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 B. pertussis as the model organism, it is a slowly growing Gram-negative bacteria which is the agent of whooping cough. It was previously demonstrated that B. pertussis can expresses different phenotypes as a function of the physical-chemical properties of the environment. In this contribution, we highlight that B. pertussis generates a cantilever movement pattern that depends on its phenotype. More precisely, we noticed that nanometric scale oscillations of B. pertussis 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.