ArticleNature communications2018
Deconvolution of subcellular protrusion heterogeneity and the underlying actin regulator dynamics from live cell imaging.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Diffraction-informed deep learning for molecular-specific holograms of breast cancer cells.APL bioengineering · 2025Article
- Fine-grained forecasting of COVID-19 trends at the county level in the United States.NPJ digital medicine · 2025Article
- Spatiotemporal analysis of F-actin polymerization with micropillar arrays reveals synchronization between adhesion sites.Molecular biology of the cell · 2024Article
- Interpretable Fine-Grained Phenotypes of Subcellular Dynamics via Unsupervised Deep Learning.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- PPP2R1A regulates migration persistence through the NHSL1-containing WAVE Shell Complex.Nature communications · 2023Article
- Deep cross-modal feature learning applied to predict acutely decompensated heart failure using in-home collected electrocardiography and transthoracic bioimpedance.Artificial intelligence in medicine · 2023Article
- Unsupervised Contour Tracking of Live Cells by Mechanical and Cycle Consistency Losses.Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition · 2023Article
- Protocol for live cell image segmentation to profile cellular morphodynamics using MARS-Net.STAR protocols · 2022Article
- Granger-causal inference of the lamellipodial actin regulator hierarchy by live cell imaging without perturbation.Cell systems · 2022Article
- A machine learning pipeline revealing heterogeneous responses to drug perturbations on vascular smooth muscle cell spheroid morphology and formation.Scientific reports · 2021Article
- A deep learning-based segmentation pipeline for profiling cellular morphodynamics using multiple types of live cell microscopy.Cell reports methods · 2021Article
- Emerging machine learning approaches to phenotyping cellular motility and morphodynamics.Physical biology · 2021Review
- Data science in cell imaging.Journal of cell science · 2021Review
- New insights and best practices for the successful use of Empirical Mode Decomposition, Iterative Filtering and derived algorithms.Scientific reports · 2020Article
- Lamellipodin tunes cell migration by stabilizing protrusions and promoting adhesion formation.Journal of cell science · 2020Article
- Direct measurement of vertical forces shows correlation between mechanical activity and proteolytic ability of invadopodia.Science advances · 2020Article
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Authors and funding
8 authors.
Funding
Abstract
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.
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