The goal of the infectious disease genomics program in the Center for Genes, Environment and Health is to utilize the tools of modern genomics and bioinformatics to investigate clinically relevant infectious disease pathogens at the genome, transcriptome, and proteome levels, as well as to expand our understanding of the human response to infectious disease. By expanding our understanding of infectious disease pathogens and our human response to pathogens, we will be able to devise more effective strategies to identify, monitor and combat disease.
Whole Genome Sequencing of Pathogenic
We are conducting whole genome sequencing of clinically relevant pathogenic micro-organisms using the SOLiD, 454, and IonTorrent next generation sequencing platforms. These studies allow us to identify and investigate genetic polymorphisms, including single nucleotide polymorphisms (snps), indels, genomic duplications, and genomic rearrangements that may contribute to phenotypic traits ranging from increased virulence to drug resistance. These studies have also enabled us to identify regions of variation among closely related species that may be used for improved diagnostic classifications.
Transcriptome Profiling of Humans and Pathogens
Investigators in the Center for Genes, Environment and Health are collaborating on a number of projects investigating human and pathogen transcriptional profiles. These studies are aimed at increasing our understanding of the transcriptome of clinically relevant pathogens during infection, as well as the human response to pathogen insults. These studies will help us not only to expand our understanding of the human transcriptional response to pathogenic microorganisms, but also will be used to identify novel biomarkers to identify disease, monitor progression of disease, and assess the effectiveness of therapeutic interventions. We also hope that these experiments will help us devise novel strategies to better combat infectious disease pathogens.
Human and Pathogen Networks
Building on combined experimental and computational information, we are working to develop improved methods and new visualization strategies to examine genome-wide biomolecular networks in humans and human pathogens. These studies help us identify and investigate important features of the molecular circuitry of life, and serve as a scaffold for interpreting genomic, proteomic, and metabolomic studies. We are also very interested in using network analysis to better understand gene-disease-chemical relationships important to a variety of respiratory diseases.
We are complementing our whole genome sequencing efforts with computational methods to examine newly identified polymorphisms at the protein structure level. Among our interests, are investigating mutations that confer drug resistance and contribute to virulence. These methods complement experimental strategies, such as X-ray crystallography and NMR, by utilizing computational tools for homology modeling and small molecule docking.