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Exploiting geometric similarity for statistical quantification of fluorescence spatial patterns in bacterial colonies.
BMC Bioinformatics ( IF 2.9 ) Pub Date : 2020-06-03 , DOI: 10.1186/s12859-020-3490-1
David R Espeso 1 , Elena Algar 1 , Esteban Martínez-García 1 , Víctor de Lorenzo 1
Affiliation  

Currently the combination of molecular tools, imaging techniques and analysis software offer the possibility of studying gene activity through the use of fluorescent reporters and infer its distribution within complex biological three-dimensional structures. For example, the use of Confocal Scanning Laser Microscopy (CSLM) is a regularly-used approach to visually inspect the spatial distribution of a fluorescent signal. Although a plethora of generalist imaging software is available to analyze experimental pictures, the development of tailor-made software for every specific problem is still the most straightforward approach to perform the best possible image analysis. In this manuscript, we focused on developing a simple methodology to satisfy one particular need: automated processing and analysis of CSLM image stacks to generate 3D fluorescence profiles showing the average distribution detected in bacterial colonies grown in different experimental conditions for comparison purposes. The presented method processes batches of CSLM stacks containing three-dimensional images of an arbitrary number of colonies. Quasi-circular colonies are identified, filtered and projected onto a normalized orthogonal coordinate system, where a numerical interpolation is performed to obtain fluorescence values within a spatially fixed grid. A statistically representative three-dimensional fluorescent pattern is then generated from this data, allowing for standardized fluorescence analysis regardless of variability in colony size. The proposed methodology was evaluated by analyzing fluorescence from GFP expression subject to regulation by a stress-inducible promoter. This method provides a statistically reliable spatial distribution profile of fluorescence detected in analyzed samples, helping the researcher to establish general correlations between gene expression and spatial allocation under differential experimental regimes. The described methodology was coded into a MATLAB script and shared under an open source license to make it accessible to the whole community.

中文翻译:

利用几何相似性对细菌菌落中的荧光空间模式进行统计量化。

目前,分子工具,成像技术和分析软件的结合提供了通过使用荧光报告基因研究基因活性并推断其在复杂的生物三维结构中的分布的可能性。例如,共聚焦扫描激光显微镜(CSLM)的使用是一种常规使用的方法,用于在视觉上检查荧光信号的空间分布。尽管可以使用大量的通用成像软件来分析实验图片,但是针对每个特定问题开发量身定制的软件仍然是执行最佳图像分析的最直接方法。在此手稿中,我们集中于开发一种简单的方法来满足特定的需求:CSLM图像堆栈的自动处理和分析以生成3D荧光图,该图显示了在不同实验条件下生长的细菌菌落中检测到的平均分布,以进行比较。提出的方法处理包含任意数量菌落的三维图像的CSLM堆栈批次。准圆形菌落被识别,过滤并投影到归一化的正交坐标系上,在此处进行数值插值以获得空间固定网格内的荧光值。然后从该数据生成具有统计意义的三维荧光图案,无论菌落大小如何变化,都可以进行标准化的荧光分析。通过分析来自GFP表达的荧光来评估拟议的方法,该GFP表达受应激诱导型启动子调控。该方法提供了在统计上可靠的空间分布图,该空间分布图是在分析的样品中检测到的,有助于研究人员在不同的实验方案下建立基因表达与空间分配之间的一般相关性。所描述的方法已编码为MATLAB脚本,并在开放源代码许可下共享,以使整个社区都可以访问。
更新日期:2020-06-03
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