Instituto de Investigação e Inovação em Saúde (i3S), Porto, Portugal.
Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP), Porto, Portugal.
Sci Rep. 2018 Jul 6;8(1):10266. doi: 10.1038/s41598-018-28570-z.
Immunofluorescence is the gold standard technique to determine the level and spatial distribution of fluorescent-tagged molecules. However, quantitative analysis of fluorescence microscopy images faces crucial challenges such as morphologic variability within cells. In this work, we developed an analytical strategy to deal with cell shape and size variability that is based on an elastic geometric alignment algorithm. Firstly, synthetic images mimicking cell populations with morphological variability were used to test and optimize the algorithm, under controlled conditions. We have computed expression profiles specifically assessing cell-cell interactions (IN profiles) and profiles focusing on the distribution of a marker throughout the intracellular space of single cells (RD profiles). To experimentally validate our analytical pipeline, we have used real images of cell cultures stained for E-cadherin, tubulin and a mitochondria dye, selected as prototypes of membrane, cytoplasmic and organelle-specific markers. The results demonstrated that our algorithm is able to generate a detailed quantitative report and a faithful representation of a large panel of molecules, distributed in distinct cellular compartments, independently of cell's morphological features. This is a simple end-user method that can be widely explored in research and diagnostic labs to unravel protein regulation mechanisms or identify protein expression patterns associated with disease.
免疫荧光是确定荧光标记分子水平和空间分布的金标准技术。然而，荧光显微镜图像的定量分析面临着细胞内形态变异等关键挑战。在这项工作中，我们开发了一种基于弹性几何配准算法的分析策略来处理细胞形状和大小的可变性。首先，使用模拟具有形态变异的细胞群体的合成图像在受控条件下测试和优化算法。我们已经计算了专门评估细胞-细胞相互作用的表达谱（IN 谱）和集中于单个细胞内细胞空间中标记物分布的谱（RD 谱）。为了实验验证我们的分析流程，我们使用了针对 E-钙粘蛋白、微管蛋白和线粒体染料染色的细胞培养物的真实图像，这些图像被选为膜、细胞质和细胞器特异性标记物的原型。结果表明，我们的算法能够生成一个详细的定量报告和一个大面板的分子的忠实表示，分布在不同的细胞区室中，而不受细胞形态特征的影响。这是一种简单的终端用户方法，可以在研究和诊断实验室中广泛探索，以揭示蛋白质调节机制或识别与疾病相关的蛋白质表达模式。
