The Koskella lab at UC Berkeley seeks to understand how interactions among species generate and maintain much of the diversity we see on earth. For more information on ongoing research projects, look here.
PI: Britt Koskella
I am an evolutionary ecologist interested in how species interactions influence genetic diversity within populations, diversity between populations, and species diversity at the community level. By combining evolutionary theory on coevolution, population dynamics, and infection genetics, I directly test the underlying assumptions and predicted outcomes of host-pathogen and microbial interactions through the lens of complex environmental change and the importance of agricultural sustainability.
My work has been primarily on host – parasite coevolution. First between a smut fungus and a plant (e.g. how pathogen relatedness affects the outcome of coinfection), then a trematode and a snail (e.g. whether parasites mediate negative frequency dependent selection), and now between bacteriophage viruses and the bacteria they infect, which are themselves parasites of plants (e.g. if phages are locally adapted to bacteria, and coevolving with bacterial hosts over time). The types of questions I address are:
1) Are pathogens/parasites adapting to better infect their hosts? If so, at what scale and at what speed are they adapting?
2) Are hosts responding to this adaptation (in other words, coevolving) by becoming more resistant to their local pathogens/parasites? If so, are they paying a significant cost for this resistance?
3) Can this coevolution lead to increased diversity? For example, are pathogens/parasites preferentially targeting common hosts (i.e. the hosts that are the most fit) and therefore imposing a rare-host advantage? Or are pathogens/parasites from one host population driving their hosts in a different direction than parasites from another host population?
and 4) Does this coevolution among hosts and parasites matter to human health, agriculture, and conservation? Can we use our understanding about when and how pathogens/parasites evolve to design better treatments and to predict and prevent the spread of diseases?
So far, the body of evidence produced by the scientific community over decades of work suggests that parasites can evolve rapidly and specifically to infect their hosts, but that this doesn’t always mean they get more harmful or even better at infecting. There is also clear evidence that hosts respond by evolving increased resistance, and that this often comes at a cost such as decreased growth or reproduction. This ongoing coevolution, in which neither parasite nor host is winning the battle has been called ‘Red Queen’ dynamics, based on the idea from “Alice Through the Looking Glass” that you have to run as fast as you can just to stay in the same place. At last, these ideas are beginning to be incorporated into the design and use of drug treatments (sometimes referred to as Darwinian Medicine) and used to build predictive models of disease spread in our increasingly-connected world.
My own data is only the latest in a long chain of such evidences, but I am working to ask these questions in situations that incorporate more realistic complexity; for example by examining coevolution with multiple parasites (Koskella et al. 2012, Proc R Soc) and within larger ecological contexts (Koskella & Meaden 2013, Viruses).
I have also been using a very powerful approach to address these questions by experimentally evolving hosts and parasites in the laboratory, therefore controlling for all the other “noise” out there in nature (Brockhurst & Koskella 2013). However, I always try to go back to nature’s microcosm to find out whether what holds true in the lab can be used to explain what we see in the real world.