Automated image-based phenotypic analysis in zebrafish embryos.
Automated image-based phenotypic analysis in zebrafish embryos.
复制标题
DOI：
10.1002/dvdy.21892
复制
发表时间：
2009-03
影响因子：
2.5
通讯作者：
Hukriede, Neil A.
中科院分区：
文献类型：
--
作者：
Vogt, Andreas;Cholewinski, Andrzej;Shen, Xiaoqiang;Nelson, Scott G.;Lazo, John S.;Tsang, Michael;Hukriede, Neil A.
目前，斑马鱼是唯一与当代药物发现范式兼容的脊椎动物模型。斑马鱼胚胎适合高通量化学筛选所需的自动化，光学透明性使它们可能适合基于图像的筛选。然而，缺乏自动分析复杂图像的工具是利用斑马鱼作为高通量筛选模型的障碍。我们已经开发了一种自动化系统，用于在多孔板中成像和分析斑马鱼胚胎，无论胚胎的方向如何，也无需用户干预。荧光胚胎的图像在高含量阅读器上获取，并使用基于人工智能的图像分析方法进行分析，称为认知网络技术（CNT）。CNT可靠地检测了96孔板中排列的转基因荧光胚胎（Tg(fli1:EGFP)y1），并量化了经小分子血管生成抑制剂处理的胚胎的节段间血管发育。结果表明，采用基于图像的高含量筛选方法来测量复杂的生物体表型是可行的。
Presently, the zebrafish is the only vertebrate model compatible with contemporary paradigms of drug discovery. Zebrafish embryos are amenable to automation necessary for high-throughput chemical screens, and optical transparency makes them potentially suited for image-based screening. However, the lack of tools for automated analysis of complex images presents an obstacle to utilizing the zebrafish as a high-throughput screening model. We have developed an automated system for imaging and analyzing zebrafish embryos in multi-well plates regardless of embryo orientation and without user intervention. Images of fluorescent embryos were acquired on a high-content reader and analyzed using an artificial intelligence-based image analysis method termed Cognition Network Technology (CNT). CNT reliably detected transgenic fluorescent embryos (Tg(fli1:EGFP)y1) arrayed in 96-well plates and quantified intersegmental blood vessel development in embryos treated with small molecule inhibitors of anigiogenesis. The results demonstrate it is feasible to adapt image-based high-content screening methodology to measure complex whole organism phenotypes.
登录
查看更多内容
影响因子：
--
作者：
Molina GA;Watkins SC;Tsang M
通讯作者：
Tsang M
影响因子：
3.7
作者：
Sachidanandan, Chetana;Yeh, Jing-Ruey J.;Peterson, Randall T.
通讯作者：
Peterson, Randall T.
影响因子：
14.8
作者：
Burns, CG;Milan, DJ;Fishman, MC
通讯作者：
Fishman, MC
影响因子：
11.2
作者：
Tran, T. Cameron;Sneed, Blossom;Sandberg, Eric M.
通讯作者：
Sandberg, Eric M.
影响因子：
3.6
作者：
Belleri, M;Ribatti, D;Presta, M
通讯作者：
Presta, M