Transmission and coevolutionary dynamics drive the evolution of generalist and specialist viruses

Viruses show tremendous diversity in the hosts that they attack - both generalists and specialists are common in nature. Unlike specialists, generalist viruses are able to infect a range host species, whereas specialists infect a single host type. What explains this variation in the types of interactions between hosts and their viruses? How do viruses and their hosts interact? Can the way they interact evolve over time? Answers to these questions are central to understanding the dynamics of disease. The underlying processes governing viral-host interactions are highly complex - ranging from molecular and cellular through to population and multi-trophic levels - and crucially depend on the interplay between ecology and coevolution, a process of simultaneous evolution of hosts and viruses in response to each other. However, this complexity presents numerous challenges to achieving a mechanistic understanding of disease dynamics.

The proposed research will investigate the evolution of specialist and generalist viruses - from genes to cells to populations to the community. It will consider how hosts and viruses evolve simultaneously and in response to each other, paying particular attention to how viruses are transmitted. The novel approach proposed here will intertwine experimental evolution and mathematical models, using the bacteria, Escherichia coli and viruses that attack bacteria, bacteriophages, as a model system that can help us understand virus evolution in nature. Experiments will document coevolution in real-time and directly test theoretical predictions put forth by the theoretical framework. At the same time, data generated from the experiments will be incorporated into a new generation of mathematical models that will provide a range of both specific and general predictions regarding the evolution of specialist and generalist viruses. The results of this work will further our general understanding of the dynamics of disease.

Viruses show tremendous diversity in host-use strategies - both generalists and specialists are common in nature - thus the questions of how, when and why these strategies evolve have long intrigued epidemiologists. Yet, the causal mechanisms underlying the evolution of generalist and specialist viruses remain unclear.

We will use a pioneering combination of experimental evolution (with E.coli-lambdavir and E.coli-T3 systems) and mathematical modeling across multiple biological scales to investigate (a) molecular and environmental basis for variation in viral-host interactions; (b) if these interactions change over the course of coevolution; and (c) the effects of transmission dynamics on evolutionary change. The mathematical and experimental approaches will be developed in parallel, merging recent eco-evolutionary theory and epidemiology to advance our understanding of the dynamics of infectious disease in novel directions. A key component of our approach is the ability to provide a general understanding of the ecology and evolutionary of viral-host dynamics beyond our specific study system (Forde et al. 2008).

Our project combines the following innovative approaches:

1. A mathematical modeling framework designed to bridge the gap between laboratory experiments and the dynamics of naturally occurring diseases.
2. An experimental evolution approach that will allow us to manipulate evolution of viral infection strategies using bioengineering to directly test our theoretical predictions.

Our interdisciplinary approach of combining molecular details of viral-host interactions into an ecological and coevolutionary framework will provide new insights into long-standing questions of the role of transmission dynamics in the evolution of viral infection strategies, and critically inform research in natural viral-host systems.

The proposed research will be of exceptionally broad interest. Naturally, it will be of interest to those working epidemiology and the evolution of virulence, where more general infection models are usually assumed. In addition, explicitly addressing the coevolutionary dynamics of infectious disease is becoming a leading approach in biomedical research, with applications ranging from reliable molecular diagnostics to monitoring pathogenicity. Our results will provide the biomedical and epidemiological communities with data based on precisely modelled interactions between hosts and viruses that are experimentally verified. Our results will improve public health initiatives through increasing our understanding of the ecology and evolution underlying pathogen infection strategies.

The proposed research provides a middle ground between the relative simplicity of current mathematical models and the complexity of field studies, and thus will allow us to identify those components of both theory and empirical work that are likely to be generalisable to other host-viral systems. Furthermore, our results will be of interest to those working in ecology and evolution, and host-parasite interactions in general. In addition, the proposed work will provide a better understanding regarding the ecology and evolution of microbes. Microorganisms are ubiquitous, abundant and mediate environmental processes of great importance.