Singan Vasanth R, Handzic Kenan, Curran Kathleen M, Simpson Jeremy C
School of Biology and Environmental Science & Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin 4, Belfield, Ireland.
BMC Res Notes. 2012 Jun 8;5:281. doi: 10.1186/1756-0500-5-281.
The localization of proteins to specific subcellular structures in eukaryotic cells provides important information with respect to their function. Fluorescence microscopy approaches to determine localization distribution have proved to be an essential tool in the characterization of unknown proteins, and are now particularly pertinent as a result of the wide availability of fluorescently-tagged constructs and antibodies. However, there are currently very few image analysis options able to effectively discriminate proteins with apparently similar distributions in cells, despite this information being important for protein characterization.
We have developed a novel method for combining two existing image analysis approaches, which results in highly efficient and accurate discrimination of proteins with seemingly similar distributions. We have combined image texture-based analysis with quantitative co-localization coefficients, a method that has traditionally only been used to study the spatial overlap between two populations of molecules. Here we describe and present a novel application for quantitative co-localization, as applied to the study of Rab family small GTP binding proteins localizing to the endomembrane system of cultured cells.
We show how quantitative co-localization can be used alongside texture feature analysis, resulting in improved clustering of microscopy images. The use of co-localization as an additional clustering parameter is non-biased and highly applicable to high-throughput image data sets.
真核细胞中蛋白质定位于特定亚细胞结构可提供有关其功能的重要信息。荧光显微镜方法用于确定定位分布，已被证明是表征未知蛋白质的重要工具，并且由于荧光标记构建体和抗体的广泛可得性，现在尤为适用。然而，尽管这些信息对蛋白质表征很重要，但目前能够有效区分细胞中分布看似相似的蛋白质的图像分析选项很少。
我们开发了一种将两种现有图像分析方法相结合的新方法，可高效、准确地区分分布看似相似的蛋白质。我们将基于图像纹理的分析与定量共定位系数相结合，定量共定位系数是一种传统上仅用于研究两类分子之间空间重叠的方法。在此，我们描述并展示了定量共定位在研究定位于培养细胞内膜系统的Rab家族小GTP结合蛋白中的新应用。
我们展示了定量共定位如何与纹理特征分析一起使用，从而改善显微镜图像的聚类。将共定位用作额外的聚类参数是无偏差的，并且高度适用于高通量图像数据集。
