Bacteria communicate using external chemical signals called autoinducers (AI) in a process known as quorum sensing (QS). QS efficiency is reduced by both limitations of AI diffusion and potential interference from neighboring strains. There is thus a need for theoretical approaches that yield nontrivial quantitative predictions of how spatial community structure shapes information processing in complex microbial ecosystems. As a step in this direction, we apply a reaction-diffusion model to study autoinducer signaling dynamics in a growing bacterial community as a function of the density of metapopulations, or spatially dispersed colonies , in the total system. We predict a non-equilibrium phase transition between a local quorum sensing (LQS) regime at low dispersal, with AI signaling dynamics primarily controlled by the local population density of colonies, and a global quorum sensing (GQS) regime at high dispersal , with the dynamics being governed by the collective metapopulation density. In addition, we propose an observable order parameter for this system, termed the Neighbor Interference Fraction (NIF), which accounts for the ratio of neighbor-produced to self-produced signal at a colony. The transition between LQS to GQS is intimately connected to a tradeoff between the signaling network's latency, or speed of activation, and its throughput, or the total spatial range over which all the components of the system communicate . Levels of dispersal near the phase boundary provide an optimal compromise that enables simultaneously high latency and throughput in a given environment .
Bacteria communicate using external chemical signals called autoinducers (AI) in a process known as quorum sensing (QS). QS efficiency is reduced by both limitations of AI diffusion and potential interference from neighboring strains. There is thus a need for predictive theories of how spatial community structure shapes information processing in complex microbial ecosystems. As a step in this direction, we apply a reaction-diffusion model to study autoinducer signaling dynamics in a single-species community as a function of the spatial distribution of colonies in the system. We predict a dynamical transition between a local quorum sensing (LQS) regime , with the AI signaling dynamics primarily controlled by the local population densities of individual colonies, and a global quorum sensing (GQS) regime , with the dynamics being dependent on collective inter-colony diffusive interactions. The crossover between LQS to GQS is intimately connected to a tradeoff between the signaling network's latency, or speed of activation, and its throughput, or the total spatial range over which all the components of the system communicate .
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theoretical approaches that yield nontrivial quantitative predictions
predictive theories
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growing bacterial
single-species
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density of metapopulations, or spatially dispersed colonies , in the total
spatial distribution of colonies in the
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non-equilibrium phase
dynamical
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at low dispersal, with
, with the
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density of
densities of individual
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at high dispersal
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governed by the collective metapopulation density. In addition, we propose an observable order parameter for this system, termed the Neighbor Interference Fraction (NIF), which accounts for the ratio of neighbor-produced to self-produced signal at a colony. The transition
dependent on collective inter-colony diffusive interactions. The crossover
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. Levels of dispersal near the phase boundary provide an optimal compromise that enables simultaneously high latency and throughput in a given environment