Search for: All records

Abstract Bacteria utilize cell-cell signaling to coordinate gene expression in populations of cells. Bacterial signal exchange was originally interpreted as a mechanism bacteria use to regulate gene expression in response to changes in cell density, denoted as quorum sensing. Bacterial communication is now known to encompass the exchange of multiple chemical signals between different species of bacteria. Such signal crosstalk within communities of bacteria can have unexpected consequences. Some bacterial species even utilize more than one orthogonal signaling molecule, enabling such species to simultaneously communicate within distinct subsets of species. Such cells utilizing two sets of signals act as a bridge to link gene expression states within the community. Here, a mathematical model was implemented to investigate the consequences of multi-signal communication within heterogeneous bacterial communities. The model was inspired by simple neural networks, with nodes representing bacterial species and directed weights between nodes accounting for the impacts of inter-species signal exchange on gene expression. The activity state of such a network is defined as the gene expression state of each species within the community. Using the model, the stability of the activity states of such networks to changes in signal concentration and population size were quantified. Networks exchanging one set of signals were compared to network exchanging two orthogonal sets of signals. A multilayer neural network model was developed to analyze such networks exchanging orthogonal sets of signals. The model reveals that signal crosstalk increased the activity of the network. These networks were largely resilient to perturbation, however networks were more sensitive to perturbations of the largest population size. Bacterial species utilizing two orthogonal signals, within multilayer networks, had the potential to couple activity states of species that cannot directly communicate. These results give insight into strategies for manipulating signal exchange to predict and control gene expression within bacterial communities. 

Insect diversification has been catalyzed by widespread specialization on novel hosts - a process underlying exceptional radiations of phytophagous beetles, lepidopterans, parasitoid wasps, and inordinate lineages of symbionts, predators and other trophic specialists. The strict fidelity of many such interspecies associations is posited to hinge on sensory tuning to host-derived cues, a model supported by studies of neural function in host-specific model species. Here, we investigated the sensory basis of symbiotic interactions between a myrmecophile rove beetle and its single, natural host ant species. We show that host cues trigger analogous behaviors in both ant and symbiont. Cuticular hydrocarbons - the ant's nestmate recognition pheromones - elicit partner recognition by the beetle and execution of ant grooming behavior, integrating the beetle into the colony via chemical mimicry. The beetle also follows host trail pheromones, permitting inter-colony dispersal. Remarkably, the rove beetle also performs its symbiotic behaviors with ant species separated by ~95 million years, and shows minimal preference for its natural host over non-host ants. Experimentally validated agent-based modeling supports a scenario in which specificity is enforced by physiological constraints on symbiont dispersal, and negative fitness interactions with alternative hosts, rather than via sensory tuning. Enforced specificity may be a pervasive mechanism of host range restriction of specialists embedded within host niches. Chance realization of latent compatibilities with alternative hosts may facilitate host switching, enabling deep-time persistence of obligately symbiotic lineages.