Optimized immobilization of gold nanoparticles on planar surfaces through alkyldithiols and their use to build 3D biosensors

Abstract

This paper describes a controlled way to immobilize gold nanoparticles on planar gold surfaces and the use of the resulting 3D platform to build up a 3D biosensor. The surface was first functionalized by grafting hexanedithiol, this molecule has 2 thiol end groups, which enables its chemical grafting to planar gold while retaining a free thiol group to attach nanoparticles. This step was optimized by varying experimental parameters such as solvent, temperature and immersion time. The grafting was monitored by polarization modulation infrared reflection absorption spectroscopy (PM-IRRAS) and X-ray photoelectron spectroscopy (XPS). The high resolution XPS sulfur peak made clear the existence of two contributions, S bound to gold and free S, thus led us to determine the optimal conditions to graft hexanedithiol in an extended conformation. 15 nm spherical gold nanoparticles were then immobilized on the resulting surface and their presence was evidenced by surface enhanced Raman spectroscopy (SERS) and atomic force microscopy (AFM). The resulting gold layer was used to build up a 3D biosensor by grafting protein A (PrA), rabbit immunoglobulin (rIgG), and bovine serum albumin (BSA), respectively. Each step was characterized by PM-IRRAS then compared to the results on planar gold surface. Despite the small size of particles and their rather low density on the planar surface, the amount of immobilized proteins, starting from PrA, was almost doubled. The amount of rIgG fixed on the 3D layer was also significantly increased (∼4 times higher than on planar surfaces), however accompanied by a slight decrease of their accessibility, checked by assaying the recognition of a secondary IgG. This work demonstrates the feasibility and interest of building arrays of nanoparticles to immobilize molecular receptors; it also shows that controlling the conditions of elaboration of the biosensor at each step is determining for optimizing the number of molecular receptors.