1. Development of a High-Throughput ex-Vivo Burn Wound Model Using Porcine Skin, and Its Application to Evaluate New Approaches to Control Wound Infection
- Author
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Diana R. Alves, Simon P. Booth, Paola Scavone, Pascale Schellenberger, Jonathan Salvage, Cinzia Dedi, Naing-Tun Thet, A. Toby A. Jenkins, Ryan Waters, Keng W. Ng, Andrew D. J. Overall, Anthony D. Metcalfe, Jonathan Nzakizwanayo, and Brian V. Jones
- Subjects
ex-vivo burn wound model ,infection ,Staphylococcus aureus ,bacteriophage therapy ,biofilm ,accessory gene regulator ,Microbiology ,QR1-502 - Abstract
Biofilm formation in wounds is considered a major barrier to successful treatment, and has been associated with the transition of wounds to a chronic non-healing state. Here, we present a novel laboratory model of wound biofilm formation using ex-vivo porcine skin and a custom burn wound array device. The model supports high-throughput studies of biofilm formation and is compatible with a range of established methods for monitoring bacterial growth, biofilm formation, and gene expression. We demonstrate the use of this model by evaluating the potential for bacteriophage to control biofilm formation by Staphylococcus aureus, and for population density dependant expression of S. aureus virulence factors (regulated by the Accessory Gene Regulator, agr) to signal clinically relevant wound infection. Enumeration of colony forming units and metabolic activity using the XTT assay, confirmed growth of bacteria in wounds and showed a significant reduction in viable cells after phage treatment. Confocal laser scanning microscopy confirmed the growth of biofilms in wounds, and showed phage treatment could significantly reduce the formation of these communities. Evaluation of agr activity by qRT-PCR showed an increase in activity during growth in wound models for most strains. Activation of a prototype infection-responsive dressing designed to provide a visual signal of wound infection, was related to increased agr activity. In all assays, excellent reproducibility was observed between replicates using this model.
- Published
- 2018
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