Magnetically Assisted Surface-Enhanced Raman Scattering Selective Determination of Dopamine in an Artificial Cerebrospinal Fluid and a Mouse Striatum Using Fe3O4/Ag Nanocomposite

• Published in: Analytical chemistry (Washington) Vol. 86; no. 6; pp. 2939 - 2946
• Main Authors: Ranc, Vaclav, Markova, Zdenka, Hajduch, Marian, Prucek, Robert, Kvitek, Libor, Kaslik, Josef, Safarova, Klara, Zboril, Radek
• Format: Journal Article
• Language: English
• Published: American Chemical Society 18.03.2014
• ISSN: 0003-2700; 1520-6882
• DOI: 10.1021/ac500394g

The dopaminergic neural system is a crucial part of the brain responsible for many of its functions including mood, arousal, and other roles. Dopamine is the key neurotransmitter of this system, and a determination of its level presents a demanding task needed for a deeper understanding of the processes, even pathological, involving this brain part. In this work, we present a method for a fast analysis of dopamine levels in samples of cerebrospinal fluid and mouse striatum. The method is based on a nanocomposite composed of magnetite and silver nanoparticles, whose surface is modified with iron nitriloacetic acid (Fe-NTA)a dopamine-selective compound. The magnetic properties of this nanocomposite enable simple separation of targeted molecules from a complex matrix while the silver acts as a platform for surface-enhanced Raman scattering (SERS). Silver and magnetite nanoparticles are joined by carboxymethyl chitosan, useful in biological environments and enhancing the sensitivity due to the presence of carboxyl groups. This system reveals a good stability and reproducibility. Moreover, rapid and simple quantitative experiments show an improvement in the detection of dopamine levels in biological assays at low femtomolar concentrations. The comparative data performed with clinical samples of mouse striatum show that the developed magnetic SERS is a strong alternative to conventional high-performance liquid chromatography–mass spectrometry (HPLC–MS) with even several superior aspects including faster and cheaper analysis and no necessity of sample preconcentration or derivatization.