Session T42: Focus Session: Evolutionary Systems Biology III - Evolutionary Games

Bacterial tower of Babel --How cheating and lying diversify bacterial communication

In microbial ``quorum sensing'' (QS) communication systems, microbes produce and respond to a signaling molecule, enabling a cooperative response at high cell densities. Many species of bacteria show fast, intraspecific, evolutionary divergence of their QS pathway specificity---signaling molecules activate cognate receptors in the same strain but fail to activate, and sometimes inhibit, those of other strains. Despite many molecular studies, it has remained unclear how a signaling molecule and receptor can coevolve, what maintains diversity, and what drives the evolution of cross-inhibition. Here I use mathematical analysis to show that when QS controls the production of extracellular enzymes ---``public goods''---diversification can readily evolve. Coevolution is positively selected by cycles of alternating ``cheating'' receptor mutations and ``cheating immunity'' signaling mutations. The maintenance of diversity and the evolution of cross-inhibition between strains are facilitated by facultative cheating between the competing strains. My results suggest a role for complex social strategies in the long-term evolution of QS systems. More generally, my model of QS divergence suggests a form of kin recognition where different kin types coexist in unstructured populations.   

Coupling between evolutionary and population dynamics in experimental microbial populations

It has been often been assumed that population dynamics and evolutionary dynamics occur at such different timescales that they are effectively de-coupled. This view has been challenged recently, due to observations of evolutionary changes occurring in short timescales. This has led to a growing interest in understanding eco-evolutionary dynamics of populations. In this context, recent theoretical models have predicted that coupling between population dynamics and evolutionary dynamics can have important effects for the evolution and stability of cooperation, and lead to extremely rich and varied dynamics. Here, we report our investigation of the eco-evolutionary dynamics of a cooperative social behavior, sucrose metabolism, in experimental yeast populations. We have devised an experimental strategy to visualize trajectories in the phase space formed by the population size (N) and the fraction of cooperator cells in the population (f). Our measurements confirm a strong coupling between evolutionary and population dynamics, and allowed us to characterize the bifurcation plots. We used this approach to investigate how sudden environmental changes affect the stability and recovery of populations, and therefore the stability of cooperation.   

Competition between species can drive public goods cooperation within a species

Costly cooperative strategies are vulnerable to exploitation by cheats. Microbial studies have suggested that cooperation can be maintained in nature by mechanisms such as reciprocity, spatial structure and multi-level selection. So far, however, almost all laboratory experiments aimed at understanding cooperation have relied on studying a single species in isolation. In contrast, species in the wild live within complex communities where they interact with other species. Little effort has focused on understanding the effect of interspecies competition on the evolution of cooperation within a species. We test this relationship by using sucrose metabolism of budding yeast as a model cooperative system. We find that when co-cultured with a bacterial competitor, yeast populations become more cooperative compared to isolated populations. We show that this increase in cooperation within yeast is mainly driven by resource competition imposed by the bacterial competitor. A similar increase in cooperation is observed in a pure yeast culture when essential nutrients in the media are limited experimentally.   

The emergence of cooperation from a single cooperative mutant

Population structure is one central condition which promotes the stability of cooperation: If cooperators more likely interact with other cooperators (positive assortment), they keep most of their benefit for themselves and are less exploited by non-cooperators. However, positive assortment can only act successfully if cooperation is already well established in the population such that cooperative individuals can successfully assort. But how can cooperation emerge when starting with a single cooperative mutant? Here we study this issue for a generic situation of microbial systems where microbes regularly form new colonies and show strong population growth. We show how and when the dynamical interplay between colony formation, population growth and evolution within colonies can provoke the emergence of cooperation. In particular, the probability for a single cooperative mutant to succeed is robustly large when colony-formation is fast or comparable to the time-scale of growth within colonies; growth supports cooperation.\\[4pt] [1]~A. Melbinger, J. Cremer, and E. Frey, Evolutionary game theory in growing populations, \emph{Phys. Rev. Lett.} {\bf 105}, 178101 (2010)\\[0pt] [2]~J. Cremer, A. Melbinger, and E. Frey, Evolutionary and population dynamics: a coupled approach, arXiv:1108.2604   

Coping with stress in a synthetic world

A major focus of synthetic biology is the engineering of gene circuits to perform user-defined functions. In addition to generating systems of practical applications, such efforts have led to the identification and evaluation of design strategies that enable robust control of dynamics in single cells and in cell populations. On the other hand, there is an increasing emphasis on using engineered systems programmed by simple circuits to explore fundamental biological questions of broad significance. In this talk, I will discuss our efforts along this line of research, whereby we have used engineered gene circuits to examine the evolutionary dynamics of two common bacterial survival strategies in stress response: programmed death and cell-cell communication.   

Bacterial cheating limits antibiotic resistance

The widespread use of antibiotics has led to the evolution of resistance in bacteria. Bacteria can gain resistance to the antibiotic ampicillin by acquiring a plasmid carrying the gene beta-lactamase, which inactivates the antibiotic. This inactivation may represent a cooperative behavior, as the entire bacterial population benefits from removing the antibiotic. The cooperative nature of this growth suggests that a cheater strain---which does not contribute to breaking down the antibiotic---may be able to take advantage of cells cooperatively inactivating the antibiotic. Here we find experimentally that a ``sensitive'' bacterial strain lacking the plasmid conferring resistance can invade a population of resistant bacteria, even in antibiotic concentrations that should kill the sensitive strain. We observe stable coexistence between the two strains and find that a simple model successfully explains the behavior as a function of antibiotic concentration and cell density. We anticipate that our results will provide insight into the evolutionary origin of phenotypic diversity and cooperative behaviors.   

Bacterial Transformation and Competition Under Antibiotic Stress

Transformation, the process by which bacteria uptake DNA directly from their environment and incorporate it as their own genetic material, is a form of Horizontal Gene Transfer that occurs throughout nature as an important mechanism for spurring on bacterial evolution. We examine the capacity of bacteria to undergo transformation and will discuss work that has been done by the Austin group using Micro-Habitat Patches (MHPs) to examine the emergence of phenotypes due to horizontal gene transfer.   

Rapid Antibiotic Resistance Evolution of GASP Mutants

The GASP phenotype in bacteria is due to a mutation which enables the bacteria to grow under high stress conditions where other bacteria stop growing. We probe using our Death Galaxy microenvironment how rapidly the GASP mutant can evolve resistance to mutagenic antibiotics compared to wild-type bacteria, and explore the genomic landscape changes due to the evolution of resistance.   

Spatial vs. individual variability with inheritance in a stochastic Lotka-Volterra system

We investigate a stochastic spatial Lotka-Volterra predator-prey model with randomized interaction rates that are either affixed to the lattice sites and quenched, and / or specific to individuals in either population. In the latter situation, we include rate inheritance with mutations from the particles' progenitors. Thus we arrive at a simple model for competitive evolution with environmental variability and selection pressure. We employ Monte Carlo simulations in zero and two dimensions to study the time evolution of both species' densities and their interaction rate distributions. The predator and prey concentrations in the ensuing steady states depend crucially on the environmental variability, whereas the temporal evolution of the individualized rate distributions leads to largely neutral optimization. Contrary to, e.g., linear gene expression models, this system does not experience fixation at extreme values. An approximate description of the resulting data is achieved by means of an effective master equation approach for the interaction rate distribution.