The spread of any infectious agent, including HIV, is caused by a multitude of factors including epidemiological, demographic, and biological. We have several on-going studies that attempt to tease apart these factors by modeling the evolutionary dynamics of the HIV epidemics in Baltimore, Florida, and East/Central Africa. Large studies such as these require database development, massive sequence alignments and significant computational resources and skills.
Rapidly evolving viruses like HIV can compartmentalize in host cells or tissues where they can evade drug therapy. We use viruses sampled over time and within different anatomical compartments to identify how and when the virus evolves within an individual. These studies use time-rooted phylogenies and measure biologically important properties of the virus including selection pressures and structural variation.
Although current anti-HIV therapy significantly reduces the risk of AIDS, many HIV-infected individuals will develop HIV-associated co-morbidities such as atherosclerosis, neurological disease and a variety of cancers. This trend suggests a link between viral-associated inflammation and disease. We investigate the associations between viral genetic variants and their evolutionary trajectories during the development of these pathologies. These studies combine our bioinformatics background with our understanding of pathology and immunology.
Although large-scale genetic sequence data has become a standard in many fields of biology, methods and software for analyzing such data are have not kept pace. We are actively addressing this challenge through development of software applications that are user-friendly, intuitive, and widely adaptable to most datasets and computational platforms.
Because of our considerable access to skilled genetic laboratory technicians, equipment, and biological specimens from our collaborations, we are also developing novel laboratory techniques that can help answer outstanding questions and assist in big-data analysis.