UC Irvine

The zebrafish model has been demonstrated as an ideal vertebrate model system for a diverse range of biological studies. Along with conventional approaches, monitoring and analysis of zebrafish electrocardiogram (ECG) have been utilized for cardio-physiological screening and elucidation. ECG monitoring has been carried out with fish treated with anesthetic drugs, rendering the short period of time in recording the signals (<5 minutes). In this work, a prolonged sedation system for continuous ECG monitoring of multiple zebrafish was proposed and developed. The design allows the minimization of the effects of anesthetic drugs and temperature variation to zebrafish cardiac signals for experiments that need continuous data acquisition in real time. Moreover, a graphical user interface (GUI) was built in National Instruments LabView platform for real-time recording, processing and analysis. The program provided important features, such as signal de-noising, characteristic wave detection. Further, machine learning-based approach was first utilized for anomaly detection, yielding above 90% of accuracy to classify different types of heart disease with zebrafish ECG data. Last but not least, the device showed a robust ECG acquisition and analytics for various applications including arrhythmia in Na+-induced sinus arrest, temperature-induced heart rate variation, and drug-induced arrhythmia in Tg(SCN5A-D1275N) mutant and wildtype fish. The multiple channel acquisition also enables the implementation of randomized controlled trials on zebrafish models. Two fish per group may be utilized simultaneously in identical conditions of experiments. Finally, the developed ECG system holds promise and solves current drawbacks to greatly accelerate other cardiovascular studies and drug screening applications using zebrafish.