Fine-grained, nonlinear registration of live cell movies reveals spatiotemporal organization of diffuse molecular processes.
Fine-grained, nonlinear registration of live cell movies reveals spatiotemporal organization of diffuse molecular processes.
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DOI：
10.1371/journal.pcbi.1009667
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发表时间：
2022-12
影响因子：
4.3
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我们提出了一种应用非线性图像配准的方法，用于在显微镜下将细胞轮廓和内部的每一帧的时间推移序列与参考系中同一细胞的轮廓和内部进行比对。配准依赖于亚细胞基准标记、细胞运动掩码和拓扑正则化，该拓扑正则化在配准上强制差同胚，而不显著损失粒度。这使得可以对整个细胞中极其嘈杂和扩散的分子过程进行时空分析。我们通过测量肌动蛋白细胞骨架图像的预测和原始时间推移序列之间的强度差异，以及揭示基于FRET的活性生物传感器在MDA-MB-231细胞中可视化的空间组织的Global和GTPase信号动力学区域，验证了不同基准标记的配准方法。然后，我们结合随机时间序列分析演示了配准方法的应用。我们描述了U2OS细胞中细胞质蛋白轮廓蛋白局部相干动力学的不同区域。对Profilin动力学的进一步分析表明，在细胞对称性破坏和极化过程中，Profilin与肌动蛋白细胞骨架重组有很强的关系。因此，这项研究提供了一个提取信息的框架，以探索细胞形态动力学、蛋白质分布和细胞中持续形状变化的信号之间的功能相互作用。实现所提出的配准方法的matlab代码可在https://github.com/DanuserLab/Mask-Regularized-Diffeomorphic-Cell-Registration.上找到通过采用基于光流的非线性图像配准，我们创建了一种跨整个细胞的局部亚细胞过程的时间序列分析方法。这是我们之前发表的基于单元边缘的参考方法的扩展，该方法不允许提取离单元边缘超过几微米的有意义的亚细胞时间序列。我们利用在每个亚细胞位置的新采样能力，在对称破坏和极化细胞中发现有组织的轮廓蛋白动力学，这反过来又与其调控目标肌动蛋白的动力学有关。
We present an application of nonlinear image registration to align in microscopy time lapse sequences for every frame the cell outline and interior with the outline and interior of the same cell in a reference frame. The registration relies on a subcellular fiducial marker, a cell motion mask, and a topological regularization that enforces diffeomorphism on the registration without significant loss of granularity. This allows spatiotemporal analysis of extremely noisy and diffuse molecular processes across the entire cell. We validate the registration method for different fiducial markers by measuring the intensity differences between predicted and original time lapse sequences of Actin cytoskeleton images and by uncovering zones of spatially organized GEF- and GTPase signaling dynamics visualized by FRET-based activity biosensors in MDA-MB-231 cells. We then demonstrate applications of the registration method in conjunction with stochastic time-series analysis. We describe distinct zones of locally coherent dynamics of the cytoplasmic protein Profilin in U2OS cells. Further analysis of the Profilin dynamics revealed strong relationships with Actin cytoskeleton reorganization during cell symmetry-breaking and polarization. This study thus provides a framework for extracting information to explore functional interactions between cell morphodynamics, protein distributions, and signaling in cells undergoing continuous shape changes. Matlab code implementing the proposed registration method is available at https://github.com/DanuserLab/Mask-Regularized-Diffeomorphic-Cell-Registration. By adapting optical flow based, nonlinear image registration we created a method for the time-series analysis of local subcellular processes across the entire cell. This is an extension to our previously published cell edge-based referencing method, which does not allow the extraction of meaningful subcellular time-series more than a few microns away from the cell edge. We leverage the new capacity of sampling at every subcellular location for the discovery of organized Profilin dynamics in symmetry-breaking and polarizing cells, which in turn are related to the dynamics of its regulatory target Actin.
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影响因子：
64.8
作者：
通讯作者：
--
影响因子：
7.7
作者：
Damiano-Guercio, Julia;Kurzawa, Laetitia;Faix, Jan
通讯作者：
Faix, Jan
DOI：
10.1126/science.aaq1392
发表时间：
2018-04-20
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Liu TL;Upadhyayula S;Milkie DE;Singh V;Wang K;Swinburne IA;Mosaliganti KR;Collins ZM;Hiscock TW;Shea J;Kohrman AQ;Medwig TN;Dambournet D;Forster R;Cunniff B;Ruan Y;Yashiro H;Scholpp S;Meyerowitz EM;Hockemeyer D;Drubin DG;Martin BL;Matus DQ;Koyama M;Megason SG;Kirchhausen T;Betzig E
通讯作者：
Betzig E
影响因子：
7.7
作者：
Funk, Johanna;Merino, Felipe;Bieling, Peter
通讯作者：
Bieling, Peter
影响因子：
7.8
作者：
Azoitei, Mihai L.;Noh, Jungsik;Danuser, Gaudenz
通讯作者：
Danuser, Gaudenz