Calcium homeostasis is essential to cardiac and skeletal muscle physiology, where contractile function requires tight but dynamic control of calcium levels across different cellular compartments. The major calcium storage protein in muscle tissues is calsequestrin, a highly acidic protein responsible for buffering up to 50 % of total sarcoplasmic reticulum (SR) calcium. Mutations in cardiac calsequestrin cause a highly lethal familial arrhythmia,

catecholaminergic polymorphic ventricular tachycardia (CPVT), while mutations in skeletal muscle calsequestrin have been linked to myopathies. Calsequestrin’s high density calcium storage is facilitated by homomultimerization of the protein into filaments, but a compelling atomic-resolution structure of a calsequestrin filament is lacking. This gap in knowledge has limited our understanding of calsequestrin biochemistry, SR calcium storage, and molecular mechanisms of calseqestrin-associated diseases. We report here a crystal structure of a cardiac calsequestrin filament with supporting mutation analysis by an in vitro filamentation assay. We also report and characterize a novel disease-associated mutation, S173I, which localizes to the structure’s filament-forming interface. In addition, we show that a previously reported dominant calsequestrin-associated CPVT mutation, K180R, maps to the same multimerization surface. Both mutations disrupt filamentation in vitro, suggesting a model where dominant disease arises from mutations that disrupt multimer formation. Finally, a ytterbium-derivatized structure pinpoints multiple credible calcium sites at filament-forming interfaces, explaining the atomic basis of calsequestrin filamentation in the presence of calcium. This work advances our basic understanding of calsequestrin biochemistry and also provides a unifying structure-function molecular mechanism by which dominant-acting calsequestrin mutations provoke lethal arrhythmias.

With increasing human development encroaching on wild areas, an understanding of the interactions of wildlife in their natural surroundings is becoming imperative. Over the past few decades, a concern for the conserva¬tion of herpetofauna throughout the world has become prevalent. Lack of information on reptiles and amphibians have raised many questions on the effects of roads on their populations. In this study, snake movements on roads in a mostly natural area were examined. Individuals of the copperhead snake (Agkistrodon contortrix) were studied in the Land Between the Lakes National Recreation Area (LBL) in Kentucky. LBL is a 170,000-acre federally protected area between Kentucky Lake and Lake Barkley in Western Kentucky and Tennessee. On a typical night of road cruising, over 60 percent of the snakes captured are copperheads in this area. Over two hundred individual copperheads, both alive and dead, were observed during this study from April 2002 through October 2003. Males and females exhibited differ¬ent frequencies of movements, while juveniles exhibited different frequencies of movements when compared to adults. Road-crossing sites were not random, showing a preference toward less maintained roads with a denser canopy cover. Slightly more snakes were found dead on the road (DOR) than alive on the road (AOR). Significantly higher percentages of DOR were also observed on the highly traveled road as compared to the less maintained roads. Thus, a concern arose with the high numbers of road mortality observed because even though the snakes preferred to cross in areas of low traffic and more cover, significantly higher mortality was seen on the high speed and high traffic road. With LBL being a fairly undisturbed area, this poses a concern for the survivability of the copperhead, along with other wildlife, in more densely populated areas.

The rapid growth in biomedical research has generated vast amounts of data, including genomic, molecular, imaging, and clinical information from humans and other species. Leveraging this data is essential for groundbreaking scientific discoveries and a deeper understanding of health and disease across different species. However, the complexity and volume of these datasets present significant computational challenges, limiting their potential.This dissertation addresses two key challenges in biomedical data analysis: the efficient evaluation of sequencing data and the effective management and analysis of gene sets. By focusing on these areas, we develop innovative computational methods that enable the rapid, scalable, and accurate processing of large-scale biomedical data. For sequencing data, we create algorithms that enhance the speed and precision of data evaluation, making it feasible to manage the increasing volume of sequences generated by modern technologies. For gene sets, we devise tools for their efficient management and analysis, allowing researchers to draw meaningful insights from complex genetic information. Through this research, we aim to contribute to the development of new analytical tools and methods, ultimately supporting the advancement of precision medicine and personalized healthcare for both human and veterinary applications.