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CORSEN a new software dedicated to microscope-based 3D distance measurements: mRNA–mitochondria distance from single-cell to population analyses

机译:CORSEN一款专用于基于显微镜的3D距离测量的新软件:mRNA –线粒体距离从单细胞到群体分析

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摘要

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.
机译:显微镜技术的最新改进允许检测RNA的单分子,但是缺少用于大规模自动分析颗粒分布的工具。越来越多的影像学研究强调了mRNA定位在定义细胞区域或细胞区室的生物发生中的重要性。 CORSEN是一种专用于从成像实验进行三维(3D)距离测量的新工具,专门开发用于访问RNA分子与细胞区室标记之间的最小距离。 CORSEN包含3D分割算法,可对要处理的蜂窝对象进行提取和表征(表面确定,聚集分解),以实现最小距离计算。 CORSEN的主要贡献在于探索性统计分析,细胞群体表征和高通量分析,这些方法可通过执行批处理分析来实现。我们着重介绍了CORSEN在研究mRNA分子和线粒体相对位置方面的效用:CORSEN清楚地区分了位于线粒体附近的mRNA与在游离细胞质多核糖体上翻译的mRNA。此外,它量化了mRNA定位的细胞间差异,并强调了统计方法的必要性。可以扩展该方法以评估不同细胞环境中特定mRNA与其他细胞结构之间距离的演变。 CORSEN是为生物学家设计的,旨在提供一种易于使用且高度灵活的工具,该工具可用于解决各种距离量化问题。

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