Traveling waves in response to a diffusing quorum sensing signal in spatially-extended bacterial colonies

Langebrake, Jessica; Dilanji, Gabriel E.; Hagen, Stephen J.; Leenheer, Patrick De

doi:10.1016/j.jtbi.2014.07.033

Cited by 33 publications

(31 citation statements)

References 41 publications

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“…Recently, a one-dimensional reaction-diffusion model for QS-regulated bioluminescence of the marine bacterium Aliivibrio fischeri was presented in Langebrake et al (2014). The model is based on Dilanji et al (2012) and consists of a reaction-diffusion equation for the autoinducer concentration and an equation for the LuxI concentration measured as luminescence.…”

Section: Bioluminescencementioning

confidence: 99%

Mathematical Modelling of Bacterial Quorum Sensing: A Review

2016

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Bacterial quorum sensing (QS) refers to the process of cell-to-cell bacterial communication enabled through the production and sensing of the local concentration of small molecules called autoinducers to regulate the production of gene products (e.g. enzymes or virulence factors). Through autoinducers, bacteria interact with individuals of the same species, other bacterial species, and with their host. Among QS-regulated processes mediated through autoinducers are aggregation, biofilm formation, bioluminescence, and sporulation. Autoinducers are therefore "master" regulators of bacterial lifestyles. For over 10 years, mathematical modelling of QS has sought, in parallel to experimental discoveries, to elucidate the mechanisms regulating this process. In this review, we present the progress in mathematical modelling of QS, highlighting the various theoretical approaches that have been used and discussing some of the insights that have emerged. Modelling of QS has benefited almost from the onset of the involvement of experimentalists, with many of the papers which we review, published in non-mathematical journals. This review therefore attempts to give a broad overview of the topic to the mathematical biology community, as well as the current modelling efforts and future challenges.B Judith Pérez-Velázquez

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Section: Bioluminescencementioning

confidence: 99%

Mathematical Modelling of Bacterial Quorum Sensing: A Review

2016

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“…Attempts to integrate such different views have been made, thereby connecting local with global population properties1112. The QS response itself was recently shown to exhibit complex spatio-temporal patterns under flow1314, whereas purely diffusing signals might sustain QS activation waves that travel across spatially extended colonies1516.…”

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confidence: 99%

Modeling quorum sensing trade-offs between bacterial cell density and system extension from open boundaries

Marenda

Zanardo

Trovato

et al. 2016

Sci Rep

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Bacterial communities undergo collective behavioural switches upon producing and sensing diffusible signal molecules; a mechanism referred to as Quorum Sensing (QS). Exemplarily, biofilm organic matrices are built concertedly by bacteria in several environments. QS scope in bacterial ecology has been debated for over 20 years. Different perspectives counterpose the role of density reporter for populations to that of local environment diffusivity probe for individual cells. Here we devise a model system where tubes of different heights contain matrix-embedded producers and sensors. These tubes allow non-limiting signal diffusion from one open end, thereby showing that population spatial extension away from an open boundary can be a main critical factor in QS. Experimental data, successfully recapitulated by a comprehensive mathematical model, demonstrate how tube height can overtake the role of producer density in triggering sensor activation. The biotic degradation of the signal is found to play a major role and to be species-specific and entirely feedback-independent.

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“…f Adapted from information in [28]. In particular, point production intensity is (0.43 nM/hr) × l, where l is the luminescence, ranging between 0 to 3000 (normalized), thus corresponding to an intensity range from about 0 to 1300 nM/hr.…”

Section: Figmentioning

confidence: 99%

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

Yusufaly

Boedicker

2016

Phys. Rev. E

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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...

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Traveling waves in response to a diffusing quorum sensing signal in spatially-extended bacterial colonies

Cited by 33 publications

References 41 publications

Mathematical Modelling of Bacterial Quorum Sensing: A Review

Mathematical Modelling of Bacterial Quorum Sensing: A Review

Modeling quorum sensing trade-offs between bacterial cell density and system extension from open boundaries

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

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