Investigations and evaluation of gold nanoparticle chemiresistor sensors platform for rapid antibiotic susceptibility testing

<p dir="ltr">The escalating threat of antimicrobial resistance (AMR) demands innovative solutions for rapid and accurate Antibiotic Susceptibility Testing (AST). This doctoral thesis explores groundbreaking approaches employing gold nanoparticle (AuNP) chemiresistor sensors to advance phenotypic AST by focusing on investigating the AuNP sensor’s ability to distinguish bacteria based on signature metabolites. The first of this study investigates a novel AuNP sensor array's capability to differentiate drug-sensitive from drug-resistant gram-negative bacteria strains. Leveraging the unique electrical resistance changes in response to bacterial metabolite variations during growth and antibiotic exposure, the AuNP sensor array exhibited promising results across various culture media, including Muller Hinton broth, Minimal Media A, and urine. By designing a sensor array comprising of hydrophobic and hydrophilic thiol-functionalized AuNPs, the investigations successfully determined the AST profile for <i>Escherichia coli</i> and <i>Acinetobacter baumannii</i>. This approach demonstrated the sensor's ability to identify distinct metabolite patterns, effectively distinguishing between live and dead bacteria, with a particular focus on β-lactam antibiotics. Preliminary metabolomics analyses provided insights into the specific metabolites correlating with bacterial viability or death. The second study involved the utilisation of bacterial osmoregulation as a novel protocol for determining microorganism viability, independent of cultivation, in the context of AST. This label-free and rapid method relies on the response of AuNP chemiresistor sensors to osmotic stress induced by bacterial osmoregulatory proteins. These investigations lead to findings that successfully demonstrated the protocol's efficacy in distinguishing live from heat-killed bacteria and extended its applicability to AST, particularly with<i> E. coli</i> and <i>S. aureus</i>, using various antibiotics. Hydrophobic sensors exhibited heightened responses to dead bacteria, while semi-hydrophilic sensors were more responsive to live bacteria. Further studies explored the impact of osmotic pressure on sensor responses, revealing enhanced sensitivity in concentrated media. Notably, the osmoregulation protocol and the AuNP sensor array showcased potential in differentiating bacterial susceptibility levels based on medium salinity and osmolyte release. This label-free assessment for AST presents a notable departure from traditional methods reliant on cell multiplication, offering a rapid and effective alternative for bacterial characterization. This thesis represents an advancement in rapid AST, incorporating innovative sensor technologies and methodologies rooted in metabolite detection and bacterial osmoregulation. The integration of these approaches holds promise for transforming clinical decision-making, infectious disease management, and antimicrobial stewardship, subject to further validation across diverse microorganisms, antibiotics, and sample types in future research.</p>