Chastagnier Yan, Moutin Enora, Hemonnot Anne-Laure, Perroy Julie
Centre National de la Recherche Scientifique, UMR-5203, Institut de Génomique Fonctionnelle, Montpellier, France.
Institut National de la Santé Et de la Recherche Médicale, U1191, Montpellier, France.
Front Comput Neurosci. 2018 Jan 9;11:118. doi: 10.3389/fncom.2017.00118. eCollection 2017.
A growing number of tools now allow live recordings of various signaling pathways and protein-protein interaction dynamics in time and space by ratiometric measurements, such as Bioluminescence Resonance Energy Transfer (BRET) Imaging. Accurate and reproducible analysis of ratiometric measurements has thus become mandatory to interpret quantitative imaging. In order to fulfill this necessity, we have developed an open source toolset for Fiji--allowing a systematic analysis, from image processing to ratio quantification. We share this open source solution and a step-by-step tutorial at https://github.com/ychastagnier/BRET-Analyzer. This toolset proposes (1) image background subtraction, (2) image alignment over time, (3) a composite thresholding method of the image used as the denominator of the ratio to refine the precise limits of the sample, (4) pixel by pixel division of the images and efficient distribution of the ratio intensity on a pseudocolor scale, and (5) quantification of the ratio mean intensity and standard variation among pixels in chosen areas. In addition to systematize the analysis process, we show that the allows proper reconstitution and quantification of the ratiometric image in time and space, even from heterogeneous subcellular volumes. Indeed, analyzing twice the same images, we demonstrate that compared to standard analysis precisely define the luminescent specimen limits, enlightening proficient strengths from small and big ensembles over time. For example, we followed and quantified, in live, scaffold proteins interaction dynamics in neuronal sub-cellular compartments including dendritic spines, for half an hour. In conclusion, provides a complete, versatile and efficient toolset for automated reproducible and meaningful image ratio analysis.
现在，越来越多的工具能够通过诸如生物发光共振能量转移（BRET）成像等比率测量方法，实时记录各种信号通路以及蛋白质 - 蛋白质相互作用在时间和空间上的动态变化。因此，为了解读定量成像结果，对比率测量进行准确且可重复的分析已成为必要。为满足这一需求，我们为Fiji开发了一套开源工具集，可实现从图像处理到比率量化的系统分析。我们在https://github.com/ychastagnier/BRET - Analyzer上分享了这个开源解决方案以及详细的分步教程。该工具集提供了以下功能：（1）图像背景减法；（2）随时间的图像对齐；（3）用作比率分母的图像的复合阈值化方法，以细化样本的精确边界；（4）图像的逐像素除法，并将比率强度有效地分布在伪彩色标度上；（5）对选定区域内像素的比率平均强度和标准偏差进行量化。除了使分析过程系统化之外，我们还表明，该工具集能够在时间和空间上对比率图像进行适当的重构和量化，即使是来自异质亚细胞体积的图像也能处理。实际上，通过对相同图像进行两次分析，我们证明，与标准分析相比，该工具集能够精确界定发光样本的边界，揭示大小不同的样本随时间变化的优势。例如，我们实时跟踪并量化了神经元亚细胞区室（包括树突棘）中支架蛋白的相互作用动态，时长为半小时。总之，该工具集为自动化的、可重复且有意义的图像比率分析提供了一个完整、通用且高效的工具集。
