• 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