Predictive modelling of a novel anti-adhesion therapy to combat bacterial colonisation of burn wounds

Paul A. Roberts, Ryan M. Huebinger, Emma Keen, Anne Marie Krachler, Sara Jabbari

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

As the development of new classes of antibiotics slows, bacterial resistance to existing antibiotics is becoming an increasing problem. A potential solution is to develop treatment strategies with an alternative mode of action. We consider one such strategy: anti-adhesion therapy. Whereas antibiotics act directly upon bacteria, either killing them or inhibiting their growth, anti-adhesion therapy impedes the binding of bacteria to host cells. This prevents bacteria from deploying their arsenal of virulence mechanisms, while simultaneously rendering them more susceptible to natural and artificial clearance. In this paper, we consider a particular form of anti-adhesion therapy, involving biomimetic multivalent adhesion molecule 7 coupled polystyrene microbeads, which competitively inhibit the binding of bacteria to host cells. We develop a mathematical model, formulated as a system of ordinary differential equations, to describe inhibitor treatment of a Pseudomonas aeruginosa burn wound infection in the rat. Benchmarking our model against in vivo data from an ongoing experimental programme, we use the model to explain bacteria population dynamics and to predict the efficacy of a range of treatment strategies, with the aim of improving treatment outcome. The model consists of two physical compartments: the host cells and the exudate. It is found that, when effective in reducing the bacterial burden, inhibitor treatment operates both by preventing bacteria from binding to the host cells and by reducing the flux of daughter cells from the host cells into the exudate. Our model predicts that inhibitor treatment cannot eliminate the bacterial burden when used in isolation; however, when combined with regular or continuous debridement of the exudate, elimination is theoretically possible. Lastly, we present ways to improve therapeutic efficacy, as predicted by our mathematical model.

Original languageEnglish (US)
Article numbere1006071
JournalPLoS Computational Biology
Volume14
Issue number5
DOIs
StatePublished - May 1 2018

Fingerprint

Predictive Modeling
bacterial colonization
Adhesion
adhesion
Bacteria
Therapy
colonization
therapeutics
bacterium
bacteria
Cell
Wounds and Injuries
Antibiotics
Exudates and Transudates
antibiotics
Inhibitor
modeling
inhibitor
cells
Efficacy

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Ecology
  • Molecular Biology
  • Genetics
  • Cellular and Molecular Neuroscience
  • Computational Theory and Mathematics

Cite this

Predictive modelling of a novel anti-adhesion therapy to combat bacterial colonisation of burn wounds. / Roberts, Paul A.; Huebinger, Ryan M.; Keen, Emma; Krachler, Anne Marie; Jabbari, Sara.

In: PLoS Computational Biology, Vol. 14, No. 5, e1006071, 01.05.2018.

Research output: Contribution to journalArticle

Roberts, Paul A. ; Huebinger, Ryan M. ; Keen, Emma ; Krachler, Anne Marie ; Jabbari, Sara. / Predictive modelling of a novel anti-adhesion therapy to combat bacterial colonisation of burn wounds. In: PLoS Computational Biology. 2018 ; Vol. 14, No. 5.
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