Department of Biology, Indiana University, 1001 E 3rd Street, Bloomington, Indiana 47405, USA.
Nat Microbiol. 2016 Jun 20;1(7):16077. doi: 10.1038/nmicrobiol.2016.77.
Single-cell analysis of bacteria and subcellular protein localization dynamics has shown that bacteria have elaborate life cycles, cytoskeletal protein networks and complex signal transduction pathways driven by localized proteins. The volume of multidimensional images generated in such experiments and the computation time required to detect, associate and track cells and subcellular features pose considerable challenges, especially for high-throughput experiments. There is therefore a need for a versatile, computationally efficient image analysis tool capable of extracting the desired relationships from images in a meaningful and unbiased way. Here, we present MicrobeJ, a plug-in for the open-source platform ImageJ(1). MicrobeJ provides a comprehensive framework to process images derived from a wide variety of microscopy experiments with special emphasis on large image sets. It performs the most common intensity and morphology measurements as well as customized detection of poles, septa, fluorescent foci and organelles, determines their subcellular localization with subpixel resolution, and tracks them over time. Because a dynamic link is maintained between the images, measurements and all data representations derived from them, the editor and suite of advanced data presentation tools facilitates the image analysis process and provides a robust way to verify the accuracy and veracity of the data.
单细胞分析细菌和亚细胞蛋白定位动力学表明,细菌具有精细的生命周期、细胞骨架蛋白网络和由局部蛋白驱动的复杂信号转导途径。此类实验生成的多维图像的数量和检测、关联和跟踪细胞和亚细胞特征所需的计算时间都带来了相当大的挑战,尤其是对于高通量实验而言。因此,需要一种通用的、计算效率高的图像分析工具,能够以有意义且无偏倚的方式从图像中提取所需的关系。在这里,我们介绍了 MicrobeJ,它是开源平台 ImageJ(1)的一个插件。MicrobeJ 提供了一个全面的框架,用于处理来自各种显微镜实验的图像,特别强调大型图像集。它执行最常见的强度和形态测量,以及对极、隔膜、荧光焦点和细胞器的定制检测,以亚像素分辨率确定它们的亚细胞定位,并随时间跟踪它们。由于图像、测量值以及从中得出的所有数据表示之间保持动态链接,因此编辑器和高级数据表示工具套件简化了图像分析过程,并提供了一种可靠的方法来验证数据的准确性和真实性。