Investigating the Effect of Antibody-Antigen Reactions on the Internal Convection in a Sessile Droplet via Microparticle Image Velocimetry and DLVO Analysis.

Abstract

The evaporation of antigen-laden sessile droplets on antibody-immobilized PDMS substrates could be used in place of microwells for detection purposes owing to the lesser requirements of analytes and a reduced reaction time. To develop such techniques, the effects of different parameters on the reaction efficiency and on the resulting deposition patterns of antigens on the surface after evaporation need to be well understood. While the resultant deposition patterns from the evaporation of droplets of biological fluids on surfaces are being studied for various biomedical applications, systems where the analyte of interest in the droplet binds to the surface have not been investigated until now. While the effect of temperature on the internal convection within sessile droplets has been studied, the effect of the analyte (antigen in this work) concentration and the analyte-surface (antigen-antibody in this work) binding on the internal convection has not been studied until now. Therefore, to gain insight, the evaporation dynamics of sessile droplets with different concentrations of antigens along with polystyrene microspheres (used as tracers) in phosphate-buffered saline (PBS) on antibody-immobilized PDMS substrates were experimentally studied using microparticle image velocimetry (PIV). It was found that Marangoni flow due to concentration gradients and surface reactions was responsible for the observed velocity field. The antibody-antigen reaction (as compared to the control case of no surface reaction) and higher concentrations of prostate specific antigen (PSA) resulted in increased strength of Marangoni convection. To obtain further insight into the different deposition patterns obtained, the contributions of different particle-particle and particle-substrate forces were determined, and it was observed that the Marangoni forces along with surface tension and DLVO forces create a uniform deposition of the particles present within the droplet. This learning could be used to design biosensors.