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

Deconvolution of subcellular protrusion heterogeneity and the underlying actin regulator dynamics from live cell imaging.
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DOI:
10.1038/s41467-018-04030-0
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发表时间:
2018-04-27
影响因子:
16.6
通讯作者:
Lee K
Lee K
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Wang C;Choi HJ;Kim SJ;Desai A;Lee N;Kim D;Bae Y;Lee K

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细胞突出在亚细胞水平上具有形态动力学异质性。然而,基于肌动蛋白调节动力学的整体平均,细胞突出的机制已经被理解。在这里,我们建立了一个称为HACKS(亚细胞水平细胞骨架协调异质性活动的反卷积)的计算框架,以从活细胞成像中反卷积板脚突的亚细胞异质性。HACKS基于机器学习算法识别了不同的亚细胞突起表型,并在前沿揭示了其潜在的肌动蛋白调节动力学。利用我们的方法,我们发现了“加速突出”,这是由Arp2/3和VASP活性的时间有序协调驱动的。我们通过药理学扰动验证了我们的发现,并进一步确定了Arp2/3和VASP募集与加速突出相关的精细调节。我们的研究表明黑客可以识别易受药理学干扰的特定亚细胞突出表型,并揭示肌动蛋白调节动力学是如何被扰动改变的。细胞突出动力学在亚细胞水平上是异质的,但目前的分析是在细胞或整体水平上进行的。在这里,作者开发了一个计算框架来量化亚细胞突出表型,并揭示了前沿潜在的肌动蛋白调节动力学。
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. Cell protrusion dynamics are heterogeneous at the subcellular level, but current analyses operate at the cellular or ensemble level. Here the authors develop a computational framework to quantify subcellular protrusion phenotypes and reveal the underlying actin regulator dynamics at the leading edge.
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