Experiments examining the social dynamics of bacterial quorum sensing (QS) have focused on mutants which do not respond to signals and the role of QS-regulated exoproducts as public goods. The potential for QS signal molecules to themselves be social public goods has received much less attention. Here, we analyze how signal-deficient ( lasI) mutants of the opportunistic pathogen Pseudomonas aeruginosa interact with wild-type cells in an environment where QS is required for growth. We show that when growth requires a “private” intracellular metabolic mechanism activated by the presence of QS signal, lasI mutants act as social cheats and outcompete signal-producing wild-type bacteria in mixed cultures, because they can exploit the signals produced by wild-type cells. However, reducing the ability of signal molecules to diffuse through the growth medium results in signal molecules becoming less accessible to mutants, leading to reduced cheating. Our results indicate that QS signal molecules can be considered social public goods in a way that has been previously described for other exoproducts but that spatial structuring of populations reduces exploitation by noncooperative signal cheats.
Bacteria communicate via signaling molecules to regulate the expression of a whole range of genes. This process, termed quorum sensing (QS), moderates bacterial metabolism under many environmental conditions, from soil and water (where QS-regulated genes influence nutrient cycling) to animal hosts (where QS-regulated genes determine pathogen virulence). Understanding the ecology of QS could therefore yield vital clues to how we might modify bacterial behavior for environmental or clinical gains. Here, we demonstrate that QS signals act as shareable public goods. This means that their evolution, and therefore population-level responses to interference with QS, will be constrained by population structure. Further, we show that environmental structure (constraints on signal diffusion) alters the accessibility of QS signals and demonstrates that we need to consider population and environmental structure to help us further our understanding of QS signaling systems.