Determination of brain injury biomarkers by surface-enhanced Raman scattering using hollow gold nanospheres

The development of rapid, highly sensitive detection methods for neuron-specific enolase (NSE) and S100-beta protein is very important as the levels of NSE and S100-beta protein in the blood are closely related to brain injury. Therefore, we can use NSE and S100-beta protein concentration detection to realize the preliminary judgment of brain injury. In this paper, we report that a simple label-free three dimensional hierarchical plasmonic nano-architecture has been designed for the sensitive surface-enhanced Raman scattering immunosensor detection of NSE and S100-beta. Owing to the active group of the hollow gold nanospheres (HAuNPs), the redox molecules 4-mercaptobenzoic acid (4-MBA) and Nile blue A (NBA) absorb antibodies and provide signal generation. The prepared HAuNPs@4-MBA and HAuNPs@NBA are used as probes to easily construct a surface-enhanced Raman scattering immunosensor. When protein biomarkers are present, the sandwich nanoparticles are captured over the substrate, forming a confined plasmonic field, leading to an enhanced electromagnetic field in intensity and in space. As a result, the Raman reporter molecules are exposed to a high density of "hot spots", which remarkably amplify the Raman signal, improving the sensitivity of the surface-enhanced Raman scattering immunosensor. Under the optimized conditions, the linear range of the proposed immunosensor is from 0.2 to 22 ng mL(-1) for both NSE and S100-beta. The lowest detectable concentration is 0.1 and 0.06 ng mL(-1) for NSE and S100-beta, respectively. The assay results for serum samples with the proposed method were in a good agreement with the standard enzyme-linked immunosorbent assay method. The proposed immunosensor is promising in clinical diagnosis. This method, which utilizes the surface-enhanced Raman scattering of HAuNPs, has great potential in the detection of biomarkers, which are vital in medical diagnoses and disease monitoring.