A Modular View of the Diversity of Cell-Density-Encoding Schemes in Bacterial Quorum-Sensing Systems

Abstract

Certain environmental parameters are accessible to cells only indirectly and require an encoding step for cells to retrieve the relevant information. A prominent example is the phenomenon of quorum sensing by microorganisms, where information about cell density is encoded by means of secreted signaling molecules. The mapping of cell density to signal molecule concentration and the corresponding network modules involved have been at least partially characterized in many bacteria, and vary markedly between different systems. In this study, we investigate theoretically how differences in signal transport, signal modification, and site of signal detection shape the encoding function and affect the sensitivity and the noise characteristics of the cell-density-encoding process. We find that different modules are capable of implementing both fairly basic as well as more complex encoding schemes, whose qualitative characteristics vary with cell density and are linked to network architecture, providing the basis for a hierarchical classification scheme. We exploit the tight relationship between encoding behavior and network architecture to constrain the network topology of partially characterized natural systems, and verify one such prediction by showing experimentally that Vibrio harveyi is capable of importing Autoinducer 2. The framework developed in this research can serve not only to guide reverse engineering of natural systems but also to stimulate the design of synthetic systems and generally facilitate a better understanding of the complexities arising in the quorum-sensing process because of variations in the physical organization of the encoder network module.

Ecological feedback in quorum-sensing microbial populations can induce heterogeneous production of autoinducers

“…We refer to the function R( p ) as the response function, which is the same for all individuals. The response function encapsulates all biochemical steps involved in the autoinducer production between perception of the average production level p and adjustment of the individual production degree to R( p ) in response [2,11,35,46,47]; see Fig. 1(B).…”

Parallel quorum sensing signaling pathways in Vibrio cholerae

“…Indeed, bacterial species have evolved independently to have differential contributions from multiple signaling inputs to control particular behaviors, which depend on specific environmental niches (e.g., in V. cholerae , biofilm formation in the aquatic environment and virulence factor production inside the host, both of which are controlled by QS). V. cholerae is just one of several QS bacterial species that utilizes a multi-signal network configuration to accomplish specific goals (Cornforth, et al 2014, Drees, et al 2014). Other research has shown that there is an association between variable environmental challenges and multi-signal complexity for bacteria that have multiple niches, like V. cholerae , Pseudomonas aeruginosa , Burkholderia thailandensis , and some Bacillus species which have niches both inside and outside of human hosts (Cornforth, et al 2014, Pollak, et al 2015, Schuster, et al 2013, Williams, et al 2007, Yang and Lan 2015).…”

The Phosphorylation Flow of the Vibrio harveyi Quorum-Sensing Cascade Determines Levels of Phenotypic Heterogeneity in the Population

“…This phenomenon was first described for luminescent bacteria such as the symbiotic marine bacterium Vibrio fischeri (1)(2)(3). Since then, many different QS systems have been discovered in Gram-negative as well as Gram-positive bacteria (4). AIs are synthesized and released into the environment, therefore accumulating in a cell-number-dependent manner.…”