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Updated: Jul 6, 2025

A High-content Assay for Monitoring AMPA Receptor Trafficking
Published on: January 28, 2019
ABHD6 drives endocytosis of AMPA receptors to regulate synaptic plasticity and learning flexibility
Mengping Wei1, Lei Yang1, Feng Su2
1School of Basic Medical Sciences, Beijing Key Laboratory of Neural Regeneration and Repair, Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 100069, China; State Key Laboratory of Neurology and Oncology Drug Development, Nanjing 210000, Jiangsu, China; Chinese Institute for Brain Research, Beijing 102206, China.
Abstract:
Trafficking of α-Amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) receptors (AMPARs), mediated by AMPAR interacting proteins, enabled neurons to maintain tuning capabilities at rest or active state. α/β-Hydrolase domain-containing 6 (ABHD6), an endocannabinoid hydrolase, was an AMPAR auxiliary subunit found to negatively regulate the surface delivery of AMPARs. While ABHD6 was found to prevent AMPAR tetramerization in endoplasmic reticulum, ABHD6 was also reported to localize at postsynaptic site. Yet, the role of ABHD6 interacting with AMPAR at postsynaptic site, and the physiological significance of ABHD6 regulating AMPAR trafficking remains elusive. Here, we generated the ABHD6 knockout (ABHD6KO) mice and found that deletion of ABHD6 selectively enhanced AMPAR-mediated basal synaptic responses and the surface expression of postsynaptic AMPARs. Furthermore, we found that loss of ABHD6 impaired hippocampal long-term depression (LTD) and synaptic downscaling in hippocampal synapses. AMPAR internalization assays revealed that ABHD6 was essential for neuronal activity-dependent endocytosis of surface AMPARs, which is independent of ABHD6's hydrolase activity. The defects of AMPAR endocytosis and LTD are expressed as deficits in learning flexibility in ABHD6KO mice. Collectively, we demonstrated that ABHD6 is an endocytic accessory protein promoting AMPAR endocytosis, thereby contributes to the formation of LTD, synaptic downscaling and reversal learning.
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