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Description
This thesis describes the studies for two groups of molecules in the gas-phase: (a) copper monofluoride (CuF) and copper hydroxide (CuOH); (b) thorium monoxide (ThO) and tungsten carbide (WC). Copper-containing molecules (Group a) are selected to investigate the ionic bonding in transition metal-containing molecules because they have a relatively simple electronic state distribution due to the nearly filled 3d-orbital. ThO and WC (Group b) are in support of particle physics for the determination of electron electric dipole moment (eEDM), de, the existence of which indicates new physics beyond the Standard Model. The determination of the tiny eEDM requires large electric fields applied to the electron. The 3(Delta)1 states for heavy polar molecules were proposed [E. R. Meyer, J. L. Bohn, and M. P. Deskevich, Phys. Rev. A 73, 062108 (2006)] to determine de with the following attractive features: (1) large electric dipole moments; (2) large internal electric fields, Eeff, experienced by valence electrons; (3) nearly degenerate omega-doublets; (4) extremely small magnetic dipole moments. The H3(Delta)1 state for ThO and the X3(Delta)1 state for WC are both good candidates. Spectroscopic parameters (i.e. molecular electric and magnetic dipole moments, omega-doubling parameters, etc) are required for the 3(Delta)1 states of ThO and WC. High resolution optical spectra (linewidth ~50 MHz) of CuF, CuOH, ThO and WC were recorded field-free and in the presence of a static electric field (or magnetic field) using laser ablation source/supersonic expansion and laser induced fluorescence (LIF) detection. The spectra were modeled by a zero-field effective Hamiltonian operator and a Stark (or Zeeman) Hamiltonian operator with various molecular parameters. The determined molecular parameters are compared to theoretical predictions. The small omega-doubling parameter was well determined using the pump/probe microwave optical double resonance (PPMODR) technique with a much higher resolution (linewidth ~60 kHz) than optical spectroscopy. In addition to the above mentioned studies of the two groups of molecules, a resonance enhanced multi-photon ionization (REMPI) combined with a time-of-flight mass spectrometer (TOFMS) has been developed to identify the molecules responsible for observed LIF signals. The operation of this spectrometer has been tested by recording the mass spectrum of Ti/O2 and the REMPI spectrum for TiO using a two-color excitation scheme.
ContributorsWang, Fang (Author) / Steimle, Timothy C (Thesis advisor) / Chizmeshya, Andrew (Committee member) / Wolf, George (Committee member) / Arizona State University (Publisher)
Created2012
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
Infertility has become an increasing problem in developed countries and in many cases can be attributed to compromised sperm quality. Assessment of male fertility typically utilizes semen analysis which mainly examines sperm morphology, however many males whose sperm appear normal are sub- or infertile, suggesting that sperm from these males may be deficient in a protein or suite of proteins. To date, very little is known about the composition of sperm or the complex maturation process that confers motility and fertilization competency to sperm. Chapter 1 discusses the use of whole cell mass spectrometry to identify 1247 proteins comprising the Rhesus macaque (Macaca mulatta) sperm proteome, a commonly used model of human reproduction. This study provides a more robust proxy of human sperm composition than was previously available and facilitates studies of sperm using the rhesus macaque as a model. Chapters 2 & 3 provide a systems level overview of changes in sperm proteome composition that occurs during epididymal transit. Chapter 2 reports the proteomes of sperm collected from the caput, corpus and cauda segments of the mouse epididymis, identifying 1536, 1720 and 1234 proteins respectively. Chapter 3 reports the sperm proteome from four distinct segments of the Rhesus macaque epididymis, including the caput, proximal corpus, distal corpus and cauda, identifying 1951, 2014, 1764 and 1423 proteins respectively. These studies identify a number of proteins that are added and removed from sperm during epididymal transit which likely play an important role in the sperm maturation process. To date no comparative evolutionary studies of sperm proteomes have been undertaken. Chapter 4 compares four mammalian sperm proteomes including the human, macaque, mouse and rat. This study identified 98 proteins common to all four sperm proteomes, 82 primate and 90 rodent lineage-specific proteins and 494, 467, 566, and 193 species specific proteins in the human, macaque, mouse and rat sperm proteomes respectively and discusses how differences in sperm composition may ultimately lead to functional differences across species. Finally, chapter 5 uses sperm proteome data to inform the preliminary design of a rodent contraceptive vaccine delivered orally using recombinant attenuated Salmonella vaccine vectors.
ContributorsSkerget, Sheri Jo (Author) / Karr, Timothy L. (Thesis advisor) / Lake, Douglas (Committee member) / Petritis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2013
Description
A new analytical method is proposed for measuring the deuterium to hydrogen ratio (D/H) of non-stoichiometric water in hydrous minerals via pyrolysis facilitated gas-chromatography - isotope ratio mass spectrometry (GC-IRMS). Previously published analytical methods have reported a poorly understood nonlinear dependence of D/H on sample size, for which any accurate correction is difficult. This sample size effect been variously attributed to kinetic isotope fractionation within the mass spectrometer and peripheral instruments, ion source linearity issues, and an unstable H_3^+-factor or incorrect H_3^+-factor calculations. The cause of the sample size effect is here identified by examinations of individual chromatograms as well as bulk data from chromatographic peaks. It is here determined that it is primarily an artifact of the calculations employed by the manufacturer's computer program, used to both monitor the functions of the mass spectrometer and to collect data. Ancillary causes of the sample size effect include a combination of persistent background interferences and chromatographic separation of the isotopologues of molecular hydrogen. Previously published methods are evaluated in light of these findings. A new method of H_3^+-factor and D/H calculation is proposed which makes portions of the Isodat software as well as other published calculation methods unnecessary. Using this new method, D/H is measured in non-stoichiometric water in chert from the Cretaceous Edwards Group, Texas, as well as the Precambrian Kromberg Formation, South Africa, to assess hydrological conditions as well as to estimate the maximum average surface temperature during precipitation of the chert. Data from Cretaceous chert are consistent with previously published data and interpretations, based upon conventional analyses of large samples. Data from Precambrian chert are consistent with maximum average surface temperatures approaching 65°C during the Archean, instead of the much lower temperatures derived from erroneous methods of sample preparation and analysis. D/H is likewise measured in non-stoichiometric water in silicified basalt from the Precambrian Hooggenoeg Complex, South Africa. Data are shown to be consistent with D/H of the Archean ocean similar to present day values.
ContributorsSheehan, Michael Robert (Author) / Knauth, Leroy P (Thesis advisor) / Anbar, Ariel (Committee member) / Farmer, Jack (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis discusses the use of mass spectrometry and polymerase chain reaction (PCR), among other methods, to detect biomarkers of microorganisms in the environment. These methods can be used to detect bacteria involved in the degradation of environmental pollutants (bioremediation) or various single-celled pathogens, including those posing potential threats as bioterrorism agents. The first chapter introduces the hurdles in detecting in diverse environmental compartments in which they could be found, a select list of single-celled pathogens representing known or potential bioterrorism agents. These hurdles take the form of substances that interfere either directly or indirectly with the detection method. In the case of mass spectrometry-based detection, many of these substances (interferences) can be removed via effective sample pretreatment. Chapters 2 through 4 highlight specific methods developed to detect bioremediation or bioterrorism agents in environmental matrices. These methods are qualitative mass spectrometry, quantitative PCR, and quantitative mass spectrometry, respectively. The targeted organisms in these methods include several bioremediation agents, e.g. Pseudomonas putida F1 and Sphingomonas wittichii RW1, and bioterrorism agents, e.g. norovirus and Cryptosporidium parvum. In Chapter 2, I identify using qualitative mass spectrometry, biomarkers for three bacterial species involved in bioremediation. In Chapter 3, I report on a new quantitative PCR method suitable for monitoring of a key gene in yet another bioremediation agent, Sphingomonas wittichii RW1; furthermore, I apply this method to track the efficacy of bioremediation in bioaugmented environmental microcosms. In Chapter 4, I report on the development of new quantitative mass spectrometry methods for two organisms, S. wittichii RW1 and Cryptosporidium parvum, and evaluate two previously published methods for their applicability to the analysis of complex environmental samples. In Chapter 5, I review state-of-the-art methods for the detection of emerging biological contaminants, specifically viruses, in environmental samples. While this summary deals exclusively with viral pathogens, the advantages and remaining challenges identified are also applicable to all single-celled organisms in environmental settings. The suggestions I make at the end of this chapter are expected to be valid not only for future needs for emerging viruses but also for bacteria, eukaryotic pathogens, and prions. In general, it is advisable to continue the trend towards quantification and to standardize methods to facilitate comparison of results between studies.
ContributorsHartmann, Erica Marie (Author) / Halden, Rolf U. (Thesis advisor) / Ghirlanda, Giovanna (Committee member) / Nelson, Randall W. (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
Oxygen fugacity (ƒO2) is a thermodynamic variable used to represent the redox state of a material or a system. It is equivalent to the partial pressure of oxygen in a particular environment corrected for the non-ideal behavior of the gas. ƒO2 is often used to indicate the potential for iron to occur in a more oxidized or reduced state at a particular temperature and pressure in a natural system. Secondary ion mass spectrometry (SIMS) is a powerful analytical instrument that can be used to analyze elemental and isotopic compositional information about microscopic features within solid materials. SIMS analyses of the secondary ion energy distribution of semi-pure metals demonstrate that the energy spectrum of individual mass lines can provide information about alterations in its surface environment.
The application of high-resolution (see Appendix C) energy spectrum calibrations to natural ilmenite led to the investigation of zirconium (90Zr+) and niobium (93Nb+) as potential indicators of sample ƒO2. Energy spectrum measurements were performed on an array of ilmenite crystals from the earth’s upper mantle retrieved from kimberlites and from a reduced meteorite. In all studied materials, variability in the peak shape and width of the energy spectra has been correlated with inferred sample ƒO2. The best descriptor of this relationship is the full-width at half-maximum (FWHM; see Appendix C) of the energy spectra for each sample. It has been estimated that a 1eV change in the FWHM of 93Nb+ energy spectra is roughly equivalent to 1 log unit ƒO2. Simple estimates of precision suggest the FWHM values can be trusted to 1eV and sample ƒO2 can be predicted to ±1 log unit, assuming the temperature of formation is known.
The work of this thesis also explores the applicability of this technique beyond analysis of semi-pure metals and ilmenite crystals from kimberlites. This technique was applied to titanium oxides experimentally formed at known ƒO2 as well as an ilmenite crystal that showed compositional variations across the grain (i.e., core to rim chemical variations). Analyses of titanium oxides formed at known ƒO2 agree with the estimation that 1 eV change in the FWHM of 93Nb+ is equivalent to ~1 log unit ƒO2 (in all cases but one); this is also true for analyses of a natural ilmenite crystal with compositional variations across the grain.
The application of high-resolution (see Appendix C) energy spectrum calibrations to natural ilmenite led to the investigation of zirconium (90Zr+) and niobium (93Nb+) as potential indicators of sample ƒO2. Energy spectrum measurements were performed on an array of ilmenite crystals from the earth’s upper mantle retrieved from kimberlites and from a reduced meteorite. In all studied materials, variability in the peak shape and width of the energy spectra has been correlated with inferred sample ƒO2. The best descriptor of this relationship is the full-width at half-maximum (FWHM; see Appendix C) of the energy spectra for each sample. It has been estimated that a 1eV change in the FWHM of 93Nb+ energy spectra is roughly equivalent to 1 log unit ƒO2. Simple estimates of precision suggest the FWHM values can be trusted to 1eV and sample ƒO2 can be predicted to ±1 log unit, assuming the temperature of formation is known.
The work of this thesis also explores the applicability of this technique beyond analysis of semi-pure metals and ilmenite crystals from kimberlites. This technique was applied to titanium oxides experimentally formed at known ƒO2 as well as an ilmenite crystal that showed compositional variations across the grain (i.e., core to rim chemical variations). Analyses of titanium oxides formed at known ƒO2 agree with the estimation that 1 eV change in the FWHM of 93Nb+ is equivalent to ~1 log unit ƒO2 (in all cases but one); this is also true for analyses of a natural ilmenite crystal with compositional variations across the grain.
ContributorsDillon, Sarah Marie (Author) / Hervig, Richard L (Thesis advisor) / Shim, Sang-Heon (Committee member) / Williams, Peter (Committee member) / Arizona State University (Publisher)
Created2019
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
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
ContributorsEvans, Bartlett R. (Conductor) / Schildkret, David (Conductor) / Glenn, Erica (Conductor) / Concert Choir (Performer) / Chamber Singers (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-16