Research

Phylodynamics of infectious pathogens

Research in the group is largely focused on developing new phylogenetic methods for tracking the spread of infectious diseases using pathogen sequence data. These methods are built on phylodynamic models that relate the transmission dynamics of a pathogen to the branching pattern of a pathogen’s phylogenetic tree. Because epidemic dynamics strongly shape the phylogenetic history of a pathogen, we can use phylogenies to reconstruct the spread of pathogens over time, through space and between different host populations. Phylogenies also often contain information about the source of new infections in a host population, which is mostly absent from traditional epidemiological data such as case reports.

Phylodynamics has already been applied to study the transmission dynamics of many human viruses such as dengue, influenza and HIV. At NC State, we plan to improve and adapt phylodynamic methods to study agricultural pathogens in plants and animals. Because each pathogen has its own unique natural history, new phylodynamic models are required to relate the ecological and evolutionary dynamics of these pathogens to their phylogenetic history. For instance, for a plant fungal pathogen, spatial variation in environmental conditions like humidity might be a key factor limiting spread. Incorporating geospatial information about environmental conditions into our phylodynamic models is therefore necessary, and is a primary goal of ongoing work.

Phylodynamics in an adaptive world

Microbial pathogens rapidly evolve to escape host defenses and can adapt to novel hosts, as evidenced by the continual emergence of new pathogens in humans and other species. Yet almost all current phylogenetic methods assume evolution at the sequence level is neutral and that new mutations do not impact the fitness of lineages in a phylogeny. Because this assumption is obviously unrealistic, we are extending phylodynamic models to consider adaptive molecular evolution at the sequence level. In particular, we are developing new methods for estimating the fitness effects of individual mutations from their impact on the shape of pathogen phylogenies. We then hope to be able to use to these methods to identify the causal mutations driving pathogen adaptation to selective pressures such as antimicrobial drugs, host immune responses and novel host environments.

Phylogeny showing the sequence of mutations by which Ebola virus adapted to humans in the West African epidemic of 2013-16. Lineages are colored according to their inferred relative fitness.

Experimental viral evolution and pathogen emergence

To remain viable, pathogens must adapt to constantly changing environments within and between hosts, including jumps to entirely new host species. At the same time, experimental evolution studies in microbes have mainly investigated adaptation to constant environments. While these studies have provided remarkable insights into the genetic basis of adaptation, we know far less about adaptation to highly variable environments and novel hosts.

We are therefore studying adaption to varying host environments using experimental evolution studies in plant viruses, such as Tomato spotted wilt virus. Studying viral adaptation in the lab will allow us to carefully manipulate movement between different plant hosts and vectors, as well as track viral evolution by periodically re-sequencing the viral population. Questions we are interested in addressing include:

  • Do fitness tradeoffs between environments constrain adaptation and the emergence of generalist pathogens?
  • Can selection resolve fitness tradeoffs between different hosts environments (i.e. antagonistic pleiotropy)?
  • Is adaptation to changing environments limited by the supply of new mutations?
  • Can genetic architecture itself evolve over time to facilitate adaptation to new host environments? 
    TSWV infected and uninfected <em>Emilia</em> leaves (left) and <em>Datura</em> plants (right) in an experiment passaging virus between alternate host plants (Photo credit: Brian Bonville)