Multimodal detection of dopamine by sniffer cells expressing genetically encoded fluorescent sensors

Carmen Klein Herenbrink, Jonatan Fullerton Støier, William Dalseg Reith, Abeer Dagra, Miguel Alejandro Cuadrado Gregorek, Reto B Cola, Tommaso Patriarchi, Yulong Li, Lin Tian, Ulrik Gether, Freja Herborg

Research output: Contribution to journalJournal articleResearchpeer-review

15 Citations (Scopus)
33 Downloads (Pure)

Abstract

Dopamine supports locomotor control and higher brain functions such as motivation and learning. Consistently, dopaminergic dysfunction is involved in a spectrum of neurological and neuropsychiatric diseases. Detailed data on dopamine dynamics is needed to understand how dopamine signals translate into cellular and behavioral responses, and to uncover pathological disturbances in dopamine-related diseases. Genetically encoded fluorescent dopamine sensors have recently enabled unprecedented monitoring of dopamine dynamics in vivo. However, these sensors' utility for in vitro and ex vivo assays remains unexplored. Here, we present a blueprint for making dopamine sniffer cells for multimodal dopamine detection. We generated sniffer cell lines with inducible expression of seven different dopamine sensors and perform a head-to-head comparison of sensor properties to guide users in sensor selection. In proof-of-principle experiments, we apply the sniffer cells to record endogenous dopamine release from cultured neurons and striatal slices, and for determining tissue dopamine content. Furthermore, we use the sniffer cells to measure dopamine uptake and release via the dopamine transporter as a radiotracer free, high-throughput alternative to electrochemical- and radiotracer-based assays. Importantly, the sniffer cell framework can readily be applied to the growing list of genetically encoded fluorescent neurotransmitter sensors.

Original languageEnglish
Article number578
JournalCommunications Biology
Volume5
Issue number1
ISSN2399-3642
DOIs
Publication statusPublished - 2022

Bibliographical note

© 2022. The Author(s).

Keywords

  • Corpus Striatum/metabolism
  • Dopamine/metabolism
  • Learning
  • Neurons/metabolism
  • Neurotransmitter Agents

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