Project Summary Long QT syndrome (LQTS) is a cardiac disorder characterized by the prolongation of the latter portion of the electrocardiogram trace (the QT interval) that increases risk of cardiac arrythmia, cardiac arrest, and sudden unexpected death. Approximately 1 in 2500 individuals suffer from the congenital form of LQTS, with 30-50% of cases being caused by mutations in the voltage gated potassium channel protein KCNQ1 (type 1 LQTS, or LQT1). Over 250 LQT1-associated mutations in KCNQ1 have been identified, but the impact of these mutations on the channel’s structure and function, and whether there are common mechanisms through which these mutations lead to KCNQ1 dysfunction in LQT1, is still unknown. The primary goal of this proposed project is to explore mistrafficking as a potential mechanism of KCNQ1 loss of function in long QT syndrome. Previous studies of LQT1-associated mutations in the KCNQ1 voltage sensing domain (VSD) found that the majority decreased KCNQ1 trafficking to the plasma membrane and destabilized the VSD. Additional studies have shown that mutations in KCNQ1 can lead to retention in the endoplasmic reticulum (ER) and increased proteasomal degradation. This has led to the hypothesis that mistrafficking is a common mechanism of protein dysfunction in LQT1. Mistrafficking has been identified as a disease mechanism in several other membrane-protein associated diseases, such as cystic fibrosis and retinitis pigmentosa, and in the case of cystic fibrosis, drugs have been developed to rescue mistrafficking and alleviate disease symptoms. This leads to the additional hypothesis that drugs that bind nascent KCNQ1 channels and increase their stability can increase the trafficking of KCNQ1. In line with these hypotheses, I propose two aims: 1) to classify mutations across KCNQ1 based on their impact on KCNQ1 trafficking, and 2) to develop a high throughput screening method to identify small molecules that increase cell surface trafficking. In Aim 1, I will classify the trafficking of all possible KCNQ1 variants with a fluorescence-activated cell sorting (FACS)-based deep mutational scanning method. This will allow me to determine whether the majority of LQT1-associated mutations cause mistrafficking and also provide information on variants of unknown significance (VUS) and other KCNQ1 variants. In Aim 2, I will utilize immunofluorescence and high content imaging to screen for small molecules that increase WT or mutant KCNQ1 trafficking. This will test the hypothesis that KCNQ1 mistrafficking is rescuable with small molecules. Together, the results of these aims will provide further insight into the molecular mechanisms behind KCNQ1 dysfunction in LQT1 and explore a possible route for developing novel treatments for LQT1.