Cell-signalling repression in bacterial quorum sensing

Abstract

In this paper we expand on two mathematical models for investigating the role of three distinct repression mechanisms within the so called quorum sensing (QS) cell-signalling process of bacterial colonies growing (1) in liquid cultures and (2) in biofilms. The repression mechanisms studied are (i) reduction of cell signalling molecule (QSM) production by a constitutively produced agent degrading the messenger RNA of a crucial enzyme (QSE), (ii) lower QSM production rate due to a negative feedback process and (iii) loss of QSMs by binding directly to a constitutively produced agent; the first two mechanisms are known to be employed by the pathogenic bacterium Pseudomonas aeruginosa and the last is relevant to the plant pathogen Agrobacterium tumefaciens. The modelling approach assumes that the bacterial colony consists of two sub-populations, namely down-and up-regulated cells, that differ in the rates at which they produce QSMs, while QSM concentration governs the switching between sub-populations. Parameter estimates are obtained by curve-fitting experimental data (involving P. aeruginosa growth in liquid culture, obtained as part of this study) to solutions of model (1). Asymptotic analysis of the model (1) shows that mechanism (i) is necessary, but not sufficient, to predict the observed saturation of QSM levels in an exponentially growing colony; either mechanism (ii) or (iii) also needs to be incorporated to obtain saturation. Consequently, only a fraction of the population will become up-regulated. Furthermore, only mechanisms (i) and (iii) effect the main timescales for up regulation. Repression was found to play less significant role in a biofilms, but mechanisms (i)-(iii) were nevertheless found to reduce the ulitimate up-regulated cell fraction and mechanisms (i) and (iii) increase the timescale for substantial up regulation and decrease the wave speed of an expanding front of QS activity.

Mathematical Modelling of Bacterial Quorum Sensing: A Review

“…Ward et al (2004) presented a mathematical model to investigate three of these mechanisms: the first two involve reducing the signalling molecule production (1) by a constitutively produced agent (background inhibition), and (2) due to a negative feedback process. These two processes are employed by P. aeruginosa.…”

“…The biofilm is viewed as a multiphase fluid whose growth is governed by nutrients that diffuse from the surrounding fluid. They extended Anguige's series of papers (Anguige et al 2004(Anguige et al , 2005(Anguige et al , 2006 on QS inhibitors, which are based on Ward et al (2001Ward et al ( , 2004. The model is for the LasRI QS System of P. aeruginosa.…”

Thin-film modelling of biofilm growth and quorum sensing

“…The issue that motivated our earlier biofilm model [36] was to determine under what conditions bacterial QS would be significant in advancing biofilm development; the QS aspects of the modelling here is discussed in more detail in [35,37]. We assume, as in that earlier model, that bacteria can swap between two sub-populations, namely up-regulated (volume fraction n u (x, t), wherex = (x, y, z)) and down-regulated (volume fraction n d (x, t)) cells, dependent on the presence of QS molecules (QSMs, concentration a(x, t)); the total volume fraction of cells is thus n u + n d = 1 − ν.…”

“…The right-hand side of (8) describes, in order, QSM diffusion, production by up-regulated cells, production by down-regulated cells, loss via protein-QSM complex formation (either that which binds, αan d , or that which does not bind, η(1 − ν), to the lux-box relevant promoter site) and, lastly, natural decay with rate constant λ. The quantity g(a) ∈ [0, 1] describes a negative feedback pathway, namely, the RsaL system in P. aeruginosa, which is up-regulated by QS which in turn interferes with QSM output; this process is discussed further in [37].…”

Invasion and Survival of Salmonella in the Environment: The Role of Biofilms

“…The specific threshold level can be different for each population. Examples of density-dependent changes include the turning on of bioluminescence within Vibrio fischeri, conjugal transfer in Agrobacterium tumefaciens, swarming in Serratia liquefacians, production of virulence factors in Burkholderia cepacia and Pseudomonas aeruginosa, and biofilm formation in numerous species including Pseudomonas aeruginosa, Pantoea stewartii and Vibrio cholera (Bottomley et al, 2007;Davies et al, 1997;Nadell et al, 2008;Ward et al, 2004).…”