Stochastic Severing of Actin Filaments by Actin Depolymerizing Factor/Cofilin Controls the Emergence of a Steady Dynamical Regime

Université Joseph Fourier, TIMC-IMAG Laboratory, Grenoble, France.
Biophysical Journal (Impact Factor: 3.97). 04/2008; 94(6):2082-94. DOI: 10.1529/biophysj.107.121988
Source: PubMed


Actin dynamics (i.e., polymerization/depolymerization) powers a large number of cellular processes. However, a great deal remains to be learned to explain the rapid actin filament turnover observed in vivo. Here, we developed a minimal kinetic model that describes key details of actin filament dynamics in the presence of actin depolymerizing factor (ADF)/cofilin. We limited the molecular mechanism to 1), the spontaneous growth of filaments by polymerization of actin monomers, 2), the ageing of actin subunits in filaments, 3), the cooperative binding of ADF/cofilin to actin filament subunits, and 4), filament severing by ADF/cofilin. First, from numerical simulations and mathematical analysis, we found that the average filament length, L, is controlled by the concentration of actin monomers (power law: 5/6) and ADF/cofilin (power law: -2/3). We also showed that the average subunit residence time inside the filament, T, depends on the actin monomer (power law: -1/6) and ADF/cofilin (power law: -2/3) concentrations. In addition, filament length fluctuations are approximately 20% of the average filament length. Moreover, ADF/cofilin fragmentation while modulating filament length keeps filaments in a high molar ratio of ATP- or ADP-P(i) versus ADP-bound subunits. This latter property has a protective effect against a too high severing activity of ADF/cofilin. We propose that the activity of ADF/cofilin in vivo is under the control of an affinity gradient that builds up dynamically along growing actin filaments. Our analysis shows that ADF/cofilin regulation maintains actin filaments in a highly dynamical state compatible with the cytoskeleton dynamics observed in vivo.

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    • "While at high concentrations they can increase the polymerization by nucleating new actin filaments (Andrianantoandro and Pollard, 2006). ADF/cofilins can keep the actin filaments in a very dynamic state by inducing a steady regime in the filament length fluctuation (Roland et al., 2008). The ADF/cofilins can bind actin monomers as well (Paavilainen et al., 2004). "
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    ABSTRACT: Several cellular processes rely on the fine tuning of actin cytoskeleton. A central component in the regulation of this cellular machinery is the ADF-H domain proteins. Despite sharing the same domain, ADF-H domain proteins produce a diverse functional landscape in the regulation of the actin cytoskeleton. Recent findings emphasize that the functional and structural features of these proteins can differ not only between ADF-H families but even within the same family. The structural and evolutional background of this functional diversity is poorly understood. This review focuses on the specific functional characteristics of ADF-H domain proteins and how these features can be linked to structural differences in the ADF-H domain and also to different conformational transitions in actin. In the light of recent discoveries we pay special attention to the ADF/cofilin proteins to find tendencies along which the functional and structural diversification is governed through the evolution.
    European Journal of Cell Biology 05/2014; 93(5-6). DOI:10.1016/j.ejcb.2013.12.001 · 3.83 Impact Factor
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    • "Actin polymerization plays a key role in cell morphology and motility [59] [60]. Roland et al. [40] presented a dynamic model of actin polymerization featuring filament elongation by monomer addition, stabilization by ATP hydrolysis, and severing mediated by actin depolymerizing factor (ADF)/cofilin. Sneddon et al. [14] presented a rule-based formulation of the Roland et al. model and replicated their results using NFsim. The model features an excess of actin monomer and ADF molecules. "
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    ABSTRACT: Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This "network-free" approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of "partial network expansion" into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility.
    PLoS Computational Biology 04/2014; 10(4):e1003544. DOI:10.1371/journal.pcbi.1003544 · 4.62 Impact Factor
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    • "It is already known that one of the aspects of osmotic stress resistance is to trigger cytoskeletal reorganization in the form of actin filament rearrangements [29], [30]. Furthermore, the regulation of CFL further strengthens the theory, as CFL has been shown to be an essential actin regulatory protein that severs filaments and accelerates actin assembly dynamics [32], [33]. "
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    ABSTRACT: Osmotic stress has been shown to regulate cytoskeletal protein expression. It is generally known that vimentin is rapidly degraded during apoptosis by multiple caspases, resulting in diverse vimentin fragments. Despite the existence of the known apoptotic vimentin fragments, we demonstrated in our study the existence of different forms of vimentin VIM I, II, III, and IV with different molecular weights in various renal cell lines. Using a proteomics approach followed by western blot analyses and immunofluorescence staining, we proved the apoptosis-independent existence and differential regulation of different vimentin forms under varying conditions of osmolarity in renal cells. Similar impacts of osmotic stress were also observed on the expression of other cytoskeleton intermediate filament proteins; e.g., cytokeratin. Interestingly, 2D western blot analysis revealed that the forms of vimentin are regulated independently of each other under glucose and NaCl osmotic stress. Renal cells, adapted to high NaCl osmotic stress, express a high level of VIM IV (the form with the highest molecular weight), besides the three other forms, and exhibit higher resistance to apoptotic induction with TNF-α or staurosporin compared to the control. In contrast, renal cells that are adapted to high glucose concentration and express only the lower-molecular-weight forms VIM I and II, were more susceptible to apoptosis. Our data proved the existence of different vimentin forms, which play an important role in cell resistance to osmotic stress and are involved in cell protection against apoptosis.
    PLoS ONE 07/2013; 8(7):e68301. DOI:10.1371/journal.pone.0068301 · 3.23 Impact Factor
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