Gold nanoparticles (AuNPs) are some of the most extensively studied nanomaterials. Because of their unique optical, chemical, electrical, and catalytic properties, AuNPs have attracted enormous amount of interest for applications in biological and chemical detection and analysis. The purpose of this critical review is to provide the readers with an update on the recent developments in the field of AuNPs for sensing applications based on their optical properties. An overview of the optical properties of AuNPs is presented first, followed by a more detailed literature survey. As the last part of this review, we compare the advantages and disadvantages of each technique, briefly discuss their commercialization status, and some technical issues that remain to be solved in order to move the technique forward (151 references).

The detection limit is one of the most important performance parameters for bioanalytical techniques. Here we present a generic method to estimate the detection limit of biomolecular assays based on a step-by-step analysis of the assay procedure. Enzyme-linked immunosorbent assay (ELISA) is used here as an example; however, much of the information presented in this article may be applied to other types of biomolecular assays and analytical techniques. A clear understanding of what affects the detection limit can help researchers to evaluate different bio-analytical techniques properly, and to design better strategies to optimize and achieve the best analytical performance.

In recent years, there has been considerable interest and research activity in using gold nanoparticle materials for biomedical applications including biomolecular detection, bioimaging, drug delivery, and photothermal therapy. In order to apply gold nanoparticles in the real biological world, we need to have a better understanding of the potential interactions between gold nanoparticle materials and biomolecules in vivo and in vitro. Here, we report the use of dynamic light scattering (DLS) for gold nanorods characterization and nanorod–protein interaction study. In the size distribution diagram, gold nanorods with certain aspect ratios exhibit two size distribution peaks, one with an average hydrodynamic diameter at 5–7 nm, and one at 70–80 nm. The small size peak is attributed to the rotational diffusion of the nanorods instead of an actual dimension of the nanorods. When proteins are adsorbed to the gold nanorods, the average particle size of the nanorods increases and the rotational diffusion-related size distribution peak also changes dramatically. We examined the interaction between four different proteins, bovine serum albumin, human serum albumin, immunoglobulin G, and immunoglobulin A (IgA) with four gold nanorods that have the same diameter but different aspect ratios. From this study, we found that protein adsorption to gold nanorods is strongly dependent on the aspect ratio of the nanorods, and varies significantly from protein to protein. The two serum albumin proteins caused nanorod aggregation upon interaction with the nanorods, while the two immunoglobulin proteins formed a stable protein corona on the nanorod surface without causing significant nanorod aggregation. This study demonstrates that DLS is a valuable tool for nanorod characterization. It reveals information complementary to molecular spectroscopic techniques on gold nanorod–protein interactions.

Gold nanoparticles (AuNPs) scatter light intensely at or near their surface plasmon wavelength region. Using AuNPs coupled with dynamic light scattering (DLS) detection, we developed a facile nanoparticle immunoassay for serum protein biomarker detection and analysis. A serum sample was first mixed with a citrate-protected AuNP solution. Proteins from the serum were adsorbed to the AuNPs to form a protein corona on the nanoparticle surface. An antibody solution was then added to the assay solution to analyze the target proteins of interest that are present in the protein corona. The protein corona formation and the subsequent binding of antibody to the target proteins in the protein corona were detected by DLS.

Over-diagnosis and treatment of prostate cancer has been a major problem in prostate cancer care and management. Currently the most relevant prognostic factor to predict a patient's risk of death due to prostate cancer is the Gleason score of the biopsied tissue samples. However, pathological analysis is subjective, and the Gleason score is only a qualitative estimate of the cancer malignancy. Molecular biomarkers and diagnostic tests that can accurately predict prostate tumor aggressiveness are rather limited.