Abstract
Growing antimicrobial resistance (AMR) is a serious global threat to human health. Current methods to detect resistance include phenotypic antibiotic sensitivity testing (AST), which measures bacterial growth and is therefore hampered by a slow time to obtain results (∼12–24 h). Therefore, new rapid phenotypic methods for AST are urgently needed. Nanomechanical cantilever sensors have recently shown promise for rapid AST but challenges of bacterial immobilization can lead to variable results. Herein, a novel cantilever-based method is described for detecting phenotypic antibiotic resistance within ∼45 min, capable of detecting single bacteria. This method does not require complex, variable bacterial immobilization and instead uses a laser and detector system to detect single bacterial cells in media as they pass through the laser focus. This provides a simple readout of bacterial antibiotic resistance by detecting growth (resistant) or death (sensitive), much faster than the current methods. The potential of this technique is demonstrated by determining the resistance in both laboratory and clinical strains of Escherichia coli (E. coli), a key species responsible for clinically burdensome urinary tract infections. This work provides the basis for a simple and fast diagnostic tool to detect antibiotic resistance in bacteria, reducing the health and economic burdens of AMR.
Highlights
Antimicrobial resistance (AMR) is steadily increasing and poses a major threat to global health, with estimates of AMR leading to 10 million deaths per year and costing the global economy $100tn by 2050.1,2 The increase in AMR has been caused by several factors including the overuse of antibiotics.[3]
When we initially sought to reproduce the Longo method and apply it to clinical samples, a significant issue was found in obtaining consistent bacterial immobilization on the cantilever surface
Bacterial immobilization numbers were found to vary from cantilever to cantilever, from zero/low numbers to very high clumpy immobilization (Figure S1)
Summary
Antimicrobial resistance (AMR) is steadily increasing and poses a major threat to global health, with estimates of AMR leading to 10 million deaths per year and costing the global economy $100tn by 2050.1,2 The increase in AMR has been caused by several factors including the overuse of antibiotics.[3]. Having access to the identity and antibiogram of the pathogen just a few hours earlier could avoid unnecessary costs associated with inappropriate prescribing, increase patient welfare, and reduce the effects of AMR.[5,6] to reduce the damaging effects of AMR, we require solutions in the form of novel diagnostic tools to detect resistance and improve antibiotic stewardship, surveillance, and patient management.[7,8] Recent developments in this field have exploited single-cell methods for faster and more sensitive detection of antibiotic resistance. This novel optical method is able to rapidly detect antibiotic resistance in bacterial solutions with single-cell resolution
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