Dynamics and evolution of influenza strain variation
Professor Rustom Antia (Emory University) is the Lead on Research Project 4.
The Investigators are based at Emory University, FHCRC, University of Washington, University of Florida, and Duke University.
The overall objective of this research is to understand how diseases of public health relevance exhibit continual evolution by generating new strains which change key regions (epitopes) recognized by the immune system, allowing these new strains to infect some of the individuals with immunity to previous strains. The model virus in the initial research will be influenza, with plans for extension into dengue.
- To uncover the relationship between antigenic evolution and molecular constraints on viral evolution. This research will develop an experimentally motivated framework for modeling constraints on antigenic evolution by the capacity of protein antigens to tolerate antigenic mutations. This framework will be used to address why some viral epitopes are largely conserved, while others are highly variable.
- To understand how the within-host dynamics of infection change as individuals are exposed to new strains circulating in the population, and as well as following vaccination. Within-host models describing immune responses to influenza will be extended to include strain variation. This will involve developing models of how the generation of B and T cell responses interacts with viral evolution, considering conserved compared to variable viral epitopes. These models will be used to determine how pre-existing immunity to earlier virus strains affects the dynamics of infections with new virus strains. They will also be used to generate new strategies for designing vaccines against influenza.
- To develop epidemiological models of varying complexity to gain an improved understanding of influenza dynamics at the level of the population. These models will incorporate molecular constraints as well as complex immunological interactions between strains, based on the quantitative findings from objectives 1 and 2. We will further determine whether the rate of influenza's antigenic evolution is primarily limited by mutational constraints or by selective processes by interfacing simulations of these models with genetic and epidemiological data. This determination will enable us to qualitatively predict how antiviral drugs and vaccination strategies will impact influenza's ecological and evolutionary dynamics. For quantitative prediction, we will integrate these intervention strategies into our epidemiological models.