Importance of non-conserved distal carboxyl terminal amino acids in two peptidases belonging to the M1 family: Thermoplasma acidophilum Tricorn interacting factor F2 and Escherichia coli Peptidase N

Enzymes belonging to the M1 family play important cellular roles and the key amino acids (aa) in the catalytic domain are conserved. However, C-terminal domain aa are highly variable and demonstrate distinct differences in organization. To address a functional role for the C-terminal domain, progressive deletions were generated in Tricorn interacting factor F2 from Thermoplasma acidophilum (F2) and Peptidase N from Escherichia coli (PepN). Catalytic activity was partially reduced in PepN lacking 4 C-terminal residues (PepNΔC4) whereas it was greatly reduced in F2 lacking 10 C-terminal residues (F2ΔC10) or PepN lacking eleven C-terminal residues (PepNΔC11). Notably, expression of PepNΔC4, but not PepNΔC11, in E. coliΔpepN increased its ability to resist nutritional and high temperature stress, demonstrating physiological significance. Purified C-terminal deleted proteins demonstrated greater sensitivity to trypsin and bound stronger to 8-amino 1-napthalene sulphonic acid (ANS), revealing greater numbers of surface exposed hydrophobic aa. Also, F2 or PepN containing large aa deletions in the C-termini, but not smaller deletions, were present in high amounts in the insoluble fraction of cell extracts probably due to reduced protein solubility. Modeling studies, using the crystal structure of E. coli PepN, demonstrated increase in hydrophobic surface area and change in accessibility of several aa from buried to exposed upon deletion of C-terminal aa. Together, these studies revealed that non-conserved distal C-terminal aa repress the surface exposure of apolar aa, enhance protein solubility, and catalytic activity in two soluble and distinct members of the M1 family.

Methods to improve gene signal: Application to cDNA microarrays

Microarrays are high throughput biological assays that allow the screening of thousands of genes for their expression. The main idea behind microarrays is to compute for each gene a unique signal that is directly proportional to the quantity of mRNA that was hybridized on the chip. A large number of steps and errors associated with each step make the generated expression signal noisy. As a result, microarray data need to be carefully pre-processed before their analysis can be assumed to lead to reliable and biologically relevant conclusions. This thesis focuses on developing methods for improving gene signal and further utilizing this improved signal for higher level analysis. To achieve this, first, approaches for designing microarray experiments using various optimality criteria, considering both biological and technical replicates, are described. A carefully designed experiment leads to signal with low noise, as the effect of unwanted variations is minimized and the precision of the estimates of the parameters of interest are maximized. Second, a system for improving the gene signal by using three scans at varying scanner sensitivities is developed. A novel Bayesian latent intensity model is then applied on these three sets of expression values, corresponding to the three scans, to estimate the suitably calibrated true signal of genes. Third, a novel image segmentation approach that segregates the fluorescent signal from the undesired noise is developed using an additional dye, SYBR green RNA II. This technique helped in identifying signal only with respect to the hybridized DNA, and signal corresponding to dust, scratch, spilling of dye, and other noises, are avoided. Fourth, an integrated statistical model is developed, where signal correction, systematic array effects, dye effects, and differential expression, are modelled jointly as opposed to a sequential application of several methods of analysis. The methods described in here have been tested only for cDNA microarrays, but can also, with some modifications, be applied to other high-throughput technologies. Keywords: High-throughput technology, microarray, cDNA, multiple scans, Bayesian hierarchical models, image analysis, experimental design, MCMC, WinBUGS.

Gene flow from transgenic plant populations: models and applications for risk assessment

The future use of genetically modified (GM) plants in food, feed and biomass production requires a careful consideration of possible risks related to the unintended spread of trangenes into new habitats. This may occur via introgression of the transgene to conventional genotypes, due to cross-pollination, and via the invasion of GM plants to new habitats. Assessment of possible environmental impacts of GM plants requires estimation of the level of gene flow from a GM population. Furthermore, management measures for reducing gene flow from GM populations are needed in order to prevent possible unwanted effects of transgenes on ecosystems. This work develops modeling tools for estimating gene flow from GM plant populations in boreal environments and for investigating the mechanisms of the gene flow process. To describe spatial dimensions of the gene flow, dispersal models are developed for the local and regional scale spread of pollen grains and seeds, with special emphasis on wind dispersal. This study provides tools for describing cross-pollination between GM and conventional populations and for estimating the levels of transgenic contamination of the conventional crops. For perennial populations, a modeling framework describing the dynamics of plants and genotypes is developed, in order to estimate the gene flow process over a sequence of years. The dispersal of airborne pollen and seeds cannot be easily controlled, and small amounts of these particles are likely to disperse over long distances. Wind dispersal processes are highly stochastic due to variation in atmospheric conditions, so that there may be considerable variation between individual dispersal patterns. This, in turn, is reflected to the large amount of variation in annual levels of cross-pollination between GM and conventional populations. Even though land-use practices have effects on the average levels of cross-pollination between GM and conventional fields, the level of transgenic contamination of a conventional crop remains highly stochastic. The demographic effects of a transgene have impacts on the establishment of trangenic plants amongst conventional genotypes of the same species. If the transgene gives a plant a considerable fitness advantage in comparison to conventional genotypes, the spread of transgenes to conventional population can be strongly increased. In such cases, dominance of the transgene considerably increases gene flow from GM to conventional populations, due to the enhanced fitness of heterozygous hybrids. The fitness of GM plants in conventional populations can be reduced by linking the selectively favoured primary transgene to a disfavoured mitigation transgene. Recombination between these transgenes is a major risk related to this technique, especially because it tends to take place amongst the conventional genotypes and thus promotes the establishment of invasive transgenic plants in conventional populations.

Bayesian statistical analysis of bacterial diversity

Bacteria play an important role in many ecological systems. The molecular characterization of bacteria using either cultivation-dependent or cultivation-independent methods reveals the large scale of bacterial diversity in natural communities, and the vastness of subpopulations within a species or genus. Understanding how bacterial diversity varies across different environments and also within populations should provide insights into many important questions of bacterial evolution and population dynamics. This thesis presents novel statistical methods for analyzing bacterial diversity using widely employed molecular fingerprinting techniques. The first objective of this thesis was to develop Bayesian clustering models to identify bacterial population structures. Bacterial isolates were identified using multilous sequence typing (MLST), and Bayesian clustering models were used to explore the evolutionary relationships among isolates. Our method involves the inference of genetic population structures via an unsupervised clustering framework where the dependence between loci is represented using graphical models. The population dynamics that generate such a population stratification were investigated using a stochastic model, in which homologous recombination between subpopulations can be quantified within a gene flow network. The second part of the thesis focuses on cluster analysis of community compositional data produced by two different cultivation-independent analyses: terminal restriction fragment length polymorphism (T-RFLP) analysis, and fatty acid methyl ester (FAME) analysis. The cluster analysis aims to group bacterial communities that are similar in composition, which is an important step for understanding the overall influences of environmental and ecological perturbations on bacterial diversity. A common feature of T-RFLP and FAME data is zero-inflation, which indicates that the observation of a zero value is much more frequent than would be expected, for example, from a Poisson distribution in the discrete case, or a Gaussian distribution in the continuous case. We provided two strategies for modeling zero-inflation in the clustering framework, which were validated by both synthetic and empirical complex data sets. We show in the thesis that our model that takes into account dependencies between loci in MLST data can produce better clustering results than those methods which assume independent loci. Furthermore, computer algorithms that are efficient in analyzing large scale data were adopted for meeting the increasing computational need. Our method that detects homologous recombination in subpopulations may provide a theoretical criterion for defining bacterial species. The clustering of bacterial community data include T-RFLP and FAME provides an initial effort for discovering the evolutionary dynamics that structure and maintain bacterial diversity in the natural environment.

A novel concept for airport terminal design integrating flexibility

The current research proposed a conceptual design framework for airports to obtain flexible departure layouts based on passenger activity analysis obtained from Business Process Models (BPM). BPMs available for airport terminals were used as a design tool in the current research to uncover the relationships existing between spatial layout and corresponding passenger activities. An algorithm has been developed that demonstrates the applicability of the proposed design framework by obtaining relative spatial layouts based on passenger activity analysis. The generated relative spatial layout assists architects in achieving suitable alternative layouts to meet the changing needs of an airport terminal.

Construction of a global map of human gene expression : the process, tools and analysis

This thesis studies human gene expression space using high throughput gene expression data from DNA microarrays. In molecular biology, high throughput techniques allow numerical measurements of expression of tens of thousands of genes simultaneously. In a single study, this data is traditionally obtained from a limited number of sample types with a small number of replicates. For organism-wide analysis, this data has been largely unavailable and the global structure of human transcriptome has remained unknown. This thesis introduces a human transcriptome map of different biological entities and analysis of its general structure. The map is constructed from gene expression data from the two largest public microarray data repositories, GEO and ArrayExpress. The creation of this map contributed to the development of ArrayExpress by identifying and retrofitting the previously unusable and missing data and by improving the access to its data. It also contributed to creation of several new tools for microarray data manipulation and establishment of data exchange between GEO and ArrayExpress. The data integration for the global map required creation of a new large ontology of human cell types, disease states, organism parts and cell lines. The ontology was used in a new text mining and decision tree based method for automatic conversion of human readable free text microarray data annotations into categorised format. The data comparability and minimisation of the systematic measurement errors that are characteristic to each lab- oratory in this large cross-laboratories integrated dataset, was ensured by computation of a range of microarray data quality metrics and exclusion of incomparable data. The structure of a global map of human gene expression was then explored by principal component analysis and hierarchical clustering using heuristics and help from another purpose built sample ontology. A preface and motivation to the construction and analysis of a global map of human gene expression is given by analysis of two microarray datasets of human malignant melanoma. The analysis of these sets incorporate indirect comparison of statistical methods for finding differentially expressed genes and point to the need to study gene expression on a global level.

Computational Methods for Locating and Analyzing Conserved Gene Regulatory DNA Elements

This thesis presents methods for locating and analyzing cis-regulatory DNA elements involved with the regulation of gene expression in multicellular organisms. The regulation of gene expression is carried out by the combined effort of several transcription factor proteins collectively binding the DNA on the cis-regulatory elements. Only sparse knowledge of the 'genetic code' of these elements exists today. An automatic tool for discovery of putative cis-regulatory elements could help their experimental analysis, which would result in a more detailed view of the cis-regulatory element structure and function. We have developed a computational model for the evolutionary conservation of cis-regulatory elements. The elements are modeled as evolutionarily conserved clusters of sequence-specific transcription factor binding sites. We give an efficient dynamic programming algorithm that locates the putative cis-regulatory elements and scores them according to the conservation model. A notable proportion of the high-scoring DNA sequences show transcriptional enhancer activity in transgenic mouse embryos. The conservation model includes four parameters whose optimal values are estimated with simulated annealing. With good parameter values the model discriminates well between the DNA sequences with evolutionarily conserved cis-regulatory elements and the DNA sequences that have evolved neutrally. In further inquiry, the set of highest scoring putative cis-regulatory elements were found to be sensitive to small variations in the parameter values. The statistical significance of the putative cis-regulatory elements is estimated with the Two Component Extreme Value Distribution. The p-values grade the conservation of the cis-regulatory elements above the neutral expectation. The parameter values for the distribution are estimated by simulating the neutral DNA evolution. The conservation of the transcription factor binding sites can be used in the upstream analysis of regulatory interactions. This approach may provide mechanistic insight to the transcription level data from, e.g., microarray experiments. Here we give a method to predict shared transcriptional regulators for a set of co-expressed genes. The EEL (Enhancer Element Locator) software implements the method for locating putative cis-regulatory elements. The software facilitates both interactive use and distributed batch processing. We have used it to analyze the non-coding regions around all human genes with respect to the orthologous regions in various other species including mouse. The data from these genome-wide analyzes is stored in a relational database which is used in the publicly available web services for upstream analysis and visualization of the putative cis-regulatory elements in the human genome.

Gene flow from Corymbia hybrids in northern New South Wales

Some of the most productive taxa for forestry are interspecific F1 hybrids grown as exotics in the tropics and subtropics. Attributes of resilience, adaptability and vigour which engender the hybrids for wood production, may also exacerbate the risk they present from gene flow to native species gene pools or to local ecologies as weeds. To determine the biological and genetic factors that influence the extent of hybridisation, we examine the distribution and genealogy of wildlings surrounding plantings of locally-exotic Corymbia torelliana (Section Cadageria) near native C. henryi (Section Maculatae) in northern New South Wales. Our study showed pre-mating and pre- and post-zygotic barriers were incomplete, with in situ generation and natural establishment of both F1 hybrids (n = 3) and advanced generation hybrids under the disturbed conditions bordering native forest. As hybrids were located on alluvial flats exposed to frost, they also likely have an extended ecological range relative to native C. henryi. Despite the likely generation of large viable seed crops on F1 trees at the site over many years, establishment success and survival of advanced generation hybrids may be low, as only 5 immature and no mature advanced generation hybrids were identified. Propagation and genetic analysis of a seed crop from one F1 wildling showed early survival and vigour of seedlings in cultivation was high, and that at least for some F1 in some seasons, backcrossing to the recurrent native C. henryi parent is favoured (60%), whereas selfing (10%) and crossing with other F1 (30%) was less frequent. Transport of seed by stingless bees probably accounted for long distance dispersal from C. torelliana, but this mechanism does not appear to supplement gravity-dispersal of seed from the F1. Coupled with other evidence from studies of bee behaviour, controlled pollination in Corymbia sp., and long-term fitness in second generation eucalypt hybrids, we anticipate gene flow via pollen rather than seed will be the greater challenge for managing the risk of introgression of C. torelliana ancestry into native species from the planted F1 hybrid. If large sources of F1 pollen become available to compete with native pollen, gene flow will probably be frequent and hybrids may establish in disturbed conditions and in habitats beyond the ecological range of their native parent. Further study is needed to determine the degree to which outbreeding depression and poor survival inhibits on-going gene flow.

Identification of I-7 expands the repertoire of genes for resistance to Fusarium wilt in tomato to three resistance gene classes

The tomato I-3 and I-7 genes confer resistance to Fusarium oxysporum f. sp. lycopersici (Fol) race 3 and were introgressed into the cultivated tomato, Solanum lycopersicum, from the wild relative Solanum pennellii. I-3 has been identified previously on chromosome 7 and encodes an S-receptor-like kinase, but little is known about I-7. Molecular markers have been developed for the marker-assisted breeding of I-3, but none are available for I-7. We used an RNA-seq and single nucleotide polymorphism (SNP) analysis approach to map I-7 to a small introgression of S. pennellii DNA (c. 210 kb) on chromosome 8, and identified I-7 as a gene encoding a leucine-rich repeat receptor-like protein (LRR-RLP), thereby expanding the repertoire of resistance protein classes conferring resistance to Fol. Using an eds1 mutant of tomato, we showed that I-7, like many other LRR-RLPs conferring pathogen resistance in tomato, is EDS1 (Enhanced Disease Susceptibility 1) dependent. Using transgenic tomato plants carrying only the I-7 gene for Fol resistance, we found that I-7 also confers resistance to Fol races 1 and 2. Given that Fol race 1 carries Avr1, resistance to Fol race 1 indicates that I-7-mediated resistance, unlike I-2- or I-3-mediated resistance, is not suppressed by Avr1. This suggests that Avr1 is not a general suppressor of Fol resistance in tomato, leading us to hypothesize that Avr1 may be acting against an EDS1-independent pathway for resistance activation. The identification of I-7 has allowed us to develop molecular markers for marker-assisted breeding of both genes currently known to confer Fol race 3 resistance (I-3 and I-7). Given that I-7-mediated resistance is not suppressed by Avr1, I-7 may be a useful addition to I-3 in the tomato breeder's toolbox.

The crystal and molecular structure of the amino terminal tetrapeptide of alamethicin. A novel 310 helical conformation

The molecular structure of N-benzyloxycarbonyl-α-aminoisobutyryl-prolyl-α-aminoisobutyryl-alanyl methyl ester (Z-Aib-Pro-Aib-Ala-OMe), the amino terminal tetrapeptide of alamethicin is reported. The molecule contains two consecutive β-turns with Aib-Pro and Pro-Aib at the corners, forming an incipient 310 helix. This constitutes the first example of an X2-Pro3 β-turn in the crystal structure of a small peptide.

A single point mutation disrupts the capsid assembly in Sesbania Mosaic Virus resulting in a stable isolated dimer

Protein-protein interactions play a Crucial role in Virus assembly and stability. With the view of disrupting capsid assembly and capturing smaller oligomers, interfacial residue mutations were carried Out in the coat protein gene of Sesbania Mosaic Virus, a T=3 ss (+) RNA plant virus. A single point mutation of a Trp 170 present at the five-fold interface of the virus to a charged residue (Glu or Lys) arrested assembly of virus like particles and resulted in stable Soluble dimers of the capsid Protein. The X-ray crystal structure of one of the isolated dimer mutants - rCP Delta N65W170K was determined to a resolution of 2.65 angstrom. Detailed analysis of the dimeric mutant protein structure revealed that a number of Structural changes take place, especially in the loop and interfacial regions during the course of assembly. The isolated chiller was ``more relaxed'' than the dimer found in the T=3 or T=1 capsids. The isolated dimer does not bind Ca2+ ion and consequently four C-terminal residues are disordered. The FG loop, which interacts with RNA in the Virus, has different conformations in the isolated dimer and the intact Virus Suggesting its flexible nature and the conformational changes that accompany assembly. The isolated choler mutant was much less stable when compared to the assembled capsids, suggesting the importance of inter-subunit interactions and Ca2+ mediated interactions in the stability of the capsids. With this study, SeMV becomes the first icosahedral virus for which X-ray crystal Structures of T=3, T=1 capsids as well as a smaller oligomer of the capsid protein have been determined.

Identification of key DNA elements involved in promoter recognition by Mxr1p, a master regulator of methanol utilization pathway in Pichia pastoris

Mxr1p (methanol expression regulator 1) functions as a key regulator of methanol metabolism in the methylotrophic yeast Pichia pastoris. In this study, a recombinant Mxr1p protein containing the N-terminal zinc finger DNA binding domain was overexpressed and purified from E coli cells and its ability to bind to promoter sequences of AOXI encoding alcohol oxidase was examined. In the AOXI promoter, Mxr1p binds at six different regions. Deletions encompassing these regions result in a significant decrease in AOXI promoter activity in vivo. Based on the analysis of AOXI promoter sequences, a consensus sequence for Mxr1p binding consisting of a core 5' CYCC 3' motif was identified. When the core CYCC sequence is mutated to CYCA, CYCT or CYCM (M = 5-methylcytosine), Mxr1p binding is abolished. Though Mxr1p is the homologue of Saccharomyces cerevisiae Adr1p transcription factor, it does not bind to Adr1p binding site of S. cerevisiae alcohol dehydrogenase promoter (ADH2UAS1). However, two point mutations convert ADH2UAS1 into an Mxr1p binding site. The identification of key DNA elements involved in promoter recognition by Mxr1p is an important step in understanding its function as a master regulator of the methanol utilization pathway in P. pastoris.

Endoplasmic reticulum stress and cell death mechanisms in the cell model of Huntington’s disease

This thesis clarifies important molecular pathways that are activated during the cell death observed in Huntington’s disease. Huntington’s disease is one of the most common inherited neurodegenerative diseases, which is primarily inherited in an autosomal dominant manner. HD is caused by an expansion of CAG repeats in the first exon of the IT15 gene. IT15 encodes the production of a Huntington’s disease protein huntingtin. Mutation of the IT15 gene results in a long stretch of polyQ residues close to the amino-terminal region of huntingtin. Huntington’s disease is a fatal autosomal neurodegenerative disorder. Despite the current knowledge of HD, the precise mechanism behind the selective neuronal death, and how the disease propagates, still remains an enigma. The studies mainly focused on the control of endoplasmic reticulum (ER) stress triggered by the mutant huntingtin proteins. The ER is a delicate organelle having essential roles in protein folding and calcium regulation. Even the slightest perturbations on ER homeostasis are effective enough to trigger ER stress and its adaptation pathways, called unfolded protein response (UPR). UPR is essential for cellular homeostasis and it adapts ER to the changing environment and decreases ER stress. If adaptation processes fail and stress is excessive and prolonged; irreversible cell death pathways are engaged. The results showed that inhibition of ER stress with chemical agents are able to decrease cell death and formation of toxic cell aggregates caused by mutant huntingtin proteins. The study concentrated also to the NF-κB (nuclear factor-kappaB) pathway, which is activated during ER stress. NF-κB pathway is capable to regulate the levels of important cellular antioxidants. Cellular antioxidants provide a first line of defence against excess reactive oxygen species. Excess accumulation of reactive oxygen species and subsequent activation of oxidative stress damages motley of vital cellular processes and induce cell degeneration. Data showed that mutant huntingtin proteins downregulate the expression levels of NF-κB and vital antioxidants, which was followed by increased oxidative stress and cell death. Treatment with antioxidants and inhibition of oxidative stress were able to counteract these adverse effects. In addition, thesis connects ER stress caused by mutant huntingtin to the cytoprotective autophagy. Autophagy sustains cellular balance by degrading potentially toxic cell proteins and components observed in Huntington’s disease. The results revealed that cytoprotective autophagy is active at the early points (24h) of ER stress after expression of mutant huntingtin proteins. GADD34 (growth arrest and DNA damage-inducible gene 34), which is previously connected to the regulation of translation during cell stress, was shown to control the stimulation of autophagy. However, GADD34 and autophagy were downregulated at later time points (48h) during mutant huntingtin proteins induced ER stress, and subsequently cell survival decreased. Overexpression GADD34 enhanced autophagy and decreased cell death, indicating that GADD34 plays a critical role in cell protection. The thesis reveales new interesting data about the neuronal cell death pathways seen in Huntington’s disease, and how cell degeneration is partly counteracted by various therapeutic agents. Expression of mutant huntingtin proteins is shown to alter signaling events that control ER stress, oxidative stress and autophagy. Despite that Huntington’s disease is mainly an untreatable disorder; these findings offer potential targets and neuroprotective strategies in designing novel therapies for Huntington’s disease.