No description available.

No description available.

No description available.

This thesis represents two lines of investigation that as a whole integrate physiology and ecology of infectious diseases. While each chapter is a distinct body of work, these studies are linked in that both focus on extrinsic or intrinsic factors influencing hosts’ susceptibility to infection, as well as hosts’ potential to transmit disease. In chapter one, I used a meta-analysis as a tool to review what is known about the stress-linked susceptibility hypothesis, which poses that persistent activation of the stress axis might result in increased disease susceptibility in wild animals, mainly as a result of allostatic overload and the immunosuppressive actions of stress hormones. My goal in evaluating the strength of association between distinct stressors and health indices in wildlife populations was manifold. First, I wanted to investigate which specific stressors are more likely to increase disease susceptibility in wild animals. Second, I was interested in the reliability of stress biomarkers as indicators of stress-induced immunosuppression or disease susceptibility. Finally, I used this chapter as a bridge for my second chapter by addressing how “fast-paced” and “slow-paced” phenotypes within wild populations cope differently with stressors, thus also differentially altering epizootic risk. My meta-analysis indicated that the highly variable outcomes of ecological studies can be attributed to several factors, ranging from possible erroneous classification of stimuli as physiological stressors to a lack of consensus on the endocrine profiles of stressed animals. The second chapter of this work consists of an empirical investigation of the pace-of-life (POL) hypothesis in the context of host disease susceptibility and transmissibility. Individuals with a fast-paced life history often exhibit relatively high metabolic rates and investment in growth, development, and reproduction. To support these faster rates, they often exhibit decreased investment in immunity, as well as associated bold behaviors for increased foraging and competiveness to ensure access to resources. These associated functional physiological and behavioral traits likely also influence exposure and susceptibility to pathogens, and infectiousness; factors central to disease dynamics. Through transmission trials using ranavirus and larval amphibians as a model system, I found that repeatable latency-to-food profiles of larval hosts, which characterize a POL axis associated with development and metabolic rates, were predictive of individual susceptibility and infectiousness. Faster-paced larval amphibians had greater exposure to pathogens (contacts), higher risk of infection (susceptibility), and shed greater pathogen populations when infected. Through these findings, I argue that The POL framework can allow for a priori identification of individual hosts that are more likely to spread infectious disease and may provide insight into understanding and potentially managing disease outbreaks that threaten wildlife and humans alike.

Cultivation in the laboratory is essential for understanding the phenotypic characteristics and environmental preferences of bacteria. However, basic phenotypic information is not readily accessible. Here, we compiled phenotypic and environmental tolerance information for > 5,000 bacterial strains described in the International Journal of Systematic and Evolutionary Microbiology (IJSEM) with all information made publicly available in an updatable database. Although the data span 23 different bacterial phyla, most entries described aerobic, mesophilic, neutrophilic strains from Proteobacteria (mainly Alpha-and Gammaproteobacteria), Actinobacteria, Firmicutes, and Bacteroidetes isolated from soils, marine habitats, and plants. Most of the routinely measured traits tended to show a significant phylogenetic signal, although this signal was weak for environmental preferences. We demonstrated how this database could be used to link genomic attributes to differences in pH and salinity optima. We found that adaptations to high salinity or high-pH conditions are related to cell surface transporter genes, along with previously uncharacterized genes that might play a role in regulating environmental tolerances. Together, this work highlights the utility of this database for associating bacterial taxonomy, phylogeny, or specific genes to measured phenotypic traits and emphasizes the need for more comprehensive and consistent measurements of traits across a broader diversity of bacteria. IMPORTANCE Cultivation in the laboratory is key for understanding the phenotypic characteristics, growth requirements, metabolism, and environmental preferences of bacteria. However, oftentimes, phenotypic information is not easily accessible. Here, we compiled phenotypic and environmental tolerance information for > 5,000 bacterial strains described in the International Journal of Systematic and Evolutionary Microbiology (IJSEM). We demonstrate how this database can be used to link bacterial taxonomy, phylogeny, or specific genes to measured phenotypic traits and environmental preferences. The phenotypic database can be freely accessed (https://doi.org/10.6084/m9.figshare.472392), and we have included instructions for researchers interested in adding new entries or curating existing ones.

Pleiotropy refers to the shared effects of a gene or genes on multiple phenotypes, a major reason for genetic correlation between phenotypes. For example, for osteoporosis, bone mineral densities at different skeletal sites may share common genetic factors; thus, examining the shared effects of genes may enable more effective fracture treatments. To date, methods are not available for estimating and testing the pleiotropic effects of single nucleotide polymorphisms (SNPs) in genetic association studies. In this dissertation, we explore two types of methods to evaluate the SNP-specific pleiotropic effect based on multivariate techniques. First, we propose two approaches based on variance components (VC) analysis for family-based studies, which quantify and test the pleiotropic effect by examining the contribution of specific genetic marker(s) to polygenic correlation or covariance of traits. Second, we propose a multivariate linear regression approach for population-based studies with samples of families or unrelated subjects. This method partitions the specific effect of the marker(s) from phenotypic covariance. We evaluate the performance of our proposed methods in simulation studies, compare them to existing multivariate analysis methods and illustrate their application using real data to assess candidate SNPs for osteoporosis-related phenotypes in the Framingham Osteoporosis Study. In contrast to existing methods, our newly proposed approaches allow the quantification of pleiotropic effects. The bootstrap resampling percentile method is used to construct confidence intervals for statistical hypothesis testing. Simulation results suggest that the VC-based approaches are affected by the polygenic correlation level. The covariance analysis approach outperforms the VC-based approaches, with unbiased estimates and better power, which remain consistent regardless of the polygenic correlation. In addition, the covariance analysis approach is simple to implement and can be applied to both family data and genetically unrelated data. Using simulation, we also show that existing methods, such as MANOVA, can have high rejection rates when a SNP has a large effect on a single trait, which prevent us from using them for pleiotropic effect analysis. In summary, this dissertation introduces promising new approaches in multiple phenotypic models for SNP-specific pleiotropic effect.

No description available.

This thesis describes the cloning and characterisation of two <I>Candida albicans</I> genes which were candidates for having a role in the phenotypic switching phenomenon of <I>C. albicans</I>. Phenotypic switching in <I>C. albicans</I> is a spontaneously occurring event whereby the surface morphology and several physiological processes of the <I>C. albicans</I> colony can change. These spontaneous switching events occur at high frequency and there are a range of up to fifteen different morphological forms that have been described. Switching is reversible and interconvertible (between the different phenotypes). The candidate genes chosen to investigate phenotypic switching were <I>RAD52</I>, a DNA double strand break repair gene and <I>H4</I>, a histone. <I>RAD52</I> was isolated following homologous probing of a <I>C. albicans</I> genomic library using a fragment of the gene sequence which was available on a public data base [http://alces.med.umn.edu/candida/html], as a probe. <I>H4</I> was isolated following PCR probing of a cosmid library. The switching repertoire of the <I>ura</I>- CAI4 strain of <I>C. albicans</I> was characterised. Attempts were also made to characterise switching frequencies. This strain was then used as the host for both knockout and overexpression studies of the candidate genes. The effect of overexpression of these genes on phenotypic switching was observed by recording growth rates, phenotypes and phenotypic switching frequencies. It was found that overexpression of <I>RAD52</I> affected the morphotype and growth of the yeast colonies compared the CAI4 parental strain. Overexpression of the H4 gene did not appear to affect growth, but a fourth morphological form named "root" appeared that had not arisen during characterisation of the CAI4 phenotypic switching repertoire. The degree to which the "root" phenotype was manifest appeared to correlate with the degree of overexpression of the <I>H4</I> gene. The effect of knocking out a single copy of <I>H4</I> was also observed. Growth was not affected. Observations of colony morphologies showed a preponderance of one particular morphology ("irregular wrinkle"). This data suggests that altering the wild type levels of expression of these genes can affect phenotypic switching in <I>C. albicans</I>.

The genetic basis of the different cancer phenotypes has been a continuous and accelerating subject of investigation. Data accumulated thanks to recently introduced genome-wide scanning technologies have revealed that human diversity and diseases susceptibility is also greatly influenced by structural alterations in the human genome, such as DNA copy number variants (CNVs) and copy number alterations (CNAs), which influence gene expression in both healthy and pathological cells. Our research aims to investigate the influence of structural alterations on gene expression in cancer cells using SNP microarray data. Specifically, we focus on analyzing DNA copy number alternations (CNAs), which can significantly influence gene expression in cancer cells. Several cancer-predisposing mutations affect genes that are responsible for maintaining the integrity of the chromosomes during cell division, which can result in translocations, gains or losses of large parts of chromosome. To our knowledge, there have been no publications that link whole-genome copy number alterations in cancer to gene expression variations using the full range of possibilities offered by SNP arrays. The accurate use of SNP arrays in the analysis of cancer has been difficult due to tumour purity, tumour heterogeneity, aneuploidy/polyploidy and complex patterns of CNA and loss-of-heterozygosity (LOH). In our work, we use and further extend a recently developed novel tool for tumour genome profiling called OncoSNP (Yau, Mouradov et al. 2010), in order to resolve some of those problems and accurately estimate copy number alterations (CNA) and loss-of-heterozygosity (LOH) from SNP array data in cancer cell samples. The methods developed in this thesis tackle the problem of cancer genomic investigation by developing and validating an extension (DPS smoothing) of a new method (OncoSNP). This approach is used in the analysis of global expression versus CNA patterns in experimental systems and large clinical datasets. We analyse various cancer SNP and gene expression arrays of increasing complexity and heterogeneity, starting with a dataset of head and neck squamous cell carcinoma (HNSCC) cell lines, followed by leukaemia samples and finally a large breast cancer dataset. The central findings of our research are multifold. In the HNSCC dataset we find that the level of genetic instability is not indicative of the pathological state; i.e. there are premalignant lesions displaying extensive mutations. However some genetic features are typical of certain lesion type; e.g. we consistently observe copy loss in the short arm of chromosome 3 in carcinoma. The pattern of homozygous deletion in the dataset reveals common deletion of cancer related genes, especially CDK4 (pI6). Furthermore we notice a significant positive correlation between the copy number and the expression on a systematic level. In Leukaemia, we do not observe extended uniparental disomy as previously published (Akagi, Shih et al. 2009) and expected. However large alterations (whole arm amplification) are observed in individual patients: copy loss in chromosome 7 (2 patients), copy gain in chromosome 8 (3 patients) as well as common alterations around the centromeres and telomeres. In the breast cancer dataset significantly different level of mutations were observed in the different subtypes in the cohort. Furthermore 499 genes were identified with significant correlation between their gene expression (GE) and underlying genomic alterations (either copy number (CN) or loss-of-heterozygosity (LOH)). Performing hierarchical clustering on the cohort using the 499 correlated genes enabled us to recover the subtypes' separation previously based on gene expression alone.

Severe malaria caused by Plasmodium falciparum (P. falciparum) remains a leading cause of death in many low and middle income countries. The intraerythrocytic reproduction cycle of the parasite is responsible for all the symptoms and mortality of malaria. The merozoite, first invade a red blood cell (RBC) in the circulation, then grows, develops and multiplies within it by clonal division. Merozoite invasion is a complex process involving dynamic interactions between ligands in the merozoite coat and receptors on the red blood cell membrane. Therefore, filming the complete malaria invasion processes may shed the light on its mechanism. The rationale of this work is that learning how the various ligand-receptor interactions affect invasion phenotypes will lead us to a better understanding of the key biological and biophysical aspects of parasite growth in the blood. The work described has firstly involved the development of an optimised imaging platform for recording egress-invasion sequences. I used live cell microscopy to understand this stage of malarial infection better, by monitoring egress-invasion sequences in live cultures under controlled conditions and addressing the morphology and kinetics of erythrocyte invasion by P. falciparum. In addition, the erythrocyte invasion phenotypes of the various P. falciparum strains were systematically investigated for the first time by live cell microscopy. Furthermore, to better understand genetic recombination affecting erythrocyte invasion phenotypes, progeny from the 7G8 x GB4 cross was compared to their parents. In order to investigate specific receptor-ligand interactions and their distinct functional characterisations at each distinct stage, the enzymes that cleave receptors on the erythrocytes and antibodies targeting ligands on the merozoites were studied and their effects observed using the live-imaging platform. In the results, the functions of ligands on the merozoites demonstrated for the first time distinct and sequential functions of proteins during erythrocyte invasion, which could potentially guide the design of more effective malaria vaccines. In addition, I have designed microfluidic devices for studying blood stage malaria. Polydimethylsiloxane (PDMS) microfluidic devices are optically transparent, non-toxic and have biocompatible features. Building on previous work, I made specific microfluidic devices for achieving a high throughput of egress-invasion observations. Infected red blood cells were delivered into a microfluidic device channel containing cage-like "nests". The nests were designed to selectively trap these stiff, egress-ready cells, in order to obtain streams of merozoites on maturation. Uninfected RBCs were delivered from another input into a long serpentine channel co-flowing with the egressed merozoites. The results indicated that, during P. falciparum erythrocyte invasion under flow conditions, the morphological effect on erythrocytes and the kinetic properties show significant differences to those in static conditions. In addition, with optimised flow rates, it is possible to reach higher throughput of egress-invasion observations than static conditions. Both the static and flow experiments carried out in this study highlight important mechanisms and processes of malaria invasion, and represent new ways of studying blood stage malaria. Precise and high throughout recording of single-event host-pathogen interaction events will allow us to address a new area of fundamental biological questions in future work.