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In this study, we have aimed at developing a novel electrochemical sensing approach capable of detecting dopamine, the main biomarker in Parkinson's disease, within the highly complex cell culture matrix of human midbrain organoids in a non-invasive and label-free manner. With its ability to generate organotypic structures in vitro, induced pluripotent stem cell technology has provided the basis for the development of advanced patient-derived disease models. These include models of the human midbrain, the affected region in the neurodegenerative disorder Parkinson's disease. Up to now, however, the analysis of so-called human midbrain organoids has relied on time-consuming and invasive strategies, incapable of monitoring organoid development. Using a redox-cycling approach in combination with a 3-mercaptopropionic acid self-assembled monolayer modification enabled the increase of sensor selectivity and sensitivity towards dopamine, while simultaneously reducing matrix-mediated interferences. In this work, we demonstrate the ability to detect and monitor even small differences in dopamine release between healthy and Parkinson`s disease-specific midbrain organoids over prolonged cultivation periods, which was additionally verified using liquid chromatography-multiple reaction monitoring mass spectrometry. Furthermore, the detection of a phenotypic rescue in midbrain organoids carrying a pathogenic mutation in leucine-rich repeat kinase 2, upon treatment with the leucine-rich repeat kinase 2 inhibitor II underlines the practical implementability of our sensing approach for drug screening applications as well as personalized disease modelling.

Citation

Cristian Zanetti, Sarah Spitz, Emanuel Berger, Silvia Bolognin, Lisa M Smits, Philipp Crepaz, Mario Rothbauer, Julie M Rosser, Martina Marchetti-Deschmann, Jens C Schwamborn, Peter Ertl. Monitoring the neurotransmitter release of human midbrain organoids using a redox cycling microsensor as a novel tool for personalized Parkinson's disease modelling and drug screening. The Analyst. 2021 Apr 07;146(7):2358-2367

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PMID: 33625407

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