Department of Computational and Systems Biology, School of Medicine, Pittsburgh, PA 15213, USA.
Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Bioinformatics. 2021 May 5;37(5):677-683. doi: 10.1093/bioinformatics/btaa874.
Many biological processes are regulated by single molecules and molecular assemblies within cells that are visible by microscopy as punctate features, often diffraction limited. Here, we present detecting-NEMO (dNEMO), a computational tool optimized for accurate and rapid measurement of fluorescent puncta in fixed-cell and time-lapse images.
The spot detection algorithm uses the à trous wavelet transform, a computationally inexpensive method that is robust to imaging noise. By combining automated with manual spot curation in the user interface, fluorescent puncta can be carefully selected and measured against their local background to extract high-quality single-cell data. Integrated into the workflow are segmentation and spot-inspection tools that enable almost real-time interaction with images without time consuming pre-processing steps. Although the software is agnostic to the type of puncta imaged, we demonstrate dNEMO using smFISH to measure transcript numbers in single cells in addition to the transient formation of IKK/NEMO puncta from time-lapse images of cells exposed to inflammatory stimuli. We conclude that dNEMO is an ideal user interface for rapid and accurate measurement of fluorescent molecular assemblies in biological imaging data.
The data and software are freely available online at https://github.com/recleelab.
Supplementary data are available at Bioinformatics online.
许多生物过程受到细胞内单个分子和分子组装体的调节,这些分子和分子组装体在显微镜下可见为点状特征,通常是衍射受限的。在这里,我们介绍了检测-NEMO(dNEMO),这是一种针对固定细胞和延时图像中荧光斑点进行准确快速测量而优化的计算工具。
斑点检测算法使用了一种具有计算成本效益的不敏感小波变换方法,该方法对成像噪声具有鲁棒性。通过在用户界面中将自动和手动斑点选择结合起来,可以仔细选择荧光斑点并对其局部背景进行测量,以提取高质量的单细胞数据。该软件集成了分割和斑点检查工具,可以在不进行耗时的预处理步骤的情况下,几乎实时地与图像进行交互。虽然该软件与所成像的斑点类型无关,但我们使用 smFISH 演示了 dNEMO,除了从暴露于炎症刺激的细胞的延时图像中 IKK/NEMO 斑点的瞬态形成之外,还可以测量单个细胞中的转录物数量。我们得出结论,dNEMO 是一种用于快速准确测量生物成像数据中荧光分子组装体的理想用户界面。
数据和软件可在 https://github.com/recleelab 上免费在线获取。
补充数据可在 Bioinformatics 在线获取。