Development of a mechanistically informative genome-wide, in vitro chemicals screening technology

开发机械信息丰富的全基因组体外化学物质筛选技术

• 批准号: G0800702/1
• 负责人: Andrew Cossins
• 金额: $ 67.86万
• 依托单位: University of Liverpool
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2008
• 资助国家: 英国
• 起止时间: 2008 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=G0800702%2F1
• 关键词: Development; mechanistically; informative; genome; wide

Modern industrial society generates large amounts of novel chemicals to which humans are exposed both directly and indirectly through environmental release. Governments specify test procedures with which to regulate the release of these chemicals, though ensuring that the chosen test method relates to the safety and environmental consequences of release is a major scientific issue. In principle the most informative tests involve experiments on whole, living animals, but there is powerful societal pressure to reduce the numbers of animals used this way. Scientists have sought to identify alternatives to the use of living animals, and two systems are now being developed, namely the use of cell cultures and the use of early stage, developing embryos. This project seeks to greatly refine these alternative test methods to generate far more information on how the cells or embryos respond to chemicals treatment by using a new technology for simultaneously interrogating the performance of all of the genes in the cells or embryo. This technique holds much promise for identifying the properties of the entire system and this gives a much more profound view of how chemicals have their effects. This information will be use with computer modeling to generate an ability to predict the responses of animals to chemicals with unknown properties.

现代工业社会产生了大量的新型化学物质，人类通过环境释放直接或间接地暴露于这些化学物质。各国政府规定了管制这些化学品释放的测试程序，但确保所选测试方法与释放的安全和环境后果有关是一个重大的科学问题。原则上，信息量最大的测试涉及对整个活体动物的实验，但有强大的社会压力要求减少以这种方式使用的动物数量。科学家们一直在寻找使用活体动物的替代方法，目前正在开发两种系统，即使用细胞培养和使用早期发育胚胎。该项目旨在通过使用一种新技术同时询问细胞或胚胎中所有基因的表现，大大改进这些替代测试方法，以生成更多关于细胞或胚胎如何对化学处理做出反应的信息。这项技术对于识别整个系统的属性有很大的希望，这对化学品如何产生影响提供了更深刻的看法。这些信息将与计算机建模一起使用，以产生预测动物对未知性质的化学品的反应的能力。