Session B55: Complex Microbial Communities

Evolution of Metabolic Dependency

Microbes are often found to have lost their ability to make essential metabolites (auxotrophs) and instead rely on other individuals for these metabolites. How might metabolic dependency evolve to be so common? When microbes live inside a host (endosymbionts), amply host metabolites support auxotrophic endosymbionts. If the host transmits only a small number of endosymbionts to its offspring, then auxotrophic endosymbionts can rise to high frequency simply by chance. On the other hand, auxotrophs have also been observed in abundant free-living bacteria found in ocean water where nutrient supply is low. How might auxotrophs rise to an appreciable frequency in a large population when nutrient supply is low? We have found commonly-encountered conditions that facilitate the evolution of metabolic dependency. Metabolic interactions can in turn shape spatial organization of microbial communities (Momeni et al. (2013) eLife 2, 00230; Momeni et al. (2013) eLife 2, 00960; Estrela and Brown (2013) PLoS Comput Biol 9, e1003398; Muller et al. (2014) PNAS 111, 1037-1042). Rapid evolution of metabolic dependency can contribute to the complexity of microbial communities.   

Visualizing the population dynamics of microbial communities in the larval zebrafish gut

In each of our digestive tracts, trillions of microbes representing hundreds of different species colonize local environments, reproduce, and compete with one another. The resulting ecosystems influence many aspects their host’s development and health. Little is known about how gut microbial communities vary in space and time: how they grow, fluctuate, and respond to various perturbations. To address this and investigate microbial colonization of the vertebrate gut, we apply light sheet fluorescence microscopy to a model system that combines a realistic {\em in vivo} environment with a high degree of experimental control: larval zebrafish with defined subsets of commensal bacterial species. Light sheet microscopy enables three-dimensional imaging with high resolution over the entire intestine, providing visualizations that would be difficult or impossible to achieve with other techniques. Quantitative analysis of image data enables measurement of bacterial abundances and distributions. I will describe this approach and focus especially on recent experiments in which a colonizing bacterial species is challenged by the invasion of a second species, which leads to the decline of the first group. Imaging reveals dramatic population collapses that differentially affect the two species due to their different biogeographies and morphologies. The collapses are driven by the peristaltic motion of the zebrafish intestine, indicating that the physical activity of the host environment can play a major role in mediating inter-species competition. role in mediating inter-species competition.   

Forming Stable Complex Communities: Random vs. Evolved Interactions

We examine the problem of constructing a stable complex community of competing species. We first investigate the case of a randomly generated set of interactions and investigate the different regimes. Here, May showed that if the interactions are not very weak, the system typically does not a steady-state with all species present. We show from simulation that the system typically goes to a non-steady state for interaction strengths above an order 1 multiple of the critical May strength. When demographic stochasticity is added, the system typically jumps from one invadable state to another. For extremely strong competition however, the system does revert to one of a number of steady state. Our model contains, as special cases, the celebrated neutral island theories of Wilson-MacArthur and Hubbell. Moreover, we show that slight deviations from perfect neutrality may lead to each of the phases, as the Hubbell point appears to be quadracritical. If, however, the system is allowed to evolve its set of interactions, each new species inheriting its interactions from its parent species, then the system can produce an interaction matrix which is capable of supporting a large number (> 100) of coexisting species. The key to evolutionary success turns out to be how the child species interacts with its parent.   

Adaptive landscapes: Top-down and bottom-up perspectives

Sewall Wright introduced the metaphor of the~adaptive~landscape, a map from genotype to fitness, more than 80 years ago to help describe his view of~adaptive~evolution.~ This metaphor has been immensely popular and has been used in a variety of incarnations.~ However, a systematic study of the genotype-fitness map presents significant problems. The space of possible genotypes is vast, and the mapping is likely dependent on both environment and the composition of genotypes in a population.~ In this talk, I will discuss some of these problems and present experimental strategies for uncovering features of~adaptive~landscapes.~ In particular, I will discuss how population structure can be used as an experimental variable to elucidate~landscape~topography and how a combination of experimental evolution and genetic engineering can reveal important~landscape~features in changing environments.~ I will also present some potential applications of this work to the problem of antibiotic resistance and potential implications for evolutionary rescue in the face of global climate change.~ For some of these topics, the classic notion of the~adaptive~landscape~must itself be adapted; however, I propose that there are fruitful ways to continue to apply this metaphor.   

Principles of Virus-Microbe Dynamics: From Ecology to Evolution and Back Again

Viruses are ubiquitous in the environment and can function like microbial predators, regulating the density and diversity of microbes present in a community. However, efforts to understand the dynamics of complex virus-microbe communities remain in their infancy. In this talk, I present examples of the interplay between evolutionary and ecological dynamics arising due to virus-microbe interactions. I begin by introducing canonical models of virus-microbe population dynamics in the context of observed oscillations of E. coli and associated phage. I then present a series of examples in which novel features observed in time series data arising from phage interactions with E. coli and V. cholerae can be understood when considering both population and evolutionary dynamics together. I conclude by presenting our recent efforts to extend the results of laboratory experiments to an environmental context, with significantly higher diversity of both viruses and microbes. Despite this increase in diversity, I show how network theoretic methods can reveal common principles underlying the dynamic coexistence of complex virus and host communities. Building on these findings, I describe new efforts to infer who infects whom directly from time series of multi-strain communities.