Laboratory of Cellular and Molecular Biology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, USA.
Department of Physics and Astronomy, Seoul National University, Seoul, Korea.
Sci Rep. 2019 Jun 4;9(1):8267. doi: 10.1038/s41598-019-44783-2.
Localization of RNAs to various subcellular destinations has emerged as a widely used mechanism that regulates a large proportion of transcripts in polarized cells. A number of methodologies have been developed that allow detection and imaging of RNAs at single-molecule resolution. However, methodologies to quantitatively describe RNA distributions are limited. Such approaches usually rely on the identification of cytoplasmic and nuclear boundaries which are used as reference points. Here, we describe an automated, interactive image analysis program that facilitates the accurate generation of cellular outlines from single cells and the subsequent calculation of metrics that quantify how a population of RNA molecules is distributed in the cell cytoplasm. We apply this analysis to mRNAs in mouse and human cells to demonstrate how these metrics can highlight differences in the distribution patterns of distinct RNA species. We further discuss considerations for the practical use of this tool. This program provides a way to facilitate and expedite the analysis of subcellular RNA localization for mechanistic and functional studies.
RNA 在各种亚细胞靶位的定位已成为一种广泛应用的调控机制,可调节大部分极化细胞中的转录本。已经开发出许多方法来实现单分子分辨率下的 RNA 检测和成像。然而,定量描述 RNA 分布的方法有限。此类方法通常依赖于鉴定细胞质和核的边界,这些边界被用作参考点。在这里,我们描述了一种自动化、交互式的图像分析程序,可从单个细胞中准确生成细胞轮廓,并随后计算度量值,以量化细胞细胞质中 RNA 分子的分布情况。我们将该分析应用于小鼠和人类细胞中的 mRNAs,以证明这些度量值如何突出不同 RNA 种类分布模式的差异。我们进一步讨论了该工具实际应用的注意事项。该程序为进行机制和功能研究的亚细胞 RNA 定位分析提供了一种便利和加速的方法。