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cellPLATO - 一种用于识别异质细胞轨迹数据中细胞行为的无监督方法。

cellPLATO - an unsupervised method for identifying cell behaviour in heterogeneous cell trajectory data.

机构信息

Department of Pediatrics, Vagelos College of Physicians and Surgeons, Columbia University Medical Center, NYC, NY 10032, USA.

Institute for the Physics of Living Systems, Institute for Structural and Molecular Biology and London Centre for Nanotechnology, University College London, London WC1H 0AH, UK.

出版信息

J Cell Sci. 2024 Oct 15;137(20). doi: 10.1242/jcs.261887. Epub 2024 Jun 12.

DOI:10.1242/jcs.261887
PMID:38738282
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11213520/
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

成像、分割和跟踪技术的进步已经使得大规模、复杂的显微镜数据集的生成成为常规操作。需要新的工具来处理这种“表型组学”类型的数据。在这里,我们介绍了“细胞可塑性分析工具”(cellPLATO),这是一个基于 Python 的分析软件,用于根据细胞形态和运动的聚类特征来测量和分类细胞行为。该工具在分割和跟踪之后使用,从每个细胞的每个时间点提取特征,使用这些特征将细胞分为具有维度降低的行为亚型。得到的细胞轨迹在每个时间点描述一个“行为 ID”,相似性分析允许将行为序列分组为具有指定 ID 的离散轨迹。在这里,我们使用 cellPLATO 来研究白细胞介素 15(IL-15)在调节人类自然杀伤(NK)细胞在细胞间黏附分子 1(ICAM-1)或血管细胞黏附分子 1(VCAM-1)上的迁移中的作用。我们根据 NK 细胞在单个时间点的形状和迁移动力学,确定了八个行为亚群,根据这些行为的时间序列确定了四个轨迹。因此,通过使用 cellPLATO,我们表明 IL-15 增加了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。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c066/11213520/5cd90156edfc/joces-137-261887-g8.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c066/11213520/5cd90156edfc/joces-137-261887-g8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c066/11213520/bbf6d259c35f/joces-137-261887-g1.jpg
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