No description available.

A great deal of our current understanding about the biology of neurodegenerative diseases has come from studying the function of genes linked to inherited forms of these disorders. Work performed in animal models, including vertebrates as well as invertebrates, has been instrumental in deciphering the cellular, physiological and behavioural deficits arising from the expression of disease-causing genes. Using the fruit fly, Drosophila melanogaster, as a model we examined the normal and aberrant function of two genes linked to the onset of neurodegeneration in humans, presenilin and superoxide dismutase. Drosophila is an extremely versatile model and in many ways is ideal for studying the genetic basis of human disease. The high degree of genetic conservation coupled with low genetic redundancy make this model particularly well suited for studying the function of disease causing genes. We demonstrate a novel genetic,physical and physiological interaction between presenilin and calmodulin and describe how this interaction impacts a very early cellular defect associated with Alzheimer?s Disease, intracellular calcium dyshomeostasis. We also describe progressive locomotory deficits in flies expressing mutant alleles of the superoxide dismutase gene, which have been linked to the onset of familial amyotrophic lateral sclerosis. Collectively, our work demonstrates that Drosophila can be used to study the cellular, physiological and behavioural basis of human neurodegenerative diseases and may provide a model to identify novel therapeutic avenues for neurodegenerative diseases.

A great deal of our current understanding about the biology of neurodegenerative diseases has come from studying the function of genes linked to inherited forms of these disorders. Work performed in animal models, including vertebrates as well as invertebrates, has been instrumental in deciphering the cellular, physiological and behavioural deficits arising from the expression of disease-causing genes. Using the fruit fly, Drosophila melanogaster, as a model we examined the normal and aberrant function of two genes linked to the onset of neurodegeneration in humans, presenilin and superoxide dismutase. Drosophila is an extremely versatile model and in many ways is ideal for studying the genetic basis of human disease. The high degree of genetic conservation coupled with low genetic redundancy make this model particularly well suited for studying the function of disease causing genes. We demonstrate a novel genetic,physical and physiological interaction between presenilin and calmodulin and describe how this interaction impacts a very early cellular defect associated with Alzheimer?s Disease, intracellular calcium dyshomeostasis. We also describe progressive locomotory deficits in flies expressing mutant alleles of the superoxide dismutase gene, which have been linked to the onset of familial amyotrophic lateral sclerosis. Collectively, our work demonstrates that Drosophila can be used to study the cellular, physiological and behavioural basis of human neurodegenerative diseases and may provide a model to identify novel therapeutic avenues for neurodegenerative diseases.

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Naegleria fowleri, a free-living ameba, is the causative agent of Primary Amebic Meningoencephalitis. Highly-pathogenic mouse-passaged amebae (Mp) and weakly-pathogenic axenically-grown (Ax) N. fowleri were examined for peptidase activity. Zymography and azocasein peptidase activity assays demonstrated that Mp and Ax N. fowleri exhibited a similar peptidase pattern. Prominent for whole cell lysates, membranes and conditioned medium from Mp and Ax amebae were the presence of an activity band of approximately 58kDa and 100 kDa bands susceptible to the action of cysteine and metallopeptidase inhibitors, respectively. Further roles of the peptidases during the invasion process were examined by in vitro invasion assays in the presence of inhibitors and Cysteine and metallopeptidase inhibitors were found to greatly reduce invasion through the ECM. This study establishes a functional linkage of the expressed peptidases to the invasion process, and these peptidases may serve as a candidate target for therapeutic management of N. fowleri infection.

The ability to predict is one of the hallmarks of successful theories. Historically, the predictive power of biology has lagged behind disciplines like physics because the biological world is complex, challenging to quantify, and full of exceptions. However, in recent years the amount of available data has expanded exponentially and biological predictions based on this data become a possibility. The functional gene network is a quantitative way to integrate this data and a useful framework for making biological predictions. This study demonstrates that functional networks capture real biological insight and uses the network to predict both subcellular protein localization and the phenotypic outcome of gene knockouts. Furthermore, I use the functional network to evaluate genetic modules shared between diverse organisms that lead to orthologous phenotypes, many that are non-obvious. I show that the successful predictions of the functional network have broad applicability and implications that range from the design of large-scale biological experiments to the discovery of genes with potential roles in human disease. / text

Deciphering the functionality encoded in the genome constitutes an essential first step to understanding the context through which mutations can cause human disease. In this dissertation, I present multiple studies based on the use or development of comparative genomics techniques to elucidate function (or lack of function) from the genomes of humans and other animal species. Collectively, these studies focus on two biological entities encoded in the human genome: genes related to human disease susceptibility and those that encode microRNAs - small RNAs that have important gene-regulatory roles in normal biological function and in human disease. Extending this work, I investigated the evolution of these biological entities within animals to shed light on how their underlying functions arose and how they can be modeled in non-human species. Additionally, I present a new tool that uses large-scale clinical genomic data to identify human mutations that may affect microRNA regulatory functions, thereby providing a method by which state-of-the-art genomic technologies can be fully utilized in the search for new disease mechanisms and potential drug targets. The scientific contributions made in this dissertation utilize current data sets generated using high-throughput sequencing technologies. For example, recent whole-genome sequencing studies of the most distant animal lineages have effectively restructured the animal tree of life as we understand it. The first two chapters utilize data from this new high-confidence animal phylogeny - in addition to data generated in the course of my work - to demonstrate that (1) certain classes of human disease have uncommonly large proportions of genes that evolved with the earliest animals and/or vertebrates, and (2) that canonical microRNA functionality - absent in at least two of the early branching animal lineages - likely evolved after the first animals. In the third chapter, I expand upon recent research in predicting microRNA target sites, describing a novel tool for predicting clinically significant microRNA target site variants and demonstrating its applicability to the analysis of clinical genomic data. Thus, the studies detailed in this dissertation represent significant advances in our understanding of the functions of disease genes and microRNAs from both an evolutionary and a clinical perspective.

No description available.

Besides helping us advance the understanding of the physicochemical principles governing the three-dimensional folding of proteins and their mechanisms of action, the ability to build, evaluate, and optimize reliable 3D protein models has provided valuable tools for the development of different applications in the fields of biotechnology, medicine, and synthetic biology. The development of automated algorithms has made many of the current methodologies for protein modelling and visualization available to researchers from all backgrounds, without the need to be familiarized with the inner workings of their statistical and biophysical principles. However, there is still a lack in some areas where the learning curves are too steep for the methods to be widely used by the average non-programmer molecular biologist, or the implementation of the methods lacks key features to improve the interpretability and impact of their results. Throughout this work, I will focus on two different applications in the field of structural biology where computational methods provide useful tools to aid in synthetic biology or medical research. The first application is the implementation of a pipeline to build models of protein complexes by joining structured domains with disordered linkers, in individual or multiple chains, and with the possibility of building symmetric structures. Its capabilities and performance for the generation of complex constructs are evaluated, and possible areas of improvement described. The second application, but not less important, involves the structural analysis of patient-derived protein mutants using protein modelling techniques and visualization tools, to elucidate the potential molecular basis for the patient’s phenotype. The methodology for these analyses is described, along with the results and observations from 22 such cases in 13 different proteins. Finally, the need for a dedicated pipeline for the structure-based prediction of the effect of different types of mutations on the stability and function of proteins, complementary to available sequence-based approaches, is highlighted.

Atrial fibrillation, long QT syndrome, and Middle East Respiratory Syndrome are three deadly human diseases for which genetic animal models are needed. From elucidating disease pathogenesis to facilitating the development of treatments, animal models are crucial for studying human disease. One of the most effective ways to generate specific animal models is through genetic modification. Historically, mice have been most widely used as genetically modified models, despite a number of limitations. New gene editing technologies such as CRISPR/Cas9 have made developing alternative genetic models that better recapitulate some human diseases better and more feasible. In this thesis, I describe my efforts to develop genetically modified goat and hamster models for atrial fibrillation and long QT syndrome, and genetically modified hamster models for Middle East Respiratory Syndrome. For long QT syndrome model development, I knocked out the KCNQ1 gene in goat fetal fibroblast cells and baby hamster kidney cells using the CRIPSR/Cas9 system. The knockout results in loss-of-function mutations, a known cause of human long QT syndrome. The edited goat fibroblast cells will be nuclear donors for future cloning experiments to produce live goats possessing the KCNQ1 knockout. The CRISPR gene targeting sgRNA/Cas9 vector, specific for the hamster KCNQ1, has been used for pronuclear injections to produce KCNQ1 knockout hamsters. For atrial fibrillation model development, I designed a single-stranded donor oligonucleotide that generates a KCNQ1 gainof-function mutation resulting in the disease. This oligonucleotide was injected into hamster embryos along with the KCNQ1 sgRNA/Cas9-expressing vector to generate hamsters containing the gain-of-function mutation. Finally, for Middle East Respiratory Syndrome model development, I established a breeding colony of human DPP4 transgenic hamsters in the STAT2 knockout background. Human DPP4 transgenic hamsters are susceptible to MERS-CoV infection, showing mild clinical signs and allowing viral replication in lung tissue. Giving these hamsters a STAT2 knockout background should promote a more severe disease progression. For all three diseases, the foundations for the development of genetic animal models have been laid.