Environmental modulation of microbial conflict and cooperation Microorganisms have tremendous impacts on human health, from the often beneficial effects of the gut microbiome to the deleterious effects of pathogenic bacteria. A key determinant of these health outcomes is the interactions within the microbial community and between the community and the environment of the host. Examples include the collective inactivation of antibiotics by a bacterial population and exchange of nutrients within the microbial population. Despite the clear importance of these interactions, our ability to manipulate them to improve health is often rudimentary. A major obstacle to improved understanding of microbial communities has been the lack of feedback between theoretical models in ecology and experimentally tractable microbial model communities. I propose to use quantitative experiments of microbial communities to explore how environmental changes can transform the consequences of a particular interaction within the community. Over the course of this grant we will take a bottom-up approach to explore how environmental changes will influence three canonical forms of interactions within a microbial community. First we will explore simple cooperation within a population, and in particular whether this cooperation can limit the ability of the population to survive deteriorating environments. As a model system we will explore whether budding yeast can evolve to survive high salt concentrations, and how this survival probability depends upon whether the sugar source requires cooperation within the population. Next we will study how nutrient concentration modulates the properties of a mutualism in which two strains of micro-organism are cross- feeding essential nutrients. We will demonstrate that increasing nutrient concentrations can transform the interaction from a beneficial mutualism into a parasitism, where one partner is actually harmed by the other. Finally, we will study a situation in which two populations are each cooperating with themselves but in a way that harms the other population. We will demonstrate that in low nutrient environments these populations can coexist because population sizes are sufficiently low to prevent excessive negative interaction, but as nutrient concentrations increase there can actually be a loss of diversity. My goal is to transform our understanding of microbial communities while also developing concrete model communities that can be used to quantitatively test ideas from theoretical ecology. The fields of ecology and biomedicine have had little exchange of ideas over the last thirty years, but I believe that many key challenges to human health will require ecological approaches. For example, many of the concepts developed in microbial community ecology may be useful to researchers studying other interacting populations, from the immune system to cancer.
Microbes can have dramatic health effects, from the beneficial role played by bacteria in the human gut to the deleterious effects of pathogenic bacteria. In both cases, the health outcomes are often determined by the way in which the microbes interact with themselves and the human host. Here we use quantitative experiments to develop a predictive understanding of how the environment modulates the interactions within microbial communities.
|Ratzke, Christoph; Denk, Jonas; Gore, Jeff (2018) Ecological suicide in microbes. Nat Ecol Evol 2:867-872|
|Gokhale, Shreyas; Conwill, Arolyn; Ranjan, Tanvi et al. (2018) Migration alters oscillatory dynamics and promotes survival in connected bacterial populations. Nat Commun 9:5273|
|Hoek, Tim A; Axelrod, Kevin; Biancalani, Tommaso et al. (2016) Resource Availability Modulates the Cooperative and Competitive Nature of a Microbial Cross-Feeding Mutualism. PLoS Biol 14:e1002540|
|Yurtsev, Eugene Anatoly; Conwill, Arolyn; Gore, Jeff (2016) Oscillatory dynamics in a bacterial cross-protection mutualism. Proc Natl Acad Sci U S A 113:6236-41|
|Artemova, Tatiana; Gerardin, Ylaine; Dudley, Carmel et al. (2015) Isolated cell behavior drives the evolution of antibiotic resistance. Mol Syst Biol 11:822|
|Vega, Nicole M; Gore, Jeff (2014) Collective antibiotic resistance: mechanisms and implications. Curr Opin Microbiol 21:28-34|
|Yurtsev, Eugene A; Chao, Hui Xiao; Datta, Manoshi S et al. (2013) Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids. Mol Syst Biol 9:683|