Saunders Darren N, Falkenberg Katrina J, Simpson Kaylene J
Cancer Research Program, The Kinghorn Cancer Centre, Garvan Institute of Medical Research, Darlinghurst, New South Wales 2010, Australia St. Vincent's Clinical School, University of New South Wales Medicine, Sydney, New South Wales 2000, Australia.
Victorian Centre for Functional Genomics, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Australia Department of Pathology, The University of Melbourne, Parkville, Victoria 3052, Australia.
Cold Spring Harb Protoc. 2014 Jun 2;2014(6):591-601. doi: 10.1101/pdb.top072561.
Cell death is integral to developmental and disease processes, and high-throughput screening (HTS) has been instrumental both for understanding biological mechanisms underlying cell death and for discovering novel therapeutic agents targeting these pathways. The various cell death modalities and their distinctive morphological and biochemical features have led to the development of a staggering variety of assays to measure these features, many of which have been adapted to HTS format. Although not all cell death assays are readily amenable to a high-throughput format, the potential power of HTS assays and increasing accessibility to associated technology make it likely that new approaches will continue to emerge. In particular, many recent studies in this field have used multiplex assays and high-content imaging to measure several features concurrently. Here, we discuss a broad array of considerations for designing HTS cell death assays, including some common challenges and pitfalls. We aim to provide a framework for deciding the most appropriate biological readouts, assay strategy and mode, workflow, controls, validation, and bioinformatics.
细胞死亡是发育和疾病过程中不可或缺的一部分，高通量筛选（HTS）对于理解细胞死亡背后的生物学机制以及发现针对这些途径的新型治疗药物都起到了重要作用。各种细胞死亡方式及其独特的形态和生化特征促使人们开发出了大量用于测量这些特征的检测方法，其中许多已被改编为高通量筛选形式。尽管并非所有细胞死亡检测方法都易于采用高通量形式，但高通量筛选检测方法的潜在威力以及相关技术的日益普及使得新方法可能会不断涌现。特别是，该领域最近的许多研究都使用了多重检测和高内涵成像来同时测量多个特征。在此，我们讨论设计高通量筛选细胞死亡检测方法时需要考虑的一系列广泛因素，包括一些常见的挑战和陷阱。我们旨在提供一个框架，用于确定最合适的生物学读数、检测策略和模式、工作流程、对照、验证以及生物信息学。
