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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.


Diffusion occurs as the result of the Brownian motion of a large number of particles. a Time snapshot of the dispersal of 350 solute particles undergoing one-dimensional (1D) Brownian movement. Particles were initially located along the central plane of the box. The conditions were T = 37°C, η = 1 × 10−4 kgm−1 s−1, particle radii = 5 nm, snapshot time =0.001 s. b Dispersal profile described in terms of the number particle linear density as calculated using Eq. 1a (solid lines) and via stochastic simulation of the individual particles trajectories (dots) using Eq. 1b (circles). For solutions carried out using Eq. 1a, DI was estimated from the theoretical relation given in Eq. 1b. Simulation times were t = 0.001 s (green), t = 0.0001 s (red), and t = 0.00001 s (blue)
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Fig2: Diffusion occurs as the result of the Brownian motion of a large number of particles. a Time snapshot of the dispersal of 350 solute particles undergoing one-dimensional (1D) Brownian movement. Particles were initially located along the central plane of the box. The conditions were T = 37°C, η = 1 × 10−4 kgm−1 s−1, particle radii = 5 nm, snapshot time =0.001 s. b Dispersal profile described in terms of the number particle linear density as calculated using Eq. 1a (solid lines) and via stochastic simulation of the individual particles trajectories (dots) using Eq. 1b (circles). For solutions carried out using Eq. 1a, DI was estimated from the theoretical relation given in Eq. 1b. Simulation times were t = 0.001 s (green), t = 0.0001 s (red), and t = 0.00001 s (blue)

Mentions: Particles in fluids undergo near continual random displacements due to collisions and subsequent momentum transfer with the surrounding solvent molecules—a situation termed ‘Brownian motion’.2 For a large number of particles initially located near to the same region in space, such Brownian motion has the consequence that the particles will tend to disperse over time, this situation being known as diffusion (Fig. 2). At the macroscopic level, the dispersal of the concentration profile of an arbitrary ideal solute component i, Ci(r,t), can be described by Fick’s second law of diffusion3 (Eq. 1a), which is an equation relating the partial time derivative of the concentration to its second partial spatial derivative using a phenomenological4 coefficient of diffusion, Di (units of m2s-1). At the time of its development, the diffusion coefficient was interpreted as a simple constant denoting a shared characteristic of the diffusing component i and the operative solution conditions under which the experiment was conducted. Throughout the period from 1905 to 1908, three scientists, Einstein (Einstein 1956), Smoluchowski (Fulinski 1998) and Langevin (Langevin 1908), all using different approaches, were able to provide a theoretical link between the phenomenological diffusion coefficient utilized by Fick and the system properties governing the individual particle displacements, ∆ri = [∆x, ∆y, ∆z]T, occurring over time intervals, ∆t, first observed by Brown (Eq. 1b)5 (Fig. 2).Fig. 2


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

Hall D, Hoshino M - Biophys Rev (2010)

Diffusion occurs as the result of the Brownian motion of a large number of particles. a Time snapshot of the dispersal of 350 solute particles undergoing one-dimensional (1D) Brownian movement. Particles were initially located along the central plane of the box. The conditions were T = 37°C, η = 1 × 10−4 kgm−1 s−1, particle radii = 5 nm, snapshot time =0.001 s. b Dispersal profile described in terms of the number particle linear density as calculated using Eq. 1a (solid lines) and via stochastic simulation of the individual particles trajectories (dots) using Eq. 1b (circles). For solutions carried out using Eq. 1a, DI was estimated from the theoretical relation given in Eq. 1b. Simulation times were t = 0.001 s (green), t = 0.0001 s (red), and t = 0.00001 s (blue)
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Related In: Results  -  Collection

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Fig2: Diffusion occurs as the result of the Brownian motion of a large number of particles. a Time snapshot of the dispersal of 350 solute particles undergoing one-dimensional (1D) Brownian movement. Particles were initially located along the central plane of the box. The conditions were T = 37°C, η = 1 × 10−4 kgm−1 s−1, particle radii = 5 nm, snapshot time =0.001 s. b Dispersal profile described in terms of the number particle linear density as calculated using Eq. 1a (solid lines) and via stochastic simulation of the individual particles trajectories (dots) using Eq. 1b (circles). For solutions carried out using Eq. 1a, DI was estimated from the theoretical relation given in Eq. 1b. Simulation times were t = 0.001 s (green), t = 0.0001 s (red), and t = 0.00001 s (blue)
Mentions: Particles in fluids undergo near continual random displacements due to collisions and subsequent momentum transfer with the surrounding solvent molecules—a situation termed ‘Brownian motion’.2 For a large number of particles initially located near to the same region in space, such Brownian motion has the consequence that the particles will tend to disperse over time, this situation being known as diffusion (Fig. 2). At the macroscopic level, the dispersal of the concentration profile of an arbitrary ideal solute component i, Ci(r,t), can be described by Fick’s second law of diffusion3 (Eq. 1a), which is an equation relating the partial time derivative of the concentration to its second partial spatial derivative using a phenomenological4 coefficient of diffusion, Di (units of m2s-1). At the time of its development, the diffusion coefficient was interpreted as a simple constant denoting a shared characteristic of the diffusing component i and the operative solution conditions under which the experiment was conducted. Throughout the period from 1905 to 1908, three scientists, Einstein (Einstein 1956), Smoluchowski (Fulinski 1998) and Langevin (Langevin 1908), all using different approaches, were able to provide a theoretical link between the phenomenological diffusion coefficient utilized by Fick and the system properties governing the individual particle displacements, ∆ri = [∆x, ∆y, ∆z]T, occurring over time intervals, ∆t, first observed by Brown (Eq. 1b)5 (Fig. 2).Fig. 2

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.