Translational diffusion of individual class II MHC membrane proteins in cells

Single-molecule epifluorescence microscopy was used to observe the translational motion of GPI-linked and native I-E(k) class II MHC membrane proteins in the plasma membrane of CHO cells. The purpose of the study was to look for deviations from Brownian diffusion that might arise from barriers to this motion. Detergent extraction had suggested that these proteins may be confined to lipid microdomains in the plasma membrane. The individual I-E(k) proteins were visualized with a Cy5-labeled peptide that binds to a specific extracytoplasmic site common to both proteins. Single-molecule trajectories were used to compute a radial distribution of displacements, yielding average diffusion coefficients equal to 0.22 (GPI-linked I-E(k)) and 0.18 microm(2)/s (native I-E(k)). The relative diffusion of pairs of proteins was also studied for intermolecular separations in the range 0.3-1.0 microm, to distinguish between free diffusion of a protein molecule and diffusion of proteins restricted to a rapidly diffusing small domain. Both analyses show that motion is predominantly Brownian. This study finds no strong evidence for significant confinement of either GPI-linked or native I-E(k) in the plasma membrane of CHO cells.     

Spatial Structure and Diffusive Dynamics from Single-Particle Trajectories Using Spline Analysis

Single-particle tracking of biomolecular probes has provided a wealth of information about intracellular trafficking and the dynamics of proteins and lipids in the cell membrane. Conventional mean-square displacement (MSD) analysis of single-particle trajectories often assumes that probes are moving in a uniform environment. However, the observed two-dimensional motion of probe particles is influenced by the local three-dimensional geometry of the cell membrane and intracellular structures, which are rarely flat at the submicron scale. This complex geometry can lead to spatially confined trajectories that are difficult to analyze and interpret using conventional two-dimensional MSD analysis. Here we present two methods to analyze spatially confined trajectories: spline-curve dynamics analysis, which extends conventional MSD analysis to measure diffusive motion in confined trajectories; and spline-curve spatial analysis, which measures spatial structures smaller than the limits of optical resolution. We show, using simulated random walks and experimental trajectories of quantum dot probes, that differences in measured two-dimensional diffusion coefficients do not always reflect differences in underlying diffusive dynamics, but can instead be due to differences in confinement geometries of cellular structures.     

Bayesian Decision Tree for the Classification of the Mode of Motion in Single-Molecule Trajectories

Membrane proteins move in heterogeneous environments with spatially (sometimes temporally) varying friction and with biochemical interactions with various partners. It is important to reliably distinguish different modes of motion to improve our knowledge of the membrane architecture and to understand the nature of interactions between membrane proteins and their environments. Here, we present an analysis technique for single molecule tracking (SMT) trajectories that can determine the preferred model of motion that best matches observed trajectories. The method is based on Bayesian inference to calculate the posteriori probability of an observed trajectory according to a certain model. Information theory criteria, such as the Bayesian information criterion (BIC), the Akaike information criterion (AIC), and modified AIC (AICc), are used to select the preferred model. The considered group of models includes free Brownian motion, and confined motion in 2nd or 4th order potentials. We determine the best information criteria for classifying trajectories. We tested its limits through simulations matching large sets of experimental conditions and we built a decision tree. This decision tree first uses the BIC to distinguish between free Brownian motion and confined motion. In a second step, it classifies the confining potential further using the AIC. We apply the method to experimental Clostridium Perfingens -toxin (CPT) receptor trajectories to show that these receptors are confined by a spring-like potential. An adaptation of this technique was applied on a sliding window in the temporal dimension along the trajectory. We applied this adaptation to experimental CPT trajectories that lose confinement due to disaggregation of confining domains. This new technique adds another dimension to the discussion of SMT data. The mode of motion of a receptor might hold more biologically relevant information than the diffusion coefficient or domain size and may be a better tool to classify and compare different SMT experiments.     

Confined lateral diffusion of membrane receptors as studied by single particle tracking (nanovid microscopy). Effects of calcium-induced differentiation in cultured epithelial cells.

The movements of E-cadherin, epidermal growth factor receptor, and transferrin receptor in the plasma membrane of a cultured mouse keratinocyte cell line were studied using both single particle tracking (SPT; nanovid microscopy) and fluorescence photobleaching recovery (FPR). In the SPT technique, the receptor molecules are labeled with 40 nm-phi colloidal gold particles, and their movements are followed by video-enhanced differential interference contrast microscopy at a temporal resolution of 33 ms and at a nanometer-level spatial precision. The trajectories of the receptor molecules obtained by SPT were analyzed by developing a method that is based on the plot of the mean-square displacement against time. Four characteristic types of motion were observed: (a) stationary mode, in which the microscopic diffusion coefficient is less than 4.6 x 10(-12) cm2/s; (b) simple Brownian diffusion mode; (c) directed diffusion mode, in which unidirectional movements are superimposed on random motion; and (d) confined diffusion mode, in which particles undergoing Brownian diffusion (microscopic diffusion coefficient between 4.6 x 10(-12) and 1 x 10(-9) cm2/s) are confined within a limited area, probably by the membrane-associated cytoskeleton network. Comparison of these data obtained by SPT with those obtained by FPR suggests that the plasma membrane is compartmentalized into many small domains 300-600 nm in diameter (0.04-0.24 microns2 in area), in which receptor molecules are confined in the time scale of 3-30 s, and that the long-range diffusion observed by FPR can occur by successive movements of the receptors to adjacent compartments. Calcium-induced differentiation decreases the sum of the percentages of molecules in the directed diffusion and the stationary modes outside of the cell-cell contact regions on the cell surface (which is proposed to be the percentage of E-cadherin bound to the cytoskeleton/membrane-skeleton), from approximately 60% to 8% (low- and high-calcium mediums, respectively).     

Analysis of transient behavior in complex trajectories: application to secretory vesicle dynamics

Analysis of trajectories of dynamical biological objects, such as breeding ants or cell organelles, is essential to reveal the interactions they develop with their environments. Many previous works used a global characterization based on parameters calculated for entire trajectories. In cases where transient behavior was detected, this usually concerned only a particular type, such as confinement or directed motion. However, these approaches are not appropriate in situations in which the tracked objects may display many different types of transient motion. We have developed a method to exhaustively analyze different kinds of transient behavior that the tracked objects may exhibit. The method discriminates stalled periods, constrained and directed motions from random dynamics by evaluating the diffusion coefficient, the mean-square displacement curvature, and the trajectory asymmetry along individual trajectories. To detect transient motions of various durations, these parameters are calculated along trajectories using a rolling analysis window whose width is variable. The method was applied to the study of secretory vesicle dynamics in the subplasmalemmal region of human carcinoid BON cells. Analysis of transitions between transient motion periods, combined with plausible assumptions about the origin of each motion type, leads to a model of dynamical subplasmalemmal organization.     

Analysis of molecular diffusion by first-passage time variance identifies the size of confinement zones

The diffusion of receptors within the two-dimensional environment of the plasma membrane is a complex process. Although certain components diffuse according to a random walk model (Brownian diffusion), an overwhelming body of work has found that membrane diffusion is nonideal (anomalous diffusion). One of the most powerful methods for studying membrane diffusion is single particle tracking (SPT), which records the trajectory of a label attached to a membrane component of interest. One of the outstanding problems in SPT is the analysis of data to identify the presence of heterogeneity. We have adapted a first-passage time (FPT) algorithm, originally developed for the interpretation of animal movement, for the analysis of SPT data. We discuss the general application of the FPT analysis to molecular diffusion, and use simulations to test the method against data containing known regions of confinement. We conclude that FPT can be used to identify the presence and size of confinement within trajectories of the receptor LFA-1, and these results are consistent with previous reports on the size of LFA-1 clusters. The analysis of trajectory data for cell surface receptors by FPT provides a robust method to determine the presence and size of confined regions of diffusion.     

Interpretation of NMR relaxation properties of Pin1, a two-domain protein, based on Brownian dynamic simulations

Many important proteins contain multiple domains connected by flexible linkers. Inter-domain motion is suggested to play a key role in many processes involving molecular recognition. Heteronuclear NMR relaxation is sensitive to motions in the relevant time scales and could provide valuable information on the dynamics of multi-domain proteins. However, the standard analysis based on the separation of global tumbling and fast local motions is no longer valid for multi-domain proteins undergoing internal motions involving complete domains and that take place on the same time scale than the overall motion.The complexity of the motions experienced even for the simplest two-domain proteins are difficult to capture with simple extensions of the classical Lipari-Szabo approach. Hydrodynamic effects are expected to dominate the motion of the individual globular domains, as well as that of the complete protein. Using Pin1 as a test case, we have simulated its motion at the microsecond time scale, at a reasonable computational expense, using Brownian Dynamic simulations on simplified models. The resulting trajectories provide insight on the interplay between global and inter-domain motion and can be analyzed using the recently published method of isotropic Reorientational Mode Dynamics which offer a way of calculating their contribution to heteronuclear relaxation rates. The analysis of trajectories computed with Pin1 models of different flexibility provides a general framework to understand the dynamics of multi-domain proteins and explains some of the observed features in the relaxation rate profile of free Pin1.     

Kalman smoothing improves the estimation of joint kinematics and kinetics in marker-based human gait analysis

We developed a Kalman smoothing algorithm to improve estimates of joint kinematics from measured marker trajectories during motion analysis. Kalman smoothing estimates are based on complete marker trajectories. This is an improvement over other techniques, such as the global optimisation method (GOM), Kalman filtering, and local marker estimation (LME), where the estimate at each time instant is only based on part of the marker trajectories. We applied GOM, Kalman filtering, LME, and Kalman smoothing to marker trajectories from both simulated and experimental gait motion, to estimate the joint kinematics of a ten segment biomechanical model, with 21 degrees of freedom. Three simulated marker trajectories were studied: without errors, with instrumental errors, and with soft tissue artefacts (STA). Two modelling errors were studied: increased thigh length and hip centre dislocation. We calculated estimation errors from the known joint kinematics in the simulation study. Compared with other techniques, Kalman smoothing reduced the estimation errors for the joint positions, by more than 50% for the simulated marker trajectories without errors and with instrumental errors. Compared with GOM, Kalman smoothing reduced the estimation errors for the joint moments by more than 35%. Compared with Kalman filtering and LME, Kalman smoothing reduced the estimation errors for the joint accelerations by at least 50%. Our simulation results show that the use of Kalman smoothing substantially improves the estimates of joint kinematics and kinetics compared with previously proposed techniques (GOM, Kalman filtering, and LME) for both simulated, with and without modelling errors, and experimentally measured gait motion.     

Auditory Hair Cell Centrioles Undergo Confined Brownian Motion Throughout the Developmental Migration of the Kinocilium

Planar polarization of the forming hair bundle, the mechanosensory antenna of auditory hair cells, depends on the poorly characterized center-to-edge displacement of a primary cilium, the kinocilium, at their apical surface. Taking advantage of the gradient of hair cell differentiation along the cochlea, we reconstituted a map of the kinocilia displacements in the mouse embryonic cochlea. We then developed a cochlear organotypic culture and video-microscopy approach to monitor the movements of the kinocilium basal body (mother centriole) and its daughter centriole, which we analyzed using particle tracking and modeling. We found that both hair cell centrioles undergo confined Brownian movements around their equilibrium positions, under the apparent constraint of a radial restoring force of ∼0.1 pN. This magnitude depended little on centriole position, suggesting nonlinear interactions with constraining, presumably cytoskeletal elements. The only dynamic change observed during the period of kinocilium migration was a doubling of the centrioles’ confinement area taking place early in the process. It emerges from these static and dynamic observations that kinocilia migrate gradually in parallel with the organization of hair cells into rows during cochlear neuroepithelium extension. Analysis of the confined motion of hair cell centrioles under normal and pathological conditions should help determine which structures contribute to the restoring force exerting on them.     

Quantitative Microscopy: Protein Dynamics and Membrane Organisation

The mobility of membrane proteins is a critical determinant of their interaction capabilities and protein functions. The heterogeneity of cell membranes imparts different types of motion onto proteins; immobility, random Brownian motion, anomalous sub-diffusion, 'hop' or confined diffusion, or directed flow. Quantifying the motion of proteins therefore enables insights into the lateral organisation of cell membranes, particularly membrane microdomains with high viscosity such as lipid rafts. In this review, we examine the hypotheses and findings of three main techniques for analysing protein dynamics: fluorescence recovery after photobleaching, single particle tracking and fluorescence correlation spectroscopy. These techniques, and the physical models employed in data analysis, have become increasingly sophisticated and provide unprecedented details of the biophysical properties of protein dynamics and membrane domains in cell membranes. Yet despite these advances, there remain significant unknowns in the relationships between cholesterol-dependent lipid microdomains, protein-protein interactions, and the effect of the underlying cytoskeleton. New multi-dimensional microscopy approaches may afford greater temporal and spatial resolution resulting in more accurate quantification of protein and membrane dynamics in live cells.     

Confined diffusion without fences of a g-protein-coupled receptor as revealed by single particle tracking

Single particle tracking is a powerful tool for probing the organization and dynamics of the plasma membrane constituents. We used this technique to study the micro -opioid receptor belonging to the large family of the G-protein-coupled receptors involved with other partners in a signal transduction pathway. The specific labeling of the receptor coupled to a T7-tag at its N-terminus, stably expressed in fibroblastic cells, was achieved by colloidal gold coupled to a monoclonal anti T7-tag antibody. The lateral movements of the particles were followed by nanovideomicroscopy at 40 ms time resolution during 2 min with a spatial precision of 15 nm. The receptors were found to have either a slow or directed diffusion mode (10%) or a walking confined diffusion mode (90%) composed of a long-term random diffusion and a short-term confined diffusion, and corresponding to a diffusion confined within a domain that itself diffuses. The results indicate that the confinement is due to an effective harmonic potential generated by long-range attraction between the membrane proteins. A simple model for interacting membrane proteins diffusion is proposed that explains the variations with the domain size of the short-term and long-term diffusion coefficients.     

Individual analyses of Lévy walk in semi-free ranging Tonkean macaques (Macaca tonkeana)

Animals adapt their movement patterns to their environment in order to maximize their efficiency when searching for food. The Lévy walk and the Brownian walk are two types of random movement found in different species. Studies have shown that these random movements can switch from a Brownian to a Lévy walk according to the size distribution of food patches. However no study to date has analysed how characteristics such as sex, age, dominance or body mass affect the movement patterns of an individual. In this study we used the maximum likelihood method to examine the nature of the distribution of step lengths and waiting times and assessed how these distributions are influenced by the age and the sex of group members in a semi free-ranging group of ten Tonkean macaques. Individuals highly differed in their activity budget and in their movement patterns. We found an effect of age and sex of individuals on the power distribution of their step lengths and of their waiting times. The males and old individuals displayed a higher proportion of longer trajectories than females and young ones. As regards waiting times, females and old individuals displayed higher rates of long stationary periods than males and young individuals. These movement patterns resembling random walks can probably be explained by the animals moving from one location to other known locations. The power distribution of step lengths might be due to a power distribution of food patches in the enclosure while the power distribution of waiting times might be due to the power distribution of the patch sizes.     

Filtering molecular dynamics trajectories to reveal low-frequency collective motions: phospholipase A2

A novel method for analysing molecular dynamics trajectories has been developed, which filters out high frequencies using digital signal processing techniques and facilitates focusing on the low-frequency collective motions of proteins. These motions involve low energy slow motions, which lead to important biological phenomena such as domain closure and allosteric effects in enzymes. The filtering method treats each of the atomic trajectories obtained from the molecular dynamics simulation as a "signal". The trajectories of each of the atoms in the system (or any subset of interest) are Fourier transformed to the frequency domain, a filtering function is applied and then an inverse transformation back to the time domain yields the filtered trajectory. The filtering method has been used to study the dynamics of the enzyme phospholipase A2. In the filtered trajectory, all the high frequency bond and valence angle vibrations were eliminated, leaving only low-frequency motion, mainly fluctuations in torsions and conformational transitions. Analysis of this trajectory revealed interesting motions of the protein, including concerted movements of helices, and changes in shape of the active site cavity. Unlike normal mode analysis, which has been used to study the motion of proteins, this method does not require converged minimizations or diagonalization of a matrix of second derivatives. In addition, anharmonicity, multiple minima and conformational transitions are treated explicitly. Thus, the filtering method avoids most of the approximations implicit in other investigations of the dynamic behaviour of large systems.     

Compartmentalized structure of the plasma membrane for receptor movements as revealed by a nanometer-level motion analysis

Movements of transferrin and alpha 2-macroglobulin receptor molecules in the plasma membrane of cultured normal rat kidney (NRK) fibroblastic cells were investigated by video-enhanced contrast optical microscopy with 1.8 nm spatial precision and 33 ms temporal resolution by labeling the receptors with the ligand-coated nanometer-sized colloidal gold particles. For both receptor species, most of the movement trajectories are of the confined diffusion type, within domains of approximately 0.25 microns2 (500-700 nm in diagonal length). Movement within the domains is random with a diffusion coefficient approximately 10(-9) cm2/s, which is consistent with that expected for free Brownian diffusion of proteins in the plasma membrane. The receptor molecules move from one domain to one of the adjacent domains at an average frequency of 0.034 s-1 (the residence time within a domain approximately 29 s), indicating that the plasma membrane is compartmentalized for diffusion of membrane receptors and that long- range diffusion is the result of successive intercompartmental jumps. The macroscopic diffusion coefficients for these two receptor molecules calculated on the basis of the compartment size and the intercompartmental jump rate are approximately 2.4 x 10(-11) cm2/s, which is consistent with those determined by averaging the long-term movements of many particles. Partial destruction of the cytoskeleton decreased the confined diffusion mode, increased the simple diffusion mode, and induced the directed diffusion (transport) mode. These results suggest that the boundaries between compartments are made of dynamically fluctuating membrane skeletons (membrane-skeleton fence model).     

Lévy flight and Brownian search patterns of a free-ranging predator reflect different prey field characteristics

1. Search processes play an important role in physical, chemical and biological systems. In animal foraging, the search strategy predators should use to search optimally for prey is an enduring question. Some models demonstrate that when prey is sparsely distributed, an optimal search pattern is a specialised random walk known as a Lévy flight, whereas when prey is abundant, simple Brownian motion is sufficiently efficient. These predictions form part of what has been termed the Lévy flight foraging hypothesis (LFF) which states that as Lévy flights optimise random searches, movements approximated by optimal Lévy flights may have naturally evolved in organisms to enhance encounters with targets (e.g. prey) when knowledge of their locations is incomplete. 2. Whether free-ranging predators exhibit the movement patterns predicted in the LFF hypothesis in response to known prey types and distributions, however, has not been determined. We tested this using vertical and horizontal movement data from electronic tagging of an apex predator, the great white shark Carcharodon carcharias, across widely differing habitats reflecting different prey types. 3. Individual white sharks exhibited movement patterns that predicted well the prey types expected under the LFF hypothesis. Shark movements were best approximated by Brownian motion when hunting near abundant, predictable sources of prey (e.g. seal colonies, fish aggregations), whereas movements approximating truncated Lévy flights were present when searching for sparsely distributed or potentially difficult-to-detect prey in oceanic or shelf environments, respectively. 4. That movement patterns approximated by truncated Lévy flights and Brownian behaviour were present in the predicted prey fields indicates search strategies adopted by white sharks appear to be the most efficient ones for encountering prey in the habitats where such patterns are observed. This suggests that C. carcharias appears capable of exhibiting search patterns that are approximated as optimal in response to encountered changes in prey type and abundance, and across diverse marine habitats, from the surf zone to the deep ocean. 5. Our results provide some support for the LFF hypothesis. However, it is possible that the observed Lévy patterns of white sharks may not arise from an adaptive behaviour but could be an emergent property arising from simple, straight-line movements between complex (e.g. fractal) distributions of prey. Experimental studies are needed in vertebrates to test for the presence of Lévy behaviour patterns in the absence of complex prey distributions.     

Universal Behavior of Extreme Price Movements in Stock Markets

Many studies assume stock prices follow a random process known as geometric Brownian motion. Although approximately correct, this model fails to explain the frequent occurrence of extreme price movements, such as stock market crashes. Using a large collection of data from three different stock markets, we present evidence that a modification to the random model—adding a slow, but significant, fluctuation to the standard deviation of the process—accurately explains the probability of different-sized price changes, including the relative high frequency of extreme movements. Furthermore, we show that this process is similar across stocks so that their price fluctuations can be characterized by a single curve. Because the behavior of price fluctuations is rooted in the characteristics of volatility, we expect our results to bring increased interest to stochastic volatility models, and especially to those that can produce the properties of volatility reported here.     

Computational Tool for Ensemble Averaging of Single-Molecule Data

Molecular motors couple chemical transitions to conformational changes that perform mechanical work in a wide variety of biological processes. Disruption of this coupling can lead to diseases, and therefore there is a need to accurately measure mechanochemical coupling in motors in both health and disease. Optical tweezers with nanometer spatial and millisecond temporal resolution have provided valuable insights into these processes. However, fluctuations due to Brownian motion can make it difficult to precisely resolve these conformational changes. One powerful analysis technique that has improved our ability to accurately measure mechanochemical coupling in motor proteins is ensemble averaging of individual trajectories. Here, we present a user-friendly computational tool, Software for Precise Analysis of Single Molecules (SPASM), for generating ensemble averages of single-molecule data. This tool utilizes several conceptual advances, including optimized procedures for identifying single-molecule interactions and the implementation of a change-point algorithm, to more precisely resolve molecular transitions. Using both simulated and experimental data, we demonstrate that these advances allow for accurate determination of the mechanics and kinetics of the myosin working stroke with a smaller set of data. Importantly, we provide our open-source MATLAB-based program with a graphical user interface that enables others to readily apply these advances to the analysis of their own data.     

Correlation analysis of frequency distributions of residues in proteins

Autocorrelation and spectrum analyses of amino acid residues along protein chains in a large data base has been performed. Results reveal the presence of general long range correlations. Similar analyses of simulated (random) peptides do not exhibit any such long range correlations. Based on the results of nur analysis, an attempt has been made to model the distribution of residues in protein sequences on a fractional Brownian motion and individual sequences as multi-fractals. For this purpose, the characteristics of an fractional Brownian motion namely, the scaling parameterH. the spectral exponent β and the fractal dimensionD, have been described     

Transient directed motions of GABA(A) receptors in growth cones detected by a speed correlation index

Single-molecule tracking of membrane proteins has become an important tool for investigating dynamic processes in live cells, such as cell signaling, membrane compartmentation or trafficking. The extraction of relevant parameters, such as interaction times between molecular partners or confinement-zone sizes, from the trajectories of single molecules requires appropriate statistical methods. Here we report a new tool, the speed correlation index, designed to detect transient periods of directed motion within trajectories of diffusing molecules. The ability to detect such events in a wide range of biologically relevant parameter values (speed, diffusion coefficient, and durations of the directed period) was first established on simulated data. The method was next applied to analyze the trajectories of quantum-dot-labeled GABA(A) receptors in nerve growth cones. The use of the speed correlation index revealed that the receptors had a "conveyor belt" type of motion due to temporary interactions ( approximately 4.0 s) between the receptors and the microtubules, leading to an average directed motion (velocity approximately 0.3 mum s(-1)) in the growth-cone membrane. Our observations point to the possibility of a cytoskeleton-dependent redistribution of the sensing molecules in the membrane, which could play a role in the modulation of the cell response to external signals.