Mathematical Modeling of Bacteria Communication in Continuous Cultures

et al. 2020

Chinese Phys. B

Quorum sensing (QS) refers to the cell communication through signaling molecules that regulate many important biological functions of bacteria by monitoring their population density. Although a wide spectrum of studies on the QS system mechanisms have been carried out in experiments, mathematical modeling to explore the QS system has become a powerful approach as well. In this paper, we review the research progress of network modeling in bacterial QS to capture the system’s underlying mechanisms. There are four types of QS system models for bacteria: the Gram-negative QS system model, the Gram-positive QS system model, the model for both Gram-negative and Gram-positive QS system, and the synthetic QS system model. These QS system models are mostly described by the ordinary differential equations (ODE) or partial differential equations (PDE) to study the changes of signaling molecule dynamics in time and space and the cell population density variations. Besides the deterministic simulations, the stochastic modeling approaches have also been introduced to discuss the noise effects on kinetics in QS systems. Taken together, these current modeling efforts advance our understanding of the QS system by providing systematic and quantitative dynamics description, which can hardly be obtained in experiments.

Section: Mathematical Modeling Of the Qs Systems Inmentioning

confidence: 99%

Quantitative modeling of bacterial quorum sensing dynamics in time and space*

et al. 2020

Chinese Phys. B

“…Mathematical modeling has been a useful tool to answer basic and conceptual research questions in microbial physiology. In the last decade, mathematical modeling of QS has provided understanding to key components of QS networks 20 . It has been used to examine P. aeruginosa LasR/I circuit and predict the biochemical switch between two steady states of system (low and high levels of signal perception) and QS response to colony size and cell density 21 .…”

Section: Introductionmentioning

confidence: 99%

Combination Therapy Strategy of Quorum Quenching Enzyme and Quorum Sensing Inhibitor in Suppressing Multiple Quorum Sensing Pathways of P. aeruginosa

Fong

Yang

et al. 2018

Sci Rep

The threat of antibiotic resistant bacteria has called for alternative antimicrobial strategies that would mitigate the increase of classical resistance mechanism. Many bacteria employ quorum sensing (QS) to govern the production of virulence factors and formation of drug-resistant biofilms. Targeting the mechanism of QS has proven to be a functional alternative to conventional antibiotic control of infections. However, the presence of multiple QS systems in individual bacterial species poses a challenge to this approach. Quorum sensing inhibitors (QSI) and quorum quenching enzymes (QQE) have been both investigated for their QS interfering capabilities. Here, we first simulated the combination effect of QQE and QSI in blocking bacterial QS. The effect was next validated by experiments using AiiA as QQE and G1 as QSI on Pseudomonas aeruginosa LasR/I and RhlR/I QS circuits. Combination of QQE and QSI almost completely blocked the P. aeruginosa las and rhl QS systems. Our findings provide a potential chemical biology application strategy for bacterial QS disruption.The emerging threat of antibiotic resistant bacterial pathogens has called for alternative strategies that could replace the usage of current antibiotics and minimize the development of resistance mechanism. One such strategy is to interfere with the bacterial signaling pathways governing the social behaviors involved in pathogenesis and drug-resistant biofilm formation 1 . Microbial organisms exhibit social behaviors and communicate with each other through quorum sensing (QS) [2][3][4] . By synthesizing small signal molecules, they respond collectively to regulate expression of virulence factors, biofilm development, secondary metabolite production, interactions with host and other microbes in a population-density dependent manner 5 . Targeting QS mechanisms has been put forward as an attractive approach to conventional infection control 1 .Acylhomoserine lactone (AHL)-based QS signals are found in more than 70 bacterial species, in which many of them are pathogens 3,6 . In most cases, the structures of the AHLs are conserved with a homoserine lactone (HSL) ring connected to an acyl group with different chain length (n = 4-16) 5,7 . Multiple AHL-based QS systems often co-exist in individual bacterial species. There are two AHL-mediated QS systems in the opportunistic

“…Mathematical modeling has been a useful tool to answer basic and conceptual research questions. In the last decade, mathematical modeling of QS has provided understanding to key components of the QS networks 20 . It has been used to examine P. aeruginosa LasR/I circuit and predict the biochemical switch between two steady states of system (low and high levels of signal perception) and QS response to colony size and cell density 21 .…”

Section: Introductionmentioning

confidence: 99%

Synergy of Quorum Quenching Enzyme and Quorum Sensing Inhibitor in InhibitingP.aeruginosaQuorum Sensing

Fong

Yang

et al. 2017

Preprint

22The threat of antibiotic resistant bacteria has called for alternative antimicrobial strategies 23 that would mitigate the increase of classical resistance mechanism. Many bacteria employ 24 quorum sensing (QS) to govern the production of virulence genes and formation of drug-25 resistance biofilms. Blocking QS mechanisms have proven to be a functional alternative 26 to conventional antibiotic control of infections. The concepts of quorum sensing 27 inhibitors (QSI) and quorum quenching enzymes (QQ) have been investigated separately. 28In this study however, we simulated the synergistic effect of QQ and QSI in blocking 29 bacterial QS. This effect was validated by experiments using AiiA and G1 as QQ and 30 QSI respectively on Pseudomonas aeruginosa LasR/I and RhlR/I QS circuits. The 31 combination of a QQ and a QSI almost completely blocked the P. aeruginosa QS las and 32 peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/182543 doi: bioRxiv preprint first posted online 2 rhl system. Our findings provided a potential application strategy for bacterial QS 33 disruption. 34