Unraveling the molecular interactions between α7 nicotinic receptor and a RIC3 variant associated with backward speech.
Aditi PradhanHayley S MountfordJessica PeixinhoEdward ReaEmmanouela EpeslidouJulia S ScottJoanna CullSusan MaxwellRichard WebsterDavid BeesonYin Yao DongStefan PrekovicIsabel BermudezDianne F NewburyPublished in: Cellular and molecular life sciences : CMLS (2024)
Recent work putatively linked a rare genetic variant of the chaperone Resistant to Inhibitors of acetylcholinesterase (RIC3) (NM_024557.4:c.262G > A, NP_078833.3:p.G88R) to a unique ability to speak backwards, a language skill that is associated with exceptional working memory capacity. RIC3 is important for the folding, maturation, and functional expression of α7 nicotinic acetylcholine receptors (nAChR). We compared and contrasted the effects of RIC3G88R on assembly, cell surface expression, and function of human α7 receptors using fluorescent protein tagged α7 nAChR and Förster resonance energy transfer (FRET) microscopy imaging in combination with functional assays and 125 I-α-bungarotoxin binding. As expected, the wild-type RIC3 protein was found to increase both cell surface and functional expression of α7 receptors. In contrast, the variant form of RIC3 decreased both. FRET analysis showed that RICG88R increased the interactions between RIC3 and α7 protein in the endoplasmic reticulum. These results provide interesting and novel data to show that a RIC3 variant alters the interaction of RIC3 and α7, which translates to decreased cell surface and functional expression of α7 nAChR.
Keyphrases
- energy transfer
- cell surface
- binding protein
- poor prognosis
- working memory
- single molecule
- quantum dots
- endoplasmic reticulum
- high resolution
- high throughput
- living cells
- long non coding rna
- wild type
- protein protein
- autism spectrum disorder
- attention deficit hyperactivity disorder
- endothelial cells
- magnetic resonance imaging
- gene expression
- magnetic resonance
- photodynamic therapy
- fluorescent probe
- genome wide
- machine learning
- heat shock protein
- artificial intelligence
- high speed