1Institute of Biology of the Ecole Normale Supérieure, CNRS UMR8197, INSERM U1024, 75230 Paris Cedex 05, France.
RNA. 2010 Jul;16(7):1301-7. doi: 10.1261/rna.1996810. Epub 2010 May 21.
Recent improvements in microscopy technology allow detection of single molecules of RNA, but tools for large-scale automatic analyses of particle distributions are lacking. An increasing number of imaging studies emphasize the importance of mRNA localization in the definition of cell territory or the biogenesis of cell compartments. CORSEN is a new tool dedicated to three-dimensional (3D) distance measurements from imaging experiments especially developed to access the minimal distance between RNA molecules and cellular compartment markers. CORSEN includes a 3D segmentation algorithm allowing the extraction and the characterization of the cellular objects to be processed--surface determination, aggregate decomposition--for minimal distance calculations. CORSEN's main contribution lies in exploratory statistical analysis, cell population characterization, and high-throughput assays that are made possible by the implementation of a batch process analysis. We highlighted CORSEN's utility for the study of relative positions of mRNA molecules and mitochondria: CORSEN clearly discriminates mRNA localized to the vicinity of mitochondria from those that are translated on free cytoplasmic polysomes. Moreover, it quantifies the cell-to-cell variations of mRNA localization and emphasizes the necessity for statistical approaches. This method can be extended to assess the evolution of the distance between specific mRNAs and other cellular structures in different cellular contexts. CORSEN was designed for the biologist community with the concern to provide an easy-to-use and highly flexible tool that can be applied for diverse distance quantification issues.
近年来,显微镜技术的进步使得能够检测单个 RNA 分子,但缺乏大规模自动分析粒子分布的工具。越来越多的成像研究强调了 mRNA 定位在定义细胞区域或细胞区室生物发生中的重要性。CORSEN 是一种新工具,专门用于从成像实验进行三维(3D)距离测量,特别是为了获得 RNA 分子和细胞区室标志物之间的最小距离而开发的。CORSEN 包括一个 3D 分割算法,允许提取和表征要处理的细胞对象——表面确定、聚集体分解——用于最小距离计算。CORSEN 的主要贡献在于探索性统计分析、细胞群体特征描述和高通量测定,这得益于批处理过程分析的实现。我们强调了 CORSEN 在研究 mRNA 分子和线粒体相对位置方面的实用性:CORSEN 清楚地区分了定位于线粒体附近的 mRNA 和那些在游离细胞质多核糖体上翻译的 mRNA。此外,它还量化了 mRNA 定位的细胞间变化,并强调了需要进行统计分析。该方法可扩展到评估特定 mRNA 与其他细胞结构之间的距离在不同细胞环境中的演变。CORSEN 是为生物学家社区设计的,关注提供易于使用且高度灵活的工具,可应用于各种距离定量问题。