Reconstructing Actin Dynamics of the Leading Edge from Observational Data

Mesenchymal cell migration starts with the protrusion of the cell's leading edge, enabled by the branching growth of the actin network. Two crucial molecular players in protrusion are actin filaments and the Arp2/3 protein complex, the branching agent. Traditionally, protrusion models are intuited from several perturbative experiments. Recent multiplex microscopy imaging data promise to drastically change this paradigm by providing measurements of naturally fluctuating densities of key proteins at the leading edge of unperturbed cells. We report the first attempt to reconstruct the mechanistic protrusion model from such data. We analyze fluctuations of F-actin and Arp2/3 densities and cell edge velocity using phase space and regression analysis to reconstruct linearized stochastic actin-Arp2/3-velocity coupled dynamics. We then build a nonlinear partial differential equation model of these dynamics based on previous knowledge of this system and parsimony. The resulting model recovers the rates of reactions and mechanical and transport processes in the lamellipodium from a single non-perturbative experiment. The model posits that the only essential nonlinearities in the lamellipodial dynamics stem from the retrograde flow of F-actin. The model suggests that the protrusion is dominated by a damped oscillatory cycle resulting from a combination of positive feedback from Arp2/3 to protrusion velocity and negative feedback from F-actin to the velocity.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-02-01
DOI
https://doi.org/10.64898/2026.01.31.703047
Primary Topic
Cellular Mechanics and Interactions
Type
article
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article

Reconstructing Actin Dynamics of the Leading Edge from Observational Data

Alex Mogilner, Gaudenz Danuser, Jungsik Noh, Christopher Miles et al.
bioRxiv (Cold Spring Harbor Laboratory)
Cellular Mechanics and Interactions
article

Reconstructing Actin Dynamics of the Leading Edge from Observational Data

Alex Mogilner, Gaudenz Danuser, Jungsik Noh, Christopher Miles, Wenzheng Shi
article en

Abstract

Mesenchymal cell migration starts with the protrusion of the cell's leading edge, enabled by the branching growth of the actin network. Two crucial molecular players in protrusion are actin filaments and the Arp2/3 protein complex, the branching agent. Traditionally, protrusion models are intuited from several perturbative experiments. Recent multiplex microscopy imaging data promise to drastically change this paradigm by providing measurements of naturally fluctuating densities of key proteins at the leading edge of unperturbed cells. We report the first attempt to reconstruct the mechanistic protrusion model from such data. We analyze fluctuations of F-actin and Arp2/3 densities and cell edge velocity using phase space and regression analysis to reconstruct linearized stochastic actin-Arp2/3-velocity coupled dynamics. We then build a nonlinear partial differential equation model of these dynamics based on previous knowledge of this system and parsimony. The resulting model recovers the rates of reactions and mechanical and transport processes in the lamellipodium from a single non-perturbative experiment. The model posits that the only essential nonlinearities in the lamellipodial dynamics stem from the retrograde flow of F-actin. The model suggests that the protrusion is dominated by a damped oscillatory cycle resulting from a combination of positive feedback from Arp2/3 to protrusion velocity and negative feedback from F-actin to the velocity.

bioRxiv (Cold Spring Harbor Laboratory)
University of Utah (US), Courant Institute of Mathematical Sciences (US), Southwestern Medical Center (US), Southwestern Medical Center (US), New York University (US), The University of Texas Southwestern Medical Center (US)
Openalex Percentile: Top 72%
Cellular Mechanics and Interactions
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Reconstructing Actin Dynamics of the Leading Edge from Observational Data — Alex Mogilner, Gaudenz Danuser, et al. · bioRxiv (Cold Spring Harbor Laboratory) (2026) | TGRS Research Map | TGRS