DocumentCode :
16926
Title :
Simulation of the Dynamics of Bacterial Quorum Sensing
Author :
Psarras, Anastasios I. ; Karafyllidis, Ioannis G.
Author_Institution :
Dept. of Electr. & Comput. Eng., Democritus Univ. of Thrace, Xanthi, Greece
Volume :
14
Issue :
4
fYear :
2015
fDate :
Jun-15
Firstpage :
440
Lastpage :
446
Abstract :
Quorum sensing (QS) is a signaling mechanism that pathogenic bacteria use to communicate and synchronize the production of exofactors to attack their hosts. Understanding and controlling QS is an important step towards a possible solution to the growing problem of antibiotic resistance. QS is a cooperative effort of a bacterial population in which some of the bacteria do not participate. This phenomenon is usually studied using game theory and the non-participating bacteria are modeled as cheaters that exploit the production of common goods (exofactors) by other bacteria. Here, we take a different approach to study the QS dynamics of a growing bacterial population. We model the bacterial population as a growing graph and use spectral graph theory to compute the evolution of its synchronizability. We also treat each bacterium as a source of signaling molecules and use the diffusion equation to compute the signaling molecule distribution. We formulate a cost function based on Lagrangian dynamics that combines the time-like synchronization with the space-like diffusion of signaling molecules. Our results show that the presence of non-participating bacteria improves the homogeneity of the signaling molecule distribution preventing thus an early onset of exofactor production and has a positive effect on the optimization of QS signaling and on attack synchronization.
Keywords :
biodiffusion; cell motility; graph theory; microorganisms; molecular biophysics; physiological models; Lagrangian dynamics; antibiotic resistance; bacterial quorum sensing dynamics; diffusion equation; exofactor production; game theory; pathogenic bacteria; signaling molecule distribution computation; spectral graph theory; Eigenvalues and eigenfunctions; Mathematical model; Microorganisms; Production; Sociology; Statistics; Synchronization; Bacterial signaling; quorum sensing; systems biology;
fLanguage :
English
Journal_Title :
NanoBioscience, IEEE Transactions on
Publisher :
ieee
ISSN :
1536-1241
Type :
jour
DOI :
10.1109/TNB.2014.2385109
Filename :
7008560
Link To Document :
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