Combinatorial quorum sensing allows bacteria to resolve their social and physical environment

Abstract

Quorum sensing (QS) is a cell-cell communication system that controls gene expression in many bacterial species, mediated by diffusible signal molecules. Although the intracellular regulatory mechanisms of QS are often well-understood, the functional roles of QS remain controversial. In particular, the use of multiple signals by many bacterial species poses a serious challenge to current functional theories. Here, we address this challenge by showing that bacteria can use multiple QS signals to infer both their social (density) and physical (mass-transfer) environment. Analytical and evolutionary simulation models show that the detection of, and response to, complex social/physical contrasts requires multiple signals with distinct half-lives and combinatorial (nonadditive) responses to signal concentrations. We test these predictions using the opportunistic pathogen Pseudomonas aeruginosa and demonstrate significant differences in signal decay between its two primary signal molecules, as well as diverse combinatorial responses to dual-signal inputs. QS is associated with the control of secreted factors, and we show that secretome genes are preferentially controlled by synergistic "AND-gate" responses to multiple signal inputs, ensuring the effective expression of secreted factors in high-density and low mass-transfer environments. Our results support a new functional hypothesis for the use of multiple signals and, more generally, show that bacteria are capable of combinatorial communication.diffusion sensing | bacterial signaling | efficiency sensing | collective behavior | bacterial cooperation

Transcriptomics-Aided Dissection of the Intracellular and Extracellular Roles of Microcystin in Microcystis aeruginosa PCC 7806

“…Examples for these cell-cell communication models were investigated in quorum-sensing (QS) systems, which are well known in Gram-negative bacteria. Quorum sensing usually is mediated by diffusible signals that accumulate under higher cell densities and then often controls the expression of other QS signals and more complex secondary metabolites (44). A recent study using Pseudomonas aeruginosa as a model has provided strong evidence that, by using only multiple and interconnected signals, the cells can infer both their social and physical environments (44).…”

Phaeobacter sp. Strain Y4I Utilizes Two Separate Cell-to-Cell Communication Systems To Regulate Production of the Antimicrobial Indigoidine

“…In addition, the two luxRI systems appear to modulate other physiologies in this strain. Again, though, the contributions of the two systems to these behaviors do not appear to be equivalent, which is further suggestive of the presence of a hierarchical regulatory network or of one that is modulated by a combinational response to multiple AHL signals (59).…”

Core Principles of Bacterial Autoinducer Systems

“…Theoretically, the content of push information could also vary between different AIs; e.g., if dependent on molecule size or hydrophilic properties, information about different aspects of mass transfer properties of the surrounding environment are transported, which may be relevant for different public goods. Very recent experimental evidence supports this notion, suggesting that under certain conditions, a combination of multiple AI systems in P. aeruginosa could be employed to discriminate between different push aspects (46). However, the differential regulation of these AI systems by nutrient conditions indicates the additional relevance of pull factors (125).…”

“…In nature, usually a combination of factors, namely, cell density, mass transfer, and clustering, determines the local AI concentration, and there is experimental evidence for this notion (40,44,45). Which factor(s) dominates varies depending on the specific conditions and can hardly be estimated by the cells, although an independent estimation of environmental (e.g., mass transfer) properties via multiple signals with different physical characteristics or via other measurement strategies is possible under certain conditions (46). Note that cell density and cell distribution (or degree of cell aggregation) are independent physical traits (Fig.…”