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Deconvolution of subcellular protrusion heterogeneity and the underlying actin regulator dynamics from live cell imaging

机译:来自活细胞成像的亚细胞突起异质性和基础肌动蛋白调节剂动力学的反卷积

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Cell protrusion is morphodynamically heterogeneous at the subcellular level. However, the mechanism of cell protrusion has been understood based on the ensemble average of actin regulator dynamics. Here, we establish a computational framework called HACKS (deconvolution of heterogeneous activity in coordination of cytoskeleton at the subcellular level) to deconvolve the subcellular heterogeneity of lamellipodial protrusion from live cell imaging. HACKS identifies distinct subcellular protrusion phenotypes based on machine-learning algorithms and reveals their underlying actin regulator dynamics at the leading edge. Using our method, we discover “accelerating protrusion”, which is driven by the temporally ordered coordination of Arp2/3 and VASP activities. We validate our finding by pharmacological perturbations and further identify the fine regulation of Arp2/3 and VASP recruitment associated with accelerating protrusion. Our study suggests HACKS can identify specific subcellular protrusion phenotypes susceptible to pharmacological perturbation and reveal how actin regulator dynamics are changed by the perturbation.
机译:细胞突起在亚细胞水平上在形态动力学上是异质的。但是,已经基于肌动蛋白调节剂动力学的整体平均值了解了细胞突出的机制。在这里,我们建立了一个称为HACKS(在亚细胞水平上协调细胞骨架中的异质活性的反卷积)以消除活细胞成像中的lamellipodial突起的亚细胞异质性的计算框架。 HACKS基于机器学习算法识别不同的亚细胞突出表型,并在前沿揭示其潜在的肌动蛋白调节剂动力学。使用我们的方法,我们发现“加速突起”,这是由Arp2 / 3和VASP活动的时间顺序协调驱动的。我们通过药理学扰动验证了我们的发现,并进一步确定了与加速突起相关的Arp2 / 3和VASP募集的精细调节。我们的研究表明,HACKS可以识别易受药理学扰动的特定亚细胞突出表型,并揭示肌动蛋白调节剂动力学如何因扰动而改变。

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