Detection of antimicrobial susceptibility on microfluidics sensor by electrochemical impedance sensing.

Antimicrobial resistance (AMR) is emerging as a global health threat; even common infections are becoming harder to treat with empirical antibiotics. Antimicrobial susceptibility testing (AST) ensures the current choice of antibiotics for treating specific infections. We explored the impedance characteristic of the bacterial cells at the cell-electrode interface for AST. Impedance changes over time when the bacterial cells grow/die in response to antibiotics. This change in impedance is correlated with the susceptibility profile of bacteria. We employed a microfluidic device with a screen-printed electrode to determine AST. Four carbon electrodes with alternate working and counter electrodes of 0.5 mm were screen printed on a glass slide. To fabricate a PDMS microfluidic device, 3D printed mould was used. The screen-printed electrode and the PDMS device were attached to plasma. The channel was functionalised with poly-L-Lysine to enhance bacterial attachment. Before bacterial attachment, 10% Nutrient Media (NM) impedance was measured. Bacterial suspension of 10⁸ CFU/mL was introduced, and unattached bacteria were washed off. Electrochemical impedance sensing (EIS) was performed with bacteria attached to the electrode of the microfluidic device. The device is then incubated for two hours without antibiotics and used as a positive control (PC). For the test device, we introduced an antibiotic (Ampicillin – 5µg/mL) and the 10% NM at t=0 hr and impedance was measured with respect to time. R_ct decreased in PC, implying bacterial growth, whereas in the test device, there was no change. In PC, R_ct difference can be attributed to the increased electrode coverage due to bacterial growth. The constant R_ct after incubation in the test device suggests the inhibition of bacterial growth in the presence of antibiotics. Using a low conductivity medium and selection of R_ct as a response signal enables the AST even with simple microfluidic geometry. The change in R_ct was related well to the bacterial growth profile. We performed the experiment with resistant bacteria and human samples and got the expected result. The proposed detection system will enable rapid AST detection and allows front-line healthcare workers to perform AST with minimal training.