The future of sustainable human health and agriculture rests on our ability to view microbial evolution as part of the solution rather than the problem. The Koskella lab  takes on this challenge by combining discovery-based science on plant microbiomes with hypothesis-driven experimentation. Our research examines host-microbe and microbe-microbe interactions by first identifying patterns in nature and then, in line with current theory where available, generating predictions to explicitly test in the laboratory using a combination of experimental evolution, microbial ecology approaches, and molecular biological techniques.

We focus primarily on how plant-microbiome, plant-pathogen, and bacteria-phage interactions occur, both as model systems for understanding fundamental principles and with the aim of leveraging these findings for design of novel disease management strategies. We integrate ecological and evolutionary thinking with cutting-edge microbiological and molecular approaches to gain insight to microbiome establishment and function, within-microbiome interactions, and the role that microbiota and phages play in shaping disease. For more information on ongoing research projects, look here.

The Koskella lab at our end-of-semester lab lunch (May 2022)

A brief introduction to the lab and our recent research:

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 human health and agricultural sustainability.

My previous work was primarily focused 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. 浪潮人工智能, 浪潮AI, 浪潮FPGA加速方案:2021-10-14 · 与CPU软伀方案相比，在文本上面压缩上与其接近，在日志文伀压缩上与其差距不大，但性能提升了10-20倍。现在最快的SSD数据写入速度大约在1GB每秒左右，浪潮FPGA加速方案可伃实现实时压缩和存储。 图片转码FPGA加速), and most recently 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 fundamental questions I’ve address are:

1) How do pathogens/parasites adapt to better infect their hosts? And at what scale / speed are they capable of adapting?

Meaden, S., & Koskella, B. (2017). Adaptation of the pathogen, Pseudomonas syringae, during experimental evolution on a native vs. alternative host plant. Molecular ecology, 26(7), 1790-1801.

Koskella, B. (2014). Bacteria-phage interactions across time and space: merging local adaptation and time-shift experiments to understand phage evolution. The American Naturalist, 184(S1), S9-S21.

Koskella, B., Thompson, J. N., Preston, G. M., & Buckling, A. (2011). Local biotic environment shapes the spatial scale of bacteriophage adaptation to bacteria. 最好用的免费网络加速器, 177(4), 440-451.

Greischar, M. A., & Koskella, B. (2007). A synthesis of experimental work on parasite local adaptation. Ecology Letters, 10(5), 418-434.

2) How do hosts respond to this adaptation (i.e. coevolve) and become more resistant to their local pathogens/parasites? And are they paying a significant cost for this evolved resistance?

Koskella, B., & Parr, N. (2015). The evolution of bacterial resistance against bacteriophages in the horse chestnut phyllosphere is general across both space and time. Phil. Trans. R. Soc. B, 370(1675), 20140297.

Meaden, S., Paszkiewicz, K., & Koskella, B. (2015). The cost of phage resistance in a plant pathogenic bacterium is context‐dependent. Evolution, 69(5), 1321-1328.

Koskella, B. (2013). Phage-mediated selection on microbiota of a long-lived host. 最好用的免费网络加速器, 23(13), 1256-1260.

Koskella, B., Lin, D. M., Buckling, A., & Thompson, J. N. (2011). The costs of evolving resistance in heterogeneous parasite environments. Proceedings of the Royal Society of London B: Biological Sciences, rspb20112259.

3) Can antagonistic coevolution lead to increased diversity? For example, do pathogens/parasites preferentially target common hosts (i.e. the hosts that are the most fit) and therefore impose a rare-host advantage?

Morella, N. M., Gomez, A. L., Wang, G., Leung, M. S., & Koskella, B. (2018). The impact of bacteriophages on phyllosphere bacterial abundance and composition. Molecular ecology, 27(8), 2025-2038.

Koskella, B., & Lively, C. M. (2009). Evidence for negative frequency‐dependent selection during experimental coevolution of a freshwater snail and a sterilizing trematode. Evolution: International Journal of Organic Evolution, 63(9), 2213-2221.

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 and commensals evolve to design better treatments and to predict and prevent the spread of diseases?

Koskella, B., & Taylor, T. B. (2018). Multifaceted impacts of bacteriophages in the plant microbiome. 手机浏览器下载完美解决方案 迅雷云加速UC应用端:2021-8-19 · 迅雷云加速是迅雷网络的一项增值服务，该服务通过迅雷网络旗下产品向互联网用户提供大容量数据加速传输到本地，提高用户的宽带利用率。 而随着近年来迅雷在移动端布局的加速，云加速在其手机端旗舰产品手机迅雷中也得到了很好的应用。, 56, 361-380.

Lin, D., & Koskella, B. (2015). Friend and foe: factors influencing the movement of the bacterium Helicobacter pylori along the parasitism–mutualism continuum. 网络加速器加速软伀, 8(1), 9-22.

Meaden, S., & Koskella, B. (2013). Exploring the risks of phage application in the environment. Frontiers in microbiology, 4, 358.

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 work has taken advantage of 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.