Abstract
Staphylococcus aureus, an important human pathogen, is the leading cause of infection-related death globally. It stands out as the only bacterial pathogen, apart from Mycobacterium tuberculosis, responsible for over a million fatalities each year. The emergence of antibiotic-resistant strains, such as methicillin-resistant S. aureus (MRSA), has created challenges in detecting S. aureus infections, as treatment depends on identifying the specific strain causing the infection. This study highlights the use of an array-based colorimetric aptasensor platform using aptamers, which exhibit specific binding across different S. aureus strains. This platform generates unique colorimetric fingerprints for different S. aureus strains, thus enabling an unbiased and strain-specific detection system. The unique signatures arise from differences in the dissociation dynamics of aptamers on the surface of nanozymes. The sensor response was analysed using pattern recognition tools trained on responses from the aptasensor array to identify individual S. aureus strains. Furthermore, the sensing platform offers additional functionality by providing information about the virulence factors associated with pathogenicity, such as the presence of markers like Panton-Valentine leukocidin (pvl), which is a marker of increased virulence and sensitivity/resistance to antibiotics. The platform would be capable of recognising previously unencountered S. aureus strains, enabling predictive capabilities and utility in clinical diagnostics.