Atomic force microscopy (AFM)-based nanomotion detection is a label-free technique that has been used to monitor the response of microorganisms to antibiotics in a time frame of minutes. The method consists of attaching living organisms onto an AFM cantilever and in monitoring its nanometric scale oscillations as a function of different physical-chemical stimuli. Up to now, we only used the cantilever oscillations variance signal to assess the viability of the attached organisms. In this contribution, we demonstrate that a more precise analysis of the motion pattern of the cantilever can unveil relevant medical information about bacterial phenotype. We used as the model organism, it is a slowly growing Gram-negative bacteria which is the agent of whooping cough. It was previously demonstrated that can expresses different phenotypes as a function of the physical-chemical properties of the environment. In this contribution, we highlight that generates a cantilever movement pattern that depends on its phenotype. More precisely, we noticed that nanometric scale oscillations of can be correlated with the virulence state of the bacteria. The results indicate a correlation between metabolic/virulent bacterial states and bacterial nanomotion pattern and paves the way to novel rapid and label-free pathogenic microorganism detection assays.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8398272 | PMC |
http://dx.doi.org/10.3390/microorganisms9081545 | DOI Listing |
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