Related Experiment Video
Updated: Jun 18, 2026

Nanomechanics of Drug-target Interactions and Antibacterial Resistance Detection
Published on: October 25, 2013
Fiber-integrated cantilever-based nanomechanical biosensors as a tool for rapid antibiotic susceptibility testing
Jie Zhou1,2, Jiabin Huang1,2, Haoqiang Huang1,2
1Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China.
Abstract:
There is an urgent need for developing rapid and affordable antibiotic susceptibility testing (AST) technologies to inhibit the overuse of antibiotics. In this study, a novel microcantilever nanomechanical biosensor based on Fabry-Pérot interference demodulation was developed for AST. To construct the biosensor, a cantilever was integrated with the single mode fiber in order to form the Fabry-Pérot interferometer (FPI). After the attachment of bacteria on the cantilever, the fluctuations of cantilever caused by the bacterial movements were detected by monitoring the changes of resonance wavelength in the interference spectrum. We applied this methodology to Escherichia coli and Staphylococcus aureus, showing the amplitude of cantilever's fluctuations was positively related on the quantity of bacteria immobilized on the cantilever and associated with the bacterial metabolism. The response of bacteria to antibiotics was dependent on the types of bacteria, the types and concentrations of antibiotics. Moreover, the minimum inhibitory and bactericidal concentrations for Escherichia coli were obtained within 30 minutes, demonstrating the capacity of this method for rapid AST. Benefiting from the simplicity and portability of the optical fiber FPI-based nanomotion detection device, the developed nanomechanical biosensor in this study provides a promising technique for AST and a more rapid alternative for clinical laboratories.
Related Concept Videos
Microbial Biosensors
Rapid Identification of Pathogens
Automated Microbial Diagnostics

