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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
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
Clean water for drinking, food preparation, and bathing is essential for astronaut health and safety during long duration habitation of the International Space Station (ISS), including future missions to Mars. Despite stringent water treatment and recycling efforts on the ISS, it is impossible to completely prevent microbial contamination of onboard water supplies. In this work, we used a spaceflight analogue culture system to better understand how the microgravity environment can influence the pathogenesis-related characteristics of Burkholderia cepacia complex (Bcc), an opportunistic pathogen previously recovered from the ISS water system. The results of the present study suggest that there may be important differences in how this pathogen can respond and adapt to spaceflight and other low fluid shear environments encountered during their natural life cycles. Future studies are aimed at understanding the underlying mechanisms responsible for these phenotypes.
ContributorsKang, Bianca Younseon (Author) / Nickerson, Cheryl (Thesis director) / Barrila, Jennifer (Committee member) / Ott, Mark (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Spaceflight and spaceflight analogue culture enhance the virulence and pathogenesis-related stress resistance of the foodborne pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium). This is an alarming finding as it suggests that astronauts may have an increased risk of infection during spaceflight. This risk is further exacerbated as multiple studies indicate that spaceflight negatively impacts aspects of the immune system. In order to ensure astronaut safety during long term missions, it is important to study the phenotypic effects of the microgravity environment on a range of medically important microbial pathogens that might be encountered by the crew. This ground-based study uses the NASA-engineered Rotating Wall Vessel (RWV) bioreactor as a spaceflight analogue culture system to grow bacteria under low fluid shear forces relative to those encountered in microgravity, and interestingly, in the intestinal tract during infection. The culture environment in the RWV is commonly referred to as low shear modeled microgravity (LSMMG). In this study, we characterized the stationary phase stress response of the enteric pathogen, Salmonella enterica serovar Enteritidis (S. Enteritidis), to LSMMG culture. We showed that LSMMG enhanced the resistance of stationary phase cultures of S. Enteritidis to acid and thermal stressors, which differed from the LSSMG stationary phase response of the closely related pathovar, S. Typhimurium. Interestingly, LSMMG increased the ability of both S. Enteritidis and S. Typhimurium to adhere to, invade into, and survive within an in vitro 3-D intestinal co-culture model containing immune cells. Our results indicate that LSMMG regulates pathogenesis-related characteristics of S. Enteritidis in ways that may present an increased health risk to astronauts during spaceflight missions.
ContributorsKoroli, Sara (Author) / Nickerson, Cheryl (Thesis director) / Barrila, Jennifer (Committee member) / Ott, C. Mark (Committee member) / School of Life Sciences (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
The International Space Station (ISS) utilizes recycled water for consumption, cleaning and air humidity control. The Environmental Control and Life Support Systems (ECLSS) have been rigorously tested at the NASA Johnson Space Center. Despite the advanced engineering of the water recovery system, bacterial biofilms have been recovered from this potable water source. Microbial contamination of potable water poses a potential threat to crew members onboard the ISS. Because astronauts have been found to have compromised immune systems, bacterial strains that would not typically be considered a danger must be carefully studied to better understand the mechanisms enabling their survival, including polymicrobial interactions. The need for a more thorough understanding of the effect of spaceflight environment on polymicrobial interactions and potential impact on crew health and vehicle integrity is heightened since 1) several potential pathogens have been isolated from the ISS potable water system, 2) spaceflight has been shown to induce unexpected alterations in microbial responses, and 3) emergent phenotypes are often observed when multiple bacterial species are co- cultured together, as compared to pure cultures of single species. In order to address these concerns, suitable growth media are required that will not only support the isolation of these microbes but also the ability to distinguish between them when grown as mixed cultures. In this study, selective and/or differential media were developed for bacterial isolates collected from the ISS potable water supply. In addition to facilitating discrimination between bacteria, the ideal media for each strain was intended to have a 100% recovery rate compared to traditional R2A media. Antibiotic and reagent susceptibility and resistance tests were conducted for the purpose of developing each individual medium. To study a wide range of targets, 12 antibiotics were selected from seven major classes, including penicillin, cephalosporins, fluoroquinolones, aminoglycosides, glycopeptides/lipoglycopeptides, macrolides/lincosamides/streptogramins, tetracyclines, in addition to seven unclassified antibiotics and three reagents. Once developed, medium efficacy was determined by means of growth curve experiments. The development of these media is a critical step for further research into the mechanisms utilized by these strains to survive the harsh conditions of the ISS water system. Furthermore, with an understanding of the complex nature of these polymicrobial communities, specific contamination targeting and control can be conducted to reduce the risk to crew members. Understanding these microbial species and their susceptibilities has potential application for future NASA human explorations, including those to Mars.
ContributorsKing, Olivia Grace (Author) / Nickerson, Cheryl (Thesis director) / Barrila, Jennifer (Committee member) / Ott, Mark (Committee member) / School of Sustainability (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (Committee member) / Arizona State University (Publisher)
Created2021
Description
One of the identified health risk areas for human spaceflight is infectious disease, particularly involving environmental microorganisms already found on the International Space Station (ISS). In particular, bacteria belonging to the Burkholderia cepacia complex (Bcc) which can cause human disease in those who are immunocompromised, have been identified in the ISS water supply. This present study characterized the effect of spaceflight analog culture conditions on Bcc to certain physiological stresses (acid and thermal as well as intracellular survival in U927 human macrophage cells). The NASA-designed Rotating Wall Vessel (RWV) bioreactor was used as the spaceflight analogue culture system in these studies to grow Bcc bacterial cells under Low Shear Modeled Microgravity (LSMMG) conditions. Results show that LSMMG culture increased the resistance of Bcc to both acid and thermal stressors, but did not alter phagocytic uptake in 2-D monolayers of human monocytes.
ContributorsVu, Christian-Alexander (Author) / Nickerson, Cheryl (Thesis director) / Barrila, Jennifer (Committee member) / Ott, Mark (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2023-05