Time-Lapse Electrochemical Impedance Detection of Bacteria Proliferation for Accurate Antibiotic Evaluation

Abstract

Antibiotic detection includes direct detection and indirect detection. Indirect detection of antibiotic concentration reflected by the change of bacterial concentration is a more intuitive evaluation of antibiotic effect. It can not only accurately evaluate antibiotics, but also be used for tracking evaluation and analysis of antibacterial effects under long-term low-threshold levels. In this paper, a novel method of electrode modification based on AuNPs modified nitrocellulose membrane (NC membrane) was applied to detect bacterial proliferation through electrochemical impedance to accurately quantify antibiotics. The NC-AuNPs-Anti composite membrane was adopted for time-lapse effect of low concentration of amikacin sulfate on E. coli, and the change in AC impedance was analyzed by the equivalent model. t-SNE method was applied to visualize high-dimensional parameters and perform feature screening, and a machine learning model was adopted to accurately predict antibiotics. The experimental results show that this method can reach the antibiotic prediction accuracy of ±2.9E- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$03 ~\mu \text{L}$ </tex-math></inline-formula> /mL at 2, 3, and 4 hours after dosing, so as to provide a better quantitative analysis method for accurate antibiotic evaluation through the electrochemical impedance detection by bacteria proliferation.