Thesis (Ph. D.)--University of Oregon, 2002. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 101-112). Also available for download via the World Wide Web; free to University of Oregon users.

The catechol meta-fission pathway, a degradation pathway for simple aromatic compounds, is rich in enzyme chemistry and replete with structural and evolutionary diversity. Vinyl pyruvate hydratase (VPH) and MhpD catalyze the same reaction in this pathway, but in different bacterial species. These metal ion-dependent enzymes reportedly catalyze a 1,5-keto-enol tautomerization reaction followed by a Michael addition of water. MhpD, and most likely VPH, are members of the fumarylacetoacetate hydrolase (FAH) superfamily. The crystal structure of MhpD and the sequence of VPH identified four potential active site residues, Lys-60, Leu-72, Asp-78, and Ser-160 (Ser-161 in VPH). The K60A and D78N mutants of VPH and MhpD had the most damaging effects on catalysis. Moreover, the K60A mutant seemingly uncoupled tautomerization from hydration and provided evidence for an [alpha, beta]-unsaturated ketone in the reaction. The effects of the L72A and S160A (S161A in VPH) mutants were smaller, suggesting less important roles in the mechanism. 5-(carboxymethyl)-2-Oxo-3-hexene-1,6-dioate decarboxylase (COHED) is a metal ion-dependent enzyme in the homoprotocatechuate (HPC) pathway, a chromosomally encoded meta-fission pathway from Escherichia coli C that parallels the catechol meta-fission pathway. COHED is also a member of the FAH superfamily. It is a monomeric protein with two domains. It is postulated that the C-terminal domain catalyzes the decarboxylation reaction and the N-terminal domain carries out the 1,3-keto-enol tautomerization reaction. Site-directed mutagenesis, NMR, and kinetic analysis with different substrates and inhibitors have identified three potential active-site residues Glu-276, Glu-278 (in the C-terminal domain), and Lys-110 (in the N-terminal domain). Replacement of either glutamate with a glutamine eliminated both the decarboxylase and tautomerase activities. The K110A mutant also diminished both activities, but more importantly eliminated the C-3 proton/deuteron exchange reaction observed for substrate analogs. The enzymes of the catechol and homoprotocatechuate pathways provide examples of enzyme optimization toward a specific substrate even among related compounds, as reflected by the FAH superfamily. Hence, the results of these studies add to the growing body of information about how enzymes evolve and how pathways are assembled. / text

published_or_final_version / Pathology / Master / Master of Philosophy

published_or_final_version / Medical Sciences / Master / Master of Medical Sciences

published_or_final_version / Biochemistry / Doctoral / Doctor of Philosophy

The rapidly developing sequencing technology has brought up an opportunity to scientists to look into the detailed genotype information in human genome. Computational programs have played important roles in identifying disease related genomic variants from huge amount of sequencing data. In the past years, a number of computational algorithms have been developed, solving many crucial problems in sequencing data analysis, such as mapping sequencing reads to genome and identifying SNPs. However, many difficult and important issues are still expecting satisfactory solutions. A key challenge is identifying disease related mutations in the background of non-pathogenic polymorphisms. Another crucial problem is detecting INDELs especially the long deletions under the technical limitations of second generation sequencing technology. To predict disease related mutations, we developed a machine learning-based (Random forests) prediction tool, EFIN (Evaluation of Functional Impact of Nonsynonymous mutations). We build A Multiple Sequence Alignment (MSA) for a querying protein with its homologous sequences. MSA is later divided into different blocks according to taxonomic information of the sequences. After that, we quantified the conservation in each block using a number of selected features, for example, entropy, a concept borrowed from information theory. EFIN was trained by Swiss-Prot and HumDiv datasets. By a series of fair comparisons, EFIN showed better results than the widely-used algorithms in terms of AUC (Area under ROC curve), accuracy, specificity and sensitivity. The web-based database is provided to worldwide user at paed.hku.hk/efin. To solve the second problem, we developed Linux-based software, SPLindel that detects deletions (especially long deletions) and insertions using second generation sequencing data. For each sample, SPLindel uses split-read method to detect the candidate INDELs by building alternative references to go along with the reference sequences. And then we remap all the relevant reads using both original references and alternative allele references. A Bayesian model integrating paired-end information was used to assign the reads to the most likely locations on either the original reference allele or the alternative allele. Finally we count the number of reads that support the alternative allele (with insertion or deletions comparing to the original reference allele) and the original allele, and fit a beta-binomial mixture model. Based on this model, the likelihood for each INDEL is calculated and the genotype is predicted. SPLindel runs about the same speed as GATK and DINDEL, but much faster than DINDEL. SPLindel obtained very similar results as GATK and DINDEL for the INDELs of size 1-15 bps, but is much more effective in detecting INDELs of larger size. Using machine learning method and statistical modeling technology, we proposed the tools to solve these two important problems in sequencing data analysis. This study will help identify novel damaging nsSNPs more accurately and efficiently, and equip researcher with more powerful tool in identifying INDELs, especially long deletions. As more and more sequencing data are generated, methods and tools introduced in this thesis may help us extract useful information to facilitate identification of causal mutations to human diseases. / published_or_final_version / Paediatrics and Adolescent Medicine / Doctoral / Doctor of Philosophy

abstract / Biochemistry / Doctoral / Doctor of Philosophy

Mutation is a fundamental process in evolution because affects the amount of genetic variation in evolving populations. Molecular-structure models offer significant advantages over traditional population-genetics models for studying mutation, mainly because such models incorporate simple, tractable genotype-to-phenotype maps. Here, I use RNA secondary structure models to study four basic properties of mutation. The first section of this thesis studies the statistical properties of beneficial mutations. According to population genetics theory, the fitness effects of new beneficial mutations will be exponentially distributed. I show that in RNA there is sufficient correlation between a genotype and its point mutant neighbors to produce non-exponential distributions of fitness effects of beneficial mutations. These results suggest that more sophisticated statistical models may be necessary to adequately describe the distribution of fitness effects of new beneficial mutations. The second section of this thesis addresses the dynamics of deleterious mutations in evolving populations. There is a vast body of theoretical work addressing deleterious mutations that almost universally assumes that the fitness effects of deleterious mutations are static. I use an RNA simulation model to show that, at moderately high mutation rates, initially deleterious mutations may ultimately confer beneficial effects to the individuals harboring them. This result suggests that deleterious mutations may play a more important role in evolution than previously thought. The third section of this thesis studies the global patterns of mutations connecting phenotypes in fitness landscapes. I developed a network model to describe global characteristics of the relationship between sequence and structure in RNA fitness landscapes. I show that phenotype abundance varies in a predictable manner and critically influences evolutionary dynamics. A study of naturally occurring functional RNA molecules using a new structural statistic suggests that these molecules are biased towards abundant phenotypes. These results are consistent with an "ascent of the abundant" hypothesis, in which evolution yields abundant phenotypes even when they are not the most fit. The final section of this thesis addresses the evolution of mutation rates infinite asexual populations. I developed an RNA-based simulation model in which each individual's mutation rate is controlled by a neutral modifier locus. Using this model, I show that smaller populations maintain higher mutation rates than larger populations. I also show that genome length and shape of the fitness function do not significantly determine the evolved mutation rate. Lastly, I show that intermediate rates of environmental change favor evolution of the largest mutation rates. / text

published_or_final_version / Medical Sciences / Master / Master of Medical Sciences

In this work we studied various aspects of DNA repair in plants, focusing mainly on point mutation repair and its interconnection with double-strand break repair. We were using transgenic point mutation and recombination substrates as a primary tool in our experiments. We have compared two transgenic homologous recombination assays (B-glucuronidase- and luciferase-based), analyzed the sensitivity of DNA repair machinery to ultraviolet radiation and assessed the involvement of AtKu80, Atm and AtXpd repair genes in point mutation repair. Ours study revealed the following: the luciferase-based recombination assay is more sensitive then B-glucuronidase-based; double-stand break repair machinery is sensitive to ultraviolet radiation, which results in increased pint mutation formation; chosen DNA repair genes might be impaired in point mutation repair, however further experimentations are needed to confirm this. / xi, 132 leaves : ill. ; 29 cm.