Iris Holmes

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My lab studies the interactions between host and microbial communities across changing landscapes. We are particularly interested in the processes that allow microbes to jump to new hosts. Pandemic pathogen emergence is one example of a microbial host jump that can have huge consequences. We use ecological and evolutionary tools to answer questions like:

 

1. What makes a host species more or less likely to be infected by a novel microbe?

2. Which traits predict a microbes’ ability to survive and spread to new hosts?

3. What environmental conditions lead to higher rates of microbes infecting novel host species?

 

We use interactions between full host and microbial communities to both increase statistical power and to capture emergent effects of community interactions. Pandemic pathogen emergences are very rare, which makes identifying risk factors a challenge. Looking at the ecological predictors and evolutionary consequences of all microbial host jumps creates a more robust dataset and also allows us to determine whether pathogen host jumps differ from host jumps by non-pathogenic microbes.

 

Natural processes – like climatic events and habitat disturbance – may microbes more likely to occupy novel hosts. However, unpicking these drivers using large-scale data from many sources requires understanding potential biases in reporting spillover events. Our lab uses comparisons between recently disturbed and intact habitats to quantify the impacts of disturbance on microbial community assembly, host range, and evolutionary trajectories.

 

We also use large-scale pathogen and microbial datasets to understand how the processes we study generalize across space and time. These datasets integrate records of pathogen occurrence from many sources; the strategies that determine whether a pathogen will be identified and reported can vary from place to place due to local policy decisions. We work with political scientists to identify and correct for variation in reporting rates of pathogen spillover across space and time. Ultimately, our work can inform policy by identifying the land use practices that reduce the risk of pathogen spillover.