Rapid and real-time monitoring of bacterial growth against antibiotics in solid growth medium using a contactless planar microwave resonator sensor

Abstract Infection diagnosis and antibiotic susceptibility testing (AST) are pertinent clinical microbiology practices that are in dire need of improvement, due to the inadequacy of current standards in early detection of bacterial response to antibiotics and affordability of contemporarily used met...

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Autores principales: Mandeep Chhajer Jain, Anupama Vijaya Nadaraja, Rakesh Narang, Mohammad Hossein Zarifi
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/dfde7163faa1486aaccdc2ffa9d911f5
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Sumario:Abstract Infection diagnosis and antibiotic susceptibility testing (AST) are pertinent clinical microbiology practices that are in dire need of improvement, due to the inadequacy of current standards in early detection of bacterial response to antibiotics and affordability of contemporarily used methods. This paper presents a novel way to conduct AST which hybridizes disk diffusion AST with microwave resonators for rapid, contactless, and non-invasive sensing and monitoring. In this research, the effect of antibiotic (erythromycin) concentrations on test bacterium, Escherichia coli (E. coli) cultured on solid agar medium (MH agar) are monitored through employing a microwave split-ring resonator. A one-port microwave resonator operating at a 1.76 GHz resonant frequency, featuring a 5 mm2 sensitive sensing region, was designed and optimized to perform this. Upon introducing uninhibited growth of the bacteria, the sensor measured 0.005 dB/hr, with a maximum change of 0.07 dB over the course of 15 hours. The amplitude change decreased to negligible values to signify inhibited growth of the bacteria at higher concentrations of antibiotics, such as a change of 0.005 dB in resonant amplitude variation while using 45 µg of antibiotic. Moreover, this sensor demonstrated decisive results of antibiotic susceptibility in under 6 hours and shows great promise to expand automation to the intricate AST workflow in clinical settings, while providing rapid, sensitive, and non-invasive detection capabilities.