Extracellular noise-induced stochastic synchronization in heterogeneous quorum sensing network

Hong, Dawei; Saidel, William M.; Man, Shushuang; Martin, Joseph V.

doi:10.1016/j.jtbi.2006.12.006

Cited by 14 publications

(9 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…More recently, the spatial heterogeneous structure of biofilms was addressed in multi-dimensional models. Various mathematical modelling techniques have been applied, namely stochastic individual-based models (Müller et al 2006;Hong et al 2007), stochastic cellular automata models (Pizarro et al 2004;Chambless and Stewart 2007;Machineni et al 2017), deterministic differential equation models (Frederick et al 2011;Schroeder et al 2015;Rahman et al 2015) and hybrid models (Weber and Buceta 2013). While using different approaches, all these models share complexity as their major limitation (Emerenini et al 2015).…”

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

View full text Add to dashboard Cite

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.

show abstract

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

View full text Add to dashboard Cite

show abstract

“…In particular, the characterization of the collective response as a synchronization phenomenon where the phenotypic variations can be generically predicted has been proposed [47]. However, this approach requires gene regulatory interactions controlling the QS switch that do not induce bistability and lead to a monostable behaviour, e.g.…”

Section: Discussionmentioning

confidence: 99%

Dynamics of the quorum sensing switch: stochastic and non-stationary effects

Weber¹,

Buceta²

2013

BMC Syst Biol

View full text Add to dashboard Cite

Background: A wide range of bacteria species are known to communicate through the so called quorum sensing (QS) mechanism by means of which they produce a small molecule that can freely diffuse in the environment and in the cells. Upon reaching a threshold concentration, the signalling molecule activates the QS-controlled genes that promote phenotypic changes. This mechanism, for its simplicity, has become the model system for studying the emergence of a global response in prokaryotic cells. Yet, how cells precisely measure the signal concentration and act coordinately, despite the presence of fluctuations that unavoidably affects cell regulation and signalling, remains unclear. Results: We propose a model for the QS signalling mechanism in Vibrio fischeri based on the synthetic strains lux01 and lux02. Our approach takes into account the key regulatory interactions between LuxR and LuxI, the autoinducer transport, the cellular growth and the division dynamics. By using both deterministic and stochastic models, we analyze the response and dynamics at the single-cell level and compare them to the global response at the population level. Our results show how fluctuations interfere with the synchronization of the cell activation and lead to a bimodal phenotypic distribution. In this context, we introduce the concept of precision in order to characterize the reliability of the QS communication process in the colony. We show that increasing the noise in the expression of LuxR helps cells to get activated at lower autoinducer concentrations but, at the same time, slows down the global response. The precision of the QS switch under non-stationary conditions decreases with noise, while at steady-state it is independent of the noise value. Conclusions:Our in silico experiments show that the response of the LuxR/LuxI system depends on the interplay between non-stationary and stochastic effects and that the burst size of the transcription/translation noise at the level of LuxR controls the phenotypic variability of the population. These results, together with recent experimental evidences on LuxR regulation in wild-type species, suggest that bacteria have evolved mechanisms to regulate the intensity of those fluctuations.

show abstract

“…Another model on the topic of extracellular noise we would like to mention, but do not review due to the lack of space, is that of Hong et al (2007).…”

Section: Circuit and Feedback Loops Modelsmentioning

confidence: 99%

Mathematical Modelling of Bacterial Quorum Sensing: A Review

2016

View full text Add to dashboard Cite

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

show abstract

Extracellular noise-induced stochastic synchronization in heterogeneous quorum sensing network

Cited by 14 publications

References 28 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

Dynamics of the quorum sensing switch: stochastic and non-stationary effects

Mathematical Modelling of Bacterial Quorum Sensing: A Review

Contact Info

Product

Resources

About