Biophysical Society Conference | Tahoe 2022

Molecular Biophysics of Membranes

Poster Abstracts

9-POS Board 3 INVESTIGATING KCNQ1 MISTRAFFICKING IN LONG QT SYNDROME Katherine R. Clowes ; Hui Huang 1 ; Alfred L George 2 ; Charles Sanders 1 ;

1 Vanderbilt University, Biochemistry, Nashville, TN, USA 2 Northwestern University, Pharmacology, Chicago, IL, USA

It is estimated that 1 in 2500 individuals suffer from congenital long QT syndrome (LQTS), a cardiac disorder that can cause syncope, cardiac arrythmia, and cardiac arrest, which can be fatal. Loss of function mutations in the voltage gated potassium channel protein KCNQ1 cause 30- 50% of cases of congenital LQTS, and over 250 LQTS-associated mutations in KCNQ1 have been identified. These mutations are distributed throughout the protein and result in variable severity of symptoms, leading to uncertainty about how these mutations cause loss of function. We have characterized 51 mutations in the KCNQ1 voltage sensing domain (VSD) by their impact on KCNQ1 expression, trafficking, stability, and function. We found that reduced trafficking to the plasma membrane (mistrafficking) was a common cause of protein dysfunction in the KCNQ1 VSD. This led to the hypothesis that mistrafficking is a common mechanism of protein dysfunction across domains in KCNQ1, and an interest in characterizing the impact of additional mutations on trafficking. The trafficking assay used in prior studies only allows for analysis of one mutant at a time, requiring use of a more high throughput method. Here, we describe a deep mutational scanning approach to determine the impact of a library of KCNQ1 variants on KCNQ1 cell surface trafficking. KCNQ1 variants are stably expressed in cells, which are sorted into “trafficking competent” and “trafficking deficient” populations based on their cell surface expression of KCNQ1 via flow cytometry. The proportion of each mutant in the two populations is then determined to identify mutations that increase or decrease KCNQ1 trafficking. This allows us to determine residues and regions that are important for KCNQ1 trafficking. Using this method, we have begun characterizing trafficking phenotypes of mutations in KCNQ1 in a high-throughput fashion, providing additional information on the mechanisms of KCNQ1 loss of function in long-QT syndrome.

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