An Approximative Approach for Single Cell Spatial Modeling of Quorum Sensing

Gölgeli, Meltem; Müller, Johannes; Kuttler, Christina; Hense, Burkhard A.

doi:10.1089/cmb.2014.0198

Cited by 6 publications

(4 citation statements)

References 16 publications

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“…As stated earlier, while a pure mathematical approach is possible for the simplest scenarios, the complexity of the calculations increases considerably for scenarios of this complexity, because molecules collide among themselves and higher deviations will naturally occur. Matur et al 2015). Further models treated extracellular molecular concentration as a parameter, and studied the response of a single cell.…”

Section: Discussionmentioning

confidence: 99%

Agent-based model of diffusion of N-acyl homoserine lactones in a multicellular environment of Pseudomonas aeruginosa and Candida albicans

et al. 2018

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Experimental incapacity to track microbe-microbe interactions in structures like biofilms, and the complexity inherent to the mathematical modelling of those interactions, raises the need for feasible, alternative modelling approaches. This work proposes an agent-based representation of the diffusion of N-acyl homoserine lactones (AHL) in a multicellular environment formed by Pseudomonas aeruginosa and Candida albicans. Depending on the spatial location, C. albicans cells were variably exposed to AHLs, an observation that might help explain why phenotypic switching of individual cells in biofilms occurred at different time points. The simulation and algebraic results were similar for simpler scenarios, although some statistical differences could be observed (p < 0.05). The model was also successfully applied to a more complex scenario representing a small multicellular environment containing C. albicans and P. aeruginosa cells encased in a 3-D matrix. Further development of this model may help create a predictive tool to depict biofilm heterogeneity at the single-cell level.

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Section: Discussionmentioning

confidence: 99%

Agent-based model of diffusion of N-acyl homoserine lactones in a multicellular environment of Pseudomonas aeruginosa and Candida albicans

et al. 2018

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“…Gölgeli Matur et al (2014) addressed the QS mechanism of single cells in the stationary case, which is crucial to understanding the effect of chemical gradients and inter-cell variations. Based on a reaction-diffusion system, they developed a method that drastically reduces the computational complexity of the model.…”

Section: Othersmentioning

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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“…Because the signal concentration decreases with distance from its source, cells should be located close to each other in order to send and receive enough signaling molecules to and from their neighbors (Hense et al, 2007;Matur et al, 2015). The distance between two QS induced microbial cells or aggregates is referred to as the "calling distance" and has been reported to be 5-78 mm between individual cells (Gantner et al, 2006) and~180 mm between microbial aggregates (Darch et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Numerical investigation of microbial quorum sensing under various flow conditions

Jung¹,

Meile²

2020

PeerJ

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Microorganisms efficiently coordinate phenotype expressions through a decision-making process known as quorum sensing (QS). We investigated QS amongst distinct, spatially distributed microbial aggregates under various flow conditions using a process-driven numerical model. Model simulations assess the conditions suitable for QS induction and quantify the importance of advective transport of signaling molecules. In addition, advection dilutes signaling molecules so that faster flow conditions require higher microbial densities, faster signal production rates, or higher sensitivities to signaling molecules to induce QS. However, autoinduction of signal production can substantially increase the transport distance of signaling molecules in both upstream and downstream directions. We present empirical approximations to the solutions of the advection–diffusion–reaction equation that describe the concentration profiles of signaling molecules for a wide range of flow and reaction rates. These empirical relationships, which predict the distribution of dissolved solutes along pore channels, allow to quantitatively estimate the effective communication distances amongst multiple microbial aggregates without further numerical simulations.

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An Approximative Approach for Single Cell Spatial Modeling of Quorum Sensing

Cited by 6 publications

References 16 publications

Agent-based model of diffusion of N-acyl homoserine lactones in a multicellular environment of Pseudomonas aeruginosa and Candida albicans

Agent-based model of diffusion of N-acyl homoserine lactones in a multicellular environment of Pseudomonas aeruginosa and Candida albicans

Mathematical Modelling of Bacterial Quorum Sensing: A Review

Numerical investigation of microbial quorum sensing under various flow conditions

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