An Automated High-Content Imaging Platform for Caenorhabditis elegans

亚利桑那大学获得一项奖励，用于开发和传播一种先进的高含量成像平台，用于对秀丽隐杆线虫进行全面、长期的研究。秀丽隐杆线虫是一种广泛应用于生物学研究的实验系统，因其寿命短、实验室培养简单、成本低、可获得强大的分子工具而受到青睐。即使有这些优点，评估生理和分子特征的标准方法往往是劳动密集型的，并且通常仅限于观察一个或几个特征。该项目旨在改变这一过程，整合自动化图像采集，机器学习和专业数据分析的最新进展，同时捕获和解释许多生理和分子特征，显着提高数据收集效率。该平台将进一步允许对同一动物的整个生命周期进行持续监测，提供一个独特的机会来观察分子过程随时间的动态变化，以及种群中个体之间的随机变化。该平台将与数百种现有的转基因荧光生物标记菌株兼容，并为更广泛的科学界提供服务，促进不同生物领域的合作和创新研究，包括衰老、发育、代谢、应激反应、毒理学、炎症和免疫。该项目还通过为学生提供机器人、成像技术、机器学习、数据库系统和基因工程等方面的实际培训，促进体验式教育。该研究项目的核心是开发和验证用于原始数据收集的机器人成像系统，该系统由辅助数据库和分析套件支持，用于有效的数据处理、存储和分析。该项目将进一步产生一组经过验证的转基因秀丽隐杆线虫菌株，每个菌株表达多种荧光生物标志物，旨在报告不同的关键分子过程，这些过程经过优化，可用于成像平台和支持不同分支学科的研究人员。该平台将使研究人员能够通过提高实验效率、范围和吞吐量来观察生理结果（如生存、体型、活动）和潜在分子系统（如核心分子信号或应激反应途径的激活）之间的动态相互作用，同时通过限制测量和分析中的人为偏差来提高可重复性。通过长期收集同一只动物的数据，该项目将使研究人员能够深入研究种群中分子和生理特征之间的动态相互作用。总之，该项目将产生一个创新的成像平台，这将增强我们研究基础生物过程的能力，并加速生物科学不同学科的发现。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

An award is made to the University of Arizona to develop and disseminate an advanced high-content imaging platform for comprehensive, long-term study of the roundworm Caenorhabditis elegans. C. elegans, a widely used experimental system in biological research, is favored for its short lifespan, easy and cost-effective lab cultivation, and the availability of powerful molecular tools. Even with these advantages, standard methods to assess physiological and molecular characteristics are often labor intensive and are typically limited to observing only one or a few traits. This project aims to transform this process, integrating recent advancements in automated image acquisition, machine learning, and specialized data analysis to concurrently capture and interpret numerous physiological and molecular traits, significantly enhancing data collection efficiency. The platform will further allow for continuous monitoring of the same animals throughout their lifespan, offering a unique opportunity to observe dynamic changes in molecular processes over time, as well as stochastic variation among individuals within a population. The platform will be compatible with hundreds of existing transgenic fluorescent biomarker strains and made accessible to the wider scientific community, fostering collaboration and promoting innovative research across diverse biological fields, including aging, development, metabolism, stress response, toxicology, inflammation, and immunity. This project also promotes experiential education by providing students with real-world training in robotics, imaging technology, machine learning, database systems, and genetic engineering.The core of this research project is the development and validation of a robotic imaging system for primary data collection, supported by a complementary database and analysis suite for efficient data processing, storage, and analysis. The project will further generate a panel of validated transgenic C. elegans strains, each expressing multiple fluorescent biomarkers designed to report on different key molecular processes optimized for use with the imaging platform and supporting researchers in various subdisciplines. This platform will enable researchers to observe dynamic interactions between physiological outcomes (e.g., survival, body size, activity) and underlying molecular systems (e.g., activation of core molecular signaling or stress response pathways) by enhancing experimental efficiency, scope, and throughput while improving reproducibility by limiting human bias in measurement and analysis. By collecting data on the same individual animals over time, the project will allow researchers to delve into dynamic interactions between molecular and physiological signatures within a population. In summary, this project will produce an innovative imaging platform that will enhance our ability to study fundamental biological processes and accelerate discovery across diverse disciplines of biological sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.