Acquisition, Processing and Analysis of Electrocardiogram in Awake Zebrafish.

Long-term monitoring of intrinsic electrocardiogram (ECG) in zebrafish plays a crucial role in heart disease studies as well as drug screening. In this work, we developed a polymer-based apparatus with embedded flexible thin-film electrodes to acquire ECG signals of awake zebrafish. The apparatus was made of polydimethylsiloxane (PDMS) using the molding technique with molds formed by 3D printing. 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 and anomaly detection. Further, it could operate on both real-time coming signals as well as previously-saved data, facilitating analysis and interpretation. We demonstrated the use of our system to investigate the effects of the anesthetic drug, namely Tricaine (MS-222), on cardiac electrophysiology of zebrafish, revealing promising findings. We speculate that our novel system may contribute to a host of studies in various disciplines using the zebrafish model.

Real-Time Monitoring and Analysis of Zebrafish Electrocardiogram with Anomaly Detection.

Heart disease is the leading cause of mortality in the U.S. with approximately 610,000 people dying every year. Effective therapies for many cardiac diseases are lacking, largely due to an incomplete understanding of their genetic basis and underlying molecular mechanisms. Zebrafish (Danio rerio) are an excellent model system for studying heart disease as they enable a forward genetic approach to tackle this unmet medical need. In recent years, our team has been employing electrocardiogram (ECG) as an efficient tool to study the zebrafish heart along with conventional approaches, such as immunohistochemistry, DNA and protein analyses. We have overcome various challenges in the small size and aquatic environment of zebrafish in order to obtain ECG signals with favorable signal-to-noise ratio (SNR), and high spatial and temporal resolution. In this paper, we highlight our recent efforts in zebrafish ECG acquisition with a cost-effective simplified microelectrode array (MEA) membrane providing multi-channel recording, a novel multi-chamber apparatus for simultaneous screening, and a LabVIEW program to facilitate recording and processing. We also demonstrate the use of machine learning-based programs to recognize specific ECG patterns, yielding promising results with our current limited amount of zebrafish data. Our solutions hold promise to carry out numerous studies of heart diseases, drug screening, stem cell-based therapy validation, and regenerative medicine.