Effects of Epilepsy-Associated Mutations on GABAA Receptor Assembly, Trafficking, and Function

Abstract

GABAA receptors are pentameric, ligand-gated chloride channels that mediate the majority of fast inhibition in the brain. Because they are assembled from an array of 19 subunit subtypes, GABAA receptors are remarkable among neurotransmitter receptors for their potential diversity. Subunit composition determines the physiological and pharmacological properties of each isoform, so this diversity is both valuable for modulation of neuronal excitability and worthy of extensive study. It is clear that subunits do not assemble at random; rather, clear “rules” limit isoform production. The heterogeneity of receptor isoforms has been studied for decades, but there have been few comprehensive attempts to define the requirements for assembly and trafficking of functional pentamers. Here, we addressed this problem by expressing various combinations of GABAA receptor subunits in fibroblasts and using high-throughput screening techniques to determine what combinations successfully produce functional surface receptors. Furthermore, we assessed the stoichiometry and subunit adjacency of successfully assembled receptors. We confirmed previously-suspected rules and discovered previously-unknown determinants for assembly of common receptor isoforms, and we identified the efficient production of uncommon isoforms that should be sought in vivo. Given that GABAA receptors are essential for neuronal inhibition, it is perhaps unsurprising that numerous epilepsy-associated mutations have been identified in GABAA receptor subunit genes. However, the vast majority of idiopathic generalized epilepsies (IGEs) are polygenic, and for that reason there have been several recent efforts to detect variants in epileptic cohorts. The ultimate goal of these studies is to improve future diagnosis and treatment of IGEs, but a chasm remains between that goal and current knowledge. It is impossible to comprehensively characterize all variants; however, it may be possible to construct a framework that allows us to predict which variants in certain channels are likely to be deleterious. As such, the second part of this dissertation presents thorough characterizations of some reported monogenic mutations as well as our first efforts to use high-throughput screening to classify previously unstudied variants identified in epileptic cohorts.