Journal article
Unlocking opioid neuropeptide dynamics with genetically encoded biosensors
Nature neuroscience, Vol.27(9), pp.1844-1857
07/15/2024
DOI: 10.1038/s41593-024-01697-1
PMCID: PMC11374718
PMID: 39009835
Abstract
Neuropeptides are ubiquitous in the nervous system. Research into neuropeptides has been limited by a lack of experimental tools that allow for the precise dissection of their complex and diverse dynamics in a circuit-specific manner. Opioid peptides modulate pain, reward and aversion and as such have high clinical relevance. To illuminate the spatiotemporal dynamics of endogenous opioid signaling in the brain, we developed a class of genetically encoded fluorescence sensors based on kappa, delta and mu opioid receptors: κLight, δLight and µLight, respectively. We characterized the pharmacological profiles of these sensors in mammalian cells and in dissociated neurons. We used κLight to identify electrical stimulation parameters that trigger endogenous opioid release and the spatiotemporal scale of dynorphin volume transmission in brain slices. Using in vivo fiber photometry in mice, we demonstrated the utility of these sensors in detecting optogenetically driven opioid release and observed differential opioid release dynamics in response to fearful and rewarding conditions.Neuropeptides are ubiquitous in the nervous system. Research into neuropeptides has been limited by a lack of experimental tools that allow for the precise dissection of their complex and diverse dynamics in a circuit-specific manner. Opioid peptides modulate pain, reward and aversion and as such have high clinical relevance. To illuminate the spatiotemporal dynamics of endogenous opioid signaling in the brain, we developed a class of genetically encoded fluorescence sensors based on kappa, delta and mu opioid receptors: κLight, δLight and µLight, respectively. We characterized the pharmacological profiles of these sensors in mammalian cells and in dissociated neurons. We used κLight to identify electrical stimulation parameters that trigger endogenous opioid release and the spatiotemporal scale of dynorphin volume transmission in brain slices. Using in vivo fiber photometry in mice, we demonstrated the utility of these sensors in detecting optogenetically driven opioid release and observed differential opioid release dynamics in response to fearful and rewarding conditions.
Details
- Title: Subtitle
- Unlocking opioid neuropeptide dynamics with genetically encoded biosensors
- Creators
- Chunyang Dong - University of California, DavisRaajaram Gowrishankar - University of WashingtonYihan Jin - University of California, DavisXinyi Jenny He - University of California, San DiegoAchla Gupta - Icahn School of Medicine at Mount SinaiHuikun Wang - National Institute of Mental HealthNilüfer Sayar-AtasoyRodolfo J Flores - National Institute of Mental HealthKaran Mahe - University of California, DavisNikki Tjahjono - University of California, DavisRuqiang Liang - University of California, DavisAaron Marley - University of California, San FranciscoGrace Or MizunoDarren K Lo - University of California, DavisQingtao Sun - Cold Spring Harbor LaboratoryJennifer L Whistler - University of California, DavisBo Li - Cold Spring Harbor LaboratoryIvone Gomes - Icahn School of Medicine at Mount SinaiMark Von Zastrow - University of California, San FranciscoHugo A Tejeda - National Institute of Mental HealthDeniz Atasoy - University of IowaLakshmi A Devi - Icahn School of Medicine at Mount SinaiMichael R Bruchas - University of WashingtonMatthew R Banghart - University of California, San DiegoLin Tian - University of California, Davis
- Resource Type
- Journal article
- Publication Details
- Nature neuroscience, Vol.27(9), pp.1844-1857
- DOI
- 10.1038/s41593-024-01697-1
- PMID
- 39009835
- PMCID
- PMC11374718
- ISSN
- 1546-1726
- eISSN
- 1546-1726
- Language
- English
- Electronic publication date
- 07/15/2024
- Academic Unit
- Iowa Neuroscience Institute; Fraternal Order of Eagles Diabetes Research Center; Neuroscience and Pharmacology
- Record Identifier
- 9984658358702771
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