Spatial dispersal of bacterial colonies induces a dynamical transition from local to global quorum sensing

Abstract

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 intercolony 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.Multicellular communities, such as colonies of bacteria, communicate with each other to coordinate changes in their collective group behavior. This communication usually takes the form of the production and secretion of extracellular signaling molecules called autoinducers (AI), as illustrated in Figure 1. Released autoinducers diffuse through the environment, and each cell senses the local concentration of signal to inform changes in gene regulation. This intercellular signaling network, known as quorum sensing (QS), is crucial for a wide array of important microbial processes, including biofilm formation, regulation of virulence and horizontal gene transfer [1][2][3].Decades of research have advanced our knowledge of QS, but several subtleties remain unresolved. In particular, AI signals may convey information about many aspects of the cellular network and local environment beyond simply the total number of cells in the system [4]. Far from being reducible to homogeneous, uniform density populations, microbial communities are typically characterized by high spatial heterogeneity [5]. As a result, several new phenomena emerge due to crosstalk between spatially segregated populations [6]. Consequently, it appears that AI molecules can be an indicator of increased local population density, and can also be proxies of other variables, such as population dispersal [7][8][9][10][11].In recent years, advances in the ability to experimentally probe the properties of cellular populations at the single-cell level [12] have resulted in a growing community of theoretical physicists working to catalogue the different classes of collective behavior found in interacting communities of organisms [13][14][15][16][17]. This approach has already successfully yielded insight into a wide variety of ecological problems, with notable recent examples including the effects of invasion in cooperative populations [18], opti...

Burst statistics in an early biofilm quorum sensing model: the role of spatial colony-growth heterogeneity

“…We refer also to 14 for the discussion of various effects of cell density, mass-transfer properties of the environment, and spatial distribution of bacteria onto AI concentration and QS. This is in contrast to homogeneous scenarios 47 , in which a concerted induction occurs (a mean-field description). As the local concentration after a given number of cell divisions is lower in the homogeneous situation the induction occurs later (local versus global QS) 47 .…”

“…This is in contrast to homogeneous scenarios 47 , in which a concerted induction occurs (a mean-field description). As the local concentration after a given number of cell divisions is lower in the homogeneous situation the induction occurs later (local versus global QS) 47 .…”

“…Namely, how is this induction process influenced by the spatial distribution of cells in the growing biofilm, in particular, the spreading of the daughter cells after cell divisions due to bacterial motility or diffusion? While the typical cell-cell distance in a growing colony can be a decisive factor for the local AI concentration and, thus, for the timing of the biofilm-induction event (see the recent study 47 ), we explore what happens when the local cell density varies statistically. Such a spatially disordered scenario is natural for a realistic growing colony in which randomly placed seed cells divide and cover an increasing area, leading to local regions with varying cell density (see Fig.…”

Self-organization of active particles by quorum sensing rules

“…Quorum sensing in living systems requires communication between individuals, which is achieved by the release of signalling molecules with production rate γ 29 . Because such molecules have a finite lifetime, each organism senses the molecular concentration Here, is the distance to the neighbour labelled j , σ the linear size of the individuals, and (with D c the diffusion coefficient of the signalling molecules and τ their lifetime) a decay length, defining the range of the concentration profile and thus the distance over which particles communicate.…”

Disruption of microbial communication yields a two-dimensional percolation transition

“…From a physics perspective, such multispecies communities offer a novel context in which to discover and characterize emergent, collective phenomena in strongly interacting many-body networks [9][10][11][12][13]. One particularly notable and relevant example of such collective behavior is percolation, where networks display an abrupt transition in large-scale global connectivity at a critical threshold of a varying parameter, typically occupation probability.…”