@article {Stroebel16630, author = {David Stroebel and St{\'e}phanie Carvalho and Teddy Grand and Shujia Zhu and Pierre Paoletti}, title = {Controlling NMDA Receptor Subunit Composition Using Ectopic Retention Signals}, volume = {34}, number = {50}, pages = {16630--16636}, year = {2014}, doi = {10.1523/JNEUROSCI.2736-14.2014}, publisher = {Society for Neuroscience}, abstract = {Ligand-gated ion channels (LGICs) mediate fast synaptic transmission in the CNS. Typically, these membrane proteins are multimeric complexes associating several homologous subunits around a central pore. Because of the large repertoire of subunits within each family, LGICs exist in vivo as multiple subtypes that differ in subunit composition and functional properties. Establishing the specific properties of individual receptor subtypes remains a major goal in the field of neuroscience and molecular pharmacology. However, isolating specific receptor subtype in recombinant systems can be problematic because of the mixture of receptor populations. This is the case for NMDA receptors (NMDARs), a large family of tetrameric glutamate-gated ion channels that play key roles in brain physiology and pathology. A significant fraction of native NMDARs are triheteromers composed of two GluN1 subunits and two different GluN2 subunits (GluN2A-D). We developed a method based on dual retention signals adapted from G-protein-coupled GABA-B receptors allowing exclusive cell surface expression of triheteromeric rat NMDARs while coexpressed diheteromeric receptors (which contain a single type of GluN2 subunit) are retained intracellularly. Using this approach, we determined the functional properties of GluN1/GluN2A/GluN2B triheteromers, one of the most abundant NMDAR subtypes in the adult forebrain, revealing their unique gating and pharmacological attributes. We envision applicability of the retention signal approach for the study of a variety of heteromeric glutamate-gated ion channel receptors with defined subunit composition.}, issn = {0270-6474}, URL = {https://www.jneurosci.org/content/34/50/16630}, eprint = {https://www.jneurosci.org/content/34/50/16630.full.pdf}, journal = {Journal of Neuroscience} }