Thesis (Ph. D.)--University of Washington, 2007. / Vita. Includes bibliographical references (leaves 145-152).

No description available.

Choy, Man Fai. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 120-123). / Abstracts in English and Chinese. / Title Page --- p.1 / Abstract (English) --- p.2 / Abstract (Chinese) --- p.3 / Acknowledgement --- p.4 / Declaration --- p.5 / Table of Content --- p.6 / Lists of Figures --- p.9 / Lists of Tables --- p.12 / List of Schemes --- p.13 / Chapter Chapter One --- Introduction / Historical perspective and overview of tandem mass spectrometry for structural biochemistry --- p.14 / Electrospray ionization (ESI) --- p.15 / Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) --- p.18 / Chapter 1.3.1 --- History of FTICR --- p.18 / Chapter 1.3.2 --- Theory of FTICR --- p.21 / Chapter 1.4 --- Sequencing of DNA fragments --- p.26 / Chapter 1.4.1 --- Conventional and mass spectrometric sequencing techniques --- p.26 / Chapter 1.4.2 --- Fragment-ion nomenclature --- p.27 / Chapter 1.4.3 --- Tandem mass spectrometry of oligonucleotide ions --- p.29 / Chapter 1.4.4 --- Electron capture dissociation of oligonucleotide ions --- p.31 / Chapter 1.5 --- Outline of the present work --- p.32 / Chapter Chapter Two --- Instrument and Experimental / Chapter 2.1 --- Instrumentation --- p.35 / Chapter 2.1.1 --- Fourier-transform ion cyclotron resonance mass spectrometer --- p.35 / Chapter 2.1.2 --- Vacuum system --- p.35 / Chapter 2.1.3 --- Nanospray ion source --- p.39 / Chapter 2.1.4 --- Ion Transfer system --- p.41 / Chapter 2.1.5 --- Infinity cell --- p.43 / Chapter 2.1.6 --- Electron emission source --- p.44 / Chapter 2.2 --- Experimental section --- p.47 / Chapter 2.2.1 --- Simple acquisition pulse program --- p.47 / Chapter 2.2.2 --- ECD pulse program --- p.49 / Chapter Chapter Three --- Production of Doubly-prontonated Oligonucleotide ions using Nanospray Ionization / Chapter 3.1 --- Introduction --- p.52 / Chapter 3.2 --- Experimental and instrumental section --- p.53 / Chapter 3.2.1 --- Materials --- p.53 / Chapter 3.2.2 --- Sample preparation --- p.53 / Chapter 3.2.3 --- Instrumentation --- p.54 / Chapter 3.3 --- Results and discussion --- p.54 / Chapter 3.3.1 --- Effect of the concentration of ammonium formate --- p.54 / Chapter 3.3.2 --- Effects of the anionic pair of the ammonium salts --- p.57 / Chapter 3.3.3 --- Effects of solvent composition --- p.64 / Chapter 3.3.4 --- Effects of analyte concentration --- p.66 / Chapter 3.4 --- Conclusion --- p.68 / Chapter Chapter Four --- Electron Capture Dissociation of Model Oligonucleotides / Chapter 4.1 --- Introduction --- p.69 / Chapter 4.2 --- Experimental and instrumental section --- p.70 / Chapter 4.2.1 --- Materials --- p.70 / Chapter 4.2.2 --- Sample preparation --- p.70 / Chapter 4.2.3 --- Instrumentation --- p.71 / Chapter 4.2.4 --- Method of calculations --- p.71 / Chapter 4.3 --- Results and discussion --- p.72 / Chapter 4.3.1 --- "ECD of d(CCCCC), d(CCAAC), d(CCTTC) and d(CCGGC)" --- p.72 / Chapter 4.3.1.1 --- General features --- p.72 / Chapter 4.3.1.2 --- Protonated nucleobases and nucleoside-like fragments --- p.73 / Chapter 4.3.1.3 --- Doubly-charged fragment ions --- p.79 / Chapter 4.3.2 --- Theoretical calculation of electron capture affinities of common functionalities in oligonucleotides --- p.80 / Chapter 4.3.3 --- Electron capture dissociation of C/T binary-based oligonucleotides --- p.81 / Chapter 4.3.3.1 --- "ECD of d(CTCTC), d(TCCCT) and d(CTTTC)" --- p.84 / Chapter 4.3.3.2 --- ECD of d(CCCCT) and d(TCCCC) --- p.84 / Chapter 4.3.4 --- Mechanistic implications --- p.89 / Chapter 4.4 --- Conclusion --- p.99 / Chapter Chapter Five --- Electron Capture Dissociation of a Series of G/T Binary Base of Oligonucleotides / Chapter 5.1 --- Introduction --- p.100 / Chapter 5.2 --- Experimental and instrumental section --- p.100 / Chapter 5.2.1 --- Materials --- p.100 / Chapter 5.2.2 --- Sample preparation --- p.100 / Chapter 5.2.3 --- Instrumentation --- p.101 / Chapter 5.3 --- Results and discussion --- p.101 / Chapter 5.3.1 --- Electron capture dissociation of d(GGGGG) --- p.101 / Chapter 5.3.2 --- Electron capture dissociation of G/T binary-based oligonucleotides --- p.104 / Chapter 5.3.2.1 --- "ECD of d(GTGTG), d(GTTTG) and d(TGGGT)" --- p.104 / Chapter 5.3.2.2 --- ECD of d(GGGGT) and d(TGGGG) --- p.107 / Chapter 5.3.3 --- Mechanistic implications --- p.110 / Chapter 5.4 --- Conclusion --- p.117 / Chapter Chapter Six --- Conclusion Remarks --- p.118 / References --- p.120 / Appendix A --- p.124 / Appendix B --- p.127

published_or_final_version / Biological Sciences / Doctoral / Doctor of Philosophy

Spurious, falsely-labeled, falsified or counterfeit (SFFC) pharmaceuticals are a health concern that claims hundreds of thousands of lives annually1, a violation of intellectual property rights which cost legitimate companies billions2, and a low-risk high yield revenue stream for organized crime2. While ports of entry and border control points are the primary access control points for SFFC3,4, advances in field portable detection and equipment offers an increasingly effective method for the assessment of pharmaceuticals at regional centers and points of distribution. This is particularly important for less developed countries (LDC) who do not maintain satellite or regional testing facilities. As part of a proposed protocol to assess field portable detection equipment, an ultrafast liquid chromatography, tandem mass spectrometry (UFLC-MS/MS) method for the quantification of liquid formulation Oxytocin was developed. The six minute method was found to have a within run %bias of +/-16%, a linear dynamic range of 150-1000 nanograms/milliliter (ng/ml), and an accuracy within acceptability criteria for all tested concentrations. The effectiveness of three identified transition ions, 723.1, 86.2 and 70.1 Daltons, for the analysis of oxytocin by mass spectrometry was assessed across several figures of merit to include signal to noise ratio, %CV, calibration sensitivity, and analytical sensitivity. The 723.1 ion fragment was recommended for quantification, while the 70.1 dalton ion was recommended as a qualifier ion, although 86.2 also performed within acceptability criteria. A method for the UFLC-MS/MS assessment of degradation products for oxytocin was proposed for specificity testing. Degradation of oxytocin by exposure to highly acidic, basic, and thermal conditions for one hour was attempted. Formation of degraded products was not observed. Additionally, existing High Performance Liquid Chromatography (HPLC) methods for the simultaneous assessment of Artesunate and Amodiaquine HCl were modified to assess compatibility with UFLC. No method assessed produced sufficient quality signal to continue with method development.

No description available.

Nonribosomal peptides (NRP) are highlighted in pharmacological studies as novel NRPs are often promising substances for new drug development. To effectively discover novel NRPs from microbial fermentations, a crucial step is to identify known NRPs in an early stage and exclude them from further investigation. This so-called dereplication step ensures the scarce resource is only spent on the novel NRPs in the following up experiments. Tandem mass spectrometry has been routinely used for NRP dereplication. However, few bioinformatics tools have been developed to computationally identify NRP compounds from mass spectra, while manual identification is currently the roadblock hindering the throughput of novel NRP discovery. In this thesis, we review the nature of nonribosomal peptides and investigate the challenges in computationally solving the identification problem. After that, iSNAP software is proposed as an automated and high throughput solution for tandem mass spectrometry based NRP identification. The algorithm has been evolved from the traditional database search approach for identifying sequential peptides, to one that is competent at handling complicated NRP structures. It is designed to be capable of identifying mixtures of NRP compounds from LC-MS/MS of complex extract, and also finding structural analogs which differ from an identified known NRP compound with one monomer. Combined with an in-house NRP structural database of 1107 compounds, iSNAP is tested to be an effective tool for mass spectrometry based NRP identification. The software is available as a web service at http://monod.uwaterloo.ca/isnap for the research community.

High-throughput techniques are currently some of the most promising methods to study molecular biology, with the potential to improve medicine and enable new biological applications. In proteomics, the large scale study of proteins, the leading method is mass spectrometry. At present researchers can routinely identify and quantify thousands of proteins in a single experiment with the technique called shotgun proteomics. A challenge of these experiments is the computational analysis and the interpretation of the mass spectra. A shotgun proteomics experiment easily generates tens of thousands of spectra, each thought to represent a peptide from a protein. Due to the immense biological and technical complexity, however, our computational tools often misinterpret these spectra and derive incorrect peptides. As a consequence, the biological interpretation of the experiment relies heavily on the statistical confidence that we estimate for the identifications. In this thesis, I have included four articles from my research on the accuracy of the statistical confidence estimates in shotgun proteomics, how to accomplish and evaluate it. In the first two papers a new method to use pre-characterized protein samples to evaluate this accuracy is presented. The third paper deals with how to avoid statistical inaccuracies when using machine learning techniques to analyze the data. In the fourth paper, we present a new tool for analyzing shotgun proteomics results, and evaluate the accuracy of  its statistical estimates using the method from the first papers. The work I have included here can facilitate the development of new and accurate computational tools in mass spectrometry-based proteomics. Such tools will help making the interpretation of the spectra and the downstream biological conclusions more reliable.

Tandem mass spectrometry (MS/MS) is a powerful tool for identifying peptide sequences. In a typical experiment, incorrect peptide identifications may result due to noise contained in the MS/MS spectra and to the low quality of the spectra. Filtering methods are widely used to remove the noise and improve the quality of the spectra before the subsequent spectra identification process. However, existing filtering methods often use features and empirically assigned weights. These weights may not reflect the reality that the contribution (reflected by weight) of each feature may vary from dataset to dataset. Therefore, filtering methods that can adapt to different datasets have the potential to improve peptide identification results. This thesis proposes two adaptive filtering methods; denoising and quality assessment, both of which improve efficiency and effectiveness of peptide identification. First, the denoising approach employs an adaptive method for picking signal peaks that is more suitable for the datasets of interest. By applying the approach to two tandem mass spectra datasets, about 66% of peaks (likely noise peaks) can be removed. The number of peptides identified later by peptide identification on those datasets increased by 14% and 23%, respectively, compared to previous work (Ding et al., 2009a). Second, the quality assessment method estimates the probabilities of spectra being high quality based on quality assessments of the individual features. The probabilities are estimated by solving a constraint optimization problem. Experimental results on two datasets illustrate that searching only the high-quality tandem spectra determined using this method saves about 56% and 62% of database searching time and loses 9% of high-quality spectra. Finally, the thesis suggests future research directions including feature selection and clustering of peptides.

Nonribosomal peptides (NRP) are highlighted in pharmacological studies as novel NRPs are often promising substances for new drug development. To effectively discover novel NRPs from microbial fermentations, a crucial step is to identify known NRPs in an early stage and exclude them from further investigation. This so-called dereplication step ensures the scarce resource is only spent on the novel NRPs in the following up experiments. Tandem mass spectrometry has been routinely used for NRP dereplication. However, few bioinformatics tools have been developed to computationally identify NRP compounds from mass spectra, while manual identification is currently the roadblock hindering the throughput of novel NRP discovery. In this thesis, we review the nature of nonribosomal peptides and investigate the challenges in computationally solving the identification problem. After that, iSNAP software is proposed as an automated and high throughput solution for tandem mass spectrometry based NRP identification. The algorithm has been evolved from the traditional database search approach for identifying sequential peptides, to one that is competent at handling complicated NRP structures. It is designed to be capable of identifying mixtures of NRP compounds from LC-MS/MS of complex extract, and also finding structural analogs which differ from an identified known NRP compound with one monomer. Combined with an in-house NRP structural database of 1107 compounds, iSNAP is tested to be an effective tool for mass spectrometry based NRP identification. The software is available as a web service at http://monod.uwaterloo.ca/isnap for the research community.