SERS detection of dopamine in artificial cerebrospinal fluid and in Parkinson’s disease-induced mouse cortex using a hybrid ZnO@Ag nanostructured platform

• We demonstrated that nanopatterned hybrid SERS substrates detected DA in µM levels. • Artificial cerebrospinal fluid and mouse brain tissue were used for spectral pathology. • SERS combined with PCA and ELISA helped discriminating healthy or PD-induced mice. Rapid, direct, and sensitive detection of metabolites or clinically relevant biomarkers in complex biological samples is still challenging. We report a label-free surface-enhanced Raman scattering (SERS)-based approach for highly sensitive detection of dopamine (DA) in artificial cerebrospinal fluid (aCSF) and mouse brain tissue samples. The hybrid SERS-active sensing platform was designed to maximize the hot spot distribution. It encompasses a network of flexible and polymeric nanotrenches and nanogaps fabricated by nanoimprint lithography (NIL) covered by thin films of zinc oxide (ZnO) and silver (Ag) deposited using pulsed laser deposition (PLD) and direct current magnetron sputtering (DC-MS), respectively. The growth of the ZnO and Ag thin films was assessed by scanning electron microscopy (SEM) technique. The proposed SERS substrate benefits from the interlayered semiconductor–metal contribution in SERS enhancement, leading to a versatile sensing platform with improved detection sensitivity through the increased hot spots distribution. Using this strategy, the proposed assay can achieve an ultralow DA determination at the nM level, a short testing time (<30 min), and high signal reproducibility (RSD 11 %). We also assessed the sensing attributes of our in house developed SERS platform to detect DA in spiked aCSF samples, and a limit of detection (LOD) of 10 μM was achieved. Additionally, after in vivo inducing Parkinson’s disease (PD) in mice, relevant biological samples (striatum and cortical brain tissue) were investigated by SERS and ELISA. Given its good stability and accuracy in complex samples, the SERS-ELISA analysis has great potential to be a powerful tool for the reliable detection of DA in remote conditions.