UMass Chan Medical School Faculty Publications

UMMS Affiliation

Department of Molecular, Cell and Cancer Biology; UMass Metabolic Network

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Article Preprint


Amino Acids, Peptides, and Proteins | Biological Factors | Cell Biology | Cells | Computational Biology | Heterocyclic Compounds


Cell protrusion is morphodynamically heterogeneous at the subcellular level. However, the mechanistic understanding of protrusion activities is usually based on the ensemble average of actin regulator dynamics at the cellular or population levels. Here, we establish a machine learning-based computational framework called HACKS (deconvolution of Heterogeneous Activity Coordination in cytosKeleton at a Subcellular level) to deconvolve the subcellular heterogeneity of lamellipodial protrusion in migrating cells. HACKS quantitatively identifies distinct subcellular protrusion phenotypes from highly heterogeneous protrusion activities and reveals their underlying actin regulator dynamics at the leading edge. Furthermore, it can identify specific subcellular protrusion phenotypes susceptible to pharmacological perturbation and reveal how actin regulator dynamics are changed by the perturbation. Using our method, we discovered 'accelerating' protrusion phenotype in addition to 'fluctuating' and 'periodic' protrusions. Intriguingly, the accelerating protrusion was driven by the temporally coordinated actions between Arp2/3 and VASP: initiated by Arp2/3-mediated actin nucleation, and then accelerated by VASP-mediated actin elongation. We were able to confirm it by pharmacological perturbations using CK666 and Cytochalasin D, which specifically reduced 'strong accelerating protrusion' activities. Taken together, we have demonstrated that HACKS allows us to discover the fine differential coordination of molecular dynamics underlying subcellular protrusion heterogeneity via a machine learning analysis of live cell imaging data.


cell protrusion, heterogeneity, actin, deconvolution, Heterogeneous Activity Coordination in cytosKeleton, HACKS, VASP, cell biology

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The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license.

DOI of Published Version



bioRxiv 144238; doi: Link to preprint on bioRxiv service.

Related Resources

Now published in Nature Communications doi: 10.1038/s41467-018-04030-0

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Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.