The University of California at Irvine MIDAS team will develop computational models to study the molecular basis of viral evolution. Questions the researchers will ask include:
- What sorts of changes in molecular shape and charge evolve during viral evolution to a new host?
- What is the best vaccination strategy against evolving viruses, moving targets for control by vaccination?
- What processes allow different strains of a pathogen to co-circulate in a host population or cause one strain to outcompete and replace the others?
The team initially will base their models on the extensive molecular data available from influenza surveillance. This approach allows the researchers to model the connections between molecular change and the evolutionary dynamics of populations in a realistic way. Extensive empirical study of influenza also allows them to make testable predictions that can be evaluated in the coming years. As model development progresses, the researchers will extend their approach to other pathogens.
The models will be designed to make predictions about the relative danger of emerging viral strains. These predictions will be useful in evaluating surveillance data for potential cross-species transfers and in designing vaccines to control pathogens that evolve to escape host immunity.
The research will have three specific aims:
- To better understand how pathogens adapt to new hosts. The team will use structural homology modeling to analyze the molecular changes in influenza that occurred during and immediately after transfer from birds to humans. The particular molecular adaptations in past transfers allow the scientists to develop predictive models for the relative danger posed by existing avian viruses or new viral introductions to humans. These studies of influenza will provide the basis for studying other potentially dangerous zoonotic diseases.
- To predict the optimal vaccination strategy against a rapidly evolving virus. The researchers will use their prior success in predicting influenza evolution to evaluate the gain in vaccinating against future predicted strains.
- To study the interference competition between co-circulating pathogen strains. The team will develop mathematical and computer models to study the conditions that maintain co-circulating pathogen strains and the conditions that favor one strain to replace another. The researchers will evaluate whether interference competition between strains mediated by cross-reactive host immunity can explain the observed patterns of fluctuating influenza strains. Their computational models will help predict when new strains may arise and outcompete current strains.
Co-Principal Investigators: Steven Frank, Ph.D., of the University of California, Irvine and Nancy Cox, Ph.D., Chief of the Influenza Branch, US Centers for Disease Control and Prevention
