The Hevesy Laboratory, Center for Nuclear Technologies, Technical University of Denmark, Roskilde, Denmark.
Department of Energy Conversion and Storage, Technical University of Denmark, Roskilde, Denmark.
PLoS One. 2018 Nov 7;13(11):e0205823. doi: 10.1371/journal.pone.0205823. eCollection 2018.
Clonogenic assays are powerful tools for testing cell reproductive death after biological damage caused by, for example, ionizing radiation. Traditionally, the methods require a cumbersome, slow and eye-straining manual counting of viable colonies under a microscope. To speed up the counting process and minimize those issues related to the subjective decisions of the scoring personnel, we developed a semi-automated, image-based cell colony counting setup, named CoCoNut (Colony Counter developed by the Nutech department at the Technical University of Denmark). It consists in an ImageJ macro and a photographic 3D-printed light-box, conceived and demonstrated to work together for Crystal Violet-stained colonies. Careful attention was given to the image acquisition process, which allows background removal (i.e. any unwanted element in the picture) in a minimally invasive manner. This is mainly achieved by optimal lighting conditions in the light-box and dividing the image of a flask that contains viable colonies by the picture of an empty flask. In this way, CoCoNut avoids using aggressive background removal filters that usually lead to suboptimal colony count recovery. The full method was tested with V79 and HeLa cell survival samples. Results were compared to other freely available tools. CoCoNut proved able to successfully distinguish between single and merged colonies and to identify colonies bordering on flask edges. CoCoNut software calibration is fast; it requires the adjustment of a single parameter that is the smallest colony area to be counted. The employment of a single parameter reduces the risk of subjectivity, providing a robust and user-friendly tool, whose results can be easily compared over time and among different bio-laboratories. The method is inexpensive and easy to obtain. Among its advantages, we highlight the possibility of combining the macro with a perfectly reproducible 3D-printed light-box. The CoCoNut software and the 3D-printer files are provided as supporting information (S1 CoCoNut Files).
集落形成分析是一种强大的工具,可用于测试细胞在受到生物损伤后的增殖死亡情况,例如电离辐射。传统上,这些方法需要繁琐、缓慢且费眼力的显微镜下人工计数有活力的集落。为了加快计数过程并最小化评分人员主观决策相关的问题,我们开发了一种半自动化的、基于图像的细胞集落计数设置,命名为 CoCoNut(丹麦技术大学 Nutech 部门开发的集落计数器)。它由一个 ImageJ 宏和一个摄影 3D 打印的灯箱组成,该灯箱的设计理念是与 Crystal Violet 染色集落协同工作。我们特别注意图像采集过程,该过程以微创方式实现背景去除(即图片中任何不需要的元素)。这主要通过灯箱中的最佳照明条件和将含有有活力集落的培养瓶的图像与空培养瓶的图像进行分割来实现。通过这种方式,CoCoNut 避免使用通常会导致集落计数恢复不佳的激进背景去除过滤器。该方法已在 V79 和 HeLa 细胞存活样本中进行了全面测试,并与其他免费可用的工具进行了比较。CoCoNut 能够成功区分单个和合并的集落,并识别靠近培养瓶边缘的集落。CoCoNut 软件的校准速度很快;只需要调整一个参数,即要计数的最小集落面积。使用单个参数可以降低主观性的风险,提供一种稳健且用户友好的工具,其结果可以随着时间的推移和不同的生物实验室之间轻松比较。该方法成本低廉,易于获得。我们强调的优点包括将宏与可完全重现的 3D 打印灯箱相结合的可能性。CoCoNut 软件和 3D 打印机文件作为支持信息提供(S1 CoCoNut Files)。