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Individual-based simulations for cell biochemistry in crowded environments| old_uid | 4157 |
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| title | Individual-based simulations for cell biochemistry in crowded environments |
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| start_date | 2008/02/22 |
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| schedule | 09h |
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| online | no |
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| summary | Standard modeling works in cell biochemistry are usually based on mean-field equations, most often referred to as "laws of mass-action". Yet, the derivation of these laws is based on strict assumptions. In particular, the reaction medium must be dilute, perfectly-mixed, three-dimensional and spatially homogeneous and the resulting kinetics are purely deterministic. Many of these assumptions may be violated in cells. Notably, single-cell measurements show that protein diffusion in most compartments (including cytosol, nucleus and membranes) is subdiffusive (anomalous diffusion). This phenomenon is mainly caused by physical obstruction to diffusion due to large-size obstacles, that actually abounds in cells (organelles, internal networks, large macromolecular complexes...). Fundamentally, this experimental observation tells us that diffusion in cells is not perfectly mixing and that cellular media can be considered as spatially inhomogeneous. My objective is thus to try and evaluate what kind of behaviors can be expected that are not accounted for by the laws of mass-action. To simulate these effects, usual stochastic kinetic approaches such as Gillespie's algorithms are not well suited, because they explicitly assume perfect mixing and do not take into account physical obstruction. Conversely, lattice gas automata or individual-based modeling appears to be the most appropriate tools. In this talk, I will present two application examples of such individual-based simulations.
The first example concerns simple enzyme reactions in cell membranes with molecular crowding. Individual-based simulations indicate that the classical mean-field formalism for these reactions (Michaelis-Menten kinetics) fails short of describing the kinetics. Conversely, so-called "fractal" kinetics can be used to describe the observed behaviors. Furthermore, the simulations uncover a spontaneous tendency to segregate reaction substrates and products within distinct spatial zones of the membrane, i.e. a phenomenon similar to morphogenesis.
The second example concerns aging in E. coli and protein aggregation. F. Taddei and A. Lindner (U571 INSERM, Necker, Paris) showed that E. coli indeed ages, and that aging in this bacterium is related to specific spatial aggregation patterns of chaperones. We very recently started a collaboration work to simulate these behaviors and try and determine what basic mechanisms are likely to be at play, with a focus on the influence of molecular crowding. I will present how individual-based simulations may be used to address several aspects related to this issue.
Finally, I will conclude with a brief overview of a current collaboration with Olivier Michel (Ibisc Lab., CNRS FRE 2873, University of Evry, Genopole) about hybrid simulation methods, i.e. simulation techniques mixing continuous mean-field modeling at the relevant length scale or spatial location, with discrete, individual-based simulations in other locations. |
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| responsibles | Bourgine |
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