Automated image analysis with the potential for process quality control applications in stem cell maintenance and differentiation.
Automated image analysis with the potential for process quality control applications in stem cell maintenance and differentiation.
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DOI：
10.1002/btpr.2199
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发表时间：
2016-01
影响因子：
2.9
通讯作者：
Thomas R
中科院分区：
文献类型：
--
作者：
Smith D;Glen K;Thomas R
将实验室流程转化为适合制造的规模化生产系统是细胞疗法面临的重大挑战；特别是缺乏信息丰富且有效的过程控制分析方法。这里探讨了图像分析作为解决这一问题的一部分的潜力，使用多能干细胞集落作为有价值且具有挑战性的范例。 Cell-IQ 活细胞成像平台用于构建形态培养属性的图像库，例如集落“边缘”、“核心外围”或“核心”细胞。使用免疫染色和流式细胞术技术，传统的生物标志物，例如 Oct3/4、Nanog 和 Sox-2，被证明与特定的形态相对应。使用参考图像库对过程中的这些形态学属性进行定量监测表明，对不同培养基交换方案或添加诱导细胞因子 BMP4 的中胚层谱系引起的变化具有快速敏感性。为每个形态属性定义了成像样本大小与精度的关系，以表明可以使用相对较低的成像样本来实现这种灵敏度。此外，单个菌落的形态状态可能与单个菌落的结果相关。较小的集落被认为是同质早期中胚层分化的最佳选择，而较大的集落则保持形态上的多能核心。最后，我们展示了相同图像库评估培养物中细胞数量的潜力，其准确性与牺牲消化和计数相当。这些数据支持定量图像分析在制定过程规范中发挥潜在的强大作用，并且还可以在开发过程中筛选过程操作的影响，这与当前优化和制造中的分析高度互补。 © 2015 The Authors Biotechnology Progress，由 Wiley periodicals, Inc. 代表美国化学工程师学会出版，32:215–223，2016 年
The translation of laboratory processes into scaled production systems suitable for manufacture is a significant challenge for cell based therapies; in particular there is a lack of analytical methods that are informative and efficient for process control. Here the potential of image analysis as one part of the solution to this issue is explored, using pluripotent stem cell colonies as a valuable and challenging exemplar. The Cell‐IQ live cell imaging platform was used to build image libraries of morphological culture attributes such as colony “edge,” “core periphery” or “core” cells. Conventional biomarkers, such as Oct3/4, Nanog, and Sox‐2, were shown to correspond to specific morphologies using immunostaining and flow cytometry techniques. Quantitative monitoring of these morphological attributes in‐process using the reference image libraries showed rapid sensitivity to changes induced by different media exchange regimes or the addition of mesoderm lineage inducing cytokine BMP4. The imaging sample size to precision relationship was defined for each morphological attribute to show that this sensitivity could be achieved with a relatively low imaging sample. Further, the morphological state of single colonies could be correlated to individual colony outcomes; smaller colonies were identified as optimum for homogenous early mesoderm differentiation, while larger colonies maintained a morphologically pluripotent core. Finally, we show the potential of the same image libraries to assess cell number in culture with accuracy comparable to sacrificial digestion and counting. The data supports a potentially powerful role for quantitative image analysis in the setting of in‐process specifications, and also for screening the effects of process actions during development, which is highly complementary to current analysis in optimization and manufacture. © 2015 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers, 32:215–223, 2016