Matching Items (33)
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
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
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
Description
While exercising mammalian muscle increasingly relies on carbohydrates for fuel as aerobic exercise intensity rises above the moderate range, flying birds are extraordinary endurance athletes and fuel flight, a moderate-high intensity exercise, almost exclusively with lipid. In addition, Aves have long lifespans compared to weight-matched mammals. As skeletal muscle mitochondria account for the majority of oxygen consumption during aerobic exercise, the primary goal was to investigate differences in isolated muscle mitochondria between these species and to examine to what extent factors intrinsic to mitochondria may account for the behavior observed in the intact tissue and whole organism. First, maximal enzyme activities were assessed in sparrow and rat mitochondria. Citrate synthase and aspartate aminotransferase activity were higher in sparrow compared to rat mitochondria, while glutamate dehydrogenase activity was lower. Sparrow mitochondrial NAD-linked isocitrate dehydrogenase activity was dependent on phosphate, unlike the mammalian enzyme. Next, the rate of oxygen consumption (JO), electron transport chain (ETC) activity, and reactive oxygen species (ROS) production were assessed in intact mitochondria. Maximal rates of fat oxidation were lower than for carbohydrate in rat but not sparrow mitochondria. ETC activity was higher in sparrows, but no differences were found in ROS production between species. Finally, fuel selection and control of respiration at three rates between rest and maximum were assessed. Mitochondrial fuel oxidation and selection mirrored that of the whole body; in rat mitochondria the reliance on carbohydrate increased as the rate of oxygen consumption increased, whereas fat dominated under all conditions in the sparrow. These data indicate fuel selection, at least in part, can be modulated at the level of the mitochondrial matrix when multiple substrates are present at saturating levels. As an increase in matrix oxidation-reduction potential has been linked to a suppression of fat oxidation and high ROS production, the high ETC activity relative to dehydrogenase activity in avian compared to mammalian mitochondria may result in lower matrix oxidation-reduction potential, allowing fatty acid oxidation to proceed while also resulting in low ROS production in vivo.
ContributorsKuzmiak, Sarah (Author) / Willis, Wayne T (Thesis advisor) / Mandarino, Lawrence (Committee member) / Sweazea, Karen (Committee member) / Harrison, Jon (Committee member) / Gadau, Juergen (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
Biomarkers are the cornerstone of modern-day medicine. They are defined as any biological substance in or outside the body that gives insight to the body's condition. Doctors and researchers can measure specific biomarkers to diagnose and treat patients, such as the concentration of hemoglobin Alc and its connection to diabetes. There are a variety of methods, or assays, to detect biomarkers, but the most common assay is enzyme-linked immunosorbent assay (ELISA). A new-generation assay termed mass spectrometric immunoassay (MSIA) can measure proteoforms, the different chemical variations of proteins, and their relative abundance. ELISA on the other hand measures the overall concentration of protein in the sample. Measuring each of the proteoforms of a protein is important because only one or two variations could be biologically significant and/or cause diseases. However, running MSIA is expensive. For this reason, an alternative plate-based MSIA technique was tested for its ability to detect the proteoforms of a protein called apolipoprotein C-III (ApoC-III). This technique combines the protein capturing procedure of ELISA to isolate the protein with detection in a mass spectrometer. A larger amount of ApoC-III present in the body indicates a considerable risk for coronary heart disease. The precision of the assay is determined on the coefficient of variation (CV). A CV value is the ratio of standard deviation in relation to the mean, represented as a percentage. The smaller the percentage, the less variation the assay has, and therefore the more ability it has to detect subtle changes in the biomarker. An accepted CV would be less than 10% for single-day tests (intra-day) and less than 15% for multi-day tests (inter-day). The plate-based MSIA was started by first coating a 96-well round bottom plate with 2.5 micrograms of ApoC-III antibody. Next, a series of steps were conducted: a buffer wash, then the sample incubation, followed by another buffer wash and two consecutive water washes. After the final wash, the wells were filled with a MALDI matrix, then spotted onto a gold plate to dry. The dry gold target was then placed into a MALDI-TOF mass spectrometer to produce mass spectra for each spot. The mass spectra were calibrated and the area underneath each of the four peaks representing the ApoC-III proteoforms was exported as an Excel file. The intra-day CV values were found by dividing the standard deviation by the average relative abundance of each peak. After repeating the same procedure for three more days, the inter-day CVs were found using the same method. After completing the experiment, the CV values were all within the acceptable guidelines. Therefore, the plate-based MSIA is a viable alternative for finding proteoforms than the more expensive MSIA tips. To further validate this, additional tests will need to be conducted with different proteins and number of samples to determine assay flexibility.
ContributorsTieu, Luc (Author) / Borges, Chad (Thesis director) / Nedelkov, Dobrin (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Massive glycerol cluster ions with many charges (~ 106 Da, ~ ±100 charges) have been generated by electrospray to bombard biomolecules and biological sample surfaces. The low impact energy per nucleon facilitates intact sputtering and ionization of biomolecules which can be subsequently imaged. Various lipids, peptides and proteins have been studied. The primary cluster ion source has been coupled with an ion-microscope imaging mass spectrometer (TRIFT-1, Physical Electronics). A lateral resolution of ~3µm has been demonstrated, which is acceptable for sub-cellular imaging of animal cells (e.g. single cancer cell imaging in early diagnosis). Since the available amount of target molecules per pixel is limited in biological samples, the measurement of useful ion yields (ratio of detected molecular ion counts to the sample molecules sputtered) is important to determine whether enough ion counts per pixel can be obtained. The useful ion yields of several lipids and peptides are in the 1-3×10-5 range. A 3×3 µm2lipid bilayer can produce ~260 counts/pixel for a meaningful 3×3 µm2 pixel ion image. This method can probably be used in cell imaging in the future, when there is a change in the lipid contents of the cell membrane (e.g. cancer cells vs. normal cells).
ContributorsZhang, Jitao (Author) / Williams, Peter (Thesis advisor) / Hayes, Mark (Committee member) / Nelson, Randall (Committee member) / Arizona State University (Publisher)
Created2015
Description
Cell heterogeneity is widely present in the biological world and exists even in an isogenic population. Resolving the protein heterogeneity at the single cell level is of enormous biological and clinical relevance. However, single cell protein analysis has proven to be challenging due to extremely low amount of protein in a single cell and the huge complexity of proteome. This requires appropriate sampling and sensitive detection techniques. Here, a new approach, microfluidics combined with MALDI-TOF mass spectrometry was brought forward, for the analysis of proteins in single cells. The detection sensitivity of peptides as low as 300 molecules and of proteins as low as 10^6 molecules has been demonstrated. Furthermore, an immunoassay was successfully integrated in the microfluidic device for capturing the proteins of interest and further identifying them by subsequent enzymatic digestion. Moreover, an improved microfluidic platform was designed with separate chambers and valves, allowing the absolute quantification by employing iTRAQ tags or an isotopically labeled peptide. The study was further extended to analyze a protein in MCF-7 cell lysate. The approach capable of identifying and quantifying protein molecules in MCF-7 cells is promising for future proteomic studies at the single cell level.
ContributorsYang, Mian (Author) / Ros, Alexandra (Thesis advisor) / Hayes, Mark (Committee member) / Nelson, Randall (Committee member) / Arizona State University (Publisher)
Created2016
Description
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.
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
Description
Human protein diversity arises as a result of alternative splicing, single nucleotide polymorphisms (SNPs) and posttranslational modifications. Because of these processes, each protein can exists as multiple variants in vivo. Tailored strategies are needed to study these protein variants and understand their role in health and disease. In this work we utilized quantitative mass spectrometric immunoassays to determine the protein variants concentration of beta-2-microglobulin, cystatin C, retinol binding protein, and transthyretin, in a population of 500 healthy individuals. Additionally, we determined the longitudinal concentration changes for the protein variants from four individuals over a 6 month period. Along with the native forms of the four proteins, 13 posttranslationally modified variants and 7 SNP-derived variants were detected and their concentration determined. Correlations of the variants concentration with geographical origin, gender, and age of the individuals were also examined. This work represents an important step toward building a catalog of protein variants concentrations and examining their longitudinal changes.
ContributorsTrenchevska, Olgica (Author) / Phillips, David A. (Author) / Nelson, Randall (Author) / Nedelkov, Dobrin (Author) / Biodesign Institute (Contributor)
Created2014-06-23