Férézou Isabelle, Hill Elisa L, Cauli Bruno, Gibelin Nathalie, Kaneko Takeshi, Rossier Jean, Lambolez Bertrand
Laboratoire de Neurobiologie et Diversité Cellulaire, CNRS UMR 7637, Ecole Supérieure de Physique et de Chimie Industrielles, 75005 Paris, France.
Cereb Cortex. 2007 Aug;17(8):1948-57. doi: 10.1093/cercor/bhl104. Epub 2006 Oct 26.
We studied mu-opioid transmission in acute slices of rat neocortex using whole-cell recordings and single-cell reverse transcription-polymerase chain reaction. The mu-opioid receptor (MOR) was found in gamma-aminobutyric acidergic (GABAergic) interneurons that were either layer I cells frequently expressing neuropeptide Y or layers II-V cells expressing vasoactive intestinal peptide and enkephalin (Enk). We found that mu-opioid agonists inhibit these interneurons that are selectively excited by nicotinic agonists. The extensive overlap of mu-opioid and nicotinic responsiveness allowed mu-opioid agonists to inhibit nicotinic excitation of responsive interneurons and of their GABAergic output onto pyramidal cells. Finally, nicotinic stimulation resulted in a dynamic sequence where GABAergic transmission was first enhanced and then depressed below its baseline. This latter disinhibitory effect was prevented by a mu-opioid antagonist, indicating that excitation of nicotinic-responsive interneurons induced the release of endogenous Enk, which in turn led to MOR activation. Our results suggest that neocortical mu-opioid transmission acts as an inhibitory feedback onto nicotinic-responsive interneurons, which may change network excitability and inhibition patterns during cholinergic excitation.
我们使用全细胞膜片钳记录和单细胞逆转录聚合酶链反应,研究了大鼠新皮质急性脑片中的μ-阿片类递质传递。在γ-氨基丁酸能(GABA能)中间神经元中发现了μ-阿片受体(MOR),这些中间神经元要么是经常表达神经肽Y的I层细胞,要么是表达血管活性肠肽和脑啡肽(Enk)的II-V层细胞。我们发现,μ-阿片类激动剂抑制这些被烟碱类激动剂选择性兴奋的中间神经元。μ-阿片类和烟碱类反应性的广泛重叠,使得μ-阿片类激动剂能够抑制反应性中间神经元及其对锥体细胞的GABA能输出的烟碱类兴奋。最后,烟碱类刺激导致了一个动态过程,其中GABA能传递首先增强,然后低于其基线水平受到抑制。后一种去抑制作用被μ-阿片类拮抗剂所阻止,这表明烟碱反应性中间神经元的兴奋诱导了内源性Enk的释放,进而导致MOR激活。我们的结果表明,新皮质μ-阿片类递质传递对烟碱反应性中间神经元起到抑制性反馈作用,这可能在胆碱能兴奋期间改变网络兴奋性和抑制模式。