SERS-based detection of 5- S -cysteinyl-dopamine as a novel biomarker of Parkinson's disease in artificial biofluids.
Isidro Badillo-RamírezBruno C Landeros-RiveraJosé Manuel SanigerJürgen PoppDana Cialla-MayPublished in: The Analyst (2023)
The early detection of Parkinson's disease (PD) can significantly improve treatment and quality of life in patients. 5- S -Cysteinyl-dopamine (CDA) is a key metabolite of high relevance for the early detection of PD. Therefore, its sensitive detection with fast and robust methods can improve its use as a biomarker. In this work we show the potentialities of label-free SERS spectroscopy in detecting CDA in aqueous solutions and artificial biofluids, with a simple, fast and sensitive approach. We present a detailed experimental SERS band assignment of CDA employing silver nanoparticle (AgNP) substrates in aqueous media, which was supported by theoretical calculations and simulated Raman and SERS spectra. The tentative orientation of CDA over the AgNP was also studied, indicating that catechol and carboxylic acid play a key role in the metallic surface adsorption. Moreover, we showed that SERS can allow us to identify CDA in aqueous media at low concentration, leading to the identification of some of its characteristic bands in pure water and in synthetic cerebrospinal fluid (SCSF) below 1 × 10 -8 M, while its band identification in simulated urine (SUR) can be reached at 1 × 10 -7 M. In conclusion, we show that CDA can be suitably detected by means of label-free SERS spectroscopy, which can significantly improve its sensitive detection for further analytical studies as a novel biomarker and further clinical diagnosis in PD patients.
Keyphrases
- sensitive detection
- label free
- quantum dots
- gold nanoparticles
- loop mediated isothermal amplification
- end stage renal disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- cerebrospinal fluid
- prognostic factors
- raman spectroscopy
- single molecule
- patient reported outcomes
- patient reported
- combination therapy
- silver nanoparticles
- smoking cessation
- bioinformatics analysis