i3S - Instituto de Investigação e Inovação em Saúde, Epithelial Interactions in Cancer (EpIC) Group, Universidade do Porto, Porto, Portugal.
IPATIMUP, Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal.
Lab Invest. 2017 May;97(5):615-625. doi: 10.1038/labinvest.2017.13. Epub 2017 Mar 6.
In the past decades, there has been an amazing progress in the understanding of the molecular mechanisms of the cell cycle. This has been possible largely due to a better conceptualization of the cycle itself, but also as a consequence of technological advances. Herein, we propose a new fluorescence image-based framework targeted at the identification and segmentation of stained nuclei with the purpose to determine DNA content in distinct cell cycle stages. The method is based on discriminative features, such as total intensity and area, retrieved from in situ stained nuclei by fluorescence microscopy, allowing the determination of the cell cycle phase of both single and sub-population of cells. The analysis framework was built on a modified k-means clustering strategy and refined with a Gaussian mixture model classifier, which enabled the definition of highly accurate classification clusters corresponding to G1, S and G2 phases. Using the information retrieved from area and fluorescence total intensity, the modified k-means (k=3) cluster imaging framework classified 64.7% of the imaged nuclei, as being at G1 phase, 12.0% at G2 phase and 23.2% at S phase. Performance of the imaging framework was ascertained with normal murine mammary gland cells constitutively expressing the Fucci2 technology, exhibiting an overall sensitivity of 94.0%. Further, the results indicate that the imaging framework has a robust capacity to both identify a given DAPI-stained nucleus to its correct cell cycle phase, as well as to determine, with very high probability, true negatives. Importantly, this novel imaging approach is a non-disruptive method that allows an integrative and simultaneous quantitative analysis of molecular and morphological parameters, thus awarding the possibility of cell cycle profiling in cytological and histological samples.
在过去的几十年中,人们对细胞周期的分子机制的理解取得了惊人的进展。这在很大程度上要归功于对周期本身的更好理解,也得益于技术的进步。在此,我们提出了一种新的荧光图像分析框架,旨在识别和分割染色核,目的是确定不同细胞周期阶段的 DNA 含量。该方法基于荧光显微镜从原位染色核中提取的总强度和面积等有区别的特征,从而能够确定单个细胞和细胞亚群的细胞周期阶段。分析框架建立在改进的 k-均值聚类策略的基础上,并通过高斯混合模型分类器进行了优化,从而能够定义对应于 G1、S 和 G2 期的高度准确的分类簇。使用从面积和荧光总强度中检索到的信息,修改后的 k-均值(k=3)聚类成像框架将 64.7%的成像核分类为 G1 期,12.0%为 G2 期,23.2%为 S 期。成像框架的性能通过持续表达 Fucci2 技术的正常鼠乳腺细胞进行了验证,其总体灵敏度为 94.0%。此外,结果表明,该成像框架具有很强的能力,可以将给定的 DAPI 染色核准确地识别到其正确的细胞周期阶段,并非常有可能确定真正的阴性。重要的是,这种新的成像方法是非破坏性的,它允许对分子和形态参数进行综合和同时的定量分析,从而有可能对细胞学和组织学样本中的细胞周期进行分析。