Competition and cooperation in host-associated microbial communities: insights from computational and mathematical models

Thesis

Our bodies contain a vast number and diversity of microbes. These microbes interact, and these interactions can define how microbes affect us. Microbial ecology and evolution, therefore, are important for both microbiology and human health. However, our understanding of microbial communities remains limited. There is a need for theory that dissects the complexity and identifies the key factors and processes affecting microbial groups. Here I develop realistic computer simulations and population models of microbial communities. My first project seeks to explain microbial communication (quorum sensing) and argues that quorum sensing is a way to infer when competing genotypes are no longer a threat. The second project proposes an evolutionary explanation for another major microbial trait: adhesion. I argue that adhesion is a weapon allowing cells to compete within microbial groups and push competitors out, particularly when growing on a host epithelium. The third project moves from microbes to the host and asks whether a host can control which microbes grow and persist inside it. I develop a model of the human gut epithelium and show that the gut architecture amplifies the ability of hosts to select helpful microbes over harmful ones using nutrient secretion. In addition to selecting particular microbial strains, a host will also benefit from stable symbiotic communities that behave in a predictable manner. But what determines whether host-associated communities are ecologically stable? My final project uses ecological network theory to show that ecological stability is likely to be a problem for gut communities that are diverse and contain species that cooperate with each other. However, I argue that the host should function as an ecosystem engineer that increases ecological stability by weakening the strong dependence of cooperating species upon one another. While host-associated communities are complex ecological systems, my thesis identifies key factors that affect their form and function.

Authors: Schluter, J

• Publication date: 2014
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: systems biology; mathematical biology; evolution; computational biology; ecology
• Subjects: Evolution (zoology); Biology and other natural sciences (mathematics); Ecology (zoology); Mathematical biology; Microbiology