Clark (Committee member) / Sanabria, Federico (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Department of Psychology (Contributor)
Created2013-05
Description
Signal processing techniques have been used extensively in many engineering problems and in recent years its application has extended to non-traditional research fields such as biological systems. Many of these applications require extraction of a signal or parameter of interest from degraded measurements. One such application is mass spectrometry immunoassay (MSIA) which has been one of the primary methods of biomarker discovery techniques. MSIA analyzes protein molecules as potential biomarkers using time of flight mass spectrometry (TOF-MS). Peak detection in TOF-MS is important for biomarker analysis and many other MS related application. Though many peak detection algorithms exist, most of them are based on heuristics models. One of the ways of detecting signal peaks is by deploying stochastic models of the signal and noise observations. Likelihood ratio test (LRT) detector, based on the Neyman-Pearson (NP) lemma, is an uniformly most powerful test to decision making in the form of a hypothesis test. The primary goal of this dissertation is to develop signal and noise models for the electrospray ionization (ESI) TOF-MS data. A new method is proposed for developing the signal model by employing first principles calculations based on device physics and molecular properties. The noise model is developed by analyzing MS data from careful experiments in the ESI mass spectrometer. A non-flat baseline in MS data is common. The reasons behind the formation of this baseline has not been fully comprehended. A new signal model explaining the presence of baseline is proposed, though detailed experiments are needed to further substantiate the model assumptions. Signal detection schemes based on these signal and noise models are proposed. A maximum likelihood (ML) method is introduced for estimating the signal peak amplitudes. The performance of the detection methods and ML estimation are evaluated with Monte Carlo simulation which shows promising results. An application of these methods is proposed for fractional abundance calculation for biomarker analysis, which is mathematically robust and fundamentally different than the current algorithms. Biomarker panels for type 2 diabetes and cardiovascular disease are analyzed using existing MS analysis algorithms. Finally, a support vector machine based multi-classification algorithm is developed for evaluating the biomarkers' effectiveness in discriminating type 2 diabetes and cardiovascular diseases and is shown to perform better than a linear discriminant analysis based classifier.
ContributorsBuddi, Sai (Author) / Taylor, Thomas (Thesis advisor) / Cochran, Douglas (Thesis advisor) / Nelson, Randall (Committee member) / Duman, Tolga (Committee member) / Arizona State University (Publisher)
Created2012
Description
Cancer claims hundreds of thousands of lives every year in US alone. Finding ways for early detection of cancer onset is crucial for better management and treatment of cancer. Thus, biomarkers especially protein biomarkers, being the functional units which reflect dynamic physiological changes, need to be discovered. Though important, there are only a few approved protein cancer biomarkers till date. To accelerate this process, fast, comprehensive and affordable assays are required which can be applied to large population studies. For this, these assays should be able to comprehensively characterize and explore the molecular diversity of nominally "single" proteins across populations. This information is usually unavailable with commonly used immunoassays such as ELISA (enzyme linked immunosorbent assay) which either ignore protein microheterogeneity, or are confounded by it. To this end, mass spectrometric immuno assays (MSIA) for three different human plasma proteins have been developed. These proteins viz. IGF-1, hemopexin and tetranectin have been found in reported literature to show correlations with many diseases along with several carcinomas. Developed assays were used to extract entire proteins from plasma samples and subsequently analyzed on mass spectrometric platforms. Matrix assisted laser desorption ionization (MALDI) and electrospray ionization (ESI) mass spectrometric techniques where used due to their availability and suitability for the analysis. This resulted in visibility of different structural forms of these proteins showing their structural micro-heterogeneity which is invisible to commonly used immunoassays. These assays are fast, comprehensive and can be applied in large sample studies to analyze proteins for biomarker discovery.
ContributorsRai, Samita (Author) / Nelson, Randall (Thesis advisor) / Hayes, Mark (Thesis advisor) / Borges, Chad (Committee member) / Ros, Alexandra (Committee member) / Arizona State University (Publisher)
Created2012
Description
Background: Both puberty and diets composed of high levels of saturated fats have been shown to result in central adiposity, fasting hyperinsulinemia, insulin resistance and impaired glucose tolerance. While a significantly insulinogenic phenotypic change occurs in these two incidences, glucose homeostasis does not appear to be affected. Methods: Male, Sprague-dawley rats were fed diets consisting of CHOW or low fat (LF), High Fat Diet and High Fat Diet (HFD) with supplementary Canola Oil (Monounsaturated fat). These rats were given these diets at 4-5 weeks old and given intraperitoneal and oral glucose tolerance tests(IPGTT; OGTT) at 4 and 8 weeks to further understand glucose and insulin behavior under different treatments. (IPGTT: LF-n=14, HFD-n=16, HFD+CAN-n=12; OGTT: LF-n=8, HFD-n=8, HFD+CAN-n=6). Results: When comparing LF fed rats at 8 weeks with 4 week glucose challenge test, area under the curve (AUC) of glucose was 1.2 that of 4 weeks. At 8 weeks, HFD fed rats AUCg was much greater than LF fed rats under both IPGTT and OGTT. When supplemented with Canola oil, HFD fed rats AUC returned to LF data range. Despite the alleviating glucose homeostasis affects of Canola oil the AUC of insulin curve, which was elevated by HFD, remained high. Conclusion: HFD in maturing rats elevates fasting insulin levels, increases insulin resistance and lowers glucose homeostasis. When given a monounsaturated fatty acid (MUFA) supplement fasting hyperinsulinemia, and late hyperinsulinemia still occur though glucose homeostasis is regained. For OGTT HFD also induced late hyper c-peptide levels and compared to LF and HFD+CAN, a higher c-peptide level over time.
ContributorsRay, Tyler John (Author) / Caplan, Michael (Thesis director) / Herman, Richard (Committee member) / Towner, Kali (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / W. P. Carey School of Business (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2015-05
Description
Nucleic acids encode the information required to create life, and polymerases are the gatekeepers charged with maintaining the storage and flow of this genetic information. Synthetic biologists utilize this universal property to modify organisms and other systems to create unique traits or improve the function of others. One of the many realms in synthetic biology involves the study of biopolymers that do not exist naturally, which is known as xenobiology. Although life depends on two biopolymers for genetic storage, it may be possible that alternative molecules (xenonucleic acids – XNAs), could be used in their place in either a living or non-living system. However, implementation of an XNA based system requires the development of polymerases that can encode and decode information stored in these artificial polymers. A strategy called directed evolution is used to modify or alter the function of a protein of interest, but identifying mutations that can modify polymerase function is made problematic by their size and overall complexity. To reduce the amount of sequence space that needs to be samples when attempting to identify polymerase variants, we can try to make informed decisions about which amino acid residues may have functional roles in catalysis. An analysis of Family B polymerases has shown that residues which are involved in substrate specificity are often highly conserved both at the sequence and structure level. In order to validate the hypothesis that a strong correlation exists between structural conservation and catalytic activity, we have selected and mutated residues in the 9°N polymerase using a loss of function mutagenesis strategy based on a computational analysis of several homologues from a diverse range of taxa. Improvement of these models will hopefully lead to quicker identification of loci which are ideal engineering targets.
ContributorsHaeberle, Tyler Matthew (Author) / Chaput, John (Thesis director) / Chen, Julian (Committee member) / Larsen, Andrew (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
Lung cancer is the leading cause of cancer-related deaths in the US. Low-dose computed tomography (LDCT) scans are speculated to reduce lung cancer mortality. However LDCT scans impose multiple risks including false-negative results, false- positive results, overdiagnosis, and cancer due to repeated exposure to radiation. Immunosignaturing is a new method proposed to screen and detect lung cancer, eliminating the risks associated with LDCT scans. Known and blinded primary blood sera from participants with lung cancer and no cancer were run on peptide microarrays and analyzed. Immunosignatures for each known sample collectively indicated 120 peptides unique to lung cancer and non-cancer participants. These 120 peptides were used to determine the status of the blinded samples. Verification of the results from Vanderbilt is pending.
ContributorsNguyen, Geneva Trieu (Author) / Woodbury, Neal (Thesis director) / Zhao, Zhan-Gong (Committee member) / Stafford, Phillip (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Department of Psychology (Contributor)
Created2015-05
Description
Using DNA nanotechnology a library of structures of various geometries have been built; these structures are modified chemically and/or enzymatically at nanometer precisions. With DNA being chemically very stable, these structures can be functionalized through an abundance of well-established protocols. Additionally, they can be used for various biological and medicinal purposes, such as drug delivery. For in vivo applications, the DNA nanostructures must have a long circulation life in the bloodstream; otherwise, they could be easily excreted shortly after entry. One way of making these nanostructures long lasting in the blood is to cover them with the biocompatible polymer, polyethylene glycol (PEG). Adding DNA to PEG before forming structures has been found to interfere in the hybridization of the DNA in the structure, resulting in formation of deformed structures. In this study we have developed a new methodology based on "click chemistry" (CC) to modify the surface of DNA nanostructures with PEG after they are formed. These structures can then be used for in vivo studies and potential applications in the future.
ContributorsSmith, Eric Lynn (Author) / Yan, Hao (Thesis director) / Liu, Yan (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05
Description
The prospect of anti-aging or life extension technology is controversial in biogerentology but deemed even by skeptical experts to warrant discussion. I discuss the justifications that the probability of life extension technology being developed in the near future is reasonably high and that this research justifies the time and money it receives. I investigate potential ethical and societal issues anti-aging technology might create. This paper addresses inequality of access, economic cost, changes in quality of life, the role of death in human life, if and how the technology should be regulated and how parties who choose not to undergo treatment can be fairly treated, even when they are a minority.
ContributorsGlesener, Julia Hannah (Author) / McGregor, Joan (Thesis director) / DeSerpa, Allan (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor)
Created2015-05
Description
For many pre-health and graduate programs, organic chemistry is often the most difficult prerequisite course that students will take. To alleviate this difficulty, an intelligent tutoring system was developed to provide valuable feedback to practice problems within organic chemistry. This paper focuses on the design and use of an intelligent input parser for nomenclature questions within this system. Students in Dr. Gould's Fall 2014 organic chemistry class used this system and their data was collected to analyze the effectiveness of the input parser. Overall the students' feedback was optimistic and there was a positive relationship between test scores and student use of the system.
ContributorsHusarcik, Edward Andrew (Author) / Gould, Ian (Thesis director) / VanLehn, Kurt (Committee member) / Beerman, Eric (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05