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Abstract：
Advances in imaging, segmentation and tracking have led to the routine generation of large and complex microscopy datasets. New tools are required to process this \'phenomics\' type data. Here, we present \'Cell PLasticity Analysis Tool\' (cellPLATO), a Python-based analysis software designed for measurement and classification of cell behaviours based on clustering features of cell morphology and motility. Used after segmentation and tracking, the tool extracts features from each cell per timepoint, using them to segregate cells into dimensionally reduced behavioural subtypes. Resultant cell tracks describe a \'behavioural ID\' at each timepoint, and similarity analysis allows the grouping of behavioural sequences into discrete trajectories with assigned IDs. Here, we use cellPLATO to investigate the role of IL-15 in modulating human natural killer (NK) cell migration on ICAM-1 or VCAM-1. We find eight behavioural subsets of NK cells based on their shape and migration dynamics between single timepoints, and four trajectories based on sequences of these behaviours over time. Therefore, by using cellPLATO, we show that IL-15 increases plasticity between cell migration behaviours and that different integrin ligands induce different forms of NK cell migration.
摘要：
影像学的进展，分割，和跟踪导致常规生成大型和复杂的显微镜数据集。需要新工具来处理此“表型组学”类型的数据。细胞方度分析工具（cellPLATO）是一种基于Python的分析软件，旨在根据细胞形态和运动性的聚类特征对细胞行为进行测量和分类。在分割和跟踪后使用，该工具从每个时间点的每个单元中提取特征，使用它们将细胞分离为降维的行为亚型。结果细胞轨迹描述了每个时间点的“行为ID”，相似性分析允许将行为序列分组为具有分配ID的离散轨迹。这里,我们使用cellPLATO研究IL-15在ICAM-1或VCAM-1上调节人NK细胞迁移中的作用。我们根据NK细胞的形状和单个时间点之间的迁移动力学发现了8个行为亚群，和4个轨迹基于这些行为随时间的序列。因此,使用cellPLATO，我们显示IL-15增加细胞迁移行为之间的可塑性，并且不同的整合素配体诱导不同形式的NK细胞迁移。
