Research Project
7104890
DESCRIPTION: The human oral cavity is home to a complex community of >700 microorganisms with a central role in oral health and disease. In our application, this oral microbial community, or oral microbiome, is viewed as a single dynamic entity, with variation in its behavior and composition across space (different oral niches in different individuals), time, and with perturbation. Despite the critical importance of this community in maintaining human health and provoking oral disease, the genetic basis for its behavior has not been well explored. The long-term objectives of this application are to develop a comprehensive understanding of the oral microbial community at the genomic level so that oral health can be promoted, and disease ameliorated or prevented. We will address these goals by characterizing relative gene and genome abundance and gene expression in the oral microbiome in subjects with healthy periodontal and mucosal tissues, and then extend our analysis to the oral microbiome associated with chronic periodontal diseases. Data from this application will not only be used to build a database for genes in the oral microbiome, but will also lead to new experimental paradigms for exploring gene abundance and expression, and examining the interaction of the microbiome with the human host. The Specific Aims of this application are: Aim 1. Characterize the gene and genome content of the healthy human oral microbiome. Our approaches include high-throughput sequencing of random and targeted plasmid and fosmid genomic libraries and classification of functional genes and gene families. Aim 2. Characterize the gene and genome content of the oral microbiome associated with chronic periodontitis. Aim 3. Development of community genomic tools for oral microbiome data. An oral microbiome gene database will be created for use by the scientific community. A high-density DNA microarray with approximately 2,000 genes identified in Aims 1 and 2 will be developed with the ultimate goal of identifying patterns of gene abundance and expression that predict clinical natural history and response to manipulation. Among the expected long-term benefits of this work will be a revolutionized understanding of the human oral ecosystem and new approaches for classification and management of oral diseases.
