Affiliation:
1. Research Laboratory of Scanning Probe Microscopy, Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia
2. Department “Nanotechnology and Biotechnology”, Nizhny Novgorod State Technical University named after Alekseev R.E., 603155 Nizhny Novgorod, Russia
Abstract
Objectives: To develop a system for the rapid detection of Acinetobacter baumannii 173-p1 antibiotic resistance (to ensure reliable fixation of bacteria on a cantilever without losing their nanomotion, to show that nanomotion is due to bacterial metabolism, to compare the nanomotion of bacteria in suspension form and inside of the biofilms), to study the sensitivity/resistance of A. baumannii 173-p1 to antibiotics (lincomycin, ceftriaxone and doxycycline) using the oscillation method of atomic force microscopy and to evaluate the sensitivity and speed of the method in comparison with the classical disk diffusion method. Methods: The oscillation mode of atomic force microscopy, scanning electron microscopy and the classical disk diffusion method were used for a complex parallel study of A. baumannii 173-p1 antibiotic resistance, which included testing of fixing agents (poly-L-lysine, rosin and fibronectin), comparison of bacterial metabolism in a set of media (normal saline solution, meat-peptone broth and lysogeny broth) and assessment of antibiotic sensitivity/resistance per se. Results: A method for express testing of Acinetobacter baumannii antibiotic resistance using AFM was developed; it is shown that bacterial nanomotion directly correlates with bacteria metabolic activity and that bacterial nanomotion is more easily detected in suspension form, rather than in biofilms. Conclusion: The express testing method gave results that are completely comparable with the classical disk diffusion test and with the results of morphology studies by the SEM method, but it significantly exceeded them in speed, allowing a conclusion to be made on the sensitivity/resistance of bacteria less than an hour after the start of the diagnostics.
Funder
Russian Science Foundation
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