| Popis: |
Recent technological advances have brought us to the precipice of true high-content data collection methods for long-term tracking of individual Caenorhabditis elegans. C. elegans are among the most prominent experimental systems across many disciplines in the biological sciences, including aging, stress response, toxicology, host-microbe interaction, and developmental biology. Over the past decade, steady progress in robotic imaging and machine learning has led to the development of automated tools for measuring physiological metrics including survival, activity, behavior, and health. In parallel, streamlined image processing pipelines now allow rapid and automated quantification of fluorescent biomarkers that report on a broad range of molecular processes. Finally, recent techniques enable life-long tracking of individual animals in solid media culture environments analogous to standard C. elegans laboratory culture. The objective of this work is to combine these advances into an integrated imaging platform that will enable high-content, life-long collection of both physiological and molecular biomarker data from individual C. elegans. This platform will comprise a robotic imaging system for primary data collection (Aim 1), a database and analysis suite to streamline data processing, storage, and analysis (Aim 2), and a panel of validated transgenic C. elegans strains each expressing multiple fluorescent biomarkers across several subdisciplines of biology (Aim 3). This platform will allow researchers across many biological disciplines to accelerate both discovery and mechanistic research by allowing key data types to be collected and analyzed in parallel. The associated database and analysis suite will enable rapid data processing, sharing, and dissemination, particularly for time-to-event and time course data. |
