Manipulation with atomic force microscopy: DNA and yeast micro/nanoparticles in biological environments

Abstract

Although significant attempts have been made to automate the manipulation of biological cells with atomic force microscopy, these efforts have faced many limitations and restrictions. Researchers have recently tried to measure the interacting forces in order to improve the reliability of manipulation operations with atomic force microscopy. By manipulation of micro/nanoparticles of different materials and shapes, as the target particles, in different biological environments, the interacting forces existing between these micro/nanoparticles and the biological environment will be different from those in the air medium. Therefore, in this paper, first, a general overview and simulation of the important forces acting in the biological environment was presented, and forces such as the adhesion force, hydration force and the electrostatic double-layer force were modeled and simulated in different environments (e.g. water, alcohol and blood plasma). After different biological environments (in comparison with the air medium) were explored and modeled, the manipulation operations with atomic force microscopy were simulated for different micro/nanoparticles such as gold, DNA and yeast by considering the forces existing in various biological environments. The results of manipulation in this paper indicate that in the air and liquid environments, the biological particles (DNA and yeast) will start to move after a longer time and by a higher magnitude force relative to the gold particles. This outcome is predictable, given the properties and stickiness of the biological particles. Also by comparing the obtained results, it is found that the critical force and critical time of manipulation with atomic force microscopy for gold nanoparticles slightly increase in water relative to air, which can be due to the properties of water and the existing forces in water that resist against the movement of nanoparticles. Finally, the obtained results were compared with the available empirical results. It can be seen that the obtained simulation values have a good correlation with the empirical results. The closeness of these two values confirms the validity of the performed simulation.