DESCRIPTION (provided by applicant): This application focuses upon the Apicomplexa, etiologic agents of many diseases in the developing world and relevant to global health (thematic area 4). It uses genomics and other high throughput technologies (thematic area 1) with a systems-level integration, analysis and mining of large datasets with the overarching goal of translating our discoveries into new insights into therapy and disease prevention (thematic area 2). To accomplish our goals, we have assembled a multidisciplinary collaborative team with expertise in infectious diseases, diabetes, metabolism, pathology, molecular biology, animal models and pathophysiology to conduct an innovative study in challenging biomedical areas (thematic area 5). As major emerging and reemerging pathogens, Apicomplexan parasites infect more than a third of the world's population. These obligate intracellular parasites include Toxoplasma gondii, Plasmodium species and Cryptosporidium. Toxoplasma gondii is a major opportunistic pathogen of the AIDS epidemic, a cause of birth defects and is also a Category B priority agent due to its association with waterborne outbreaks. Plasmodium species, the agents of malaria, infect over 267 million people per year and cause nearly 1 million deaths per year. Despite the importance of these parasites in human disease, there are no effective vaccines for these pathogens, and new strategies for treatment and prevention of disease are needed. Very little is understood how the Apicomplexa regulate virulence traits and respond to changes in their environment. The development of new high-throughput technologies has enabled collection of large genomic and proteomics datasets. These can be used to develop an integrated understanding of how eukaryotic cells regulate gene expression. We will take advantage of genome manipulation, genome-wide arrays, high throughput sequencing, and proteomics to develop datasets that will facilitate an integrated systems approach to understanding regulation of gene expression and epigenetics in the model apicomplexan T.gondii. We will test the essentiality of chromatin remodellers and candidate transcription factors using a moderate through-put gene disruption strategy. Using epitope tagged chromatin remodelers and transcription factors, we will use high throughput sequencing of chromatin immunoprecipitates and expression microarrays to identify groups of co-regulated genes. Finally, we will perform high-throughput proteomics to characterize the constituents of macromolecular complexes involved in regulation of gene expression. These epigenomic, transcriptome, and proteomic datasets will facilitate computational approaches to model how epigenetic and genetic factors in the Apicomplexa interact within gene networks. This effort will create important community resources to enable a systems biology approach toward understanding expression of virulence traits and identification of novel drug targets for apicomplexan parasites. PUBLIC HEALTH RELEVANCE: Toxoplasma gondii is a parasitic pathogen that causes severe disease in immunocompromised individuals including people with AIDS, causes birth defects, and is a Biodefense Category B pathogen due to its association with waterborne outbreaks. Finally it is a model system for other parasites like Plasmodium, which cause human malaria. These parasites affect over a third of the world's population. We are trying to generate large datasets that will help us understand how these parasitic pathogens change in response to interaction with human hosts and how they regulate genes that cause disease. These data take advantage of genome sequencing projects and will use new powerful high throughput technologies. Gathering these data will be important for developing new treatments that will prevent T. gondii from persisting in infected people, and understanding how Apicomplexan parasites cause disease.
|Effective start/end date||9/30/10 → 9/29/13|
- Immunology and Microbiology(all)
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.