Novel therapies for the prevention and management of orthopaedic biomaterial associated Staphylococcus aureus infections
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Date
08/12/2021Author
Tsang, Shao-Ting Jerry
Metadata
Abstract
The use of implanted biomaterials to augment the human body in the
treatment of musculoskeletal conditions is one of the great successes of
modern medicine. However implanted biomaterials create a unique ecological
niche for bacteria to exploit; often resulting in recalcitrant infections that are
refractory to conventional antimicrobial drug therapies. Compounding this
complex clinical problem is the loss of treatment options through the global rise
in antimicrobial resistance, which threaten to halt elective orthopaedic
biomaterial-associated procedures. An evaluation of Staphylococcus aureus
screening and eradication programmes revealed that the use of molecular
diagnostics or pre-enrichment culture improved detection of MSSA
colonisation. Adoption of these screening techniques was estimated to prevent
~1200 cases of prosthetic joint infections annually (potentially saving £160
million in treatment costs). A novel in vitro biofilm model was developed and
shown to be reproducible and suitably responsive to clinically-relevant
antimicrobial challenges. It was found that the bacteriostatic antimicrobials
commonly used in PJI management antagonised gentamicin action when used
against staphylococcal biofilms. A clinically-acceptable concentration of acetic
acid (5%) and a bacterial endopeptidase, lysostaphin (100μg/mL), were shown
to be effective in the eradication of S. aureus biofilms. The use of a machine
learning segmentation algorithm to perform quantitative image analysis of
biofilms was shown to be feasible. Low intensity pulsed ultrasound therapy
potentiated the eradication effect of gentamicin on S. aureus biofilms, bringing
it to within clinically achievable levels. Metabolic pathways critical in the
reversal of gentamicin tolerance within biofilm-associated S. aureus were
identified using a metabolomic approach. This thesis identified shortcomings
in current preventative and therapeutic approaches to S. aureus biomaterial-associated infections. It also validated a novel in vitro biofilm model and
demonstrated the feasibility of machine learning image analysis in biofilm
studies. Finally, novel non-drug therapies were shown to have potential in the
management of biomaterial-associated S. aureus infections.