Myosin VI walks hand-over-hand along actin

Myosin VI is a molecular motor that can walk processively on actin filaments with a 36-nm step size. The walking mechanism of myosin VI is controversial because it takes very large steps without an apparent lever arm of required length. Therefore, myosin VI is argued to be the first exception to the widely established lever arm theory. It is therefore critical to directly demonstrate whether this motor walks hand-over-hand along actin despite its short lever arm. Here, we follow the displacement of a single myosin VI head during the stepping process. A single head is displaced 72 nm during stepping, whereas the center of mass previously has been shown to move 36 nm. The most likely explanation for this result is a hand-over-hand walking mechanism. We hypothesize the existence of a flexible element that would allow the motor to bridge the observed 72-nm distance.     

Stochasticity, invasions, and branching random walks

We link deterministic integrodifference equations to stochastic, individual-based simulations by means of branching random walks. Using standard methods, we determine speeds of invasion for both average densities and furthest-forward individuals. For density-independent branching random walks, demographic stochasticity can produce extinction. Demographic stochasticity does not, however, reduce the overall asymptotic speed of invasion or preclude continually accelerating invasions.     

Simulation of pedigree genotypes by random walks.

A random walk method, based on the Metropolis algorithm, is developed for simulating the distribution of trait and linkage marker genotypes in pedigrees where trait phenotypes are already known. The method complements techniques suggested by Ploughman and Boehnke and by Ott that are based on sequential sampling of genotypes within a pedigree. These methods are useful for estimating the power of linkage analysis before complete study of a pedigree is undertaken. We apply the random walk technique to a partially penetrant disease, schizophrenia, and to a recessive disease, ataxia-telangiectasia. In the first case we show that accessory phenotypes with higher penetrance than that of schizophrenia itself may be crucial for effective linkage analysis, and in the second case we show that impressionistic selection of informative pedigrees may be misleading.     

Estimation of inbreeding by random walks in pedigrees

Summary Wright and McPhee (1925) suggested a method of estimating the inbreeding coefficient of an individual based on the probability that a pair of lineages traced randomly, one through the maternal line and one through the paternal line, both contain a common ancestor. (One-half of this probability is an unbiased estimate of the inbreeding coefficient). In their procedure, maternal and paternal lines are chosen in pairs, and comparisons are made only between the lines in a pair. A more efficient procedure is to compare every maternal line with every paternal line, a procedure used by Robertson and Mason (1954). In this paper we provide estimates of the sampling variance of the inbreeding coefficient as estimated by the multiple comparison method, and we examine the relative efficiency of this method and the Wright-McPhee procedure. Formulae are also provided for ascertaining the optimal sampling method for estimating the average inbreeding coefficient of a group or herd.Work supported by NSF grant GB43209, NIH grant GM21732 and by Research Career Award GM0002301.     

Dwell time symmetry in random walks and molecular motors

The statistics of steps and dwell times in reversible molecular motors differ from those of cycle completion in enzyme kinetics. The reason is that a step is only one of several transitions in the mechanochemical cycle. As a result, theoretical results for cycle completion in enzyme kinetics do not apply to stepping data. To allow correct parameter estimation, and to guide data analysis and experiment design, a theoretical treatment is needed that takes this observation into account. In this article, we model the distribution of dwell times and number of forward and backward steps using first passage processes, based on the assumption that forward and backward steps correspond to different directions of the same transition. We extend recent results for systems with a single cycle and consider the full dwell time distributions as well as models with multiple pathways, detectable substeps, and detachments. Our main results are a symmetry relation for the dwell time distributions in reversible motors, and a relation between certain relative step frequencies and the free energy per cycle. We demonstrate our results by analyzing recent stepping data for a bacterial flagellar motor, and discuss the implications for the efficiency and reversibility of the force-generating subunits.     

Predicting genetic interactions with random walks on biological networks

Background  

Several studies have demonstrated that synthetic lethal genetic interactions between gene mutations provide an indication of functional redundancy between molecular complexes and pathways. These observations help explain the finding that organisms are able to tolerate single gene deletions for a large majority of genes. For example, system-wide gene knockout/knockdown studies in S. cerevisiae and C. elegans revealed non-viable phenotypes for a mere 18% and 10% of the genome, respectively. It has been postulated that the low percentage of essential genes reflects the extensive amount of genetic buffering that occurs within genomes. Consistent with this hypothesis, systematic double-knockout screens in S. cerevisiae and C. elegans show that, on average, 0.5% of tested gene pairs are synthetic sick or synthetic lethal. While knowledge of synthetic lethal interactions provides valuable insight into molecular functionality, testing all combinations of gene pairs represents a daunting task for molecular biologists, as the combinatorial nature of these relationships imposes a large experimental burden. Still, the task of mapping pairwise interactions between genes is essential to discovering functional relationships between molecular complexes and pathways, as they form the basis of genetic robustness. Towards the goal of alleviating the experimental workload, computational techniques that accurately predict genetic interactions can potentially aid in targeting the most likely candidate interactions. Building on previous studies that analyzed properties of network topology to predict genetic interactions, we apply random walks on biological networks to accurately predict pairwise genetic interactions. Furthermore, we incorporate all published non-interactions into our algorithm for measuring the topological relatedness between two genes. We apply our method to S. cerevisiae and C. elegans datasets and, using a decision tree classifier, integrate diverse biological networks and show that our method outperforms established methods.     

Biological organization,Jarkievich measures and asymmetric random walks

In this paper we analyze the organization imposed by the energy input during the migration of enzymes on DNA. We attempt to measure that organization by means of a concept proposed by A.A. Jarkievich in 1961. We found relationships among a Jarkievich measure, the energy dissipation, and the fluctuations in the kinematic velocity of the enzyme on the DNA.     

Lowering the barriers to random walks on the cell surface

We used fluorescence recovery after photobleaching (FRAP) and single particle tracking (SPT) techniques to compare diffusion of class I major histocompatibility complex molecules (MHC) on normal and alpha-spectrin-deficient murine erythroleukemia (MEL) cells. Because the cytoskeleton mesh acts as a barrier to lateral mobility of membrane proteins, we expected that diffusion of membrane proteins in alpha-spectrin-deficient MEL cells would differ greatly from that in normal MEL cells. In the event, diffusion coefficients derived from either FRAP or SPT analysis were similar for alpha-spectrin-deficient and normal MEL cells, differing by a factor of approximately 2, on three different timescales: tens of seconds, 1-10 s, and 100 ms. SPT analysis showed that the diffusion of most class I MHC molecules was confined on both cell types. On the normal MEL cells, the mean diagonal length of the confined area was 330 nm with a mean residency time of 40s. On the alpha-spectrin-deficient MEL cells, the mean diagonal length was 650 nm with a mean residency time of 45s. Thus there are fewer barriers to lateral diffusion on cytoskeleton mutant MEL cells than on normal MEL cells, but this difference does not strongly affect lateral diffusion on the scales measured here.     

Sampling rate effects on measurements of correlated and biased random walks

When observing the two-dimensional movement of animals or microorganisms, it is usually necessary to impose a fixed sampling rate, so that observations are made at certain fixed intervals of time and the trajectory is split into a set of discrete steps. A sampling rate that is too small will result in information about the original path and correlation being lost. If random walk models are to be used to predict movement patterns or to estimate parameters to be used in continuum models, then it is essential to be able to quantify and understand the effect of the sampling rate imposed by the observer on real trajectories. We use a velocity jump process with a realistic reorientation model to simulate correlated and biased random walks and investigate the effect of sampling rate on the observed angular deviation, apparent speed and mean turning angle. We discuss a method of estimating the values of the reorientation parameters used in the original random walk from the rediscretized data that assumes a linear relation between sampling time step and the parameter values.     

Why the null matters: statistical tests,random walks and evolution

A number of statistical tests have been developed to determine what type of dynamics underlie observed changes in morphology in evolutionary time series, based on the pattern of change within the time series. The theory of the scaled maximum, the log-rate-interval (LRI) method, and the Hurst exponent all operate on the same principle of comparing the maximum change, or rate of change, in the observed dataset to the maximum change expected of a random walk. Less change in a dataset than expected of a random walk has been interpreted as indicating stabilizing selection, while more change implies directional selection. The runs test in contrast, operates on the sequencing of steps, rather than on excursion. Applications of these tests to computer generated, simulated time series of known dynamical form and various levels of additive noise indicate that there is a fundamental asymmetry in the rate of type II errors of the tests based on excursion: they are all highly sensitive to noise in models of directional selection that result in a linear trend within a time series, but are largely noise immune in the case of a simple model of stabilizing selection. Additionally, the LRI method has a lower sensitivity than originally claimed, due to the large range of LRI rates produced by random walks. Examination of the published results of these tests show that they have seldom produced a conclusion that an observed evolutionary time series was due to directional selection, a result which needs closer examination in light of the asymmetric response of these tests.     

On the mapping of chains of first order chemical reactions on random walks

We present the transient solution to a random walk problem which characterizes chemical kinetic processes in which a particular state may have a finite number of internal states. While there are many chemical and physical examples, we introduce the solution through models of biophysical interest.     

RRW: repeated random walks on genome-scale protein networks for local cluster discovery

Background  

We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW) for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins.     

Limited capacity of working memory in unihemispheric random walks implies conceivable slow dispersal

Phenomenologically inspired by dolphins’ unihemispheric sleep, we introduce a minimal model for random walks with physiological memory. The physiological memory consists of long-term memory which includes unconscious implicit memory and conscious explicit memory, and working memory which serves as a multi-component system for integrating, manipulating and managing short-term storage. The model assumes that the sleeping state allows retrievals of episodic objects merely from the episodic buffer where these memory objects are invoked corresponding to the ambient objects and are thus object-oriented, together with intermittent but increasing use of implicit memory in which decisions are unconsciously picked up from historical time series. The process of memory decay and forgetting is constructed in the episodic buffer. The walker’s risk attitude, as a product of physiological heuristics according to the performance of objected-oriented decisions, is imposed on implicit memory. The analytical results of unihemispheric random walks with the mixture of object-oriented and time-oriented memory, as well as the long-time behavior which tends to the use of implicit memory, are provided, indicating the common sense that a conservative risk attitude is inclinable to slow movement.     

'Dicty dynamics': Dictyostelium motility as persistent random motion

We model the motility of Dictyostelium cells in a systematic data-driven manner. We deduce a minimal dynamical model that reproduces the statistical features of experimental trajectories. These are trajectories of the centroid of the cell perimeter, which is more sensitive to pseudopod activity than the usual tracking by centroid or nucleus. Our data account for cell individuality and dictate a model that extends the cell-type specific models recently derived for mammalian cells. Two generalized Langevin equations model stochastic periodic pseudopod motion parallel and orthogonal to the amoeba's direction of motion. This motion propels the amoeba with a random periodic left-right waddle in a direction that has a long persistence time. The model fully accounts for the statistics of the experimental trajectories, including velocity power spectra and auto-correlations, non-Gaussian velocity distributions, and multiplicative noise. Thus, we find neither need nor place in our data for an interpretation in terms of anomalous diffusion. The model faithfully captures cell individuality as different parameter values in the model, and serves as a basis for integrating the local mechanics of cell motion with our observed long-term behavior.     

Cell motility as persistent random motion: theories from experiments

Experimental time series for trajectories of motile cells may contain so much information that a systematic analysis will yield cell-type-specific motility models. Here we demonstrate how, using human keratinocytes and fibroblasts as examples. The two resulting models reflect the cells' different roles in the organism, it seems, and show that a cell has a memory of past velocities. They also suggest how to distinguish quantitatively between various surfaces' compatibility with the two cell types.     

A Rac switch regulates random versus directionally persistent cell migration

Directional migration moves cells rapidly between points, whereas random migration allows cells to explore their local environments. We describe a Rac1 mechanism for determining whether cell patterns of migration are intrinsically random or directionally persistent. Rac activity promoted the formation of peripheral lamellae that mediated random migration. Decreasing Rac activity suppressed peripheral lamellae and switched the cell migration patterns of fibroblasts and epithelial cells from random to directionally persistent. In three-dimensional rather than traditional two-dimensional cell culture, cells had a lower level of Rac activity that was associated with rapid, directional migration. In contrast to the directed migration of chemotaxis, this intrinsic directional persistence of migration was not mediated by phosphatidylinositol 3'-kinase lipid signaling. Total Rac1 activity can therefore provide a regulatory switch between patterns of cell migration by a mechanism distinct from chemotaxis.