Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany.
Research Unit Sensory Biology and Organogenesis, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany.
Cytometry A. 2018 Mar;93(3):314-322. doi: 10.1002/cyto.a.23260. Epub 2017 Nov 10.
Proliferating stem cells in the adult body are the source of constant regeneration. In the brain, neural stem cells (NSCs) divide to maintain the stem cell population and generate neural progenitor cells that eventually replenish mature neurons and glial cells. How much spatial coordination of NSC division and differentiation is present in a functional brain is an open question. To quantify the patterns of stem cell divisions, one has to (i) identify the pool of NSCs that have the ability to divide, (ii) determine NSCs that divide within a given time window, and (iii) analyze the degree of spatial coordination. Here, we present a bioimage informatics pipeline that automatically identifies GFP expressing NSCs in three-dimensional image stacks of zebrafish brain from whole-mount preparations. We exploit the fact that NSCs in the zebrafish hemispheres are located on a two-dimensional surface and identify between 1,500 and 2,500 NSCs in six brain hemispheres. We then determine the position of dividing NSCs in the hemisphere by EdU incorporation into cells undergoing S-phase and calculate all pairwise NSC distances with three alternative metrics. Finally, we fit a probabilistic model to the observed spatial patterns that accounts for the non-homogeneous distribution of NSCs. We find a weak positive coordination between dividing NSCs irrespective of the metric and conclude that neither strong inhibitory nor strong attractive signals drive NSC divisions in the adult zebrafish brain. © 2017 International Society for Advancement of Cytometry.
成年生物体内不断增殖的干细胞是持续再生的来源。在大脑中，神经干细胞 (NSC) 分裂以维持干细胞群体并产生神经祖细胞，这些细胞最终会补充成熟神经元和神经胶质细胞。在功能正常的大脑中，NSC 分裂和分化的空间协调程度是一个悬而未决的问题。为了量化干细胞分裂的模式，人们必须：（i）识别具有分裂能力的 NSC 池；（ii）确定在给定时间窗口内分裂的 NSCs；（iii）分析空间协调的程度。在这里，我们提出了一个生物图像信息学管道，该管道可以自动识别来自全脑准备的斑马鱼大脑三维图像堆栈中表达 GFP 的 NSCs。我们利用了这样一个事实，即斑马鱼半球中的 NSCs 位于二维表面上，并在六个大脑半球中鉴定出 1500 到 2500 个 NSCs。然后，我们通过 EdU 掺入到 S 期细胞中来确定半球中正在分裂的 NSCs 的位置，并使用三种替代度量标准计算所有两两 NSC 之间的距离。最后，我们使用观察到的空间模式拟合概率模型，该模型解释了 NSCs 的非均匀分布。我们发现，无论使用哪种度量标准，正在分裂的 NSCs 之间都存在微弱的正协调关系，这表明在成年斑马鱼大脑中，既没有强烈的抑制性信号，也没有强烈的吸引性信号来驱动 NSC 分裂。©2017 国际细胞分析协会。
