Influence of biologically inspired nanometer surface roughness on antigen–antibody interactions for immunoassay–biosensor applications

Current research efforts to improve immunoassay–biosensor functionality have centered on detection through the optimal design of microfluidic chambers, electrical circuitry, optical sensing elements, and so on. To date, little attention has been paid to the immunoassay–biosensor membrane surface on which interactions between antibodies and antigens must occur. For this reason, the objective of the present study was to manipulate the nanometer surface roughness of a model immunoassay–biosensor membrane to determine its role on sensitivity and specificity. It was hypothesized that surface roughness characteristics similar to those used by the body’s own immune system with B-lymphocyte cell membranes would promote antigen-antibody interactions and minimize non-specific binding. To test this hypothesis, polystyrene 96-well plate surfaces were modified to possess similar topographies as those of B-lymphocyte cell membranes. This was accomplished by immobilizing Protein A conjugated gold particles and Protein A conjugated polystyrene particles ranging in sizes from 40 to 860 nm to the bottom of polystyrene wells. Atomic force microscopy results provided evidence of well-dispersed immunoassay–biosensor surfaces for all particles tested with high degrees of biologically inspired nanometer roughness. Testing the functionality of these immunosurfaces using antigenic fluorescent microspheres showed that specific antigen capture increased with greater nanometer surface roughness while nonspecific antigen capture did not correlate with surface roughness. In this manner, results from this study suggest that large degrees of biologically inspired nanometer surface roughness not only increases the amount of immobilized antibodies onto the immunosurface membrane, but it also enhances the functionality of those antibodies for optimal antigen capture, criteria critical for improving immunoassay–biosensor sensitivity and specificity.