Improving Husbandry and Data Reproducibility Through Automated Health Monitoring in Zebrafish Facilities

通过斑马鱼设施的自动健康监测改善饲养和数据再现性

• 批准号: 10761190
• 负责人: Trisha Brock
• 金额: $ 38.88万
• 依托单位: NEMAMETRIX, INC.
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10761190
• 关键词: Achievement; Affect; Algorithmic Software; Animal Model; Aquaculture; Consumption; Data; Development; Disease; Ensure; Fishes; Funding; Genes; Health; Hour; Human; Image; Laboratories; Monitor; Mus; Orthologous Gene; Phase; Population; Reproducibility; Research; Site; Small Business Innovation Research Grant; Standardization; System; Systems Analysis; Testing; Therapeutic; Time; United States; Zebrafish; drug development; human disease; human model; improved; insight; screening; software development; tool; wasting; water quality

ABSTRACT / SUMMARY The zebrafish is an invaluable tool for developing and screening human therapeutics and modeling human diseases. This animal model is strikingly genetically similar to humans, sharing 70% of all human genes (by comparison, mice have orthologs of ~80% of human genes), and 82-90% of human disease-associated genes. Currently, however, zebrafish facilities lack an affordable, precise way to monitor and track the health of their fish stock in an automated way, and to correlate fish health with extrinsic factors that may affect it. As a result, research using unhealthy fish may lead to irreproducibility in research and spurious conclusions, ultimately wasting time, money, and scientific effort. We propose the creation of a zebrafish health monitoring system, “FishCam,” which has the potential to automate wellness checks and track them along with environmental data (e.g., water quality) and, thus, revolutionize fish husbandry in aquaculture and zebrafish laboratories. In Phase 1 Aim 1, we will build a system that reliably captures images and video of a zebrafish population. In Phase 1 Aim 2, we will develop software algorithms that extract parameters such as how many fish are in each tank, their size and their activity levels over the previous 48 hours. In Phase 2 Aim 1, we will extend the FishCam imaging and analysis system to be compatible with commercial zebrafish rack and tank systems (“FishCam Smart Rack”). Finally, in Phase 2 Aim 2, we will perform beta testing of the FishCam Smart Rack system, optimizing it for real-world installations at external sites in the United States. Achievement of these aims will produce an automated, standardized system for zebrafish health monitoring which will reduce variability and help ensure scientific validity of zebrafish research. By advancing zebrafish husbandry, the proposed project aims to facilitate greater insights into human diseases and streamline the development of human therapeutics.

摘要 /摘要 斑马鱼是开发和筛查人类治疗和建模人类的宝贵工具 疾病。这种动物模型在遗传上与人类非常相似，共享了所有人类基因的70％（通过 比较，小鼠的直系同源物为约80％的人类基因）和82-90％的人类疾病相关基因。 但是，目前，斑马鱼设施缺乏一种负担得起的准确方法来监视和跟踪的健康 他们的鱼类以自动化的方式储备，并将鱼类健康与可能影响其影响的外部因素相关联。作为 结果，使用不健康的鱼类的研究可能导致研究和虚假结论的不可重复性， 最终浪费时间，金钱和科学努力。我们建议创建斑马鱼健康监测 系统，“鱼车”，有可能自动检查健康并跟踪它们 环境数据（例如水质），因此彻底改变了水产养殖和斑马鱼的饲养 实验室。在第1阶段AIM 1中，我们将构建一个可靠的系统，该系统可靠地捕获斑马鱼的图像和视频 人口。在第1阶段AIM 2中，我们将开发软件算法来提取参数，例如多少 鱼在每个水箱中，它们的大小和活动水平在过去的48小时内。在第2阶段目标1中，我们将 扩展鱼缸成像和分析系统，与商业斑马鱼架和坦克兼容 系统（“鱼车智能架”）。最后，在第2阶段AIM 2中，我们将对鱼柜进行beta测试 机架系统，将其优化为在美国外部站点的实际安装。 这些目标的实现将为斑马鱼健康产生自动化的标准化系统 监测将降低可变性并有助于确保斑马鱼研究的科学有效性。通过前进 斑马饲养的旨在促进对人类疾病和的更多见解 简化人类治疗的发展。