Actin polymerization driven mitochondrial transport in mating S. cerevisiae

Abstract

The dynamic microenvironment of cells depends on macromolecular architecture, equilibrium fluctuations, and nonequilibrium forces generated by cytoskeletal proteins. We studied the influence of these factors on the motions of mitochondria in mating S. cerevisiae using Fourier imaging correlation spectroscopy (FICS). Our measurements provide detailed length-scale dependent information about the dynamic behavior of mitochondria. We investigate the influence of the actin cytoskeleton on mitochondrial motion and make comparisons between conditions in which actin network assembly and disassembly is varied either by using disruptive pharmacological agents or mutations that alter the rates of actin polymerization. Under physiological conditions, nonequilibrium dynamics of the actin cytoskeleton leads to 1.5-fold enhancement of the long-time mitochondrial diffusion coefficient and a transient subdiffusive temporal scaling of the mean-square displacement (MSD ∝ τ α , with α ¼ 2∕3). We find that nonequilibrium forces associated with actin polymerization are a predominant factor in driving mitochondrial transport. Moreover, our results lend support to an existing model in which these forces are directly coupled to mitochondrial membrane surfaces.anomalous diffusion | Arp2/3-mediated actin polymerization | Fourier imaging correlation spectroscopy | intracellular transport | mitochondrial dynamics T he intracellular environment is a dynamic multicomponent fluid with relaxations spanning a broad range of length and time scales. As in ordinary fluids, in cells thermally generated inertial forces give rise to stochastic particle motions, which may be characterized by the particle mean-square displacement (MSD). Under many circumstances, thermal diffusion is a primary mechanism of intracellular transport. However, nonequilibrium forces that are generated by protein polymerization, motor proteins, and gradients in thermodynamic potentials can additionally influence particle motion. A central question in modeling cell transport is whether the cytoplasm may be viewed as a simple extension of a complex fluid at equilibrium or if nonequilibrium effects dominate the motions of intracellular species.For a spatially homogeneous fluid at equilibrium, the MSD scales linearly in time (i.e. MSD ∝ τ α with α ¼ 1). However, microscopic heterogeneity and viscoelasticity of multicomponent fluids results in "anomalous" particle motion (1-5). In the context of cell dynamics the motion of a macromolecule or larger particle may become hindered by obstacles in its immediate environment, leading to subdiffusive scaling of the MSD (i.e. α < 1), over an appreciable time range (4). For example, the motions of small proteins in bacteria appear to be diffusive (6-8), whereas those of larger particles, such as mRNA-protein clusters in E. coli and yolk granules in yeast, appear to be subdiffusive (2, 3). These differences in the dynamics of intracellular species and host organisms may be reconciled by accounting for the relative size of the mobile particles...

Anomalous Processes with General Waiting Times: Functionals and Multipoint Structure

“…[1,2] and the references therein), we usually distinguish between normal and anomalous diffusive processes for which the MSD scales linearly in time or as a power law, respectively [1][2][3][4][5][6]. However, because of the improvement of experimental techniques, evidence of more complicated nonlinear MSDs, characterized by different scaling regimes over the measurement time, has been found in recent experiments of diffusion in biophysical systems [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. Here, we investigate a general class of anomalous diffusive processes that can capture such complicated MSD behavior by means of a generalized waiting time distribution.…”

“…Figure 1(d) shows the MSD of mitochondria diffusing in mating S. cerevisiae cells, depleted of actin microfilaments, obtained with Fourier imaging correlation spectroscopy [17]. The crossover from a transient subdiffusive scaling with α ¼ 0.66 to normal diffusion cannot be captured quantitatively by the tempered Lévy-stable Φ since the curvature at the crossover between the two pure power laws cannot be modulated.…”

“…We now apply our formalism to MSD data exhibiting crossover scaling between subdiffusive and normal diffusive regimes, as is frequently observed in experiments [15,17,18]. Figure 1(d) shows the MSD of mitochondria diffusing in mating S. cerevisiae cells, depleted of actin microfilaments, obtained with Fourier imaging correlation spectroscopy [17].…”

Biological measurement beyond the quantum limit

“…Another important and particularly relevant application is real-time measurement of particle mobility within living cells (17). Such measurements have revealed information about motor proteins, chemical gradients, and protein polymerization (18), and can even allow intracellular microrheology experiments which measure the viscoelasticity of the cytoplasm (19) and the viscoelastic changes during dynamic cellular proceses (20).…”

Metabolic Optimization by Enzyme-Enzyme and Enzyme-Cytoskeleton Associations

“…Mitochondrial functions are regulated by interactions with other organelles and cytoplasmic proteins (Kostal & Arriaga, 2011). Cytoskeletal proteins such as actin and tubulin, direct mitochondria to specific sites in the cell (Senning & Marcus, 2010) and control coupling of phosphorylation by interacting with mitochondrial porin (Xu et al, 2001;Lemasters & Holmuhamedov, 2006;Rostovtseva et al, 2008;Rostovtseva et al, 2004;Xu et al, 2001). In addition to cytoeskeletal proteins, hexokinase, a glycolytic enzyme binds mitochondria in mammalians (Pastorino & Hoek, 2008), yeast and plants (Balasubramanian et al, 2008) regulatin the energy yield of mitochondria as well as the induction of programmed cell death (Kroemer et al, 2005;Pastorino & Hoek, 2008;Xie & Wilson, 1988).…”