Modeling of the Binding Kinetics of Bacteria with Magnetic Nanoparticles in Bioreaction and Magnetic Separation Processes

Abstract

Abstract. Molecular biological interactions with magnetic separation have been used to pretreat samples to capture, separate, and concentrate biological targets in complex samples for further detection. Some simulation models have been developed to predict the magnetic forces applied on magnetic particles (MPs), but very little focus on the biological molecules interactions and diffusion with MPs on a scale lower than 150 nm. In this research, a simulation model was developed with the help of Comsol Multiphysics and Matlab software to describe the diffusion and binding kinetics of all biological materials involved in the biological reactions and magnetic separation processes. The model was constructed based on the properties of bacterial cells, antibodies, and magnetic nanoparticles (MNPs) incorporated with a mixing and a magnetic separation device. Escherichia coli (E. coli) O157:H7 was used to represent the bacteria target. Experiments in this study were conducted to determine some model parameters and to validate the model. The results showed that the developed model could be used to optimize the pretreatment process in terms of biological reaction and separation efficiency as well as time based on MNP size and surface modification, properties of the biological target, and the mixing and magnetic separation device. For one case using E. coli O157:H7 covered with 1 µm MPs, the results indicated that the separation efficiency increased from 50% to 92% as the mixing time was increased from 10 min to 40 min. For the same experiment using 150 nm MNPs, it was found that the separation efficiency of 93% was achieved even without the use of a mixer. Another experiment showed that the separation efficiency increased in an increasing magnetic field strength. However, once the magnetic field strengths became greater than 1.3 T, the bonds between the biological components were disrupted leading to lower separation efficiency. Any optimization to increase binding and separation efficiency and lower time would greatly improve upon current research methods. The model in this research provides a powerful tool in the optimization of biological reaction and magnetic separation involving E. coli with a great potential for other bacteria, viruses, and cells.