Development and validation of 'AutoRIF': software for the automated analysis of radiation-induced foci.

Q4 Biochemistry, Genetics and Molecular Biology
Andrew McVean, Simon Kent, Alexei Bakanov, Tom Hobbs, Rhona Anderson
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引用次数: 18

Abstract

Background: The quantification of radiation-induced foci (RIF) to investigate the induction and subsequent repair of DNA double strands breaks is now commonplace. Over the last decade systems specific for the automatic quantification of RIF have been developed for this purpose, however to ask more mechanistic questions on the spatio-temporal aspects of RIF, an automated RIF analysis platform that also quantifies RIF size/volume and relative three-dimensional (3D) distribution of RIF within individual nuclei, is required.

Results: A java-based image analysis system has been developed (AutoRIF) that quantifies the number, size/volume and relative nuclear locations of RIF within 3D nuclear volumes. Our approach identifies nuclei using the dynamic Otsu threshold and RIF by enhanced Laplacian filtering and maximum entropy thresholding steps and, has an application 'batch optimisation' process to ensure reproducible quantification of RIF. AutoRIF was validated by comparing output against manual quantification of the same 2D and 3D image stacks with results showing excellent concordance over a whole range of sample time points (and therefore range of total RIF/nucleus) after low-LET radiation exposure.

Conclusions: This high-throughput automated RIF analysis system generates data with greater depth of information and reproducibility than that which can be achieved manually and may contribute toward the standardisation of RIF analysis. In particular, AutoRIF is a powerful tool for studying spatio-temporal relationships of RIF using a range of DNA damage response markers and can be run independently of other software, enabling most personal computers to perform image analysis. Future considerations for AutoRIF will likely include more complex algorithms that enable multiplex analysis for increasing combinations of cellular markers.

Abstract Image

Abstract Image

Abstract Image

开发和验证“AutoRIF”:用于自动分析辐射诱发焦点的软件。
背景:量化辐射诱导病灶(RIF)来研究DNA双链断裂的诱导和随后的修复现在是司空见惯的。在过去的十年中,专门用于RIF自动量化的系统已经为此目的开发出来,然而,为了对RIF的时空方面提出更多的机械问题,还需要一个自动化的RIF分析平台,该平台还可以量化RIF的大小/体积和RIF在单个核内的相对三维(3D)分布。结果:开发了一个基于java的图像分析系统(AutoRIF),可以量化三维核体积内RIF的数量、大小/体积和相对核位置。我们的方法通过增强的拉普拉斯滤波和最大熵阈值步骤,使用动态Otsu阈值和RIF来识别原子核,并具有应用程序“批量优化”过程,以确保RIF的可重复性量化。通过将输出结果与相同2D和3D图像堆栈的人工量化结果进行比较,验证了AutoRIF,结果显示低let辐射暴露后,在整个样本时间点范围内(因此是总RIF/核范围)具有良好的一致性。结论:该高通量自动化RIF分析系统生成的数据比人工获得的数据具有更深入的信息和可重复性,可能有助于RIF分析的标准化。特别是,AutoRIF是一个使用一系列DNA损伤反应标记研究RIF时空关系的强大工具,可以独立于其他软件运行,使大多数个人计算机能够执行图像分析。AutoRIF的未来考虑可能包括更复杂的算法,使多路分析能够增加细胞标记的组合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Genome Integrity
Genome Integrity Biochemistry, Genetics and Molecular Biology-Genetics
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