1. Non-invasive in vivo sensing of bacterial implant infection using catalytically-optimised gold nanocluster-loaded liposomes for urinary readout
- Author
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Kaili Chen, Adrian Najer, Patrick Charchar, Catherine Saunders, Chalaisorn Thanapongpibul, Anna Klöckner, Mohamed Chami, David J. Peeler, Inês Silva, Luca Panariello, Kersti Karu, Colleen N. Loynachan, Leah C. Frenette, Michael Potter, John S. Tregoning, Ivan P. Parkin, Andrew M. Edwards, Thomas B. Clarke, Irene Yarovsky, and Molly M. Stevens
- Subjects
Science - Abstract
Abstract Staphylococcus aureus is a leading cause of nosocomial implant-associated infections, causing significant morbidity and mortality, underscoring the need for rapid, non-invasive, and cost-effective diagnostics. Here, we optimise the synthesis of renal-clearable gold nanoclusters (AuNCs) for enhanced catalytic activity with the aim of developing a sensitive colourimetric diagnostic for bacterial infection. All-atom molecular dynamics (MD) simulations confirm the stability of glutathione-coated AuNCs and surface access for peroxidase-like activity in complex physiological environments. We subsequently develop a biosensor by encapsulating these optimised AuNCs in bacterial toxin-responsive liposomes, which is extensively studied by various single-particle techniques. Upon exposure to S. aureus toxins, the liposomes rupture, releasing AuNCs that generate a colourimetric signal after kidney-mimetic filtration. The biosensor is further validated in vitro and in vivo using a hyaluronic acid (HA) hydrogel implant infection model. Urine samples collected from mice with bacteria-infected HA hydrogel implants turn blue upon substrate addition, confirming the suitability of the sensor for non-invasive detection of implant-associated infections. This platform has significant potential as a versatile, cost-effective diagnostic tool.
- Published
- 2024
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