Label-Free Analysis of Protein Biomarkers Using Pattern-Optimized Graphene-Nanopyramid SERS for the Rapid Diagnosis of Alzheimer’s Disease

Abstract

The quantitative and highly sensitive detection of biomarkers such as Tau proteins and Aβ polypeptides is considered one of the most effective methods for the early diagnosis of Alzheimer’s disease (AD). Surface-enhanced Raman spectroscopy (SERS) detection is a promising method that faces, however, challenges like insufficient sensitivity due to the non-optimized nanostructures for specialized analyte sizes and insufficient control of the location of SERS hot spots. Thus, the SERS detection of AD biomarkers is restricted. We reported here an in-depth study of the analytical Raman enhancement factor (EF) of the wafer-scale graphene-Au nanopyramid hybrid SERS substrates using a combination of both theoretical calculation and experimental measurements. Experimental results show that larger nanopyramids and smaller gap spacing lead to a larger SERS EF, with an optimized analytical EF up to 1.1 × 1010. The hybrid SERS substrate exhibited detection limits of 10–15 M for Tau and phospho-Tau (P-Tau) proteins and 10–14 M for Aβ polypeptides, respectively. Principal component analysis correctly categorized the SERS spectra of different biomarkers at ultralow concentrations (10–13 M) using the optimized substrate. Amide III bands at 1200–1300 cm–1 reflect different structural conformations of proteins or polypeptides. Tau and P-Tau proteins are inherently disordered with a few α-helix residuals. The structure of Aβ42 polypeptides transitioned from the α-helix to the β-sheet as the concentration increased. These results demonstrate that the hybrid SERS method could be a simple and effective way for the label-free detection of protein biomarkers to enable the rapid early diagnosis of AD and other diseases