Heart rhythm disorders (i.e. cardiac arrhythmias) remain a large and growing cause of mortality and morbidity, including stroke and heart failure. One example of the commonality of arrhythmia, is atrial fibrillation, which is expected to affect more than 20% of the population above 65. However, treatment of arrhythmias is generally still suboptimal, while our knowledge of the underlying mechanisms remains incomplete. Hence, these heart rhythm disturbances represent one of the biggest challenges in modern medicine as it current socioeconomic impact is enormous without the perspective of any breakthrough improvement. Current methods to study and treat arrhythmia are based on chemistry (i.e. drug therapy) and electronics (i.e. ablation and device therapy), which come with inherent limitations such as poor specificity, irreversible changes, hospital-restricted use, and severe pain. All these limitation could be overcome by allowing the heart itself to detect and termination arrhythmia to restore normal rhythm. That is why this projects will break loose from current paradigms and methods, by investigating whether and how the heart itself can be enabled to detect and terminate heart rhythm disorders, which is here referred to as biological auto-detection and termination. In order to explore this novel concept of fully biological defibrillation, my team will investigate how forced expression of engineered proteins could i) allow cardiac tissue to become a detector of arrhythmias through rapid sensing of acute changes in electrophysiology upon their initiation. And how after detection, ii) this cardiac tissue (now as effector), could terminate the arrhythmia by generating a painless electroshock through activation of these proteins. To this purpose, we will (1) first explore the requirements for such detection & termination by studying arrhythmia initiation and termination in rat models of atrial & ventricular arrhythmias using optical probes and light-gated ion channels. These insights will (2) guide computer-based screening of virtual proteins to identify those properties allowing effective arrhythmia detection & termination. These data will be used for (3) rational engineering of proteins with the desired properties, followed by their (4) forced expression in cardiac cells, slices and whole hearts to assess anti-arrhythmic potential & safety.
