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Effects of macromolecular crowding on intracellular diffusion from a single particle perspective.

Hall D, Hoshino M - Biophys Rev (2010)

Bottom Line: Through a range of intermolecular forces and pseudo-forces, this complex background environment may cause biochemical reactions to behave differently to their in vitro counterparts.Engaging the subject from the perspective of a single particle's motion, we place the focus of our review on two areas: (1) experimental procedures for conducting single particle tracking experiments within cells along with methods for extracting information from these experiments; (2) theoretical factors affecting the translational diffusion of single molecules within crowded two-dimensional membrane and three-dimensional solution environments.We conclude by discussing a number of recent publications relating to intracellular diffusion in light of the reviewed material.

View Article: PubMed Central - PubMed

ABSTRACT
Compared to biochemical reactions taking place in relatively well-defined aqueous solutions in vitro, the corresponding reactions happening in vivo occur in extremely complex environments containing only 60-70% water by volume, with the remainder consisting of an undefined array of bio-molecules. In a biological setting, such extremely complex and volume-occupied solution environments are termed 'crowded'. Through a range of intermolecular forces and pseudo-forces, this complex background environment may cause biochemical reactions to behave differently to their in vitro counterparts. In this review, we seek to highlight how the complex background environment of the cell can affect the diffusion of substances within it. Engaging the subject from the perspective of a single particle's motion, we place the focus of our review on two areas: (1) experimental procedures for conducting single particle tracking experiments within cells along with methods for extracting information from these experiments; (2) theoretical factors affecting the translational diffusion of single molecules within crowded two-dimensional membrane and three-dimensional solution environments. We conclude by discussing a number of recent publications relating to intracellular diffusion in light of the reviewed material.

No MeSH data available.


Related in: MedlinePlus

Effect of crowding on diffusion Top panel (a and b) Schematic showing diffusion of a tracer particle in crowded and confined 2D and 3D fluids of same sized particles (tracer R = 2 nm, H = 5 nm, fluid vessel radius 30 nm). Central panel (c and d) Normalized long-time tracer diffusion coefficients as a function of fractional area, θ, or volume, ϕ: occupation for repulsive saw tooth (blue), attractive saw tooth (black) and hard particle (red) intermolecular potentials operative between tracer and crowder molecules (ε = +kBT, -kBT or 0, Lij = Ri) (all trajectories were ended before approaching the wall). Green line indicates reduction in long-time tracer diffusion for hard particle cases as calculated for unconfined 2D fluids by Bussell et al. 1995 and in unconfined 3D fluids by Tokuyama and Oppenheim 1994. Bottom panel (e and f) Averaged diagonal elements of the mean squared displacements from the diffusion tensor for repulsive (blue), attractive (black) and hard particle only (red) for the most crowded cases considered in 2D and 3D, respectively
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Fig7: Effect of crowding on diffusion Top panel (a and b) Schematic showing diffusion of a tracer particle in crowded and confined 2D and 3D fluids of same sized particles (tracer R = 2 nm, H = 5 nm, fluid vessel radius 30 nm). Central panel (c and d) Normalized long-time tracer diffusion coefficients as a function of fractional area, θ, or volume, ϕ: occupation for repulsive saw tooth (blue), attractive saw tooth (black) and hard particle (red) intermolecular potentials operative between tracer and crowder molecules (ε = +kBT, -kBT or 0, Lij = Ri) (all trajectories were ended before approaching the wall). Green line indicates reduction in long-time tracer diffusion for hard particle cases as calculated for unconfined 2D fluids by Bussell et al. 1995 and in unconfined 3D fluids by Tokuyama and Oppenheim 1994. Bottom panel (e and f) Averaged diagonal elements of the mean squared displacements from the diffusion tensor for repulsive (blue), attractive (black) and hard particle only (red) for the most crowded cases considered in 2D and 3D, respectively

Mentions: From the very earliest studies of diffusive motion in the 2D and 3D biological environments of the cell membrane and cell cytosol, strong differences to the simple behaviour predicted for continuum fluids have been observed (e.g. 3D: Jacobson and Wojcieszyn 1984; Gershon et al. 1985; Arrio-Dupont et al. 2000; Goulian and Simon 2000; e.g. 2D: Schlessinger et al. 1977; Sheetz et al. 1980; Haggie and Verkman 2002; Sakaki et al. 1982). Recently, rather than being interpreted as just unnecessary complications, these effects are now seen as probable design features of the cellular reaction environment that have resulted from the natural optimization process of evolution (Kurganov et al. 1985; Bray 1998; Luby-Phelps et al. 1988; Burdzy and Hołyst 2001; Haggie and Verkman 2002; Schnell and Turner 2004; Sear 2005; Ma'ayan et al. 2005; Weiss 2008). In this vein, the degree of anomalous diffusion in the cytoplasm has been interpreted as a means of tuning the search process for an interacting partner (Burz et al. 2006; Iwahara and Clore 2006;Tang et al. 2006) in crowded solution conditions by helping to both spatially determine the location of the interacting partner and also to enhance the probability of encounter (Weiss 2008; Szymanski and Weiss 2009). In cells lacking significant compartmentalization and structural organization (e.g. prokaryotes), the intracellular 2D and 3D fluids might be approximated by concentrated macromolecular environments (Zimmerman and Trach 1991; Konopka et al. 2006). Using the Brownian dynamics algorithm presented in Eq. 17b, we provide example simulations of 2D and 3D diffusion in a crowded solution of particles of identical size (Fig. 7). Estimates of the long time tracer diffusion coefficient12 indicate that for intermediate crowding regimes, the effect of a repulsive potential is to increase the magnitude of the short-time diffusion coefficient by helping to keep the tracer particle out of the ‘stagnant’ region associated with high local densities of background particles. Not surprisingly, the effect of a weakly attractive potential shows the reverse behaviour, with the tracer diffusion coefficient decreasing due to a combination effect arising from the attractive intermolecular potential (i.e. larger particles diffuse more slowly) and the HI forces (i.e. the tracer spends more time located in higher viscosity regions). The purely hard sphere tracer case with no associated potential was also simulated and is intermediate between the two13. The time dependence of the diffusion coefficient was also analysed and is displayed in Fig. 7 e, f for the three different types of associated intermolecular potential. All three examples demonstrated anomalous diffusion characteristics (α ≈ 0.85) similar in magnitude to those previously measured (Banks and Fradin 2005; Szymanski and Weiss 2009).Fig. 7


Effects of macromolecular crowding on intracellular diffusion from a single particle perspective.

Hall D, Hoshino M - Biophys Rev (2010)

Effect of crowding on diffusion Top panel (a and b) Schematic showing diffusion of a tracer particle in crowded and confined 2D and 3D fluids of same sized particles (tracer R = 2 nm, H = 5 nm, fluid vessel radius 30 nm). Central panel (c and d) Normalized long-time tracer diffusion coefficients as a function of fractional area, θ, or volume, ϕ: occupation for repulsive saw tooth (blue), attractive saw tooth (black) and hard particle (red) intermolecular potentials operative between tracer and crowder molecules (ε = +kBT, -kBT or 0, Lij = Ri) (all trajectories were ended before approaching the wall). Green line indicates reduction in long-time tracer diffusion for hard particle cases as calculated for unconfined 2D fluids by Bussell et al. 1995 and in unconfined 3D fluids by Tokuyama and Oppenheim 1994. Bottom panel (e and f) Averaged diagonal elements of the mean squared displacements from the diffusion tensor for repulsive (blue), attractive (black) and hard particle only (red) for the most crowded cases considered in 2D and 3D, respectively
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2957576&req=5

Fig7: Effect of crowding on diffusion Top panel (a and b) Schematic showing diffusion of a tracer particle in crowded and confined 2D and 3D fluids of same sized particles (tracer R = 2 nm, H = 5 nm, fluid vessel radius 30 nm). Central panel (c and d) Normalized long-time tracer diffusion coefficients as a function of fractional area, θ, or volume, ϕ: occupation for repulsive saw tooth (blue), attractive saw tooth (black) and hard particle (red) intermolecular potentials operative between tracer and crowder molecules (ε = +kBT, -kBT or 0, Lij = Ri) (all trajectories were ended before approaching the wall). Green line indicates reduction in long-time tracer diffusion for hard particle cases as calculated for unconfined 2D fluids by Bussell et al. 1995 and in unconfined 3D fluids by Tokuyama and Oppenheim 1994. Bottom panel (e and f) Averaged diagonal elements of the mean squared displacements from the diffusion tensor for repulsive (blue), attractive (black) and hard particle only (red) for the most crowded cases considered in 2D and 3D, respectively
Mentions: From the very earliest studies of diffusive motion in the 2D and 3D biological environments of the cell membrane and cell cytosol, strong differences to the simple behaviour predicted for continuum fluids have been observed (e.g. 3D: Jacobson and Wojcieszyn 1984; Gershon et al. 1985; Arrio-Dupont et al. 2000; Goulian and Simon 2000; e.g. 2D: Schlessinger et al. 1977; Sheetz et al. 1980; Haggie and Verkman 2002; Sakaki et al. 1982). Recently, rather than being interpreted as just unnecessary complications, these effects are now seen as probable design features of the cellular reaction environment that have resulted from the natural optimization process of evolution (Kurganov et al. 1985; Bray 1998; Luby-Phelps et al. 1988; Burdzy and Hołyst 2001; Haggie and Verkman 2002; Schnell and Turner 2004; Sear 2005; Ma'ayan et al. 2005; Weiss 2008). In this vein, the degree of anomalous diffusion in the cytoplasm has been interpreted as a means of tuning the search process for an interacting partner (Burz et al. 2006; Iwahara and Clore 2006;Tang et al. 2006) in crowded solution conditions by helping to both spatially determine the location of the interacting partner and also to enhance the probability of encounter (Weiss 2008; Szymanski and Weiss 2009). In cells lacking significant compartmentalization and structural organization (e.g. prokaryotes), the intracellular 2D and 3D fluids might be approximated by concentrated macromolecular environments (Zimmerman and Trach 1991; Konopka et al. 2006). Using the Brownian dynamics algorithm presented in Eq. 17b, we provide example simulations of 2D and 3D diffusion in a crowded solution of particles of identical size (Fig. 7). Estimates of the long time tracer diffusion coefficient12 indicate that for intermediate crowding regimes, the effect of a repulsive potential is to increase the magnitude of the short-time diffusion coefficient by helping to keep the tracer particle out of the ‘stagnant’ region associated with high local densities of background particles. Not surprisingly, the effect of a weakly attractive potential shows the reverse behaviour, with the tracer diffusion coefficient decreasing due to a combination effect arising from the attractive intermolecular potential (i.e. larger particles diffuse more slowly) and the HI forces (i.e. the tracer spends more time located in higher viscosity regions). The purely hard sphere tracer case with no associated potential was also simulated and is intermediate between the two13. The time dependence of the diffusion coefficient was also analysed and is displayed in Fig. 7 e, f for the three different types of associated intermolecular potential. All three examples demonstrated anomalous diffusion characteristics (α ≈ 0.85) similar in magnitude to those previously measured (Banks and Fradin 2005; Szymanski and Weiss 2009).Fig. 7

Bottom Line: Through a range of intermolecular forces and pseudo-forces, this complex background environment may cause biochemical reactions to behave differently to their in vitro counterparts.Engaging the subject from the perspective of a single particle's motion, we place the focus of our review on two areas: (1) experimental procedures for conducting single particle tracking experiments within cells along with methods for extracting information from these experiments; (2) theoretical factors affecting the translational diffusion of single molecules within crowded two-dimensional membrane and three-dimensional solution environments.We conclude by discussing a number of recent publications relating to intracellular diffusion in light of the reviewed material.

View Article: PubMed Central - PubMed

ABSTRACT
Compared to biochemical reactions taking place in relatively well-defined aqueous solutions in vitro, the corresponding reactions happening in vivo occur in extremely complex environments containing only 60-70% water by volume, with the remainder consisting of an undefined array of bio-molecules. In a biological setting, such extremely complex and volume-occupied solution environments are termed 'crowded'. Through a range of intermolecular forces and pseudo-forces, this complex background environment may cause biochemical reactions to behave differently to their in vitro counterparts. In this review, we seek to highlight how the complex background environment of the cell can affect the diffusion of substances within it. Engaging the subject from the perspective of a single particle's motion, we place the focus of our review on two areas: (1) experimental procedures for conducting single particle tracking experiments within cells along with methods for extracting information from these experiments; (2) theoretical factors affecting the translational diffusion of single molecules within crowded two-dimensional membrane and three-dimensional solution environments. We conclude by discussing a number of recent publications relating to intracellular diffusion in light of the reviewed material.

No MeSH data available.


Related in: MedlinePlus