Cloud-based High-throughput Acquisition and Analytics of Zebrafish Electrocardiogram for Cardiac Studies and Drug Development

项目摘要 Sensoriis，Inc.是一家开发基于证据的传感解决方案以支持生物 调查和解决卫生保健问题。NIH SBIR第二阶段拨款的目标是与加州大学合作 加州欧文公司将提供新的系统来评估斑马鱼模型的心脏电生理学， 支持心脏病研究和药物筛选。 心脏病是困扰世界的主要死亡原因。仅有心律失常类疾病 每年在美国造成约35万人死亡，尽管其中一些人的致病基因一直是 虽然部分已被发现，但大多数人的遗传基础仍然知之甚少。斑马鱼(达里奥·雷里奥) 模型系统具有体积小、维护成本低等优点，是重要的脊椎动物实验模型。 世代时间短，遗传顺从和保守，光学透明。斑马鱼长期以来一直是 用作了解人类心脏发育、疾病和再生的模型系统。此外， 斑马鱼模型提供了一种正向遗传方法来揭示遗传基础和潜在的分子 许多心脏疾病的机制。由于与人类在生理上的相似性，斑马鱼 也被证明是一个理想的药物筛选模型系统。 斑马鱼心脏表型获取的常规设置(即心电-心电图)包括 导致功能变化的麻醉。到目前为止，还没有一种系统可以提供心脏表型 对自由游动的斑马鱼进行监测，更不用说同时监测多条鱼了。此外，数据 处理和分析都是人工完成的，不可能进行大规模的研究。 在这方面，我们建议使用多学科方法制定长期路线图，以使i) 提供多种鱼(包括成鱼和幼鱼)长时间可靠的心电数据的新型设备和系统 2)有效地处理、解释和研究大规模数据的基于云的系统； 以及iii)使用斑马鱼模型和我们的新工具进行的大量心脏研究以及药物调查。

Project Summary Sensoriis, Inc is a company that, develops evidence-based sensing solutions to support biological investigations and address health care problems. The goal of this NIH SBIR Phase II grant with University of California Irvine is to provide novel systems to assess cardiac electrophysiology in zebrafish models, supporting heart disease studies and drug screening. Heart disease plagues the world as the leading cause of mortality. Cardiac arrhythmic diseases alone contributed about 350,000 deaths annually in the U.S. Although causative genes for some of them have been partially discovered, genetic basis for the majority remains poorly understood. The zebrafish (Dario rerio) model system is an important vertebrate experimental model owing to its small size, low-cost for maintenance, short generation time, amenable and conserved genetics, and optical transparency. Zebrafish have long been used as model system for understanding human cardiac development, disease, and regeneration. Further, zebrafish model enables a forward genetic approach to reveal the genetic basis and underlying molecular mechanisms of numerous heart diseases. Owing to the physiological similarities to humans’, zebrafish have also proven to be an ideal model system for drug screening. The conventional setup for cardiac phenotype acquisition in zebrafish (i.e. electrocardiogram – ECG) involves anesthesia causing variation in functionality. To date, there is no system which can offer cardiac phenotype monitoring in freely-swimming zebrafish, not to mention for multiple fish simultaneously. Further, data processing and analysis have been done manually, making it impossible to conduct large-scale studies. In this context, we propose to establish a long-term roadmap using multidisciplinary approaches to enable i) novel devices and systems to provide reliable ECG data of multiple fish (both adult fish and larvae) over a long period of time; ii) cloud-based systems to effectively process and interpret as well as study large-scale data; and iii) a host of cardiac studies as well as drug investigations using the zebrafish models and our novel tools.