A multi-phase mathematical model of quorum sensing in a maturing Pseudomonas aeruginosa biofilm

Anguige, Keith; King, John R.; Ward, J. P.

doi:10.1016/j.mbs.2006.05.009

Cited by 57 publications

(49 citation statements)

References 21 publications

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“…To describe the complex structure of biofilms, we consider, as in [3], four different components: Live cyanobacteria (B), Dead cyanobacteria (D), Extracellular matrix of Polymeric Substances or EPS (E), and Liquid (L). We denote the concentration of biomass by C φ = ρ φ φ , where ρ φ is the mass density of a phase in [g/cm 3 ] and φ = B, D, E, L is the volume fraction of the phases.…”

Section: The Fluid Dynamics Modelmentioning

confidence: 99%

A fluid dynamics model of the growth of phototrophic biofilms

et al. 2012

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ABSTRACT. A system of nonlinear hyperbolic partial differential equations is derived using mixture theory to model the formation of biofilms. In contrast with most of the existing models, our equations have a finite speed of propagation, without using artificial free boundary conditions. Adapted numerical scheme will be described in detail and several simulations will be presented in one and more space dimensions in the particular case of cyanobacteria biofilms. Besides, the numerical scheme we present is able to deal in a natural and effective way with regions where one of the phases is vanishing. Fluid dynamics model and Hyperbolic equations and Phototrophic biofilms and Front propagation AMS : 92C17, 35L50, 65M06.

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Section: The Fluid Dynamics Modelmentioning

confidence: 99%

A fluid dynamics model of the growth of phototrophic biofilms

et al. 2012

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“…There are several manuscripts describing mathematical models of the QS systems of P. aeruginosa and other bacterial species, including planktonic cells (17) and biofilm cells (18) in closed and open spaces, such as microfluidic devices (19). Most of these models describe the effect of classical antibiotics and antivirulence compounds and suggest a narrow therapeutic concentration range for the QQ agent to be effective in biofilms.…”

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confidence: 99%

Resistance to Quorum-Quenching Compounds

García‐Contreras

Maeda

Wood

2013

Appl Environ Microbiol

104

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c Bacteria have the remarkable ability to communicate as a group in what has become known as quorum sensing (QS), and this trait has been associated with important bacterial phenotypes, such as virulence and biofilm formation. Bacteria also have an incredible ability to evolve resistance to all known antimicrobials. Hence, although inhibition of QS has been hailed as a means to reduce virulence in a manner that is impervious to bacterial resistance mechanisms, this approach is unlikely to be a panacea. Here we review the evidence that bacteria can evolve resistance to quorum-quenching compounds. Infectious diseases are the leading cause of death (1), and all antibiotics fail (2); therefore, it is imperative to develop novel ways to fight microbial infections. Here we review the use of chemicals that interfere with cell communication and investigate the likelihood that bacteria will evolve resistance to these compounds.QS and QQ. Bacteria use secreted chemicals as signals for a variety purposes, including virulence and biofilm formation. When the compounds build to a threshold concentration and trigger gene expression, the signals are known as quorum-sensing (QS) signals. Examples of well-studied QS signals include acylhomoserine lactones, autoinducer 2, and peptide signals, but many other signals, such as indole, exist (3). In addition to signals, signal synthases, signal receptors, signal response regulators, and regulated genes (QS regulon) are key components of any QS system (4). For example, LuxI-type enzymes are signal synthases which synthesize acylhomoserine lactones. In addition, LuxR-type regulators are receptor proteins for the autoinducer signals, and signalreceptor binding is responsible for the expression of QS regulons. Since numerous compounds that inhibit QS have been identified, since QS is linked to virulence, and since inhibition of QS does not usually affect growth (in rich medium), it has been reasoned that inhibition of QS may be an effective means of reducing pathogenicity that is not subject to the usual resistance mechanisms of bacteria (1,(5)(6)(7)(8). Inhibition of QS is also known as quorum quenching (QQ) and is a form of antivirulence.The well-known examples (9) of QQ compounds include lactonases/acylases that degrade the N-(3-oxoctanoyl)-homoserine lactone (HSL) autoinducers, synthase inhibitors, like analogues of anthranilic acid that block synthesis of quinolone signals (10), and receptor inhibitors, such as brominated furanones (11). In addition, low concentrations of azithromycin, ceftazidime, and ciprofloxacin (antibiotics) inhibit QS in Pseudomonas aeruginosa (12). Also, among the thousands of drugs approved for clinical use, the anthelmintic drug niclosamide is a QQ compound (13); this drug reduces surface motility, biofilm formation, and production of the secreted virulence factors elastase, pyocyanin, and rhamnolipids. The rhizosphere bacterium Stenotrophomonas maltophilia produces cis-9-octadecenoic acid, which is a QQ compound that reduces violacein production by Chromoba...

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“…5 It concerns the biofilm produced by the Pseudomonas aeruginosa, a bacterium that causes serious infections. This is an one-dimensional and multispecies PDEs model, where four different phases are considered: live cells, dead cells, EPS, and liquid.…”

Section: Previous Modelsmentioning

confidence: 99%

Mathematical Models for Biofilms on the Surface of Monuments

Clarelli

Russo²,

Murialdo³

et al. 2009

Applied and Industrial Mathematics in Italy III

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In this article, a system of nonlinear hyperbolic-elliptic partial differential equations is introduced to model the formation of biofilms. First, a short introduction to some basic concepts about biofilms is given. Then a detailed derivation of the model is presented, which is mainly based on the theory of mixtures, also in comparison with previous models. Adapted numerical schemes will be presented and numerical simulations will be discussed.

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A multi-phase mathematical model of quorum sensing in a maturing Pseudomonas aeruginosa biofilm

Cited by 57 publications

References 21 publications

A fluid dynamics model of the growth of phototrophic biofilms

A fluid dynamics model of the growth of phototrophic biofilms

Resistance to Quorum-Quenching Compounds

Mathematical Models for Biofilms on the Surface of Monuments

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