• Shou Group 2014 
  • Cross-section of a yeast community by Babak Momeni 
  • Photo of Mount Rainier by Richard Mitchell 
  • Flocculating yeast by Aric Capel 
  • Photo of the Hutch and Lake Union by Richard Mitchell 
  • Shou Group 2011 

 

The web of life is weaved from diverse symbiotic interactions between species. Symbioses vary from antagonistic interactions such as competition and predation to beneficial interactions such as mutualism. Symbioses not only impact our ecosystems, but also directly shape our health: the mutualistic symbiosis between us and gut microbes can influence our body weight; the antagonistic symbiosis between us and parasites can shape our immune system.

What are the bases for the origin and persistence of symbiosis? What affects the ecology and evolution of symbioses? How do symbiotic interactions generate ecological patterns? How do symbiotic partners evolve and co-evolve? To address these fundamental biological questions, we can choose among different classes of model systems.

The trade-offs among different systems.
The trade-offs among different systems.

We can study natural systems in their natural environments, but the complexity can be prohibitive and lessons learned from one system may not be generalizable to other systems. Alternatively, we can study simplified natural systems obtained through, for instance, enrichment culturing to select for microbial subcommunities capable of performing a specific function such as cellulose degradation. We can also engineer symbioses among model organisms using the powerful molecular and genetic tools developed over the past few decades. Finally, we can use mathematical models to capture intricate biological networks and perform "experiments" that would otherwise be impossible to carry out. The tradeoff between complexity and controllability among these different classes of model systems is apparent. Our lab uses a variety of these systems to explore the ecology and evolution of symbiosis.

We welcome undergraduate students, PhD candidates, and postdoctoral fellows with a strong background in one or a combination of the following fields: biology, physics, mathematics, engineering, and computer sciences.

Subscribe to The Quantitative Biology Group at the Fred Hutchinson Cancer Research Center RSS