Deterministic and stochastic modelling of endosome escape by Staphylococcus aureus: ?quorum? sensing by a single bacterium

Koerber, Adrian; King, John R.; Williams, Paul

doi:10.1007/s00285-004-0296-0

Cited by 23 publications

(19 citation statements)

References 23 publications

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“…Production of AI-2 by growing bacteria within mammalian tissues may also serve to control gene expression via self-induction. Related to that hypothesis, it has also been suggested that isolated bacteria may utilize pheromones such as AI-2 to sense the permeability of their surroundings (29,40).…”

Section: Discussionmentioning

confidence: 99%

Synthesis of Autoinducer 2 by the Lyme Disease Spirochete,Borrelia burgdorferi

et al. 2005

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Defining the metabolic capabilities and regulatory mechanisms controlling gene expression is a valuable step in understanding the pathogenic properties of infectious agents such as Borrelia burgdorferi. The present studies demonstrated that B. burgdorferi encodes functional Pfs and LuxS enzymes for the breakdown of toxic products of methylation reactions. Consistent with those observations, B. burgdorferi was shown to synthesize the end product 4,5-dihydroxy-2,3-pentanedione (DPD) during laboratory cultivation. DPD undergoes spontaneous rearrangements to produce a class of pheromones collectively named autoinducer 2 (AI-2). Addition of in vitro-synthesized DPD to cultured B. burgdorferi resulted in differential expression of a distinct subset of proteins, including the outer surface lipoprotein VlsE. Although many bacteria can utilize the other LuxS product, homocysteine, for regeneration of methionine, B. burgdorferi was found to lack such ability. It is hypothesized that B. burgdorferi produces LuxS for the express purpose of synthesizing DPD and utilizes a form of that molecule as an AI-2 pheromone to control gene expression.

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Section: Discussionmentioning

confidence: 99%

Synthesis of Autoinducer 2 by the Lyme Disease Spirochete,Borrelia burgdorferi

et al. 2005

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“…swimming, foraging) Tang et al (2007), van Gestel et al (2012) Virulence Pseudomonas aeruginosa Dockery and Keener (2001), Fagerlind et al (2003Fagerlind et al ( , 2005, Viretta and Fussenegger (2004), Netotea et al (2009) AHL, AHQ Koerber et al (2005), Jabbari et al (2010), Gustafsson et al (2004) AIP Escherichia coli Li et al (2006) AI-2, Indole Lee et al (2007) See Taga and Bassler (2003), Miller and Bassler (2001) and West et al (2012) for a more comprehensive list. Note that not all models concentrate on a particular bacterium…”

Section: Hunter Et Al (2013) Ahlmentioning

confidence: 99%

Mathematical Modelling of Bacterial Quorum Sensing: A Review

2016

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Bacterial quorum sensing (QS) refers to the process of cell-to-cell bacterial communication enabled through the production and sensing of the local concentration of small molecules called autoinducers to regulate the production of gene products (e.g. enzymes or virulence factors). Through autoinducers, bacteria interact with individuals of the same species, other bacterial species, and with their host. Among QS-regulated processes mediated through autoinducers are aggregation, biofilm formation, bioluminescence, and sporulation. Autoinducers are therefore "master" regulators of bacterial lifestyles. For over 10 years, mathematical modelling of QS has sought, in parallel to experimental discoveries, to elucidate the mechanisms regulating this process. In this review, we present the progress in mathematical modelling of QS, highlighting the various theoretical approaches that have been used and discussing some of the insights that have emerged. Modelling of QS has benefited almost from the onset of the involvement of experimentalists, with many of the papers which we review, published in non-mathematical journals. This review therefore attempts to give a broad overview of the topic to the mathematical biology community, as well as the current modelling efforts and future challenges.B Judith Pérez-Velázquez

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“…. Mathematical models of stall and infected wounds with focus on host tissue degradation by bacteria or quorum-sensing by bacteria have also been considered [12,13,14,15,16,31]. These papers provide complex models expressed as deterministic reaction-diffusion equations that must be solved numerically.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Bacteria on Epidermal Wound Healing

Agyingi

Maggelakis

Ross

2010

Math. Model. Nat. Phenom.

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Abstract. Epidermal wound healing is a complex process that repairs injured tissue. The complexity of this process increases when bacteria are present in a wound; the bacteria interaction determines whether infection sets in. Because of underlying physiological problems infected wounds do not follow the normal healing pattern. In this paper we present a mathematical model of the healing of both infected and uninfected wounds. At the core of our model is an account of the initiation of angiogenesis by macrophage-derived growth factors. We express the model as a system of reaction-diffusion equations, and we present results of computations for a version of the model with one spatial dimension.

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Deterministic and stochastic modelling of endosome escape by Staphylococcus aureus: ?quorum? sensing by a single bacterium

Cited by 23 publications

References 23 publications

Synthesis of Autoinducer 2 by the Lyme Disease Spirochete,Borrelia burgdorferi

Synthesis of Autoinducer 2 by the Lyme Disease Spirochete,Borrelia burgdorferi

Mathematical Modelling of Bacterial Quorum Sensing: A Review

The Effect of Bacteria on Epidermal Wound Healing

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