Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.

Darmstadt, Techn. Univ., Diss., 2005. / Dateien im PDF-Format

Universiẗat, Diss., 1999--Tübingen.

Techn. Universiẗat, Diss., 2004--Berlin.

Universiẗat, Diss., 2005--Jena.

There are many reactions that are sensitive to the surface structure of a catalyst. In order to obtain a comprehensive understanding of structure sensitive surface chemistry we use Surface Structure Spread Single Crystals (S4Cs) that expose a continuous distribution of crystal planes across their surfaces. Those crystal planes that lack mirror symmetry contain terraces, monatomic steps, and kinks and can be described as chiral with an R or an S orientation. When coupled with spatially resolved surface analysis techniques, S4Cs can be used to study the effects of surface structure and chirality on surface chemistry across a continuous distribution of crystal planes. A set of six Cu S4Cs has been created that spans all possible crystal planes of Cu. The Cu(111) S4C was used to study the structure sensitivity of L- and D-tartaric acid (TA) decomposition and the Cu(100) S4C was used to study the structure sensitivity of L-4-13C and D-aspartic acid (AA) decomposition. Isothermal Temperature Programmed Reaction Spectroscopy (TPRS) was implemented in which the S4Cs with monolayers of TA and AA were held at a temperature below the temperature of peak decomposition observed in a standard TPR experiment (heating at 1 K/s). At various times during isothermal heating, the surface was cooled to quench the reaction. Spatially resolved X-ray Photoelectron Spectroscopy (XPS) was performed to identify those regions on the surface in which the adsorbates had decomposed and those in which they were still intact. On the Cu(111) S4C which exposes both (100) and (110) step edges, TA decomposition is most sensitive to the density of (100) steps. AA decomposition on the Cu(100) S4C was enantioselective: L-AA-4-13C decomposed on S surfaces before R surfaces while D-AA decomposed on R surfaces before S surfaces. The decomposition of CH3CH2OH, CD3CD2OD, and CF3CH2OH on Zn was studied using temperature programmed reaction spectroscopy (TPRS). The decomposition products of each reaction were determined and a reaction mechanism was proposed for CH3CH2OH decomposition based on the product ratios and peak temperature locations. The CH3CH2OH decomposition mechanism includes the formation of two intermediate species on the surface: CH3CH2- to form CH2=CH2 and CH3CH2O- to form CH3CH=O.

The advent of high-throughput DNA and RNA sequencing has made possible the assay of millions of nucleic acid molecules in parallel. This allows functional genomic elements to be identified from background in single-tube experiments. This dissertation discusses the development of two such functional screens as well as work implementing a third that was previously developed in my thesis laboratory. Restriction-Associated DNA sequencing (RAD-Seq) is a complexity reduction sequencing method that allows the same subset of genomic sequence to be read across multiple samples. Differences in sample collection and data analysis allow manifold applications of RAD-Seq. Here we use RAD-Seq to identify mutant genes responsible for altered phenotypes in Caenorhabditis elegans and to identify hyper-invasive alleles in trout population admixtures. Apart from acquiring genomic sequence data, massively-parallel sequencing can be used for counting applications that quantify activity across a large number of test molecules. This dissertation describes the development of a technique for simultaneously quantifying the activity of a restriction enzyme across all possible DNA substrates by linking digest of a sequenced genome to Illumina-sequencing in an unbiased fashion. Finally, a powerful approach to analyze transcriptional activation is described. This method quantifies output from millions of potential DNA transcriptional enhancers via RNA amplicon sequencing of covalently-linked randomer tags and is used in conjunction with RNA-Seq to provide a mechanistic view of hypoxic gene regulation in Drosophila. This dissertation includes previously published, co-authored material

No description available.

Many pathogenic microorganisms are believed to stochastically switch into low metabolic states that display resistance to supra-lethal levels of antibiotics. These so-called “persister” cells have been associated with recurrent infections and the development of antibiotic resistance. Whilst a compound that eliminates Staphylococcus aureus persister cells has been described, it is not active against Gram-negative bacteria. The aim of my PhD project was to develop a high-throughput assay for compounds that eradicate persister cells in the -proteobacterium Burkholderia thailandensis. Further to this, I aimed to develop “hit” compounds from screening into lead series through investigation of structure activity relationships and, use a chemical genetics approach to elucidate potential mechanisms of action. I developed a phenotypic assay to identify compounds that eradicate persister cells. The assay was based on the reduction of the resazurin based dye PrestoBlue. Optimization of the assay gave a Z’ prime of 0.41 when screened in high throughput at the DDU. Screening of the library of 61,250 compounds identified 2,127 compounds that gave a statistically significant reduction in persister cell numbers. Follow-up assays highlighted 29 compounds with a pIC50 greater than five. Detailed investigation allowed me to down select to six “best in class” compounds, which included the licensed drug chloroxine. A time dependent killing assay showed that chloroxine reduced levels of persister cells by three orders of magnitude over 72 hours (P = 0.01). Hit expansion around chloroxine using commercially available compounds did not identify any more potent compounds, but did highlight key features of the molecule for activity. Assay protocols were provided to collaborators at DSTL who were able to iv show that chloroxine is also active against persister cells formed by the tropical pathogen and Tier 1 biological agent Burkholderia pseudomallei. Investigations into the mechanism of action of chloroxine used Next Generation Sequencing of an over expression library, identifying two putative genes involved in inhibition of persister cells by chloroxine. My findings demonstrate a phenotypic assay against persister cells in Gram-negative bacteria, which has the power to identify potent anti-persister agents to assist in chemotherapy. Structural activity relationship and mechanism of action investigations have indicated lead series and genetic starting points for future development of this research. My PhD project has concluded with sufficient data for continuation of research following a number of leads and is at an ideal stage for instigation of a medicinal chemistry program for development of chloroxine as a clinical option for treatment of persistent melioidosis.

Master of Science / Department of Computer Science / Mitchell L. Neilsen / Kansas State University is a world leader in the study of small grain genetics to develop new varieties which tolerate a wide range of environmental conditions. A phenotype is a composite of a plants observable traits. Several mobile applications, called PhenoApps, have been developed for field-based, high-throughput phenotyping (HTP) to advance plant breeding programs around the world. These applications require novel image analysis algorithms to be developed to model and extract plant phenotypes. Some of the first algorithms developed were focused on using static image analysis to count and characterize a wide variety of seeds in a single image with a static colored background. This thesis describes both a static algorithm and development of a hopper system for a dynamic, real-time algorithm to accurately count and characterize seeds using a modest mobile device. The static algorithm analyzes a single image of a particular seed sample, captured on a mobile device; whereas, the dynamic algorithm analyzes multiple frames from the video input of a mobile device in real time. Novel 3D models are designed and printed to set a steady flow rate for the seeds, but the analysis is also completed to consider seeds flowing at variable rates and to determine the range of allowable flow rates and achievable precision for a wide variety of seeds. Both algorithms have been implemented in user-friendly mobile applications for realistic, field-based use. A plant breeder can use the applications to both count and characterize a smaller sample using the static approach or a larger sample using the dynamic approach, with seeds sampled in real time without the need to analyze multiple static images. There are many directions for future research to enhance the algorithms performance and accuracy.