Bhadriraju Kiran, Halter Michael, Amelot Julien, Bajcsy Peter, Chalfoun Joe, Vandecreme Antoine, Mallon Barbara S, Park Kye-Yoon, Sista Subhash, Elliott John T, Plant Anne L
Department of Bioengineering, University of Maryland, College Park, MD 20742, USA.
Biosystems and Biomaterials Division, Materials Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA.
Stem Cell Res. 2016 Jul;17(1):122-9. doi: 10.1016/j.scr.2016.05.012. Epub 2016 May 22.
Identification and quantification of the characteristics of stem cell preparations is critical for understanding stem cell biology and for the development and manufacturing of stem cell based therapies. We have developed image analysis and visualization software that allows effective use of time-lapse microscopy to provide spatial and dynamic information from large numbers of human embryonic stem cell colonies. To achieve statistically relevant sampling, we examined >680 colonies from 3 different preparations of cells over 5days each, generating a total experimental dataset of 0.9 terabyte (TB). The 0.5 Giga-pixel images at each time point were represented by multi-resolution pyramids and visualized using the Deep Zoom Javascript library extended to support viewing Giga-pixel images over time and extracting data on individual colonies. We present a methodology that enables quantification of variations in nominally-identical preparations and between colonies, correlation of colony characteristics with Oct4 expression, and identification of rare events.
识别和量化干细胞制剂的特征对于理解干细胞生物学以及基于干细胞的疗法的开发和制造至关重要。我们开发了图像分析和可视化软件,该软件能够有效利用延时显微镜,从大量人类胚胎干细胞集落中提供空间和动态信息。为了实现具有统计学意义的采样,我们在5天内对来自3种不同细胞制剂的680多个集落进行了检查,生成了一个总计0.9太字节(TB)的实验数据集。每个时间点的0.5千兆像素图像由多分辨率金字塔表示,并使用扩展后的Deep Zoom Javascript库进行可视化,以支持随时间查看千兆像素图像并提取单个集落的数据。我们提出了一种方法,该方法能够量化名义上相同的制剂之间以及集落之间的差异,将集落特征与Oct4表达相关联,并识别罕见事件。