Olga I Guliy, Stella S Evstigneeva, Alexander A Shirokov, Victor D Bunin
Applied microbiology and biotechnology 2024 Jan 24The resistance of biofilms to antibiotics is a key factor that makes bacterial infections unsusceptible to antimicrobial therapy. The results of classical tests of cell sensitivity to antibiotics cannot be used to predict therapeutic success in infections associated with biofilm formation. We describe a simple and rapid method for the real-time evaluation of bacterial biofilm sensitivity to antibiotics, with Pseudomonas putida and ampicillin as examples. The method uses an electric biosensor to detect the difference between changes in the biofilm electric polarizability, thereby evaluating antibiotic sensitivity. The electric signals showed that P. putida biofilms were susceptible to ampicillin and that at high antibiotic concentrations, the biofilms differed markedly in their susceptibility (dose-dependent effect). The sensor also detected differences between biofilms before and after ampicillin treatment. The electric-signal changes enabled us to describe the physical picture of the processes occurring in bacterial biofilms in the presence of ampicillin. The approach used in this study is promising for evaluating the activity of various compounds against biofilms, because it permits a conclusion about the antibiotic sensitivity of biofilm bacteria to be made in real time and in a short period (analysis time, not longer than 20 min). An added strong point is that analysis can be done directly in liquid, without preliminary sample preparation. KEY POINTS: • Sensor system to analyze biofilm antimicrobial susceptibility is described. • The signal change depended on the ampicillin concentration (dose-dependent effect). • The sensor allows real-time determination of the antibiofilm effect of ampicillin. © 2024. The Author(s).
Olga I Guliy, Stella S Evstigneeva, Alexander A Shirokov, Victor D Bunin. Sensor system for analysis of biofilm sensitivity to ampicillin. Applied microbiology and biotechnology. 2024 Jan 24;108(1):172
PMID: 38265501
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