![Quantitative SERS Detection of Uric Acid via Formation of Precise Plasmonic Nanojunctions within Aggregates of Gold Nanoparticles and Cucurbit[n]uril](/_next/image?url=https%3A%2F%2Fcloudfront.jove.com%2FCDNSource%2Fteasers%2F61682.jpg&w=3840&q=50)
Prussian blue (PB) modified gold nanoparticles as a SERS-based sensing platform for capturing and detection of
Chen Liu1, Gabriel Jiménez-Avalos2, Wen-Shu Zhang3
1Leibniz Institute of Photonic Technology, Member of Leibniz Health Technologies, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert-Einstein-Straße 9, 07745, Jena, Germany; Institute of Physical Chemistry (IPC) and Abbe Center of Photonics (ACP), Friedrich Schiller University Jena, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Helmholtzweg 4, 07743, Jena, Germany.
Abstract:
Pyrazinoic acid (POA) is a metabolite of the anti-tuberculosis drug pyrazinamide (PZA), and its detection can be used to assess the resistance of Mycobacterium tuberculosis in cultures, as only sensitive strains of the bacteria can metabolize PZA into POA. Prussian blue is a well-known metal-organic framework compound widely used in various sensing platforms such as electrochemical, photochemical, and magnetic sensors. In this study, we present a novel sensing platform based on Prussian blue-modified gold nanoparticles (AuNPs) designed to enhance the affinity of POA towards the sensing surface and to capture POA molecules from aqueous solutions. This SERS-based method allows for the selective enrichment of POA, which can be detected in both pure aqueous solution and in the presence of its pro-drug PZA. The limit of detection (LOD) for POA was estimated to be 1.08 μM in pure aqueous solution and 0.18 mM in the presence of PZA. Furthermore, the precision of the SERS method was verified by the relative standard deviation (RSD) of 3.34-12.02% for three parallel samples using different matrices, i.e. aqueous solution, spiked river water and spiked simulated saliva. The recoveries of the samples ranged from 92.65 to 118.51%. These all demonstrate the potential application of the proposed detection scheme in medical research.
