Image-based cell subpopulation identification through automated cell tracking, principal component analysis, and partitioning around medoids clustering
Image-based cell subpopulation identification through automated cell tracking, principal component analysis, and partitioning around medoids clustering
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DOI：
10.1007/s11517-021-02418-7
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发表时间：
2021-07-31
影响因子：
3.2
通讯作者：
Henderson, James H.
中科院分区：
文献类型：
--
作者：
Brasch, Megan E.;Pena, Alexis N.;Henderson, James H.
体外细胞培养模型系统通常采用单一培养，尽管细胞通常存在于体内多样化、异质的微环境中。因此，异质培养越来越多地被用于研究细胞表型如何相互作用。然而，在异质系统中准确识别和表征不同表型亚群的能力仍然是一个主要挑战。在这里，我们提出了一种基于计算的图像分析方法，包括用于特征识别的基于轮廓的自动细胞跟踪，用于特征还原的主成分分析，以及用于亚群表征的围绕介质的划分，以非破坏性和非侵入性地从活细胞显微镜图像数据中识别功能不同的细胞表型亚群。利用内皮细胞和平滑肌细胞的异质模型系统，我们证明了这种方法可以应用于单一和共培养的核形态测量和运动数据，以识别细胞表型亚群。形态聚类鉴定了单培养与共培养的最小差异，而运动性聚类揭示了一部分内皮细胞和平滑肌细胞在共培养中具有更高的运动性，这在单培养中没有观察到。我们预计，这种使用非破坏性和非侵入性成像的方法可以广泛应用于异质细胞培养模型系统，以促进对异质性如何改变细胞表型的理解。
In vitro cell culture model systems often employ monocultures, despite the fact that cells generally exist in a diverse, heterogeneous microenvironment in vivo. In response, heterogeneous cultures are increasingly being used to study how cell phenotypes interact. However, the ability to accurately identify and characterize distinct phenotypic subpopulations within heterogeneous systems remains a major challenge. Here, we present the use of a computational, image analysis-based approach-comprising automated contour-based cell tracking for feature identification, principal component analysis for feature reduction, and partitioning around medoids for subpopulation characterization-to non-destructively and non-invasively identify functionally distinct cell phenotypic subpopulations from live-cell microscopy image data. Using a heterogeneous model system of endothelial and smooth muscle cells, we demonstrate that this approach can be applied to both mono and co-culture nuclear morphometric and motility data to discern cell phenotypic subpopulations. Morphometric clustering identified minimal difference in mono- versus co-culture, while motility clustering revealed that a portion of endothelial cells and smooth muscle cells adopt increased motility rates in co-culture that are not observed in monoculture. We anticipate that this approach using non-destructive and non-invasive imaging can be applied broadly to heterogeneous cell culture model systems to advance understanding of how heterogeneity alters cell phenotype.