bioRxivNeurosciencePreprint
Crosstalk between AQP4-dependent ATP/Adenosine release and dopamine neurotransmission in depressive behavior during cocaine withdrawal
S. Okada, Masashi KobayashiiD, Hyun Joo LeeiD, C. Nuralifah, M. Morita
Abstract
Our previous study has demonstrated the AQP4-dependent ATP release and following elevation of extracellular adenosine in hippocampal slices during hypo-osmotic treatment. In the present study, we examined the crosstalk between AQP4-dependent adenosine elevation and dopaminergic neurotransmissions, especially focusing on the mouse depressive behavior during cocaine withdrawal. The depressive behavior was mitigated in AQP4 knockout mice, and was sensitive to adenosine A1 receptor antagonists. Thus, the influence of cocaine withdrawal on the adenosine or dopamine elevation in the slices from the striatum or medial prefrontal cortex, which is the focus of depression was analyzed by the originally-developed biosensor cells, which elevates intracellular Ca2+ in response to adenosine or dopamine. We have found that the evoked-dopamine release in the striatum is tonically suppressed via A1 receptor in a AQP4 dependent manner, and this suppression is augmented by the cocaine withdrawal. In contrast, the evoked dopamine elevation in the medial prefrontal cortex was suppressed by treating slices with adenosine or an A1 receptor antagonist, and the cocaine withdrawal abolished the suppression by A1 receptor antagonist alone in an AQP4-dependent manner. Since a GABAA or group II metabotropic glutamate receptor antagonist occluded the suppression by A1 receptor antagonist, it has been suggested that the glutamatergic and GABAergic terminals suppressing dopamine releases have A1 receptors, which the cocaine withdrawal down-regulates in a AQP4-dependent manner. These results indicate that astrocytes modulate dopaminergic neurotransmissions via A1 receptor in an AQP4-dependent manner, and suggest that cocaine causes depression by changing this modulation.
- organism: mouse
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 0
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