Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references. Available also in a digital version from Dissertation Abstracts.

Thesis (M.S.)--University of North Texas, Dec., 2008. / Title from title page display. Includes bibliographical references.

Thesis (Ph. D.)--Carleton University, 2000. / Also available in electronic format on the Internet.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a sensitive technique used to analyse the molecular composition of solid samples using keV ion beam sputtering. However only a small fraction (typically < 10⁻³) of the desorbed material issecondary ions - the majority species (neutrals) cannot be extracted and detected by the mass spectrometer. To increase the sensitivity and efficiency of the SIMS technique, post-ionisation above the surface can be used. Lasers have been widely employed for molecular mass spectrometry due to the available high intensity, short pulse width, high spectral purity and spatial coherence that allow them to be highly focused. For molecular samples the challenge is to achieve efficient post-ionisation without inducing extensive fragmentation, which limits the diagnostic value of the resulting mass spectrum. An investigation was performed into the ionisation and dissociation characteristics of a series of organic molecules under the action of intense laser fields. This study is directed towards the analysis of biomolecules using laser post-ionisation. Here is reported progress towards the calibration of the experimental set-up and mass spectral data from representative biomolecules in the gas phase. In this work a Ti:Sapphire laser was used with fundamental wavelength of 800 nm and non-linear optical methods (OPAs) are used to extend the wavelength into the mid-IR region. System calibration is achieved using the ionisation of xenon atoms and comparing the results to established atomic tunnelling theory. This was followed by the analysis of representative organic and biological molecules to study ionisation-dissociation characteristics. The molecules chosen were toluene, acetone, nitroaniline and histamine. A clear transition in behavior is observed favoring molecular ion production. This behavior is discussed in the context of the underlying mechanisms, and the implications for molecular post-ionisation analysis using focused ion beams.

Nanoparticles, simple yet groundbreaking objects have led to the discovery of invaluable information due to their physiological, chemical, and physical properties, have become a hot topic in various fields of study including but not limited to chemistry, biology, and physics. In the work presented here, demonstrations of various applications of chemical free nanoparticles are explored, from the determination of a non-invasive method for the study of the exposome via using soft-landing ion mobility (SLIM) deposited nanoparticles as a matrix-assisted laser desorption/ionization (MALDI-MS) matrix replacement, to the direct SLIM-exposure of nanoparticles onto living organisms. While there is plenty of published work in soft-landing at operating pressures of 1 Torr, the work presented here shows how this technology can be operated at the less common ambient pressure. The ease of construction of this instrument allows for various modifications to be performed for a wide array of applications, furthermore the flexibility in metallic sample, operating pressure, and deposition time only open doors to many other future applications. The work presented will also show that our ambient SLIM system is also able to be operated for toxicological studies, as the operation at ambient pressure opens the door to new applications where vacuum conditions are not desired.

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Brevetoxins are natural neurotoxins that are produced by "red tide" algae. In this study, brevetoxin-1 and brevetoxin-2 were incubated with rat liver hepatocytes and rat liver microsomes, respectively. After clean-up steps, samples were analyzed by liquid chromatography (LC) coupled with electrospray mass spectrometry (LC-MS). For the incubation sample of brevetoxin- 1, two metabolites were found: brevetoxin-1-M1 and brevetoxin- 1-M2. The tandem mass spectrometry study of the [brevetoxin-1- M1+H]+ led to the conclusion that it was formed by converting one double bond in the E or F ring of brevetoxin-1 into a diol. The second metabolite (brevetoxin-1-M2) is proposed to be a hydrolysis product of brevetoxin-1 involving opening of the lactone ring with the addition of a water molecule. The study of incubation of brevetoxin-2 found two metabolites: brevetoxin-2- M1 gave a large [M-H]- peak, and its product ion mass spectrum allowed the deduction that this metabolite was the hydrolysis product of brevetoxin-2; the second metabolite (brevetoxin-2-M2) was deduced to have the same structure as that of brevetoxin-3.

The glycoproteome is an intricate and diverse component of a cell, and it plays a key role in the definition of the interface between that cell and the rest of its world. Methods for studying the glycoproteome have been developed for released glycan glycomics and site-localized bottom-up glycoproteomics using liquid chromatography-coupled mass spectrometry and tandem mass spectrometry (LC-MS/MS), which is itself a complex problem. Algorithms for interpreting these data are necessary to be able to extract biologically meaningful information in a high throughput, automated context. Several existing solutions have been proposed but may be found lacking for larger glycopeptides, for complex samples, different experimental conditions, different instrument vendors, or even because they simply ignore fundamentals of glycobiology. I present a series of open algorithms that approach the problem from an instrument vendor neutral, cross-platform fashion to address these challenges, and integrate key concepts from the underlying biochemical context into the interpretation process. In this work, I created a suite of deisotoping and charge state deconvolution algorithms for processing raw mass spectra at an LC scale from a variety of instrument types. These tools performed better than previously published algorithms by enforcing the underlying chemical model more strictly, while maintaining a higher degree of signal fidelity. From this summarized, vendor-normalized data, I composed a set of algorithms for interpreting glycan profiling experiments that can be used to quantify glycan expression. From this I constructed a graphical method to model the active biosynthetic pathways of the sample glycome and dig deeper into those signals than would be possible from the raw data alone. Lastly, I created a glycopeptide database search engine from these components which is capable of identifying the widest array of glycosylation types available, and demonstrate a learning algorithm which can be used to tune the model to better understand the process of glycopeptide fragmentation under specific experimental conditions to outperform a simpler model by between 10% and 15%. This approach can be further augmented with sample-wide or site-specific glycome models to increase depth-of-coverage for glycoforms consistent with prior beliefs.