All-electrical antibiotic susceptibility testing within 30 min using silicon nano transistors

Rapid and reliable antibiotic susceptibility testing (AST) platform is highly desired to select the right antibiotics to treat infectious disease at early stage. Here, we demonstrate rapid ASTs using nanoscale silicon ion-selective field-effect transistor sensors. Our sensors profile bacterial metab...

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Veröffentlicht in:Sensors and actuators. B, Chemical Chemical, 2022-04, Vol.357, p.131458, Article 131458
Hauptverfasser: Xu, Xingxing, Chen, Si, Yu, Yingtao, Virtanen, Petra, Wu, Jiyue, Hu, Qitao, Koskiniemi, Sanna, Zhang, Zhen
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Sprache:eng
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Zusammenfassung:Rapid and reliable antibiotic susceptibility testing (AST) platform is highly desired to select the right antibiotics to treat infectious disease at early stage. Here, we demonstrate rapid ASTs using nanoscale silicon ion-selective field-effect transistor sensors. Our sensors profile bacterial metabolic kinetics by monitoring the metabolism induced acidification in the growth media with the absence and the presence of different antibiotics. Rapid AST results could be determined from the metabolic profiles with a total assay time less than 30 min for different bacterial strains. In addition, the sensors could also distinguish the bactericidal mechanisms for antibiotics with different modes of actions. Furthermore, the initial bacterial concentration in an unknown sample, a key parameter to determine its clinic relevance, could be estimated based on the metabolic profiles. Our demonstrated AST method is all-electrical, label-free and silicon technology compatible, and holds great promise for the development of a high-throughput and low-cost point-of-care device. [Display omitted] •All-electrical, label-free and silicon technology compatible AST method.•Monitoring the metabolism induced acidification in the growth media.•Rapid AST results determined with a total assay time less than 30 min.•Distinguish the bactericidal mechanisms for antibiotics with different modes of actions.•Quantify the initial bacterial concentration in an unknown sample based on the metabolic profiles.
ISSN:0925-4005
1873-3077
1873-3077
DOI:10.1016/j.snb.2022.131458