GPCR-based dopamine sensors—a detailed guide to inform sensor choice for in vivo imaging
- Labouesse, Marie A. Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA - Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY 10032, USA
- Cola, Reto B. Anatomy and Program in Neuroscience, University of Fribourg, 1700 Fribourg, Switzerland - Institute of Pharmacology and Toxicology, University of Zurich, 8057 Zurich, Switzerland
- Patriarchi, Tommaso Institute of Pharmacology and Toxicology, University of Zurich, 8057 Zurich, Switzerland - Neuroscience Center Zurich, University and ETH Zurich, 8057 Zurich, Switzerland
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28.10.2020
Published in:
- International Journal of Molecular Sciences. - 2020, vol. 21, no. 21, p. 8048
English
Understanding how dopamine (DA) encodes behavior depends on technologies that can reliably monitor DA release in freely-behaving animals. Recently, red and green genetically encoded sensors for DA (dLight, GRAB-DA) were developed and now provide the ability to track release dynamics at a subsecond resolution, with submicromolar affinity and high molecular specificity. Combined with rapid developments in in vivo imaging, these sensors have the potential to transform the field of DA sensing and DA-based drug discovery. When implementing these tools in the laboratory, it is important to consider there is not a ‘one-size-fits-all’ sensor. Sensor properties, most importantly their affinity and dynamic range, must be carefully chosen to match local DA levels. Molecular specificity, sensor kinetics, spectral properties, brightness, sensor scaffold and pharmacology can further influence sensor choice depending on the experimental question. In this review, we use DA as an example; we briefly summarize old and new techniques to monitor DA release, including DA biosensors. We then outline a map of DA heterogeneity across the brain and provide a guide for optimal sensor choice and implementation based on local DA levels and other experimental parameters. Altogether this review should act as a tool to guide DA sensor choice for end-users.
- Faculty
- Faculté des sciences et de médecine
- Department
- Département de Médecine
- Language
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- English
- Classification
- Biological sciences
- License
- License undefined
- Identifiers
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- RERO DOC 329772
- DOI 10.3390/ijms21218048
- Persistent URL
- https://folia.unifr.ch/unifr/documents/308979
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